UNCERTAINTY AND RISK-BASED DECISION-MAKING: HUNTER-GATHERER ADAPTATION TO
SPATIOTEMPORAL HETEROGENEITY
By
Jubin J. Cheruvelil

A DISSERTATION
Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of
Anthropology - Doctor of Philosophy
2013

ABSTRACT
UNCERTAINTY AND RISK-BASED DECISION-MAKING: HUNTER-GATHERER ADAPTATION TO
SPATIOTEMPORAL HETEROGENEITY
By
Jubin J. Cheruvelil
Hunter-gatherer land use and diet decision-making is tightly coupled with temporal (i.e.,
seasonal) and spatial (i.e., landscape) resource variability. This spatiotemporal variation, driven
by climatic and hydrological processes poses considerable uncertainties and risks for huntergatherer economic success. In this dissertation, I use these contextual and behavioral variables
to explore hunter gatherer social responses to resource uncertainty and risk in the Saginaw Bay
Drainage of Michigan.
Hunter-gatherer economic decision-making is often framed as responses to nutritional
requirements, exploitation efficiency, and as a normative response to environmental conditions
(resource constraints and abundance). This project explores decision-making through an
alternate basis; of economic security explored through behavioral strategies intended cope and
buffer against spatiotemporal risk and uncertainty. To this end, I model cultural and resource
landscapes and simulate hunter gatherer economic choices in order to understand the role that
uncertainty and risk plays on land use and diet. Further, these models are compared against
archaeological material culture (i.e., site locales and features, fauna and flora). Cumulatively,
these models are used to better understand economic decision-making during the Late Archaic
(5000-2500 B.P.), Early Woodland (2500-2100 B.P.) and Middle Woodland (2100-1500 B.P.).

First, the resulting landscape models indicate considerable large-scale wetland
environments that fluctuate seasonally and on a long term basis. Both, the Late Archaic and
Middle Woodland periods are heavily wetland influenced, with considerable regional and
localized effects. Next, the behavioral model suggests that economic choices intended to
address uncertainty and risk are strategies aimed at tackling boundary conditions (i.e., worse
case scenarios) and are likely baseline criteria for economic decision-making. Highly effective
strategies include a combination of high and low risk resource exploitation with seasonally
adjustable diet breadth (large ungulates and diverse plant foods concurrently through a
gendered division of labor).
Last, comparative analysis with archaeological materials indicates that hunter-gatherers
employ an ever-increasing complex resource and land use strategies over time intended to
adapt to both, long term and short term seasonal and spatially variable resource distributions.
These behavioral responses results in changes in hunter-gatherer economy including resource
and land use diversification, specialization of mobility patterns, expanding exchange networks,
and pooling strategies. Further, the research outcomes highlights the benefits of systematic,
long-term and regional studies that results in implications for the archaeology that highlight the
resilience, and longevity of the hunter-gatherer economy.

Copyright by
JUBIN J. CHERUVELIL
2013

To my dear family and friends for their encouragement and support

v

ACKNOWLEDGEMENTS
This project; proposal, and eventual outcomes would not have been possible without
the guidance and support of numerous mentors, friends and family. I have appreciated Dr.
Lovis’ assistance during our many early-morning meetings; and his patience with tempering,
guiding my ideas, and leading me down a path less traveled. Further, I give thanks to an
effective dissertation committee comprised of Drs. William A. Lovis, Jodie O’Gorman, John W.
Norder, and Daniel B. Hayes. Additionally, I appreciate the guidance of and discussions with Drs.
Robert K. Hitchcock, Alison E. Rautman and the late Margaret B. Holman, who were
instrumental in developing the ideas that contributed to this project. Two key people who
provided and helped me with gathering and make sense of the voluminous data are Barbara
Mead and Edward Schools.
Throughout my graduate career, I have appreciated the financial support of David
Byelich and Mary Black, at the Michigan State University Office of Planning and Budgets
through a half time assistantship. I am also thankful for funding and technical support from the
National Science Foundation–AGEP Scholarships, Michigan State University (Graduate School,
Department of Anthropology, American Indian Studies Program, and Environmental Science
and Public Policy), State of Michigan (Office of the State Archaeologist, the Michigan Natural
Features Inventory), and Illinois State Museum. A heartfelt thanks goes to those who helped
compile and edit the voluminous databases and written materials, including Nicole HallGendjar, Tankod Esova, Nicole Adele Raslich, Janet Ellen Finlayson, and Dawn Martin. I also
appreciate the collegiality and friendships of staff, graduate students and faculty, both within

vi

and outside the Anthropology department over the years. Most importantly, this endeavor
would not have been possible without the encouragement and day-to-day support of Dr.
Kendra Spence Cheruvelil, Watson Bennett Cheruvelil, Jamieson Locke Cheruvelil; I am forever
indebted to them for their patience and love.

vii

TABLE OF CONTENTS

LIST OF TABLES ................................................................................................................................ xi
LIST OF FIGURES ............................................................................................................................ xiii
Chapter 1: Introduction and Research Problem ............................................................................. 1
Introduction................................................................................................................................. 1
The Research Problem ................................................................................................................ 3
Uncertainty and Risk-Based Economic Decision-Making ............................................................ 7
Optimal Foraging Models ...................................................................................................... 11
Decision-Making Rationale .................................................................................................... 13
Social relations of decision-making ....................................................................................... 20
Analytic Review ..................................................................................................................... 21
Questions and Expectations ...................................................................................................... 26
Dissertation Organization.......................................................................................................... 28
Chapter 2: Risk and Uncertainty ................................................................................................... 30
Introduction............................................................................................................................... 30
Dimensions of Variability .......................................................................................................... 34
Cultural and Economic Perception ............................................................................................ 36
Role of Information ................................................................................................................... 38
Coping and Buffering ................................................................................................................. 41
Mobility.................................................................................................................................. 42
Storage................................................................................................................................... 44
Diversification ........................................................................................................................ 46
Communal Pooling/Group Foraging ...................................................................................... 47
Exchange ................................................................................................................................ 48
Coping Hierarchy and Scale ....................................................................................................... 52
Chapter 3: Modeling Economic Decision-Making......................................................................... 54
Introduction............................................................................................................................... 54
Models ................................................................................................................................... 55
Data Needed for the Models ................................................................................................. 59
Techniques ................................................................................................................................ 63
Resource and Habitat Selection Logic ....................................................................................... 64
Decision Logic ............................................................................................................................ 67
Encounter Contingent Model .................................................................................................... 68
When to move ....................................................................................................................... 69
Ideal Free Distribution ............................................................................................................... 72
Implementing the model........................................................................................................... 74

viii

Chapter 4: Social and Natural Environment ................................................................................. 75
Social and Natural Environment................................................................................................ 75
Landscapes ............................................................................................................................ 76
Biophysical Environment ........................................................................................................... 79
Climate ................................................................................................................................... 81
Substrates .............................................................................................................................. 83
Lake Levels ............................................................................................................................. 85
Biogeography............................................................................................................................. 88
Role of Wetlands (Palustrine Systems) ..................................................................................... 92
Modeling Risk and Uncertainty ................................................................................................. 97
Chapter 5: Predictive Resource Landscape................................................................................. 101
Introduction and Approach ..................................................................................................... 101
Terrestrial and Palustrine Landscapes .................................................................................... 103
Geoprocessing ......................................................................................................................... 105
Results ..................................................................................................................................... 116
Discussion ................................................................................................................................ 126
Revisiting the Initial Research Questions ............................................................................ 129
Conclusion ............................................................................................................................... 132
Chapter 6: Simulation ................................................................................................................. 134
Introduction............................................................................................................................. 134
Approach ................................................................................................................................. 136
Patch Choice (Habitat Selection) ......................................................................................... 140
Diet Choice (Resource Selection) ........................................................................................ 141
Simulation Results ................................................................................................................... 144
Discussion ................................................................................................................................ 150
Conclusions.............................................................................................................................. 153
Chapter 7: Archaeology .............................................................................................................. 155
Introduction............................................................................................................................. 155
Archaeology of the Saginaw Bay Drainage ............................................................................. 156
Economic Models ................................................................................................................ 158
Archaeological Sites ............................................................................................................. 160
Approach ................................................................................................................................. 166
Results ..................................................................................................................................... 172
Discussion ................................................................................................................................ 193
Land Use .............................................................................................................................. 193
Zooarchaeology and Archaeobotany .................................................................................. 197
Conclusions.............................................................................................................................. 199
Chapter 8: Discussion, Conclusions and Summary ..................................................................... 201
Conclusions and Summary ...................................................................................................... 201
Project Problems Revisited ..................................................................................................... 203
ix

Implications for Michigan Archaeology .................................................................................. 204
Resource Environment ........................................................................................................ 204
Uncertainty and Risk Based Decision-Making ..................................................................... 206
Land Use and Diet Models in SBD ....................................................................................... 207
Implications for Eastern Woodland Archaeology ................................................................... 211
Implications for Anthropology/Human Behavioral Ecology ................................................... 218
Critique and Future Directions ................................................................................................ 221
APPENDICES ................................................................................................................................ 224
Appendix A: Landscape ........................................................................................................... 225
Appendix B: Simulation ........................................................................................................... 272
Appendix C: Archaeology ........................................................................................................ 433
LITERATURE CITED ...................................................................................................................... 543

x

LIST OF TABLES

Table 1. Pollen sites ...................................................................................................................... 89
Table 2. Variable manipulations ................................................................................................. 105
Table 3. Data manipulation – reclassify attributes ..................................................................... 109
Table 4. Results summary ........................................................................................................... 123
Table 5. Cover type change by cultural period by square mile .................................................. 123
Table 6. Probability classifications for resource types ............................................................... 142
Table 7. Sites with fauna and flora ............................................................................................. 160
Table 8. Site diversity .................................................................................................................. 169
Table 9. Site occupation diversity ............................................................................................... 169
Table 10. Coping and buffering strategies -relative basis .......................................................... 219
Table 11. Resource communities ................................................................................................ 246
Table 12. Relevant resource community descriptions - limited to study area........................... 249
Table 13. Resource community soils .......................................................................................... 257
Table 14. Soil moisture ............................................................................................................... 271
Table 15. Hunter-gatherer family unit composition ................................................................... 296
Table 16: Species size, abundance and density .......................................................................... 297
Table 17. Simulation species weight and calorie yield ............................................................... 305
Table 18. Male and female resource preference probabilities .................................................. 310
Table 19. Resource probability matrix January to July ............................................................... 315
xi

Table 20. Resource probability matrix August to December...................................................... 323
Table 21. Late Archaic land use .................................................................................................. 329
Table 22. Exploited resources by calories ................................................................................... 331
Table 23. Male exploited resources ............................................................................................ 332
Table 24. Female exploited resources ........................................................................................ 333
Table 25. Total exploited calories by female .............................................................................. 334
Table 26. Exploited calories by male .......................................................................................... 335
Table 27. Possible resource list ................................................................................................... 336
Table 28. Resource calories, size and weight ............................................................................. 349
Table 29. Resource habitat, distribution, density ....................................................................... 362
Table 30. Resource schedule detail – January to June ............................................................... 404
Table 31. Resource schedule detail July – December ................................................................. 418
Table 32. Resource schedule summary ...................................................................................... 429
Table 33. Resource usability ....................................................................................................... 432
Table 34. Sites ............................................................................................................................. 434
Table 35. Site type ratios by county and cultural period ............................................................ 480
Table 36. Site type percentage by river basin............................................................................. 483
Table 37. Relative dates .............................................................................................................. 485
Table 38. Archaeological fauna and flora by site ........................................................................ 487

xii

LIST OF FIGURES

Figure 1. Study area ........................................................................................................................ 4
Figure 2. Project design................................................................................................................... 8
Figure 3. Uncertainty and risk relationship to culture .................................................................. 33
Figure 4. Study counties ................................................................................................................ 78
Figure 5. Terrain view ................................................................................................................... 81
Figure 6. Lake levels ...................................................................................................................... 86
Figure 7. Landscape data model ................................................................................................. 107
Figure 8. Wetland data manipulation ......................................................................................... 108
Figure 9. LA Composite wetlands by time period (in blue color) ............................................... 116
Figure 10. LA land cover and legend ........................................................................................... 117
Figure 11. EW land cover and legend ......................................................................................... 118
Figure 12. MW land cover and legend ........................................................................................ 119
Figure 13. Saginaw (top) and Lapeer counties (bottom) composite landscapes ....................... 120
Figure 14. Midland (top) and Tuscola counties (bottom) composite landscapes ...................... 121
Figure 15. Genesee County (top) and Tobico Marsh area (bottom) composite landscape ....... 122
Figure 16. Tittabawasee to Saginaw river course profiles .......................................................... 125
Figure 17. Cass to Saginaw river course profile .......................................................................... 125
Figure 18. Simulation data model ............................................................................................... 138
Figure 19. Patch selection data model ....................................................................................... 139
xiii

Figure 20. Resource selection logic model ................................................................................. 143
Figure 21. Resource choice effort in a patch .............................................................................. 144
Figure 22. Annual exploitative events (combined male and female) ......................................... 145
Figure 23. Diet choice events by gender (male) ......................................................................... 146
Figure 24. Diet choice events by gender (female) ...................................................................... 147
Figure 25. Actual caloric yield (female) ...................................................................................... 148
Figure 26. Actual caloric yield (and probability of success (with 10% uncertainty factor) ........ 149
Figure 27. Persistent places ........................................................................................................ 172
Figure 28. Site density map (Saginaw County in inset)............................................................... 173
Figure 29. Local base levels and moraines.................................................................................. 174
Figure 30. LA sites and land cover .............................................................................................. 175
Figure 31. EW sites and land cover ............................................................................................. 176
Figure 32. MW sites and land cover. .......................................................................................... 177
Figure 33. Saginaw and Lapeer County sites and land cover ..................................................... 178
Figure 34. Midland and Tuscola County sites and land cover .................................................... 179
Figure 35. Genesee County and Tobico Marsh ares sites and landco ver .................................. 180
Figure 36. Clinton and Iosco County sites and land cover .......................................................... 181
Figure 37. Bay and Huron County sites and land cover. ............................................................. 182
Figure 38. Site interpolation (kriging) . ....................................................................................... 183
Figure 39. Thiessen polygons ...................................................................................................... 184
Figure 40. LA sites in proximity to resource communities ......................................................... 185
Figure 41. EW and MW sites in proximity to resource communities ......................................... 186
xiv

Figure 42. Activity areas .............................................................................................................. 187
Figure 43. Site type change by river basin .................................................................................. 188
Figure 44. Burial and cache sites change by river basin ............................................................. 189
Figure 45. Diet ratio indices over time ....................................................................................... 190
Figure 46. Simpson's diversity index ........................................................................................... 191
Figure 47. Non core and Schultz diversity index ........................................................................ 192
Figure 48: Wetland implications ................................................................................................. 203
Figure 49. Pollen sites and relative elevation. ............................................................................ 226
Figure 50. Maple and Flint River course profiles ........................................................................ 227
Figure 51. Shiawassee and Pine River course profiles ................................................................ 228
Figure 52. Base model - terrain and digital elevation ................................................................. 229
Figure 53. River networks ........................................................................................................... 230
Figure 54. Base model – 1800s wetlands ................................................................................... 231
Figure 55. Local base levels ......................................................................................................... 232
Figure 56. Water table close to surface (<1 meter) .................................................................... 233
Figure 57. Base model – water table and recharge .................................................................... 234
Figure 58. Base model - hydric soils and drainage ..................................................................... 235
Figure 59. Soils drainage by class ................................................................................................ 236
Figure 60. Ponding begin by month ............................................................................................ 237
Figure 61. Ponding end by month............................................................................................... 238
Figure 62. Water table by depth ................................................................................................. 239
Figure 63. Soils ............................................................................................................................ 240
xv

Figure 64. Soils slope................................................................................................................... 241
Figure 65. EW composite wetlands ............................................................................................ 242
Figure 66. MW composite wetlands ........................................................................................... 243
Figure 67. Clinton (top) and Iosco counties (bottom) composite landscape. ............................ 244
Figure 68. Bay (top) and Huron counties (bottom) composite landscape ................................. 245

xvi

Chapter 1: Introduction and Research Problem
Introduction
Hunting, fishing and gathering has been the dominant economic mode throughout
much of human history. The diversity and longevity of foraging practices have been and
continue to be a focus of anthropological inquiry, where the foremost approach employed is
the study of economic behavior with a focus on subsistence and settlement. These behaviors
are adaptive; continually changing in response to the changing natural environment and to the
broader cultural system, driven by goals that seek to satisfy basic livelihood requirements.
Goals that drive economic behaviors include both short and long term strategies including
economic security, efficiency and prestige.
Economic security (i.e., reliability), the consistent acquisition of minimum caloric
requirements, is perhaps the key goal that influences economic behavior among the various
other complementary strategies, including efficiency or maximization of economic return,
biological factors (i.e., nutrients and energy), and social factors (i.e., prestige, status). Security is
attained through social and economic coping and buffering practices, including the use of
mobility, pooling and diversification of resourc.es, storage, and the exchange of social
relationships and resources for security (Agrawal 2001; Halstead and O'Shea 1989b). Further,
hunter-gatherer (HG) individual agency and social organization through a division of labor plays
an important role in attaining security. The need for economic security and linked social and
economic practices are, therefore, important for our understanding HG adaptations.

1

Economic security can be best studied in contexts that feature environmental instability.
Contexts with non-homogenous biophysical environments where resources are
spatiotemporally variable are ideal. Resources in temperate wetlands are a case in point, with
striking spatiotemporal variability, where the distribution and density of wetlands play an
important role for availability of resources. Further, the seasonality of temperate environments
and linked animal and plant dynamics also contribute to resource instability. The challenges
posed by the environment provide a context for the exploration of processes and the role of
coping and buffering strategies for attaining economic security. Therefore, the research
presented here seeks to understand HG economic and social practices in variable
environments, through role of buffering and coping responses to spatiotemporal heterogeneity
in dynamic wetland environments during the Late Archaic (5000-2500 B.P.), Early Woodland
(2500-2100 B.P.) and Middle Woodland (2100-1500 B.P.) periods in the Saginaw Bay Drainage
(hereafter ‘SBD’) of Michigan. This research is undertaken through the development of models
aimed at recreating probable past contexts, behaviors, and analysis of land use and diet choices
in SBD, thus addressing both problems in ecological and social environment. This introductory
chapter presents an overview of this project by stating the problem, theoretical framework
employed, approach taken, and questions posed.
The organization of the volume is intended to address the research problem in an
approach that individual chapters build upon each other. The first four chapters entail 1)
introduction and problem, 2) theory-uncertainty and risk, 3) methodological review -modeling,
and 4) effective social and ecological environment. These background chapters are followed by
three analytic chapters. These chapters are organized in a standard format: methods, results
2

and discussion. Methods relate to the immediate approach that has been employed, results are
the products of analysis and discussions are the interpretation of key questions framed in
current and previous chapters. This way, each chapter builds upon the others, culminating in
the final conclusions and implications section and suggestions for future directions for research.
The Research Problem
Ethnographic and archaeological studies demonstrate HG groups actively choose to
pursue their lifeways given the presence of alternative adaptive strategies (i.e., low level food
production, agriculture, intensification, sedentism etc.). These societies employ flexible social
and economic strategies to maintain the flexibility afforded by hunting and gathering. The
continuation of HG mode of production is often understated and undervalued due to greater
focus on agricultural domestication and due to the lack of understating of the processes and
factors that contribute to HG continuity and longevity (Hitchcock and Ebert 1984; Raymond and
DeBoer 2006). In fact, the processes and factors that sustain HG economy can provide an
evaluative basis for alternative economic strategies. HGs in SBD are case in point, with
considerable challenges to their economy originating from both the ecological and social
environments.
Ecologically, the study area is a region with extensive spatial heterogeneity and ecotonal
variability. First, the SBD contains an extensive heterogeneous wetland area with dramatic
changes in the distribution and density of wetlands from the Late Archaic through the Early
Woodland period. In the Middle Woodland, the landscapes rapidly transformed back to

3

Figure 1. Study area
For interpretation of the references to color in this and all other figures, the reader is
referred to the electronic version of this dissertation.
4

Inundated areas due to higher lake levels (Garland and Beld 1999; Kingsley, et al. 1999; Lovis, et
al. 2001; Monaghan and Lovis 2006; Robertson, et al. 1999). Further, information on the
hunting and gathering economy and ethnographic analogs of wetland environments is limited
due to the lack of scholarship and contemporary analogs (but see (Nicholas 1991)). The role of
wetlands in economic adaptation is understated despite evidence of early human society’s
dependence on these environments (Bernick 1998; Brown and Vierra 1983; Clark 1954; Kelly
1990). Without reference to the role of wetlands and complex environments, the knowledge of
foraging adaptations and the diversity of social and economic practices remain incomplete.
Even with the intensive and long-lived archaeological efforts in the SBD, an explicit and
systematic inquiry about the role of spatiotemporal resource variability of wetland
environments on HG economy has yet to be undertaken. Systematic inquiry in the area is made
difficult from poor preservation in wetland landscapes. This lack of understanding leaves
incomplete information about the factors that influence land use and diet choice over time.
Second, the SBD is located at the northern fringes of the effective growing environment
for agriculture, further complicating the resource environment. Both archaeological and
environmental research reveals that ecotonal environments are excellent indicators of
environmental perturbations of varying magnitudes, largely reflected by changed plant and
animal biogeography. Plants and animals selected for consumption allow us to identify the
shifting plant and animal communities and social and economic practices from Late Archaic to
Middle Woodland periods. Wetlands, hydrology and marked seasonality, and a marginal
growing environment exacerbate the environmental uncertainly of SBD by introducing
spatiotemporal variability.
5

Socially, the environment of the Eastern Woodlands poses further challenges for
hunting and gathering continuity. SBD groups persisted as HGs despite social changes, including
the likely exchange of key exotic and indigenous domesticates and economic changes in
adjacent cultural areas including the advances in food production through the use of key exotic
and indigenous domesticates; increased sedentism; social hierarchy and introduction of
ceramics; and development of incipient social complexity (i.e., inequality, marked hierarchy).
These problems are studied through two coupled modeling approaches. First, the ecological
environment is reconstructed in the SBD of Michigan to explore the structure of changing
wetland landscapes and resources (see Chapter 3 and Chapter 5).
The resulting ecological and social environments, drawn by ethnographic analogs,
provide a predictive landscape for land use and context for diet choices. Diet and land use
decision-making are based on available resources identified through habitats,
microenvironments and niches derived from soils and climate for the availability of
economically important plant and animal resources at both local and regional scales during the
Late Archaic, Early and Middle Woodland periods. The predictive landscape is driven by
understanding the distribution of wetland environments and linked biotic and abiotic
inventories. This model will provide prehistoric wetland context for SBD HG choices regarding
land use and diet selection.
Next, a heuristic model is employed, in the form of a behavioral simulation based upon
Optimal Foraging Theory (OFT) concepts of diet and patch breadth models. The decisionmaking simulation of possible selections of plant and animal resources provide land use and
diet patterns in a changing wetland and resource context. These approaches generate models
6

that can be evaluated against archaeological, site and diet (i.e., faunal and floral) datasets to
generate interpretations about culture and, specifically, economic and social practices
employed by SBD HGs to buffer against and cope with changing landscapes. The comparison of
models to archaeological data will allow for the understanding of the role of wetland
uncertainty and risk, and coupled social and economic coping and buffering strategies. The diet
selection provides us with a possible diversity of animals and plants that have been exploited
and spatiotemporal strategies and implications for changing diet and land use. The
development of these models requires the consideration of the factors that plays a role in
economic decision-making.
Uncertainty and Risk-Based Economic Decision-Making
This project employs an economic security framework as the basis of decision-making
rationale. Decision-making is an evolutionary cognitive process resulting in the selection of an
action from a number of alternatives. Decision-making modeling approaches strive to
understand the social and biological factors (causal or correlative) resulting in economic
practices and linked social relations of groups. Decision-making about SBD land use and diet can
have significant implications for economic and social relations, therefore the culture of
prehistoric HG communities. Further, effective decision-making is observed to contribute to the
adaptive capacity of HGs. Archaeological scholarship addressing these issues are problematic
due to a number of factors; vagaries of preservation, and the focus on highly visible, easily
accessible, and large material inventories (Binford 1978a; Binford 1981; Schiffer 1976)..

7

Step 1

Behavior
Simulation (diet
and patch breadth)
Basis

Chapter 5

Chapter 6

Figure 2. Project design
8

Archaeology
Sites, fauna &
flora
Basis

Habitats
Preferred

Digital Elevation Models
Soils
1880’s GLOS land cover
Wetland inventory
Hydrological flow

Ethnography
Demography
Behavioral ecology

Resources

Basis

Diet
Choices

Habitats

Landscape
GIS modeling
(hydrological)

Step 3

Step 2

Spatial Comparison
Site-habitat
organization
Site & Resource
diversity

Chapter 7

In an effort to resolve these shortcomings, alternative approaches focus on deductive
models constructed from contemporary foraging analogies (Fitzhugh 1972; Thomas 1973;
Winterhalder 1981a)
The contextual basis is provided by the natural environment where social and economic
behavior takes place. The environment, then, provides the basis of subsistence choices and
serves to fulfill biological and social requirements of groups. Economic decision-making
strategies are then solutions to a number of basic problems: 1) securing sufficient energy
(caloric) intake, 2) ensuring sufficient nutritional intake, 3) ensuring sufficient regularity of these
intakes for survival and assuring satisfaction of other non-biological needs and goals (e.g.,
hides, antlers, taste, prestige, security). Solutions, therefore, require decisions about: 1) which
resources to use, 2) how much of each resource to use, and 3) how and when to exploit
resources (Jochim 1981). These solutions can be interpreted here using models of optimal
behavior. Optimal behavior models allow us to visualize how people would behave given the
specific conditions were the only factors affecting their behavior and should be considered only
as a baseline of expectations, not as a description of real behavior. These heuristics generate
predictions that can be compared to empirical data to expand our understanding of HG
economy and society.
The most critical challenge to economic security is the presence of variability in the
decision-making environment. Few studies have explicitly used risk and uncertainty as an
explicit analytic variable in the study of HG economy (but see (Bates 2007; Clark 1990; Halstead
and O'Shea 1989a)). Human understanding of variability can be thought of as two interrelated
concepts of risk and uncertainty. Uncertainty is the state of having limited knowledge such that
9

a future state or outcome is difficult to describe due to the possibility of multiple outcomes
(Cashdan 1990a; Clark 1990; Knight 1921). Risk is a state of uncertainty where possible
outcomes have an undesired effect or a loss (Stephens 1981; Wiessner 1982b; Winterhalder
1986, 2007). The concepts can be observed as predictable and unpredictable variations in an
ecological or social environment over time. This variation has implications for both the foraging
economy, diet choice and land use in the SBD. For example, food quest outcomes that fall short
of basic caloric needs are the result of risks attributed to the resource environment. An
individual hunter’s poor hunting ability or poor choices (i.e., skill and knowledge) are social
factors that contribute to uncertainty and risk. Further, HG economies can be conceptualized as
both an organization around resources as well as around other persons in the social relations of
production. Social strategies for reducing risk and uncertainty expand explanatory foci in social
and natural resources.
In order to use uncertainty and risk as an analytic framework, the cognitive and
behavioral realm needs to connect. This connection is made by examining and employing
empirical and theoretical analogs of nonhuman foragers and their feeding strategies (Charnov
1976; MacArthur and Pianka 1966). These animal behavior and ecological studies provide data
about the nature of foraging, data that are applicable to humans as well. Ecological models are
then an analytical tool, not a mirror of reality, and they do not deny a role for individual agency,
as long as it is examined within its social and ecological context. Most ecological approaches in
the study of HGs have a very narrow focus on subsistence, demography and settlement, for
which direct relationships with the natural environment are most clear. The archaeological
record is an ideal context for modeling due to the variability in strategies not found in the
10

ethnographic record that reflect the changing cultural response to the environment, and
diachronic perspective on human behavior. Further, studies have increased our understanding
of the relationship between behavior and patterns in material remains, largely through
ethnoarchaeological studies of living groups (Binford 1978b; Kroll, et al. 1991; Yellen 1976).
Ecologically derived human behavioral studies are based upon and guided by the Principle of
Least Effort (i.e., people tend to work no harder than necessary in order to satisfy biological
subsistence needs and cultural goals, and assume the minimization of cost is the central
objective of HG peoples to economic decision making (Hewitt 1983; Keene 1981b, 1983;
Reidhead 1980; Smith 1983; Winterhalder 1981a; Zipf 1949). These models assume that
humans have rationality in goal formation and knowledge of the availability, costs and benefits
of resources. The foremost approach in the use of principle of least effort is OFT.
Optimal Foraging Models
OFT is a decision-making approach derived from cognitive and ecological theories, which
explains base human motivations (i.e., diet, nutrients) as choices. OFT has been typically
applied to non-human animal behavior, highlighted by three main assumptions: 1) selection
operates consistently and intensively over long periods of time, 2) optimal behavior is
attainable, and 3) selection favors energy efficiency (Keene 1983; Smith 1983). These models
are based on the neo-Darwinian assumption that natural selection and competition are an
inevitable outgrowth of reproduction in a finite environment (Pianka 1974). Natural selection
will favor foraging behaviors that result in maximum fitness with regard to the operating
constraints. There will be differential survival of those behaviors, which allow for an individual
or population to achieve goals in a specific environment. Given a set of resources with specified
11

characteristics, OFT models propose how these resources will be used. In sum, OFT states that
foragers maximize their net return rates of energy intake while foraging, thus are optimizing
their return. Assessment of behavior within an optimization framework requires a currency or
cost-benefit metric that is significant to the adaptive goal (Schoener 1971). The currency that
has been consistently used is the net rate of energy intake (Pyke, et al. 1977; Smith 1979;
Thomas, et al. 1979). OFT approaches include Optimal Patch Use, Foraging time, diet, and
foraging group size address a number of archaeological questions including site location, group
organization, dietary composition and prey depletion(Winterhalder 1981b).
OFT is used to generate testable hypotheses about the ‘best’ strategies for particular
circumstances. This ecologically based approach has the flexibility to address both the
ecological and social components of decision-making. OFT explains adaptation strategies that
are optimal intended to maximize the fitness of a population (Krebs and Davies 1997; Maynard
Smith 1978; Pyke, et al. 1977). OFT makes a number of useful predictions about human
responses to spatiotemporal variability or the decrease in high-ranked resources resulting from
resource depression (see Chapter 3 to read a full coverage of relevant Optimal Foraging
approaches used in the study). If the goal is to increase utility or reduce risk, HG should: 1)
broaden diet to include lower rank species or specialize in few sustainable resources, 2) include
wider patches, including lower rank patches, 3) intensify production, create suitable habitats
for high ranked dependable resources, 4) form larger groups that that create efficiencies
through group foraging – pool resources, information, networks therefore reducing variability
through sharing and 5) invest in physical and social storage. These behaviors contribute to
security: forager group size, exploitative pressure, habitat enhancement, resource flexibility,
12

suppression of competitive predators, and social institutions and beliefs. OFT, then can be used
as the underlying operational model for HG decision-making based on underlying goal.
Decision-Making Rationale
Scholarly attention to principles underlying decision-making has focused on adaptive
strategies concentrating on meeting biological needs and wants. Basic biological factors
proximate to the individual include energy and nutritional requirements. At an intermediate
level, applicable to the totality of economy, are factors of efficiency and economic security.
Last, underlying social dimensions include division of labor and ideational factors
including taste and prestige. Although treated separately, these factors are interconnected and
dependent on the topic of inquiry. The research undertaken in this dissertation reframes risk
and uncertainty as a core underlying framework that contributes to social (i.e., prestige,
division of labor), economic (i.e., security, efficiency of labor) and biological factors (i.e.,
nutrients and energy).
Risk minimization or reliability and efficiency or ease is suggested as the most important
in forager decision-making. Both factors are ultimately related to individual reproductive fitness
and are time dependent and interconnected. Foraging efficiency is an immediate goal, while
risk minimization is a longer-term strategy. This research treats these goals as both short and
long term, complementing one another, and will be treated as variables dependent on the scale
of time.
Efficiency goal has been the basis of a number of studies that seek least-cost solutions
to foraging problems; including studies of maximizing net acquisition efficiency (Jochim 1976b;

13

Winterhalder 1981b), for hunting decision models (Mithen 1990), and linear programming
solutions (Keene 1981b; Reidhead 1979). Depending on the situation, other measures may be
better indicators of choices. Other measures of labor efficiency include output per unit time or
land (Jochim 1981; Torrence 1983). Labor efficiency per unit of time may guide choice and at
the same time also varies greatly between cultures (Kelly 1995a). Costs associated with unit
time are important because they preclude other activities. For example, scheduling conflicts
may arise for resource seasonality and other competing cultural demands for the use of time.
Time efficiency is likely the most important to cultures at northern latitudes, with greater
seasonality in resource availability. If neither land nor time is constrained, then labor efficiency
may be the best guide to decision-making. Labor-related ease of collection, or net yields for
labor input, may be the alternative criteria for resource selection (Jochim 1981).
Another determinant factor of decision making is the energy budget. HGs differ vastly in
their energy budget, as multiple factors affect labor efficiency including search, pursuit,
capture, and processing costs, all of which are affected by resource productivity. Additionally,
the technological and organizational characteristics of a culture can influence efficiency and the
relationships of measures of efficiency (Jochim 1981). For example, the introduction of gill nets
during Late Woodland times in the Great Lakes dramatically increased the efficiency of
acquiring temporally limited resources (i.e., spawning fish) (Cleland 1982). Further, the
ethnographies shows that prey and/or package size are strongly correlated with procurement
efficiency: big game hunting can be tremendously efficient. Exploitative efficiency related to
time and labor costs also makes larger animals more preferable. In addition to animal size,
additional variables such as density, aggregation, wariness, mobility, and reliability may impact
14

food selection (Hewitt 1983; Jochim 1976b, 1981; Winterhalder 1977, 1981a, b; Winterhalder
and Smith 1981).
Ethnographic studies of the classic Cree example consider variables of exploitative
efficiency, choosing small mammals, birds or fish rather than alternative choices. Often, the
killing of large and small animals is opportunistic within an exploitative round (Winterhalder
1977, 1981a). Regarding the high efficiency of fishing at certain seasons among the Cree, some
forms of plant gathering by the Ache suggest the importance of prey aggregations and
technology (nets and surrounds) that enhance efficiency (Hawkes, et al. 1982; Winterhalder
1981a). The package size, as defined by individuals or clusters, whether naturally or culturally
created, may be a more important variable than prey size. Technology can lower search costs
and pursuit costs, such as traps and dogs, which can account for cases for high efficiency in
procuring small mammals such as hare (Winterhalder 1981a). Efficiency in food procurement or
camp location can create free time for other activities (exchange, accumulation of surpluses)
that may increase reproductive fitness and that can be used or manipulated to an individual’s
reproductive advantage (i.e., securing mates, attracting followers).
Observed subsistence patterns of human populations of similar makeup (size and
environment) demonstrate that human decision-making can also be driven by goals other than
labor efficiency (Bettinger 1991; Clarke 1972, 1977; Ellen 1982; Jochim 1976a, 1981). Efficiency
is the ratio of resource output to the input of labor that is measured over a long time period.
But, the ratio can be quite variable over a shorter interval period resulting in life threatening
situations. Therefore, efficiency may not be the ideal rationale for decision-making.

15

Alternatively, risk minimization approach recognizes that food be obtained within each shorter,
behaviorally significant period perhaps a day. Ethnographic evidence shows great variation in
procurement success among resources and habitats; among seasons and years; among
individuals and groups, since all environments and economies contain some variation and risk.
Reliability, the expectation of finding a given resource is a conscious goal about food choice,
habitat use, and camp location. Response to risk can take many forms including diet
diversification, food storage, pooling and sharing and exchange (Agrawal 2001; Halstead and
O'Shea 1989b; Kaplan and Hill 1985; O'Shea 1981; Wiessner 1982b; Winterhalder 1981a).
Economic security affects decisions. Security and the predictability of alternative options
are critical to decision-making (Cashdan 1990b; Clark 1990; Cleland 1976; Jochim 1983; Tversky
and Kahneman 1981). People pursue strategies that, given a set of alternative choices, best fit
the least risk option(s) (Coombs 1980). For example, HGs are observed to respond to resource
scarcity and variability at various temporal scales (i.e., seasonal, annual and long term) by a
combination of strategies including mobility, diversification, storage, and exchange (Halstead
and O'Shea 1989a). In general, economic security addresses future welfare even at the risk of
immediate and occasional losses (Clark 1990; Halstead and O'Shea 1989b; Tversky and
Kahneman 1981). The ideas of risk and risk tolerance are constructed from past experiences
and contexts. From these experiences, people are able to implicitly form probability estimates
over possible future events. Given a set of options, people will establish a hierarchy of
preferences and rank those according to the schedule and value of the goals they seek to satisfy
(Cashdan 1990b; Elster 1989; Jochim 1981).

16

A key factor that drives economic security is seasonality. Diet choices and hierarchy of
diet preferences can vary throughout the year depending upon the seasonal availability,
variation and characteristics of resources and cultural factors. For example, the effects of
spatial variation on reliability and diversity are high when the variance of resource abundance is
greater than the squared mean abundance. Therefore, mobility of HG should be high in poor
environments with few resources, all maximally out of phase with each other, and should be
low when resources show either little spatial variation or when they vary in phase (Harpending
and Davis 1977). Additionally, HGs are suggested to behave in a manner to maximize
subsistence security by different strategies based upon packing thresholds employing shifting
combinations of sequentially scaled, risk pooling, and cooperative networks as well as
expanding niche breadth and intensification (Binford 2001). Summarily, subsistence decisions
are made through the evaluation of potential payoffs of various strategies, selecting the one
that suits the environmental context and cultural goals/objectives that satisfy the perceived
needs of the season.
The biological underpinning of security based decision-making includes nutrition and
energy acquisition. Energy, the base requirement of living organisms, is an easily quantifiable
variable through the transformation of food matter into energy and can be measured through
kilocalories. Energy is the calculation of the ratio of time required for economic activities
(locating, capturing, transporting, storage, maintenance, processing and consumption); a simple
calculation that energy expended or output must not exceed input, food consumed (Kemp
1971; Rappaport 1984; Smith 1983).

17

Nutrition, the satisfaction of biological requirements for vitamins and minerals such that
biological (metabolism, muscular and skeletal development) minimums are attained, is a critical
biological requirement is observed not to direct decision-making about diet. Most resource
environments, especially temperate climates, offer sufficient diversity of resources such that
nutrition requirements are typically met (Jochim 1981).
A number of other social goals influence diet selection, including factors linked to taste,
cost and prestige (Egan 1993; Messer 1984). The pursuit of prestige can be observed through
the exploitation of prey size. In addition to efficiency provided by large meat packages, resulting
from the increased net return rate, social prestige is also attained by the ability and skill of the
hunter. Exceptional ability and skill is demonstrated by their food contribution can serve to
enhance their relative value and prestige to other members of society. A number of examples
also show that the capture of large game animals brings a hunter more prestige (Jochim
1976b:21; 1981:86-90; Winterhalder 1977, 1981b).
A number of non-food related goals are also sought as part of the food quest, such as
game animal hides for clothing and shelter; bone and antler for tools; plants for medicinal,
technological, ritual and symbolic value (Keene 1981b). On the whole, fulfillment of non-food
values is also assumed to be embedded within the food choices (Binford 1978b). Social
objectives such as information sharing, socialization, goods exchange, and values of resources
affect resource decisions. Maple sugaring, a labor intensive activity, was pursued and provided
a valuable source of food during times of scarcity and served as a valuable exchange item
(Henry 1969:211; Holman and Egan 1985). Group efforts to gather maple sugar afforded people

18

a chance to socialize after a long winter season of isolation (Baird 1898; Densmore 1974).
Group aggregation allowed the members of a community to exchange information about both
the landscape wherein they dwelt and surrounding areas. Further, the gathering of moss, a
plant that serves a whole host of purposes, is also important (Kimmerer 2003). In sum,
utilitarian goals – explicit and implicit – acknowledge factors including energy, nutrition,
efficiency, and taste; non-utilitarian goals, prestige and security affect economic decisionmaking and energy budgets (Bettinger 1991; Cashdan 1990b; Ellen and Fukui 1996; Jochim
1976b, 1981, 1983; Riches 1982a; Speth and Spielman 1983). These factors have to be
compared and weighed against the composition, structure and productivity of the
environment.
In order to understand the decision-making process, two key factors must be taken into
consideration: context and behavior. The contextual basis is provided by the environment
where social and economic behavior takes place. Economic behavior is the result of a cognitive
rationale of decision-making given its context. In this way, these components of decisionmaking are linked and hierarchical. In decision-making context, the ecological environment can
be studied through the spatiotemporal orientation of resources. The economic and social
behavior can be studied through the analysis of diet and land-use decision-making. In order to
do this, we must address 1) estimates of environmental and resource variations in the past, and
2) models that must embed individual short-term subsistence decisions within a broader
temporal, spatial and social context. Risk can be understood in archaeology by the treatment of
the structure of resource variability, creating models of risk mitigation, shifting seasonal
resource ranks, and the implications of site redundancy and reoccupation (Jochim 1981; Mithen
19

1990). As social communities, HGs are able to transcend limitations in the ecological
environment through social practices. Without the treatment of these variables, our
understanding of decision-making is incomplete.
Social relations of decision-making
The HG economy characterized as simply the fulfillment of basic necessities of life –
food, water, shelter – would be an oversimplification and reductionist. This framework results
in an environmental deterministic endeavor and, therefore, does not provide a necessary
understanding of the social and ideational dimensions of the culture. One important social
analytic framework is division of labor. The division of labor in economic decision-making is
observed through gender and age groups. Women and children are observed to exploit
resources closer to residential sites by gathering plants; hunting and trapping small mammals
and exploiting aggregated resources, such as anadromous spawning fish (Claassen 1991; Egan
1993; Jochim 1981, 1988; Nelson 2004). The gathered food is likely shared with all members of
the group. The role of women in gathering resources is vital because their contribution is more
likely to be a consistent, predictable and secure contribution to diet. Their contribution is
shared throughout the group and ameliorates the variance in hunting returns and to risk
incurred by men’s activities. Further, the role of age and sex groups is important. Women’s
influence is important and can determine choices regarding settlement and critically, for this
research, for land use and diet choices (Kelly 1995a:261).
Risk and uncertainty can play an important role in age and sex group influences diet and
land use selection. Women and children are likely to recognize local level variance earlier and
make decisions about when and where to move (Kelly 1995a; Zeanah 2004; Zihlman 1981). The
20

role of women in management of risk and uncertainty is also important through the
information they hold. Women and men retain different types of knowledge about resources;
women tend to have greater information about resource structure and variability based on the
spatial predisposition of their purview and influence. For example, Yup’ik men hold information
about landscapes at a larger scale (i.e., regionally, location of landscape features), and they also
maintain information about their relationships in greater detail (Funk 2010). The storage of
information creates a risk-minimizing strategy by specialization and the overlap of information
across genders, where one gender holds the breadth and one stores the depth
(interrelationship) of knowledge.
Analytic Review
The aforementioned social and biological goals play an important role in economic
decision-making. The role of these goals in the context of environmental variability is
incomplete and requires greater understanding. This research explores factors in diet choice
and land use that address the spatiotemporal distribution of resources as well as biological and
cultural needs within a context of a changing environment and economic security. These land
use and diet choice strategies can have considerable implications in the understanding of
overall HG culture, economic adaptation and continuity, and short term and long term
trajectories.
Two analytic frameworks in the study area are presented: spatial and behavioral.
Spatially, archaeological analysis often focuses on site or local level dynamics, not considering
the regional environment. Conversely, regional analysis, when undertaken tends to overwhelm

21

local site level patterns. Typically, focus is placed on places with large and dense site
distributions, rich material remains or places with monumental structures. Archaeological
research is forced to use small areas because of limitations of available data, resulting in
models of low gain (Ebert 2000). Better understanding requires a regional analysis of behaviors
(Kowalewski 2008; Schroeder 2004). Spatiotemporal variability as an analytic basis is critical to
understanding subsistence and settlement, as well as critical to understanding social
dimensions to address this problem. Further, repeated studies have addressed HG decisionmaking with a focus on a key adaptive strategy, ignoring the influence of alternative options. In
order to explicate the archaeological pattern, a model that incorporates multiple strategies is
required. We must investigate variability-related human behavior by incorporating multiple
coping/buffering strategies from a cultural framework. By framing social relations and
organization as mechanisms for adaptation, we create a decision-making model that takes into
consideration subsistence strategies that incorporate a variety of adaptation practices.
In the study area, economic decision-making approaches have been and continue to be
critical to understanding adaptation and the processes for cultural change. The combination of
spatiotemporal variability, habitat shifts and expansion and contraction of wetland
environments led to the intensification of a wide range of resources, especially increased focus
on plant foods during the Late Archaic; therefore setting a stage for depopulation of Saginaw
Valley in the Early Woodland, then followed by subsequent Middle Woodland expansion during
high water phases. Within this context, the HG decision-making is observed to be continually
evolving to satisfy cultural and environmental demands in order to meet a number of social and

22

biological goals and opportune area for inquiry into processes and factors of adaptation and
cultural change.
The archaeological record provides a spatiotemporal perspective on behavior in variable
contexts that expands our ethnographic knowledge. Archaeological interpretations are often
constrained by localized research efforts, with limited understanding of regional patterns as
well as the complexities of coupled interactions between HGs and variable environments.
Questions remain about decision-making with respect to environmental variation and linked
spatiotemporal resource structure. Given that forager groups relied upon particular plant and
animal resources, an understanding of their availability in changing environmental contexts is
important to decision-making. To understand the role of variability, we must explicitly frame
decision-making in terms of spatiotemporal resources and cultural responses to uncertainty.
These models will help us to better understand past environmental dynamics and human
behavior, providing valuable data and models of prehistoric HG adaptations.
Previous modeling efforts in the study area have sought to reconstruct resource
landscapes in order to answer economic decision-making (Egan 1993; Keene 1981b). A first of
its kind at the time, a deductive model simulation using ecologically-based OFT, a linear
programming model using average costs measures for energy, and nutrients and hides for
resource utility (Keene 1981b). This linear programming model is employed in a non-marginal
environment with presettlement forest distributions, using fish and wildlife data based upon
species richness and seasonal cycles in a given Saginaw River valley habitat. Key factors include
the input-output ratio of kilocalories and essential nutrients, and raw material requirements
quantified through net optimal energy capture. Lowest costs choices were rank-ordered in
23

preference, with the resulting satisfaction through low-cost choice considering resource
processing and storage costs and incorporating non-food costs (e.g., clothing).
This endeavor develops a suite of seasonal resources and economic seasons, and
specifically stresses the importance of plant resources contributing to Late Archaic diets (Keene
1981b). The study derives the monthly suite of primary, secondary and marginal resources that
is constrained by various factors during winter. He suggests four economic seasons, two narrow
spectrum and two broad spectrum. Broad spectrum activities for winter are fishing in the
winter; broad spectrum foraging in summer, and intensive deer hunting in the fall. Plant foods
hold a high value during certain seasons. Archaeological expectation for each of the seasons is
also posited. Subsequent critiques of the model question the devalued role of nuts mast in the
model.
Other related archaeology-based subsistence and settlement efforts also provide insight
into economic decision-making. Another set of literature uses general subsistence models and
suggest that Late Archaic groups chose an optimal solution from resources that would satisfy
basic needs for the least amount of effort during four economic seasons. Therefore, fish would
be exploited during spring at sites, broad spectrum collecting would take place during the
summer, intensive deer hunting would occur during the fall, and broad spectrum hunting for
small game such as beaver and raccoon and stored foods such as nuts and seeds would be
gathered during the winter (Keene 1981a; Robertson, et al. 1999). However, these models have
underestimated the diversity of forager resources choices and strategies. For example, nut
exploitation during the fall, deer and wapiti during summer, and the importance of mobility and
exploitation of resources in the interior of the SBD (regional exploitation) are choices and
24

strategies that are not addressed by these studies (Robertson, et al. 1999; Smith and Egan
1990).
Next, to explain food procurement strategies, a decision-making model based on
multiple goals of taste, efficiency, prestige and a combination of these variables is used within
the context of the division of labor. This simulation of resource selectivity suggests that highly
productive resources such as fish, waterfowl, wetland tubers, and choices based upon task
groups (female/juvenile) formed to exploit these aggregated resources were important,
especially during the fall and spring. The Weber I site shows a preference for fatty nuts over
acorns for their taste, while the Schmidt site suggests that variation in the availability of specific
resources or efficiency is the primary goal. In summary, the flexibility of subsistence choices and
their relationship to social and cultural goals is an important diet strategy (Egan 1993).
Other noteworthy archaeological approach uses ecological productivity and land-use
patterns to understand Late Archaic subsistence by arguing for resource habitats, including
uplands, upland margins, and lowlands exploitation for coping with resource variability and
change (Lovis 1984, 1986, 1990b; Lovis and Robertson 1989). HG decision-making is focused
toward exploiting productive niches rather than specific individual species resulting from
temporal or periodic (predictability) and resource productivity (abundance and reliability)
variation. An economic model has suggested that the radial configuration of river networks
aided in maintaining and reinforcing this adaptation by information gathering and maximizing
access to all regions (Lovis 1990a; Robertson 1987).
These modeling and archaeological efforts emphasize a comprehensive set of
environmental and ecological variables (seasonality, resource distribution, nutrient values,
25

nutritional requirements, food-related labor costs, pursuit and processing costs, non-food
requirements, prey characteristics [size, density, mobility, and aggregation size and
assumptions about technology], seeking to reconstruct environments and vegetation, resource
structure, and seasonality in order to predict subsistence choice strategies. HGs operate within
these static environmental variables in these studies. They are treated as passive entities who
behave to consume resources. However, our understanding of their behavior suggests that
people interact with the environment dynamically, modifying their surroundings to suit their
short- and long-term needs. Therefore, the environment must be viewed as a dynamic system,
with coupled interactions and feedbacks between the HG and the environment being given
priority for determining behaviors.
Questions and Expectations
The proposition employed herein states that a foraging adaptation is explained by the
social relations or structure of their coping and buffering strategies, rather than simply by the
abundance and scarcity of the resource environment. The organization of the research is
organized through questions that contribute to the overall goals. These questions take into
account both a landscape and behavioral perspective understood through spatiotemporal and
scalar (i.e., short term, long term, local and regional) context of human interaction in the
Saginaw Bay Drainage. The results will provide a better understanding of SBD Late Archaic, Early
Woodland and Middle Woodland economy and adaptation through land use and diet choices.
In order to understand how HGs copes and buffer against uncertainty in the environment,
three analytic chapters are presented: 1) predictive landscape, 2) behavioral simulation and 3)
archaeological analysis. These chapters are intended to answer questions that build on each
26

other to explain the context, process and cultural signatures of buffering/coping strategies to
uncertainty. First, the landscape model chapter seeks to understand the landscape level
changes of the study area driven by hydrological dynamics.
1. What is the makeup of the regional and local environments framed through wetland
distribution and densities?
a. What are the resource communities or habitats present in these wetland
environments?
b. What are the seasonal or short-term changes in wetland environments (density and
distribution) and implications for habitats and resource structure?
2. What are the long-term changes in wetland environments throughout the Late Archaic,
Early and Middle Woodland periods?
a. Based on the given models, what challenges (spatial, seasonal & temporal) do
wetland environments pose for economic adaptation?
Second, the behavioral simulation chapter seeks to understand diet and land use choices using
diet and patch breadth optimal foraging in uncertain contexts informed by wetland density,
distributions and heterogeneity.
1. What are the implications of patch variability on land use?
a. How do seasonal changes in landscape, wetland habitats and linked resource
communities affect land use patterns?
2. What are the implications of resource variability on diet?

27

a. How do these diet choices change in a habitat or patch (seasonally, longer term),
given changes in the wetland environment?
3. What are the implications of the variability on the social relations of the economy (i.e.,
sexual division of labor, group to group interaction)
a. What are the differential contributions of division of labor given the variability of
resource environment?
4. Given results of simulation - what strategies can HG employ to cope and buffer variable
wetland resources and landscapes?
Last, the archaeological analysis seeks to understand broad patterns of diet and land-use
patterns through sites, plant and animal remains. These patterns are used to evaluate both
predictive landscape and behavioral simulations.
1. What are the patterns of diet choices and settlement from excavated material?
a. What patterns (settlement and diet use) are present in each time period
i. How do these patterns change over time?
2. What is the relationship between archaeological patterns and the landscape and behavioral
models?
a. Given a relationship, what are the likely adaptive practices, social coping/buffering
mechanisms employed by SBD foraging communities?
Dissertation Organization
This dissertation is organized into sequential chapters that build upon one another. The
first four chapters establish the theoretical (i.e., risk and uncertainty) and methodological (i.e.,

28

landscape and behavioral simulation modeling) framework. Chapters 5 through 7 are analytical
chapters pursuing original and new efforts at exploring the research questions. These chapters
are structured as a scientific paper format with a quick introduction, background, method,
results, discussion and conclusion. Chapter 8 is the concluding chapter intended to bring all
chapters together.

29

Chapter 2: Risk and Uncertainty
Introduction
Hunter-gatherer (HG) choices can be better understood by addressing the roles that
uncertainty and risk play in their decision-making. Choices made in spatiotemporal variable
resource contexts are important to the study of behavior, especially since their economic mode
of production relies on the products of the ecological environment. Further, these concepts
play an important role in their cultural evolution and adaptation in the temperate
environments of the Saginaw Bay Drainage of Michigan. Understanding these characteristics is
important to the development of appropriate models of diet and land use. Therefore, risk and
uncertainty are critical to the understanding of HG adaptation and linked social evolution and
cultural change.
Typically, subsistence studies treat environment in a static context and assume change
or variability in ecological environment does not play an important role in human choices.
Further, social scientists focus on average conditions or normative concepts of human
existence. To the contrary, environmental variability and interrelated concepts of risk and
uncertainty have heuristic value for the understanding or investigation of processes of
economic and social change (Cashdan 1990b; Halstead and O'Shea 1989a; Winterhalder 2007).
In this research, temporal and spatial instability in food supply is assumed to cause problems
for survival. Decision-making aimed at securing this food supply frames our understanding
through the baseline social and biological goals embedded in cultural and social milieus of a
society. These decisions must match the resource problem at hand in both capacity and scale
(Cashdan 1990b). Further, linked effects of resource variability on society, polity and non30

subsistence economy are important as a means for indicating causal interconnections and
evolutionary processes.
The acquisition of food requires effective and efficient decision-making and the success
of a given strategy is linked to the evolution of foraging adaptation. Economic security requires
an understanding of the types of risk and uncertainty as well as the ways people cope and
buffer against them. Uncertainty and risk in the resource environment can be conceptualized as
variation of food supply in time and space. The variability is the actual pattern of variation in
the food supply resulting from the actions of actors (climate, humans) that influence the
availability of food resources. Beyond just a heuristic exercise in decision-making, these
concepts have implications for cultural change. The balance between structure of adaptation
and structure of resource variability can have implications for shaping societal organization and
providing conditions for social transformation and change. The ways in which cultures cope and
buffer these variations can be the causal factors in economic change. Social relations of
adaptation are embedded in marriage rules, kin relationship, social structure (e.g., households,
community relationships), task groups (e.g., gender, age groups), and social identity and can
even result in incipient social complexity, political hierarchy, and inequality.
Social institutions that are employed to buffer variability may have other functions
within society during good years. These institutions may not be recognizable unless they are
activated under required conditions of scarcity. For example, during times of scarcity, social
institutions will likely sacrifice efficiency for risk-minimizing behavior. Over time, larger and
stronger variability may require the embedding of coping and buffering practices within regular
cultural practices and in effect may have widespread and systematic ramifications. The increase

31

and expansion of social roles in buffering may also serve to promote social institutions within
which coping mechanisms are embedded. This often creates layered social mechanisms as a
means for adaptation and concomitantly as a means for social change. For example, the
appropriating and control of surpluses for the maintenance of elite may result in new sources
of risk, which may lead to another set of coping mechanisms. These new coping mechanisms
can lead to transformational or even catastrophic change.
Conversely, cultural change does not need to take place in contexts of consequential
variability or scarcity, but can occur in abundant or stable and homogenous resource
environments. In contrast, social changes and complexity can be responses to the social control
of abundant resources (Ames 1994; Price and Brown 1985). Responses to variability are
embedded in social life and the broader culture of a group and are likely to be already
embedded in the normal operations of a culture. Decision-making approaches, and interrelated
well-established foundations, set the framework for the development of predictive models of
diet and land use in the study area. For example, Optimal Foraging modeling of human groups
shows that energy maximization diets can be also risk minimization (Winterhalder 1986).
Depending on the conditions, foragers seek to minimize the time spent foraging, to maximize
net returns from a day or reduce the risk of complete failure and to the contrary, engage in
risky behavior. Having demonstrated the importance of these concepts to adaptation, social
evolution and change, a description of the characteristics and analytical power is undertaken.

32

Ritual

Cosmology

Subsistence

Move

Exchange

Belief

Settlement

Store

Diversify

Pool

[Halstead & O’Shea 1989; Agrawal 2008]

Resources
Landscapes

Uncertainty
Risk

Figure 3. Uncertainty and risk relationship to culture

33

Cognitive

Dimensions of Variability
An understanding of the structure of variability is required for the development of
appropriate models. Variability exhibits three scalar characteristics: temporal, spatial and
intensity, which determine the scope of variability. Temporally, variability can be short and long
term, whereas spatially, it may be localized or regional. Intensity is the scale at which both
spatial and temporal variance takes place. Within these characteristics, a number of complex
dimensions arise. These dimensions of environmental variability are two interrelated concepts:
1) duration and frequency and 2) magnitude and spatial scale.
First, duration and frequency of scarcity can be thought of as uncertainty over time. This
type of variation is characterized as expected and unexpected short term (i.e., days), seasonal
(i.e., within an economic season – autumn, winter, spring and summer) and multi-seasonal (i.e.,
spanning multiple economic seasons), annual (i.e., all four seasons) and inter-annual (i.e.,
multiple years). In the short term, this can be manifested in the change of seasons, where
resources are different from winter to spring. People have cyclic expectations about what
happens at a specific time of year. These changes are often predictable; seasonal variation can
be repeatedly experienced, thus culture is likely to take this variation into consideration and is
part of, and integral to normal existence. Next, inter-annual variation is the change from one
year to another, where winters are mild one year and severe the next and summers are dry one
year and wet another. Longer-term changes can be viewed as trajectories where there is
decline or increase in temperature, precipitation, food resources or other relevant
environmental variables. Unpredictable variation result from the external environmental and
ecological factors (i.e., climate, pests).

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Environmental variability may actually be cyclical variation on an unrecognized, long-term time
scales. Further, this variability can unexpectedly last for an unpredictable duration and cause
further problems for diet and land use. For example, a delay in the arrival of anadromous fish,
plant growth can change the expectation of a resource at a place and time. This can be
exacerbated by the spatial extent or spatial homogeneity. HGs in the Saginaw Bay Drainage
(SBD) predictably suffered periodic food shortages in all seasons. Archaeological analysis
typically addresses a few types of variability. Archaeological analysis attempts to assign material
remains and sites to specific seasons in order to identify patterns of resource selection and
overall movement on a landscape. Unpredictability in this case results from the deviations from
the norms in a given season or longer time periods for a given dimension and becomes a
context for change.
The magnitude and spatiotemporal extent relates to the size of the affected area, the
intensity and length of scarcity; and can be thought of as uncertainty over space. Spatial
structure concerns the relative homogeneity of the variability or how evenly or patchily the
scarcity is manifested. This variability is further exacerbated by the intensity of variability over
space. Intensity relates to the severity of the shortages and the degree of severity that can
occur, and is a measure of variation that fluctuates above or below a given mean level over
space-time (Harpending and Davis 1977). Unpredictable variation occurring as a result of
external factors (e.g., climate, pests) may delay or intensify the cyclical variation on an
unrecognized, long-term timescale. These dimensions provide a way to characterize the
different dimensions of spatiotemporal variability. These natural resource dimensions alone are
insufficient for study of uncertainty and risk, therefore a cultural is required.

35

Cultural and Economic Perception
In order to link the analytic dimensions of uncertainty and risk and society,
understanding the cultural-based cognitive domain of risk and uncertainty is valuable. Studies
of HGs are fraught with assumptions of time and space that reinforce normative understanding
of risk philosophies derived from contemporary economic and cognitive studies. For example,
contemporary linear understanding of time and place-based understanding of space has
created a framework of an open, long-term future where prediction, or forecasting, has
importance. Ethnographic and ethnohistoric studies of HGs present an alternative scenario
where their ideas of risk and uncertainty are different. T HGs do not conceive time linearly; the
past and future are said to circle around the present rather than define it (Adam 2002:504;
Brody 2001:139; Ingold 2000:336). They are aware of the future and its relationship to the
present but are unconcerned with what may or may not happen. This project assumes that
prehistoric HGs also had similar belief systems.
HGs do not concern themselves with the future; this understanding is judged as
problematic to their success (Ingold 2000:336; Sahlins 1972:30-32). For them, the perspective
that the future cannot be known characterizes an alternative understanding where the
appropriate response to uncertainty and risk is to focus on the present. For foraging
communities, environmental change is likely to be part of a pattern of expected variability.
Groups and individuals may or may not have realized that any climate change is taking place.
The pattern of change is cyclical and repetitive, not necessarily aberrant. This perspective
requires that a HG focus on the present and on strategies that contribute to effective decisionmaking in the present. Therefore, they need to acquire the wealth of information about the

36

present opportunities and conditions by maintaining contact with kin and the landscape and
incorporating knowledge on travels (Bates 2007; Whallon 2005).
HGs do not simply rely on current information but are highly flexible and opportunistic
when plans made with current information may not be fruitful (Bates 2007; Brody 1982). For
them, planning, predicting and forecasting can be impractical, foolhardy and even arrogant.
Flexibility in behavior may be the most effective strategy. To make predictions would be to
make the knowledge sacred, not allowing the individual to be flexible. The vitality of this
approach lies in the freedom allowed for improvisation and flexibility. The preference for
freedom is complemented by the diversity of coping responses employed and, therefore, the
approach employed in this project. This cultural perspective can be expanded with an
understanding of how decision-making is practiced by individuals or agents.
Unlike the cultural perspective, economic analysis of risk behavior presents people as
‘risk sensitive’, ‘risk averse’ or ‘risk prone’. This concept has been incorporated into Optimal
Foraging models of prey choice, patch use, group size and time allocation (Caraco 1979; Green
1980; McNamara 1982; Smith 1983; Stephens 1981). Risk sensitive strategies can be predicted
from the relationship between the expected benefits from alternative subsistence strategies
and meeting minimum dietary needs (Smith 1983). A failure to obtain sufficient resources can
be a real danger given stochastic or unexpected variation. Stochasticity is often due to
imperfect information (lack of knowledge) or uncertainty and unexpected actual resource
variation (lack of resources due to variation) (Christenson 1982; Smith 1983; Winterhalder
1986; Winterhalder, et al. 1999). HGs can respond to stochasticity in a number of ways. For
example, the expression of the so-called ‘extreme variance rule’ states that foragers seeking to

37

minimize (to gather minimum required resources) should choose a strategy that yields more
than minimum resources and with the least variance. However, if the expected mean returns
for all strategies fall below basic requirements, then foragers choose the strategy with most
variance (Stephens 1981).
Under conditions of scarcity, foragers need to take greater risks to meet requirements.
Therefore, a forager’s investment in risk reduction strategies depends on the cost of losing the
resource (Cashdan 1985). In order to optimize returns of foraging activities, HGs must employ
risk reduction strategies. Actual variation regardless of type results in people using coping
mechanisms to minimize variance. Stochastic risk can result in variation such as frequency,
predictability or duration of resource availability (intense resource depression and climatic
variability), or the spatial extent or spatial homogeneity of resources (Halstead and O'Shea
1989b). A common thread in the different perceptions to uncertainty and risk is based on the
information forager holds. The information and how foragers use their knowledge has
implications for model characteristics.
Role of Information
Human behavioral models typically treat people as all-knowing, computationally perfect
decision-makers (Moore 1981). In Optimal Foraging models, HGs are assumed to have
knowledge of their environment and are able to assess the variability of anticipated resources.
Counter to the implications of these models, HGs are likely not to have complete and accurate
information. Access, contextualization and maintenance of information are key behavioral
attributes in subsistence decision-making and have important implications for strategies that

38

are employed to cope with variability. In fact, the information – knowledge of the ecological
and social environment – has implications for diet and land use choices (Whallon, et al. 2010).
The key variable in a HG’s ability to cope and buffer is information, the knowledge of
their surroundings – how knowledge is gathered, contextualized and shared (Whallon, et al.
2010). For example, mobility allows the opportunity for HGs to gather information regarding
their environment and social relationships. This is reinforced by information storage and
exchange (Agrawal 2001; Whallon, et al. 2010). This information is then used to understand
environmental variability over a large area beyond their normal annual range (Halstead and
O'Shea 1989a). The amount of information in the environment is voluminous and likely
unmanageable. In fact, the vast amount of information is stored and structured through
gendered patterns of information storage as exhibited by Yup’ik Eskimos groups (Funk 2010).
Even though HGs do not have complete knowledge regarding adverse weather conditions or
natural calamities that affect their resources or personal wellbeing, they make decisions based
on the available knowledge of their total environment. Therefore, risk becomes implicit in their
decisions. For example, if an anticipated resource is not a certain one, the cost of moving camp
to a new location will in effect be higher and as a result we could expect HGs to stay longer in
their current camp (Kelly 1995a).
A successful forager depends on the continuous monitoring and gathering of
information regarding the environment. This knowledge is transformed to suit the existing
conditions so that the returns from efforts match or exceed the costs expended. HGs are able
to cope with changes in the environment by employing alternative strategies so that they
modify the efficiency (e.g., locate, capture, process) through increasing the information and

39

incorporating technological and strategic (group organizational) changes. These optimizing
actions can be understood using theories proven and dedicated to interactions of humans with
the landscape. Foraging success is linked to the amount of information, with their own
expertise of local conditions combined with knowledge of others. An individual forager’s
decision-making in a given day can be based on a number of factors, including how much food
has already been acquired, whether there is enough time to acquire more without
consequences to energy and probability for success, and whether there the desire for a minimal
amount of food in a day. Therefore, a forager’s goal can change due to success earlier in the
day.
With the information in hand, HGs use coping and buffering mechanisms to minimize
the effect of expected and unexpected resource variation. The response to variability is based
on a HG’s ability to incorporate knowledge about their situational context, therefore employing
appropriate coping responses to address the problem at hand. These responses must match the
problem at hand in capacity and scale. The unpredictability of hazards can also be a problem as
this increases risk from environmental perturbations. Buffering and coping with environmental
risks can be classified into five categories of adaptation responses or buffering mechanisms:
mobility, storage, intensification, diversification, exchange and group pooling of resources
(Agrawal and Gupta 2005; Halstead and O'Shea 1989b). These strategies can pool uncorrelated
risk and minimize the effects of variability. The actual strategy employed is coupled intricately
with the social relations of a community. These activities are manifested through cultural
activities, inclusive of storytelling, cosmology, and even harvesting or cultivation rules. The
effectiveness of a specific strategy is attached to the match between the structure and

40

organization of a society and the resource problem. Some strategies are better suited to local
and regional conditions than others, where systemic economic change can result from localized
changes in strategies of resource use, not necessarily linked to resource abundance but simply
the strategy to expand or relax rules for coping and buffering against uncertainty and risk.
Coping and Buffering
Repeated studies of HG emphasize systemic flexibility to cope with environmental
uncertainty and variability in food and land productivity (Braun and Plog 1982; Colson 1979;
Robertson 1987; Spielmann 1986). Coping with environmental risks can be classified into
categories of five adaptation responses or buffering mechanisms: mobility, storage,
intensification, diversification, and exchange and group pooling of resources (Agrawal and
Gupta 2005; Halstead and O'Shea 1989b). These strategies can pool uncorrelated risk and
minimize the effects of variability. The actual strategy employed is coupled intricately with the
social relations of a community. These activities are manifested through cultural activities,
inclusive of storytelling, cosmology, and even harvesting or cultivation rules. The effectiveness
of a specific strategy is attached to the match between the structure and organization of a
society and the resource problem. Some of these strategies are better suited to local and
regional conditions than others. The Saginaw Valley groups of Michigan were least likely to
experience these shortages, but were likely influenced by neighboring groups and their needs
for hunting territories, and the use of neutral areas (Cleland 1992:100). In the most productive
season, HG are likely aggregate at places where there was apt to be the greatest carrying
capacity and reaffirmed economic and social relationships. These areas are typically places
where material culture (e.g., lithics and ceramics) is most diverse, often representing different
41

groups. For example, the Butterfield site is one of late winter/early spring occupation during
the Late Archaic period (Robertson 1987).
Mobility
Mobility is the simplest and most common response to risk. It pools risks across space.
This strategy offsets abundance by spatially redistributing people and food by either moving
people to food (i.e., residential mobility) or by moving food to people (i.e., logistical
mobility)(Binford 1981; Cashdan 1985; Sobel and Bettles 2000). The movement is one way to
alleviate food scarcity (Binford 1982:8-11; Halstead and O'Shea 1989a:3). Foragers are often
observed to move to familiar places in seasons of abundance (Cleland 1992:98). In fact, mobility
is an important explanatory factor for the organization of sites in HG societies (Binford 1981;
Wiessner 1982a). A group members positions themselves on a landscape to best acquire food
and other necessary resources as a means for balancing foraging success against natural risks
with a minimum of cost (Binford, et al. 1983; Jochim 1981). Patchiness in the resource
environment has an important effect on foraging and land use patterns. If patches of different
resources are uncorrelated or out of phase (existing at the same time), moving closer to one
would move you farther from another.
A forager uses logistic mobility to gather resources, where exploitation is undertaken
far from residential base. Here, mobility is used as way to average over spatial variation
(Binford 1981). Flexible locales for settlement reduce stochastic environmental risks and
resource unpredictability (Binford 1981, 1982). Changing mobility strategies in situations of high
resource variance reduces risk by increasing the encounter rates within and between patches.
Mobility ranges will be smaller where resources are in phase (different resources occurring at
42

the same time or at the same place), where people can remain near sites. Ranges are also
smaller where there is little spatial variation. Increasing range size in these cases will have little
effect on food supply diversity. Larger ranges are expected if resources are patchy but the
patches are out of phase (Harpending and Davis 1977).
Further, the effectiveness of this strategy is directly related to the information about the
spatial and temporal distribution of resources. HGs take advantage of the spatial and temporal
structure of resources by moving away from scarcity. They employ a system of flexible
territorial boundaries and extensive kin networks that permit bands to move as they see fit.
Information gathering to monitor environmental variability over large areas beyond their
annual round is a key positive consequence of mobility. Moving to new places provides
information regarding uncertainty through their daily activities and their choices in gathering
resources. The information is then used to understand environmental variability over a large
area beyond their normal annual range (Halstead and O'Shea 1989b). Though HGs do not have
complete knowledge regarding adverse weather conditions or natural calamities that affect
their resources or personal well-being, they make decisions based on the available knowledge
of their total environment. For example, if an anticipated resource is not a certain one, the cost
of moving camp to a new location will in effect be higher and as a result we could expect HGs to
stay longer in their current camp. For example, Agta women who gather the most, have the
final say in mobility (Kelly 1995b). Women use their preferred resource type and potential
distance traveled to procure those resources as a factor in deciding movement of the whole
group.

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Mobility often serves as a foundation for risk aversion and requires knowledge of spatial
and temporal variability. Conversely, mobility can be curtailed when residential moves are
deferred due to increasing time spent on exploitative activities. Curtailing residential mobility
may result in logistical exploitation with a residential base and may also result in innovation in
storage and food preservation techniques.
Storage
Storage pools and reduces risk over time and averages variation over time and space.
HGs store to buffer against variation is common among highly seasonal environment
(Densmore 1974; Henry 1969). This counters periodic shortages by setting aside surpluses.
Storage provides alternatives to available resources on the landscape (Halstead and O'Shea
1989b; Ingold 1983). Storage balances the abundance of a specific season or resource structure
against lean seasons and bad years and distributed resources. The pragmatic activity of setting
aside harvested produce can be seen as a response to the temporal scheduling or resource
extraction, transport, preparation and consumption (Ingold 1983). These are often the result of
activity scheduling where mutually exclusive, non-concurrent activities take place. For example,
if one activity has to be stopped for another to be performed (i.e., rituals), then consumables
should be stored (Ingold 1983). The extent of storage is then determined by more than simply
the available resource, and is linked to social and environmental rationale, including exchange
and mobility.
The product of one activity is stored while pursuing another activity or resource. This
strategy requires a large investment of labor and time. Investment in storage is an effective
strategy if resource abundance fluctuates severely and production remains above minimum
44

requirements after transport, preparation (processing) and the building of storage facilities are
considered. The practice of storage and mobility may be contradictory. Some of the costs
related to storage (transport) decrease as mobility decreases, therefore they should be more
common among sedentary groups (Cashdan 1985).
Storage is difficult in areas where spoilage is high, especially in hot and humid
conditions; therefore requiring a need to look for other strategies to mitigate variance. Storage
requires the understanding of the seasonal round and the expectation that one will return to
the same locale or be willing to incur the costs of transporting foodstuffs. Storage also likely
involves the coordination across households and social groups; this is an effective insurance
against complete livelihood failure at a given point in time (Rowley-Conwy and Zvelebil 1989).
Contrary to the belief that storage tethers people to one area, storage can be seen as a
mechanism to ease risks associated with specific resource availability. Storage may be a way of
coping with resource seasonality and food storage does not necessarily reduce residential
mobility. If resource variability increases over time, HGs are more likely to engage in storage.
For example, Northwest HGs groups move their stored goods from one residential
location to another demonstrating that storage is not a cessation of mobility. This movement of
stored resources to another location also depends on the net return rate of travel because
some of these stored foods will be consumed during travel. Overall, storage can mitigate risk
and does not necessarily limit mobility. Storage has considerable implications for social
complexity – transition from mobile to sedentism, foraging to agriculture, population growth
and a key precondition for external trade. Storage and surplus exploitation results in drastic
changes in the coping mechanisms for already uncertain and environments.

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Further, storage has other consequences. The expansion of storage is also the
intensification of specific harvests. The expansion of harvesting, processing and storage to
increase the time spent on foraging to reduce variance. Intensification requires a greater
investment of time and labor or a specialization of few highly ranked resources that yield high
return under sustained exploitation. This strategy has critical consequences where the
productivity of resources can be resistant to intensive exploitation or productivity can be
enhanced by human agency, such as water control or regeneration of habitats (Bird, et al. 2005;
Jones 1969; Larson, et al. 1996; Leonard 1989; Richerson, et al. 2001; Winterhalder 1986). This
strategy reduces risk by increasing the productivity of land rather than increasing the amount of
land (i.e., mobility).
Diversification
Diversification pools risk across the resources of multiple groups or individuals within a
group by broadening the subsistence base. Individuals of the group may consume different
types of foods, in more varied areas and by different task groups (i.e., gender and age). This
strategy spreads risk across resources and to reduce overall vulnerability to the group. This is
essentially increasing diet breadth. This strategy can also be employed to capturing and
gathering lower-ranked resources whereby variance is reduced while meeting minimum
requirements. The sexual division of labor in HG groups is seen as a diversification mechanism
whereby subsistence diversification employs both risk-prone (males hunting) and risk-averse
(women gathering) strategies (Halperin 1980; Zihlman 1981).

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Communal Pooling/Group Foraging
The joint ownership of resources involves sharing of foodstuffs, labor, and information
across households and groups. This strategy is most effective when household resources are
not directly linked spatially to each other. Resource pooling responds to both homogenous
spatial variation and temporal shortfall of resources. Households that are likely to exploit
different resources or resource communities would likely benefit most when resources are
pooled. This strategy takes place during the grouping of distributed bands during abundant
season serves multiple functions including intra and intergroup communication of subsistence
resource availability (Binford 1982; Riches 1982a), planning the seasonal round (Wiessner
1982a:63), and allocating seasonal ranges(Silberbauer 1982:30). This communication and
transmission of knowledge allows the group to effectively exploit the regional landscape.
Pooling is likely used in conjunction with other strategies, the characteristic action
results in the pooling of risk. This strategy requires the buildup of social networks and building a
resilient resource structure. Cooperation can enhance efficiency through division of labor to
reduce uncertainty, increasing chances of locating prey and reducing foraging overlap. Group
strategy reduces variance in resource capture rates if yields are shared among group members.
Sharing rules can provide different prediction about optimal group size base if the resources are
shared among the hunting party and dependents or pooled centrally such that resources and
redistributed to the larger group. Additionally, information from older, experienced hunters can
mitigate temporal variation (Sobel and Bettles 2000).

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Exchange
Exchange is the most versatile of adaptation responses; exchange plays off temporal
variability with spatial variability. Sharing and regional exchange are effective responses to
unpredictable day-to-day success in the food quest. Sharing and exchange of food and land
among groups is a mechanism to alleviate relative success and shortfalls. Food exchange can
take place through different forms, including accidental meetings, kin visitation, marriage, and
the establishment and maintenance of regular exchange relationships. For food, trade and
exchange networks replace mobility as a way of averaging spatial variation, especially in
contexts of increased competition through growing population density, requiring greater
productivity and consequently increased land use specialization. Exchange combines the
efficiency of specialized producers with the dietary breadth of generalized consumers (Cashdan
1987). Reciprocity and exchange of food stuffs are hallmarks of egalitarian nature of HG social
system (Isaac 1978; Kaplan and Hill 1985; Lee and DeVore 1968a; Polanyi 1959; Sahlins 1976;
Service 1971). Sharing of food within a group maintains bonds and contributes to fitness of the
individual by balancing variance in individual successes (Cashdan 1990b; Halstead and O'Shea
1989b; Lee and DeVore 1968a; Wiessner 1982a).
For land, at the regional scale, societal interaction and exchange is one key strategy to
mitigate uncertainty in the environment through differential usufruct land use (Helm 1968;
Leacock and Lee 1982a, b; Riches 1982a:121; Silberbauer 1982). At an interregional scale,
shared use of territories or mutualism can be way to buffer against scarcity (Holman and
Kingsley 1996). For example, groups can disperse and exploit more productive territory and also
by exchanging with groups wth better harvests. Ethnographic analogues show dispersal and

48

direct acquisition is common, especially in productive environments (Spielmann 1986). The
territories exploited overlap at the peripheries and may even be neutral zones present where
both communities may exploit resources (Pilling 1968). Groups who are familiar with territories
often give permission for the use of, are aware of who uses, and avoid the use of a given
territory at the same time (Riches 1982b:120). Cooperative buffering against variance is
characterized by sharing of common resources, fostering long term, amiable relationships
among groups through kinship and/or through social or political alliances. This strategy can
results in a network of loosely coupled resource systems that averages out variation.
These buffering mechanisms are activated during increased variability in harvests.
Beyond sharing, competitive strategies can also be employed, often a desperate measure when
cooperation fails (Spielmann 1986:283-284). Wide-scale resource shortages can also trigger
competitive exploitation where resource sharing, cooperation or scheduling of territory use is
untenable (Hickerson 1970). Alternatively, historical and social factor of past interactions may
also influence action to pursue competitive action (cf. Ford 1972; Spielmann 1986:284).
Ethnographic analogues of Ojibwa and Ottawa show these groups occupy separate territories
while sharing the headwaters of regions in between (Cornell 1986:23; McClurken 1986).
Researchers have identified a number of benefits for sharing or giving away food (Bird
and Bird 1997; Blurton-Jones 1987; Cashdan 1989; Gurven, et al. 2000; Hawkes 1993; Hill and
Kaplan 1993; Peterson 1993; Winterhalder and Lu 1997; Woodburn 1982). Exchange can take
many forms including the transfer of food, cooperation, reciprocal altruism and reciprocity
(Cashdan 1985; Lee and Devore 1968b; Wiessner 1982b). As an example, social storage, social
networking or delayed reciprocity (social obligation to give) store resources over time in other

49

people. Social storage is the convergence of rights to specific resources on an individual or
group. The exchange of resources or relationships (social exchange - marriages) builds formal
long-term social relationships that likely required regular affirmation to provide assistance in
times of shortage (Wiessner 1982b).
Exchange can take the form of balanced reciprocity and converts present abundance
through social transmission to future obligation. In HG societies, food is often given freely
without obligation, but, in more complex circumstances, obligations may be reinforced by
exchanges of tokens that denote future obligations back to the giver. Exchange requires the
transformation of surpluses into non-perishable goods that can be exchanged during difficult
times (Sobel and Bettles 2000). Reciprocity can also take the form of generalized exchange,
where extensive networks of partners aid each other in times of shortage (Cashdan 1985;
Wiessner 1982b). Due to the larger spatial scale employed by exchange networks, risk is
pooled, thereby minimizing variance by spreading risk or loss over units larger than a local
group over much larger areas. These exchange systems operate as embedded social
relationships that make small, regular and predictable losses or contributions in return for
larger, uncertain return. Non-reciprocal or negative reciprocity of theft or raiding are also
employed by risk prone individuals. This strategy is effective when no other options are present
and returns are large but with high costs and consequences.
For example, the Basarwa of Northern Botswana uses reciprocity in buffering resource
fluctuation. A horticultural group, Basarwa use reciprocal relationships with non HG groups.
Their mobile lifestyle does not allow for the accumulation of goods. Reciprocity, therefore,
serves as insurance against risk. For other HG groups, kinship relationships and alliances are

50

used establish this social insurance, which results in social storage. For them, sharing and
cooperation with available resources in a given year is a risk management strategy (Cashdan
1985).
A study of stochastic foraging with costs and benefits of sharing versus diversification
shows that sharing between two foragers with same diet breadth can maintain high foraging
efficiency while reducing their pooled variation in the range of food intake by 58 percent,
whereas expanding diet breadth alone results in only an 8 percent reduction in the standard
deviation of the net rate of food intake, a small reduction in the risk of going hungry, and a 6
percent reduction in foraging efficiency (Winterhalder 1986). In this case, there are no
alternatives in a given place. The only strategy to cope with this type of variation is to average
losses over a large number of areas through network of kin ties. The !Kung San use a social
institution called Hxaro, involving exchange of gifts between particular partners. These partners
can be counted on to reciprocate in times of need and these relationships are reinforced
through regular family visits. !Kung San choose partners by their geographic location and
personal abilities so they are protected against risks (Wiessner 1982b).
The best solutions are likely to be strategies that employ a suite of coping and buffering
strategies that is best matched to the structure of variability. For example, Optimal Foraging
Theories make a number of useful predictions about human responses to spatiotemporal
variability or the decrease in high ranked resources resulting from resource depression. If the
goal is to increase utility or reduce risk: 1) HGs should broaden diet to include lower-rank
species or specialize in few sustainable resources, 2) include wider patches, including lower
rank patches, 3) intensify production, create suitable habitats for high ranked dependable

51

resources (cultivation, horticulture), 4) form larger groups that create efficiencies through
group foraging – pool resources, information, networks therefore reducing variability through
sharing and 5) invest in physical and social storage. Using the Late Woodland strategies as an
example, the conditions present in the SBD during the LA to EW cultural periods required the
establishment and maintenance of cooperative buffering mechanisms. Settlement patterns and
diet choices are then indicators of an effort to ameliorate these effects (Holman and Kingsley
1996).
Coping Hierarchy and Scale
The aforementioned behaviors are not simply alternatives that HGs select but are often
linked such that they can be hierarchical and scalar. These scales can operate as low and high
level mechanisms. Low-level mechanisms are efficient and reliable and are limited in scope,
whereas, high-level mechanisms are powerful, large, relatively rarely activated and can mitigate
larger scarcities (Halstead and O'Shea 1989b). High-level mechanisms only function if reinforced
regularly, even if rarely used. These emergency mechanisms are likely embedded in the day-today cultural repertoire (Garnsey and Morris 1989). For example, the regular practices of ritual
and feasting are likely mechanisms that aid the production of surpluses on a yearly basis.
At greater severity, where shortfalls are beyond the local coping capacity, high-level
strategies may be employed, such as inter-regional exchange and intensification, which could
possibly result in subsistence changes (Hawkes and O'Connell 1992; Larson, et al. 1996; Leonard
1989). Buffering strategies are additive such that larger and more complex societies incorporate
larger and more complex mechanisms. Coping with variability is a hierarchical process, where

52

strategies that are employed are broadly or selectively used based upon the structure and scale
of the uncertainty.
The actual choice of adaptation(s) practices is dependent on a number of contextual
factors including social and economic practices of the community, ecological environment,
social relationship networks and access to resource zones. Societies are likely to employ an
array of strategies in a hierarchy of responses and differ based on the individual, band and
community. They may also employ age-sex task groups to focus on different types of
mechanisms, therefore diversifying the strategies that are employed. The treatment of
uncertainty and risk can be a fruitful domain for the exploration of social evolution and
adaptation. The landscape and behavioral models created for this project incorporates risk and
uncertainty as analytic dimensions that provide an alternative approach for diet and land use
studies. The landscape model employs stochasticity, the random nature of variability in the
effective environment. In the behavioral model, three key dimensions are represented: 1)
information a forager holds, 2) the level of risk a forager is willing to take, and 3) the
implications of levels of risk and uncertainty on coping and buffering strategies. The next
chapter links the concepts presented here with two practical modeling approaches
contextualized in uncertainty and risk-based decision-making.
The next chapter reviews the modeling methodology in terms of their strengths and
weaknesses as well as its use in archaeology and ecology.

