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thesis entitled

RESOURCE QUALITY AND RECRUITMENT OF TREE SPECIES IN

PLANTATION FORESTS OF SOUTHWESTERN MICHIGAN
presented by

Diane Harlow Burbank

has been accepted towards fulfillment
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Master of Science Forestry

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RESOURCE QUALITY AND RECRUITMENT OF TREE SPECIES IN
PLANTATION FORESTS OF SOUTHWESTERN MICHIGAN

By

Diane Harlow Burbank

A THESIS

Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of

MASTER OF SCIENCE

Department of Forestry

1991

ABSTRACT

RESOURCE QUALITY AND RECRUITMENT OF TREE SPECIES IN
PLANTATION FORESTS OF SOUTHWESTERN MICHIGAN

By

Diane Harlow Burbank

Patterns of tree recruitment, soil moisture, potential N mineralization, and
light availability were examined for twelve plantations and three oak-hickory
forests on similar upland soils in southwestern Michigan. Levels of all
resources varied significantly across stands. Stands dominated by hardwoods
were highest in soil resources, while red pine and Douglas-fir stands were
lowest. Percent light was lowest beneath white pine stands and highest under
red pine and scots pine stands. Principal components analysis produced a
stand ordination reflecting a contrast between soil resources and light. The
most abundant seedling and sapling species were red maple and black cherry,
while oaks and several mesic-site species were sparsely represented. Red
maple and black cherry showed no relationship to stand type or resource
gradients, and were not dispersal-limited. These two species, by exhibiting
wide tolerances for resources and aggressive colonization and dispersal, are

likely to dominate those plantations allowed to senesce undisturbed.

To my Dad, Richard A. Harlow In, who planted the seed, to my family
Cynthia, Chip, and David, who nurtured the sapling, and to m y husband
Mike, who provided the stability and love for the tree to bear fruit, I am
eternally in your debt.

iii

ACKNOWLEDGEMENTS

There is a Zen saying "When the mind is ready, a teacher appears". It has
been my good fortune to have been surrounded by some of the finest teachers
throughout both this achievement and my life. I would first like to express
my gratitude to my committee members, who in two short years have
transformed my thinking about ecological concepts and processes: to Dr. Kurt
Pregitzer, for introducing me to the world within the soil and for guiding me
with kindness and patience above all; to Dr. Carl Ramm, for introducing me
to multivariate statistics and ' for demanding statistical rigor in all efforts; and
to Dr. Katherine Cross, for introducing me to the vast world of plant
community ecology, for re—introducing me to succession, and for providing
balance and understanding. Funding for this research was provided by the
Department of Forestry, McIntire-Stennis, and Dr. George Lauff of the Kellogg
Biological Station, for which I am grateful. My appreciation is extended to the
staff at both K85 and the Kellogg Forest for finding creative ways to make my
work easier, and especially to Walt Lemmien, who's detailed notes and vivid
memory provided much of the historical background of this study. I would
like to thank Andrew Burton, Brian Palik, Ron Hendrick, Dr. Eunice Padley,
Chuck Campbell, Dr. Rose-Marie Muzika, Carol Hyldahl, Mike Swisher, Dr.
Mark McDonnell, Dr. Charles Canham, Dr. Margaret Carreiro, and Dr. David
Parkhurst for the discussions, insights and support that helped me through.
To my parents and to my husband Mike, who have been the finest teachers of
all, I am always and forever thankful.

iv

TABLE OF CONTENTS

LIST OF TABLES .......................................................................................................... vii
LIST OF FIGURES ........................................................................................................ ix
INTRODUCTION ........................................................................................................ 1
Studies of Succession ...................................................................................... 1
Succession in Plantation Forests .................................................................. 8
OBJECTIVE AND HYPO’I'HESES ............................................................................. 14
METHODS ..................................................................................................................... 17
Study Area ......................................................................................................... 17
Historical Records ............................................................................................ 21
Stand Selection ................................................................................................. 22
Field Sampling ................................................................................................. 24
Laboratory Analysis ........................................................................................ .30
Data Analysis .................................................................................................... 32
RESULTS ...................................................................................................................... .36
Presettlement Vegetation ............................................................................... 36
Post Settlement Records ................................................................................. 38
Natural Disturbance and Herbivory ............................................................ 40
Stand Descriptions and Histories ................................................................. 41
Resource/ pH Gradients and Correlations ................................................. .54
PCA of Site Variables ...................................................................................... 58
Species-Resource Relationships ................................................................... 72
Species-Seed Source Relationships .............................................................. 94

DISCUSSION ................................................................................................................ 105

Stands and Resources ...................................................................................... 105
Species Distributions Among Plantations .................................................. 1 12
Long-term Community Development ....................................................... 118
SUMMARY AND CONCLUSIONS ......................................................................... 121
APPENDDC .................................................................................................................... 124
Directions to Plots in the 15 Stands Surveyed ........................................... 124
Compartment Map of the W. K. Kellogg Forest ....................................... 132
LIST OF REFERENCES ............................................................................................... 133

vi

LIST OF TABLES

Table 1. Type characteristics of several soils found in the W. K Kellogg
Forest and Kellogg Biological Station, southwestern Michigan
(Austin 6: Konwinski 1979) ........................................................................................ 19

Table 2. Stand types surveyed in the W. K. Kellogg Forest and Kellogg
Biological Station, southwestern Michigan ............................................................. 23

Table 3a. Kellogg Forest Presettlement Vegetation-1826. T15, R9W~
Sections 21 ,22,27,28; 21 corners .................................................................................... 37

Table 3b. Kellogg Biological Station Presettlement Vegetation-1826.
T15, R9W—Sections 5,6,7,8, 6:1 / 2 of 4 6t 9; 17 corners ............................................ 37

Table 4. Presettlement mean distances and diameters for species
chosen as bearing trees, classified by line description, Kellogg Biological
Station, southwestern Michigan. ............................................................................... 39

Table 5. Overstory, soil, and topographic characteristics of 15 planted and
natural stands in the W. K. Kellogg Forest and Kellogg Biological Station,
southwestern Michigan. All overstory values, except age, are means with
standard errors in parentheses; n=3 for all stands. Dashes indicate basal

areas of 0 ........................................................................................................................... 42

Table 6. Correlation matrix used in PCA for the untransformed resource
variables mineralizable nitrogen, soil moisture, and light. ................................. 61

Table 7. Eigenvalues, their proportion of explained variance, and their
associated eigenvectors for PCA of resource correlation matrix ......................... 62

Table 8. Correlation matrix used in PCA for the untransformed resource
variables and pH, aspect, and slope ............................................................................ 65

Table 9. Eigenvalues, their proportion of explained variance, and their

associated eigenvectors for PCA of resource and site correlation
matrix. .............................................................................................................................. 66

vii

Table 10. Sapling dominance (mean square meters of basal area per
hectare) for 15 stands in the W. K. Kellogg Forest and Kellogg Biological
Station, southwestern Michigan ................................................................................ 73

Table 11 . Seedling dominance (mean number of stems per hectare) for
15 stands in the W. K. Kellogg Forest and Kellogg Biological Station,
southwestern Michigan. ............................................................................................... 84

Table 12. Distance (m) from plot center to potential seed sources for
sapling species found frequently in plots in the W. K. Kellogg Forest,
southwestern Michigan ............................................................................................... 97

Table 13. One-way chi-square goodness-of—fit analyses, for each species,

comparing the distribution, across distance classes, of plots with saplings
present with a theoretically uniform distribution of the same plots ............... 101

viii

LIST OF FIGURES

Figure 1. Location of and landforms associated with the study areas of
Kellogg Forest and Kellogg Biological Station, Ross Township,
Kalamazoo County, Michigan--- -- ......... 18

 

Figure 2. Field sampling design used in the planted and natural stands
surveyed at the W. K. Kellogg Forest and Kellogg Biological Station,
southwestern Michigan ................................................................................................ 26

Figure 3. Levels of pH and resources for 15 stands in the W. K. Kellogg

Forest and Kellogg Biological Station, southwestern Michigan. Columns
represent the mean of three plots with standard error bars of 1 unit above

the mean. Stands associated with the same letter are not significantly
different (alpha=0.05). For figures C-F, AN OVA results are based upon

data transformed in order to stabilize variance ...................................................... 55

Figure 4. Bivariate plots and Spearman's coefficient of rank correlation of
resource variables and pH for 15 stands at the W. K. Kellogg Forest and
Kellogg Biological Station, southwestern Michigan .............................................. 59

Figure 5. The relationship between the distribution of stands and the

first and second principal components for resource variables. Scaled
eigenvectors for each variable are also plotted: PM, percent moisture;

MN, mineralizable nitrogen; LTO, light at 0 meters; LT25, light at 2.5

meters; LTS, light at 5 meters ...................................................................................... 63

Figure 6. The relationship between the distribution of stands and the

first and second principal components for resource and site variables.

Scaled eigenvectors for each variable are also plotted: labels as defined in
Figure 5, with the addition of PH, ASP, aspect; SLP, sloPe ................................... 68

Figure 7. The relationship between the distribution of stands and the

first and third principal components for resource and site variables.

Scaled eigenvectors for each variable are also plotted: labels as defined in
Figure 6 ............................................................................................................................. 69

ix

Figure 8. The relationship between the distribution of stands and the
second and third principal components for resource and site variables.
Scaled eigenvectors for each variable are also plotted labels as defined m

Figure 6 _- - - - - -------- 70

Figure 9. Sapling basal area in square meters] ha for 15 stands in the
W. K. Kellogg Forest and Kellogg Biological Station, southwestern
Michigan. Stands are ranked from low to high values for mineralizable

nitrogen (ug/ g) ................................................................................................................ 76

Figure 10. Sapling basal area in square meters/ ha for 15 stands in the

W. K. Kellogg Forest and Kellogg Biological Station, southwestern

Michigan. Stands are ranked from low to high values for soil moisture

(%) ..................................................................................................................................... 77

 

Figure 11. Sapling basal area in square meters/ ha for 15 stands in the

W. K. Kellogg Forest and Kellogg Biological Station, southwestern

Michigan. Stands are ranked from low to high values for light averaged

over 2.5 m and 5 m heights (70) .................................................................................. 78

Figure 12. Distribution of 11 sapling species, relative to the first and

second principal component axes for resources. Values indicate species
importance on a 0-5 scale using divisions of 20% relative basal area:

0, 0%; 1, 1-20%; 2, 21-40%; 3, 41-60%; 4, 61-80%; 5, 81-100% ................................... 80

Figure 13. Seedling numbers/ ha, in 1000's, for 15 stands in the W. K.
Kellogg Forest and Kellogg Biological Station, southwestern Michigan.
Stands are ranked from low to high values of mineralizable nitrogen

(us/g) ..... ---- ....... .... 86

Figure 14. Seedling numbers] ha, in 1000's, for 15 stands in the W. K.
Kellogg Forest and Kellogg Biological Station, southwestern Michigan.
Stands are ranked from low to high values of soil moisture (%) ....................... 87

 

Figure 15. Seedling numbers/ ha, in 1000's, for 15 stands in the W. K.
Kellogg Forest and Kellogg Biological Station, southwestern Michigan.
Stands are ranked from low to high values of light at 0 meters (96) .................. 88

Figure 16. Distribution of 10 seedling species, relative to the first and

second principal component axes for resources. Values indicate species
importance on a 0-5 scale using divisions of 20% relative density: 0, 0%;

1, 1-20%; 2, 21-40%; 3, 41-60%; 4, 61-80%; 5, 81-100% .............................................. 90

Figure 17. Percent frequency of plots occupied by each sapling species,
classified by distance from nearest potential seed source, for 36 plots in 12
plantations of the W. K. Kellogg Forest, southwestern Michigan. Numbers
above bars refer to the total number of plots within each distance class ........... 99

Figure 18. Percent frequency of numbers of each sapling species counted,

by distance to potential seed source class, for 36 plots in 12 plantations

of the W. K. Kellogg Forest, southwestern Michigan. Numbers above bars
refer to the number of saplings counted within each distance class ................ 103

INTRODUCTION

Plantation forests are common feature of the landscape in the
Northeast and Lake States Region of the United States. Many of these forests
were established 50-60 years ago in an effort to reclaim and restore wom-out
agricultural land and clearcut natural hardwood forests. Foresters and other
concerned individuals involved in these early restoration efforts often had as
their primary concern the stabilization of soils on these degraded landscapes,
as well as the potential wood products that could be extracted in the future
from these plantations. However, it was the rare individual who thought
beyond the 50-year conifer rotation, and wondered about the nature of the
contribution these conifers would make to nutrient cycling, succession, and
other ecosystem processes occuring on these sites. The effect of conifers on
these landscapes is becoming more important now, as rotation age is
approached and these stands are either harvested or allowed to senesce and
succeed. This study was initiated to explore the effect of these conifers on
succession within an oak-hickory landscape in southwestern Michigan. A
review of other studies of succession is appropriate to aid in understanding

these patterns of vegetation and resource development over time.

Studies of Succession
Over the last 100 years, patterns of succession have been examined in

detail for a wide array of herbaceous and woody ecosystems (cf. Cowles 1899;

2

Clements 1916; Watt 1947; Holt 1972; Forcier 1975; Bormann and Likens 1979;
Petranka and McPherson 1979; Woods 1979; West et al. 1981; Werner and
Harbeck 1982; Lorimer 1983; Whitney 1986; Host et a1. 1987; Tilman 1988;
Halpern 1989). In response to this large body of descriptive and empirical
research, a concomitant body of literature on successional theory has evolved
(cf. Clements 1916; Gleason 1926; Egler 1954; Drury and Nisbet 1973; Horn
1974; Connell and Slatyer 1977; Fox 1977; Bazzaz 1979; Grime 1979; Feet and
Christensen 1980; West et a1. 1981; F‘megan 1984; Tilman 1985; Huston and
Smith 1987). This literature, in an attempt to reduce the enormous variability
in patterns of succession observed to a few universal tenets, has tended to

generate controversy as well as concepts.

However, four general factors which appear to influence plant
community dynamics and thereby succession can be discerned from this
literature. These are: (1) availability of space and limiting resources, over
which plants often compete (Tourney and Keinholz 1931; Grime 1977; Tilman
1985; Zak et a1. 1986), (2) climate and physical site characteristics (Barnes et al.
1982; Pregitzer and Barnes 1984; Host et al. 1987), (3) disturbance (Heinselman
1973; Sprugel 1976; Whitney 1986), and (4) predation by insects, pathogens,
and other herbivores (McNaughton 1983; Bryant and Chapin 1986). Rarely do
these factors operate in a vacuum, and often they vary in importance at
different temporal and spatial scales (O'Neill et a1. 1986). The thread that ties
these factors to patterns of plant response in a successional system is the
autecology of individual species (Gleason 1926; Egler 1954; Holt 1972; Forcier
1975; Grime 1977; Bazzaz 1979; Woods 1979; Huston and Smith 1987).

3

The following review demonstrates the importance of these variables in
community development, and the need for their quantification when

interpreting patterns of species establishment and recruitment.

Availability of Limiting Resources

Availability and quality of essential resources, and their modification by
competing plants, has been suggested as the predominant mechanism
operating in succession (Tilman 1985, 1988). In most forest ecosystems, these
resources generally include nitrogen, water, and light (Spurr and Barnes
1980). Historically, competition for light or shade tolerance has been seen as a
dominant force driving patterns of successional change in forests (Heyer 1852,
as cited in Tourney and Kienholz 1931). In 1931, Toumey and Kienholz
demonstrated the importance of below-ground competition for soil resources
in canopy-understory interactions._ Mitchell and Chandler (1939)
demonstrated that several deciduous species in the northeastern United
States had different tolerances for soil nitrogen levels. However, while
species react to differences in resource availability, they also can alter the

resource quality of a site.

