EVALUATING ENVIRONMENTAL RESPONSE AND RECOVERY
USING A MULTIPROXY PALEOLIMNOLOGICAL APPROACH

By
Colleen E. McLean

A DISSERTATION
Submitted to
Michigan State University
In partial fulfillment of the requirements
for the degree of
DOCTOR OF PHILOSOPHY
Environmental Geosciences
2011

i

ABSTRACT
EVALUATING ENVIRONMENTAL RESPONSE AND RECOVERY
USING A MULTIPROXY PALEOLIMNOLOGICAL APPROACH
By
Colleen E. McLean

Human activity has influenced ecosystems since antiquity, with the health and
function of aquatic ecosystems being significantly impacted since the industrial
revolution. A better understanding of the response of modern aquatic ecosystems to
natural and anthropogenic influences can be gleaned by reconstructing an environmental
history of a system. An effective way to do this is to merge the record of historical
perturbations with the overprint of modern stressors, which can be evaluated using lake
sediment cores as they archive both historic and recent changes.
In a paleolimnological study of Muskegon Lake, Michigan, USA, multiple
environmental proxies were analyzed to evaluate a system‟s response and recovery to
human perturbation through time. The overarching hypothesis was that the disturbances
from human activities (e.g., land use change) have been at an intensity that will not
permit ecosystems to return to a pre-disturbance state; and because of other continuing
and emerging stressors (e.g. climate change), ecosystems will not evolve to a new state of
balance (characterized as steady state and/or equilibrium processes). To investigate this
hypothesis, geochemical and biological proxies from a 150 cm sediment core were
evaluated and compared to a chronology of human activity in the watershed. If true, the
temporal patterns of biological and geochemical proxies will correspond to the
chronology of natural and anthropogenic changes in the watershed.
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The geochemical data from the core revealed suites of elements that corresponded
to the source of the material, including terrestrial, productivity and anthropogenic related
inputs. These elemental groups closely tracked the history of human activity and
identified three phases of human influence. Phase one represented pre-disturbance
(reference) conditions, phase two identified anthropogenic influence, and phase three
suggested partial system recovery from phase two. Moreover, the profiles of
anthropogenic elements were used to evaluate a geochemical reference condition for the
system, and showed that the modern concentrations have not decreased to pre-historical
values, thus indicating a scenario of an adapting reference condition state.
The biological reconstruction, inferred from fossil diatoms, also identified three
distinct paleoecological phases corresponding to environmental change. The ecological
preferences of individual diatom taxa suggest that biostratigraphic trends were driven by
temperature, cultural nutrient inputs, and recently emerging stressors (e.g. climate and
invasive species). Further, the benthic v. planktonic community structure of diatoms was
used to reconstruct productivity regimes in the lake through time, which identified a
significant shift from planktonic to benthic dominated productivity occurring in recovery
phase of the core.
Finally, to better understand ecosystem function (e.g. time-lags and feedbacks),
the proxies were integrated. Unique relationships among geochemical and biological
proxies confirm the three phases representing ecosystem response to environmental
change, supporting the overarching hypothesis. However, results also indicated apparent
ecological change in response to up-and-coming stressors - of which little is known.
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Copyright by
COLLEEN E. MCLEAN
2011

iv

DEDICATION
DEDICATION
This dissertation is dedicated to my children, parents, and sister; and the memory
of my grandmother, Catherine Devenny Elwood.

v

ACKNOWLEDGEMENTS
I would like to thank the Great Lakes Fishery Trust for funding this research.
Thank you to the Michigan State University Aqueous and Environmental Science
Laboratory for laboratory support, as well as Glenn Schmidt and the Michigan
Department of Environmental Quality for data collection support. Thanks and
appreciation to Dr. Nadja Ognjanova-Rumenova for diatom processing and identification.
Special thanks to Dr. Lina Patino and Dr. David Syzmanski for ICPMS laboratory
analyses and support; as well as Sarah Voice, Scott Wasielewski, Kari Stone and Lori
Babcock for field and laboratory assistance.
I thank my advisor, Dr. David T. Long, for the tremendous support; and kind
guidance with seeing the forest through the trees. Also, much thanks and gratitude to my
committee members: Dr. Catherine Yansa, Dr. Patricia Soranno and Dr. Thomas Voice
for invaluable input with this study. I feel very fortunate to have had an interdisciplinary
perspective with my research.
Finally, big thanks the many people who provided lively discussion and
invaluable moral support. My officemates and friends: Dean Baas, Matthew J. Parsons,
Ryan Vannier, Merideth Lindeman Fitzpatrick and Nate Saladin; and dear friends: Karen
Tefend, Malee Jinuntuya, Meredith Benedict, and Angela Donatelle were all quite
instrumental to the completion of this work. Thank you.

vi

TABLE OF CONTENTS

LIST OF TABLES……………………………………………………………………......ix
LIST OF FIGURES…………………………………………………………………….....x
CHAPTER 1. INTRODUCTION……………………………….………………………...1
Abstract………………………………………………………….……………….........1
Introduction………………………………………………….…….…………………..2
Literature Review……………………………………………………………………..3
Research Hypothesis …………………………………………………………………8
Research Area…………………………………………………………………….….11
Methods.……………………………………………….……………………………..23
Research Approach…………………………………………………………………..25
Literature Cited………………………………………………………………………28
CHAPTER 2. EVALUATING REFERENCE CONDITIONS USING GEOCHEMICAL
CHRONOLOGIES FROM A LACUSTRINE SEDIMENT CORE….…………………38
Abstract………………………………………………………….……………….......38
Introduction………………………………………………….…….…………………40
Methods…………………………………………………….……….………………..48
Results……………………………………………………………….……………….52
Discussion…………………………………………………………….……………...73
Conclusions……………………………………………………………………….….87
Literature Cited……………………………………………………….……………...90
CHAPTER 3. IDENTIFYING ECOLOGICAL REGIME SHIFTS FROM DIATOM
ABUNDANCE STRATIGRAPHY……….…………………………………………….96
Abstract……………………………….………………………………………………96
Introduction…………..………………………………………………………………97
Methods……………………………………………………………………………...104
Results……………………………………………………………………………….105
Discussion…………………………………………………………………………...125
Conclusions………………………………………………………………………….137
Literature Cited……………………………………………………………………...140
CHAPTER 4. ASSESSING ENVIRONMENTAL CHANGE USING AN
INTEGRATED PALEOECOLOGICAL APPROACH…………………….………….148
Abstract……………………………………………………………………………...148
Introduction…………………………………………………………………………149
Methods……………………………………………………………………………..151
Results……………………………………………………………………………….152
Discussion…………………………………………………………………………...157
vii

Conclusions………………………………………………………………………….163
Literature Cited……………………………………………………………………...167
APPENDICES
Appendix 1: A description of the sediment core characteristics……………………..170
Appendix 2: Muskegon Lake sediment core porosity………….…………………….177
Appendix 3: Muskegon Lake sediment geochemistry………………………..……….182
Appendix 4: A list of the 177 diatom taxa present in Muskegon Lake core…………195
Appendix 5: Relative abundances of common Muskegon Lake diatoms….…………203
Appendix 6: Habitat and ecological preference Muskegon Lake diatoms….…..........212

viii

LIST OF TABLES

Table 2.1: Muskegon Lake core chronology……………….………..………................57
Table 2.2: Compilation of Muskegon Lake geochemistry…….…….…………………72
Table 3.1: Relative contribution of primary production in lakes…….……..…………100

Table A.1: A description of the sediment core characteristics………………………...170
Table A.2: Muskegon Lake sediment core porosity…………………………………...177
Table A.3: Muskegon Lake sediment geochemistry…………………………………...182
Table A.4: A list of the 177 diatom taxa present in Muskegon Lake core………….…195
Table A.5: Relative abundances of common Muskegon Lake diatoms………………..203
Table A.6: Habitat and ecological preference Muskegon Lake diatoms………………212

ix

LIST OF FIGURES

Figure 1.1:

Conceptual map of potential environmental system interactions
(modified from Dearing 2006)………………………………………..4

Figure 1.2:

Conceptual model of environmental response to anthropogenic
influence in varying regions delineated by development status; and
under contrasting management strategies through time. The line to
point A shows a linear relationship with population/development and
environmental impact. Point A to B depicts an exponential increase of
environmental impacts related to industrialization. The line from B to
C1 results when no management strategies are in place to mitigate
environmental degradation from human activity. The line from B to
C2 illustrates the trajectory of environmental impacts with minimal
management oversight. The line from B to C3 demonstrates partial
environmental recovery with strict environmental regulations.
(Modified from Garcier 2007)…………………………………..…….6

Figure 1.3:

Location of the Muskegon River Watershed in Michigan, USA…….13

Figure 1.4:

Modern land use in the Muskegon River Watershed, Michigan,
USA………………………………………………………………….14

Figure 1.5:

Timeline of relevant historical events in the Muskegon River
Watershed……...…………………………………………………….17

Figure 1.6:

Modern land use within a 500m of Muskegon Lake………………...20

Figure 1.7:

Graphs showing historic land uses of a 500m buffer of Muskegon
Lake…………………………………………………………………..21

Figure 1.8:

Map of Muskegon Lake showing loss in shoreline since 1877…...…22

Figure 2.1:

Diagram depicting ecosystem response to various stressors and the
change in reference condition targets as a function of environmental
legacy to anthropogenic stress. Modified from Battarbee 1999 and
Battarbee et al. 2005…………………………………………………46

Figure 2.2:

Chronology comparision for Muskegon Lake for a. 2006 long core, b.
2003 short core, and c. 2006 short core……………………………...56

Figure 2.3:

Chronology comparision for Muskegon Lake for a. 2006 long core, b.
2003 short core, and c. 2006 short core……………………………...58

Figure 2.4:

Concentration profiles of normalized redox indicator proxies………62
x

Figure 2.5:

Concentration profiles of normalized terrestrial indicator data……...63

Figure 2.6:

Concentration profiles of productivity indicators calcium
phosphorus…………………………………………………………...64

Figure 2.7:

Concentration profiles of normalized anthropogenic indicators……..66

Figure 2.8a:

Geochemical inventories of anthropogenic elements………………..66

Figure 2.8b:

Geochemical inventories of anthropogenic elements………………..69

Figure 2.9:

Productivity indicators and geochemical phases…………………….78

Figure 2.10:

Concentration profiles of normalized anthropogenic indicators……..82

Figure 2.11:

Adapting reference conditions using geochemical data……………...87

Figure 3.1:

Hypothetical conceptual diagram of regime shifts (Modified from
Carpenter 2003)…………………………………………………….101

Figure 3.2:

Muskegon Lake diatom taxa which are at least 20% abundant in one
level…………....................................................................................108

Figure 3.3:

Muskegon Lake diatom taxa which are at least 10% abundant in one
level…………………………………………………………………110

Figure 3.4:

Muskegon Lake diatom taxa which are at least 7% abundant in one
level…………………………………………………………………112

Figure 3.5:

Muskegon Lake diatom taxa which are at least 5% abundant in one
level…………………………………………………………………114

Figure 3.6:

Muskegon Lake diatom taxa which are at least 2% abundant in one
level…………………………………………………………………116

Figure 3.7:

The sum of dominant diatom productivity habitats in Muskegon
Lake………………………………………………………………...117

Figure 3.8a:

Zone specific relative abundance of all common benthic Muskegon
Lake diatoms………………………………………………………..119

Figure 3.8b:

Zone specific relative abundance of all common planktonic Muskegon
Lake
diatoms………………………………………………………...........120
xi

Figure 4.1:

A comparison of geochemical and biological phases as related to
watershed events……………………………………………………154

Figure 4.2a:

Trends from AD1800 for land use in the Muskegon River
Watershed…………………………………………………………..156

Figure 4.2b:

Trends from AD1800 for population in Muskegon County………..156

Figure 4.2c:

Trends from AD 1800 for temperature in the state of Michigan…...156

Figure 4.2d:

Trends from AD1800 for precipitation in the state of Michigan…...156

Figure 4.3:

Conceptual map of observed Muskegon Lake ecosystem interactions
(modified from Dearing 2006)……………………………………...160

Figure 4.4:

Conceptual model of environmental response to anthropogenic
influence in varying regions delineated by development status; and
under contrasting management strategies through time. (Modified from
Garcier 2007)………………………………...……………………..163

xii

CHAPTER 1
INTRODUCTION TO EVLUATING ENVIRONMENTAL RESPONSE AND
RECOVERY USING A MULTIPROXY PALEOLIMNOLOGICAL APPROACH

1.1 Introduction
The rate and magnitude of human influence has increased in recent centuries,
which has resulted in greater impacts to ecological systems worldwide and added to
concerns about society‟s reliance on natural resources as we attempt to achieve a
sustainable society. Aquatic ecosystems provide particularly important natural capital for
ecosystem services (e.g. potable water, fisheries, and recreation); yet they are particularly
vulnerable to anthropogenic environmental change as atmospheric and terrestrial
pollutants are ultimately funneled into rivers and lakes. Global increases in population
and economic development, as well as land use transformations (e.g. deforestation,
agriculture, and urbanization) impact the health of ecological systems, ultimately
affecting the quality (and quantity) of water resources. As such, the societal relevance in
understanding the full extent of anthropogenic impacts on aquatic ecosystems is of
critical importance because the demand for ecological services is increasing. However,
while understanding ecosystem dynamics is critical for developing sustainable societies,
it also presents a challenge given the complexity of varying timescales and intensities of
past anthropogenic stressors.
The broad goals of this study are to 1) interpret the response of aquatic
ecosystems to human impacts and 2) untangle the complexity of ecosystem processes
using archives of ecological indicators from lake sediments. This study utilizes a
paleoecological approach, which is suitable because it provides a long-term chronological
1

record of changing ecological conditions, that reveal functional dynamics and
interrelationships (feedbacks) within systems and reconstructs the continued
environmental response as the role of humans becomes more dominant. Identifying the
signals of ecological response can help policy makers understand the past, present and
future scenarios of freshwater ecosystems, thus making better decisions for sustainable
management (Dearing et al. 2008).
Currently, there are gaps in knowledge about aquatic ecosystem response to
human influence, and importantly, what that may indicate for water resources globally
(Brock et al. 2008; Carpenter et al. 2003; Messerli et al. 2000). This disconnect exists, in
large part, because while we have a detailed chronology of human activities available in
historical records, we lack reliable long-term ecological history. This gap can be
narrowed using a paleolimnological approach and addressing the following questions: 1)
how have systems responded to multiple anthropogenic stressors?; 2) how does the
current ecosystem state compare to the pre-perturbation state?; 3) is it possible to infer
significant system shifts using indirect (e.g. fossil diatom) proxy methods?; 4) does using
multiple proxies (e.g. chemical and biological) improve interpretations of environmental
change?; and 5) can we predict future ecosystem recovery and/or a stable state scenario
resulting from the advent of environmental regulations (e.g. Clean Air/Clean Water
Acts)?

2

1.2 Literature review
Environmental system science
Given the complexity of environmental dynamics, it is necessary to carefully
frame this study using a system that includes interactions between large, key „system
components‟, as well smaller scale internal processes embedded within those
components, called „constituents‟ (Kay 2008a; Kay 2008b). Figure 1.1 is a conceptual
diagram showing key environmental system components and select constituents. The bidirectional arrows in the figure represent the potential interactions of modern systems
using three major components: ecological, planetary and human forcings. The circular
arrows within each box represent the relationships among select internal constituents of
that component. The targeted system for this study, an aquatic ecosystem, is an open
system, and therefore both a source and a sink for the flow of matter and energy. For
example, the web of ecological processes in aquatic ecosystems is influenced by physical,
chemical and biological processes operating internally through feedback mechanisms
(e.g. nutrient cycling with primary producers); as well as the external relationships with
other components (e.g. solar radiation influence on primary producers).

3

Figure 1.1: Conceptual map of potential environmental system interactions (modified
from Dearing 2006)

Dynamics in environmental systems are not naturally temporally static. Most
ecological systems slowly change over time (e.g. natural succession - ontology), which
slowly changes the type and function of the ecosystem (Battarbee et al. 2005). Prehistorically, before major human perturbation, a two component system of ecological and
planetary forces operated in a state of interconnected and successional balance. In this
type of environment, the system evolves to new states, but the time scale typically allows
for components and constituents to slowly adapt. Modern ecosystems, however,
encounter an additional forcing from human perturbations (forcing), resulting in a three
component system where the human component often dominates (Dearing et al. 2006a;
Dearing et al. 2006b). Consequently, global ecosystems have changed where humans
4

have an impact on earth systems; at times causing abrupt, catastrophic ecological change,
and shifting a predictable balance between components, resulting in an unpredictable and
unstable state (Scheffer and Carpenter 2003; Carpenter 2008)
A vital aspect to ensuring that ecosystem health, and thus, ecosystem services are
maintained requires employing sustainable management practices. Determining what is a
sustainable, or even a feasible management strategy necessitates an understanding of how
complex ecological systems respond to the long term effects of anthropogenic stressors
(e.g. land use changes and climate change) (Dearing et al. 2008). Figure 1.2 shows a
conceptual model of environmental response to anthropogenic influence at varying
temporal scales. This figure is delineated by development status; and by varying degree
of management strategies (modified from Garcier 2007). Because of the inherent
uncertainty, and at times, lack of documentation regarding human influence in both the
Europe/Asia region and in modern developing nations, sites (systems) in North America
present a good opportunity to study environmental change. Systems in this region
possess a near complete recorded timeline of human manipulation of the environment. In
the Great Lakes Region, this began in earnest in the early 1800s following the arrival of
Europeans to the North American continent (Alexander 2006).
Correlating human events with ecological conditions since that time are used to
evaluate how humans have impacted the environment (Dixit et al. 1992; 1999; Reavie et
al. 1998). Reconstructing environmental response is further useful given that future
ecological conditions depend on management decisions; therefore, understanding

5

environmental response is directly linked to the feasibility of making informed
recommendations that best restore and maintain sustainable systems.

Figure 1.2: Conceptual model of environmental response to anthropogenic influence in
varying regions delineated by development status; and under contrasting
management strategies through time. The line to point A shows a linear
relationship with population/development and environmental impact. Point
A to B depicts an exponential increase of environmental impacts related to
industrialization. The line from B to C1 results when no management
strategies are in place to mitigate environmental degradation from human
activity. The line from B to C2 illustrates the trajectory of environmental
impacts with minimal management oversight. The line from B to C3
demonstrates partial environmental recovery with strict environmental
regulations. (Modified from Garcier 2007)

6

Paleoecology
Paleolimnological archives offer a unique opportunity for understanding the broad
scope of ecological change, as paleoecological reconstructions reveal the complexity of
the ecological-planetary-human system (Dearing et al. 2006a; Dearing et al. 2008). This
approach is useful for evaluating environmental response because assessing pre-historic
ecological health from contemporary environmental measurements (e.g. water column
total phosphorous) is not possible without using inferences. Furthermore, ongoing
monitoring efforts since the 1970s have not sufficiently captured the dynamics of longterm environmental behavior (Bennion and Battarbee 2007).
Paleoecological studies main focus was historically on a single indicator or a
limited number of proxies from lake sediments to infer climate change, to evaluate
regional and watershed scale perturbation in land use and land cover change, and to
reconstruct historic environmental events such as fires, logging (e.g., Cooper and Brush
1993; Cooper 1995; Stoermer et al. 1996; Bunting et al. 1997; Bradbury et al. 1997; Smol
and Cummings 2000; Reavie et al. 2000; Huang and O‟Connell 2000; Garrison and
Wakeman 2000; Paterson et al. 2001; Yohn et al. 2002; Sorvari et al. 2002; Das 2002;
Brugam et al. 2003; Cohen et al. 2005). Commonly used paleoecological proxies
include: multi-element sediment geochemistry (Olsson et al. 1997; Chapman et al. 1998;
Yohn et al. 2002; Siver et al. 2003; Parsons et al. 2004; O‟Reilly et al. 2005); diatom
population structure (Wolfe et al. 1996; Hall et al. 1997; Hall and Smol 1999; Slate and
Stevenson 2000; Battarbee et al. 2001; Ramstack et al. 2003); pollen stratigraphy (Yansa
and Ashworth 2005; Birks and Birks 2002; Cohen et al. 2005b; Davidson et al. 2005);
ostracodes (Forester 1991, 1987, 1983; Smith 1993); chrysophycean statospores,
7

silicoflagellates and algal pigments (Smol 2002). While these can be effective for
specific research objectives (e.g., nutrient loading), a single inference proxy is not robust
enough to determine the comprehensive influence of environmental change on stressorresponses within aquatic ecosystems (Dearing et al. 2008). This investigation uses
multiple proxies archived in lake sediment to gain an understanding of historic reference
conditions and ecological regime shifts. Deciphering the impact of multiple
environmental stressors that operate at different timescales and intensities will lend
insight to overall stressor-response relationships.
The key to understanding ecological behavior under the modern three component
system lies in the slice of history since the human component has become dominant, in
North America this is roughly the past 300 years. Lake sediment collects material
deposited in lakes during this slice of time, as atmospheric and terrestrial pollutants
ultimately funnel into lake basins (Smol 2002; Wetzel 2003). This process naturally
records environmental change, and the subsequent internal and external feedback
mechanisms driving that change (Smol 2002). Consequently, the time period focused on
in this study will document the historic reference condition (before human impacts) and
the human induced ecological regime shifts. These tell the broader story of ecosystem
processes, and facilitate a mechanistic understanding of environmental dynamics.

1.3 Research hypothesis
Modern systems have deviated from the pre-perturbation two-system dynamic,
where ecological balance slowly adapted in concert through natural succession (ontology)
8

(Dearing et al. 2006(a)). What remains unclear is: the degree to which modern systems
have been altered, which specific human impacts (e.g. logging, industry and
urbanization) have resulted in the most catastrophic changes, the environmental legacy of
past watershed activity on modern systems is, and the future scenarios expected with the
overprint of multiple contemporary stressors. To understand these issues, it is necessary
to reconstruct the ecological history to understand mechanisms of system
transformations. Therefore, a temporal perspective of ecological behavior is
advantageous to understanding how systems respond (Smol 2002). Aspects of this
include investigating the time-lags, the strength of system resiliency, the thresholds for
irreversible change, and the “stability” of ecological regimes (Scheffer and Carpenter
2003).
Aquatic ecosystems are good ecosystems to investigate environmental change,
because they are particularly sensitive to the effects of human forcing as the ecological
endpoint of material flushed from the atmosphere and terrestrial landscape (Smol 2002;
Andersen et al 2004; Bennion and Battarbee 2007). Consequently, aquatic ecosystem
„response‟ to anthropogenic inputs, as recorded in sediment, offers a reliable indication of
a system‟s ecological history, in terms of how it changes as a consequence of human
perturbations (Dearing et al. 2008).
The objective of this research is to examine environmental change through the
lens of an “environmental systems approach” that will best interpret ecological processes.
Specific objectives of this study include; 1) to determine how aquatic ecosystems respond
to specific perturbations (e.g. logging, industry, urbanization) using individual
9

paleoecological proxies (e.g. geochemistry and diatoms); 2) to interpret the
environmental legacy of anthropogenic stressors by calculating deviation from
geochemical reference concentration and by identifying ecological regime shifts; 3) to
identify correlations/relationships among geochemical and diatom sediment chronologies
that infer process such as lag-time and feedback mechanisms. The overarching
hypothesis driving this research was that: ecosystems highly disturbed by human activity
cannot be expected to return to a pre-disturbance state; and further, with the influence of
climate change, and other continuing and emerging stressors, ecosystems will not obtain
a new state of balance (steady state and/or equilibrium).
To evaluate this hypothesis, data from multi-element sediment geochemistry and
fossil diatoms were examined independently, and then integrated to better understand the
temporal dynamics of aquatic ecosystem function as a whole system. The main tools
developed in this study will identify/validate relationships among proxy groups of the
core geochemistry, and examine planktonic versus benthic diatom community structure
to better understand productivity regime shifts. The integration chapter will contribute to
how the indicators can be merged to enhance single proxy interpretations. This study is
important for contributing to an understanding of long term environmental response
trends related to the history of anthropogenic activity and changing climate influences in
the Great Lakes region. This framework is also transferable to other regions as it will
address the system response to management strategies aimed at protecting water quality
in watersheds.

10

1.4 Study Area
Great Lakes Watershed
The Laurentian Great Lakes region has experienced exponential growth in human
development due to increased trade, logging and industry since the advent of EuroAmerican settlement. These developments emerged from the use of the region‟s natural
resources, including vast forests of white pine and hardwood species, as well as metal
deposits, including copper, iron, gold and silver (Alexander 2006; Wells 1978). The
utility of abundant tributaries connected to the massive Great Lakes corridor allowed raw
materials and finished goods to be transported to ports throughout the region in the 19th
and 20th centuries, and ultimately distributed around the world (Alexander 2006).
Historically, these activities and related modifications to hydrology for agriculture and
municipal uses (e.g., dams, diversions and reservoirs) have contributed to the degradation
of aquatic ecosystems in the Great Lakes watershed (Wolin and Stoermer 2005).
Ecological change in the Great Lakes region has been coupled with the overprint
of a warmer and wetter climate regime since the Little Ice Age ended (~1850), further
stressing ecosystems with changing environmental conditions (Magnuson et al. 1997). A
study by Magnuson et al. (2000), data indicate that ice phenologies (records of ice freeze
and thaw dates) in the Great Lakes region since the Little Ice Age have averaged ~6 days
later and ~6 days earlier per 100 years, which corresponds to a 1.2°C increase in the last
100 years. Ecological response to warming conditions can further complicate impacts on
aquatic ecosystems; with various feedback mechanisms little understood and highly
uncertain (Magnuson et al. 1997).
11

Muskegon River Watershed
The Muskegon River Watershed is part of the Great Lakes Watershed, located in
the Lower Peninsula of western Michigan. It is a dominant drainage network in the state,
fed by wetlands, groundwater springs, lakes, agricultural drains and tributaries. Figure
2

1.3 shows the Muskegon River Watershed which encompasses 7057 km of western and
central Michigan (Wahrer 1996; U‟Ren 2002; Pijanowski et al. 2008). The Muskegon
River flows more than 350 km from its headwaters at Houghton and Higgins Lake to its
mouth at Muskegon Lake, then eventually empties into Lake Michigan through a
navigation channel (De Mol ANNIS 2005; Pijanowski et al. 2008; Steinman et al. 2008).
Average rain fall is increasing in the watershed, with a recent average of 90 cm per year;
while from 1899 through 2001, the average was 83 cm. A lower average precipitation of
75 cm occurred from 1920-1940 (Pijanowski et al. 2008). Surficial glacial deposits
dominate the Muskegon River Watershed. These deposits overlay Jurassic “red-beds” in
the upper reaches, to Pennsylvanian Period Grand River – Saginaw Formations in the
central portion, and Mississippian Period Parma Sandstone, Bayport Limestone,
Michigan Formation and Marshall Sandstone in the lower segment of the watershed
(Wahrer et al., 1996; Westjohn and Weaver, 1997; U‟Ren and Conzelmann 2002;
Fitzpatrick et al. 2007).

12

Figure 1.3: Location of the
Muskegon River Watershed in
Michigan, USA.

Land use varies throughout the watershed, but is dominated by forests and
agricultural lands, with small scattered urban areas (Varnakovida et al. 2005). Figure 1.4
shows modern land use in the Muskegon River Watershed. In the upper watershed,
nearly twenty percent of the watershed is state forest land in public ownership, with the
remaining land also being predominately forested (Pijanowski et al. 2008). The middle
watershed is dominated by agriculture, with increasing urbanization and reforestation as
agriculture decreases in significance. The lower watershed is the most developed, and
has the largest urban and industrial areas. The city of Muskegon, where the Muskegon
River discharges into Muskegon Lake, is the largest urban area in the watershed with an
estimated population of 40,000 people in 2000 (Pijanowski et al. 2008). Tourism and
recreation on Muskegon Lake and throughout the watershed are vital ecosystem services
that rely heavily on the lake‟s fisheries. However, it is forecasted that there will be an
increase in urbanization in the watershed which may contribute to further watershed
degradation and therefore decrease the economic vitality of the region, since it relies on
13

revenue from the fisheries for a significant portion of its economy (Tang et al. 2005;
Pijanowski et al. 2005).

Figure 1.4: Current land use in the Muskegon River Watershed, Michigan, USA.

Historic Muskegon River Watershed Disturbances
Until the seventeenth century, the Muskegon River Watershed was not
significantly altered by humans, despite human occupation for several thousands of years.
Paleo-Indian hunters were the first inhabitants following the retreat of the late
14

Wisconsinsan glaciers (Alexander 2006). This population was succeeded by Archaic
Woodland and other cultural traditions. Before Euro-American settlements appeared,
various bands of Ottawa and Pottawatomi Indians were the predominant tribes in the
area. The name “Muskegon” is a derivation of the Ottawa Indian word “Masquigon”
meaning “river with marshes”. This is supported by the fact that the Masquigon River is
how the Muskegon River is identified on French maps dating from the late seventeenth
century; also indicating that French fur trappers probably reached the western coast of
Michigan by that time (Alexander 2006). Fur trapping in the region was followed by
exploitation of the vast pine forests present in Michigan (Whitney 1987; Alexander
2006). Besides logging in the Muskegon River watershed, rivers and streams were used
to transport logs to newly developing cities. At one point during the lumber peak of the
1880s, the city of Muskegon had more than 47 sawmills (Alexander 2006). By 1890, the
watershed‟s dense White Pine forest was almost completely harvested, and logging came
to a halt by 1910 (Alexander 2006; Wells 1978). Declining lumbering prior to 1900
began to be replaced by heavy industry.
Following the depletion of lumber resources, emerging 20th century
developments included a growing industrial base (The Association for Iron and Steel,
1904). Among the first major factories to locate to Muskegon Lake‟s shoreline was the
Central Paper Company, currently SAPPI Fine Paper - North America (Alexander, 1999).
The paper mill, foundries, oil tank farms, and other factories that located to the City of
Muskegon, City of Roosevelt Park, City of Norton Shores, and City of Muskegon
Heights, contributed to heavy metals and toxic chemicals inputs to Muskegon Lake.
Some of this development was undermined by the Great Depression in the 1930s;
15

however, the economy rebounded during the World War II era, with Muskegon having a
role in arsenal production, with oil and chemical industries having a prominent presence
(Alexander 2006). In the mid-1900s, foundries, metal finishing plants, a paper mill, and
petrochemical storage facilities were on the shore of Muskegon Lake (Steinman et al.
2008; Alexander 2006). Subsequently, industrial pollution concerns dominated
Muskegon environmental issues and effected human health for decades (Carter et al.
2006; Rediske et al. 2002). Expansion of heavy industry and shipping in 1960s and
3

1970s contributed to over 100,000m /day of wastewater discharged from industrial and
municipal sources (Great Lakes Commission 2000, Evans 1992). The initial logging and
later effects of the automobile (leaded gasoline), coupled with other industrial activities,
have permanently altered the natural environmental landscape and degraded habitat
quality in the lake and its tributaries. The legacy of those impacts resulted in two
superfund sites in the Muskegon Lake watershed area, and multiple advisories on fish and
wildlife consumption due to mercury and PCB contamination (MDEQ 2006).
Additionally, invasive species such as zebra mussel and blooms of the exotic marine
microalgae, Enteromorpha flexuosa, have plagued Muskegon Lake, thereby having
degraded water quality, aesthetics, and fishery habitats (Lougheed et al. 2004). See
Figure 1.5 for a timeline of relevant events in the history of the Muskegon River
Watershed.

16

Figure 1.5: Timeline of relevant historical events in the Muskegon River Watershed.