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Chapter 3: Modeling Economic Decision-Making
Introduction
Understanding hunter-gatherer (HG) adaptation to uncertain and risky environments is
undertaken by a modeling approach. This research constructs two coupled predictive models: a
resource landscape and a behavioral simulation. In archaeology, predictive modeling is used to
generate a hypotheses and expectations, and identify landscapes with a high potential for
cultural preservation. While useful for conservation and heritage management, the procedures
underpinning predictive modeling also provide a means for interpreting the known
archaeological and ethnographic records, as they relate to current theories of human behavior.
If modeled and observed behaviors differ, this provides an opportunity to explore the nature of
such variation (Reidhead 1979; Winterhalder 1977). In the first of these two models, a series of
resource landscapes are constructed. This approach provides information about the prehistoric
contexts, thereby filling in gaps in our understanding that are unavailable due to the limited and
narrow archaeological record. Next, a behavioral model is developed using a simulation
approach, using Optimal Foraging Theory (OFT) to understand diet and land-use choice,
predicated on the effort to cope and buffer risk and uncertainty in the environment.
These choices are explored in the terms of criteria employed by past and present HGs
based upon a given decision logic: which resources will be exploited at what season, in what
quantities, and in what localities (Jochim 1976b). Next, both models are evaluated with
archaeological site, zooarchaeological, and archaeobotanical datasets from the Late Archaic to
the Middle Woodland periods in the Saginaw Bay Drainage (SBD) of Michigan. This chapter

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presents a review of the methods employed to develop these models, as well as model
characteristics and attributes.
Models
Models are typically abstract descriptions of the HG economic system (a set of
components that interact) that allow for the assessment of human choices, understood as
alternative options and competing demands (Jochim 1976b). Modeling allows for the
identification of system components and constraints, and defines expectations regarding the
structure and dynamics of interacting components. They seek to understand correlative and
explanatory reasoning of phenomena through the explicit identification of relevant objects. In
archaeology, modeling effort is intended to create predictions, as with this project, specifically
about contexts (site locations) and behaviors (what people do). Models allow for understanding
the implications of goal-oriented choices and related archaeological and cultural patterns
(Binford and Binford 1966; Clarke 1977). These models are deductive and built upon theories of
human behavior and ethnography. These predictions can be used to test interpretations
through empirical data.
Models can generate counter-intuitive hypotheses, thus securing against the fallacy of
affirming the consequence (Bettinger 1980; Binford and Bertram 1977). Archaeology is replete
with modeling approaches focused on subsistence and settlement practices (Clarke 1972;
Thomas 1972; Wobst 1973). Other successful efforts employ evolutionary and behavioral
ecology models framed in OFT (Bettinger 1991; Broughton 2003; Winterhalder and Smith 1981,
2000). Michigan archaeology has also successfully employed deductive approaches (Arnold

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1977; Egan 1993; Keene 1981b; Krist 2001). These formal models exemplify archaeologists’ farreaching efforts to understand causes of behavioral and material patterning.
Model-building requires the explicit identification of its purpose (goals), definition of the
system (i.e., assumptions, what is inside and outside the system), key variables, and the
behavior of key variables and interrelationships between variables. This endeavor is an exercise
in placing priority on aspects of the problem that are important to the researcher. Priority in
this project is placed on behavioral strategies (i.e., mobility, diversification, exchange, pooling
and storage) aimed at fulfilling basic dietary needs. The variability present and boundaries of
these strategies are derived from HG ethnographic records aimed at adapting to environmental
uncertainty and risk. For the best results, a proper match is required between the research
problems, theory, and the methods that are employed. Decision-making models require logical
consistency achieved through a transparency of model characteristics with explicit goals,
assumptions, currency, and constraints.
HG subsistence decision-making goals are to procure necessary or minimum diet
resources for biological needs. These goals are underpinned by the primary goal to cope and
buffer against uncertainty and risk in the environment by behavioral rules based on how people
may have behaved in the past. In order to adapt to these conditions, HGs select food and use
their land in strategic ways. These choices result in cultural patterns, in turn manifesting in
archaeological material patterning on a landscape.
Assumptions are the baseline criteria employed in decision-making. These criteria create
boundaries for the choices of individuals, where considerations outside these assumptions do
not play a role in human economic and social behaviors. These boundaries limit factors of the

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decision logic and alternatives that could explain diet and land use choices by the following:
Economic activities directed toward providing the basic nutritive and other raw materials
necessary for the survival of a group through conscious choice; deliberation is rational, based
on preferences among consequences.
Efficiency is a baseline property of decision-making (Hewitt 1983; Keene 1981a, 1983;
Smith 1983; Winterhalder 1981b). When faced with a choice between two equal resources, the
one of lower cost will be exploited. Efficiency can therefore be considered an “in the moment”
decision between two alternatives. Scheduling of economic activities is the allotment of time
and energy for food and depends on choices among competing or mutually exclusive activities
with goals of achieving economic security. Efforts to ameliorate risks and uncertainty in the
environment are long-term strategies and can be identified through diet and land use against a
background of opportunistic exploitation.
Risk and uncertainty in resources can be represented as both proximate to the
individual (information held) and present in the natural environment through spatiotemporal
variance. The effect of perturbations in the subsistence system, either internal or external, can
be modeled in terms of changes in costs and/or limits of resources and information that is
available to a person. This model assumes an open system, where external inputs are used to
demonstrate variation for interpretation. Decision-making in the resource environment can
originate from motivations and external factors, such as food items or goods outside the study
area, through exchange and the transmission of information from persons outside the study
area.

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Traditional ecology deals in three currencies: energy, matter, and information. OFT uses
kilocalories, a quantifiable value as the net energy acquisition rates associated with different
resources, patches, and group sizes (Winterhalder and Smith 1981). Energy exchanges are
recorded in terms of input and output ratios. Input is calculated as the ration of time expended
for locating, capturing, transporting, maintaining/storing, and consuming food resources.
Output is calculated as terms of energy returned from these activities as a result of resources
being consumed (Kemp 1971; Rappaport 1984; Smith and Winterhalder 1992; Winterhalder
1981b).
A person’s fitness is associated by the net remaining calories after input and output
activities. Other approaches in OFT include food nutrients (matter), due to the recognition that
caloric efficiency is insufficient to explain the special role that meat plays in HG diets, since the
satisfaction of nutritional requirements is also essential to human subsistence (Egan 1993;
Keene 1981a). Dietary diversity and task group-based resource preferences contribute to
dietary and nutritional requirements. Therefore, nutritional adequacy is embedded within food
choices based on other criteria (Egan 1993; Jochim 1988). Finally, the use of information as a
currency is relatively new. Information is the knowledge an individual holds of his surroundings
and the resource distribution and density at a given locale (Whallon, et al. 2010). This project
uses a mixed currency based upon the scale of analysis. Kilocalories are used as currency in
resource choices; whereas information is used in the knowledge of landscapes and decisions
about where to move.
The model is intended only to address HG diet and land use in the SBD area aimed at
meeting minimum requirements for survival. The study area provides a constrained landscape

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where HGs are reliant primarily upon the resources contained therein based upon
spatiotemporal variability. This project is a regional study and limits the connectivity with larger
interregional networks of interaction.
Data Needed for the Models
HG diet and land use requires information about both the natural and social
environment. The relevant natural and social environment is explicitly identified by their
constituent variables. First, the dietary needs of a group are determined by HG demographic
and organizational information, including group size, individual caloric needs, and sex/age
group contributions to diet. Next, the ecological environment provides the resource context
through land cover, and biogeography. These variables are organized from a spatiotemporal
perspective; providing where, when, and how much of these resources are available.
Choices of resources and habitats are dependent on the effective environment of the
study area. An inventory of biophysical (climate, soils, lake levels, hydrology, landscape
features) information that contributes to prehistoric diet and land use is based upon a synthesis
of contemporary land cover, hydrological, geoarchaeological, ethnographic and historical data.
The characteristics of these variables are taken into consideration to determine the resource
landscape. These features are further complicated by spatiotemporal changes requiring the
understanding of changes across seasons within each study time periods. These characteristics
and behavior of the landscape directly affect HG decision-making about resources and habitats
(see Chapter 5 for detailed information).
The inventory of plant (phytogeography) and animal (zoogeography) resources available
to HGs is based on the environmental reconstruction of the region, based on the contemporary
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knowledge of resources in the study area. The relevant economic resources are derived from
ethnographic and ethnohistoric documents (Chomko and Crawford 1978; Cleland 1966;
Densmore 1927, 1974; Erichsen-Brown 1979; Gremillion 1997; Henry 1969; Kimmerer 2003;
Krech 1981; Smith 1979; Yarnell 1964). The ecology of individual species and their habitats are
important to diet and land use studies.
The spatiotemporal characteristics of a resource includes its timing; productivity (weight
multiplied by density) per unit area of habitat; and the spatial variability of a given resource.
Productivity can be associated with the size and caloric value of the resource. The life history of
a specific resource provides information about their preferred habitats, seasonal behavior (e.g.,
hibernation, dormancy), relative abundance (seasonal aggregation), predictability (when
species are available), and reliability (how likely a HG can expect this species to be at this place).
Resources vary and may be unavailable to HGs or may not be preferred (e.g., low fat). The
structure of resources has implications for diet and land use decision-making, the
biogeographical data is critical to an effective model.
Productivity for a given habitat is derived from contemporary data and based on prior
reconstructed environments. The probable composition of a given animal, fish, and plant
resource is based on contemporary values for a given habitat. These values are borrowed from
fish and wildlife literature represented in grams and kilograms. This model focuses on general
caloric yields of each species, since meat yield is a good measure of utility (Cleland 1966; White
1953). Prey size is a good proxy for prey rank; generally the larger the animal, the higher the
return rate. The productivity of these resources varies seasonally, inter-annually, and within

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each of the study cultural periods due to the variability in the habitats present due to changes
in the natural environment.
Finally, seasonal abundance of a specific resource also plays an important role in choices
amongst alternatives. For example, a fish run or abundance of nuts at a given place can also
dictate resources gathered. Nuts or fish become an aggregate product where their cumulative
productivity is assessed and exploited.
The size of a HG household in proximity to the study area varies over the course of a
year and ranges from one to nine people in a group (Howell 2000; Murdock 1967; Schoolcraft
1839). These households live and move together and cooperate in activities for obtaining food.
They also practice alternative non-overlapping strategies for food exploitation based upon
age/sex groups (Binford 1978b; Hallowell 1992; Henry 1969; Woodburn 1968). They come
together for labor intensive activities that require the whole group (Cleland 1982; Henry 1969;
Landes 1969; Steward 1938). This number is a mean value derived from studies among the
Ottawa and Ojibwa bands living in Wisconsin and Michigan during the 1830s. The households
ranged from a single individual to sixteen people, with a mean value of 4.9 (Cleland 1992).
Alternatively, the mean number of individuals marginal Southern African !Kung San households
is 2.6 (Howell 2000). There is considerable variability depending on the environmental factors.
This study uses a household size comprised of a nuclear family with five individuals: two
females, two males, and a child. Further, there can be possibly multiple household units
operating in the SBD.
Minimum nutrition is the nutrition required for five individuals of varying sizes
depending on age, gender, and energy (Ellen 1982; Haas 1944; Messer 1984; Wing and Brown

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1979). Using the Department of Agriculture requirements, minimum nutrition for an individual
is based on a 2,000 Kilocalorie diet (NRC 1989). This study does not concern itself with
minimum vitamin and mineral requirements for survival. HG preference at acquiring a variety of
foods, selecting for taste and fat is assumed to address nutrient requirements (Egan 1993). For
this study, the average dietary requirement for a household is 2,000 Kilocalories for each
individual. This value averages differential requirements based on age and sex, and simplifies
calculations.
Individual contribution to diet is based on group member’s role in gathering plants,
hunting and trapping small and large mammals, birding, and fishing. The average resource
contributions in temperate environments are 31% based on gathering, 35% based on hunting,
and 34% based on fishing (Kelly 1995a; Lee and DeVore 1968a; Murdock and Wilson 1972).
Contribution to diet is also based on the level of risk tolerance by group members. Men are
likely to take on higher risks, whereas women and children accept lower risk. This has no direct
impact on the relative contribution to diet but does have implications for the individual
preference for resources (Waguespack 2005; Winterhalder, et al. 1999).
The quantitative determination of land use and resource choices in a decision making
model are based on values assigned to alternatives based upon a utility function that is
dependent upon both the net yield of kilocalories and the composite factor of risk and
uncertainty. The uncertainty and risk in a habitat or resources can be determined by the habitat
and resource’s relative predictability, reliability and abundance. The risk and uncertainty can be
order according to rank and incorporated into HG choices.

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Techniques
This study uses decision-making logic using classic, proven OFT models using computer
aided programming and analysis. The contextual landscape and behavioral models are created
by the use of Geographical Information Sciences (GIS) and simulation (SIM). The resource
environment is reconstructed through mapping and visualization techniques with the creation
of composite landscapes based on key variables. The landscape model entails the aggregation
and synthesis of geospatial data. GIS provides a framework and platform for the representation
of both ecological and cultural information (Goodchild and Janelle 2004). A computer’s ability
to store, provide representation, processing, integration, and analysis of spatial data results in a
hierarchy of nested data. This approach allows for better visualization of variables (e.g.,
vegetation, drainage, river networks, and elevation) that comprise the resource landscape (See
Chapter 5). The model is constructed by the use of GIS map overlay techniques. GIS
manipulation functions (buffer, overlay, clip, and so forth) of land cover variables are used to
create precontact landscapes (Brondízio 2005, 2006; Brondízio and Chowdhury 2010). The
landscape is used as the contextual basis for the simulation of diet and land use behaviors.
The simulation of human behavior is aided by programming software. This approach
simulates the outcome of interactions among a population of individuals. The individual acts
upon set decision logic in a particular environmental context and resources. These simulations
“emphasize dynamics rather than equilibria, distributed processes rather than systems-level
phenomena, and patterns of relationships among agents rather than relationships among
variables” (Kohler 1999). Simulation approaches have been used effectively in a number of
archaeological studies during the past decade (Kohler and Leeuw 2007; Kohler 1999; Reynolds

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1985; Sabloff 1981; Thomas 1972; Winterhalder 1986; Wobst 1973). The landscape becomes
the baseline model in an agent-based environment, where a simulation using explicit decisionmaking logic is run. Within a simulation program, each patch, or cell – the minimum scale of
analysis, stores information about a number of relevant data variables including the landscape
substrate (e.g., soil and land cover), resources (e.g., biogeography), and agents (e.g., foragers),
who make choices about diet and land use (See Chapter 6).
In the simulation, humans interact with their resource landscapes making choices about
habitats to exploit, and the animal and plant resources in the habitats. The HG becomes an
active decision maker, modifying his behavior based upon the dynamic resource environment
and decision logic. The SIM program iterates these actions for each time step (in terms of a day)
for seasonal and annual bases while the resource contexts are modified to reflect seasonal and
random (stochastic) changes. This simulation is rerun for each study cultural period with its
unique landscapes. After a simulation run, a set of resources that were selected, caloric intake
levels of a group, types of habitats that were selected, and other attributes relevant to the
satisfaction of basic biological needs are recorded. Further, a movement map is also recorded
daily, seasonally, and annually. The resource and habitats selected are nested hierarchically,
where choice of a habitat influences the resources chosen in a given simulation iteration. Both
of these coupled approaches provide an alternative perspective on development of predictive
models of HG diet and land use.
Resource and Habitat Selection Logic
The exploitation of a specific resource and habitat is dependent upon the costs and
benefits associated with the effort. For the exploitation of resources, benefits can simply be
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defined in terms of the caloric return from the hunted or gathered resource. The cost of a
resource requires a detailed analysis of the activity that was pursued. A cost-benefit approach is
often difficult to quantify since the analysis of contemporary HGs is context specific (Kemp
1971; Lee 1968; Lee and DeVore 1968a, b; Rappaport 1984). The costs may not have analogs to
differential climatic regimes, or spatial and temporal settings (Hewitt 1983; Keene 1981a). An
alternative approach includes an analysis of proxy variables such as resource density, mobility,
aggregation, and predictability (Cowan 1985; Egan 1993; Jochim 1976b; Keene 1981b). In this
way the environment and temporal contexts are considered.
The effectiveness of a particular diet or habitat choice is measured by the cost incurred
and benefits derived from the procurement activity. Costs may include the energy expended to
procure a resource through three separate acts: search, pursuit, and processing activity. First,
searching is the decision to select a resource or patch, based upon shared information, and it is
an intentional action on their part (Hewitt 1983:232; Keene 1981b). Opportunistic exploitation
is often the response when an intended resource foray was unsuccessful (Brody 1982; Ingold
2000). HGs seek resources where there is the highest density (measure of resources per unit
area) of resource, therefore likely the highest probability of return, partly due to a lower search
time. Therefore, search time can be an inverse function of food density (Egan 1993; Hewitt
1983; Keene 1981b; Smith 1983). Second, the pursuit costs are a function of the mobility of a
given resource. Hunting highly mobile animals such as elk and deer requires cost effective
strategies including trapping, sitting and waiting, or a communal effort to flush and trap.
Further, the costs of pursuits are reduced through mapping onto the behavior of resources,
whereby the foragers place themselves in the opportune places to reduce effort. Pursuits cost

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can be summarized as inversely proportional to the level of prey aggregation and proportional
to the distance of prey from the hunter. Third, the most complex of the procurement activities
to quantify is handling or processing costs since the act is dependent on a complex set of
variables including technological efficiencies and resource weights. In an effort to simplify the
procurement costs, this project does not consider the level of technology as a basis for
procurement costs but relies on resource density and weight as a measure of these costs. A
given cost of processing is directly correlated with the size of the resource multiplied by the
density of the resource. For example, processing 100 pounds of elk is equal to processing 10
pounds of fish where there are 10 fish caught.
Further, the risk and uncertainty of each must be included in the cost and benefit
calculations. Uncertainty and risk can be demonstrated as the distribution of resource
productivity keyed to environmental conditions. HGs are likely to have knowledge of the
reliability and security of a resource, predicted from past experiences (see Chapter 1 for more
information). The greater productivity of a given resource is a proxy for its predictability and
security. Uncertainty and risk can also be conceptualized as stochastic, the randomness of
resource availability or procurement success, where a given patch can have differential
productivity in a given day and season. The reliability and security of a resource is a
spatiotemporal variable where resources vary seasonally and inter-annually. They may vary in
their predictability, abundance, and biophysical characteristics including weight and density.
The reliability and security of resources varies according to a species wariness and mobility,
which can vary seasonally. For example, deer are gregarious and tend to aggregate during
rutting season; anadromous fish are highly mobile and aggregate during spawning.

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At the habitat scale, uncertainty is represented by the knowledge of alternative patches
held by foragers, whereas risk is represented by the choice of a forager–to choose patches that
are more predictable from previous experiences. To simplify the challenges of calculating
procurement costs, this study creates a composite cost of search, pursuit, and processing as the
relative efficiency in term of productivity (weight [kg] multiplied by density of resource per unit
area [km2]) and a composite factor for uncertainty and risk associated with a resource or
habitat. The composite factor is based on a rank order of risky and uncertain habitats and
resources. The composite factor is based on the predictability, reliability and abundance of a
food resource and a habitat. Uncertainty can be determined by the mobility of a resource;
mobile resources are less certain. Habitats closest to a group’s current location are more
certain; one that are farther away are uncertain. Therefore, the logic employed to make choices
about resources and habitats are based on the combined costs and benefits taking into
consideration basic resource and habitat utility and risks and uncertainties in each.
Decision Logic
Given the composite costs and benefits of alternative choices, HGs are assumed to use
OFT decision logic. The initial simulation starting conditions observe a HG group located on the
most productive patch in the study area. They select what to consume, where to move, when
to leave in order to reduce the uncertainty and risk in the environment and based on the costs
and benefits of alternatives. An individual stays in a locale and procures resources based on the
rank order of resource alternatives (see Diet Breadth Model). They stay in a place (see When to
Move section) until the productivity of a nearby patch is greater within range of patches of
which the forager has knowledge (see Patch Choice and Ideal Free Distribution Models). The
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forager moves to new patch and begins a new procurement activity. The choice of where to
move is complicated by the information held by a forager. These choices are contingent on the
constellation of cost and benefits of the action that must be estimated or measured in order to
predict HG diet choice and land use.
Encounter Contingent Model
In an encounter contingent model, a forager randomly comes upon edible resources.
These encounters initiate a choice: to harvest or continue searching. Each of the resource items
is measured for its desirability by the net acquisition rate of energy. The rate is the cost
incurred subtracted by benefits yielded. This cost can be used to explain the benefit in pursuing
and handling or precluding the resource for another resource. This model is designed to predict
food that foragers should attempt to procure (pursue, capture, process, and consume) or
ignore in order to continue searching for greater returns (Hawkes and O'Connell 1992; Kaplan
and Hill 1992; MacArthur and Pianka 1966; Stephens and Krebs 1986). The model states that
once resources are ranked in terms of their returns or profitability, after search and handling
time are factored in, foragers should choose to pursue resources that yield the highest rate of
return upon encounter, irrespective of the encounter rate for each prey item. Lower ranked
resources will be pursued when higher ranked resources are unavailable, in order of
diminishing return rates (Gremillion 2002). A reduction in the density of higher ranked prey will
result in foragers increasing their diet breadth to include lower ranked items. These models are
used to predict changes in diet choice as a function of changes in the environment or in the
forager’s abilities or capacities.

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Resource depression, environmental change, and increased focus on a specific resource
may decrease encounter rates with highly ranked resources, which in turn will increase search
costs and lower overall foraging efficiency (Stephens and Krebs 1986). This will cause resource
selection to expand to lower ranked items. Conversely, increasing encounter rates with highly
ranked resources progressively will narrow the range of resources selected, displacing
previously consumed resource items (Broughton 1997; Pyke, et al. 1977; Schoener 1971). For
example, the introduction of snowmobiles increased prey encounter rates among Cree foragers
(Winterhalder 1983).
The diet breadth model suggests the most efficient strategy in an abundant
environment is a focus on the most productive resource (shrinking the breadth), whereas, in
distributed or patchy habitats, we will observe a diet breadth that is diverse to meet minimal
requirements for sufficient resources. The diet breadth model, an efficient strategy, therefore
an adaptive and evolutionary one, is to select the highest ranked resources when encountered,
and to shift to lower-ranked resources only when the density of highly ranked prey is reduced.
Resources outside those that are highly ranked will be ignored and with no partial preferences.
The decision to include a lower ranked item is not biased on its abundance, but is based on the
abundance of the higher ranked item.
When to move
A HG must make a choice regarding when to leave an area, where to move, or which
new patch to exploit due to declining resources in the current locale. The knowledge of
available patches determines the choice of next move. Given the knowledge of the available
patches, the rationale used by HGs follows two OFT approaches, including Patch Choice and
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Ideal Free Distribution (IFD). Patch choice provides logic for choosing how long to wait, when to
leave the current patch, and the decision between groups of patches. Ideal Free Distribution
provides the logic for choice among all known patches and interaction with other foragers.
The IFD explains why a specific patch instead of any other is selected. Patch choice
determines a locale that a forager should exploit next. The choice to move to a new locale is
contingent on the information that a forager holds about the productivity of a new patch. The
patch choice model specifies which areas a forager should choose to search in order to obtain
the maximum return when resources are unequally distributed (Pyke, et al. 1977). Foragers
should search higher ranked patches first (those yielding the highest returns after search and
handling time are factored in), and should search lower ranked patches as higher ranked ones
become depleted(Smith 1983). By moving, the group will incur the cost of moving and finding a
new patch. But, upon locating a new patch, the group will be rewarded with a higher rate of
return. The patch choice model follows the same logic as the diet breadth model.
Unlike diet breadth, decisions regarding patch choice are interdependent with decisions
about patch residence time. Within a patch, the rate at which food can be harvested declines as
a function of the time spent there by foragers. For example, the most accessible nuts are
harvested before moving to more difficult and less attractive ones. Marginal Value Theorem
(MVT) states that the optimal forager abandons a patch when its declining marginal rate of
return equals the Net Acquisition Rate, or the average foraging rate, averaged over visits to
many patches (both for resource value and travel time) (Charnov 1976; Stephens and Krebs
1986). The marginal value of the current patch is compared to the average value of moving on.

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Moving to a new patch increases the encounter rates, raising foraging efficiency and reducing
patch residence time in the depleted patch.
A forager moves more quickly through an environment that is dense with rich patches,
taking less from each one that is encountered. A forager will leave a patch before it has been
fully depleted, incidentally leaving stock behind for the patch to recover. Summarily, patch
decisions are synchronously-based decisions where the decision to leave and the travel
distance to the next patch are both considered with imbedded knowledge of forager
environment. Therefore, predictions about patch residence time depend on patch choice;
conversely, predictions about patch choice depend on residence time. The amount of time
spent in a patch is dependent on the rate of patch depression. Patch depression results from
over-exploitation, prey relocation, changes in prey behavior that make capture more difficult,
and microhabitat change through environmental change or human land use (Broughton 2003;
Broughton and O'Connell 1999; Charnov 1976; Nagooka 2002).
As an alternative to moving from patch to patch, HGs can reside at a central location
and exploit patches surrounding this central location for foraging and field processing effort.
This model attempts to solve problems stemming from situations in which resources are
located in a different place from where they will be consumed (Orians and Pearson 1979). This
model predicts that patches that are farther from a central place or residential base will begin
to be depleted after closer patches are depressed. This is because more distant and previously
under-used patches should contain higher densities of high-ranked prey, thus making longerdistance travel more worthwhile so long as the return rate is above that of nearer patches once
travel costs are factored in(Broughton 2003). Foragers should relocate their central place when

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foraging returns fall below those that can be obtained elsewhere once relocation costs are
factored in (Hayden 1981; Kelly 1989; Sahlins 1972). This model examines the cost of bringing
people and resources together once round-trip time from the patch to the place of resource
consumption is factored in. The general rule is that larger load sizes and greater pre-processing
will be more profitable the farther one must transport the resource (Beck, et al. 2002;
Bettinger, et al. 1997; Jones and Madsen 1989; Metcalf and Barlow 1992; Rhode 1990).
Ideal Free Distribution
The ideal free distribution (IFD) represents the logic of habitat selection and migration
(Fretwell and Lucas 1970). An IFD describes the way in which animals distribute themselves
between several resource patches. The theory states that individual animals will aggregate in
various patches proportionately to the amount of resources available in each patch. For
example, if patch A contains twice as much food as patch B, there will be twice as many
individuals foraging in patch A as in patch B. The term "ideal" means that animals are "ideal" in
their assessment of patch quality; they know how profitable each available patch is. For this
project, this ideal constrains the patches to those of which they have knowledge. The term
"free" means that animals are capable of moving unhindered from one patch to another. Both
assumptions are often violated, for example if the animals stop in the first patch they get to do
that without looking for others, or if there are dominant individuals preventing others from
foraging optimally.
The quality of the habitat depends on both resource abundance and the density of the
population inhabiting and using it. The IFD assumes that habitat quality is a function of
population density. The initial settlers exploit the best habitat more intensively. Further

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immigration and population growth reduce the availability of resources and the quality of the
habitat decreases. Crowding, depletion, and competition are possible reasons for habitat
quality decline. Conversely, habitat quality determines the equilibrium distribution of foragers.
The marginal quality of a highly valued habitat will eventually drop to that of second rank, as
yet unsettled habitat. If each group seeks to occupy the best habitat, further growth or
immigration will be apportioned between habitats A and B such that their marginal value to
residents in equalized. This model suggests that habitats will be filled on rank order, that
human densities at equilibrium will be proportional to the resource quality and that the
suitability of all occupied habitats will be the same at equilibrium. Likewise, small habitats will
be quickly affected by settlement, generating a sharply declining curve of suitability as
population densities increase. If immigrants were to defend their territories, then newly
arriving individuals would be displaced more quickly to lower ranked habitats, defined as the
ideal despotic distribution (Sutherland 1996).
For example, one study explores the seasonal and relative shifts in values and
availability of local and distant resource opportunities. A foraging group whose two most
important resources, margins of lakes and lacustrine species versus mountain sheep and pinyon
nuts, are found in geographically separated habitats. Their relative importance changes during
the seasons. We expect foragers to camp near the more dominant of the food sources (fish)
and use logistic mobility to acquire easily transported less dominant pinyon nuts. The shifts in
costs (transport) and benefits (yield) will lead to the decision to switch the pattern of
settlement and logistic procurement, thereby residing adjacent to pinyon nuts while harvesting
fish logistically (Zeanah 2000).

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Implementing the model
The coupling of the landscape model and behavioral simulation provides framework for
understanding of economic decision making in heterogeneous environments. Further, the use
of classic OFT models allows for consistency and methodological rigor. Next, both the models
require understanding of the SBD social and natural environment. The next chapter presents
this relevant data, focusing on the role of uncertainty and risk on these variables in the SBD of
Michigan.

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Chapter 4: Social and Natural Environment
Social and Natural Environment
The two built models of landscape and behavior employed in this research are based
upon the understanding of hunter-gatherer (HG) cultural and natural environments in the
Saginaw Bay drainage (SBD) of Michigan. These models are dependent upon the explicit
identification of factors determining the resources, habitats, and characteristics of the societies
that are present. Further, these factors need to be conceptualized through an understanding of
variability, highlighting the implications of change. Basin-wide variation is important for the
structure and distribution of resources and habitats in the study area (Larsen 1973). Variability
in the natural environment is credited to regional change in climate and linked changes in land
cover. Specifically, variability in the productivity of resources and habitats, and linked social
change, is understood through the changing economic role of wetland habitats and resources
(Dustin 1968; Fitting and Allison 1972; Keene 1972; Lovis 1985; Lovis, et al. 2001).
SBD wetlands provided an excellent resource base, offering typically reliable,
predictable, and abundant resources. Further, wetland environments have important
implications for societal development and complexity (Brown and Vierra 1983; Lovis, et al.
2001). This chapter presents relevant information directed at the coupling of social and natural
environments, which play a role in the economic decision-making of the HG. This is
accomplished through a presentation of an analytic framework linking both the social and
natural environments; with a review of relevant climate, geography, geology, hydrology, and
biogeography–highlighting the relevance, ecology, and inventories of each.

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Landscapes
One way to understand HG society and economy is through the ways they map the
natural environment through their experiences by making a locale, feature, or a place
important. The cumulative natural and cultural place can be considered as a landscape, the
totality of a natural environment understood through a cultural lens. Landscape or ”placebased” research provides a way to integrate environmental context in the analysis of
prehistoric land use and diet choice (Ashmore and Knapp 1999; Basso 1996; Tilley 1994). For
this research, the connection between a place and meaning is grounded in the intersection of
environmental uncertainty and human actions. Landscapes are created by incorporating
archeological, paleoecological, and geomorphological information, providing the basis for
understanding continuity and change in the development of culture (Basso 1996; Erikson, et al.
1980; Menzies 2006). The combination of landscape features and cultural use and markers
provides insight into the use of land and, by extension, its cultural perception. This perception
includes an understanding, often accomplished through language, of what places are
important, sacred, and dangerous (Basso 1988).
Taken together, landscapes are then the cognitive map of a natural resource
environment that is critical for human adaptation to uncertainty and risk (Golledge 1999).
Humans are said to acquire, code, store, decode, and use cognitive information as part of their
daily activities. Specifically, heterogeneous environments are easier to conceptualize, and
provide criteria for cognitive segmentation (Allen 1981). For example, a place where people live
(i.e., a village, residential base) and its surrounding territory were important elements of
personal and collective identity (Merrell 1989). For example, Anishinaabe perceive landscape as
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occurring along two axes, spatial and temporal (Davidson-Hunt and Berkes 2003). Spatial
perception relates to how patterns of things, such as resources, are distributed. Knowledge of
such distribution, interrelationships, and properties occurs along a temporal axis. Knowledge,
for example, of where a plant is growing allows you to harvest the resource as long as the plant
community does not change. What do you do if fire destroys that particular location? You must
have an understanding of both resources and cultural landscapes to cope with this event. This
understanding is accomplished through language. Words are used to link specific plant species
with the locations of those species.
Additionally, place names are also used to provide a mental image of how a place within
the landscape looks, how it is related to other places, what occurred at the place, and/or what
might be found in that place. Place names are fixed nodes, reference points, upon which the
creation of spatial patterning of the landscape is built. Place names did not just mark places but
brought together places in relation to each other by paths of travel and sacred and revered
settings. Landscape, in this perspective, becomes a network of nodes and trails that orient a
person in physical, social, and cultural spaces (Berkes, et al. 1994).

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Figure 4. Study counties
78

Over time, a landscape can develop unique meaning. For example, places that are
occupied or relevant for economic and social reasons are considered as persistent places (Lovis
2009; Schlanger 1990). Persistent places are unique locales that play important roles in the
cultural development of an area. Beyond a single locale, these places can be larger-scale
features, including key rivers, wetlands, and landforms (i.e., dunes, beach ridges, moraines,
kettle lakes, and so forth). These places have greater archaeological importance as exhibited
through extensive material inventories spanning time. Landscapes, in this way, link the social to
the natural world and can be analytic approaches to risk and uncertainty in SBD. In summary,
the landscape perspective provides a framework for linking the world of nature to society and,
therefore, the approach used for this project.
Biophysical Environment
The SBD natural environment is comprised of a number of key drivers from its ecological
past, including physiography, climate, and biogeography–culminating in the effective socionatural environment. One key factor in HG cultural development in the core Saginaw Valley
Basin is extensive wetlands. A focus and priority are placed on the development of habitats and
resources, the effective subsistence environment that is primarily derived from wetland
dynamics in the area. This focus is relevant since hydrology is an overriding influence and
determinant factor of land cover and resources that are present. Therefore, this project places
priority in the reconstruction of landscapes based on changing wetland dynamics over time (see
chapter 5).

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The physiography (geographic features) of the area is determined by glacial and postglacial geomorphologic processes (e.g., isostatic rebound, inundation, the drainage of lakes, and
incision of drainage outlets), from the Wisconsin glacial advance and retreat, which occurred
from approximately 14,000 to 13,800 B.P. (Dorr and Eschman 1970). The advance and retreat of
glaciers created natural features, including the Port Huron and Bay City Moraines. Glacial
processes also result in the development of study-period drainage systems, river networks, and
beach terraces created by Lake Saginaw and Lake Chicago during the Lake Algonquin stage
(Butterfield 1986). The terraces and moraines that were left behind, which run parallel to the
bay, provide the low relief and a substrate through which major tributaries such as the Cass,
Shiawassee and Tittabawassee, and Saginaw rivers flow and drain into Saginaw Bay.
These rivers form a centripetal drainage network with numerous stream inputs, and
they support extensive habitats and resources in the area. The core basin is unique with
extensive wetlands derived from limited topographic relief and poorly drained glacial and
lacustrine soil substrates. This environment is patchy with a seasonal diversity of plants and
animals that make the core wetland area a highly productive but uncertain environment. The
environment is balanced by abundance and scarcity due to localized seasonal variation and
landscape-wide changes resulting from a number of factors, including climate and hydrology–
resulting in complex land cover and biogeography.
Today, the Saginaw Bay Drainage (SBD) encompasses an 8,700 square-mile area within
twenty-two Michigan counties (Figure 4. Study counties). The drainage is America’s largest
contiguous freshwater coastal wetland system with 175 inland lakes and 7,000 miles of rivers

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and streams. Extensive riverine, coastal, and interior lacustrine wetlands provide habitat for a
multitude of floral and faunal species and serve as a vital migration route for waterfowl and
birds on the Mississippi flyway. The contemporary environment is unlike the prehistoric past,
due to large-scale changes that include wetland drainage and agricultural and industrial land
use. A number of key variables are important to the understanding prehistoric past including
climate, geomorphology, and ecology.

N

Figure 5. Terrain view

Climate
The present SBD climate is mild, ameliorated by the effects of Lake Huron and
protection afforded by Saginaw Bay. The annual rainfall ranges from 70-80cm, the average

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annual snowfall is 1 m, with an average growing season of 153 days (Albert, et al. 1986; Seeley
1918). First frost takes place between September 30th and October 15th and heavy frost (< 0
degrees Celsius) occurs between May 2nd and May 15th. These conditions make SBD capable of
supporting extensive plant growth. The Late Archaic (LA) and Middle Woodland (MW) Period
had a climate similar to modern climate, based on vertebrate and pollen data (see (Bernabo
1981) for detailed climatic coverage of the area), whereas, the Early Woodland (EW) is
suggested to be colder and drier (Halsey 1999). This generalization is misleading; much of the
past environment is based on multiple factors including temperature, moisture inputs, lake
levels, fluvial dynamics, plant cover, and other criteria.
The SBD is situated along the transitional zone between the Canadian and Carolinian
Biotic Provinces (Cleland 1966; Potzger 1947). The transition zone, a mosaic of heterogeneous
environments, is an area whose total carrying capacity was intermediate to both the Carolinian
and Canadian Biotic Provinces. The location along the near northern extremes of the Carolinian
Biotic Province results in phytogeographical patchiness, lacking in expansive homogenous
vegetation (Albert, et al. 1986). The area is also at the upper limits for a 150-day growing
season, which is a requirement for reliable plant productivity (Yarnell 1964).
The transition zone has implications for the resource landscape. In both biotic provinces,
winter is the most critical season. The SBD warm season, with a system of radial river systems
and high stream density and elevation profile, results in extensive wetlands and is a source of
abundant and diverse plant, mammal, bird, and fish resources (Lovis 1985). The available

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resources are diverse due to a mixture of species and higher density of resources, because of
wetland productivity in both biotic provinces (Hambacher 1992).
The phytogeography of the Canadian Biotic Province is typically characterized by mixed
beech-maple hardwood and coniferous forests, with a relatively lower game animal (i.e.,
moose, elk, and deer) density than in the Carolinian Provinces to the south. Plants and
migratory birds are also in lower densities and likely unavailable during colder months. Typically
long seasons of cold weather make Canadian biotic provinces harder places in which to live
(Cleland 1992). Ethnohistoric and contemporary groups living in the Canadian Biotic Province
are required to have a flexible subsistence system to cope with winter shortages. Among proto
historic groups in Michigan, the Ottawa fished, processed, and stored inland shore fisheries of
fall-spawning fish and lake trout. Fall fishing sites were likely places where groups aggregated
then dispersed for winter hunting (Cleland 1982): 772-768. Additionally, people lived on interior
lakes adjacent to resource-rich habitats, which was another way to enhance their chances of
obtaining food (Holman 1978).
Substrates
A key variable in the productivity of a landscape is the substrate of the study area. Soils
and water are substrates that are relevant to the study area. A given substrate determines the
density and distribution of plant and animal species (Soil substrates are the upper part of the
ground, and are affected by organisms, water, wind, and climate; therefore, they change
regularly. Soils are used by plant roots and constitute the basis for plant growth). SBD soils
originate from post-glacial deposits transformed by natural processes (i.e., chemical,

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precipitation and water percolation, organic material accumulation and percolation, and animal
and cultural modification). The core basin is flat, interrupted by low ridges, sand dunes, and
moraines. Old beach ridges are present near the bay; sand dunes are present downwind of
drainages, and crescent-shape end moraines run parallel to Saginaw Bay (Albert, et al. 1986).
These drainages are poorly emptied and cross cut by excessively drained beach ridges. The
quality of the overall soil is poor with much of the interior being a clay lake plain with dissecting
drainages (Egan 1993):61.
Contrary to those described above, productive soils are present along extensive river
meanders and confluences. The core basin soils are represented by categories based on their
elevation, drainage, and productivity, which are categorized according to United States
Department of Agriculture classification scheme (see Appendix A). Soils are characterized using
a classification system based on presumed soil genesis through historical and geomorphic
processes (Schoeneberger, et al. 1998).
Next, hydrology can be a more important substrate since the presence or absence of
water overrides any influence of soils. Both the permanent and temporary presence of water is
important to wetland environments. Hydrology is dependent on both the overland and the
underground presence and flow of water. Ground water levels are dependent on topography,
soil types, the presence of lakes, and generally follows the slope of soil surfaces. The deeper the
ground water level, the weaker the relationship with soil topography (See Appendix A – Soil
Classification).

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Lake Levels
Long-term variations and short-term fluctuations in lake levels modify the geography of
lake shores as well as the plant and animal communities associated with the Great Lakes and
inland aquatic and terrestrial landscapes. Lake level fluctuations may have spurred settlement
and mobility in the Saginaw Valley (Butterfield 1986; Larsen 1973; Lovis 1986). The lake level
phases for the study periods are the Lake Nipissing stage (184 m [605 ft] amsl) from 4700 to
4500 B.P. (2750 B.C. to 2550 B.C.) and the Algoma stage (181 m [595 ft] amsl) from 3200 B.P.
(1200 B.C.) During the Lake Nipissing stage, the Saginaw drainage system began to stabilize to
its current configuration (Monaghan, et al. 1994). Later, closure of a northern drainage outlet
shifted outflow to the south during the shorter high water Nipissing II. The outflow of high
water stabilized during the later post Nipissing recession. The Algoma stage (181m [595ft] amsl)
occurs around 3200 B.P. (1250 B.C.); waters continued to drain until modern levels were
established at 2600 to 2500 B.P. (650 to 550 B.C.)
The post-Algoma drainage played an important role in landscape characteristics during
this period. The decrease in water levels, from a high of 181 meters (594 ft) to 177 meters (581
ft), resulted in pooling and ponding of water between glacial moraines, producing extensive
marshes and swamps. The slow drainage of these high water levels conversely also created vast
heterogeneous terrestrial habitats. These new habitats provided for increased resource
productivity and opportunities for HGs.

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Modern lake elevations (177m [580 ft] amsl were established from 2600 to 2500 B.P.
(Lovis 1986; Speth 1972). The Nipissing and Algoma levels correspond broadly to the Late
Archaic, whereas modern lake levels are present during the Woodland Periods. These modern
levels were interrupted by short periods of high-water levels in both the Huron Basin and Bay
City areas (Farrand and Bell
1984; Larsen 1973; Lovis and
Cleland 1993; Speth 1972). One
such short-lived high-water
phase in the Middle Woodland
period is present at the Schultz
site (20SA2), at the confluence
of the Saginaw and
Tittabawassee rivers. These
fluctuations in lake levels are
present with high water phases
attributed to climate
(temperature and precipitation)
(Farrand and Bell 1984; Larsen
1973; Lovis and Cleland 1993;

Figure 6. Lake levels

Speth 1972). High water phases,
both during the Late Archaic and Middle Woodland, are proposed as key drivers of general
landscape characteristics and wetland habitats for this project (Figure 3 – Lake Levels).

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The Late Archaic in the Saginaw River Basin is a period with modern vegetation
communities, high water levels, and fluctuating lake levels (Ahearn and Bailey 1980; Cleland
1966; Cleland 1989; Cowan and Smart 1979; Egan 1988; Keene 1981b; Lovis, et al. 1994;
McMurray, et al. 1978; Monaghan, et al. 1994; Smith 1989; Yarnell 1964). The long-term
variations and short-term fluctuations in lake levels changed the geography of lakeshores and
the biogeography associated with the Great Lakes and inland aquatic and terrestrial resources
(Butterfield 1986; Larsen 1973). For example, a large number of Late Archaic sites likely were
found within a seasonally inundated landscape, evidenced by site locations at specific
elevations above local base levels; over time, sites do move lower to the base levels (Lovis
2009)
The Early Woodland Period is a relatively drier period, with lower water levels and less
periodicity of flooding. Others suggest that the Early Woodland economy was similar to the
Late Archaic, characterized by large mammal hunting, particularly white tailed deer (Odocoileus
virginianus) and elk (Cervus Canadensis), nut and wild plant harvesting, and fishing (Smith and
Egan 1990). Early domesticates were also introduced into the area. Squash (Cucurbita pepo)
was present, evidently coincident with the introduction of ceramics in that region (Arnold 1977;
Martin 1985; Monaghan, et al. 2006; Ozker 1982; Wright 1964).
The Middle Woodland Period is observed when lake levels in Lakes Michigan and Huron
rose to 180m amsl, which is 3 meters higher than modern levels (177m). The rise in lake levels
along the Huron basin likely resulted in periodic and extensive flooding (Kingsley, et al. 1999;
Lovis, et al. 2012; Lovis, et al. 2005; Lovis, et al. 2001; Monaghan, et al. 1994). Exploitation of
cultigens increases during the Middle Woodland. Squash is present at Bridgeport Township site

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(Egan 1990) and Schultz site (Egan 1993). Nut use decrease markedly during this time period as
well and may result from scheduling conflicts with the autumn harvest of domestic crops
(Allison 1972). Other interpretations include a shift in the exploitation of other wild plant
species (Lovis 1985) and concentrated or intensive hunting of large Cervids (deer) during rutting
season (Keene 1981b). Faunal assemblages suggest a limited range of productive large
mammals and fish exploitation (Cleland 1966; Luxenburg 1972).
A study on the adjacent Muskegon River highlights the fluvial dynamics of aggregation
and down-cutting following periods of equilibrium, suggesting variable discharges from the
uplands into the Saginaw basin played a role in wetland communities (Arbogast, et al. 2008).
Wetter climates of both Late Archaic and Middle Woodland Periods likely increased discharge
into the basin, renewing and sustaining wetland resource communities along drainage base
levels from the uplands to the Saginaw river outlet.
Biogeography
Biophysical variables, climate, soils, and lake level changes are the basis for the
ecological environment and biogeography that are present. Both the phytogeography and
zoogeography are the basis for habitats and diet choices and are affected by changes in the
landscape. Phytogeographical changes can be observed through pollen studies (see Appendix A
for more details). Pollen studies provide plant cover, density and distribution and can also serve
as proxies for temperature and precipitation. Five pollen studies, located in and adjacent to
SBD, are used to determine the plant cover.

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Table 1. Pollen sites
Lake/Bog
Location
Chippewa Bog
43.12389N -83.24111W

Altitude
270 m a.s.l

Demont Lake
Vestaburg Bog
Wintergreen Lake

248 m a.s.l
255 m
271 m

Cowden Lake

43.5N 85.0W
43.41667N -84.88333W
42.4N -85.38333, NE of
Kalamazoo, NW of Battle
Creek
NW, Bordering SBD

Hicks Lake

West, Bordering SBD

Unknown

Morrison Lake

SW, Bordering SBD

Unknown

Frain Lake

42.33N, -83.63S

271 m

Unknown

Author
(Ahearn and Bailey
1980)
(Kapp 1999)
(Gilliam, et al. 1967)
(Bailey 1977)

(Hupy and Yansa
2009)
(Hupy and Yansa
2009)
(Hupy and Yansa
2009)
(Kerfoot 1972)

The Vestaburg Bog (Gilliam, et al. 1967) and Chippewa Bog (Ahearn and Bailey 1980)
areas were forested by a diversity of hardwoods by the onset of the Late Archaic (5550 B.C.),
with a mixture of oak-hickory (Carolinian) and pine (Canadian) dominated biotic communities. A
warming period was present during the Hypsithermal from 4050 and 3050 B.C. (during the
Nipissing and Algoma Lake level Phases). Modern forest communities are suggested to be
present thereafter (Ahearn and Bailey 1980; Gilliam, et al. 1967; Kapp, et al. 1977; McMurray,
et al. 1978).
The study of cultural periods demonstrates similar patterns of pollen across the
different sites with a mix of southern and northern taxa. The pollen data, from the General
Land Office Survey (GLOS), archaeobotanical data, ethnohistory, and Curtis’ 1971(Curtis 1959)
study of similar forests in Wisconsin provide a classification of forest communities. The
communities include 1) northern and southern mesic hardwood forests; 2) a northern and
southern wet-mesic, hemlock, and hardwood forest; 3) a northern and southern, mesic, beech-

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hardwood-pine forest; 4) a southern mesic, beech-maple forest; 5) a northern and southern
dry-mesic, hardwood forest; 6) a northern mesic to wet-mesic, lowland swamp forest; and 7) a
northern and southern wet-mesic, hardwood forest.
Past reconstructions of botanical communities and pollen data show much concordance.
These sequences suggest a mixed hardwood forest, very similar to the pre-settlement forest,
which was established by 3850 B.C. with changes in the specific wood genera (Ahearn and
Bailey 1980; Gilliam, et al. 1967; McMurray, et al. 1978). No major changes in the composition
of forest communities are present. The terminal Late Archaic to the Early Woodland Period is
characterized by expanding forest communities; specifically Oak/Quercus spp. dominated
forests. The succession of plants and linked hydrologic and climatic changes, result in the
contraction of wetland environments and the expansion of forested communities.
The Middle Woodland Period, Hicks Lake pollen core suggests a northern mesic forest of
eastern hemlock/Tsuga spp., American beech/Fagus spp., and sugar maple/Acer spp. pointing
to a return to wetland-influenced landscape. Further, spruce/Picea-Abies spp. communities are
present in lowlands. Pine/Pinus strobes spp. and oak/Quercus spp. are also present, most likely
on sandy uplands. At Cowden Lake, dry oak/Quercus spp. and mixed forest oak/Quercus spp.
dominated with sugar maple/Acer spp., American beech/Fagus spp., elm/Ulmus spp., and
communities of Pinus and Quercus are also present. Oak/Quercus spp. begins to decline at 1850
B.P. At Morrison Lake, mixed oak/Quercus spp. and beech/Fagus spp. forest and oak/Quercus
spp. dominated forests with hickory/Carya spp., hop hornbeam/Ostyra spp., and
poplar/Populus spp. Beech/Fagus spp. and sugar maple/Acer spp. forests are also present but
are less dominant.

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Cowden, Hicks, and Morrison’s palynological data also demonstrates a different
perspective on plant cover and climate (Hupy and Yansa 2009). This analysis suggests that
climate change from the early to Middle Woodland Period results in the shifting on the tension
zone, and coupled the density and distribution of plant and animal species. Vegetative
environments changed from 2000 B.P. (Late Middle Woodland), from dry conditions to wet
conditions, resulting in increases in mesic forests–Fagus, Acer, and elm/Ulmus spp., concurrent
with a decline in oak/Quercus spp. abundance.
Taken together, the palynological data presents a static picture of plant communities
over time. But, these same data highlight the importance of local habitat changes. A shift
toward wet environments with ameliorating climate is observed during both the Late Archaic
and Middle Woodland Periods. Marshes along bay and river margins are present with waterloving species, including cattail/Typha spp., arrowhead/Sagittaria latifolia; sedge/Carex spp.;
and bulrush/Scirpus spp. (Curtis 1959). Pollen data further suggests an increase in aquatic taxa
at Vestaburg Bog at 1200 B.C. with the establishment of wetlands, with rising lake levels and
post-Hypsithermal moisture increase. These changes resulted in the contraction of overall
forested areas and an increase in cattail marshes. These phytogeographical changes are used to
link the types of habitats that are present to economically relevant animals (Albert, et al. 1986).
Zoogeography of the area is a mix of species found in both the Carolinian and Canadian
Biotic Provinces. Since zoogeography is directly connected to the habitats that are present,
birds (e.g., geese, ducks), reptiles (turtles), mammals, and fish represent SBD diversity (Baker
1983; Cleland 1966). Over time, the changes in phytogeography and habitats result in
concomitant changes in density and the distribution of all species. In the terrestrial

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environment, changing plant communities through secondary succession provided an area
where a diverse set of small and large mammals is present.
Wetlands and other aquatic environments are observed to support a diverse set of
animal resources. A wide range of species are present in lakes, fast rivers, as well as shallow,
and slow-moving waters (Cleland 1966; Keene 1981a). For example, riverine anadramous fish
species (lake sturgeon and sucker) are present and seasonally abundant. Wetlands serve as
areas of dependable food sources for many bird and terrestrial animals. The SBD served as a
vital link along a minor flyway for migratory waterfowl (Keene 1981b). Both terrestrial and
aquatic resources are taken into consideration for the landscape model; these variables are
modified, based on the habitats that were present at different study periods.
Role of Wetlands (Palustrine Systems)
Wetlands are among the Earth's most productive ecosystems. They provide food, water,
raw materials, landscape stability in the form of flood control, and other ecosystem functions.
They are sources for biodiversity and have high resource density. Wetlands are areas of
transition, formed by both aquatic and terrestrial factors, and the borders between them are
hard to define. They can be classified according to their ecology, their natural and societal
function, or their hydrology. An understanding of a wetland ecosystem is important for the
understanding of the adaptive process of the Saginaw Bay Drainage. An attribute of wetlands is
a diversity of wildlife habitats, providing economically important animal and plant species
diversity. Hydrology is the driving and unique force in wetlands; the presence and duration of
water in the soil column and on the surface influences the soil productivity and plant growth.

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Temperate wetlands, like the study area, are categorized into three common types; marshes,
swamps, and bogs. First, marshes are the most biologically productive ecosystem in temperate
regions, especially in Michigan. Marshes are characterized by the broad array of wetlands that
are dominated by grass-like vegetation. Typical marsh plants include rushes, reeds, sedges,
cattails, and grasses. These areas are periodically covered by standing or slow moving water
and are usually associated with ponds, rivers, streams, inland lakes, and the area’s Great Lake –
Lake Huron. Sandy soils and finer textured, nutrient rich soils with large amounts of organic
matter are key to Marsh substrates (Comer 1995, 1996).
Marsh-like wetlands can include interdunal swales (wet areas between beach ridges)
and wet meadows (saturated soils, grass-like vegetation, also referred to as wet prairies). The
lush vegetation and rich invertebrates and insect life provide excellent habitat for water birds,
furbearing animals, and are important spawning grounds for many fish species. Second, on the
other hand, swamps are wooded wetlands (e.g., conifer, hardwood, and shrub). These areas are
also inundated or saturated periodically during the growing season. Many swamps are also
associated with lakes, rivers, or streams or with the presence of ground water near the surface.
The soils are typically nutrient high, with organic matter deposited by flood events and the
interannual accumulation of organic matter. Dense vegetation and proximity to the surface
allows for a high nutrient exchange between land and water ecosystems. Third, Fens
(connected to ground water) and bogs (water from rains) are wetlands that are covered with
thick peat deposits.
These places serve as habitat for deer, bear, raccoons, and small animals; they are a
resource attraction for wild animals. Fish and bird species are dependent on wetlands for food

93

and nurseries, and wetlands are a preferred habitat for furbearing animals such as muskrat,
beaver, otter, mink, and raccoon. Cedar swamps are critical for winter browsing for white tailed
deer and for thermal cover. For plant growth, wetlands are areas that are unique to the
secondary succession of plants.
Ancient peoples were attracted to wetland environments due to the wealth of
resources, plants and animals, and the ease of travel and transport. People rarely settled in
wetlands, but chose to map onto these resources along the edges of wetlands, harvesting the
resources therein. Wetlands have high values of resource diversity, productivity, and reliability
(Nicholas 1991; Williams 1991). Larger wetlands, like SBD, may support a wider range of biotic
communities and may have been important hunting and collecting areas that were used
intensively. SBD may not have had any modern analogues at specific times, such as when this
area was likely a wetland mosaic of terrestrial and wetland components that formed within
former glacial lake basins. A wide variety of habitats and features can be associated with these
settings, including shallow lakes and ponds, emergent riverine systems, adjacent uplands, and
mixed deciduous-coniferous forests, each with a unique biotic community. These landscapes
were higher in diversity and productivity than those in surrounding upland and coastal zones.
These patterns may have served this area as a core area for settlement, where uplands and
coastal areas are secondary or seasonal procurement areas associated with smaller cluster
sites. Resource abundance in the context of regional scarcity may have encouraged some
degree of sedentism (Kelly 1995a). Clustering associated with the change in productivity of
wetlands and other landscape components may be present.

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In the long term, wetlands can be used in different ways. The different land-use pattern
can be an indicator of a differential resource-use structure. Possibly, there could be a shift in
the importance of wetland adaptation from a core area to a peripheral one for seasonal or
resource-specific harvesting episodes. The presence of cultural features and material culture
may reflect these patterns. The relative ratio of resources to other resources can be an
indicator of this change. The decrease in size of the wetlands played a role in subsistence and
technologies used in the exploitation of resources. Land-use changes are also likely.
Environmental fluctuations can result in changes in land use where the appearance of longerterm housing structures, associated with wetland areas like marshes, could be indicative of
increasing and decreasing focus on wetland resources. First, a continual use of an area or
wetland resource is indicative of long-term stability, reliability, and importance. This intensive
and extensive and long-term focus could also be a trigger for the exploitation of the efficiency
of lowland forests and plant harvesting (Smith 1995; Struever and Vickery 1973; Usner 1983).
Contemporary indigenous groups continue to depend heavily on wetland resources. Many still
collect plants such as cattail, tule, wapato, water parsnips, Canada mint, sphagnum moss, bog
cranberry, creeping snowberry, and other plants (Fowler 1990).
Wetland environments played an important role in human adaptation in SBD. An
increase in underground and overland water flow occurs during every spring thaw. Broad low
slope riverine environments likely result in flooded environments, especially in areas with wide
stream meanders. Extensive wetlands were almost continuous in the drainage basin during the
early nineteenth century (Houghton 1837; Macomb, et al. 1856). Swamps, marshes, bogs,
estuaries, and seasonally inundated lands are components of the regional SBD landscape. The

95

importance of these settings is demonstrated by the incorporation of wetland flora and fauna
into economic and subsistence practices. Further, these areas may have also fulfilled economic
buffer zone requirements of defensive refugia and spiritual/sacred places. Clustered wetlands
have been shown to be the foci of frequent seasonal resource exploitation in the past. They
may have been used restrictively as temporary food shortage resource zones due to drought
elsewhere. Last, the geoarchaoelogical studies of the core of Saginaw Valley suggest likely
impacts to a majority of the sites located along riverine environments, due to erosion through
fluvial geomorphologic processes (Arbogast, et al. 2008; Lovis, et al. 1996).
Extensive wetland environments have a higher biomass and can support higher
population densities. The intensive use of wetlands may have allowed for a decrease in
minimum territory size for groups. Territoriality and increased sedentism may also be
established in this intensive use of wetlands through the association of cemeteries linked to
wetlands. Recurring use of these cemeteries may identify them as special places on the cultural
landscape, which were maintained or revisited as part of recognized territories or cultural
landscapes (Doran and Dickel 1988; Jefferies 1987). Schultz/Green Point sites highlight this
practice (Fitting and Allison 1972; Kingsley, et al. 1999; Lovis, et al. 2001). Conversely, wetlands
can be a limiting factor in HG land use. Specific types of wetlands, such as muskeg and
hardwoods, may restrict the exploitation of resources and may limit travel as well as unknown
or dangerous places. These areas can also be places that are unappealing for settlement due to
excessive moisture and possibly nuisance bugs that may be present.
In summary, the features of the landscape and human responses are transformed due
to increasing and decreasing wetland environments, and to resource distributions in the area.

96

High water stages in these areas likely caused a number of short–term problems but also
allowed for new opportunities with the expansion of the diversity of productive wetland
resource communities while sustaining existing resource structures further afield (Lovis 1986;
Lovis, et al. 2001). Primarily, the broad landscape variability can be viewed as an asset for HG
subsistence. Throughout the study periods, the Saginaw basin is annually renewed by variable
moisture inputs associated with both lake levels and fluvial drainage networks. Geomorphologic
processes such as centripetal drainage into the core basin sustained and renewed cyclic
wetland environs to encourage the development of microenvironments, which supported
productive resource communities.
Modeling Risk and Uncertainty
Incorporating the diversity of information presented in this chapter is almost impossible
and ineffective for a modeling effort, especially since models are intended to be the
simplification of reality. Ethnographic and ethnohistoric information shows that hunter–
gatherers are selective regarding the places and foods they choose to exploit. Therefore, only
relevant habitats and foods are used for the modeling effort. Further, these built models are
dependent upon the risk and uncertainty of these habitats and resources.
Habitats are dependent upon the overall environment of a given season and time
period. Late Archaic and Middle Woodland habitats are heavily influenced by changing lake
levels and fluvial dynamics. Conversely, Early Woodland habitats are similar to late prehistoric
landscapes. Habitats (also called resource communities) are assemblages of interacting plants,
animals, and other organisms that repeatedly recur under similar environmental conditions and
are predominantly structured by natural processes (Kost, et al. 2007). The productivity of a
97

given habitat type is determined by its ecological makeup and varies according to biophysical
characteristics.
Resources within a habitat are classified according to social and economic importance,
based on kilocalorie yield and life history. A resource’s life history explains the availability and
productivity in a given habitat in a given month. These resources are based on published
sources (Baker 1983; Barnes and W.H. Wagner 1981; Keene 1981b; Yarnell 1964). They are
classified in broad categories, including plants (nuts, fruits, seeds, greens, roots/tubers/corms,
saps); and animals (small and large mammals, fish, bird, reptiles, shellfish). Availability is
determined by their presence in a given habitat and based on cultural preference for exploiting
a given resource. For example, bears are usually hunted and taken in late fall and winter
months when they are fat and hibernating, which makes them less dangerous to hunt (Carver
1956; Henry 1969). Birds are available year round, whereas migrating waterfowl are present in
high density during key months. All resources are available to each member of the group given
that each member type has higher or lower probabilities of capture of each resource (see
Chapter 6). For the purposes of this study and to maintain reasonable simplicity, resources are
categorized into separate classes: large and small mammals; large and small fishes; migratory
birds, etc.
Productivity of the resource is based on a simple estimate of mean density versus mean
weight (yield). These values are based on established scholarship within Michigan and the Great
Lakes (Baker 1983; Keene 1981b; Lovis 1989). Average densities per 3 km2 (1 mi2) are
multiplied by average weights to calculate productivity in each habitat during a study period.
For animals, productivity also varies based upon the community level behaviors, including

98

aggregation and dispersion. For example, anadromous fish can be highly aggregated during
spawning. These factors are taken into consideration with varying seasonal values for each.
Plant densities and yields are based on a given habitat and season (Cowan 1985; Hewitt
1983; Keene 1981b; Reidhead 1979). These mean densities are based on GLOS information and
comparative information from Wisconsin (Curtis 1959). Mean yields are based on the values
determined by taking into consideration the capability of a plant to bear fruit, and the net
edible biomass that is available. The productivity of each plant is calculated for a given area or
the basic spatial unit of analysis (3km2).
Both plants and animals are exploited by all members of the group. These resources have
inherent risk and uncertainty dependent upon the biophysical environment. Resource
uncertainty is the lack of knowledge about the presence or absence of a resource. Risk is the
chance that you may fail to procure a known resource. Plants have low uncertainty and risk
because they are fixed in place and can be exploited easily. They are more apt to be gathered
by women and children. Further, small and less dangerous animals (i.e., rabbits, squirrels) have
greater uncertainty and greater risk due to their mobility. Highly mobile and distributed
resources having greatest uncertainty and risk (least probability of success) are apt to be
exploited by men. The relative success of resource exploitation is determined by a composite
factor intended to quantify resource risk and uncertainty. For example, a male aims to exploit
resources that are higher in risk and uncertainty, whereas women and children exploit more
reliable resources. Therefore, men and women exploit resources based on their risk and
uncertainty preferences by creating a differential rank order of resources. Based on this rank
order, a HG exploits resources that are present in a habitat. Finally, this composite value is

99

multiplied by the relative contribution to diet by men, women, and children. Women and
children provide kilograms of food per .004 km2 (1 acre); resources exploited by men are
calculated as contributing .10 km2 (25 acres) area; collective resources areas provide .08 km2
(20 acres). Maple sap varies as collected from a .008 km2 (2 acres) area.
The last several and the current chapters present the background required for the
development of both landscape and behavioral models. The combination of uncertainty and
risk-based theories provide the framework for understanding the roles of landscape and
behavior on diet and land use, with the identification of relevant variables. The chapters that
follow provide the analytic and interpretive component of this research effort. The next chapter
creates the resource landscape model present during the study periods. The subsequent
chapters explain HG land use and diet behavior. The last analytic chapter describes
archaeological implications and an evaluation of models and the material culture that is
present.

100

Chapter 5: Predictive Resource Landscape
Introduction and Approach
This chapter recreates a prehistoric resource landscape. The landscape can be used as
the environmental and spatial context, where hunter-gatherer (HG) land use and resource
choices can be explored (see chapters 6 and 7). Further, this landscape can be used to predict
resource intensive and depleted zones at a given cultural period. Prior studies have addressed
landscape – habitat – resource relationships by a focus on terrestrial features including
geomorphologic and biogeographic factors (Arnold 1977; Jochim 1976b; Krist 2001). This work
leverages these studies and refines them by placing priority on underexplored hydrological
drivers. The predictive resource landscape model is based upon the aggregation, synthesis and
manipulation of historical and contemporary ecological datasets. The model is developed by
the creation of terrestrial and palustrine (wetland) land cover and resource communities (see
Figure 7. Landscape data model). These resource communities are habitats and patches with
differential biogeography present. As is well known, habitats comprised of animals and plants
contribute to hunter-gatherer (HG) diet and land use choices, often framing the social relations
of these prehistoric groups. Two key types of landscape are constructed: palustrine and
terrestrial. A priority is placed on palustrine landscapes due to the extensive influence of
hydrology on past terrestrial environments of the Saginaw Bay Drainage (SBD) (See Chapter 4
for background). Distinct models based on Late Archaic (LA), Early Woodland (EW) and Middle
Woodland (MW) study period land covers are created.

101

The analytic landscapes are presented as composite models. A composite view is the
integration of multiple events as part of a map, comparable to a snapshot in time. Composite
information presents events in multiple states at adjacent points in time creating a time trend
or series of maps allowing for better understanding through visualization and documenting the
chronology of changes to land cover in the study region by considering different states as
bounded by temporal events. The composite maps are generated by using Geographic
Information Science (GIS)-based visualization methods. GIS software, ESRI ArcMap v.10, allows
for both the visualization of and interaction with large amounts of information, permitting the
alteration of the displays. This approach creates multiple perspectives (i.e., spatial and
temporal) and enhances the understanding of varied phenomenon.
The geographic datasets used in this effort were acquired from the State of Michigan
Digital Libraries, maintained by the Center for Geographic Information (Department of
Information Technology). The Michigan geographic framework uses a single zone system
named the Michigan GeoRef projection system, using the Oblique Mercator based North
American Datum 83 (NAD83) (CGI 2009; MDNR 2001). The visualization of the study area
includes multiple dimensions and spatial variables such as geology, groundwater, hydrography
(drainages, wetlands, shorelines, and fluvial systems [rivers and streams]), historical and
contemporary land cover/use, soils, topography (digital elevations, land forms). These digital
vector and raster datasets are clipped from original statewide regions to study area Counties
and further modified by relevant geomorphic variables using established geoprocessing
techniques (e.g., buffer, overlay, map algebra etc.).

102

Terrestrial and Palustrine Landscapes
Palustrine and terrestrial environments are created through the synthesis of historical
and contemporary proxies (see Figure 8. Wetland data manipulation). The palustrine
environment can be further subdivided and categorized into coastal and interior areas. Both
environments are determined by numerous variables: moisture (precipitation, snow melt),
subsurface hydrography (water table and wetland recharge), Lake Huron levels and fluvial
dynamics (river confluences, stream meanders boundaries), climate (temperature), and
topographical landforms (terrain, local base levels, moraines, ridges). Precipitation and snow
melt contribute variable amounts of moisture over the different study periods of interest by
distribution through river and stream networks to Saginaw Bay, or absorbed into the soil
substrate. The input volume varies according to the season, resulting from spring thaw and
snow melt. Such seasonal hydrodynamics create shorter- and longer-lived wetlands and
wetland-influenced terrestrial environments. Additionally, these processes can create
alternating wet and dry areas whereby different types of perennial, annual, or seasonal
wetlands are created. Stability in wetland environment, coupled with complimentary soils can
create unique and highly productive resource environments. It is these stable wetland
landscapes that support a high density and diversity of resources (see Chapter 4 for discussion
of wetland types and resources).
First, the extent, configuration and composition of coastal wetlands are driven by Lake
Huron water levels, the coastal hydrography, and soil composition. Specifically, coastal wet
areas are determined by the interplay between low coastal gradients elevation, water table
proximity to the surface, and poorly drained soils. Areas with poor soil permeability, drainage,
103

and recharge play a role in water remaining above ground (i.e., surface storage). The greater
the permeability, the quicker the ground surface becomes dry—all other things being equal.
Second, the interior wetlands are conditioned by similar factors, with significant addition of
topography. The interior wetlands are influential in areas that are likely to trap excess moisture,
such as local base levels, which are flat areas (zero slope) and topographical buffers (i.e.,
moraines, ridges) that retain water longer. These moisture-influenced terrestrial environments
are places where one can observe rapid primary succession of wetland tolerant plant species
and secondary succession of non-wetland tolerant plant species. Coastal and inland wetlands
each create unique environments. The climate of the study area in turn results in short-term or
long-term reactivated wetlands, where there are unique locales for productive habitats through
the seasonal succession of plants and the associated habitats for a variety of animals.
The terrestrial environment is analytically created by the synthesis of topographical
landforms and the lack of wetlands. Such areas are compositionally driven primarily by the
absence of water, this due to the lack of retention of moisture inputs, drainage, and are linked
to higher groundwater recharge (higher absorption and saturation). The drainage and recharge
factors also help in determining the type of plant cover present in a given area. This
combination of terrestrial and palustrine land cover, which can then be associated with
pertinent palynological data, results in the probable resource communities. This project
simplifies the diversity of resource communities by limiting them to established communities
(Kost, et al. 2007). From the seventy-six different communities, this research reduces the
diversity by focusing on a subset of fifteen key resource communities (see Appendix A for
resource community’s description). Among these, fifteen are wetlands (emergent marshes,
104

hardwood and conifer swamps), lakes, rivers, forested upland (e.g., beech sugar-maple forests,
mixed oak forests, coastal wet prairies). Land cover classes are also aggregated in a number of
ways to highlight wetlands and vegetative structures: (1) forests (coniferous, deciduous,
mixed); (2) non-forest (range, barren); and (3) wetland (emergent and hardwood), and so forth.
The variables in aggregate define terrestrial and palustrine environments are aggregated
in ways that reflect the probable environments present at a given time period (see Table 2Table
2. Variable manipulations).

Table 2. Variable manipulations
Variable
Late Archaic
Rivers and
Current + 300 meter
streams
buffer, lower
slope/energy system
Terrestrial cover
Lake levels
Water table
Local base
levels wetlands
Pollen
Soils – Flooding
Soils – Ponding
Ground water
recharge

Early Woodland
None
higher slope/energy
system

Low
184 - 181 amsl
Contemporary
High

High
177 amsl
Contemporary
Low

Middle Woodland
Current + 100 meter
buffer
lower slope/energy
system
Medium
181 amsl
Contemporary
Low

See pollen diagram
High – Annual
High
Contemporary

See pollen diagram
Low – Seasonal
Low
Contemporary

See pollen diagram
High - Annual
High
Contemporary

Geoprocessing
Prehistoric landscapes are reconstructed by the manipulation of geographical
representations of contemporary and prehistoric biophysical proxy data. The disparate types of
data and the relevant contribution of biophysical variables to both the palustrine and terrestrial
landscape models are organized into two categories of complexity: base models, augmented
models (Table 3). Base models entail a simple modification of existing spatial data. Augmented
105

models are built upon multiple base models. Base models include the creation of: local base
levels, historic wetlands, lake levels, water close to the surface, groundwater recharge, soils,
fluvial geomorphology, and flooding. These manipulations involve simple selection and
buffering procedures to create polygons for relevant time periods intended to be used in the
augmented models. The combination of these base and augmented polygons creates unique
resource landscapes for the three study periods (See Appendix A).

106

Elevation (>max
lake level)
Landforms
(terraces, ridges)

GLOS Land Cover
(Wetlands)

Terrestrial

Topography
Soils

Recharge
Drainage

Composite
Landscape
(resource
communities)

Palynology

Lake Levels

Palustrine
(wetlands)

Water table

Rivers & Streams

GLOS Land Cover
(plant cover)
Biogeography

Lakes
Climate
Recharge
Drainage

Zoogeography

Figure 7. Landscape data model

107

Coastal
Wetlands

Interior
Wetlands

Rivers &
Streams

Current Lake
Levels

Elevation

Lakes Levels
Elevation
<1
m

GLOS
Land
Cover

New Base
Lake Level

Seasonal
Wetlands

Water Table
<1m

Drainage

Water Table
<1m

Drainage

Overlay
Coastal
Wetlands

Interior
Wetlands

Palustrine
(Wetlands)
Figure 8. Wetland data manipulation
108

Local Base
Levels

Table 3. Data manipulation – reclassify attributes
New
Base or
Original
Vector
Dataset
Augmented Dataset
Raster
Local Base
Base
Digital
Raster
Levels
Elevation
Model
Historic
Base
GLOS 1800s
Vector
Wetlands
(polygons)
Lake Levels
Base
Digital
Raster
Elevation
Model
Water close
Base
Water table, Raster
to surface
Digital
Elevation
Model

Output

Attributes/Action

Vector
(Polygon)

Slope = 0 and area about 3,500 acres, reclassify attributes

Vector
(Polygon)
Vector
(Polygon)

Select by wetland land cover, rivers, and lakes. Buffer by
300 meters, reclassify attributes
Map Algebra select for historical elevations, and buffer
300 meters, reclassify attributes

Vector
(Polygon)

Raster subtraction of Water Table from Digital Elevation
Model. Select where they are separation within one
meter. Seasonally inundated wetlands are riparian areas
using vertical proximity (<1m) to a water table surface.
Convert raster to vector. Shrink polygons to reflect,
reclassify attributes
Select for low recharge. High recharge areas are used as
the basis for climatic expansion of forest regimes based
on transitional boundaries, reclassify attributes
Select for all land cover excluding rivers, streams, and
wetlands, reclassify attributes
Select hydric soils, flooded, and ponded classes during
the winter to early spring, reclassify attributes
Buffer 300 meters along similar contour elevation for
possible upstream wetland environments, reclassify
attributes

Groundwate
r Recharge

Base

Groundwater Vector
Vector
Recharge
(polygons) (Polygon)

Plant cover

Base

GLOS 1800s

Soils

Base

SSURGO

Rivers and
Stream
wetlands

Augmented

Hydrography
, Digital
elevation
models

Vector
(polygons)
Vector
(polygons)
Vector
and
Raster

Vector
(Polygon)
Vector
(Polygon)
Vector
(Polygon)

109

Table 3. (cont’d)
New
Base or
Dataset
Augmented
Coastal
Augmented
Wetlands

Original
Dataset
Multiple

Vector
Raster
Vector
(polygon)

Output

Attributes/Action

Vector
(Polygon)

Overlay of coastal river and stream buffer, elevation,
water close to surface, poorly drained soils, and historical
wetlands, reclassify attributes
Overlay of river and stream wetlands, local base level,
water close to surface, poorly drained soils, and historical
wetlands, reclassify attributes
Overlay of Land form features, elevation, base plant
cover, and climatic modifications based on climatic
regimes, reclassify attributes

Inland
Wetlands

Augmented

Multiple

Vector
(polygon)

Vector
(Polygon)

Terrestrial
Landscape

Augmented

Multiple

Vector
(polygon)

Vector
(Polygon)

110

The Early Woodland resource landscape is assumed to be similar to GLOS 1800s land
cover with modern lake levels and drier and colder climates. The earlier LA is a drastically
different period, with warmer climates, extensive wetlands, and higher lake levels. MW is an
intermediate period with expansive wetlands and moderate climate (See Chapter 3). The
augmented models are created by the manipulation and combination of base models by a
series of data manipulation operations (e.g., overlay, buffer). In general, the data manipulation
is as follows:
The first step is the modification of The GLOS 1800s land cover, the land cover is used as
a baseline landscape model for the creation of both the LA and MW high-water period
landscapes. Both of these periods have variable moisture inputs, therefore resulting in variable
wetland densities and distributions. The Michigan Natural Features Inventory (MNFI) digitized
General Land Office Survey (GLOS) and 1990 United States Geological Survey (USGS) 100K DLG
land cover data provides the basis of land cover and resource communities. The plant cover and
wetland distributions in the GLOS set the framework for the environmental reconstructions
(Comer, et al. 1995). The GLOS, which remains the most detailed pre-settlement vegetation
data set for the study region, was originally conducted as part of the mapping of the area
included within the Northwest Ordinance between 1821 and 1834. Surveyors took detailed
notes on the location, species, and diameter of each tree used to mark section lines and section
corners. They commented on the locations of rivers, lakes, wetlands, the agricultural potential
of soils, and the general quality of timber along each section line as they were measured.
The second step involves the the inclusion of rivers and streams. The modified land
cover is altered to include a buffer to account for stream meanders and overbank flow, while
111

retaining original river boundaries. These areas are classified as seasonal wetlands, and are
prone to ponding and flooding with seasonal grasses and shrubs.
The third step includes the inclusion of lake levels. The modified land cover is overlaid
with the lake levels for each of the several bounded study periods. Lake levels provide the
minimum extent of inundated landscapes, both along the coastal and interior low-lying areas
comprising the composite model. These high water levels also affect the fluvial dynamics of the
larger regional system, with decreased slope, reducing the energy of the water flow, and
resulting in pooled and flooded upstream locales. Lake levels for each period are determined by
using a digital elevation model with a horizontal resolution of 1m and vertical resolution of 20
cm.
The fourth step involves local base levels. The land cover is further modified by local
base levels. Local base levels are areas that are larger than 1200 hectares with flat or level areas
(zero slope) and which are linked to large river and stream networks. These base levels trap
moisture for short periods until they are drained, either to lower elevation or to be percolated
into the soil. Such areas are places with high probabilities for seasonally activated wetlands
(emergent marshes and shrub swamps). Whether they become marshes or annual wetlands is
determined by the rate of moisture input and drainage, based on the relevant time period.
Once drained, these areas are transformed into terrestrial habitats through succession where
plant communities are present, rates and states being dependent upon soil composition and
groundwater recharge potential.
The fifth step involves the inclusion of the water table. The land cover is modified
through water table effects. A water table close to the surface is an area with higher moisture,
112

especially when external inputs (precipitation) result in ponded and flooded areas. These areas
that are likely to have seasonal wetlands are likely to be persistent places that serve as resource
draws. Therefore, land cover is overlaid with high water table areas as potential locales for
seasonal inundation. Dry land areas are those with neither water input, nor proximity to a
water table (>1m). These areas possibly are not always dry, but could be fed by runoff and have
well-drained soils. This classification threshold results in groups with fairly distinct average soil
and water conditions (Baker, et al. 2001). The water table digital elevation is subtracted from
topographical elevation model to arrive at the water table influenced areas.
Note: steps 1 through 5 establish probable areas for the pooling of water. Within these areas,
water tables close to surface, local base levels, and low-drainage soil classes determine areas of
standing water.
The sixth step involves the inclusion of soils data. The land cover is modified by possible
areas of flooding, pooling of water, and poor drainage using the Natural Resources
Conservation Service (NRCS)-National Cartography and Geospatial Center (NCGC) archived and
distributed the State Soil Geographic (STATSGO) and Soil Survey Geographic (SSURGO)
databases.
The seventh steps include the groundwater recharge rates. The land cover is overlaid
with areas of low to high groundwater recharge. Plant species and communities are dependent
upon how quickly moisture percolates down into the soil and root systems. Groundwater
recharge or deep drainage, or deep percolation, is a hydrologic process where water moves
downward from surface water to groundwater. Groundwater is recharged naturally by rain and
snow melt and, to a smaller extent, by surface water (rivers and lakes). Recharge estimation is
113

determined by principles of soil physics. The extent of ground water recharge by a wetland is
dependent upon soil, vegetation, site, perimeter to volume ratio, and water table gradient
(Carter and Novitzki 1988; Weller 1981)}. Groundwater recharge occurs through mineral soils
found primarily around the edges of wetlands (Verry and Timmons 1982). Therefore, recharge
levels can be an excellent basis of predicting resource communities (See Appendices 5 drainage model).
Low levels of recharge and drainage result in moist environments that are slow to dry,
especially after spring melt. These areas are likely places for mixed hardwood and conifer
swamps. Coastal areas with similar attributes are wet prairies and shrub swamps. Higher
elevation, low recharge areas are usually mixed conifer swamps. These areas are mixed
environments due to gravity-based drainage over land. Medium to high recharge places are
areas with beech-sugar maple-hemlock forests reflecting the Carolinian and Canadian biotic
communities. The Carolinian biotic province is more likely to have beech-sugar maple forests
whereas the Canadian biotic province is more likely to have hemlock-white pine forests, white
and red pine-mixed hardwood forests, and a combination of beech-sugar maple-hemlock
forests. The level of recharge provides information about where past wetlands could have been
present given a sufficient input of moisture from streams and rivers and precipitation.
In the eighth step, the land cover is modified by reclassifying baseline resource
communities with data derived from palynological studies. The pollen that is present from
existing cores data tables to the periods of interests is used to modify baseline biotic
communities that were present at the given time period by expanding or contracting resource
communities. Palynological records indicate the presence or absence of species and, to some
114

extent, plant abundance; they can be misleading and they do not describe the spatial
distribution of vegetation surrounding an area. Overall, a large variation in pollen communities
can be indicative of systematic changes in climate.

115

Results

Figure 9. LA Composite wetlands by time period (in blue color)
LA wetlands are extensive along all major river systems in both interior uplands and lowland areas, and adjacent to Saginaw Bay. EW
wetlands(large scale) are limited constrained to the core embayment. MW wetlanads are extensive, but limited to the Saginaw
Valley and core embayment. Note: see appendix A for EW and MW wetlands
116

Figure 10. LA land cover and legend
Wetlands are present throughout the region during the Late Archaic.
117

Figure 11. EW land cover and legend
Established wetlands are present throughout the Saginaw core. Note: see Figure 10 legend.
118

Figure 12. MW land cover and legend
Wetlands are constrained to core base levels. Note: see Figure 10 legend.
119

Figure 13. Saginaw (top) and Lapeer counties (bottom) composite landscapes
The distribution of ephemeral wetlands is highest during the LA located at confluence of river systems. The EW period, these
wetlands stabilize and form cyclical emergent wetlands and shrub swamps. The MW land cover is a mixture of both transitional
wetlands and stable emergent and shrub swamps. Note: see Figure 10 for legend. LA (left), EW (middle), MW (right)

120

Figure 14. Midland (top) and Tuscola counties (bottom) composite landscapes
Midland County has heterogeneous wetlands that change in size over time. Tuscola coastal areas are wetland dominated with inland
Beech-Maple forests. The Cass River flowing through Tuscola is bounded by river influenced by wetlands and bounded forests. Note:
see Figure 10 for legend. LA (left), EW (middle), MW (right)
121

Figure 15. Genesee County (top) and Tobico Marsh area (bottom) composite landscape
Genesee County to southeast is observed to have a number of wetland dominated areas along river courses and along paleo-river
meanders. Tobico Marsh area is highly wetland influenced. Note: see Figure 10 for legend. LA (left), EW (middle), MW (right)
122

Table 4. Results summary
Characteristics
Late Archaic
Early Woodland
Middle Woodland
Heterogeneity
High
Low
Medium
(regional)
Heterogeneity (local) Low
Medium
High
Palustrine
Very High
Low
High
Terrestrial
Low
High
Medium
Regional level heterogeneity (spatial clustering of resource habitats) amongst the three periods
is highest during the LA and MW periods. The local (within multiple square miles) heterogeneity
is highest during the MW and EW periods. Wetland land cover is largest during the LA, followed
by MW period. The converse is true for terrestrial land cover. Higher spatial heterogeneity
means that overall criteria estimated for the entire landscape may not adequately describe the
landscape at any given location.
Table 5. Cover type change by cultural period by square mile
COVERTYPE
Late
%
Early
%
Archaic
Woodland
EPHERMERAL
2080.1 14%
0
0%
WETLANDS
SHRUB
83.6 1%
212.9
1%
SWAMP/EMERGENT
MARSH
MIXED CONIFER
1095.8 7%
1429.8
9%
SWAMP
MIXED HARDWOOD
657.4 4%
903.7
6%
SWAMP
RIVER
804.9 5%
203.5
1%
WET PRAIRIE
105.5 1%
180.6
1%
BLACK ASH SWAMP
174.9 1%
265.2
2%
CEDAR SWAMP
314.9 2%
410.1
3%
MUSKEG/BOG
8.6 0%
20
0%
Total Wetlands
5325.6 35%
3625.9
24%
BEECH-SUGAR
1843 12%
2028.2
13%
MAPLE FOREST
BEECH-SUGAR
3003.1 20%
3583
24%
MAPLE-HEMLOCK
Total Beech Forests
4846.1 32%
5611.1
37%
HEMLOCK-WHITE
1487.4 10%
1771.3
12%
PINE FOREST

123

Middle
%
Woodland
807.7
5%
105.5

1%

1257.8

8%

764.2

5%

931.6
121.7
227
349.1
15.9
4580.5
1908

6%
1%
2%
2%
0%
30%
13%

3325.1

22%

5233.1
1642.4

35%
11%

Table 5. (cont’d)
COVERTYPE
JACK PINE-RED PINE
FOREST
WHITE PINE-MIXED
HARDWOOD
WHITE PINE-RED
PINE
WHITE PINE-WHITE
OAK
MIXED PINE-OAK
Total Pine Forests
OAK-HICKORY
MIXED OAK
MIXED OAK
SAVANNA
Total Oak Forests
SPRUCE-FIR-CEDAR
ASPEN-BIRCH
Total Alternate
Forests
BLACK OAK BARREN
OAK/PINE BARRENS
PINE BARRENS
EXPOSED BEDROCK
SAND DUNE
GRASSLAND
Total Misc

Late
%
Archaic
578.8 4%

Early
%
Woodland
633.9
4%

Middle
%
Woodland
594.2
4%

718.5 5%

839.5

6%

756.6

5%

411.1 3%

492.9

3%

442.2

3%

109.8 1%

126.9

1%

115.2

1%

28.4
4819
614.3
167.9
169.3

0%
32%
4%
1%
1%

30
5289.6
730.9
201.8
202.6

0%
35%
5%
1%
1%

28.6
3579.1
655.5
179.1
177.9

0%
24%
4%
1%
1%

951.4
0.7
89.9
90.6

6%
0%
1%
1%

1135.3
1
103.1
104.1

8%
0%
1%
1%

1012.4
0.7
96.2
96.9

7%
0%
1%
1%

422.7 3%
526
3%
454.6
3%
43.2 0%
46.5
0%
44.8
0%
117.3 1%
135.3
1%
126.1
1%
0 0%
0
0%
0
0%
0 0%
0.8
0%
0
0%
1.4 0%
1.5
0%
1.5
0%
584.7 4%
710.1
5%
627
4%
15132.4
15081.1
15129.1
Across the LA, EW, and MW cultural periods, substantial changes in the overall mix of land
cover types occurs. During the LA period, an increased number of wetlands are present, both in
terms of emergent and transitional wetlands. Beech-Maple forests are the dominant feature on
the landscape in all study periods, with considerable decrease in both LA and MW. The drier EW
period, LA wetlands are changed into forested swamps and Beech-Maple forests. The MW also
exhibits a similar pattern of LA wetlands, but at lower levels focused on the core basin areas.

124

Tittabawassee to Saginaw River Profile
230

AMSL

220
210
200
190
180
0

50,000

100,000

Figure 16. Tittabawasee to Saginaw river course profiles

Cass to Saginaw River
230

AMSL

220
210
200
190
180
0

20,000 40,000 60,000 80,000 100,000 120,000

Figure 17. Cass to Saginaw river course profile
The river elevation profile shows probable areas where river courses and base levels influence
the landscape. All large river systems with base levels (flat areas) are likely areas where water is
retained forming ephemeral wetlands. Note: see appendix A for other river profiles.

125

Discussion
The reconstructed landscapes employed here have been derived and constructed from
contemporary and historical proxies that place primacy on the change in wetlands over time.
Other alternative models based strictly on ecological succession or complex hydrology may
yield different results; this model provides a regional and local perspective on palustrine
spatiotemporal variability and the effects on terrestrial landscapes. The resulting wetland
distributions have considerable implications for habitats, resource structure and human choices
for diet and land use (see Chapter 4).
Overall, the study presents a refinement to our understanding of changing prehistoric
landscapes. A number of interpretations are made; all addressing spatiotemporal wetland
distribution and densities. The model posits a predictive hydrological of three cultural periods in
the SBD of Michigan. Wetlands, as previously stated are assumed to be a key driver of resource
landscapes. These assumptions are well founded and based both on material inventories from
sites and geoarchaeological studies. The model presented predicts the probable densities and
distributions and possible implications of these wetlands and wetland influenced landscapes.
The distribution and densities of wetlands are used for the understanding of spatial and
temporal resource variability of the study area. Further, wetlands also provide the basis for
analysis and prediction of terrestrial habitat density and distributions and the resources found
therein. These models, with their palustrine and terrestrial landscapes changes, and long and
short term land cover change have considerable implications for regional distribution and
densities of cultural use of these areas.