It is widely recognized that litter quality can influence nutrient
availability (Swift et al. 1979; Gosz 1981; Staaf and Berg 1981; Bryant and
Chapin 1986; Blair et al. 1990), and that variation exists among species in
general and along successional and site quality gradients for litter quality
(Robertson and Vitousek 1981; Perala and Alban 1982; Vitousek et al. 1982;
Pastor et al. 1984; Zak et al. 1986; Perry et al. 1987; Bryant and Chapin 1986;
Montagnini et al. 1989). It has been hypothesized that litter quality and
nutrient availability, both of which respond to and bring about species

4

replacements, are keys to understanding the dynamics of secondary
succession (Pastor et al. 1984; Thorne and Hamburg 1985; Bryant and Chapin

1986; Tilman 1988).

Tilman (1982, 1985, 1984, 1988), looking at early successional old field
communities and, more recently, forest systems, combined competition for
light and nitrogen with individual species requirements for these resources
into an hypothesis of community dynamics in secondary succession.
Tilman's "resource-ratio hypothesis” suggests that temporal changes in the
ratio of light and soil nitrogen control the composition and direction of plant
community change. Competition for these resources is seen as a selective
force on species characteristics, which determines their distribution along a
resource-ratio gradient consisting of an inverse relationship between light ,
and nitrogen. However, this hypothesis does not explicitly involve other
potentially important factors such as soil moisture levels or disturbance
regime. The assumption appears to be that plant responses to nitrogen and
light operate at a more fundamental level than responses to other factors ie.
factors such as moisture and disturbance ultimately influence light and
nitrogen levels, and therefore their effect upon plant community dynamics is
seen indirectly through their effect upon these two fundamental resources
(T ilman 1988).

An interesting aspect of Tilman's most recent work (1988) is his ,
recognition of the role of transient dynamics in secondary succession,
especially on nutrient-rich sites and in forest communities. Transient
dynamics is a phenomenon by which plants that are not competitive

dominants for a site's equilibrial resource ratio become community

5

dorninants nonetheless. Variation in resource availability and species'

colonizing abilities have been suggested to strongly influence transient
dynamics (Tilman 1988).

Availability of and competition for soil moisture limits the distribution
of many plant species (Spurr and Barnes 1980). In addition, moisture is
limiting to the microbial biomass present in the soil, which releases nutrients
for plant uptake through decomposition. Because of this, nutrient
availability is sometimes used as an index of moisture availability (Tilman
1988). As moisture also has a direct physiological effect on tree growth and
seedling establishment, a characterization of moisture regime in addition to
nutrient regime should be undertaken in any succession study.

Climate and Site

Research has demonstrated the influence of variation in climate,
topography and physical site characteristics on successional development
(Clements 1916; Daubenmire 1966; Whittaker 1975; Host et al 1987). The
contrasting concepts of discrete communities separated by ecotones
(Daubenmire 1966), and continuous distributions of species along
environmental gradients (Whittaker 1975), both make use of climate and
topography in understanding species replacements and succession. The
German Baden-Wiirttemberg model for ecological site classification, and the
subsequent Ecological Classification System developed in the United States,
make direct use of these variables in the first levels of their respective
hierarchies (Barnes et al. 1982; Pregitzer and Barnes 1984). The two models
then break broader environmental levels into site units representing the

interactions between vegetation, soil and landform. These systems have

6

become increasingly useful, both as a practical management tool for site
quality determination and as a conceptual framework for investigating
interrelationships among the biological and physical variables influencing
community dynamics (Zak et al. 1986; Host et al. 1987, 1988; Padley 1989).

Disturbance

Disturbance has been recognized for its contribution to the maintenance
of diversity and vegetative mosaics, and for its influence on successional
pathways within forest ecosystems (Heinselman 1973; Pickett and White 1985;
Whitney 1986; Boerner et al. 1988; Halpern 1988, 1989). Disturbance in this
context ranges from naturally occurring events such as individual treefalls
and catastrophic perturbations such as fires, hurricanes, and ice storms, to
human-related disturbance such as plantation forests, logging, and forest
conversion to agriculture followed by land abandonment and old-field
succession back to forest. Gap formation as a result of smaller disturbances,
such as small tree falls, has been implicated as a primary factor in secondary
succession of older forests (Runkle 1982; Canham 1984, 1989, 1990; Connell
1989). The intensity, frequency, and degree of heterogeneity of large
disturbances may also have considerable effect on the direction of community
development in forest systems (Heinselman 1973; Sprugel 1976; Runkle 1982;
Whitney 1986; Halpern 1988, 1989). Anthropogenic disturbances tend to set
forest succession back to stages in which plants ranging from field annuals to
pioneer forest species dominate large areas. Regardless of its form,
disturbance also interacts with nitrogen mineralization and nitrification
through changes in litter quality, soil mixing, and erosion (Bormann and
Likens 1979; Vitousek and Matson 1985; Perry et al. 1987), leading eventually
to changes in species composition.

Herbivory
Although widely acknowledged as a potential factor influencing forest

succession, herbivory has been often neglected in successional studies
(Connell and Slatyer 1977 ; Bryant and Chapin 1986). Plant chemical defenses
for herbivory, which decrease the palatability of live foliage to consumers,
also tend to decrease the rate at which plant litter is decomposed by soil-based
consumers (McNaughton 1983; Bryant and Chapin 1986). This in turn
reduces nutrient availability. In fact, Bryant and Chapin (1986) have
hypothesized that in boreal forests, mammalian browsing of the palatable
tissues of deciduous saplings can lead to their replacement by the less
palatable conifers, a typical successional pathway in these forests.
Insectivorous leaf feeders such as gypsy moth (Lyman tria dispar) and spruce
budworm (Choristaneura fumiferana) are well known for the tree mortality
they can cause through successive defoliations. This mortality can play an
important role in community dynamics, and may provide an opportunity for
changes in species composition. Seed predation by insects, birds, and
mammals is another often observed but infrequently quantified
phenomenon that could have large impacts upon successional pathways

(Fenner 1985).

Autecology

The importance of the autecology of individual plant species in
community dynamics and succession is obvious. Life history characteristics
such as longevity, age to first reproduction, seed production and dispersal
characteristics, as well as physiological tolerance of various stresses, have all

been used to explain variation in species composition and success, both

8

spatially and temporally (Gleason 1926; Egler 1954; Curtis 1959; Forcier 1975;
Harper, 1977; Bazzaz 1979; McDonnell and Stiles 1983; Huston and Smith
1987). Despite its importance, the explicit incorporation of autecological
characteristics in models of succession has only recently become popular
(Connell and Slatyer 1977; Grime 1977; Tilman 1982, 1984, 1988; Huston and
Smith 1987)..

Two such models have been proposed. Grime's (1977) population
model hypothesizes that three primary plant strategies exist based upon site
conditions (stress tolerators), resource levels (competitors) and disturbance
levels (ruderals). Huston and Smith (1987) take an individualistic approach
and "envision a continuum of plant strategies resulting in a different
hierarchy of relative adaptation to each different set of conditions" (p. 170).
These models, in contrast to Tilman's competition model, emphasize that
site conditions and disturbance, in addition to competition for resources,
interact to produce conditions eliciting different plant strategies. Weldon and
Slauson (1986) maintain that any stressful factor, such as abiotic stress or
disturbance, has the potential to be as important as competition in directing
individual success and ultimately community composition and structure.

Succession in Plantation Forests

In the northeastern United States, the bulk of succession research has
focused on old field systems and naturally regenerating primary and
secondary forest systems. The majority of this work has examined deciduous
forests of New England (Tubbs 1969; Forcier 1975; Bormann and Likens 1979;
Woods 1979; Woods and Whittaker 1981 ; Hibbs 1983), and the Lake States
(McIntosh 1957; Feet and Loucks 1977; Lorimer 1983; McCune and Cottam

9

1985). These investigations have involved examination and manipulation of
primary and older second-growth forest communities, and have shown
interesting community dynamics involving different combinations of
biological, physical and stochastic variables in space and time. Such ecological
concepts as reciprocal species replacements and climax or equilibrial states of
existence as they relate to forest ecosystems have been explored within these

communities.

However, considerably less is known about succession in plantation
forests (but see Grisez 1968; Carmean et al. 1976; Artigas and Boerner 1989). In
the 1930's, the Civilian Conservation Corps (CCC) was employed to reforest
abandoned agricultural land and cut-over forestland throughout the
Northeast and Midwest. Often the planted forests resulting from these efforts
consisted of conifers, exotic or native, growing outside their natural ranges on
what at one time were sites dominated by hardwoods. Many of the hardwood
sites on which they have been planted were previously degraded in some
way, especially through intensive agriculture or clearcutting that often
resulted in the loss of topsoil through erosion. In addition to the CCC, land-
grant universities and conservation-minded individuals also established

plantations, especially conifers, for economic, aesthetic, and research

In establishing these plantations, careful consideration was often given
to the moisture demands of particular tree species in order to match site and
species and thereby maximize success (Walt Lemmien, personal
communication). In other instances, species availability in nurseries was the

primary consideration (Artigas and Boerner 1989). Soil conditions at these

10

disturbed and depleted sites were often harsh and required repeated
replanting. In addition, tree seedlings in these plantations often competed
with vigorous weedy herbs, grasses, and hardwood saplings for growing space
and resources. During the early years of these plantations, removal of woody
competition was often a regular occurrence (Walt Lemmien, personal
communication). Once the conifers had gained an advantage , however, the
plantations were often left unmanaged, or thinned once or twice. After the
introduction of chemical fertilizers and herbicides in the 1940's, more drastic

and intensive methods were used to control competition.

The success of these early attempts at forest restoration can be measured
in the 50-60 year old forests scattered throughout the Northeast and Lake
States. Although many of these forest patches are still under active, often
intensive management, many plantations have been abandoned from

management and are succeeding naturally.

In one study of 37 plantations of diverse coniferous composition
ranging in age from 36-64 years in northwestern Pennsylvania, Grisez (1968)
found volunteer seedlings and saplings in all plantations, especially under
cover of Scots pine (Pinus sylvestris). Volunteer species included black cherry
(Prunus serotina), red maple (Acer rubrum), white ash (Fraxinus americana)
and oaks (Quercus spp.) in order of frequency of occurrence. However, the
focus of his research was on growth of the conifers and not on that of the

volunteers.

Several plantation studies have looked at and demonstrated how soil
properties change with different plantation types. Byrnes and Kardos (1963)

11

demonstrated that water infiltration into upper soil horizons was higher for
hardwood forests as compared to red pine (Pinus resinosa) plantations, and
higher under red pine than in old fields. Challinor (1968) found that soil
beneath different species of conifers varied both in litter quantity and in
nutrient levels in the upper 5 cm of soil. Perry et al. (1987) documented that
nitrogen cycling varied between stands of pure conifers and those mixed with
hardwoods. They suggested that a mixed system is more complex than
simply adding the effects of individual species involved. Only the study by
Carmean et al. (1976) looked at how changes in soil properties due to
differences in woody cover affected subsequent growth by hardwoods. In this
study, however, the plantation overstory was removed and the hardwoods
were planted, making it difficult to generalize about long term changes in

natural succession within plantations.

A study recently completed by Artigas and Boerner (1989) analyzed the
abundance of seedlings and saplings under replicated plantations of red pine,
white pine (Pinus strobus), and Virginia pine (Pinus virginiana) to determine
if successional pathways varied between plantation types. They found that
differences in pH levels, litter depth, and stem density over all stands were
associated with different suites of sapling/ seedling species. They also found
differences between plantation types in structural diversity that were
associated with increased density of saplings/ seedlings. Although ten
environmental and five mensurative variables were used to analyze the

sapling/ seedling data, a notable exception was any measure of nitrogen.

There are several reasons why an investigation into the patterns of

successional development in plantation communities would be worthwhile.

12

It is widely accepted that a mor type of humus development is typical beneath
conifer plantations due to the high C:N ratio of coniferous foliage (Spurr and
Barnes 1980). In addition, as mentioned above, species differ widely in the
resistance of their foliage to decay, and thereby in the efficiency with which
nutrients immobilized in the litter they produce can be released for use
(Kucera 1959; Perala and Alban 1982; Zak et al. 1986). As Perry et al. (1987)
suggest, different combinations of hardwoods and conifers could alter
nitrogen dynamics on similar sites. Site quality, simply put, is influenced by
the type of species planted. In addition, species vary in the amount of light
extinguished through their crowns; plantations of varied composition may
offer a natural gradient in light available beneath the dominant canopy.
Given that species differ in requirements for essential resources, it would not
be unreasonable to suggest that invading species would respond differently to
these changes in resource availability. Patterns of succession may therefore
vary depending upon the dominant overstory species, as has been found in
natural communities.‘ Alternatively, site quality in plantations may vary,
regardless of overstory canopy, due to the level of soil degradation before
plantation establishment, soil physical characteristics which are difficult to

survey accurately, and the cover or crop before planting.

As the study by Artigas and Boerner (1990) appears to be the only one to
explicitly investigate patterns of abundance and dominance of volunteer
species in plantations, it is difficult to characterize the variability in these
patterns, or how the overstory may be modifying environmental conditions
to produce these patterns. Investigation in this area could help to determine
the appropriate species for planting, depending upon management objectives.
Research undertaken within the geographical area of this study provides

13

evidence that red pine, planted on a site previously occupied by hardwoods
followed by agricultural crops, exerts a negative feedback on the system via
low litter quality (Palik and Pregitzer, unpublished manuscript). It is unclear
how this lowering of site quality will affect the establishment and recruitment
of hardwoods naturally dispersed into this red pine stand or others like it.
Negative feedback is not desirable if the management goal is restoration of
productive ecosystems similar to those native to a particular region.
Reforestation efforts to avert global warming need to be framed in the context
of long-term effects upon the ecosystem as a whole, not just short-term
benefits to one part. Certain conifers could conceivably act as nurse crops to
hardwoods (Grisez, 1968), providing a short rotation forest product while
leaving an established hardwood stand perhaps similar to the original
vegetation. A clearer understanding of community development in
plantations is needed in order to anticipate, with some degree of certainty, the
effect of plantation composition on establishment and recruitment of trees

beneath these canopies.

osmcrrvs AND momssss

The general objective of this study is to characterize patterns of
variation in tree establishment and recruitment within plantation forests,
and to relate these patterns to gradients in light, nitrogen and moisture, and
to topographic variation, disturbance history, and distance to potential seed
sources. This study does not quantitatively address herbivory due to the time
and labor intensive nature of the methods that would be involved, and the
preliminary nature of the investigation. Its potential importance is, however,
acknowledged. It should be noted also that although I chose to look at
nitrogen levels, this does not diminish the potential importance of other
nutrients for tree growth. However, nitrogen is an important nutrient in
many northeastern forest systems because its supply is more limited than that
of other essential nutrients (Spurr and Barnes 1980). In addition, because its
input in available form into the forest system is predominantly through
decomposition of litter by the microbial biomass, it tends to be more
indicative of changes in fertility brought about by overstory composition than

other nutrients which are derived from mineral soil.

Nitrogen availability in this study was measured as potential N
mineralization. Powers (1980) and others have demonstrated that potential
mineralized soil N correlates well with tree growth and yield in conifer
stands, and is an effective index of soil N availability. Nitrification levels

14

15

were not addressed in this study. Several researchers have demonstrated that
the nitrification process is not an important contributor of available nitrogen
in oak or coniferous forests, and on dry sites in general (Gosz 1981; Aber and
Melillo 1982; Vitousek et al. 1982; Zak et al. 1986). However, there is also
evidence for considerable variability in nitrification across stands of differing
composition and soil depths (Federer 1983). In addition, there is evidence to
suggest that nitrification may be important where basswood (Tilia americana)
or tulip tree (Liriodendron tulipifera) are present in the overstory and
contribute their nutrient-rich and easily decomposed litter to the system
(Pastor et al. 1984; Zak et al. 1986). An investigation into variation in both
nitrogen mineralization and nitrification rates among plantation types would

be an interesting extension of this study.