As part of remediation efforts in the early 1970s, one directive set to minimize
human effects on the Muskegon River Watershed, including Muskegon Lake, was the
installation of a waste water treatment plant (Steinman et al. 2008; Carter et al. 2006).
An 11,000 acre tertiary facility was constructed in 1973 to divert industrial and municipal
wastewater from surface and groundwater discharges. This land application system is
capable of treating 42 million gallons a day using aeration, lagoon impoundment, slowrate irrigation and rapid-sand filtration (http://co.muskegon.mi.us/wwtf.htm). The
Muskegon River receives the treated wastewater at a point nearly 26 miles upstream of

17

Muskegon Lake, near Mosquito Creek. As a result, there have been substantial
improvements in the water quality of Muskegon Lake.
Muskegon Lake
2

Muskegon Lake is a 16.91 km inland water body located in the Laurentian Great
Lakes region (W 86° 17 25.42 , N 43°13 59.45 ). Mean depth in the lake is 7 m with a
maximum depth of 23 m. Muskegon Lake itself is the end point of drowned river mouth
system that connects the Muskegon River Watershed to the coastal zone of Lake
Michigan through a navigation channel (Steinman et al. 2008). Residence time is ~23
days, with the primary inflow being the Muskegon River, and the primary outlet flowing
to Lake Michigan (Freedman et al. 1979). The lakes proximity to the Great Lakes and
general ecological setting make it an important fishery, though invasive species, habitat
loss and degradation continue to be factors of concern (Clapp et al. 2001; LaMP 2004).
Muskegon Lake has a history of intense anthropogenic activity on its shoreline
since early 1800s. At one point during the lumber peak in the 1880s, the city of
Muskegon had more than 47 sawmills (Alexander 2006). Following the depletion of
lumber resources, turn of the century development in Muskegon involved industrial
corporations; but this was quickly undermined by the Great Depression in the 1930s. The
economy rebounded during the World War II era, with Muskegon having a role in arsenal
production, with oil and chemical industries having a prominent presence (Alexander
2006). In the mid-1900s, foundries, metal finishing plants, a paper mill and
petrochemical storage facilities were on the shore of Muskegon Lake (Steinman et al.
2008). Subsequently, industrial pollution concerns dominated Muskegon environmental
18

issues and effected human and ecological health concerns for decades (Rediske et al.
2002; Carter et al. 2006; Steinman et al. 2008). Expansion of heavy industry and
3

shipping in 1960s and 1970s contributed to over 100,000m /day of wastewater
discharged from industrial and municipal sources until a tertiary waste water treatment
plant was installed in 1973 (Freedman et al. 1979; Evans 1992; Great Lakes Commission
2000, Steinman et al. 2008).
Historical land use around Muskegon Lake is available for a 500 m buffer from
1900 to present. Figure 1.6 shows Muskegon Lake with a defined 500 m buffer, and the
dominant modern land uses from MiDGL. Figure 1.7 shows the historical percentage of
water, wetlands, grasslands, agriculture, forests and urban land use (Ray and Pijanowski
2010).

19

N
W

E
S

500 m Buffer
Mu sk egon Lak e
Basin Boun dary
Lan d Use
Urb an
Agricultural
Forested /Undevelop ed
Wetland s
Water

4

0

4

8 Kilometers

Figure 1.6: Modern land use near Muskegon Lake, with a 500 m buffer delineated.

20

2010

A.

1995
1980
1965
1950

Forest

1935

Agriculture

1920

Urban

1905

1890
0

20

40

60

80

100

2010

B.

1995
1980
1965
1950

Wetland

1935

Water

1920

Grassland

1905

1890
0

2

4

6

8

10

Figure 1.7a and b: Graphs showing historic land uses of a 500m buffer of Muskegon
Lake (Ray and Pijanowski 2010)

Shoreline development has furthered the declining ecological status of Muskegon
Lake by altering natural buffers and habitats, and by introducing metal, organic and
nutrient pollutants. Many of these pollutants impact biota in the water column before
being buried in the sediment of the lake (Carter et al. 2006; Redieski et al. 2002). A
21

recent inventory of 49.99 km of Muskegon Lake shoreline shows that 64.93% (32.46 km)
is hardened and 35.07% (16.99 km) is natural. Of the hardened shoreline, 10.31 km is
metal seawall, 9.98 km concrete riprap, and 3.85 km rock riprap. The natural shoreline is
predominately located on the lake‟s north side; while remaining industrial activity is
concentrated on the south shore (Steinman et al. 2008). Figure 1.8 shows the change in
the shoreline of Muskegon Lake (Steinman, personal communication, 2008).

Figure 1.8: Map of Muskegon Lake showing loss in shoreline since 1877.
(Steinman, personal communication, 2008)

As mentioned, substantial water quality improvements in Muskegon Lake resulted
from the installation of the Wastewater Management System (WMS) in 1973. Total
phosphorus and soluble reactive phosphorus decreased from 68 to 27 µg/L, and from 20
to 5 µg/L, respectively, from installation to 2006 (Steinman et al. 2008). Secchi disk
22

depth also increased from 1.5 to 2.2 m. Conversely, nitrate concentrations have increased
from 70 to 270 μg/L over the same time period (Steinman et al. 2008; Freedman et al.
1979).
Overall, the Muskegon Lake ecosystem improved as a result of this particular
environmental directive. However, non-point source stressors and a history of
contaminated sediments have plagued the lake and may be a factor in the observed
modern increases in water column nitrate concentrations (Steinman et al. 2008; Carter et
al. 2006; Rediske et al. 2002).
Though there is great awareness through stakeholder involvement, and policy
initiatives in place to restore ecological integrity to Muskegon Lake (e.g. Great Lakes
Fisheries Trust funding). However, there remains a need to understand how the system
will respond to these efforts, particularly with the overprint of modern stressors such as
land use change and climate change. Understanding historic ecological response in
Muskegon Lake will clarify future scenarios of ecological health, not only for the
Muskegon River Watershed, but for the larger Great Lakes Watershed and similar
environments globally.

1.5 Methods
Sampling
The Michigan Department of Environmental Quality M/V Nibi and a modified
Mooring Systems Model 2172 Piston Corer were used to collect a 149 cm core from the
depositional basin of Muskegon Lake. The core was collected as close as possible to the
23

latitude and longitude of the 2003 coring location reported in Parsons et al. (2004)(
43º14.042'N, 86º17.006'W) as determined using a bathymetric map, and GPS electronic
depth finder (to facilitate core chronology). On shore immediately following sampling,
the core was sectioned at 1 cm resolution using a hydraulic extruder. Sediment were
placed in acid washed polypropylene jars and quickly put on ice to maintain the chemical
and biological integrity of the sample. Subsamples were double homogenized, split for
sediment geochemical and diatom analyses, placed in whirl-pak® bags and frozen.
Sediment description
Descriptions of sediment color and texture were recorded for each increment of
the 149 cm core at the time of sampling. Throughout, lithographic units were not easily
discernable, with mostly dark, thick mud. Visual inspection showed that: sediment were
mostly organic and watery from 0 to 9 cm; consisted of brown mud from 10 to 20 cm;
became moderately thicker with fragments of shells and petroleum odor intermittent from
21 to 59 cm; darker and thicker mud was present with continued shells and other organic
fragments from 60 to 98 cm; more dark brown and thick sediment from 99 to 149 cm,
with lenses of wood fragments present from 95 to 115 cm (presumably from logging).
An additional, more detailed visual inspection of sediment performed in search for 14C
dating material revealed that wood fragments and saw dust was prominent between 94
and 115 cm depth. This is believed to indicate the time period of 1870 through 1910
when logging was the dominant human activity in the watershed. Descriptions of the
sediment core characteristics are given in Appendix I.

24

Porosity
Porosity was determined by placing a separate subsample in a pre-weighed
whirlpak® bag and then reweighing after freeze-drying. Results of porosity from the
Muskegon Lake core are given in Appendix II. Porosity was determined from a separate
sub-sample using the calculation:

φ = (Mass of wet – Mass of dry) / Mass total

1.6 Research Approach
This chapter has discussed the overall concept and objectives for this research.
While other research has explored multiple paleoecological proxies, the perspective of
this study that links theory to observation using a highly disturbed system is unique.
Particularly, integrating the use of high resolution geochemistry and biological indicators,
coupled with the detailed record of human activity in the Muskegon River Watershed will
further the understanding of environmental response to successive waves of human
influence. Furthermore, the nature of perturbations in the Great Lakes region is unique in
that there has been significant environmental change in a relatively short span of time,
allowing paleolimnology to capture insight to the pre-disturbance „state of the system‟.
The analyses presented in each of the chapters demonstrate an approach for interpretation
of environmental change using ecological indicators.
Chapter 2 focuses on how contemporary geochemical concentrations can be
assessed by investigating their deviation from „reference‟ concentrations (with
25

consideration of underlying natural variability). A suite of elements was employed to
best define elemental classes and relationships among classes through time in response to
the multiple anthropogenic stressors of Muskegon Lake.
Chapter 3 investigates the application of regime shifts to ecological systems using
diatom community structure. Shifts in benthic versus planktonic taxa from the lake
sediment will be the focus of this chapter, as they have been shown to effectively record
productivity and corresponding nutrient conditions as inferred through community
stratigraphy.
Chapter 4 integrates chemical and biological proxies to determine
interrelationships and feedback mechanisms. This final chapter seeks to understand
irreversible and non-linear changes in complex environmental systems following human
perturbations that resulted in abrupt and unpredictable catastrophic environmental
change.

26

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Olsson, S., J. Regnell, A. Person and P. Sandgren. 1997. Sediment-chemistry response to
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240.

37

CHAPTER 2
EVALUATING REFERENCE CONDITIONS USING GEOCHEMICAL
CHRONOLOGIES FROM A LACUSTRINE SEDIMENT CORE

Abstract

In recent centuries, human impacts such deforestation, chemical pollution and
invasive species have stressed freshwater ecosystems in the Great Lakes Region, altered
the rate and function of biogeochemical processes, and resulted in surface water
impairment. Efforts to mitigate environmental degradation increasingly refer to an
ecological reference condition as a target for remediation goals. However, questions and
uncertainty remain as to whether this is an appropriate or feasible target since it is
difficult to determine a system‘s prehistorical reference condition using contemporary
monitoring techniques.
This study used a lacustrine sediment core from a highly perturbed watershed to
investigate the magnitude and intensity of environmental change, with an emphasis on
identifying the geochemical reference condition; or the system‘s geochemistry prior to
Euro-American logging. The hypothesis for this study is that, 1) disturbance of
ecosystems from prehistoric reference conditions can be identified by changes in
temporal trends of individual elementals as well as the relationships among proxy groups,
and 2) systems have not returned to prehistoric reference conditions but rather are
evolving to new states of balance due to the legacy of human perturbation. To test this

38

hypothesis, sediment core geochemical profiles were evaluated to determine how the
system responded to secular and human perturbations.
Results identified three temporal phases of geochemical response; 1) preperturbation, or ―reference conditions‖ (core bottom), 2) human dominated phase with
increased anthropogenic element concentrations (core middle), and 3) policy response
phase with decreased anthropogenic element concentrations (top 25 cm of core). Modern
elemental concentrations at the top of the core did not match the ‗reference values‘ from
the bottom of the core. The environmental ‗recovery‘ phase, following the installation of
a tertiary waste water treatment plant upstream from Muskegon Lake, did reflect
decreasing anthropogenic loading of metals and nutrients; however, effects of terrestrial
run-off and increased urbanization continue to be observed in the certain sediment
geochemical profiles. While the hypothesis was supported by the results, as both
individual elements and proxy groups tracked temporal geochemical changes and
identified the prehistorical reference condition, this investigation suggests greater
consideration needs to be directed at the environmental legacy of human behavior when
interpreting modern sediment geochemical trends. Additionally, conclusions from this
study suggest a reassessment of reasonable ecological recovery expectations may be
necessary, given the influence of contemporary human disturbances and the
superimposed predicted changes in climate.

39

2.1 Introduction
Problem
In recent centuries, human impacts have been a major force stressing global
freshwater ecosystems (Smol 2002). In the Great Lakes region, major human
perturbation began with rapid and catastrophic deforestation, as Euro-American settlers
leveled forests to clear land for agriculture; and later, industrialization and urban
development (Tang et al. 2005; Anderson 2004; Pijanowski et al. 2007). Since the
1800s, these activities have resulted in altered hydrology, disrupted biological
communities and chemical contamination of aquatic ecosystems (Freedman et al. 1979;
Hall and Smol 1995; Anderson 2004; Steinman et al. 2008). Environmental regulations
(e.g. Clean Water/Clean Air Acts) initiated in the early 1970s were designed to mitigate
the effects of catastrophic ecological degradation, and to maintain critical ecosystem
services such as potable water, fisheries, and tourism. Efforts to restore ecological health
of degraded systems often recommend a prehistorical ―reference condition‖ (also referred
to as background, pre-perturbation or pre-settlement) as a remediation target (Andersen et
al. 2004; Battarbee et al. 2005; Bennion and Battarbee 2007). A challenge with this
recommendation is that quantifying a genuine reference condition, or state of the
environmental system prior to disturbance, is not possible using modern empirical data.
Additionally, it has been suggested that the reference condition adapts through time as a
function of secular changes and/or the legacy of anthropogenic impacts (Battarbee 1999;
Battarbee et al. 2005; Long et al. 2010). This chapter presents lake sediment
geochemical data to explore aspects of historic system response to environmental change,
40

evaluate the reference condition concept, and determine modern trends to lend insight
about what can be expected from system recovery.
Reference conditions
Reference conditions are defined as a baseline, or background measure of an
ecosystem variable (including biological, chemical, or physical attributes) representative
of a system having no (or minimal) human influence (Karr 1981, Bennion et al. 2004;
Bennion and Battarbee 2007). In the absence of long-term monitoring data that identify
an ecological reference condition, paleolimnology is a tool that provides the temporal
framework; since sediments in aquatic ecosystems are excellent recorders of
environmental change and thus offer a solution for establishing reference conditions
(Leira et al. 2006, Ekdahl et al. 2007). Using paleolimnology, pre-perturbation
conditions can be reconstructed using a single inference proxy, or combination of proxies
(Anderson 1993; Last and Smol 2001). Proxies often include fossilized indicators
representing the flora (e.g. planktonic and benthic diatoms, aquatic plant macrofossils,
pollen) and fauna (e.g. chironomids, ostracods, cladocerans, fish scales) of aquatic
systems (Bennion and Batterbee 2007) and select geochemistry (Smol 1992; Bailey et al.
2004).
Sediment cores reveal the legacy of naturally occurring and human induced
changes through geochemical signals that provide information about atmospheric
deposition, watershed scale terrestrial inputs, and internal processes of lacustrine systems
(Olsson et al. 1997; Dean 2002; Yohn et al. 2002; O‘Reilly et al. 2005). Thus, sediment
cores can help answer questions such as: how stable were systems before anthropogenic
41

impacts, how have lake systems responded to various human activities, including
logging, industrialization, etc., and are systems showing recovery with the advent of
stricter management? Paleolimnological studies that focus on core geochemisty to
investigate reference conditions have mainly employed major elements (e.g. Al, Fe that
can indicate landscape stability or erosion) or anthropogenic elements (e.g. Hg, Pb) to
evaluate chemical deviation from pre-perturbation, mostly in tandem with biological
proxies such as diatoms (Ekdahl et al. 2007). While using select major elements can be
effective for specific objectives, including geochemical pollution inventories, these alone
are not sufficient for understanding the dynamics of system response (e.g. productivity,
toxicity) to specific environmental disturbances (Smol 2002; Battarbee et al. 2005;
Bennion and Battarbee 2007).
Interpretation of chemical profiles is at times difficult, and can be additionally
challenging due to post-depositional environments where diagenetic processes and
bioturbation may convolute the record (Berner 1980; Engstrom and Wright 1984; Long et
al. 2010). Nevertheless, advances in analytical techniques, such as inductively coupled
plasma mass spectroscopy (ICPMS) encourage multi-element data analysis by providing
trace element data that can untangle many of the interpretation complexities. Recent
work by Yohn et al. (2004) and Long et al. (2010) demonstrate that ‗classes‘ of elements
(e.g. terrestrial, carbonate, diagenetic and anthropogenic) reliably track system response
because groups of like elements tend to have similar source and in-lake biogeochemical
behavior, and thus behave in similar ways.
Categorizing classes of elements in a multi-element approach can give another
line of evidence to validate biogeochemical behavior and help to understand overall
42

system response to change more clearly. For example, in pristine environments where
ecological and planetary components are the only components (see Fig. 1.1), certain
elements may be coupled (demonstrated by having similar profile trajectories); then, with
the influence of a third, human component (whether it be from a terrestrial disturbance or
atmospheric deposition), the elemental response changes, reflecting a different trajectory
with new trends forming in concert with changing biogeochemical dynamics.
The reference condition concept, as discussed here, has been applied to most
freshwater ecosystems, including rivers, lakes and wetlands, and is used to identify
conditions of low impacted environments (Karr 1991, Bennion and Battarbee 2007).
Furthermore, it has been incorporated into national and international programs for
monitoring and assessing environmental conditions (Dodds et al. 2004; Dodds et al.
2006, Leira et al. 2006). The United States Environmental Protection Agency‘s Clean
Water Act (CWA) uses the reference condition as a restoration target, while the European
Union (EU) has the reference condition concept as an explicitly stated feature of the
Water Framework Directive (WFD) (Stoddard et al. 2006). The pre-industralization
condition c AD 1850 is commonly used in both Europe and North America to define
reference conditions (Andersen et al. 2004; Bailey et al. 2004; Bennion and Battarbee
2007). Examining reference conditions through the lens of geochemical classes
untangles some of the complexity of multi-element analyses, and improves insight to
ecological response, including biogeochemical processes. Ultimately, this may lead to
the development of a cost-effective toolbox of techniques for assessing water quality
conditions and setting realistic remediation targets.

43

Generally, a comparison of the top and bottom portions of a sediment core is used
to establish the ‗before‘ (reference) and ‗after‘ (present) condition of the water body,
indicating the magnitude of change from reference (Dixit et al. 1999; Garrison et al.
2005). However, examining only the top and bottom of an undated core does not ensure
reaching ‗reference‘, nor does it lend insight to the biogeochemical dynamics of system
response to anthropogenic disturbances occurring in the rest of the core. Therefore, an
examination of the geochemistry from a complete core, particularly at high resolution,
offers the best potential for identifying the reference state and for understanding how the
system adapted through time.
Role of geochemistry to reference conditions
Investigating sediment chemical chronologies is a useful approach for comparing
contemporary and pre-disturbance environmental conditions, thus providing insight to the
ecological response of past, present, and future anthropogenic influence (Engstrom and
Wright, 1984; Smol 1992; Dean 2002; Smol 2002; Andersen et al. 2004; Reimann and
Garrett 2005). Establishing an elemental baseline (e.g. the chemical reference condition)
can differentiate natural inputs from anthropogenic inputs (by subtracting the
anthropogenic concentration from the pre-anthropogenic value) and thus establish the
reference condition concentration for an element. A firm understanding of how systems
temporally and mechanistically respond to stressors is important to assess environmental
health, and to target restoration efforts (Bennion et al. 1996; Engstrom et al. 2006). To
this end, profiles of sediment geochemistry lend insight about environmental response
that can facilitate an understanding of the trajectory of future environmental conditions.
The goal of this study is to examine the variability of system recovery as shown in
44

historic vs. modern geochemical enrichments, and how systems respond and adapt
through time, to identify geochemical response signals to specific events (e.g. logging),
as well as the influence of multiple, simultaneous anthropogenic stressors. Important to
note for this study is that both ecological degradation and recovery efforts are considered
human induced environmental change, and are equally significant under the umbrella of
understanding environmental dynamics in this study.
A conceptual example of systems with adapting reference conditions is shown in
Figure 2.1. This figure conceptually depicts environmental change in response to
multiple stressors, and corresponding ecosystem recovery resulting from implementation
of management strategies. The trends depicted on this figure can be described using a
generalized example of anthropogenic disturbance in aquatic ecosystems in the Great
Lakes region. The first major perturbation was the catastrophic impact of logging (stress
1), which disturbed the terrestrial environment and increased erosion (response 1). As
forest resources became depleted, the landscape began to ―recover‖ from logging and
erosion decreased. However, afforestation takes decades or centuries, and the legacy of
catastrophic clear-cutting had an effect on succeeding land cover. For instance, in a later
span of time, increases in agricultural and urban land uses (stress 2) has led to increased
nutrient inputs (response 2), which resulted in cultural eutrophication. This second stress
compounds on the first stress, and the system is unable to return to a pre-perturbation
state. Though environmental legislation in the 1970s mandated a nutrient flux decrease
to aquatic ecosystems from point-sources, non-point sources are more difficult to mitigate
and continue to influence the overall system. This results in the reference condition
adapting through time.
45

Management

Figure 2.1: Diagram depicting ecosystem response to various stressors and the
change in reference condition targets as a function of environmental legacy to
anthropogenic stress. Modified from Battarbee (1999) and Battarbee et al. (2005).

The stressor/response relationship is the foundation of the adapting reference
condition concept. This is particularly relevant in light of the magnitude and duration of
human disturbance, and the superimposed predictions of climate change. While it is a
challenge to interpret or predict what the long term recovery from environmental
stressors may look like, it is possible to define the system‘s prehistoric reference
condition, identify deviation from reference to determine ecosystem response to stressors,
and subsequently assess current ecological health. This study utilizes geochemical
profiles to determine if: 1) is it possible to identify stressor/response relationships when
multiple stressors are present at once? 2) are scenarios of modern ecosystem equilibrium
likely to resemble historical reference conditions due to persistent perturbations?, and 3)
is the adapted reference condition stable?

46

Approach
This study uses a multi-element geochemical approach to gain insight into the
temporal dynamics of the system. The role of geochemical reference conditions are
explored as a tool for understanding long-term ecosystem response to anthropogenic
activity. The state of the system before significant human perturbation will be examined
for trends that identify the environmental condition of the system under a two component
system (planetary and ecological – see chapter 1). Then, these conditions will be
compared to the subsequent state(s) of the three component system where the human
influence is considered. From this, change from reference will be determined to assess
system response and magnitude of change through time.

The hypotheses for this study are that, 1) in disturbed ecosystems the sediment
geochemistry has changed from a historic geochemical reference condition; and 2) that
due to the legacy of human perturbation, elemental and proxy group trends have not
obtained a new state of balance. To test these hypotheses, a sediment core from
Muskegon Lake, Michigan was analyzed for a suite of 23 elements. If true, then we
would expect the geochemical profiles to reflect changing trajectories during periods of
specific secular/human influence. Grouping elements allowed an examination of
ecosystem response using inter-elemental class relationships (e.g. terrestrial,
anthropogenic and carbonates) that identify ‗fingerprint‘ signals of specific human
perturbations (e.g. logging = increase in terrestrial sourced material) (Long et al. 2010).
In this way, the study could explore the effect of multiple stressors/influences, including
recent environmental regulations. Evaluating environmental response to perturbation
47

events improves the understanding of relationships among elements, among classes of
elements, and infers geochemical processes associated with a range of anthropogenic
activity (Smol, 2002; Bennion and Battarbee 2007). Importantly, the advanced insight
developed in this study can be exported to other systems influenced by human activity,
and are particularly beneficial to developing areas where similar issues are now
emerging.

2.2 Methods
A description of the study area, and core collection methods are described in
Chapter 1.
Laboratory Analyses
After collection, sediments were stored on ice and transported to MSU‘s Aqueous
and Environmental Geochemistry Laboratories where they were double homogenized,
placed in whirl-pak® bags and frozen. In preparation for chemical analysis, sediment
were freeze-dried in a lyophilizer, digested (U.S. EPA Method 3051) using nitric acid in
a CEM-MDS-81D microwave (Hewitt and Renyolds, 1990) and then filtered through an
acid-washed, E-pure (Barnstead International, Dubuque, IA) water rinsed 0.40 µm
polycarbonate filter (Nuclepore™). Sediments were analyzed for a suite of metals and
metalloids including Mg, Al, Si, P, K, Ca, Sc, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Se,
Sr, Mo, Cd, Sn, Ba, Hg, Pb, U. All samples were analyzed on inductively coupled,
plasma, mass spectrometer (ICP-MS) with hexapole technology (Micromass). Separate
analyses of freeze-dried sediments for total mercury were performed on a Lumex R-915+
48

Zeeman corrected atomic absorption spectrometer with an R-915 pyrolyzer attachment
(www.ohiolumex.com). This instrument and method is approved for mercury analysis
under EPA Method 7473. For all chemical analyses, analytical blanks and standard
reference material (NIST SRM 8407 Buffalo River Sediment) were utilized to maintain
quality control and quality assurance. Vanadium data were not collected for all samples
in this core. Results below the detection limits for each element were eliminated from the
data.
Chronology
Establishing core chronology for Muskegon Lake presented unique challenges
3 -1

since Muskegon Lake is a large fluvial lake with a mean annual inflow of 55.5 m s
(Carter et al. 2006), and the endpoint of the second largest watershed in the state of

Michigan (Steinman et al. 2008). Variable inputs make Muskegon Lake a complicated
system and therefore difficult to date, since the rate of supply of sediment was likely not
constant. As a consequence, several dating techniques were integrated to determine core
chronology.
The first approach was to use accelerator mass spectrometry (AMS) radiocarbon
technique to obtain a chronology. Two wood samples from the Muskegon Lake core,
from depths 110 cm and 101 cm, were sent for analysis to Beta Analytic Inc. in Miami,
Florida, USA. Samples below (older) these depths could not be included because they
did not contain viable material for

14

C testing. The resulting

49

14

C dates from 101 cm and

110 cm depths were converted to calendar dates (AD) through calibration with the
IntCal04 calibration curve using CALIB 5.0 software (http://calib.qub.ac.uk/calib).
The second chronological technique employed was a quantitative comparison of
anthropogenic elements from a

210

Pb dated short cores collected in the same depositional

basin; one collected in 2006 (43 cm) and one collected in 2003 (52 cm). The short cores
were collected as part of the Michigan State University/Michigan Department of
Environmental Quality Inland Lakes project (Parsons et al 2004; 2007). The

210

Pb

analyses took place at the Freshwater Institute, in Manitoba, Canada. The data were
validated using

137

Cs peak, derived from atomic-bomb testing that peaked in about 1963.

Elemental concentrations of anthropogenic elements in

210

Pb dated short cores (e.g.

stable Pb, Mo, Cd, Cr, and Hg) were used as ‗indicator elements‘ to correlate
peaks/trends in the long core for corroborating chronology. However, because the shorter
210

Pb dated cores did not reach prior to 1955, this method is only reliable in the top

section of the core. Merging these approaches, combined with an appraisal of event
based indicators from the watershed, such as logging, allowed for a qualitative
approximation of chronology.
Sediment chemical concentration analysis
Elemental concentration data from the Muskegon Lake core were
manipulated in several ways. First, geochemical data were divided into four classes
based on source and known environmental behavior (e.g., export, redox, anthropogenic
and productivity). Categorizing elements in this manner has been a useful approach to
50

infer physical, chemical and biological processes in other studies examining
environmental response to anthropogenic activity (e.g. Yohn et al. 2004; Long et al.
2010). In this study, terrestrial export proxies include Al, Mg, Ti and K that are
influenced by physical processes, such as erosion from the landscape (Dean et al. 2002;
Yohn et al. 2002; Long et al. 2010). Redox proxies include Fe, As and Mn that are
influenced by post-depositional diagenetic chemical processes (Mortimer, 1942; Berner
1980). Productivity proxies include Ca and P that are influenced by biological processes,
and are often used to infer primary productivity dynamics (Dean et al., 2002; Engstrom et
al., 2006). Anthropogenic proxies encompass a wide variety of trace elements, including
Cu, Pb, Hg, Cr and Zn, among others, which are influenced by human activities (Yohn et
al. 2002; 2004). Anthropogenic proxies can also facilitate an understanding of the source
and transport of pollutants (e.g. Yohn et al. 2002; Parsons et al. 2007).
Second, sediment geochemical profiles were analyzed to determine prehistoric
(geochemical) reference concentrations. Based on the historical timeline of human
activity in the Muskegon River Watershed (see Chapter 1) and the established chronology
of the core (see below), it was determined that samples below the 129 cm depth
conservatively preceded significant human influence for the ecosystem. Concentrations
of all samples below that depth were averaged to establish a reference concentration for
each element. Then, the deviations from those concentrations were followed throughout
other phases of the core. Specifically, these values were compared to peak
concentrations that, for many elements, occurred during a phase of significant human
influence. The reference values are also compared to modern concentrations that were

51

averaged from the top 8 cm of the core. Geochemical inventories were calculated to
using the following formula:

Inventory (µg/cm2) = (Σ [C * ((1 - φ) * ρ * d)])
Where:
C = concentration of chemical at an increment (mg/kg)
Φ = porosity (%)
ρ = bulk density (g/L)
d = thickness of increment (cm)

These comparisons determined not only the magnitude of human influence, but
allowed the current state of the system to be assessed within the context of pre historical
conditions to better frame an understanding of modern trends.
Geochemical profiles of specific, mainly anthropogenic elements (e.g. Pb, Hg,
Cd, Sn, and Mo) were considered in detail to evaluate the trajectory of human influence,
and the environmental legacy of human activity in the Muskegon area. Using the profiles
of known contaminants to Muskegon Lake allowed the analysis of the system response
to, and recovery from, particular perturbation events (e.g. logging, industry and
urbanization). From this, it was possible to determine how modern conditions deviate
from what is considered reference.

52

2.3 Results
Sediment core characteristics are discussed in Chapter 1, with Appendix I giving a 1
cm resolution sediment description. Porosity results are given in Appendix II. A
timeline of human activity in the Muskegon River Watershed is also given in Chapter 1.
Chronology
Results from two

14

C AMS radiocarbon analyses confirm the difficulty in

establishing a chronology for the Muskegon Lake core. The 110 cm depth sample
reported a conventional radiocarbon age of 280 years BP +/- 40 years; while the 101 cm
depth sample reported as 161.5 +/- 0.5 pMC, indicating that the sample had more

14

C

than did the modern (AD 1950) reference standard. The unit ―pMC‖ stands for ―percent
modern carbon‖ and is used when samples are part of a system respiring carbon after the
on-set of thermo-nuclear bomb testing (AD 1950s).
A comparison of the cores indicates apparent differences in sedimentation rates.
The analysis of

210

Pb dated short cores from Muskegon Lake reveal a sediment
2

accumulation rate of 1711 g/m /y (or 1.08 cm/y) for the 2003 Muskegon Lake short core
2

(Parsons et al. 2004) and 1607 g/m /y (or 1.02 cm/y) for the 2006 short core (Parsons et
al. 2007). Assuming a similar sedimentation rate in the 149 cm core, the sediment at the
bottom of the long core would be extrapolated to ~ AD 1868. However, it is evident
through event based dating that the core is older than AD 1868, since the bottom of the
core has ~30 cm of pre-logging sediment (identified by the presence of wood fragments,
indicating the logging era, between 98 – 118 cm depth). This suggests that the long core
was compacted during sampling, decreasing the sedimentation rate reflected by the core,
53

and thus capturing a longer temporal record. Therefore, the sedimentation rate is
believed to be nonlinear throughout the core, due to compaction and the multiple human
disturbances which altered the amount of material washed into the lake, such as erosion
from logging. For that reason, geochemical trends and peaks of select elements among
the cores were used to compare chronology of the long core.
Comparison of concentrations of Cd and Mo from the

210

Pb dated short cores

from Muskegon Lake in 2003 and 2006 show a correlation in trends and peak values to
the long core that could be used to establish chronology. Figures 2.2 and 2.3 show the
correlation comparison for trends and peaks of Mo, Cd, Pb, and Cr. Figure 2.2 highlights
the correlations using Mo and Cd. In both the 2003 short core and 2006 long core, Mo
has a peak that equates to ~1980 (shown by point A). Point B is represented in all cores
by a peak in Cd which corresponds to dates 1964 in 2003 and 1966 in 2006 short cores.
The 2003 short core reflects Mo decreasing dramatically at the ~34 cm depth in the long
core, corresponding to ~1955 AD, shown by point C. To support these correlations,
Figure 2.3 illustrates a comparison using Cr and Pb. Point A shows where Cr has a slight
decrease in concentration at ~4 cm depth in the long core, which is dated to 2005 in the
2006 long core (though this is too shallow in the core to be exempt from bioturbation
effects). All cores show a decoupling of Cr and Pb (at point B) that equates to ~1978 in
the 2003, and ~1974 in the 2006 short cores. Point C is positioned at ~32 cm depth in the
long core, and corresponds to 1962 and 1966 using a Cr peak in the 2003 and 2006 short
cores, respectively. Using these profiles, it was possible to establish a qualitative
chronology for the 2006 Muskegon Lake long core that is shown in Table 2.1.
54

Importantly, the long core does appear to reach a chemically ‗stable‘ background
concentration with regards to anthropogenic elements, whereas the shorter cores do not.
Additionally, pollen analysis from the 104 cm depth and below show that Pinus strobustype (white pine) is the dominant pollen type, which indicate that this level was prior to
logging. This interpretation is supported by the near absence of Ambrosia-type (ragweed)
pollen, which is a clear marker of disturbance that followed logging (Grimm, 1983).
These two pollen signatures in the core suggest that the bottom of the core captured the
reference condition, the pre-logging time prior to 1840. This indicates that the 2006 long
core reaches system reference conditions (assumed to be pre-logging, or pre-1840).