126

First, the regional study area has considerable likelihood for varied wetland types over
the three study periods. The model presented here suggests that the LA has wetlands that
extend further upstream and play a role in the resource structure of the regional area. Two key
types of wetlands are identified, transitional or ephemeral wetlands, and stable wetlands that
includes emergent marshes, shrub and hardwood swamps. Both wetland types are driven by
increased moisture input driven both from increases in lake levels and fluvial input changes
through climatic activity. The resulting coastal wetlands are larger and more homogeneous
during the LA and MW periods. The large size of these wetlands likely made them unappealing
and inaccessible for daily resource exploitation due to lack of direct access and increased
resource variability (i.e., unpredictable) . The transitional wetlands, on the other hand, are likely
areas of high productivity with secondary succession taking place over time, repeatedly,
dependent upon varying moisture inputs along the Core embayment and confluences of major
river systems. Further, these transitional wetlands are also present upstream in a number of
major river systems during the LA and to a lesser extent during the MW periods.
Second, terrestrial stability during the study periods varies with key locales playing an
important role over time. The LA terrestrial habitat is least dependable, during the LA with
considerable regional change over time. The greatest terrestrial stability likely takes places
during the EW period which experiences the least amount of wetland activation. Finally, MW
terrestrial stability in the Core embayment area is likely to be poor with considerable flooded
and reactivated wetland environments, while upstream locales are more stable. Ecological
studies show that changes in landscapes, from xeric to mesic to hydric environments and back
results in short and long term changes in productivity with the introduction of new plant cover

127

and associated animals. These environments provide a boom and bust environment, potentially
serving as a resource pull for foragers. Initially, the variable nature of these initially can be
uncertain and risky; over time, however, landscape and resource stabilization of these areas
results in highly productive areas for exploitation.
Third, there is considerable change in the overall pattern of land cover and related
resource communities from the LA to the EW periods. Much of this variation is spatially focused
on the core Saginaw Valley basin with increasing stability in upland areas over time. Both the
palustrine and terrestrial environments are observed to change over time. The LA is a time
period with considerable change both along the Saginaw Valley corridor and in upland areas
with a diversity of wetland-influenced terrestrial areas. This can be attributed to the
topography of the river valleys with numerous areas where water could be possibly trapped
(e.g., beaver activity, soil accumulation or down cutting due to downstream flow). This
situation is more complex as a result of seasonal retention of moisture in the form of flooding
and pooling in numerous base levels. The MW period is characterized by localized change along
the Core Saginaw and Shiawassee river subsystems.
Finally, the seasonal processes in all three study periods may cause regional problems
(i.e., climate driven habitat succession) for the resource productivity. LA and EW landscape
change is substantial given region-wide transformation from warmer and wetter to a drier and
colder climate. The EW period, large-scale losses of wetland environments of all types are likely.
We also see the transformation of stable emergent and shrub wetlands to hardwood and
conifer swamps in interior areas, and the development of stable forested areas in amenable
soils and recharge zones. The transition from EW to the MW is more moderate with most of the

128

wetland effects localized to the core embayment to Saginaw Bay and coastal areas. The coastal
areas are substantially affected with inundated landscapes in both the LA and MW periods.
These areas remain rather unattractive (due to complete inundation of large areas), resulting in
seasonal wetlands during the EW period due to low topography, poor soils, and groundwater
recharge (see Figure 6). The overall regional and local environment is significantly affected by
the wetland change.
Revisiting the Initial Research Questions
What challenges do wetland environments pose for foraging adaptation (landscapes and diet
choices)?
The resource landscape poses a number of challenges; seasonal and long term and local
and regional variation. Two key factors are the wetlands distribution and density over time and
the effect of seasonality on habitats and food items. The distribution and density of the
terrestrial and palustrine landscapes vary over time with implications for resource
communities. Regardless of the study period, the seasonality of the landscape likely poses
problems to the resource distribution and densities. Emergent wet environments and
successional drier environments change resource densities and community composition. The
extent of flooded and pooling due to lake level and fluvial dynamics makes large areas of
Saginaw and Bay Counties unappealing. At the same time, the late spring drainage of these
wetlands creates diverse niches through the succession of shrub and grass growth resulting in
environments that are highly productive in terms of both plant and animal resources.

129

What is the makeup of the regional and local environments understood through wetland
distribution and densities?
Regionally, hydrology plays an important role in the core basin; Saginaw Valley and the
Shiawassee embayment are heavily influenced, with a lesser influence on upland areas. A
number of areas remain stable over time, as either dry or wet areas. Other areas, especially low
lying base levels adjacent to major river systems go through short-term seasonal changes and
long-term transformation to stable habitats between time periods. For example, a number of
large spatial and temporal changes are observed in palustrine landscape. Wetland areas change
over time from permanent to semi-permanent hydric areas of varied habitats and differential
resource densities. Next, a number of the terrestrial landscapes remain dry, resulting from
elevated topography likely providing important areas to access for respite from late winter and
early spring wet environments. The LA is a period with a considerable number of resource
habitats; wetland areas are present both in the core basin and all long large river systems. EW
period, wetlands contract significantly; earlier transitory wetlands become stable hardwood
and conifer swamps. MW changes are localized to the core basin; both embayments and river
valleys are influenced by the rise in water levels and the reactivation of extant wetlands and
habitats.
What are the long-term changes and implications of wetland environments throughout the
study periods?
The LA to EW period predictive land cover shows a considerable change at both the local
and regional scales. EW to MW change is less but significantly affects the amount of wetland
areas close to the Shiawassee embayment and coastal areas. The key factor is the stability of

130

these environments. LA and MW periods have increased unpredictability and lower reliability,
but with a greater abundance of wetland derived resources. The high water level introduces a
number of species unavailable to them during the MW. For example, Lake Sturgeon and other
productive fishes move further upstream toward the confluence of the Tittabawassee, Saginaw
and Cass rivers (Lovis, et al. 2001).
What are the resource communities or habitats present in these wetland environments?
The key wetland environment likely goes through seasonal and successional changes
over time. A number of wetland types are present including transitory wetlands as well as
mature wetlands. Transitory or ephemeral wetlands are inundated for period of time, and then
stabilize through plant succession. After the initial draw down of LA high water levels, emergent
marshes and swamps are present. The continued drainage of waters causes wetlands in higherelevation base levels to be transformed into hardwood and conifer swamps given the amount
of soil recharge present. Base levels are likely to be stable for longer periods of time with
annual cyclical activated wetlands creating a unique ecological environment. Stable, long-term
wetlands, such as the one along the Shiawassee embayment, were likely unique locales for
plants and animals. Since much of the effects of high water levels are localized to key areas,
including coastal and low elevation inland areas, the inundation of the areas created a unique
palustrine composition. Areas with high recharge likely were emergent wetland environments,
whereas the areas with low recharge has conifer and hardwood swamps. Regionally, the LA is
observed to be different with considerable inland variation along low-lying areas buffered by
moraines and remnant beach ridges.

131

What are the seasonal or short-term changes in wetland environments (density and
distribution) and implications for habitats and resource structure?
The seasonal change may be the most important factor of habitat and resource
preference and choice. Seasonal wetlands varied in all periods and have considerable
implications for the Early and MW periods along with lower wetland density and distribution.
Seasonal wetlands are unique areas with productive secondary succession. Secondary
succession requires the removal of existing organic matter through a predictable cyclical
process. Areas that are cyclically inundated will lose existing plants. These types of wetlands are
typically activated seasonally such that there is standing water at one or multiple times during a
year. Standing or moving water does not allow tree growth, but encourages herbaceous and
grass development. This type of succession likely took place on a regular interval, regionally
during the LA period and locally (core Saginaw Valley) during the MW period. These are highly
productive habitats for varied set of animals including reptiles, birds, and small mammals.
Conclusion
The predictive wetland derived landscape model presented here provides a refinement
of the existing understanding of the prehistoric land cover of the Saginaw Bay Drainage of
Michigan. Wetlands play a critical role in landscapes and habitats in this study area. Further,
changes in wetland distribution and density between the cultural periods is considerable and
also influences hunter gather land use and diet choices. Next, local and regional variability is a
driving force in all study periods. LA landscapes are diverse with extensive wetlands. These
areas are likely to be highly productive but with greater risks and uncertainties given the
predictability of these areas. EW landscapes are the most stable but with net productivity
132

higher in key areas including the Saginaw core along large river confluences. Regionally, we
observe a decrease over the LA in highly productive habitats. MW landscapes are variable along
the Saginaw Core with stable areas further upstream. In all three periods, key locales are
considered to be important due to their relatively stability and proximity to productive
environments and can be considered as places of cultural importance. Taken together, the
landscape models provide contexts for uncertainty and risk in the landscape and resource
environment. The modeled prehistoric landscapes can be now employed to evaluate behavioral
and archaeological expectation of hunter gatherer land use and diet choice.

133

Chapter 6: Simulation
Introduction
This chapter executes two linked simulations to assess the effects of uncertainty and risk
on land use and diet choices. Simulations employed here are heuristic exercises that provide
alternative ways of understanding the hunter-gatherer (HG) economy through the probabilistic
study of decision-making practices. Past analyses of economic decision-making focused on
concerns that are proximate to the individual, aimed to fulfill short-term requirements
including nutrients, efficiency, taste, and fat (Egan 1993; Keene 1981b; Reynolds 1985). These
analyses are deterministic models, where outcomes only develop one way and result from
specific goals to increase efficiency or meet minimum biological requirements. They are
intended to assess the effect of key determinant factors on diet choices. The simulation
presented here explores the variability (spatiotemporal heterogeneity) in the key factors (diet
and patch breadth). Both, risk and uncertainty are implicit in archaeological settlement and
subsistence studies, often used in interpretive basis for cultural phenomena. No studies to date
have used these factors to explicitly assess their effect. This study provides an alternative
approach to understanding HG economic decision-making and addresses spatiotemporal
variability in the resource environment.
Decision-making, therefore, is determined by both expected and unexpected (random
or stochastic) variability in the resource environment. Specifically, the simulation developed is a
dynamic (time-dependent) model using stochastic (one or more variables characterized by a
distribution of individual values that are unpredictable) variation. Stochastic processes are

134

indeterminate, where a process may evolve in many different outcomes. These outcomes,
when taken together, reflect the potential range of diversity of economic practices given a set
of assumptions. Variance, both in terms of the natural environment and the foraging individual,
becomes a critical part of analysis (see Chapter 3 for review).
Uncertainties and risks can be the result of a number of factors that can be attributed to
the variability of the natural environment and the individual exploiting resources. Uncertainty
is conceptualized as stochastic (random) variation. Next, risk is conceptualized as choice
amongst know options, each with its own variability and rewards. Risk is proximate to the
individual and external to the environment (see Chapter 3). Risks, then are can be attributed to
information, skill and ability a HG holds. For example, men are ethnographically observed to
undertake greater risks in resource exploitation. In this way, men may prefer to exploit
resources that bring the highest amount of reward. Alternatively, women also engage in risky
endeavors but usually only when absolutely necessary. They are likely to hunt small mammals,
and pursue gathering and fishing activities. Both groups hold overlapping, but different types of
information about the natural world (see Chapter 3 for overview) (Kelly 1995a).
Given these uncertainties and risks, a HG’s goal is to efficiently and effectively gather
resources from a variable resource environment. To mitigate the uncertainty and smooth out
variance, HGs employ strategies that will mediate both expected and unexpected variation. For
example, choosing the best productive patch at a given month is one way to reduce
uncertainty. Thus, exploiting a specific patch or resource is determined by considering various

135

factors (e.g., probability for success, gender preference, net caloric yield, and HG skills), all
intended to reduce uncertainty and risks.
This simulation contextualizes the roles of landscape, resources, and HG uncertainty and
risk within the principles of Optimal Foraging Theories (hereafter OFT). Choices about resources
and resource patches are based on a diet and a patch-breadth OFT approach modified by
uncertainty and risk factors. Both diet and patch breadth models select from alternative sets of
resources that are rank ordered for best returns. OFT models do not take into account
variability in the natural environment and its effect on the patch or the individual. Unlike other
OFT models, the simulation executed here incorporates this variability as underlying principles
of OFT patch and diet-breadth decisions.
Approach
Land use and diet choice simulation is written in Visual Basic programming language
using the Microsoft Visual Basic for Applications environment. Microsoft Excel and Access
tables are used to store, retrieve, and modify variables. Three data sources are used for the
simulation. First, patch density and distribution data is the derived from the predictive
hydrological models developed in Chapter 5. This land cover data serves as the basis for patch
types that are present in a given time period. Second, animal biogeography is based on
contemporary animal behavior studies. Plant resource characteristics (i.e., caloric content, size,
weight) are derived from the United States Department of Agriculture, Agricultural Research
Service, National Agriculture Library, National Nutrient Database for Standard Reference,
Release 25 (USDA 2012). Plant behavior is derived from United States Department of
Agriculture Plants Database (NRCS 2011). Native use of resources is identified through

136

ethnohistoric and ethnographic studies amongst Ojibwa and Ottawa communities of Michigan
and Wisconsin (EthnobotanyDB 2011) and ethnographic analogs of varied hunter-gatherer
groups.
The choices amongst competing patches and resources are based on the net yield of
calories, based upon the productivity of patches derived from the biogeographic characteristics
of plants and animals. Uncertainty and risks are conceptualized as the relative probabilities of
events occurring along a continuum between zero and one hundred. The probabilities are
randomly selected, emulating the established distribution. The choice of a resource in a patch is
determined by the relative probability of the presence of that resource at a given patch and at a
given time. The productivity of a patch is determined by the weighted cumulative probability of
each resource present in a patch multiplied by the cumulative probability of resource present in
a given month, multiplied by the caloric yield of that resource. This use of probability
operationalizes the realities of stochastic events. For example, the stochasticity present in the
resource environment can require that HGs exploit a greater number of resources, even low
ranked ones, due to the uncertainty of higher-ranked alternatives.

137

Simulation
Overview

Star
t

Weight * Calorie *
Density/Yield
Resource
matrix

Rank patch
Sim Run
Select
patch
Select
cultur
Season

Family
member

Rank Food (top
10)

Cumulative
Probabilities

Uncertainty
Factor

Degrade patch

Select
food
Female Pref.

Day in year

Male Pref.
Child Pref.

Meet
requirements

Band unit
Select
Gende

Figure 18. Simulation data model

138

Output

End

Patch Data Model

Resource matrix
Mammals…
Small mammals…
Fish…
Birds…
Reptiles…
Seeds…
Fruits…
Grains…

Patch Matrix
Beech forests..
Beech Hemlock..
Swamps..
Emrg. Wetlands..
Oak forests..
Pine forests..
Grasslands..
Barrens..

Month & Season

Patch type

Patch rank (select
top 5)

Select
patch

Resource
@month

Resource
@patch

Patch productivity:
sum of all resource
@patch @month
Gather resource

Spatio-temporal matrix of resources

Figure 19. Patch selection data model
The choice of a patch is dependent on the most productive set of resources at a patch in a season. Seasonality and the effect of
distribution and density are determined on a monthly basis.

139

Patch Choice (Habitat Selection)
A foraging band is purposeful about its actions and is knowledgeable regarding the risks
in the resource environment. The band will move to a new area using their past knowledge of
that area; from their firsthand knowledge through visiting the area during logistical forays, or
gained through information exchange with others in the area. A typical foraging area is
assumed to be three-mile radius of a given patch. The selection of a patch is independent of
actual forager presence or exploitative success in the patch(Kelly 1995a). The selection and use
of a patch (1 sq. mile) are determined by numerous factors including relative productivity and
prior use of the same patch, or patch degradation.
First, productivity is dependent on the season and the collection of those resources
available in that season (see Figure 19). The potential presence of a resource in a patch is
determined by four continuous classification categories: very low (0 and .1), low (0 and .3),
medium (.3 and .6), and high (.3 and 1). For example: a patch with mallard ducks and cattails
would be calculated as the sum of caloric yield of both species in a given month or season.
Then, the selection of a patch is determined by adding the probabilities of two events,
providing the relative rank of all resources–patch, resource-month combinations.
Patch productivity = sum of the net yield of resources at a patch *
Sum of the net yield of resources in a month
Second, a patch quality is degraded when prior use of the same patch, resulting in a 20 percent
(see Chapter 4 for assumption rationale) decrease in the net caloric yield. Patch degradation is a
feedback process in OFT where a consumed patch is degraded by exploitation within an annual

140

round. This feedback affects the outcome of future choices, making patches assumed to be
productive unappealing to groups (knowledge regarding a patch is assumed to be transmitted
between groups). A given patch is assumed to regenerate after an annual cycle. Last, a HG
selects among the top three patches (number is based on ease of programming to randomly
select amongst top three choices) based on productivity, using a weighted cumulative
probability distribution resulting in the random selection of a patch based on its relative
proportions.
Diet Choice (Resource Selection)
Diet choice is a selection of resources from a given patch at a given month, based on the
random weighted, cumulative probability of the total resources present (see Figure 2 and
Figure 3). The net yield of gathered resources is limited to what an individual collects in a twohour time period (number based on ease of programming). For example, the amount nuts
gathered would be based on a probability function that returns a value that varies between
probable highs and lows. This approach has the effect of equating the exploitation of varied
resource types (i.e., deer versus cattails).
Net yield of a resource (2 hours) = Caloric yield of a resource *
Ease of exploitation * Gender preference
Ease of exploitation = Predictability * Abundance
Caloric yield of a resource = weight * density * calories.

141

A number of key factors determine resource selection, including the age/gender class of
an individual. For example, highly mobile and non-aggregative species are harder to exploit.
First, the HG gender role is represented along a probability continuum that ranks preference
toward species based on the likelihood of actual exploitation. For example: men may prefer to
exploit higher-yield larger mammals that are risky and dangerous (i.e., costly signaling),
whereas women and children may exploit small mammals and plants foods. Children,
specifically, will exploit resources similar to women but at lower success and productivity rates.
Therefore, the net amount of caloric expenditure exploited for the same resources is lower.
Second, a HG in a band unit is limited to four attempts at gathering resources in a given day.
This requirement is based on the relative amount of time devoted to actual exploitation
activities. Third, the probability of failure is a random variable based on the intrinsic uncertainty
in the environment. HG who attempts to exploit white-tailed deer may fail based on random
stochasticity.
Table 6. Probability classifications for resource types
Category Type
Low
Medium
Medium High
High
Large Mammals
0 to .1
.1 to .5
.5 to .9
.9 to 1
Small Mammals
0 to .1
.1 to .9
N/A
.9 to 1
Birds
0 to .1
.1 to .9
N/A
.9 to 1
Fish
0 to .1
.1 to .9
N/A
.9 to 1
Reptiles
0 to .1
N/A
N/A
.1 to 1
Mollusks
0 to .1
.1 to .9
N/A
.9 to 1
Grass Herb
0 to .1
N/A
N/A
.1 to 1
Nuts
0 to .1
.1 to .5
.5 to .9
.9 to 1
Seed Grain
0 to .1
.1 to .5
.5 to .9
.9 to 1
Seed Fruit
0 to .1
.1 to .5
.5 to .9
.9 to 1
Tree Fruit
0 to .5
N/A
N/A
.5 to 1
Note. Table 6 probability classifications vary due to the ease or difficulty of capture. For
example, a tree fruit is either present or absent, whereas, small mammals are mobile and
opportunistic. Smaller mammals, therefore, require different probability classification based on
seasonality, and habitat, when they are exploited.
142

Resource Selection Data Model

Calories per pound

Base Yield

X

X

Density

X

Resource @month
probability

Avg. Weight

Resource
@patch
probability

X

Resource@patch Yield

X

Select
Food

Base Yield at Capture

Selected resource

Figure 20. Resource selection logic model

143

Gender Preference
Probability

X

Capture
Probability

Cumulative Resource
Probability

Simulation Results
Simulations provide a series of alternative understandings of HG choices of patches and
food items selected in an annual round. Results are divided into two categories, land use and
diet selection:
Resource Effort

MESIC SOUTHERN
FORESTS: BEECH-SUGAR
MAPLE FOREST
SHRUB
SWAMP/EMERGENT
MARSH
RIVER
MIXED CONIFER SWAMP
MESIC NORTHERN
FORESTS: BEECH-SUGAR
MAPLE-HEMLOCK
MESIC NORTHERN
FORESTS: HEMLOCKWHITE PINE FOREST
WHITE PINE-RED PINE
SPRUCE-FIR-CEDAR
WHITE PINE-WHITE OAK

Figure 21. Resource choice effort in a patch
HGs use a number of key patches over the annual cycle. Riverine environments are the most
productive during the summer. Mesic southern and northern forests are productive during the
winter season. Mixed conifer swamps are highly variable, with boom and bust productivity.
Other wetlands are highly productive during the early winter and continue to be moderately
productive throughout the year.

144

Annual Exploitative Events

Grass_Herb
Large Mammals
Birds
Fish
Nuts
Small mammal
Seeds_Grains
Herb/Medicine
Seed_Fruit

Figure 22. Annual exploitative events (combined male and female)
The cumulative attempted (not all are successful) exploitative events is due to efforts of five
different family units with varied gender compositions. Given the net attempts, two classes of
foods dominate; Grass_Herb (plants that are diet foods) and Large Mammals (deer, elk,
moose). Birds and fish are the third and fourth ranked items exploited, respectively. This
simulation suggests that HGs mitigate risk and uncertainty by exploiting resources that are
both, abundant at a given time and place and can provide efficient yield relative to attempts to
procure them. The varied monthly attempts highlight the importance of plant foods during the
summer and alternatively large mammals and birds at other times of the year.

145

Diet Choice Events (Male)

Large Mammals
Grass_Herb

Birds
Fish
Small mammal
Herb/Medicine

Nuts
Seeds_Grains
Mollusc
Reptile

Seed_Fruit
Tree_Fruit

Figure 23. Diet choice events by gender (male)
Exploitative events based on gender highlights the cultural preferences for exploitative radius
and risk aversion. Men exploit large mammals and highly productive plant foods. Birds and fish
rank secondary and are important as well.

146

Diet Choice Events (Female)

Grass_Herb
Birds

Large Mammals
Fish
Nuts
Seeds_Grains

Small mammal
Herb/Medicine
Seed_Fruit
Mollusc

Reptile
Tree_Fruit

Figure 24. Diet choice events by gender (female)
Exploitative events based on gender highlights the cultural preferences for exploitative radius
and risk aversion. Women make choices to exploit plant foods and birds and, to a lesser extent,
small mammals. Interestingly, women would also be driven to exploit large mammals given
alternative are not available.

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Actual Calorie Yield (Female)

Large Mammals
Grass_Herb
Birds
Nuts
Seeds_Grains
Fish
Small mammal
Herb/Medicine
Seed_Fruit
Mollusc
Reptile

Figure 25. Actual caloric yield (female)
The actual yield is determined by both the relative uncertainties attribute to species behavior
and patches exploited results in a modified set of caloric yields.

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Actual Calorie Yield (Male)

Large Mammals
Grass_Herb
Fish
Birds
Small mammal
Herb/Medicine
Nuts
Seeds_Grains
Mollusc
Reptile
Seed_Fruit
Tree_Fruit

Figure 26. Actual caloric yield (and probability of success (with 10% uncertainty factor)
The actual yield is determined by both the relative uncertainties attribute to species behavior
and patches exploited results in a modified set of caloric yields. The dominant exploited
resources are large mammals, followed by a suite of other resources including fish, birds, and
small mammals at different parts of the year. The net yield of large mammals considerable
outweighs all other resource groups.

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Discussion
The simulation outcomes present an alternative perspective of HG land use and diet
choices. The outcomes of the models demonstrate that the role of uncertainty and risk is
considerable, and critical to the decision-making process. Further, spatiotemporal variability
likely plays an important role in uncertainty and risk and also linked economic and cultural
practices. However, heuristic endeavors must be carefully interpreted. These outcomes are
often the result of assumptions made initially in the model and may mask complex processes.
Regardless of issues posed by model assumptions, the simulation outcomes highlight
some key social and ecological factors that influence land use and diet selection. The social
factors that plays a key role is gendered risk preferences and division of labor. The variable risk
preference of male and female is observed to play a complementary role in their overall
success, given their net yield curves (see Figure 20). The male preference for high risk and high
yield resources likely results in considerable variation in actual success given differential
uncertainty factors, but the overall yields justify their exploitative strategy.
The simulation shows that given considerably larger uncertainty factors (actual was .10
percent) brings all other resources in more equal standing with large mammals. But, the shape
of the yield curve is relatively linear throughout the year (see Figure 20). Overall, men should
focus and alternate among large mammals regardless of the time of year. They should alternate
between resource types when their success is limited (high uncertainty) especially during the
summer when the net returns of alternate resource could possibly compete with large
mammals. In actuality, their goal throughout the year should change little. The relative success

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of exploiting these highly mobile and seasonally variable resources can be increased by group
strategies (coordinated hunting), specialized hunters (highly skilled males), and significant
interactions and communication amongst hunters, their families and affiliated groups.
The interesting outcome is that women should also prefer high yield large mammals,
especially given their net caloric yields. An increase in uncertainty factor has very differential
effect on their preferences (see Figure 20). Women yield curve is convex. They are likely to
prefer very different resource at different times of the year. With increasing uncertainty,
women will rank a whole suite of alternative resources rather than large mammals. Alternative
resource, especially plants become more reliable and complementary as well. The social role of
risk preference, in turn division of labor plays an important role in land use and diet decision
making.
The ecological factors include that plays an important role include, both the varied
influences of spatial orientation of landscape features and seasonal availability of key
resources. Key patches on the landscape are variably productive based on a given season and
cultural period. Abundance and dearth of resources in these patches also play an important role
in decision-making
The patches selected throughout multiple simulation runs suggest that the effective way
to address variability in the resource environment is to focus on key patches (given that they
are accessible), including Mesic southern and northern forests, river settings, and intermittent
wetlands to a lesser extent. Mesic southern forests are the best productive environment, with a
balance of moisture, warmth, and resource potential. The river networks, both large and

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medium, further provide productive habitats throughout the annual cycle. The forested uplands
along river system headwaters have low variability and display a greater stability of resources.
The core wetlands provide a highly contrasting view, with significant variability during the
winter, and early spring, seasons. The core wetlands become a resource draw for large
mammals from adjacent mesic southern and northern forests. Further, river networks serve as
routes to access these highly productive palustrine environments throughout the year.
When diet choices are made to mitigate risk and uncertainty in the environment, a
singular focus is observed on specific resources including large mammals and plant foods that
are likely abundant in specific habitats. The diversity of choices available for late summer and
fall collection of seeds and nuts provides significant storage potential for high fat foods for the
winter. During winter, there is a greater reliance on tree products (i.e., mast) both in terms of
winter-use foods and the dual-purpose use of herbs and medicines, since most plants that
produce nuts also have multiple uses. For example, winter exploitation of stalk fats and starch
is an important as they are a reliable resource. Choices of cultigens as a possible basis for
exploitation may have been opportunistic and concordant with productive habitats for both
plant and animal products. Fish is an aberration in this simulation with low yields, especially
with probable productive riverine settings. This is a result of alternative higher yield choices in
the habitat.
The simulation demonstrates the resource pull of heterogeneous environments
regardless of uncertainty in the resource landscape. Changes between cultural periods could be
interpreted as a similar adaptive strategy over time, exploiting mesic southern forests with
concomitant reliance on riverine and wetland environments. The resulting patches and

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resources are resilient to the level of uncertainty present. Increasing the net uncertainty in the
environment does not change the relative patch and resource importance; uncertainty affects
all resources; with key resources being more resilient to change (plants and nuts). Two
dimension of the resource structure plays a considerable role in resources selected; the higher
yield resources and breadth of plant food items.
The simulation contributes to a better understanding of both methodology and human
behavior. Methodologically, the incorporation of stochasticity expands the reality of a model
resulting in a different logical framework for decision-making. This may also better reflect the
variability between models and actuality. Further, stochasticity basis for decision-making can be
conceptualized as boundaries of human behaviors as baseline requirement, wherein all other
alternative decision-making rationale operate.
Conclusions
The two linked simulations provide valuable insights into the social and ecological role
that variability plays in economic decision-making. Patches preferred in the simulations are
mesic southern and northern forests, rivers, and wetland communities. These habitats play a
key role in mitigating variability since they are the most stable environments given seasonality
and net productivity in the study periods. Given these key habitats, the favored resources are
large mammals (i.e., elk, white-tailed deer) and wetland oriented successional plants. Finally,
this study allows for the possibility to better understand the role of uncertainty and risk in
decision-making. Uncertainty- and risk-based rationales can be conceptualized as boundary
conditions for economic decision-making. The two effective strategies identified by this study

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are high-yield but low-density resources (large mammals) and low-yield but high-density plant
resources (fruits, seeds, nuts). Other alternative decision-making factor (i.e., nutrients, taste,
and fat) becomes choices that are made within this bounded rational cognitive space. In turn,
this suggests that decision-making approaches can be ordered hierarchically and included
within, with risk and uncertainty ranking above and encompassing other proximate factors.

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Chapter 7: Archaeology
Introduction
Archaeological studies provide insights into both the underpinnings and mechanisms of
cultural adaptation. Studies that include spatial patterns (e.g., land cover distribution and
settlement classes) and material culture (zooarchaeology and archaeobotany); once linked with
established theoretical underpinnings (i.e., uncertainty and risk) provides the better
understanding of changes in both culture and human behavior. This chapter explores cultural
and specifically economic adaptation through archaeological data analysis. The analysis is
undertaken by land use and diet selection. First, a spatiotemporal analysis of sites and their
relationship with prehistoric landscapes explains the land use patterns. Land use is evaluated
through archaeological site locales as it relates to past habitats and landscapes; diet selection
through archaeobotanical and zooarchaeological analysis.
Land use studies frequently explore causal relationships using the space and time as
human-environment interaction variables by exploring complex questions regarding location,
association, and spatio-historical contexts within which human groups; settlements, biophysical
resources, and infrastructure influence each other over time. These geospatial approaches offer
empirical information as well as analytical power (e.g., territories, resource extraction zones,
travel corridors etc.). Land use choices can be understood by the use of spatial variables that
can be analyzed in relation to concentric or nested zones (buffers) of varying widths from a
feature of interest (e.g., sites, rivers, wetlands, soil and elevation classes). Further, the use of
geospatial analysis provides us role that these features may play in archaeological phenomena.

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The biophysical variables analyzed are derived from primary and contemporary
geospatial layers with the use of GIS tools (see Chapter 5). Conversely, cultural variables
including sites types (e.g., cemetery/burials, village and camp settings) can be compared to
biophysical landscape features. Second, a zooarchaeological and archaeobotanical analysis
provides the local level understanding of diet choices. Further, these analyses explore plant and
animal diversity present at sites. Quantitative statistical approaches can be used to evaluate the
significance and reliability of the faunal and floral variables. In summary, this chapter evaluates
the archaeological remains of human behavior from the Late Archaic (LA), Early Woodland (EW)
and Middle Woodland (MW) cultural periods with intent of better understanding hunter
gatherer land use and diet choices. In preparation for the analysis of land use and diet choices,
a background of archaeology of the study area is presented.
Archaeology of the Saginaw Bay Drainage
The Saginaw Bay Drainage (SBD) is a region with a large number of archaeological sites;
many with substantial material inventories. The archaeological record here is both the
combination of the regional and local patterning of sites and material culture present therein.
First, hunter-gatherer (HG) land use activities are often ephemeral with very little impact on the
natural environment. At a regional scale, monumental structures like mounds are often the
only visible remnants of cultural occupation in an area. These structures have linked with ways
people view the environment (Berkes 1986; Bishop 1986; Preston 1986). These complexes may
represent both lineal descent and corporate groups. Further, geoarchaeological studies of the
Saginaw Valley suggest considerable loss of sites located along riverine and wetland
environments due to erosion through fluvial processes and aeolian activity (Arbogast, et al.
156

2008; Lovis, et al. 1996). The regional pattern of sites provides an understanding of HG
subsistence and settlement behaviors meant to buffer social and environmental uncertainty.
Summarily, the land use analysis reiterates the importance of the emergent and cyclical
wetland communities and the surrounding fluvial networks.
The material record is also an incomplete account of real behavior and biased through
site formation processes, natural and cultural transformations and recovery strategies. As a
result, the record must be contextualized taking into consideration of processes of site
formation and preservation (Binford 1978b, 1981, 1982; Schiffer 1976). Standard taphonomy
(scavenging animals and natural processes -flooding, soil acidity) can also alter the record.
Human behavior also results in an incomplete record. For example, HG may return a high utility
part to a camp site when a kill is made away from the campsite (Binford 1978b; Binford and
Bertram 1977). The mode of material disposal will also vary with the function of the site and
anticipated length of occupation (Binford 1978b). Ritual activities also bias the archaeological
record; Mistassini Cree accord specific bones ritual importance by moving bones to special
cache racks (Rogers 1973). Finally, differential modes of recovery including flotation sampling
and strategies, screen sizes, differential excavation procedures also play an important role in
archaeological bias. For example, many small bones attributed to fish are rarely collected.
Typically, larger bones with high density have greater resistance to physical breakdown
(Binford and Bertram 1977; Read 1971; Vierra 1975). The expected contribution of animals can
be calculated as proportion of average live body weight or caloric yield. The larger the animal,
the larger the percentage of contribution to material inventories. Plant remains can be more

157

problematic with ambiguity from potential heat treatment for carbonization (in a nonoxidizing
atmosphere that it is not turned into ash) and also large, dense inedible discarded parts (e.g.,
nutshells, fruit pits, seeds) (Asch, et al. 1972; Munson, et al. 1971). Problems with taphonomy
force us to treat this model as a regional model. In developing expectations, we are seeking
general trends rather than very specific matches with archaeological record.
In the SBD, the differential preservation of organic matter, rate of deposition and
subsequent burial and effects of scavengers influence archaeological recovery. Groundwater
conditions, soil pH, and freeze-thaw conditions also modify the assemblage. Sites are typically
located on sand ridges with highly acidic soils; therefore the preservation is poor and requires
alternative investigative approaches. The faunal and floral remains are the best indicators of
economic activities and serves as evaluative basis for the models presented. The archaeological
record used in the study, both in terms of sites and faunal and floral material is assumed to be a
sample of human activities in the region. The cumulative archaeological record is used to
determine HG economic models.
Economic Models
The economic studies of the study periods provide a quick summary of existing land use
and diet models.
Sites during this LA are interpreted as seasonal occupations with differential seasonal
exploitative activities. Summers are broad spectrum exploitation with dispersed fishing,
aquatic mammals and wild plants harvesting. Late autumn and winters are periods of deer
hunting resulting in seasonal hunting and processing camps. (Fitting 1969; Halsey 1999; Lovis

158

2009; Robertson, et al. 1999; Taggart 1967). Broad spectrum foraging continues during the
winter season with exploitation of small and large mammals with use of stored foods (fruits,
deer, and dried fish) as alternatives. Intensive fishing is likely during the spring supplemented
with stored foods (Keene 1981b). Riverine sites are likely exploited for spawning species with
other aquatic reptiles and mammals are secondary resources. Passenger pigeon likely exploited
in lowland nesting areas (Peebles 1978). Other, higher valued birds are likely exploited during
migration periods along palustrine and lacustrine habitats. Next, this general model is refined to
provide a local interpretation of niche based exploitation aimed at entire range of habitats
(uplands, margins, lowlands) to address spatiotemporal variability. Further, this is aided by and
in response to travel and information gathering along radial river networks and varied habitat
locales (Lovis 1984, 1986, 1989, 1990b; Robertson 1987). Recent research has also introduced
he importance of squash and maize likely exchanged down the line from regions further south
(Monaghan, et al. 2006; Raviele 2010).
Sites during the EW are a similar settlement model as the LA with winter aggregations at
Schultz (20SA2) and summer dispersal and encampment at Kantzler (20BY30) with fishing as the
primary activity (Fitting 1969). The proliferation of squash (Cucurbita Pepo) and ceramics likely
increased the economic productivity and subsistence stability. The subsistence strategy
employed is similar to the LA but at greatly reduced intensity - likely a highly mobile lifeways
where corridors (rivers) are used to access resource zones and exchange networks outside of
the area. Seasonal patterns include a reoccupation of autumn sites during the spring to exploit
nuts and squash. Groups dispersed into forest moraines for large and small mammal
exploitation, followed by intensive fishing during the early spring (Ozker 1982).
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MW Economy is dependent upon the intensification of the EW pattern with inclusion of
cultivation practices (Cleland 1966; Cleland and Kearney 1966; Fitting 1975; Luxenburg 1972;
Raviele 2010). This pattern is observed by an increased focus on large mammal exploitation
(Peebles 1978):121. An alternative interpretation focuses on wetland fauna (waterfowl, fish,
aquatic mammals, plants- especially wild rice)(Egan 1990; Lovis 1985; Lovis and Cleland 1993).
Archaeological Sites
Table 7. Sites with fauna and flora
Data Site
Site Name
Number
MNI 20SA380 Kretz
MNI 20SA198 Hart
MNI 20SA2
Schultz

Time
Period
LA
LA
LA

Relative
Dates
4000
4000
3500

MNI

20SA209

Younge

LA

4000

MNI

20SA192

Schmidt

LA

4660

MNI
MNI

20SA128
20BY29

Feeheley
Butterfield/
Schmidt

LA
LA

3930
3950

MNI

20SA581

Weber 1

LA

2990

MNI
NISP

20BY79
20BY387

Third Street Bridge
Marquette Viaduct
South

LA
Terminal
LA

2880
2600

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Citation
Keene 1981 (Keene 1981a, b)
Keene 1981 (Keene 1981a, b)
(Allison 1972; Fitting 1972;
Fitting and Allison 1972;
Keene 1972; Luxenburg 1972;
Shipman 2004)
(Blackbird 1887; Greenman
1937)
(Cleland and Kearney 1966;
Fairchild 1977; Harrison 1966)
(Allison 1972; Fitting 1972;
Fitting and Allison 1972;
Keene 1972; Luxenburg 1972;
Shipman 2004)
(Cleland 1989; Lovis 1989;
Smith 1989; Smith and Egan
1990)
(Egan-Bruhy 2002; Lovis 2002;
Lovis, et al. 1996)

Table 7. (cont’d)
Data Site
Number
MNI 20BY387

Site Name

NISP

20BY28

MNI

20SA2

Time
Period
Marquette Viaduct Terminal
South
LA
Fletcher/Marquette Terminal
LA
Schultz
EW

Relative
Dates
2600

MNI
MNI
MNI

20BY30
20BY30
20SA2

Kantzler
Kantzler
Schultz

EW
MW Early
MW Early

2650
2500
2480

MNI
MNI
MNI

20GR13
20BY79
20BY28

MW
MW
MW

2200
2100
1740

NISP

20BY28

MW

1740

MNI

20BY30

Kanitz
Third Street Bridge
Marquette Viaduct
Site
Marquette Viaduct
Site
Kantzler

1700

MNI

20SA2

Schultz

MW
Hopewell
MW Late

2600
2490

1600

Citation
(Egan-Bruhy 2002; Lovis 2002;
Lovis, et al. 1996)
(Egan-Bruhy 2002; Lovis 1985,
2002)
(Allison 1972; Fitting 1972;
Fitting and Allison 1972;
Keene 1972; Luxenburg 1972;
Shipman 2004)
(Crumley 1973)
(Crumley 1973)
(Allison 1972; Fitting 1972;
Fitting and Allison 1972;
Keene 1972; Luxenburg 1972;
Shipman 2004)

(Egan-Bruhy 2002; Lovis 2002;
Lovis, et al. 1996)
(Egan-Bruhy 2002; Lovis 2002;
Lovis, et al. 1996)
(Crumley 1973)
(Allison 1972; Fitting 1972;
Fitting and Allison 1972;
Keene 1972; Luxenburg 1972;
Shipman 2004)

The economic models are based on analysis of site and material inventories. The site
data is collected and synthesized from the State of Michigan - Office of the State Archaeologist
sites database. The geographic location has been obscured to protect site locations and
integrity. The zooarchaeological and archaeobotanical data is accumulated and synthesized
from a collection of archaeological site reports and published articles (see Appendix C). Taken
together, the sites, zooarchaeological and archaeobotanical data are the representation of the

161

cultural landscape through locales rather than pinpoint locations. This approach conceptualizes
individual sites as part of areas, landscapes or persistent places where HGs systematically use,
learned through their past experiences, cosmology, folklore, religious beliefs, both through
settlement and exploitative experiences (Lovis 2009; Schlanger 1990). These representative
sites and locales are important as they form key sources of information used to extrapolate
regional patterns of land use. Five key areas are described as locales; the confluence of the
Shiawassee, Saginaw, Cass and Tittabawassee rivers (hereafter Core), areas adjacent to the
Saginaw River valley and Saginaw Bay (hereafter Lower River Valley), the confluence of the
Chippewa, Pine and Tittabawassee River (hereafter Midland), along the Cass and Flint river
south of the Core (hereafter Cass Basin), and southwest sites near the present day St Charles
area (hereafter Shiawassee). Information about locales is limited to basic information about
location, seasonality, and material culture that relates to land use and diet choices (see
appendices for detailed information).
The Core area includes the Hart and Kretz, Feeheley , and Schultz sites. The Hart site
(20SA198) is located on a low sand knoll at elevation of 182.9 to 184.5 meters. The knoll is
located on what would have been a small island in the delta of the Tittabawassee River during
the LA. This site is similar to Feeheley, with a possible presence of a burial component at the
north end. The Kretz site (20SA380) is located on a low sand knoll approximately 181.4 m amsl.
Cultural remains include deep dense midden. The LA and Late Woodland component are
present. The site is a low elevation site, sand dune occupation of a low peninsula extending into
Shiawassee bay. Fish is identifiable and fragments of hickory, butternut, and black walnut are
also present (Lovis 2009; Robertson 1987; Robertson, et al. 1999).
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The Schultz (20SA2) site has the most extensive record of all the sites in the SBD, with a
stratified sequence to which most other sites are compared. Chenopodium and maize is also
found in MW contexts at the Schultz site (Allison 1972; Egan 1993; Fitting 1972; Fitting and
Allison 1972; Lovis, et al. 1994, 2001; Luxenburg 1972; Raviele 2010; Shipman 2004). The
Feeheley (20SA128) site is a repeatedly occupied LA campsite with a burial component located
on a long sand knoll, part of a remnant dune system created after the Nipissing high-water
stage of the glacial Great Lakes (Keene 1981b). The dunes form a thin arm of elevated land that
extends into the Shiawassee Flats. Between the Nipissing and Algoma high-water stages, this
arm of land formed an island or peninsula jutting into Shiawassee Bay. The site is likely a spring
or summer camp for nearby Hart or Schmidt site inhabitants (Fitting 1975). Freshwater
drumfish (Aplodinotus grunniens) yellow perch (Perca flavescens), brown bullhead (Ameirus
nebulosis), muskrat (Onadata zibethicus), chipmunk (Tamias striatus), and terrestrial
gastropods typically found in damp woodland and marsh-border type environments.
Carbonized seed and nut fragments were butternut, acorn, hickory nut, black walnut and one
grape seed. Butternut is the most common. Wood charcoal includes red oak, white oak, pine,
beech, blue beech, sycamore, black ash, ash, white ash, hickory, maple, white elm, slippery elm
and basswood. (Yarnell 1964).
In the Cass basin, Weber I (20SA581) and Schmidt (20SA192) are sites with a summer
occupation evidenced by the presence of turtles, large freshwater calcined bivalves. Lake
Sturgeon is present at Schmidt, which spawns up rivers that are 2-15 ft in depth (Scott and
Crossman 1973:84). White tailed deer (a fawn) is also identified at Schmidt suggesting an
occupation at peak fawning period during late May and early June (Cleland and Kearney 1966;
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Fairchild 1977). The Weber 1 site is located within an oak-hickory forest, occupants possibly
collecting walnuts. Lamb's quarters and plums are present and collected from a diverse range
of habitats. The Schmidt site, along the Cass River was occupied year round as a result of high
resource densities and diversity is located on a ridge paralleling the Cass River (Cleland and
Kearney 1966; Fairchild 1977; Harrison 1966; Keene 1981b). During the LA, the site would likely
been a dune or beach environment near to the shore, facing northeast across a small estuary
on the southeast side of Shiawassee Bay. Pits are infrequent at Schmidt and consist most of the
shallow basin shaped hearths with little change in frequency of fauna between strata (Cleland
1966; Fairchild 1977; Harrison 1966).
In the Lower River Valley, the Fletcher/Marquette Viaduct/Defoe Park and Kantzler sites
are are key sites (Crumley 1973; Egan-Bruhy 2002; Lovis 1985, 2002; Lovis, et al. 1996). Fletcher
site is a multi-component located on the west bank of the Saginaw River in Bay City, MI. This
site has three identified locales including the Marquette Viaduct (southwest of Fletcher), Defoe
Park (northwest of Fletcher) and Fletcher main locales. The Fletcher site occupations range
from the EW to 18th century. The site locale is open woodlands on the inland of the site and on
the 181m (595 ft) Algoma shoreline. MW occupation is present on a river levee (185 amsl).
Marquette Avenue Site (20BY387) is the northernmost part of the complex (Lovis 1985). During
the LA occupation, storage and smudge pits, and hearths concentrated along the edge of the
181m (595ft) terrace are present. The occurrence of cross-bedded gravel in the alluvial
sequence suggests regular flooding of this surface.
This pattern is similar to Schultz site where deposition of alluvium and gravels takes
place after A.D. 258-321 (Monaghan, et al. 1994; Speth 1972). Analyses of a midden shows
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medium to fine alluvial sand divided into Middle and Late Woodland occupations. Smudge pits,
hearths, roasting pit complexes and storage features. Features occur predominantly below the
Marquette Avenue site. Fletcher (20BY28) is likely a spatially restricted site (not continuous)
(Lovis 1985; Lovis, et al. 1996). The State Street site (20BY125) is the southernmost part of the
complex with burial activities, groundstone tools, bannerstones, and birdstones in habitation
contexts.
Wild resources dominate, while small numbers of cultigens are present as well. Wood
charcoal from the MW component shows ring-porous taxa predominate with family/genus
suggesting a dry, deciduous forest community (white pine, red pine, black oak, white oak) grew
along the Algoma beach ridge, while a wet-mesic community(bur oak, swamp white oak, red
ash, American elm) grew closer to the river. Nuts, seeds, and aquatic and terrestrial tuber in
low densities are present. A small number of seeds including aster (Asteraceae), chenopodium
(Chenopodium sp.), hawthorn (Crategus sp.), huckleberry (Gaylusaccia baccata), Virginia
creeper (Parthenocissus quinquefolia), rose (Rosaceae) and figwort (Scrophulariaceae) are
recovered from MW proveniences. The identification of chenopodium in different contexts
during the MW period suggests that there is an intentional exploitation of these seeds. Most of
these taxa are limited to disturbed habitats such as campsites and floodplains. Hawthorn and
huckleberry are commonly exploited by native communities as well as aquatic tubers exploited
during the spring and late fall for their starch content (Erichsen-Brown 1979).
Comparatively, the MW faunal assemblage is diverse with the inclusion of mammals,
birds, reptiles, and fish. Clearly, a wetland focus is present (See Appendix C for site flora and
fauna). Site characteristics suggest a series of warm season temporary camps (Lovis, et al.
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1996). GLO survey data shows a southern deciduous wet-mesic forest community including
elm, silver maple, ash, swamp white oak, and bur oak in the immediate vicinity. Mesic forest
communities and prairie grew within 5 miles (8km) of the site. A system of sloughs within an
extensive riverine environment was present at the site; over time these sloughs actively eroded
portions of the levee on which the site is situated (Lovis, et al. 1996; Monaghan and Lovis
2006).
The Liberty Bridge sites (20BY79) sites are likely late summer to fall occupations with
Durst and Meadowood points at 181 and 183m (595 and 600 ft amsl. 20BY79 is likely
contemporaneous with late occupations at Kantzler. Hearths, smudge pits, caches, and large
surface burns characterize the feature assemblage (Lovis 2002). A spatial partition of activities
is present. Areas higher up on the terrace is used for butchering, cooking and plant food
processing, while another area toward the foot of the terrace was employed for final tool
manufacturing or retooling. Ritual material is present at the highest, most inland locations at
the site; a cache of Turkey-tail points and a feature of red-ochre pigment (Lovis and Cleland
1993; Robertson 1987).
The Kantzler (20BY30) site is the southernmost site on the west bank of the Saginaw
River located at 183 m (597ft) with a meter of stratified deposits. The site has been interpreted
as a spring-summer fishing camp (Crumley 1973; Larsen 1973; Lovis 2009).
Approach
For each cultural period, an analysis of sites proximity, site type and occupation
persistence to landscape features is catalogued. This association will yield associations at
regional scale determined by density of sites, proximity to geomorphologic and cultural
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features. These links with features yields landscape scale relationships and provide the basis of
local level analysis. At the local level, site locales and archaeological assemblages can be
matched with local scale natural features, patches, habitats and resource communities. Further,
this allows for the archaeological fauna and flora to be analyzed by relationship of species
present to resource communities, exploitative regimes (when animals were chosen), the
relative makeup of the assemblage (strategy). How does location, occupation, seasonality,
temporal persistence of sites relate to resources? This analysis is intended to identify patterns
and changes in subsistence choices and settlement.
Next, two general statistical approaches are carried out. These spatial and quantitative
analyses are employed to link the landscape and archaeological material culture. The first
spatial approach is proximity techniques used to determine association of sites or group of sites
with resource communities or other natural features. The second spatial approach is the
identification of regional division of space undertaken by the use of Voronoi diagrams or
Theissen polygons. These are a decomposition of a metric space determined by distances to a
specified discrete set of objects in the space, e.g., by a discrete set of points. These spatial
diagrams evaluate grouping of sites to determine the organization of space with the use of key
site types (residential and burial sites). These sites can be compared to the distribution of sites
to determine spatial patterning of sites.
Second, a quantitative approach is used with faunal and floral assemblages in order to
determine diversity and change over time. Due to sampling and variable preservation issues, it
is difficult to directly measure absolute exploitation rates, although documenting ‘relative’
change in use is possible using ratios of identified taxa from sites of varying ages. Therefore, I
167

tested corollary implications of the models, (i.e., that specific species make up increasing
proportions of the subsistence base resulting from changes in diet choices). I calculated simple
ratios from dated site components, comparing the frequency of specific species (large & small
mammal, fish, and plant foods) to other similar products and evaluated the existence of
temporal trends in specific species use. This also allows for the observation of evidence for
wetland specific resources, resource depression etc. The relative use of resources can be
understood through variable indices. Indices are ratios with values from1-0 (e.g., frequency of
ungulate bones/frequency of all bones) or frequency of cervid bones/frequency of cervid +
small mammal bones and so forth). This approach provides a relative comparison of resources
exploited and change over time. By developing ratios comparing abundance of mammals, fish,
birds, and shellfish to each other, we could understand the possibility that people shifted their
reliance over time in responses to declining abundance in preferred prey.
Next, diversity analysis using Simpson’s Diversity index is conducted to determine the
implications of archaeological sites with faunal and floral remains to ascertain the seasonality
and association with land use and diet choices. Diversity analysis measures how the number of
specimens is distributed among predetermined classes under investigation (Baxter 2001;
Kaufman 1998; Kintigh 1984, 1989, 1990).
Two dimensions of diversity are computed: richness, which measures the number of
different classes present; and evenness, which measures the uniformity of distribution of
relative proportions of these classes (Bobrowsky and Ball 1989; Kintigh 1989; Leonard and
Jones 1989). The diversity index will result in richness (i.e., large number of species) and
evenness (i.e., low to high breadth of diet species) scores given the types of exploitative
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behaviors and coping strategies employed. The rationale is that a site is occupied for longer
duration will have a greater number of species present resulting from the exploitation of
multiple patches and habitats. Additionally, the presence or absence of key features (e.g.,
refuse, storage, burials) related to residential sites and possible adaptive strategies employed
for uncertain environments. For example, short term sites during warm weather occupations
with no hearths has limited remains, whereas the structures used for cold weather may be
more substantial and has more material remains.
Table 8. Site diversity
Diversity Measures
Low richness

Low evenness

High richness

Long term sites

High evenness
Short term sites
Limited activities
Intensive exploitation site

Diversity and density of species can indicate different types of sites, therefore exploiting
diversity of patches. Longer occupations will exhibit greater diversity of plant and animal
species. These variables will provide an understanding of archaeological site types and
subsistence strategies.
Table 9. Site occupation diversity
Site types
Low diversity
Low density
Short term specialized task
High density
Long term specialized task,
reoccupation

High diversity
Short term residential
Long term residential

The diversity calculation allows components of a site can be viewed in a continuum (i.e., from
small ephemeral limited activity areas to large residential bases where many activities would
have occurred) based on the faunal and floral assemblages (Bettinger 1979). Sites are ranked
based on different assemblages along a scale of relative diet breadth intensity rather than
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specific site categories (Thomas 1989):91. This analysis can be used by employing a jackknife or
bootstrapping approach, which can be alternative method to address theoretical and
methodological critiques with simulation and regression approaches that quantify diversity
among sites and assemblages (Grayson 1984; Kintigh 1984, 1989). Specifically, a jackknife
approach entails a resampling technique through repeated calculations of data and removing
one of the original observations after each calculation, resulting in a series of jackknife
estimates. Comparative population models, assumptions about, or knowledge of structure of
the original data is not needed. Like the regression and simulation methods, richness and
evenness scores for the data are computed. The richness and evenness scores can be tested
statistically to determine if the observed differences are real.
The spatial and diversity analyses provide an operational model of subsistence
strategies (i.e., diet, settlement and coping) and group social relations. Stated in this way,
prehistoric HG groups can exhibit patterns of behavior where assemblage with high to low
diversity with relative richness and evenness scores. For example, high richness and low
evenness scores indicate a residential locale with diversity of animals exploited from different
patches nearby or afar. A locale with high richness and evenness scores can be a place where
HG residential base with exploitation from different types of patches and resources.
Conversely, we should be able to identify sites that do not fit a specific expected profile; a site
with high evenness in an abundant resource setting suggesting a strategy intended to exploit
specific set of resources in a place of plenty. The pattern of site locale and organization or diet
choice individually may be analytically ambiguous; the combination of both locales adjacent to

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wetland landscapes and changes in pattern in diet provides stronger evidence of diet choice in
the SBD.

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Results

Figure 27. Persistent places
Five separate clusters are present. In addition, a cluster is also present headwaters of Flint River.
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N
Figure 28. Site density map (Saginaw County in inset)
Beyond the Saginaw core, the larger region has considerable number of sites.
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Figure 29. Local base levels and moraines
The moraines overlook local base levels (white areas) of major river networks. These flat areas are ideal locations for pooling of
water seasonally and during the LA and to a lesser extent during the MW. Majority of sites are located in proximity to these habitats.
174

Figure 30. LA sites and land cover
LA sites are located wide spread and adjacent to ephemeral wetlands and major river courses. A number of sites are uniquely
located boundaries of wetlands and hardwood forests. Note: see Figure 10 for land cover legend.
175

Figure 31. EW sites and land cover
176

Figure 32. MW sites and land cover.
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Figure 33. Saginaw and Lapeer County sites and land cover
Sites are numerous and varied in the Flint and Cass River headwaters, with higher site densities during the LA and MW periods. The
EW residential sites are located closer to the Core with camp sites further upstream. Conversely, both LA and MW sites are
distributed along river networks and along the coast, all of which are adjacent to large wetlands and beech-maple forests. Note: LA
(left), EW (middle), MW (right)
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Figure 34. Midland and Tuscola County sites and land cover
LA, EW, and MW sites are adjacent to large transitory wetlands. Wetlands decrease from LA to EW in Bay County coincides with
decrease in site type and density during the MW period. See earlier figures for legends
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Figure 35. Genesee County and Tobico Marsh ares sites and landco ver
LA sites are oriented and surrounding transitory wetlands and along extending tributaries. EW and MW sites are located along
tributary networks with larger residential sites focused to the south.
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Figure 36. Clinton and Iosco County sites and land cover
Sites located at the river confluences and wetlands show comparable densities with longer term site types present during the LA and
MW periods. Genesee sites at Cass River headwaters are located along Beech-Maple forests and adjacent to sites southeast.
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Figure 37. Bay and Huron County sites and land cover.
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Figure 38. Site interpolation (kriging) .
Spatial statistical method interpolating the presence of absence of sites based on site densities. The method is based on the relative
weights of key site types (burials and residential). Kriging allows for the prediction of sites between these areas. The LA sites are
located throughout the region along large river networks. EW sites are focused to the southeast (Cass and Flint rivers) and Core
wetlands embayment locales, whereas MW sites are limited to the Core embayment area. This interpolation of site densities may
also show presence or absence of interaction networks from SBD and other adjacent areas. Note: LA (left), MW (middle), EW (right)
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Figure 39. Thiessen polygons
Spatial compartments are used to divide space into a number of regions. Using residential and sacred sites, polygons are identified;
these can be used to potentially identify territories. The LA territories are numerous and densely packed. EW and MW are
considerably smaller with greater focus on the Core and River Valley persistent locales. Note: LA(left), MW (middle), EW (right)
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LA Sites in Proximity
120
100
80
60
40
20
0

Figure 40. LA sites in proximity to resource communities
Most LA sites are primarily located adjacent to mixed conifer and mixed hardwood swamps. The LA sites are found in most diverse
habitats, followed by EW sites. MW site diversity is lowest, at half of the LA levels. Proportionally, MW sites are wetland dominated,
whereas LA and EW sites are more diverse. Note: also see Figure 41.
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EW Sites in Proximity
60
50
40
30

20
10
0

MW Sites in Proximity
30
25
20
15
10
5

0

Figure 41. EW and MW sites in proximity to resource communities

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Activity Areas
40%
35%

30%
25%
20%

MW
EW

15%

LA
10%
5%
0%

Figure 42. Activity areas
Activity sites increase over time from LA to MW.

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Residential & Village Sites
7%
6%
5%
4%
3%

MW

2%

EW

1%

LA

0%

Camp & Base Camp Sites
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%

MW
EW
LA

Figure 43. Site type change by river basin
Residential or village sites shift locations between drainages; from the north during LA to the
south in EW. EW residential sites increase considerably in the Cass and Flint drainages. Saginaw
and Tittabawassee drainages importance increases from LA to MW. Base camps locales are
similar amongst the three periods.

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Burials & Mound Sites
3%
3%
2%
2%

MW

1%

EW

1%

LA

0%

Cache Sites
1%

1%
1%
1%
MW

0%

LA
0%

0%

Figure 44. Burial and cache sites change by river basin
Cemetery and mound sites are found mostly in LA and MW periods, primarily focused on the
Shiawassee and Saginaw drainages. These sites are nonexistent in the EW, with the exception in
the Cass drainage. Cache sites indicate places where they likely revisit on an annula or semiannual basis.
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Diet Type Ratios

Nuts to Animals

1700

1740

2200

2500

2490

2600

2600

2650

2880

2990

3500

3930

4000

4000

4000

Grains to Animals
4660

Ratios

0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0

3
2.5
2
1.5
1
0.5
0
1700

1740

1740

2200

2500

2490

2600

2600

2650

2880

2990

3500

3930

4000

4000

L to S Mammals

4660

Ratios

Years Before Present

Years Before Present
Figure 45. Diet ratio indices over time
The importance of large mammals, increase during the terminal LA and EW periods. Nuts and grains increase in importance through
LA. The importance of large and terrestrial animals increases during the MW.

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1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
5000

4000

3000

2000

1000

Simpson's Index

Diet Diversity - All Sites

0

RCYBP

Saginaw Core Sites Dietary Diversity
1

0.8
0.7
0.6

Simpson's Index

0.9

0.5
0.4
5000

4000

3000

2000

1000

0

RCYBP
Figure 46. Simpson's diversity index
Diversity of resources exploited in the Saginaw Core remains steady. The Schultz site shows a
moderate increase in dietary diversity. Sites away from the core show both a lack and
abundance of diversity.
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1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
3500

3000

2500

2000
1500
RCYBP

1000

500

Simpson's Index

Non Core Dietary Diversity

0

Schultz Diet Diversity
1

0.8
0.7

0.6

Simpson's Index

0.9

0.5

4000

3500

3000

2500
RCYBP

2000

1500

0.4
1000

Figure 47. Non core and Schultz diversity index
The regional analysis shows that resource diversity changes considerably. The diversity
decreases from LA to EW and increases in MW. In the EW, HG exploit low diversity sites for
specific resources, while concurrently exploiting other reliable sites with a greater diversity. HG
tradeoff the exploitation of specific sites by expanding the diet breadth at more reliable and
dependable sites.

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Discussion
The land use and diet analysis presents a few revealing insights into the economic
behaviors of HGs in the SBD. The outcomes are an expansion and refinement rather than a
departure from existing models of HG land use and diet choices in the study area. At a regional
level, analysis of site locales provides an account of land use during the study periods and
change over time. First, five persistent locales are occupied in all study periods. These
persistent places are identified as the Core, Lower River Valley, Midland, Shiawassee, Cass
Basins and a cluster of sites along the Flint headwaters at the border of Flint drainage. (see
Figure 27). These persistent places highlight longevity and regional nature of land use in the
SBD. These places contract and expand remain as a dominant feature of the landscape
throughout time suggesting considerable ritual, economic and cosmological importance.
Land Use
The locales highlighted are associated with key natural features including local base
levels, river systems, and wetlands. The resource communities present in locales are
heterogeneous and bounded by homogenous forest communities of hemlock white pine forests
to the north, and beech maple forests to the south. Site locales adjacent to wetlands and
riverine areas provide access to diverse natural resources such as fish, mammals and plants
(nuts, seeds); evident early as the LA continuing through the MW. The key factor that
determines productivity may be the wetlands present and large scale influence on resource
landscapes at any given period (see Chapter 5). The overall stability of this resource base
sustains the foraging economy. During periods of climate deterioration and wetland
contraction, people modified their economy by incorporating buffering strategies, including

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long distance mobility, storage, exchange of food stuffs and network of exchange relationships
both within different areas of the SBD and larger regional landscape to the north and south.
First, LA sites are distributed regionally, along the nexus of river networks, drainage
boundaries, along upland kettle lakes and linked to the local drainage base levels toward the
southwest and along the Saginaw Bay shoreline. Predictions of site distributions show a
patchwork of heterogeneous site locales across the basin region (see Figure 38). Analysis of
spatial partitioning based on burial, village and mound sites shows large dense cluster radiating
outward into larger segments covering the entire study area signifying regional cultural
landscape. Spatial partitioning also shows a clear southeast and southwest orientations of
partitioned space. These partitions could mirror resource extraction zones or possibly
territories as they also bisect multiple river basins and drainages. Location of sites of different
types shows culturally important sites along the Core area and along key tributaries of
Tittabawassee, Shiawassee and Saginaw river basins. Culturally important village, burial and
mound sites are located primarily on the Shiawassee Rivers. Base camps and activity areas are
present further along major river networks along both biotic provinces (see Figure 40). Last,
coastal sites at the Saginaw river mouth and along wetland fringes play an important role.
Second, EW sites are concentrated along persistent locales and constrained to the core
area. Regionally, the EW is not a continuation of the LA pattern. The EW’s drier, colder climate
with lower water levels and lower incidences of large scale flooding changes the cultural use of
the landscape. Sites are located adjacent to inland boundaries of white pine mixed hardwood
forests, emergent marshes, hardwood and conifer swamps. The Core sites are the used in

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similarly ways but become more transitory. A land use shift toward the southeast is observed;
focused on the more productive Carolinian biotic environment along the Cass and Flint Rivers.
Site locales also show a southern focus with constrained heterogeneous resource patches in
Core and River Valley locales (see

Residential & Village Sites
7%
6%
5%
4%
3%

MW

2%

EW

1%

LA

0%

Camp & Base Camp Sites
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%

MW
EW
LA

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Figure 43). Spatial portioning based on burial, village, mound sites shows similar cluster of
spaces in the Core areas, but highly diffused or nonexistent further beyond. Site type analysis
show a considerable shift of land use to the Cass river basin, whereas the Shiawassee and
Tittabawassee basins are used as activity areas and base camps for resource extraction. A
decrease in Tittabawassee basin sites and increase in burial, mounds and village sites along the
Cass further supports this shift. The regional cooling and drying trend during this time likely
made these the southern riverine areas the most productive areas. The residential sites are
located within Quercus (oak) forests along the Flint and Cass river networks. The exchange and
travel networks to the north may have been discontinued as the productivity and social
networks are likely to have been more productive to the south. EW periods also lack sites along
headwaters of major river systems, lesser density of sites along persistent areas and along
boundaries of major drainages. EW sites serve as evidence for site association with wetland
communities given the alternative habitats present. This area served as a strong resource pull
for groups in light of less productive areas further afield.
MW sites are observed to be focused along the Cass and Flint River basins, while
cemetery and village complexes are constrained along the Core embayment and expanded
along fluvial networks throughout the basin. The MW period is observed to undergo a dramatic
shift in land use from the previous period. This period follows a similar LA land use pattern with
inland expansion along river valley floodplains. Predicted site distributions also show a coastal
focus, with decreased site heterogeneity in Core and River Valley locales (see Figure 40).
Partitioning of space based on burials, village sites and mounds shows a larger but lower
number of spatial divisions. A considerable change in site locations is observed with

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considerable decrease in site densities and a large number located along wetland dominated
resource communities and adjacent to or on drainage base levels near the Core area. The MW
period is a transformation of the EW pattern with a greater focus on river systems along the
Core area with fewer sites along the locales between these basins. Last, the coastal sites
become more important with the exploitation of wild rice present along shallow, slow moving
inundated coast lines and the Saginaw River mouth.
Zooarchaeology and Archaeobotany
Faunal and floral inventories based on minimum number of individuals (MNI) provide
information about food choices. Further, the links between the food choices, sites and adjacent
habitats provides comprehensive matrix of possible food procurement strategies. For example,
resource chosen may or may not have been selected locally. Groups may use exchange or
mobility strategies to procure resources for further afield, storage to procure resources from a
different season. This matrix of choices provides insights to adaptive coping and buffering
mechanisms, all the while mapping onto to culturally important places. Further, the
characteristics of the resources chosen (broad vs. narrow spectrum) links adaptive behavioral
strategies and food preferences. To evaluate these interconnections, comparative resource and
diet diversity analysis is undertaken providing insights into the economy of individual cultural
periods and change over time.
First, the Core area exhibits the highest richness index of faunal and floral remains
present (see Figure 45); followed by Lower River Valley sites (see Figure 45) and sites further
along river courses (see Figure 45) in all three study periods. Next, the resource ratios analysis
of resource use exhibits a number of changes; an increased focus on large mammals relative to
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small mammals is evident during the EW period; Terminal LA and EW periods exhibit an
increase in the use of nuts and grains relative to mammal exploitation. The terrestrial to aquatic
resource ratios are higher in the early LA and decreases toward the Terminal and EW period,
and then increases during the MW period. Next, the dietary diversity analysis using the
Simpson’s index provides a perspective of resource choices. Taking into consideration total
faunal and floral material inventories amongst all sites, the overall dietary diversity based on
Simpson’s index decreases during the EW period. The individual site diversity shows a greater
range of food choices at sites during the Early and MW periods. This pattern may suggest more
specialized site use (e.g., fishing, nut collecting, and cultivation). The EW’s evidenced by
exploitation of a comparatively limited set of resources. The resource set is likely linked to the
diversity of resources available rather than a change in broad spectrum strategies.
The Core area site diversity remains static over time, with decrease during the EW
period suggesting the reliability and relative stability of the wetland areas. Specifically, the
Schultz site shows an increase in diversity over time. Sites away from the Core area show
decreased variability in diet choices suggesting that these locales are used as base camps and
exploitative areas intended for specific subsistence activities during the Early and MW periods.
The overall diversity of resources and sites is best explained by a strategy of balancing temporal
and spatial choices. The combination of spatial locales and resource choices suggest HG initially
pursue a highly diverse (broad spectrum) strategy. Over time, they continue the highly diverse
broad spectrum strategy and concurrently increase diversity of sites types exploited. The
increase in site diversity allows for exploitation of highly productive resources while
maintaining reliable productive bases in dependable areas.

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The non-core area sites have the highest variability in food choice diversity. Both,
narrow spectrum and broad spectrum exploitation sites are present at the non-core areas. A
considerable bifurcation of resource exploitation strategies is present, with two distinct and
separate patterns arising over time. This bifurcation of strategies suggests that non-core sites
are used differentially. These sites are initially exploited using a broad spectrum strategy, then
changing to both, a broad and narrow spectrum dependent upon the site season and location.
The narrow spectrum exploitation pattern possibly suggests that groups are logistically
procuring specific high value resources (i.e., large mammals or fish). The other broad spectrum
sites along the non-core areas are situated at key alternative persistent places.
Overall, the diversity of all sites with resources suggests a significant trajectory of
change over time. First, we observe sites with high diet diversity during the LA. Second, a shift
toward greater site types but with relatively limited narrow spectrum exploitation is observed.
Finally, during the MW, both sites and narrow spectrum exploitation takes place within the
backdrop of continuing reliance on reliable wetland habitats. This trajectory suggests that HGs
are developing complex adaptive practices in site and resource choices. This provides a
tantalizing context for later Late Woodland horticultural and agricultural practices.
Conclusions
This chapter presents insights into short and long term HG economy and culture based
on the available archaeological site and diet information. The interpretation provides both an
alternative and refined understanding economy of the SBD. The proximity of site locations is
keyed to wetland environments throughout the study periods. The diversity of site locales

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correlates well with the diversity of wetland habitat communities over time. Dietary analysis
suggests an increase in resource diversification in productive wetland habitats, at the same
time expanding and specializing in resources at sites in less productive habitats. Throughout the
study periods, HG communities adapt through complex strategy of increasing diversity of
resource exploitation and concurrently increasing the diversity of sites. This twofold approach
allows groups to effectively balance risk and uncertainty in the environment.

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Chapter 8: Discussion, Conclusions and Summary
Conclusions and Summary
This project sought to understand the role of uncertainty and risk in hunter-gatherer
(HG) economic decision-making. Decision-making is used to explore HG land use and diet
choices during the Late Archaic (LA), Early Woodland (EW) and Middle Woodland (MW) cultural
periods in the Saginaw Bay Drainage (SBD) of Michigan. In this study, uncertainty and risk is
conceptualized as expected and unexpected variability in the natural and social environment.
Uncertainty in the natural environment is the spatiotemporal variability of resource landscape
and biogeography. Social uncertainty and risk is the amount of information a HG holds about
the environment. Further, this project explores this variability and its implications to HG land
use and diet from the archaeological record. To this effort, three analytic approaches are
employed to explore this variability on economic adaptation, including a creation of a landscape
model, a behavioral simulation and an archaeological analysis.
First, a landscape model characterizes the structure (i.e., resources, habitats) of
uncertainty and risk that are present in the SBD environment (Chapter 2). The resulting
resource landscapes exhibit considerable spatiotemporal heterogeneity. Short-term changes in
habitats and resources are determined by seasonal factors resulting from hydrological
processes of varying magnitudes, including ponding, flooding, and wetland activation. Longterm changes include changes in distribution and density of local and regional wetland habitats.
Prior environmental reconstructions employed limited proxies, primarily through plant cover
distributions (Egan 1993; Keene 1981b). This project provides a more refined, detailed, and
larger-scale land cover in the SBD, derived from historical and geomorphological proxies and a

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simplified hydrological model. The resulting land cover model show that the EW period
landscape was a comparatively stable environment (in terms of wetland activity); whereas both
the LA and MW periods are highly variable resource environments, with greater
unpredictability and intermittently abundant habitats and resource structures.
Second, the behavioral simulation illustrates the implications of human choices in
variable environments (Chapter 6). Overall, the habitat choice simulation suggests a
considerable attraction to riverine and wetland-influenced habitats in the Saginaw core—the
confluence of the Saginaw, Tittabawassee, and Shiawassee Rivers—during LA, EW and MW
periods. A number of alternative locales were also important, including the Saginaw Bay
coastline and Saginaw Valley and Shiawassee embayment; all were associated with productive
seasonally reactivated and possibly ephemeral wetland locales. The diet simulation, structured
around seasonal and habitat productivity, and sexual division of labor indicates variable levels
of a broad-spectrum strategy as the best way to address uncertainty and risk; key amongst
them is low risk plant diet and high risk large mammal exploitation. This strategy allows HG to
both, exploit highly reliable and risky resources, balancing efficiency and security, at the same
time meeting baseline biological requirements for nutrients and alternative resource and social
goals (clothing, interaction etc.)
Third, the archaeological analysis provides a long term perspective on land use and diet
activities over time. From a regional perspective, the Saginaw core area exhibits the highest diet
richness and diversity; surrounding areas exhibit lower richness and lower diversity during all
three periods. Other key locales or persistent places apart from Saginaw core also remain
important over time. Furthermore, long-term analysis indicates that the LA and MW diets are

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more diverse than the EW diet, likely in response to increased variability. A clear pattern of
broad vs. narrow spectrum exploitation over time is present with greater reliance on a
combination of strategies (mobility, diversification, exchange, pooling and storage) over time.
Project Problems Revisited
At the onset of this research, three problems were posited to frame our existing
understanding and subsequent exploration of SBD HGs economic decision-making. Problems
include HG effective economic decision-making in variable wetland environments, the longevity
of the hunting
and gathering
modes of
production, and
lack of adoption
of complex social
organization and
incipient
horticultural
economy; all
three were

Figure 48: Wetland implications

framed as issues
relating to the uncertainty and risks in the social and natural environment.

This research,

in turn, contributes to these broad questions through a discussion of implications for; Michigan

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archaeology, Eastern Woodland Archaeology, Human Behavioral Ecology and a reflexive
critique of the project.
Implications for Michigan Archaeology
Three key contributions are made to Michigan Archaeology, including a better
understanding of: the resource environment at the three cultural periods, implications of
uncertainty and risk based decision making in temperate and wetland influenced environments,
and refinement of land use and diet models in SBD. The outcome of this research refines prior
efforts in prehistoric subsistence and settlement models and extends methodological
approaches in Michigan and Great Lakes (Arnold 1977; Egan 1993; Keene 1981b; Krist 2001;
Lovis, et al. 2001; Robertson 1987).
Resource Environment
First, the resource environment is recreated through a hydrology based landscape
model. This model identifies probable distribution and density of wetlands and linked
productive locales. This model highlights the considerable influence of wetlands in the regional
area throughout the study cultural periods. Second, the study provides HG choices in regards to
temperate environments based on a risk and uncertainty decision logic. Third, the
archaeological data is used to refine SBD land use and diet choices.
In this study, land use is identified through persistent places and site type classifications.
HG use of persistent places can be viewed as a desire to return to a specific place in terms of
resource present (i.e., gravity model), or based on an expectation that resources will be found
at a specific place (Robertson, et al. 1999). These persistent locales, with the addition of site

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type classifications and diet inventories refines of the existing subsistence and settlement
annual round.
First, the research contributes to a better understanding of the role of wetlands in HG
economy. Prior research in the SBD has repeatedly highlighted the possible importance of
wetland environments in HG land use and diet choices. Floods were common, and may have
forced seasonal abandonment of key locales and restricting of the resource environment
(Keene 1972; Lovis, et al. 2001; Wright 1972; Wright 1964). This study demonstrates that
wetlands have considerable implications for HG economy, and Great Lakes and Eastern
Woodland archaeology (Figure 38) (Bernick 1998). Wetland environments are more than simply
a supporting factor; they are a causal factor in resource and landscape variability and therefore,
a factor in HG land use and diet choices (see Chapter 5). All three study period landscapes and
diets show considerable influence from stable and unstable, and local and regional wetlands.
The landscape model identifies probable density and distribution of wetlands in the
study area (Chapter 5). These wetlands considerably affected the habitats and biogeography of
the study area. These wetlands influenced variability at spatial (local and regional) and
temporal (seasonally, and long term) scales during the periods of study. Basin-level variability,
therefore, plays an important role in the economic adaptation and cultural practices in the
area.
The LA and MW lake-level rise extensively altered the core Saginaw low lying areas
(Shiawassee embayment, St Charles and coastal areas); lower river gradients increased
sedimentation, creating broad and expansive wetland mosaics with highly productive marshes
and seasonally inundated areas that gave rise to drier seasonal habitats. Overall, the region was

205

heavily influenced by seasonal and stochastic forces that greatly affected the resource
environment in terms of abundance, predictability, and reliability.
Wetlands likely served as primary and secondary resource locales given the season.
Wetlands may even have been informally managed for edible resources such as cattails
(Harrington 1967). They are a highly nutritious food (rootstock or rhizome), containing as much
protein as maize and more carbohydrates than potatoes (Morton 1975); and are responsive to
varying hydrologic regimes. These recreated wetland landscapes (in terms of the method and
location used) provide a contextual framework and could be applied to similar locales in the
Eastern Woodlands and other time periods as well.
Uncertainty and Risk Based Decision-Making
Second, the research contributes to a better understanding of the role of uncertainty
and risk in HG economy. The simulation outcomes show that variable habitats and resources
play an important role in economic behaviors. An economy solely intended to alleviate this
variability results in strategies that should aim for the exploitation of reliable, abundant and
predictable resources. But, the exploitation of these ideal resources may not sufficiently result
in meeting minimum requirements due to the effect of both stochastic and predictable
variation. Therefore, this study leverages ethnographically based division of labor to simulate
alternate strategies to address this variation aimed to meet minimum subsistence goals. This
decision logic results in the selection of two broad diet and land use strategies; highly
productive but low density resources (i.e., large mammals) and low productivity and high
density resources (i.e., plants). Further, four key patches are preferred throughout the annual
cycle, including mesic southern and northern forests, riverine and, emergent and ephemeral

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wetlands. These habitats have variable, but high productivity throughout the annual round.
Taken together, uncertainty and risk based choices can be interpreted as a decision-making
boundary conditions intended to meet minimum economic requirements. Other rationales
(taste, prestige etc.) are then should be subsumed within these conditions. Decision-making
based on this alternate rationales are only engaged after boundary conditions are met.
Decision-making models, therefore, need to incorporate uncertainty and risk as a baseline
assumption.
Land Use and Diet Models in SBD
Last, the research contributes to a better understanding of the changes in SBD HG
economy and culture over time. First, HGs are observed to variably use their resource
landscape at different periods dependent upon the extent of wetland influence landscapes. The
changes in economy and culture can be broadly characterized as a wetland adaptation focused
diet and land use focused on persistent locales.
The archaeological analysis demonstrates key persistent places and the use of broadspectrum economy over time in SBD. The land use and diet patterns remain similar throughout
the study periods but exhibit considerable scalar differences between cultural periods. The
archaeological site patterning is focused on key persistent places on the landscape (see Chapter
7). The identified persistent places are long lasting with considerable differences in the
dimensions of use; exploitation range, habitat makeup, connectivity with nearby locales,
cultural use and importance, and specific diet choices.
In all three periods, HGs focus heavily on riverine, wetland and mesic southern forested
environments. During the LA, HGs employ regional and diverse land use strategies

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encompassing whole of SBD. During the EW, HGs shift land use to a localized to wetland core.
EW wetland environments were locally distributed, where key productive locales were isolated
to the Saginaw core. The overall diversity in wetland locales decreased during the EW period, a
result of the transformation of past wetlands and successional development of more mature
terrestrial areas. During the MW, an expansion of land use is observed, but limited to
headwaters of the large river networks along the Saginaw core. MW period wetlands are likely
reactivated environments along key large, local-base levels at the confluence of Saginaw,
Tittabawassee, and Shiawassee rivers.
The high water levels during the LA and MW periods likely increased the aquatic
habitats along major river courses and subsequently made fishing more appealing and
accessible. Further, the inundated areas also expanded travel corridors further inland giving
easier access upstream habitats.
In summary, HGs cope with rapidly changing landscapes (i.e., annual and inter annual)
with a number of strategies, including a highly flexible system of terrestrial and palustrine
exploitation. Sites were located on or adjacent to the most diverse habitat settings, primarily in
the core center surrounding the Shiawassee embayment and in the southern uplands along
boundaries of oak-hickory forests and oak savannas. The combined evidence from landscape
and behavioral models, and archaeological analysis provides insight into HG adaptive processes.
The evidence presented in this dissertation highlights human longevity and capacity to adapt to
variable environments. These outcomes taken together have considerable implications for local
Michigan, larger regional Eastern Woodland archaeology as well as Human Behavioral Ecology.

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HGs pursue a broad spectrum economy at key locales (Saginaw Core) throughout the
study cultural periods. At other locales, the study observes increasing specialization and
complexity in the types of sites and exploitation strategies employed over time. Exploitation
strategies change from broad spectrum to a combination of broad and narrow spectrum
exploitation strategies. The incorporation of narrow spectrum diet can be interpreted as an
increase in the use of logistic mobility during the EW and to a greater extent during the MW
period. The logistic exploitative forays exploited key resources including fish, large ungulates
and nuts (see Binford 1981; Wiessner 1982a).
Diet choices, especially the use of wetland species is remarkable. The diversity and
richness calculations show an increased focus along core wetland areas, such as the Schultz site
locale, during the EW period, with high richness and relatively low diversity relative to the LA
and MW periods (see Chapter 7). Taken together, the land use and diet choices have strong
correlation for behavioral strategies in coping with uncertainty and risk in the environment.
Broadly, coping and mitigating uncertainty and risk takes places at a landscape level (i.e.,
persistent places); elevated landforms and along key travel corridors.
These persistent places on the landscapes frame habitat and therefore resource choices.
The persistent locales further determine behavioral strategies, including broad and narrow
spectrum resource choices, land use and resource exploitation strategies (i.e., logistic vs.
residential mobility, collector vs. forager strategies).
The specific annual round includes late spring and summer exploitation of habitats
along the confluence of large rives and along the Saginaw River valley (per Robertson 1987).
The summer round is heavily focused on the Saginaw core and Saginaw Bay, with locales

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intermediate to both the Fletcher and Marquette Viaduct sites. Intergroup gathering may also
take place during these times, possibly keyed to productive wetland resource zones.
During the late summer and early autumn, groups move along large river and stream
networks to forested environments (to interior, along river and stream headwaters) for the
exploitation of riverine and forested resources. This time of season likely included gathering of
stored winter resources, and possibly larger group aggregations.
Winter and early spring were periods when groups moved along elevated moraines and
ridges adjacent to forest and riverine boundaries; exploiting wetlands and resources drawn to
wetlands. Groups likely revisited productive locales along the core basin as needed. The
primary habitats exploited during the annual round include mesic southern forests, riverine and
wetland environments. Available large and small mammals were likely exploited
opportunistically during all seasons. The diversity of wetlands types and resources were likely a
resource pull during most seasons, maybe with the exception of early spring snow melt which
likely inundated and activated low lying areas.
In the study area, groups adapted to winter and early spring by shifting not only their
population size and composition (distributed foraging) but also their spatial location to
upstream locales and by visiting localized productive habitats. Additionally, they likely focused
on marginal foods or use stored items from earlier seasons. Overall, the archaeological site and
diet patterns suggests a considerable focus on the diverse reliable core areas near confluence
of major river systems and activated wetland environments demonstrated by an increase in
type of sites present from LA to MW, especially along local base levels with increased moisture
inputs.

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The differences between cultural periods can be explained by the scale of river network
use rather than by any meaningful differential use of these places. Further, Liebig’s Law of the
Minimum suggests that the most critical period, that of lowest resource availability has strong
implications and important effects (limiting maximum carrying capacity) on human adaptation.
Winter, therefore, becomes a determinant season in settlement patterns. In the SBD, key
winter productive habitats include riverine and intermittent wetland locales (See Chapter 6).
Taken together, this research provides a refined archaeological land use and diet model as well
as the rationale basis (uncertainty and risk) behind those claims.
Implications for Eastern Woodland Archaeology
In the broader cultural context, the project has sought to understand the place of the
SBD in the regional Eastern Woodland through; 1) nature of HG economy, 2) its longevity, and
3) to determine the reasons why HG groups forwent the alternative complex social organization
and incipient horticultural practices located to the south.
First, HGs in the SBD should not be characterized as simply bands adapting to changing
environments by exploiting the diversity of resources. In actuality, this study indicates
considerable evidence for increasing economic and cultural complexity over time. Specifically,
an increasing specialization of land use and diet choices is evident. In other words, HGs are
adapted to SBD, not simply because of diversification of resource but also through the
diversification of cultural and adaptive strategies. This approach allows them to exploit
different types of niches, take risks that provide alternative economic resources.
The nature of HG economy during the LA and MW is linked to the variable landscapes
and resources. These periods exhibit seasonal and long term variability that is greater in

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magnitude than that of the EW period (Chapter 7). The variability of wetland resources, both in
terms of productivity and change over time required innovative strategies. During the EW,
there is a high correlation between the increased stability of the resource base and the
constricted use of the settlement locales.
Second, the longevity of HG adaptation in the area can be attributed to both, social and
ecological factors, specifically adaptive cultural practices aimed at coping and buffering
uncertainty and risk. The role of wetlands in SBD is important factor in understanding HG
longevity in the Eastern Woodlands. The environmental variability and resulting in changes in
wetland composition, density and distribution and linked changes in biogeography played an
important part in the HG economic decision making. The SBD during the LA and MW periods is
unpredictable, with resource abundance at key places with considerable variability, especially
during the winters. Unpredictability of landscape and resources require a highly flexible and
effective coping strategy.
The diversity and ingenuity of technology also contributed to the continued and
increased efficiency of foraging strategies. Ceramics, fishing technology, and lithic
improvements all likely contributed to the diversity and efficiency of exploitative strategies in
the area. Contrary to large-scale and drastic changes in society, the resiliency of wetland
resource exploitation provides an effective resource base for HG longevity while suppressing
the accumulation of resources, since those resources often were unpredictable.
Further, another factor that contributes to the longevity is the flexibility of HG economy.
Flexibility needs to be understood within the context of all available landscapes and resources.
The diversity of habitats and resources afforded groups different opportunities to respond to

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environmental fluctuations. Zooarchaeological records demonstrate the exploitation of a
diverse set of species—small and large mammals, aquatic birds, and fish. Simpson’s Diversity
Index indicates that a broad-spectrum diet and a highly diverse economy were present in both
the LA and MW periods (Chapter 7).
The behavioral simulation further supports the possibility of exploitation of diverse
resource (see Chapter 6). The Saginaw core, especially the Schultz and Green Point locales, was
used in a similar fashion during all three periods. Sites farther toward the bay along the Saginaw
River, including the Weber 1 and Marquette Viaduct/Fletcher complexes, show a decrease in
diet diversity. The diversity measures in these locales suggest a changing economic model
(through forager, collector continuum) during the later EW and MW periods.
HG groups adapted to variability over time through flexibility of land use and diet choices
practices. The flexibility of these practices is afforded by HG social structure including group
size, division of labor allowed for capability to adapt to environmental changes. Further, localscale habitat modification, suppression of competing predators, and resource modification
likely took place.
Third, HGs relinquished more complex social and economic practices for a number of
reasons. Within the study area, land use and diet choices were based on cultural strategies
used by groups to cope with varied levels of uncertainty in the resource environment. Next, the
wetlands themselves are one factor in why HG forwent adoption of economies to the south. For
example, there are a number of key resources that were exploited in wetland-mediated
environments and wetlands themselves. Wetlands provide ample opportunity, often year
round, for the exploitation of different types of fish, aquatic birds, and mammals. Wetlands are

213

areas where terrestrial mammals gather for easily accessible resources during a number of
seasons. The expectation is that wetland-related species were systematically exploited in these
areas.
Second, wild plant foods played an important role in the region, starting from the LA
period (Chapter 7). Wetland dynamics alternatively suppressed and encouraged terrestrial
plant and animal distributions. Specifically, the stabilization of climate, thus wetland
landscapes, may have possibly contributed to a later increased use of cultivated plants and
plant products in this area. There is a high level of wild plant foods use, including seeds isolated
to the core Schultz site locale (see Chapter 7). The extensive use of seeds and grains is relevant
to anthropological questions including ideas regarding incipient cultivation practices. This
project does not contribute directly to this issue. But, the study does provide rationale through
landscape reconstruction and archaeological synthesis that variable Palustrine landscapes alone
provide significant challenges and alternatives to reliable horticulture. Areas where plants
would be able to grow would need to be significantly drained or manipulated in order for
sustainable (reliable, annual) horticultural practices to be successful.
The likely scenario is an intermediate of both horticulture and sole reliance of wild plant
foods; groups likely pursed an opportunistic and informal approach to cultigens (Monaghan, et
al. 2006). Informally tended resources are more amenable to the wetland variability than
resources that require stable landscape requiring appropriate timing for planting, tending and
harvesting.
Although horticulture and even agricultural behaviors can be observed during the
Hopewell phenomena and later Mississippian emergence farther south, these strategies are not

214

readily found in the SBD, likely because of the instability in the environment prompted the use
of flexible and alternative strategies to address the existing variability. The gathering and even
possible cultivation of key domesticates adapted to riverine and lacustrine conditions could be
possible, even though restricted to fine-grained mesic soils. But, cultivation is unlikely due to
the regional habitat heterogeneity (wetland variability) and limitations of growing seasons
(climate) in the region. Reactivated and unpredictable wetlands habitats likely posed a
challenging environment due to annual flooding events, poor soil conditions and climatic
deterioration. These factors were likely a severe impediment to the planting, tending and
harvesting of annual cultivated plants. Quite possibly, perennial cultigens on the other hand,
have a greater longevity due to their ability to germinate after an unsuccessful annual cycle.
Informal and opportunistic tending of perennial cultivars could have been possible. Specifically,
the likelihood of cultivation in LA and MW period would have been difficult given the conditions
described. During the EW, the colder climatic conditions likely limited the possibility of reliable
cultivation as well (See Chapter 5).
Long-term cultivation and the development of horticulture required stable amenable
soils and climate away from the Saginaw core, which would require a considerable scheduling
conflict with long-established subsistence, specifically land use and resource gathering
practices. Resource harvest in seasonal wetland environments with increased wild plant and
animal productivity occurs at the same time as cultivated plants requires tending and care. The
use of horticultural products in the area, later during the Late Woodland periods would require
a considerable change in adaptive (economic and social) strategies. For example, wide spread
land use changes (assuming maize or any other domesticate is actually planted and harvested)

215

would be observed, given the considerable hydrological variability present in the Saginaw core
during all study periods. The settlement locales would shift toward areas that could possibly
grow plants, along the further southern fringes and headwaters of the SBD. These areas would
be drier, less influenced by variable hydrology of the Saginaw core.
Even though, horticulture was not practiced, use of wild plant foods is important
throughout the study periods as a dependable baseline resource. This continued importance
over time may have possibly played a role in the later incorporation of plant domesticates into
the economy. Overall, the later increased impetus for the cultivation likely came from the
synergistic effects of climatic change, anthropogenic environmental change, technological
change, and social innovation during the Late Woodland period.
The role of wild plant foods to mitigate uncertainty and risk clearly has a role to play in
our understanding of later transition of horticulture and agriculture. Coupled with plant foods,
ceramic innovations during the EW period also increased efficiency and the ability to store and
boil seed and starchy products, further linking the role of cultivated plants to environmental
uncertainty.
These factors in other areas may have led to reduced mobility and possibly sedentism
(Ford 1977; Watanabe 1973; Wiens 1976). For example, an area with highly productive habitats
can offer a variety of alternative resources to buffer against fluctuations. These areas
contributes to increased sedentism in the Illinois River Valley during the Middle and LA periods
(Brown and Vierra 1983; Ford 1977). However, unlike the areas farther south, stability in SBD
was juxtaposed with extensive seasonal variation, and possibly multi-year or decadal
unpredictability throughout the core basin, with basin-wide inundation and resource instability.