The hypotheses to be tested in this study are: (1) levels of light, soil
nitrogen and soil moisture form a gradient across different plantation types
established on soils of similar origin and physical characteristics, (2) patterns
of individual tree species establishment and recruitment vary across different
plantation types, and (3) there are associations between resource levels and

species establishment and recruitment across plantation types.

A test of these hypotheses will involve (1) determining levels of light,
soil nitrogen and soil moisture within each of several different plantation
types, (2) plotting resources against plantation types to determine if a gradient
exists for each resource, (3) ordination of plantations based upon resources to
determine if a gradient exists involving a linear combination of these
variables, (4) determining patterns of dominance of individual tree species as

seedlings (establishment) and saplings (recruitment) in the understory of

16

different plantation types, (5) using bivariate plots to associate species
dominance patterns with individual resources, and (6) comparing plantation
ordinations with species dominance patterns to associate establishment and
recruitment with a composite of resources. In addition, data collected on site
characteristics, disturbance history, and distance to potential seed sources will
be used to aid in interpreting the species dominance patterns found.

METHODS

Study Area

The areas chosen for this study are located within the Kellogg Biological
Station (KBS), Hickory Corner's, Michigan, and the W. K. Kellogg
Experimental Forest (Kellogg Forest), Augusta, Michigan. Both areas are
found in Ross Township, Kalamazoo County in southwestern Michigan
(Figure 1). These areas are administered by Michigan State University and
were acquired as abandoned agricultural land in the early 1930's. The land-
use history of these areas up to the beginning of the 1930's was fairly typical of
that which occurred throughout much of southwestern Michigan (Whitney
1987). Presently, KBS is a mixture of cultivated and abandoned fields, and old
woodlots, while Kellogg Forest consists of a matrix of plantations of varied
composition on abandoned agricultural land. The extensive documentation
of land use history collected for these two sites by forest and farm managers,
and incorporated as an integral part of this research, allows for a case history
approach to this study. As a direct focus on succession within plantation
communities is rare, this approach seemed to be the appropriate first step.
These areas offer interesting contrasts in management techniques for the
revegetation of abandoned farmland, as well as fertile ground for
comparative analyses of canopy-understory interactions and succession over a

wide array of well-documented land uses.

17

18

R055 TOWNSHIP (T .15., R.9W.)

 

 

 

 

 

 

 

 

{2‘45 - \

 

 

 

 

 

 

 

 

 

 

 

Figure 1. Location of and landforms associated with the study areas of Kellogg Forest and
Kellogg Biological Station, Ross Township, Kalamazoo County, Michigan.

19

The general landscape of Ross Township is characterized by a matrix of
agricultural lands and woodlots situated on rolling to hilly terrain, the steeper
slopes occurring in the Kellogg Forest. Upland soils tend to be sandy, and are
represented primarily by Oshtemo sandy loam on hills (coarse-loamy, mixed,
mesic Typic Hapludalf), and Ockley loam and sandy loam (fine-loamy, mixed,
mesic Typic Hapludalf) at lower elevations and flatter slopes. Secondary soils
include Fox sandy loam (fine-loamy, mixed, mesic Typic Hapludalf), Hillsdale
sandy loam (coarse-loamy, mixed, mesic Typic Hapludalf), and Spinks loamy
sand (sandy, mixed, mesic Psammentic Hapludalf) (Table 1). These soils are
generally deep, well-drained, with moderate to rapid permeability. Kellogg
Forest appears to be more xeric in nature than forested areas of KBS.

Monaghan (1984) has described the glacial geology in detail of
Kalamazoo County, and a series of maps for this county describe its surficial
and bedrock geology (Monaghan and Larson, 1982). The two study areas in
general occupy glacial outwash composed of medium to coarse sand and

Table 1. Type characteristics of several soils found in the W. K. Kellogg Forest and Kellogg
Biological Station, southwestern Michigan (Austin & Konwinski 1979).

 

 

 

Characteristic
Depth of
Subgroup Texture Drainage 1 / Solurn (cm)
Soil Type
Oshtemo Typic Hapludalf sandy loam WD 102-190
Ockley Typic Hapludalf sandy loam to loam WD 102-183
Spinks Psammentic Hapludalf loamy sand WD 91-152
Fox Typic Hapludalf sandy loam WD 61-102
Hillsdale Typic Hapludalf sandy loam WD 102-203

 

1/ we, well-drained.

20

gravel. Soils of KBS and the western half of the Kellogg Forest were formed
in outwash deposits of the Galesburg-Vicksburg outwash plain. Soils of the
eastern half of the Kellogg Forest were formed in outwash deposited by
Augusta Creek, which formed an incised valley train within the Galesburg-
Vicksburg outwash plain. These deposits are on the northwestern edge of
larger masses of undifferentiated sand and till associated with the Tekonsha

Moraine.

The present natural vegetation of Kellogg Forest woodlots is dominated
by black, white and to some extent red oak (Quercus velutina, Q. alba, Q.
rubra), and pignut and shagbark hickories (Caryn glabra, C. avata), with black
cherry, red maple, sassafras (Sassafras albidum) and flowering dogwood
(Camus florida) in the understory. The natural forest vegetation at KBS is
more mesic in nature, and consists of one woodlot, Long Woods, that is
dominated by red oak, sugar maple (Acer saccharum) and pignut hickory.
The understory is represented by black cherry, sassafras, flowering dogwood,
and sugar maple. The average age of the dominant natural vegetation of
Kellogg Forest appears to be 124 years (C. Ramm, personal communication).
Long Woods is at least 50 years old with an extensive area of larger trees of at
least 100 years of age. In addition, there are several remnant seed trees that
remained uncut during farming practices and occurred in the middle of fields
or along fence rows in both of these areas. These seed trees were mapped at
Kellogg Forest in an intensive vegetation survey conducted in 1940. Many of
these trees are still present in the landscape today and are producing seed.

21

Historical Records

Under the auspices of the General Land Office (GLO) survey program,
all townships in Michigan, including Ross Township, were surveyed by the
federal government prior to settlement. In the early to mid-1800's, surveyors
systematically recorded the nature of the vegetation and landscape as they
traversed the state, providing a detailed picture of the presettlement
vegetation in the nineteenth century. These notes have seen increasing use
as they offer a quantitative, though systematic, sample of the vegetation every
800 m along both range and township lines in the state.

Several researchers have investigated the reliability of these surveys in
providing a reconstruction of presettlement vegetation (Buordo 1956; Curtis
1959; Whitney 1986). Bias in selection of witness trees (towards moderate-
sized, long-lived trees), and fictitious data have been found to be potential
problems, although these appear to be of limited extent in Michigan (Buordo
1956; Whitney 1986).

An initial investigation of the GLO survey notes (located at the Real
Estate Division, Michigan Department of Natural Resources, East Lansing,
Michigan) for Kellogg Forest and KBS was undertaken to provide a
description of the presettlement vegetation. The survey of the interior of
Ross Township ('1' 1 S, R 9 W) was conducted between 1825-1826. Generally,
the two nearest trees in different quadrants at each quarter section corner
were blazed as witness trees, and their species, diameter, and distance to
corner recorded. In addition, soil, topographic, and general vegetation

22

descriptions were recorded for each section line, and disturbances such as

burned areas or windthrow were noted as surveyors crossed through them.

For the purposes of this study, all witness trees at section and quarter
section corners that fell within or on KBS and Kellogg Forest boundaries were
transcribed from the survey notes. Average diameter, relative basal area,
relative density, and relative frequency were then calculated for each species.
Section line descriptions of soils, topography, and vegetation were also noted
to develop a picture of the presettlement landscape.

Records for changes in land use and disturbance regimes in this area
since the GLO survey were located in the literature, as well as in the diaries,

surveys, and notes recorded by forest managers at Kellogg Forest.

Stand Selection

Upland plantation and natural communities, representing
combinations of various cover types and topographic positions, were chosen
. to quantify and compare patterns of tree seedling and sapling importance and
site variation. Stands selected were at least 0.5 ha in size, 45 m wide, and 50
years old, with minimal to no man-made disturbance over the past 25-50
years. These criteria were established to ensure at least the potential presence
of tree seedlings and saplings and to avoid edge effects. Out of 71
compartments and subcompartments of natural and planted vegetation
available at Kellogg Forest, 56 could be classified as upland communities.
Within these 56 compartments, 14 stand types met the stand selection criteria

and were chosen for sampling. Most rejections were due either to age or size.

23

Of the 14 stands selected, 12 consisted of plantations composed of
various single and multiple species combinations (Table 2). Plantation types
included two white pine plantations, two red pine plantations, two Scots pine
plantations, one European larch (Larix decidua) plantation, one Douglas-fir
(Pseudotsuga menziesii) plantation, one plantation mix of white and Scots
pine, one plantation mix of white and red pine, one plantation mix of white
pine, red oak and basswood, and one plantation of tulip tree. Within 7 of the
12 plantations, thinning plots had been established within the past 50 years.
Where these plot locations were known (in 4 out of 7 occasions), they were
avoided for sampling. It was often necessary to locate sampling plots within
the established thinning control plots, which were randomly distributed
within the stand and undisturbed. This was due to an inadequate buffer of
otherwise undisturbed vegetation within these thinned stands. In the
remaining 3 stands with unknown thinning plot locations, potential plot

locations where recent removal of trees was evident were rejected.

Table 2. Stand types surveyed in the W. K. Kellogg Forest and Kellogg Biological Station,
southwestern Michigan.

 

PLANTED HARDWOOD- CONEER CONIFER
NATURAL HARDWOOD CONIFER hflX MIX MONOCUL'TURE
Oak-hickory (3) Tulip tree White pine-red Red pine Red pine (2)

oak-basswood white pine
Scots pine- Scots pine (2)
white pine
White pine (2)
European larch
Douglas-fir

24

The variation in replication of plantation types is reflective of the
distribution of these types in the area. Red, white and Scots pine were
frequently planted species throughout much of the Northeast, and Kellogg
Forest is no exception. Therefore, there were more stands of these types in
which to sample. The mixed species plantations, as well as those of European
larch, Douglas-fir, and tulip tree, were infrequent plantation types in this area.
Therefore only one representative stand of each was found to meet the size

area and disturbance criteria required.

Included among the 14 stand types are two naturally established oak-
hickory woodlots to serve as representatives of the natural vegetation native
to this area (Table 2). An additional oak-hickory woodlot at KBS, known as
Long Woods, also met selection criteria and was chosen for sampling,
bringing the total number of stands sampled to 15. These woodlots are
generally even-aged, and have been subjected to a variety of man-made
disturbances, including silvicultural operations, livestock grazing and
firewood cutting (personal communication, KBS and Kellogg Forest staff).
The last grazing in these woodlots occurred before 1965, and one woodlot has
been preserved since 1956 as a natural area. Areas within these woodlots
undergoing current silvicultural treatments were avoided for sampling; for
the most part control plots of undisturbed forest in the woodlots have been
maintained for at least 25 years, and offered a large enough area in which to

sample.

Field Sampling
Within each of the 15 stands chosen, three plots were randomly located
in which to sample overstory tree dominance, seedling and sapling

25

composition and importance, soil mineralizable nitrogen, soil moisture,
light, and tapographic variables. Distance to potential seed sources was
measured in relation to these plots as well. Exact locations of these plots and
the stands in which they are found are presented in the Appendix.

Site

Three topographic measures were recorded for each plot. Quantitative
measures of topography consisted of percent slope and aspect by 45° class. A
description of topographic position was also included (eg. middle slope, high
plateau) to aid in interpretation of the data. Soil series were determined
using both a map produced in an intensive soil survey of Kellogg Forest in
1966, and the Soil Survey of Kalamazoo County (1979).

Vegetation

Within each stand, three .01 ha circular plots (radius=5.64 m) were
permanently established (Figure 2). These sample plots were randomly
located by using a random number table and a dot sheet laid over a map of
each stand. Within each plot, species, diameter at breast height (dbh, 1.37 m)
by 2.5 cm classes (eg. 8.6-10.0 cm), and height (meters) were recorded for each
individual. Three classes of individuals were defined based upon vertical
stratification within stands: overstory, saplings, and seedlings. For the
purposes of this study, dominance in the seedling class represents species
success at establishment, while dominance in the sapling class represents
species recruitment success. All individuals with a dbh of at least 8.6 cm were
classified as overstory trees. Tree saplings were defined as individuals with
the capacity to become overstory dorninants having a dbh of 1.3-8.6 cm. Tree
seedlings, defined as having a dbh of less than 1.3 cm, were sampled by using

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27

five 1-m2 circular subplots (radius-=56 m). One subplot was placed at plot
center, while the other four were located 3 m from plot center in each
cardinal direction (Figure 2). Species, basal diameter and heights of tree
seedlings within each subplot were recorded. In addition, species, presence
and number of small trees, shrubs and ground flora characteristic of forest

understories were recorded.

Light

Within each seedling subplot, percent light was determined at three
levels below the canopy: ground level (LTO), at 2.5 m above the ground
(LT25), and at 5.0 m above the ground (LT5). The understory layer was
generally, though not always, less than 5.0 m in height. This allowed light
intercepted by overstory, sapling, and seedling crowns to be differentiated. A
Decagon sunfleck ceptometer was used for these measures. It has the capacity
to make 80 simultaneous readings of incoming photosynthetically active
radiation (PAR, 400-700 nm) at one sample point, and produce and store the
average photon flux density (ue-cm'z-s'l) and time at each point. The utility
and reliability of this instrument was tested by Pierce and Running (1988), and
found superior to techniques that use a single photodiode moved quickly
from point to point.

Sampling was completed during five cloudless days in a seven day
period in August 1989. An average of three stands per day across the range of
overstory types was measured for light intensity between 10:00 AM and 2:00
PM local solar time. Eight samples were taken within each subplot and at
each height by extending the ceptometer out from the subplot center, rotating
in a 360°circle, and stopping for a measure every 45°. The 2.5 m and 5.0 m

28

measurements were made using a telescoping pole. Subplot averages were
stored in the ceptometer’s microcomputer along with the time each
measurement was taken. A measure of full sunlight was also taken before
and after sampling in each stand. From this information, full sunlight was
estimated for each time recorded with a measure of understory PAR. Percent
of full sunlight was then calculated for each light measurement taken at each
height.

Soil

Soil samples were collected randomly from within each of the five
subplots and composited for each .01 ha plot. Soil samples for measuring
potential N mineralization and pH were obtained by removing 100 cm2 x 5
cm deep soil cores, starting below the 01 horizon, or loose litter (L) layer.
Shallow sampling is used to avoid "priming effects" as described by Salonius
(1978), Thorne and Hamburg (1985) and Zak et al (1986). A priming effect can
be defined as an acceleration of microbial activity stimulated by the
introduction of less decomposed and more readily available organic matter
into deeper soil horizons through mixing of a deep soil sample (Salonius,
1978). This can lead to an overestimation of net mineralizable N. Samples
were placed undisturbed in polyethylene bags and placed in a cooler on ice
until they could be refrigerated at 2°C. Laboratory analysis was initiated

within 48 hours of sample collection.

Soil samples for moisture determinations were collected randomly
within each subplot using a 1.5 cm diameter soil probe inserted to a 20 cm
depth, again starting below the O1 horizon. All samples were removed
between 10:00 AM and 4:00 PM during one day in July of 1989. A composite

29

for each plot was obtained by combining subplot samples. Samples were then
stored in polyethyelene bags and kept on ice in a cooler until they could be
refrigerated. Soils were prepared and analyses begun within 48 hours of

sampling.

Although there are obvious problems with using one measure in time
to characterize a moisture regime for a forested stand, one can still compare
stand values and get an impression of relative moisture holding capacity. It
was presumed that the relatively dry climatic conditions which preceded this
sampling would accentuate any stand differences in moisture holding

capacity.