55

Concentration (mg/kg dry weight)
0.000
0

0

5.000
5

10.000
10

15.000
15

20.000
20

25.000
25

30.000
30

0

A
.

A
B

30
30

Depth (cm)
Depth(cm)

C

60
60

Cd
Mo

90
90
A. At ~13cm Mo has a brief peak. Equates
to ~1980 in 2003 short core.

120
120

150
150

B. At ~26cm Mo peaks. Equates to ~1964 in
2003 short and ~1966 in 2006 short.
C. At ~34cm Mo is decreasing. Equates to
~1955 in 2003 short core.

Figure 2.2a: Chronology comparision for Cd and Mo in Muskegon Lake 2006 long core.
56

B
.

C
.

2010

2003 Muskegon Lake short core

2010.0

2006 Title
ChartMuskegon Lake short core

2005.0

2000

2000.0
1995.0

1990

Year

Year

1990.0

A

1980

Cd
1970

Mo

1980.0

Mo

B

1985.0

Cd

1975.0
1970.0

1960

B

1965.0

C

1960.0

1950
0

5

10

0

15

2

4

6

8

10

Concentration (mg/kg dry weight)

Concentration (mg/kg dry weight)

Figure 2.2b-c: Chronology comparision for Muskegon Lake for 2003 and 2006 short cores (see page
58 for comparison with short cores).

57

Concentration (mg/kg dry weight)
0
0.000
0

0

100
100.000

200
200.000

300
300.000

400
400.000

500
500.000

600
600.000

A
.

A
B

C

Depth (cm)
Depth (cm)

30
30

Pb

60
60

Cr

90
90

120
120

A. At ~4cm depth in long core, Cr decreases
somewhat. This equates to ~2005 in short core.
B. At ~23cm depth in long core, Cr and Pb
decouple. This coresponds to ~1978 in 2003
and ~1974 in 2006 short cores.
C. Cr peaks at ~32cm depth in long core, which is
~1962 in 2003 and ~1966 in 2006 short cores.
Pb peaks at ~64cm depth in long core, which is
not represented in either short core.

150
150

Figure 2.2a: Chronology comparision for Cr and Pb in Muskegon Lake 2006 long core.
58

B
.

C
.

2010

2003 Muskegon Lake short core

A

2005.0

2000

2006 Muskegon Lake short core

2000.0
1995.0

Year

1990

Year

2010.0

B

1980

1990.0
1985.0

Pb

1980.0

Cr

1970

1975.0

C

Cr
B

Pb

1970.0

1960

C

1965.0
1950

1960.0
0

100

200

300

400

500

600

0

Concentration (mg/kg dry weight)

100

200

300

400

Concentration (mg/kg dry weight)

Figure 2.3b-c: Chronology comparision for Cr and Pb sediment geochemistry in Muskegon Lake 2006 long core.

59

Table 2.1: Chronology summary for Muskegon Lake 2006 long core.
Depth
(cm)
0
4
10
13
15
20
23
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
100
105
110
115
120
125
130
135
140
145
150

Chronology
Date (AD)
2006
2005

Method

Watershed event
year/decade

Cr

2004 flood

1980

Mo, Cd

1986 flood

1976
1965
1960
1955
1951
1947
1943
1939
1935
1931
1927
1923
1919
1915
1911
1897.5
1885
1872.5
1860
1847.5
1835

Pb, Cr
Mo, Cd
Cr
Mo
extrapolation
extrapolation
extrapolation
extrapolation
extrapolation
extrapolation
extrapolation
extrapolation
extrapolation
extrapolation
no wood
Wood
Wood/charcoal
Wood/charcoal
Wood
Wood
no wood

60

WWTP installation
Newaygo dam out (1969)
US131 opens(1964)

WWII
Dust Bowl
Great Depression

WWI
Start of industry/
logging
logging
logging/1874 fire
logging
logging
Pre-logging

Sediment geochemistry
The full dataset of sediment geochemical concentrations for the Muskegon Lake
core is listed in Appendix III. Specific geochemical patterns are reported below, with
trends detailed by proxy group, and individually profiles as relevant. The elemental
concentrations reveal multiple anthropogenic perturbations (e.g. including logging,
hydrological perturbations, and industrialization in the watershed). The core also
captures geochemical response to management efforts aimed at mitigating human
disturbance, including the Clean Air and Clean Water Acts in 1970. Specifically to the
MRW, the 1973 installation of the WWTP shows notable influence on the geochemistry
of the core. Recovery due to mitigation practices indicates a shift to a new geochemical
state which is different from the apparent reference concentrations. Results of the
chemical trends are reported and discussed below.
Indicator proxy groups
Categorizing elements to indicator proxy groups allowed different geochemical
relationships and processes to be discerned. The redox indicator group, consisting of As,
Fe and Mn shown in Figure 2.4 indicate variability in concentrations throughout the core.
The profile trends indicate that the bottom of the core has more variable concentrations
than in the middle and top. From 30-90 cm depth, the proxies appear the most coupled,
which may indicate a change in oxygen conditions in the lake. Iron and Mn have the
most similar trajectories for much of the core as compared to As, with the exception of
the very bottom. Important to note is the offset peaks of Mn and Fe at the top of the core
which could indicate a modern redox boundary.
61

A.

B.

C.

Figure 2.4a-c: Concentration profiles of the redox proxies.

Elements under no or low influence of redox dynamics include the terrestrial,
productivity, and anthropogenic groups. The trends of Al, K, Mg and Ti, shown in
Figure 2.5, were used to infer terrestrial export from the landscape. Overall, their profiles
show temporal variability in concentrations, which may be due to the flow through
hydrology of Muskegon Lake. Magnesium and Al are coupled through most of the core
(suggesting a similar source and/or similar transport mechanism). Potassium also appears
coupled with Mg and Al for much of the core, but becomes decoupled in the top 5 cm as
K decreases and Mg and Al increase. Titanium is often used to infer terrestrial export,
62

though in Muskegon Lake the relationship with other terrestrial elements is not strong.
All terrestrial elements reflect a decrease in normalized concentration beginning at 118
cm depth. This ‗dip‘ is followed by increasing concentrations for ~10 cm.

A.

B.

C.

D.

Figure 2.5a-d: Concentration profiles of terrestrial proxies.

Productivity indicators, P and Ca, shown in Figure 2.6 have normalized
concentrations that are similar through most of the core. Between 120 and 95 cm depth,
they behave similarly, much the same as the terrestrial and redox indicator proxies. The
elements appear to behave in a similar manner between 90 – 120 cm depth as they begin
to increase in concentration. These two elements continue to move toward peak
concentrations, and track one another until ~30 cm depth. A distinct decoupling occurs
63

at ~18 cm, which continues until about the top 3 cm of the core when they have similar
trajectories again.

A.

B.

Figure 2.6a-b: Concentration profiles of productivity proxies a) calcium b) phosphorus.

Geochemical reference concentrations
The non-redox group with the most distinct trends is the anthropogenic proxy
group. Select elements from this group, Cd, Cr, Hg, Pb and Sn, are shown in Figure 2.7.
The stratigraphy of these elements are divisible into three zones, identified as ―G‖ zones,
for geochemical stratigraphy, which are illustrated by grey envelopes (Figure 2.7). Zone
GI is below the 120 cm depth where the geochemical profiles show relativley aligned and
parallel trends with near constant low concentrations. These are considered to be the
64

reference concentrations because they are relatively parallel and low concentrations. The
beginning of zone GII, identified by the first observed deviation from the reference
concentrations, occurs at about the 118 cm depth. At this depth, the normalized
concentrations of anthropogenic proxies decrease slightly, then increase to a small peak
at about the 105 cm depth, and decrease again at 97 cm. From the 97 cm depth, the
profiles show a generally increasing trend, with many elements having peak
concentrations before the 60 cm level. For example, Cd and Hg peak at ~75 cm, and Pb
and Sn peak ~ 64 cm. All elements decrease at 60 cm, but generally increase again
between 45 and 35 cm. The exception of this is Cd, which continues to decrease slightly,
and Cr that peaks at 33 cm. Between ~33 cm to 8 cm, concentrations of Cd, Cr and Sn
decrease significantly; though Pb and Hg do not consistently decrease until the 23 cm
depth. Mercury increases again with peaks at 19 cm and 3 cm, but the general trend is of
decreasing concentrations. Zone G3 is between 25 cm to the top of the core. In this
zone, elements are observed to have the same decreasing trajectory. Notably, all
elements also show a small increase to a peak ~20 cm. Though concentrations are varied
in the top 8 cm of the core, there is an overall increasing trend in concetnrations of most
anthropogenic elements to the surface.

65

2005
1960

Year

1935

1910

1835

Figure 2.7: Concentration profiles of normalized anthropogenic proxies, delineated into
geochemical zones.
Geochemical inventories associated with human activity
Anthropogenic inventories were calculated for select elements from Muskegon
Lake. The values are in µg/cm², and convey the mass of the chemical that has been
added to the lake as the result of human activity. Results for anthropogenic inventories of
Hg, Pb, Sn, Mo, Cd, Cr, Cu and Zn are shown in Figures 2.8a and 2.8b, and are plotted
next to an abbreviated list of dated MRW events. With the exception of Mo, it is
observed that the largest proportion of the chemical inventories occur in the top 90 cm of
the core after the initial departure from reference concentrations at ~118 cm depth, which
approximately dates to the 1840s and 1850s, when logging began and the Newaygo Dam
was built (Alexander 2006). Molybdenum inventory increases later in the core, at ~65
cm depth, with a sharp increase and peak between 23-28 cm depth, corresponding to
66

dates in the late 1960s and early 1970s. All elements show a decreasing trend from their
zone G3 peaks, with slight episodic increases at 15 cm and 3 cm.

67

Year

Figure 2.8a: Geochemical inventories of anthropogenic elements.

68

Watershed Event

2004
1986
1973
1960s
1940s
1930s
1910s
1911
1900s
1901
1874
1854
1830s

Flood
Flood
Tertiary treatment plant
US 31 opens and Newaygo Dam out
WWII
Great Depression and Dust Bowl
WWI
Last log run on Muskegon River
Rogers and Croton Dams built
Muskegon Industrial Age begins
City of Muskegon fire
Newaygo Dam built
MRW logging begins

Year
2004
1986
1973
1960s
1940s
1930s
1910s
1911
1900s
1901
1874
1854
1830s

Figure 2.8b: Geochemical inventories of anthropogenic elements.

69

Watershed Event
Flood
Flood
Tertiary treatment plant
US 31 opens and Newaygo Dam out
WWII
Great Depression and Dust Bowl
WWI
Last log run on Muskegon River
Rogers and Croton Dams built
Muskegon Industrial Age begins
City of Muskegon fire
Newaygo Dam built
MRW logging begins

Variability of recovery demonstrated by historic v. modern enrichment
Sediment concentrations of all elements were evaluated to determine historic
geochemical reference concentrations to compare with modern concentrations. Not all
groups showed indications of geochemical reference, as many redox and terrestrial
elements show high variability in the bottom of the core, indicating natural variability not
conducive to determining reference concentrations. However, as reported above,
productivity proxies, and especially anthropogenic proxies, reveal reference
concentrations that do indicate pre-perturbation conditions were reflected in this sediment
core. Therefore, profiles of these proxy groups are particularly useful to evaluate
environmental change from pre-perturbation conditions, and to assess the state of the
modern system conditions.
Geochemical concentrations of sediment deeper than 129 cm were considered
pre-perturbation. This sediment conservatively precedes significant logging, settlement
or other significant human influences in the watershed. Table 2.2 summarizes
geochemical results by illustrating: a reference concentration average for select elements;
the depth where trajectories of elements may change; the peak concentration; the total
geochemical inventories (ug/cm²) of anthropogenic elements (Sn, Cd, Pb, Mo, Cr, Zn,
Cu, and Hg); and nutrient indicator P, since the advent of human influence. Results
shown include all elements, and are grouped by proxy classes slightly different than those
reported above in that redox related indicators are grouped between anthropogenic and
productivity, because of duel influences; and productivity elements include Sr and Ba as
they can be influenced by productivity dynamics. A group named ‗other‘ includes
70

elements without a clear association to any group. Though there is an overlapping nature
of many of the elements (e.g. Mo and As are redox sensitive, but also have anthropogenic
sources, and P, which is most commonly a nutrient, is also redox sensitive), this table
puts elements in their dominant group.
Results for select elements in table 2.2 (e.g. Fe, U, Mn, Ca, Ba, Sr, Rb, Co, Mg,
K, Al and Ti) are not complete due to significant variability and unclear trends in
concentration profiles. With the exception of P, inventories for these elements and nickel
are not complete for the same reason. Excluding the geochemical change that occurs
between 115 and 120 cm depth due to logging, the onset of increasing concentrations
varies by element. As seen in figures 2.8a and b, concentrations of many elements (e.g.
Cu, Hg, Pb, Sn and Zn) begin to increase between 90 and 96 cm, while Cr and Mo are the
last at 80 cm and 65 cm respectively. This variability is assumed to be attributed to
differences in source that will be discussed later in this chapter. The depth of the peak of
anthropogenic elements varies greatly in the range of 22 – 76 cm. Again, a function of
source that will be later discussed. Total elemental inventories are also reported, which
lists the total mass of the element deposited to the lake to date. The greatest inventory is
for P (101690 µg/cm²) and the smallest is Hg at 35 µg/cm². Peak enrichments were
calculated by dividing the peak concentration by the reference concentration. Results
show that Sn has the most significant enrichment at 92 times the reference concentration,
while Cd, Pb, and Mo are also >30 times enriched over reference. Peak enrichments
were compared to modern sediment enrichments, calculated from averaging
concentrations from the top 8 cm and dividing by the reference concentration. It is
71

observed that these values are much less than peak enrichments, thus indicating some
degree of system response/recovery. However, the modern enrichments do not return to
1, a value which would indicate concentrations similar to reference. This indicates that
modern recovery, although significant, does not resemble reference.

72

Table 2.2: Geochemical Compilation

Terrestrial

Other

Productivity

Redox
related

Anthropogenic

Proxy
class

Depth
Reference of first
average increase
Element (mg/kg)
(cm)

depth
of
peak
(cm)

Peak
Peak
Total
Modern Modern
Status of
conc.
Enrich- inventory average Enrichmodern
(mg/kg) ment
(µg/cm2) (mg/kg)
ment
concentrations

Zn
Cu
Cr
Cd
Hg
Pb
Sn
Ni
Mo
Fe
U
Mn
As
P
Ca
Ba
Sr
Rb
Co
Mg
K
Al

119
15.23
29.18
0.38
0.04
10.67
0.06
21.37
0.37
52556
0.776
1542
5.24
860
31427
156
37.10
18.41
9.53
18371
1645
16466

95
94
80
90
95
96
90
96
65
---96
95
-96
96
------

76
77
33
77
75-76
64
61
22
25
---21
45
7
74
7
93
93
54
105
54

1275
161
506
24.12
0.26
324
5.36
44.58
10.84
---19.13
4885
106254
443
118
25.89
11.62
24736
2323
24222

10.66
10.59
17.36
62.85
6.07
30.37
92.38
2.09
29.03
---3.65
5.68
3.38
2.83
3.18
1.41
1.22
1.35
1.41
1.47

21638
5486
16043
870
35.59
13304
165
-181
----101690
---------

161
52.38
48.89
2.05
0.15
57.47
0.48
20.57
1.10
32286
0.790
2426
11.53
1514
86178
181
103
14.44
7.15
14742
1563
12540

1.35
3.44
1.68
5.34
3.56
5.38
8.34
0.96
2.95
---2.20
1.76
2.74
1.16
2.79
0.78
0.75
0.80
0.95
0.76

Semi-stable
Semi-stable
Stable
Stable
Semi-stable
Semi-stable
Semi-stable
Semi-stable
Semi-stable
Not stable
Semi-stable
Not stable
Not stable
Not stable
Not stable
Not stable
Not stable
Semi-stable
Not stable
Not stable
Not stable
Not stable

Ti

47.63

--

12

98.18

2.06

--

43.55

0.91

Semi-stable

73

2.4 Discussion
Chronology
It is possible to reconcile discrepancies with the results of two AMS analyses,
though this method is ultimately not that useful for establishing the chronology of this
sediment core. The results indicated a 200 year difference in 9 cm of sediment, which is
unlikely given the documented high sedimentation rate in Muskegon Lake (Parsons et al.
2006). Instead, it is likely that the 101 cm depth sample was material that got pulled
down from shallower in the core during sampling (Darden Hood, personal
communication, 2008). It was also concluded that the 110 cm sample, which reported a
280 ±40 year age, was in fact that old - despite it being deposited approximately 145
years ago. Conceivably, this occurs if a wood sample from the inner ring of a tree
harvested from an old growth forest was deposited during the logging era in the
Muskegon River Watershed. To further support the event based dating, abundant ―wood
chip‖, ―saw dust‖, and ―charcoal‖ type material was identified between 94 and 115 cm
depth, and was interpreted as deposited during the logging era. According to Wells
(1978) and Alexander (2006), clear cut logging is event dated to AD 1830s – 1900 in the
Muskegon River Watershed. Overall, chronology established using geochemical
correlations from the

210

Pb dated cores, as well as watershed events (e.g. onset of

industry, etc.) offered good indicators for qualitative dating.
Proxy group patterns represent a geochemical reference state
Grouping elemental geochemistry into indicator proxy groups proved useful in
interpreting the Muskegon Lake core. Though the redox and terrestrial proxies were not
74

as valuable as productivity and anthropogenic proxies at identifying geochemical
reference conditions, they did provide evidence for perturbation events and specific
system dynamics. The redox proxies did reflect a coupling/decoupling dynamic,
seemingly in response to human influences; while the terrestrial proxies were variable
throughout the core, likely the result of flow-through dynamics of the lake system. Taken
together, the patterns of the proxy groups represented the reference state of Muskegon
Lake. Specific results of how the groups tracked perturbation response are discussed
below.
Overall, the terrestrial proxies were unclear in identifying reference conditions, as
the concentrations of the elements in the bottom of the core (identified to be reference)
were highly variable (refer to Figure 2.5). This is likely due to Muskegon Lake being a
large drowned river mouth system that has such significant inputs that the record
becomes convoluted. However, these is a similarity to the trends for Al and Mg,
indicating that they have similar source or transport mechanism (e.g. input from
Muskegon River and other tributaries). Potassium and Ti were not as closely coupled to
Al and Mg, though the K profile did show a similar trajectory to Al and Mg for most of
the core, with the exception of the top 5 cm. Titanium was least associated with the
terrestrial proxies overall, instead showing an increase in concentration during the
industrial phase (see Figure 2.11) of the core, as well as high variability in the top 25 cm
of the core, suggesting a significant anthropogenic influence in this system. Due to
variability, it may be useful to consider the mean concentration of these elements can be
used to establish a reference state.

75

Important to assessing geochemical response to perturbation events in this system
were the trajectories observed during the logging era. Terrestrial elements followed
similar concentration changes during this time (~90-120 cm depth), suggesting that their
concentrations were influenced by similar process. An unexpected decrease in
concentrations occured before and after significant logging. Possible explanations of this
decrease include the following. First, it is possible that decreased sediment influx
resulting from altered hydrology, and thus the flow of material to Muskegon Lake, from
the installation of Newaygo Dam may have decreased the relative concentrations of
terrestrial elements. The Newaygo Dam was constructed in 1854 to power the Big Red
Mill, and was the first major dam on the Muskegon River (Alexander 2006). Moreover,
Rogers Dam, near Big Rapids was installed in 1906, and Croton Dam, also near
Newaygo, was built in 1907; both correspond to points in the core where there decrease
in concentrations of the terrestrial proxies. The latter two dams are farther up in the
watershed, but could still have a substantial influence on sediment flux.
It is a possiblility that terrestrial elements were diluted due to an increase in the
proportion of leached (metal deficient) upper mineral soil horizon layer following abovenormal erosion due to initial logging (Davis et al. 2006). The subsequent increase in
concentrations would then be due to a new stage of erosion reaching the deeper mineral
rich soil, followed by another decrease when large scale logging ceases in the late 1890s
and early 1900s. The timing of the installation of the dams correspond closely to the
onset of logging in the watershed, making it difficult to untangle the stressor/response
trajectory.

76

Coupling/decoupling trends of productivity proxies may indicate a regime shift
Human activity appears to be correlated with productivity proxies in the
Muskegon Lake core, as depicted by coupling and decoupling of the elements. Figure
2.9 shows phases of human activity that correspond to zones of geochemical trends
delineated above for anthropogenic elements (see Figure 2.7). Phase GI reflects the preperturbation conditions that were identified by P and Ca concentrations that fluctuate
around a mean concentration in the bottom 30 cm. Core chronology confirms this depth
precedes significant human influence and is considered the system‘s reference state; and
the observed variability in concentrations indicative of Muskegon Lake‘s inherent flow
through dynamics. The pre-perturbation segment of the core does not reflect a clear
relationship between Ca and P until ~118 cm depth, which coincides approximately with
the start of logging in the watershed; this depth also marks the early part of Phase GII, the
anthropogenic phase. Both elements show a decreasing trend near this depth, though
there is an offset with the trend as P begins to decrease first at 125 cm depth, then Ca
later at 118 cm. The decrease in P that precedes Ca may indicate a process related to
nutrient dyanamics or terrestrial inputs. While other studies (e.g. Long et al. 2010) have
reported a relationship between Mg and P that indicates a terrestrial source, this core does
not reflect a coupling of this pair. As such, this is unlikely the result of variable
terrestrial inputs as discussed above and more likely reflects in-lake processes play a
greater role in driving P biogeochemical dynamics. Productivity is a major factor of inlake processes, which can be examined in the patterns of Ca and P after logging; and
through the correlation in the trends of Ca and Mg through most of the core.

77

Productivity Indicators
Productivity Indicators
0

2005

0.00

Phase GIII

Depth(cm)
Depth (cm)

30

1960

60.00

60

1935

90

1910

90.00

Year

30.00

Phase GII

1835

120

120.00

Ca

150
0.00
0

P

Phase GI

150.00

0.10
0.1

0.20
0.2

0.30
0.3

0.40
0.4

0.50
0.5

0.60
0.6

0.70
0.7

0.80
0.8

0.90
0.9

1.00
1.0

Normalized Concentrations
Normalized Concentrations

Figure 2.9: Geochemical phases of productivity proxies.

From a core depth of 90 to 25 cm, the productivity proxies track one another and
seemingly reflect the response of changing nutrient conditions in Muskegon Lake, as
concentrations increase in this portion and are considerd consistent with increasing
productivity. Phosphorus and Ca have aligned trajecories in this segment (also part of
phase GII) attributed to increased photosynthesis resulting from increasing nutrient
inputs. This occurs because increasing water column photosynthesis will consume CO2
and increase pH. Higher pH values will cause more CaCO3 to precipitate, resulting in
increased Ca concentrations in the sediment profiles. Moreover, increased organic matter
due to increased photosynthesis will increase the particulate P, which is why these
elements together are considered proxies for productivity. An important caveat for
78

interpreting P sediment profiles is that in some systems, anoxic bottom water can release
P from sediments to overlying water. While this is not believed to be a factor in
Muskegon Lake due to short residence time, historical and seasonal anoxia have been
reported and may influence the sediment accumulation of P (Anderson et al. 1993).
Based on the relationship observed between P and Ca in this segment of the core, the
increases are more likely related to productivity than redox processes. However, the
decoupling of Ca and P at 18 cm depth deviates from this assumption.
At the 20 cm depth, Ca and P are inversely coupled, as P concentrations decrease
and Ca concentrations increase. This depth is the start of Phase GIII, which is considered
to be the ―recovery phase‖ since it corresponds to environmental regulatory efforts.
These efforts were designed to reduce nutrient and contaminant loading to Muskegon
Lake.
The Muskegon Waste Water Treatment facility was installed in 1973 (at ~23 cm
depth), which is near the time that the productivity elements shift to inversely coupling.
Steinman et al. (2008) reported that this facility was successful in decreasing nutrient
imputs as water column TP values declined from 68 - 27 µg/L from 1972 to 2005.
Phosphorus concentrations would be expected to decrease with reduced inputs.
However, P concentrations begin to slowly increase at 10cm, and may reflect an increase
in non-point source nutrients and/or inputs from increased urbanization (see Figure 1.4).
The P concentrations in the top 5 cm decrease, but caution should be noted in interpreting
this due to the before mentioned redox sensitivity of P; though Ca decreases in the top 57 cm as well, so it is possible this indicates the productivity elements are again coupling
and re-establishing a relationship following ‗remediation‘ and an oligiotrophication
79

processes (Anderson et al. 2005). Biological proxies in the next chapter will help resolve
that unclear interpretation. A comparison of Ca with Ba and Sr, other productivity
related elements often correlated with Ca, show related trends throughout the core.
However, there is no relationship between them at the top of the core; though Sr is
coupled with Ca, indicating similar processes/behavior.
Freedman et al. (1972) measured surface and bottom TP values, and reported that
they were ~60 and ~80 µg/L, respectively. These measurements correspond to decreases
in water column P documented by Steinmann et al. (2008). The segment between 3 and
18 cm where the productivity proxies are decoupled may reflect a period where the
system is responding to changing nutrient conditions.
Geochemical sub-phases reflect human activities
A distinct response to the effects of human stressors was reflected by the
anthropogenic proxy group. Sediment geochemical profiles for the elements in this
group show consistent low concentrations among all elements in the bottom 30 cm of the
core. These concentrations are indicative of the ―reference state‖ before the human
component significantly influenced biogeochemical processes (see Chapter 1).
Consequently, these concentrations are the baseline against which later concentrations are
assessed. This phase is represented by Phase GI in Figure 2.10.
The next phase is GII that begins with GIIA at the 118 cm depth, when
concentrations of many elements, not just the anthropogenic, respond to logging. Phase
GIIB further illustrates human induced environmental degradation as high concentrations
of anthropogenic elements reflect the response to intense industrialization dominate.
Many of the contaminants depicted here came from point source discharges or surface
80

runoff as industry replaced logging. This activity continued through WWI and until the
Great Depression. During the Great Depression, the area surrounding Muskegon Lake
experienced a decline in industrial production which is marked in the sediment core by
decreasing concentrations of anthropogenic elements near the 60 cm depth. Following
the Great Depression, demand for industrial materials again increased due to WWII,
which is reflected by an increase in anthropogenic elements in phase GIIC. Many of the
anthropognic concentrations are variable, though remained high until a slight decrease in
the late 1960s when a decline in economic conditions decreased much of the industrial
productity of the region. Further decreases in inputs of anthropogenic elements are
observed in the 1970s after environmental mitigation was legislated and reduced inputs of
certain pollutants, indicating the start of the next phase beginning at ~25 cm depth.
The most recent phase is GIII that occurs in the top 25 cm and represents an era of
environmental regulation. Concentrations of anthropogenic indicators greatly decrease in
this phase. Isolated increases at ~15 and 3 cm depths may represent major floods in the
watershed in 1986 and 2004, respectively. Or, the slight increasing trend in the top 8 cm
may indicate an increase in non-point sources, or the environmental legacy from intense
pollution (being flushed in as it erodes from the landscape). Consequently, this segment
of the core is important to understanding system response under management efforts.

81

Select Anthropogenic Indicators
0

0.00

2005
GIII

1960
GIIC

60

1935

60.00

90

90.00

Year

Depth (cm)
Depth(cm)

30
30.00

1910

GIIB
GIIA

120

1835

120.00

Cd

Cr

Hg

Pb

Sn

GI

150

150.00

0

0.00

0.1

0.10

0.2

0.20

0.30
0.3

0.40
0.4

0.5

0.50

0.6

0.60

0.70
0.7

0.80
0.8

0.9

0.90

1.0

1.00

Normalized Concentrations
Normalized Concentrations
Figure 2.10: Concentration profiles of normalized anthropogenic proxy group elements.

Specific elements lend insight to specific watershed activity
Human influence in the Muskegon River Watershed began with the onset of
massive deforestation in the watershed. The human settlements established from the
logging era set the stage for growth of industry, as many lumbermen began to foresee the
need to diversify as the forest became depleted. Before the turn of the 20th century,
several companies began to open mills and foundries as lumbermen in Muskegon exerted
their interest in diversification. In the early 1880s, the Lumbermen‘s Exchange, a trade
and pricing group, reorganized as the Muskegon Board of Trade. The board inaugurated
a newspaper advertising campaign to promote Muskegon as a place for industry. They
brought two new railroads into the area and stressed the need to establish nonlumberrelated industries. This strategy worked and several firms were started with capital from
82

lumbermen or with support from the Board of Trade. These companies included
Chemical Fire Company, Muskegon Cracker Company, Sargent Manufacturing
Company, Chase Brothers Piano, and the Muskegon Rolling Mills (Kilar 1990). The
accumulation of many anthropogenic elements can be compared directly to these
companies. Notably, enrichments for different elements occur at different depths,
indicating different sources and pathways for different elements.
According to a book on industrial activity in 1900 (American Iron and Steel
Institute, 1904), industry was becoming established in the Great Lakes region at the turn
of the century. For example, as of 1 November 1901, Michigan had a total of 16 Rolling
Mills, Steel Works, Tinplate Works etc., while Ohio and Pennsylvania had 855 and 1478,
respectively. This trend illustrates the movement of industrialization from east to west,
similar to the logging movement decades earlier. The American Tin Company, also
owned by the United States Steel Corporation, had the first black plate mills in the
Muskegon Works complex, situated on the shores of Muskegon Lake. Added in 1899,
this facility housed 6 double heating furnaces, 2 annealing furnaces, 6 single pair
furnaces, and six 26-inch hot and five 24-inch cold mills. Annual capacity in 1902 was
12,000 gross tons of iron, steel black plates for tinning, tin and terne plates (terne plates
are similar, but the ‗bath‘ is not tin, but lead, and therefore not shiny but dull, hence
terne). Fueling the facility was coal and manufactured gas (American Iron and Steel
Institute, 1902). Figure 2.8a shows the profile for Tin, with early increases being
attributed to the American Tin Plate Company.

83

Continental Motors was another early company that contributed to industrial base of
Muskegon. Opening in 1905, it is plausible that this company contributed to a significant
portion of the metals in Muskegon Lake sediment. They built industrial engines, and bus
and truck motors and increased production with military vehicles in WWI. At one time,
Continental Motors produced nearly 90% of US aircraft engines with less than 75
horsepower, though the Great Depression of 1930s greatly decreased the demand for this
industry. After the Great Depression, Continental Motors built engines for tanks, landing
craft and other military vehicles for WWII. Also, beginning in 1943, they made Rolls
Royce Merlin engines used in the P-51 Mustang. In the late 1960s, Continental was sold
twice, and the downtown Muskegon Plant was removed in 1993. Chromium (Figure
2.8b) remains a common element used in Muskegon industry, and continues today in
aspects of manufacturing. Specifically, the Sealed Power Division of the SPX
Corporation which is a metal finishing facility in Muskegon that reports its hard
chromium electroplating plates had to comply with compliance standards by January
1997 (http://www.nmfrc.org/epadocs/int1996f.htm ).
Cannon Muskegon opened in 1969 and is currently still operating. This company
is a metallurgical specialist of premium-grade alloys for medical and aerospace casting
applications. The website for this company lists Ni, Co, Cr, Ti, Al, Cu and Mo as
elements used in their industry. It is evident from the profile of Mo (Figure 2.8a) that it
did not have significant accumulations until later, which is different than most other
anthropogenic elements (e.g. Pb, Sn) and suggests it was not heavily used until the late
1950s and peaked in the late 1960s/early 1970s.