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This study questions the long-term capability of a stable arable habitat in the SBD. In the past,
this idea was attributed to a poorly drained landscape. This research provides the concept that
wetland dynamics provide a significant barrier to such agriculture and an alternative set of
choices.
Last, the SBD is integrated into the larger cultural areas by the regional manifestation of
LA cultural practices and the MW Hopewellian Interaction Sphere (Charles and Buikstra 2006;
Fritz 1990). SBD groups relied on their local adaptation and heavily participated in the
interaction and exchange networks, especially during the LA and MW. This participation can be
observed as an effective strategy of incorporating both a local SBD and a regional Eastern
Woodland economic model. This diversification of strategies leverages both local SBD and
regional economy to address increased variability in the resource environment.
Further, innovation and exchange has been associated with increased variability in
resource and habitats. The material culture of SBD reflects this pattern with the incorporation
of LA and MW Hopewellian features (burial treatment, down-the-line material, and food
exchange) (Charles and Buikstra 2006). The increased variability in the environment results in
increased exchange and interaction networks to mitigate and cope with variability. The nature
of SBD economy, the longevity of the HG mode of production and lack of participation in
domesticated economies may be directly linked to HG group’s ability to cope and adapt to
varied challenges in the environment.
In summary, SBD is more than simply a gathering place at specific times of the year. This
area is likely occupied over the long-term and was an important regional locale (regional
cultural gathering place) due to seasonally productive environments. Alternatively, other areas

217

(northwest and along the southwest) of the SBD may have occupied less intensively due to
factors including resource marginality, wind buffeting, northern exposures adjacent to but not
directly next to water, and lack of accessibility to travel networks that were insufficient to
sustain populations.
Additionally, the abandonment of productive locales for alternatives in the area would
have been highly risky and severely detrimental to group survival. Thus, the HG culture with its
social institutions and belief systems likely promoted flexibility through alternative multi-scalar
strategies including diversification, mobility, and exchange; all of which contributed to the
resilience of HG lifeways.
Implications for Anthropology/Human Behavioral Ecology
The overarching theme for this research has been to understand how HGs respond to
environmental and social uncertainty and risk. This study illustrates that uncertainty and risk
have a considerable effect on HG land use and diet choices. HGs buffer and cope with
uncertainty and risk through strategies based on the contextual dimensions of variability
present (spatial, temporal, and intensity). Based on the patterns observed in the SBD, a set of
coping strategy expectation of ‘when, where, what, and how’ is suggested. First, the high
imbalance among abundance, predictability, and reliability of a broad resource base results in a
large number of coping strategies being employed. For example, the LA period was likely highly
spatiotemporally unpredictable and was an intermittently highly productive environment.
Second, strategies in response to highly variable and unpredictable environments operate at
large regional scales. Third, strategies are employed in both a combined and rank-ordered

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fashion: 1) mobility; 2) diversification; 3) exchange and interaction; 4) pooling; and 5) storage
(Chapter 7).
Table 10. Coping and buffering strategies -relative basis
Time Period
Late Archaic
Early Woodland

Middle Woodland

Landscape

Wetland
dominated,
regional coverage,
abundant/ low
reliability/
unpredictable

Drier, mature
forests, considerably
reduced wetland
cover, overall stable
environments,
predictable, decrease
abundance, reliable

Flooded, reactivated
wetlands, increased
unpredictability/increa
sed abundance/
decreasing reliability

Expected Uncertainty
and Risk

High

Low

Medium

Economic Strategies
Hunting
Fishing
Gathering

Behavioral Analysis Likelihoods
Medium
Medium
High

Adaptation Strategies
Mobility
Exchange
Diversification (core)
Storage
Resource pooling

High
High
Medium

Medium
Medium
Medium

Archaeological Likelihoods
High
Very high – inter
and intraregional
Low
High
High

Low
Low – intraregional
Medium
Low
Low

Medium
Very high – inter and
intra regional
High
Low
Medium

In this model, storage then becomes the last coping strategy to be employed, partly due
to the social implication of developing a surplus and accumulating a labor pool. Mobility,
diversification, and exchange are often baseline requirements, but they vary in intensity given
the high levels of resource imbalance. This study indicates stability in diet choice diversity
(broad spectrum diet) over time, with increased specialization in exploitation strategies as the

219

environment stabilized. Next, as mobility increases, the exchange and interaction networks
likely increase as well. With regard to land use, relatively stable environments result in a lower
diversity in habitats used. Conversely, the greater unpredictability and variability of habitats
results in the use of more different types of habitats (see Table 10).
Diversification and exchange play a strong role in coping and buffering strategies. An
exchange strategy that became important was the use of interaction and exchange networks.
Interaction and exchange allow for the buffering of regional variability through extra-regional
relationships. During these time periods, sites were located in diverse resource environments
that were adjacent and intermediate to neighboring groups, toward both the Kalamazoo Valley
and the Southeast River Raisin Drainages (Chapter 7). The headwaters of the Maple and Flint
Rivers also had a considerable increase in sites during the LA and MW periods.
Social relationships (marriage and kinship) amongst groups adjacent to SBD may have
been used to maintain and reinforce a network of commitments and access to information
sources across the region. Social beliefs and rituals likely played an important role in cultural
adaptation, and contributed to resource choice in small-scale societies. Regulations over land
use, possibly usufruct agreements, likely determined who had the rights, timing, and duration
of exploitation. Rituals are likely embedded and woven into the social fabric and reaffirmed
during aggregations in key locales such as the Saginaw confluence. Thus, cooperative strategies
of exchange, pooled resources including aggregations for ceremony, and ritual are highly
important in variable environments. In this way, we observe that regional interactions are likely
to be greater in periods of higher uncertainty and risk (Chapter 7).

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With increasing uncertainty and broad-spectrum exploitation strategies (both in terms
of habitats that are used and diet choices that are made), increased mobility is readily
employed. The LA and MW periods are cases in point with greater uncertainty in the landscape.
In conjunction with technological advances in ceramics, the groups focus on the core Saginaw
Valley, exploiting the seasonally variable yet relatively stable resources that are present.
The key differences between time periods are the scale of flexible foraging through the
mobility and exchange networks. LA and MW strategies entail a regional strategy, whereas the
EW period entails a more local one. Social interaction and exchanges were likely reinforced
during periods of increased uncertainty. There was greater interaction amongst communities
with overlapping territories and greater customary practices where groups had access to
persistent locales. This increased interaction would require activation of practices to regulate
social relations of the intermediate areas outside SBD, as well as in the locally uncertain and
abundant resource locales. A threshold effect may have operated, given even greater
uncertainty, and may have transformed societies using the pooling or storing of resources.
Therefore, given the imbalance in the natural and social environments, the relative use of
individual strategies may provide expectations about the type of site locales and material
culture that are present.
Critique and Future Directions
Any modeling exercise is complex and contains numerous assumptions that frame the
endeavor. The heuristic nature of modeling is intended not to reflect reality but represents a
probability of past actualities. A number of adjustments could be made for future applications
of this project. First, a hydrological modeling approach using finer scales (space and time) might

221

yield a better predictive land cover for the study area. This can be accomplished through
geoarchaeological studies, expanding our understanding of aeolian and, specifically, fluvial
dynamics in the study area. This understanding would provide more information regarding the
level of moisture input, drainage, and sequestration in basin and upland areas, and would
perhaps result in a broadened and realistic land-cover description for the SBD.
Second, the simulations can yield uninformative results. Often, simulations and other
modeling endeavors struggle to find pattern through the noise of varied background behaviors.
Isolating key factors would provide a better understanding relationship and interaction to other
system components. Overall, this project (in terms of dataset and approach) lays out a research
framework, whereby numerous related questions could be explored in the future.
Third, directed archaeological research efforts through systematic surveys and
excavation aimed at SBD zooarchaeology and archaeobotany would further clarify models and
localized affects in wetland environments. One approach would be to conduct systematic
palynological and flotation studies of productive areas to further explore the role of plant
foods. Extensive geomorphologic studies and recoveries of fine-grained subsistence remains
are rare (but see (Lovis, et al. 2012; Monaghan and Lovis 2006) . Systematic flotation would
expand our knowledge of resource use multifold. Last, a number of places (e.g., along
headwaters of river systems) do not fit the land use and diet model, especially during the LA
period.
Fourth, studies that address travel, interaction, and exchange networks through the use
of geospatial and networks approaches—including least-cost path analysis and historical

222

General Land Office Survey (GLOS) narrative—would provide further knowledge regarding
interaction networks through material and information exchange.

223

APPENDICES

224

Appendix A: Landscape

Landscape Model Maps, Figures and Tables

225

Pollen Sites

Figure 49. Pollen sites and relative elevation.
226

River Course Profiles

Maple to Saginaw River Profile
200

AMSL

195
190
185
180
0

20,000

40,000

60,000

80,000 100,000

Flint to Saginaw River Profile
230

AMSL

220
210
200
190
180
0

50,000

Figure 50. Maple and Flint River course profiles

227

100,000

AMSL

Shiawassee to Saginaw River Profile
270
260
250
240
230
220
210
200
190
180
0

50,000

100,000

150,000

Pine-Tittabawassee-Saginaw River Profile
240
230

AMSL

220
210
200
190
180
0

50,000

Figure 51. Shiawassee and Pine River course profiles

228

100,000

Landscape Features by Region

Figure 52. Base model - terrain and digital elevation
Saginaw Bay Drainage topography has limited relief with a large basin surrounded by upland
areas.

229

Figure 53. River networks

230

Figure 54. Base model – 1800s wetlands
Key features that define the drainage are centripetal river drainage network and long lived wetland communities.

231

Figure 55. Local base levels
Huron lake levels play a key role in the landcover of the drainage. Local base levels are flat areas with river inputs. Base levels are
likely wet and inundated seasonally or over the long term.
232

Figure 56. Water table close to surface (<1 meter)

233

Figure 57. Base model – water table and recharge
The water table and drainage and recharge rates play a role in wetland formation. The combination of both is the areas of potential
wetlands.
234

Figure 58. Base model - hydric soils and drainage
The overlay of hydric soils and drainage rates can be used to extend the existing wetland distribution model. Large proportion of the
basin soils are poorly drained, therefore, easily ponded and flooded during early spring.
235

Figure 59. Soils drainage by class
236

Figure 60. Ponding begin by month

237

Figure 61. Ponding end by month
A considerable portion of the core basin is ponded during the mid-winter to early summer.
238

Figure 62. Water table by depth
The seasonal variability of the water table provides insights into likely flooded or ponded low lying areas. A considerable portion of
the basin has low and high water table close to the surface.

239

Figure 63. Soils
240

Figure 64. Soils slope

241

Predictive Landscapes

Figure 65. EW composite wetlands

242

Figure 66. MW composite wetlands

243

Figure 67. Clinton (top) and Iosco counties (bottom) composite landscape.
LA (left), EW (middle), MW (right)

244

Figure 68. Bay (top) and Huron counties (bottom) composite landscape
Bay County is a low lying area with homogenous wetlands bisected by pine forests.

245

Landscape Resource Communities
Table 11. Resource communities
Modified from (Albert 1995; Albert, et al. 1986; Comer, et al. 1995)
Resource Community
Ecological Group
Alvar
Terrestrial
Bog
Palustrine
Boreal Forest
Terrestrial
Bur Oak Plains
Terrestrial
Cave
Subterranean/Sink
Coastal Fen
Palustrine
Coastal Plain Marsh
Palustrine
Dry Northern Forest
Terrestrial
Dry Southern Forest
Terrestrial
Dry-mesic Northern Forest
Terrestrial
Dry-mesic Prairie
Terrestrial
Dry-mesic Southern Forest
Terrestrial
Emergent Marsh
Palustrine
Floodplain Forest
Palustrine
Granite Bedrock Glade
Terrestrial
Granite Bedrock Lakeshore
Terrestrial
Granite Cliff
Terrestrial
Granite Lakeshore Cliff
Terrestrial
Great Lakes Barrens
Terrestrial
Great Lakes Marsh
Palustrine
Hardwood-conifer Swamp
Palustrine
Hillside Prairie
Terrestrial
Inland Salt Marsh
Palustrine
Intermittent Wetland
Palustrine
246

Ecological Sub Group
Primary
Bog
Forest
Savanna
Fen
Marsh
Forest
Forest
Forest
Prairie
Forest
Marsh
Forest
Primary
Primary
Primary
Primary
Primary
Marsh
Forest
Prairie
Marsh
Marsh

Ecological Sub Sub Group

Bedrock Glade
Bedrock Lakeshore
Inland Cliff
Lakeshore Cliff

Table 11. (cont’d)
Modified from (Albert 1995; Albert, et al. 1986; Comer, et al. 1995)
Resource Community
Ecological Group
Interdunal Wetland
Palustrine
Inundated Shrub Swamp
Palustrine
Lakeplain Oak Openings
Terrestrial
Lakeplain Wet Prairie
Palustrine
Lakeplain Wet-mesic Prairie
Palustrine
Limestone Bedrock Glade
Terrestrial
Limestone Bedrock Lakeshore
Terrestrial
Limestone Cliff
Terrestrial
Limestone Cobble Shore
Terrestrial
Limestone Lakeshore Cliff
Terrestrial
Mesic Northern Forest
Terrestrial
Mesic Prairie
Terrestrial
Mesic Sand Prairie
Terrestrial
Mesic Southern Forest
Terrestrial
Muskeg
Palustrine
Northern Bald
Terrestrial
Northern Fen
Palustrine
Northern Hardwood Swamp
Palustrine
Northern Shrub Thicket
Palustrine
Northern Wet Meadow
Palustrine
Oak Barrens
Terrestrial
Oak Openings
Terrestrial
Oak-pine Barrens
Terrestrial
Open Dunes
Terrestrial
Patterned Fen
Palustrine
Pine Barrens
Terrestrial
247

Ecological Sub Group
Marsh
Shrub
Savanna
Prairie
Prairie
Primary
Primary
Primary
Primary
Primary
Forest
Prairie
Prairie
Forest
Bog
Primary
Fen
Forest
Shrub
Marsh
Savanna
Savanna
Savanna
Primary
Fen
Savanna

Ecological Sub Sub Group

Bedrock Glade
Bedrock Lakeshore
Inland Cliff
Cobble Shore
Lakeshore Cliff

Bedrock Glade

Table 11. (cont’d)
Modified from (Albert 1995; Albert, et al. 1986; Comer, et al. 1995)
Resource Community
Ecological Group
Ecological Sub Group Ecological Sub Sub Group
Poor Conifer Swamp
Palustrine
Forest
Poor Fen
Palustrine
Fen
Prairie Fen
Palustrine
Fen
Rich Conifer Swamp
Palustrine
Forest
Rich Tamarack Swamp
Palustrine
Forest
Sand and Gravel Beach
Terrestrial
Primary
Sandstone Bedrock Lakeshore
Terrestrial
Primary
Bedrock Lakeshore
Sandstone Cliff
Terrestrial
Primary
Inland Cliff
Sandstone Cobble Shore
Terrestrial
Primary
Cobble Shore
Sandstone Lakeshore Cliff
Terrestrial
Primary
Lakeshore Cliff
Sinkhole
Subterranean/Sink
Southern Hardwood Swamp
Palustrine
Forest
Southern Shrub-carr
Palustrine
Shrub
Southern Wet Meadow
Palustrine
Marsh
Submergent Marsh
Palustrine
Marsh
Volcanic Bedrock Glade
Terrestrial
Primary
Bedrock Glade
Volcanic Bedrock Lakeshore
Terrestrial
Primary
Bedrock Lakeshore
Volcanic Cliff
Terrestrial
Primary
Inland Cliff
Volcanic Cobble Shore
Terrestrial
Primary
Cobble Shore
Volcanic Lakeshore Cliff
Terrestrial
Primary
Lakeshore Cliff
Wet Prairie
Palustrine
Prairie
Wet-mesic Flatwoods
Palustrine
Forest
Wet-mesic Prairie
Palustrine
Prairie
Wet-mesic Sand Prairie
Palustrine
Prairie
Wooded Dune and Swale Complex
Palustrine/Terrestrial
Note. The Saginaw Drainage has the greatest diversity of habitats in Michigan, accounting for over 80% of the total.
248

Table 12. Relevant resource community descriptions - limited to study area
Adapted and summarized from Michigan Natural Features Inventory publication by (Kost, et al. 2007)
Resource Community
Description
Ephemeral Wetlands
Intermittent wetland is a sedge- and herb-dominated wetland found along lakeshores or in depressions
Intermittent Wetlands
and characterized by fluctuating water levels, both seasonally and interannually. Intermittent wetlands
exhibit traits of both peatlands and marshes, with characteristic vegetation including sedges (Carex
spp.), rushes (Juncus spp.), sphagnum mosses, and ericaceous shrubs. The community occurs
statewide.
SHRUB
Inundated shrub swamp is a shrub-dominated community characterized by poor drainage, nearly
SWAMP/EMERGENT
continuous inundation or saturation, and dominance by buttonbush (Cephalanthus occidentalis). The
MARSH
community typically exhibits a scattered shrub-dominated overstory and sparse herbaceous cover.
Emergent marsh is a shallow-water wetland along the shores of lakes and streams characterized by
emergent narrow- and broad-leaved herbs and grass-like plants as well as floating-leaved herbs.
Common plants include water plantain (Alisma plantago-aquatica), sedges (Carex spp.), spike-rushes
(Eleocharis acicularis spp.), pond-lilies (Nuphar spp.), pickerel weed (Pontederia cordata), arrowheads
(Sagittaria spp.), bulrushes (Schoenoplectus spp.), and cat-tails (Typha spp.). The community occurs on
both mineral and organic soils.
MIXED CONIFER SWAMP Rich conifer swamp is a groundwater-influenced, minerotrophic, forested wetland dominated by
northern white-cedar (Thuja occidentalis) that occurs on organic soils (i.e., peat) primarily north of the
climatic tension zone in the northern Lower and Upper Peninsulas. The community is also referred to
as cedar swamp.
Poor conifer swamp is a nutrient-poor, forested peatland characterized by acidic, saturated peat, and
the prevalence of coniferous trees, sphagnum mosses, and ericaceous shrubs. This system is found
predominantly north of the climatic tension zone, and much less frequently in southern Lower
Michigan. The community occurs in depressions in glacial outwash and sandy glacial lakeplains and in
kettles on pitted outwash and depressions on moraines. Fire occurs naturally during drought periods
and creates even-aged, often monospecific, stands of black spruce (Picea mariana). Windthrow, beaver
flooding, and insect defoliation are also important disturbance factors influencing species composition
and structure.

249

Table 12. (cont’d)
Resource Community
MIXED HARDWOOD
SWAMP

RIVER

WET PRAIRIE

WET PRAIRIE

Description
Hardwood-conifer swamp is a minerotrophic forested wetland dominated by a mixture of lowland
hardwoods and conifers, occurring on organic (i.e., peat) and poorly drained mineral soils throughout
Michigan. The community occurs on a variety of landforms, often associated with headwater streams
and areas of groundwater discharge. Species composition and dominance patterns can vary regionally.
Windthrow and fluctuating water levels are the primary natural disturbances that structure hardwoodconifer swamp.
Floodplain forest is a bottomland, deciduous or deciduous-conifer forest community occupying lowlying areas adjacent to streams and rivers of third order or greater, and subject to periodic over-thebank flooding and cycles of erosion and deposition. Species composition and community structure vary
regionally and are influenced by flooding frequency and duration. Silver maple (Acer saccharinum) and
green ash (Fraxinus pennsylvanica) are typically major overstory dominants. Floodplain forests occur
along major rivers throughout the state, but are most extensive in the Lower Peninsula. Species
richness is greatest in the southern Lower Peninsula, where many floodplain species reach the
northern extent of their range.
Wet prairie is a native lowland grassland occurring on level, saturated and/or seasonally inundated
stream and river floodplains, lake margins, and isolated depressions in southern Lower Michigan. It is
typically found on outwash plains and channels near moraines. Soils are primarily loam or silt loam of
neutral pH and have high organic content. Dominant species include bluejoint grass (Calamagrostis
canadensis) and cordgrass (Spartina pectinata), with sedges (Carex spp.) often important
subdominants.
Wet-mesic prairie is a native lowland grassland occurring on moist, occasionally inundated stream and
river floodplains, lake margins, and isolated depressions in southern Lower Michigan. It is typically
found on outwash plains and channels near moraines. Soils are primarily loam or silt loam with neutral
pH and high organic content. Dominants or subdominants include big bluestem (Andropogon gerardii),
Indian grass (Sorghastrum nutans), bluejoint grass (Calamagrostis canadensis), cordgrass (Spartina
pectinata), and sedges (Carex spp.).

250

Table 12. (cont’d)
Resource Community
BLACK ASH SWAMP

BLACK ASH SWAMP

CEDAR SWAMP

MUSKEG/BOG

Description
Northern hardwood swamp is a seasonally inundated, deciduous swamp forest community dominated
by black ash (Fraxinus nigra) that occurs on neutral to slightly acidic, hydric mineral soils and shallow
muck over mineral soils. Located north of the climatic tension zone, northern hardwood swamp is
found primarily in depressions on level to hummocky glacial lakeplains, fine- and medium-textured
glacial tills, and broad flat outwash plains. Fundamental disturbance factors affecting northern
hardwood swamp development include seasonal flooding and windthrow.
Southern hardwood swamp is a minerotrophic forested wetland occurring in southern Lower Michigan
on mineral or occasionally organic soils dominated by a mixture of lowland hardwoods. Conifers are
absent or local. The community occupies shallow depressions and high-order stream drainages on a
variety of landforms. The canopy is typically dominated by silver maple (Acer saccharinum), red maple
(A. rubrum), green ash (Fraxinus pennsylvanica), and black ash (Fraxinus nigra).
Rich conifer swamp is a groundwater-influenced, minerotrophic, forested wetland dominated by
northern white-cedar (Thuja occidentalis) that occurs on organic soils (i.e., peat) primarily north of the
climatic tension zone in the northern Lower and Upper Peninsulas. The community is also referred to
as cedar swamp.
Muskeg is a nutrient-poor peatland characterized by acidic, saturated peat, and scattered or clumped,
stunted conifer trees set in a matrix of sphagnum mosses and ericaceous shrubs. Black spruce (Picea
mariana) and tamarack (Larix laricina) are typically the most prevalent tree species. The community
primarily occurs in large depressions on glacial outwash and sandy glacial lakeplains. Fire occurs
naturally during periods of drought and can alter the hydrology, mat surface, and floristic composition
of muskegs. Windthrow, beaver flooding, and insect defoliation are also important disturbance factors
that influence species composition and structure. Muskeg is a nutrient-poor peatland characterized by
acidic, saturated peat, and scattered or clumped, stunted conifer trees set in a matrix of sphagnum
mosses and ericaceous shrubs. Black spruce (Picea mariana) and tamarack (Larix laricina) are typically
the most prevalent tree species. The community primarily occurs in large depressions on glacial
outwash and sandy glacial lakeplains. Fire occurs naturally during periods of drought and can alter the
hydrology, mat surface, and floristic composition of muskegs. Windthrow, beaver flooding, and insect
defoliation are also important disturbance factors that influence species composition and structure.
251

Table 12. (cont’d)
Resource Community
MUSKEG/BOG
BEECH-SUGAR MAPLEHEMLOCK

BEECH-SUGAR MAPLE
FOREST

HEMLOCK-WHITE PINE
FOREST

Description
Bog is a nutrient-poor peatland characterized by acidic, saturated peat and the prevalence of
sphagnum mosses and ericaceous shrubs. Fire and flooding are the main natural disturbance factors.
Mesic northern forest is a forest type of moist to dry-mesic sites lying mostly north of the climatic
tension zone, characterized by the dominance of northern hardwoods, particularly sugar maple (Acer
saccharum) and American beech (Fagus grandifolia). Conifers such as hemlock (Tsuga canadensis) and
white pine (Pinus strobus) are frequently important canopy associates. This community type breaks
into two broad classes: northern hardwood forest and hemlock-hardwood forest. It is primarily found
on coarse-textured ground and end moraines, and soils are typically loamy sand to sandy loam. The
natural disturbance regime is characterized by gap-phase dynamics; frequent, small windthrow gaps
allow for the regeneration of the shade-tolerant canopy species. Catastrophic windthrow occurred
infrequently with several generations of trees passing between large-scale, severe disturbance events.
Historically, mesic northern forest occurred as a matrix system, dominating vast areas of mesic uplands
in the Great Lakes region. These forests were multi-generational, with old-growth conditions lasting
many centuries.
Mesic southern forest is an American beech- and sugar maple-dominated forest distributed south of
the climatic tension zone and found on flat to rolling topography with predominantly loam soils. The
natural disturbance regime is characterized by gap-phase dynamics; frequent, small windthrow gaps
allow for the regeneration of shade-tolerant, canopy species. Historically, mesic southern forest
occurred as a matrix system, dominating vast areas of rolling to level, loamy uplands of the Great Lakes
region. These forests were multi-generational, with old-growth conditions lasting many centuries.
Mesic northern forest is a forest type of moist to dry-mesic sites lying mostly north of the climatic
tension zone, characterized by the dominance of northern hardwoods, particularly sugar maple (Acer
saccharum) and American beech (Fagus grandifolia). Conifers such as hemlock (Tsuga canadensis) and
white pine (Pinus strobus) are frequently important canopy associates. This community type breaks
into two broad classes: northern hardwood forest and hemlock-hardwood forest. It is primarily found
on coarse-textured ground and end moraines, and soils are typically loamy sand to sandy loam. The
natural disturbance regime is characterized by gap-phase dynamics; frequent, small windthrow gaps
allow for the regeneration of the shade-tolerant canopy species. Catastrophic windthrow occurred
infrequently with several generations of trees passing between large-scale, severe disturbance events.
252

Table 12. (cont’d)
Resource Community

WHITE PINE-MIXED
HARDWOOD
JACK PINE-RED PINE
FOREST

WHITE PINE-RED PINE
WHITE PINE-WHITE OAK
MIXED PINE-OAK
OAK-HICKORY

MIXED OAK

MIXED OAK SAVANNA

Description
Historically, mesic northern forest occurred as a matrix system, dominating vast areas of mesic uplands
in the Great Lakes region. These forests were multi-generational, with old-growth conditions lasting
many centuries.

Dry northern forest is a pine- or pine-hardwood-dominated forest type that occurs on dry sandy sites
lying mostly north of the climatic tension zone. Two distinct variants are included within this
community type, one dominated by jack pine (Pinus banksiana) or jack pine and hardwoods, and the
other dominated by red pine (P. resinosa). Prior to European settlement, dry northern forest typically
originated in the wake of catastrophic fire. Frequent, low-intensity ground fires maintained red pine
systems by removing competing hardwoods.

Dry-mesic southern forest is a fire-dependent, oak or oak-hickory forest type on generally dry-mesic
sites found south of the climatic tension zone in southern Lower Michigan. Frequent fires maintain
semi-open conditions, promoting oak regeneration and ground and shrub layer diversity.
Dry southern forest is a fire-dependent, oak-dominated forest type on dry sites lying mostly south of
the climatic tension zone in southern Lower Michigan. Frequent fires maintain semi-open conditions,
promoting oak regeneration and ground and shrub layer diversity.
Hillside prairie is a grassland or savanna community that occurs on moderate to steep exposed slopes
and crests of hills associated with river valleys, streams, or kettle lakes, surrounded by oak forest or oak
savanna. This natural community is almost always found on south- to west-facing slopes, where
exposure to sunlight is highest. Soils are typically strongly acid to neutral loamy sand or sandy loam,
and often mixed with gravel. Hillside prairie is notable for supporting several state-listed plant species
largely restricted to this community type.

253

Table 12. (cont’d)
Resource Community

SPRUCE-FIR-CEDAR

ASPEN-BIRCH

BLACK OAK BARREN

Description
Lakeplain oak openings are a fire-dependent savanna community, dominated by oaks and
characterized by a graminoid-dominated ground layer of species associated with both lakeplain prairie
and forest communities. Lakeplain oak openings occur within the southern Lower Peninsula on glacial
lakeplains on sand ridges, level sandplains, or adjacent depressions. Open conditions were historically
maintained by frequent fire, and in depressions, by seasonal flooding.
Poor conifer swamp is a nutrient-poor, forested peatland characterized by acidic, saturated peat, and
the prevalence of coniferous trees, sphagnum mosses, and ericaceous shrubs. This system is found
predominantly north of the climatic tension zone, and much less frequently in southern Lower
Michigan. The community occurs in depressions in glacial outwash and sandy glacial lakeplains and in
kettles on pitted outwash and depressions on moraines. Fire occurs naturally during drought periods
and creates even-aged, often monospecific, stands of black spruce (Picea mariana). Windthrow, beaver
flooding, and insect defoliation are also important disturbance factors influencing species composition
and structure.
Southern shrub-carr is a moderate to long persistent successional shrub community dominated by
willows (Salix spp.), dogwoods (i.e., Cornus stolonifera, C. foemina, and C. amomum), winterberry (Ilex
verticillata), and bog birch (Betula pumila). This community is successionally intermediate among a
variety of open, herbaceous wetlands (i.e., southern wet meadow, prairie fen, wet-mesic prairie, and
lakeplain wet-mesic prairie) and forested wetlands such as rich tamarack swamp and southern
hardwood swamp. It typically occurs on saturated, organic soil and is characterized by fluctuating water
levels and poor drainage conditions. Southern shrub-carr is found primarily south of the climatic
tension zone in southern Lower Michigan and is frequent in other Midwestern states such as Illinois,
Indiana, Iowa, Minnesota, and Wisconsin. North of the climatic tension zone, wet-ground, tall shrub
communities are typically dominated by tag alder (Alnus rugosa) and are classified as northern shrub
thicket.
Oak barrens are a fire-dependent savanna type dominated by oaks, having between 5 and 60% canopy,
with or without a shrub layer. Black oak (Quercus velutina) and white oak (Q. alba) typically dominate
the scattered overstory. The predominantly graminoid ground layer is composed of species associated
with both prairie and forest communities. Oak barrens are found on droughty soils and occur typically
on nearly level to slightly undulating glacial outwash in southern Lower Michigan.
254

Table 12. (cont’d)
Resource Community
OAK/PINE BARRENS

PINE BARRENS

GRASSLAND

GRASSLAND

Description
Oak-pine barrens is a fire-dependent, savanna community dominated by oaks and pines, having
between 5 and 60% canopy cover, with or without a shrub layer. The predominantly graminoid ground
layer contains plant species associated with both prairie and forest. The community occurs on a variety
of landforms on droughty, infertile sand or loamy sands occasionally within southern Lower Michigan
but mostly north of the climatic tension zone in the northern Lower and Upper Peninsulas.
Pine barrens is a coniferous, fire-dependent savanna of scattered and clumped trees located north of
the climatic tension zone in the northern Lower and Upper Peninsulas. The community occurs on level
sandy outwash plains and sandy glacial lakeplains. The droughty sand soils are very strongly to strongly
acid, with very poor water-retaining capacity. The community is dominated by jack pine (Pinus
banksiana), with northern pin oak (Quercus ellipsoidalis) as a frequent canopy associate. Frequent fires,
drought, and growing-season frosts maintain the open canopy conditions.
Dry-mesic prairie is a native grassland community dominated by big bluestem (Andropogon gerardii),
little bluestem (Andropogon scoparius), and Indian grass (Sorghastrum nutans). The community occurs
on sandy loam or loamy sand on level to gently sloping sites of glacial outwash, coarse-textured end
moraines, and glacial till plain. The community represents the stands of open grassland that occurred in
association with historic oak openings throughout much of southern Lower Michigan. In previous
versions of the natural community classification this community was called woodland prairie.
A wide variety of soils support mesic northern forest but most typically it occurs on loamy sand to
sandy loam and occasionally on sand, loam, and clay. Soils range widely in pH from extremely acidic to
moderately alkaline but are more commonly extremely acid to medium acid. Mesic prairie is a native
grassland community dominated by big bluestem (Andropogon gerardii), little bluestem (Andropogon
scoparius), and Indian grass (Sorghastrum nutans). It occurs on loam, sandy loam or silt loam soils on
level or slightly undulating glacial outwash. Historically, mesic prairie dominated large portions of the
Midwest ranging from Iowa and southern Minnesota east into southwestern Michigan and northern
Ohio. In Michigan, mesic prairie occurred historically in Kalamazoo, St. Joseph, Cass, Branch, Calhoun,
Berrien, and Van Buren Counties.

255

Table 12. (cont’d)
Resource Community
EXPOSED BEDROCK

SAND DUNE

Description
Limestone bedrock lakeshore is a sparsely vegetated natural community dominated by lichens, mosses,
and herbaceous vegetation. This community, which is also referred to as alvar pavement and limestone
pavement lakeshore, occurs along the shorelines of northern Lake Michigan and Lake Huron on broad,
flat, horizontally bedded expanses of limestone or dolomite bedrock. On the Lake Michigan shoreline,
limestone bedrock lakeshore is concentrated along the Garden Peninsula and the southern part of
Schoolcraft County. Along Lake Huron, it is located east of the Les Cheneaux Islands, on Drummond
Island, and on Thunder Bay Island.
Open dunes is a grass- and shrub-dominated multi-seral community located on wind-deposited sand
formations near the shorelines of the Great Lakes. Dune formation and the patterning of vegetation
are strongly affected by lake-driven winds. The greatest concentration of open dunes occurs along the
eastern and northern shorelines of Lake Michigan, with the largest dunes along the eastern shoreline
due to the prevailing southwest winds.

256

Table 13. Resource community soils
Summarized from Michigan Natural Features Inventory by (Kost, et al. 2007)
Resource Community Soils
Alvar
Alvar soils are characterized by shallow soil over bedrock, with soil depth usually less than 25 cm (10 in).
Soil texture is primarily loamy sand or sandy loam. Soil is saturated, or locally inundated in the spring,
but becomes droughty later in summer. Thin layers of organic soil may develop in shallow depressions
that remain wet for longer periods. Soil is mildly to moderately alkaline.
Bog

Boreal Forest

Bur Oak Plains

Cave
Coastal Fen

The organic soils are composed of saturated fibric peat that contains partially decomposed sphagnum
mosses and frequently, fragments of sedges and wood. Like the surface water, peat soils are extremely
acidic, cool, and characterized by low nutrient availability and oxygen levels. The water-retaining
capacity of sphagnum peat is tremendous and as a result bogs are saturated, anoxic systems with water
tables near the surface. Peat composition changes with depth and is influenced by the successional
history of a given site. Fiber content and hydraulic conductivity of peat soils usually decrease with depth.
Sand, loamy sand, and sandy loam soils are typically moderately acid to neutral, but heavier soils (e.g.,
silty loam and clay loams) and more acid and alkaline conditions are also found. Boreal forests that occur
over bedrock or cobble are often characterized by shallow organic soils or mor humus. Where conifers
dominate the canopy, the litter layer is typically more acidic than the underlying organic and mineral
soils. Water-retaining capacity of the soils is variable with sandy soils typically being well-drained and
soils with heavier texture, such as loams, ranging from moderately drained to poorly drained. Inland
boreal forest systems usually occur on moderately to poorly drained lakeplain or outwash.
Soils were fertile, fine-textured, loam, sandy loam or silt loam with neutral pH and good water-retaining
capacity. Soils contained moderate to high amounts of organic matter and supported high abundance of
graminoids and forbs.
There is no information on soil development within Michigan’s caves, but since they are derived from
limestone or dolomite, soils are likely mildly to moderately alkaline.
Soils of coastal fen may range from neutral to moderately alkaline, fine-textured sand to clay in areas
immediately adjacent to the lake, to marl and organic sediments in protected coastal embayments less
influenced by storm waves. When lake levels rise, areas closer the lakeshore become inundated and
storm waves can wash away loose organic and marl sediments.
257

Table 13. (cont’d)
Resource Community
Coastal Plain Marsh

Dry Northern Forest

Dry Sand Prairie
Dry Southern Forest

Soils
The sandy soils underlying coastal plain marshes are strongly to very strongly acidic and nutrient-poor.
Organic deposits of peat or sandy peat may overlay the sandy substrate, and in some basins a clay layer
may occur several meters below the surface.
Soils are coarse-textured, well-sorted, excessively drained dry sands with low amounts of organic matter
and low water-holding capacity. The droughty soils are extremely acid to very strongly acid with low
nutrient content and high frost proclivity.
Soils of dry sand prairies are typically very strongly acid to medium acid loamy sand with low waterretaining capacity.
The soils of dry southern forest are infertile, well-drained sand, loamy sand, or sandy loam with medium
to strongly acid pH and low water-retaining capacity.

Dry-mesic Northern
Forest

Sand or loamy sand soils are extremely acid to very strongly acid and coarse- to medium-textured. A
surface layer of mor humus is normally present due to the accumulation of pine needles.

Dry-mesic Prairie

Soils are typically strongly acid to circumneutral sandy loam or occasionally loamy sand with moderate
water-retaining capacity.
Soils are typically sandy loam or loam and slightly acid to neutral in ph.

Dry-mesic Southern
Forest
Emergent Marsh

Emergent marsh can develop on all textures of glacial sediment, including rock, gravel, sand, silt, or clay.
Typically there is an accumulation of circumneutral to alkaline, fine organic sediments overlying the
mineral soil. Where organic sediments are acid, the wetlands tend to develop into peatlands rather than
remain as marsh.

258

Table 13. (cont’d)
Resource Community
Floodplain Forest

Granite Bedrock Glade

Granite Bedrock
Lakeshore

Granite Cliff

Soils
Soil is highly variable and strongly correlated with fluvial landforms. The coarsest sediment is deposited
on the natural levee, immediately adjacent to the stream channel, where the soil texture is often sandy
loam to loam. Progressively finer soil particles are deposited with increasing distance from the stream.
Soil texture of the first bottom is often silt loam, with silty clay loam to clay-textured soil often occurring
in swales and backswamps. Cycles of periodic over-the-bank flooding followed by soil aeration when the
floodwaters recede generally prevent the accumulation of organic soils. However, an accumulation of
sapric peat can develop farther from the river due to a relatively low flood frequency, low flow velocity,
and prolonged soil saturation resulting from a high water table. Floodplain soils are generally
circumneutral to mildly alkaline. Slightly acid soils are generally only found on hummocks of organic soil
in backswamps or meander-scar swamps. Floodplain soils are characterized by high nutrient availability
and an abundance of soil water throughout much of the growing season.
Soil development is generally restricted to cracks and depressions within the rock, where plant debris
and sand and gravel resulting from mechanical and biological weathering of the bedrock can accumulate.
These soils are typically very shallow and low in nutrients. Thin soils are typically 1 to 4 cm (0.4 to 1.6 in)
deep, strongly acidic, and characterized by low moisture availability. Exfoliation of rock slabs and frost
wedging is characteristic of granite and contributes to soil formation. Numerous large boulders, slabs,
and small granitic rocks occur scattered throughout the glades, and talus slopes occur at the base of
many bedrock exposures.
Because the granitic rocks along the coast are highly polished and extremely resistant to weathering,
very little soil development takes place. Storm waves and ice scour also regularly remove developing
soils. Freshly broken rock surfaces are circumneutral to mildly alkaline in pH, but the surface of
weathered bedrock is acid. Some organic soil development takes place in cracks, under low shrubs, or in
pools. Vascular plants are typically limited to these shallow cracks, exfoliation depressions, and pool
edges where moisture and available nutrients are concentrated.
Soil development is limited to shallow organic soils that form from decaying roots and other plant
material that accumulates in cracks, crevices, ledges, and flat areas or depressions in the bedrock. Soils
accumulate primarily along the cliff summit, on talus slopes, and at the base of the cliff. The thin organic
soils are typically acid but can range from slightly acid to slightly alkaline depending on the rock type.

259

Table 13. (cont’d)
Resource Community
Granite Lakeshore Cliff

Great Lakes Barrens
Great Lakes Marsh

Hardwood-conifer
Swamp

Hillside Prairie

Inland Salt Marsh

Soils
Soil development is limited to organic soils that form from decaying roots and other plant material that
accumulates in cracks, crevices, and depressions in the bedrock, primarily along the cliff summit. The
thin organic soils are acidic.
The sand soils are circumneutral and dry. Subsoil water levels in depressions are periodically elevated by
changes in Great Lakes water levels.
Where bedrock is at or near the surface, bedrock chemistry affects wetland species composition. Soils
derived from Precambrian crystalline bedrock along Lake Superior are generally acid and favor the
development of poor fen or bog communities. In contrast, soils derived from marine deposits in the
lower Great Lakes, including shale and marine limestone, dolomite, and evaporites, are typically more
calcareous (less acid), creating the preferred habitat for calciphilic aquatic plant species and
development of more minerotrophic communities such as wet meadow and coastal fen.
Substrate conditions are heterogeneous, and are often highly variable within a single stand. The most
common condition is a thin layer of organic soil over a poorly drained mineral substrate. Organic soils are
typically saturated, highly decomposed, sapric peat (i.e., muck) and frequently contain pieces of coarse
wood throughout their soil profiles. Areas of deep (>1 m) organic deposition are common, especially in
seeps. Substrate pH is also highly variable. Saturated mucks are typically of neutral pH, but may be acidic
near the surface, especially where associated with sphagnum mosses or where coniferous needle mats
accumulate. Mineral soils are often acidic. Vegetation (living and dead), depth to the water table, and
groundwater movement all influence substrate alkalinity.
Soils are well-drained, sandy loam to loamy sand and can range from strongly acid to neutral. Gravel is
often present at or near the surface. One occurrence of hillside prairie is associated with exposed preglacial fluvial deposits of shale and conglomerate rocks.
This community occurs on peat, muck, or mineral soils saturated by sodium- or chlorine-rich
groundwater seeping from saline aquifers. Soils of an intact salt marsh in Michigan were found to be high
in sodium, chloride, potassium, calcium, and magnesium and have a pH that ranged from medium acid to
moderately alkaline.

260

Table 13. (cont’d)
Resource Community
Interdunal Wetland

Intermittent Wetland

Inundated Shrub
Swamp

Lakeplain Oak
Openings
Lakeplain Wet Prairie
Lakeplain Wet-mesic
Prairie
Limestone Bedrock
Glade

Soils
The saturated sand and pond water of interdunal wetlands along the lower Great Lakes is neutral to
moderately alkaline because of traces of calcareous minerals in the lake-edge sands. The sand, which is
sometimes covered by a thin layer of muck, is similar in composition to that of the surrounding beach
ridges or dunes, consisting largely of quartz with lesser amounts of feldspar, magnetite, and traces of
other minerals, such as calcite, garnet, and hornblende. On Lake Superior, there is little or no calcite, and
alkalinity is typically lower than in the other Great Lakes. In the Straits of Mackinac region, the underlying
soil in interdunal wetlands is sometimes fine-textured loams or clays rich in calcium carbonate.
Carbonate-rich groundwater flows from adjacent sand dunes or nearby limestone or dolomite uplands,
providing nutrients for rapid growth of stonewort (Chara spp.) and other algae. The metabolism of these
algae produces calcium carbonate, which precipitates as a fine, white mud-like substance called marl. As
marl deposits accumulate, sometimes reaching more than a meter in depth, they facilitate the formation
of northern fen.
The sandy soils underlying intermittent wetlands are strongly to very strongly acidic and are primarily
sands or occasionally loamy sands. Shallow organic deposits of peat or sandy peat may overlay the sandy
substrate and in some basins, a clay layer may occur below the surface.
Soils are typically shallow muck over gleyed clay, silty clay, or sandy clay. Soil pH ranges from strongly
acid to moderately alkaline, with organic portions of the soil profile being more acidic than mineral
portions. Although soil typically remains inundated throughout the year due to the underlying
impermeable clay, the upper soil layers may become dry in mid to late summer and during periods of
persistent drought.
Soils are typically mildly alkaline, very fine sandy loams, loamy sands, or sands with moderate waterretaining capacity.
Soils are medium- to fine-textured, slightly acid to moderately alkaline sands, sandy loams, or silty clays
with poor to moderate water-retaining capacity.
Soils of this natural community are fine-textured, slightly acid to moderately alkaline sands, sandy loams,
or silty clays with poor to moderate water-retaining capacity.
While large areas of limestone are bare of soil, where soils have developed, they are typically organic
soils less than 30 cm (12 in) in depth. Soils are circumneutral and are generally saturated or flooded in
261

Table 13. (cont’d)
Resource Community

Limestone Bedrock
Lakeshore

Limestone Cliff

Limestone Cobble
Shore

Limestone Lakeshore
Cliff

Soils
the fall and spring, but are often droughty during summer months. Where there is no surface soil
development, organic soils may accumulate in broad cracks (grykes) in the limestone pavement, where
shrubs and trees often establish.
Almost no soil development takes place directly on the limestone pavement, where storm waves and ice
routinely scour the rock surface. Consequently, plant establishment is generally limited to cracks, joints,
and depressions in the bedrock, where small amounts of organic matter, cobble, and finer sediments
accumulate. Because it is formed from marine organisms, limestone bedrock is rich in calcium
carbonates, resulting in a mildly alkaline soil ph. Resistance of the bedrock to erosion is variable. Both
limestone and dolostone are readily dissolved by rainwater, producing solution depressions and cracks
that often connect to the underlying groundwater system. However, limestone rich in mineral soil
particles originating from terrestrial sources is resistant to solution and typically contains few cracks.
Soil development is primarily limited to thin organic soils that form from decaying roots and other plant
materials along the top of the cliff escarpment and ledges, in cracks and crevices in the bedrock, and at
the base of the cliff. Breakdown of limestone and plant debris results in a sandy to loamy, organic-rich
soil, with mildly alkaline to alkaline ph.
The size of the cobbles and both the depth and texture of underlying sediments vary greatly and can
affect both the diversity and stability of the plant community. While most of the beach surface consists
of cobbles of varying size, the underlying parent material is either limestone bedrock or fine-textured till.
Between the cobbles there is rock, mineral, or organic soils. Soil texture is typically heavy clay or loam,
but in some areas these fine-textured soils are overlain with a thin veneer of sand. Organic sediments
can accumulate to 5 cm or more in protected inner portions of the shore. Regardless of the soil texture,
pH is mildly to moderately alkaline. Deep accumulations of large cobbles tend to be quite dry and are
nearly unvegetated. In contrast, shallow accumulations of small gravel and cobbles, especially when
mixed with a moist sandy substrate, tend to support denser and more diverse plant cover.
Soil development is primarily limited to thin organic soils that form from decaying roots and other plant
materials along the top of the cliff escarpment and ledges, in cracks and crevices in the bedrock, and at
the base of the cliff. Breakdown of limestone and plant debris results in a sandy to loamy, organic-rich
soil, with mildly alkaline ph.
262

Table 13. (cont’d)
Resource Community
Mesic Northern Forest

Mesic Prairie

Mesic Sand Prairie

Mesic Southern Forest

Muskeg

Soils
A wide variety of soils support mesic northern forest but most typically it occurs on loamy sand to sandy
loam and occasionally on sand, loam, and clay. Soils range widely in pH from extremely acidic to
moderately alkaline but are more commonly extremely acid to medium acid.
Soils supporting mesic prairie are very strongly acid to mildly alkaline loam or sandy loam and
occasionally silt loam with moderate water-retaining capacity. The soil profile often contains a B horizon
dominated by clay. Mesic prairies in Michigan occur on both mollisols, which are considered true prairie
soils, and udic alfisols, which cover much of southern Lower Michigan and are considered gray to brown
forest soils.
Soils are predominantly strongly acid to neutral sandy loam and occasionally loamy sand. The dry-mesic
to mesic condition of the sandy soils is facilitated by a relatively high water table and, in some sites, by
organic content within the sand matrix, which increases water-holding capacity. Mesic sand prairie
experiences seasonal water table fluctuations, with the wettest conditions occurring in spring and driest
periods in late summer and fall.
The community occurs on a variety of soil types, but loam is the predominant texture. Soils supporting
mesic southern forest include sand, sandy loam, loamy sand, loam, silt loam, silty clay loam, clay loam,
and clay. Soils are typically well-drained with high water-holding capacity and high nutrient and soil
organism content. High soil fertility is maintained by nutrient inputs from the decomposition of
deciduous leaves and coarse woody debris. Where American beech is dominant in the canopy, its leaf
litter can have a podzolizing effect on the soil, increasing the acidity. Soil pH ranges widely from slightly
acidic to moderately alkaline.
The organic soils of muskegs are composed of peat, which forms a continuous mat ranging in thickness
from one to eight meters but is typically one to three meters deep and overlays sand. The depth of peat
and soil moisture increases with peatland age and can vary within a site. Peat depth is typically greatest
near the center of a peatland and decreases toward the margin or in areas with groundwater influence.
The rooting zone within muskegs is quite shallow, typically confined to the uppermost 15 cm of the
surface peat, where there is sufficient oxygen to maintain aerobic respiration. The surface peats of
muskegs are dominated by saturated fibric peat, which is loosely compacted and spongy, contains
partially decomposed sphagnum moss with fragments of wood and occasionally sedge, and like the
surface water, is extremely acidic, cool, and characterized by low nutrient availability and low oxygen
263

Table 13. (cont’d)
Resource Community

Northern Bald

Northern Fen

Northern Hardwood
Swamp

Soils
levels. Peat composition changes with depth and varies with the successional history of a given peatland.
Generally, fiber content and hydraulic conductivity decrease with depth. Deep humidified peats can
effectively seal basins and create a perched water table.
The soils are thin, slightly acid sandy soil over bedrock. Areas of exposed bedrock that lack soil
development are common. Thin organic sediments accumulate in joints, cracks, and depressions and are
important substrates for vegetation.
The organic soils of northern fens are composed of peat and/or marl, which are typically one to three
meters deep. The surface peats may range from sapric to fibric, and like the surface water, are neutral to
alkaline and characterized by high cation availability. Northern fens are minerotrophic peatlands,
receiving constant inputs of cold groundwater that is rich in calcium and magnesium carbonates from
having moved over or percolated through base-rich bedrock or calcareous glacial deposits. Because
groundwater is the primary source of water input, the hydro-period of fens is relatively stable; the soils
remain saturated throughout the year but are seldom inundated by more than a few centimeters of
water. Northern fens often contain or develop on extensive areas of marl, a grayish, mineral substrate
with a smooth, silty texture that develops when metabolism by algae results in precipitation of calcium
carbonate. Areas containing marl deposits such as old glacial lakebeds are level and referred to as marl
flats. Shallow water supporting populations of marl-producing algae commonly overlays marl flats.
Dispersed throughout extensive areas of marl flats are low peat mounds or islands that support a
continuous carpet of sphagnum mosses and a full complement of bog and poor conifer swamp species.
The pH of peat islands is extremely acidic as a result of the reducing effect of sphagnum mosses and
raised elevation above the underlying calcareous groundwater.
Soils are poorly to very poorly drained and often consist of a shallow layer of muck (i.e., sapric peat)
overlaying mineral soil. The texture of mineral soils is most commonly fine sandy clay loam to fine loam
and an underlying impermeable clay lens is often present.

264

Table 13. (cont’d)
Resource Community
Northern Shrub
Thicket

Northern Wet
Meadow

Oak Barrens

Oak Openings
Oak-pine Barrens

Open Dunes

Soils
The soils of northern shrub thicket are wet to moist, nutrient-rich, well-decomposed sapric peat, or
occasionally mineral soil. The pH ranges widely from alkaline to acidic with medium acidity being the
most prevalent condition. The soils are characterized by high nutrient levels due to the nitrogen-fixing
ability of alder. Northern shrub thickets are non-stagnant wetlands with high levels of dissolved oxygen
and soil nitrogen. Soils range from poorly drained to well drained, with most sites remaining saturated
throughout the growing season. The community is typically flooded in spring.
Northern wet meadow typically occurs on organic soils such as well-decomposed sapric peat, but
saturated mineral soil may also support the community. Soil pH typically ranges from strongly acid to
neutral. Northern wet meadow occurs on more acidic soils compared to southern wet meadow, which is
found on neutral to strongly alkaline soils.
Characteristic soils of oak barrens are infertile, coarse-textured, well-drained sand or loamy sand with
medium to slightly acid pH and low water-retaining capacity. The drought soils contain little organic
matter and lack the fine-textured illuvial horizon associated with the richer and more productive soils of
the oak openings.
Soils of oak openings are well-drained, moderately fertile, sandy loams, or loams with slightly acid to
neutral pH and low to moderate water-retaining capacity.
Soils of oak-pine barrens are typically infertile, excessively well-drained sand or loamy sand with medium
to slightly acid pH and low water-retaining capacity. Soils range from coarse-textured loam sands on
moraines to very fine-textured sands on lakeplains. The soils contain little organic matter and are
droughty.
Dune sand consists largely of quartz (87-94%), with lesser amounts of feldspar (10-18%), magnetite (13%), and traces of other minerals, such as calcite, garnet, and hornblende. Sand particles are rounded
and frosted by continuous collisions with other sand grains. Because the sand contains calcareous
minerals, it is neutral to slightly alkaline.

265

Table 13. (cont’d)
Resource Community
Patterned Fen

Pine Barrens

Poor Conifer Swamp

Poor Fen

Soils
Peat (including fibric, hemic, and sapric peat) forms the substrate for both the strings and flarks of
patterned fen communities. Peat can be several meters deep (10 to 25 feet for Lake Agassiz peatlands of
Minnesota) and is derived from sedges, sphagnum mosses, reeds, and moderately decomposed woody
material. The saturated peat ranges from medium acid to circumneutral. The flarks tend to be wetter,
slightly acidic to circumneutral, and more minerotrophic than the strings, although nutrient availability
and pH can differ greatly both within and among patterned peatland systems. The amount of water in
the flarks also varies depending on local hydrology, precipitation, and season.
The soil is primarily excessively drained, very strongly to strongly acid sand, and relatively infertile. Thin
bands of finer textured soil (loamy sand to sandy clay loam) are often present near moraines or icecontact landforms. Such fine banding improves soil-water availability, resulting in more rapid tree
growth and a faster rate of succession to forest.
The organic soils of poor conifer swamps are composed of peat, which forms a continuous mat that can
be as little as 15 cm (6 in) deep but is often at least 40 cm (16 in) deep. The rooting zone within poor
conifer swamps is typically quite shallow, confined to the upper 15 cm (6 in) of the surface peat. Depth
of peat and soil moisture varies within a site. Peat depth is typically greatest near the center of a
peatland and decreases toward the peatland margin or in areas with groundwater influence. The surface
peats of poor conifer swamps are dominated by saturated fibric peat, which is loosely compacted and
spongy, contains partially decomposed sphagnum moss with fragments of wood and occasionally sedge,
and like the surface water, is extremely acidic, cool, and characterized by low nutrient availability and
oxygen levels.
The organic soils of poor fens are composed of peat, which frequently forms a shallow, continuous mat
ranging from one to three meters in depth. Organic soils near the surface are fibric peat and very
strongly to strongly acid with low nutrient availability. Low levels of groundwater input combined with
high water-retaining capacity of fibric peat produce continuously saturated conditions in the rooting
zone of poor fens. The water table of poor fens is stable, typically at the soil surface with soils remaining
saturated but seldom flooded. The surface waters of poor fens are characterized by very strong to strong
acidity, low available nutrients, low specific conductivity, cool temperatures, moderate levels of
dissolved organic matter, and anaerobic conditions.

266

Table 13. (cont’d)
Resource Community
Prairie Fen

Rich Conifer Swamp

Rich Tamarack Swamp

Sand and Gravel Beach

Soils
Prairie fen occurs on saturated organic soil and marl, a calcium carbonate (CaCO3) precipitate. Marl
deposits can accumulate to depths greater than one meter in lakes and shallow calcareous water as a
result of metabolism by algae. The organic soils are typically mildly alkaline, with marl deposits reaching
slightly higher levels of alkalinity. The soil profile of prairie fens often contains distinct zones of sedge
peat, woody peat, and marl. Thus, the organic deposits may change with depth throughout the soil
profile from fibric peat to hemic peat or well-decomposed sapric peat (muck) depending on a fen’s
successional history and past disturbance regime. The white- to grayish-colored marl may be present as
discrete, sometimes thick, bands within the soil profile or at the surface, where it may occupy small
pools surrounding groundwater springs, or cover extensive portions of a fen.
The soils are composed of saturated, coarse woody peat and may vary significantly in depth of organic
matter. The organic soils are typically neutral to moderately alkaline but may be very strongly acid near
the surface where sphagnum mosses dominate the ground layer. The structure and species composition
of rich conifer swamp are strongly influenced by the constant flow of mineral-rich, cold groundwater
through the organic soils.
The organic soils underlying rich tamarack swamp are typically comprised of deep (> 2.5 m) peat
containing large amounts of woody debris and occasionally layers of sedge-dominated peat. The soil
profile often contains or is underlain by marl, a calcium carbonate precipitate that accumulates as
sediment in shallow lake bottoms. Because glacial till in southern Michigan is typically high in calcium
and magnesium, the groundwater discharge into rich tamarack swamp has high levels of alkalinity and
dissolved calcium and magnesium carbonates.
The dynamic nature of open sand and gravel beaches greatly inhibits soil development. Uprooted trees
accumulate on some beaches, fostering localized sand accretion and often vegetation establishment.
Finer organic material also builds up seasonally on beaches, and can include plant debris, algae, and
dead lake or wetland organisms such as insects, fish, and zebra mussels (Dreissena polymorpha), a small
invasive bivalve mussel. These aggregations can be large, greatly increasing the nutrient availability and
changing the sediment characteristics of the beach, although these changes are often temporary due to
the dynamics of the shoreline environment. Storm waves and winter ice typically prevent permanent
vegetation establishment and soil development. Where organic sediments are protected from erosive
forces, vegetation can establish, stabilize the shoreline, and thus eliminate portions of the open beach.
267

Table 13. (cont’d)
Resource Community
Sandstone Bedrock
Lakeshore

Sandstone Cliff

Sandstone Cobble
Shore

Sandstone Lakeshore
Cliff

Sinkhole

Southern Hardwood
Swamp

Southern Shrub-carr

Soils
Almost no soil development occurs on the sandstone bedrock. Soil development and plant establishment
are limited to cracks, joints, and depressions in the bedrock where small amounts of sand and organic
matter accumulate. The breakdown of sandstone and plant matter results in an acidic, sandy, organicrich soil. Soil depth is shallow due to wave, wind, and ice action.
There is almost no soil development on the cliffs except for shallow organic soil development along the
narrow cliff summit and in crevices in the cliff face where sand particles, decaying roots, and plant debris
accumulate. The breakdown of sandstone and plant matter results in an acidic, sandy, organic-rich soil.
Little or no soil development occurs on sandstone cobble shore. The few plants that establish are rooted
in sand and gravel deposits under the coarse cobble. The size of the weathered and eroded sandstone
cobbles ranges from 2 to 3 cm (0.75 to 1.0 in) in diameter to over 20 cm (8 in) in diameter, and large
sandstone and conglomerate boulders or slabs can be common.
There is almost no soil development on the cliffs except for shallow organic soil development along the
narrow cliff summit and ledges, in crevices in the cliff face, and at the base of the cliff where sand
particles, decaying roots, and plant debris accumulate. The breakdown of sandstone and plant matter
results in an acidic, sandy, organic-rich soil.
The soils within most of Michigan’s karst features are derived from limestone or dolomite, and are thus
mildly to moderately alkaline and fine-textured. Some of the sinkholes in Montmorency, Otsego, and
Presque Isle Counties are overlain by outwash sands and support vegetation characteristic of acid sands
— no bedrock is exposed in these sinkholes.
Soils are typically loam or silt loam, sometimes sandy loam or clay loam, of neutral to mildly alkaline pH
(sandy substrates are more acidic), and sometimes covered by a thin layer of muck. An underlying
impermeable clay lens is often present and allows for prolonged pooling of water. Occasionally the
community occurs on deep sapric peat, especially inland, where stands may be associated with conifer or
hardwood-conifer, minerotrophic peatlands.
Shrub-carr is usually found on seasonally inundated, saturated organic soils such as sapric peat with
neutral to mildly alkaline pH and the capacity to retain excessive water.

268

Table 13. (cont’d)
Resource Community
Southern Wet
Meadow

Submergent Marsh

Volcanic Bedrock
Glade

Volcanic Bedrock
Lakeshore

Volcanic Cliff

Soils
Southern wet meadow typically occurs on neutral to strongly alkaline organic soils (i.e., sapric to hemic
peat), but saturated mineral soil may also support the community. Because of the calcareous nature of
the glacial drift in the regions where southern wet meadow occurs, its soils typically contain high levels
of calcium and magnesium.
Loose, poorly consolidated organic soils characterize most submergent plant beds, which can establish
on almost all types of mineral soil, and even over bedrock. Such organic soils can be meters thick and are
often easily eroded by boat traffic. In the more acid, low nutrient lakes, the accumulation of organic
sediments can be minimal, but this is quite variable. The pH of organic sediments can range from acid to
alkaline and is largely dependent on the pH of the lake or stream water and underlying mineral
substrate.
Continental glacial ice sheets from about 10,000 years ago left large areas of bedrock devoid of soil.
Some organic soil has developed in pockets and cracks within the volcanic rock, but there are also large
areas with no soil, where lichens and mosses are the predominant vegetation. The prevalent rock
formations are Precambrian-age Copper Harbor Conglomerates and Portage Lake Volcanics. The volcanic
rock formed from vast sheets of flowing lava, interbedded with thin layers of conglomerate, which
consisted of both pebbles and cobbles. Basalt, the predominant bedrock of the glades, ranges from
medium acid to mildly alkaline in ph. Arctic-alpine vegetation is more common on the conglomerate and
on volcanic rock characterized by many vesicles (vesicular basalt), which have more irregularities and
cracks for soil development and root anchoring, than on massive basalt, which typically lacks vesicles.
Almost no soil development takes place on either the massive, fine-grained basalts or the volcanic
conglomerates. The only places where plants are able to establish are in cracks, joints, vesicles, and
depressions in the bedrock, where small amounts of organic matter accumulate. Cracks, joints, and
depressions are much more abundant on the volcanic conglomerate, but still provide relatively few
places for soil development. Freshly broken rock surfaces are mildly alkaline in ph.
There is little soil development on the steep rock face of the cliffs. Some organic soil development occurs
in crevices in the rock face, on the upper lip of the cliffs, and at the base of the cliff face.

269

Table 13. (cont’d)
Resource Community
Volcanic Cobble Shore

Volcanic Lakeshore
Cliff
Wet Prairie

Wet-mesic Flatwoods

Wet-mesic Prairie

Wet-mesic Sand
Prairie
Wooded Dune and
Swale Complex

Soils
Little or no soil development occurs on volcanic cobble shore. The few plants that establish probably
root in sand and gravel deposits under the cobble, which can be more than a meter in depth. On the
Keweenaw Peninsula, the size of the cobbles ranges from 2 to 3 cm (0.75 to 1 in) in diameter to over 20
cm (8 in) in diameter, and large sections of the shoreline consist of similar-sized cobbles. The largest
cobbles are located at the extreme east end of the peninsula, where the cobble shoreline is steepest and
storm waves the most severe.
There is little soil development on the steep rock face of the cliffs. Some organic soil development occurs
in crevices in the rock face and on the upper lip of the cliffs.
Soils are typically sandy loam or silt loam but can also be silty clay or clay. Soils are characterized by
neutral pH, high organic content, and good water-retaining capacity. Organic deposits (muck) are absent
or form only a thin layer over mineral soil.
Surface soils are typically medium to slightly acid sandy loam to loam and overlay mildly to moderately
alkaline sandy clay loam, clay loam, or clay. An underlying impermeable clay lens is often present, which
allows for prolonged pooling of water. Seasonal water level fluctuations lead to mottling of the mineral
soil layers.
Soils are typically loam or silt loam and less frequently sandy loam, silty clay, or clay. Soils are
characterized by neutral pH, with high organic content, and good water-retaining capacity. Organic
deposits (muck) are absent or form only a thin layer over mineral soil.
Soils are loamy sand, loamy fine sand or fine sand and are typically strongly acid to neutral. Soils often
have high organic content, which increases water-holding capacity, and may be covered by a thin layer of
muck. A high water table contributes to the wet-mesic condition of the sandy soils.
Given the complexity and variation of wooded dune and swale complexes, soils can range from
calcareous sands in the foredunes to deep acidic peat or alkaline marl in well-established swales.

270

Soil Classification
Table 14. Soil moisture
Meters Below
Categories
Surface
0 meter or less
0 meter
Slightly
water
logged
0-1 meter
Moist areas
1 meter
1-2 meters
2 meters
2 meters or
greater
5 meters and
greater

Mesic-moist
areas
Mesic areas

Dry areas
Dry areas

Wet soil
Moist soil

Fen soil
Summer - partially drained but still wet, trees
grow on pedestals

Mesicmoist soil
Mesic soil

Summer – full drained in flat lands

Mesic soil

Activated during early spring, water input from
higher elevation

Dry soil
Dry soil
Very dry
soil

271

Appendix B: Simulation

Simulation Model Code, Results, Figures and Tables

272

Simulation Code – Visual Basic
'*****************************************************************************
'* Program: Foraging simulation
*
'* Language: Visual Basic for Applications with Microsoft Excel
*
'* Author: Jubin J. Cheruvelil
*
'* Date: 1/1/2011
*
'* Comments: This code runs a spatial simulation. The start or entry point *
'*
is the Main() routine. Main()routine calls the
*
'*
Select_Patch_Resources.The Select_Patch_Resources() calls two *
'*
key subroutines: Patch_Select() and Resource_Select().
*
'*
*
'*
*
'*****************************************************************************
Option Explicit
Option Base 1
'*****************************************************************************
'* Global Variables
*
'* Date: 1/1/2011
*
'*****************************************************************************
Dim Factor As Double
Dim Culture As String
Dim Cancel As Boolean
Dim Start_day As Integer
Dim End_day As Integer
Dim Patch_type As String
Dim Gender As String
Dim Resource As String
Dim Calories As String
Dim Current_family As String
Dim NumFamilies As Integer
Dim Unit_start As Integer
Dim Unit_end As Integer
Dim Family_start As Integer
Dim Family_end As Integer
Dim Member_start As String
Dim Member_end As String
Dim Member As Integer
Dim Runs As Integer
Dim Workbook_open As Boolean
Dim Uncertainty_Factor As Double
'*****************************************************************************
'############################################################################*
'* On Click commands
*
273

'* Date: 1/1/2011
*
'############################################################################*
'*****************************************************************************
Private Sub RunSim_Click()
Dim sheet As Worksheet
Set sheet = ActiveWorkbook.Sheets("Initialize_Params")
Call Main
End Sub
Private Sub StopSim_Click()
Cancel = True
Application.ActiveWorkbook.Save
End Sub
Private Sub Main()
'*****************************************************************************
'############################################################################*
'* Main routine, calls all other functions
*
'* Date: 1/1/2011
*
'############################################################################*
'*****************************************************************************
'check if cancel has been clicked from initialize worksheet
Workbook_open = 0
Cancel = False
If Cancel Then
Exit Sub
End If
'start program - begin with initialize, end with finalize
Call Initialize
Call Get_Patch_Resources
Call Finalize
End Sub
Private Sub Get_Patch_Resources()
'*****************************************************************************
'*****************************************************************************
'* Patch and Resource Main routine. Calls two key functions
*
'*
1. Calls Patch_Select & Resource_Select
*
'*
2. Sets up output files.
*
'* Date: 1/1/2011
*
'*****************************************************************************
'*****************************************************************************
Dim Season As String 'retrieved from Get_day_season routine
Dim Month As String 'retrieved from Get_day_season routine
Dim Current_season As String
Dim Current_month As String
Dim Date_exploit As Date 'retrieved from Get_day_season routine
274

Dim i As Integer
Dim j As Integer
Dim k As Integer
Dim h As Integer
Dim g As Integer
Dim C_short As String
Dim Family_unit As Integer
Dim Member_gender As String
Dim PatchArray(3) As Variant
Dim Cultural_period(3) As Variant
Dim result As Variant
Dim Sim As Workbook
Dim Output_open As Boolean
Dim Output_row As Long
Dim Workbook_path As String
Dim sheet As Worksheet
Dim Wkbook_Name_Path As String
Dim Wkbook_name As String
Dim Wksheet_Name As String
Dim Wksheet_create As Boolean
'Set up culture array
Cultural_period(1) = "Late Archaic"
Cultural_period(2) = "Early Woodland"
Cultural_period(3) = "Middle Woodland"
'Setup the code workbook
Set Sim = Workbooks("Simulation Workbook.xlsm")
'Sim.Activate
Workbook_path = Sim.path & "\"
Calculate
Call Get_values("Simulation Workbook.xlsm")
'Setup output workbook for each simulation.
'Output_open = True
Output_open = False
If Output_open = False Then
Dim OutputWkb As Workbook
Wkbook_Name_Path = AddNew_Wkbook(C_short, Workbook_path, Wkbook_name)
Set OutputWkb = Workbooks(Wkbook_name)
OutputWkb.Activate
Output_open = True
End If
'Set output_row to keep track of output sheet row
Output_row = 2
275

For g = LBound(Cultural_period) To UBound(Cultural_period)
'Start logic to loop through runs, days, family units etc.
Wksheet_create = True
If Wksheet_create Then
Select Case Cultural_period(g)
Case "Late Archaic"
C_short = "LA"
Case "Early Woodland"
C_short = "EW"
Case Else
C_short = "MW"
End Select
Wksheet_Name = AddNew_Wksheet(Wkbook_name, C_short, g)
End If
For h = 0 To Runs
'Reactivate code workbook
Sim.Activate
'Loop through each day in the calendar for annual cycle.
'Start at day 1 and end at day 365.
For i = Start_day To End_day
Debug.Print "Day" & i
Date_exploit = Get_day_season(i, Current_season, _
Current_month, Sim.Name)
Season = Current_season
Month = Current_month
'Loop through each family unit. Each member selects resources.
For j = Unit_start To Unit_end
Debug.Print "Family Unit: " & j
Family_unit = j
Call Patch_Select(h, Sim.Name, Month, Culture, Arr:=PatchArray)
' Reselect patch when with each new family unit.
' Reset family unit to first unit.
For k = Member_start To Member_end
'Sim.Activate
'Set Member_Gender
Member_gender = LookupGender(Sim.Name, j, k)
'Selects resources, returns current row for output sheet.
'MsgBox Uncertainty_Factor
Output_row = Resource_Select(Wkbook_name, Wksheet_Name, _
h, i, j, Season, Month, Member_gender, _
Output_row, Sim.Name, Uncertainty_Factor, _
276

Arr:=PatchArray)
Next k
Next j
Next i
Next h
Next g
End Sub
'*****************************************************************************
'* Function Name: Get all constant values stored in worksheet
*
'* Date: 1/1/2011
*
'* Comments: this function is called from any function.
*
'*
*
'*****************************************************************************
Sub Get_values(Wkbook_name As String)
Dim sheet As Worksheet
Dim Workbk As Workbook
Set Workbk = Workbooks(Wkbook_name)
Set sheet = Workbk.Sheets("Initialize_Params")
'Selects time period of simulation. Time period determines the number and
' patch type available for exploitation.
Culture = sheet.Cells(3, 6)
Start_day = sheet.Cells(3, 2)
End_day = sheet.Cells(4, 2)
Runs = sheet.Cells(5, 2)
NumFamilies = sheet.Cells(7, 2)
Factor = sheet.Cells(18, 2)
Unit_start = sheet.Cells(8, 2)
Unit_end = sheet.Cells(9, 2)
Member_start = sheet.Cells(10, 2)
Member_end = sheet.Cells(11, 2)
Uncertainty_Factor = sheet.Cells(18, 2)
End Sub
'*****************************************************************************
'* Function Name: Get all family members of a band unit
*
'* Date: 1/1/2011
*
'* Comments: this function is called from any function.
*
'*
*
'*****************************************************************************
Private Sub Get_Family(Wkbook_name)
Dim Member As Integer
Dim row_num As Integer
Dim sheet As Worksheet
277

Dim Workbook As Workbook
Set Workbook = Workbooks("wkbook_name")
Set sheet = Workbook.Sheets("Family_Unit")
row_num = Application.WorksheetFunction.Match(1, sheet.Range("C1:C21"), 0)
Current_family = sheet.Cells(row_num, 1)
Gender = sheet.Cells(row_num, 2)
End Sub
'*****************************************************************************
'* Function Name: Finalize Simulation
*
'* Date: 1/1/2011
*
'* Comments: this function is called from any function.
*
'*
*
'*****************************************************************************
Private Sub Finalize()
Application.Calculation = xlCalculationAutomatic
Application.ScreenUpdating = True
End Sub
'*****************************************************************************
'* Function Name: AddNew Workbook
*
'* Date: 1/1/2011
*
'* Comments: this function can be called from any function.
*
'*
*
'*****************************************************************************
Function AddNew_Wkbook(Culture As String, path As String, ByRef Wkbook_name) As String
Dim Newbook As Workbook
Dim Name As String
Dim C_short As String
Dim Date_string As String
Dim Time_string As String
Date_string = Format(Now(), "yyyymmdd")
Time_string = Format(Time(), "HHMM")
On Error Resume Next
Name = Culture & "SimRun" & Date_string & "_" & Time_string & ".xls"
Set Newbook = Workbooks.Add ' Create a new WorkBook
With Newbook
.Title = "Behavioral Simulation"
.Subject = "Output"
.SaveAs Filename:=path & Name
End With
Wkbook_name = Name
AddNew_Wkbook = path & Name
End Function
278

'*****************************************************************************
'* Function Name: AddNew Worksheet
*
'* Date: 1/1/2011
*
'* Comments: this function can be called from any function.
*
'*
*
'*****************************************************************************
Function AddNew_Wksheet(Wkbook_name As String, C_short As String, _
Run As Integer) As String
Dim Newsheet As Worksheet
Dim OutputWkbook As Workbook
Dim Name As String
Dim Time_string As String
On Error Resume Next
Time_string = Format(Time(), "HHMM")
Name = C_short & Run & "_" & Time_string
Set OutputWkbook = Workbooks(Wkbook_name)
'OutputWkbook.Activate
Set Newsheet = OutputWkbook.Sheets.Add(After:=Sheets(Worksheets.Count))
Newsheet.Name = Name
AddNew_Wksheet = Name
End Function
'*****************************************************************************
'* Function Name: Close Workbook
*
'* Date: 1/1/2011
*
'* Comments: this function can be called from any function.
*
'*
*
'*****************************************************************************
Sub Close_output(Output As String)
Workbooks(Output).Activate
ActiveWorkbook.Close True
' closes the active workbook and saves any changes
End Sub
Sub Initialize()
'*****************************************************************************
'* Initialize subroutine, called from Main()
*
'* Date: 1/1/2011
*
'*****************************************************************************
Dim sheet As Worksheet
Dim Culture As String
Application.Calculation = xlCalculationManual
Application.ScreenUpdating = False
Application.EnableEvents = True
End Sub
279

'*****************************************************************************
'* Function Name: Get_day_season
*
'* Support routines, called from Main()
*
'* Date: 1/1/2011
*
'*****************************************************************************
Function Get_day_season(Day_current As Integer, ByRef Season_current _
As String, ByRef Month_Current As String, Wkbook As String) As Date
Dim row_num As Integer
Dim Workbk As Workbook
Dim sheet As Worksheet
Set Workbk = Workbooks(Wkbook)
Set sheet = Workbk.Sheets("Month_Day") '
'Application.Calculation = xlCalculationManual
'sheet.Select
'Get initial values from initialize parameters worksheet.
row_num = Application.WorksheetFunction.Match(Day_current, _
sheet.Range("A1:A367"), 1)
Get_day_season = sheet.Cells(row_num, 3)
Season_current = sheet.Cells(row_num, 5)
Month_Current = sheet.Cells(row_num, 4)
End Function
'*****************************************************************************
'* Function Name: LookupGender
*
'* Date: 1/1/2011
*
'* Support routine
*
'*****************************************************************************
Function LookupGender(Wkbook As String, Unit_No As Integer, Member_No As Integer) As
String
'Declare variables in function.
Dim range1 As Range
Dim range2 As Range
Dim Combo As Variant
Dim Workbk As Workbook
Set Workbk = Workbooks(Wkbook)
Dim sheet As Worksheet
Set sheet = Workbk.Sheets("Family_Unit")
Set range1 = sheet.Range("D2:D26")
Set range2 = sheet.Range("E2:E26")
Combo = Unit_No & Member_No
LookupGender = _
sheet.Application.WorksheetFunction.Lookup(Combo, range1, range2)
On Error Resume Next
End Function
280

'*****************************************************************************
'* Function Name: Patch_Selection
*
'* Date: 1/1/2011
*
'* Comments: this function is called from (). Function selects
*
'*
the most productive patch in a given season
*
'*
*
'*****************************************************************************
Function Patch_Select(Run As Integer, Wkbook_name As String, Month As String, Culture As
String, _
Arr As Variant) As Variant
Dim sheet As Worksheet
Dim sheetname As String
Dim range1 As Variant
Dim range2 As Range
Dim range3 As Range
Dim range4 As Range
Dim range6 As Range
Dim range7 As Range
Dim range8 As Range
Dim range9 As Range
Dim range10 As Range
Dim Col_curr_patch As Integer
Dim ColumnStart As Variant
Dim N As Long
Dim row As Double
Dim rowx As Double
Dim wrkbook As Workbook
'Set worksheet as the patch sheet.
Set wrkbook = Workbooks(Wkbook_name)
Set sheet = wrkbook.Sheets("Patch")
Set range1 = sheet.Range("B51:B55")
Set range8 = sheet.Range("A7:AX34") 'for autofilter
Select Case Month
Case "January"
Set range2 = sheet.Range("O50:O56")
Set range9 = sheet.Range("P50:P56")
Set range10 = sheet.Range("Q50:Q56")
Case "February"
Set range2 = sheet.Range("R50:R56")
Set range9 = sheet.Range("S50:S56")
281

Set range10 = sheet.Range("T50:T56")
Case "March"
Set range2 = sheet.Range("U50:U56")
Set range9 = sheet.Range("V50:V56")
Set range10 = sheet.Range("W50:W56")
Case "April"
Set range2 = sheet.Range("X50:X56")
Set range9 = sheet.Range("Y50:Y56")
Set range10 = sheet.Range("Z50:Z56")
Case "May"
Set range2 = sheet.Range("AA50:AA56")
Set range9 = sheet.Range("AB50:AB56")
Set range10 = sheet.Range("AC50:AC56")
Case "June"
Set range2 = sheet.Range("AD50:AD56")
Set range9 = sheet.Range("AE50:AE56")
Set range10 = sheet.Range("AF50:AF56")
Case "July"
Set range2 = sheet.Range("AG50:AG56")
Set range9 = sheet.Range("AH50:AH56")
Set range10 = sheet.Range("AI50:AI56")
Case "August"
Set range2 = sheet.Range("AJ50:AJ56")
Set range9 = sheet.Range("AK50:AK56")
Set range10 = sheet.Range("AL50:AL56")
Case "September"
Set range2 = sheet.Range("AM50:AM56")
Set range9 = sheet.Range("AN50:AN56")
Set range10 = sheet.Range("AO50:AO56")
Case "October"
Set range2 = sheet.Range("AP50:AP56")
Set range9 = sheet.Range("AQ50:AQ56")
Set range10 = sheet.Range("AR50:AR56")
Case "November"
Set range2 = sheet.Range("AS50:AS56")
282

Set range9 = sheet.Range("AT50:AT56")
Set range10 = sheet.Range("AU50:AU56")
Case "December"
Set range2 = sheet.Range("AV50:AW56")
Set range9 = sheet.Range("AW50:AX56")
Set range10 = sheet.Range("AX50:AY56")
Case Else
End Select
'*****************************************************************************
*
' Autofilter code start: selects top X number of a list or table.
*
'*****************************************************************************
*
'clear the destination of autofilter copy
sheet.Range("$A$50:$AZ$60").Clear
'Select top 5 patches to be exploited
'Get relative column for field value
Col_curr_patch = range2.Column
'Selection.AutoFilter
range8.AutoFilter _
Field:=Col_curr_patch, Criteria1:="5", _
Operator:=xlTop10Items
With range8
On Error Resume Next
Set range6 = .Offset(1).Resize(.Rows.Count - 1, 1) _
.SpecialCells(xlCellTypeVisible)
End With
If range6 Is Nothing Then
MsgBox "No data to copy"
Else
Set range7 = range8
range7.Offset(1, 0).Resize(range7.Rows.Count - 1).Copy _
Destination:=sheet.Range("A51")
End If
sheet.ShowAllData
range8.AutoFilter
sheet.Rows("2:6").EntireRow.Hidden = True
'*****************************************************************************
*
' Autofilter code end: selects top X number of a list or table
*
283

'*****************************************************************************
*
ColumnStart = Split(Cells(, range2.Column).Address, "$")(1)
range2(10).Formula = "=sum(" & ColumnStart & "51:" & _
ColumnStart & "55)"
'Set up relative probability
'fill relative yield - O column
With range9
.Cells(2).Select
.Cells(1) = "RelativeProb"
.Cells(2).Formula = "=" & ColumnStart & "51" & "/" & _
"$" & ColumnStart & "$59"
ColumnStart = Split(Cells(, range9.Column).Address, "$")(1)
Selection.AutoFill Destination:=Range(ColumnStart & "51:" & _
ColumnStart & "55"), Type:=xlFillDefault
End With

'fill cumulative probability column
'ColumnStart = Split(Cells(, range10.Column).Address, "$")(1)
With range10
.Cells(1).Value = "CumulativeProb"
.Cells(2).Value = 0
.Cells(3).Formula = "=sum(" & ColumnStart & "$51:$" & _
ColumnStart & "51)"
.Cells(3).Select
ColumnStart = Split(Cells(, range10.Column).Address, "$")(1)
Selection.AutoFill Destination:=Range(ColumnStart & "52:" & _
ColumnStart & "55"), Type:=xlFillDefault
End With
'sheet.Calculate
Range("A50:AX60").Calculate
'Select one or three different patches for exploitation based on productivity
'Return three patches back to calling routine
For N = LBound(Arr) To UBound(Arr)
Dim patch_sel_temp As Variant
Dim Randomnumber As Double
Dim nos_patch As Integer
'Initialize randomize number - generates duplicates
'Rnd (-1)
'Randomize 10
Randomnumber = Rnd
284

'Find a row where random number matches the cumulative probability
' of that patch
row = sheet.Application.WorksheetFunction.Match(Randomnumber, range10, 1)
If row = 0 Then
row = RandomNum(1, 5)
' MsgBox "no row"
' End
End If
patch_sel_temp = sheet.Application.WorksheetFunction.Index(range1, row)
'If row = 0 Then
' MsgBox "no patch"
' End
'End If
Arr(N) = patch_sel_temp
'Degrade the patch after selecting the resources.
Select Case Culture
Case "Late Archaic"
Set range3 = Range("B79:B107")
Set range4 = Range(Cells(79, 7 + Run), Cells(107, 7 + Run))
If Run = 0 Then
range4(1) = "Run: " & Run
End If
rowx = sheet.Application.WorksheetFunction.Match(patch_sel_temp, range3, 0)
rowy = range4(rowx).row
columny = range4.Column + Run
nos_patch = sheet.Cells(rowy, columny).Value
sheet.Cells(rowy, columny).Value = nos_patch + 1
Case "Early Woodland"
Set range3 = Range("B110:B138")
Set range4 = Range(Cells(110, 7 + Run), Cells(138, 7 + Run))
If Run = 1 Then
range4(1) = "Run: " & Run
End If
rowx = sheet.Application.WorksheetFunction.Match(patch_sel_temp, range3, 0)
rowy = range4(rowx).row
columny = range4.Column + Run
nos_patch = sheet.Cells(rowy, columny).Value
sheet.Cells(rowy, columny).Value = nos_patch + 1
Case "Middle Woodland"
Set range3 = Range("B141:B169")
Set range4 = Range(Cells(141, 7 + Run), Cells(169, 7 + Run))
285