Distance to Potential Seed Source

As indicated earlier, the vast majority of Kellogg Forest had been cleared
of trees for agriculture in the early to mid 1800's. However, older seed-
producing trees were not infrequent in these early farmlands. Large
individuals were often left in the center of pasture and fields to provide shade
for farmhands and grazing livestock. Trees and shrubs were established and
maintained along fencerows, which were a common feature in the landscape.
In addition, the 2 large woodlots in the area, while providing lumber and
firewood, also functioned as a repository for seeds of the native forest
vegetation.

Potential seed sources for each sapling species found within the
plantations and woodlots were located using a combination of aerial
photographs taken in 1938, and maps produced during an intensive
vegetation survey of the Kellogg Forest study area in 1940. All potential seed

30

sources were visible using both sources of information, providing mutual
verification of seed source location. In addition, the two information sources
were complementary, in that the photographs provided an indication of tree
size and therefore an inference of age, while the maps provided the species
designations. Only those sapling species capable of becoming overstory
dorninants, and those species mentioned in the GLO survey notes for this
area, were examined in this aspect of the study. Distance to the nearest
potential seed source was measured from each plot center to the nearest edge
of the seed source crown. Composition in 1930 of the Kellogg Forest woodlots
was determined from early stand records, and the nearest woodlot edge was
used as the nearest seed source when there were no closer individuals to be
found. Plots in the oak-hickory woodlots were not examined for distance to
seed source because most, if not all, sources of seed for sapling species present
are located within the woodlots.

Laboratory Analysis

Potential Net Mineralizable Nitrogen

Potential net mineralizable nitrogen (NI-I4+-N) was determined using
anaerobic soil incubation (Waring and Bremner, 1964, Powers, 1980; Keeney,
1982; Perry et al., 1987). This method was chosen over that of aerobic or in
situ incubations due to its relative simplicity and because determinations of
nitrification potentials were not within the realm of this study (V itousek et
al., 1982). The technique, developed by Waring and Bremner (1964), has met
with mixed reviews as an index of actual N mineralization rates and nitrogen
availability (Powers 1980; Keeney 1982; Myrold 1987; Padley 1989). However,
Myrold (1987) suggests that this technique measures N mineralized from the

31

microbial biomass and that microbial biomass N may represent a pool of
readily available N for plant uptake. Padley (1989), in a review of techniques
for measuring potential N mineralization, concludes that a measure of

microbial biomass N would be an appropriate index of overall site potential.

In preparation for analysis, the field moist soil sample for each plot was
thoroughly mixed and sieved, excluding material >2 mm but rubbing
through fine roots. From the remaining plot sample material, six 10 g
subsamples were removed for analysis of potential mineralizable nitrogen.
Two subsamples were oven-dried to constant mass at 110°C for 24 hours in
order to provide replication of the field moist to dry soil ratio needed for N-
mineralization calculations. Another two subsamples were extracted using 40
ml of 2M KCl to measure initial levels of ammonium (Myrold 1987). The
soil-KCl solution was shaken mechanically for 15 minutes, after which it was
centrifuged for 5 minutes at approximately 5000 RPM (Perry et al. 1987). After
settling, two 1 ml samples of the supernatant were pipetted into plastic
technicon cups, capped, and stored refrigerated until analysis. The last two
subsamples were placed into two plastic centrifuge tubes, and 20 ml of
deionized water was added to each. The tubes were sealed with paraffin to
ensure anaerobic conditions (Padley 1989), stoppered, and placed in an oven
with a constant temperature of 40°C for 7 days. At the end of incubation, the
samples were extracted with 20 ml of 4M KCl as outlined above and
refrigerated. Initial and incubated deionized water assays were included as

controls.

All soil samples were analyzed colorimetrically for NH4+-N using a

Technicon Autoanalyzer 11. Solution concentrations were determined based

32

upon peak height, and then converted to ammonium concentrations.
Potential mineralizable nitrogen is determined by the difference between the
initial concentration of NH4+-N and the incubated concentration. As bulk

density was not determined, all mineralization values are expressed in ug/ g.

pH

Soil pH was determined using the method outlined by McLean (1982),
involving a 1:1 soil-distilled water mixture and measurement by glass
electrodes on a standardized pH meter. Two 10 g subsamples per plot were
removed from the sieved samples used in the nitrogen assays for this ‘

purpose.

Soil Moisture

Gravimetric moisture determinations were made on the soil sample
composites taken from 0-20 cm depth. The sample for each plot was
thoroughly mixed, after which a 100g subsample was removed for analysis.
The subsample was then oven-dried to constant mass at 1 10°C for 24 hours.
The difference between dry and fresh weights divided by dry weight gives the
proportion of moisture available within that range of depth at that one point
in time (Robertson and Vitousek 1981).

Data Analysis

Overstory and sapling basal area per hectare, by species, was calculated
for each plot and averaged for each of the 15 stands. Seedling dominance was
characterized as numbers per hectare and averaged by species at the plot and
stand levels. Potential mineralized N (MN), percent moisture (PM), percent
light at each height (LTO, LT25, LTS), and pH were averaged for each stand.

33

Aspect was converted to a more ecologically meaningful value using the
Beers et al. (1966) transformation. Means of slope (SLP) and aspect (ASP) were
then calculated at the stand level.

There are several statistical hurdles that this study was unable to clear.
These included adequate replication of stands, adequate sample size, and
normality of the vegetation data. However, replication of plots within stands
is sufficient to explore associations apparent in the data when the inference
space is not larger than that over which the plots were distributed (Hurlbert
1984). In this study, inferences are restricted to Kellogg Forest and Kellogg
Biological Station. The lack of suitable stands as replicates in the near vicinity

prevents broader generalizations.

Resource levels and pH were analyzed at the stand level using analysis
of variance; in this data, the ”treatment" implies the stand classification, and
is appropriate for assessing whether or not levels of these variables differ
from stand to stand (Steel and Torrie 1980). In order to stabilize variance, soil
moisture and light variables were transformed for this analysis using the Box-
Cox family of transformations (Box et al. 1978). Fisher's protected LSD for
unplanned comparisons was used to compare means (Steel and Torrie 1980;
Feldman and Gagnon 1986). Univariate plots of resource levels and pH across
stands, and bivariate plots of resources in relation to each other, were
constructed to look for gradients and correlations of these variables.
Spearman's coefficients of rank correlation were then determined for the
untransformed variables. However, product-moment correlation coefficients
were used in principal components analysis as it is a distribution-free

method.

Principal components analyses (PCA) were run on resource and site data
to reduce the dimensionality of these variables and to present a two-
dimensional image of how stands are distributed in relation to linear
composites of these variables. Biplots showing the position, in two-
dimensional space, of the scaled eigenvectors for site variables and PC scores
for stands were constructed to aid in interpretation. The correlation matrix
was used in PCA because the variables were measured in different scales.
Although this scaling procedure is somewhat arbitrary and does not solve
scaling problems, it seems appropriate in this case because research has
supported the relatively equal importance of these variables (Chatfield and
Collins 1980). Two sets of site data were used in PCA: one set including the
resource variables mineralizable nitrogen, percent moisture, and percent light
at three heights, and another set consisting of the data just mentioned as well
as pH, slope and aspect. More rigorous multivariate techniques, such as
canonical correlation analysis, could not be applied because assumptions of
multivariate normality, adequate sample size and equal covariance matrices

would be violated (Morrison 1990).

Plots of sapling and seedling species distributions across stands and in
relation to individual resources were Constructed by ranking stands from low
to high levels of a resource variable and then comparing the distributions.
These distributions were based upon the dominance values for individual
species: basal area/ ha for saplings and number of stems/ ha for seedlings.
Relative dominance of saplings and seedlings were also compared to the PCA
results using a graphical method devised by Curtis and McIntosh‘(1951). This

35

provided a visual representation of species relationships to the linear
composite of resources for both seedling and sapling classes.

Measures of central tendency were obtained for distances of potential
seed sources to plot centers for the plantations. Plot distances were then
compared with sapling species densities for those species native and common
to the region in presettlement times. Due to various problems with the
sapling density data, such as generally low frequencies and densities, unstable
variances, and non-normal distributions, relationships between dispersal
distances and sapling densities were analyzed nonparametrically. Distance
data were divided into four classes, and then compared with presence data for
each sapling species in order to detect trends or patterns relative to potential
dispersal distance. The distributions of plot sapling densities across these
distance classes, for each sapling species, were also examined. Chi-square
goodness-of-fit analyses, by species, were performed using two distance
classes: 0-100 m and >100 111. Pooling of classes was necessary in order to
attain expected values of > 1.0, a necessity for this test (Box et al. 1978)
although considered low by others (Sokal and Rohlf 1981). A uniform
distribution of plots having a given species present across these two classes
was tested, as other more meaningful distributions tended to produce
expected values of < 1.0 for most species.

RESULTS

Presettlement Vegetation

Kenoyer (1929, 1934, 1940) has described the presettlement vegetation of
Kalamazoo County using the survey notes of southwestern Michigan, He
found this vegetation to be representative of six major associations: beech-
maple (Fagus grandifolia-Acer spp.); oak-hickory (Quercus spp.-Carya spp.);
swamp forests; oak-pine (Quercus spp.-Pinus spp.); bur oak (Quercus
macrocarpa); and prairie. Beech-maple and oak-hickory types were the most
prevalent in Kalamazoo County between 1826-1830. In addition, Kenoyer
(1929) noted the presence of oak barrens or savannas scattered throughout the
oak-hickory and bur oak types.

In the presettlement survey notes of the Kellogg Forest and KBS areas,
the species of highest relative density was white oak at 75—80% (Table 3a,b).
"Yellow" or chinkapin oak (Quercus muehlenbergit) and bur oak were also
constituents in both areas. Elm (Ulmus spp.) and h0phornbeam (Ostrya
oirginiana) were less frequent Swamp forest vegetation was represented by

tamarack (Larix laricina) and black ash (Fraxinus nigra).

The section line descriptions add insight into the general landscape and
vegetation of both areas. The land was generally described as rolling or hilly,
with "second rate" soil. Vegetation was often described simply as oak,

37

Table 3a. Kellogg Forest Presettlement Vegetation-1826.
T15, TOW-Sections 21 ,22,27,28; 21 corners.

 

 

Number of
Number of Relative Points w/ Relative
Bearing and Line Trees Individuals Density Spades Frequency Frequency

 

Quacus alba 45 80% 19 90% 73%
Quercus odutina 3 5% 1 5% 4%
Quercus mudllenbergii 1 2% 1 5% 4%
Unix lan‘cr'na 2 4% 1 5% 4%
Ostrya oirginiana 2 4% 2 10% 8%
Ubnus spp. 2 4% 1 5% 4%
Fraxinus nigra 1 2% 1 5% 4%

TOTALS 56 100% 124% 100%

Table 3b. Kellogg Biological Station Presettlement Vegetation-1826
T15, R9W-Sections 5,6,7,8, &1/2 of 4 h 9; 17 corners.

Number of
Number of Relative Points w/ Relative
Bearing and Line Trees Individuals Density Species Frequency Fregm

Quacus alba 39 75% 15 88% 60%
Quercus muehlenbergii 5 10% 4 24% 16%
Quacus odutina 5 10% 3 18% 12%
Ulnlus spp. 1 2% 1 6% 4%
Fagus grandifolia 1 2% 1 6% 4%
Acer sacchanon 1 2% 1 6% 4%

 

TOTALS 52 100% 147% 100%

38
although more often bur, white and black oak were differentiated. The

section lines in the eastern third of KBS were described as thinly timbered,
suggesting an oak savanna. A comparison of the distance to corner and
diameter, by species, between lines described as thinly timbered and those
described as oak showed an almost two-fold increase in both variables for the
thinly timbered lines, supporting the hypothesis of an oak savanna (Table 4).

Post Settlement Records

Kalamazoo County was first settled in the 1830's, and most of the area
was immediately converted to farmland (Kenoyer 1929). The land was
productive initially, and was used especially for corn at the turn of the
century with the advent of the cereal business (Wright and Rudolph 1982).
Woodlots were generally high-graded for lumber and firewood, as well as
grazed by cattle and other livestock (Whitney 1987; W. Lemmien, personal
communication). By the early 1900's, much of the land had eroded badly and
farms were abandoned (Wright and Rudolph 1982). Between 1928-1931, W. K.
Kellogg, who resided in the Battle Creek area, donated to Michigan State
College parcels of worn out farmland which would become the Kellogg
Biological Station (421 ha; 1928-1930) and the Kellogg Reforestation Tract (114
ha; 1931). Kellogg's goal in donating this land was to have it returned to
productive status through reforestation and conservative farming practices

(Wright and Rudolph 1982).

Between 1932-1940, most of the original Reforestation Tract was
planted to trees, predominantly red, white and Scots pines (Wright and
Rudolph 1982). However, as species was secondary to the reforestation

mission, any species available was often planted, creating a remarkably

39

Table4. Presettlementrneandistancssanddiametersforspedeschosenas
bearing trees, classified by line description, Kellogg Biological Station,

 

 

 

 

 

 

 

 

 

 

 

 

 

 

southwestern Michigan.
Lines described as 'fisnly timbered”
Mean
Distance Mean
Species No. Trees To Post Std. dev. Diameter Std. dev.
lode“ inches f
Quacus alba 11.0 121.7 106.8 19.5 9.3
Quacus mudllenbcrgii 2.0 154.5 135.1 19.0 1.4
Quacus oelutina 3.0 46.7 25.6 23.0 11.4
Other 0.0 0.0 0.0 0.0 0.0
All Species Present 16.0 111.8 100.3 20.1 8.8
Lines described generally as “Oak”
Mean
Distance Mean
Species No. Trees To Post Std. dev. Diameter Std. dev.
links' inchs t
Quotas alba 16.0 58.8 34.2 11.8 3.9
Quacus muehlenbergii 3.0 20.3 4.9 16.7 6.4
Quercus oelutina 0.0 0.0 0.0 0.0 0.0
Other 3.0 40.0 24.1 8.7 1.5
All Species Present 22.0 60.0 33.1 12.0 4.4
All Lines
Mean
Distance Mean
Species No. Trees To Post Std. dev. Diameter Std. dev.
linle’ inchs t
Quercus alba 27.0 84.4 77.8 14.9 7.5
Quacus mudllenbergii 5.0 74.0 99.9 17.6 4.8
Querc'us oelutina 3.0 46.7 25.6 23.0 11.4
Other 3.0 40.0 24.1 8.7 1.5
All Species 38.0 76.6 75.0 15.4 7.6

 

 

° 1 link=02012 meter
1’ 1 inch=2.54 cm

40
diverse group of plantations. In most cases species were planted in what at

that time appeared to be their most ecologically suitable environments (W.

Lemmien, personal communication).

Research and demonstration were also missions for the new forest. R
H. Westveld and Merle Dieters were the first managers of the Reforestation
Tract, and were responsible for the establishment of most of the stands
surveyed in this study. Initial inventories, compartment descriptions, and
planting records were recorded in detail by these two men. Walter Lemmien,
who began his 41 year tenure as forest manager in 1941, also kept meticulous
and detailed records of plantings and research carried out on the forest. This
degree of documentation is very unusual to find, and provides a reliable
account of disturbance and silvicultural manipulations operating over that
span of time. In addition, an engaging history of Kellogg Forest can be found
it a report by Wright and Rudolph (1932).

Kellogg Biological Station was donated to Michigan State College for
the original purpose of demonstrating conservative farming practices.
Consequently, much of the area is in active fields. However, an ecological
reserve has recently been set aside, enabling the detailed study of old-field
succession. This reserve includes fields that have been abandoned for as
many as 40 years, as well as the woodlot, Long Woods, investigated in this
study.