84

Evidence of adapting reference conditions
A goal of this study was to shed light on how a system responds and adapts to
various human perturbations. The geochemical trends within indicator groups lend
insight to the degree and trajectory of change. Though inferring if a system is recovering
from anthropogenic perturbation is challenging with a single proxy type (e.g.
geochemistry), the geochemical patterns for many anthropogenic elements in Muskegon
Lake sediment do become lower in concentration again near the top of the core. This
may be interpreted to indicate a return/trend towards a historic reference state; however
elemental concentrations are, in many cases, far from pre-disturbance concentrations.
The modern concentrations and trends for many elements (e.g. Cd, Sn, Hg, Pb,
Cu, and Mo) are generally much lower than peak enrichments, though still above the
reference concentration (Table 2.2). This suggests an adapting reference condition,
where the modern condition, because of the magnitude of human perturbation, does not
resemble the reference state. Profiles for Sn, Cr and Mo specifically illustrate the
trajectory of change for anthropogenic inventories, and depict concentrations near the top
of the core that show the geochemical response to regional and local management efforts
to reduced loading of pollutants. While Figure 2.11 (below) depicts the adapting
reference condition as related to the normalized profiles of Pb, Cr, and Sn, that each have
a specific role in reconstructing Muskegon Lake influences, but reinforce identification of
85

multiple stressors. This figure is meant to represent, using real data, the concept
presented in Figure 2.1, which was modified from Battarbee et al. (2005). The arrow for
stress 1 reflects system response to logging perturbation; the concentration of Pb, Cr and
Sn in the figure increase then decrease, though the decrease does not reach the reference
conditions baseline. The next stress (2) is the advent of industrial activity and WWI
engine production in the Muskegon area, and shows a very significant increase of
concentrations in the core. Again, the concentrations decrease when the Great
Depression halts much of the industrial activity – though, the concentrations do not reach
reference, nor do they decrease to the post-stressor 1 concentration, possibly because the
next stressor occurred too quickly for a more substantial/complete recovery. In response
to stress 3, concentrations increase again, corresponding to WWII military industry and
later, continued automotive related production in the region. Tin and Cr have a greater
enrichment with this stress, likely the result of direct industrial activity in the Muskegon
area. The recovery segment observed is due in part to an economic downturn in the
region, as well as environmental legislation that mandated a decrease in atmospheric and
terrestrial inputs.

86

Figure 2.11: Adapting reference conditions using Muskegon Lake geochemical data.

87

2.5 Conclusions
This chapter applied the reference condition concept to a paleolimnological study
using geochemical profiles and trends of individual elements and proxy groups from a
highly perturbed lake system. The investigation predicted that modern ecosystem
equilibrium was not likely to resemble historical reference conditions. An evaluation of
the post-disturbance state of the system relative to pre-disturbance (with consideration of
the influence of management strategies) supported the hypothesis. The results showed
that, for many anthropogenic proxies, what may be considered the reference
concentration has adapted through time with the overprint of multiple stressors.
Policy mandates have dramatically reduced the loading of nutrients and metals
and improved the water quality of Muskegon Lake. The current geochemical conditions
in the lake core reflect significant recovery from high concentrations of many elements.
However, concentrations have not returned to the identified ―reference‖ values but reflect
an adapted reference state as evidenced by geochemical profiles and the trends within
proxy groups. Specific differences in geochemical profiles within the proxy groups (e.g.
anthropogenic and terrestrial) reveal watershed scale sources and are linked to historic
human activity in Muskegon, MI, USA.
Due to the adapting nature of the geochemical reference condition evidenced by
this study, it is suggested that modern remediation targets need to consider the legacy of
human impacts and further be cognizant of emerging stressors. While addition proxy
groups (e.g. terrestrial and productivity) were useful in untangling biogeochemical
response, particularly in the top of the core when productivity proxies become decoupled,
88

further lines of evidence (e.g. biological proxies) would be useful to validate those
potential regime shift interpretations. Therefore, based on these results, there appears to
be a need to investigate additional constituents of ecological system components to
evaluate system response. Select elements reliably track anthropogenic activity and/or
are able to indicate a specific biogeochemical process. Therefore, integrating biological
proxies could help gain a better understanding of environmental processes resulting from
anthropogenic influence.

89

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90

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CHAPTER 3
IDENTIFYING PALEOECOLOGICAL REGIME SHIFTS USING
FRESHWATER DIATOMS AS PRIMARY PRODUCTIVITY INDICATORS

Abstract
Understanding primary productivity in a system can lend insight to overall
biogeochemical dynamics, as it is an essential part of aquatic ecosystem function. This
chapter uses fossil diatoms to investigate shifts in primary productivity habitat to better
understand the role of the aquatic biological response to environmental change. Based in
part on the geochemical results presented in Chapter 2, and continuing with the
hypothesis that disturbances from human activities have been so intense that ecosystems
cannot fully return to a pre-disturbance state (particularly with the influence of emerging
stressors), this chapter addressed the following questions: 1) how do specific
environmental changes affect diatom assemblages, 2) what dictates the dominant primary
productivity habitat ratio (planktonic:benthic), 3) what is the mechanism within systems
that may shift that ratio? Fossil diatoms in a sediment core from Muskegon Lake, MI
were used to assess these questions. Each taxon was evaluated individually for specific
ecological preference, then, taxa were grouped as benthic or planktonic to investigate
broader changes in the productivity regime of the system. The Muskegon Lake core
showed variability with the 27 “common” taxa, revealing distinct changes in water
quality, and a recent shift in the dominant habitat of primary production. The hypotheis
was supported with three temporal phases identified using fossil diatom data: 1) predisturbance, 2) anthropogenic disturbance, and 3) recovery. Specific taxa indicated
increasing nutrient conditions (e.g. Fragilaria spp.), with additional restructuring
96

occurring in response to the Waste Water Treatment Facility installation, indicating that
monitoring of primary productivity trends is critical to ecological health assessments.

3.1 Introduction
Problem
The intensity of global environmental change has been extraordinary in recent
centuries, adversely affecting ecological systems worldwide (Ricciardi and Rasmussen
1999; Murray et al. 2004). The status of global freshwater resources in particular has
become a prominent environmental concern; with the demand for clean/potable water
forecasted to increase. An understanding of how aquatic ecosystems respond to natural
and anthropogenic stressors is critical to ensuring both a sustainable supply of potable
water, as well as associated ecosystem services (Bennett et al. 2003). However, due to
variability of, and within, aquatic ecosystems, questions remain about their structure and
function. Specifically, how are systems driven by natural factors (e.g. climate and
succession), how do they react to anthropogenic impacts (e.g. cultural eutrophication),
and does employing management/mitigation strategies result in system recovery – and
what that recovery can be expected to be? Answers to these questions require a long term
evaluation of system dynamics, which is not available using modern empirical data, or
even decadal scale monitoring strategies (Battarbee et al. 2005).
Paleolimnology is a reliable tool for inferring historical environmental conditions
(Smol 2002; Bennion and Battarbee 2007; Ekdahl et al. 2007). In particular, diatoms can
be used as paleoecological indicators for reconstructing water quality conditions, such as
97

nutrient status, pH, temperature, and have been shown to successfully reflect
anthropogenic impacts (Smol 2002; Wolin and Stoermer 2005; Chen et al. 2008). In this
study, the biostratigraphic record of subfossil diatoms from a lake core is used to
reconstruct the effects of human activity in a highly impacted watershed in the Great
Lakes region.
Diatoms
Freshwater algae are photosynthesizing organisms that react rapidly to changes in
solar radiation (light), temperature, and nutrient conditions. In particular, diatoms play a
prominent role in paleoecological studies because their valves are opaline silica, which
are preserved well in lacustrine sediment compared to soft algae species (Hall and Smol
1999). Thus, diatoms recovered from sediment cores reliably reflect changing
environmental conditions (Wolfe et al. 1996; Hall et al. 1997; Hall and Smol 1999; Slate
and Stevenson 2000; Battarbee et al. 2001; Smol 2002; Ramstack et al. 2003). Moreover,
the biostratigraphic record of diatoms can reconstruct historical (pre-disturbance) water
quality conditions (e.g. nutrient loading) because of distinct preferences of individual
diatom taxa. Consequently, diatoms have been used to identify ecological reference
conditions (Leira et al. 2006; Bennion and Battarbee 2007) and productivity regime shifts
(Vadeboncoeur et al. 2001; 2002), both of which have applications to aquatic
management and recovery strategies (Smol 1992; Hall and Smol 1999; Smol and
Cumming 2000; Smol 2002; Bennion et al. 2004; Batterbee et al. 2005; Leira et al. 2006;
Lepisto et al. 2006; Taylor et al. 2006; Carpenter et al. 2008).

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Algae, as the base of the food web, play a significant role in the biogeochemical
cycling of nutrients and are sensitive to nutrient loading (Wetzel 2003). Shifts in
biomass or species composition indicate not only a change in external environmental
conditions (e.g. nutrient inputs), but also lend insight to internal lake process (e.g.
feedback mechanisms) (Vadeboncoeur et al. 2001). Notably, shifts in primary
productivity habitat, including benthic and planktonic, reveal shifts in ecological
dynamics; since primary productivity is an important factor in trophic transfer, and thus,
the flow of energy through a lake system (Vadeboncoeur et al. 2002).
A systems internal response from an external stressor, such as cultural
eutrophication can be complex (Scheffer and Carpenter 2006). Using diatoms as an
ecological indicator, the analysis of individual taxa dynamics and dominant habitat lends
insight to complexity of the system (Vadeboncoeur et al. 2001). For example, it is known
that increasing nutrient inputs increases the productivity of the water column (the pelagic
zone) (Vollenveider 1976, Schindler 1978). Cultural eutrophication often leads to a
higher abundance of planktonic diatoms, which sequesters nutrients and blocks light from
reaching the benthic habitat. This decreases the relative benthic productivity; and thus,
changes the productivity regime of the system (Vadeboncoeur et al. 2001; 2002).
An examination of the complex dynamics with biological interactions provide
important insight to both the diatom assemblage composition at any given time, as well
as lend insight to primary productivity habitats (Dokulil and Teubner 2005). During
times when a system is transitioning between states (the spectrum of oligotrophic to
eutrophic regimes), phytoplankton composition does not always track the typical
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succession expected using the chemically determined nutrient status, as phytoplankton
response – particularly to oligotrophication – is often delayed; this apparent hysteresis is
not well understood (Sas 1989; Dokulil and Teubner 2005). Furthermore, phytoplankton
community structure shows a lag time response to oligotrophication even when
phosphorus and Secchi depth parameters reflect a concomitant change during restoration
efforts (Dokulil and Teubner 2005). Further understanding whole-ecosystem dynamics is
important to identify primary productivity regime shifts, as triggered by natural or
anthropogenic activities.
Regime shift approach
In ecological systems, a regime is considered to be a set of conditions that remain
relatively stable and persistent over time (Carpenter 2003; Scheffer and Carpenter 2003;
Carpenter et al. 2008). These can be identified by examining the temporal composition
and diversity of the biological community (Das et al. 2009). The concept of ecological
regime shifts includes consideration of thresholds and resiliency, often driven by internal
feedback mechanisms (Carpenter 2003; Scheffer and Carpenter 2003; Walker and
Meyers 2004). Figure 3.1 shows a hypothetical system response given successive
perturbations. This figure illustrates how systems have the capacity to recover from a
single perturbation event, but subsequent perturbations may push a system past a
threshold, and kick it into a new regime (Scheffer et al. 2001; Carpenter 2003; Dearing et
al 2006). In other words, a system has a certain resiliency to perturbations and can resist
major change to a degree, but under persistent or multiple stressors, the system reaches a
threshold which tips the ecosystem to a different state. Ecological variables, as
demonstrated in this figure, can act as indicators of ecological regime shifts, and their
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temporal dynamics offer clues to system function (Scheffer et al. 2001; Carpenter and
Brock 2006).

Figure 3.1: Hypothetical conceptual diagram of regime shifts (modified from Carpenter
2003).

This chapter considers shifts in ecological regimes through the lens of primary
productivity habitats as the ecological variable. Specifically, this study examines the
ecological response to successive waves of environmental perturbation, and the
effectiveness of attempt(s) to mitigate human perturbations. Two distinct ecosystem
regimes (states), including benthic dominated production and planktonic dominated
production, are examined as they lend insight to system response (Vadeboncoeur et al.
2001; McGowen et al. 2005). Because of the relationships described above, lakes
dominated by benthic production are typically reported as clear water systems associated
with oligotrophic to mesotrophic conditions (Vadeboncoeur et al. 2002). Conversely,
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planktonic production dominated lakes are associated with increased nutrient inputs,
turbid water, and potential anoxic conditions resulting from cultural stressors of urban
development and agriculture (Vadeboncoeur et al. 2002; Wetzel 2003). Another factor
important to the habitat of productivity is lake morphology, with the proportion of
planktonic dominated productivity typically higher in large deep lakes (Wetzel 2003).
Table 3.1 depicts the relative contribution of primary producers under eutrophic
and oligotrophic conditions. Conceptually, primary productivity habitat can change the
flow of energy in a system (e.g. which begins with and where algal production is
greatest), and may influence the overall trophic structure (Scheffer and Carpenter 2003;
Scheffer et al. 2007). For example, decreased algae productivity in the water column
may result in more herbivores, less planktivores and more piscivores in open water
(Carpenter et al. 1985; Wetzel 2003). This chapter considers these associations with the
intent of understanding ecological dynamics and the consequential significance of
internal feedbacks in systems influenced by human stressors.
Table 3.1: Relative contribution of primary production in lakes

Oligotrophic Eutrophic
Pelagic
productivity
Benthic
productivity

Low

High

High

Low

This study used the record of fossil diatoms to reconstruct the rate and magnitude
of human influence in a highly impacted watershed in the Great Lakes region. This
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chapter regarding a system‟s biological component is intended to compliment results of
the geochemical proxies presented in Chapter 2 which identified phases of human
influence. Based on the conclusions of that investigation, it is expected that fossil
diatoms will have a similar temporal response, with any significant change in species
composition occurring along the same phase boundaries as anthropogenic geochemical
proxies. The hypothesis driving this study was that fossil diatoms archived in lacustrine
sediment reflect environmental change through changes in species assemblages; and
further, that productivity regime shifts that occur in response to anthropogenic activity
can be discerned by examining the dominant productivity habitat structure. Fossil
diatoms archived in sediment from Muskegon Lake (Michigan, USA), an ecosystem
influenced by human activity since the early 1800s, were used to investigate this
hypothesis. If true, the composition of diatom species assemblages will reflect shifts in
primary productivity dominance that correspond to a known historical timeline of
anthropogenic influence in the lake (see Chapter 1). Understanding these relationships is
important, particularly as the ecological response to the overprint of warming conditions
in the Great Lakes Region further complicates impacts on aquatic ecosystems; and
consequently, various feedback mechanisms which remain little understood and highly
uncertain (Magnuson et al. 1997). While many studies use diatoms to reconstruct
historical human perturbation through nutrient and pH inferences, few use them to
understand the processes influencing the behavior of the whole ecosystem (Bennion et
al., 2004; Ekdahl et al. 2007; Chen et al. 2008). Though diatom proxies are less
quantitative than chemical proxies, (e.g. the variability and range of acceptable conditions
for diatoms versus the actual accumulation/concentration of elements); interpreting
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ecological change with diatom stratigraphy does indicate change in environmental
conditions as diatoms also have the potential to integrate hydrological and chemical
changes. Therefore, this study contributes to an understanding of long term
environmental response trends (pre and post-disturbance), and also addresses the
effectiveness of current management strategies aimed to protect water quality in the
larger Great Lakes watershed.
3.2 Methods
Productivity regimes in Muskegon Lake were investigated using data and information
previously reported, and with additional fossil diatom assemblage data. The history of
the study area, sampling methods, and description of sediment core characteristics are
(Appendix I) from Chapter 1. Core chronology and sediment geochemistry are detailed
in Chapter 2.
Diatom processing
Diatom processing and taxonomical identification was performed by Dr. Nadja
Ognjanova-Rumenova at Michigan State University‟s Algal Ecology Laboratory.
Analysis was at 4 cm resolution throughout the core, using standard methods after
Battarbee (1986). A total of 38 stratigraphic levels were analyzed from the 149 cm core.
Slide preparation began by digesting approximately 0.5 g of homogenized sediment with
a strong acid and heating for an hour at 80 C. Digested slurries were rinsed with distilled
water until acid-free, and then the siliceous material was mounted on slides. At least 600
valves from each sample were counted and identified using oil immersion objectives at a
1000x magnification. The data were reported as counts per total, and converted to
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percent relative abundance. Common species were defined as those with at least 2%
relative abundance in at least 2 strata levels.
Zone delineation
Ecological zones were determined for the Muskegon Lake core using trends of
individual phytoplankton taxa, the composition of overall community structure, and
statistical analysis. For the Muskegon Lake core, each common species was first
categorized by habitat. Then, the sum of the abundances of all taxa for each habitat was
calculated. Notably, the sum for most strata levels does not reach 100%, due to the
proportion of “uncommon” taxa which are not accounted for in the calculation. Using
these methods, the transitions from benthic to planktonic dominated primary production
were clearly established by identifying the percent change in dominant habitat, or by
identifying significant change in the trajectories of habitat. Also, where applicable, the
distinct preferences of certain taxa (e.g. Diatoma tenuis relationship to chloride) were
used to delineate zones. To capture less distinct changes in diatom community structure
and verify identified zones, a stratigraphically constrained cluster analysis by incremental
sum of squares (CONISS) using the program ZONE Version 1.2 was performed on
common diatom taxa data (Juggins 1992).

3.3 Results
Diatom abundances
The algal community in the Muskegon Lake sediment core showed high
variability in both species composition and relative abundance. A total of 177 taxa were
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identified in the 38 strata levels sampled from the Muskegon Lake sediment core.
Appendix IV lists the 177 diatom species, with authorities, for all taxa present in the
Muskegon Lake core. Of the 177 taxa, 27 taxa were considered common, defined as
species with at least 2% relative abundance in at least 2 strata levels; these are listed in
Appendix V. Results of diatom stratigraphy are reported below.
Throughout the core, both Aulacoseira ambigua (Grunow) Simonsen and
Aulacoseira granulata (Ehrenberg) Simonsen were dominant, ranging from 5.7 - 60.0%
and 5.1 - 57.3% minimum and maximum relative abundance, respectively. These species
are typical of large, open water deep lakes; therefore, it is expected they would dominate
the diatom community (Chen et al. 2008). Aulacoseira ambigua is further associated
with turbulent water, fitting the flow-through conditions of Muskegon Lake (Wolin and
Stoermer 2005). Aulacoseira ambigua varies throughout the core, with peaks at 148,
132, 104 and 32 cm depths. Aulacoseira granulata is most prevalent in the bottom twothirds of the core, with peaks between 121 and 128 cm depth at nearly 57%; then, this
taxa shows a decreasing trend toward the surface, with <10% relative abundance in top
two samples. Both species share the same classifications as ecological indicators,
including eutrophic conditions, moderate (~50%) oxygen saturation, and alkaliphilous pH
(occurring mainly >7), detailed by van Dam et al. (2004). The relative abundances of
these two taxa vary in the Muskegon Lake core, however, because of their similarities
with water quality requirements and apparent inverse relationship throughout the core,
they are considered to indicate the overall ecological environment (e.g. large, flow
through, high nutrient) of Muskegon Lake. Also notable is that both taxa are at their
lowest abundances in the top 8cm of the core (<20%).
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Additional taxa comprising >20% abundance in at least one level include
Cavinula scutelloides (W Smith), Fragilaria capucina Desmazieres, and Stephanodiscus
minutulus (Kütz) and are shown in Figure 3.2. Cavinula scutelloides is particularly
notable because it is associated with cooler climate conditions (N. Ognianova, personal
communication 2007). Furthermore, this species is abundant in the bottom (oldest)
section of the core, likely associated with the end of the Little Ice Age (1850 AD), before
significant changes in ice phonologies (Magnuson et al. 1997). The abundance of C.
scutelloides abruptly increases in relative abundance to 20%, then decreases at the 112
cm level and fluctuates between 2.5% and the peak between 96 and 148 cm. From the
88cm depth to the top of the core, Cavinula scutelloides is much less abundant, with
typically only 0.25% abundance or less. Fragilaria capucina, and S. minutulus have
peak abundances in the upper and mid sections of the core, respectively. Fragilaria
capucina is a small, tychoplanktonic (present in littoral and other benthic habitats),
requires high light penetration (indicating shallow water) that is typically indicative of
higher nutrient conditions (Ramstack et al. 2003; Panizzo et al. 2008). Fragilaria
capucina first appears at 108 cm in very low numbers, until reaching 3% abundance at 64
cm; then it increases significantly from 4 to 23% between 12 and 8 cm depth. The peak
for F. capucina is 30% at 4 cm, while the top sample (2 cm) decreases by half to ~15%.
Stephanodiscus minutulus is also a planktonic species, associated with hypereutrophic
conditions (van Dam et al. 1994). This taxa is not present in the bottom of the core, but
shows an abrupt maximum abundance of 24% at 64 cm (it is1.6% or less before that).
Stephanodiscus minutulus increases again between 44 and 52 cm, and at 28 cm, but then
decreases significantly to the surface.
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Figure 3.2: Muskegon Lake diatom taxa which are at least 20% abundant in one level.

The next group consists of those taxa that were at least 10% abundant in one
sample or more. These include Aulacoseira granulata fo curvata, Cocconeis placentula
Ehrenberg, Pseudostaurosira brevistriata (Grun in VH) Williams & Round,
Stephanodiscus hantzschii Grun in Figure 3.3. Aulacoseira granulata fo curvata has a
distinct presence throughout the core, and is most common between 36-76 cm. This
planktonic species shares an ecological indicator preference similar to other Aulacoseira
species (van Dam 1994). Cocconeis placentula is considered an epiphytic, alkaliphilous,
cosmopolitan diatom, with maximum development in nutrient rich and very well
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oxygenated waters (Ehrlich 1973; Foged 1980; Steinberg and Schiefele 1988; van Dam et
al. 1994; Bennion and Appleby 1999). The abundance of this taxon in the Muskegon
Lake core is highest between 81 and 88 cm, with a maximum of 19.6% relative
abundance at 84 cm; and increases toward the surface to 2-4%. Pseudostaurosira
brevistriata is classified a benthic species (Kenney et al. 2002; Taylor et al. 2006). This
species is present throughout the core, and fluctuates between 1 and 3% abundance in the
bottom third (>96 cm), then increases in significance through the upper 12 cm, peaking in
the top sample at 14.5%. Pseudostaurosira brevistriata is inverse to the trend of S.
hantzschii which significantly decreases in abundance in the top 16 cm to <1%. S.
hantzschii is small, centric, planktonic taxa, present in highly eutrophic conditions
(Bennion and Appleby 1999; Taylor et al. 2006). Further, S. hantzschii has been shown
to be resistant to human impacts (Witkowski et at. 2004). Overall, this group shows more
distinct trends versus the cosmopolitan taxa of the >20% abundant group, and can
provide better indications of ecological conditions.

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Figure 3.3: Muskegon Lake diatom taxa which are at least 10% abundant in one level.
Diatom taxa with at least 7% abundance are shown in Figure 3.4 and include
Amphora pediculus (Kützing) Grun, Cocconeis placentula var euglypta (Ehrenberg)
Cleve, Fragilaria capucina var gracilis (Østr) Hust, Fragilaria crotonensis Kitton,
Opephora martyi Hérib, Staurosira construens (Ehr) Williams & Round. Amphora
pediculus is a benthic epiphyte species classified as eutrophic and alkaliphilous (van Dam
et al. 1994; Bennion and Appleby 1999; Taylor et al. 2006; Chen et al. 2008). Amphora
pediculus is present in nearly all samples of this core, and peaks at ~10% at 92 cm depth,
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but shows an increasing trend in the top 12 cm as well. Cocconeis placentula var
euglypta is most common in the top two-thirds of the Muskegon Lake core; this benthic
taxon peak abundance is at 84 cm, and is also increasing in the top 8 cm. Fragilaria
capucina var gracilis is a small, tychoplanktonic (adaptive to thermal changes) taxa
present mainly in the top sample (2 cm depth) (Panizzo et al. 2008). Van Dam et al.
(1994) classifies F. capucina var gracilis as associated with oligio-mesotrophic
conditions in Netherland lakes, and corresponds to decreasing P concentrations in the
water column of Muskegon Lake (Steinman et al. 2008). Fragilaria crotonensis is
another small, tychoplanktonic taxa which has been observed to respond to changing
nutrient conditions and rising nitrate conditions (van Dam et al. 1994; Wolin and
Stoermer 2005; Panizzo et al. 2008). Fragilaria crotonensis is classified as mesotrophic
by van Dam et al. (1994). The presence of this taxon in the Muskegon Lake core is
mainly in the top half, with up to 10.4% abundance at 52 cm depth, yet it decreases to 0%
in the top sample. Opephora martyi is a benthic species mainly present in the bottom half
of the core, with maximum abundance of 9.8% at 144 cm depth. Staurosira construens
varies throughout the core; with the most dominant appearance in the top two samples (2
and 4 cm). Staurosira construens is a competitive meso-eutrophic planktonic species
documented as growing well in low nutrient arctic lakes (Cremer et al. 2001). Notably,
this species is absent from depths 21-48 cm, which is a phase of high P concentrations in
Muskegon Lake‟s water column.

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Figure 3.4: Muskegon Lake diatom taxa which are at least 7% abundant in one level.

Taxa of 5% abundance consist of Achnanthidium minutissimum (Kützing)
Czarnecki, Asterionella formosa Hassal, Aulacoseira granulata var angustissima (O
Müller) Simonsen, Cocconeis neodiminuta Krammer, Cocconeis neothumensis Krammer,
Stephanodiscus niagarae Ehr., shown in Figure 3.5. Achnanthidium minutissimum is a
benthic (epiphytic) generalist species present in circumneutral pH and oligio-eutrophic
conditions (van Dam et al. 1994; Anderson 1997; Chen et al. 2008; Panizzo et al. 2008).
Achnanthidium minutissimum is present in most of the core, but in very low overall
relative abundances; however, this species becomes more abundant in the top 8cm of the
core, reaching a peak abundance of ~5% in the very top sample. Asterionella formosa is
present from 24 to 64 cm depth, with a peak of 5.6% at 52 cm depth. Asterionella
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Formosa is an open water planktonic species sensitive to light changes, documented to
respond to changing nutrient conditions, and found to be seasonally dominant in
eutrophic lakes (Leitao and Leglize, 2000; Wolin and Stoermer 2005; Chen et al. 2008;
Vanormelignen et al. 2008). The presence of this taxon corresponds to a period of
significant human influence in the study area. Aulacoseira granulata var angustissima
has one sample above 5% at 81 cm depth and is otherwise intermittent throughout the
core. Aulacoseira granulata var angustissima is similar to other Aulacoseira spp. and
indicative of eutrophic, alkaliphilic conditions (van Dam et al. 1994). Both Cocconeis
spp. are benthic and show highest abundance in the bottom third of the core. They also
both peak at 112 cm, then decrease substantially until the very top of the core again.
Stephanodiscus niagarae is a planktonic species present throughout the Muskegon Lake
core. The maximum abundance for Stephanodiscus niagarae is 5.4% at depth 108 cm.
Overall, this group of algae (the 5% or more abundant) show distinct variability in both
preferred habitat, and temporal presence helping to better define environmental
conditions.

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Figure 3.5: Muskegon Lake diatom taxa which are at least 5% abundant in one level.

The least abundant of common taxa, those consisting of >2% in the Muskegon
Lake core are shown in Figure 3.6. This group includes Actinocyclus normanii fo
subsalsus (Juhlin-Dannfelt) Hustedt, Aulacoseira subartica (O Müller) Haworth,
Cocconeis pediculus Ehrenberg, Diatoma tenuis Ag, Planothidium frequentissimum
(Lange-Bertalot) Lange-Bertalot, Staurosirella pinnata (Ehr) Williams & Round.
Actinocyclus normanii fo subsalsus is a large, centric, planktonic species which has been
associated with human disturbance, including eutrophication in modern European rivers,
but has also been found in much older riverine sediment (van Dam et al. 1994; Leitao and
Leglize 2000; Witkowski et al. 2004). In the Muskegon core, A. normanii fo subsalsus is
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present from 48 cm and above, with a peak at 44 cm. This species is not present in the
top of the core. Aulacoseira subartica is a planktonic species with intermittent presence
through most of the core, except the top and bottom samples, with a maximum of 2.7% at
42 and 72 cm depths (Taylor et al. 2006). It is again observed that this taxon is
represented in a zone of significant human disturbance which agrees with its association
with oligio-mesotrophic conditions (van Dam et al. 1994) and tolerance to increasing
nutrient conditions (Dokulil and Teubner 2005; and Wolin and Stoermer 2005). Next is
C. pediculus, another hypereutrophic, alkaliphic and benthic taxa (van Dam et al. 1994;
Chen et al. 2008). Cocconeis pediculus has two zones of peak abundance, one between
68 and 88 cm, and another between 4 and 12 cm; and additional, though small, presence
through much of the top two-thirds of the core. Diatoma tenuis has a distinct presence in
the core in that it is more clustered in the top half of the core; the peak for D. tenuis is
~6% at depth 28 cm. Then, this hypereutrophic, alkaliphic benthic species decreases to
less than 1% from 16 cm to the top (van Dam et al. 1994; Chen et al. 2008).
Planothidium frequentissimum and S. pinnata are both present through most strata levels
in the core. Planothidium frequentissimum is a benthic species, though not much has
been published on it; while S. pinnata is benthic (epiphytic) and alkaliphic (Taylor et al.
2006; Chen et al. 2008).

115

salsu

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1835

Depth (cm)
Depth (cm)

Year

0

2
4
8
12
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24
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52
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64
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0.0 1.0 2.0 3.0 4.0

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2.0

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0.0 2.0 4.0 6.0 8.0

0 2 4 6 8

0.0

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1.0 2.0

1

2

3.0

3

0.01.02.03.04.05.0

0

2.5

5

% Relative Abundance
Figure 3.6: Muskegon Lake diatom taxa which are at least 2% abundant in one level.

Though all species in the Muskegon Lake core contribute to an understanding of
the evolving ecological status of the lake, some are better than others at lending insight to
changing environmental conditions. As reported above, there is a general consensus
among many taxa regarding the dominant conditions of Muskegon Lake (e.g. A.
granulata and A. ambigua). Moreover, a majority of common species in Muskegon Lake
prefer alkaliphilic conditions, and are classified as meso-eutrophic to eutrophic. Results
shown above also demonstrate that the diatom community assemblage in Muskegon Lake
responded to environmental change due to human influence. For the purpose of
understanding the collective response of diatoms to stressors, the remainder of this
section will focus on deciphering differences in the diatom community structure.
116

Specific attention will be given to the dominant habitat of taxa to better identify system
dynamics, and shifts in primary productivity regimes.
Dominant habitat of diatom paleoproductivity
Diatom taxa from the Muskegon Lake core were classified by habitat (benthic or
planktonic) to identify primary productivity regimes. Appendix VI shows a list of the
common taxa, with habitat and
ecological preferences. Figure 3.7
illustrates stratigraphic habitat

of
Sum

preferences for the common taxa, with a

time represented by the core. The
bottom of the core reflects between 56

of
Sum

bent

hic

2005

30

1960

60

1935
1910

90

1835

120

and 77% as planktonic dominated taxa.
The sum of planktonic diatom

Year

planktonic habitats, over the period of

tonic

0

2
4
8
12
16
21
24
28
32
36
40
44
48
52
56
61
64
68
72
76
81
84
88
92
96
101
104
108
112
116
121
124
128
132
136
139
144
148

Depth (cm)
Depth(cm)

marked change shown for benthic and

plank

150
0 20 40 60 80 100

0

abundance peaks at 88% abundant in

50

0 20 40 60 80 100

100 0 0

50

100

% Relative Abundance
the 24 cm depth sample, then decrease
to 26- 37% in the top 8 cm of

Figure 3.7: The sum of dominant diatom
productivity habitats in Muskegon Lake
the core. The

segment from ~8 cm to the top is significant because it reflects a shift in the dominant
habitat of diatoms, with the benthic taxa becoming 54 – 62% abundant.