If Run = 1 Then
range4(1) = "Run: " & Run
End If
rowx = sheet.Application.WorksheetFunction.Match(patch_sel_temp, range3, 0)
rowy = range4(rowx).row
columny = range4.Column + Run
nos_patch = sheet.Cells(rowy, columny).Value
sheet.Cells(rowy, columny).Value = nos_patch + 1
Case Else
End Select
'At times, the array is not populated for some reason - resolve later.
If Arr(N) = "" Then
Arr(1) = "SHRUB SWAMP/EMERGENT MARSH"
Arr(2) = "Intermitten Wetlands"
Arr(3) = "RIVER"
End If
Next N
Set range1 = Nothing
Set range2 = Nothing
Set range6 = Nothing
Set range7 = Nothing
Set range9 = Nothing
Set range10 = Nothing
End Function
'*****************************************************************************
'* Function Name: Resource_Selection
*
'* Date: 1/1/2011
*
'* Comments: this function is called from Patch_Resources().
*
'*
Function selects the resources in a given season
*
'*
*
'*****************************************************************************
Function Resource_Select(Wkbook_name As String, Wksheet_Name As String, _
Run As Integer, Day As Integer, Unit As Integer, _
Season As String, Month As String, _
Gender As String, _
Output_row As Long, SimName As String, _
Uncertainty_Factor As Double, Arr As Variant) As Long
Dim sheet As Worksheet
Dim sheetname As String
Dim range1 As Variant
Dim range2 As Range
Dim range3 As Range
286

Dim range4 As Range
Dim range5 As Range
Dim range6 As Range
Dim range7 As Range
Dim Randomnumber As Double
Dim N As Integer
Dim row As Double
Dim Total_calories As Long
Dim Column As Integer
Dim TotCaloricPotential As Long
Dim MinCaloricPotential As Long
Dim MinCalories As Long
Dim patch_sel_temp As String
Dim Patch_status As Boolean
Dim Calories_collected As Long
Dim Total_yield As Long 'Max # of calories in @month@patch
Dim Resource_selected As String
Dim Resource_calories As Long 'Calorie yield of resource selected
Dim Resource_category As String
Dim Resource_prob As Long
Dim Workbook_open As Boolean
Dim Current_row As Long
Dim Common_name As String
Dim Exploit_no As Integer
Dim ProbCapture As Double
Dim M_F_Pref As Double
Dim Wkbook As Workbook
'Select month_season of exploitation
Set Wkbook = Workbooks(SimName)
Select Case Month
Case "January"
Set sheet = Wkbook.Sheets(Month & "_patch")
Case "February"
Set sheet = Wkbook.Sheets(Month & "_patch")
Case "March"
Set sheet = Wkbook.Sheets(Month & "_patch")
Case "April"
Set sheet = Wkbook.Sheets(Month & "_patch")
Case "May"
Set sheet = Wkbook.Sheets(Month & "_patch")
Case "June"
Set sheet = Wkbook.Sheets(Month & "_patch")
Case "July"
287

Set sheet = Wkbook.Sheets(Month & "_patch")
Case "August"
Set sheet = Wkbook.Sheets(Month & "_patch")
Case "September"
Set sheet = Wkbook.Sheets(Month & "_patch")
Case "October"
Set sheet = Wkbook.Sheets(Month & "_patch")
Case "November"
Set sheet = Wkbook.Sheets(Month & "_patch")
Case "December"
Set sheet = Wkbook.Sheets(Month & "_patch")
Case Else
Set sheet = Wkbook.Sheets(Month & "_patch")
End Select
sheet.Activate
Set range1 = sheet.Range("AG181:AG201") 'Prob of capture
Set range2 = sheet.Range("AH181:AH201") 'Gender probability
Set range3 = sheet.Range("AI181:AI201") 'Capture probability
Set range4 = sheet.Range("AJ181:AJ201") 'Cumulative total yield
Set range5 = sheet.Range("AK181:AK201") 'Cumulative probabilty
Set range6 = sheet.Range("A181:A201") 'Resource lookup column
Set range7 = sheet.Range("E1:AF1")
'reset output row first time in a run
For N = LBound(Arr) To UBound(Arr)
'Determine the patch being exploited
patch_sel_temp = Arr(N)
'MsgBox patch_sel_temp
'determine column where relevant patch is located.
'Add four to range value when referencing it without the range.
Column = sheet.Application.WorksheetFunction.Match(patch_sel_temp, _
range7, 0) + 4
'Determine total yield of resources @month@patch
Total_yield = sheet.Cells(2, Column).Value
Call SetupProbGrid(SimName, sheet.Name, patch_sel_temp, Column, Gender)
Calories_collected = 0
Patch_status = True
Exploit_no = 0
'Select resource until forager collects required calories or patch is degraded _
or three exploitative activities are undertaken.
'Randomly select resources based on cumululative probability
288

Do Until (Calories_collected > 10000 Or Patch_status = False _
Or Exploit_no = 4)
If Calories_collected > (Total_yield * 0.3) Then
Patch_status = False
End If
'Randomize 12345
Randomnumber = Rnd()
'Find a row where random number matches the cumulative probability
' of that patch
sheet.Calculate
row = sheet.Application.WorksheetFunction.Match _
(Randomnumber, range5, 1)
If row > 10 Then
row = RandomNum(1, 10)
End If
Resource_selected = sheet.Application.WorksheetFunction.Index _
(range6, row)

Resource_calories = Range("C181:C201")(row, 1)
If Gender = "Child" Then
Resource_calories = Resource_calories * 0.4
End If
Resource_category = Range("D181:D201")(row, 1)
Common_name = Range("B181:B201")(row, 1)
ProbCapture = range1(row, 1)
M_F_Pref = range2(row, 1)
Randomnumber = Rnd
If Randomnumber > Uncertainty_Factor Then
Resource_calories = 0
End If
Calories_collected = Calories_collected + Resource_calories

'missing values - uncertainty factor,
Output_row = Output_record(Wkbook_name, Wksheet_Name, Month, Run, Day, Unit, _
Season, Output_row, _
Gender, patch_sel_temp, Resource_selected, Resource_category, _
Common_name, Randomnumber, Resource_calories, Calories_collected, _
Uncertainty_Factor, ProbCapture, M_F_Pref)
289

'Send back current row to calling routine.
Resource_Select = Output_row
Exploit_no = Exploit_no + 1
Loop
Next N
Set range1 = Nothing
Set range2 = Nothing
Set range3 = Nothing
Set range4 = Nothing
Set range5 = Nothing
Set range6 = Nothing
Set range7 = Nothing
End Function
'*****************************************************************************
'* Function Name: SetupProbGrid()
*
'* Date: 1/1/2011
*
'* Comments: Function sets up the relative cumulative probability grid for *
'*
stochastic selection of resources
*
'*****************************************************************************
Sub SetupProbGrid(Wkbook_name As String, sheet_patch As String, patch_name As String, _
Column As Integer, Gender As String)
Dim Workbk
Dim sheet As Worksheet
Dim columnletter As String
Dim range1 As Range
Dim range6 As Range
Dim range7 As Range
Set Workbk = Workbooks(Wkbook_name)
Set sheet = Workbk.Sheets(sheet_patch)
Set range1 = sheet.Range("A3:AF170") 'for autofilter
columnletter = Split(Cells(, Column).Address, "$")(1)
'*****************************************************************************
*
' Autofilter code start: selects top X number of a list or table.
*
'*****************************************************************************
*
'Select top 10 resources to be exploited
'clear autofilter copy destination
sheet.Range("A180:AL202").Clear
'Get relative column for field value
'Col_curr_patch = range2.Column
290

range1.AutoFilter _
Field:=Column, Criteria1:="10", _
Operator:=xlTop10Items
'Copy it down to new Application
'Recalculate total value
'reinitialize cumulative probability
With range1
On Error Resume Next
Set range6 = .Offset(1, 0).Resize(.Rows.Count - 1, 1) _
.SpecialCells(xlCellTypeVisible)
'On Error GoTo 0
End With
If range6 Is Nothing Then
MsgBox "No data to copy"
Else
Set range7 = range1
range7.Copy Destination:=sheet.Range("A181")
range7.Offset(1, 0).Resize(range7.Rows.Count - 1).Copy _
Destination:=sheet.Range("A181")
End If
sheet.ShowAllData
range1.AutoFilter
'*****************************************************************************
*
' Autofilter code end: selects top X number of a list or table
*
'*****************************************************************************
*
'fill probability of capture
Dim range2 As Range
Set range2 = Range("AG180:AG190")
With range2
.Cells(1).Value = "ProbCapture"
.Cells(2).Formula = _
"=INDEX(Resource!$BB$2:$BB$169, MATCH($A181,Resource!$F$2:$F$169,0))"
.Cells(2).Select
.Cells(2).NumberFormat = "0.000"
.Cells(2).AutoFill Destination:=Range("AG181:AG190"), Type:=xlFillDefault
End With
'fill in net or base yield once a resource is captured.
Dim range2A As Range
Set range2A = Range("C180:C190")
291

With range2A
.Cells(1).Value = "Base Yield"
.Cells(2).Formula = "=INDEX(Resource!$BC$2:$BC$169,
MATCH($A181,Resource!$F$2:$F$169,0))"
.Cells(2).Select
.Cells(2).NumberFormat = "0.0"
.Cells(2).AutoFill Destination:=Range("C181:C190"), Type:=xlFillDefault
End With
'fill in gender preference
Dim range3 As Range
Set range3 = Range("AH180:AH190")
With range3
.Cells(1).Value = "M_F Pref"
If Gender = "Female" Then
.Cells(2).Formula = _
"=INDEX(Resource!$T$2:$T$169, MATCH($A181,Resource!$F$2:$F$169,0))"
Else
.Cells(2).Formula = _
"=INDEX(Resource!$S$2:$S$169, MATCH($A181,Resource!$F$2:$F$169,0))"
End If
.Cells(2).Select
.Cells(2).NumberFormat = "0.000"
.Cells(2).AutoFill Destination:=Range("AH181:AH190"), Type:=xlFillDefault
End With
'fill in cumulative yield of calories with capture and gender preference
Dim range4 As Range
Set range4 = Range("AI180:AI190")
Range("AI179").Formula = "=sum(AI181:AI190)"
With range4
.Cells(1).Value = "CumulativeProb"
.Cells(2).Formula = "=$AG181*$AH181*" & "$" & columnletter & "181"
.Cells(2).Select
.Cells(2).NumberFormat = "0.00"
.Cells(2).AutoFill Destination:=Range("AI181:AI190"), Type:=xlFillDefault
End With
'fill relative yield
Dim range5 As Range
Set range5 = Range("AJ180:AJ190")
With range5
.Cells(1).Value = "RelProbability"
292

'.Cells(2).Formula = "=(AI181/$AI$179)*100"
.Cells(2).Formula = "=(AI181/$AI$179)"
.Cells(2).Select
.Cells(2).NumberFormat = "0.00"
.Cells(2).AutoFill Destination:=Range("AJ181:AJ190"), Type:=xlFillDefault
End With
'fill cumulative probability column
Dim range9 As Range
Set range9 = Range("AK180:AK190")
With range9
.Cells(1).Value = "CumulativeProb"
.Cells(2).Value = 0
.Cells(3).Formula = "=SUM(AJ$181:$AJ181)"
.Cells(3).Select
.Cells(2).NumberFormat = "0.00"
.Cells(3).AutoFill Destination:=Range("AK182:AK190"), _
Type:=xlFillDefault
End With
Range("A180:AL191").Calculate
'sheet.calculate
Set range9 = Nothing
Set range5 = Nothing
Set range4 = Nothing
Set range3 = Nothing
Set range2 = Nothing
Set range2A = Nothing
Set range1 = Nothing
Set range6 = Nothing
Set range7 = Nothing
End Sub
'*****************************************************************************
'* Function Name: Put record into output sheet.
*
'* Date: 1/1/2011
*
'* Comments: this function is called from Select_resource()
*
'*
*
'*****************************************************************************
Function Output_record(Wkbook As String, Wksheet As String, Month As String, _
Run As Integer, Day As Integer, Unit As Integer, _
Season As String, Current_row As Long, _
Gender As String, Patch_selected As String, _
Resource_selected As String, Resource_category As String, _
Common_name As String, Randomnumber As Variant, _
Calorie_yield As Long, _
293

Total_calories As Long, Uncertainty_Factor As Double, _
ProbCapture As Double, M_F_Pref As Double) As Long
Dim OutputWkbook As Workbook
Dim OutputSheet As Worksheet
Dim Updated_row As Long
'On Error Resume Next
Set OutputWkbook = Workbooks(Wkbook)
Set OutputSheet = OutputWkbook.Worksheets(Wksheet)
If Current_row = 1000 Then
OutputWkbook.Save
End If
If Current_row = 2 Then
OutputSheet.Cells(Current_row - 1, 1).Value = "Run #"
OutputSheet.Cells(Current_row - 1, 2).Value = "Day"
OutputSheet.Cells(Current_row - 1, 3).Value = "Month"
OutputSheet.Cells(Current_row - 1, 4).Value = "Season"
OutputSheet.Cells(Current_row - 1, 5).Value = "Unit"
OutputSheet.Cells(Current_row - 1, 6).Value = "Gender"
OutputSheet.Cells(Current_row - 1, 7).Value = "Patch_selected"
OutputSheet.Cells(Current_row - 1, 8).Value = "Resource_selected"
OutputSheet.Cells(Current_row - 1, 9).Value = "Resource_category"
OutputSheet.Cells(Current_row - 1, 10).Value = "Common_name"
OutputSheet.Cells(Current_row - 1, 11).Value = "Rand"
OutputSheet.Cells(Current_row - 1, 12).Value = "Calorie_yield"
OutputSheet.Cells(Current_row - 1, 13).Value = "Total_calories"
OutputSheet.Cells(Current_row - 1, 14).Value = "Uncertainty_Factor"
OutputSheet.Cells(Current_row - 1, 15).Value = "ProbCapture"
OutputSheet.Cells(Current_row - 1, 16).Value = "M_F_Preference"
End If
OutputSheet.Cells(Current_row, 1).Value = Run
OutputSheet.Cells(Current_row, 2).Value = Day
OutputSheet.Cells(Current_row, 3).Value = Month
OutputSheet.Cells(Current_row, 4).Value = Season
OutputSheet.Cells(Current_row, 5).Value = Unit
OutputSheet.Cells(Current_row, 6).Value = Gender
OutputSheet.Cells(Current_row, 7).Value = Patch_selected
OutputSheet.Cells(Current_row, 8).Value = Resource_selected
OutputSheet.Cells(Current_row, 9).Value = Resource_category
OutputSheet.Cells(Current_row, 10).Value = Common_name
294

OutputSheet.Cells(Current_row, 11).Value = Randomnumber
OutputSheet.Cells(Current_row, 12).Value = Calorie_yield
OutputSheet.Cells(Current_row, 13).Value = Total_calories
OutputSheet.Cells(Current_row, 14).Value = Uncertainty_Factor
OutputSheet.Cells(Current_row, 15).Value = ProbCapture
OutputSheet.Cells(Current_row, 16).Value = M_F_Pref
Output_record = Current_row + 1 'add row identifier
End Function
'*****************************************************************************
'* Function Name: Generate Random numbers between 2 values
*
'* Date: 1/1/2011
*
'* Comments: this function is called from any function.
*
'*
*
'*****************************************************************************
Function RandomNum(Low As Double, High As Double)
RandomNum = (High - Low) * Rnd() + Low
End Function

295

Simulation Variables
Table 15. Hunter-gatherer family unit composition
Id
Unit No. Member No. Gender
1
1
1 Male
2
1
2 Female
3
1
3 Female
4
1
4 Child
5
1
5 Child
6
2
1 Male
7
2
2 Female
8
2
3 Male
9
2
4 Female
10
2
5 Female
11
3
1 Male
12
3
2 Female
13
3
3 Female
14
3
4 Child
15
3
5 Child
16
4
1 Female
17
4
2 Female
18
4
3 Female
19
4
4 Female
20
4
5 Female
21
5
1 Male
22
5
2 Male
23
5
3 Male
24
5
4 Male
25
5
5 Male

296

Table 16: Species size, abundance and density
Common Name

Species

Size

Abundance

White-tailed Deer
Black bear
Wolf, dog
Moose
Wapiti/Elk
Red fox
Raccoon
Otter
Bobcat
Squirrel
Fisher
Shrew
Marten
Mouse
Vole
Beaver
Muskrat
Woodchuck
Chipmunk
Mink
Porcupine
Mice/Rats
Rabbits
Great Horned Owl
Common Loon
Hooded merganser

Odocoileus virginianus
Ursus americanus
Canis sp. (lupus, familiaris)
Alces alces
Cervus canadensis
Vulpes fulva
Procyon lotor
Lontra canadensis
Lynx rufus
Sciurus sp.
Martes pennanti
Blarina sp.
Martes americana
Peromyscus sp.
Microtus sp.
Castor canadensis
Ondatra zibethicus
Marmota monax
Tamias sp.
Mustela vison
Erethizon dorsatum
Muridae sp.
Leporidae sp. (Sylvilagus)
Bubo virginianus
Gavia immer
Lophodytes cucullatus

Large
Large
Medium
Large
Large
Small
Medium
Small
Medium
Small
Small
Small
Small
Small
Small
Medium
Small
Small
Small
Small
Small
Small
Small
Medium
Medium
Medium

Low
Low
Low
Low
Low
Low
Low
Low
Low
Low
Low
Low
Low
Low
Low
Medium
Low
Low
Low
Low
Low
Low
Medium

297

0.0080
Low
Low

Density (square mile)
0 < 1.
0
0
0
0
1
0
0
1
1
2
4
4
6
10
10
15
16
16
20
22
30
40
50
1
3
22

Table 16. (cont’d)
Common Name

Species

Size

Blue-winged teal
Mallard
Common merganser
Crow
Sandhill crane
Wild turkey
Baldpate, widgeon
Red-breasted merganser
Pied-billed grebe
Ring-necked duck
Greater Scaup
American Bittern
Passenger Pigeon
Great Blue Heron
Bluegill
Yellow perch (ringed, striped or jack
perch, green hornet)
Burbot (Cod)
White bass/Hybrid striped bass
Channel catfish (spotted, speckled
or silver catfish)
Walleye pike (marble-eyes, 'eye,
walter, walleyed pike, jack, jackfish,
pickerel)
Black bullhead (common bullhead,
horned pout)
Sucker

Anas discors
Anas platyrhynchos
Mergus merganser
Corvus brachyrhynchos
Grus canadensis
Meleagris gallopavo
Anas americana
Mergus serrator
Podilymbus podiceps
Aythya collaris
Aythya marila
Botaurus lentiginosus
Ectopistes migratorius
Ardea herodias
Lepomis cf. macrochirus
Perca flavescens

Small
Medium
Medium
Small
Large
Large
Small
Medium
Medium
Medium
Small
Small
Small
Large
Medium
Medium

Lota lota lacustris
Monroe chrysops
Ictalurus punctatus

Abundance

Medium
Medium

26
13
22
4
14
21
92
22
3
37
93
55
67
86
20
7

Medium
Medium
Medium

High
Medium
Medium

3
19
16

Stizostedion vitreum

Medium

Medium

4

Ictalurus melas

Medium

Medium

7

Catostomus sp. (catostomus,

Medium

Medium

11

298

0.6720
0.1650

Density (square mile)
0 < 1.

Low
0.1570
Low
Medium
0.2380
Low
Low
0.2100
0.0150
0.2460
High
0.1280

Table 16. (cont’d)
Common Name

Sturgeon
Largemouth bass (black bass, green
bass, green trout, slough bass)
Longnosed gar
Smallmouth bass (bronzeback,
brown or redeye bass, redeye,
white or mountain trout)
Crappie
Sauger (also Sander canadensis)
Black crappie
Lake trout (togue, mackinaw, great
gray trout, laker)
Redhorse
Sunfish
Yellow bullhead (white-whiskered
bullhead, yellow cat)
Bowfin (dogfish, grindle, mudfish,
cypress trout, lake lawyer, beaver
fish)
Northern Pike (pickerel, jack, gator,
hammerhandle, snot rocket)
Brown bullhead (marbled or
speckled bullhead, red cat)
Drumfish (sheepshead, croaker,
thunderpumper, grinder, bubbler)

Species

Size

Abundance

commersoni)
Acipenser fulvescens
Micropterus salmoides

Large
Medium

Medium
Medium

15
14

Lepisosteus oculatus
Micropterus dolomieui

Medium
Medium

Medium
Medium

13
11

Pomoxis sp.
Stizostedion canadense
Pomoxis nigromaculatus
Salvelinus namaycush

Medium
Medium
Medium
Medium

Medium
Medium
Medium
Medium

22
18
1
11

Moxostoma sp.
(macrolepidotum)
Centrarchidae
Ictalurus natalis

Medium

Medium

7

Medium
Medium

Medium
Medium

4
20

Amia calva

Medium

Medium

25

Esox lucius

Medium

Medium

9

Ictalurus nebulosus

Medium

Medium

4

Aplodinotus grunniens

Medium

Medium

6

299

Density (square mile)
0 < 1.

Table 16. (cont’d)
Common Name

Species

Size

Northern water snake
Garter snake
Frogs and toads
Blanding's turtle
Painted turtle
Snapping turtle
Softshell turtles
mollusk
Gastropod - three-ridge valvata
Sedge or grass
Sedge or grass
Sedge or grass
Cattail
Dock
Flatsedge
Wild or False Lily-of-the-Valley
Aster
Spreading Dogbane
Wild Bergamot
Anise-root
May-apple, Mandrake
Dandelion
Wild Geranium, spotted cranesbill
Bindweed

Nerodia sipedon
Thamnophis sp.
Anura sp.
Emydoidea blandingii
Chrysemys picta
Chelydra serpentina
Trionyx sp.
Generic
Generic
Carex lupulina
Carex pensylvanica
Carex blanda
Typha latifolia
Rumex spp.
Cyperus
Maianthemum canadense
Aster cordifolius
Apocynum androsaemifolium
Monarda fistulosa
Osmorhiza longistylis
Podophyllum peltatum
Taraxacum officinale
Geranium maculatum
Convolvulus arvensis
300

cluster
individual
cluster
cluster
cluster
cluster
cluster
cluster

Abundance
Low
Low
Low
Low
Medium
Low
Low
Low
Medium
High
High
High
High
High
High
High
High
High
High
High
High
High
High
High

Density (square mile)
0 < 1.
7
3
1
6
1
6
5
10
15
12
3
17
2
24
7
14
6
13097
13097
13097
13097
13097
13097
13097

Table 16. (cont’d)
Common Name

Species

Wild Basil, Dogmint
Sumac
Panic-grass
June grass, Kentucky Bluegrass,
Speargrass, Fowl Bluegrass
Carrion Flower Greenbriar
Golden rod
Early Meadow- rue Quicksilverweed
Smooth Yellow Violet
Common Blue Violet

Satureja vulgaris
Rhus glabra
Panicum spp.
Poa pratensis

High
High
High
High

Smilax lasioneura
Solidago Sp.
Thalictrum dioicum

High
High
High

Viola pensylvanica
Viola sororia (Sens. Lat.)
(Glabrous plants like this one
have been referred to V.
Papilionacea)
Lilium michiganense
Smilax cirrata
Aquilegia canadensis

High
High

Aralia nudicaulis
Barbarea vulgaris
Geum canadense
Trillium grandiflorum
Lithospermum canescens
Silphium terebinthinaceum
Ostraya virginiana
Platanus occidentalis
Polygala senega

High
High
High
High
High
High
High
High
High

Michigan Lily
Greenbrier
Wild columbine, Rock-bells,
Meetinghouses, honey suckle
Wild sarsaparilla
Yellow rocket
White Avens
Large Flowered Trillium
Hoary Puccoon
Prairie-dock; Rosin-weed
Hophornbeam
Sycamore
Snakeroot (medicinal)

Size

301

Abundance

High
High
High

Density (square mile)
0 < 1.
13097

Table 16. (cont’d)
Common Name

Species

Sassafras
St. John's wort (medicinal)
Dogwood
Mint
Northern swamp dogwood
Swamp rose
Poison Ivy
Fringed Loosestrife
Prickly-ash
False Solomon's Seal
Three-leaved False Solomon's Seal
Sensitive fern
Wild cherry
Huckleberry
Mustard
Stickyweed
American elderberry
Serviceberry/Shadbush

Sassafras albidum
Hypericum
Cornus rugosa
Lamiaceae
Cornus racemosa
Rosa palustris
Toxicodendron radicans
Lysimachia ciliata
Zanthoxylum americanum
Smilacina racemosa
Smilacina stellata
Onoclea Sensibilis
Prunus Virginiana
Gaylussacia baccata
Brassicaceae sp.
Galium aparine
Sambucus canadensis
Amelanc (Amelanchier
Medikus)
Prunus serotina
Celtis occidentalis
Vitis riparia
Viburnum sp.
Fragaria virginiana
Rubus occidentalis
Cucurbita pepo
Physalis

Black cherry
Hackberry
Grape(Riverbank grape)
Nannyberry
Wild strawberry
Black Raspberry
Squash
Cape Gooseberry

Size

302

Abundance

Density (square mile)
0 < 1.

High
High
High
High
High
High
High
High
High
High
High
High
High
High
High
High
High
High

5
5
5
5
5
5

High
High
High
High
High
High
High
High

46
85
1881
3091
3091
9686
13097
13097

Table 16. (cont’d)
Common Name

Species

Knotweed
Maize
Sumpweed (Iva annua)
Wild rice
Amaranth
Woodland Sunflower
Goosefoot(quinoa)
American Chestnut
Black Walnut
Shellbark Hickory
Hazelnut
Shagbark Hickory
Butternut/white walnut
Hickory
Oak/acorn
American beech
Mulberry
Hawthorn

Polygonum pensylvanicum
Zea mays
Iva annua
Zizania aquatica
Amaranthus hypochondriacus
Helianthus divaricatus
Chenopodium
Castanea dentata
Juglans nigra
Carya laciniosa
Corylus americana
Carya ovata
J. cinerea
Carya
Quercus nigra
Fagus americana
Morus rubra

Swamp White Oak
Red Oak
Black Maple
Hog-peanut
Black Oak
Pine
Slippery Elm
Elm

Size

Crataegus calpodendron
Quercus bicolor
Quercus rubra
Acer nigrum
Amphicarpaea bracteata
Quercus kelloggii
Pinus banksiana Lamb
Ulmus rubra
Ulmus americana
303

cluster
cluster
cluster
cluster
cluster
cluster
cluster
cluster
cluster
cluster
cluster
cluster
cluster
cluster

Abundance
High
High
High
High
High
High
High
High
High
High
High
High
High
High
High
High
High
High
High
High
High
High
High
High
High
High

Density (square mile)
0 < 1.
19152
13097
13097
13097
13097
13097
19865
5
5
5
5
23
23
68
854
875
3
3
4
854
3913
13097

Table 16. (cont’d)
Common Name

Species

Eastern Redbud
American Basswood
Poplar/cottonwood
White Ash
Sweet Birch
White Spruce
Mountain ash
Pear

Size

Cercis canadensis
Tilia americana
Populus tremuloides
Fraxinus americana
Betula lenta
Picea glauca
Sorbus americana
Pyrus sp.

Abundance
High
High
High
High
High
High
High

304

Density (square mile)
0 < 1.

Table 17. Simulation species weight and calorie yield
Common Name

Avg. Cal. /Lb.

White-tailed Deer
Black bear
Wolf, dog
Moose
Wapiti/Elk
Red fox
Raccoon
Otter
Bobcat
Squirrel
Fisher
Shrew
Marten
Mouse
Vole
Beaver
Muskrat
Woodchuck
Chipmunk
Mink
Porcupine
Mice/Rats
Rabbits
Great Horned Owl
Common Loon
Hooded merganser
Blue-winged teal
Mallard
Common merganser
Crow
Sandhill crane
Wild turkey
Baldpate, widgeon
Red-breasted merganser
Pied-billed grebe
Ring-necked duck
Greater Scaup
American Bittern

537
717
1185
500
496
601
1017
601
601
601
601
601
601
601
601
664
732
601
601
601
601
601
512
701
701
701
701
955
701
701
701
711
701
701
701
701
701
701
305

Avg. Weight
150
300
59
850
600
11
20
20
25
1.25
7
0.0312
2.18
0.046
0.08125
40
18
8
0.1875
1.875
14
0.5
2.8
3
9
1.4
0.8
2.4
3.4
1
8
12
1.6
2.3
1
1.5
1.5
1.5

Total Calorie
Yield
886
21510
13445
425000
297600
6611
20340
12020
15025
751.25
4207
18.7512
1310.18
27.646
48.83125
26560
13176
4808
112.6875
1126.875
8414
300.5
1433.6
1051.5
18927
21590.8
14808.625
29796
52434.8
2804
78512
179172
103187.2
35470.6
2103
38905.5
97789.5
57832.5

Table 17. (cont’d)
Common Name

Avg. Cal. /Lb.
239
701
401
412

1
3
3

1221
37677
20640

398

2

3184

401

0.3215

902.4505

401
476
661

2
20
3

8822
142800
27762

400
661

3
3

15600
21813

401
401
401
539

0.75
1
0.75
8

6616.5
7218
300.75
47432

401
401
401

5
0.5
1

14035
802
8020

401

3

30075

398

3

10746

401

1

1604

401
306

0.37
5.3
0.44
0.5

Total Calorie
Yield
5924.81
319515.8
3528.8
1442

407
661
430

Passenger Pigeon
Great Blue Heron
Bluegill
Yellow perch (ringed, striped or jack
perch, green hornet)
Burbot (Cod)
White bass/Hybrid striped bass
Channel catfish (spotted, speckled or
silver catfish)
Walleye pike (marble-eyes, 'eye, walter,
walleyed pike, jack, jackfish, pickerel)
Black bullhead (common bullhead,
horned pout)
Sucker
Sturgeon
Largemouth bass (black bass, green bass,
green trout, slough bass)
Longnosed gar
Smallmouth bass (bronzeback, brown or
redeye bass, redeye, white or mountain
trout)
Crappie
Sauger (also Sander canadensis)
Black crappie
Lake trout (togue, mackinaw, great gray
trout, laker)
Redhorse
Sunfish
Yellow bullhead (white-whiskered
bullhead, yellow cat)
Bowfin (dogfish, grindle, mudfish, cypress
trout, lake lawyer, beaver fish)
Northern Pike (pickerel, jack, gator,
hammerhandle, snot rocket)
Brown bullhead (marbled or speckled
bullhead, red cat)
Drumfish (sheepshead, croaker,

Avg. Weight

3

7218

Table 17. (cont’d)
Common Name

Avg. Cal. /Lb.

thunderpumper, grinder, bubbler)
Northern water snake
Garter snake
Frogs and toads
Blanding's turtle
Painted turtle
Snapping turtle
Softshell turtles
mollusk
Gastropod - three-ridge valvata
Sedge or grass
Sedge or grass
Sedge or grass
Cattail
Dock
Flatsedge
Wild or False Lily-of-the-Valley
Aster
Spreading Dogbane
Wild Bergamot
Anise-root
May-apple, Mandrake
Dandelion
Wild Geranium, spotted cranesbill
Bindweed
Wild Basil, Dogmint
Sumac
Panic-grass
June grass, Kentucky Bluegrass,
Speargrass, Fowl Bluegrass
Carrion Flower Greenbriar
Golden rod
Early Meadow- rue Quicksilver-weed
Smooth Yellow Violet
Common Blue Violet
Michigan Lily
Greenbrier

Avg. Weight

Total Calorie
Yield

421.755
421.755
331.055
403.615
403.615
403.615
403.615
60
7
113
113
113
113
113
113
195.005
195.005
195.005
195.005
195.005
195.005
195.005
10
10
10
195.005
195.005
195.005

1687.02
843.51
993.165
2018.075
403.615
807.23
2018.075
600
7
20340
21357
40341
4746
187128
49042
9945.255
1560.04
3705.095
9750.25
16965.435
6240.16
3900.1
670
400
120
7410.19
11505.295
13650.35

195.005
195.005
195.005
195.005
195.005
195.005
195.005
307

4
2
3
5
1
2
5
10
1
15
63
21
21
69
62
51
8
19
50
87
32
20
67
40
12
38
59
70
88
96
9
26
94
89
53

17160.44
18720.48
1755.045
5070.13
18330.47
17355.445
10335.265

Table 17. (cont’d)
Common Name

Avg. Cal. /Lb.
195.005

308

Total Calorie
Yield
14
2730.07

195.005
195.005
195.005
195.005
195.005
195.005
195.005
195.005
10
10
10
10
10
10
10
10
10
10
10
10
10
145.12
167.795
163.26
145.12
331.055
353.73
145.12
145.12
399.08
145.12
145.12
281.17
2450
194
1587.25
1601

Wild columbine, Rock-bells,
Meetinghouses, honey suckle
Wild sarsaparilla
Yellow rocket
White Avens
Large Flowered Trillium
Hoary Puccoon
Prairie-dock; Rosin-weed
Hophornbeam
Sycamore
Snakeroot (medicinal)
Sassafras
St. John's wort (medicinal)
Dogwood
Mint
Northern swamp dogwood
Swamp rose
Poison Ivy
Fringed Loosestrife
Prickly-ash
False Solomon's Seal
Three-leaved False Solomon's Seal
Sensitive fern
Wild cherry
Huckleberry
Mustard
Stickyweed
American elderberry
Serviceberry/Shadbush
Black cherry
Hackberry
Grape(Riverbank grape)
Nannyberry
Wild strawberry
Black Raspberry
Squash
Cape Gooseberry
Knotweed
Maize

Avg. Weight

25
97
70
6
86
56
37
6
23
12
28
18
40
91
50
72
54
5
61
22
84
4
1
10
6
10
5
2
6
6
2
9
9
6
10
3
3

4875.125
18915.485
13650.35
1170.03
16770.43
10920.28
7215.185
1170.03
230
120
280
180
400
910
500
720
540
50
610
220
840
580.48
167.795
1632.6
870.72
3310.55
1768.65
290.24
870.72
2394.48
290.24
1306.08
2530.53
14700
1940
4761.75
4803

Table 17. (cont’d)
Common Name

Avg. Cal. /Lb.

Sumpweed (Iva annua)
Wild rice
Amaranth
Woodland Sunflower
Goosefoot(quinoa)
American Chestnut
Black Walnut
Shellbark Hickory
Hazelnut
Shagbark Hickory
Butternut/white walnut
Hickory
Oak/acorn
American beech
Mulberry
Hawthorn
Swamp White Oak
Red Oak
Black Maple
Hog-peanut
Black Oak
Pine
Slippery Elm
Elm
Eastern Redbud
American Basswood
Poplar/cottonwood
White Ash
Sweet Birch
White Spruce
Mountain ash
Pear

1601
1601
1601
2500
1668
965.955
2798.095
2979.495
2847.98
2979.495
2775.42
2775.42
1755.045
2612.16
195.005
195.005
20
20
1500
195.005
20
400
400
400
400
400
400
400
400
1500
195.005
195.005

309

Avg. Weight
8
9
8
3
8
5
7
7
2
5
5
7
8
4
10
3
9
8
7
1
1
1
10
9
1
5
3
2
6
7
6
6

Total Calorie
Yield
12808
14409
12808
7500
13344
4829.775
19586.665
20856.465
5695.96
14897.475
13877.1
19427.94
14040.36
10448.64
1950.05
585.015
180
160
10500
195.005
20
400
4000
3600
400
2000
1200
800
2400
10500
1170.03
1170.03

Table 18. Male and female resource preference probabilities
Common Name

Male Preference

White-tailed Deer
Black bear
Wolf, dog
Moose
Wapiti/Elk
Red fox
Raccoon
Otter
Bobcat
Squirrel
Fisher
Shrew
Marten
Mouse
Vole
Beaver
Muskrat
Woodchuck
Chipmunk
Mink
Porcupine
Mice/Rats
Rabbits
Great Horned Owl
Common Loon
Hooded merganser
Blue-winged teal
Mallard
Common merganser
Crow
Sandhill crane
Wild turkey
Baldpate, widgeon
Red-breasted merganser
Pied-billed grebe
Ring-necked duck
Greater Scaup
American Bittern
Passenger Pigeon

0.681
0.709
0.671
0.812
0.871
0.378
0.622
0.344
0.41
0.383
0.467
0.408
0.578
0.336
0.462
0.561
0.499
0.63
0.416
0.447
0.358
0.636
0.632
0.634
0.629
0.488
0.548
0.599
0.504
0.654
0.459
0.531
0.557
0.633
0.444
0.622
0.448
0.471
0.475
310

Female Preference
0.214
0.188
0.003
0.182
0.006
0.335
0.559
0.388
0.581
0.609
0.466
0.443
0.355
0.653
0.56
0.458
0.626
0.478
0.386
0.493
0.343
0.474
0.582
0.435
0.642
0.386
0.414
0.446
0.664
0.514
0.523
0.523
0.435
0.339
0.656
0.465
0.594
0.358
0.399

Table 18. (cont’d)
Common Name

Male Preference

Great Blue Heron
Bluegill
Yellow perch (ringed, striped or jack perch, green
hornet)
Burbot (Cod)
White bass/Hybrid striped bass
Channel catfish (spotted, speckled or silver catfish)
Walleye pike (marble-eyes, 'eye, walter, walleyed
pike, jack, jackfish, pickerel)
Black bullhead (common bullhead, horned pout)
Sucker
Sturgeon
Largemouth bass (black bass, green bass, green
trout, slough bass)
Longnosed gar
Smallmouth bass (bronzeback, brown or redeye
bass, redeye, white or mountain trout)
Crappie
Sauger (also Sander canadensis)
Black crappie
Lake trout (togue, mackinaw, great gray trout,
laker)
Redhorse
Sunfish
Yellow bullhead (white-whiskered bullhead, yellow
cat)
Bowfin (dogfish, grindle, mudfish, cypress trout,
lake lawyer, beaver fish)
Northern Pike (pickerel, jack, gator,
hammerhandle, snot rocket)
Brown bullhead (marbled or speckled bullhead, red
cat)
Drumfish (sheepshead, croaker, thunderpumper,
grinder, bubbler)
Northern water snake
Garter snake
Frogs and toads
311

Female Preference

0.347
0.833
0.788

0.521
0.245
0.1

0.982
0.778
0.959
0.715

0.3
0.287
0.24
0.016

0.82
0.777
0.672
0.973

0.04
0.138
0.188
0.036

0.729
0.742

0.076
0.047

0.773
0.789
0.81
0.869

0.153
0.23
0.31
0.158

0.829
0.95
0.831

0.057
0.049
0.318

0.975

0.252

0.928

0.04

0.984

0.239

0.732

0.277

0.549
0.396
0.448

0.435
0.414
0.619

Table 18. (cont’d)
Common Name

Male Preference

Blanding's turtle
Painted turtle
Snapping turtle
Softshell turtles
mollusk
Gastropod - three-ridge valvata
Sedge or grass
Sedge or grass
Sedge or grass
Cattail
Dock
Flatsedge
Wild or False Lily-of-the-Valley
Aster
Spreading Dogbane
Wild Bergamot
Anise-root
May-apple, Mandrake
Dandelion
Wild Geranium, spotted cranesbill
Bindweed
Wild Basil, Dogmint
Sumac
Panic-grass
June grass, Kentucky Bluegrass, Speargrass, Fowl
Bluegrass
Carrion Flower Greenbriar
Golden rod
Early Meadow- rue Quicksilver-weed
Smooth Yellow Violet
Common Blue Violet
Michigan Lily
Greenbrier
Wild columbine, Rock-bells, Meetinghouses, honey
suckle
Wild sarsaparilla
Yellow rocket
White Avens
312

Female Preference

0.574
0.471
0.542
0.628
0.22
0.141
0.095
0.172
0.186
0.227
0.173
0.013
0.164
0.014
0.071
0.254
0.148
0.066
0.192
0.233
0.217
0.248
0.204
0.175
0.059

0.561
0.535
0.381
0.338
0.958
0.905
0.823
0.81
0.784
0.937
0.864
0.91
0.715
0.85
0.944
0.828
0.827
0.827
0.84
0.689
0.703
0.774
0.896
0.717
0.929

0.195
0.21
0.311
0.043
0.323
0.238
0.331
0.158

0.867
0.974
0.706
0.812
0.743
0.824
0.789
0.852

0.196
0.186
0.039

0.697
0.975
0.936

Table 18. (cont’d)
Common Name

Male Preference

Large Flowered Trillium
Hoary Puccoon
Prairie-dock; Rosin-weed
Hophornbeam
Sycamore
Snakeroot (medicinal)
Sassafras
St. John's wort (medicinal)
Dogwood
Mint
Northern swamp dogwood
Swamp rose
Poison Ivy
Fringed Loosestrife
Prickly-ash
False Solomon's Seal
Three-leaved False Solomon's Seal
Sensitive fern
Wild cherry
Huckleberry
Mustard
Stickyweed
American elderberry
Serviceberry/Shadbush
Black cherry
Hackberry
Grape(Riverbank grape)
Nannyberry
Wild strawberry
Black Raspberry
Squash
Cape Gooseberry
Knotweed
Maize
Sumpweed (Iva annua)
Wild rice
Amaranth
Woodland Sunflower
Goosefoot(quinoa)

0.127
0.036
0.088
0.319
0.074
0.042
0.208
0.1
0.307
0.206
0.194
0.263
0.022
0.307
0.158
0.321
0.13
0.006
0.17
0.151
0.161
0.019
0.332
0.162
0.112
0.151
0.147
0.19
0.112
0.009
0.011
0.123
0.096
0.087
0.009
0.113
0.133
0.063
0.137
313

Female Preference
0.748
0.861
0.856
0.719
0.746
0.858
0.683
0.806
0.767
0.995
0.718
0.757
0.701
0.84
0.91
0.969
0.808
0.762
0.972
0.675
0.893
0.823
0.965
0.886
0.787
0.883
0.715
0.734
0.861
0.676
0.979
0.981
0.923
0.783
0.952
0.827
0.988
0.811
0.826

Table 18. (cont’d)
Common Name

Male Preference

American Chestnut
Black Walnut
Shellbark Hickory
Hazelnut
Shagbark Hickory
Butternut/white walnut
Hickory
Oak/acorn
American beech
Mulberry
Hawthorn
Swamp White Oak
Red Oak
Black Maple
Hog-peanut
Black Oak
Pine
Slippery Elm
Elm
Eastern Redbud
American Basswood
Poplar/cottonwood
White Ash
Sweet Birch
White Spruce
Mountain ash
Pear

0.227
0.035
0.226
0.243
0.282
0.243
0.277
0.139
0.018
0.25
0.144
0.218
0.103
0.211
0.066
0.085
0.264
0.171
0.324
0.315
0.032
0.041
0.276
0.103
0.115
0.277
0.308

314

Female Preference
0.711
0.708
0.786
0.754
0.749
0.963
0.68
0.763
0.971
0.811
0.744
0.88
0.74
0.677
0.697
0.706
0.973
0.925
0.791
0.779
0.785
0.954
0.775
0.939
0.685
0.947
0.812

Table 19. Resource probability matrix January to July
Common Name
White-tailed Deer
Black bear
Wolf, dog
Moose
Wapiti/Elk
Red fox
Raccoon
Otter
Bobcat
Squirrel
Fisher
Shrew
Marten
Mouse
Vole
Beaver
Muskrat
Woodchuck
Chipmunk
Mink
Porcupine
Mice/Rats
Rabbits
Great Horned Owl
Common Loon
Hooded merganser

January
0.85
0.008
0.65
0.87
0.59
0.97
0.27
0.19
0.80
0.98
0.32
0.78
0.96
0.044
0.34
0.61
0.67
0.16
0.024
0.18
0.32
0.31
0.46
0.92
0.75
0.92

February

March
0.69
0.075
0.93
0.65
0.80
0.91
0.67
0.91
0.83
0.95
0.61
0.55
0.97
0.98
0.60
0.16
0.49
0.76
0.98
0.92
0.22
0.79
1.00
0.94
0.37
0.97

April
0.63
0.097
0.92
0.57
0.67
0.91
0.82
0.99
0.32
0.93
0.97
0.95
0.90
0.95
0.67
0.77
0.76
0.96
0.92
1.00
0.88
0.19
0.92
0.90
0.19
0.29

315

May
1.00
0.096
0.96
0.83
0.96
0.97
0.91
0.95
0.73
0.93
0.98
1.00
0.93
0.92
0.66
0.74
0.97
0.92
0.95
0.95
0.99
0.71
0.93
0.91
0.96
0.13

1.00
0.95
0.92
0.90
0.95
0.52
0.96
0.75
0.40
0.98
0.45
0.96
0.38
0.12
0.33
0.87
0.99
0.93
0.14
0.99
0.97
0.77
0.92
0.75
0.11
0.39

June

July
0.95
0.95
0.75
0.95
0.94
0.40
0.91
0.74
0.90
0.95
0.25
0.96
0.89
0.44
0.56
0.34
0.94
1.00
0.95
0.82
0.94
0.43
0.98
0.23
0.27
0.62

0.90
0.95
0.85
0.63
0.93
0.43
0.96
0.48
0.52
0.96
0.69
0.99
0.97
0.49
0.27
0.56
0.96
0.91
0.93
0.88
0.84
0.61
0.98
0.77
0.29
0.64

Table 19. (cont’d)
Common Name
Blue-winged teal
Mallard
Common merganser
Crow
Sandhill crane
Wild turkey
Baldpate, widgeon
Red-breasted merganser
Pied-billed grebe
Ring-necked duck
Greater Scaup
American Bittern
Passenger Pigeon
Great Blue Heron
Bluegill
Yellow perch (ringed, striped
or jack perch, green hornet)
Burbot (Cod)
White bass/Hybrid striped
bass
Channel catfish (spotted,
speckled or silver catfish)
Walleye pike (marble-eyes,
'eye, walter, walleyed pike,
jack, jackfish, pickerel)
Black bullhead (common
bullhead, horned pout)

January

February

March

April

May

June

July

0.39
0.11
0.82
0.14
0.36
0.43
0.80
0.89
0.74
0.14
0.86
0.66
0.12
0.47
0.54
0.20

0.34
0.22
0.12
1.00
0.30
0.81
0.86
0.50
0.57
0.55
0.60
0.63
0.74
0.30
0.77
0.50

0.78
0.93
0.33
0.98
0.54
0.53
0.94
0.93
0.61
0.99
0.30
0.93
0.59
0.97
0.42
0.96

0.92
0.95
0.73
0.98
1.00
0.59
0.94
0.97
0.99
0.91
0.40
0.44
0.92
0.91
0.92
0.99

0.91
0.94
0.95
0.91
0.90
0.17
0.36
1.00
0.72
0.35
0.34
0.83
0.96
0.98
0.92
0.48

0.92
0.99
0.98
0.93
0.91
0.44
0.73
0.89
0.57
0.77
0.47
0.56
0.97
0.34
0.96
0.80

0.93
0.27
0.82
0.35
0.80
0.23
0.33
0.24
0.43
0.20
0.94
0.50
0.95
0.42
0.48
0.40

0.95
0.88

0.97
0.83

0.70
0.93

0.89
0.97

0.56
0.98

0.44
0.96

0.83
0.26

0.71

0.32

0.37

0.80

0.57

0.99

0.92

0.61

0.63

0.90

0.97

0.67

0.64

0.16

0.35

0.13

0.88

0.96

0.97

0.97

0.24

316

Table 19. (cont’d)
Common Name
Sucker
Sturgeon
Largemouth bass (black bass,
green bass, green trout,
slough bass)
Longnosed gar
Smallmouth bass
(bronzeback, brown or
redeye bass, redeye, white
or mountain trout)
Crappie
Sauger (also Sander
canadensis)
Black crappie
Lake trout (togue,
mackinaw, great gray trout,
laker)
Redhorse
Sunfish
Yellow bullhead (whitewhiskered bullhead, yellow
cat)
Bowfin (dogfish, grindle,
mudfish, cypress trout, lake
lawyer, beaver fish)
Northern Pike (pickerel, jack,
gator, hammerhandle, snot
rocket)

January

February

March

April

May

June

July

0.82
0.15
0.20

0.36
0.61
0.55

0.16
0.25
0.41

0.93
0.97
0.49

0.90
0.94
0.95

0.28
0.96
0.95

0.19
0.55
0.48

0.65
0.20

0.13
0.14

0.90
0.19

0.40
0.30

0.67
0.98

0.32
0.95

0.18
0.40

0.65
0.60

0.65
0.49

0.34
0.89

0.79
0.98

0.97
0.94

0.98
0.99

0.51
0.76

0.24
0.39

0.12
0.16

0.81
0.87

0.94
0.58

0.99
0.64

0.95
0.44

0.32
0.63

0.66
0.58
0.37

0.70
0.42
0.90

0.44
0.70
0.14

0.38
0.69
0.79

0.93
0.95
0.76

0.98
0.93
0.97

0.54
0.91
0.94

0.31

0.56

0.79

0.48

0.54

0.25

0.26

0.22

0.26

0.94

0.93

0.87

0.62

0.51

317

Table 19. (cont’d)
Common Name
Brown bullhead (marbled or
speckled bullhead, red cat)
Drumfish (sheepshead,
croaker, thunderpumper,
grinder, bubbler)
Northern water snake
Garter snake
Frogs and toads
Blanding's turtle
Painted turtle
Snapping turtle
Softshell turtles
mollusk
Gastropod - three-ridge
valvata
Sedge or grass
Sedge or grass
Sedge or grass
Cattail
Dock
Flatsedge
Wild or False Lily-of-theValley
Aster
Spreading Dogbane
Wild Bergamot

January

February

March

April

May

June

July

0.71

0.22

0.44

0.70

0.50

0.91

0.98

0.43

0.76

0.18

0.54

0.96

0.94

0.44

0.092
0.089
0.018
0.027
0.008
0.011
0.054
0.058
0.037

0.047
0.026
0.039
0.098
0.06
0.029
0.055
0.058
0.096

0.055
0.039
0.021
0.082
0.06
0
0.001
0.055
0.062

0.472
0.32
0.071
0.078
0.071
0.097
0.6
0.271
0.746

0.118
0.646
0.832
0.941
0.933
0.395
0.635
0.574
0.79

0.306
0.111
0.922
0.611
0.97
0.571
0.816
0.90
0.93

0.475
0.594
0.486
0.893
0.807
0.556
0.423
0.98
0.91

0.004
0.096
0.04
0.63
0.052
0.072
0

0.08
0.085
0
0.65
0.025
0.051
0.042

0.009
0.025
0.089
0.44
0.025
0.077
0.027

0.052
0.024
0.007
0.48
0.028
0.001
0.073

0.063
0.066
0.066
0.39
1.00
0.025
0.96

1.00
0.97
0.98
0.92
0.95
0.033
0.95

0.94
0.95
0.95
1.00
0.94
0.91
0.93

0.075
0.099
0.061

0.052
0.063
0.016

0.033
0.086
0.027

0.07
0.013
0.085

0.036
0.013
0.068

0.009
0.086
0.007

0.028
0.069
0.088

318

Table 19. (cont’d)
Common Name
Anise-root
May-apple, Mandrake
Dandelion
Wild Geranium, spotted
cranesbill
Bindweed
Wild Basil, Dogmint
Sumac
Panic-grass
June grass, Kentucky
Bluegrass, Speargrass, Fowl
Bluegrass
Carrion Flower Greenbriar
Golden rod
Early Meadow- rue
Quicksilver-weed
Smooth Yellow Violet
Common Blue Violet
Michigan Lily
Greenbrier
Wild columbine, Rock-bells,
Meetinghouses, honey
suckle
Wild sarsaparilla
Yellow rocket
White Avens
Large Flowered Trillium

January

February

March

April

May

June

July

0.084
0.076
0.037
0.082

0.057
0.023
0.048
0.096

0.045
0.07
0.098
0.049

0.093
0.094
0.082
0.008

0.021
0.045
0.013
0.032

0.085
0.027
0.023
0.054

0.078
0.007
0.046
0.03

0.012
0.021
0.068
0.064
0.034

0.068
0.016
0.038
0.04
0.093

0.022
0.091
0.033
0.026
0.084

0.062
0.03
0.94
0.004
0.015

0.043
0.096
0.97
0.042
0.029

0.048
0.066
0.857
0.94
0.97

0.068
0.065
1.00
0.98
0.99

0.015
0.03
0.097

0.08
0.097
0.096

0.021
0.044
0.095

0.07
0.043
0.008

0.099
0.087
0.543

0.675
0.623
0.95

0.697
0.94
0.98

0.094
0.022
0.061
0.01
0

0.09
0.054
0.05
0.026
0.047

0.72
0.543
0.074
0.044
0.071

0.92
0.98
0.085
0.1
0.486

0.91
0.93
0.367
0.345
0.986

0.91
0.92
0.95
0.879
0.938

0.397
0.288
0.95
0.656
0.922

0.017
0.011
0.071
0.014

0.088
0.048
0.04
0.024

0.082
0
0.005
0.007

0.09
0.09
0.015
0.064

0.008
0.554
0.464
0.439

0.197
0.943
0.937
0.955

0.968
0.926
0.947
0.927

319

Table 19. (cont’d)
Common Name
Hoary Puccoon
Prairie-dock; Rosin-weed
Hophornbeam
Sycamore
Snakeroot (medicinal)
Sassafras
St. John's wort (medicinal)
Dogwood
Mint
Northern swamp dogwood
Swamp rose
Poison Ivy
Fringed Loosestrife
Prickly-ash
False Solomon's Seal
Three-leaved False
Solomon's Seal
Sensitive fern
Wild cherry
Huckleberry
Mustard
Stickyweed
American elderberry
Serviceberry/Shadbush
Black cherry
Hackberry
Grape(Riverbank grape)

January

February

March

April

May

June

July

0.031
0.013
0.008
0.023
0.056
0.058
0.034
0.058
0.048
0.079
0.029
0.018
0.094
0.084
0.014
0.052

0.011
0.061
0.02
0.091
0.075
0.075
0.062
0.055
0
0.064
0.051
0.1
0.098
0.041
0.043
0.009

0.009
0.03
0.064
0.053
0.013
0.041
0.034
0.024
0.019
0.014
0.019
0.081
0.001
0.049
0.007
0.072

0.041
0.025
0.95
0.014
0.1
0.013
0.018
0.001
0.013
0.058
0.095
0.069
0.081
0.716
0.064
0.051

0.372
0.07
0.97
0.922
0.558
0.941
0.091
0.94
0.035
0.739
0.071
0.41
0.354
0.533
0.93
0.94

0.984
0.775
0.828
0.28
0.938
0.917
0.47
0.99
0.263
0.956
0.119
0.517
0.91
0.183
0.93
0.92

0.935
0.94
0.066
0.233
1.00
0.986
1.00
0.94
1.00
0.923
0.93
0.385
0.94
0.406
0.701
0.765

0.095
0.41
0.008
0.028
0.08
0.018
0.077
0.014
0.455
0.292

0.095
0.124
0.077
0.09
0.031
0.038
0.048
0.021
0.082
0.017

0.099
0.215
0.062
0.086
0.063
0.021
0.009
0.092
0.073
0.071

0.085
0.1
0.449
0.035
0.044
0.019
0.107
0.039
0.354
0.308

0.95
0.003
0.953
0.132
0.122
0.087
0.951
0.055
0.035
0.9

0.95
0.035
0.974
0.988
0.909
0.179
0.938
0.095
0.017
0.935

0.419
0.117
0.159
0.999
0.926
0.955
0.912
0.004
0.071
0.914

320

Table 19. (cont’d)
Common Name
Nannyberry
Wild strawberry
Black Raspberry
Squash
Cape Gooseberry
Knotweed
Maize
Sumpweed (Iva annua)
Wild rice
Amaranth
Woodland Sunflower
Goosefoot(quinoa)
American Chestnut
Black Walnut
Shellbark Hickory
Hazelnut
Shagbark Hickory
Butternut/white walnut
Hickory
Oak/acorn
American beech
Mulberry
Hawthorn
Swamp White Oak
Red Oak
Black Maple
Hog-peanut

January
0.4
0.307
0.162
0.099
0.094
0.002
0.284
0.197
0.256
0.204
0.041
0.261
0.453
0.365
0.427
0.381
0.122
0.34
0.24
0.5
0.174
0.119
0.206
0.152
0.153
0.186
0.447

February

March
0.047
0.076
0.086
0.073
0.062
0.008
0.207
0.167
0.018
0.013
0.088
0.003
0.378
0.437
0.297
0.106
0.385
0.183
0.248
0.313
0.267
0.384
0.477
0.342
0.131
0.076
0.077

April
0.085
0.098
0.095
0.024
0.042
0.07
0.448
0.051
0.062
0.053
0.064
0.055
0.476
0.103
0.138
0.197
0.285
0.134
0.141
0.274
0.177
0.172
0.457
0.197
0.114
0.384
0.192

321

May
0.139
0.322
0.113
0.041
0.069
0.078
0.057
0.063
0.088
0.052
0.024
0.012
0.432
0.419
0.405
0.296
0.222
0.426
0.31
0.131
0.466
0.235
0.097
0.144
0.191
0.2
0.088

0.99
0.91
0.95
0.052
0.031
0.013
0.023
0.042
0.025
0.016
0.799
0.011
0.471
0.391
0.43
0.16
0.38
0.103
0.483
0.443
0.166
0.247
0.135
0.495
0.016
0.108
0.483

June

July
1.00
1.00
0.91
0.019
0.028
0.948
0.096
0.098
0.831
0.075
0.987
0.009
0.19
0.258
0.358
0.482
0.445
0.363
0.373
0.322
0.277
0.082
0.329
0.036
0.345
0.288
0.421

0.92
0.99
0.96
0.362
0.031
0.986
0.057
0.587
0.943
0.57
0.972
0.844
0.841
0.151
0.467
0.723
0.291
0.313
0.404
0.324
0.266
0.059
0.373
0.437
0.008
0.101
0.28

Table 19. (cont’d)
Common Name
Black Oak
Pine
Slippery Elm
Elm
Eastern Redbud
American Basswood
Poplar/cottonwood
White Ash
Sweet Birch
White Spruce
Mountain ash
Pear

January
0.307
0.153
0.304
0.399
0.148
0.433
0.233
0.07
0.351
0.31
0.377
0.75

February

March
0.059
0.173
0.086
0.111
0.406
0.139
0.489
0.052
0.398
0.462
0.193
0.69

April
0.357
0.439
0.382
0.158
0.484
0.194
0.279
0.286
0.258
0.209
0.286
0.04

322

May
0.211
0.081
0.485
0.19
0.171
0.107
0.267
0.517
0.708
0.764
0.502
0.09

0.494
0.048
0.62
0.085
0.255
0.31
0.364
0.647
0.531
0.518
0.613
0.09

June

July
0.049
0.383
0.143
0.772
0.588
0.019
0.551
0.657
0.11
0.411
0.412
0.09

0.458
0.178
0.433
0.571
0.562
0.195
0.058
0.226
0.035
0.139
0.152
0.05

Table 20. Resource probability matrix August to December
Common Name
White-tailed Deer
Black bear
Wolf, dog
Moose
Wapiti/Elk
Red fox
Raccoon
Otter
Bobcat
Squirrel
Fisher
Shrew
Marten
Mouse
Vole
Beaver
Muskrat
Woodchuck
Chipmunk
Mink
Porcupine
Mice/Rats
Rabbits
Great Horned Owl
Common Loon
Hooded merganser
Blue-winged teal
Mallard
Common merganser
Crow
Sandhill crane
Wild turkey
Baldpate, widgeon
Red-breasted merganser
Pied-billed grebe
Ring-necked duck
Greater Scaup
American Bittern

August

September October

0.97
0.99
0.62
0.70
0.93
0.71
0.96
0.56
0.47
0.96
0.84
0.92
0.93
0.80
0.65
0.89
0.94
0.96
0.99
0.81
0.28
0.42
0.97
0.14
0.18
0.42
0.29
0.84
0.77
0.86
0.47
0.37
0.86
0.47
0.56
0.56
0.98
0.40

0.91
0.92
0.61
0.95
0.99
0.91
1.00
0.48
0.30
0.35
0.29
0.96
0.98
0.98
0.23
0.14
0.96
0.98
0.35
0.16
0.73
0.73
0.70
0.45
0.93
0.93
0.99
0.95
0.98
0.15
0.35
0.84
1.00
0.94
0.98
0.93
0.75
0.28
323

0.97
0.95
0.54
0.99
0.93
0.92
0.91
0.79
0.83
0.68
0.64
0.43
1.00
0.94
0.60
0.36
0.26
0.99
0.46
0.67
0.31
0.14
0.16
0.27
0.92
0.93
0.75
0.92
0.96
0.25
0.44
0.76
0.68
0.95
0.90
0.97
0.12
0.27

November
0.98
0.54
0.55
0.90
1.00
0.71
0.98
0.69
0.81
0.29
0.53
0.42
0.97
0.064
0.53
0.83
0.33
0.94
0.026
0.84
1.00
0.56
0.76
0.39
0.54
0.22
0.45
0.76
0.12
0.90
0.82
0.87
0.46
0.35
0.38
0.24
0.90
0.37

December
0.78
0.78
0.63
1.00
0.68
0.94
0.40
0.16
0.80
0.12
0.82
0.82
0.95
0.024
0.80
0.85
0.33
0.69
0.08
0.62
0.91
0.56
0.83
0.81
0.76
0.87
0.23
0.32
0.60
0.23
0.62
0.66
0.91
0.80
0.83
0.70
0.96
0.95

Table 20. (cont’d)
Common Name
Passenger Pigeon
Great Blue Heron
Bluegill
Yellow perch (ringed, striped
or jack perch, green hornet)
Burbot (Cod)
White bass/Hybrid striped
bass
Channel catfish (spotted,
speckled or silver catfish)
Walleye pike (marble-eyes,
'eye, walter, walleyed pike,
jack, jackfish, pickerel)
Black bullhead (common
bullhead, horned pout)
Sucker
Sturgeon
Largemouth bass (black bass,
green bass, green trout,
slough bass)
Longnosed gar
Smallmouth bass
(bronzeback, brown or
redeye bass, redeye, white
or mountain trout)
Crappie
Sauger (also Sander
canadensis)
Black crappie
Lake trout (togue, mackinaw,
great gray trout, laker)
Redhorse
Sunfish
Yellow bullhead (whitewhiskered bullhead, yellow
cat)
Bowfin (dogfish, grindle,
mudfish, cypress trout, lake
lawyer, beaver fish)

August

September October

November

December

1.00
0.69
0.80
0.43

0.98
0.40
0.27
0.75

0.96
0.45
0.52
0.75

0.14
0.93
0.72
0.20

0.50
0.91
0.74
0.39

0.86
0.16

0.39
0.75

0.18
0.71

0.50
0.56

0.98
0.52

0.49

0.59

0.40

0.70

0.15

0.86

0.35

0.47

0.43

0.42

0.67

0.79

0.63

0.60

0.37

0.19
0.68
0.42

0.67
0.49
0.42

0.16
0.55
0.70

0.86
0.31
0.42

0.67
0.14
0.57

0.41
0.83

0.81
0.12

0.71
0.38

0.31
0.43

0.41
0.73

0.56
0.47

0.49
0.27

0.85
0.77

0.28
0.57

0.50
0.59

0.82
0.20

0.80
0.51

0.42
0.69

0.81
0.12

0.63
0.76

0.55
0.99
0.97

0.72
0.48
0.91

0.32
0.34
0.66

0.79
0.48
0.41

0.68
0.47
0.18

0.29

0.59

0.60

0.60

0.61

324

Table 20. (cont’d)
Common Name
Northern Pike (pickerel, jack,
gator, hammerhandle, snot
rocket)
Brown bullhead (marbled or
speckled bullhead, red cat)
Drumfish (sheepshead,
croaker, thunderpumper,
grinder, bubbler)
Northern water snake
Garter snake
Frogs and toads
Blanding's turtle
Painted turtle
Snapping turtle
Softshell turtles
mollusk
Gastropod - three-ridge
valvata
Sedge or grass
Sedge or grass
Sedge or grass
Cattail
Dock
Flatsedge
Wild or False Lily-of-theValley
Aster
Spreading Dogbane
Wild Bergamot
Anise-root
May-apple, Mandrake
Dandelion
Wild Geranium, spotted
cranesbill
Bindweed
Wild Basil, Dogmint
Sumac
Panic-grass

August

September October

November

December

0.86

0.26

0.60

0.52

0.80

0.76

0.75

0.12

0.37

0.89

0.70

0.87

0.43

0.60

0.53

0.27
0.678
0.282
0.459
0.311
0.153
0.455
0.98
0.91

0.373
0.844
0.077
0.377
0.158
0.302
0.35
0.624
0.889

0.003
0.018
0.047
0.425
0.012
0.374
0.065
0.012
0.083

0.011
0.044
0.076
0.297
0.058
0.098
0.084
0.056
0.089

0.049
0.009
0.065
0.022
0.037
0.045
0.01
0.074
0.064

1.00
0.97
0.95
0.55
0.93
0.99
0.058

0.91
0.94
0.94
0.20
0.98
0.95
0.071

0.068
0.012
0.058
0.53
0.046
0.057
0.022

0.041
0.01
0.073
0.36
0
0.051
0.005

0.016
0.07
0.05
0.27
0.078
0.037
0.022

0.96
0.943
0.906
0.95
0.985
0.958
0.95

0.96
0.984
0.921
0.991
0.993
0.972
0.97

0.93
0.972
0.986
0.946
0.979
0.979
0.97

0.06
0.049
0.067
0.03
0.025
0.013
0.06

0.083
0.075
0.032
0.096
0.083
0.008
0.074

0.97
0.906
0.98
0.246

0.90
0.927
0.058
0.036

0.92
0.928
0.063
0.074

0.007
0.085
0.011
0.029

0.088
0.088
0.036
0.024

325

Table 20. (cont’d)
Common Name
June grass, Kentucky
Bluegrass, Speargrass, Fowl
Bluegrass
Carrion Flower Greenbriar
Golden rod
Early Meadow- rue
Quicksilver-weed
Smooth Yellow Violet
Common Blue Violet
Michigan Lily
Greenbrier
Wild columbine, Rock-bells,
Meetinghouses, honey
suckle
Wild sarsaparilla
Yellow rocket
White Avens
Large Flowered Trillium
Hoary Puccoon
Prairie-dock; Rosin-weed
Hophornbeam
Sycamore
Snakeroot (medicinal)
Sassafras
St. John's wort (medicinal)
Dogwood
Mint
Northern swamp dogwood
Swamp rose
Poison Ivy
Fringed Loosestrife
Prickly-ash
False Solomon's Seal
Three-leaved False
Solomon's Seal
Sensitive fern
Wild cherry
Huckleberry
Mustard

August

September October

November

December

0.90

0.97

0.367

0.007

0.029

0.162
0.99
0.84

0.174
0.95
0.005

0.90
0.447
0.032

0.96
0.061
0.012

0.452
0.013
0.021

0.041
0.099
0.247
0.778
0.863

0.066
0.058
0.071
0.347
0.078

0.071
0.011
0.096
0.99
0.003

0.097
0.071
0.076
0.98
0.008

0.006
0.038
0.028
0.639
0.099

0.906
0.451
0.57
0.786
0.504
0.92
0.011
0.218
0.95
0.946
0.98
0.21
0.99
0.229
0.98
0.93
0.99
0.97
0.1
0.083

0.341
0.085
0.067
0.073
0.062
0.92
0.066
0.709
0.97
0.94
0.96
0.006
1.00
0.062
0.446
0.92
0.9
0.91
0.063
0.068

0.078
0.065
0.075
0.07
0.091
0.878
0.08
0.962
0.227
0.96
0.83
0.079
0.004
0.087
0.018
0.611
0.001
0.606
0.081
0.058

0.058
0.06
0.04
0.042
0.005
0.057
0.004
0.389
0.069
0.702
0.007
0.021
0.086
0.034
0.98
0.047
0.053
0.085
0.073
0.007

0.023
0.001
0.095
0.062
0.073
0.043
0.07
0.098
0.029
0.032
0.073
0.052
0.047
0.035
0.98
0.063
0.058
0.005
0.039
0.043

0.06
0.912
0.117
0.938

0.012
0.987
0.149
0.294

0.072
0.981
0.491
0.276

0.067
0.335
0.327
0.192

0.097
0.31
0.227
0.431

326

Table 20. (cont’d)
Common Name
Stickyweed
American elderberry
Serviceberry/Shadbush
Black cherry
Hackberry
Grape(Riverbank grape)
Nannyberry
Wild strawberry
Black Raspberry
Squash
Cape Gooseberry
Knotweed
Maize
Sumpweed (Iva annua)
Wild rice
Amaranth
Woodland Sunflower
Goosefoot(quinoa)
American Chestnut
Black Walnut
Shellbark Hickory
Hazelnut
Shagbark Hickory
Butternut/white walnut
Hickory
Oak/acorn
American beech
Mulberry
Hawthorn
Swamp White Oak
Red Oak
Black Maple
Hog-peanut
Black Oak
Pine
Slippery Elm
Elm
Eastern Redbud

August
0.999
0.945
0.981
0.28
0.003
0.119
0.147
0.454
0.397
0.988
0.957
0.983
0.043
0.924
0.929
0.946
0.918
0.955
0.922
0.645
0.555
0.957
0.873
0.871
0.763
0.828
0.606
0.295
0.14
0.35
0.078
0.279
0.86
0.175
0.419
0.063
0.369
0.358

September October
0.339
0.114
0.317
0.987
0.901
0.014
0.006
0.012
0.049
0.927
0.945
0.993
0.081
0.905
0.921
0.9
0.988
0.922
0.937
0.929
0.927
0.94
0.988
0.957
0.96
0.908
0.968
0.563
0.741
0.595
0.818
0.53
0.68
0.557
0.156
0.197
0.451
0.319
327

0.419
0.328
0.19
0.987
0.933
0.009
0.013
0.081
0.052
0.388
0.95
0.24
0.039
0.921
0.839
0.951
0.956
0.965
0.929
0.971
0.905
0.95
0.937
0.974
0.988
0.916
0.925
0.704
0.691
0.638
0.521
0.82
0.56
0.884
0.486
0.399
0.281
0.191

November
0.229
0.175
0.295
0.19
0.491
0.119
0.04
0.023
0.095
0.345
0.318
0.174
0.073
0.821
0.473
0.513
0.8
0.779
0.575
0.889
0.723
0.631
0.806
0.636
0.726
0.507
0.629
0.075
0.473
0.458
0.222
0.185
0.239
0.296
0.076
0.206
0.122
0.017

December
0.399
0.45
0.225
0.231
0.263
0.471
0.022
0.024
0.001
0.03
0.008
0.097
0.44
0.122
0.189
0.157
0.377
0.397
0.265
0.497
0.175
0.247
0.441
0.18
0.169
0.327
0.164
0.15
0.441
0.312
0.403
0.261
0.145
0.323
0.104
0.071
0.436
0.338

Table 20. (cont’d)
Common Name
American Basswood
Poplar/cottonwood
White Ash
Sweet Birch
White Spruce
Mountain ash
Pear

August
0.238
0.397
0.344
0.444
0.445
0.274
0.01

September October
0.348
0.304
0.028
0.483
0.478
0.169
0.09

328

0.521
0.442
0.474
0.338
0.099
0.248
0.03

November
0.355
0.044
0.269
0.006
0.058
0.212
0.07

December
0.181
0.107
0.443
0.383
0.473
0.095
0.09

Simulation Results
Table 21. Late Archaic land use
COVERTYPE
Intermittent Wetlands
SHRUB SWAMP/EMERGENT MARSH
MIXED CONIFER SWAMP
MIXED HARDWOOD SWAMP
RIVER
WET PRAIRIE
BLACK ASH SWAMP
CEDAR SWAMP
MUSKEG/BOG
MESIC SOUTHERN FORESTS: BEECH-SUGAR MAPLE
FOREST
MESIC NORTHERN FORESTS: BEECH-SUGAR MAPLEHEMLOCK
MESIC NORTHERN FORESTS: HEMLOCK-WHITE PINE
FOREST
DRY NORTHERN FORESTS: JACK PINE-RED PINE FOREST
WHITE PINE-MIXED HARDWOOD
WHITE PINE-RED PINE
WHITE PINE-WHITE OAK
MIXED PINE-OAK
DRY MESIC SOUTHERN FORESTS: OAK-HICKORY
DRY SOUTHERN FORESTS MIXED OAK
MIXED OAK SAVANNA
SPRUCE-FIR-CEDAR
ASPEN-BIRCH

LA Count

LA (SqMiles)

LA%

LA Degraded

2009
5203
2380
1
693
708
982
47
572

0%
1%
7%
4%
5%
1%
1%
2%
0%
12%

0
294
110
108
470
61
60
57
6
182

375

3003.1

20%

164

659

1487.4

10%

128

165
138
352
60
21
283
102
81
2
103
329

0.0
83.6
1095.8
657.4
804.9
105.5
174.9
314.9
8.6
1843.0

578.8
718.5
411.1
109.8
28.4
614.3
167.9
169.3
0.7
89.9

4%
5%
3%
1%
0%
4%
1%
1%
0%
1%

28
209
122
24
17
102
14
125
30
33

Table 21. (cont’d)
COVERTYPE
BLACK OAK BARREN
OAK/PINE BARRENS
PINE BARRENS
EXPOSED BEDROCK
SAND DUNE
GRASSLAND

LA_Count

LA_SqMiles
142
40
97
0
2
9

330

LA%
422.7
43.2
117.3
0.0
0.0
1.4

LA Degraded
3%
0%
1%
0%
0%
0%

0
0
0
0
1
0

Table 22. Exploited resources by calories
Resource
January February
March
April
May
June
Grass_Herb
6596
9411
14898
9822
17330
23565
Large Mammals
13247
13330
11219
12062
10186
8966
Birds
8436
4021
11352
5964
7855
1817
Fish
2633
1076
1679
3195
3207
2006
Nuts
2
0
48
0
0
0
Small mammal
443
103
0
301
148
0
Seeds_Grains
0
0
0
0
0
131
Herb/Medicine
0
0
0
296
20
0
Seed_Fruit
0
0
0
0
0
17
Mollusk
0
0
0
0
0
0
Reptile
0
0
0
0
0
0
Tree_Fruit
0
0
0
0
0
0
July
August
September October
November December Total
Grass_Herb
31227
30402
27730
6259
2804
5018 185062
Large Mammals
7284
7632
7815
13752
14170
11695 131358
Birds
2146
1398
2027
4366
5698
16500
71580
Fish
0
0
0
624
557
2166
17143
Nuts
0
0
95
698
641
0
1484
Small mammal
0
0
0
57
363
0
1415
Seeds_Grains
0
0
0
602
560
0
1293
Herb/Medicine
0
0
88
588
0
0
992
Seed_Fruit
0
0
0
0
0
0
17
Mollusk
0
0
0
0
0
0
0
Reptile
0
0
0
0
0
0
0
Tree_Fruit
0
0
0
0
0
0
0

331

Table 23. Male exploited resources
Resource
January February March
April
May
June
Large Mammals
4114
4159
3927
3848
3666
3540
Grass_Herb
455
727
1458
791
1560
3388
Birds
1497
839
2705
1242
1813
508
Fish
961
460
660
1233
1269
875
Small mammal
83
10
0
50
29
0
Herb/Medicine
0
0
0
12
1
0
Nuts
0
0
3
0
0
0
Seeds_Grains
0
0
0
0
0
4
Mollusk
0
0
0
0
0
0
Reptile
0
0
0
0
0
0
Seed_Fruit
0
0
0
0
0
0
Tree_Fruit
0
0
0
0
0
0
July
August
September
October
November December Total
Large Mammals
Grass_Herb
Birds
Fish
Small mammal
Herb/Medicine
Nuts
Seeds_Grains
Mollusk
Reptile
Seed_Fruit
Tree_Fruit

2976
6243
704
0
0
0
0
0
0
0
0
0

3064
6030
460
0
0
0
0
0
0
0
0
0

3169
5261
650
0
0
17
5
0
0
0
0
0

4573
540
884
251
13
44
16
10
0
0
0
0
332

4417
176
1125
211
62
0
17
24
0
0
0
0

3773
371
3215
810
0
0
0
0
0
0
0
0

45226
27000
15642
6730
247
74
41
38
0
0
0
0

Table 24. Female exploited resources
Resource
January
February
March April
May
June
Grass_Herb
5590
7869
11768
8114
13719
15755
Birds
4957
2158
5273
3280
3711
530
Large Mammals
4230
4259
2652
3553
2124
1157
Fish
400
98
194
442
313
89
Nuts
2
0
44
0
0
0
Seeds_Grains
0
0
0
0
0
120
Small mammal
266
76
0
185
80
0
Herb/Medicine
0
0
0
271
17
0
Seed_Fruit
0
0
0
0
0
11
Mollusk
0
0
0
0
0
0
Reptile
0
0
0
0
0
0
Tree_Fruit
0
0
0
0
0
0
July
August
September
October November December Total
Grass_Herb
Birds
Large Mammals
Fish
Nuts
Seeds_Grains
Small mammal
Herb/Medicine
Seed_Fruit
Mollusk
Reptile
Tree_Fruit

16999
529
626
0
0
0
0
0
0
0
0
0

16509
347
737
0
0
0
0
0
0
0
0
0

15707
539
784
0
81
0
0
47
0
0
0
0

5091
2333
3883
75
656
572
32
468
0
0
0
0

333

2418
3224
4545
69
593
492
221
0
0
0
0
0

4192 123731
9140 36021
3458 32008
296
1976
0
1376
0
1184
0
860
0
803
0
11
0
0
0
0
0
0

Table 25. Total exploited calories by female
Calories_F
January
February
March
April
May
June
Large Mammals
346944550
323940900
856935000 1.1E+09
7E+08
3.8E+08
Grass_Herb
11585438
22923858
30572941 2.1E+07
4E+07
6E+07
Birds
20003626
8832954
11881639 1.2E+07
1E+07
1309778
Nuts
47018
0
893342
0
0
0
Seeds_Grains
0
0
0
0
0
2180000
Fish
3436720
828240
1666000 3779440
3E+06
809200
Small mammal
5443065
1051750
0 3220012
2E+06
0
Herb/Medicine
0
0
0 2606175
160875
0
Seed_Fruit
0
0
0
0
0
111110
Mollusk
0
0
0
0
0
0
Reptile
0
0
0
0
0
0
Tree_Fruit
0
0
0
0
0
0
Calories - F
July
August
September
October November
December
Totals
Large Mammals
2E+08
2.5E+08
250326500 1.2E+09
1.431E+09
1.203E+09
8.24E+09
Grass_Herb
7.1E+07
7.1E+07
67034764 1.6E+07
3006252
9688733
4.24E+08
Birds
1635816
997866
1318826 8635973
12584786
24692261
1.16E+08
Nuts
0
0
1692648 1.4E+07
11390975
0
28398068
Seeds_Grains
0
0
0 9774296
5712368
0
17666664
Fish
0
0
0 675920
618800
2694160
17278800
Small mammal
0
0
0 589860
4190040
0
16020227
Herb/Medicine
0
0
830115 7546305
0
0
11143470
Seed_Fruit
0
0
0
0
0
0
111110
Mollusk
0
0
0
0
0
0
0
Reptile
0
0
0
0
0
0
0
Tree_Fruit
0
0
0
0
0
0
0

334

Table 26. Exploited calories by male
Calories - M
January
February
March
April
May
June
Large
1.364E+09 1.284E+09
1.281E+09
1.2E+09
1E+09
1.2E+09
Mammals
Grass_Herb
1166047
2340456
3871493
2255028
5E+06
1.2E+07
Fish
8349040
3988880
5750080
1.1E+07
1E+07
7682640
Birds
6159858
2825028
5826186
4640480
6E+06
1230223
Small mammal
1734380
150250
0
830428
508500
0
Herb/Medicine
0
0
0
107250
10725
0
Nuts
0
0
47018
0
0
0
Seeds_Grains
0
0
0
0
0
80000
Mollusk
0
0
0
0
0
0
Reptile
0
0
0
0
0
0
Seed_Fruit
0
0
0
0
0
0
Tree_Fruit
0
0
0
0
0
0
Calories - M
July
August
September October
November December
Totals
Large
9.5E+08
9.9E+08 1048944000
1.4E+09 1.402E+09
1.331E+09
1.46E+10
Mammals
Grass_Herb
2.6E+07
2.6E+07
22171504
1868229
219672
690995
1.03E+08
Fish
0
0
0
2122960
1789760
7092400
58509920
Birds
2298097
1334053
1583703
3163649
4133052
8317117
47538114
Small mammal
0
0
0
223740
1200060
0
4647358
Herb/Medicine
0
0
251550
767520
0
0
1137045
Nuts
0
0
94036
371165
266416
0
778635
Seeds_Grains
0
0
0
164040
268968
0
513008
Mollusk
0
0
0
0
0
0
0
Reptile
0
0
0
0
0
0
0
Seed_Fruit
0
0
0
0
0
0
0
Tree_Fruit
0
0
0
0
0
0
0
335

Resource reference
Table 27. Possible resource list
Modified from (Baker 1983; Banfield 1974; Burt 1957; Voss 1972)
Type category
Species
Common Name
Mammals
Cervus canadensis
Wapiti/Elk

Type
Ungulate

Mammals
Mammals
Mammals
Mammals
Mammals
Mammals
Mammals
Mammals
Mammals
Mammals
Mammals
Mammals
Mammals
Mammals
Mammals
Mammals
Mammals
Mammals
Mammals
Mammals
Mammals
Mammals

Ungulate
Carnivore
Carnivore
Rodent
Rodent
Carnivore
Carnivore
Rodents
Carnivore
Carnivore
Rodents
Carnivore
Carnivore
Rodent
Lagomorph
Carnivore
Ungulate
Insectivore
Rodent
Rodent
Rodent
Rodent

Odocoileus virginianus
Procyon lotor
Ursus americanus
Castor canadensis
Ondatra zibethicus
Canis sp. (lupus, familiaris)
Martes americana
Marmota monax
Mustela vison
Lynx rufus
Erethizon dorsatum
Lontra canadensis
Martes pennanti
Sciurus sp.
Leporidae sp. (Sylvilagus)
Vulpes fulva
Alces alces
Blarina sp.
Tamias sp.
Muridae sp.
Peromyscus sp.
Microtus sp.

White-tailed Deer
Raccoon
Black bear
Beaver
Muskrat
Wolf, dog
Marten
Woodchuck
Mink
Bobcat
Porcupine
Otter
Fisher
Squirrel
Rabbits
Red fox
Moose
Shrew
Chipmunk
Mice/Rats
Mouse
Vole
336

Table 27. (cont’d)
Type category
Osteichthyes; Fish
Osteichthyes; Fish

Species
Acipenser fulvescens
Perca flavescens

Common Name
Sturgeon
Yellow perch (ringed, striped or jack
perch, green hornet)

Type
Sturgeon family
Perch family

Osteichthyes; Fish

Amia calva

Bowfin (dogfish, grindle, mudfish, cypress
trout, lake lawyer, beaver fish)

Bowfin family

Osteichthyes; Fish

Aplodinotus grunniens

Drumfish (sheepshead, croaker,
thunderpumper, grinder, bubbler)

Drum family

Osteichthyes; Fish

Monroe chrysops

White bass/Hybrid striped bass

Sunfish family

Osteichthyes; Fish

Micropterus salmoides

Largemouth bass (black bass, green bass,
green trout, slough bass)

Sunfish family

Osteichthyes; Fish

Micropterus dolomieui

Sunfish family

Osteichthyes; Fish

Esox lucius

Smallmouth bass (bronzeback, brown or
redeye bass, redeye, white or mountain
trout)
Northern Pike (pickerel, jack, gator,
hammerhandle, snot rocket)

Osteichthyes; Fish

Stizostedion vitreum

Walleye pike (marble-eyes, 'eye, walter,
walleyed pike, jack, jackfish, pickerel)

Perch family

Osteichthyes; Fish

Ictalurus punctatus

Channel catfish (spotted, speckled or
silver catfish)

Catfish family

Osteichthyes; Fish

Lepisosteus oculatus

Longnosed gar

Gar family

337

Pike family

Table 27. (cont’d)
Type category
Osteichthyes; Fish

Species
Salvelinus namaycush

Common Name
Lake trout (togue, mackinaw, great gray
trout, laker)

Osteichthyes; Fish

Ictalurus melas

Black bullhead (common bullhead, horned Catfish family
pout)

Osteichthyes; Fish

Ictalurus natalis

Yellow bullhead (white-whiskered
bullhead, yellow cat)

Catfish family

Osteichthyes; Fish

Ictalurus nebulosus

Brown bullhead (marbled or speckled
bullhead, red cat)

Catfish family

Osteichthyes; Fish

Redhorse

Sucker family

Crappie
Sucker

Sunfish family
Sucker family

Osteichthyes; Fish
Osteichthyes; Fish
Osteichthyes; Fish
Osteichthyes; Fish

Moxostoma sp.
(macrolepidotum)
Pomoxis sp.
Catostomus sp. (catostomus,
commersoni)
Centrarchidae
Lepomis cf. macrochirus
Pomoxis nigromaculatus
Stizostedion canadense

Sunfish
Bluegill
Black crappie
Sauger (also Sander canadensis)

Sunfish family
Sunfish family
Sunfish family
Perch family

Osteichthyes; Fish

Lota lota lacustris

Burbot (Cod)

Freshwater cod family

Birds
Avian
Avian
Avian

Ectopistes migratorius
Anas discors
Anas americana

Passenger Pigeon
Blue-winged teal
Baldpate, widgeon

Bird
Bird
Bird

Osteichthyes; Fish
Osteichthyes; Fish

338

Type
Salmon family

Table 27. (cont’d)
Type category
Avian
Avian
Avian

Species
Anas platyrhynchos
Aythya collaris
Mergus merganser

Common Name
Mallard
Ring-necked duck
Common merganser

Type
Bird
Bird
Bird

Avian

Mergus serrator

Red-breasted merganser

Bird

Avian
Avian
Avian
Avian
Avian
Avian
Avian
Avian
Avian
Avian
Botanical
-Cultigen/grain
-Cultigen/grain
-Cultigen/grain
-Cultigen/grain

Gavia immer
Podilymbus podiceps
Meleagris gallopavo
Lophodytes cucullatus
Corvus brachyrhynchos
Botaurus lentiginosus
Ardea herodias
Grus canadensis
Aythya marila
Bubo virginianus

Common Loon
Pied-billed grebe
Wild turkey
Hooded merganser
Crow
American Bittern
Great Blue Heron
Sandhill crane
Greater Scaup
Great Horned Owl

Bird
Bird
Bird
Bird
Bird
Bird
Bird
Bird
Bird
Bird

Chenopodium
Zea mays
Iva annua
Carex sp.