Natural Disturbance and Herbivory
Diaries and notes of each forest manager contain several references to

natural disturbance at the forest. In 1931, severe defoliation in the woodlot

41
oaks by June beetle (Phyllophaga spp.) was noted by the comment, ”This
insect has been particularly serious during the past two years...and this two
year defoliation combined with the drought during the last few seasons on
this upland area has caused the death of a considerable number of large oaks".
In 1933, Xenotemna pallorana (Tortricidae) was introduced via nursery stock
to the forest and was causing serious damage to the planted conifers by 1939.
In 1938, the pine sawfly (Neodl'prion spp.) and European pine shoot moth
(Rhyacionia buoliana) were also causing damage, leading to the control of
these insects by insecticides in 1939. In the 1950's, an increase in the size of
the deer herd, although welcome, led to severe overbrowsing in the forest.
Since 1960, hunting has been allowed to control the population, although
evidence of browsing is still frequent today. A hard winter in 1976 and
serious ice storm in 1982 caused extensive damage to plantation canopies,
from which it appears several areas are still recovering. Although hard
winters and ice storms obviously occurred between 1931 and 1976, they
apparently were not as noteworthy as these.

Stand Descriptions and Histories

The following series of descriptions provides, when available, a history
of disturbance and changes in composition for each stand. Histories were
found in the notes and diaries of the forest managers, especially those of Walt
Lemmien, and from personal communications with present and past forest
staff. The section starts with the natural oak-hickory stands, and progresses
through the remaining hardwood and mixed stands to the conifer
plantations. In addition, Table 5 provides a summary of overstory, soil, and
topographic characteristics found in these stands.

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43

Oak-Hickory 1 (0H1)

This stand, located in Compartment 10 of the forest, has had a long
history of use. Covering 18 ha, this woodlot has provided firewood, lumber,
and research material for at least the last 60 years. In 1931, an area of
approximately 1 1 ha in the western two-thirds of Compartment 10 was
covered with mature trees. The remainder of this stand was dominated by
sapling and pole-size trees as a result of clearcutting undertaken within the
previous 20—30 years. An inventory taken in 1931 noted the dominant
presence of red, black and white oaks, and hickory in the woodlot. Black
cherry and red (soft) maple were also noted as occasional dorninants, while
aspen (Populus spp.), sassafras, white ash, sugar maple, and dogwood were
noted as common components of the understory and disturbed areas. Some
cutting in the mature timber was done in 1931, primarily to remove dead and
defective trees, and "inferior" species such as sassafras, aspen, and dogwood;
red maple was removed when it interfered with the growth of oak.

In 1954, a hardwood regeneration study was initiated in the mature
forest which involved several silvicultural manipulations conducted every
five years until 1987. Four 0.4 ha rectangular control plots of undisturbed
vegetation were also established at this time for the duration of the study. In
1987, an oak regeneration study was initiated overlaying the layout of the
original study. This study involved removal of overstory trees except in the
control plots, effectively shrinking the area of undisturbed, mature forest

available for sampling to 1.6 ha spread over four patches.

44
The three plots for my study were randomly located in the control

areas of the oak regeneration study, one plot per area. As can be seen in Table
5, there is variability in soil series and topography that was unavoidable due
to location of the control areas. It is also clear from Table 5 that species
composition and dominance in Compartment 10 have not changed
substantially over the past 60 years.

Oak-Hickory 2 (OI-12)

This stand, located in Compartment 228, is a small 2.5 ha woodlot that
has been relatively undisturbed since 1954. Purchased in 1939, a cruise of the
woodlot in 1942 found it dominated by red, black and white oaks, shagbark
hickory, red maple, and black cherry. All of these species were well
represented in the larger diameter classes (> 30 cm dbh). Surprisingly, the
largest volume tallied was for black cherry, followed by red maple and then
the oaks and hickory. Slippery elm (Ulmus rubra) was also represented in the
woodlot. This area has seen limited tree removal, primarily dead trees, and

was set aside as a natural area in 1954.

The stand composition today is similar to what it was in 1939 (Table 5).
It does appear that canopy gaps are more frequent now; one plot had a basal
area of only 5 sq m/ ha due to the presence of a recently dead black oak 76 cm
in dbh that dominated the plot. Unlike 0H1, witch hazel (Hamamel is
virginiana) and maple-leaf Viburnum (Viburnum acerifoiium) are common
in the understory. The oaks, mostly black and white, are often quite large,
and vertical stratification is becoming less defined in this stand. 0H2 is
located in a more mesic part of Kellogg Forest than OH], and appears to be
somewhat sheltered as well (Table 5). Higher site quality is also indicated by

45
the average canopy height of 33 m, which is much greater than that of 0H1

(Table 5).

Long Woods (01-13)

This 10 ha stand, located at KBS, has a less well documented history
than the other oak-hickory stands. It is known that grazing of livestock had
been allowed in the woodlot up to the early 1960's, and that there was
occasional cutting of trees for firewood and building supplies. Aerial photos
for 1938 also indicate that the eastern half of the woodlot had recently been
clearcut, while the western half appeared relatively contiguous. Indications
of grazing, such as the abundance of barberry (Berberis thunbergit) and
Japanese rose (Rosa multifiora), are prevalent in the northern half of the

original forested portion of the woodlot.

The composition of this woodlot is predominantly oak-hickory,
although stand characteristics varied considerably from plot to plot (Table 5).
Plot 1 was located in a mesic area in the southern portion of the woodlot, and
was dominated exclusively by very large red oaks having an average canopy
height of 32 m and dbh > 50 cm. Plot 2 was located farther north, and had
indications of previous grazing from the thorny ground flora. Here, pignut
hickory and white oak were more common, and the average canopy height
was shorter than Plot 1 at 26 m. Plot 3 was located to the east in the younger
forest, where canopy height was even shorter at 20 m, and canopy dorninants

included smaller pignut hickory, red oak, and red maple.

Tulip Tree (UR)

This 0.8 ha plantation was established in 1939, and has a linear
configuration, barely making the width criteria for stand selection. Located in
Compartment 22C, it is adjacent to 0H2, and resides in the same mesic
sheltered location as that stand (Table 5). Ground cover at the time of
establishment included mixed grass, dewberry (Rubus flagellaris), and Canada
thistle (Cirsium amense). Disturbance in this plantation has been
intermittent, consisting of selection thinnings in 1969 and 1971. Although
this appears to violate disturbance criteria, disturbance to the stand appeared
minimal, and there were plenty of seedlings and saplings of all sizes present.
Average canopy height at 32 m is substantial for a 50 year old plantation,
although not unusual for tulip tree on a mesic site (Table 5).

White Pine—Red Oak-Basswood (POB)

Located in Compartment 13C, this 1.7 ha plantation is perhaps the most
interesting because of the unusual species mix planted. This stand was
established between 1932-1935 with an 8 x 8 foot spacing (2.4 m) of species
planted in alternate rows. For three years prior to planting, the site had been
in hay; previous to this the area had been in cultivation for many years.
Ground flora at the time of establishment consisted of a heavy cover of
Canada thistle, timothy (Phleum pretense), and other grasses. By the 1940
vegetation survey, Queen Anne's Lace (Daucus carota) had gained
considerable dominance. The survey also noted the occurrence of maple,
hickory, and elm seed trees within the stand boundaries. This stand has been
undisturbed since establishment.

47
Topographically, the stand occupies a generally west-facing, middle to
low slope (Table 5). In all but one plot, each species planted was represented.
However, white pine appears to be larger in diameter and height than the
other components of the overstory, especially towards the lower part of the
slope (Table 5). The low to flat slope portion of the stand also has an
extensive ground cover of Virginia creeper (Parthenocissus quinquefolia)

with an abrupt edge to the east as the slope steepens.

Scots Pine-White Pine (SXW)

This 2.8 ha plantation in Compartment 4A occupies a very gentle
northwest slope (Table 5), close to Augusta Creek. The northwestern half of
the stand closest to the creek grows on a Sleeth soil, which belongs to a
different taxonomic family, and was therefore avoided in sampling. The
stand was established between 1931-1935 using an 8 x 8 foot spacing for white
pine and a 6 x 6 foot spacing for Scots pine. The last crop grown on the site
was wheat (Triticum aestioum) in 1929. The area was seeded to timothy and
clover (Trifolium spp.) immediately after the wheat harvest, with the last cut
for hay in 1931. Prior to planting, the sod cover was approximately 40%. The
1940 vegetation survey showed a ground cover of clover, grass, and daisy
fleabane (Erigeron annuus), as well as seed trees of oak, hickory, cherry, elm,
basswood, and sugar maple within or on the edges of the stand.

In 1948, a thinning and pruning study was initiated that lasted until
1951 when the last cut was made. In 1958, a survey of the stand indicated
advanced reproduction of red and sugar maple, black cherry, white ash,
basswood, elm, and oak. Recommendations were to allow for a natural
conversion to hardwoods. Therefore, in 1962, a selection thinning was

48
performed in this stand to remove poor individuals of all species, leaving
vigorous pine and hardwoods. In addition, open areas were planted to tulip
tree to provide a future seed source, although none were observed while
sampling. The plots studied in this research indicate that white pine,
although infrequent in the overstory, is quite vigorous, and has grown to
considerable height (Table 5). The Scots pine is present in larger numbers,
and also has grown quite tall, combining with white pine for an average stand

height of 25.1 m.

Red Pine-White Pine (RXW)

This 3.8 ha stand, comprising all of Compartment 7, occupies a steep,
irregularly broken west slope (Table 5), with severe erosion from the 1930's
still evident in places. The plantation was established between 1933-1935
using an 8 x 8 foot spacing. Although the area was in pasture before being
planted, ground cover was described as sparse, consisting of mostly sorrel
(Rumex acetosella) and june grass (Poo pratensis) with patches of goldenrod
(Solidago spp.) (Rudolph and Lemmien 1955). By 1940, the ground cover
hadn't changed much except for the appearance of poverty grass (Danthonia
spica to). A wide fencerow of aspen, sassafras, and oak was noted along the

eastern stand edge.

After a selection thinning in 1956, an ongoing thinning study was
initiated in which permanent plots, including control plots, were established.
The study was stratified by three slope positions, with two controls in each
stratum. This allowed for the random location of my study plots within these
controls, although it also necessitated spreading the plots out across a slope
gradient. The slope gradient also reflects a gradient in size and species

49
dominance, with the steep upper slope and midslope having smaller sizes
and red pine dominant, while the lower slope has larger white pine
dominant. The mean stand basal area does appear to reflect the greater
relative success of red pine on this site as compared to white pine, although
the mean stand height is likely biased upwards by the much taller white pine
on the lowslope (Table 5). In 1964, a reproduction survey noted the
overwhelming abundance of white pine seedlings (average of 102 per milacre
plot), while a few individuals of black cherry, sugar maple, sassafras, red

maple, and oak were also counted.

Red Pine 1 (RP1)

This 5.1 ha plantation in Compartment 8A, established in 1937 using a
6 x 6 foot spacing, occupies a rolling but gentle southwestern facing slope
which continues on to Augusta Creek (Table 5). The 1940 survey shows
mixed grasses and poverty grass as dominant, but interspersed with patches of
7-finger (Potentilla recto), goldenrod, and sandbur (Cenchrus spp.).
Hawthornes (Crataegus spp.) and hazelnut (Corylus spp.) were noted in the
area, as well as a large oak at the northern edge of the stand surrounded by a
wide circle of oak reproduction. In 1960, a thinning study was initiated
throughout most of the stand, although some areas were left undisturbed in
addition to controls. Plots for this study were located in these unthinned

areas.

Red Pine 2 (RPZ)
Established between 1936-1938, this 3.4 ha plantation in Compartment 9
consists of red pine with a 6 x 6 foot spacing, occupying the northwest, west,

and south faces of a southwest-oriented ridge (Table 5). Erosional gullies

50
from the 1930's are still evident, and the stand has a very xeric appearance.

The ground cover at the time of establishment and in 1940 consisted of a
sparse covering of mixed grass with scattered patches of 7—finger. The only
occurrence of juniper (Iuniperus spp.) noted in the 1940 vegetation survey
was in this plantation. In addition, several black cherries, and an occasional

hickory and oak seed tree were found within stand boundaries.

The thinning study initiated in 1960 for RPI also involved this plantation.
However, most of the plots occurred on the lower slopes of this stand, leaving
a relatively steep but large area of unthinned pine on the upper slopes. There
is also a low, somewhat protected area in the northern third of the plantation
having a northeast-southwest orientation. Within this gully one can find
scattered about several large black cherries, presumed to be natural, and a few
large tulip trees, the origin of which is uncertain but probably planted from
stock. Two of the plots for this study are located in the pine on the upper
slopes, one at the top of the slope and another on the steep midslope; the
third is on a low slope, near but not in the gully, randomly placed in a control
plot. There is a decrease in red pine basal area as one moves downslope, with
a corresponding slight increase in canopy height (Table 5). Again, as in the
RXW stand, choosing plots perpendicular to the slope gradient was
necessitated by the lack of enough undisturbed plantation at any one

topographic position.

European Larch (EUL)
This plantation, located in Compartment 9, was established in 1937 at
the foot of the ridge which extends into RP2, and is generally flat in slope and

narrow in width (Table 5). Approximately 1 ha in size, the area was planted

51

with European larch at a 7 x 8 foot spacing, in north-south oriented rows.
Ground cover at the time of establishment consisted of mixed grasses, with
scattered patches of dewberry, goldenrod, and poverty grass, and two
hawthornes. In 1966, thinning plots were established within the plantation.
The control plots for the thinning study provided a relatively undisturbed
location for my plots. Larch basal area is relatively uniform in the stand, as is
height (Table 5). However, common buckthorn (Rhamnus cathartica) is
especially prevalent in the sapling size classes in this stand, with an average
of 2000 stems / ha.

Douglas-Fir (DGF)

This 1.1 ha plantation was established in 1939 at a dense spacing, and is
located in the center of Compartment 22A. This irregularly shaped stand
occupies the southwest face of a slight ridge, and has a relatively gentle slope
(Table 5). The dominant ground cover of this area in 1940 was poverty grass,
with patches of 7-finger and blue joint grass (Calamagrostis canadensis). On
the western edge of the plantation was a small patch of undisturbed
vegetation consisting mostly of oaks, black cherry, hickory and red maple.
This plantation has not been disturbed since planting. Although relatively
uniform in diameter and height (Table 5), there is some mortality of Douglas-
fir presumably due to competition. This has allowed patches of sunlight into
the stand, although the dead trees remain standing with many of their fine

branches intact.

Scots Pine 2 (SP2)
To the south and east of DGF, this 1.2 ha plantation in Compartment
2A was established in 1939 around the brow of the southeast-oriented ridge

52
that extends, through DGF. The southeastern slopes are relatively steep, as

compared to the southwestern slopes (Table 5). Dominant ground cover in
this area during planting was poverty grass, with patches of sandbur, sumac
(Rhus spp.), and dewberry. Although a selection thinning was noted to have
taken place in 1973, I could find no clear indication of the location in records
or in the field; the understory was also quite vigorous and well distributed
over diameter classes. Plot 2 in this stand was unusual in that several of the
Scots pine occurring there had damaged or dying crowns, and light
penetration to the understory was considerable. It is likely that this damage
was caused by the 1982 ice storm.

Scots Pine 1 (SP1)

The remaining three stands occur in the portion of Kellogg Forest west
of Augusta Road. This region of the forest is a little different from the eastern
part, in that it consists of an extensive plateau surrounded by steep, often
irregular slopes. Several steep erosional gullies from the 1930's add to this
irregularity. SPl covers approximately 0.8 ha in Compartment 21, and was
established in 1938 at a 6 x 8 foot spacing. Slopes in this plantation vary from
flat to steep, while aspects vary from north to southeast (Table 5). The 1940
survey shows 7—finger as the dominant ground cover, and a fencerow along
the western edge consisting of hawthorne, cherry, and sassafras. A mature
hickory and white oak were nearby as potential seed sources. A selection
thinning took place in the western and southern portions of the plantation in
1980, and these areas were avoided for sampling. This plantation had the
lowest mean basal area of all stands, although it appeared quite uniform in
distribution (Table 5).