117

Diatom zones
The diatom stratigraphy of Muskegon Lake was divided into three major zones
according to habitat, ecological preferences of individual taxa, and results of the Zone
analysis. Figure 3.8a (benthic) and 3.8b (planktonic) shows zone specific relative
abundance of all common Muskegon Lake diatoms. Delineating zones distinguished predisturbance and post-disturbance phases, as well as the post-regulation ecosystem state
(e.g. Clean Air and Clean Water Acts). Importantly, this method clarified the response of
diatoms to multiple stressors, and delineated phases of anthropogenic influence.

118

ant
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A
2
4
8
12
16
21
24
28
32
36
40
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52
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68
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76
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84
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92
96
101
104
108
112
116
121
124
128
132
136
139
144
148

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0

D III B
D III B
D III A
D III A

Depth(cm)
Depth (cm)

30
D D IIC
II C

60
D II B
D II B

90
D D IIA
II A

120
DI

150

0.0

0

2.0

4.0

6.0 0

4

8

12

0

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16

240.0

3 6 0 6 12 0 10 20 0

2.0

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2.4

4.8

7.2 0.0

1.0

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8 12 16 20

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4.8

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8

16 24 32 0.0 2.0 4.0 6.0 8.0 0

4 8 0 16 32 0

4

8

12 0.0 2.0 4.0 6.0 8.010.0 0.0

% Relative Abundance

Figure 3.8a: Fossil diatoms from Muskegon Lake associated with benthic preferences.
Figure 3.8b: Fossil diatoms from Muskegon Lake associated with planktonic preferences

119

1.0

2.0

3.0 0

3

6

9 12 15 0.0 1.0 2.0 3.0 4.0 5.0 0 20 40 60 80 100

4 8 0 6 12 0 5 10 0 1.5 3 0 8 16 0 2.5 5 0 100

DI

0

D III B
D III A

30

Depth (cm)

D II C

60
D II B

90
D II A

120
DI

150
0

2

4 0

3

6 0

32

64 0

30

60 0

10

20 0

3.5

7 0

1.5

3 0

5

10 0

7

14 0

% Relative Abundance
Figure 3.8b: Fossil diatoms from Muskegon Lake associated with planktonic preferences.
120

15 30 0

4

8

0

50 100

Zone DI: Pre-disturbance (149-116cm depth)
The bottom of the Muskegon Lake core reflects conditions prior to significant
anthropogenic disturbance. Though there are still noted changes in the overall diatom
community structure, the dominant assemblages at the bottom of the core were
Aulacoseira ambigua and A. granulata, who show interchangeable dominance in the
bottom zone, fluctuating between 54 and 75% of the total abundance. Additional
taxonomic changes include a peak of Amphora pediculus at 139 cm depth, and both
Cavinula scutelloides and Opephora martyi at depth 144 cm depth. Even though these
taxanomic changes were observed, the diatom community structure is stable for the most
part, and the bottom of the core is dominated by planktonic algal production (from ~60 to
77% from bottom to 112 cm depth). The 116 cm depth, where benthic productivity
becomes dominant, marks the boundary between zone I and zone II. Though this switch
from planktonic to benthic is just for one level, it marks the first significant change in
overall composition of diatoms in the core.
Zone DII: Disturbance (116 - 21cm depth)
The second zone delineated in the Muskegon Lake core is that of anthropogenic
influence. This zone reflects shifts in individual taxa abundances, as well transitions in
planktonic versus benthic dominated habitats. Zone DII begins at ~116 cm depth (~1840
AD) and end at the 24 cm depth (1973 AD). In this zone, there is biostratigraphical
evidence (e.g. appearance and disappearance of indicator taxa) of considerable human
impacts from land use changes (e.g. industry, agriculture and urbanization). To make
clear the response to human perturbation, this zone is further divided into three sub-zones
that correspond to distinct floristic change.
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Sub-zone DIIA (116 – 92 cm depth) is the initial disturbance zone revealed in the
disturbance zone. As throughout the core, Aulacoseira granulata and A. ambigua are
dominant in this sub-zone. Stephanodiscus niagarae increases somewhat in abundance at
108 cm depth (accounting for >5%). Cavinula scutelloides has an outlying peak at 21%
at 112 cm depth, then returns to the 2-5% range in the younger samples. Opephora
martyi maintains zone I abundance, while Staurosirella pinnata increases slightly.
Cocconeis neodiminuta and C. neothumensis show peaks in this sub-zone that correlate to
the Cavinula scutelloides peak at 112cm depth. Both then sharply decline to abundances
lower than in zone DI. Cocconeis pediculus, C. placentula, and C. placentula var
euglypta all slightly increase. In addition, Amphora pedediculus declines in this zone,
and Staurosirella Pinnata have higher abundances at the upper and lower boundary of
DIIA; Cocconeis pediculus, C. placentula and C. placentula v. euglypta increase, so
define this zone with first significant presence (up to 5%).
The next sub-zone (DIIB) in the Muskegon Lake core is from 92 – 64 cm depth.
In this sub-zone, the Muskegon Lake‟s cosmopolitan species, Aulacoseira granulata and
A. ambigua remain dominant, though there are changes for several taxa that are good
ecological indicators. The benthic and planktonic taxa percentages are relatively stable,
with the exception of the 84cm depth where benthic taxa comprise 49% of the total and
become dominant for one level. However, despite the stability, specific taxa are observed
to be responding to the environmental change. For example, the other Aulacoseria spp.
show high abundances in this sub-zone as Aulacoseira granulate fo curvata and
Aulacoseira granulata var angustissima have increases. Also, Cocconeis placentula and
C. placentula var euglypta both peak in this sub-zone to nearly 20 and 15%, respectively,
122

that together comprise nearly 35% of the total at 84 cm depth. Stephanodiscus minutulus
is dominant in this zone, with 24% abundance at 64 cm depth; marking the boundary with
sub-zone DIIC. Additionally, the first noteworthy appearance of Fragilaria capucina,
Fragilaria capucina var gracilis and Fragilaria crotonensis occurs at the boundary,
illustrating an important compositional change which becomes more significant in the
next zones.
The youngest of the disturbance sub-zones is DIIC, delineated between 64 – 24
cm depth. In this disturbance sub-zone, planktonic diatom taxa Actinocyclus normanii fo
subsalsus, Asterionella formosa, Stephanodiscus hantzschii, and S. minutulus peak in
abundance. Two common benthic species also become more abundant in this sub-zone
as Diatoma tenuis and Fragilaria crotonensis both reach sustained high relative
abundances at these depths (accounting for 2-7% and 3-10%, respectively). Conversely,
benthic taxa Amphora pediculus, Cocconeis pediculus, C. placentula decline in this zone
to their lowest abundances; while Cavinula scutelloides, Cocconeis neodimiminuta, C.
neothumensis and Opephora martyi are very low or zero abundance in this zone.
Zone DIII: Mitigation
Beginning at the 24 cm depth, the Muskegon Lake core reflects a shift from
planktonic to benthic dominated diatom habitat, with a separate, stronger shift from 8cm
to the top. This zone lends insight to ecological response following a mitigation strategy;
the installation of waste water treatment plant that diverted municipal and industrial
waste away from Muskegon Lake. Consequently, the diatom community structure
reflects a change in composition in this zone.
123

Several taxonomic changes occur in the first mitigationsub-zone, DIIIA. For
example, Diatoma tenuis is observed to decline from ~3% total abundance, to nearly
zero. The environmentally resistant taxa Stephanodiscus hantzschii and S. minutulus,
also decline toward the surface; while Asterionella formosa disappears entirely for the
remainder of the core. Notably, the core‟s most dominant planktonic species,
Aulacoseira ambigua and A. granulata, both display a decreasing trend in abundance to
the surface, beginning at the 24 cm depth, then more significantly in the top 8 cm,
accounting for 12.6 and 7.6%, respectively of the total abundance in the most modern
sample. Taxa that increase in this sub-zone include the benthic Fragilaria crotonensis
and Pseudostaurosira brevistriata.
Further floristic change persists in the top 8 cm (sub-zone DIIIB). Benthic taxa
become dominant in this subzone, and maintain that dominance to the modern sample (at
2 cm depth). The benthic Achnanthidium minutissimum, Amphora pediculus, Cocconeis
pediculus, C. placentula, C. placentula var euglypta, Fragilaria capucina, F. capucina
var gracilis, Pseudostaurosira brevistriata and Staurosirella pinnata all increase in
relative abundance in this sub-zone. Staurosira construens is the sole planktonic taxon to
experience an increase in abundance in this sub-zone, and accounts for 8.6 and 5% in the
8 cm and 4 cm depth samples, respectively.
Dominant diatom habitats
A summary of results for benthic versus planktonic primary productivity are
shown in Figure 3.7. Described by zones, it is apparent that zone DIIIB reflects a shift in
the dominant habitat from planktonic to benthic. The relative percentage of benthic taxa
124

in this zone peaks at 61.5% at the 4 cm depth, compared to a 23% average in zone DI.
Also notable are levels 112 and 84 cm, where the benthic habitat has significant
increases.

3.4 Discussion
The fossil diatom based interpretation of the ecological state of Muskegon Lake
suggests that there have been significant environmental change since major human
settlement in the late 1800s. Diatom stratigraphy from this core reveals abrupt shifts in
community structure, and paleoproductivity habitats indicate altered nutrient dynamics.
Feedback mechanisms driving ecological dynamics can be indentified in these shifts,
based on the delineation of zones, and coupled with the documented historical watershed
activity. Using the three major zones identified by fossil diatom assemblages, it is
possible to correlate ecological dynamics to phases of human influence in the watershed.
Phase I
The first phase represented by the core is that of pre-disturbance, corresponding to
zone DI described in the results. Aulacoseira ambigua and A. granulata are dominant in
this phase. According to the classification by van Dam et al. (1994), the planktonic taxa
present are associated with mesotrophic to meso-eutrophic conditions, and likely
indicative of Muskegon Lake‟s flow-through hydrology which inputs ample nutrients
from the vast Muskegon River Watershed. Aulacoseira ambigua is present in this zone
and has a relatively high Si requirement for growth (Kilham; Kilham and Hecky, 1986).
Further, A. ambigua was found in nearby Lower Herring Lake (MI) and reported to be
125

prevalent in turbulent conditions, as they require mixing conditions to remain suspended
in water column (Wolin and Stoermer 2005). This requirement may explain its predisturbance dominance and peaks of A. ambigua at the 148 and 132 cm depths in that it
may reflect periods of flood events, or otherwise high flow from the Muskegon River
Watershed.
Phase 2
Phase two of the Muskegon Lake core is characterized by the initial period of
human disturbance, which is also reflected in the fossil diatom assemblages. The initial
stage of this phase (corresponding to sub-zone DIIA) commenced in the 1840s and
corresponds to large-scale logging in the Muskegon River watershed (Alexander 2006).
This activity led to pronounced effects in the composition of the algae population,
perhaps initially due to increased erosion that increased turbidity in water column, and
perhaps due to increased nutrients released with erosion (Fritz et al. 1993). Because
Aulacoseira granulata and A. ambigua maintain overall dominance in this sub-zone,
algae indicate no broad change in dominant productivity habitat. Aulacoseira ambigua
was reported by Bradbury et al. (2002) to be present after deforestation. In Muskegon
Lake, this species is at least 8% abundant in nearly all levels and does not appear to
specifically indicate a deforestation signal. However, the peak, then quick decline of
Cavinula scutelloides, reported to be a cooler water taxa, may signify a change in the
thermal regime in the watershed. The C. scutelloides decline may be the result of water
temperature increases due to changes in climate following the end of the Little Ice Age.
Or, the data could indicate that the removal (from logging) of shade trees along the shores
126

of the Muskegon River and its tributaries warmed the inflow waters enough to have
influenced the decline of C. scutelloides. The peaks of Cocconeis neodiminuta and C.
neothumensis at 112 cm depth correlate to the Cavinula scutelloides peak; then, they also
decrease to abundances lower than in predisturbance phase (zone DI). The coupling of
these three taxa suggests a change in environmental conditions, and because they are all
benthic taxa, it may suggest an increase in turbidity from erosion or logging material
(saw dust) which blocked light from the benthic habitat, thus decreasing their
abundances. Cocconeis pediculus, C. placentula, and C. placentula var euglypta all
slightly increase in zone DIIA. The increase with these taxa may indicate the first human
induced contributions of increased nutrients, either from terrestrial erosion, or increased
population, as these taxa respond to such conditions (Steinberg and Schiefele 1988). As
the logging era ended due to depleted lumber resources (~1905 AD) the next phase of
Muskegon Lake began as deforested land was converted for agriculture, industry and
urbanization (Tang et al. 2005; Alexander 2006; Ray and Pijonowski 2010).
Sub-phase IIB in the Muskegon Lake core (corresponding to sub-zone DIIB)
marks the next wave of anthropogenic influence, namely due to industrialization.
Muskegon Lake has a history of industrial activity on its shoreline and surrounding city
(see Steinman et al. 2008 and Ray and Pijanowski 2010). By the mid-1900s, industrial
activity along the lake‟s shoreline included foundries, metal finishing plants, a paper mill,
and petrochemical storage facilities that influence ecological conditions. Through the
advent of industrial pollution, Muskegon Lake‟s cosmopolitan species, Aulacoseira
granulata and A. ambigua, remain dominant. The benthic and planktonic taxa ratios are

127

relatively stable, with the exception of the 84 cm depth where benthic taxa become
dominant for one level.
Despite this stability, the abundances of specific taxa seemingly respond to the
environmental change. Aulacoseria spp. show high relative abundances in this sub-phase
as Aulacoseira granulata fo curvata and Aulacoseira granulata var angustissima
increase. Also, Cocconeis placentula and Cocconeis placentula var euglypta both peak
in this sub-zone to nearly 20 and 15%, respectively, together comprising nearly 35% of
the total at 84 cm depth. These taxa are indicative of eutrophic conditions, and as noted
above, have maximum growth in nutrient rich and well oxygenated waters (Steinberg and
Schiefele 1988; van Dam et al. 1994). Stephanodiscus minutulus, a planktonic eutrophic
species, also gains dominance in this zone, with a 24% abundance at the 64 cm depth,
marking the boundary with sub-zone DIIC. Other high nutrient indicator taxa that
increase toward the sub-zone boundary (e.g. Fragilaria capucina, F. capucina var
gracilis, and F. crotonensis) further illustrate the influence of increasing nutrient inputs
that are the focus of sub-zone DIIC.
The youngest portion of the disturbance phase corresponds to sub-zone DIIC,
which seemingly reflects the floristic response to excessive nutrient inputs (see Freedman
et al. 1979; Steinman et al. 2008); presumably the result of population growth, advent of
widespread fertilizer use, and direct inputs of municipal and industrial waste water. From
61- 24 cm depth, planktonic diatom taxa indicative of highly eutrophic conditions gain
prevalence in the fossil diatom assemblage (though attempted diatom inferred total
phosphorus reconstructions were inconclusive), similar to qualitative interpretations by
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Fritz et al. 1993. Taxa in this sub-phase include Actinocyclus normanii fo subsalsus,
Asterionella formosa, Stephanodiscus hantzschii, and S. minutulus; which all reach their
maximum abundances in this sub-zone and who all have been documented as being
associated with human disturbance and changing nutrient conditions (Bennion and
Appleby 1999; Leitao and Leglize 2000; Witkowski et al. 2004; Wolin and Stoermer
2005; Taylor et al. 2006; Chen et al. 2008). Moreover, two common benthic species
abundant in this sub-zone, Diatoma tenuis and Fragilaria crotonensis, both reach
sustained high relative abundances at these depths. These taxa, because of their distinct
presence in the core and well-defined ecological preferences specifically noted in other
regional investigations (e.g. Ramstack et al. 2003; Wolin and Stoermer 2005), they are
indicative of further changing nutrient conditions and inputs, as compared to zone DIIB
(Bradbury 1975; Brugam 1979; Wolin and Stoermer 2005). In particular, Diatoma tenuis
is common in culturally eutrophied areas of the Great Lakes region (Wolin and Stoermer
2005), and a study of water quality trends in Minnesota published by Ramstack et al.
-1

(2003) inferred a chloride optimum of 81.8 meq l for the taxon D. tenuis. Moreover, the
Wolin and Stoermer (2005) investigation supported these findings, as this taxon was
found to correlate to a “high conservative ion loading”. Wolin and Stoermer (2005) also
report that Fragilaria crotonensis is associated with high nitrate concentrations, which is
consistent with the reported increases of nitrate in Muskegon Lake during this time
period (see Chapter 1) (Freedman et al. 1979; Steinman et al. 2008). Conversely, benthic
taxa Amphora pediculus, Cocconeis pediculus and C. placentula decline in this zone to
their lowest abundances, perhaps the result of abundant planktonic taxa blocking light
and nutrients from benthic habitats. (Another caveat to the data worth noting is that
129

seasonal productivity cannot be determined when using abundance data at this
resolution.) Also, noticeable increases in the small Stephanodiscus spp., which
reportedly have high phosphorus optima, occur in this sub-phase of the Muskegon Lake
core (Bradbury 1975; Fritz et al. 1993; Bennion et al. 1996). These taxa become largely
absent in the next phase, likely due to the competitive advantage of benthic taxa as
increased water clarity results from environmental regulations (Steinmann et al. 2008).
Phase 3: Mitigation
The mitigation phase lends insight to a unique event in recent environmental
management of the Muskegon River Watershed, and particularly for efforts to remediate
Muskegon Lake. In 1973, the County of Muskegon installed a tertiary waste water
treatment plant, the Muskegon County Wastewater Management System (MCWMS) to
divert municipal and industrial waste water (Alexander 2006; Steinman et al. 2008). The
MCWMS replaced smaller individual community systems which were overburdened, and
to capture industrial effluent being directly discharged to Muskegon Lake with
inadequate treatment (http://www.muskegoncountywastewater.com/aboutus.shtml).
Consequently, this zone reflects the ecological response of management actions, designed
to mitigate much of the anthropogenic influence of phase II. Using correlating
chronology of

210

Pb dated short core the MCWMS installation event is dated to ~24 cm

depth, and is associated with change in the biostratigraphy of diatoms.
At the 24 cm depth, the Muskegon Lake core shows a shift from planktonic to
benthic dominated diatom habitat. The first subzone (DIIIA) of the Mitigation Phase
appears to be a transition phase where taxa attempt to„re-equilibrate‟ to decreasing
130

nutrients, metals, and conservative ions (e.g. Cl-) that were diverted by the 1973
MCWMS installation. A distinct change in this zone is the sharp decline in Diatoma
tenuis. This is a notable change, as this taxon has been found to be common in
eutrophicated lakes of the Great Lakes and indicative of high conservative ion loading
(van Dam et al. 1994; Chen et al 2008). Its decline is likely related to the wastewater
diversion that reduces chloride from the lake, allowing other taxa to be more competitive,
and thus, higher relative abundance. The decline of Stephanodiscus hantzschii and S.
minutulus, and the disappearance of Asterionella formosa, all of which are associated
with hypertrophic conditions, also reflect the ecological response to the diversion of
wastewater (and nutrients) (Bennion and Appleby 1999; Witkowski et al. 2004; Taylor et
al. 2006). Stephanodiscus hantzschii is notable for its presence in the anthropogenic zone
of the core, since it is a species tolerant of human disturbance (Bennion and Appleby
1999; Taylor et al. 2006). The decline of this taxon after the installation of the waste
water treatment plant suggests the system responded by allowing less tolerant taxa to
become more competitive under improved water quality conditions. Finally, the decline
of Aulacoseira ambigua and A. granulata, play a significant role in the overall decline of
planktonic taxa in sub-zone DIIIA; a trend that was most distinct in sub-zone DIIIB.
The modern diatom assemblage in the top 8 cm (sub-zone DIIIB) reflects further
floristic change. This sub-zone indicates the continued evolution of the diatom
paleoproductivity as it responds to human influences. Benthic taxa become dominant in
this subzone, and maintain that dominance to the most modern sample at 2 cm depth, a
sustained transition that suggests a shift in productivity habitat. Though this shift should
be interpreted with caution as the system could still be in a transitional state, increases in
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the benthic Achnanthidium minutissimum, Amphora pediculus, Cocconeis pediculus, C.
placentula, C. placentula var. euglypta, Fragilaria capucina, F. capucina var. gracilis,
Pseudostaurosira brevistriata and Staurosirella pinnata do indicate that the benthic
habitat became more competitive compared to the planktonic habitat in this phase.
Though, benthic diatoms probably do not compete for resources with planktonic diatoms;
however, planktonic productivity may influence the benthic through shading, but no
similar reciprocal effect of benthic on planktonic taxa.
Evidence of productivity regime shifts reflected habitat of fossil diatoms
Shifts in benthic and planktonic primary productivity indicate shifts in ecological
function, because primary productivity is an important factor in trophic transfer, and thus
the flow of energy through the lake system (Vabdeboncoeur et al. 2003). Metal
contamination, as observed in Muskegon Lake, can also play a role in habitat shifts, as
Cattaneo et al. (2008) reported that under increased contaminant conditions, there was a
shift from planktonic to benthic taxa dominance. Cattaneo et al. also suggested that
littoral zones were a refuge under high contamination conditions. However, this result is
not supported by diatom data from Muskegon Lake.
In assessing the Muskegon Lake diatom community post-management policies,
one would expect a community structure similar to pre-perturbation; or at least a
community trending in that direction. However, what is observed in the biostratigraphy
of Muskegon Lake suggests a restructuring of the diatom community. The total shift in
habitat dominance from planktonic to benthic in the Mitigation Phase is by a substantial
margin, from 88% total planktonic at 24 cm depth, decreasing to 27% at 2 cm depth,
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indicating a clear shift in primary productivity regimes. Though, because we are
interpreting relative abundance data, care must be taken with the interpretations, as the
increase in benthic may not be attributed to an actual increase in benthic diatom
productivity, but a decrease in relative planktonic diatom abundance.
Referring to Figure 3.9, one can relate the „perturbation‟ of the MCWMS
installation as the event that kicked the system to a new regime (a benthic dominated
regime). This is interpreted to indicate that as water clarity increased, the benthic habitat
reflected an increase in relative productivity, perhaps aided with the legacy of ample
nutrients left over in the sediment (evidenced by sediment P profile). Further supporting
the idea of a new productivity regime for Muskegon Lake is that the benthic community
has remained dominant for close to two decades.
This leads to questions of how and why has the benthic community dominance
been sustained, since it is unlikely that „extra‟ sediment nutrients would last this long.
Furthermore, the historic loss of littoral habitat (see Figure 1.8, chapter 1) should
decrease the relative abundance of benthic diatoms; however, their abundance is
increasing to surface despite this? An attempt to answer these questions suggests an
additional change in the function of the ecosystem that alters feedback mechanisms. It
has been reported that invasive zebra mussels entered Muskegon Lake in ~1989 (Jeff
Alexander, personal communication, 2008). Zebra mussels further increase water clarity,
and their waste adds to nutrients in the benthic habitat, thus creating a positive feedback
loop. It is important to note that caution needs to be applied to this idea, since there could
be unknown factors contributing to these trends not related to this interpretation. For
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example, it is possible that increased urbanization and/or non-point sources are
contributing to the trajectory of change by adding nutrients to the system/sediment. This
possibility will be explored in chapter 4, with a comparison of sediment geochemical
productivity proxies.
Influence of management strategies on environmental recovery
The Muskegon Lake record provides the opportunity to explore the response of
highly perturbed lake to pollution reduction due to management strategies. While the
implied „recovery‟ for Muskegon Lake is somewhat unclear, the diatom community
structure has contributed to understanding of ecological process. The compositional
structure in the pre-disturbance phase reflects a state of system stability. The abrupt
changes in diatom assemblage stratigraphy in the Anthropogenic phase (DII) indicate
dramatic (possibly irreversible) environmental change. The productivity habitat regime
shift in the Mitigation phase indicates a more dramatic change in the ecological function
of the lake, suggesting there were unforeseen consequences, or factors driving ecological
response to this management strategy (though, this is not necessarily negative, just
arguably unexpected). If environmental response is evaluated using the conceptual
model in chapter 1 (Figure 1.2), it would indicate that Muskegon Lake is currently at
point C2. Moreover, there are additional impacts to the Muskegon Lake ecosystem from
human influence that need addressed. These results indicate that ecological assessments
and policy recommendations need to consider environmental change over longer spans of
time. Looking at systems in this paleoecological method is a beneficial approach to
understanding system response and recovery.
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Recovery challenges
This study suggests continued challenges to the ecological health of Muskegon
Lake. Though the fossil diatom record from this core suggests that efforts to reduce
nutrient loading have had some success (supported by change in taxa and record of
monitoring data); new sources (e.g. riverine inputs from increasing urbanization and
storm water effluent), or continued recycling of phosphorus from sediments may degrade
water quality, and be reflected by the future diatom community structure. Additionally,
the overprint of warmer climate in the Muskegon River Watershed could have
implications for ecological recovery in this system, as has been observed already from the
bottom of core to the top with taxa indicating thermal sensitivities (e.g. Cavinula
scutelloides). Finally, the influence of invasive species (e.g. zebra mussel) could further
alter ecological dynamics in the larger Great Lakes Region.
Comparison to regional diatom studies
Diatom results from Muskegon Lake are in many ways distinct from other
regional studies. In particular, the presence of Cavinula scutelloides is notable because it
has not been identified in other regional studies (Fritz et al. 1993; Garrison and Fitzgerald
2005; Wolin and Stoermer 2005; Watchorn et al. 2008). Also, because of the high
relative abundance of this taxon in the the lower (reference) part of the core, it is difficult
to reconstruct a quantitative ecological history (e.g. total phosphorus). Other taxa not
identified in other regional studies include the Cocconeis spp.
However, many taxa which were identified and described in regional studies can
be used for comparisons to the Muskegon Lake community. For example, the small
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benthic Fragilaria capucina has been found to be associated with floating agal mats
(mostly green algae) (Garrison and Fitzgerald 2005). Staurosira construens is a
planktonic taxon identified by Bradbury and Winter (1976) to be found growing attached
to macrophytes in eutrophic conditions; this taxa increases in the top 8 cm of the core.
Importantly, the shift in habitat of primary productivity is a key indicator of
ecological dynamics in Muskegon Lake. In a study of Canadian Arctic lakes, the
taxonomic shift was towards greater relative abundance in the planktonic community, not
from planktonic to benthic as reflected in the Muskegon lake core (Rühland et al. 2003).
Whereas in a study of shoreline development and commercial cranberry farming in
Wisconsin, USA, Garrison and Fitzgerald (2005) found that the lake experienced an
increase in the density of the epiphytic diatom community, driven by increased nutrient
inputs.
Limitations
There are limitations to this study that need addressed. First, it is important to
note that this study reports relative abundance of fossil diatoms, which is not the same as
diatom biomass. Therefore, what is represented here is not the volume of algae present,
but the relative abundance of each taxon. It is also important to note that inferences from
diatom stratigraphy can be muted, or otherwise convoluted due to varying accumulation
rates, chemical dissolution, or bioturbation/re-suspension during the sedimentation
process (Engstrom and Swain 1986; Wolin and Stoermer 2005). Errors in chronology are
also possible, though have no influence on biological interpretations, only the estimated

136

timing of ecosystem state changes. The relative importance and magnitude of
productivity changes are still reflected accurately.
Also, due to the lack of documented ecological preferences with some of the taxa,
it is difficult to assign specific optimal conditions for each core level and did not allow
for credible diatom inferred reconstructions of total phosphorus or pH, etc. Additionally,
many taxa have a range of tolerance which complicates interpretations (Panizzo et al.
2008). Anderson et al. (1993) and Bradshaw and Anderson (2001) caution the ability of
diatoms to infer nutrients, as they observed little change in diatom species composition
above 100 µg/L (epilimnetic TP). That said, there is adequate variability within the
community structure of the Muskegon Lake diatom biostratigraphy to confidently assert a
shift in primary productivity habitats.
Interpretations from Wolin and Stoermer (2005) were particularly important to
this study, due to the close geographical proximity that adds credibility to the ecological
preferences of the diatoms, as so many other studies are outside of North America (e.g.
Chen et al. 2008; Taylor et al. 2006; Bennion and Appleby 1999). Moreover, the
similarity of species composition in the Wolin and Stoermer (2005) study facilitates a
better evaluation of algal response to changing environmental conditions.
3.5 Conclusions
This chapter examined the history of human influence in Muskegon Lake using
diatom stratigraphy as an indicator of the biological response of the system. Human
impacts have not only changed the relative abundance of individual taxa within
137

Muskegon Lake, but have restructured the dominant habitats of primary productivity.
Floristic changes in the Muskegon Lake core reflect the relative timeline of
anthropogenic impacts in the Great Lakes region and support the hypothesis that human
influence has changed the diatom community structure, and has shifted the dominant
habitat of productivity.
This study demonstrated that Muskegon Lake experienced seemingly irreversible
change in the structure of its primary productivity dynamics in the past two centuries due
to natural and anthropogenic environmental change. The overall diatom community
structure has changed, with distinct shifts in habitat dominance between planktonic and
benthic habitats. Importantly, these changes do not yet appear to be stabilized, and may
indicate the system is in a state of hysteresis.
The biostratigraphic change in Muskegon Lake diatoms was mainly attributed to
various human stressors, based on the timeline of human activity. The diatoms have
clearly undergone dramatic change in response to various stressors, including thermal
pollution and water chemistry changes, resulting in accelerated eutrophication due to
deforestation, agriculture and urbanization of the catchment. Though there was recent
recovery in the water quality of the lake (Steinmann et al. 2008), data indicate that the
biological community is still changing in response to human impacts and will continue to
be influenced by contemporary human activity and legacy effects. This suggests that
further management strategies need to target the non-point source nutrient inputs, and
emphasize the influence of emerging disturbances (e.g. invasive species and climate) to
productivity dynamics.
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This chapter further concludes the following:
The pre-settlement diatom community is markedly different than composition of
the modern assemblage, though diatoms display natural variability in the bottom
of the core, which could reflect conditions unique to the Muskegon Lake system
(large drowned river mouth ecosystem). In phases II (Anthropogenic) and III
(Mitigation), biostratigraphic change suggests a relationship to chronology of
human activity in the watershed.
The shifts in benthic versus planktonic dominated primary productivity is
dramatic in the top of the core; presumably in response to the installation of the
WWTP and invasion of zebra mussels. This suggests a re-structuring of the
diatom community to a condition not resembling the pre-perturbation regime.
These interpretations are predicated on the response of diatom flora alone. As a
result, they only indicate how the biological community is behaving under
anthropogenic stressors. Integrating diatom data with additional environmental
indicators (e.g. geochemistry) can further untangle certain system complexities
that will better identify signals of system response.