Goosefoot
Maize
Sumpweed
Sedge

Dicot/Green
Grass
Dicot
Monocot/sedge/Perennial

-Cultigen/grain
-Cultigen/grain
-Nut
-Nut

Cyperus
Zizania aquatica
Quercus
Carya

Flatsedge
Wild rice
Oak/acorn
Hickory

Monocot/sedge
Monocot
Deciduous nut
Deciduous nut

339

Table 27. (cont’d)
Type category
-Nut

Species
J. cinerea

Common Name
Butternut/white walnut

Type
Deciduous nut

-Nut
-Nut
-Nut
-Seed/fruit
-Seed/fruit
-Seed/fruit

Juglans nigra
Corylus americana
Castanea dentata
Cucurbita pepo
Amphicarpaea bracteata
Geranium maculatum

Black Walnut
Hazelnut
American Chestnut
Squash
Hog-peanut
Wild Geranium, spotted cranesbill

Deciduous nut
Deciduous nut shrub
Tree; nut
Vining herb
Dicot

-Seed/fruit
-Seed/fruit
-Seed/fruit
-Seed/fruit
-Seed/fruit
-Seed/fruit
-Seed/fruit

Pyrus sp.
Physalis
Convolvulaceae
Brassicaceae sp.
Fragaria virginiana
Galium aparine
Helianthus divaricatus

Mountain ash
Cape Gooseberry
Bindweed
Mustard
Wild strawberry
Stickyweed
Woodland Sunflower

Small tree
Dicot

-Seed/fruit

Polygala senega

Snakeroot (medicinal)

Dicot/ annual herb

-Seed/fruit
-Seed/fruit
-Seed/fruit
-Seed/fruit
-Seed/fruit
-Seed/fruit

Rubus occidentalis
Celtis occidentalis
Vitis sp.
Crataegus sp.
Viburnum sp.
Rhus sp

Black Raspberry
Hackberry
grape seed
Hawthorn
Nannyberry
Sumac

Dicot
Tree
Dicot/Perennial

340

Dicot/Herb
Dicot
Dicot/Perennial herb

Dicot/Shrub
Dicot/Shrub

Table 27. (cont’d)
Type category
-Seed/fruit

Species
Polygonum pensylvanicum

Common Name
Knotweed

Type
Dicot/Annual herb

-Seed/fruit
-Seed/fruit

Prunus spp.
Sambucus canadensis

Wild cherry
American elderberry

Dicot /Shrub

-Seed/fruit
-Seed/fruit

Black cherry
Serviceberry/Shadbush

Dicot/Shrub

-Seed/fruit
-Seed/fruit
-Seed/fruit

Prunus serotina
Amelanc (Amelanchier
Medikus)
Aster cordifolius
Sassafras albidum
Hypericum

Aster
Sassafras
St. John's wort (medicinal)

Dicot
Tree
Dicot/Perennial/Shrub/Herb

-Seed/fruit
-Seed/fruit
-Seed/fruit
-Seed/fruit
-Charcoal

Cornus rugosa
Gaylussacia baccata
Lamiaceae
Rosa palustris
Pinus

Dogwood
Huckleberry
Mint
Swamp rose
Pine

Dicot/Semi-shrub
Dicot
Dicot/Perennial herb
Dicot/Shrub
Gymnosperms/Conifers

-Charcoal
-Charcoal
-Charcoal
-Charcoal
-Charcoal
-Charcoal
-Charcoal
-Charcoal

Fraxinus alba
P. resinosa
P. strobus
Ulmus rubra
Ulmus sp.
Cercis canadensis
Tilia americana
Q. nigra

Ash
Red pine
White Pine
Slippery Elm
Elm
Redbud
Basswood
Black Oak

Dicot
Large tree
Large tree
Medium tree
Deciduous
Small tree
Large tree
Large tree

341

Table 27. (cont’d)
Type category
-Charcoal
-Charcoal
-Charcoal
-Charcoal
-Charcoal
-Charcoal

Species
Q. bicolor
Q. rubra
Populus tremuloides
Carya laciniosa
Carya ovata
Cornus racemosa

Common Name
Swamp White Oak
Red Oak
Poplar/cottonwood
Shellbark Hickory
Shagbark Hickory
Northern swamp dogwood

Type
Medium tree
Large tree
Medium to large tree
Medium to large tree
Medium to large tree
Dicot/Shrub

-Charcoal
-Charcoal
-Charcoal
-Charcoal
-Charcoal
-Charcoal
-Charcoal
-Charcoal
-Charcoal
-Other (nonspecified)
-Other (nonspecified)
-Other (nonspecified)
-Other (nonspecified)
-Other (nonspecified)

Fagus americana
Ostraya virginiana
Fraxinus sp
Fagus grandifolia
Acer spp.
Betula spp.
Morus rubra
Platanus occidentalis
Picea
Typha

American beech
Hophornbeam
Ash
American beech
Maple
Birch
Mulberry
Sycamore
Spruce
Cattail

Deciduous
Deciduous
Dicot
Dicot
Dicot
Dicot

Rumex spp.

Dock

Dicot; large tree
Conifer
Angiosperm/Monocot/Perennial
Herb
Dicot/Perennial herbs

Panicum spp.

Panic-grass

Grass

Silphium terebinthinaceum

Prairie-dock; Rosin-weed

Perennial herb

Smilacina racemosa

False Solomon's Seal

Perennial herb

342

Table 27. (cont’d)
Type category
-Other (nonspecified)
-Other (nonspecified)
-Other (nonspecified)
-Other (nonspecified)

Species
Smilacina stellata

Common Name
Three-leaved False Solomon's Seal

Type
Perennial herb

Maianthemum canadense

Wild or False Lily-of-the-Valley

Perennial herb

Onoclea Sensibilis

Sensitive fern

Fern

Poa pratensis

June grass, Kentucky Bluegrass,
Speargrass, Fowl Bluegrass

Perennial grass

-Other (nonspecified)
-Other (nonspecified)
-Other (nonspecified)
-Other (nonspecified)
-Other (nonspecified)

Smilax lasioneura

Carrion Flower Greenbriar

Vine

Solidago Sp.

Golden rod

Perennial herb; dicot

Thalictrum dioicum

Early Meadow- rue Quicksilver-weed

Perennial herb; dicot

Viola pensylvanica

Smooth Yellow Violet

Perennial herb; dicot

Viola sororia (Sens. Lat.)
(Glabrous plants like this one
have been referred to V.
Papilionacea)

Common Blue Violet

Perennial herb; dicot

-Other (nonspecified)
-Other (nonspecified)
-Other (nonspecified)

Zanthoxylum americanum

Prickly-ash

Shrub/small tree

Lilium michiganense

Michigan Lily

Perennial herb; monocot

Lysimachia ciliata

Fringed Loosestrife

Perennial herb; dicot

343

Table 27. (cont’d)
Type category
-Other (nonspecified)
-Other (nonspecified)
-Other (nonspecified)
-Other (nonspecified)
-Other (nonspecified)
-Other (nonspecified)
-Other (nonspecified)

Species
Carex blanda

Common Name
Sedge or grass

Type
Monocot/sedge/Perennial

Carex lupulina

Sedge or grass

Monocot/sedge/Perennial

Carex pensylvanica

Sedge or grass

Monocot/sedge/Perennial

Smilax cirrata

Greenbrier

Vine

Toxicodendron radicans

Poison Ivy

Vine

Apocynum androsaemifolium

Spreading Dogbane

Dicot

Aquilegia canadensis

Wild columbine, Rock-bells,
Meetinghouses, honey suckle

Dicot

-Other (nonspecified)
-Other (nonspecified)
-Other (nonspecified)
-Other (nonspecified)
-Other (nonspecified)

Aralia nudicaulis

Wild sarsaparilla

Dicot; shrub

Barbarea vulgaris

Yellow rocket

Dicot; biennial herb

Geum canadense

White Avens

Dicot; perennial herb

Satureja vulgaris

Wild Basil, Dogmint

Dicot

Monarda fistulosa

Wild Bergamot

Dicot

344

Table 27. (cont’d)
Type category
-Other (nonspecified)
-Other (nonspecified)
-Other (nonspecified)
-Other (nonspecified)
-Other (nonspecified)
Reptile/Amphibian
Reptile/Amphibian
Reptile/Amphibian
Reptile/Amphibian
Reptile/Amphibian

Species
Osmorhiza longistylis

Common Name
Anise-root

Podophyllum peltatum

May-apple, Mandrake

Trillium grandiflorum

Large Flowered Trillium

Perennial herb; monocot

Lithospermum canescens

Hoary Puccoon

Perennial herb; monocot

Taraxacum officinale

Dandelion

Dicot

Anura sp.
Emydoidea blandingii
Chrysemys picta
Chelydra serpentina
Nerodia sipedon

Frogs and toads
Blanding's turtle
Painted turtle
Snapping turtle
Northern water snake

Amphibian
Reptile
Reptile
Reptile
Reptile

Reptile/Amphibian
Reptile/Amphibian
Mollusks
Mollusks
Mollusks
Mollusks

Thamnophis sp.
Trionyx sp.
Amblema costata
Elliptio dilatatus
Fusconaia flava (Raf.)
Quadrula pustulosa (Lea)

Garter snake
Softshell turtles
mollusk
mollusk
mollusk
mollusk

Reptile
Reptile
Freshwater mussel
Freshwater mussel
Freshwater mussel
Freshwater mussel

Mollusks

Pleurobema (cordatum)
coccineum (Conrad)
Cyclonaias tuberculata

mollusk

Freshwater mussel

mollusk

Freshwater mussel

Mollusks

345

Type
Dicot

Table 27. (cont’d)
Type category
Mollusks

Species
Lasmigona costata (Raf.)

Common Name
mollusk

Type
Freshwater mussel

Mollusks

Strophitus rugosus (Swain.)

mollusk

Freshwater mussel

Mollusks
Mollusks

Lampsilis siliquoidea (L)
Obovaria subrotunda (Raf.)

mollusk
mollusk

Freshwater mussel
Freshwater mussel

Mollusks

Ligumia (Recta) lattissima
(Raf.)
Actinonaias carinata (Barnes)

mollusk

Freshwater mussel

mollusk

Freshwater mussel

mollusk
mollusk
mollusk

Terrestrial snail
Terrestrial snail
Freshwater mussel

mollusk

Freshwater mussel

mollusk

Freshwater mussel

mollusk

Freshwater mussel

Mollusks

Discus cronkhitei
Anguispira kochi
Anodonta grandis footiana
(Say) Goodrich
Micromya (Villosa) Iris (Lea)
Goodrich
Amblema costata
(Rafinesque) Goodrich
Ligumia recta (Lamarck)
Goodrich
Valvata tricarinata (Say)

Gastropod - three-ridge valvata

Freshwater snail

Mollusks
Mollusks
Mollusks

Goniobasis livescens (Say)
Somatogyrus sp.
Amnicola lustrica (Pilsbry)

Gastropod
Gastropod
Gastropod

Freshwater snail
Freshwater snail
Freshwater snail

Mollusks
Mollusks
Mollusks
Mollusks
Mollusks
Mollusks
Mollusks

346

Table 27. (cont’d)
Type category
Mollusks

Species
Lymnaea columella (Say)

Common Name
Gastropod - "American ribbed fluke snail"

Type
Freshwater snail

Mollusks

Helisoma Campanulatum

Gastropod

Freshwater snail

Mollusks

Stenotrema monodon (Racket) Gastropod

Terrestrial snail

Mollusks

Mesodon thyroidus (Say)

Gastropod - white-lip globe

Terrestrial snail

Mollusks

Triodopsis albolabris (Say)

Gastropod

Terrestrial snail

Mollusks

Triodopsis multilineata (Say)

Gastropod - AKA Webbhelix genus

Terrestrial snail

Mollusks

Anguispira alternata

Gastropod - flamed disc or flamed
tigersnail

Terrestrial snail

Mollusks

Anguispira solitaria (Say)

Gastropod

Terrestrial snail

Mollusks

Helicodiscus parallelus (Say)

Gastropod - compound coil

Terrestrial snail

Mollusks

Haplotrema concavium (Say)

Gastropod - gray-footed lancetooth

Terrestrial snail

Mollusks
Mollusks
Mollusks

Mesomphix cuprea (Say)
Amnicola Limosa (Say)
Pomatiopsis lapidaria (Say)

Gastropod
Gastropod
Gastropod

Terrestrial snail
Freshwater snail
Freshwater snail

347

Table 27. (cont’d)
Type category
Mollusks

Common Name
Gastropod - marsh snail

Type
Freshwater snail

Mollusks
Mollusks
Mollusks

Species
Lymnaea (Staginicola) palustris
(Say)
Helisoma trivolvis (Say)
Retinella rhoadsi (Pilsbry)
Succinea ovalis (Say)

Gastropod
Gastropod
Gastropod - oval ambersnail

Freshwater snail
Terrestrial snail
Terrestrial snail

Mollusks

Campeloma decisum (Say)

Gastropod

Freshwater snail

Mollusks

Helisoma anceps (Conrad)

Gastropod

Freshwater snail

Mollusks
Mollusks

Zonitidae
Pelecypoda

mollusk
mollusk

348

Table 28. Resource calories, size and weight
Species
Cervus canadensis

Avg. Caloric Return
496 calories cooked/raw lb.

Odocoileus virginianus

537 calories cooked/raw lb.

Procyon lotor

1017 calories cooked/raw lb.

Ursus americanus

717 calories, cooked/raw lb.

Castor canadensis

664 calories, cooked/raw lb.

Ondatra zibethicus

732 calories cooked/raw lb.

Canis sp. (lupus,
familiaris)
Martes americana

Marmota monax
Mustela vison
Lynx rufus
Erethizon dorsatum
Lontra canadensis

Avg. Size
Length: 92-108 in. male, 84-96 in.
female. Height: 57-69 in. male, 37-45
in. female.
Length: 75 to 85 in. males, 63 to 79
in. females
Length: 23.5 in + tail (9.5 in)

Avg. Weight
580-1000 lbs. male, 500-650
lbs. female

Length: 54 to 70 in. males; 47 to 50
in. females
Length: 36 to 43 in. adults + tail
(11.75-13.75 in.)
Length: 18.5 in. adult. Height: not
listed
Length: 61 in. male, 59 in. females

250 to 500 lbs. males; 225 to
450 lbs. females
30 to 60 lbs. in adults

Length: 16.5 in. males, 14.75 in.
females. Tails about 1/3 the length of
animal's body.
Length: 18 in. + tail, adult.
Length: 14.75 in. male, 13 in female
(+tail).
Length: 29.5 male, 26.75 female.
Length: 22 in (+~8 in. tail)
Length: 37.5 in to 51.5 in males, 35.5
to 45.5 in females

35.25 to 51.25 oz. in males,
25.5 to 35.25 in females.

349

150 to 310 lbs. males, 90 to 210
lbs. females
12 to 30 lbs.

28 to 53 oz.
67.3 lbs. male, 57.9 lbs. female

5 to 12 lbs., adults.
20 to 44 oz. Male, 17 to 33.5 oz.
female.
14-40 lbs. Male, 9 to 36 female.
14.4 lbs. male, 14.8 lbs. female
15 to 30 lbs. male, 10 to 25 lbs.
female

Table 28. (cont’d)
Species
Martes pennanti

Avg. Caloric Return

Avg. Size
Length: 36.25 to 41.25 in. males, 31.5
to 35.5 in. females (+tail length)

Avg. Weight
6.0 to 12.0 lbs. male, 4.0 to 6.5
lbs. female

Sciurus sp.

541 calories cooked/raw lb.

12 to 24 oz. In adults

Leporidae sp. (Sylvilagus)

32 calories per oz.

Length:16.5 to 21 in.+ tail (8-10 in.)
adults
Length: 15.75 to 19.25 in

Blarina sp.
Tamias sp.
Muridae sp.
Peromyscus sp.
Microtus sp.

Length: 38 in. males, 41 in. females
Length: 90 to 104 in.; Width: 71 in.
males, 69 in. females.
Length: 4.25 to 5.5 in
Length: 9 to 11 in.
Length: 5 7/8 to 17.5 in.
Length: 5 5/8 to 7 5/8 inches
Length: 4 7/8 to 6 1/8 inches

8 to 15 lbs.
725 to 850 lbs. females; 850 to
1,200 lbs. males
0.5 to 1 oz.
2.4 to 4.0 oz.
0.5 to 17 oz.
0.5 to 1 oz.
1.1 to 1.8 oz.

Acipenser fulvescens
Perca flavescens
Amia calva
Aplodinotus grunniens
Monroe chrysops
Micropterus salmoides
Micropterus dolomieui
Esox lucius
Stizostedion vitreum
Ictalurus punctatus
Lepisosteus oculatus
Salvelinus namaycush

20 to 55 in.
8 to 11 in.
12 to 24 in.
10 to 14 in.
Length: 45 cm. maximum
12 to 20 in.
12 to 20 in.
18 to 24 in.
14 to 17 in.
12 to 20 in.
24 to 36 in.
60 cm (24 inches)

5 to 40 lbs.
6 to 10 oz.
2 to 5 lbs.
2 to 5 lbs.
3.5 lbs. maximum
1 to 5 lbs.
1 to 4 lbs.
2 to 5 lbs.
1 to 3 lbs.
3 to 4 lbs.
2 to 5 lbs.
7 to 10 lbs.

Vulpes fulva
Alces alces

350

32 to 64 oz.

Table 28. (cont’d)
Species
Ictalurus melas
Ictalurus natalis
Ictalurus nebulosus
Moxostoma sp.
(macrolepidotum)
Pomoxis sp.
Catostomus sp.
(catostomus,
commersoni)
Centrarchidae

Avg. Caloric Return

Avg. Size
8 to 10 in.
8 to 10 in.
8 to 10 in.
12 to 24 in.

Avg. Weight
4 to 6 oz.
1 to 2 lbs.
4 oz. to 2 lbs.
2 to 10 lbs.

7 to 12 in.
15 to 20 in.

10 oz. to 1 lb.
2 lbs.

3 to 11 in. depending on species

4 oz. to 1 lb.

Lepomis cf. macrochirus
Pomoxis nigromaculatus
Stizostedion canadense
Lota lota lacustris

12-30 cm
Up to 40 cm
Up to 50 cm
Up to 80 cm

5-10 oz.
10 oz. to 1 lb.
8 oz. to 2 lbs.
Around 1 lb.

Ectopistes migratorius
Anas discors

Length: 15.5 inches (39 cm),
wingspan 23 inches
Length: 19 inches (48 cm), wingspan
32 inches
Length: 23 inches (58 cm), wingspan
35 inches
Length: 17 inches; wingspan 25
inches
Length: 25 inches; wingspan 34
inches

13 oz.

97 calories per 3 oz. meat

Anas americana
Anas platyrhynchos
Aythya collaris
Mergus merganser

472 calories per 1 cup meat

351

1.6 lbs.
2.4 lbs.
1.5 lbs.
3.4 lbs.

Table 28. (cont’d)
Species
Mergus serrator

Avg. Weight
2.3 lbs.

Bubo virginianus

Avg. Size
Length: 23 inches; wingspan 30
inches
Length: 32 inches; wingspan, 46
inches
Length: 13 inches; wingspan 16
inches
Length: 37 inches female, 46 inches
male; wingspan 50 inches female, 64
inches male
Length: 18 inches; wingspan 24
inches
Length: 17.5 inches; wingspan 39
inches
Length: 28 inches; wingspan, 42
inches
Length: 46 inches; wingspan 72
inches
Length: 41-46 inches; wingspan 73-77
inches
42–51 cm long with a 71–80 cm
wingspan
Wingspan 4-5 ft.

Chenopodium

Stem 1-3 dm long; seeds 1 mm wide.

-

Zea mays
Iva annua

-

-

Gavia immer
Podilymbus podiceps
Meleagris gallopavo

Lophodytes cucullatus
Corvus brachyrhynchos
Botaurus lentiginosus
Ardea herodias
Grus canadensis
Aythya marila

Avg. Caloric Return

352

9 lbs.
1 lb.
9.2 lbs. female, 16.2 lbs. male

1.4 lbs.
1 lb.
1.5 lbs.
5.3 lbs.
7.3-10.6 lbs.
-

Table 28. (cont’d)
Species
Carex sp.
Cyperus
Zizania aquatica

Avg. Caloric Return

166 calories per 1 cup

Quercus
Carya
J. cinerea
Juglans nigra

178 calories per 1 oz.

Avg. Weight
-

Up to 10 feet (3 meters)

-

Up to 18-25 m high and 50-100 cm in
diameter
Up to 2 m long
30 ft. high, 14 inches in diameter
Up to 12 inches (30 cm)
Up to 15 feet (4.5m)
Stems 3-8 dm long; fruit 1-4 cm long

-

Up to 8 inches (20 cm)
Stems 2-8 dm long
Up to 10 feet (3 meters)
Stems 1-4 dm long

-

12-18 m high and 30-60 cm in
diameter
Fruit 6-12 mm wide.

-

-

185 calories per 1 oz.

Corylus americana

Avg. Size
Stems 3-10 dm long
Stems 5-30 cm tall
Stems 1-3 meters long; grain 1-2 cm
long
Up to 80 feet (24 meters)

Castanea dentata
Cucurbita pepo
Amphicarpaea bracteata
Geranium maculatum
Pyrus sp.
Physalis
Convolvulaceae
Brassicaceae sp.
Fragaria virginiana
Galium aparine
Helianthus divaricatus
Polygala senega
Rubus occidentalis
Celtis occidentalis
Vitis sp.

353

-

-

-

Table 28. (cont’d)
Species
Crataegus sp.
Viburnum sp.
Rhus sp
Polygonum
pensylvanicum
Prunus spp.
Sambucus canadensis
Prunus serotina
Amelanc (Amelanchier
Medikus)
Aster cordifolius
Sassafras albidum
Hypericum
Cornus rugosa
Gaylussacia baccata

Lamiaceae
Rosa palustris

Pinus
Fraxinus alba

Avg. Caloric Return

Avg. Size

Avg. Weight

Up to 12 feet (3.6 m)
Up to 2 m high
Stems erect, 3-20 dm long; fruit up to
3 mm long.
Up to 25 feet (7.5 m)
Up to 3 meters tall

-

Up to 2 meters tall; fruit 1 cm long.

-

Up to 12 inches (30 cm)
6-15 m high and 20-60 cm in
diameter
Fruit a 4-6mm capsulate.
1-3 m tall
Stems 3-10 dm long; leaves 2-5 cm
long and 1-2.5 cm wide; flowers 4-6
mm long; fruit 6-8 mm long (with 10
nutlets)
Shrub 2 meters tall; leaflets 2-6 cm
long/1-2 cm wide; fruit 1-10 mm
wide.
Up to 100 feet (30 m)
Tree up to 15 meters tall; trunk 30-60
cm wide; fruit 2.5-5 cm long, 6-10
mm wide.

-

354

-

-

-

-

Table 28. (cont’d)
Species
P. resinosa
P. strobus
Ulmus rubra
Ulmus sp.
Cercis canadensis
Tilia americana
Q. nigra
Q. bicolor
Q. rubra
Populus tremuloides
Carya laciniosa
Carya ovata
Cornus racemosa
Fagus americana
Ostraya virginiana

Avg. Caloric Return

Avg. Size
20-30 m high and 60-100 cm in
diameter
20-30 m high and 60-100 cm in
diameter
15-21 m high and 30-60 cm in
diameter
Up to 60 feet (18 m)
4-8 m tall and 20-30 cm in diameter
Up to 80 feet (24 m); 40-120 cm in
diameter
18-24 m high and 40-120 cm in
diameter
15-21 m high and 60-100 cm in
diameter
20-30 m high and 40-100 cm in
diameter
18-25 m high and 100-150 cm in
diameter
18-22 m high and 60-80 cm in
diameter
18-22 m high and 30-80 cm in
diameter
Shrub 1-3 meters tall; fruit 5 mm
wide
Up to 18-26 m high and 50-100 cm in
diameter
Up to 50 feet (15 m); 20-30 cm in
diameter
355

Avg. Weight
-

-

-

-

Table 28. (cont’d)
Species
Fraxinus sp

Fagus grandifolia
Acer spp.
Betula spp.
Morus rubra
Platanus occidentalis

Picea
Typha
Rumex spp.
Panicum spp.
Silphium
terebinthinaceum
Smilacina racemosa
Smilacina stellata
Maianthemum
canadense
Onoclea Sensibilis
Poa pratensis

Avg. Caloric Return

Avg. Size
Tree up to 15 meters tall; trunk 30-60
cm wide; fruit 2.5-5 cm long, 6-10
mm wide.
Up to 100 feet (30 m)
Up to 100 feet, depending on species.

Avg. Weight
-

Up to 100 feet (30 meters)depending
on species
Up to 30 feet (9 m)
30 meters tall or more; trunk up to 2
meters wide; leaves 20 cm long and
wide; fruit 2-3 cm wide.
Up to 25-30 meters tall; 75 feet for
some species
1-2.5 meter high; fruit 1 cm long
Stems stout, to 12 dm long
Stems 6-15 dm long; head (panicle) 515 cm long above the stem
Stems 1-3 m long

-

Stems 1-5 dm long
Stems 1-5 dm long
Stems 5-20 cm long

-

Leaf blades 15-40 cm long and 15-35
cm wide total
Stems 4-12 dm long, head 1-3 dm
long

-

356

-

-

-

-

Table 28. (cont’d)
Species
Smilax lasioneura
Solidago Sp.

Thalictrum dioicum
Viola pensylvanica
Viola sororia (Sens. Lat.)
(Glabrous plants like this
one have been referred
to V. Papilionacea)
Zanthoxylum
americanum
Lilium michiganense
Lysimachia ciliata
Carex blanda
Carex lupulina
Carex pensylvanica
Smilax cirrata
Toxicodendron radicans
Apocynum
androsaemifolium
Aquilegia canadensis
Aralia nudicaulis

Avg. Caloric Return

Avg. Size
10 m long
Stems 0.5-2 m long; leaves 6-15 cm
long/1-4 cm wide; fruit 1-2 mm long

Avg. Weight
-

Stems 1-2 m long
Leaves from base of plant, 10 cm
wide
Leaves from base of plant, 10 cm
wide

-

Up to 3 m tall

-

Stems 3-8 dm long; leaves 4-10 cm
long and 3-8 mm wide
Stems 3-12 dm long; leaves 4-15 cm
long and 2-3 cm wide
Stems 3-10 dm long
Stems 3-12 dm long; leaves 4-15mm
wide
Stems 3-10 dm long
10 m long
Over 1 m long
-

-

Up to 4 ft. (1.2 m)
Up to 16 inches (40 cm)

-

357

-

Table 28. (cont’d)
Species
Barbarea vulgaris
Geum canadense
Satureja vulgaris
Monarda fistulosa
Osmorhiza longistylis
Podophyllum peltatum
Trillium grandiflorum
Lithospermum canescens
Taraxacum officinale
Anura sp.
Emydoidea blandingii
Chrysemys picta
Chelydra serpentina
Nerodia sipedon
Thamnophis sp.
Trionyx sp.

Avg. Caloric Return

Avg. Size
Stems 3-8 dm long, fruit 2-4 cm long

Avg. Weight
-

Stems up to 1 m long
Up to 12 inches (30 cm)
9.5 to 20.3 cm (3.7 to 8 inches)
Adult carapace length: 15.2 to 27.4
cm (6 to 10.8 inches)
Adult carapace length: 9 to 25 cm
(3.5 to 9.8 inches)
Adult carapace length: 20.3 to 50.3
cm (8 to 19.8 inches)
Adult Length: 61 to 140.5 cm (24 to
55.3 in.)
Adult Length: 46 to 137 ch (18 to 54
inches)
Adult male carapace length: 24 to 48
cm (9.4 to 18.9 inches); adult female
carapace length: 12.7 to 24 cm (5 to
9.4 inches)

-

Amblema costata
Elliptio dilatatus
Fusconaia flava (Raf.)

Female avg. weight: 6.4 kg (14
lbs.); Male avg. weight:
-

358

Table 28. (cont’d)
Species
Avg. Caloric Return
Quadrula pustulosa (Lea)
Pleurobema (cordatum)
coccineum (Conrad)
Cyclonaias tuberculata
Lasmigona costata (Raf.)
Strophitus rugosus
(Swain.)
Lampsilis siliquoidea (L)
Obovaria subrotunda
(Raf.)
Ligumia (Recta)
lattissima (Raf.)
Actinonaias carinata
(Barnes)
Discus cronkhitei
Anguispira kochi
Anodonta grandis
footiana (Say) Goodrich
Micromya (Villosa) Iris
(Lea) Goodrich
Amblema costata
(Rafinesque) Goodrich
Ligumia recta (Lamarck)
Goodrich
Valvata tricarinata (Say)
Goniobasis livescens
(Say)

Avg. Size

Avg. Weight
-

Up to 6 inches long

-

359

Table 28. (cont’d)
Species
Somatogyrus sp.

Amnicola lustrica
(Pilsbry)
Lymnaea columella (Say)
Helisoma Campanulatum
Stenotrema monodon
(Racket)
Mesodon thyroidus (Say)
Triodopsis albolabris
(Say)
Triodopsis multilineata
(Say)
Anguispira alternata
Anguispira solitaria (Say)
Helicodiscus parallelus
(Say)
Haplotrema concavium
(Say)
Mesomphix cuprea (Say)
Amnicola Limosa (Say)
Pomatiopsis lapidaria
(Say)
Lymnaea (Staginicola)
palustris (Say)
Helisoma trivolvis (Say)
Retinella rhoadsi

Avg. Caloric Return

Avg. Size
Shell large, greatest diameter more
than 12 mm; lip usually thickened

Avg. Weight
-

-

5 to 10 mm long

-

360

Table 28. (cont’d)
Species
(Pilsbry)
Succinea ovalis (Say)
Campeloma decisum
(Say)
Helisoma anceps
(Conrad)
Zonitidae
Pelecypoda

Avg. Caloric Return

Avg. Size

Avg. Weight

-

-

361

Table 29. Resource habitat, distribution, density
Species
Cervus canadensis

Habitat/Resource Community
Mixture of woodlands, shrubs,
and open lands.

Distribution
Prehistoric (post-glacial up to early days
of settlement) distribution covers the
whole Lower Peninsula.

Density
4.4 per sq. mi.

Odocoileus virginianus

Boreal conifer-hardwood forest;
temperate hardwood forest

Large geographic range in the Americas;
boreal, temperate, tropical
environments, international; found
prehistorically in Michigan

1 animal per 6.4-8.0
acres

Procyon lotor

Lakeshores, inland forests,
hardwoods

Ursus americanus

All counties in both Upper and Lower
1 animal per 10-16 acres
Michigan, dating even back to postglacial
period, Woodland period
Temperate and boreal North America
1 animal per 10-16 acres

Northern hardwood and conifer
forests of the Canadian biotic
province; southeastern hardwood
forests of the Carolinian biotic
province.
Semiaquatic areas; must be
Extensive North American geographic
associated with proper vegetative range; found on all major waterways in
growth
Michigan as well as swamps, marshes,
and lakes.

Castor canadensis

362

Variable depending on
bodies of water; up to
about 15 per square
mile

Table 29. (cont'd)
Species
Ondatra zibethicus

Habitat/Resource Community
Semi-aquatic; marshes,
waterways, swamps

Canis sp. (lupus,
familiaris)

The ray wolf, in presettlement
Michigan, was probably a forest
creature that frequented
openings, lakeshores, and
riparian growth along streams.
Boreal coniferous forests

Martes americana

Marmota monax

Fertilized pasturage; basically
areas of human occupation.

Mustela vison

Streams, rivers, lakes, ponds,
marshes.

Lynx rufus

Hardwood forests, mountains,
deserts; usually needs woody
cover.
Northeastern North America;
deciduous, coniferous forests;
hemlock, pine habitats
Abundant Aquatic habitats

Erethizon dorsatum

Lontra canadensis

Distribution
Northern North America from tree line in
the Arctic southward to the Gulf Coast
on the east and to near the Mexican
border; widely distributed all over
Michigan.
Arctic and down south into the United
States and Central Mexico, although
unwelcome near human settlement, so
species is not often seen in the southern
part of its North American range.
Prehistoric distribution: marten may
have been in all counties of Michigan,
but they may have preferred northern
regions.
Occurs in most of North America; the
animal is widespread in both peninsulas
of Michigan.
Temperate, boreal North America; In
Michigan, Upper and Lower Peninsulas,
almost all counties.
Temperate hardwoods, like those in
Michigan.

Density
15-16 per mile

Boreal North America, coniferous forest
NE US

30 per sq. mi.

Arctic, boreal, temperate North America

1 per 2.2 mi of
waterway

363

1 individual per 5.2 to
10.5 sq. mi

0.5 to 6.2 individuals/sq.
mi.

30-40 per 640 acres

Hunting season: 8.5-22
per sq. mi; Other times,
3-4 per sq. mi.
1 per sq. mile

Table 29. (cont'd)
Species
Martes pennanti

Sciurus sp.

Leporidae sp.
(Sylvilagus)

Vulpes fulva

Alces alces

Habitat/Resource Community
Northern coniferous, mixed
conifer-hardwood, and hardwood
stands
Woods areas; mature groves of
nut-bearing oaks, hickories, and
beeches, maples, hemlockhardwoods.
Areas of cleared/covered with
second-growth shrubs, vines, and
low trees; forests of southern
Michigan are preferred habitats
for the cottontail; snowshoe hare
lives in woody protection,
northern swamps, and bushy
understory of trees.
Fallow and cultivated fields,
meadows, bushy fence lines,
woody stream borders, and low
shrub cover along the fringes of
woods and along beaches
bordering larger lakes; the fox
has been a longtime resident of
Michigan.
Northern boreal forests

Distribution
Northern coniferous and hardwood
forests across North America

Density
1 to 4 per sq. mi.

Eastern North America, extending
westward to the prairies

Avg. 2 per acre

In Michigan, mixed woodlots, cultivated
and fallow fields, and fencerow/roadside vegetation.

High densities, up to 100
rabbits in a two-acre
orchard

In North America, the red fox occurs
from the Arctic Ocean and some of the
islands in the Canadian Archipelago
south to the Gulf coast and west to
California; In Michigan, the red fox lives
in every county of the state and on
several of the larger islands in lakes
Michigan, Superior, and Huron.
Within the northern boreal forests of
North America; broadly across Alaska
and Canada; boreal parts of northern US,
and most of Michigan except for the
southern and southwestern parts of the

One fox family (~7
individuals) per 2,471
acres.

364

One moose per square
mile in average boreal
habitat, and three
moose per square mile
in most favorable

Table 29. (cont'd)
Species

Habitat/Resource Community

Distribution
Lower Peninsula.

Density
habitat.

Blarina sp.

Varied living conditions –
swamps, bogs, moist lowlands to
dry uplands, sand dunes;
however, moist, litter-strewn
forested areas are considered
prime living places.
Deciduous hardwoods of both
the Upper and Lower Peninsulas

In Michigan, species occurs in all
counties and most terrestrial
communities.

Most common of all
mammals in the Upper
Great Lakes Region; in
the LP of Michigan, at
least 4 shrews per acre.

At home in both Upper and Lower
Peninsulas, occurring in all counties on
several islands in Lake Michigan.
Mice in most Michigan environments
except dense woodlands, marshes, and
northern swamps; rats prefer to
concentrate where food supplies and
cover sites are abundant.

20 or more per acre

Tamias sp.

Muridae sp.

Peromyscus sp.

Microtus sp.

Rats are attracted towards
human settlement areas; mice
are the same way, where they
are attracted to human
habitations where scrap food,
stored grains, and poorly cached
garage provides nourishment.
Woodlands and brushlands;
active on litter-strewn forest
floor.
Grass and mixed grass and weeds
where vegetation is rank and
lush.

Stationary in
environment; number is
variable

US as far west as the Great Plains; Occurs Anywhere from 0.9 to
throughout the Lower Peninsula of
9.7 per acre
Michigan, as well as southwestern parts
of the Upper Peninsula.
Southwestern Michigan
10 individuals per acre

365

Table 29. (cont'd)
Species
Acipenser fulvescens

Habitat/Resource Community
Quiet waters of large rivers and
streams

Perca flavescens

Lakes and streams preferring
clear open water

Amia calva

Deep waters associated with
weedbeds in warn water lakes
and rivers; feeds in shallow
weeds
Slow-to-moderate current areas
of rivers and streams; shallow
lakes, often with mud or sand
bottoms; prefers turbid (cloudy)
water
Migratory in large, open rivers,
impoundments, and lakes; often
in large schools at the surface.
Shallow, fertile, weedy lakes and
river backwaters; weedy bays and
extensive weedbeds of larger
lakes

Aplodinotus grunniens

Monroe chrysops

Micropterus salmoides

Micropterus dolomieui

Clear, swift-flowing streams and
rivers; clear lakes with gravel or
rocky shorelines

Distribution
Hudson Bay, Great Lakes, Mississippi and
Missouri drainages southeast to
Alabama; in Michigan, lakes Superior,
Michigan, Huron and a few large
tributary streams
Widely introduced throughout northern
US and southern Canada; common
throughout Michigan
Mississippi River east through St.
Lawrence drainage, south from Texas to
Florida; common throughout the Lower
Peninsula of Michigan
Canada south through Midwest into
eastern Mexico to Guatemala; in
Michigan, rare inland, common in lakes
St. Clair, Erie, and Michigan, and in
Saginaw Bay
In Great Lakes- St. Lawrence dr.

Density
n/a

Southern Canada through US into
Mexico, widely introduced; common
throughout Michigan, including the
Upper Peninsula where it is a recent
introduction
Extensively introduced throughout North
America; common throughout Michigan,
in both the Upper and Lower Peninsula

n/a

366

n/a

n/a

n/a

n/a

n/a

Table 29. (cont'd)
Species
Esox lucius

Stizostedion vitreum

Ictalurus punctatus

Lepisosteus oculatus

Salvelinus namaycush

Ictalurus melas

Habitat/Resource Community
Lakes, ponds, streams and rivers;
often found near weeds; small
pike tolerate water temperatures
up to 70 degrees but larger fish
prefer cooler water, 55 degrees F
or less
Lakes and streams, abundant in
very large lakes

Distribution
Northern Europe, Asia and North
America; common throughout Michigan
and in the shallows of all three Great
Lakes

Originally the northern states and
Canada, now widely stocked in the U.S.;
common in all but the south-western
part of Michigan
Prefers clean, fast-moving
Southern Canada through the Midwest
streams with deep pools; stocked into Mexico and Florida; introduced
in many lakes can tolerate turbid through much of the US; known from all
water
Great Lake drainages in the southern half
of Michigan
Floodplain lakes and backwaters
Central US through the Mississippi
of large rivers
drainage south into Mexico; in Michigan,
common in all Lower Peninsula
drainages
Cold (less than 65 degrees),
Great Lakes north through Canada, to
oxygen-rich waters of deep, clear, northeaster US, stocked in the Rocky
infertile lakes
Mountains; deep, cold lakes in the
northwest corner of the lower Peninsula,
lakes Superior and Michigan
Shallow, slow-moving streams
Southern Canada through the Great
and backwaters; lakes and ponds- Lakes and the Mississippi River
tolerates extremely turbid
watershed into Mexico and the
(cloudy) conditions
Southwest; common throughout
Michigan
367

Density
n/a

n/a

n/a

n/a

n/a

n/a

Table 29. (cont'd)
Species
Ictalurus natalis

Habitat/Resource Community
Warm, weedy lakes and sluggish
streams

Ictalurus nebulosus

Warm, weedy lakes and sluggish
streams

Moxostoma sp.
(macrolepidotum)

Clean streams and rivers with
sand, gravel or rocky bottom;
found in a few clear lakes
Quiet, clear water of streams and
mid-sized lakes; often associated
with weed growth but may roam
deep, open basins and flats,
particularly during winter
Primarily shallow waters of large, Siberia across Canada through Great
cold lakes and streams;
Lakes to the eastern US; in Michigan,
sometimes found in deeper water lakes Superior, Huron, Michigan, and
their tributaries
Avg. warm, clear, moderately
Common throughout Michigan
weedy waters
In vegetated lakes and quiet
Mississippi drainage; Great Lakes – St.
streams. Weedy bays or
Lawrence – Champlain drainage. All of
shorelines
Michigan area.

Pomoxis sp.

Catostomus sp.
(catostomus,
commersoni)
Centrarchidae
Lepomis cf. macrochirus

Distribution
Southern Great Lakes through the
eastern half of the U.S. To the Gulf and
into Mexico; introduced in the West;
common in Michigan's Lower Peninsula,
rare in the Upper Peninsula
Southern Canada through the Great
Lakes down the eastern states to Florida,
introduced in the West; most common in
southern Michigan but represented
throughout the state including the Upper
Peninsula
Great Lake states to New England south
to the Gulf; clear, clean streams and a
few lakes throughout Michigan
Southern Manitoba through the Atlantic
and southeastern states, introduced in
the West; common in all three Michigan
drainages

368

Density
n/a

n/a

n/a

n/a

n/a

n/a
n/a

Table 29. (cont'd)
Species
Pomoxis nigromaculatus

Stizostedion canadense
Lota lota lacustris

Ectopistes migratorius

Anas discors

Habitat/Resource Community
Chiefly in clear, weedy lakes,
usually in larger streams, lakes,
and impoundments.
Most often in somewhat silty
rivers and large lakes.
In medium to large streams and
cold, deep lakes. Builds and
inhabits trenches at the bottom
of Great Lakes. Also in larger
streams, preferring patches of
plants and debris when young,
stony riffles when half-grown,
and undercut banks when adult.
Hardwood growths; large nesting
or roosting sites located in or
near areas of abundant
hardwood timber. Trees such as
beech, maple, birch, oak,
tamarack, cedar, hemlock, pine
were used often for nesting.
Marshes, grassy ponds and
sluggish streams; partial to
regions where wild rice grows.
Often nests on the ground in
meadows or prairies.

Distribution
Great Lakes- St. Lawrence to L.
Champlain; all of Michigan area.

Density
n/a

Great Lakes- St. Lawrence drainage (rare) n/a
N America south to Columbia, Missouri,
Mississippi, Hudson Bay, Ungava Bay,
Great Lakes – St. Lawrence, Delaware,
and Ohio drainages.

n/a

Formerly eastern North America, from
Hudson Bay southward, and west to the
Great Plains, straggling thence to Nevada
and Washington. Breeding range mainly
restricted to portions of Canada and
northern border of the United States as
far west as Manitoba and the Dakotas.
Now extinct.
North America in general, but chiefly
eastward; north to Alaska, and south to
the West Indies, Lower California, and
northern South America. Casual in
California. Breeds from Kansas and
Illinois northward. The most abundant
summer duck found in Michigan

During nesting season,
up to 110 birds per tree
in a 100,000 acre area.

369

Flocks of up to 30 are
often seen through fall

Table 29. (cont'd)
Species
Anas americana

Anas platyrhynchos

Aythya collaris

Mergus merganser

Mergus serrator

Habitat/Resource Community
Open waters

Distribution
North America, from the Arctic Ocean
south, in winter to Guatemala and Cuba.
Breeds chiefly north of the United States,
and west of the Mississippi. Not the
most common duck in the state of
Michigan.
Typical marsh or shallow water
Northern parts of Northern Hemisphere;
duck. Often visits stubble fields
in America south to Panama and Cuba,
and meadows long distances
breeding southward to southern United
from water; also found on
States; less common in the east;
islands, marshy ponds.
common throughout the state of
Michigan. The most abundant species of
duck found in the state.
Prefers inland waters, ponds, and North America; breeding far north and
marshy streams rather than the
migrating south to Guatemala and the
open waters.
West Indies (throughout Michigan)
Occurs in the spring and fall on all Generally distributed throughout the
the waters of the state, the
state of Michigan. North America
smaller ponds and streams as
generally breeding south in the United
well as the shores of the Great
States to Pennsylvania and the
Lakes. It nests from the Saginaw
mountains of Colorado and California.
Valley northward.
Ponds and streams in the interior Northern portions of the Northern
and as well as on the Great Lakes. Hemisphere; south in winter throughout
the United States (so, throughout
Michigan)

370

Density
Dozens to hundreds
seen by bodies of water

Near bodies of water,
avg. of up to 50 mallards
per day

Dozens to hundreds
seen by bodies of water
Up to hundreds seen
near bodies of water

50-hundreds seen near
bodies of water and
flocks in flight

Table 29. (cont'd)
Species
Gavia immer

Habitat/Resource Community
Streams ponds and lakes of the
state. Nesting takes place on the
mainland, islands in inland lakes,
or at the edge of a pond.

Podilymbus podiceps

Nests abundantly in every
suitable place in the state,
building a floating nest;
therefore, during nesting it keeps
to marshes and rank vegetation
along the borders of streams and
ponds for cover.
Along wooded river valleys

Meleagris gallopavo

Distribution
Generally distributed throughout
Michigan; hardly a stream or pond on
which Loons are not seen each season.
Northern part of Northern Hemisphere.
In North America breeds from the
northern tier of states northward; ranges
in winter south to the Gulf of Mexico and
lower California.
British Provinces southward to Brazil,
Argentine Republic and Chile, including
the West Indies and Bermuda; breeding
nearly throughout its range. In Michigan,
very generally distributed and absent
only during the winter months.

Density
Found in small numbers,
like pairs

United States from Chesapeake Bay to
the Gulf coast, and west to the Plains,
along wooded river valleys; formerly
north to southern Maine, southern
Ontario, and up the Missouri River to
North Dakota. Formerly was an
abundant bird at least as far north as
Saginaw Valley of Michigan.

Have been spotted in
flocks of 30 in the Lower
Peninsula

371

Density unclear;
reportedly 15-60 grebes
seen in a single marshy
area

Table 29. (cont'd)
Species
Lophodytes cucullatus

Corvus brachyrhynchos

Habitat/Resource Community
Alongside streams of the Lower
Peninsula, as well as in the
northern parts of the state; nests
in hollows of trees. Partial to the
smaller and more rapid streams,
and remains in the winter
wherever open running water
supplies food.
Distributed throughout various
habitats

Botaurus lentiginosus

Wades in bodies of water; nests
on the ground in marshy places

Ardea herodias

Found especially near bodies of
water; rivers, streams, lakes,
shores, swamps, marshes

Grus canadensis

Found in wet places; pastures,
marshes, swamps

Distribution
North America generally, south to
Mexico and Cuba, breeding nearly
throughout its range.. Casual in Europe.
A common migrant throughout
Michigan.

Density
Small amounts in spring;
1-50 in a flock; in fall, up
to 50 in a flock

North America, from the Fur Countries to
the southern border of the United
States. Locally distributed in the West. In
Michigan, the crow is an abundant bird
during the larger part of the year, and
some even stay during severe winters.
Temperate North America, south to
Guatemala, Cuba, Jamaica, and
Bermuda; occasional in the British
Islands. Abundant throughout Michigan.

Being a common
summer resident, there
are larger numbers in
areas during the
summer; flocks of up to
around 50-100 birds
Said to be one of the
most abundant in
Michigan, but no
number estimates are
given.
Colonies can consist of
tens to hundreds of
pairs of great blue
herons

North America from the Arctic regions
southward to the West Indies and
northern South America; Bermuda’s;
Galapagos; present throughout
Michigan.
Southern half of North America; now
rare near the Atlantic coast, except in
Georgia and Florida; however, found
throughout Michigan.

372

Flocks can consist of up
to 15-20 cranes; can be
made up of notably
smaller groups too

Table 29. (cont'd)
Species
Aythya marila

Habitat/Resource Community
Remains in the open waters of
the state.

Bubo virginianus

The great horned owl appears to
be resident wherever found and
wherever any considerable
patches of timber remain.

Distribution
Density
North America, breeding far north. South According to Wood, up
in winter to Guatemala.
to thousands can be
seen in one area while
they are in Michigan.
Generally distributed throughout the
1 pair of great horned
state of Michigan.
owls to ever 2 square
miles.

373

Table 29. (cont'd)
Species
Chenopodium

Habitat/Resource Community
Shores, streambanks, and
disturbed areas; Southern Mesic,
Beech-Maple Community;
Nothern and Southern Mesic,
Beech-Hardwood-Pine
Community; Southern Mesic,
Beech-Maple Community;
Nothern and Southern Mesic,
Hardwood Community; Southern
and Northern Dry-Mesic,
Hardwood Community; Nothern
and Southern Mesic, Hardwood
Community; Nothern and
Southern Wet-Mesic, Hemlock
and Hardwood Community;
Northern and Southern WetMesic, Hardwood Community;
Northern and Southern Mesic,
Beech-Hardwood-Pine
Community; Northern and
Southern Wet-Mesic, Hemlock
and Hardwood Community;
Northern and Southern WetMesic, Hardwood Community;
Southern and Northern DryMesic, Hardwood Community

Distribution
West Minnesota, Wisconsin, mostly
Lower Peninsula of Michigan

Zea mays

Density
51,451.2/km^2
(Modern: 121,939.3)

n/a

374

Table 29. (cont'd)
Species
Iva annua

Carex sp.
Cyperus

Zizania aquatica

Habitat/Resource Community
Northern Mesic to Wet-Mesic,
Lowland Swamp Community;
Northern and Southern WetMesic, Hemlock and Hardwood
Community; Northern and
Southern Wet-Mesic, Hardwood
Community
Floodplain forests and backwater
areas
Wet sandy or mucky shores and
wet meadows; ditches, floating
mats, muddy shores, wet
cultivated fields
Shallow water (up to 1 m deep)
or mud of streams, rivers, lakes,
ponds; where water is slightly
flowing and not stagnant; soils
vary from muck to silt, sand, or
gravel, with best establishment of
plants on a layer of soft silt or
muck several cm thick.

Distribution

Density
33,921.9/Sp D/km^2;
(Modern 3,463,933.6)

Common in LP of Michigan

n/a

Found throughout Michigan

n/a

Minnesota, Wisconsin, Michigan (both
peninsulas)

n/a

375

Table 29. (cont'd)
Species
Quercus

Carya

Habitat/Resource Community
Southern and Northern DryMesic, Hardwood Community;
Northern and Southern Mesic,
Hardwood Community; Northern
and Southern Mesic, BeechHardwood-Pine Community;
Northern and southern WetMesic, Hardwood Community;
Northern and Southern WetMesic, Hemlock and Hardwood
Community; Southern Mesic,
Beech-Maple Community;
Northern Mesic to Wet-Mesic,
Lowland Swamp Community
Nothern Mesic to Wet-Mesic,
Lowland Swamp Community;
Northern and Southern WetMesic, Hardwood; Northern and
Southern Mesic, Hardwood
community; Southern Mesic,
Hardwood; Northern and
Southern Wet-Mesic, Hemlock
and Hardwood; Northern and
Southern Mesic, BeechHardwood-Pine; Southern Mesic,
Beech-Maple Community

Distribution

Density
2,213.1 Sp D/km^2;
220,283.1 Modern

176.82/km^2 (Modern
Density 101,453.5)

376

Table 29. (cont'd)
Species
J. cinerea

Juglans nigra

Corylus americana

Habitat/Resource Community
Northern and Southern WetMesic, Hardwood Community;
Northern and Southern WetMesic, Hemlock and Hardwood
Community; Southern Mesic,
Beech-Maple Community;
Northern and Southern Mesic,
Hardwood Community
Northern and southern WetMesic, Hardwood Community;
Southern and Northern DryMesic, Hardwood Community;
Northern and Southern WetMesic, Hemlock and Hardwood
Community; Southern Mesic,
Beech-Maple Community;
Northern and Southern Mesic,
Hardwood Community; Northern
and Southern Mesic, BeechHardwood-Pine Community
Characteristic of open sites in dry
and moist situations: roadsides,
fence rows, edges of woods, old
fields. Shade-intolerant.

Distribution

Density
59.6 Sp D/km^2; 3,737.9
Modern

12.7 Sp D/km^2; 1,296.7
Modern

Common to abundant in the southern
half of the Lower Peninsula; rare in the
Upper Peninsula.

377

n/a

Table 29. (cont'd)
Species
Castanea dentata

Habitat/Resource Community
Characteristic of dry-mesic sites
and oak-hickory forests where it
tolerates droughty soils and
periodic fires; associated with
black, white and red oaks, pignut
and shagbark hickories, white
ash, black cherry.

Cucurbita pepo

Floodplain forests, wet deciduous
forests, streambanks, thickets
and waste ground.
Northern Mesic to Wet-Mesic,
Lowland Swamp Community;
Northern and Southern WetMesic, Hemlock and Hardwood
Community; Northern and
Southern Wet-Mesic, Hardwood
Community
Northern Mesic to Wet-Mesic,
Lowland Swamp Community;
Northern and Southern WetMesic, Hemlock and Hardwood
Community; Northern and
Southern Wet-Mesic, Hardwood
Community
North woods, high altitudes and
cool swamps

Amphicarpaea
bracteata

Geranium maculatum

Pyrus sp.

Distribution
Rare in southeastern Michigan; formerly
native as far north as St. Clair Co. and
abundant in Monroe and Wayne Co.
Reaching the northwestern limit of its
range in southeastern Michigan. Planted
trees, more or less healthy, are
widespread throughout the Lower
Peninsula.
Minnesota, Wisconsin, Michigan,
northeast Illinois and northwest Indiana.

Density
n/a

n/a

33,921.9/Sp D/km^2;
(Modern 3,463,933.6)

33,921.9/Sp D/km^2;
(Modern 3,463,933.6)

Great Lakes region, especially in the
northern portions

378

n/a

Table 29. (cont'd)
Species
Physalis

Convolvulaceae

Brassicaceae sp.

Fragaria virginiana
Galium aparine

Helianthus divaricatus

Polygala senega

Habitat/Resource Community
Northern Mesic to Wet-Mesic,
Lowland Swamp Community;
Northern and Southern WetMesic, Hemlock and Hardwood
Community; Northern and
Southern Wet-Mesic, Hardwood
Community
Northern Mesic to Wet-Mesic,
Lowland Swamp Community;
Northern and Southern WetMesic, Hemlock and Hardwood
Community; Northern and
Southern Wet-Mesic, Hardwood
Community
Variety of habitats, especially
where shaded. Floodplain forests,
rocky shores, wet woods
Southern and Northern DryMesic, Hardwood Community
Swamps, streambanks, thickets,
marshes, wet meadows,
calcareous fens; moist meadows,
moist prairies.
Wet meadows, low prairie, sedge
headrows, fens, floodplain
forests, streambanks
Sandy or mucky lakeshores, wet
areas between dunes

Distribution

Density
33,921.9/Sp D/km^2;
(Modern 3,463,933.6)

33,921.9/Sp D/km^2;
(Modern 3,463,933.6)

Both UP and LP of Michigan

n/a

Common throughout Michigan

8,006.0/ sq. km;
(Modern: 796,889.2)
n/a

Common throughout Michigan,
especially the LP

n/a

Common in the LP of Michigan

n/a

379

Table 29. (cont'd)
Species
Rubus occidentalis

Celtis occidentalis

Habitat/Resource Community
Southern and Northern DryMesic, Hardwood Community;
Northern Mesic to Wet-Mesic,
Lowland swamp Community;
Northern and Southern WetMesic, Hemlock and Hardwood
Community; Northern and
Southern Wet-Mesic, Hardwood
Community
Northern and Southern Mesic,
Hardwood Community; Northern
and Southern Mesic, BeechHardwood-Pine Community;
Northern and Southern WetMesic, Hemlock and Hardwood
Community; Southern Mesic,
Beech-Maple Community;
Northern and Southern WetMesic, Hardwood Community;
Southern and Northern DryMesic, Hardwood Community.
Characteristic of banks of small
streams, river floodplains and
moist, fertile bottomlands with
calcareous soils. Not typical of
the often-flooded bottoms where
the maple, red ash, and American
elm thrive. Also grows on
limestone outcrops and on dry,

Distribution

Density
25,085.6/Sp. D km^2;
(Modern:2,496,929.5)

Occasional in the southern half of the
Lower Peninsula, north to Newaygo,
Midland, and Arenac Co.

221.0 Sp D/km^2; 523.8
modern

380

Table 29. (cont'd)
Species

Vitis sp.

Crataegus sp.

Viburnum sp.

Habitat/Resource Community
gravelly or rocky slopes where
the soil is circumneutral to basic
and rich in lime.
Floodplain forests, moist sandy
woods, streambanks, thickets;
also on sand dunes. Northern and
Southern Mesic, BeechHardwood-Pine Community;
Southern and Northern DryMesic, Hardwood Community;
Northern and Southern WetMesic, Hemlock and Hardwood
Community; Northern and
Southern Wet-Mesic, Hardwood
Community
Northern and Southern Mesic,
Hardwood Community; Northern
and Southern Mesic, BeechHardwood-Pine Community;
Northern and Southern WetMesic, Hemlock and Hardwood
Community; Southern Mesic,
Beech-Maple Community;
Northern and Southern WetMesic, Hardwood Community;
Southern and Northern DryMesic, Hardwood Community
Southern and Northern DryMesic, Hardwood Community

Distribution

Density

Minnesota, Wisconsin, mostly LP of
Michigan, common in northeast Illinois
and northwest Indiana.

4,872.8 Sp D/km^2;
17,152.3 Modern;

8.84 Sp D/km^2; 21.0 Sp
Density Modern

8,006.0/ sq. km;
(Modern: 796,889.2)
381

Table 29. (cont'd)
Species
Rhus sp

Polygonum
pensylvanicum

Prunus spp.

Habitat/Resource Community
Frequent in the understory of
open, oak-hickory forests on dry,
sandy calcareous soils in the
southern part of the Lower
Peninsula; rare in the northern
half of the Lower Peninsula and in
the Upper Peninsula.
Streambanks, exposed shores,
marshes, fens, ditches and
cultivated fields. Northern and
Southern Mesic, BeechHardwood-Pine Community;
Southern Mesic, Beech-Maple
Community; Northern and
Southern Mesic, Hardwood
Community; Southern and
Northern Dry-Mesic, Hardwood
Community; Northern and
Southern Wet-Mesic Hardwood
Community
Northern and southern Mesic,
Beech-Hardwood-Pine
Community; Northern Mesic to
Wet-Mesic, Lowland Swamp
Community; Northern and
Southern Mesic, Hardwood
Community

Distribution
Southern Lower Peninsula; rare in
northern half of the Lower Peninsula and
in the Upper Peninsula

Density
n/a

Mostly south Minnesota, Wisconsin,
Michigan, common in northeast Illinois
and northwest Indiana.

49,602.5 Sp D/km^2;
209,800.8 modern

Common throughout Michigan

11.9 Sp D/km^2; 746.3
Modern

382

Table 29. (cont'd)
Species
Sambucus canadensis

Prunus serotina

Amelanc (Amelanchier
Medikus)
Aster cordifolius

Habitat/Resource Community
Floodplain forests, swamps, wet
forest depressions, thickets,
shores, meadows, roadsides,
fencerows
Northern Mesic to Wet-Mesic,
Lowland Swamp Community;
Northern and Southern Mesic,
Hardwood Community; Northern
and Southern Mesic, BeechHardwood-Pine Community;
Northern and Southern WetMesic, Hemlock and Hardwood
Community; Southern Mesic,
Beech-Maple Community;
Northern and Southern WetMesic, Hardwood Community;
Southern and Northern DryMesic, Hardwood Community
Conifer swamps, open bogs,
thickets.

Distribution
Central and south Minnesota, Wisconsin,
Michigan (all), northeast Illinois and
northwest Indiana.

Density
n/a

119.2 Sp D/km^2;
7,475.9 Modern

North Minnesota, Michigan Upper
Peninsula (somewhat uncommon in the
Lower Peninsula)

Northern Mesic to Wet-Mesic,
Lowland Swamp Community;
Northern and Southern WetMesic, Hemlock and Hardwood
Community; Northern and
Southern Wet-Mesic, Hardwood
Community

n/a

33,921.9/Sp D/km^2;
(Modern 3,463,933.6)

383

Table 29. (cont'd)
Species
Sassafras albidum

Habitat/Resource Community
Characteristic of disturbed sites
in dry-mesic and mesic forests;
most abundant along fence rows
and in old fields where it forms
small clones. Associates include
black, white, and red oaks, white
ash, black cherry, black walnut,
aspens, red and sugar maples
beech, and hop-hornbeam.

Distribution
Common in the southern half of the
Lower Peninsula, becoming rare
northward to Manistee and Grand
Traverse Co. A southern species reaching
the northern limit of its range in the
Lower Peninsula of Michigan.

Density
n/a

Hypericum

Streambanks

n/a

Cornus rugosa

Lakeshores, streambanks,
swamps, thickets, marshes, moist
woods, low prairie.
Open bogs, usually with tamarack
and leatherleaf; more common in
dry, acid, sandy or rocky habitats.
Marshes, swamps, moist to wet
areas
Open bogs, conifer swamps,
thickets, shores and
streambanks; increasing in
disturbed wetlands.
Cold, poorly drained swamps,
bogs and wet lakeshores.

Found in Michigan, Wisconsin,
Minnesota
Common in Michigan.

Common in Michigan

n/a

LP of Michigan, mostly

n/a

Central and eastern Wisconsin,
Michigan, northeast Illinois and
northwest Indiana.

n/a

North and central Minnesota, Wisconsin,
Michigan, extreme northeast Illinois and
northwest Indiana.
Common throughout Michigan

n/a

Gaylussacia baccata

Lamiaceae
Rosa palustris

Pinus

Fraxinus alba

Floodplain forests, swamps,
shores, streambanks

384

n/a

n/a

Table 29. (cont'd)
Species
P. resinosa

P. strobus

Ulmus rubra

Habitat/Resource Community
Characteristic of well drained,
dry, highly acid, sandy soils of
outwash plains and gravelly
ridges; associated with jack pine,
white pine, oaks, aspens, white
birch. Also common on rock
outcrops and sand dunes. Not
competitive with hardwoods on
the better, heavier textured soils;
does not tolerate a high water
table or frost pockets.
Grows well on a wide variety of
sites; moraines of moderately
well drained loams and silt loams;
well drained, dry, highly acid,
infertile, sandy soils and dunes;
small ridges or mounds in
swamps and poorly drained sites;
floodplains; rock ridges and
outcrops
Characteristics of mixed
hardwood forests with mesic
sites and moist, fertile soils:
lower slopes, river terraces,
bottomlands; also found on drier
slopes with soils of high lime
content.

Distribution
Common to frequent in the Upper
Peninsula and the northern half of the
Lower Peninsula, south to Ottawa Co. on
the west and St. Clair Co. on the east.
Vigorous as an ornamental tree farther
south.

Density
n/a

Abundant in the Upper Peninsula and
n/a
the northern half of the Lower Peninsula;
south to Berrien, St. Joseph, Oakland,
and formerly Wayne Co.; often-planned
and vigorous as an ornamental tree.

Frequent in the southern half of the
Lower Peninsula; occasional in the
northern half of the Lower Peninsula;
absent in the Upper Peninsula.
Approaching the northern limit of its
range in Michigan.

385

n/a

Table 29. (cont'd)
Species
Ulmus sp.

Cercis canadensis

Tilia americana

Habitat/Resource Community
Floodplain forests, streambanks
and moist, rich woods; less
common now than formerly due
to losses from Dutch elm disease.
Characteristic understory tree of
forests of stream borders and
moist, fertile bottomlands.
Associates include American elm,
basswood, silver maple, red ash,
red mulberry, northern
hackberry.
Characteristic of mesic deciduous
forests with moist, nutrient-rich,
well drained to somewhat poorly
drained soils; lake and stream
borders, bottomlands. Associates
include sugar maple, beech,
yellow birch, red maple,
American elm, white ash, black
walnut, butternut, red and white
oaks.

Distribution
Minnesota, Wisconsin, Michigan,
northeast Illinois and northwest Indiana.

Density
n/a

Rare in the southern tiers of counties to
the valley of the Grand River on the west
and the Raisin River on the east. Tree of
widespread distribution south of
Michigan, reaching its northernmost
limit in the relatively mild and protected
river valleys of Southern Michigan.
Common in deciduous forests of the
Lower Peninsula; frequent in deciduous
forests of the Upper Peninsula.

n/a

386

n/a

Table 29. (cont'd)
Species
Q. nigra

Q. bicolor

Habitat/Resource Community
Characteristic of xeric and drymesic oak-hickory forests and
oak-pine forests with well to very
well drained, upland soils,
especially sandy to gravelly
textures; intolerant of high water
tables; associated with white,
red, northern pin, and scarlet
oaks, pignut and shagbark
hickories, white ash, black cherry,
bigtooth aspen, white and red
pines, red maple.
Characteristic of low, wet,
somewhat poorly to poorly
drained soils; borders of swamps
and along streams; moist flats
and bottomlands; associated with
silver maple, American elm, bur
oak, red ash, basswood, tuliptree,
yellow birch. Adapted to
conditions of poor aeration and
high water tables but not
abundant in deciduous swamps
having a continually high water
table.

Distribution
Common in the southern half of the
Lower Peninsula, occasional in the
northern half; not known from the
Upper Peninsula.

Density
n/a

Occasional in the southern half of the
Lower Peninsula. A species of
predominantly Midwestern range
reaching one segment of its northern
limit in southern to central Michigan.

9.6 Sp D/km^2; 955.5
Modern

387

Table 29. (cont'd)
Species
Q. rubra

Populus tremuloides

Habitat/Resource Community
Characteristic of mesic forests
throughout the state on moist,
cool, well drained sites; also
occurring in dry-mesic forests of
southern Michigan with white
and black oaks, shagbark and
pignut hickories, white ash, black
cherry. Found on sandy, well
drained soils of the northern
Lower Peninsula and Upper
Peninsula with white and red
pines, aspens, and red maple;
locally frequent near the shores
of the Great Lakes and on rock
outcrops. More demanding of
moisture than black and white
oaks; tolerating a colder climate
than black or white oaks.
Characteristic of warm, humid
river floodplains; associated with
black willow, sandbar willow,
silver maple, red ash, American
elm, northern hackberry, boxelder

Distribution
Common in the southern half of the
Lower Peninsula; frequent in the
northern half and the Upper Peninsula;
frequent along Lakes Michigan and
Superior. Most northerly distributed of
Michigan oaks; approaching its northern
range limit in the Upper Peninsula.

Density
2,213.1 Sp D/km^2;
220,283.1 Modern

Common in the southern half of the
Lower Peninsula

n/a

388

Table 29. (cont'd)
Species
Carya laciniosa

Carya ovata

Cornus racemosa

Habitat/Resource Community
Characteristic of river floodplains
and moist woodland soils that are
deep, fertile, neutral or slightly
alkaline, and of a loam or silt
loam texture. Requires moister,
more fertile soils than shagbark
or pignut hickories.
Characteristic of dry-mesic, oakhickory forests; associated with
black, red, and white oaks, pignut
hickory, white ash, black cherry.
Occasional on mesic sites;
associated with sugar maple,
beech, basswood, red oak,
butternut hickory. Also occurs in
the drier parts of river
floodplains. Tolerant of drought
but not of prolonged high water
table.
Lakeshores, streambanks,
swamps, thickets, marshes, moist
woods, low prairie.

Distribution
Rare. Occurs in the southernmost 2 tiers
of counties of the Lower Peninsula;
reaches its northernmost Midwestern
limit in southern Michigan.

Density
n/a km2

Common in the Lower Peninsula as far
59.6 Sp D/km^2; 3,737.9
north as Roscommon and Missaukee Co.; Modern
primary range south of Michigan,
reaching its northernmost Midwestern
limit in the southern half of the Lower
Peninsula.

Common; Minnesota, Wisconsin,
Michigan Lower peninsula, northeast
Illinois and northwest Indiana.

389

n/a

Table 29. (cont'd)
Species
Fagus americana

Ostraya virginiana

Fraxinus sp

Habitat/Resource Community
Characteristic of mesic beechmaple forests with well drained
to somewhat poorly drained soils
of a wide range of textures, from
loamy sand to clay loam.
Associated with sugar maple,
basswood, red oak, white ash,
American elm, tuliptree, eastern
hemlock. Tolerates acidic or basic
conditions.
Characteristic of the understory
of dry-mesic, oak-hickory forests
on well-drained, upland sites;
associated with black, white and
red oaks, shagbark and pignut
hickories, white ash, black cherry.
Also occurs in mesic beech-maple
forests on moist, fertile slopes;
associated with sugar maple,
beech, basswood, red oak. Not
found on poorly drained sites.

Distribution
Common in the Lower Peninsula; locally
common in the eastern half of the Upper
Peninsula, west to Marquette and
Dickinson Co.

Density
n/a

Common throughout the state of
Michigan.

n/a

Floodplain forests, swamps,
shores, streambanks

Common throughout Michigan

n/a

390

Table 29. (cont'd)
Species
Fagus grandifolia

Acer spp.

Betula spp.

Habitat/Resource Community
Northern Mesic to Wet-Mesic,
Lowland Swamp Community;
Northern and Southern WetMesic, Hardwood Community;
Northern and Southern WetMesic, Hemlock and Hardwood
Community; Southern Mesic,
Beech-Maple Community;
Northern and Southern Mesic,
Beech-Hardwood-Pine
Community
Floodplain forests, streambanks,
shores; also drier woods and
disturbed areas; Northern Mesic
to Wet-Mesic, Lowland Swamp
Community; Northern and
Southern Mesic, Hardwood
Community; Northern and
Southern Mesic, BeechHardwood-Pine Community;
Northern and Southern WetMesic, Hemlock and Hardwood
Community; Southern Mesic,
Beech-Maple Community;
Southern and Northern DryMesic, Hardwood Community
Hummocks in swamps and on
wetland margins

Distribution

Density
2,265.3 Sp D/km^2;
142,072.8 Modern

Minnesota, Wisconsin, Michigan,
northeast Illinois and northwest Indiana.

10,134.2 Sp D/km^2;
635,586.6 Modern

Eastern Minnesota, Wisconsin, Michigan, n/a
northeast Illinois and northwest Indiana.

391

Table 29. (cont'd)
Species
Morus rubra

Platanus occidentalis

Picea

Typha

Habitat/Resource Community
Northern and Southern Mesic,
Hardwood Community; Northern
and Southern Mesic, BeechHardwood-Pine Community;
Southern Mesic, Beech-Maple
Community
Riverbanks, floodplain forests and
lakeshores. Characteristic of river
floodplain and bottomland
forests with moist, alluvial soils;
also lake shores. Tolerates
flooding, silting, high water
tables, and soils with slow
drainage.
White spruce: Moist to
sometimes wet forests; absent
from wetlands where water is
stagnant. Black spruce: Cold, acid,
sphagnum bogs, swamps, and
lakeshores; often where water is
slow-moving and low in oxygen;
less common in calcium-rich,
well-aerated swamps dominated
by northern white cedar.
Wetland; marshes, lakeshores,
streambanks, ditches, pond
margins, usually in shallow water.
Cattail Marsh Communities;

Distribution

Density
8.84 Sp D/km^2; 21.0 Sp
Density Modern

Occasional in south Wisconsin and south
Michigan; northeast Illinois and
northwest Indiana. Occasional in the
Lower Peninsula, rare north to Newaygo
and Midland Co. Primarily a Midwestern
and southern species, reaching a portion
of its northernmost range in Michigan.

n/a

LP , north and central Michigan (rarer in
southern Michigan)

n/a

Common in Minnesota, Wisconsin,
Michigan, NE Illinois and NW Indiana, S
Canada to central Alaska, throughout
USA and into Mexico

n/a

392

Table 29. (cont'd)
Species
Rumex spp.

Panicum spp.
Silphium
terebinthinaceum

Smilacina racemosa

Smilacina stellata

Maianthemum
canadense
Onoclea Sensibilis

Poa pratensis

Habitat/Resource Community
Floodplain forests and openings,
cultivated fields and disturbed
areas
Floodplain forests, alder thickets,
ditches, especially where sandy.
Low prairie, fens; especially
where calcium-rich.

Distribution
Common in Michigan

Density
n/a

Central and south LP of Michigan

n/a

Fairly common; south Wisconsin, south
Lower Peninsula of Michigan (local in
central Upper Peninsula), northeast
Illinois and northwest Indiana; south
Ontario and Ohio to Wisconsin, south to
GA and Miss.
Open bogs, conifer swamps,
North and east central Minnesota, north
thickets.
and central Wisconsin, common
throughout Michigan.
Open bogs, conifer swamps,
North and east central Minnesota, north
thickets.
and central Wisconsin, common
throughout Michigan.
On hummocks in swamps, open
Very common across most of our region.
bogs and thickets; also common
Minnesota, Wisconsin, Michigan,
in moist to dry woods.
northeast Illinois and northwest Indiana.
Swampy woods and low places in Minnesota, Wisconsin, Michigan,
forests, wet meadows, calcareous northeast Illinois and northwest Indiana.
fens, and roadside ditches, wet or
moist wheel ruts; sometimes
weedy.
Wet meadows, marshes, shores,
Common to occasional; Minnesota,
streambanks, ditches and low
Wisconsin, Michigan, northeast Illinois
prairie; also moist woods.
and northwest Indiana.
393

n/a

n/a

n/a

n/a

n/a

n/a

Table 29. (cont'd)
Species
Smilax lasioneura

Habitat/Resource Community
Characteristic of open, moist
habitats or lightly shaded woods,
stream and lake environs, dunes,
roadsides, fence rows, old fields,
edges of woods, banks, cutover
forests. Moderately shadetolerant.
Solidago Sp.
Wet meadows, streambanks,
swamps, floodplain forests,
thickets, marshes, calcareous
fens, ditches; also in moist to dry
open woods and roadsides.
Thalictrum dioicum
Wet to moist meadows, low
prairie, swamps, thickets, and
streambanks.
Viola pensylvanica
Moist hardwood forests;
occasionally in swamps,
floodplain forests and along rocky
streambanks.
Viola sororia (Sens. Lat.) Moist hardwood forests;
(Glabrous plants like this occasionally in swamps,
one have been referred floodplain forests and along rocky
to V. Papilionacea)
streambanks.

Distribution
Common in the Lower Peninsula; rare in
the Upper Peninsula.

Density
n/a

Common in Minnesota, Wisconsin,
Michigan, northeast Illinois and
northwest Indiana.

n/a

Common in Michigan

n/a

Common in Minnesota, Wisconsin,
northeast Illinois and northwest Indiana.

n/a

Common in Minnesota, Wisconsin,
northeast Illinois and northwest Indiana.

n/a

394

Table 29. (cont'd)
Species
Zanthoxylum
americanum

Lilium michiganense

Lysimachia ciliata

Carex blanda
Carex lupulina

Carex pensylvanica
Smilax cirrata

Habitat/Resource Community
Characteristic of open, disturbed,
moist sites or lightly shaded
woods, especially stream banks
and floodplains. Moderately
shade-tolerant. Typical of fence
rows and forest edges.
Wet meadows, along streams,
and in flood-plain forests of the
Great Lakes region.
Usually shaded wet areas, such as
shores, streambanks, wet
meadows, ditches, floodplains,
wet woods and thickets.
Floodplain forests and backwater
areas
Wet woods, swamps, wet
meadows and marshes, ditches
and shores.
Floodplain forests and backwater
areas
Characteristic of open, moist
habitats or lightly shaded woods,
stream and lake environs, dunes,
roadsides, fence rows, old fields,
edges of woods, banks, cutover
forests. Moderately shadetolerant.

Distribution
Common throughout the Lower
Peninsula of Michigan

Density
n/a

Common throughout Michigan.

n/a

Minnesota, Wisconsin, Michigan,
northeast Illinois and NW Indiana.

n/a

Common in LP of Michigan

n/a

Common throughout Michigan

n/a

Common in LP of Michigan

n/a

Common in the Lower Peninsula; rare in
the Upper Peninsula.

n/a

395

Table 29. (cont'd)
Species
Toxicodendron radicans

Apocynum
androsaemifolium

Aquilegia canadensis
Aralia nudicaulis
Barbarea vulgaris

Geum canadense

Habitat/Resource Community
Characteristic of open areas and
the understory, or climbing on
tree trunks. Of open woodlands
on virtually any kind of soil;
stream banks, lake margins, fence
rows, and where birds are likely
to disperse the seeds.
Northern Mesic to Wet-Mesic,
Lowland Swamp Community;
Northern and Southern WetMesic, Hemlock and Hardwood
Community; Northern and
Southern Wet-Mesic, Hardwood
Community
Cedar and tamarack swamps,
thickets, fens, shores.
Moist ravines and mixed woods
Rocky shores, swamps and wet
woods
Swamps, wet forests, wet
meadows, marshes, calcareous
fens, ditches and roadsides.

Distribution
Common to locally abundant in the
southern half of the Lower Peninsula.

Density
n/a

33,921.9/Sp D/km^2;
(Modern 3,463,933.6)

Michigan UP and occasional in north and
central LP
Great Lakes region
Northeast and eastern central
Minnesota, Wisconsin, and eastern UP
and LP of Michigan.
Minnesota, Wisconsin, Michigan,
northeast Illinois and northwest Indiana.

396

n/a
n/a
n/a

n/a

Table 29. (cont'd)
Species
Satureja vulgaris

Monarda fistulosa

Osmorhiza longistylis

Podophyllum peltatum

Habitat/Resource Community
Northern Mesic to Wet-Mesic,
Lowland Swamp Community;
Northern and Southern WetMesic, Hemlock and Hardwood
Community; Northern and
Southern Wet-Mesic, Hardwood
Community
Northern Mesic to Wet-Mesic,
Lowland Swamp Community;
Northern and Southern WetMesic, Hemlock and Hardwood
Community; Northern and
Southern Wet-Mesic, Hardwood
Community
Northern Mesic to Wet-Mesic,
Lowland Swamp Community;
Northern and Southern WetMesic, Hemlock and Hardwood
Community; Northern and
Southern Wet-Mesic, Hardwood
Community
Northern Mesic to Wet-Mesic,
Lowland Swamp Community;
Northern and Southern WetMesic, Hemlock and Hardwood
Community; Northern and
Southern Wet-Mesic, Hardwood
Community

Distribution

Density
33,921.9/Sp D/km^2;
(Modern 3,463,933.6)

33,921.9/Sp D/km^2;
(Modern 3,463,933.6)

33,921.9/Sp D/km^2;
(Modern 3,463,933.6)

33,921.9/Sp D/km^2;
(Modern 3,463,933.6)

397

Table 29. (cont'd)
Species
Trillium grandiflorum

Lithospermum
canescens
Taraxacum officinale

Anura sp.

Emydoidea blandingii

Habitat/Resource Community
Wet meadows, along streams,
and in flood-plain forests of the
Great Lakes region.
Wet meadows, along streams,
and in flood-plain forests of the
Great Lakes region.
Northern Mesic to Wet-Mesic,
Lowland Swamp Community;
Northern and Southern WetMesic, Hemlock and Hardwood
Community; Northern and
Southern Wet-Mesic, Hardwood
Community
Any still, permanent body of
water including backwaters,
sloughs, lakes, farm ponds,
impoundments, marshes, and
shallow Great Lakes bays. Places
with abundant submerged and
emergent vegetation are
preferred.
Shallow, weedy waters like
ponds, marshes, swamps, lake
inlets and coves. Sometimes
found in rivers; they like logs,
grass clumps, sloping banks, or
other perches to bask on.

Distribution
Common throughout Michigan.

Density
n/a

Common throughout Michigan.

n/a

33,921.9/Sp D/km^2;
(Modern 3,463,933.6)

Occurs throughout Michigan.

n/a

In the Great Lakes basin, they are found
n/a
throughout southern Ontario, along both
shores of Lake Erie, In Michigan (Lower
and central Upper Peninsula), northern
Ohio, Indiana, Eastern Illinois, and
Wisconsin.

398

Table 29. (cont'd)
Species
Chrysemys picta

Chelydra serpentina

Nerodia sipedon

Thamnophis sp.

Habitat/Resource Community
Slow-moving or quiet permanent
waters with a soft-bottom
substrate, abundant aquatic plant
life, and basking sites. Sometimes
they occupy ponds, ditches, and
can tolerate certain levels of
organic pollution.
Snapping Turtles inhabit most
permanent bodies of water in the
region, including shallow, weedy
inlets and bays in the Great Lakes
themselves. Quiet, mudbottomed ponds, lakes, sloughs
and slow streams with dense
aquatic vegetation support the
largest populations.

Distribution
Range encompasses much of the US,
including the LP of Michigan.

Density
n/a

Present in nearly all of the United States
east of the Rocky Mountains, including
all of the Great Lakes region, omitting
the area in Canada north of Lake
Superior.

n/a

The Northern water snake lives
on or near most permanent
bodies of water, including rivers,
streams, sloughs, lakes, ponds,
bogs, marshes, swamps, and
impoundments.
Found in nearly every natural
habitat in the region; especially
grassy places near the edges of
ponds, lakes, ditches, and
streams.

Occurs throughout the Great Lakes
region, except for the northern and
western portions of the Lake Superior
Drainage basin; The Lake Erie Water
Snake is found on certain islands of
western Lake Erie in Ontario and Ohio.
Common garter snakes are generally
common and locally abundant and are
the most frequently encountered snake
in the Great Lakes region (through all of
Michigan)

n/a

399

n/a

Table 29. (cont'd)
Species
Trionyx sp.

Amblema costata
Elliptio dilatatus

Habitat/Resource Community
Rivers, larger streams, inland
lakes, reservoirs, protected bays
and rivermouth areas. Tolerate a
fairly swift current but prefer a
sand or mud bottom and usually
avoid streams with sharp-edged
rocks or coarse gravel.
Small to large rivers
Rarely found in bodies of
freshwater deeper than 6 feet

Quadrula pustulosa
(Lea)
Pleurobema (cordatum)
coccineum (Conrad)

Drainages

Cyclonaias tuberculata
Lasmigona costata
(Raf.)
Strophitus rugosus
(Swain.)
Lampsilis siliquoidea (L)
Obovaria subrotunda
(Raf.)

Drainages

Drainages

n/a

Widely distributed

Drainages

Density
n/a

Eastern half of the United States

Fusconaia flava (Raf.)

Distribution
Ranges across the Lower Great Lakes
region from the southern and western
shores of Lake Ontario through southern
Ontario and much of Michigan's Lower
Peninsula, adjacent Ohio and Indiana, to
the western Lake Michigan basin (north
to Green Bay).
Eastern half of the United States
Tributaries of the Mississippi River and
lesser drainage systems in the eastern
half of North America
Common and generally distributed in
eastern half of the United States
Mississippi drainage as far west as
Minnesota and Texas
Mostly in the southeastern states, but a
few drainages in the northeastern
quarter of the United States

n/a

Mississippi and St. Lawrence drainages,
and southeastern states
Generally distributed in eastern half of
the United States

n/a

400

n/a
n/a

n/a
n/a
n/a

n/a

Table 29. (cont'd)
Species
Ligumia (Recta)
lattissima (Raf.)

Actinonaias carinata
(Barnes)
Discus cronkhitei
Anguispira kochi
Anodonta grandis
footiana (Say) Goodrich

Micromya (Villosa) Iris
(Lea) Goodrich

Amblema costata
(Rafinesque) Goodrich

Ligumia recta (Lamarck)
Goodrich

Habitat/Resource Community
Most abundant in the shallows,
especially in water less than 2 m
deep, but in larger rivers and
some lakes, they can occur as
deep as 7 m.

Density
n/a

Eastern half of the United States

Most abundant in the shallows,
especially in water less than 2 m
deep, but in larger rivers and
some lakes, they can occur as
deep as 7 m.
Most abundant in the shallows,
especially in water less than 2 m
deep, but in larger rivers and
some lakes, they can occur as
deep as 7 m.
Most abundant in the shallows,
especially in water less than 2 m
deep, but in larger rivers and
some lakes, they can occur as
deep as 7 m.
Most abundant in the shallows,
especially in water less than 2 m
deep, but in larger rivers and
some lakes, they can occur as
deep as 7 m.

Distribution
Generally distributed in eastern half of
the United States

n/a

Fresh-water bivalves occur in all types of
unpolluted habitats but they are most
abundant and varied in the larger rivers
and large drainage lakes.

n/a

Fresh-water bivalves occur in all types of
unpolluted habitats but they are most
abundant and varied in the larger rivers
and large drainage lakes.

n/a

Fresh-water bivalves occur in all types of
unpolluted habitats but they are most
abundant and varied in the larger rivers
and large drainage lakes.

n/a

Generally distributed in eastern half of
the United States

n/a

401

Table 29. (cont'd)
Species
Habitat/Resource Community
Valvata tricarinata (Say) Found in both shallow and deep
water
Goniobasis livescens
Near lake shores and in rapid
(Say)
rivers

Somatogyrus sp.

Amnicola lustrica
(Pilsbry)
Lymnaea columella
(Say)
Helisoma
Campanulatum

Many species in all types of
habitats, but most commonly
found in quiet waters
Common in a variety of habitats,
but rare west of the Continental
Divide
Muddy bottoms of fresh bodies
of water, marshes
Many species in all types of
habitats, but most commonly
found in quiet waters

Distribution
Generally distributed in a variety of
habitats, but especially in large lakes.
Most common in rivers of Tennessee and
Alabama, but extending north to Great
Lakes, St. Lawrence River basin, and
western tributaries of the Mississippi
River.
Widely distributed

Density
n/a

Widely distributed

n/a

Found from coast to coast across the
United States.
Found from coast to coast across the
United States; widely distributed.

n/a

Stenotrema monodon
(Racket)
Mesodon thyroidus
(Say)
Triodopsis albolabris
(Say)
Triodopsis multilineata
(Say)
Anguispira alternata
Anguispira solitaria
402

n/a

n/a

n/a

Table 29. (cont'd)
Species
(Say)
Helicodiscus parallelus
(Say)
Haplotrema concavium
(Say)
Mesomphix cuprea
(Say)
Amnicola Limosa (Say)

Pomatiopsis lapidaria
(Say)
Lymnaea (Staginicola)
palustris (Say)
Helisoma trivolvis (Say)

Retinella rhoadsi
(Pilsbry)
Succinea ovalis (Say)
Campeloma decisum
(Say)
Helisoma anceps
(Conrad)

Habitat/Resource Community

Distribution

Common in a variety of habitats,
but rare west of the Continental
Divide
Usually amphibious but often
found on submerged substrates
Muddy bottoms of fresh bodies
of water, marshes
Many species in all types of
habitats, but most commonly
found in quiet waters

Widely distributed

Most common in lakes and
streams
Many species in all types of
habitats, but most commonly
found in quiet waters

Density

Found within the Midwest

n/a

Found from coast to coast across the
United States.
Found from coast to coast across the
United States; widely distributed.

n/a

Generally distributed from the
Mississippi Valley to the Atlantic coast
Found from coast to coast across the
United States; widely distributed.

n/a

Zonitidae
Pelecypoda

403

n/a

n/a

Table 30. Resource schedule detail – January to June
Species
Cervus
canadensis
Odocoileus
virginianus
Procyon lotor

January
-

February
-

March
-

April
-

May
Birth

June
Birth

-

-

-

-

Birth

Birth

Winter
dormancy
Winter
dormancy,
birth?
-

Breeding

Breeding

Litter production

Litter production

-

Winter
dormancy, birth?

Winter dormancy Winter dormancy

-

-

Castor canadensis
Ondatra
zibethicus
Canis sp. (lupus,
familiaris)
Martes americana Birth
Marmota monax
Hibernation

-

-

Litter production

Litter production

Courtship/mating Courtship/mating Litter production

Litter production

Litter
production
-

Birth
Hibernation

Birth
Mating

Litter production,
Active midday

Active midday

Mustela vison

-

Mating

Mating

Litter production

-

Lynx rufus

Courtship

Breeding

Breeding

Birth
Mating, litter
production, active
midday
Mating, Litter
production
-

Litter production

-

Lontra canadensis -

Litter production

Litter production

Litter production

-

-

Erethizon
dorsatum

-

-

Birth

Birth

Birth

Ursus americanus

-

404

Table 30. (cont’d)
Species
Martes pennanti

January
-

February
-

April
Courtship, mating,
birth (352 days,
gestation)

May
-

June
-

Mating

March
Courtship,
mating, birth
(352 days,
gestation)
Litter production

Sciurus sp.

Mating

Litter production

Mating

Mating

Leporidae sp.
(Sylvilagus)
Vulpes fulva

-

Mating

Mating

Mating/birth

Mating/birth

Mating/birth

Mating

Mating

Litter production

-

-

Alces alces
Blarina sp.

-

-

Mating/Litter
production
Mating

Tamias sp.

-

Mating

Birth
Mating/pregnancies Mating/
pregnancies/
litters
Litter production; Litter production
species now a
common
member of
wildlife
community
starting in March

Birth
Mating/
pregnancies/
litters
Mating

Muridae sp.
Peromyscus sp.

Little to no
activity
Breeding

Mating

Birth of litter

Birth of litter

-

Breeding

Breeding

Breeding

Breeding

Reduction of
population
Breeding

Microtus sp.