53
White Pine 1 (WP1)

This 2.8 ha plantation was established between 1933-1935 at an 8 x 8 foot
spacing in Compartment 18. The site includes a lower flat and slope with a
generally east and northeast exposure (Table 5). The steeper portions of this
slope were described in 1933 as having lost much of the surface soil through
erosion, and having patchy grass cover. The lower slope and flat were
described as relatively fertile with a uniformly dense June grass sod. By 1940,
the herbaceous vegetation was dominated by timothy, poverty grass, and blue
grass, with patches of dewberry and 7-finger. Cherry, sassafras, hawthorne,
and dogwood were noted along the fencerows surrounding the area. A
portion of the eastern edge of the plantation was removed when Augusta
Road was widened. Otherwise, disturbance to this stand has been minimal.
White pines in the study plots are relatively uniform in size with a moderate

basal area (Table 5); slopes are also similar among plots.

White Pine 2 (WP2)

This stand sits on top of the plateau described earlier for this portion of
the forest. Established in 1937 in Compartment 20A, this 0.5 ha plantation has
a 6 x 8 foot spacing of white pine with virtually no slope or aspect (Table 5).
The ground cover during planting was June grass and timothy. By 1940, the
entire plateau was described uniformly as mixed grasses with goldenrod and
yarrow (Achilles millefolium). A selection thinning was done in 1975,
although there was no indication of cutting in the areas where the plots were
located. Although basal area for this stand is the fourth largest, canopy height
is less than that of the other stands with white pine as a dominant (Table 5).

54

Resource/pH Gradients and Correlations

Gradients in pH, moisture, mineralizable nitrogen, and light in each
stand are given in Figure 3. Results of ANOVA and multiple comparison
tests are also displayed. Moisture and light data were transformed in order to
stabilize their variances, and statistical tests were then performed on these
data. Multiple comparisons of means for each variable showed significant
differences for soil-based resources and light levels. Ranges for each variable
were generally substantial: soil moisture ranged from 6.8 to 21.5%;
mineralizable nitrogen ranged from 42.9 to 123.8 ug/ g; and light ranged from
0.4 to 6.9% at 0 meters, 0.6 to 17.1% at 2.5 meters, and 1.9 to 22.5% at 5 meters.
A more subtle gradient in pH from 4.8 to 6.7 was also detected. There are
several patterns worth noting in Figure 3. Stands 0H1, 0H2, 0H3, and LIR
grouped consistently at the high end of the N, moisture, and pH gradients.
RP1 and RP2 grouped together towards the low end of the pH and moisture
gradients, while DGF and EUL grouped close together at the low end of the
moisture and N gradients. SP1 and SP2, alternatively, grouped together in
the middle of the pH and N gradients. The remaining conifer stands did not

appear to show a consistent pattern in relation to these soil variables.

Along the light gradient, there were also consistencies among stands
across the range of heights at which light was measured. However, there was
considerable variability among plots for this resource (Figure 3 D,E,F). One
clear pattern is that WP1 and WP2, along with SXW, always group very close
together at the low end of the gradient. This is not surprising given the
relatively deep crowns and large heights of the white pine in these stands.
The hardwood stands were variable in their position along the gradient,

 

8.0

. PH

< F = 12.249
6.0 ' P = 0.0001

 

 

 

WPZRXWSXWRPIRPZSPZDGFSPIEULPOBWPIOI'BOHIOHZ UR
a a a aab ababcabcdabodbcdcddee e f

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POTENTIAL MINERALIZABLE N B
, F = 10.635
120.0 P - 0 mm

 

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WPZDGFRI’IEULWPIRPZSPIRXWSPZPOBSXWOHIOHZIJROI-B
aaababcabcbcbcbcbcbccddeeeff

STAND

Figure 3. Levels of pH and resources for 15 stands in the WK. Kellogg Forest and
Kellogg Biological Station, southwestern Michigan. Columns represent the mean of
three plots with standard error bars of 1 unit above the mean. Stands associated with
the same letter are not significantly different (alpha=0.05). For figures C-F, ANOVA
results are based upon data transformed in order to stabilize variance.

30.0

 

GRAVMETRIC MOISTURE C
F = 8.031
P = 0.0001

 

PERCENT

 

 

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aaebabcabcabcbcdcdecdecdedefefefff

LIGHT AT 0 METERS

P: 00“”

PERCENT

 

WPIWPZSXW SP1LIROH30H2EULPOBDGFOH1RPZSP2RXWRP1
aabababcabcbcdbcdcdededededededee

STAND

Figure 3 (cont'd.).

57

 

 

 

35.0
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20.0

 

 

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aaababcabcabcabcebcbcbcbccccc

STAND

Figure 3 (cont'd.).

58
although 01-13 and HR always had the least light available of the hardwood

group. RP1, RP2, and SP2 tended to group together near the high end of the
light gradient. SP2 is a special case, as mentioned earlier, due to one plot with
considerable crown damage which allowed for an increase in light
penetration. If this plot had been removed from consideration, the two Scots
pine stands would then group together at a lower point along the light
gradient.

Spearman's rank correlation analyses were run and bivariate plots
created using the 15 possible resource-pH pairs (Figure 4). The high positive
correlations of light measured at various heights are not unexpected. What is
apparent from the plots involving light is the existence of one strong outlier
at the high end of the light spectrum. One stand, SP2, was mentioned earlier
as having one plot with very high light levels at 2.5 and 5.0 meters. This
stand is important because it provides a means of assessing other variables
under high light conditions, which could be important for successional
dynamics in plantation forests. Increases in mineralizable nitrogen were
significantly correlated with increases in both soil moisture and pH, while
decreases in soil moisture were significantly correlated with increases in light
at 0 meters; pH was found to be unassociated with both soil moisture and
light (Figure 4). The plots of moisture against light at three heights also

suggest a curvilinear relationship between these two resources.

PCA of Site Variables
Although it is the level of essential resources to which plants will
respond, it is often the case that other site variables, such as slope, aspect, and

pH, are significantly correlated with resources. An increase in slope will

 

 

 

 

 

 

 

 

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Figure 4. Bivariate plots and Spearma

59

filfihtstflmeters Slightstuneius

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and pH for 15 stands at the WK. Kellogg Forest and Kellogg Biological Station, southwestern

Michigan.

 

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61

sometimes increase drainage and lead to less moisture availability, while
southwestern aspects expose sites to higher light levels for longer periods of
time, often resulting in lower moisture. In addition, pH may also influence
microbial activity, which in turn affects nitrogen availability; this relationship
is supported by the significance of the previous correlation of pH with
mineralizable nitrogen. Therefore, principal components analyses (PCA) of
two data sets, one with resource variables, and one with resources as well as
slope, aspect, and pH, were run to determine if the addition of these other site
variables would help in understanding the ordination of stands with respect

to resources.

PCA of Resources

A PCA was run using the product-moment correlation matrix for soil
moisture, mineralizable nitrogen, and light (Table 6). The correlation
coefficients are based on the untransformed data because PCA does not
require multivariate normality. The PCA indicates that 90% of the variability
present in the data set can be attributed to the first two PCs (Table 7). Using
Ioliffe's (1986) suggestion, I have ignored the PCs with eigenvalues < 0.7,

Table 6. Correlation matrix used in PCA for the untransformed resource
variables mineralizable nitrogen, soil moisture, and light.

 

Variable
Variable Nitrogen Moisture Light at 0 m Light at 2.5 m

Moisture 0.738
Light at 0 m -0.289 -0.650
Light at 2.5 m -0.127 -0.514 0.777

Light at 5 m -0.169 -0.546 0.716 0.966

62
Table 7. Eigenvalues, their proportion of explained variance, and their

associated eigenvectors for PCA of resource correlation matrix.

Component (Eigenvector)

 

 

 

 

Variable 1 2 3 4 5
Moisture 0.4558 0.4302 0.0700 0.7693 0.1031
Nitrogen 0.2727 0.7458 0.2485 -0.5546 0.0104
Light at 0 m 0.4588 0.1156 0.8056 0.2746 0.1618
Light at 25 m 0.4912 0.3719 02570 0.1571 0.7278
Light at 5 m 0.4907 0.3271 0.4672 0.0230 0.6583
Eigenvalue 3.2794 1.2439 0.3046 0.1477 0.0244

% of variance 0.6559 0.2488 0.0609 0.0295 0.0049

which leaves the first two PCs for this analysis. The first PC accounted for
greater than 65% of the variability in the data set, and appears to represent a
contrast between soil moisture and light. The eigenvectors for light at each
height level were almost identical in the first PC, suggesting that either an
average across levels or any one height level would be a sufficient
characterization of this resource. Percent moisture was assigned a larger
eigenvector than mineralizable N for the first PC, indicative of its greater
importance in that side of the contrast. The second PC accounted for an
additional 25% of the variability, and emphasized the importance of
mineralizable nitrogen, as evidenced by the large eigenvector for this variable
(Table 7). This PC could be interpreted as a weighted average across all

resources with heavy weight given to mineralizable nitrogen.

A biplot of the first two PCs, based on stand scores and scaled resource
coefficients, provides a visual representation of stand relationships to

resources (Figure 5). Those stands with high soil moisture and low light

 

 

 

 

 

 

 

4
MN
3 ..
2 . PM
L125
om
L15 5??
0H2 ’
r - us our
LTO
U 0 M an 3'"
a.
RXW
591
-1 -I m
WP1
WP2 Dar:
.2 -
‘3 r l 1 T I
.3 -1 1

PCI

Figure 5. The relationship between the distribution of stands and the first and second
principal components for resource variables. Scaled eigenvectors for each variable are also
plotted: PM, percent moisture; MN, mineralizable nitrogen; LTO, light at 0 meters; LT25,
light at 2.5 meters; LTS, light at 5 meters.

64
group to the left side of the plot, while those with high light and low soil

moisture fall to the right. The second axis further separates the stands based
primarily upon an average resource gradient dominated by nitrogen. Those
stands with high mineralizable nitrogen (or high light in the cases of RP1 and
RP2) gather in the upper half of the plot, while those stands with low levels
of mineralizable nitrogen and other resources are found in the lower half of

the plot.

Stands did not tend to form distinct clusters in this biplot; rather, they
were distributed somewhat evenly across both axes. However, three general
groups of stands can be discerned. The first consists of the Scots pine stand
SP2, and the two red pine stands RP1 and RP2, all with generally high light
levels and low soil resource levels (Figure 5). The second group consists of all
the hardwood stands (0H1, OHZ, 0H3, and LIR), as well as the mixed
hardwood-conifer stand P08 and the mixed conifer stand SXW. These have
in common generally low to moderate light levels and high soil resource
levels. The third group includes the mixed conifer stand RXW, the larch
stand EUL, the Scots pine stand SP1, the Douglas-fir stand DGF, and the two
white pine stands WP1 and WP2. These stands can be classified as having
generally low levels of all resources. This ordination of stands suggests that
by planting hardwoods, hardwood-conifer mixtures, or a combination of
different conifers, soil fertility has been enhanced more so than by planting

any one conifer species alone.

65

PCA of Resources, pH, and Topographic Variables

Principal components analysis was also run on resource and other site
data together using the product-moment correlation matrix (Table 8).
Spearman's rank correlations of the new variable combinations were
performed and, not unexpectedly, significant correlations were found
between soil moisture and slope (Spearman's r = -0.654, p -= 0.0144), soil
moisture and aspect (Spearman's r = 0.563, p = 0.0350), and between light at 0
meters and aspect (Spearman's r = -0.688, p = 0.0101). The Beers aspect
transformation used on the aspect data allocates the highest values to NE
aspects, where growing conditions tend to be more favorable, while SW
aspects have the lowest values.

In this PCA, the first three components have eigenvalues > 0.7 and
together account for 85% of the variability in the data set (Table 9). Again,

Table 8. Correlation matrix used in PCA for the untransformed resource
variables and pH, aspect, and slope.

 

Variable

 

 

Light light at Light
Variable pH Nitrogen Moisture at 0m 2.5m at 5m Aspect

Nitrogen 0.757

Moisture 0.455 0.738

Light at 0 m -0345 -0.289 -0.650

Light at 2.5 m -0.232 -0.127 -0.514 0.777

Light at 5 m -0.208 -0.169 -0.549 0.716 0.966

Aspect 0.240 0.440 0.550 -0.641 -0.322 -0.333

Slope -0.180 0307 -0.684 0.532 0.551 0.513 -0.123

 

66

Table 9. Eigenvalues, their proportion of explained variance, and their associated eigenvectors
for PCA of resource and site correlation matrix.

 

 

 

Component (Bigenvector) j
Variable 1 2 3 4 5 6 7 8
pH -0.2516 0.4977 -0.1948 0.5959 -0.3589 -0.1555 0.3779 -0.0124
Moisture 04228 0.1846 -0.1019 0.3784 0.2813 05158 05048 0.1828
Nitrogen -0.2924 0.5888 «0.1038 0.0299 0.3538 -0.0306 «0.6545 -0.0419
Light at 0 in 0.4192 0.1694 -0.2598 0.0394 -0.1440 0.1328 0.1553 -0.7229
light at 2.5 in 0.3884 0.3994 0.0467 0.3199 0.5763 —0.5008 0.3313 0.1839
Light at 5 m 0.3853 0.3759 0.0358 0.2978 -0.4459 0.0992 -0.1122 0.6317
Aspect -0.2960 0.1459 0.7593 0.2392 -0.0207 -0.4789 0.1635 0.0276
Slope 0.3310 0.1440 0.5416 -0.5010 0.3389 0.4485 0.0293 0.0919
Eigenvalue 4.3088 1.6208 0.9055 0.6831 0.3028 0.1101 0.0498 0.0191
% of variance 0.5386 0.2026 0.1132 0.0854 0.0378 0.0138 0.0062 0.0024

 

using Ioliffe's (1986) suggestion, I will only consider these three components
in discussion. The first two PCs explain a majority (74%) of the variation in
the data set. The first PC, accounting for 54% of the variation, represents a
contrast between soil resources, primarily moisture, and light, as in the
previous PCA. However, added to the soil resource side of the contrast are
pH and aspect, while slope was added to the light side of the contrast. The
second PC again appears to represent a composite or average of all variables,
and accounts for an additional 20% of the variation in the data (Table 9). This
PC is dominated by both mineralizable nitrogen and pH. The smaller
loadings received by the topographic variables in the first two PC's seem to
indicate that these variables do not contribute much more to the
interpretation of stand distribution than do resources, at least for these
components. The third PC is dominated by aspect and to a lesser degree slope,
and explains another 11 % of the variance (Table 9). This component
represents the primary contribution of adding topographic variables to the

resource data set, as it is the only one in which these variables are dominant.

67

The addition of pH and topographic variables did lead to the formation
of loose clusters of stands in a plot of PC1 against PC2 (Figure 6), as opposed to
the more even distribution of stands in the resource biplot (Figure 5). Along
the first axis, the stand ordination remained virtually unchanged from that of
the first analysis. However, the second axis contributed two changes to the
ordination. The mixed conifer stand SXW was drawn from the hardwood
group to a position in the lower half of the plot with the bulk of the conifer
stands having low levels of soil resources. The distinction in this case is the
low pH of SXW as compared to that of the hardwoods, despite its higher
levels of mineralizable nitrogen. The second change is a more subtle shift of
WP2 away from the conifer group and further down the PC2 axis. This
change is also indicative of the stand's lower pH, and therefore its low fertility
in comparison to the other stands. The three general groupings of stands
mentioned earlier remain in the same relative positions as in the previous
PCA biplot, and can be defined similarly as stands with low light and high soil
resources, stands with high light and low soil resources, or stands with low

levels of all resources. In this case soil resources include pH.