139

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CHAPTER 4
INTEGRATING SEDIMENT GEOCHEMICAL CHRONOLOGIES
AND FOSSIL DIATOM STRATIGRAPHY TO VALIDATE SHIFTS IN
PALEOECOLOGICAL PHASES
Abstract
Paleoecological relationships can be difficult to interpret when using a single indicator
from a sediment core. This chapter integrated geochemical and fossil diatom data from a
sediment core from Muskegon Lake, MI, USA, to investigate the response of the lake
system to a variety of natural and human changes. The hypothesis for this investigation
was that continued human disturbances (e.g., industrialization) have been at an intensity
that will not allow ecosystems to return to a pre-disturbance state; and because of other
continuing and emerging stressors (e.g. climate change), ecosystems will not evolve to a
new state of balance (characterized as steady state and/or an observed equilibrium with
biogeochemical processes). Geochemical and diatom inferred trends established in
earlier chapters were compared to examine this hypothesis, which, if true, should show
that the phases for each proxy determined separately are compatible when merged, and
further that the overall contemporary system state is not yet equilibrated (as identified by
stabilized trends among proxies). Results of the integration did reveal a similar temporal
response to initial disturbance in the G1 and D1 phases, which was correlated with the
chronology of human activity. However, there were minor offsets with the disturbance
phases of the core identified by geochemical and biological proxies. The transition to the
„recovery‟ segment showed good overall agreement; though there was dissimilarity
between the geochemistry and biology within recovery phase. Understanding the
relationships among proxies is important within the context of ecological dynamics, and
should be considered in studies where only one proxy may be available.
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4.1 Introduction
Aquatic ecosystems are complex and often respond to stressors in unpredictable
ways (Scheffer et al. 2001). Earlier chapters in this study have evaluated the chemical
and biological indicators archived in lake sediment, both resulting in delineated phases of
environmental response to human perturbations. In chapters 2 and 3, it was suggested
that interpretations from individual indicators could be validated and enhanced using
additional proxies. Therefore, this chapter seeks to integrate earlier biological and
chemical phase delineations to investigate the degree to which a single indicator is useful;
and determine if overall paleoecological interpretations can be improved using more than
one line of evidence.
Integrating indicators can help answer questions about the significance of
feedbacks among system constituents (e.g. physical, chemical and biological) which are
unclear. Specifically, in the Muskegon Lake core, chemical and biological proxies infer
different things; the geochemistry largely reflects extrinsic inputs, while the diatoms
capture intrinsic processes (Carpenter and Brock 2006; Patoine and Leavitt 2006; Das et
al. 2009). Theoretically, merging the proxies will tell more about whole system
dynamics and interrelationships among the system constituents (Scheffer et al. 2001;
Engstrom et al. 2006).
Integration approach
Complexity is inherent in ecological systems as many factors influence the overall
ecological state. Concepts of ecological, planetary and human forcings (all components
of the environmental system) were discussed in Chapter 1 to introduce the complex
nature of systems (Dearing et al. 2006a). Chapters 2 and 3 assessed how individual
149

proxies reflected changing environmental conditions. In chapter 2, sediment
geochemistry was examined to evaluate historic reference conditions, and chapter 3
investigated the record of fossil diatoms to demonstrate a primary productivity regime
shift; both reconstructed impacts of human influence in a highly perturbed watershed in
the Great Lakes region. The intent of this chapter is to gain insight into the
interrelationships among system components resulting from abrupt environmental
change.
The hypothesis of this chapter was that continued human disturbances (e.g.,
industrialization) have been at an intensity that will not allow ecosystems to return to a
pre-disturbance state; and because of other continuing and emerging stressors (e.g.
climate change), ecosystems will not evolve to a new state of balance (characterized as
steady state and/or an observed equilibrium with biogeochemical processes).
This hypothesis was tested using the results of previous chapters, with particular attention
given to G and D phases delineated based on geochemical and productivity indicators,
respectively. For example, to accept this hypothesis, then the interpretation of phases
identified by the sediment geochemistry and the fossil diatom species assemblages will
demonstrate similar responses to environmental changes, but will not yet be stabalized.
The results of integrating proxies in this chapter can be used to infer temporal
environmental change in the lake over time, with interest and consideration of system
thresholds and resiliency. Identifying thresholds in lake systems is critical for avoiding a
system collapse, though this has been reported more frequently in small, shallow lakes
than large lakes like Muskegon Lake (Sondergaard et al. 2001; Scheffer and Jeppesen
2007; Scheffer and van Nes 2007). Though, environmental changes are also of concern
150

for larger lakes under extreme conditions, and to that end, exploring system resiliency in
large systems is an important. Muskegon Lake can provide an example of this due to its
large size and short residence time that should, at least conceptually, support a high
degree of stability compared to shallow lake systems that have been studied (Kenney et
al. 2002; Bayley et al. 2007; Scheffer and Jeppesen 2007).
Additionally, this chapter provides suggestions for a single indicator that best
“fingerprints” specific environmental disturbances. For example, it is possible to
examine data and determine the indicator with the strongest correlation to various human
influences. It was expected that the indicator would vary with the activity; for instance,
deforestation is best identified by increased erosion of soils, which is reflected in the
sediment record by increasing terrestrial elements. This was done for biological and
geochemical proxies in the Muskegon Lake core to provide a quick assessment tool. The
intent of approach is to evaluate if reducing extraneous data collection in
paleoenvironmental investigations is possible.

4.2 Methods
An integrated investigation of ecological dynamics in Muskegon Lake used the
history of the study area, sampling methods, and description of sediment core
characteristics from Chapter 1. Methods for core chronology and sediment geochemical
chronologies are detailed in Chapter 2. Methods for diatom sampling and processing, as
well as fossil diatom taxa data are included in Chapter 3. Chapters 2 and 3 detail
methods for delineating zones for geochemical and diatom phases, respectively.
151

Phase integration
Ecological phases (G and D) determined for the Muskegon Lake core using trends
of geochemistry and diatom taxa were compared by the changes at each sediment level.
This assessed how each proxy identified phases, and contrasted the response of the
indicators.

4.3 Results
Results for sediment geochemistry and fossil diatoms are given in Appendix III IV. Figures detailing geochemical and diatom phases are found in Chapters 2 and 3.
A biogeochemical history of Muskegon Lake‟s response to human perturbation
was reconstructed using the phases delineated by geochemical and biological proxies. A
compilation of phases, with major watershed events is shown in Figure 4.1. Beginning
with the pre-disturbance phases (e.g. GI and DI), there is an offset between the sediment
level which the chronology (and corresponding wood chips) indicates as the onset of
logging in the watershed and the actual proxy response. However, despite the offset in
established chronology, there is good agreement with the indicators for the phase I to
phase II transition. There was a 1 cm difference in the phase transition here, which can
likely be attributed to the resolution of analysis. Both the GIIA and DIIA sub-phases are
completely within the logging period, which was the first major human perturbation in
the watershed. Geochemistry was first to transition to out of IIA, when GIIB starts at 97
cm depth, followed by DIIB transition (92 cm depth). Though this is a 5 cm difference,
when accounting for analysis resolution, there is near agreement with this response as
well. The change to sub-phase IIC for both indicators occurs during the time of the Great
Depression/Dust bowl, at 57 and 61 cm depth for geochemistry and diatom assemblages,
152

respectively. The diatoms are the first to transition here, but again the analysis resolution
makes this shift nearly concomitant. The economically depressed Great Depression was

153

Geochemistry
Phase

Diatom Phase
(average
planktonic:benthic)

DIIIB
(1.97)
GIII

GIIC

Watershed Events
Flood (2004)
Dreissena polymorpha appear (~1990)
Flood (1986)

DIIIA
(13.55)

WWTP Installed (1973)
Clean Air/Water Acts (1970)
US131 opens (1964)
Heavy industry and manufacturing
(1950s - 1960s)

DIIC
(9.41)

WWII (early 1940s)
Great Depression/
Dust Bowl (1930s)

GIIB

DIIB
(3.60)

WWI (1914-1918)
Logging

GIIA

DIIA
(2.41)

1874 Fire
Logging
Pre-logging (1835)

GI

DI
(3.21)

Figure 4.1: A comparison of geochemical and biological phases as related to watershed
events.
154

followed by a resurgence of manufacturing in the city of Muskegon during and post
WWII. The industrialization in the watershed temporally corresponds to significant
geochemical disturbance (sub-phase GIIC), and to the DIIC sub-phase which included
taxa that were tolerant of high nutrient and pollution conditions (see Chapter 3). Next,
the IIC disturbance sub-phases shift to the phase III of recovery. In the recovery phase,
geochemistry shows a singular zone of steadily decreasing concentrations of
anthropogenic elements (see Chapter 2); however, the diatom taxa specify two subphases that are distinguished by a shift dominant productivity habitat at 8 cm depth.
Land use, population and climate data were incorporated to this integration.
Figures 4.2a - 4.2d shows trends from AD 1800 for land use, population, precipitation
and temperature, respectively.

155

100

A.

50

0
200000

B.

100000

0
1800

1900

100

2000
C.

150
8
6
4
D.
100
80
60
1800

1900

2000

Figure 4.2a – d: Trends from 1800 for a) land use change in the Muskegon River
0 Watershed; b) population in Muskegon County; c) precipitation; and d)
temperature in the state of Michigan.
156
150

4.4 Discussion
An integration of geochemical and fossil diatom data in a sediment core from
Muskegon Lake compared phases of human influence to better understand system
response. Results show that the causal agents for many of the chemical and biological
changes in the core were directly related to watershed events. Human activity is the
dominant agent of change in this system, as land use alterations and population increases
have impacted the dynamics and trophic status of Muskegon Lake.
Beginning with phase I, the delay in response of the system at the chronological
start of logging to the G and D phase transition could be due to the time it took for the
system to reflect a response, or attributed to an error in chronology. Both possibilities
reflect the close agreement with the transition, importantly indicating that both proxies
responded at approximately the same time, and/or had the same offset in response to the
logging perturbation. The shift to the IIB sub-phase was associated with the start of
industrialization in the watershed, marked by increased metals and change in select
diatom taxa. The change to the GIIB sub-phase occurred before the change to DIIB,
suggesting that the response to an extrinsic change was inferred more quickly by the
geochemical proxies than the diatom taxa. This may expected, as the erosion associated
with logging would quickly halt export and deposition of geochemical terrestrial proxies
compared to the response of intrinsic processes driving diatom productivity. In contrast,
the transition to sub-phase IIC occurs first for the biological indicator. Though the two
indicators are closely associated, the difference in response at this sediment level may
suggest that the biological system was the first to be impacted by the climate conditions
associated with the Dust Bowl. Alternatively, the lag-time may suggest that the reduction

157

of anthropogenic elements occurred slowly in tandem with a manufacturing slow down.
GIII trends toward a geochemical recovery from industrialization, though the DIII phases
is subdivided to DIIIA and DIIIB; this suggests something is going on biologically in the
lake, which is not significant from a geochemical perspective – it is possible this is
related to the zebra mussel invasive species – which is plausible as it is chronically
supported – or it could be due to lake level changes that is increasing benthic habitat – or
the decrease in water column P, thus decreasing planktonic taxa and allowing the residual
P in sediment to support greater benthic productivity).
It is now possible to return to the questions asked in the beginning of this study to
consider how using the multi-proxy approach furthered an understanding of system
behavior, and how this insight can be a useful tool for other aquatic ecosystems.

How have systems responded to multiple anthropogenic stressors?
Many of the stressor-responses observed in the Muskegon Lake sediment core
appear to be sensitive to a combination of human forcings. The complexity of having
various stressors through time (deforestation, then industry, then invasive species) as well
as those that concurrently influence a system (climate, land use modifications, invasive
species) require a detailed interpretation of high resolution samples. Untangling what
happened when and the subsequent system response to “x” stress by “y” proxy can be
difficult. For example, in this study, direct sensitivity was seen in the geochemical
proxies to logging and industrial events while the biostratigraphy of fossil diatoms
reflected sensitivity to nutrient inputs; indicating that different indicators are proxies for
different stressors. If an indicator is disregarded, it may not be possible to evaluate all

158

agents of change in the system. Merging the stressor-responses using a multi-proxy
approach in the Muskegon Lake system resulted in the three major phases of influence
reflected in the core.
The physical constituent of Muskegon Lake was not directly analyzed in this
investigation. However, a generalization of observed regional conditions can be used to
infer both the state of the system and overall dynamics that may have influenced the
system. For example, the effect of climate is difficult to interpret for Muskegon Lake, as
it is moderated by the adjacent, larger Lake Michigan. To that end, it has been reported
that climate has been changing in the Great Lakes region for at least the past 100 years
(Magnuson et al.1997; 2000). This affects not only lake temperature, which in and of
itself would greatly influence productivity, but also ice phenology, which has the
potential to disrupt seasonal chemical and biological coupling. An example is this
interrelationship between the seasonal influx of nutrients and the Spring diatom blooms
(Winder and Schindler 2004). A shift in one or the other could disjoint the synchrony of
processes that the system relies on for its overall flow of energy.

How does the current ecosystem state compare to the pre-perturbation state?
In chapter 1, the conceptual model for ecological forcings discussed the 2 and 3
component system. If the results from this investigation are put in the context of Figure
1.1 from the first chapter, it illustrates how a change in one constituent can impact the
whole system. For example, in the Muskegon Lake core, we learned that socio-economic
developments (e.g. industrial jobs = population growth and urbanization) can have a
significant impact on the physical, chemical and biological constituents, thus shifting the

159

system from a two component to a three component human-dominated system (Dearing
et al. 2008; Messerli et al. 2000). Using insight from this study, the conceptual figure
was modified to fit the Muskegon Lake ecosystem. Figure 4.3 reconfigures the
component relationships from the original figure, to show the relative influence each has
on the other (depicted by boldness of the arrow). Using the Muskegon Lake ecosystem to
understand the concept, it was indicated that the human forcing has become more
dominant, which is predicted to continue.

Figure 4.3: Conceptual map of Muskegon Lake ecosystem interactions (modified from
Dearing 2006)
Is it possible to infer significant system regime shifts using indirect (e.g. fossil diatom)
proxy methods?
In terms of regime shifts, this study suggests it is possible to identify regime shifts
using indirect proxies, particularly that of fossil diatoms, as primary productivity is an
important indicator of overall system function. Because of the dramatic floristic change
160

observed, especially in the relative abundances of planktonic v. benthic diatoms, the
Muskegon Lake system varies from other systems in that the benthic community, not the
planktonic, becomes most dominant in modern systems (Garrison and Fitzgerald 2005).

Does using multiple proxies (e.g. chemical and biological) improve interpretations of
environmental change?
Using multiple proxies to interpret the Muskegon Lake core did improve the
overall understanding of system dynamics. Without utilizing more than one line of
evidence, there would be greater uncertainty in the phase delineation and less insight
about the geochemical/biological interrelationships observed in the system. Additionally,
identifying the role of social v. natural drivers was more robust using the multi-proxy
approach. This study is unique as it explores a system that has been significantly
impacted by humans in a very short temporal scale. While other studies evaluate long
term dynamics in systems where the environmental response is over thousands of years
and encompasses broader scale influences (see Ekdahl et al. 2007; Dearing et al. 2008),
this study has combined high resolution data with historic observational records to
evaluate the specific role of human influence and specific feedbacks in the chemical and
biological response such as nutrient input and primary productivity. A comparison of
climate attributes (see figures 4.2c-d) and human changes (see figures 4.2a-b) in the
Muskegon Lake region further emphasizes that environmental change in this study has
been dominated by human activity.

Can we predict future ecosystem recovery and/or a stable state scenario due to the
advent of environmental regulations (e.g. Clean Air/Clean Water Acts)?
The dynamics of Muskegon Lake can also be conceptually linked to Figure 1.2,
also from Chapter 1. This figure is evaluated within the context of future uncertainty
161

(Higgins et al. 2002; Bennett et al. 2003), shown in Figure 4.4, and is important to
consider as the cumulative effects of overall global change on the Muskegon Lake system
continues. Importantly, environmental legislation in the past 40 years has put the system
on a trajectory towards scenario C2 (as discussed in Chapter 3), or perhaps an ideal C3.
However, depending on how emerging stressors develop, and how society decide to
respond, the resulting system (depicted by the range within the circle) could potentially
be a severely impacted one, as shown by scenario C1. As this figure represents, it is
important to consider the environmental decision making of different nations, as
developing nations have the greatest potential to shape their impact trajectory. For that
reason, it is important to evaluate ongoing system response to capture the impact of
present-day (and future) human induced stressors (Mayer et al. 2004; Walker and Meyers
2004). Among future stressors, the role of invasive species is critical to the overall status
and dynamics of Muskegon Lake.

162

Figure 4.4: Conceptual model of environmental response to anthropogenic influence in
varying regions delineated by development status; and under contrasting
management strategies through time. (Modified from Garcier 2007)

4.5 Conclusion
The Muskegon Lake core revealed a chronological accumulation of sediment
which recorded a sequence of historical events and stressor-responses in the watershed.
As stated in the first chapter, the goal of this research was to examine environmental
change through the lens of an “environmental systems approach” that would interpret
ecological processes. The overarching hypothesis was that ecosystems highly disturbed
by human activity cannot be expected to return to a pre-disturbance state; and further,
with the influence of climate change and other emerging stressors, ecosystems will not
obtain a new regime (steady state and/or equilibrium). This hypothesis was accepted, as
163

results from chapters 2-4 demonstrate that the current ecological state of the system is not
same as the pre-perturbation state. There have been alterations to geochemical profiles,
as well as significant shifts in the diatom community structure that suggest an altered
ecological state. Further, because of Muskegon Lake‟s fluctuating geochemical
concentrations and dynamic changes in biostratigraphy, it is concluded that this new state
is not stable. Due to the uncertainty of emerging stressors (e.g. climate change, invasive
species, and land use alterations in the watershed), it is not possible to predict when the
system will become stable, and the observed changes are likely irreversible. Revisiting
specific objectives of this study should make clear what the research was able to
accomplish and contribute to the field of study.
The first objective was to determine how aquatic ecosystems responded to
specific perturbations (e.g. logging, industry, urbanization) by using individual
paleoecological proxies (e.g. geochemistry and diatoms). This objective was met by a
detailed analysis of high resolution data that clearly delineated phases of human influence
as recorded by lake sediment. With the geochemical profiles, the anthropogenic proxy
group best reflected many of the stressor-responses in the watershed, particularly the
intense period of industry in the Muskegon area. The terrestrial proxy group captured the
onset of logging, while interpretations of the productivity proxy group led to questions
further addressed by the biological component. The fossil diatoms responded both on an
individual level, and as classified by habitat. The most significant influence to the diatom
community seemed to be triggered recently. The data suggest this is partly in response to
the installation of a waste water treatment facility, and also by recent ecological
influences of cultural nutrient inputs and invasive species (e.g. zebra mussels). Overall,
164

using individual proxies was useful to fingerprint specific watershed scale events.
Though, it was more difficult to clearly define the impact of broader scale stressors (e.g.
climate), suggesting a need for continued monitoring of the ecological status of the
system.
A second objective was to determine the environmental legacy of anthropogenic
stressors by calculating deviations from geochemical reference concentrations and by
identifying ecological regime shifts. This objective was discussed in detail in chapters 2
and 3, that evaluated reference conditions and ecological regime shifts, respectively.
Specifically, it was observed that many modern geochemical concentrations (e.g.
anthropogenic proxy group elements) have not decreased to pre-perturbation
concentrations. This suggests that: 1) the system is still being influenced by the legacy of
contamination, and 2) that the system is under the influence of modern inputs of
anthropogenic elements, likely from existing industrial practices, atmospheric inputs, and
watershed runoff (e.g. agriculture and urban land uses). Given the current scenario of a
continued human-dominated system, the calculated deviations from references are not
likely to return fully to the historical reference, but continue a trajectory of an adapting
reference state. A regime shift from planktonic to benthic dominated primary production
was identified using fossil diatoms. The most dramatic shift is near the top of the core,
and likely reflects a combination of the legacy of nutrients stored in the sediment with the
emergence of zebra mussels which allow greater light penetration. This scenario has led
to a considerable increase in the relative abundance of benthic diatoms. Given this
stressor-response signal, it can be predicted that the biological communities will continue

165

to restructure under the influence of regional climate changes (Magnuson et al. 2000) and
nutrient inputs (Steinman et al. 2008).
Third, developing correlations/relationships among geochemical and diatom
sediment chronologies to infer process (e.g. lag-time and feedback mechanisms). This
chapter integrated geochemical and biological phases determined from earlier chapters to
evaluate how they are related, and what it indicates for overall system behavior.
Coupling the indicators allowed processes, suspected from interpretations of individual
proxies, to be better interpreted. In the anthropogenic phases (II and III for both G and D
indicators), the integrated data support the significant role of human disturbance in
driving system change, as both indicators respond to this influence. Also, using select
responses with the core proxies, it was possible to identify causal agents for the observed
environmental changes (e.g. deforestation and industry). Moreover, this chapter
demonstrated it is possible to link geochemical and biological response (e.g. nutrient
inputs (P) and select diatom taxa). Understanding these relationships are valuable for
environmental management strategies, particularly as threats to aquatic ecosystems
continually evolve.

166

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169

Appendix

170

APPENDIX I

DESCRIPTION OF MUSKEGON LAKE CORE SEDIMENT
CHARACTERISTICS

171

Table A.1: Description of Muskegon Lake Sediment Core Characteristics
Sample
#
1

Thickness
(cm)
1.0

Depth
(cm)
1.0

dark, extremely runny

2

1.0

2.0

dark and very runny

3

1.0

3.0

dark and runny

4

1.0

4.0

dark and runny

5

1.0

5.0

dark and runny

6

1.0

6.0

dark and runny

7

1.0

7.0

dark and runny

8

1.0

8.0

dark and somewhat runny

9

1.0

9.0

dark

10

1.0

10.0

11

1.0

11.0

dark brown

12

1.0

12.0

dark brown

13

1.0

13.0

dark brown

14

1.0

14.0

dark brown

15

1.0

15.0

dark brown

16

1.0

16.0

dark brown

17

1.0

17.0

dark brown

18

1.0

18.0

dark brown

19

1.0

19.0

dark brown

20

1.0

20.0

21

1.0

21.0

dark brown, small flowoiejr?

22

1.0

22.0

dark brown

23

1.0

23.0

dark, moderately thick

24

1.0

24.0

dark, moderately thick

25

1.0

25.0

looks brown, turns darker when mixed

26

1.0

26.0

dark, moderately thick

27

1.0

27.0

dark, moderately thick

28

1.0

28.0

dark, moderately thick

29

1.0

29.0

dark, moderately thick

30

1.0

30.0

31

1.0

31.0

less oil smell, more brown, thinner consistancy

32

1.0

32.0

dark, moderately thick

33

1.0

33.0

dark (brownish)

34

1.0

34.0

dark

Description

172

Table A.1: Description of Muskegon Lake Sediment Core Characteristics, continued
35

1.0

35.0

dark – oil odor

36

1.0

36.0

dark, moderately thick – shell fragments

37

1.0

37.0

dark

38

1.0

38.0

dark – oil odor

39

1.0

39.0

dark, moderately thick

40

1.0

40.0

41

1.0

41.0

dark, moderately thick – shell fragments

42

1.0

42.0

dark, moderately thick

43

1.0

43.0

dark, moderately thick

44

1.0

44.0

dark, moderately thick

45

1.0

45.0

dark, moderately thick – shell fragments

46

1.0

46.0

dark, moderately thick

47

1.0

47.0

dark, moderately thick

48

1.0

48.0

dark, moderately thick – shell fragments

49

1.0

49.0

dark, moderately thick – shell fragments

50

1.0

50.0

dark, moderately thick

51

1.0

51.0

dark, moderately thick

52

1.0

52.0

dark, moderately thick – shell fragments

53

1.0

53.0

dark, moderately thick – shell fragments

54

1.0

54.0

dark, moderately thick

55

1.0

55.0

dark, moderately thick

56

1.0

56.0

dark, moderately thick – shell fragments

57

1.0

57.0

58

1.0

58.0

dark, moderately thick – shell fragments and organic
matter thick stem?)
dark, moderately (plant – shell fragments

59

1.0

59.0

dark, moderately thick

60

1.0

60.0

61

1.0

61.0

dark, thick – organic fragments

62

1.0

62.0

dark, thick

63

1.0

63.0

dark, thick – shells and organic fragments present

64

1.0

64.0

dark, thick – organic fragments

65

1.0

65.0

dark, thick

66

1.0

66.0

dark, thick – shells present

67

1.0

67.0

dark, thick – shells present

68

1.0

68.0

dark, thick

69

1.0

69.0

dark, thick – shells present

173

Table A.1: Description of Muskegon Lake Sediment Core Characteristics, continued
70

1.0

70.0

dark, moderately thick

71

1.0

71.0

72

1.0

72.0

dark, thick

73

1.0

73.0

dark, thick

74

1.0

74.0

dark, thick

75

1.0

75.0

dark, thick

76

1.0

76.0

dark, thick

77

1.0

77.0

dark, thick

78

1.0

78.0

dark, thick

79

1.0

79.0

dark, thick

80

1.0

80.0

81

1.0

81.0

dark, thick

82

1.0

82.0

dark, thick with some tan streaks

83

1.0

83.0

dark, thick

84

1.0

84.0

dark, thick

85

1.0

85.0

dark, thick

86

1.0

86.0

dark, thick

87

1.0

87.0

dark, thick

88

1.0

88.0

dark, thick

89

1.0

89.0

dark, thick

90

1.0

90.0

91

1.0

91.0

dark, thick

92

1.0

92.0

dark, thick

93

1.0

93.0

dark, thick

94

1.0

94.0

dark, thick – more variation in color

95

1.0

95.0

dark, thick

96

1.0

96.0

dark, thick

97

1.0

97.0

dark, thick

98

1.0

98.0

dark, thick

99

1.0

99.0

dark brown, thick

100

1.0

100.0

101

1.0

101.0

dark brown, thick

102

1.0

102.0

dark brown, thick

103

1.0

103.0

dark brown, thick

104

1.0

104.0

dark brown, thick

174

Table A.1: Description of Muskegon Lake Sediment Core Characteristics, continued
105

1.0

105.0

dark brown, thick

106

1.0

106.0

dark brown, thick

107

1.0

107.0

dark brown, thick

108

1.0

108.0

dark brown, thick

109

1.0

109.0

dark brown, thick – small rock/fossil present

110

1.0

110.0

111

1.0

111.0

dark brown, thick – chunk of some sort of matter

112

1.0

112.0

dark brown, thick

113

1.0

113.0

grainy, some stringy matter

114

1.0

114.0

dark brown, thick (very homogenous color)

115

1.0

115.0

dark brown, thick – shell fragments

116

1.0

116.0

dark brown, thick

117

1.0

117.0

dark brown, thick

118

1.0

118.0

dark brown, thick

119

1.0

119.0

dark, thick

120

1.0

120.0

121

1.0

121.0

dark brown, thick

122

1.0

122.0

dark brown, thick

123

1.0

123.0

dark brown, thick

124

1.0

124.0

dark brown, thick

125

1.0

125.0

dark brown, thick

126

1.0

126.0

dark brown, thick

127

1.0

127.0

dark brown, thick

128

1.0

128.0

dark brown, thick

129

1.0

129.0

dark brown, thick

130

1.0

130.0

dark brown, thick – more goopy texture

131

1.0

131.0

dark brown, thick

132

1.0

132.0

dark brown, thick

133

1.0

133.0

dark brown, thick

134

1.0

134.0

dark brown, thick – organic fragments

135

1.0

135.0

dark brown, thick

136

1.0

136.0

dark brown, thick

137

1.0

137.0

dark brown, thick

138

1.0

138.0

dark brown, thick – slightly greenish tinge

139

1.0

139.0

dark brown, thick

175

Table A.1: Description of Muskegon Lake Sediment Core Characteristics, continued
140

1.0

140.0

141

1.0

141.0

dark brown, thick

142

1.0

142.0

dark brown, thick

143

1.0

143.0

dark brown, thick

144

1.0

144.0

dark brown, thick

145

1.0

145.0

dark brown, thick

146

1.0

146.0

dark brown, thick

147

1.0

147.0

dark brown, thick

148

1.0

148.0

dark brown, thick

149

1.0

149.0

dark brown, thick

176

APPENDIX II

MUSKEGON LAKE SEDIMENT CORE POROSITY

177

Table A.2: Muskegon Lake sediment core porosity
Depth (cm)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48

Wet Weight (g)

Dry Weight (g)

%Ø

6.26
10.40
9.66
8.20
8.39
9.31

3.69
4.17
4.20
4.00
4.08
4.20

41.04
59.88
56.51
51.23
51.38
54.92

9.26
9.33
9.43
9.48
8.12
8.23
10.40
11.15
9.70

4.30
4.25
4.20
4.19
3.95
3.99
4.30
4.55
4.28

53.58
54.42
55.43
55.83
51.35
51.58
58.66
59.20
55.84

10.64
10.80
11.55
12.10
11.30
11.34
11.89
9.54
10.95

4.37
4.42
4.54
4.52
4.47
4.58
4.60
4.39
4.61

58.89
59.06
60.75
62.65
60.43
59.62
61.29
54.01
57.88

10.83
10.10
11.37
11.44
10.47
11.31
12.40
9.32
12.24

4.51
4.35
4.59
4.58
4.53
4.71
4.76
4.40
4.77

58.35
56.88
59.62
59.96
56.71
58.37
61.62
52.75
61.08

12.17
11.77
11.55
10.02
11.47
13.24
7.71
6.93

4.79
4.82
4.86
4.41
4.63
5.26
4.38
2.80

60.60
59.02
57.94
55.99
59.67
60.24
43.21
59.69

178

Table A.2: Muskegon Lake sediment core porosity, continued
Depth (cm)

Wet Weight (g)

Dry Weight (g)

%Ø

49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96

6.80

2.63

61.39

8.03
6.57
7.25
7.82
7.79
8.63

2.95
2.62
2.69
2.82
2.63
3.04

63.33
60.19
62.90
63.92
66.27
64.79

7.88
8.42

2.67
2.73

66.18
67.56

6.49
7.83
10.30
6.25
6.82
8.90
6.91
5.85
6.27

2.61
2.78
3.22
2.49
2.79
2.95
2.72
2.59
2.71

59.77
64.46
68.71
60.19
59.09
66.91
60.67
55.77
56.86

7.46
9.17
6.94
8.64
7.06
9.29
8.86
8.19
5.78

2.86
3.22
2.77
3.07
2.75
3.34
3.26
3.20
2.78

61.66
64.85
60.14
64.48
61.03
64.05
63.17
60.95
51.94

7.76
8.35
8.63
5.70
9.05
7.04
7.31
8.89
7.28

3.18
3.23
3.32
2.66
3.28
2.96
2.98
3.38
3.06

58.98
61.27
61.57
53.28
63.80
57.97
59.26
62.01
57.97

7.54
8.14
8.62
7.70
8.69
9.21

3.15
3.33
3.50
3.29
3.62
4.80

58.22
59.14
59.45
57.27
58.37
47.89

179

Table A.2: Muskegon Lake sediment core porosity, continued
Depth (cm)

Wet Weight (g)

Dry Weight (g)

%Ø

97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144

9.30
6.23
7.14

4.24
3.25
3.55

54.45
47.79
50.29

7.20
9.68
7.11
6.73
6.61
9.09
6.11
6.65
6.28

3.35
3.88
3.19
2.94
2.94
3.60
2.84
2.98
2.89

53.46
59.95
55.15
56.27
55.49
60.42
53.50
55.27
54.02

7.65
9.22
5.99
7.58
6.80
7.62
7.45

52.35
53.04
42.55
48.14
46.69
45.10
47.39

6.56

3.65
4.33
3.44
3.93
3.62
4.18
3.92
3.12
3.14

7.06
5.23
6.22
6.04
4.76
7.89
4.68
6.61
6.70
5.79
5.92
5.72
4.96

3.09
2.60
2.87
2.82
2.50
3.23
2.47
2.99
3.03
2.80
2.77
2.74
2.60

56.21
50.30
53.90
53.30
47.56
59.02
47.28
54.78
54.79
51.69
53.17
52.04
47.68

6.50
6.28
6.04
6.63
6.05

2.95
2.85
2.82
2.95
2.40

54.64
54.55
53.37
55.47
60.29

5.99
8.23
7.38
8.47

2.83
3.34
3.16
3.42

52.72
59.46
57.15
59.57

52.21

180

Table A.2: Muskegon Lake sediment core porosity, continued
Depth (cm)
145
146
147
148
149