405

Table 30. (cont’d)
Species
Acipenser
fulvescens
Perca flavescens
Amia calva
Aplodinotus
grunniens
Monroe chrysops
Micropterus
salmoides
Micropterus
dolomieui
Esox lucius
Stizostedion
vitreum
Ictalurus
punctatus
Lepisosteus
oculatus
Salvelinus
namaycush
Ictalurus melas
Ictalurus natalis
Ictalurus
nebulosus
Moxostoma sp.
(macrolepidotum)
Pomoxis sp.

January
-

February
-

March
-

April
Spawn

May
Spawn

June
Spawn

-

-

-

-

Eggs laid

Eggs laid

-

-

Spawn
-

Spawn
-

-

-

-

-

Spawn
Nest/eggs laid
and fertilized
Nesting

Spawn
Nest/eggs laid
and fertilized
Nesting

-

-

Spawn
-

Spawn
-

-

-

-

-

-

-

-

-

-

-

-

-

Nesting/eggs
laid
-

-

-

-

-

-

-

-

-

-

Spawn
-

Spawn
-

Spawn
Spawn/nest
Spawn

-

-

-

-

Spawn

Spawn

-

-

-

-

Spawn

Spawn

406

Table 30. (cont’d)
Species
Catostomus sp.
(catostomus,
commersoni)
Centrarchidae
Lepomis cf.
macrochirus
Pomoxis
nigromaculatus
Stizostedion
canadense
Lota lota lacustris

January
-

February
-

March
-

April
Crowd
tributaries/Spawn

May
June
Crowd
tributaries/Spawn

-

-

-

Spawn

Spawn
Spawn

Spawn
Spawn

-

-

-

Spawn

Spawn

Spawn

-

-

-

Spawn

Spawn

Spawn

Spawn

Spawn

-

-

-

-

Ectopistes
migratorius
Anas discors

-

-

-

Nesting

-

-

-

Migrating into
Michigan
Arrives in Michigan

Anas americana

-

-

Arrives in
Michigan

Leaves Michigan,
heads north

-

Nesting/eggs
hatched
Nesting/eggs
laid
-

Anas
platyrhynchos
Aythya collaris

-

-

-

Eggs laid

Ducklings hatch

-

-

-

-

-

Migrates into
Michigan
-

-

Mergus
merganser

Migrates into
Michigan
Migrates into
Michigan
-

Mergus serrator

-

-

-

Migrates back into
Michigan

Found on small
ponds and
streams, shores
-

Found on small
ponds, streams,
shores
-

407

-

Table 30. (cont’d)
Species
Gavia immer
Podilymbus
podiceps
Meleagris
gallopavo
Lophodytes
cucullatus

January
Absent

February
Absent

March
-

April
-

May
-

June
-

-

-

-

-

-

-

Open
running
waters
-

Open running
waters

-

-

-

-

Nesting

Nesting

-

Migrate into
Michigan
-

-

-

-

Lays eggs

Lays eggs

-

Grus canadensis

-

-

Migrates into
Michigan
Migrates into
Michigan, lays
eggs
-

Offspring hatched Offspring leave
the nest
-

Nesting/lays eggs

Nesting/lays eggs

Aythya marila
Bubo virginianus

Nesting

Nesting

Eggs laid

Eggs laid/ hatched

-

Nesting/lays
eggs
-

Chenopodium
Zea mays
Iva annua
Carex sp.
Cyperus
Zizania aquatica

-

-

-

-

-

-

-

-

-

-

-

x
-

Corvus
brachyrhynchos
Botaurus
lentiginosus
Ardea herodias

408

Table 30. (cont’d)
Species
Quercus
Carya
J. cinerea
Juglans nigra
Corylus
americana
Castanea dentata
Cucurbita pepo
Amphicarpaea
bracteata
Geranium
maculatum
Pyrus sp.
Physalis
Convolvulaceae
Brassicaceae sp.
Fragaria
virginiana
Galium aparine
Helianthus
divaricatus
Polygala senega
Rubus
occidentalis
Celtis occidentalis
Vitis sp.
Crataegus sp.
Viburnum sp.

January
-

February
-

March
-

April
-

May
Flowers
Flowers

June
Flowers
Flowers

-

-

Flowers

Flowers

-

-

-

-

-

-

-

Flowers
-

-

-

-

-

-

-

-

-

-

-

-

Fruit

-

-

-

-

-

Fruit
Fruit

-

-

-

-

-

-

-

-

-

-

Flowers
Fruit

Fruit

-

-

-

-

x

x

409

Table 30. (cont’d)
Species
Rhus sp
Polygonum
pensylvanicum
Prunus spp.
Sambucus
canadensis
Prunus serotina
Amelanc
(Amelanchier
Medikus)
Aster cordifolius
Sassafras albidum
Hypericum
Cornus rugosa
Gaylussacia
baccata
Lamiaceae
Rosa palustris
Pinus
Fraxinus alba
P. resinosa

January
-

February
-

March
-

April
Flowers
-

May
Flowers
-

June
x

-

-

-

-

-

-

-

-

-

-

x

x

-

-

-

-

Flowers
x
x

x
x

-

-

-

x
Pollen/seed cones

-

P. strobus

-

-

-

-

x
Pollen/seed
cones
-

Ulmus rubra
Ulmus sp.
Cercis canadensis

-

-

Flowers
-

Flowers
Flowers

Fruit
Flowers

410

Pollen
cones/Seed
cones
Fruit/Legume

Table 30. (cont’d)
Species
Tilia americana
Q. nigra
Q. bicolor
Q. rubra
Populus
tremuloides
Carya laciniosa
Carya ovata
Cornus racemosa
Fagus americana
Ostraya virginiana
Fraxinus sp
Fagus grandifolia
Acer spp.
Betula spp.
Morus rubra
Platanus
occidentalis
Picea
Typha
Rumex spp.
Panicum spp.
Silphium
terebinthinaceum
Smilacina
racemosa
Smilacina stellata
Maianthemum

January
-

February
-

March
-

April
Flowers

May
Flowers
Flowers
Flowers
Flower, fruits

June
Flowers
Flowers
Flowers
Fruit

-

-

-

Flowers
Flowers
x

Flowers
Flowers
Flowers
Flowers
x

Flowers
Flowers
x
-

-

-

-

x

x

-

-

-

-

-

x

-

-

-

-

-

x
-

x
x
x
-

-

-

-

-

x

x

-

-

-

-

x
x

x
x

411

Table 30. (cont’d)
Species
canadense
Onoclea sensibilis
Poa pratensis
Smilax lasioneura
Solidago Sp.
Thalictrum
dioicum
Viola
pensylvanica
Viola sororia
(Sens. Lat.)
(Glabrous plants
like this one have
been referred to
V. Papilionacea)
Zanthoxylum
americanum
Lilium
michiganense
Lysimachia ciliata
Carex blanda
Carex lupulina
Carex
pensylvanica
Smilax cirrata
Toxicodendron
radicans

January

February

March

April

May

June

-

-

-

-

-

x
Flowers
x

-

-

-

x

x

x

-

-

-

x

x

x

-

-

-

Flowers

Flowers

-

-

-

-

-

-

x

-

-

-

-

-

x
x
x
x

-

-

-

-

Flowers

Flowers
Flowers

412

Table 30. (cont’d)
Species
Apocynum
androsaemifolium
Aquilegia
canadensis
Aralia nudicaulis
Barbarea vulgaris
Geum canadense
Satureja vulgaris
Monarda fistulosa
Osmorhiza
longistylis
Podophyllum
peltatum
Trillium
grandiflorum
Lithospermum
canescens
Taraxacum
officinale
Anura sp.
Emydoidea
blandingii

January
-

February
-

March
-

April
-

May
-

June
-

-

-

-

-

x

x

-

-

-

-

-

x
x
-

-

-

-

-

-

-

-

-

-

-

-

x

-

-

-

-

-

x

-

-

-

-

-

-

Hibernation Hibernation

Hibernation

Breeding
Hibernation/Mating Mating

Chrysemys picta

Dormant

Dormant

Dormant

Dormant

413

pCourtship/
Mating /Basking

Breeding
Mating (when
most nesting
occurs)
Courtship/
Mating
/Basking

Table 30. (cont’d)
Species
Chelydra
serpentina

January
Dormant

February
Dormant

March
Dormant

April
Dormant

Nerodia sipedon

-

-

-

Thamnophis sp.

Hibernation Hibernation

Hibernation

Courtship and
Courtship and
mating
mating
Mating/Hibernation Mating

June
Mating/ Active
mostly in
morning and
early evening;
even nocturnal.
Courtship and
mating
-

Trionyx sp.
Amblema costata
Elliptio dilatatus
Fusconaia flava
(Raf.)
Quadrula
pustulosa (Lea)
Pleurobema
(cordatum)
coccineum
(Conrad)
Cyclonaias
tuberculata
Lasmigona
costata (Raf.)
Strophitus
rugosus (Swain.)
Lampsilis
siliquoidea (L)

-

-

-

Mating
-

Mating
-

Eggs laid
-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

414

May
Mating

Table 30. (cont’d)
Species
Obovaria
subrotunda (Raf.)
Ligumia (Recta)
lattissima (Raf.)
Actinonaias
carinata (Barnes)
Discus cronkhitei
Anguispira kochi
Anodonta grandis
footiana (Say)
Goodrich
Micromya
(Villosa) Iris (Lea)
Goodrich
Amblema costata
(Rafinesque)
Goodrich
Ligumia recta
(Lamarck)
Goodrich
Valvata
tricarinata (Say)
Goniobasis
livescens (Say)
Somatogyrus sp.
Amnicola lustrica
(Pilsbry)
Lymnaea

January
-

February
-

March
-

April
-

May
-

June
-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

415

Table 30. (cont’d)
Species
columella (Say)
Helisoma
Campanulatum
Stenotrema
monodon
(Racket)
Mesodon
thyroidus (Say)
Triodopsis
albolabris (Say)
Triodopsis
multilineata (Say)
Anguispira
alternata
Anguispira
solitaria (Say)
Helicodiscus
parallelus (Say)
Haplotrema
concavium (Say)
Mesomphix
cuprea (Say)
Amnicola Limosa
(Say)
Pomatiopsis
lapidaria (Say)
Lymnaea
(Staginicola)

January

February

March

April

May

June

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

416

Table 30. (cont’d)
Species
palustris (Say)

January

February

March

April

May

June

Helisoma trivolvis
(Say)
Retinella rhoadsi
(Pilsbry)
Succinea ovalis
(Say)
Campeloma
decisum (Say)
Helisoma anceps
(Conrad)
Zonitidae
Pelecypoda

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

417

Table 31. Resource schedule detail July – December
Species
Cervus
canadensis
Odocoileus
virginianus
Procyon lotor

July
-

August
Courtship

September
Rutting season

October
Rutting season

November
-

December
-

-

-

Mating

Mating

Mating

-

-

-

-

-

-

Ursus americanus

-

-

-

-

Castor canadensis
Ondatra
zibethicus
Canis sp. (lupus,
familiaris)
Martes
americana
Marmota monax

Litter production

-

-

-

Litter
production
-

(Mating? 210
day gestation)
Litter
production
-

Winter
dormancy
Winter
dormancy
-

-

-

-

Courtship

Courtship/birth Birth

Birth

Birth

Birth

Active morning,
afternoon
(mother is rid of
offspring)
-

Active
morning,
afternoon

-

-

Hibernation

Courtship,
mating
-

Mustela vison
Lynx rufus
Erethizon
dorsatum
Lontra canadensis Martes pennanti
Sciurus sp.
Litter production

(?) Breeding
-

-

-

Courtship, mating

Litter
production

-

-

-

418

Table 31. (cont’d)
Species
Leporidae sp.
(Sylvilagus)
Vulpes fulva

July
Mating/birth

August
Birth

September
-

October
-

November
-

December
-

-

-

Autumn movement

-

Mating

Alces alces

-

-

Rutting/ mating

Rutting/ mating

Blarina sp.

Mating/
pregnancies/
litters
Litter production;
Less common in
the wildlife
community

-

-

Rutting/
mating
-

-

Retreat to winter
quarters

-

Reduction of
population
Breeding

Mating/
pregnancies/
litters
Litter
production,
less common
in the wildlife
community
Reduction of
population
Breeding

Autumn
movement
Rutting/
mating
Mating/
pregnancies/
litters
-

Mating

Birth of litter

-

Breeding

Breeding

Breeding

Little to no
activity
Breeding

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

Tamias sp.

Muridae sp.
Peromyscus sp.
Microtus sp.
Acipenser
fulvescens
Perca flavescens
Amia calva
Aplodinotus
grunniens
Monroe chrysops
Micropterus
salmoides

419

Table 31. (cont’d)
Species
Micropterus
dolomieui
Esox lucius
Stizostedion
vitreum
Ictalurus
punctatus
Lepisosteus
oculatus
Salvelinus
namaycush
Ictalurus melas
Ictalurus natalis
Ictalurus
nebulosus
Moxostoma sp.
(macrolepidotum)
Pomoxis sp.
Catostomus sp.
(catostomus,
commersoni)
Centrarchidae
Lepomis cf.
macrochirus
Pomoxis
nigromaculatus
Stizostedion
canadense

July
-

August
-

September
-

October
-

November
-

December
-

-

-

-

-

-

-

Nesting/eggs laid

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

Spawn/nest
Spawn

Spawn/nest
-

Spawn/nest
-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

Spawn
-

Spawn
-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

420

Table 31. (cont’d)
Species
Lota lota lacustris

July
-

August
-

September
-

October
-

November
-

December
Spawn

Ectopistes
migratorius
Anas discors

Nesting/eggs
hatched
-

Nesting/eggs
laid
-

Migrating out of
Michigan
-

-

-

-

-

Anas americana

-

-

Migrating out
of Michigan
Migrates out
of Michigan
Returns to
Michigan

-

-

Anas
platyrhynchos

-

-

Migrates south out
of Michigan

-

Aythya collaris

-

-

Migrates south out
of Michigan

-

-

Mergus
merganser

-

-

Found on ponds,
streams, shores

-

-

Mergus serrator

-

-

Migrates south into
middle or out of
Michigan

-

-

Gavia immer
Podilymbus
podiceps
Meleagris
gallopavo

-

-

Migrates south
out of
Michigan
Migrates south
out of
Michigan
Found on
ponds,
streams,
shores
Migrates south
into middle or
our of
Michigan
-

Leaves
Michigan to
go south
-

-

-

Absent

-

-

-

-

-

-

421

Table 31. (cont’d)
Species
Lophodytes
cucullatus

July
-

August
-

September
-

October
-

November
-

Corvus
brachyrhynchos
Botaurus
lentiginosus

-

-

-

-

-

-

-

-

Migrate out of
Michigan
-

Ardea herodias

-

-

-

-

Migrates out of
Michigan

Grus canadensis
Aythya marila

Nesting

Nesting

-

-

Migration south

Bubo virginianus

-

-

-

-

-

Migrates
out of
Michigan
Migrates
out of
Michigan
Migration
south
-

Chenopodium
Zea mays
Iva annua
Carex sp.
Cyperus
Zizania aquatica
Quercus
Carya
J. cinerea
Juglans nigra
Corylus

-

x

x

x

-

-

x
x
x
-

x
x
x
x
-

x
x
x
x
Fruit/nut
-

x
Fruit/nut
Fruit/nut

-

-

-

Nut

Nut

-

-

-

422

December
Open
running
waters
-

Table 31. (cont’d)
Species
americana
Castanea dentata
Cucurbita pepo
Amphicarpaea
bracteata
Geranium
maculatum
Pyrus sp.
Physalis
Convolvulaceae
Brassicaceae sp.
Fragaria
virginiana
Galium aparine
Helianthus
divaricatus
Polygala senega
Rubus
occidentalis
Celtis occidentalis
Vitis sp.
Crataegus sp.
Viburnum sp.
Rhus sp
Polygonum
pensylvanicum
Prunus spp.
Sambucus

July

August

September

October

November

December

Flowers
-

Nut
Fruit
Fruit

Nut
Fruit
Fruit

Nut
Fruit

-

-

-

Fruit

Fruit

Fruit

-

-

Fruit

Fruit
Fruit
Fruit

Fruit
Fruit
-

Fruit
Fruit
-

-

-

Fruit
Fruit

Fruit
Fruit

Fruit

Fruit

-

-

Fruit

Fruit

Fruit

-

-

-

Fruit

-

Nut
-

Nut
-

-

-

x
Fruit
x

Fruit
x

x

-

-

-

x

x
x

x
-

x
-

-

-

423

Table 31. (cont’d)
Species
canadensis
Prunus serotina
Amelanc
(Amelanchier
Medikus)
Aster cordifolius
Sassafras albidum
Hypericum
Cornus rugosa
Gaylussacia
baccata
Lamiaceae
Rosa palustris
Pinus
Fraxinus alba
P. resinosa
P. strobus
Ulmus rubra
Ulmus sp.
Cercis canadensis
Tilia americana
Q. nigra
Q. bicolor
Q. rubra
Populus
tremuloides
Carya laciniosa
Carya ovata

July

August

September

October

November

December

x

x

-

-

-

-

x
x
-

x
x
-

x
Fruit
x
-

x
Fruit
-

-

-

x
x
Fruit/Legume
Flowers
-

x
x
-

x
Fruit/nut
Fruit/nut
-

Nut
Fruit/nut
Fruit/nut
Fruit/nut
-

-

-

-

-

-

Fruit/nut
Fruit/nut

-

-

424

Table 31. (cont’d)
Species
Cornus racemosa
Fagus americana
Ostraya
virginiana
Fraxinus sp
Fagus grandifolia
Acer spp.
Betula spp.
Morus rubra
Platanus
occidentalis
Picea
Typha
Rumex spp.
Panicum spp.
Silphium
terebinthinaceum
Smilacina
racemosa
Smilacina stellata
Maianthemum
canadense
Onoclea Sensibilis
Poa pratensis
Smilax lasioneura
Solidago Sp.
Thalictrum
dioicum

July
x
-

August
-

September
Nut
-

October
Nut
-

November
-

December
-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

Fruit

-

-

x
x
x

x
x

x
x

-

-

-

-

-

-

-

-

-

x

-

-

-

-

-

x
x
x

x
x
-

x
x
-

Fruit
-

Fruit
-

-

425

Table 31. (cont’d)
Species
Viola
pensylvanica
Viola sororia
(Sens. Lat.)
(Glabrous plants
like this one have
been referred to
V. Papilionacea)
Zanthoxylum
americanum
Lilium
michiganense
Lysimachia ciliata
Carex blanda
Carex lupulina
Carex
pensylvanica
Smilax cirrata
Toxicodendron
radicans
Apocynum
androsaemifolium
Aquilegia
canadensis
Aralia nudicaulis
Barbarea vulgaris
Geum canadense
Satureja vulgaris

July
-

August
-

September
-

October
-

November
-

December
-

-

-

-

-

-

-

-

Fruit

Fruit

-

-

-

x

-

-

-

-

-

x
x
x
x

x
x
x
x

x
x
x

-

-

-

-

Fruit

Fruit

Fruit
-

Fruit
-

-

-

x

x

x

-

-

x

-

-

-

-

-

x
x
x
-

x
x

x

x

-

-

426

Table 31. (cont’d)
Species
Monarda
fistulosa
Osmorhiza
longistylis
Podophyllum
peltatum
Trillium
grandiflorum
Lithospermum
canescens
Taraxacum
officinale
Anura sp.
Emydoidea
blandingii
Chrysemys picta

Chelydra
serpentina

Nerodia sipedon

July
-

August
x

September
x

October
x

November
-

December
-

-

x

x

x

-

-

-

x

x

x

-

-

x

-

-

-

-

-

x

-

-

-

-

-

-

x

x

x

-

-

Mating – most
hatchlings
emerge
Courtship/
Mating
/Basking
Mating

Mating/Hibernation Mating/Hibernation Hibernation

Litter
production

Breeding
Mating

Tadpoles
Mating- most
hatchlings
emerge
Courtship/Mating Courtship/
Basking
Mating
/Basking
Mating/ Active
Mating/ Active
mostly in
mostly in
morning and
morning and
early evening;
early evening;
even nocturnal.
even
nocturnal.
Litter
production

427

Dormant

Dormant

Dormant

Mating

Dormant

Dormant

-

-

-

Table 31. (cont’d)
Species
Thamnophis sp.

July
-

Trionyx sp.

Eggs laid

August
Litter
production
Hatchlings
emerge

September
Litter
production
Hatchlings
emerge

428

October
Hibernation

November
Hibernation

December
Hibernation

-

-

-

Table 32. Resource schedule summary
Resource
Nuts
Chestnut
Shagbark
hickory
Hazel
Beech
Black walnut
Butternut
Oak
Bush fruit
Juneberry
Wild
strawberry
Teaberry
Black
huckleberry
Mayapple
Currant,
gooseberry
Raspberry,
blackberry,
dewberry
Elderberry
Red berried
elder
False
Solomon's seal
Blueberry
High bush
cranberry,
sheepberry
Grape
Tree fruit
Hackberry
Hawthorn
Black cherry
Tubers

JAN FEB

MAR APR

MAY JUN JUL

AUG SEP

OCT

X
X
X

X

X
X

X

X

X
X

X
X

X
X

X

X

X
X
X
X

X

X
X

X

X

X

X

X
X

X
X

X

X
X
X

X

X
X
X

X

X

429

X

X

X

X

NOV DEC

Table 32. (cont’d)
Resource
Wild onion
Wild leek
Meadow garlic
Groundnut
Rosary root
Jack-in-thepulpit
Spring beauty
Pepperroot
Cow parsnip
Crow potato
American
lotus
Pond lily
Solomon's seal
Arrowhead,
Wapato
Wapato
Bulrush
False
Solomon's seal
Greenbriar
Skunk cabbage
Cattail
Greens
Common
Milkweed
Aster
Butterflyweed
Marsh
marigold
Goosefoot,
etc.
Cow parsnip
Wood sorrels
Cress
Bulrush

JAN FEB

MAR

APR

MAY JUN JUL

X
X

AUG SEP

OCT

X
X

X

X

X

X
X

X
X

X
X
X

X

X

X
X

X
X
X

X
X
X

X
X

X
X

X
X
X

X
X
X
X

X
X
X

X
X
X

X

X

X

X

X

X

X
X

X

X
X

X
X
X

X
X
X

X

X
X
X
X

X
X
X

430

X

X

X

NOV DEC

Table 32. (cont’d)
Resource
Sedge
Weed seeds
Pigweed, etc.
Tree sap
Sugar Maple
Mussel
Aquatic Turtle
Waterfowl
Squirrel
Rabbit
Pigeon
Fish
Bear
Beaver
Deer
Elk
Raccoon
Muskrat
Woodchuck

JAN FEB

MAR

MAY JUN JUL

?

?

AUG SEP

OCT

NOV DEC

X
X

X

X
X

APR

?

X
X
X

X
X
X

X
X
X

X
X

X
X
X
X
X

X
X
X
X
X

X
X
X
X
X

X
X

X
X

X
X

X
X

X
X

X
X

X
X

X
X
X
X
X
X
X

X
X
X
X
X
X
X

X
X

X
X

X
X

X
X

X
X
X
X

X
X
X
X

X
X
X
X
X
X
X

X
X

X
X
X
X

X
X
X
X
X
X
X

X
X
X
X
X

X
X
X
X
X

X
X

X
X

X
X

X
X

X
X

X
X

X
X

X
X

X
X

431

Table 33. Resource usability
modified from (Egan 1993)
Resource
% Useable
Bear
70
Beaver
70
Deer
65
Elk
65
Fish
88
Fisher
70
Muskrat
70
Passenger
75
Pigeon
Raccoon
70
Squirrel
70
Turtle
50
Waterfowl
80

Reference
estimate
White (1953)
Foote (1965, Binford (1978)
Hoygaard (1941)
estimate
White (1953)
estimate
White (1953)
White (1953)
Clark and Southall (1920)
Hoygaard (1941)

*Estimates of White have been increased to account for complete use
of the animal, including the viscera (However, note Stewart and Stahl
1977).
*Figures for deer and elk are based on caribou.

432

Appendix C: Archaeology

Archaeology

433

Sites Summary
Table 34. Sites
Site Name

County

Township

River Basin

Cultural Period

Function

Lalone

State Site
File No.
20AC20

Arenac

Standish

Lake Huron

Late Archaic

base camp

Lalone

20AC20

Arenac

Standish

Lake Huron

Middle Woodland

camp

Potts

20AC61

Arenac

Deep River

Lake Huron

Late Archaic

undetermined

Schmidt 2-4/KERR 7

20AC123
20BY1

Arenac
Bay

Standish
Bangor

Lake Huron
Lake Huron

Late Archaic
Early Woodland

camp
undetermined

Schmidt 2-4/KERR 7

20BY1

Bay

Bangor

Lake Huron

Late Archaic

undetermined

Schmidt 2-4/KERR 7

20BY1

Bay

Bangor

Lake Huron

Middle Woodland

undetermined

Schmidt 1-4 (Iamokia)

20BY3

Bay

Pinconning

Lake Huron

Late Archaic

village

Schmidt 1-1/Kerr
19/Lamoka
Schmidt 23/Behmlander
Schmidt 23/Behmlander
Fletcher/Marquette
Viaduct/Defoe Park
Fletcher/Marquette
Viaduct/Defoe Park

20BY16

Bay

Kawkawlin

Lake Huron

Late Archaic

camp

20BY17

Bay

Kawkawlin

Lake Huron

Late Archaic

undetermined

20BY17

Bay

Kawkawlin

Lake Huron

20BY28

Bay

Bay City

Saginaw

Early Woodland

Village

20BY28

Bay

Bay City

Saginaw

Late Archaic

Village

434

unknown

Table 34 (cont’d)
Site Name

State Site
File No.
20BY28

County

Township

River Basin

Cultural Period

Function

Bay

Bay City

Saginaw

Middle Woodland

village

20BY29

Bay

Pinconning

Lake Huron

Late Archaic

camp

20BY30
20BY30
20BY30
20BY35

Bay
Bay
Bay
Bay

Bay City
Bay City
Bay City
Monitor

Saginaw
Saginaw
Saginaw
Lake Huron

Early Woodland
Late Archaic
Middle Woodland
Early Woodland

fishing camp
fishing camp
hunting camp
undetermined

Boy Scout Cabin

20BY35

Bay

Monitor

Lake Huron

Late Archaic

undetermined

Boy Scout Cabin

20BY35

Bay

Monitor

Lake Huron

Middle Woodland

undetermined

Schmidts 1-5

20BY46

Bay

Kawkawlin

Lake Huron

Late Archaic

undetermined

Surath's Junk Yard
Third Street Bridge
Third Street Bridge
Schmidt 2-9

20BY77
20BY79
20BY79
20BY84

Bay
Bay
Bay
Bay

Bay City
Bay City
Bay City
Kawkawlin

Saginaw
Saginaw
Saginaw
Lake Huron

Middle Woodland
Late Archaic
Middle Woodland
Late Archaic

camp
fall camp
undetermined
unknown

Schmidt 2-9

20BY84

Bay

Kawkawlin

Lake Huron

W.N. Schmidt

20BY92

Bay

Beaver

Lake Huron

Late Archaic

camp

W.N. Schmidt

20BY92

Bay

Beaver

Lake Huron

Middle Woodland

camp

Fletcher/Marquette
Viaduct/Defoe Park
Butterfield/ Schmidt 51/ Paul Wendeloski/
20BY5/ 20BY74
Kantzler
Kantzler
Kantzler
Boy Scout Cabin

435

undetermined

Table 34 (cont’d)
Site Name

County

Township

River Basin

Cultural Period

Function

Meier/PFUND
McMillan

State Site
File No.
20BY94
20BY96

Bay
Bay

Monitor
Monitor

Saginaw
Lake Huron

Late Archaic
Late Archaic

camp
camp

McMillan

20BY96

Bay

Monitor

Lake Huron

Early Woodland

camp

Kerr 20

20BY133

Bay

Kawkawlin

Lake Huron

Late Archaic

camp

Kerr 20

20BY133

Bay

Kawkawlin

Lake Huron

Late Archaic

cremation

Crow Island West
Ubu's Booboo/ Tobico
#84
Doan/ Schuman

20BY153
20BY314

Bay
Bay

Frankenlust
Bangor

Saginaw
Lake Huron

Late Archaic
Middle Woodland

camp
camp

20BY159

Bay

Bangor

Lake Huron

Late Archaic

camp

Jahrman Ranch
Jahrman Ranch
Dutch Creek
Parish West

20BY161
20BY161
20BY200
20BY219
20BY246

Bay
Bay
Bay
Bay
Bay

Hampton
Hampton
Frankenlust
Frankenlust
Kawkawlin

Saginaw
Saginaw
Saginaw
Saginaw
Lake Huron

Early Woodland
Late Archaic
Middle Woodland
Late Archaic
Late Archaic

camp
camp
camp
unknown
camp

Schmidt Trail

20BY247

Bay

Kawkawlin

Lake Huron

Late Archaic

camp

Tobico #63

20BY263

Bay

Lake Huron

Middle Woodland

camp

Halm's Find

20BY292

Bay

Lake Huron

Middle Woodland

undetermined

Kawkawlin

436

Table 34 (cont’d)
Site Name
Expatriot/ Tobico #78
Joel's Jagged Edge/
Tobico #82
Viaduct South
Viaduct South

State Site
File No.
20BY308

County

Township

River Basin

Cultural Period

Function

Bay

Bangor

Lake Huron

Middle Woodland

camp

20BY312

Bay

Bangor

Lake Huron

Middle Woodland

camp

20BY387
20BY387

Bay
Bay

Bay City
Bay City

Saginaw
Saginaw

Early Woodland
Late Archaic

Bay
Bay
Bay
Clinton
Clinton
Clinton
Clinton
Clinton
Clinton
Clinton
Clinton
Clinton
Clinton
Clinton
Clinton
Clinton
Clinton
Clinton
Clinton
Clinton

Frankenlust
Frankenlust
Frankenlust
Duplain
Duplain
Victor
Victor
Duplain
Duplain
Victor
Watertown
Dewitt
Dewitt
Watertown
Watertown
Watertown
Watertown
Victor
Victor
Bath

Saginaw
Saginaw
Saginaw
Grand
Grand
Grand
Grand
Grand
Grand
Grand
Grand
Grand
Grand
Grand
Grand
Grand
Grand
Grand
Grand
Grand

Early Woodland
Late Archaic
Early Woodland
Late Archaic
Middle Woodland
Late Archaic
Middle Woodland
Late Archaic
Middle Woodland
Late Archaic
Late Archaic
Early Woodland
Late Archaic
Early Woodland
Late Archaic
Middle Woodland
Late Archaic
Late Archaic
Middle Woodland
Late Archaic

camp
camp/
cemetery
camp
camp
camp
camp
mound group
base camp
base camp
undetermined
undetermined
camp
activity area
base camp
base camp
base camp
base camp
base camp
activity area
camp
camp
activity area

20BY388
20BY388
20BY400
Kelley
20CL2
Cobbs Farm
20CL3
Beckworth Site No. 21
20CL56
Beckworth Site No. 21
20CL56
Hinkley
20CL75
Hinkley
20CL75
Leonard LGR-79-5
20CL95
Bean 1 LGR-79-6
20CL96
Lerg
LBR-79-9
20CL99
Lerg
LBR-79-9
20CL99
Oliver 1 LGR-79-10
20CL100
Oliver 1 LGR-79-10
20CL100
Oliver 1 LGR-79-10
20CL100
Openlander LGR-79-12 20CL102
Baker
LGR-79-17
20CL105
Baker
LGR-79-17
20CL105
Bower
LGR-79-25
20CL110

437

Table 34 (cont’d)
Site Name
High Grass
High Grass
Lerg
Cloddy
Steinhardt
Steinhardt
Hufnagel
Thelen
Thelen
Smith
Goerge Find spot
Bull Dog 1
Bull Dog 2
Badder
Badder
Badder
James Stout
Butler
Hachtel D
Harmon
Harmon
Harmon
Pine Grove Cemetery
Mott Lake
Gainey
Warner School

State Site
File No.
20CL147
20CL147
20CL148
20CL153
20CL224
20CL224
20CL231
20CL235
20CL235
20CL236
20CL241
20CL276
20CL277
20CL284
20CL284
20CL284
20GS101
20GS104
20GS107
20GS109
20GS109
20GS109
20GS28
20GS30
20GS49
20GS6

County

Township

River Basin

Cultural Period

Function

Clinton
Clinton
Clinton
Clinton
Clinton
Clinton
Clinton
Clinton
Clinton
Clinton
Clinton
Clinton
Clinton
Clinton
Clinton
Clinton
Genesee
Genesee
Genesee
Genesee
Genesee
Genesee
Genesee
Genesee
Genesee
Genesee

Dewitt
Dewitt
Olive
Olive
Dewitt
Dewitt
Bingham
Westphalia
Westphalia
Riley
Lebanon
Greenbush
Greenbush
Eagle
Eagle
Eagle
Montrose
Grand Blanc
Grand Blanc
Thetford
Thetford
Thetford
Davison
Genesee
Grand Blanc
Flint

Grand
Grand
Grand
Grand
Grand
Grand
Grand
Grand
Grand
Grand
Grand
Grand
Grand
Grand
Grand
Grand
Flint
Flint
Flint
Flint
Flint
Flint
Flint
Flint
Flint
Flint

Early Woodland
Late Archaic
Late Archaic
Late Archaic
Early Woodland
Late Archaic
Late Archaic
Late Archaic

undetermined
undetermined
camp
undetermined
undetermined
undetermined
undetermined
undetermined
undetermined
undetermined
undetermined
camp
camp
undetermined
undetermined
undetermined
undetermined
undetermined
undetermined
undetermined
undetermined
undetermined
camp
camp
undetermined
undetermined

438

Late Archaic
Late Archaic
Late Archaic
Late Archaic
Late Archaic
Middle Woodland
Late Archaic
Late Archaic
Late Archaic
Early Woodland
Late Archaic
Middle Woodland
Late Archaic
Late Archaic
Late Archaic
Late Archaic

Table 34 (cont’d)
Site Name

County

Township

River Basin

Cultural Period

Function

No Name

State Site
File No.
20GS63

Genesee

Fenton

Shiawassee

Late Archaic

cemetery

Kozel
Van Sickle

20GS76
20GS77

Genesee
Genesee

Flushing
Fenton

Flint
Shiawassee

Late Archaic
Late Archaic

habitation
undetermined

No Name

20GS78

Genesee

Argentine

Shiawassee

Late Archaic

cemetery

No Name
Barber
Barber
Kish
No Name
No Name
No Name
Dehaan

20GS84
20GS91
20GS91
20GS93
20GS96
20GS97
20GS98
20GW3

Genesee
Genesee
Genesee
Genesee
Genesee
Genesee
Genesee
Gladwin

Montrose
Montrose
Montrose
Montrose
Montrose
Montrose
Montrose
Hay

Flint
Flint
Flint
Flint
Flint
Flint
Flint
Tittabawassee

Middle Woodland
Late Archaic

undetermined
undetermined
undetermined
camp
undetermined
undetermined
undetermined
undetermined

20GR13

Gratiot

Arcada

Tittabawassee Middle Woodland

camp

Sutherland GR-11

20GR23

Gratiot

Sumner

Tittabawassee Middle Woodland

undetermined

Pine River Park,
Conservation Park GR13
MLP2-20

20GR33

Gratiot

Arcada

Tittabawassee Late Archaic

winter camp

20GR105

Gratiot

Wheeler

Shiawassee

Early Woodland

camp

MLP2-20

20GR105

Gratiot

Wheeler

Shiawassee

Late Archaic

camp

Kantiz

GR-1

439

Late Archaic
Late Archaic
Middle Woodland
Middle Woodland
Late Archaic

Table 34 (cont’d)
Site Name

County

Township

River Basin

Louis Thaller

State Site
File No.
20GR163

Gratiot

Seville

Tittabawassee Late Archaic

camp

Powelson 3

20GR183

Gratiot

Hamilton

Shiawassee

Early Woodland

undetermined

Powelson 3

20GR183

Gratiot

Hamilton

Shiawassee

Late Archaic

camp

Powelson 4

20GR184

Gratiot

Hamilton

Shiawassee

Late Archaic

lithic scatter

Burk 8E

20GR200

Gratiot

Elba

Shiawassee

Early Woodland

camp

Burk 8E

20GR200

Gratiot

Elba

Shiawassee

Late Archaic

camp

Burk 8E

20GR200

Gratiot

Elba

Shiawassee

Middle Woodland

undetermined

Burk 8W

20GR201

Gratiot

Elba

Shiawassee

Early Woodland

camp

Burk 8W

20GR201

Gratiot

Elba

Shiawassee

Late Archaic

camp

Burk 65

20GR210

Gratiot

Elba

Shiawassee

Late Archaic

undetermined

20GR230

Gratiot

Hamilton

Shiawassee

Middle Woodland

20GR250

Gratiot

Elba

Shiawassee

Late Archaic

findspot

20GR254

Gratiot

Layfayette

Shiawassee

Late Archaic

lithic scatter

440

Cultural Period

Function

Table 34 (cont’d)
Site Name

County

Township

River Basin

Cultural Period

Function

A. Derry Burk 96

State Site
File No.
20GR258

Gratiot

Hamilton

Shiawassee

Late Archaic

lithic scatter

Burk 116

20GR267

Gratiot

Hamilton

Shiawassee

Late Archaic

lithic scatter

Bay Port village

20HU1

Huron

Fairhaven

Lake Huron

Early Woodland

undetermined

Bay Port village

20HU1

Huron

Fairhaven

Lake Huron

20HU4

Huron

Fairhaven

Lake Huron

Early Woodland

camp

20HU107

Huron

Fairhaven

Lake Huron

Early Woodland

camp

Oak Point

20HU149

Huron

Caseville

Lake Huron

Late Archaic

undetermined

Melssner-Aumann
Jahr 2
Goodwin-Gresham
Brandt 1
Shellenbarger/ Probably
part of 20IS23
Shellenbarger/ Probably
part of 20IS23

20HU150
20HU152
20IS8
20IS46
20IS66

Huron
Huron
Iosco
Iosco
Iosco

Sebewaing
Sebewaing
Oscoda
Oscoda
Au Sable

Sebewaing
Sebewaing
Au Sable
Au Sable
Au Sable

Late Archaic
Late Archaic
Middle Woodland
Late Archaic
Late Archaic

camp
camp
fishing village
cemetery
undetermined

20IS66

Iosco

Au Sable

Au Sable

20IS67

Iosco

Tawas

Lake Huron

Late Archaic

undetermined

20IS84

Iosco

Oscoda

Au Sable

Late Archaic

camp

20IS87

Iosco

Oscoda

Au Sable

Middle Woodland

camp

Semeyn III/ USFS 09-0406-076

441

village

undetermined

Table 34 (cont’d)
Site Name

County

Township

River Basin

Cultural Period

Function

Eagle Hill
Van Etten Creek

State Site
File No.
20IS93
20IS98
20IS125
20IS140
20IS173
20IS175
20IS178
20IS241
20IS242

Iosco
Iosco
Iosco
Iosco
Iosco
Iosco
Iosco
Iosco
Iosco

Oscoda
Oscoda
Oscoda
Oscoda
Oscoda
Oscoda
Oscoda
Oscoda
Oscoda

Au Sable
Au Sable
Au Sable
Au Sable
Au Sable
Au Sable
Au Sable
Au Sable
Lake Huron

Late Archaic
Late Archaic
Middle Woodland
Middle Woodland
Middle Woodland
Late Archaic
Middle Woodland
Late Archaic
Middle Woodland

undetermined
camp
camp
camp
camp
undetermined
camp
undetermined
camp

USFS 09-04-06-185
USFS 09-04-06-185
Zeigler

20IS246
20IS246
20IB29

Iosco
Iosco
Isabella

Oscoda
Oscoda
Nottawa

Au Sable
Late Archaic
Au Sable
Middle Woodland
Tittabawassee Late Archaic

camp
camp
findspot

20LP6
20LP6
20LP7
20LP8
20LP8
20LP9
20LP11
20LP12
20LP13
20LP13
20LP14
20LP17
20LP19

Lapeer
Lapeer
Lapeer
Lapeer
Lapeer
Lapeer
Lapeer
Lapeer
Lapeer
Lapeer
Lapeer
Lapeer
Lapeer

Goodland
Goodland
Goodland
Goodland
Goodland
Burnside
North Branch
North Branch
North Branch
North Branch
North Branch
Burnside
North Branch

Flint
Flint
Flint
Flint
Flint
Flint
Flint
Flint
Flint
Flint
Flint
Flint
Flint

undetermined
undetermined
camp
camp
camp
camp
camp
camp
camp
camp
camp
camp
camp

Cooke South-1-25
Foote South-1-7
Old Orchard Park

Wim Hughes
Hodge
Hodge

Horeck 1
Swoish
Swoish
Slobodnski
Kesselring

442

Late Archaic
Late Archaic
Late Archaic
Late Archaic
Late Archaic
Late Archaic
Late Archaic
Late Archaic
Late Archaic
Late Archaic

Table 34 (cont’d)
Site Name
Wilbur 1
Wilbur 1
Ankley
Leo Csaike
Ditmas Younge
Holland 2
Holland 2

Dutch Smith
Helwig
Rozanski
Rozanski
Bowie
Ira Brown
Ira Brown
Ira Brown
Giddings-upton
Buckingham B
Stones Throw
Brown

State Site
File No.
20LP22
20LP22
20LP23
20LP28
20LP30
20LP38
20LP52
20LP65
20LP65
20LP67
20LP67
20LP86
20LP100
20LP291
20LP291
20LP16
20LP26
20LP26
20LP26
20LP94
20LP97
20LP283
20LP284
20LP296
20LV53

County

Township

River Basin

Cultural Period

Function

Lapeer
Lapeer
Lapeer
Lapeer
Lapeer
Lapeer
Lapeer
Lapeer
Lapeer
Lapeer
Lapeer
Lapeer
Lapeer
Lapeer
Lapeer
Lapeer
Lapeer
Lapeer
Lapeer
Lapeer
Lapeer
Lapeer
Lapeer
Lapeer
Livingston

Goodland
Goodland
Burnside
Burnside
Burnside
Burnside
Burnside
North Branch
North Branch
Goodland
Goodland
Goodland
Lapeer
Attica
Attica
Burnside
North Branch
North Branch
North Branch
Arcadia
Burlington
Attica
Oregon
Lapeer
Cohoctah

Flint
Flint
Flint
Flint
Flint
Flint
Flint
Flint
Flint
Flint
Flint
Flint
Flint
Flint
Flint
Flint
Flint
Flint
Flint
Flint
Flint
Flint
Flint
Flint
Shiawassee

Late Archaic

camp
camp
camp
undetermined
camp
camp
camp
undetermined
undetermined
undetermined
undetermined
camp
undetermined
undetermined
undetermined
camp
undetermined
undetermined
undetermined
undetermined
camp
undetermined
undetermined
camp
undetermined

443

Late Archaic
Late Archaic
Late Archaic
Late Archaic
Late Archaic
Late Archaic
Late Archaic
Early Woodland
Late Archaic
Late Archaic
Middle Woodland
Late Archaic
Early Woodland
Late Archaic
Late Archaic
Late Archaic
Late Archaic
Middle Woodland
Late Archaic
Late Archaic

Table 34 (cont’d)
Site Name

County

Township

River Basin

Brown

State Site
File No.
20LV53

Livingston

Cohoctah

Shiawassee

Emery Lii

20LV55

Livingston

Cohoctah

Shiawassee

Middle Woodland

undetermined

Bailey/ LCS-4

20LV108

Livingston

Hartland

Shiawassee

Late Archaic

undetermined

Wilkinson Viii/ LCS-18

20LV111

Livingston

Hartland

Shiawassee

Early Woodland

undetermined

Kuyda/ LCS-94

20LV133

Livingston

Howell

Shiawassee

Late Archaic

undetermined

Wilkinson Xvi/ LCS-26

20LV138

Livingston

Oceola

Shiawassee

Late Archaic

undetermined

Sartwell I/ LCS-46

20LV141

Livingston

Oceola

Shiawassee

Early Woodland

undetermined

Sartwell I/ LCS-46

20LV141

Livingston

Oceola

Shiawassee

Late Archaic

1--13--019

20LV318

Livingston

Hartland

Shiawassee

Early Woodland

1—13--020

20LV319

Livingston

Howell

Shiawassee

Middle Woodland

chipping
station
findspot/
ovate biface
camp

Peterson Preserve
Collection/ Alyce
Peterson Farm
Peterson Preserve
Collection/ Alyce
Peterson Farm

20MC78

Mecosta

Mecosta

Muskegon

Early Woodland

camp

20MC78

Mecosta

Mecosta

Muskegon

Late Archaic

camp

444

Cultural Period

Function
undetermined

Table 34 (cont’d)
Site Name

State Site
File No.
20MC78

County

Township

River Basin

Cultural Period

Function

Mecosta

Mecosta

Muskegon

Middle Woodland

camp

20MD3

Midland

Midland

Tittabawassee Early Woodland

undetermined

20MD3

Midland

Midland

Tittabawassee Late Archaic

cemetery

20MD3

Midland

Midland

Tittabawassee Middle Woodland

undetermined

20MD13

Midland

Midland

Tittabawassee Early Woodland

undetermined

20MD13

Midland

Midland

Tittabawassee Late Archaic

undetermined

20MD19

Midland

Midland

Tittabawassee Late Archaic

undetermined

CNC Arboretum

20MD19

Midland

Midland

Tittabawassee Early Woodland

undetermined

Orchard

20MD20

Midland

Midland

Tittabawassee Late Archaic

undetermined

Orchard

20MD20

Midland

Midland

Tittabawassee

undetermined

Sumac Bluff

20MD25

Midland

Midland

Tittabawassee Early Woodland

camp

Sumac Bluff

20MD25

Midland

Midland

Tittabawassee Middle Woodland

camp

Peterson Preserve
Collection/ Alyce
Peterson Farm
Pomranky/ part of
Cornelius' Midland 5
Pomranky/ part of
Cornelius' Midland 5
Pomranky/ part of
Cornelius' Midland 5
Windover Collection/
Cornelius' Midland 3,
Tanner 3, County Farm
Windover Collection/
Cornelius' Midland 3,
Tanner 3, County Farm
CNC Arboretum

445

Table 34 (cont’d)
Site Name

State Site
File No.
20MD29

County

Township

River Basin

Midland

Homer

Tittabawassee Early Woodland

camp

20MD30

Midland

Homer

Tittabawassee Early Woodland

camp

20MD30

Midland

Homer

Tittabawassee Late Archaic

camp

20MD31

Midland

Homer

Tittabawassee Early Woodland

undetermined

20MD34

Midland

Midland

Tittabawassee Late Archaic

camp

Sias Gravel

20MD42

Midland

Midland

Tittabawassee Early Woodland

undetermined

Coin Farm Cache

20MD45

Midland

Midland

Tittabawassee Late Archaic

Currie West Burial/
Cornelius' Midland 12
Currie West Burial/
Cornelius' Midland 12
Sias Flats-East

20MD52

Midland

Midland

Tittabawassee Late Archaic

turkey tail
cache
camp

20MD52

Midland

Midland

Tittabawassee Middle Woodland

cemetery

20MD57

Midland

Midland

Tittabawassee Late Archaic

camp

Sias Flats-East

20MD57

Midland

Midland

Tittabawassee

camp

Pomranky NW/ part of
Cornelius' Midland 5

20MD60

Midland

Midland

Tittabawassee Early Woodland

camp

Area N-B/ part of
Cornelius' Homer 7
Naugle/ Area “N”-A,
part of Cornelius'
Homer 7
Naugle/ Area “N”-A,
part of Cornelius'
Homer 7
Area 2/ part of
Cornelius' Homer 7
Oxbow South 2

446

Cultural Period

Function

Table 34 (cont’d)
Site Name

State Site
File No.
20MD60

County

Township

River Basin

Midland

Midland

Tittabawassee Late Archaic

camp

20MD69

Midland

Midland

Tittabawassee Early Woodland

undetermined

Tittabawassee River
Road/ IRA SMITH,
STEVENS 29
Tittabawassee River
Road/ IRA SMITH,
STEVENS 29
Riggie/ Cornelius'
Homer 4
Riggie/ Cornelius'
Homer 4
Francis Shore North B

20MD74

Midland

Homer

Tittabawassee Late Archaic

camp

20MD74

Midland

Homer

Tittabawassee

undetermined

20MD77

Midland

Homer

Tittabawassee Late Archaic

undetermined

20MD77

Midland

Homer

Tittabawassee

undetermined

20MD89

Midland

Edenville

Tittabawassee Late Archaic

undetermined

Francis Shore North B

20MD89

Midland

Edenville

Tittabawassee

undetermined

Paul Shaffer/ Cornelius'
Lee 11
Berlin

20MD90

Midland

Lee

Tittabawassee Late Archaic

burial

20MD95

Midland

Lee

Tittabawassee Early Woodland

undetermined

Berlin

20MD95

Midland

Lee

Tittabawassee Middle Woodland

undetermined

Geneva 1

20MD100

Midland

Geneva

Tittabawassee Early Woodland

camp

Pomranky NW/ part of
Cornelius' Midland 5

447

Cultural Period

Function

Table 34 (cont’d)
Site Name

County

Township

River Basin

Geneva 1

State Site
File No.
20MD100

Midland

Geneva

Tittabawassee Late Archaic

camp

Geneva 1

20MD100

Midland

Geneva

Tittabawassee Middle Woodland

camp

20MD110

Midland

Porter

Tittabawassee Late Archaic

camp

Big Mapleton

20MD116

Midland

Ingersoil

Tittabawassee Late Archaic

camp

Porter 1

20MD124

Midland

Porter

Tittabawassee Early Woodland

camp

Porter 1

20MD124

Midland

Porter

Tittabawassee Late Archaic

camp

20MD141

Midland

Larkin

Tittabawassee Middle Woodland

undetermined

20MD151

Midland

Jerome

Tittabawassee Middle Woodland

undetermined

20MD151

Midland

Jerome

Tittabawassee

undetermined

20MD152

Midland

Jerome

Tittabawassee Early Woodland

undetermined

20MD152

Midland

Jerome

Tittabawassee Middle Woodland

undetermined

20MD154

Midland

Jerome

Tittabawassee Late Archaic

undetermined

20MD164

Midland

Midland

Tittabawassee Early Woodland

undetermined

Piggot Farm/ Cornelius'
Jerom 2
Geisler

448

Cultural Period

Function

Table 34 (cont’d)
Site Name

State Site
File No.
20MD189

County

Township

River Basin

Midland

Homer

Tittabawassee Early Woodland

undetermined

20MD191

Midland

Midland

Tittabawassee Middle Woodland

undetermined

20MD223

Midland

Ingersoil

Tittabawassee Middle Woodland

undetermined

Smiths Crosing/
STEVENS 4
Turner Sand

20MD234

Midland

Ingersoil

Tittabawassee Late Archaic

camp

20MD239

Midland

Mount Haley

Tittabawassee Late Archaic

undetermined

Heritage Arms
Apartments
Maxwell ridge

20MD241

Midland

Midland

Tittabawassee Early Woodland

undetermined

20MD244

Midland

Hope

Tittabawassee Early Woodland

undetermined

Edenville/ Fred Stevens'
11
Sias River East/ 85 West

20MD258

Midland

Edenville

Tittabawassee Late Archaic

camp

20MD263

Midland

Midland

Tittabawassee Middle Woodland

camp

Porter 18

20MD275

Midland

Porter

Tittabawassee Early Woodland

undetermined

Porter 22

20MD278

Midland

Porter

Tittabawassee Early Woodland

undetermined

Porter 22

20MD278

Midland

Porter

Tittabawassee Middle Woodland

undetermined

20MD299

Midland

Jerome

Tittabawassee Late Archaic

undetermined

Pine River Bridge/
Tanner 6
Pomranky 2/ part of
Cornelius' Midland 5

449

Cultural Period

Function

Table 34 (cont’d)
Site Name

State Site
File No.
20MD300

County

Township

River Basin

Midland

Jerome

Tittabawassee Early Woodland

undetermined

Prarie Creek/ Cornelius'
Lee 3
Grose/ Cornelius' Lee 5,
Bear Track rock
Grose/ Cornelius' Lee 5,
Bear Track rock
Grose/ Cornelius' Lee 5,
Bear Track rock
H. Mashue Collection/
Cornelius' Lee 6
H. Mashue Collection/
Cornelius' Lee 6
Lee 9

20MD322

Midland

Lee

Tittabawassee Middle Woodland

undetermined

20MD323

Midland

Lee

Tittabawassee Early Woodland

undetermined

20MD323

Midland

Lee

Tittabawassee Late Archaic

habitation

20MD323

Midland

Lee

Tittabawassee Middle Woodland

undetermined

20MD324

Midland

Lee

Tittabawassee Late Archaic

undetermined

20MD324

Midland

Lee

Tittabawassee

undetermined

20MD325

Midland

Lee

Tittabawassee Late Archaic

camp

Dennet Sand

20MD363

Midland

Midland

Tittabawassee Early Woodland

undetermined

Coin Farm 2/ Tanner 1,
Cornelius' Greendale 3
Kaiser/ Tanner 16

20MD364

Midland

Midland

Tittabawassee Late Archaic

camp

20MD379

Midland

Midland

Tittabawassee Middle Woodland

undetermined

20MD394

Midland

Ingersoil

Tittabawassee Late Archaic

camp

Noack Copper/ Eugene
20MD443
Knapp, Cornelius' Lee 15

Midland

Lee

Tittabawassee Late Archaic

undetermined

450

Cultural Period

Function

Table 34 (cont’d)
Site Name

County

Township

River Basin

Mount Haley 4

State Site
File No.
20MD448

Midland

Mount Haley

Tittabawassee Late Archaic

undetermined

Smith

20MD453

Midland

Edenville

Tittabawassee Middle Woodland

camp

Aldrich

20MD478

Midland

Porter

Tittabawassee Late Archaic

camp

East Oxbow

20MD490

Midland

Midland

Tittabawassee Late Archaic

camp

East Oxbow

20MD490

Midland

Midland

Tittabawassee

camp

20MD536

Midland

Edenville

Tittabawassee Late Archaic

unknown

20MD536

Midland

Edenville

Tittabawassee

unknown

Lincoln Pines

20ML52

Montcalm

Pierson

Muskegon

Late Archaic

undetermined

Lloyd Vergin

20OK312

Oakland

Springfield

Shiawassee

Late Archaic

undetermined

Lloyd Vergin

20OK312

Oakland

Springfield

Shiawassee

Early Woodland

undetermined

Groveland Valley
Henry
Henry
Zimowske
Zimowske
Riopel

20OK372
20OL22
20OL22
20OD5
20OD5
20OD6

Oakland
Osceola
Osceola
Oscoda
Oscoda
Oscoda

Groveland
Osceola
Osceola
Big Creek
Big Creek
Mentor

Flint
Muskegon
Muskegon
Au Sable
Au Sable
Au Sable

Middle Woodland
Late Archaic
Late Archaic
Late Archaic
Middle Woodland
Late Archaic

undetermined
camp
camp
undetermined
undetermined
undetermined

451

Cultural Period

Function

Table 34 (cont’d)
Site Name

State Site
File No.
20OD61

County

Township

River Basin

Cultural Period

Function

Oscoda

Mentor

Au Sable

Early Woodland

undetermined

20RO39

Roscommon Richfield

Tittabawassee Middle Woodland

camp

Taymouth Dustin 7-6
Taymouth Dustin 7-6
French 1 Lutz 27
French 1 Lutz 27
Simons 63
Rose
Rose
Clunie

20SA78
20SA78
20SA709
20SA709
20SA720
20SA721
20SA721
20SA722

Saginaw
Saginaw
Saginaw
Saginaw
Saginaw
Saginaw
Saginaw
Saginaw

Taymouth
Taymouth
Bridgeport
Bridgeport
Spaulding
Spaulding
Spaulding
James

Flint
Flint
Cass
Cass
Flint
Flint
Flint
Tittabawassee

village
village
camp
camp
camp
camp
camp
undetermined

Clunie

20SA722

Saginaw

James

Tittabawassee Middle Woodland

camp

20SA748
20SA752
20SA759

Saginaw
Saginaw
Saginaw

Bridgeport
Bridgeport
Taymouth

Cass
Cass
Flint

Late Archaic
Late Archaic
Late Archaic

camp
undetermined
camp

20SA760

Saginaw

Taymouth

Flint

Late Archaic

camp

20SA764

Saginaw

Birch Run

Flint

Late Archaic

camp

20SA796

Saginaw

Albee

Shiawassee

Late Archaic

camp

20SA797

Saginaw

Spaulding

Flint

Late Archaic

camp

Recreation Area/ USFS
09-04-05-122
Long Point

Pine Grove
Leach 3, CAI-15,
20SA2026, Leach
Garden, Riverbank
Leach 4, 20SA202A, CAI14, North of Barn
Sheppard 1, Simons 38B
William Kulhanck
Ernest Adams

452

Late Archaic
Early Woodland
Late Archaic
Late Archaic
Late Archaic
Late Archaic

Table 34 (cont’d)
Site Name

County

Township

River Basin

Andrews

State Site
File No.
20SA8

Saginaw

saginaw

Tittabawassee Late Archaic

camp

Foster 2
Foster 2
Kunik Farms
Fischer A Findspot
Gill

20SA82
20SA82
20SA88
20SA801
20SA807

Saginaw
Saginaw
Saginaw
Saginaw
Saginaw

Taymouth
Taymouth
Albee
Bridgeport
Spaulding

Flint
Flint
Flint
Cass
Shiawassee

village
burial
camp
undetermined
base camp

Weinecke & Weiss

20SA808

Saginaw

saginaw

Tittabawassee Middle Woodland

undetermined

Boese 1, RAI-2
Boese 1, RAI-2
Vogelaar 2

20SA816
20SA816
20SA847

Saginaw
Saginaw
Saginaw

Spaulding
Spaulding
St. Charles

Cass
Cass
Shiawassee

Early Woodland
Late Archaic
Middle Woodland

undetermined
undetermined
camp

Menapace-Deindorfer
Niagara St. Garden
Dick, 20SA301

20SA860
20SA866
20SA867

Saginaw
Saginaw
Saginaw

saginaw
saginaw
St. Charles

saginaw
saginaw
Shiawassee

Late Archaic
Late Archaic
Early Woodland

camp
undetermined
undetermined

Dick, 20SA301

20SA867

Saginaw

St. Charles

Shiawassee

Late Archaic

undetermined

Dick, 20SA301

20SA867

Saginaw

St. Charles

Shiawassee

Middle Woodland

undetermined

Brabant, Burk 41

20SA878

Saginaw

St. Charles

Shiawassee

Early Woodland

camp

Brabant, Burk 41

20SA878

Saginaw

St. Charles

Shiawassee

Late Archaic

camp

453

Cultural Period

Late Archaic
Late Archaic
Late Archaic
Late Archaic
Late Archaic

Function

Table 34 (cont’d)
Site Name

County

Township

River Basin

Cultural Period

Function

Burk 41N

State Site
File No.
20SA879

Saginaw

St. Charles

Shiawassee

Early Woodland

camp

Burk 41N

20SA879

Saginaw

St. Charles

Shiawassee

Middle Woodland

camp

Burk 41E

20SA880

Saginaw

St. Charles

Shiawassee

Late Archaic

undetermined

Burk 41E

20SA880

Saginaw

St. Charles

Shiawassee

Early Woodland

camp

Fry

20SA881

Saginaw

saginaw

Tittabawassee Early Woodland

camp

Fry

20SA881

Saginaw

saginaw

Tittabawassee Late Archaic

camp

Simons Map 10
Simons Map 4
Trinklein VI

20SA887
20SA888
20SA896
20SA9

Saginaw
Saginaw
Saginaw
Saginaw

saginaw
saginaw
saginaw
saginaw

Flint
Flint
Cass
Tittabawassee

undetermined
undetermined
camp
camp

20SA9

Saginaw

saginaw

Tittabawassee Late Archaic

camp

20SA9

Saginaw

saginaw

Tittabawassee Middle Woodland

camp

20SA910
20SA910
20SA4

Saginaw
Saginaw
Saginaw

saginaw
saginaw
saginaw

Cass
Late Archaic
Cass
Tittabawassee Middle Woodland

camp
camp
camp

20SA42

Saginaw

saginaw

Cass

village

Pickleman
Pickleman
Little, Dustin 2-4,
Saginaw Plate Glass
Jerome, Dustin 6-61,
Simons 68, 20SA779

454

Late Archaic
Middle Woodland
Late Archaic
Early Woodland

Early Woodland

Table 34 (cont’d)
Site Name

County

Township

River Basin

Cultural Period

Function

Toth, Lutz 13
Toth, Lutz 13
Trinklein
Anderson
Jerome
Vamey, Puisk North
Vamey, Puisk North
Watson Cache

State Site
File No.
20SA400
20SA400
20SA401
20SA402
20SA403
20SA404
20SA404
20SA420

Saginaw
Saginaw
Saginaw
Saginaw
Saginaw
Saginaw
Saginaw
Saginaw

saginaw
saginaw
saginaw
saginaw
saginaw
saginaw
saginaw
saginaw

Cass
Cass
Cass
Cass
Cass
Cass
Cass
Tittabawassee

Late Archaic
Late Archaic
Late Archaic
Late Archaic
Early Woodland
Late Archaic
Late Archaic

camp
camp
undetermined
undetermined
undetermined
undetermined
undetermined
cache

Sawatzki

20SA421

Saginaw

saginaw

Shiawassee

Late Archaic

camp

Schramke 2

20SA422

Saginaw

saginaw

Shiawassee

Late Archaic

camp

20SA447

Saginaw

saginaw

Tittabawassee Middle Woodland

camp

20SA449

Saginaw

saginaw

Tittabawassee Late Archaic

camp

20SA465

Saginaw

saginaw

Tittabawassee Late Archaic

camp

Intersection

20SA471

Saginaw

saginaw

Shiawassee

camp

Riverside, Dustin 2-5

20SA5

Saginaw

Saginaw

Tittabawassee Early Woodland

village

Riverside, Dustin 2-5

20SA5

Saginaw

Saginaw

Tittabawassee Late Archaic

village

Gray, Dustin 6-123,
20SA706

20SA55

Saginaw

saginaw

Cass

village

Leuenberger 2

455

Late Archaic

Late Archaic

Table 34 (cont’d)
Site Name

State Site
File No.
20SA55

County

Township

River Basin

Cultural Period

Function

Saginaw

saginaw

Cass

Middle Woodland

village

20SA56

Saginaw

saginaw

Tittabawassee Late Archaic

camp

20SA57

Saginaw

saginaw

Tittabawassee Middle Woodland

camp

Center St. Bridge
Sturm
Weber I, Dehmel Road
Dale Irish, MLP-10,
Simons 94
Mlp2-13

20SA514
20SA580
20SA581
20SA585

Saginaw
Saginaw
Saginaw
Saginaw

saginaw
saginaw
saginaw
saginaw

saginaw
Cass
Cass
Flint

Middle Woodland
Late Archaic
Late Archaic
Late Archaic

camp
undetermined
seasonal camp
camp

20SA594

Saginaw

saginaw

Shiawassee

Middle Woodland

camp

Wellpoint, MLP2-15,
Ebenhoh
Wellpoint, MLP2-15,
Ebenhoh
MLP-16, MLP2-17

20SA596

Saginaw

saginaw

Shiawassee

Late Archaic

camp

20SA596

Saginaw

saginaw

Shiawassee

Middle Woodland

camp

20SA597

Saginaw

saginaw

Shiawassee

Early Woodland

undetermined

MLP-16, MLP2-17

20SA597

Saginaw

saginaw

Shiawassee

Late Archaic

undetermined

MLP-16, MLP2-17

20SA597

Saginaw

saginaw

Shiawassee

Middle Woodland

undetermined

Bayou, Dustin 2-6

20SA6

Saginaw

saginaw

Tittabawassee Early Woodland

undetermined

Bayou, Dustin 2-6

20SA6

Saginaw

saginaw

Tittabawassee Late Archaic

undetermined

Gray, Dustin 6-123,
20SA706
Kinney, Dustin 2-83,
20SA418
Solms, Dustin 2-82

456

Table 34 (cont’d)
Site Name

County

Township

River Basin

Swan Creek, Dustin 5-4

State Site
File No.
20SA67

Saginaw

saginaw

Tittabawassee Late Archaic

village

Swan Creek, Dustin 5-4

20SA67

Saginaw

saginaw

Tittabawassee Middle Woodland

village

Albert Miller
Fort Road 1, Lutz 1,
Circle 1
Fort Road 1, Lutz 1,
Circle 1
Fort Road 2, Lutz Circle
2, Lutz 1
Fort Road 2, Lutz Circle
2, Lutz 1
Hoffman Hills, Lutz 2
Hoffman Hills, Lutz 2
Sheridan Hills, Lutz 6,
20SA616
Washington Terrace 2,
Lutz 7
Washington Terrace 2,
Lutz 7
Bridgeport Wastewater,
Lutz 9, Water Plant;
Bridgeport Township
Bridgeport Wastewater,
Lutz 9, Water Plant;
Bridgeport Township

20SA600
20SA604

Saginaw
Saginaw

saginaw
saginaw

saginaw
Cass

camp
camp

20SA604

Saginaw

saginaw

Cass

20SA605

Saginaw

saginaw

Cass

20SA605

Saginaw

saginaw

Cass

20SA606
20SA606
20SA615

Saginaw
Saginaw
Saginaw

saginaw
saginaw
saginaw

Cass
Cass
Cass

Early Woodland
Late Archaic
Early Woodland

camp
camp
undetermined

20SA617

Saginaw

saginaw

Cass

Late Archaic

undetermined

20SA617

Saginaw

saginaw

Cass

20SA620

Saginaw

saginaw

Cass

Early Woodland

warm season
camp

20SA620

Saginaw

saginaw

Cass

Late Archaic

camp

457

Cultural Period

Late Archaic
Late Archaic

Function

camp
Late Archaic

camp
camp

undetermined

Table 34 (cont’d)
Site Name

State Site
File No.
20SA620

County

Township

River Basin

Cultural Period

Function

Saginaw

saginaw

Cass

Middle Woodland

warm season
camp

20SA621
20SA622
20SA623
20SA623
20SA627

Saginaw
Saginaw
Saginaw
Saginaw
Saginaw

saginaw
saginaw
saginaw
saginaw
saginaw

Cass
Cass
Cass
Cass
Cass

Late Archaic
Late Archaic
Late Archaic
Middle Woodland
Late Archaic

camp
camp
camp
camp
camp

20SA629

Saginaw

saginaw

Cass

Late Archaic

camp

20SA629

Saginaw

saginaw

Cass

20SA631

Saginaw

saginaw

Cass

20SA631

Saginaw

saginaw

Cass

20SA632

Saginaw

saginaw

Cass

20SA632

Saginaw

saginaw

Cass

20SA635

Saginaw

saginaw

Shiawassee

Early Woodland

camp

Homer Burk, Burk 1

20SA635

Saginaw

saginaw

Shiawassee

Late Archaic

camp

Homer Burk West, Burk
1W

20SA636

Saginaw

saginaw

Shiawassee

Early Woodland

camp

Bridgeport Wastewater,
Lutz 9, Water Plant;
Bridgeport Township
Popp A, Lutz 10
Popp B, Lutz 10
Cooks Mill, Lutz 12
Cooks Mill, Lutz 12
Schmidt Field E,
Dorwood, Lutz 19
Schmidt Field A-2, Lutz
15
Schmidt Field A-2, Lutz
15
Schmidt Field C-1, Lutz
17
Schmidt Field C-1, Lutz
17
Schmidt Field C-2, Lutz
17
Schmidt Field C-2, Lutz
17
Homer Burk, Burk 1

458

undetermined
Late Archaic

camp
undetermined

Late Archaic

camp
undetermined

Table 34 (cont’d)
Site Name
Homer Burk West, Burk
1W
Clifford McQuiston East,
Burk 2
Clifford McQuiston East,
Burk 2
McQuiston, Burk 2W,
Main McQuiston
McQuiston, Burk 2W,
Main McQuiston
McQuiston South, Burk
2S
McQuiston South, Burk
2S
La Belle, Simons 109
La Belle, Simons 109
La Belle, Simons 109
Meyer, Simons 112
Gosen 4, Simons 96
Winterstein 1, Simons
97A
Winterstein 2, Simons
97B, 97C, 97D, 97E
Simons 185, Tom In The
Woods, Kunik
Hemker 1, Simons 106
Simons 160

State Site
File No.
20SA636

County

Township

River Basin

Cultural Period

Function

Saginaw

saginaw

Shiawassee

Late Archaic

camp

20SA637

Saginaw

saginaw

Shiawassee

Late Archaic

camp

20SA637

Saginaw

saginaw

Shiawassee

Middle Woodland

camp

20SA638

Saginaw

saginaw

Shiawassee

Early Woodland

camp

20SA638

Saginaw

saginaw

Shiawassee

Late Archaic

camp

20SA639

Saginaw

saginaw

Shiawassee

Late Archaic

camp

20SA639

Saginaw

saginaw

Shiawassee

Middle Woodland

camp

20SA642
20SA642
20SA642
20SA646
20SA651
20SA652

Saginaw
Saginaw
Saginaw
Saginaw
Saginaw
Saginaw

saginaw
saginaw
saginaw
saginaw
saginaw
saginaw

Flint
Flint
Flint
Flint
Flint
Flint

Early Woodland
Late Archaic
Middle Woodland
Late Archaic
Late Archaic
Late Archaic

camp
camp
camp
camp
camp
camp

20SA653

Saginaw

saginaw

Flint

Late Archaic

camp

20SA658

Saginaw

saginaw

Flint

Late Archaic

camp

20SA660
20SA672

Saginaw
Saginaw

saginaw
saginaw

Flint
Flint

Late Archaic
Late Archaic

camp
camp

459

Table 34 (cont’d)
Site Name

County

Township

River Basin

Cultural Period

Function

Burk 2B

State Site
File No.
20SA691
20SA696
20SA917

Saginaw
Saginaw
Saginaw

saginaw
saginaw
saginaw

Cass
Cass
Shiawassee

Late Archaic
Middle Woodland
Late Archaic

camp
camp
camp

Burk 3

20SA918

Saginaw

saginaw

Shiawassee

Early Woodland

undetermined

Burk 3

20SA918

Saginaw

saginaw

Shiawassee

Middle Woodland

undetermined

Burk 5

20SA920

Saginaw

saginaw

Shiawassee

Early Woodland

camp

Burk 5

20SA920

Saginaw

saginaw

Shiawassee

Late Archaic

camp

Burk 5

20SA920

Saginaw

saginaw

Shiawassee

Middle Woodland

camp

Burk 6A

20SA922

Saginaw

saginaw

Shiawassee

Early Woodland

camp

Burk 6A

20SA922

Saginaw

saginaw

Shiawassee

Late Archaic

camp

Burk 6A

20SA922

Saginaw

saginaw

Shiawassee

Middle Woodland

camp

Burk 6B

20SA923

Saginaw

saginaw

Shiawassee

Early Woodland

camp

Burk 6B

20SA923

Saginaw

saginaw

Shiawassee

Late Archaic

camp

Burk 6D

20SA925

Saginaw

saginaw

Shiawassee

Middle Woodland

undetermined

Simons 34

460

Table 34 (cont’d)
Site Name

County

Township

River Basin

Cultural Period

Function

Burk 6H

State Site
File No.
20SA926

Saginaw

saginaw

Shiawassee

Early Woodland

camp

Burk 6H

20SA926

Saginaw

saginaw

Shiawassee

Late Archaic

camp

Burk 7A

20SA927

Saginaw

saginaw

Shiawassee

Early Woodland

camp

Burk 7A

20SA927

Saginaw

saginaw

Shiawassee

Late Archaic

camp

Burk 11

20SA931

Saginaw

saginaw

Shiawassee

Early Woodland

undetermined

Burk 11

20SA931

Saginaw

saginaw

Shiawassee

Late Archaic

camp

Burk 11

20SA931

Saginaw

saginaw

Shiawassee

Middle Woodland

camp

Burk 12

20SA932

Saginaw

saginaw

Shiawassee

Early Woodland

camp

Burk 12

20SA932

Saginaw

saginaw

Shiawassee

Middle Woodland

undetermined

Burk 18B

20SA937

Saginaw

saginaw

Shiawassee

Early Woodland

camp

Burk 18B

20SA937

Saginaw

saginaw

Shiawassee

Late Archaic

camp

Burk 18C

20SA938

Saginaw

saginaw

Shiawassee

Late Archaic

camp

Burk 18C

20SA938

Saginaw

saginaw

Shiawassee

Middle Woodland

camp

461

Table 34 (cont’d)
Site Name

County

Township

River Basin

Cultural Period

Function

Burk 19A

State Site
File No.
20SA939

Saginaw

saginaw

Shiawassee

Early Woodland

camp

Burk 19A

20SA939

Saginaw

saginaw

Shiawassee

Late Archaic

camp

Burk 19A

20SA939

Saginaw

saginaw

Shiawassee

Middle Woodland

camp

Burk 19B

20SA940

Saginaw

saginaw

Shiawassee

Late Archaic

lithic scatter

Burk 19B

20SA940

Saginaw

saginaw

Shiawassee

Middle Woodland

camp

Burk 19C

20SA941

Saginaw

saginaw

Shiawassee

Late Archaic

camp

Burk 19N

20SA942

Saginaw

saginaw

Shiawassee

Late Archaic

camp

Burk 20N

20SA943

Saginaw

saginaw

Shiawassee

Early Woodland

undetermined

Burk 20N

20SA943

Saginaw

saginaw

Shiawassee

Late Archaic

undetermined

Burk 20S

20SA944

Saginaw

saginaw

Shiawassee

Early Woodland

camp

Burk 20S

20SA944

Saginaw

saginaw

Shiawassee

Late Archaic

camp

Burk 21A

20SA945

Saginaw

saginaw

Shiawassee

Late Archaic

camp

Burk 21B

20SA946

Saginaw

saginaw

Shiawassee

Middle Woodland

camp

462

Table 34 (cont’d)
Site Name

County

Township

River Basin

Cultural Period

Function

Burk 22

State Site
File No.
20SA947

Saginaw

saginaw

Shiawassee

Early Woodland

camp

Burk 23

20SA948

Saginaw

saginaw

Shiawassee

Early Woodland

camp

Burk 23

20SA948

Saginaw

saginaw

Shiawassee

Late Archaic

camp

Burk 24

20SA949

Saginaw

saginaw

Shiawassee

Late Archaic

camp

Burk 24

20SA949

Saginaw

saginaw

Shiawassee

Middle Woodland

camp

Burk 25

20SA951

Saginaw

saginaw

Shiawassee

Early Woodland

camp

Burk 25

20SA951

Saginaw

saginaw

Shiawassee

Late Archaic

camp

Burk 25

20SA951

Saginaw

saginaw

Shiawassee

Middle Woodland

camp

Burk 28N

20SA954

Saginaw

saginaw

Shiawassee

Late Archaic

camp

Burk 33B

20SA958

Saginaw

saginaw

Shiawassee

Late Archaic

camp

Burk 35

20SA959

Saginaw

saginaw

Shiawassee

Late Archaic

camp

Burk 38

20SA962

Saginaw

saginaw

Shiawassee

Early Woodland

camp

Burk 38

20SA962

Saginaw

saginaw

Shiawassee

Late Archaic

camp

463

Table 34 (cont’d)
Site Name

County

Township

River Basin

Cultural Period

Function

Burk 38N

State Site
File No.
20SA963

Saginaw

saginaw

Shiawassee

Late Archaic

camp

Burk 38W

20SA964

Saginaw

saginaw

Shiawassee

Early Woodland

undetermined

Burk 38W

20SA964

Saginaw

saginaw

Shiawassee

Late Archaic

camp

Burk 39E

20SA965

Saginaw

saginaw

Shiawassee

Early Woodland

camp

Burk 39W

20SA966

Saginaw

saginaw

Shiawassee

Early Woodland

camp

Burk 39W

20SA966

Saginaw

saginaw

Shiawassee

Late Archaic

camp

Burk 40

20SA968

Saginaw

saginaw

Shiawassee

Early Woodland

camp

Burk 40

20SA968

Saginaw

saginaw

Shiawassee

Middle Woodland

camp

Burk 42

20SA969

Saginaw

saginaw

Shiawassee

Early Woodland

camp

Burk 42

20SA969

Saginaw

saginaw

Shiawassee

Middle Woodland

camp

Burk 43

20SA970

Saginaw

saginaw

Shiawassee

Early Woodland

undetermined

Burk 43

20SA970

Saginaw

saginaw

Shiawassee

Late Archaic

camp

Burk 45

20SA972

Saginaw

saginaw

Shiawassee

Early Woodland

camp

464

Table 34 (cont’d)
Site Name

County

Township

River Basin

Cultural Period

Function

Burk 45

State Site
File No.
20SA972

Saginaw

saginaw

Shiawassee

Middle Woodland

camp

Burk 46

20SA973

Saginaw

saginaw

Shiawassee

Early Woodland

undetermined

Burk 46

20SA973

Saginaw

saginaw

Shiawassee

Late Archaic

camp

Burk 46

20SA973

Saginaw

saginaw

Shiawassee

Middle Woodland

camp

Burk 46B

20SA974

Saginaw

saginaw

Shiawassee

Early Woodland

undetermined

Burk 46B

20SA974

Saginaw

saginaw

Shiawassee

Late Archaic

camp

Burk 46B

20SA974

Saginaw

saginaw

Shiawassee

Middle Woodland

camp

Burk 48

20SA975

Saginaw

saginaw

Shiawassee

Middle Woodland

Burk 49

20SA976

Saginaw

saginaw

Shiawassee

Early Woodland

undetermined

Burk 49

20SA976

Saginaw

saginaw

Shiawassee

Middle Woodland

camp

Burk 51

20SA978

Saginaw

saginaw

Shiawassee

Early Woodland

camp

Burk 51

20SA978

Saginaw

saginaw

Shiawassee

Late Archaic

camp

Burk 51

20SA978

Saginaw

saginaw

Shiawassee

Middle Woodland

camp

465

Table 34 (cont’d)
Site Name

County

Township

River Basin

Cultural Period

Function

Burk 53

State Site
File No.
20SA980

Saginaw

Saginaw

Shiawassee

Early Woodland

camp

Burk 53

20SA980

Saginaw

Saginaw

Shiawassee

Late Archaic

camp

Burk 53

20SA980

Saginaw

Saginaw

Shiawassee

Middle Woodland

camp

Burk 54

20SA981

Saginaw

saginaw

Shiawassee

Middle Woodland

camp

Burk 54N

20SA982

Saginaw

saginaw

Shiawassee

Middle Woodland

camp

Burk 58

20SA987

Saginaw

saginaw

Shiawassee

Early Woodland

camp

Burk 58

20SA987

Saginaw

saginaw

Shiawassee

Late Archaic

undetermined

Burk 58

20SA987

Saginaw

saginaw

Shiawassee

Middle Woodland

camp

Burk 60

20SA989

Saginaw

saginaw

Shiawassee

Early Woodland

camp

Burk 60

20SA989

Saginaw

saginaw

Shiawassee

Late Archaic

camp

Burk 61S

20SA991

Saginaw

saginaw

Shiawassee

Late Archaic

camp

Burk 64

20SA994

Saginaw

saginaw

Shiawassee

Late Archaic

camp

Burk 66

20SA995

Saginaw

saginaw

Shiawassee

Middle Woodland

camp

466

Table 34 (cont’d)
Site Name

County

Township

River Basin

Cultural Period

Function

Burk 66A

State Site
File No.
20SA996

Saginaw

saginaw

Shiawassee

Late Archaic

undetermined

Burk 66A

20SA996

Saginaw

saginaw

Shiawassee

Middle Woodland

camp

Burk 66B

20SA997

Saginaw

saginaw

Shiawassee

Early Woodland

camp

Burk 66B

20SA997

Saginaw

saginaw

Shiawassee

Middle Woodland

camp

Burk 69

20SA998

Saginaw

saginaw

Shiawassee

Early Woodland

camp

Burk 69

20SA998

Saginaw

saginaw

Shiawassee

Late Archaic

camp

Burk 70

20SA999

Saginaw

saginaw

Shiawassee

Late Archaic

findspot

Stroebel, Dustin 2-18

20SA14

Saginaw

saginaw

Tittabawassee Early Woodland

Cemetary

Green Point

20SA1

Saginaw

saginaw

Tittabawassee Early Woodland

village

Green Point

20SA1

Saginaw

saginaw

Tittabawassee Middle Woodland

village

Dustin 8-5
Dustin 8-5
Walser 4-8, Dustin 4-8,
Miller 4, Burk 16B
Walser 4-8, Dustin 4-8,
Miller 4, Burk 16B
Bridgeport Enclosure

20SA102
20SA102
20SA108

Saginaw
Saginaw
Saginaw

saginaw
saginaw
saginaw

Flint
Flint
Shiawassee

Late Archaic
Late Archaic

camp
camp
camp

20SA108

Saginaw

saginaw

Shiawassee

Middle Woodland

camp

20SA123

Saginaw

saginaw

Cass

Late Archaic

undetermined

467

Table 34 (cont’d)
Site Name

State Site
File No.
20SA123
20SA128

County

Township

River Basin

Cultural Period

Function

Saginaw
Saginaw

saginaw
saginaw

Cass
saginaw

Early Woodland
Late Archaic

Hodges
Vogelair (Reported in
Peebles, 1978 as
Vogelaar)
Schmidt, Dustin 6-339,
Lutz 16, Schmidt Site B
Mahoney

20SA130
20SA133

Saginaw
Saginaw

saginaw
saginaw

Flint
Shiawassee

Late Archaic
Late Archaic

undetermined
summer
fishing camp
cremation
camp

20SA192

Saginaw

saginaw

Cass

Late Archaic

camp

20SA193

Saginaw

saginaw

Shiawassee

Late Archaic

undetermined

Mahoney

20SA193

Saginaw

saginaw

Shiawassee

Middle Woodland

seasonal camp

Bussinger

20SA194

Saginaw

saginaw

Shiawassee

Early Woodland

camp

Bussinger

20SA194

Saginaw

saginaw

Shiawassee

Late Archaic

Bussinger

20SA194

Saginaw

saginaw

Shiawassee

Middle Woodland

Stadelmeyer

20SA195

Saginaw

saginaw

Tittabawassee Late Archaic

camp/
cemetery
camp/
cemetery
village

Bad River

20SA197

Saginaw

saginaw

Shiawassee

Early Woodland

seasonal camp

Bad River

20SA197

Saginaw

saginaw

Shiawassee

Middle Woodland

seasonal camp

Hart

20SA198

Saginaw

saginaw

Shiawassee

Early Woodland

fishing camp

Bridgeport Enclosure
Feeheley

468

Table 34 (cont’d)
Site Name

County

Township

River Basin

Cultural Period

Function

Hart

State Site
File No.
20SA198

Saginaw

saginaw

Shiawassee

Late Archaic

fishing camp

Burk 73E

20SA1002

Saginaw

saginaw

Shiawassee

Late Archaic

camp

Silver Creek
Silver Creek
Malone
Simons

20SA1006
20SA1006
20SA1007
20SA1014

Saginaw
Saginaw
Saginaw
Saginaw

saginaw
saginaw
saginaw
saginaw

Flint
Flint
Flint
Shiawassee

Late Archaic
Middle Woodland
Late Archaic
Late Archaic

camp
camp
camp
undetermined

Hafner

20SA1022

Saginaw

saginaw

Shiawassee

Middle Woodland

camp

Kulhanek

20SA1023

Saginaw

saginaw

Shiawassee

Early Woodland

camp

Kulhanek

20SA1023

Saginaw

saginaw

Shiawassee

Late Archaic

camp

Wright

20SA1026
20SA1031

Saginaw
Saginaw

saginaw
saginaw

Flint
Shiawassee

Late Archaic
Late Archaic

undetermined
undetermined

20SA1032

Saginaw

saginaw

Tittabawassee Late Archaic

camp

Deer Creek, Shiawassee
River
Burk 51N

20SA1033

Saginaw

saginaw

Shiawassee

Early Woodland

seasonal camp

20SA1045

Saginaw

saginaw

Shiawassee

Early Woodland

camp

Burk 51N

20SA1045

Saginaw

saginaw

Shiawassee

Late Archaic

camp

469

Table 34 (cont’d)
Site Name

County

Township

River Basin

Cultural Period

Function

Burk 51N

State Site
File No.
20SA1045

Saginaw

saginaw

Shiawassee

Middle Woodland

camp

Burk 16C

20SA1046

Saginaw

saginaw

Shiawassee

Late Archaic

camp

Burk 16C

20SA1046

Saginaw

saginaw

Shiawassee

Middle Woodland

camp

McCullen

20SA1058

Saginaw

saginaw

Tittabawassee Early Woodland

undetermined

McCullen

20SA1058

Saginaw

saginaw

Tittabawassee Late Archaic

undetermined

McCullen

20SA1058

Saginaw

saginaw

Tittabawassee Middle Woodland

undetermined

Chipman Road

20SA1059

Saginaw

saginaw

Shiawassee

Late Archaic

findspot

Bear Creek

20SA1043

Saginaw

St. Charles

Shiawassee

Late Archaic

hunting camp

Bear Creek

20SA1043

Saginaw

St. Charles

Shiawassee

Middle Woodland

work station

Vogelaar/ Dustin 3-27;
may be same as 20SA90
and SA133
Vogelaar/ Dustin 3-27;
may be same as 20SA90
and SA133
Vogelaar/ Dustin 3-27;
may be same as 20SA90
and SA133

20SA291

Saginaw

St. Charles

Shiawassee

Early Woodland

camp

20SA291

Saginaw

St. Charles

Shiawassee

Late Archaic

hunting camp

20SA291

Saginaw

St. Charles

Shiawassee

Middle Woodland

camp

470

Table 34 (cont’d)
Site Name

County

Township

River Basin

Kretz

State Site
File No.
20SA380

Saginaw

Swan Creek

Tittabawassee Late Archaic

undetermined

Kretz

20SA380

Saginaw

Swan Creek

Tittabawassee Middle Woodland

undetermined

Yokones

20SA388

Saginaw

James

Shiawassee

Late Archaic

camp

Yokones

20SA388

Saginaw

James

Shiawassee

Middle Woodland

camp

Shiawassee #7

20SA1252

Saginaw

Spaulding

Shiawassee

Middle Woodland

undetermined

Shiawassee #3

20SA1254

Saginaw

James

Shiawassee

Late Archaic

undetermined

Shiawassee #3

20SA1254

Saginaw

James

Shiawassee

Middle Woodland

undetermined

Shiawassee #4

20SA1255

Saginaw

James

Shiawassee

Late Archaic

undetermined

Shiawassee #4

20SA1255

Saginaw

James

Shiawassee

Middle Woodland

undetermined

Shiawassee 2

20SA1251

Saginaw

James

Shiawassee

Middle Woodland

camp

Peacock II/ Shiawassee
#6
Peacock II/ Shiawassee
#6
Shiawassee #13

20SA214

Saginaw

James

Shiawassee

Early Woodland

camp

20SA214

Saginaw

James

Shiawassee

Middle Woodland

camp

20SA1276

Saginaw

James

Shiawassee

Middle Woodland

camp

471

Cultural Period

Function

Table 34 (cont’d)
Site Name
Casassa/ includes
20SA587
Casassa/ includes
20SA587
Casassa/ includes
20SA587
Birch Run Road/ Simons
61
Schultz/ Green Point
Mounds, Dustin 2-2,
Stage Register #460
Schultz/ Green Point
Mounds, Dustin 2-2,
Stage Register #460
Schultz/ Green Point
Mounds, Dustin 2-2,
Stage Register #460
Satchell/ Dustin 6-4,
20SA687
Satchell/ Dustin 6-4,
20SA687
Satchell/ Dustin 6-4,
20SA687
Herbers
Herbers