The biplot of PC1 and PC3 distinguishes WP1 and SP1 as a small
cluster, as well as SP2 and LIR as a cluster about the plot center (Figure 7).
WP1 and SP1 are stands with relatively steep slopes, but with the
northeasterly aspects more favorable for plant growth, a condition not
distinguished in the plot of the first two components. LIR is separated from
the oak-hickory stands, presumably due to its association with a southwest
aspect along the second axis. The biplot of PC2 and PC3 also emphasizes the
distinctness of WP1 and SP1 as a group, and LIR (Figure 8). The three oak-

 

 

 

 

 

 

 

MN
PH
2 5 1%"
cm 592
1 M 01-13
’ P 1.10
ASP 51-?
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591
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Figure 6. The relationship between the distribution of stands and the first and second
principal components for resource and site variables. Scaled eigenvectors for each
variable are also plotted: labels as defined in Figure 5, with the addition of PH, ASP,

upecb SLP. slope-

 

69

 

 

 

 

 

 

 

 

4
ASP
3 '-
SLP
2 __ WP1
591
1 _ 592
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om
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Figure 7. The relationship between the distribution of stands and the first and third
principal components for resource and site variables. Scaled eigenvectors for each
variable are also plotted: labels as defined in Figure 6.

70

 

 

 

 

 

 

4
ASP
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1 1- SP2
01-12
A T2 q... £1135
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Figure 8. The relationship between the distribution of stands and the second and third
principal components for resource and site variables. Scaled eigenvectors for each
variable are also plotted: labels as defined in Figure 6.

71
hickory stands form a tight cluster in this plot, not having done so in the

previous two. Here, as in previous biplots, their positions tend to suggest

moderately favorable growing conditions in most respects.

Graphically the PCA biplots that include other site variables in addition
to resources did not contribute significantly to an understanding of the stand
ordination, ie. they do not dramatically change the interpretation of stand
associations based on the PCA using resources alone. Relationships between
site characteristics and resources that were apparent in the correlation
analyses of these variables: aspect and pH with soil resources, and slope with
light, were reinforced in these biplots. This suggests that in some cases the
physical heterogeneity of this landscape may interact with overstory
composition to influence resource levels and thereby the ordination of these
stands. It appears, then, that measures of actual resource levels best
characterize the ordination of these plantation and natural forests. For this
reason, in ensuing sections that use these data to explore different questions,

the resource data set without the other site variables will be employed.

To summarize, it appears that three groups of stands can be discerned
from the PCA ordination: one group with low to moderate light and high soil
resource levels (0H1, 0H2, 0H3, LIR, POB, SXW), a second group with high
light and low to moderate soil resource levels (SP2, RP1, RP2), and a third
group with generally low levels of, all resources (RXW, SPl, EUL, WP1, WP2,
DGF). It is also interesting to note that POB, a hardwood-conifer mix
plantation, consistently occupied the middle of all ordinations depicted in the
PCA biplots.

Species-Resource Relationships

This section describes the relationship between species and resource
distributions across stands. Saplings and seedlings will be analyzed separately.
In some cases, species with potential to reach the overstory occurred with low
constancy and frequency, and were subsequently dropped from the analysis.
Exceptions to this were cases where occurrence appeared to be directly related

to levels of a particular resource.

Saplings and Resources

There are clear differences among stands in numbers and basal area of
sapling species (Table 10). The high light SP2 stand has the largest number of
species, with 10 out of 19 present. Stands with a Scots pine component (SP1,
SP2, SXW), as well as WP1, also have the largest total sapling basal area of all
stands. The stand DGF has only 2 of the 19 species present, with the large
aspen basal area here due to one large individual (Table 10); the plots were
representative of this plantation, as it appeared quite barren of advanced
regeneration of woody plants. Basal areas of all species are fairly low in
general, often representing only one individual of a species in a stand. Most
often, large basal areas represent high numbers of small stems, rather than a
few larger individuals; this was especially true for red maple.

Red maple, black cherry, and to some extent white ash, American elm,
and sassafras are quite ubiquitous throughout the area. In fact, red maple and
black cherry dominate the sapling stratum in 11 out of 15 stands (Table 10). Of
these two species, red maple appears to be the primary dominant in terms of
basal area. There do not appear to be any recognizable relationships between

 

 

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74
stand type and species basal area, except for an increase in the basal area of red

maple in association with Scots pine.

Of the 19 species present in the stands, 11 were chosen to study the
relationship between patterns of sapling dominance and resource levels. Box
elder, sassafras, and sweet cherry were not considered because they are
unlikely to become important members of future stands. In addition, none of
these species is present in enough numbers (except sassafras in WP2) to be a
potential competitor at this time in these stands (Table 10). Bitternut hickory,
hackberry, beech, aspen, and white pine, although all potential overstory
dominants, occurred with such low frequency and/ or constancy in these plots
that they were also not considered (Table 10). However, there are some
interesting notes to make on these five species. Bitternut hickory and
hackberry occur as saplings only in close proximity to seed sources, which are
quite infrequent and localized in these stands (personal observation).
Alternatively, white pine occurred as a sapling only once in all stands
surveyed, although this species makes up a large proportion of the overstory
basal area in many of these stands. This individual was found in the one
high light plot of SP2 The high basal area of beech in SP2 and aspen in DGF
were due to one individual of each species, and there appeared to be no
relationship between their locations and those of potential seed sources.

To determine if there were associations between patterns of sapling
dominance and resource levels, stands were first ranked, from low to high
levels, for soil moisture, mineralizable nitrogen and an average of light at 2.5
and 5 meters. This light measure is more biologically meaningful in this
study because sapling height is generally below 5 meters; the saplings are

75
more likely to respond to light at these levels and not at the ground. This

average is also supported by the similar loadings both light levels received in
the PCA's. Once stands were ranked for each resource level, basal area / ha by
species was graphed against each resource gradient (Figures 9-11).

Red maple, black cherry, and to a lesser extent white ash and American
elm occurred relatively evenly over a wide range of moisture and nitrogen
levels (Figures 9-10). American elm did appear to associate with somewhat
higher levels of these variables. In terms of light levels, all four species except
white ash showed a marginal shift in distribution towards lower light levels
(Figure 11). An explanation for the relationship of red maple and black cherry
with low light is that these species are creating, rather than responding to, low
light levels. This reasoning would primarily apply to the stand SPI, where
heights averaged 4.7 meters for red maple and 7.3 meters for black cherry.

The height of these saplings would have influenced the light meter readings

at all levels measured.

Four of the seven remaining sapling species exhibited distinct trends in
dominance associated with individual resources. Sugar maple, tulip tree, and
slippery elm exhibited larger basal areas at high moisture and high
mineralizable N ends of each gradient (Figures 910). Black oak, in contrast,
had its highest basal area at the low end of the soil moisture gradient and in
the middle of the mineralizable nitrogen gradient. Along the light gradient,
these two groups of species had complementary distributions, with sugar
maple, tulip tree and slippery elm grouping with low light, and black oak
with high light (Figure 11).

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79
Pignut hickory, with a distribution as wide as those of red maple and

black cherry, had small dominances associated with the stands in which it was
found, making the interpretation of its relationship to resources difficult
(Figures 9-11). Both red oak and basswood occurred in only four stands, and
their distributions were also difficult to characterize in relation to resources.
Basswood tended to be evenly distributed across the middle of both soil
resource gradients, while red oak, though also spread widely, tended towards
the higher end of these gradients (Figures 9-10)’. Along the light gradient,
however, the distributions of the two species were not parallel: red oak
occurred at lower light levels and basswood at higher light levels (Figure 11).

In order to compare relationships between species and stands along the
composite gradient generated by the PCA of resources, relative sapling basal
areas on a stand basis were determined, and then stands were classified by
species on a 0-5 scale of 20% relative basal area increments. These stand
classes were then plotted in place of the stands on the PCA biplot (Figure 5)
for each species (Figure 12). One will recall that three groupings of stands were
depicted in this biplot: stands with low resource levels in the lower half;
stands with high light and low to moderate soil resource levels to the upper
right; and stands with low to moderate light and high soil resource levels to

the upper left.

For the four most common species, red maple, black cherry, white ash,
and American elm, there were again no strong trends towards association
with any of the three groups of stands (Figure 12). Red maple and white ash
appear to associate more with stands having generally low levels of all

resources, while American elm exhibits larger relative basal areas in stands

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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component axes for resources. Values indicate species importance on a 0-5 scale
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83
with lower light and higher soil resource levels. Black cherry shows a slight

association with stands having more moderate to high levels of all resources
(the upper half of the plot). The trends described earlier that were obvious for
sugar maple, tulip tree, slippery elm, and black oak, are equally obvious with
this biplot: ie. black oak is associated with stands having high light and low
soil resource levels, with the complimentary association for the other species
(Figure 12). The association of pignut hickory with stands having lower
levels of all resources is more apparent in Figure 12, although it also is found
in the other two groups of stands. Red oak and basswood occur with low
relative basal area in each of the three groups making interpretation of their
distribution in relation to resources again difficult.

Seedlings and Resources

For seedlings, there appear to be no distinguishable patterns of species
recruitment associated with a particular stand type, as in the sapling stratum
(Table 1 1). As before, red maple and black cherry are dominant members of
the understory tree community in almost all stands, natural and planted. In
the seedling stratum, black cherry is the primary dominant and occurs in
every stand, while red maple shows reduced constancy. This situation is the
reverse of that found in the sapling stratum (Table 10). Species richness
however, does vary across stand types (Table 1 1). The oak-hickory stands
have limited seedling species richness when compared to all other stands
except EUL, SP1, and SXW. It is interesting to note that stands with relatively
low sapling species richness, especially DGF, RP2, and RXW (Table 10),
increase in numbers of species in the seedling stratum (Table 11). The stands
EUL, SP1, and SXW show a marked decrease in species richness from the
sapling stratum to the seedling stratum. A possible explanation for this

 

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85
phenomenon is that succession had been delayed in stands with higher

seedling diversity, either by earlier thinnings and hardwood removal, or
harsher site conditions. The lack of seedling diversity in stands with high
sapling diversity may be due to increased competition.

Of 22 species present as seedlings, only ten were chosen to compare
with stands across resources. Four species, box elder, serviceberry, sweet
cherry, and sassafras were not considered for the same reasons as stated for
the sapling analysis. Of these four, sassafras has the potential to be a
competitive threat because of its often large numbers (Table 11), although it
will never become a member of the overstory. There were also eight species
that, due to low constancy (eg. s 2 individuals across 45 subplots), were not
included in this part of the analysis: sugar maple, pignut hickory, hackberry,
aspen, Douglas-fir, white oak, black locust, and slippery elm. Two new species
were, however, added to the ranks of potential recruits. These were white
pine and shagbark hickory, both of which were not present in the sapling
stratum. It is interesting to note that hackberry seedlings occurred only in
WP2, the only stand close to the lone hackberry seed source, and that Douglas-
fir seedlings only appeared in the Douglas-fir stand (Table. 11).

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sapling data in order to look at possible patterns in species responses to
resources in these stands (Figures 13-15). However, the light level used in
this case was light at ground level, which is the most biologically meaningful
measure of light for the seedlings.

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89
Seedling species more or less mirrored the distributions of their sapling

counterparts relative to individual resources (Figure 13-15). For example,
black cherry had a uniform, wide distribution across the range of resource
levels as both a seedling and sapling. In fact, the seedling distribution of this
species in relation to light was wider than it was for saplings (Figures 15). Red
maple as a seedling also had a similar dominance pattern as a sapling,
although there was a bias in seedling dominance towards lower moisture and
nitrogen, and higher light levels (Figures 13-15). White ash seedlings
occurred over the range of resource levels, with peaks in dominance towards
the high ends of the soil gradients and low end of the light gradient (Figures
13-15). Basswood was again associated with the middle of all gradients.

White pine was clearly associated with high light, and with moderate levels
of moisture and nitrogen. Seedling distributions of shagbark hickory, tulip
tree, and elm coincided at high levels of soil resources and lower levels of
light (Figures 13—15). Among the oaks, red oak seedlings had a broader
distribution than black oak seedlings, while both were more abundant when

associated with moderate levels of soil resources and higher levels of light

(Figures 13-15).

Figures 16 shows the distribution of each seedling species, by relative
density class, relative to the composite resource gradients of the PCA for
resources in Figure 5. Again, the arrangement of seedling dominances across
this biplot tend to support and/ or amplify the seedling relationships in
evidence with the individual resources. Black cherry and white ash seedling
densities appear to be spread somewhat evenly across the three groups of
stands depicted earlier for this plot, while the higher red maple seedling
densities tend to be found in stands with low to moderate light and soil

 

 

 

 

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Figure 16. Distribution of 10 seedling species, relative to the first and second

principal component axes for resources. Values indicate

ies importance on a 0-5

scale using divisions of 20% relative density: 0, 0%; l, l-20%; 2, 214096; 3, 41-60%; 4,

“-80%; 5, 8140”».

 

 

 

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Figure 16. (cont'd.).

91

 

 

 

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93
resource levels (Figure 16). American elm seedlings appear to favor lower

light levels and higher soil resource levels, although the association is not as
well defined as that for elm saplings. Shagbark hickory mirrored the
individual resource results, being clearly associated with stands having
higher soil resources and low light. Both the oak and white pine associations
found in the individual resource charts were also maintained in this biplot

(Figure 16).

To summarize, red maple and black cherry are the most common
species of the understory in both seedling and sapling strata, not only having
high constancy, but also dominating each stratum. However, these species
showed no definitive associations with resource levels. Red maple tended to
dominate the sapling layer in more stands than black cherry, while cherry
dominated the seedling layer in more stands than red maple. American elm
was also a dominant member of the sapling community in three stands, and
white ash was common to both sapling and seedling strata, although it rarely
dominated either. There appears to be little recruitment in all stands of the
dominant, naturally occurring tree species in this landscape ie. the oaks and
hickories; they are present, but in very low numbers. Although there are no
apparent patterns of sapling and seedling recruitment in relation to stand
type, certain patterns did emerge for some species in relation to the resource
levels found at these stands. Saplings and seedlings of the elms, tulip tree,
sugar maple, and shagbark hickory tended to have higher dominances in
association with stands having higher soil resource levels and lower light
levels. White pine and black oak dominances in the understory were clearly
associated with low to moderate soil resource levels and high light levels.

However, most of the strong associations concerned species with relatively

94
low dominance or frequency. Although this may be an important indication
of recruitment limitation, the high variability associated with low sample size

allows little more than speculation.

Species-Seed Source Relationships

To further explore patterns in the distribution of understory species in
the 12 plantations studied, distances to the nearest original seed sources of
species present in each stand were determined at the plot level. The goal was
to see if the distributional patterns of understory tree species could be
attributed to dispersal limitation, as indicated by seed source distance.
Distances were measured from potential seed source to each of the 36 plots (3
per stand), rather than to stands, as the smaller scale is more meaningful in
relating individual species dominances to a distance. Numbers of stems were
used instead of basal area because, intuitively, this measure is more a
reflection of dispersal success and survival, while basal area reflects survival
and growth after dispersal has occurred. In addition, only the sapling data is
presented here. The relationship of seed source to seedlings is confounded by
the fact that the seed rain to the plot that produced those seedlings could have
come from a combination of original and later sources; only distance data on
original sources was gathered. This problem may also be present with
saplings, although minimized somewhat by looking at the older regeneration

in these plantations.

There were several problems with this part of the study that need to be
discussed. First, for the elms, cherries and hickories, only the generic names
"elm", "cherry”, and ”hickory" were referred to on the maps, although sweet
and black cherry, slippery and American elm, and shagbark and pignut

95
hickory were all present in the area. Because sweet cherry was an introduced

species, and because it and slippery elm and shagbark hickory were not
abundant in the landscape of 1930-1940, I assumed that the species represented
by these generic names were American elm, black cherry, and pignut hickory.
I believe this to be a fair assumption, although certainly not without

violation.