Wet Weight (g)
8.07
7.84
10.28
7.93
6.91

Dry Weight (g)
3.32
3.29
3.89
3.42
3.13

181

%Ø
58.88
58.03
62.14
56.85
54.77

APPENDIX III

MUSKEGON LAKE CORE SEDIMENT GEOCHEMISTRY

182

Table A.3: Muskegon Lake core sediment geochemistry, continued
Depth
(cm)

Al

K

Ti

Mg

Fe

Mn

As

Ca

P

Sr

Rb

Ba

2

9978.85

2049.04

33.28

10219.67

21253.80

1980.67

13.28

64387.01

1279.41

103.91

14.84

180.78

3

13161.52

1742.96

72.41

15177.78

31780.04

2560.08

11.79

84021.60

1858.27

109.16

16.36

208.00

4

11742.92

1369.38

15.88

15343.99

32625.32

2280.28

9.64

78186.48

2097.85

87.15

12.55

191.76

5

14495.44

1477.47

58.36

17233.82

37730.29

2852.70

11.12

92746.27

1520.56

102.37

14.71

187.93

6

13283.47

1390.72

53.67

16046.40

35409.32

2498.73

11.44

103061.02

1305.57

114.17

14.19

172.48

7

12900.00

1364.79

51.54

15532.28

34835.86

2549.16

11.18

106254.85

1301.05

118.16

14.24

170.89

8

12222.83

1548.15

19.74

13644.09

32367.72

2263.19

12.26

74592.91

1235.43

89.47

14.15

157.46

9

13802.96

1413.02

16.03

14683.60

33333.40

2157.25

12.00

77730.24

1502.96

81.44

13.64

158.40

11

17498.94

1613.21

67.81

19164.54

45196.60

2483.44

12.85

69449.04

1054.65

77.62

16.62

219.41

12

16975.98

1562.05

98.18

18426.76

44202.73

1830.86

13.28

62524.80

897.21

65.43

15.14

139.57

13

19623.06

1748.86

23.12

19415.71

48792.04

1093.90

14.92

62889.39

2168.78

58.20

14.84

140.84

14

13728.39

1210.89

42.03

16136.65

38451.91

1321.61

14.75

54119.28

825.95

63.54

13.60

139.49

15

14933.97

1428.35

67.54

15838.89

39167.74

1260.47

18.21

49692.95

893.59

61.60

15.19

145.90

16

17216.63

1729.91

38.21

15921.96

38980.17

910.13

17.40

46577.40

2205.33

50.30

14.71

144.46

17

16159.96

1652.29

34.09

15078.81

35253.18

967.61

17.52

44633.69

2443.43

49.62

14.45

146.61

18

14984.09

1396.39

20.82

15474.84

34532.26

1034.97

15.91

45520.65

2877.63

48.47

13.53

144.13

19

14151.12

1209.53

17.07

15166.04

32827.43

991.79

16.01

43988.99

2896.46

45.56

11.88

141.53

21

10951.39

1178.70

61.94

11664.82

27305.33

1087.42

19.13

37135.18

2085.22

55.10

12.73

173.39

22

13788.03

1056.41

63.23

14804.91

32353.85

1524.36

18.23

54201.28

2556.97

60.45

11.50

191.09

23

17257.00

1382.86

90.93

15993.83

35775.31

1642.18

17.22

61089.51

2697.51

63.19

14.07

197.18

24

17160.39

1286.53

81.18

16092.93

36987.15

1730.84

14.26

60166.38

2604.11

60.64

13.49

187.86

25

14413.81

1201.67

64.73

14944.98

30874.69

1089.96

12.97

52910.25

1922.24

64.73

13.01

226.17

26

13051.68

982.61

46.03

14398.95

30940.97

1102.10

11.51

61490.76

1929.18

73.24

11.07

203.21

27

15008.04

1280.67

72.93

13511.52

31413.70

1413.04

13.50

49267.17

2613.93

65.63

13.65

249.13

28

7220.00

1111.81

62.31

6551.96

14803.51

688.87

11.84

24257.32

2384.97

63.05

12.08

222.02

29

17746.38

1289.36

76.23

16252.34

33943.19

1478.72

13.51

76744.26

2175.62

83.77

13.64

231.45

183

Table A.3: Muskegon Lake core sediment geochemistry, continued
Depth
(cm)

Al

K

Ti

Mg

Fe

Mn

As

Ca

P

Sr

Rb

Ba

31

14072.08

1293.96

69.46

13207.36

29508.01

1417.53

12.49

53707.14

2622.68

72.73

13.94

226.41

32

16261.76

1173.79

75.30

15118.36

33637.67

1726.96

13.73

92102.68

2730.44

94.91

12.66

239.45

33

12304.77

1124.82

75.27

11654.88

28547.51

1532.32

12.75

59683.30

3057.03

82.58

12.19

237.14

34

14526.80

1343.12

84.97

12835.95

32647.93

1575.60

12.51

53459.26

2866.67

75.16

13.73

247.12

35

18891.98

1103.62

59.74

20006.72

42612.13

1977.24

11.34

91088.25

2798.13

82.85

12.50

252.72

36

14120.81

1056.92

57.62

15168.15

32157.96

1612.10

11.32

73987.69

3005.84

89.51

12.19

238.66

37

24464.19

1345.50

92.77

20693.89

45994.10

2313.32

12.03

103809.17

3075.48

89.48

14.06

226.90

38

15375.47

1096.65

65.38

15909.36

33532.02

1568.81

11.10

99313.72

2700.21

109.42

12.06

228.77

39

15449.79

946.95

61.22

16742.53

41090.25

1343.98

10.52

52808.51

2975.81

93.44

10.60

203.76

41

21072.39

1183.43

85.00

16910.65

47799.35

1946.96

12.72

79235.00

2752.37

77.93

12.78

334.61

42

20509.83

1296.88

87.95

16846.79

44226.28

2067.31

12.09

73754.91

2706.75

72.44

13.40

222.44

43

13969.94

1117.55

70.06

14643.56

35904.70

1724.34

10.92

54789.16

3670.06

71.10

12.51

224.28

44

16023.66

1478.50

91.53

13197.23

31937.15

1417.56

12.61

51339.93

2665.36

68.52

14.68

228.89

45

12527.65

980.95

77.71

11566.95

40424.84

2334.99

10.11

48507.99

4885.64

58.25

10.50

192.59

46

15133.26

1176.01

51.74

14787.34

34381.55

1323.82

10.11

72023.61

2139.46

82.02

12.60

225.15

47

13598.71

1238.05

75.11

10933.26

30202.79

1021.89

11.12

52813.95

1726.39

70.99

12.38

198.52

48

17771.88

1252.55

66.30

13917.62

39991.49

972.67

11.35

63432.48

1255.37

69.52

12.67

207.49

49

13531.32

1157.34

57.17

11562.42

31991.36

1023.54

11.30

49516.63

1726.07

66.26

12.18

194.75

51

13706.86

1405.54

75.26

10914.10

35490.67

1322.67

15.77

33819.81

2520.13

54.76

14.59

192.86

52

14955.25

1182.78

51.91

13886.94

36632.76

1671.52

14.15

55504.28

2698.20

68.72

12.89

212.46

53

19072.18

1386.82

69.48

16170.08

46636.19

1283.05

12.58

50693.51

1884.36

53.96

14.28

184.74

54

24222.46

1159.48

33.71

24736.72

59718.79

1809.72

9.01

73087.26

1681.19

58.29

13.43

213.52

55

16013.58

1210.82

56.34

13896.09

40082.30

1064.40

13.62

46747.53

1351.54

57.35

12.82

190.02

56

14763.40

1598.52

25.66

11871.60

34141.80

604.18

14.48

40655.60

2065.80

53.40

14.32

194.18

57

14183.04

1326.27

17.44

13771.20

32102.76

706.92

12.09

46882.84

2299.41

55.90

13.00

193.25

58

10295.63

1023.17

17.77

9832.10

25927.51

634.89

11.79

50965.94

2012.45

63.28

9.91

162.55

184

Table A.3: Muskegon Lake core sediment geochemistry, continued
Depth
(cm)

Al

K

Ti

Mg

Fe

59

11923.82

1052.08

17.05

11870.89

61

13114.15

844.62

21.09

14512.26

62

15142.34

1342.70

54.60

63

21962.34

1382.28

64

18232.04

65
66

Mn

As

Ca

P

Sr

Rb

Ba

35989.04

643.40

13.52

52347.26

2333.84

59.89

10.19

178.70

39978.87

1123.40

7.00

50430.19

1668.94

61.92

10.08

178.70

14335.74

37799.15

1094.04

13.00

52997.87

1546.45

75.60

14.64

208.02

66.27

19073.45

56997.36

1588.51

15.33

59761.02

1745.95

61.32

14.39

199.89

1167.51

55.88

17565.31

55927.14

1577.76

15.53

64926.12

1807.29

62.35

12.63

182.12

12428.39

1018.81

51.82

12619.07

37058.69

1194.28

12.86

70744.92

1747.44

77.18

11.27

176.02

20247.45

1417.35

76.70

18911.41

48888.39

1781.47

13.40

77783.91

2265.52

69.33

14.97

183.46

67

16148.16

1572.05

58.24

16149.59

35723.77

1330.33

11.35

38249.59

2240.68

52.36

17.56

201.86

68

17505.14

1798.66

71.34

16694.24

34369.14

1107.41

11.28

42742.39

1652.65

61.01

19.61

215.41

69

15122.80

1422.26

40.38

16229.71

33786.61

1096.03

8.95

37840.59

1706.30

51.23

16.55

198.70

71

15137.75

1840.13

79.08

13067.22

28884.16

910.31

10.64

38108.29

1295.80

60.57

19.34

199.17

72

15664.24

1490.25

49.25

16550.29

34711.85

1064.44

6.88

36441.49

1488.51

52.41

16.39

199.58

73

17247.57

1889.36

65.13

15610.67

33050.56

885.21

9.53

39007.12

1207.79

56.48

20.77

210.60

74

18396.31

1832.09

67.83

15878.69

34876.84

929.10

10.51

41110.86

1039.20

64.41

19.80

443.83

75

15969.55

1385.93

30.27

16952.88

36915.43

1180.25

7.49

37526.34

1168.56

50.00

16.95

201.83

76

19079.87

1827.69

64.88

16506.42

36197.64

999.57

10.11

43477.30

1038.99

76.49

19.64

1194.71

77

18142.68

965.71

12.72

22097.45

48607.86

1276.65

5.01

54291.08

1278.17

51.23

12.51

200.08

78

18699.17

1564.05

46.51

19408.88

40917.15

1085.74

10.89

52205.37

1350.52

59.92

18.14

195.27

79

18191.22

1754.76

73.28

17074.95

40259.31

1361.03

15.69

32972.81

1555.58

63.75

18.23

186.47

81

18191.22

1718.31

47.90

17074.95

40259.31

1361.03

11.58

32972.81

1788.35

42.46

19.64

169.64

82

21176.20

2216.16

94.30

17351.77

42280.17

1255.32

13.53

35610.44

1289.60

45.76

22.30

171.94

83

23119.83

1564.77

42.74

20565.61

49805.27

1771.10

9.54

37535.44

1793.76

43.29

17.55

175.11

84

19480.26

1776.81

52.02

20454.23

45896.96

1739.26

11.32

39648.16

1539.44

45.68

18.68

179.78

85

19305.79

1930.39

59.48

19425.11

44911.37

1925.97

11.82

35064.59

1563.15

43.07

20.26

169.08

86

22331.81

2197.69

68.63

21200.00

49343.36

2030.94

11.29

36849.24

1479.76

43.25

22.85

173.18

87

21703.39

2194.47

65.06

20361.86

43440.47

1551.06

8.64

33025.21

1255.51

40.00

23.20

169.43

185

Table A.3: Muskegon Lake core sediment geochemistry, continued
Depth
(cm)

Al

K

Ti

Mg

Fe

Mn

As

Ca

P

Sr

Rb

Ba

88

19764.73

1938.41

61.67

20412.79

46889.53

1512.79

9.52

33246.32

1134.59

44.50

20.83

361.98

89

19411.43

2184.09

64.22

19463.52

47556.26

1560.66

8.53

31330.99

1469.47

42.59

22.97

168.09

91

20812.55

2182.18

66.37

20243.73

43366.42

1335.06

8.25

30753.51

1180.90

42.60

25.85

182.07

92

16419.61

1860.11

43.00

19197.63

42695.26

1376.29

6.49

31231.90

1039.70

42.72

20.84

259.46

93

21146.90

2226.99

78.64

22510.12

53429.55

1691.32

8.61

34736.36

1323.67

42.43

25.89

176.25

94

12249.82

1859.87

37.36

14261.72

34161.90

1084.98

4.58

22152.75

1178.59

38.10

20.20

161.01

95

19714.76

1919.19

49.25

21345.53

49345.11

1655.51

4.05

34543.87

899.77

34.37

20.08

147.23

96

10069.06

872.03

14.10

12685.62

28730.07

964.49

3.09

19722.00

502.35

18.13

10.50

90.02

97

14135.39

1388.07

34.99

16857.65

36963.02

1338.57

2.13

26174.55

851.99

25.92

15.09

111.91

98

14020.83

1458.50

36.36

16958.63

35885.15

1235.65

2.23

26365.86

820.57

26.38

15.51

113.68

99

13906.26

1528.93

37.74

17059.60

34807.27

1132.73

2.32

26557.17

789.15

26.83

15.94

115.45

101

17124.90

1866.24

43.47

19988.82

42338.43

1566.47

3.73

31314.31

1127.04

35.69

19.45

175.04

102

9541.30

1677.04

34.39

11740.22

24966.52

866.09

2.22

18028.26

1396.37

34.83

18.70

152.89

103

13440.78

1740.89

38.00

15520.32

35722.88

1259.27

3.41

25370.02

1324.30

36.20

19.17

154.17

104

17340.26

1804.73

41.61

19300.43

46479.23

1652.46

4.60

32711.78

1252.23

37.58

19.64

155.44

105

21704.27

2323.10

72.03

21035.04

52554.27

1588.89

6.50

33398.08

1376.67

40.71

23.31

164.47

106

15560.92

2175.88

55.97

16071.85

38277.31

1126.26

6.05

25220.17

1246.68

41.70

22.37

167.14

107

20578.79

2285.97

59.03

20559.96

48957.14

1388.31

5.02

34301.52

1116.56

41.43

23.25

170.11

108

15908.95

1646.20

39.50

17355.46

44594.76

1169.87

3.12

28096.94

947.38

36.24

18.58

146.38

109

17486.87

1799.80

53.41

17360.39

49704.38

1175.71

4.11

28461.05

931.12

40.00

19.37

152.28

111

12584.99

1185.50

51.52

12751.43

44771.08

960.04

2.34

23085.65

1371.72

32.47

13.69

115.17

112

8281.96

608.67

24.98

11472.35

45715.29

959.61

0.24

20968.24

1012.45

26.16

8.35

97.55

113

6625.26

633.62

33.20

7418.32

29993.26

527.37

0.72

13765.68

559.03

16.23

7.66

62.40

114

7155.11

693.43

35.84

8455.68

31520.04

574.95

1.52

15856.45

517.07

18.79

8.69

69.52

115

9291.51

813.95

40.00

10214.01

41718.68

733.33

3.52

18360.72

579.70

21.80

10.00

80.17

116

10242.73

937.03

39.49

11274.23

41903.52

782.60

5.62

19979.52

479.16

26.06

11.17

125.37

186

Table A.3: Muskegon Lake core sediment geochemistry, continued
Depth
(cm)

Al

K

Ti

Mg

Fe

Mn

As

Ca

P

Sr

Rb

Ba

117

15053.64

1505.70

59.91

15007.95

50228.70

1020.31

11.85

25286.75

570.60

29.71

16.31

111.90

118

18388.04

1797.49

68.71

17563.73

56289.80

1182.35

12.29

28533.33

618.76

34.47

18.84

130.75

119

14913.52

1326.95

29.25

16676.82

51493.78

1169.10

4.74

28356.01

616.91

31.46

15.94

123.33

121

15213.32

1668.26

46.69

15493.13

47777.22

1152.27

7.18

25998.80

699.90

34.04

18.77

133.87

122

15513.11

2009.57

64.14

14309.43

44060.66

1135.45

9.61

23641.60

782.89

36.62

21.60

144.41

123

21903.25

2003.55

59.81

19786.80

63677.92

1640.04

9.55

31279.00

761.36

37.71

21.52

148.01

124

18951.08

1693.30

38.36

18643.97

59521.98

1712.07

4.07

30016.38

808.43

36.08

19.59

147.24

125

17123.58

1740.96

41.42

16170.09

54256.99

1564.85

3.21

26174.24

808.65

37.90

20.00

145.90

126

14647.40

2096.73

64.52

12799.13

44018.61

1208.44

8.59

20259.74

847.90

36.30

22.23

150.65

127

18924.00

1862.73

47.45

17670.73

60925.45

1815.09

5.71

27993.64

962.67

38.58

20.75

150.27

128

15188.45

1423.11

41.20

15020.52

52515.74

1429.08

3.92

24038.65

761.00

30.76

16.57

201.22

129

18832.75

2158.58

65.11

17964.63

60805.24

1474.89

5.87

28197.60

931.62

42.38

23.84

169.78

130

15337.65

1847.35

48.29

17245.27

41208.44

1573.46

3.89

28154.73

1363.21

38.37

19.59

157.37

131

6985.83

1766.60

47.63

7761.54

22022.27

584.62

5.97

12659.72

721.54

34.47

19.05

134.43

132

17441.03

1782.16

55.98

19954.85

57185.57

1597.94

10.06

33598.97

1041.24

39.22

19.55

156.95

133

18864.10

1915.73

63.78

20382.91

57002.14

1499.15

7.18

32651.28

699.29

35.83

20.26

140.28

134

24123.83

1863.06

49.02

25564.68

73471.28

1953.40

5.98

41042.77

771.32

36.13

20.45

145.57

135

8646.15

975.04

9.64

12953.85

34867.52

938.03

4.69

21527.78

739.10

33.59

12.44

135.41

136

22142.74

1456.14

32.82

28260.79

74115.35

2013.69

3.40

47918.26

767.68

34.92

17.32

138.65

137

16261.87

1521.76

45.88

20387.36

53003.27

1437.25

3.70

34945.75

710.87

34.84

16.78

133.62

138

16544.69

1726.41

56.27

20390.36

51827.25

1531.63

6.49

38999.63

796.33

44.72

18.72

145.48

139

16827.51

1826.14

56.69

20393.36

50651.23

1626.00

9.10

43053.51

829.86

50.92

19.20

154.48

141

17381.07

1852.96

59.40

19296.30

50004.32

1795.06

9.92

35584.57

806.30

39.77

19.51

148.56

142

13824.06

1370.53

31.53

16658.58

45706.69

1777.20

3.98

28514.64

866.84

36.86

16.44

150.59

143

17903.18

1855.49

67.54

18511.86

56701.27

2101.48

4.36

30361.23

1280.13

37.29

20.38

150.59

144

17384.43

1657.12

53.66

17718.86

57769.60

1718.13

3.41

28582.23

1059.65

37.78

18.74

305.02

187

Table A.3: Muskegon Lake core sediment geochemistry, continued
Depth
(cm)

Al

K

Ti

Mg

Fe

Mn

As

Ca

P

Sr

Rb

Ba

145

15153.55

1230.93

27.91

17272.41

53107.51

1386.00

1.46

28179.31

744.46

31.85

15.96

142.84

146

15813.10

1554.54

43.86

16503.06

50120.52

1311.79

5.11

26972.05

763.78

34.37

18.01

147.84

147

18261.20

1732.44

54.68

18173.80

56159.00

1553.80

6.54

33932.40

837.28

36.96

19.36

151.06

148

16409.98

1395.27

41.75

17007.94

52894.50

1543.38

4.40

29628.72

709.59

31.00

16.01

128.90

188

Table A.3: Muskegon Lake core sediment geochemistry, continued
Depth
(cm)

Sn

Cr

Co

Ni

Cu

Mo

Cd

Pb

Zn

U

Hg

2

0.65

46.16

6.22

19.89

48.09

1.47

2.17

50.61

136.90

0.78

0.26

3

0.49

53.35

8.52

22.45

54.53

0.86

2.16

59.49

215.56

0.78

0.12

4

0.45

45.99

5.32

19.57

51.50

0.90

2.21

60.11

159.21

0.71

0.15

5

0.44

49.56

7.95

21.89

53.03

0.93

1.93

57.05

152.26

0.77

0.14

6

0.47

47.90

7.82

19.98

51.65

1.02

1.84

55.78

158.31

0.78

0.14

7

0.38

49.62

8.04

20.11

53.19

1.03

1.81

57.85

156.12

0.78

0.14

8

0.51

49.63

6.16

20.08

54.67

1.50

2.20

61.38

151.14

0.93

0.12

9

0.42

54.23

5.91

24.58

53.91

1.46

2.31

65.40

182.47

0.95

0.14

11

0.57

72.78

8.49

23.61

59.96

1.89

2.57

83.63

440.64

1.10

0.16

12

0.80

86.23

8.05

23.54

61.72

2.83

3.01

99.59

245.10

1.09

0.19

13

0.82

98.24

5.12

23.08

61.92

3.59

4.12

119.98

259.10

1.20

0.22

14

0.81

135.08

7.63

26.29

71.27

3.69

4.62

135.87

345.76

1.00

0.40

15

0.92

146.47

7.93

28.44

75.68

4.38

4.94

144.57

287.67

1.07

0.25

16

1.45

138.44

4.37

25.69

67.44

5.63

5.35

142.90

266.06

1.09

0.26

17

1.38

138.11

4.51

25.32

68.26

5.34

5.44

145.38

265.00

1.06

0.27

18

1.20

140.02

4.47

25.55

66.97

4.39

5.42

150.02

279.46

0.90

0.25

19

1.42

148.69

4.79

25.97

66.53

4.25

5.60

146.34

363.94

0.86

0.24

21

1.83

236.10

8.10

38.87

78.89

6.52

7.72

158.42

457.51

0.92

0.27

22

2.44

339.94

8.87

44.17

82.46

8.78

10.53

174.36

517.39

0.79

0.35

23

2.82

412.00

8.33

39.34

90.47

9.40

10.64

184.36

481.73

0.91

0.35

24

2.61

392.38

7.71

34.37

87.17

9.29

9.57

176.15

421.01

0.88

0.34

25

2.34

398.68

7.66

35.65

81.30

10.84

10.29

176.17

447.18

0.90

0.36

26

2.44

413.80

7.21

35.71

79.43

9.89

10.97

172.21

431.30

0.78

0.40

27

3.20

452.04

6.89

38.63

88.17

10.17

11.63

183.39

565.07

0.83

0.43

28

2.72

403.05

6.33

33.79

80.95

9.57

10.41

170.19

703.07

0.72

0.42

29

2.57

434.85

7.70

37.23

83.62

9.91

10.57

173.64

412.30

0.79

0.39

189

Table A.3: Muskegon Lake core sediment geochemistry, continued
Depth
(cm)

Sn

Cr

Co

Ni

Cu

Mo

31

2.68

429.07

7.32

37.90

82.73

32

3.37

506.42

7.88

42.70

94.55

33

3.90

506.31

7.70

43.60

34

3.86

489.80

7.86

35

3.84

456.40

36

3.38

37

2.86

38

Cd

Pb

Zn

U

Hg

6.62

9.91

169.42

355.78

0.80

0.38

3.08

10.96

179.10

407.78

0.75

0.47

94.14

2.75

10.98

183.43

373.67

0.80

0.48

44.58

90.52

3.01

10.81

188.17

435.45

0.89

0.46

8.08

38.94

86.19

2.44

10.82

188.40

402.33

0.76

0.49

489.04

7.88

37.58

96.50

1.34

12.34

191.63

397.64

0.72

0.54

466.66

7.23

34.10

91.29

1.27

11.42

175.79

357.71

0.76

0.57

2.33

405.51

6.88

31.64

83.72

1.19

10.48

165.68

343.04

0.71

0.56

39

2.53

404.96

6.00

29.09

83.01

0.98

11.04

154.32

422.61

0.64

0.54

41

2.89

417.96

6.78

29.09

86.24

1.33

18.02

188.15

597.87

0.87

0.53

42

2.54

406.90

7.52

26.84

95.56

1.30

18.42

178.42

395.24

0.85

0.45

43

3.21

353.17

7.13

25.16

93.54

1.10

18.22

171.39

528.23

0.82

0.47

44

2.50

355.18

7.21

26.34

98.45

1.33

16.82

193.14

410.65

0.94

0.47

45

3.76

299.11

5.21

22.05

86.72

1.19

12.76

176.26

335.46

0.78

0.47

46

1.61

320.67

6.12

28.00

95.36

1.20

14.18

201.37

351.70

0.94

0.52

47

1.59

329.18

5.06

23.18

95.73

1.42

14.36

177.15

308.48

1.16

0.42

48

1.50

295.50

5.76

22.83

100.71

1.62

14.99

192.24

330.10

1.07

0.42

49

1.73

260.09

5.64

21.77

92.96

1.77

16.37

192.89

311.81

0.97

0.43

51

2.53

165.85

7.43

23.94

78.90

1.87

14.38

199.60

335.26

1.05

0.45

52

2.76

192.14

6.85

23.19

93.88

1.39

18.07

271.69

383.25

0.90

0.44

53

3.10

171.14

6.76

22.40

77.26

1.88

17.22

195.86

306.34

0.98

0.44

54

2.66

185.36

6.78

24.75

80.24

1.47

17.82

197.21

389.09

0.89

0.43

55

3.62

227.63

5.91

21.77

85.04

1.71

18.17

167.92

429.40

0.91

0.45

56

3.64

200.70

4.20

22.74

70.52

2.12

17.84

148.04

383.60

1.06

0.44

57

2.78

160.28

4.02

22.25

66.61

1.26

17.42

137.71

269.53

0.83

0.44

58

2.58

157.86

2.14

15.61

54.91

1.14

15.96

119.32

198.58

0.68

0.37

190

Table A.3: Muskegon Lake core sediment geochemistry, continued
Depth
(cm)

Sn

Cr

Co

Ni

Cu

Mo

Cd

Pb

Zn

U

Hg

59

4.12

183.27

3.42

18.71

72.95

1.64

20.15

144.52

238.64

0.83

0.50

61

5.36

220.38

6.51

22.55

87.72

1.28

18.81

184.00

283.09

0.87

0.54

62

3.17

312.32

6.72

21.94

89.36

1.32

17.85

213.36

288.64

0.89

0.59

63

3.50

362.52

7.08

22.50

84.01

1.53

15.40

298.25

615.35

0.94

0.74

64

4.16

335.51

6.00

20.63

82.80

1.45

14.16

324.12

251.78

0.84

0.61

65

3.62

344.39

5.53

18.14

71.89

1.06

10.91

221.93

227.14

0.70

0.51

66

3.42

290.94

6.74

20.84

74.22

0.98

11.65

224.28

258.11

0.75

0.54

67

2.56

201.19

7.36

24.41

78.32

0.59

14.90

268.07

296.39

0.78

0.58

68

1.87

186.13

8.11

27.41

78.85

0.51

15.97

292.33

335.37

0.78

0.62

69

1.57

189.83

7.18

25.88

83.24

0.44

19.31

308.33

296.19

0.71

0.64

71

1.23

115.65

8.49

27.02

79.56

0.48

16.54

262.12

299.08

0.79

0.69

72

1.26

96.08

8.07

27.32

90.99

0.40

17.27

262.47

462.96

0.76

0.74

73

0.92

99.21

8.50

29.48

92.85

0.41

17.23

268.63

271.80

0.90

0.73

74

0.94

97.21

8.44

32.62

97.60

0.51

17.58

268.24

1170.25

0.94

0.67

75

0.91

85.33

7.76

29.05

100.84

0.39

18.17

272.14

267.88

0.78

0.81

76

1.01

77.43

7.90

29.66

111.13

0.45

20.39

234.75

1275.87

0.88

0.81

77

1.46

49.83

7.79

30.93

161.23

0.64

24.12

134.82

434.65

1.04

0.77

78

1.05

44.13

8.45

30.83

107.46

0.70

5.12

108.33

305.45

0.97

0.71

79

1.31

38.38

7.95

32.65

95.80

0.80

3.06

107.39

258.36

0.93

0.63

81

0.75

30.28

7.82

25.16

49.89

0.45

1.61

77.73

183.92

0.79

0.56

82

0.61

32.67

8.83

25.80

50.92

0.75

1.86

78.68

178.25

1.02

0.53

83

0.78

31.54

8.99

25.08

51.29

0.55

1.67

101.37

187.47

0.86

0.71

84

0.54

36.12

8.92

23.32

57.31

0.48

1.63

118.05

213.58

0.93

0.75

85

0.43

34.55

9.25

22.02

50.13

0.43

1.42

99.94

151.82

0.86

0.61

86

0.35

33.64

9.43

23.07

43.38

0.41

1.24

72.11

156.56

0.96

0.49

87

0.25

33.07

9.24

22.99

33.71

0.36

1.17

57.80

146.36

0.87

0.33

191

Table A.3: Muskegon Lake core sediment geochemistry, continued
Depth
(cm)

Sn

Cr

88

0.27

89

0.29

91

Co

Ni

Cu

Mo

Cd

Pb

Zn

U

Hg

32.73

9.57

23.29

33.49

0.52

1.09

61.07

486.59

0.87

0.34

32.57

10.07

23.74

29.67

0.35

0.95

57.10

151.08

0.88

0.30

0.18

34.93

11.16

27.51

27.38

0.37

0.74

45.39

115.52

1.00

0.17

92

0.15

31.40

9.96

25.28

25.97

0.39

0.75

47.65

488.04

0.88

0.19

93

0.21

36.91

11.62

27.06

24.50

0.36

0.66

45.03

113.31

1.00

0.15

94

0.15

30.26

10.26

24.38

21.25

0.26

0.55

38.75

143.46

0.88

0.14

95

0.10

27.88

8.73

21.85

17.63

0.29

0.44

31.04

99.56

0.77

0.13

96

0.09

14.92

3.81

11.13

9.46

0.17

0.26

17.36

78.65

0.44

0.08

97

0.10

20.60

6.38

16.60

12.47

0.22

0.32

21.27

65.84

0.64

0.06

98

0.10

21.20

6.42

17.09

12.86

0.21

0.30

20.98

58.93

0.65

0.07

99

0.10

21.80

6.46

17.58

13.25

0.20

0.28

20.69

52.02

0.67

0.09

101

0.12

27.98

9.71

24.63

17.53

0.31

0.33

25.04

100.57

0.80

0.08

102

0.09

27.17

9.26

23.59

17.37

0.30

0.33

23.93

68.30

0.74

0.08

103

0.09

27.79

9.36

23.46

17.20

0.32

0.36

23.63

71.12

0.74

0.08

104

0.09

28.42

9.46

23.34

17.02

0.34

0.39

23.32

73.94

0.75

0.08

105

0.13

31.86

9.87

23.95

17.05

0.34

0.38

21.77

73.12

0.81

0.07

106

0.11

31.68

9.96

24.75

17.86

0.32

0.40

22.18

82.12

0.84

0.12

107

0.11

32.27

9.83

24.61

17.38

0.28

0.39

20.97

100.67

0.80

0.09

108

0.09

27.42

8.80

20.63

14.89

0.24

0.35

18.58

64.48

0.68

0.10

109

0.09

28.53

8.18

19.98

14.40

0.26

0.37

17.05

111.14

0.72

0.07

111

0.09

20.93

5.74

12.23

8.76

0.24

0.29

9.69

54.50

0.51

0.08

112

0.08

17.67

5.90

10.73

8.35

0.24

0.29

8.98

62.02

0.41

0.08

113

0.04

13.12

3.05

5.54

4.11

0.17

0.17

4.93

25.33

0.29

0.05

114

0.04

14.97

3.83

7.53

5.59

0.23

0.21

5.99

31.83

0.35

0.03

115

0.11

17.01

5.03

8.87

6.18

0.23

0.25

6.35

63.38

0.40

0.05

116

0.04

18.74

6.10

11.08

8.00

0.29

0.33

6.37

320.81

0.48

0.03

192

Table A.3: Muskegon Lake core sediment geochemistry, continued
Depth
(cm)