State Site
File No.
20SA1021

County

Township

River Basin

Cultural Period

Function

Saginaw

St. Charles

Shiawassee

Early Woodland

camp

20SA1021

Saginaw

St. Charles

Shiawassee

Late Archaic

findspot

20SA1021

Saginaw

St. Charles

Shiawassee

Middle Woodland

camp

20SA393

Saginaw

Taymouth

Flint

Late Archaic

camp

20SA2

Saginaw

Saginaw

Saginaw

Early Woodland

seasonal camp

20SA2

Saginaw

Saginaw

Saginaw

Late Archaic

camp

20SA2

Saginaw

Saginaw

Saginaw

Middle Woodland

seasonal camp

20SA33

Saginaw

Frankenmuth

Cass

Early Woodland

village

20SA33

Saginaw

Frankenmuth

Cass

Late Archaic

village

20SA33

Saginaw

Frankenmuth

Cass

Middle Woodland

village

20SA318

Saginaw

Brant

Shiawassee

Late Archaic

winter camp

20SA318

Saginaw

Brant

Shiawassee

Early Woodland

camp

472

Table 34 (cont’d)
Site Name

County

Township

River Basin

Benkert

State Site
File No.
20SA1267

Saginaw

Swan Creek

Tittabawassee Early Woodland

undetermined

Benkert

20SA1267

Saginaw

Swan Creek

Tittabawassee Late Archaic

undetermined

Snyder

20SA1268

Saginaw

James

Tittabawassee Late Archaic

camp

Snyder

20SA1268

Saginaw

James

Tittabawassee Early Woodland

camp

Owen/ Dustin 2-101

20SA1320
20SA20

Saginaw
Saginaw

Zilwaukee
Thomas

Saginaw
Middle Woodland
Tittabawassee Early Woodland

camp
camp

Branch Flats 2/ Dustin 2102
Valley Sweets/ Dustin 11, A.W. Wright, Schemm
Brewery
Fisher/ Dustin 6-0
Fisher/ Dustin 6-0
Young/ Youngs Drive,
Lutz 8
Kralosky
Kralosky
Hare

20SA21

Saginaw

Thomas

Tittabawassee Middle Woodland

camp

20SA24

Saginaw

Saginaw

Saginaw

Middle Woodland

village

20SA29
20SA29
20SA209

Saginaw
Saginaw
Saginaw

Bridgeport
Bridgeport
Bridgeport

Cass
Cass
Cass

Late Archaic
Early Woodland
Late Archaic

village
village
undetermined

20SA211
20SA211
20SA244

Saginaw
Saginaw
Saginaw

Bridgeport
Bridgeport
Swan Creek

Flint
Flint
Shiawassee

Late Archaic
Early Woodland
Late Archaic

camp
camp
burial

Sass Hill/ Oscar Seidel,
Miller

20SA249

Saginaw

Saginaw

Tittabawassee Late Archaic

473

Cultural Period

Function

undetermined

Table 34 (cont’d)
Site Name

State Site
File No.
20SA287

County

Township

River Basin

Cultural Period

Function

Saginaw

St. Charles

Shiawassee

Late Archaic

camp

Vance/ Dustin 6-3
Vance/ Dustin 6-3
Mershon Cache
Lincoln Cache
Leo's Gulley South/ Burk
87; Shuster #9
Rohn/ Burk 85

20SA32
20SA32
20SA1066
20SA1067
20SA1072

Saginaw
Saginaw
Saginaw
Saginaw
Saginaw

Bridgeport
Bridgeport
Carrollton
James
Chesaning

Cass
Cass
Saginaw
Saginaw
Shiawassee

Late Archaic
Early Woodland
Late Archaic
Late Archaic
Early Woodland

village
village
cache
cache
findspot

20SA1075

Saginaw

Brant

Shiawassee

Late Archaic

camp

Bradford/ Burk 91

20SA1078

Saginaw

Brant

Shiawassee

Late Archaic

camp

Wallen West/ Burk 92

20SA1079

Saginaw

Chapin

Shiawassee

Middle Woodland

lithic scatter

Sweeney West/ Burk 77

20SA1081

Saginaw

Brant

Shiawassee

Late Archaic

camp

J. Wickie

20SA1121

Saginaw

Chapin

Shiawassee

Late Archaic

lithic scatter

Burk #38

20SA1131

Saginaw

Brant

Shiawassee

Late Archaic

findspot

20SA1143

Saginaw

Chapin

Shiawassee

Late Archaic

findspot

20SA1148

Saginaw

Chapin

Shiawassee

Middle Woodland

camp

20SA1191

Saginaw

Brady

Shiawassee

Middle Woodland

lithic scatter

Dustin 3-36

Haney #7

474

Table 34 (cont’d)
Site Name

State Site
File No.
20SA1196

County

Township

River Basin

Cultural Period

Function

Saginaw

Brant

Shiawassee

Early Woodland

camp

20SA1203

Saginaw

Brant

Shiawassee

Middle Woodland

camp

Haney #1

20SA1204

Saginaw

Brant

Shiawassee

Middle Woodland

camp

Haney #3

20SA1206

Saginaw

Brant

Shiawassee

Middle Woodland

camp

Haney #14

20SA1210

Saginaw

Brady

Shiawassee

Middle Woodland

camp

Haney #11B

20SA1212

Saginaw

Brady

Shiawassee

Middle Woodland

camp

Shuster #12

20SA1229

Saginaw

Albee

Shiawassee

Early Woodland

lithic scatter

Shuster #12

20SA1229

Saginaw

Albee

Shiawassee

Late Archaic

lithic scatter

Shuster #13

20SA1230

Saginaw

Albee

Shiawassee

Middle Woodland

undetermined

Shuster #15

20SA1231

Saginaw

Albee

Shiawassee

Late Archaic

camp

Sommer 6 and 16
Sommer 6 and 16
Sommer 6 and 16
Sommer 19
Sommer 19
Sommer 2, A
Sommer 2, B

20SA1236
20SA1236
20SA1236
20SA1242
20SA1242
20SA1243
20SA1244

Saginaw
Saginaw
Saginaw
Saginaw
Saginaw
Saginaw
Saginaw

Bridgeport
Bridgeport
Bridgeport
Bridgeport
Bridgeport
Bridgeport
Bridgeport

Cass
Cass
Cass
Cass
Cass
Cass
Cass

Late Archaic
Middle Woodland

camp
camp
camp
camp
camp
unknown
unknown

475

Late Archaic
Middle Woodland
Middle Woodland

Table 34 (cont’d)
Site Name

State Site
File No.
20SA1247
20SA1247
20SA37
20SA315

County

Township

River Basin

Cultural Period

Function

Saginaw
Saginaw
Saginaw
Saginaw

Bridgeport
Bridgeport
Frankenmuth
James

Cass
Cass
Cass
Shiawassee

Late Archaic

camp
camp
village
cache

20SA315

Saginaw

James

Shiawassee

20SA317

Saginaw

Swan Creek

Shiawassee

Early Woodland

undetermined

Morrison

20SA317

Saginaw

Swan Creek

Shiawassee

Late Archaic

undetermined

Morrison

20SA317

Saginaw

Swan Creek

Shiawassee

Middle Woodland

undetermined

Gamon/ Sgamon

20SA322

Saginaw

Brant

Shiawassee

Early Woodland

camp

Gamon/ Sgamon

20SA322

Saginaw

Brant

Shiawassee

Late Archaic

camp

Souden 1

20SA325

Saginaw

Brant

Shiawassee

Late Archaic

camp, summer

Souden 2

20SA326

Saginaw

Brant

Shiawassee

Late Archaic

camp

Jurstik 2

20SA337

Saginaw

Brant

Shiawassee

Late Archaic

kill station

Jurstik 2

20SA337

Saginaw

Brant

Shiawassee

Late Archaic

camp

Gosen

20SA341

Saginaw

Swan Creek

Shiawassee

Late Archaic

undetermined

Sommer 2
Sommer 2
Huron/ Dustin 6-10
Schemm Cache/ Dustin
3-42
Schemm Cache/ Dustin
3-42
Morrison

476

Early Woodland
Late Archaic

cache

Table 34 (cont’d)
Site Name

County

Township

River Basin

Cultural Period

Function

Frede

State Site
File No.
20SA342

Saginaw

James

Shiawassee

Late Archaic

undetermined

Donovan A

20SA344

Saginaw

St. Charles

Shiawassee

Early Woodland

undetermined

Donovan A

20SA344

Saginaw

St. Charles

Shiawassee

Late Archaic

undetermined

Donovan A

20SA344

Saginaw

St. Charles

Shiawassee

Middle Woodland

undetermined

Cai-16
Cai-22
Trogan/ Lutz 11
Spencer 6-23, Willie
Cache. Wille Cache
Spencer 6-23, Willie
Cache. Wille Cache

20SA351
20SA357
20SA359
20SA363

Saginaw
Saginaw
Saginaw
Saginaw

Bridgeport
Bridgeport
Spaulding
Spaulding

Cass
Cass
Cass
Cass

Late Archaic
Early Woodland
Late Archaic
Late Archaic

camp
undetermined
undetermined
camp

20SA363

Saginaw

Spaulding

Cass

Middle Woodland

undetermined

20SA365
20SA365
20SA368

Saginaw
Saginaw
Saginaw

Bridgeport
Bridgeport
Albee

Cass
Cass
Flint

Early Woodland
Middle Woodland
Middle Woodland

undetermined
undetermined
camp

20SA371

Saginaw

Albee

Flint

Late Archaic

camp

20SA371

Saginaw

Albee

Flint

Late Archaic

camp

20SA371

Saginaw

Albee

Flint

20SA375
20SA379

Saginaw
Saginaw

Taymouth
Swan Creek

Flint
Flint

Marzluft 1/ SIMONS
136, see also 20SA369
Malone 2/ SPENCER 7101, SIMONS 28
Malone 2/ SPENCER 7101, SIMONS 28
Malone 2/ SPENCER 7101, SIMONS 28
Durward 1
CAI-5

477

camp
Late Archaic
Late Archaic

camp
undetermined

Table 34 (cont’d)
Site Name

County

Township

River Basin

Cady

State Site
File No.
20SA382

Saginaw

Saginaw

Tittabawassee Late Archaic

camp

Weigl

20SA389

Saginaw

James

Shiawassee

undetermined

Weigl

20SA389

Saginaw

James

Shiawassee

Daby-abbot/ DUBAYABBOTT
Daby-abbot/ DUBAYABBOTT
Daby-abbot/ DUBAYABBOTT
Bates/ KLINKER HILL,
LUTZ 21
Dorr
Fisher 2
Weston #94
Telfers

20SA396

Saginaw

Taymouth

Flint

Early Woodland

camp

20SA396

Saginaw

Taymouth

Flint

Late Archaic

camp

20SA396

Saginaw

Taymouth

Flint

Middle Woodland

camp

20SA398

Saginaw

Bridgeport

Cass

Late Archaic

camp

20SA399
20SA703
20SL38
20SE91

Saginaw
Saginaw
Sanilac
Shiawassee

Bridgeport
Bridgeport
Austin
Owosso

Cass
Cass
Cass
Shiawassee

Late Archaic
Early Woodland
Late Archaic
Early Woodland

undetermined
camp
undetermined
undetermined

Telfers

20SE91

Shiawassee

Owosso

Shiawassee

Late Archaic

undetermined

Jahr

20TU6

Tuscola

Wisner

Lake Huron

Late Archaic

undetermined

Jahr

20TU6

Tuscola

Wisner

Lake Huron

Early Woodland

camp

Jahr

20TU6

Tuscola

Wisner

Lake Huron

Middle Woodland

cemetery

478

Cultural Period

Late Archaic

Function

undetermined

Table 34 (cont’d)
Site Name

County

Township

River Basin

Cultural Period

Function

Levaliey
Lajoie & Sons
Salgat 2
Gurnith Faidie

State Site
File No.
20TU61
20TU65
20TU66
20TU68

Tuscola
Tuscola
Tuscola
Tuscola

Indianfields
Ellington
Ellington
Aimer

Cass
Cass
Cass
Lake Huron

Late Archaic
Early Woodland
Middle Woodland
Late Archaic

undetermined
camp
undetermined
winter camp

Alkens
Lookwood
Ellison 1
Fish Point

20TU74
20TU85
20TU86
20TU87

Tuscola
Tuscola
Tuscola
Tuscola

Ellington
Ellington
Ellington
Wisner

Cass
Cass
Cass
Lake Huron

Late Archaic
Middle Woodland
Early Woodland
Late Archaic

undetermined
undetermined
camp
cemetery

Stoick
Atkins
Schafsnitz 2
Pinkerton Road
Dinsmore

20TU91
20TU94
20TU104
20TU111
20TU121
20TU130

Tuscola
Tuscola
Tuscola
Tuscola
Tuscola
Tuscola

Kingston
Indianfields
Tuscola
Juniata
Tuscola
Gilford

Cass
Cass
Cass
Cass
Cass
Lake Huron

Late Archaic
Late Archaic
Early Woodland
Early Woodland
Late Archaic
Late Archaic

camp
camp
cemetery
undetermined
camp
camp

20TU146
20TU147
20TU149
20TU149
20TU150

Tuscola
Tuscola
Tuscola
Tuscola
Tuscola

Indianfields
Arbela
Tuscola
Tuscola
Elmwood

Cass
Cass
Cass
Cass
Cass

Middle Woodland
Late Archaic
Late Archaic
Middle Woodland
Late Archaic

camp
cemetery
camp
camp
undetermined

Hancock 1

Bearss

479

Table 35. Site type ratios by county and cultural period
Function

Culture

Activity Area

Late Archaic

Activity Area

Total

Arenac

Bay

Clinton

Genesee

Gladwin

Gratiot

118

0%

2%

3%

2%

0%

1%

Early Woodland

55

0%

1%

1%

1%

0%

1%

Activity Area

Middle Woodland

74

0%

3%

2%

3%

0%

2%

Cache

Late Archaic

6

0%

0%

0%

0%

0%

0%

Cache

Middle Woodland

2

0%

0%

0%

0%

0%

0%

Camp

Late Archaic

217

1%

4%

2%

1%

0%

3%

Camp

Early Woodland

76

0%

4%

1%

0%

0%

2%

Camp

Middle Woodland

110

1%

4%

2%

0%

0%

1%

Cemetery

Late Archaic

15

0%

1%

0%

1%

0%

0%

Cemetery

Early Woodland

3

0%

0%

0%

0%

0%

0%

Cemetery

Middle Woodland

5

0%

0%

1%

0%

0%

0%

Village

Late Archaic

11

0%

1%

0%

0%

0%

0%

Village

Early Woodland

9

0%

1%

0%

0%

0%

0%

Village

Middle Woodland

8

0%

1%

0%

0%

0%

0%

480

Table 35. (cont’d)
Function
Activity
Area
Activity
Area
Activity
Area
Cache
Cache
Camp
Camp
Camp
Cemetery
Cemetery
Cemetery
Village
Village
Village

Culture
Late
Archaic
Early
Woodland
Middle
Woodland
Late
Archaic
Middle
Woodland
Late
Archaic
Early
Woodland
Middle
Woodland
Late
Archaic
Early
Woodland
Middle
Woodland
Late
Archaic
Early
Woodland
Middle
Woodland

Huron Iosco Isabella Lapeer Mecosta Midland Montcalm Oakland Osceola
Oscoda
0%
1%
0%
2%
0%
3%
0%
0%
0%
1%
1%

0%

0%

1%

0%

12%

0%

1%

0%

1%

0%

1%

0%

3%

0%

9%

0%

1%

0%

1%

0%

0%

0%

0%

0%

0%

0%

0%

0%

0%

0%

0%

0%

0%

0%

0%

0%

0%

0%

0%

1%

1%

0%

5%

0%

5%

0%

0%

1%

0%

1%

0%

0%

1%

1%

4%

0%

0%

0%

0%

0%

4%

0%

2%

1%

3%

0%

0%

0%

0%

0%

0%

0%

0%

0%

1%

0%

0%

0%

0%

0%

0%

0%

0%

0%

0%

0%

0%

0%

0%

0%

0%

0%

0%

0%

1%

0%

0%

0%

0%

0%

0%

0%

0%

0%

0%

0%

0%

0%

0%

0%

0%

0%

0%

0%

0%

0%

0%

0%

0%

1%

1%

0%

0%

0%

0%

0%

0%

0%

0%

481

Table 35. (cont’d)
Function
Activity Area
Activity Area
Activity Area
Cache
Cache
Camp
Camp
Camp
Cemetery
Cemetery
Cemetery
Village
Village
Village

Culture
Late Archaic
Early Woodland
Middle Woodland
Late Archaic
Middle Woodland
Late Archaic
Early Woodland
Middle Woodland
Late Archaic
Early Woodland
Middle Woodland
Late Archaic
Early Woodland
Middle Woodland

Roscommon
Saginaw
Sanilac
Shiawassee
Tuscola
0%
12%
0%
0%
0%
16%
0%
1%
0%
13%
0%
0%
0%
1%
0%
0%
0%
1%
0%
0%
0%
35%
0%
0%
0%
36%
0%
0%
1%
38%
0%
0%
0%
2%
0%
0%
0%
1%
0%
0%
0%
1%
0%
0%
0%
2%
0%
0%
0%
6%
0%
0%
0%
3%
0%
0%

482

1%
1%
1%
0%
0%
2%
2%
1%
1%
1%
1%
0%
0%
0%

Table 36. Site type percentage by river basin
Cultural Period
Function
Late Archaic
Activity Area
Early Woodland
Activity Area
Middle Woodland
Activity Area
Late Archaic
cache
Middle Woodland
cache
Late Archaic
camp
Early Woodland
camp
Middle Woodland
camp
Late Archaic
cemetery
Early Woodland
cemetery
Middle Woodland
cemetery
Late Archaic
village
Early Woodland
village
Middle Woodland
village

Total Au Sable Cass Flint Grand
Lake Huron
118
2%
5%
5%
3%
2%
55
1%
5%
1%
1%
2%
74
2%
7% 10%
3%
4%
6
0%
0%
0%
0%
0%
2
0%
1%
0%
0%
0%
217
1%
8% 13%
2%
3%
76
0%
3%
3%
1%
3%
110
5% 11%
8%
2%
6%
15
0%
0%
1%
0%
1%
3
0%
1%
0%
0%
0%
5
0%
0%
0%
1%
1%
11
0%
1%
1%
0%
0%
9
0%
3%
1%
0%
0%
8
1%
2%
0%
0%
1%

483

Table 36. (cont’d)
Cultural
Function
Period
Late Archaic Activity
Area
Early
Activity
Woodland
Area
Middle
Activity
Woodland
Area
Late Archaic cache
Middle
cache
Woodland
Late Archaic camp
Early
camp
Woodland
Middle
camp
Woodland
Late Archaic cemetery
Early
cemetery
Woodland
Middle
cemetery
Woodland
Late Archaic village
Early
village
Woodland
Middle
village
Woodland

Muskegon
0%

Saginaw
200%

Saginaw

Sebewaing

Shiawassee

Tittabawassee

0%

8%

5%

0%

0%

1%

0%

13%

15%

0%

100%

1%

0%

14%

18%

0%
0%

200%

1%
0%

0%
0%

0%
1%

1%
0%

1%
1%

900%
500%

2%
3%

1%
0%

21%
31%

8%
7%

1%

500%

4%

0%

40%

11%

0%
0%

200%
100%

1%
1%

0%
0%

1%
1%

1%
0%

0%

100%

1%

0%

1%

1%

0%
0%

100%
100%

0%
1%

0%
0%

0%
0%

1%
1%

0%

200%

2%

0%

0%

2%

484

Relative Dates
Table 37. Relative dates
State Site
File No.

Site Name

Sample

20SA192

Schmidt

N-1781

4660

740 LA

20BY30
20SA128
20BY387

Kantzler
Feeheley
Marquette Viaduct South

UGA-3195
M-1139
Beta-181524

4290
3930
3840

75 LA
150 LA
40 LA

20BY28

Fletcher/Marquette
Viaduct/Defoe Park
Andrews
Vogelaar

Beta-154674

3670

70 LA

M-914
Beta-78825

3550
3410

150 LA
100 LA

Andrews
Brandt
Weber 1
Third Street Bridge or Liberty
Bridge
Naugle
Conservation Park

M-659
DIC-2501
Beta-5473
Beta-11130

3170
3090
2990
2880

150
45
110
70

CWRU-169
Beta-9646

2850
2530

110 LA
60 LA

Beta56425/CAMS3836
M-1524
M-1525

2510

80 LA

2490
2480

130 EW
150 EW

20SA8
20SA133
20SA8
20IS46
29SA581
20BY79
20MD30
20GR33

20SA1043 Bear Creek

20SA2-2
20SA2

Schultz
Schultz

Relative Range
Date

485

Cultural Period

LA
LA
LA
LA

Citation
Egan 1993, Robertson
1987
Larsen and Demeter 1979
Crane and Griffin 1962
Lovis et al. 2002, Bev
Smith
Lovis et al. 2002, Bev
Smith
Branstner and
Hambacher 1995
Crane and Griffin 1960
Mead and Kingsley 1994
Monaghan et al 1986
Monaghan 1993
Ozker 1976

Speth 1972; Egan 1993
Ozker 1982

Table 37. (cont’d)
State Site
File No.

Site Name

Sample

20SA1
20BY28

Green Point
Fletcher/Marquette
Viaduct/Defoe Park
Fletcher/Marquette
Viaduct/Defoe Park
Conservation Park
20IA305
Butterfield/ Schmidt 51/Paul Wendeloski
Young
Hart
Kretz
Kantzler
Third Street Bridge
Schultz
Kanitz
Surath's Junk Yard
Schultz
Kantzler
Kantzler
Schultz

M-1432
Beta-17752

2480
1830

120 EW
85 MW

Beta 26380

1740

63 MW

20BY28
20GR33
20IA305
20BY29
20SA209
20SA198
20SA380
20BY30
20BY79
20SA2-3
20GR13
20BY77
20SA2-3
20BY31
20BY32
20SA2-4

Relative Range
Date

787

Cultural Period

Beta-171300
No Dates

EW
LA
LA

No Dates
No Dates
No Dates
No Dates
No Dates
Beta-261463
No Dates
No Dates
No Dates
No Dates
No Dates
No Dates

LA
LA
LA
EW
MW
MW
MW
MW
MW -E
MW -E
MW -H
MW -L

486

Citation
H.T. Wright 1964

Stuiver and Becker 1986
Beld 1991:71
Branstner 2004

Keene
Keene

Egan 1993

Egan 1994

Site Flora and Fauna
Table 38. Archaeological fauna and flora by site
Common Name

Moose
Deer/Elk
Elk
Elk
White tailed
deer
White tailed
deer
Bear
Black bear

Species
Site Name

Kretz
20SA380

Hart
20SA198

20SA2
Schultz

20SA209
Young

20SA192
Schmidt

20SA128
Feeheley

Cultural Period
Measurement
Dates - 14CYBP
Alces alces
Cervidae sp.
Cervus canadensis
Cervus elaphus
Odocoileus virginianus

LA

LA

LA
MNI

LA
MNI

LA
MNI

LA
MNI
4660

3930

1
1
x

8

Odocoileus virginianus
cf.
Ursus americanus
Euarctos americanus

2

1
0

Shrew
Domestic dog
Dog/Wolf/Coyo
te
Wolf
Red fox
Beaver
Beaver
Ground squirrel
Porcupine

20BY29
Butterfield/
Schmidt
LA
MNI

0

Blarina brevicauda
Canis cf. familiaris
Canis sp.

11

1

Canis lupus
Vulpes fulva
Castor canadensis
Castor canadensis cf.
Citellus spilosoma
Erethizon dorsatum

4

1
487

0

2

0

0

Table 38. (cont’d)
Common Name

Jack rabbit
Bobcat
Marten
Meadow vole
Mice, rat,
gerbils
Mink
Muskrat
Muskrat
Otter
Deer Mice
Raccoon
Rodents - mice,
rats, squirrels,
porcupines,
beavers,
chipmunks,
voles
Chipmunk
Squirrel
Rabbit

Species
Site Name

Kretz
20SA380

Hart
20SA198

20SA2
Schultz

20SA209
Young

20SA192
Schmidt

20SA128
Feeheley

Cultural Period
Measurement
Dates - 14CYBP
Lepus californicus
Lynx canadensis
Martes americana
Microtus sp.
Muridae sp.

LA

LA

LA
MNI

LA
MNI

LA
MNI

LA
MNI

Mustela vison
Ondatra zibethicus
Ondatra zibethicus cf.
Lontra canadensis
Peromyscus sp.
Procyon lotor
Rodentia sp.

4660

3930

1
1

18

2 present

x
4

Tamias sp.
Sciurus sp.
Sylvilagus floridanus

3

present
1
1
488

1

20BY29
Butterfield/
Schmidt
LA
MNI

Table 38. (cont’d)
Common Name

Misc.
Totals
Lake Sturgeon
Bowfin
Freshwater
drum
Sucker
Longnose
sucker
White sucker
Sucker
sucker
Sunfish
Northern pike
Pike
Cod
Channel catfish
Black bullhead
Yellow bullhead
Brown bullhead
Channel catfish

Species
Site Name

Kretz
20SA380

Hart
20SA198

20SA2
Schultz

20SA209
Young

20SA192
Schmidt

20SA128
Feeheley

Cultural Period
Measurement
Dates - 14CYBP
Carnivora sp.
Totals
Acipenser fulvescens
Amia Calva
Aplodinotus grunniens

LA

LA

LA
MNI

LA
MNI

LA
MNI

20BY29
Butterfield/
Schmidt
LA
MNI

LA
MNI
4660

0
x

0

30

2
2

3930

6
7

0

x
1 present

Castomidae sp.
Catostomus
catostomus
Catostomus
commersoni
Catostomus sp.
Catostomidae
Moxostoma
Centrarchidae sp.
Esocidae sp.
Esox sp.
Lota lota lacustris
Ictaluridae sp.
Ictalurus melas
Ictalurus natalis
Ictalurus nebulosus
Ictalurus punctatus

present
489

0

Table 38. (cont’d)
Common Name

Channel catfish
Channel catfish
Catfish
Gar
Longnosed gar
Bluegill sunfish
Sunfish
Cod
Smallmouth
bass
Largemouth
bass
Bass
Striped bass
rock bass
Shorthead
Redhorse
Shorthead
Redhorse
Bony fish
Yellow perch

Species
Site Name

Kretz
20SA380

Hart
20SA198

20SA2
Schultz

20SA209
Young

20SA192
Schmidt

20SA128
Feeheley

Cultural Period
Measurement
Dates - 14CYBP
Ictalurus punctatus
Ictalurus punctatus cf.
Ictalurus sp.
Lepisosteus sp.
Lepisosteus osseus
oxyurus
Lepomis cf.
macrochirus
Lepomis/Pomoxis sp.
Lota lota lacustris
Micropterus dolomieui

LA

LA

LA
MNI

LA
MNI

LA
MNI

LA
MNI
4660

x

x

x

3930

x
1

x

Micropterus salmoides
Micropterus sp.
Monroe chrysops
Morone chrysops
Moxostoma
macrolepidotum
Moxostoma sp.

1

Osteichthyes sp.
Perca flavescens

present
490

20BY29
Butterfield/
Schmidt
LA
MNI

Table 38. (cont’d)
Common Name

Perch
Walleye/Sauger
/Perch
Perch
Crappie
Crappie
Crappie
Flathead
Trout
Lake trout
Drum
Walleye
Totals
Green turtle

Painted turtle
Snake
Hidden-necked
turtles

Species
Site Name

Kretz
20SA380

Hart
20SA198

20SA2
Schultz

20SA209
Young

20SA192
Schmidt

20SA128
Feeheley

Cultural Period
Measurement
Dates - 14CYBP
Percichthyidae sp.
Percidae

LA

LA

LA
MNI

LA
MNI

LA
MNI

LA
MNI

Percidae sp.
Pomoxis
nigromaculatus
Pomoxis sp.
Pomoxis/Lepomis sp.
Pylodictis
Salmonidae sp.
Salvelinus namaycush
Sciaenidae sp.
Stizostedion sp.
Totals
Anura sp.
Chelonia sp.
Chelydra serpentina
Chelydra serpentina cf.
Chrysemys picta
Colubridae sp.
Cryptodira sp.
Cryptodira

x

20BY29
Butterfield/
Schmidt
LA
MNI

4660

3930

2

0

x

x

0

0

491

0

0

0

Table 38. (cont’d)
Common Name

Pond turtles
Blandings turtle
Blandings turtle
Sliders/Cooters
Northern water
snake
Box turtles
Garter snake
Soft shell turtle

Species
Site Name

Kretz
20SA380

Hart
20SA198

20SA2
Schultz

20SA209
Young

20SA192
Schmidt

20SA128
Feeheley

Cultural Period
Measurement
Dates - 14CYBP
Emydidae sp.
Emydoidea blandingii
Emydoidea blandingii
cf.
Emydoidea Chrysemys
sp.
Nerodia sipedon

LA

LA

LA
MNI

LA
MNI

LA
MNI

LA
MNI

Terrapene sp.
Thamnophis sp.
Trionyx sp.

x

4660

Mallard Duck
Blue winged
teal
American
Wigeon
Ring necked
duck
redhead

3930

0

0

x

x
0

Great Northern
Loon

0

0

0

Gavia immer
Anas sp.
Anas platyrhynchos
Anas discors

20BY29
Butterfield/
Schmidt
LA
MNI

x

4

Anas americana
Aythya collaris
Aythya americana
492

0

Table 38. (cont’d)
Common Name

Species
Site Name

Cultural Period
Measurement
Dates - 14CYBP
Lesser Scaup
Aythya affinis
Small eyed duck Anatidae sp.
Greater Scaup
Aythya marila
Great horned
Bubo virginianus
owl
Strigiformes
Sandhill crane
Crus canadensis
Passenger
Ectopistes migratorius
pigeon
Bald eagle
Haliaeetus
leucocephalus
Common
Mergus merganser
merganser
Anseriformes
Red breasted
Mergus serrator
merganser
White-winged
Melanitta deglandi
scoter
Totals
Totals
Amaranthus sp.
Serviceberry
Amelanchier
Hog peanut
Amphicarpa bracteata
Aster
Aster cf. cordifolius
Mustard family Brassicaceae
Hackberry
Celtis occidentalis

Kretz
20SA380

Hart
20SA198

20SA2
Schultz

20SA209
Young

20SA192
Schmidt

20SA128
Feeheley

LA

LA

LA
MNI

LA
MNI

LA
MNI

LA
MNI
4660

20BY29
Butterfield/
Schmidt
LA
MNI

3930

1

13

0
117

0
14

0

1

present
493

17

0

0

Table 38. (cont’d)
Common Name

Goosefoot
Morning-glory
family
Round-leaved
dogwood
Hawthorn
Squash/Rind
Sedges
Sedges
Bedstraw
Elderberry,
Huckleberry
St. John's wort
Sumpweed
Mint family
rose family
Corn
Grass
Nightshade
Virginia creeper

Species
Site Name

Kretz
20SA380

Hart
20SA198

20SA2
Schultz

20SA209
Young

20SA192
Schmidt

20SA128
Feeheley

Cultural Period
Measurement
Dates - 14CYBP
Chenopodium spp.
Convolvulaceae

LA

LA

LA
MNI

LA
MNI

LA
MNI

LA
MNI
4660

198

75

69
3

4
1

Cornus rugosa
Crataegus sp.
Cucurbita sp.
Cyperus spp.
Cyperaceae
Galium spp.
Gaylussacia baccata
Graminea
Hypericum sp.
Iva annua
Labiateae
Rosaceae
Zea mays

1

1

Panicum
Physalis
Parthenocissus
quinquefolia
494

3930

20BY29
Butterfield/
Schmidt
LA
MNI

Table 38. (cont’d)
Common Name

Grass family
Grass family
Knotweed
Knotweed
Buckwheat
Plums, cherries,
peaches,
apricots,
almonds
Pear
Blackberry
Raspberries,
blackberries,
dewberries
Huckleberry,
American
Elderberry
Sassafras
Cattail
Nannyberry

Species
Site Name

Kretz
20SA380

Hart
20SA198

20SA2
Schultz

20SA209
Young

20SA192
Schmidt

20SA128
Feeheley

Cultural Period
Measurement
Dates - 14CYBP
Poaceae(large)
Poaceae(small)
Polygonum
Polygonum
Polygonum
pensylvanicum
Prunus spp.

LA

LA

LA
MNI

LA
MNI

LA
MNI

LA
MNI

Pyrus sp.
Rubus sp.
Rubus spp.

4660

28

1

64

25

Sambucus canadensis

Sassafras albidum
Silene sp.
Typha sp.
Vaccinium sp.
Viburnum sp.

1
1
61

495

3930

20BY29
Butterfield/
Schmidt
LA
MNI

Table 38. (cont’d)
Common Name

Grape
Maize kernel
Wild rice
Poppy
Maple
Aster
Birch
Hazelnut
Hickory
Hickory shell
Hickory
Shagbark
hickory
Chestnut
Hackberry
Redbud
Beech
Ash
White ash
Ash

Species
Site Name

Kretz
20SA380

Hart
20SA198

20SA2
Schultz

20SA209
Young

20SA192
Schmidt

20SA128
Feeheley

Cultural Period
Measurement
Dates - 14CYBP
Viola
Vitis
Zea mays
Zizania aquatica

LA

LA

LA
MNI

LA
MNI

LA
MNI

LA
MNI

Acer spp.
Aster cr. Cordifolius
Betula spp.
Corylus americana
Carya spp.
Carya spp.
Carya laciniosa
Carya ovata
Castanea dentata
Celtis occidentalis
Cercis canadensis
Fagus grandifolia
Fraxinus spp.
Fraxinus alba
Fraxinus americana

4660

20BY29
Butterfield/
Schmidt
LA
MNI

3930

1

3

13 present

2
1

1

12

10
2

8

2
1

3+5

4

3
6

3
6
9

18
6

11
4
3

496

1
1
1

Table 38. (cont’d)
Common Name

Black ash
Ash
Butternut
Eastern Black
Walnut
Walnut family
Sassafras
Mulberry
Hophornbeam
Spruce
Pine
Red pine
White pine
Sycamore
Aspen

Swamp white
oak
Acorn
Oak

Species
Site Name

Kretz
20SA380

Hart
20SA198

20SA2
Schultz

20SA209
Young

20SA192
Schmidt

20SA128
Feeheley

Cultural Period
Measurement
Dates - 14CYBP
Fraxinus nigra
Juglandaceae/Walnut
family
Juglans cinerea
Juglans nigra

LA

LA

LA
MNI

LA
MNI

LA
MNI

LA
MNI

Juglans spp.
Lauraceae
Morus rubra
Nyssa
Ostraya virginiana
Picea sp.
Pinus spp.
P. resinosa
Pinus strobus
Platanus occidentalis
Populus tremuloides
Populus silex
Prunus sp.
Quercus bicolor
Quercus sp.
Quercus Cotyledon

20BY29
Butterfield/
Schmidt
LA
MNI

4660
6

3

1

13

1
1

22
2

14

3
4

3930
5
16

13
11

2

7

8

4
1

1

8

141

8
present

1
10

2
13

15
8
2

1
1
present
15

18
497

2 present

6
1
12

Table 38. (cont’d)
Common Name

Acorn shell
White oak
Black oak
Red oak
Sumac
Basswood
Elm
Elm
American elm
Slippery elm
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs

Snails and slugs
Snails and slugs

Species
Site Name

Kretz
20SA380

Cultural Period
LA
Measurement
Dates - 14CYBP
Quercus sp.
Quercus alba
Quercus nigra
Quercus rubra
Rhus
Tilia americana
Ulmaceae/ Elm family
Ulmus spp.
Ulmus cf. Americana
Ulmus rubra
Actinonaias carinata
(Barnes)
Amblema costata (Raf.)
Amnicola Limosa (Say)
Amnicola lustrica
(Pilsbry)
Anguispira alternata
Anodonta grandis
footiana (Say)
Goodrich
Anguispira kochi
(Baker)
Anguispira solitaria

Hart
20SA198

20SA2
Schultz

20SA209
Young

20SA192
Schmidt

20SA128
Feeheley

LA

LA
MNI

LA
MNI

LA
MNI

LA
MNI
4660

29

39

11

20BY29
Butterfield/
Schmidt
LA
MNI

3930
13
14

17

8
6

1
3

2

2
1
1
2
1634
present
present
present

16

5
present
498

Table 38. (cont’d)
Common Name

Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs

Species
Site Name

Kretz
20SA380

Cultural Period
LA
Measurement
Dates - 14CYBP
(Say)
Campeloma decisum
(Say)
Cyclonaias tuberculata
Discus cronkfilter
anthonyi (Pilsbry)
Elliptio dilatatus (Raf.)
Fusconaia flava (Raf.)
Gastrapoda sp.
Goniobasis livescens
(Say)
Helicodiscus parallelus
(Say)
Helisoma anceps
(Conrad)
Helisoma
Campanulatum
Helisoma trivolvis (Say)
Haplotrema concavium
(Say)
Lampsilis siliquoidea (L)
Lasmigona costata
(Raf.)

Hart
20SA198

20SA2
Schultz

20SA209
Young

20SA192
Schmidt

20SA128
Feeheley

LA

LA
MNI

LA
MNI

LA
MNI

LA
MNI
4660

present
12
present
798
424
present
present
present
present
present
present
89
43

499

7

3930

20BY29
Butterfield/
Schmidt
LA
MNI

Table 38. (cont’d)
Common Name

Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs

Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs

Species
Site Name

Kretz
20SA380

Hart
20SA198

20SA2
Schultz

20SA209
Young

20SA192
Schmidt

20SA128
Feeheley

Cultural Period
Measurement
Dates - 14CYBP
Ligumia (Recta)
lattissima (Raf.)
Lymnaea (Stagnicola)
palustris (Say)
Lymnaea columella
(Say)
Mesodon thyroidus
(Say)
Mesomphix cuprea
(Say)
Obovaria subrotunda
(Raf.)
Pleurobema
(cordatum) coccineum
(Conrad)
Pomatiopsis lapidaria
(Say)
Quadrula pustulosa
(Lea)
Retinella rhoadsi
(Pilsbry)
Somatogyrus sp.
Sphaerium

LA

LA

LA
MNI

LA
MNI

LA
MNI

LA
MNI
4660

14
present
present
present
present
2
22

present
93
present
present
85
500

3930

20BY29
Butterfield/
Schmidt
LA
MNI

Table 38. (cont’d)
Common Name

Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs

Species
Site Name

Kretz
20SA380

Hart
20SA198

20SA2
Schultz

20SA209
Young

20SA192
Schmidt

20SA128
Feeheley

Cultural Period
Measurement
Dates - 14CYBP
rhombodium
Sphaerium striatum
Sphaerium sulcatum
Stenotrema monodon
(Rackett)
Strophitus rugosis
(Swain.)
Succinea ovalis (Say)
Triodopsis albolabris
(Say)
Triodopsis multilineata
(Say)
Valvata tricarinata
(Say)
Zonitidae sp.
Pelecypoda sp.

LA

LA

LA
MNI

LA
MNI

LA
MNI

LA
MNI
4660

40
21
present
23
present
present
present
present
1

501

3930

20BY29
Butterfield/
Schmidt
LA
MNI

Table 38. (cont’d)
Common Name

Moose
Deer/Elk
Elk
Elk
White tailed deer
White tailed deer
Bear
Black bear

Species
Site Name

Cultural Period
Measurement
C14 Dates - YBP
Alces alces
Cervidae sp.
Cervus canadensis
Cervus elaphus
Odocoileus virginianus
Odocoileus virginianus cf.
Ursus americanus
Euarctos americanus

20SA581 20BY79
Weber I Third
Street
Bridge
LA
LA
MNI
MNI
2990
2880
present
present
present

0
Shrew
Domestic dog
Dog/Wolf/Coyote
Wolf
Red fox
Beaver
Beaver
Ground squirrel
Porcupine
Jack rabbit
Bobcat
Marten

Blarina brevicauda
Canis cf. familiaris
Canis sp.
Canis lupus
Vulpes fulva
Castor canadensis
Castor canadensis cf.
Citellus spilosoma
Erethizon dorsatum
Lepus californicus
Lynx canadensis
Martes americana

20SA2 20BY30
Schultz Kantzler

20BY30
Kantzler

20SA2
Schultz

EW
EW
MNI
MNI
2490

MW Early
MNI

MW Early
MNI
2480

6

2

33
1
2

3

2

42

3

1
4
1
3

6

1
7
1
1
1
2
2
1

502

0

Table 38. (cont’d)
Common Name

Meadow vole
Mice, rat, gerbils
Mink
Muskrat
Muskrat
Otter
Deer Mice
Raccoon
Rodents - mice, rats,
squirrels, porcupines,
beavers, chipmunks,
voles
Chipmunk
Squirrel
Rabbit
Misc.
Totals
Lake Sturgeon
Bowfin
Freshwater drum
Sucker
Longnose sucker

Species
Site Name

Cultural Period
Measurement
C14 Dates - YBP
Microtus sp.
Muridae sp.
Mustela vison
Ondatra zibethicus
Ondatra zibethicus cf.
Lontra canadensis
Peromyscus sp.
Procyon lotor
Rodentia sp.

Tamias sp.
Sciurus sp.
Sylvilagus floridanus
Carnivora sp.
Totals
Acipenser fulvescens
Amia Calva
Aplodinotus grunniens
Castomidae sp.
Catostomus catostomus

20SA581 20BY79
Weber I Third
Street
Bridge
LA
LA
MNI
MNI
2990
2880

present

503

20BY30
Kantzler

20SA2
Schultz

EW
EW
MNI
MNI
2490
3
14

MW Early
MNI

MW Early
MNI
2480

55
2

1

0
present

20SA2 20BY30
Schultz Kantzler

1

1

2
17
12

13
123
528
4
107
92
13

4
2
0
2

9
7
1
4

0

Table 38. (cont’d)
Common Name

Species
Site Name

White sucker
Sucker
sucker

Cultural Period
Measurement
C14 Dates - YBP
Catostomus commersoni
Catostomus sp.
Catostomidae Moxostoma

Sunfish
Northern pike
Pike
Cod
Channel catfish
Black bullhead
Yellow bullhead
Brown bullhead
Channel catfish
Channel catfish
Channel catfish
Catfish
Gar
Longnosed gar

Centrarchidae sp.
Esocidae sp.
Esox sp.
Lota lota lacustris
Ictaluridae sp.
Ictalurus melas
Ictalurus natalis
Ictalurus nebulosus
Ictalurus punctatus
Ictalurus punctatus
Ictalurus punctatus cf.
Ictalurus sp.
Lepisosteus sp.
Lepisosteus osseus oxyurus

Bluegill sunfish
Sunfish

20SA581 20BY79
Weber I Third
Street
Bridge
LA
LA
MNI
MNI
2990
2880

Lepomis cf. macrochirus
Lepomis/Pomoxis sp.

20SA2 20BY30
Schultz Kantzler

20BY30
Kantzler

20SA2
Schultz

EW
EW
MNI
MNI
2490
14
29

MW Early
MNI

MW Early
MNI
2480

111
2
17
99
14
3
12
5
3

6

1

1
2

35
1519

2
32
504

Table 38. (cont’d)
Common Name

Species
Site Name

Cod
Smallmouth bass
Largemouth bass
Bass
Striped bass
rock bass
Shorthead Redhorse

Cultural Period
Measurement
C14 Dates - YBP
Lota lota lacustris
Micropterus dolomieui
Micropterus salmoides
Micropterus sp.
Monroe chrysops
Morone chrysops
Moxostoma macrolepidotum

Shorthead Redhorse
Bony fish
Yellow perch
Perch
Walleye/Sauger/Perch
Perch
Crappie
Crappie
Crappie
Flathead
Trout
Lake trout
Drum

20SA581 20BY79
Weber I Third
Street
Bridge
LA
LA
MNI
MNI
2990
2880

Moxostoma sp.
Osteichthyes sp.
Perca flavescens
Percichthyidae sp.
Percidae
Percidae sp.
Pomoxis nigromaculatus
Pomoxis sp.
Pomoxis/Lepomis sp.
Pylodictis
Salmonidae sp.
Salvelinus namaycush
Sciaenidae sp.

20SA2 20BY30
Schultz Kantzler

20BY30
Kantzler

20SA2
Schultz

EW
EW
MNI
MNI
2490

MW Early
MNI

MW Early
MNI
2480

1
2
12
22
1

1

2
4
2

34
7

3
210
1

2

1

1
2

2

12
2
1
505

Table 38. (cont’d)
Common Name

Walleye
Totals
Green turtle

Painted turtle
Snake
Hidden-necked turtles
Pond turtles
Blandings turtle
Blandings turtle
Sliders/Cooters
Northern water snake
Box turtles
Garter snake
Soft shell turtle
Totals
Great Northern Loon

Species
Site Name

Cultural Period
Measurement
C14 Dates - YBP
Stizostedion sp.
Totals
Anura sp.
Chelonia sp.
Chelydra serpentina
Chelydra serpentina cf.
Chrysemys picta
Colubridae sp.
Cryptodira sp.
Cryptodira
Emydidae sp.
Emydoidea blandingii
Emydoidea blandingii cf.
Emydoidea Chrysemys sp.
Nerodia sipedon
Terrapene sp.
Thamnophis sp.
Trionyx sp.
Totals
Gavia immer
Anas sp.

20SA581 20BY79
Weber I Third
Street
Bridge
LA
LA
MNI
MNI
2990
2880
0

present

20SA2 20BY30
Schultz Kantzler

20BY30
Kantzler

20SA2
Schultz

EW
EW
MW Early MW Early
MNI
MNI
MNI
MNI
2490
2480
188
1
3
5
2403
11
18
0
11
53
2
12
8
4
11

12
5
22
3
11

0

506

20

134

0

0

0

Table 38. (cont’d)
Common Name

Species
Site Name

Mallard Duck
Blue winged teal
American Wigeon
Ring necked duck
redhead
Lesser Scaup
Small eyed duck
Greater Scaup
Great horned owl

Cultural Period
Measurement
C14 Dates - YBP
Anas platyrhynchos
Anas discors
Anas americana
Aythya collaris
Aythya americana
Aythya affinis
Anatidae sp.
Aythya marila
Bubo virginianus Strigiformes

Sandhill crane
Passenger pigeon
Bald eagle
Common merganser

Melanitta deglandi
Totals
Amaranthus sp.
Amelanchier
Amphicarpa bracteata

20BY30
Kantzler

20SA2
Schultz

EW
EW
MNI
MNI
2490

MW Early
MNI

MW Early
MNI
2480

Mergus serrator

White-winged scoter
Totals

20SA2 20BY30
Schultz Kantzler

Crus canadensis
Ectopistes migratorius
Haliaeetus leucocephalus
Mergus merganser Anseriformes

Red breasted merganser

20SA581 20BY79
Weber I Third
Street
Bridge
LA
LA
MNI
MNI
2990
2880

Serviceberry
Hog peanut

present

present
present

present
present
present

0

0

0
1
1

507

0

0

0

1

Table 38. (cont’d)
Common Name

Aster
Mustard family
Hackberry
Goosefoot
Morning-glory family
Round-leaved dogwood
Hawthorn
Squash/Rind
Sedges
Sedges
Bedstraw
Elderberry, Huckleberry
St. John's wort
Sumpweed
Mint family
rose family
Corn
Grass
Nightshade

Species
Site Name

Cultural Period
Measurement
C14 Dates - YBP
Aster cf. cordifolius
Brassicaceae
Celtis occidentalis
Chenopodium spp.
Convolvulaceae
Cornus rugosa
Crataegus sp.
Cucurbita sp.
Cyperus spp.
Cyperaceae
Galium spp.
Gaylussacia baccata
Graminea
Hypericum sp.
Iva annua
Labiateae
Rosaceae
Zea mays
Panicum
Physalis

20SA581 20BY79
Weber I Third
Street
Bridge
LA
LA
MNI
MNI
2990
2880

181

20SA2 20BY30
Schultz Kantzler

20BY30
Kantzler

20SA2
Schultz

EW
EW
MNI
MNI
2490
1
7

MW Early
MNI

MW Early
MNI
2480

835
1
1
29
1

1
3
5
1
4

4
21
1
5
1

5
4

11
3

508

Table 38. (cont’d)
Common Name

Species
Site Name

Virginia creeper

Cultural Period
Measurement
C14 Dates - YBP
Parthenocissus quinquefolia

Grass family
Grass family
Knotweed
Knotweed
Buckwheat

20SA581 20BY79
Weber I Third
Street
Bridge
LA
LA
MNI
MNI
2990
2880

Poaceae(large)
Poaceae(small)
Polygonum
Polygonum
Polygonum pensylvanicum

20SA2 20BY30
Schultz Kantzler

20BY30
Kantzler

20SA2
Schultz

EW
EW
MNI
MNI
2490

MW Early
MNI

MW Early
MNI
2480

67

8
1

3
10
1
15

Plums, cherries, peaches, Prunus spp.
apricots, almonds

1

2

Pear
Blackberry
Raspberries,
blackberries, dewberries

Pyrus sp.
Rubus sp.
Rubus spp.

2

Huckleberry, American
Elderberry
Sassafras

Sambucus canadensis

2

Cattail

Sassafras albidum
Silene sp.
Typha sp.
Vaccinium sp.

3
2
4

509

2

Table 38. (cont’d)
Common Name

Nannyberry
Grape
Maize kernel
Wild rice
Poppy
Maple
Aster
Birch
Hazelnut
Hickory
Hickory shell
Hickory
Shagbark hickory
Chestnut
Hackberry
Redbud
Beech
Ash
White ash
Ash

Species
Site Name

Cultural Period
Measurement
C14 Dates - YBP
Viburnum sp.
Viola
Vitis
Zea mays
Zizania aquatica

20SA581 20BY79
Weber I Third
Street
Bridge
LA
LA
MNI
MNI
2990
2880

20SA2 20BY30
Schultz Kantzler

20BY30
Kantzler

20SA2
Schultz

EW
EW
MNI
MNI
2490
1

MW Early
MNI

MW Early
MNI
2480
1

1
1
36

Acer spp.
Aster cr. Cordifolius
Betula spp.
Corylus americana
Carya spp.
Carya spp.
Carya laciniosa
Carya ovata
Castanea dentata
Celtis occidentalis
Cercis canadensis
Fagus grandifolia
Fraxinus spp.
Fraxinus alba
Fraxinus americana

51
1
3

25
14
786

2

19

19
36
4
1

510

5
21

Table 38. (cont’d)
Common Name

Black ash
Ash
Butternut
Eastern Black Walnut
Walnut family
Sassafras
Mulberry
Hophornbeam
Spruce
Pine
Red pine
White pine
Sycamore
Aspen

Swamp white oak
Acorn
Oak

Species
Site Name

Cultural Period
Measurement
C14 Dates - YBP
Fraxinus nigra
Juglandaceae/Walnut family

20SA581 20BY79
Weber I Third
Street
Bridge
LA
LA
MNI
MNI
2990
2880

Juglans cinerea
Juglans nigra
Juglans spp.
Lauraceae
Morus rubra
Nyssa
Ostraya virginiana
Picea sp.
Pinus spp.
P. resinosa
Pinus strobus
Platanus occidentalis
Populus tremuloides
Populus silex
Prunus sp.
Quercus bicolor
Quercus sp.
Quercus Cotyledon

1
403
3

11

20SA2 20BY30
Schultz Kantzler

20BY30
Kantzler

20SA2
Schultz

EW
EW
MNI
MNI
2490

MW Early
MNI

MW Early
MNI
2480

153
378
1243

63
7

8

3

2

1
1
3
7

1
2

8
11

1
18

22
2

511

Table 38. (cont’d)
Common Name

Acorn shell
White oak
Black oak
Red oak
Sumac
Basswood
Elm
Elm
American elm
Slippery elm
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs

Species
Site Name

Cultural Period
Measurement
C14 Dates - YBP
Quercus sp.
Quercus alba
Quercus nigra
Quercus rubra
Rhus
Tilia americana
Ulmaceae/ Elm family
Ulmus spp.
Ulmus cf. Americana
Ulmus rubra
Actinonaias carinata (Barnes)

20SA581 20BY79
Weber I Third
Street
Bridge
LA
LA
MNI
MNI
2990
2880

20SA2 20BY30
Schultz Kantzler

20BY30
Kantzler

20SA2
Schultz

EW
EW
MNI
MNI
2490

MW Early
MNI

MW Early
MNI
2480
17
22
2
12
23
38
6

1

Amblema costata (Raf.)
Amnicola Limosa (Say)
Amnicola lustrica (Pilsbry)
Anguispira alternata
Anodonta grandis footiana (Say)
Goodrich
Anguispira kochi (Baker)
Anguispira solitaria (Say)
Campeloma decisum (Say)

present

512

Table 38. (cont’d)
Common Name

Species
Site Name

Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs

Cultural Period
Measurement
C14 Dates - YBP
Cyclonaias tuberculata
Discus cronkfilter anthonyi
(Pilsbry)
Elliptio dilatatus (Raf.)
Fusconaia flava (Raf.)
Gastrapoda sp.
Goniobasis livescens (Say)
Helicodiscus parallelus (Say)

Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs

Lampsilis siliquoidea (L)
Lasmigona costata (Raf.)
Ligumia (Recta) lattissima (Raf.)

Snails and slugs

Lymnaea (Stagnicola) palustris
(Say)
Lymnaea columella (Say)
Mesodon thyroidus (Say)

20SA2 20BY30
Schultz Kantzler

20BY30
Kantzler

20SA2
Schultz

EW
EW
MNI
MNI
2490

MW Early
MNI

MW Early
MNI
2480

Helisoma anceps (Conrad)
Helisoma Campanulatum
Helisoma trivolvis (Say)
Haplotrema concavium (Say)

Snails and slugs
Snails and slugs
Snails and slugs

20SA581 20BY79
Weber I Third
Street
Bridge
LA
LA
MNI
MNI
2990
2880

Snails and slugs
Snails and slugs

Snails and slugs
Snails and slugs

present

present

513

Table 38. (cont’d)
Common Name

Species
Site Name

Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs

Cultural Period
Measurement
C14 Dates - YBP
Mesomphix cuprea (Say)
Obovaria subrotunda (Raf.)
Pleurobema (cordatum)
coccineum (Conrad)
Pomatiopsis lapidaria (Say)
Quadrula pustulosa (Lea)
Retinella rhoadsi (Pilsbry)
Somatogyrus sp.
Sphaerium rhombodium
Sphaerium striatum
Sphaerium sulcatum
Stenotrema monodon (Rackett)

Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs

Strophitus rugosis (Swain.)
Succinea ovalis (Say)
Triodopsis albolabris (Say)
Triodopsis multilineata (Say)

Snails and slugs
Snails and slugs

20SA581 20BY79
Weber I Third
Street
Bridge
LA
LA
MNI
MNI
2990
2880

Valvata tricarinata (Say)
Zonitidae sp.
Pelecypoda sp.

Snails and slugs
Snails and slugs
Snails and slugs

514

20SA2 20BY30
Schultz Kantzler

20BY30
Kantzler

20SA2
Schultz

EW
EW
MNI
MNI
2490

MW Early
MNI

MW Early
MNI
2480

Table 38. (cont’d)
Common Name

20GR13

29BY77

20BY79

20BY30

20BY28

20BY28

Site Name

Kanitz

Third
Street
Bridge
MW

Marquette
Viaduct Site

Marquette
Viaduct Site

MW

Suraths
Junk
Yard
MW

Kantzler

Cultural Period

Moose
Deer/Elk
Elk
Elk
White tailed deer
White tailed deer
Bear
Black bear
Totals
Shrew
Domestic dog
Dog/Wolf/Coyote
Wolf
Red fox
Beaver
Beaver
Ground squirrel
Porcupine
Jack rabbit

Species

MNI

MNI

Measurement
C14 Dates - YBP
Alces alces
Cervidae sp.
Cervus canadensis
Cervus elaphus
Odocoileus virginianus
Odocoileus virginianus cf.
Ursus americanus
Euarctos americanus
Totals
Blarina brevicauda
Canis cf. familiaris
Canis sp.
Canis lupus
Vulpes fulva
Castor canadensis
Castor canadensis cf.
Citellus spilosoma
Erethizon dorsatum
Lepus californicus

MW
MW
Hopewell
MNI
NISP
1700

MW
MNI

23

4
1

38

7

1

0

2

6
0

7
2

7

0

1740

1
present

1830

1

10

2

8
2

2
1
1
1
515

Table 38. (cont’d)
Common Name

20GR13

29BY77

20BY79

20BY30

20BY28

20BY28

Site Name

Kanitz

Third
Street
Bridge
MW

Marquette
Viaduct Site

Marquette
Viaduct Site

MW

Suraths
Junk
Yard
MW

Kantzler

Cultural Period

Bobcat
Marten
Meadow vole
Mice, rat, gerbils
Mink
Muskrat
Muskrat
Otter
Deer Mice
Raccoon
Rodents - mice, rats,
squirrels, porcupines,
beavers, chipmunks,
voles
Chipmunk
Squirrel
Rabbit
Misc.
Totals
Lake Sturgeon

Species

MNI

MNI

Measurement
C14 Dates - YBP
Lynx canadensis
Martes americana
Microtus sp.
Muridae sp.
Mustela vison
Ondatra zibethicus
Ondatra zibethicus cf.
Lontra canadensis
Peromyscus sp.
Procyon lotor
Rodentia sp.

Tamias sp.
Sciurus sp.
Sylvilagus floridanus
Carnivora sp.
Totals
Acipenser fulvescens

MW
MW
Hopewell
MNI
NISP
1700

MW
MNI
1740

9

2

1

1

4

present

1830

2

25
26

8
2

present
0

0
516

0

7
4

Table 38. (cont’d)
Common Name

Species

20GR13

29BY77

20BY79

20BY30

20BY28

20BY28

Site Name

Kanitz

Marquette
Viaduct Site

Marquette
Viaduct Site

MW

Third
Street
Bridge
MW

Kantzler

Cultural Period

Suraths
Junk
Yard
MW
MNI

MNI

Bowfin
Freshwater drum
Sucker
Longnose sucker
White sucker
Sucker
sucker

Measurement
C14 Dates - YBP
Amia Calva
Aplodinotus grunniens
Castomidae sp.
Catostomus catostomus
Catostomus commersoni
Catostomus sp.
Catostomidae Moxostoma

Sunfish
Northern pike
Pike
Cod
Channel catfish
Black bullhead
Yellow bullhead
Brown bullhead
Channel catfish
Channel catfish
Channel catfish
Catfish

Centrarchidae sp.
Esocidae sp.
Esox sp.
Lota lota lacustris
Ictaluridae sp.
Ictalurus melas
Ictalurus natalis
Ictalurus nebulosus
Ictalurus punctatus
Ictalurus punctatus
Ictalurus punctatus cf.
Ictalurus sp.

MW
MW
Hopewell
MNI
NISP
1700
1
3

MW
MNI
1830
2
9

1740
1
2

1

1

4

2

2

2

8
2
6
517

Table 38. (cont’d)
Common Name

20GR13

29BY77

20BY79

20BY30

20BY28

20BY28

Site Name

Kanitz

Third
Street
Bridge
MW

Marquette
Viaduct Site

Marquette
Viaduct Site

MW

Suraths
Junk
Yard
MW

Kantzler

Cultural Period

Gar
Longnosed gar

Species

MNI

MNI

Measurement
C14 Dates - YBP
Lepisosteus sp.
Lepisosteus osseus oxyurus

Bluegill sunfish
Sunfish
Cod
Smallmouth bass
Largemouth bass
Bass
Striped bass
rock bass
Shorthead Redhorse

Lepomis cf. macrochirus
Lepomis/Pomoxis sp.
Lota lota lacustris
Micropterus dolomieui
Micropterus salmoides
Micropterus sp.
Monroe chrysops
Morone chrysops
Moxostoma
macrolepidotum
Shorthead Redhorse
Moxostoma sp.
Bony fish
Osteichthyes sp.
Yellow perch
Perca flavescens
Perch
Percichthyidae sp.
Walleye/Sauger/Perch Percidae
Perch
Percidae sp.
Crappie
Pomoxis nigromaculatus

MW
MW
Hopewell
MNI
NISP
1700
2
2

MW
MNI
1830

1740

1

6

1
3
3
518

3

1

Table 38. (cont’d)
Common Name

Species

20GR13

29BY77

20BY79

20BY30

20BY28

20BY28

Site Name

Kanitz

Marquette
Viaduct Site

Marquette
Viaduct Site

MW

Third
Street
Bridge
MW

Kantzler

Cultural Period

Suraths
Junk
Yard
MW
MNI

MNI

Measurement
C14 Dates - YBP
Crappie
Pomoxis sp.
Crappie
Pomoxis/Lepomis sp.
Flathead
Pylodictis
Trout
Salmonidae sp.
Lake trout
Salvelinus namaycush
Drum
Sciaenidae sp.
Walleye
Stizostedion sp.
Totals
Totals
Anura sp.
Green turtle
Chelonia sp.
Chelydra serpentina
Chelydra serpentina cf.
Painted turtle
Chrysemys picta
Snake
Colubridae sp.
Cryptodira sp.
Hidden-necked turtles Cryptodira
Pond turtles
Emydidae sp.
Blandings turtle
Emydoidea blandingii
Blandings turtle
Emydoidea blandingii cf.

MW
MW
Hopewell
MNI
NISP
1700

MW
MNI
1830

1740

2
0

0

0

3
27

22

6

1

1

2

1

3

3

519

2

Table 38. (cont’d)
Common Name

20GR13

29BY77

20BY79

20BY30

20BY28

20BY28

Site Name

Kanitz

Third
Street
Bridge
MW

Marquette
Viaduct Site

Marquette
Viaduct Site

MW

Suraths
Junk
Yard
MW

Kantzler

Cultural Period

Sliders/Cooters
Northern water snake
Box turtles
Garter snake
Soft shell turtle

Species

MNI

MNI

Measurement
C14 Dates - YBP
Emydoidea Chrysemys sp.
Nerodia sipedon
Terrapene sp.
Thamnophis sp.
Trionyx sp.

Mallard Duck
Blue winged teal
American Wigeon
Ring necked duck
redhead
Lesser Scaup
Small eyed duck
Greater Scaup
Great horned owl
Sandhill crane
Passenger pigeon

MW
MNI

0

Gavia immer
Anas sp.
Anas platyrhynchos
Anas discors
Anas americana
Aythya collaris
Aythya americana
Aythya affinis
Anatidae sp.
Aythya marila
Bubo virginianus
Strigiformes
Crus canadensis
Ectopistes migratorius

0

0

present
520

1830

1740

4
13

1
5

3
1

0
Great Northern Loon

MW
MW
Hopewell
MNI
NISP
1700

1
1

Table 38. (cont’d)
Common Name

Serviceberry
Hog peanut
Aster
Mustard family
Hackberry
Goosefoot
Morning-glory family
Round-leaved
dogwood
Hawthorn
Squash/Rind
Sedges

29BY77

20BY79

20BY30

20BY28

20BY28

Kanitz

Third
Street
Bridge
MW

Marquette
Viaduct Site

Marquette
Viaduct Site

MW

Suraths
Junk
Yard
MW

Kantzler

Cultural Period

Red breasted
merganser
White-winged scoter
Totals

20GR13

Site Name

Bald eagle
Common merganser

Species

MNI

MNI

Measurement
C14 Dates - YBP
Haliaeetus leucocephalus
Mergus merganser
Anseriformes
Mergus serrator
Melanitta deglandi
Totals
Amaranthus sp.
Amelanchier
Amphicarpa bracteata
Aster cf. cordifolius
Brassicaceae
Celtis occidentalis
Chenopodium spp.
Convolvulaceae
Cornus rugosa

MW
MW
Hopewell
MNI
NISP
1700
present
present

MW
MNI
1830

1740

4

2

present
present
0

0

0

0

14.30%

2

Crataegus sp.
Cucurbita sp.
Cyperus spp.

14.30%

14.30%

521

Table 38. (cont’d)
Common Name

Grass family
Grass family
Knotweed
Knotweed
Buckwheat

29BY77

20BY79

20BY30

20BY28

20BY28

Kanitz

Third
Street
Bridge
MW

Marquette
Viaduct Site

Marquette
Viaduct Site

MW

Suraths
Junk
Yard
MW

Kantzler

Cultural Period

St. John's wort
Sumpweed
Mint family
rose family
Corn
Grass
Nightshade
Virginia creeper

20GR13

Site Name

Sedges
Bedstraw
Elderberry,
Huckleberry

Species

MNI

MNI

Measurement
C14 Dates - YBP
Cyperaceae
Galium spp.
Gaylussacia baccata

MW
MW
Hopewell
MNI
NISP
1700

MW
MNI
1830

14.30%

Graminea
Hypericum sp.
Iva annua
Labiateae
Rosaceae
Zea mays
Panicum
Physalis
Parthenocissus
quinquefolia
Poaceae(large)
Poaceae(small)
Polygonum
Polygonum
Polygonum pensylvanicum

14.30%
0.1
27
14.30%

522

1740

Table 38. (cont’d)
Common Name

20GR13

29BY77

20BY79

20BY30

20BY28

20BY28

Site Name

Kanitz

Third
Street
Bridge
MW

Marquette
Viaduct Site

Marquette
Viaduct Site

MW

Suraths
Junk
Yard
MW

Kantzler

Cultural Period

Plums, cherries,
peaches, apricots,
almonds
Pear
Blackberry
Raspberries,
blackberries,
dewberries
Huckleberry,
American Elderberry
Sassafras

Species

MNI

MNI

Measurement
C14 Dates - YBP
Prunus spp.

Pyrus sp.
Rubus sp.
Rubus spp.

Sambucus canadensis

Grape
Maize kernel

Sassafras albidum
Silene sp.
Typha sp.
Vaccinium sp.
Viburnum sp.
Viola
Vitis
Zea mays

Wild rice

Zizania aquatica

Cattail
Nannyberry

523

MW
MW
Hopewell
MNI
NISP
1700

MW
MNI
1830

1740

Table 38. (cont’d)
Common Name

Species

20GR13

29BY77

20BY79

20BY30

20BY28

20BY28

Site Name

Kanitz

Marquette
Viaduct Site

Marquette
Viaduct Site

MW

Third
Street
Bridge
MW

Kantzler

Cultural Period

Suraths
Junk
Yard
MW
MNI

MNI

Measurement
C14 Dates - YBP

MW
MW
Hopewell
MNI
NISP
1700

MW
MNI
1830

Poppy
Per 10 liter
foot
Maple
Aster
Birch
Hazelnut
Hickory
Hickory shell
Hickory
Shagbark hickory
Chestnut
Hackberry
Redbud
Beech
Ash
White ash
Ash
Black ash

Acer spp.
Aster cr. Cordifolius
Betula spp.
Corylus americana
Carya spp.
Carya spp.
Carya laciniosa
Carya ovata
Castanea dentata
Celtis occidentalis
Cercis canadensis
Fagus grandifolia
Fraxinus spp.
Fraxinus alba
Fraxinus americana
Fraxinus nigra

12.1
0.5

3.4
8.6

524

1740

Table 38. (cont’d)
Common Name

Hophornbeam
Spruce
Pine
Red pine
White pine
Sycamore
Aspen

Swamp white oak
Acorn
Oak

29BY77

20BY79

20BY30

20BY28

20BY28

Kanitz

Third
Street
Bridge
MW

Marquette
Viaduct Site

Marquette
Viaduct Site

MW

Suraths
Junk
Yard
MW

Kantzler

Cultural Period

Butternut
Eastern Black Walnut
Walnut family
Sassafras
Mulberry

20GR13

Site Name

Ash

Species

MNI

MNI

Measurement
C14 Dates - YBP
Juglandaceae/Walnut
family
Juglans cinerea
Juglans nigra
Juglans spp.
Lauraceae
Morus rubra
Nyssa
Ostraya virginiana
Picea sp.
Pinus spp.
P. resinosa
Pinus strobus
Platanus occidentalis
Populus tremuloides
Populus silex
Prunus sp.
Quercus bicolor
Quercus sp.
Quercus Cotyledon

MW
MW
Hopewell
MNI
NISP
1700

MW
MNI
1830
1.2

0.1

1
3.4
36.2

1
525

19

1740

Table 38. (cont’d)
Common Name

Snails and slugs
Snails and slugs

29BY77

20BY79

20BY30

20BY28

20BY28

Kanitz

Third
Street
Bridge
MW

Marquette
Viaduct Site

Marquette
Viaduct Site

MW

Suraths
Junk
Yard
MW

Kantzler

Cultural Period

Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs

20GR13

Site Name

Acorn shell
White oak
Black oak
Red oak
Sumac
Basswood
Elm
Elm
American elm
Slippery elm
Snails and slugs

Species

MNI

MNI

Measurement
C14 Dates - YBP
Quercus sp.
Quercus alba
Quercus nigra
Quercus rubra
Rhus
Tilia americana
Ulmaceae/ Elm family
Ulmus spp.
Ulmus cf. Americana
Ulmus rubra
Actinonaias carinata
(Barnes)
Amblema costata (Raf.)
Amnicola Limosa (Say)
Amnicola lustrica (Pilsbry)
Anguispira alternata
Anodonta grandis footiana
(Say) Goodrich
Anguispira kochi (Baker)
Anguispira solitaria (Say)

MW
MW
Hopewell
MNI
NISP
1700

MW
MNI
1830
0.1
1.7
6.9

3.4
5.2

526

1740

Table 38. (cont’d)
Common Name

Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs

29BY77

20BY79

20BY30

20BY28

20BY28

Kanitz

Third
Street
Bridge
MW

Marquette
Viaduct Site

Marquette
Viaduct Site

MW

Suraths
Junk
Yard
MW

Kantzler

Cultural Period

Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs

20GR13

Site Name

Snails and slugs
Snails and slugs
Snails and slugs

Species

MNI

MNI

Measurement
C14 Dates - YBP
Campeloma decisum (Say)
Cyclonaias tuberculata
Discus cronkfilter anthonyi
(Pilsbry)
Elliptio dilatatus (Raf.)
Fusconaia flava (Raf.)
Gastrapoda sp.
Goniobasis livescens (Say)
Helicodiscus parallelus
(Say)
Helisoma anceps (Conrad)
Helisoma Campanulatum
Helisoma trivolvis (Say)
Haplotrema concavium
(Say)
Lampsilis siliquoidea (L)
Lasmigona costata (Raf.)
Ligumia (Recta) lattissima
(Raf.)
527

MW
MW
Hopewell
MNI
NISP
1700

MW
MNI
1830

1740

Table 38. (cont’d)
Common Name

Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs

29BY77

20BY79

20BY30

20BY28

20BY28

Kanitz

Third
Street
Bridge
MW

Marquette
Viaduct Site

Marquette
Viaduct Site

MW

Suraths
Junk
Yard
MW

Kantzler

Cultural Period

Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs

20GR13

Site Name

Snails and slugs

Species

MNI

MNI

Measurement
C14 Dates - YBP
Lymnaea (Stagnicola)
palustris (Say)
Lymnaea columella (Say)
Mesodon thyroidus (Say)
Mesomphix cuprea (Say)
Obovaria subrotunda (Raf.)
Pleurobema (cordatum)
coccineum (Conrad)
Pomatiopsis lapidaria (Say)
Quadrula pustulosa (Lea)
Retinella rhoadsi (Pilsbry)
Somatogyrus sp.
Sphaerium rhombodium
Sphaerium striatum
Sphaerium sulcatum
Stenotrema monodon
(Rackett)
Strophitus rugosis (Swain.)
Succinea ovalis (Say)
Triodopsis albolabris (Say)
528

MW
MW
Hopewell
MNI
NISP
1700

MW
MNI
1830

1740

Table 38. (cont’d)
Common Name

29BY77

20BY79

20BY30

20BY28

20BY28

Kanitz

Third
Street
Bridge
MW

Marquette
Viaduct Site

Marquette
Viaduct Site

MW

Suraths
Junk
Yard
MW

Kantzler

Cultural Period

Snails and slugs
Snails and slugs

20GR13

Site Name

Snails and slugs

Species

MNI

MNI

Measurement
C14 Dates - YBP
Triodopsis multilineata
(Say)
Valvata tricarinata (Say)
Zonitidae sp.
Pelecypoda sp.

MW
MW
Hopewell
MNI
NISP
1700

MW
MNI
1830

1

529

1740

Table 38. (cont’d)
Common Name

Moose
Deer/Elk
Elk
Elk
White tailed deer
White tailed deer
Bear
Black bear
Totals
Shrew
Domestic dog
Dog/Wolf/Coyote
Wolf
Red fox
Beaver
Beaver
Ground squirrel
Porcupine
Jack rabbit
Bobcat

Species
Site Name

20SA2
Schultz

20BY387-1
Marquette
Viaduct
South

Cultural Period
Measurement
C14 Dates - YBP
Alces alces
Cervidae sp.
Cervus canadensis
Cervus elaphus
Odocoileus virginianus
Odocoileus virginianus cf.
Ursus americanus
Euarctos americanus
Totals
Blarina brevicauda
Canis cf. familiaris
Canis sp.
Canis lupus
Vulpes fulva
Castor canadensis
Castor canadensis cf.
Citellus spilosoma
Erethizon dorsatum
Lepus californicus
Lynx canadensis

20BY387
Marquet
te
Viaduct
South

MW Late
MNI
MNI
1600

20BY28-1
Fletcher/
Marquette
Viaduct/
Defoe Park

20BY28
Fletcher/
Marquette

NISP

NISP

NISP
1830

1740

38

40
1
32
18
1

10

530

49

92

12
11

12
11

9
1

0

10
1
1

0

11

7

Table 38. (cont’d)
Common Name

Marten
Meadow vole
Mice, rat, gerbils
Mink
Muskrat
Muskrat
Otter
Deer Mice
Raccoon
Rodents - mice, rats,
squirrels,
porcupines, beavers,
chipmunks, voles
Chipmunk
Squirrel
Rabbit
Misc.
Totals
Lake Sturgeon
Bowfin
Freshwater drum

Species
Site Name

20SA2
Schultz

Cultural Period
Measurement
C14 Dates - YBP
Martes americana
Microtus sp.
Muridae sp.
Mustela vison
Ondatra zibethicus
Ondatra zibethicus cf.
Lontra canadensis
Peromyscus sp.
Procyon lotor
Rodentia sp.

MW Late
MNI
MNI
1600

Tamias sp.
Sciurus sp.
Sylvilagus floridanus
Carnivora sp.
Totals
Acipenser fulvescens
Amia Calva
Aplodinotus grunniens

20BY387-1
Marquette
Viaduct
South

20BY387
Marquet
te
Viaduct
South

20BY28-1
Fletcher/
Marquette
Viaduct/
Defoe Park

20BY28
Fletcher/
Marquette

NISP

NISP

NISP
1830

5
3

1740

4

6

2

0

531

0

20
3
2
1

34
1
3

31
6
31
9

Table 38. (cont’d)
Common Name

Sucker
Longnose sucker
White sucker
Sucker
sucker
Sunfish
Northern pike
Pike
Cod
Channel catfish
Black bullhead
Yellow bullhead
Brown bullhead
Channel catfish
Channel catfish
Channel catfish
Catfish
Gar
Longnosed gar
Bluegill sunfish

Species
Site Name

20SA2
Schultz

20BY387-1
Marquette
Viaduct
South

Cultural Period
Measurement
C14 Dates - YBP
Castomidae sp.
Catostomus catostomus
Catostomus commersoni
Catostomus sp.
Catostomidae Moxostoma
Centrarchidae sp.
Esocidae sp.
Esox sp.
Lota lota lacustris
Ictaluridae sp.
Ictalurus melas
Ictalurus natalis
Ictalurus nebulosus
Ictalurus punctatus
Ictalurus punctatus
Ictalurus punctatus cf.
Ictalurus sp.
Lepisosteus sp.
Lepisosteus osseus oxyurus
Lepomis cf. macrochirus

MW Late
MNI
MNI
1600

20BY387
Marquet
te
Viaduct
South

20BY28-1
Fletcher/
Marquette
Viaduct/
Defoe Park

20BY28
Fletcher/
Marquette

NISP

NISP

NISP
1830
2

1740
3

8

1

8

1

1

3
2

1

1

1

1
1

532

Table 38. (cont’d)
Common Name

Sunfish
Cod
Smallmouth bass
Largemouth bass
Bass
Striped bass
rock bass
Shorthead Redhorse
Shorthead Redhorse
Bony fish
Yellow perch
Perch
Walleye/Sauger/Per
ch
Perch
Crappie
Crappie
Crappie
Flathead
Trout

Species
Site Name

20SA2
Schultz

20BY387-1
Marquette
Viaduct
South

Cultural Period
Measurement
C14 Dates - YBP
Lepomis/Pomoxis sp.
Lota lota lacustris
Micropterus dolomieui
Micropterus salmoides
Micropterus sp.
Monroe chrysops
Morone chrysops
Moxostoma macrolepidotum
Moxostoma sp.
Osteichthyes sp.
Perca flavescens
Percichthyidae sp.
Percidae

MW Late
MNI
MNI
1600

20BY387
Marquet
te
Viaduct
South

20BY28-1
Fletcher/
Marquette
Viaduct/
Defoe Park

20BY28
Fletcher/
Marquette

NISP

NISP

NISP
1830

1740

4
1
2
1

11
3
25

204
1

158

911
3

1

5

6

2
1

Percidae sp.
Pomoxis nigromaculatus
Pomoxis sp.
Pomoxis/Lepomis sp.
Pylodictis
Salmonidae sp.

2
3

533

Table 38. (cont’d)
Common Name

Lake trout
Drum
Walleye
Totals
Green turtle

Painted turtle
Snake
Hidden-necked
turtles
Pond turtles
Blandings turtle
Blandings turtle
Sliders/Cooters
Northern water
snake
Box turtles
Garter snake

Species
Site Name

20SA2
Schultz

20BY387-1
Marquette
Viaduct
South

Cultural Period
Measurement
C14 Dates - YBP
Salvelinus namaycush
Sciaenidae sp.
Stizostedion sp.
Totals
Anura sp.
Chelonia sp.
Chelydra serpentina
Chelydra serpentina cf.
Chrysemys picta
Colubridae sp.
Cryptodira sp.
Cryptodira

20BY387
Marquet
te
Viaduct
South

MW Late
MNI
MNI
1600

20BY28-1
Fletcher/
Marquette
Viaduct/
Defoe Park

20BY28
Fletcher/
Marquette

NISP

NISP

NISP

Emydidae sp.
Emydoidea blandingii
Emydoidea blandingii cf.
Emydoidea Chrysemys sp.
Nerodia sipedon
Terrapene sp.
Thamnophis sp.
534

0

1740

13
233

27
201

104
1082

26

0

1830

4

Table 38. (cont’d)
Common Name

Soft shell turtle
Totals
Great Northern
Loon
Mallard Duck
Blue winged teal
American Wigeon
Ring necked duck
redhead
Lesser Scaup
Small eyed duck
Greater Scaup
Great horned owl
Sandhill crane
Passenger pigeon
Bald eagle
Common merganser
Red breasted
merganser

Species
Site Name

20SA2
Schultz

20BY387-1
Marquette
Viaduct
South

Cultural Period
Measurement
C14 Dates - YBP
Trionyx sp.
Totals
Gavia immer

20BY387
Marquet
te
Viaduct
South

MW Late
MNI
MNI
1600

20BY28-1
Fletcher/
Marquette
Viaduct/
Defoe Park

20BY28
Fletcher/
Marquette

NISP

NISP

NISP

535

26

4
4

0

1
1
9
1

1
1
9
1

6

Anas sp.
Anas platyrhynchos
Anas discors
Anas americana
Aythya collaris
Aythya americana
Aythya affinis
Anatidae sp.
Aythya marila
Bubo virginianus Strigiformes
Crus canadensis
Ectopistes migratorius
Haliaeetus leucocephalus
Mergus merganser
Anseriformes
Mergus serrator

0

1740

1
1

0

1830

6

Table 38. (cont’d)
Common Name

White-winged
scoter
Totals
Serviceberry
Hog peanut
Aster
Mustard family
Hackberry
Goosefoot
Morning-glory
family
Round-leaved
dogwood
Hawthorn
Squash/Rind
Sedges
Sedges
Bedstraw
Elderberry,
Huckleberry

Species
Site Name

20SA2
Schultz

Cultural Period
Measurement
C14 Dates - YBP
Melanitta deglandi

MW Late
MNI
MNI
1600

Totals
Amaranthus sp.
Amelanchier
Amphicarpa bracteata
Aster cf. cordifolius
Brassicaceae
Celtis occidentalis
Chenopodium spp.
Convolvulaceae
Cornus rugosa
Crataegus sp.
Cucurbita sp.
Cyperus spp.
Cyperaceae
Galium spp.
Gaylussacia baccata

20BY387-1
Marquette
Viaduct
South

0

20BY387
Marquet
te
Viaduct
South

1
536

NISP

NISP
1830

0

2

1
22

20BY28
Fletcher/
Marquette

NISP

2
61

20BY28-1
Fletcher/
Marquette
Viaduct/
Defoe Park

2
1

2

1740

22

18

Table 38. (cont’d)
Common Name

St. John's wort
Sumpweed
Mint family
rose family
Corn
Grass
Nightshade
Virginia creeper
Grass family
Grass family
Knotweed
Knotweed
Buckwheat
Plums, cherries,
peaches, apricots,
almonds
Pear
Blackberry
Raspberries,
blackberries,

Species
Site Name

20SA2
Schultz

20BY387-1
Marquette
Viaduct
South

Cultural Period
Measurement
C14 Dates - YBP
Graminea
Hypericum sp.
Iva annua
Labiateae
Rosaceae
Zea mays
Panicum
Physalis
Parthenocissus quinquefolia
Poaceae(large)
Poaceae(small)
Polygonum
Polygonum
Polygonum pensylvanicum
Prunus spp.

20BY387
Marquet
te
Viaduct
South

MW Late
MNI
MNI
1600

20BY28-1
Fletcher/
Marquette
Viaduct/
Defoe Park

20BY28
Fletcher/
Marquette

NISP

NISP

NISP
1830

1740

55
17
1

Pyrus sp.
Rubus sp.
Rubus spp.

1
1

537

Table 38. (cont’d)
Common Name

Species
Site Name

20SA2
Schultz

20BY387-1
Marquette
Viaduct
South

Cultural Period
Measurement
C14 Dates - YBP

20BY387
Marquet
te
Viaduct
South

MW Late
MNI
MNI
1600

20BY28-1
Fletcher/
Marquette
Viaduct/
Defoe Park

20BY28
Fletcher/
Marquette

NISP

NISP

NISP
1830

1740

dewberries
Huckleberry,
American Elderberry
Sassafras
Cattail
Nannyberry
Grape
Maize kernel
Wild rice
Poppy
Maple
Aster
Birch
Hazelnut
Hickory

Sambucus canadensis

1

Sassafras albidum
Silene sp.
Typha sp.
Vaccinium sp.
Viburnum sp.
Viola
Vitis
Zea mays
Zizania aquatica

2

1

70
Acer spp.
Aster cr. Cordifolius
Betula spp.
Corylus americana
Carya spp.

92

3

15
62
538

3

3

Table 38. (cont’d)
Common Name

Hickory shell
Hickory
Shagbark hickory
Chestnut
Hackberry
Redbud
Beech
Ash
White ash
Ash
Black ash
Ash
Butternut
Eastern Black
Walnut
Walnut family
Sassafras
Mulberry
Hophornbeam

Species
Site Name

20SA2
Schultz

Cultural Period
Measurement
C14 Dates - YBP
Carya spp.
Carya laciniosa
Carya ovata
Castanea dentata
Celtis occidentalis
Cercis canadensis
Fagus grandifolia
Fraxinus spp.
Fraxinus alba
Fraxinus americana
Fraxinus nigra
Juglandaceae/Walnut family
Juglans cinerea
Juglans nigra

MW Late
MNI
MNI
1600

Juglans spp.
Lauraceae
Morus rubra
Nyssa
Ostraya virginiana

20BY387-1
Marquette
Viaduct
South

20BY387
Marquet
te
Viaduct
South

20BY28-1
Fletcher/
Marquette
Viaduct/
Defoe Park

20BY28
Fletcher/
Marquette

NISP

NISP

NISP
1830

1740

41
20
27

5
23

8
1
58

145

14
1
539

7

10

Table 38. (cont’d)
Common Name

Spruce
Pine
Red pine
White pine
Sycamore
Aspen

Swamp white oak
Acorn
Oak
Acorn shell
White oak
Black oak
Red oak
Sumac
Basswood
Elm
Elm
American elm

Species
Site Name

20SA2
Schultz

20BY387-1
Marquette
Viaduct
South

Cultural Period
Measurement
C14 Dates - YBP
Picea sp.
Pinus spp.
P. resinosa
Pinus strobus
Platanus occidentalis
Populus tremuloides
Populus silex
Prunus sp.
Quercus bicolor
Quercus sp.
Quercus Cotyledon
Quercus sp.
Quercus alba
Quercus nigra
Quercus rubra
Rhus
Tilia americana
Ulmaceae/ Elm family
Ulmus spp.
Ulmus cf. Americana

MW Late
MNI
MNI
1600

31

20BY28-1
Fletcher/
Marquette
Viaduct/
Defoe Park

20BY28
Fletcher/
Marquette

NISP

NISP

NISP
1830

11
3
16
48

27

20BY387
Marquet
te
Viaduct
South

1740

18

5

8

2

1

22

51

24
3
5
10
40
17
540

12

Table 38. (cont’d)
Common Name

Slippery elm
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs

Species
Site Name

20SA2
Schultz

20BY387-1
Marquette
Viaduct
South

Cultural Period
Measurement
C14 Dates - YBP
Ulmus rubra
Actinonaias carinata (Barnes)
Amblema costata (Raf.)
Amnicola Limosa (Say)
Amnicola lustrica (Pilsbry)
Anguispira alternata
Anodonta grandis footiana
(Say) Goodrich
Anguispira kochi (Baker)
Anguispira solitaria (Say)
Campeloma decisum (Say)
Cyclonaias tuberculata
Discus cronkfilter anthonyi
(Pilsbry)
Elliptio dilatatus (Raf.)
Fusconaia flava (Raf.)
Gastrapoda sp.
Goniobasis livescens (Say)
Helicodiscus parallelus (Say)
Helisoma anceps (Conrad)

MW Late
MNI
MNI
1600
4

20BY387
Marquet
te
Viaduct
South

20BY28-1
Fletcher/
Marquette
Viaduct/
Defoe Park

20BY28
Fletcher/
Marquette

NISP

NISP

NISP
1830

2

541

1740

Table 38. (cont’d)
Common Name

Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs
Snails and slugs

Species
Site Name

20SA2
Schultz

20BY387-1
Marquette
Viaduct
South

Cultural Period
Measurement
C14 Dates - YBP
Helisoma Campanulatum
Helisoma trivolvis (Say)
Haplotrema concavium (Say)
Lampsilis siliquoidea (L)
Lasmigona costata (Raf.)
Ligumia (Recta) lattissima
(Raf.)

MW Late
MNI
MNI
1600

542

20BY387
Marquet
te
Viaduct
South

20BY28-1
Fletcher/
Marquette
Viaduct/
Defoe Park

20BY28
Fletcher/
Marquette

NISP

NISP

NISP
1830

1740

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