Sn

Cr

Co

Ni

Cu

Mo

Cd

Pb

117

0.07

25.21

8.01

15.61

10.62

0.44

0.38

118

0.08

28.39

8.59

18.47

12.31

0.41

0.37

119

0.04

26.05

8.28

17.79

12.34

0.32

121

0.05

28.99

9.04

20.27

13.76

122

0.06

31.93

9.80

22.75

123

0.09

31.93

9.94

124

0.06

30.30

10.06

125

0.09

30.17

126

0.09

127
128

Zn

U

Hg

8.39

57.15

0.71

0.04

8.96

207.02

0.76

0.05

0.36

9.03

55.75

0.71

0.05

0.38

0.39

9.73

61.76

0.82

0.05

15.18

0.43

0.41

10.43

67.77

0.92

0.05

22.68

15.37

0.41

0.41

10.50

87.86

0.87

0.05

22.33

14.96

0.34

0.39

10.32

67.22

0.78

0.05

9.85

21.97

14.48

0.31

0.37

10.09

78.54

0.76

0.05

33.05

10.06

24.11

14.87

0.32

0.39

10.04

148.81

0.80

0.05

0.05

31.62

10.45

23.84

15.65

0.29

0.45

10.40

83.27

0.82

0.05

0.06

25.28

9.14

19.38

12.95

0.26

0.36

8.84

282.95

0.66

0.04

129

0.07

36.20

11.53

26.40

18.08

0.37

0.46

11.86

77.01

0.96

0.04

130

0.10

28.70

9.59

23.54

17.35

0.33

0.37

10.77

85.10

0.72

0.04

131

0.04

28.97

9.27

20.81

14.31

0.43

0.34

9.68

59.01

0.79

0.05

132

0.08

30.37

10.12

22.37

15.20

0.43

0.39

10.43

188.41

0.82

0.05

133

0.09

29.62

9.23

20.96

14.83

0.32

0.34

9.76

80.90

0.77

0.05

134

0.02

30.91

9.81

22.17

15.15

0.30

0.38

10.23

68.15

0.81

0.04

135

0.04

25.45

9.19

19.74

14.10

0.21

0.34

9.85

66.47

0.68

0.04

136

0.06

28.46

9.23

21.14

15.35

0.33

0.39

10.04

60.60

0.77

0.04

137

0.07

27.60

8.71

19.30

14.07

0.44

0.39

9.26

60.72

0.72

0.05

138

0.04

30.10

9.57

21.53

15.24

0.52

0.39

9.90

57.73

0.85

0.04

139

0.04

31.08

10.22

22.65

15.96

0.56

0.40

10.26

63.49

0.88

0.06

141

0.06

30.70

9.90

21.79

14.92

0.45

0.39

10.02

67.61

0.80

0.04

142

0.04

28.05

9.62

21.25

17.37

0.38

0.40

9.92

193.39

0.70

0.04

143

0.08

30.83

9.70

21.67

14.39

0.34

0.40

10.13

67.42

0.74

0.04

144

0.07

29.19

9.65

21.52

14.29

0.29

0.38

9.73

545.71

0.73

0.04

193

Table A.3: Muskegon Lake core sediment geochemistry, continued
epth
(cm)

Sn

Cr

Co

Ni

Cu

Mo

Cd

145

0.02

26.73

8.92

19.57

13.89

0.34

0.39

146

0.09

29.30

9.28

22.10

19.04

0.39

0.39

147

0.04

30.48

9.76

21.84

15.26

0.44

0.40

148

0.04

25.50

8.23

17.68

12.77

0.33

0.35

194

Pb

Zn

U

Hg

9.66

76.39

0.73

0.04

11.72

158.89

0.85

0.04

10.06

73.48

0.86

0.04

8.59

60.88

0.67

0.04

APPENDIX IV

RELATIVE ABUNDANCES OF COMMON MUSKEOGN LAKE DIATOMS

195

Table A.4: Relative abundances of common Muskegon Lake diatoms, continued
Depth
(cm)

Achnanthidium
minutissimum
(Kützing)
Czarnecki

Actinocyclus normanii
fo subsalsus (JuhlinDannfelt) Hustedt

Amphora
pediculus
(Kützing) Grun

Asterionella
formosa
Hassal

2
4
8
12
16
21
24
28
32
36
40
44
48
52
56
61
64
68
72
76
81
84
88
92
96
101
104
108
112
116
121
124
128
132
136
139
144
148

5.24
1.44
2.25
0.17
0.00
0.16
0.00
0.00
0.30
0.47
0.00
0.97
0.42
0.49
0.63
0.16
0.36
0.32
0.16
0.30
1.12
0.80
0.00
0.31
0.17
0.00
0.46
0.16
0.17
0.00
0.16
0.17
0.00
0.00
0.00
0.00
0.00
0.00

0.00
0.16
0.00
0.83
0.66
0.48
0.83
1.70
3.14
1.57
0.92
3.72
1.94
0.16
0.00
0.00
0.18
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.17
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00

4.56
1.60
5.78
3.51
1.64
0.97
0.50
1.54
0.30
1.10
1.69
0.16
0.28
0.98
0.00
1.55
0.90
0.97
0.82
1.95
0.96
3.19
2.37
10.42
1.50
2.93
2.28
2.09
3.80
5.37
1.48
2.65
2.28
2.79
1.18
8.70
3.81
0.96

0.00
0.00
0.00
0.00
0.00
0.00
0.33
0.62
0.00
0.63
0.00
0.65
3.74
5.69
1.09
0.47
0.90
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00

196

Table A.4: Relative abundances of common Muskegon Lake diatoms, continued
Depth
(cm)

Aulacoseira
ambigua
(Grunow)
Simonsen

Aulacoseira
granulata
(Ehrenberg)
Simonsen

Aulacoseira
granulata fo
curvata

Aulacoseira
granulata var
angustissima (O
Müller) Simonsen

2
4
8
12
16
21
24
28
32
36
40
44
48
52
56
61
64
68
72
76
81
84
88
92
96
101
104
108
112
116
121
124
128
132
136
139
144
148

12.67
5.75
19.42
33.89
37.17
37.52
48.43
36.42
60.03
31.76
30.67
29.08
35.04
19.02
20.31
13.64
16.34
35.71
34.09
30.08
9.79
19.65
10.17
16.02
30.78
21.34
40.77
30.50
9.42
17.89
12.52
7.63
12.23
40.00
14.62
11.82
19.37
44.41

7.60
8.63
16.05
23.21
39.47
27.05
32.40
6.33
9.28
18.71
45.40
5.17
6.23
12.36
16.25
36.12
31.24
33.44
39.31
31.88
52.33
14.38
44.92
41.84
33.28
39.41
25.97
32.42
24.13
35.77
57.33
56.38
56.93
32.13
55.46
43.84
34.93
30.67

0.00
0.32
0.00
1.34
0.00
0.32
0.00
0.00
0.00
1.42
3.07
2.10
1.39
6.50
12.34
18.60
0.00
2.76
0.00
10.08
0.00
0.00
0.00
0.47
0.00
0.00
0.00
0.00
0.00
0.33
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00

0.00
0.00
0.00
0.00
0.00
0.81
0.00
0.93
0.00
1.10
0.00
0.65
0.00
0.81
1.25
0.00
1.80
0.00
0.00
1.50
6.10
0.00
3.22
0.78
0.00
0.65
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00

197

Table A.4: Relative abundances of common Muskegon Lake diatoms, continued
Depth
(cm)

Aulacoseira
subartica (O
Müller)
Haworth

Cavinula scutelloides
(W Smith) LangeBertalot et Metzeltin

Cocconeis
neodiminuta
Krammer

Cocconeis
neothumensis
Krammer

2
4
8
12
16
21
24
28
32
36
40
44
48
52
56
61
64
68
72
76
81
84
88
92
96
101
104
108
112
116
121
124
128
132
136
139
144
148

0.00
0.00
0.00
0.33
1.32
0.48
0.33
1.54
0.45
0.47
1.53
2.75
0.97
0.00
1.56
0.00
1.44
0.00
2.77
0.75
0.00
0.64
0.34
0.47
0.00
0.16
0.00
0.00
1.16
0.33
0.00
0.00
0.33
0.00
0.00
0.00
0.00
0.00

0.00
0.16
0.00
0.50
0.16
0.00
0.00
0.00
0.15
0.16
0.15
0.00
0.00
0.00
0.00
0.00
0.18
0.16
0.33
0.15
0.16
0.16
0.51
1.09
4.99
3.42
2.51
2.57
20.99
4.88
5.27
4.64
6.69
4.59
5.71
4.93
11.26
3.19

0.00
0.32
0.48
0.17
0.00
0.00
0.00
0.00
0.30
0.31
0.31
0.16
0.28
0.33
0.00
0.16
0.18
0.16
0.82
0.90
0.00
0.80
0.85
1.71
1.83
1.63
1.37
0.80
5.95
4.07
3.29
2.32
1.63
2.62
2.69
3.78
3.64
2.40

0.51
0.32
0.00
0.33
0.00
0.00
0.00
0.00
0.00
0.16
0.31
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.16
0.45
0.00
0.48
0.34
0.62
1.00
0.81
0.46
1.12
6.78
3.74
1.32
2.82
2.94
0.66
2.18
2.96
3.15
2.40

198

Table A.4: Relative abundances of common Muskegon Lake diatoms, continued
Depth
(cm)

2
4
8
12
16
21
24
28
32
36
40
44
48
52
56
61
64
68
72
76
81
84
88
92
96
101
104
108
112
116
121
124
128
132
136
139
144
148

Cocconeis
pediculus
Ehrenberg

Cocconeis
placentula
Ehrenberg

Cocconeis
placentula var
euglypta
(Ehrenberg)

Diatoma tenuis
Ag

0.68
1.12
2.41
1.17
0.33
0.32
0.17
0.31
0.45
0.31
0.31
0.48
0.28
0.81
0.31
0.00
0.18
1.14
0.98
0.60
0.64
0.96
2.03
0.47
0.17
0.81
0.91
0.80
0.00
0.00
0.00
0.00
0.00
0.00
0.17
0.00
0.00
0.16

2.53
2.56
4.17
0.83
0.99
0.64
0.50
1.08
1.80
2.20
0.61
4.36
1.80
4.55
2.50
3.41
1.97
2.92
4.73
4.96
8.35
19.65
9.66
3.27
2.00
4.40
3.64
2.89
0.99
0.81
0.49
1.16
0.33
0.66
1.34
0.49
0.33
0.48

4.56
2.72
4.33
0.33
0.33
0.64
0.00
0.31
0.45
1.10
0.46
0.81
0.55
2.60
2.81
1.09
1.62
2.92
3.59
4.06
6.90
14.38
8.47
1.71
1.83
1.14
1.59
0.96
0.33
0.33
0.00
0.17
0.16
0.00
0.50
0.00
0.00
0.00

0.17
0.16
0.00
0.33
0.16
2.58
3.31
6.17
2.84
1.73
0.15
3.39
2.35
1.79
1.56
0.16
0.36
0.00
0.00
0.00
0.00
0.48
0.00
0.31
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00

199

Table A.4: Relative abundances of common Muskegon Lake diatoms, continued
Depth
(cm)

2
4
8
12
16
21
24
28
32
36
40
44
48
52
56
61
64
68
72
76
81
84
88
92
96
101
104
108
112
116
121
124
128
132
136
139
144
148

Fragilaria
capucina
Desmazieres

Fragilaria
capucina var_
gracilis (Østr)
Hust

Fragilaria
crotonensis
Kitton

Opephora martyi
Hérib

15.71
30.51
23.27
4.67
1.97
5.96
1.65
1.54
0.45
8.49
0.00
3.39
2.22
0.65
4.84
5.74
3.77
0.00
0.65
0.00
0.80
0.64
0.00
0.93
0.00
0.16
0.00
1.28
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00

7.43
0.00
0.64
0.00
0.16
0.16
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.33
0.00
2.17
0.18
0.00
0.00
0.30
0.16
0.48
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.49
0.00
0.17
0.00
0.00
0.00
0.00
0.00
0.00

0.00
3.51
1.93
5.34
2.63
2.90
0.83
8.02
2.54
1.73
2.91
7.59
4.02
10.41
9.38
7.60
5.03
2.60
0.00
0.15
0.64
2.24
0.34
0.00
0.00
0.00
0.00
0.16
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.16

0.00
0.80
0.00
1.34
0.33
0.00
0.00
0.00
0.15
0.00
0.61
0.00
0.42
0.00
0.00
0.00
0.00
1.62
3.59
0.60
0.32
1.44
1.53
2.49
5.49
5.37
6.83
3.53
4.96
6.02
4.45
6.97
3.26
5.57
6.22
5.09
9.77
4.31

200

Table A.4: Relative abundances of common Muskegon Lake diatoms, continued
Depth
(cm)

2
4
8
12
16
21
24
28
32
36
40
44
48
52
56
61
64
68
72
76
81
84
88
92
96
101
104
108
112
116
121
124
128
132
136
139
144
148

Planothidium
frequentissimum (LangeBertalot) Lange-Bertalot

Pseudostaurosira
brevistriata (Grun in
VH) Williams & Round

Staurosira construens
(Ehr) Williams &
Round

0.17
1.12
0.32
0.83
0.49
0.00
0.33
1.54
0.45
0.63
0.46
0.16
0.14
0.98
0.47
0.47
0.36
0.97
0.16
0.90
0.48
1.76
0.68
0.93
0.83
0.81
0.46
2.57
2.98
1.30
0.16
0.50
0.82
0.82
0.00
0.66
0.00
0.32

14.53
14.06
7.22
7.18
0.00
1.45
0.17
0.93
0.15
3.14
4.60
0.00
0.00
0.00
0.00
0.62
0.00
2.11
0.33
0.15
0.00
0.00
0.17
0.16
2.50
0.81
3.19
1.61
1.32
0.81
2.31
0.50
0.65
0.98
1.68
1.64
2.65
1.44

5.07
8.63
0.64
1.84
3.29
0.16
0.00
0.00
0.15
0.00
0.31
0.32
0.00
2.76
3.75
0.00
1.80
0.00
0.16
0.30
0.00
1.76
2.88
4.04
1.66
3.42
0.23
1.77
1.98
2.28
0.33
1.16
0.49
0.00
0.84
0.82
0.66
0.00

201

Table A.4: Relative abundances of common Muskegon Lake diatoms, continued
Depth
(cm)
2
4
8
12
16
21
24
28
32
36
40
44
48
52
56
61
64
68
72
76
81
84
88
92
96
101
104
108
112
116
121
124
128
132
136
139
144
148

Staurosirella pinnata
(Her) Williams &
Round

Stephanodiscus
hantzschii Grun

Stephanodiscus
minutulus (Kütz)
Cleve & Moller

Stephanodiscus
niagarae Her

1.18
1.12
1.12
0.17
0.00
0.97
0.00
0.31
0.00
0.16
0.00
0.00
0.00
0.00
0.78
0.62
0.90
0.65
0.00
0.45
0.64
1.28
0.68
4.04
1.66
2.12
1.82
1.93
3.47
2.28
0.82
0.66
0.82
1.15
0.84
1.64
0.99
0.32

0.51
0.64
0.48
0.67
0.66
7.09
2.48
6.64
3.74
6.92
0.31
13.73
12.88
3.74
3.44
0.47
0.54
0.49
0.65
0.30
0.64
0.16
0.51
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.16
0.00
0.00

1.01
1.12
0.64
1.17
2.47
2.90
3.31
12.50
4.64
5.82
0.31
13.09
18.56
15.61
7.81
2.64
24.78
1.46
1.14
1.65
1.61
1.12
0.51
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.17
0.00
0.17
0.00

0.17
0.48
0.48
2.17
0.33
0.16
0.33
0.93
1.05
0.94
1.23
0.00
0.55
0.65
2.50
0.62
0.18
1.14
1.79
1.50
0.80
0.80
1.36
1.40
1.16
1.79
2.05
5.46
0.99
4.55
2.64
2.65
2.45
0.33
0.84
3.12
0.83
2.08

202

APPENDIX V

MUSKEGON LAKE FOSSIL DIATOM TAXA

203

Table A.5: Muskegon Lake fossil diatom data
Achnanthes
A. conspicua Mayer
Achnanthidium
A. exiguum (Grunow) Czarnecki
A. minutissimum (Kützing) Czarnecki
Actinocyclus
A. normanii fo. subsalsus (Juhlin-Dannfelt) Hustedt
Amphora
A. copulata (Kützing) Schoeman et Archibald
A. ovalis (Kützing) Kützing
A. pediculus (Kützing) Grun.
A. veneta Kützing
Aneumastus
A. tusculus (Ehrenberg) Mann et Stickle
Asterionella
A. formosa Hassal
Aulacoseira
A. ambigua (Grunow) Simonsen
A. ambigua fo curvata
A. granulata fo curvata
A. granulata fo curvata
A. granulata (Ehrenberg) Simonsen
A. granulata fo curvata
A. granulata fo. curvata
A. granulata var. angustissima (O. Müller) Simonsen
A. italica (Ehrenberg) Simonsen
A. subartica (O. Müller) Haworth
Caloneis
C. bacillum (Grunow) Cleve
Campylodiscus
C. echineis Ehrenberg

204

Table A.5: Muskegon Lake fossil diatom data, continued
Cavinula
C. cocconeiformis (Gregory ex Greville) Mann et Stickle
C. lacustris (Gregory) Mann et Stickle
C. pseudoscutiformis (Grunow ex Schmidt) Mann et Stickle
C. scutelloides (W. Smith) Lange-Bertalot et Metzeltin
Cocconeis
C. disculus (Schumann) Cleve
C. neodiminuta Krammer
C. neothumensis Krammer
C. pediculus Ehrenberg
C. placentula Ehrenberg
C. placentula var. euglypta (Ehrenberg) Cleve
Craticula
C. halophila (Grunow in Van Heurck) Mann
Ctenophora
C. pulchella (Ralfs ex Kützing) Williams & Round
Cyclostephanos
C. dubius (Fricke in A. Schmidt) Round
Cyclotella
C. atomus Hustedt
C. bodanica Grunow
C. distinguenda Hustedt
C. meneghiniana Kützing
C. michiganiana Skvortzow
C. ocellata Pantosek
C. pseudostelligera Hustedt
C. stelligera (Cleve et Grunow) Van Heurck
Cymatopleura
C. solea var. apiculata (W. Sm.) Ralfs
Cymbella
C. affinis Kütz.
C. amphicephala Naeg. ex Kütz.

205

Table A.5: Muskegon Lake fossil diatom data, continued
C. caespitosa Brun
C. cistula (Ehr.) Kirchn.
C. delicatula Kütz.
C. ehrenbergii Kütz.
C. helvetica Kütz.
C. incerta (Grun.) Cl.
C. lata Grun.
C. leptoceros (Ehr.) Kütz.
C. mexicana (Ehr.) Cl.
C. subcuspidata Kram.
Cymbellonitzschia
C. diluviana Hust.
Diatoma
D. tenuis Ag.
D. vulgaris Bory
Diploneis
D. elliptica (Kütz.) Cl.
Encyonema
E. prostratum (Berk.) Kutz.
E. silesiacum (Bleisch in Rabenhorst) Mann
E. microcephala (Grun.) Kram.
Entomoneis
E. ornata (Bail.) Reim.
Epithemia
E. adnata (Kütz.) Bréb.
E. sorex Kütz.
E. turgida (Ehr.) Kütz.
E. turgida var. granulata (Ehr.) Hust.
Eucocconeis
E. alpestris (Brun) Lange-Bertalot
Eunotia
E. arcus Ehr.

206

Table A.5: Muskegon Lake fossil diatom data, continued
E. faba (Ehr.) Grun. in V. H.
E. formica Ehr.
E. minor (Kütz.) Grun.
E. spp.
Fragilaria
F. capucina Desmazieres
F. capucina var. gracilis (Østr.) Hust.
F. capucina var. mesolepta Rabh.
F. crotonensis Kitton
F. vaucheriae (Kütz.) Peters.
Frustulia
F. vulgaris (Thwaites) DeT.
Geissleria
G. decussis (Hustedt) Lange-Bertalot et Metzeltin
Gomphoneis
G. eriense (Grun.) Skv. & Meyer
G. acuminatum Ehr.
G. angustum Ag.
G. clavatum Ehr.
G. gracile Ehr. emend. V. H.
G. grovei M. Schmidt
G. grovei var. herrmanniana (Palik) Kociolek, Yang et Stoermer
G. minutum (Ag.) Ag.
G. olivaceum (Lyngb.) Kütz.
G. parvulum (Kütz.) Kütz.
G. truncatum Ehr.
Gyrosigma
G. acuminatum (Kütz.) Rabh.
Hantzschia
H. amphioxys (Ehr.) Grun.
Hippodonta
H. capitata (Ehrenberg) Lange-Bertalot, Metzeltin et Witkowski
H. hungarica (Grunow) Lange-Bertalot, Metzeltin et Witkowski

207

Table A.5: Muskegon Lake fossil diatom data, continued
Karayevia
K. clevei Grun. in Cl. et Grun.
Lemnicola
L. hungarica (Grun.) Round and Basson
Luticola
L. mutica (Kutz.) Mann

Mastogloia
M. smithii Thw.
Melosira
M. undulata var. normanii Arnott
M. varians Ag.
Meridion
M. circulare (Grev.) Ag.
M. circulare var. constrictum (Ralfs) V. H.

Navicula
N. antonii Lange Bertalot in Rumrich
N. capitatoradiata Germain
N. cari Ehr.
N. cincta (Ehr.) Ralfs
N. cryptocephala Kütz.
N. cryptotenella L.B. in Kramm. & L.-B.
N. gregaria Donk.
N. integra (W. Sm.) Ralfs
N. laterostrata Hust.
N. peregrina (Ehr.) Kutz.
N. pseudoanglica var. signata (Hustedt) Lange-Bertalot
N. radiosa Kütz.
N. recens Lange-Bert.
N. reichardtiana Lange-Bert.
N. reinhardtii (Grun.) Grun.
N. rostellata Kützing

208

Table A.5: Muskegon Lake fossil diatom data, continued
N. tripunctata (O. F. Müll.) Bory
N. trivialis Lange-Bert.
N. utermoehlii Hust.
N. veneta Kütz.
N. viridula (Kütz.) Kütz. emend. V. H.
Neidium
N. ampliatum (Ehr.) Kramm.
Nitzschia
N. amphibia Grun.
N. dissipata (Kütz.) Grun.
N. linearis (Ag. ex W. Sm.) W. Sm.
N. palea (Kütz.) W. Sm.
Opephora
O. martyi Hérib.
Pinnularia
P. acrosphaeria (Bréb.) W. Sm.
Placoneis
P. clementis (Grun) Cox
P. elginensis (Greg.) Cox
P. exigua (Greg.) Mereschk.
P. explanata (Hust.) Cox
P. gastrum (Ehr.) Meresch.
P. placentula (Ehr.) Hienzerling
P. pseudoanglica (Lange-Bertalot) Cox
Plagiotropis
P. lepidoptera (Greg.) Kuntze
P. lepidoptera var. proboscidea (Cl.) Reim.
Planothidium
P. delicatulum (Kützing) Round et Bukhtiyarova
P. frequentissimum (Lange-Bertalot) Lange-Bertalot
P. lanceolatum
Psammothidium

209

Table A.5: Muskegon Lake fossil diatom data, continued

P. subatomoides (Hüst.) Bukht. et Round
Pseudostaurosira
P. brevistriata (Grun. in V.H.) Williams & Round
Reimeria
R. sinuata (Greg.) Kociolek & Stoermer
Rhoicosphenia
R. abbreviata (Agardh) Lange-Bertalot
Rhopalodia
R. gibba (Ehr.) O. Müll.
R. gibberula (Ehr.) O. Müll.
Sellaphora
S. mutata (Krass.) Lange-Bertalot
S. pupula (Kütz.) Meresckowsky
S. seminulum (Grun.) Mann
Stauroneis
S. smithii Grun.
Staurosira
S. construens (Ehr.) Williams & Round
S. construens fo. binodis (Ehr.) Hust.
S. construens var. venter
Staurosirella
S. lapponica (Grun. In V.H.) Williams & Round
S. leptostauron (Grun. In V.H.) Williams & Round
S. leptostauron var. dubia (Grunow) Edlund
S. leptostauron. Ehr.
S. pinnata (Her.) Williams & Round
Stephanodiscus
S. hantzschii fo. tenuis (Hust.) Hakan. & Stoerm.
S. hantzschii Grun.
S. minutulus (Kütz.) Cleve & Moller
S. niagarae Ehr.
S. sp.

210

Table A.5: Muskegon Lake fossil diatom data, continued
S. sp.
Surirella
S. angusta Kütz.
S. linearis var. constricta Grun.
S. minuta Bréb.
Synedra
S. acus var. angustissima Grun.
S. capitata Ehr.
S. ulna (Nitz.) Ehr.
Tabellaria
T. fenestrata (Lyngb.) Kütz.
T. tabulata (C. A. Ag.) Snoeijs
Thalassiosira
T. weissflogii (Grun.) Fryxell & Hasle

211

APPENDIX VI

HABITAT AND ECOLOGICAL PREFERENCE OF COMMON
MUSKEOGN LAKE DIATOMS

212

Table A.6: Habitat and ecological preference of commonMuskegon Lake fossil diatoms
Species

Habitat

Achnanthidium
minutissimum

Benthic

Ecology preferences

Fritz et al. (1993)
Panizzo et al. (2008)
Chen et al. (2008)
Anderson (1997)

Epiphytic
Generalist species
Eurytopic, periphytic
Actinocyclus normanii
fo subsalsus

Reference

Planktonic Eutrophic and alkaliphilous

van Dam et al. (1994)

Typically associated with human disturbance in Europe's
modern eutrophicated rivers, but found in much older
riverine sediment in this study
Large, centric, sometimes nuisance species
Amphora pediculus

Witkowski et al. (2004)
Leitao and Leglize (2000)

Benthic
Oligio-mesotrophic and alkaliphilous
pH > 8.0
Epiphyte

Asterionella formosa

Planktonic Open water

Taylor et al. (2006)
van Dam et al. (1994)
Chen et al. (2008)
Bennion and Appleby (1999)
Taylor et al. (2006);
Chen et al. (2008)

Responds to changing nutrient conditions

Wolin and Stoermer (2005)

Mesotrohic total phosphorus optima
Sensitive to changing light conditions

Hall and Smol (1992);
Reavie et al. (1995a)
Leitao and Leglize (2000)

Introduced by salmon in New Zealand lakes, morphospecies
considered cosmopolitan, seasonally dominant in eutrophic
lakes

Vanormelingen et al. (2008)

213

Table A.6: Habitat and ecological preference of commonMuskegon Lake fossil diatoms, continued
Species
Aulacoseira ambigua

Habitat

Ecology preferences

Planktonic Open water
Require turbulent conditions because they rely on mixing to
remain suspended in water column

Reference
Taylor et al. (2006);
Chen et al. (2008)

High Si requirements for growth
Present after deforestation

Bradbury et al. (2002)

Oligotrophic to mesotrophic

Ramstack et al. (2003); Reavie
et al. (1995a); Reavie and
Smol (2001)

Presence unrelated to trophic status
Aulacoseira granulata

Wolin and Stoermer (2005)
Fritz et al. (1993);
Kilham et al. (1986)

Brugram (1979)

Planktonic Oligohalobous, alkaliphilous, limnophilous, planktonic
Eutrophic, low silicate

Hustedt (1957); Ehrlich (1973)
Brugam (1983);
Kilham et al. (1986)

Resitant to human impacts

Witkowski et al. (2004)

Aulacoseira granulata
fo curvata

Planktonic Eutrophic and alkaliphilous

van Dam et al. (1994)

Aulacoseira granulata
var angustissima

Planktonic Eutrophic and alkaliphilous

van Dam et al. (1994)

Aulacoseira subartica

Planktonic

Taylor et al. (2006)
Associated with oligio-mesotrophic conditions

van Dam et al. (1994)

Associated with increasing nutrient rich conditions

Dokulil and Teubner (2005)

Responds to changing nutrient conditions

Wolin and Stoermer (2005)

214

Table A.6: Habitat and ecological preference of commonMuskegon Lake fossil diatoms, continued
Species

Habitat

Cavinula scutelloides
(also Navicula
scutelloides)

Benthic

Cocconeis neodiminuta

Benthic

Reference

Benthic

Cocconeis
neothumensis

Ecology preferences

Alkalibionic (exclusively at pH >7) and eutrophic

van Dam et al. (1994)

Eutrophic

van Dam et al. (1994)

Cocconeis pediculus

Benthic

Hypereutrophic, alkaliphic and benthic

van Dam et al. (1994);
Chen et al. (2008)

Cocconeis placentula

Benthic

Epiphytic, freshwater, alkaliphilous with pH values 7.5-8.0

Ehrlich (1973)

Oligosaprobic, oligohalobous "indifferent", alkaliphilous,
cosmopolitan diatom

Foged (1980)

Epiphytic taxa

Bennion and Appleby (1999)

Eutrophic species, with maximum development in utrient rich
and very well oxygenated waters

Steinberg and Schiefele (1988)

High chloride optima (81.8 mg/l)

Ramstack et al. (2003)

Common in eutrophied areas of Great Lakes and indicative of
high conservative ion loading

Wolin and Stoermer (2005)

Hypereutrophic, alkaliphic and benthic

van Dam et al. (1994);
Chen et al. (2008)

Cocconeis placentula
var euglypta
Diatoma tenuis Ag

Benthic

215

Table A.6: Habitat and ecological preference of commonMuskegon Lake fossil diatoms, continued
Species

Small, tychoplanktonic (adaptive to dynamic thermal
characteristics), require high light penetration (shallow water)

Panizzo et al. (2008)
Ramstack et al. (2003)

Benthic

Small, tychoplanktonic (adaptive to dynamic thermal
characteristics)

Panizzo et al. (2008)

Benthic

Small, tychoplanktonic (adaptive to dynamic thermal
characteristics)

Panizzo et al. (2008)
Wolin and Stoermer (2005)

Rising nitrate concentrations

Wolin and Stoermer (2005)

associated with nutrient enrichment in in lakes of low to
moderate alkalinity

Fragilaria crotonensis

Benthic

Respond to changing nutrient conditions

Fragilaria capucina
var gracilis

Ecology preferences

High chloride optima (63.2 mg/l)

Fragilaria capucina

Habitat

Bradbury (1975); Brugam
(1979)

Planktonic
Opephora martyi

Fritz et al. 1993

Benthic

Planothidium
frequentissimum

Reference

Benthic

Pseudostaurosira
brevistriata
Staurosira construens
Staurosirella pinnata

Benthic

Kenney et al. (2002);
Taylor et al. (2006)

Benthic

Grows well in short growing season, meso-eutrophic,
Planktonic competitive, common in low nutrient arctic lakes
Benthic

Cremer et al. (2001)

Benthic and epiphytic

Taylor et al. (2006)

Alkaliphic

Chen et al. (2008)

216

Table A.6: Habitat and ecological preference of commonMuskegon Lake fossil diatoms, continued
Species

Stephanodiscus spp.

Habitat

Ecology preferences

Planktonic Large centric, mesotrophic

Reference
Morabito et al. (2002)

High phosphorus requirements
Increases in this diatom in a lake in northeastern Minnesota
was coincident with increased inputs of domestic and
municipal wastes

Bradbury (1975)

High total phosphorus optima
Stephanodiscus
hantzschii

Bradbury (1975);
Bennion et al. (1996)

Fritz et al. (1993);
Ramstack et al. (2003)

Planktonic Planktonic, hypertrophic

Taylor et al. (2006)

Small centric taxa, in highly eutrophic conditions
Resistant to human impact
Stephanodiscus
minutulus

Witkowski et at. (2004)

Planktonic

Stephanodiscus
niagarae

Bennion and Appleby (1999)

Planktonic

Fritz et al. (1993)

217