The second and more serious problem involves the maples and oaks.
In many cases, species on the maps were defined, but in several cases, only the
generic names "oak" and "maple" again were used. Unlike the cherry, elm
and hickory situation, white, red, and black oak were all important trees in
the landscape, as were red and sugar maple. So in cases, for example, where
the generic ”oak" seed source was closer to a plot than a ”red oak" seed source,
a subjective decision was made as to whether the "oak" was more likely to
have been a red oak or some other species. This decision was aided by field
observations in some cases, although not all seed sources were traced in the
field. Generally, unless the distance seemed quite unreasonable, the specific
source was used for distance. In some instances, however, the difference in
distance to plot between the generic and specific seed sources determined
whether the plot was quite close or quite far from the source; differences were

>200 m in a few cases.

A third problem was encountered when species of trees found in the
overstories of both natural and planted stands were investigated. Of special
concern was red oak, as this species was a dominant in the plantation PCB,

and obviously has been of seed-bearing age for at least the past 20 years. This

96
has allowed plenty of time for its offspring to reach sapling size. So in this

case, distance to the nearest seed source, either planted or natural, was used.

There are a wide range of distances that seeds of various species have to
traverse in order to reach the plots (Table 12). Closest sources ranged from 5
m away for several species to 34 m away for sugar maple and white ash.
Farthest distances varied substantially, ranging from 122 m for black cherry to
849 m for sugar maple. Mean distances from nearest potential seed source, by
species, ranged from 33.34 m for black cherry to 301.31 m for sugar maple
(Table 12). Given the ranges in Table 12 for the wind-disseminated species
(the maples, ash, and elm), there is potential for dispersal limitation,
although long distance dispersal is an infrequent but important event. For
animal-dispersed species such as hickory, the oaks, and black cherry, dispersal
limitation may be present, but less likely a function of these distances than of
the interspersion and juxtaposition of old fields, young plantations, woodlots,
and corridors dominating this landscape; none of the ranges in distance from
potential seed source to these species appears unreasonable for an animal to
traverse (Table 12). Black cherry is noteworthy because it was so prevalent
along fencerows at the time of plantation establishment; consequently no
saplings were found farther than 122 meters from a potential seed source.

For each species, the 36 plots examined were classified into four seed
source distance categories (0-50 m, 51-100 m, 101-200 m, and > 200 m).
Distance classes were chosen as such based upon seed dispersal literature for
forests, which indicates that the bulk of seed produced by wind-disseminated
species falls within 50 m of the source (Johnson et al. 1981), although dispersal
to within 100 to 200 m is somewhat easily achieved (Green 1980). Proportions

97

Table 12. Distance (m) from plot center to potential seed sources for sapling species
found frequently in plots in the W. K. Kellogg Forest, southwestern Michigan.

 

 

 

Species
Black White Red Sugar
Stand Plot Red oak oak Cherry Elm ash maple maple Hickory
DGF 1 30 30 30 91 325 30 189 148
2 34 34 34 56 317 34 204 125
3 37 37 37 44 317 37 222 114
EUL 1 88 136 84 73 136 136 136 , 6
2 101 139 72 49 139 139 139 50
3 113 154 88 66 149 149 154 53
LIR 1 62 5 62 98 256 62 358 62
2 117 56 43 43 312 43 385 117
3 98 98 5 11 352 15 407 154
P08 1 15 277 91 91 277 47 73 69
2 15 239 88 56 291 5 46 32
3 20 235 34 44 338 67 108 55
RP1 1 20 291 27 119 152 117 139 128
2 82 226 85 111 149 149 178 216
3 52 276 105 58 103 103 125 152
RP2 1 34 34 5 73 34 34 34 34
2 76 81 18 20 81 81 81 15
3 82 82 6 79 82 82 82 50
RXW 1 174 174 88 180 174 174 174 174
2 87 87 46 224 87 87 87 87
3 128 128 122 226 128 128 128 128
SH 1 72 155 5 53 76 67 846 49
2 125 125 5 72 40 5 815 27
3 165 168 6 21 70 52 849 58
SP2 1 105 94 59 61 331 59 340 114
2 72 72 72 90 343 70 317 122
3 84 84 70 70 370 84 350 151
SXW 1 88 172 43 62 210 27 87 64
2 53 137 35 96 186 5 122 37
3 69 157 53 90 166 5 102 40
WP1 1 152 396 14 5 175 175 526 126
2 140 355 5 69 166 198 459 58
3 218 392 26 160 244 302 425 104
WP2 1 122 122 S 149 120 122 748 122
2 148 148 30 180 133 148 719 148
3 175 175 55 198 1:!) 175 693 155
Mean distance 90.36 154.75 45.92 88.56 193.31 89.25 301.31 92.89

SD 50.75 100.17 33.34 57.08 101.10 66.84 251.47 52.01

98
of those plots in each class having saplings present were then determined

(Figure 17). Given the literature just mentioned on the subject, one would
expect a decreasing proportion of plots to be occupied as distance increases.
However, the only wind-disseminated species appearing to support this trend
is American elm (Figure 17). Of the other wind-disseminated species, red
maple occurs in a high proportion of the plots within each class, while sugar
maple does not. For both of these species, long distance dispersal beyond 200
m does occur, suggesting that these species are not limited by seed dispersal.
However, 10 of the 17 plots in the 200+ m class for sugar maple were farther
than 400 m from a potential seed source (Table 12), and no saplings of this
species were found in these plots. This suggests upper limits to long-distance
dispersal for sugar maple. As sugar maple was the only species for which plot
distances from seed sources occurred above 400 m, upper limits cannot be
suggested for the other species examined. In addition, the low proportion of
plots occupied by this species overall suggests that other factors besides
dispersal distance are limiting sugar maple. White ash shows a strikingly
high level of occurrence (73%) in the 15 plots within the 101-200 m class, but
does not occur at all in the 14 plots beyond 200 m (Figure 17). This pattern
suggests dispersal limitation beyond 200 m for this species, but also indicates
that within 0-200 m of the nearest potential source, other factors are involved

in limiting this species' occurrence.

Of the animal-dispersed species, only black cherry showed high levels
of occurrence, and only within the 0-100 m range (Figure 17). As only 2 plots
occurred beyond 100 m, it is impossible to draw conclusions about long-
distance dispersal. It is clear, however, that at least for these plantations, black
cherry has little need for long distance dispersal, with 94% of the plots

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100
sampled falling within 100 m of a potential source. As most potential cherry

seed sources were found in hedgerows of the 1940 landscape, it is interesting
to note that a higher proportion of saplings occurred in the 51-101 m class,
rather than in the 0-50 m class. This may be related to perch selection by birds
disseminating these fruits, with more attractive perches occurring farther
than 50 m from the hedgerows (McDonnell and Stiles 1983). The oaks and
hickory are present in low proportions of the plots in each class, and therefore
distinct patterns do not emerge for these species (Figure 17). As the farthest
distance class was undersampled for red oak and hickory, one cannot
speculate about long-distance dispersal limitation. Only one plot farther than
200 m from a black oak seed source was found to harbor a black oak sapling;
the remaining 8 plots were farther than 230 m from a source, suggesting the
possibility of long-distance dispersal limitation for this species. However,
dispersal limitation for the oaks and hickory may have more to do with
animal vector ranges, and less to do with absolute distance to a particular seed
source. The low proportion of plots in each class occupied by these species

also suggests that other factors are more limiting towards their success.

Table 13 shows the results of the chi-square goodness-of-fit analysis, for
each species, across two distance classes pooled from the previous four classes.
Black cherry was not included as it occurred in only one of the two classes. A
uniform distribution was used to test the goodness-of-fit of the species
distributions. Only the distributions of white ash and American elm across
distance classes are significantly different from a uniform distribution, while
the distributions of the other species could not be distinguished from such a
theoretical distribution (Table 13). There could be two explanations for this.
These species, except for white ash and elm, could in fact have equal

101
Table 13. One-way chi-square goodness-of-fit analyses, for each species, comparing the
distribution, across distance classes, of plots with saplings present with a theoretically uniform
distribution of the same plots.

 

 

 

SPECIES
DISTANCE VALUE Red Sugar White American Red Black Pignut

CLASS TYPE maple maple ash elm oak oak hickory
o-ioom observed 16.0 1.0 2.0 12.0 1.0 4.0 1.0
Expected 12.5 2.5 6.5 6.5 2.0 2.5 2.5
>1mm Cbserved 9.0 4.0 11.0 1.0 3.0 1.0 4.0
Expected 12.5 2.5 6.5 6.5 2.0 2.5 2.5
z2 1.96 1.80 6.23" 9.31“ 1.00 1.80 1.80

 

‘ Values >383 are significant at alpha-015 for 1 df.
“Values >6.62 are significant at alpha-0.01 for 1 df.

probabilities of occuring in either distance class. This may be due to the fact
that over the past 40 years, inequities in site quality or herbivory among plots
have eliminated the saplings in such a way as to produce these distributions.
This may be more likely for red maple, for which there were enough plots in
which it was present to produce statistically reliable expected values.
Alternatively, it could be argued that this test was not powerful enough to
detect deviations from a uniform distribution due to the low frequencies of
plots in which these species were found, leading to low (<5.0) expected values.
This is most likely the case for sugar maple, the oaks, and hickory, although
site conditions and herbivory could still be important factors limiting the

success of these species.

Since expected values for white ash and American elm were above 5.0,
there is some confidence in the results for these species. The opposing trends
of these two species, in terms of presence relative to distance, found in Figure
17 are further emphasized here (Table 13). Although the non-uniform .

102
distribution of American elm is supported by the literature for wind-

dispersed species (Green 1980; Johnson et al. 1981), that of white ash is not. A
likely explanation for the unusual distribution of white ash appears to be that
most saplings occurring in the 7 plots within the 0-100 m class may have been
eliminated by adverse site conditions for this species, or by herbivory.

To determine if trends in species distributions relative to distance
changed when distances were compared with species densities, frequency
plots similar to those in Figure 17 were constructed (Figure 18). In this figure,
numbers above bars refer to the absolute number of stems counted in each
class ‘for each species. Although changes in magnitude for each class changed
somewhat from those in Figure 17, the patterns were maintained for all
distributions except that of red maple (Figure 18). For red maple, 98% of the
saplings counted were found within 200 m of a potential seed source.
However, only one plot, occupied by 4 saplings, was found further than 200 m
from a source. This suggests that, although red maple does not appear to be
dispersal limited in these plantations, its lack of dominance in this plot may
be due to the greatly reduced numbers of seeds likely to reach it. Adverse site
quality in this plot for red maple is unlikely, as the other two plots in this
stand (WP1) each had more than 10 individuals in residence.

As far as the other species are concerned, it is clear that the low
frequencies of saplings in the >200 m distance class (Figure 18) correspond to
the low proportion of plots occurring in that class that are occupied by each
species (Figure 17). This data suggests that dispersal distance may be limiting
the ability of all species to dominate plots further than 200 m from a seed
source, although it does not appear to limit the ability of the seeds of red

103

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104

maple, sugar maple, and black oak to at least reach these sites and germinate
successfully. As only sugar maple seed sources average greater than 200 m
from the plots established in these plantations (Table 12), it may be likely that
this long-distance dispersal limitation was not important in the development
of the understories sampled. For seed source distances between 0-200 m, the
distributions and dominances of all species except American elm indicate that
dispersal is not limiting to their successful establishment in the plantations
surveyed (Figures 17-18). American elm is the only species clearly exhibiting
the trend of decreasing presence and dominance with increasing distance
from potential seed sources. In the 9 plots occurring beyond 100 m from an
elm seed source, only one sapling was found, and this at 111 m (Figure 17).
This data strongly suggests the lack of adequate dispersal of American elm
seeds over distances greater than 100 m. It should be noted that although this
is a distinctive trend, resource quality at these 9 plots could have been harsh
enough to preclude the successful establishment of this species, despite its
ability to reach these plots.

DISCUSSION

Stands and Resources

_ Soil resource levels ranged widely across stands examined, and this was
especially true for potential mineralizable nitrogen, with threefold differences
in rates. Other studies have also shown such wide variation, but generally
across much larger geographical regions such as counties or states, and across
different soil and forest cover types. Padley (1989) used an almost identical
nitrogen mineralization assay as was used in this study, and found a range in
mineralized nitrogen concentrations from 26.5 to 150.0 ppm for several
different forest ecosystems across northeastern Lower Michigan. Myrold
(1987) also found wide variation (18.8-101.0 ppm) in mineralized nitrogen,
using anaerobic incubation, for several forest types found across Oregon.
Powers (1980), sampling forests across Northern California, and Smith (1981)
across Washington, found much lower, but still wide-ranging, values for
mineralized nitrogen using anaerobic incubation. These five studies found
three- to sixfold variation in rates across broad geographical regions, different
soils, and different forest compositions. In contrast, this study found
threefold differences across a 114 ha forest and very similar soils, but quite

different overstory compositions.

Values for pH in Northeastern forests tend to range from 3.2-5.8
(Vitousek et al. 1982; Zak et al. 1986). In studies by Nadelhoffer et al. (1983),

105

106

Artigas and Boerner (1989), and Glitzenstein et al. (1990), plantations and
natural forests of differing species composition occurring over relatively
small areas (325-512 ha) and on similar soils were examined. Values for pH
in these three studies were also widespread, with ranges of 4.4-6.3, 3.6-5.0, and
4.0-5.5, respectively. The range in this study, 4.8-6.7, tends to be high,
although only one stand (LIR) had a pH > 6.0. The higher trends in pH at the
Kellogg Forest, in predominantly conifer stands, may be explained by the
forest's relatively recent agricultural past history.

Moisture levels found in this study, although wide-ranging, tended to
be low compared to values presented in the literature for Northeastern
forests, which may range from 18-37% (Robertson and Vitousek 1981; Pastor
et al. 1984; Glitzenstein et al. 1990). Moisture availability at Kellogg Forest and
KBS may have been influenced by a short dry spell that had occurred before
sampling.

These soil resource data clearly suggest the hypothesis that rates of
potential nitrogen mineralization at 0-5 cm, pH at 0-5 cm, and possibly
moisture at 0—15 cm, are influenced by the species composition of plantation
forests. However, large variation in each of these three variables can occur
over relatively small spatial scales, as was found by Robertson et al (1988) in a
0.5 ha old field ecosystem at KBS. Strong spatial dependence was found at 25-
30 m scales for mineralizable nitrogen, < 20 m scales for pH, and <10 m scales
for moisture. It is unclear how comparable these patterns are to those in a
forest system, as little if any research has been undertaken to quantify small
scale spatial variability in soil resources for forests (Leonard 1985), although it
is well-known to exist (Stone 1975). More extensive sampling in each stand,

107

and across other stands with similar soils and species compositions, would be
necessary to adequately begin to test this hypothesis.

Although light levels in this study also varied substantially and
significantly across stands at each height measured, this was not unexpected,
given the wide variety in overstory species composition. The ranges found
tend to exceed in breadth those found in the literature for fewer stand types.
Canham et al. (1990) found a range of 0.5-5.2% global transmission of PAR at
1.5 m height across five temperate and tropical old-growth forest ecosystems,
while Artigas and Boerner (1989) found global transmission of PAR under
three different pine types in Ohio to range from 13.2-14.6% at ground level.
The strong associations of white pine-dominated stands with the lowest light
levels, and red pine-dominated stands with generally higher light levels,
clearly suggest a species-dependent effect upon this resource.

Correlations of resource and other site variables with each other help
to suggest mechanisms for overstory effects on resources. The more
important correlations are those between moisture and light, moisture and
mineralizable nitrogen, and pH and mineralizable nitrogen. The first two
form the basis for the stand ordination using PCA. Secondary relationships
that prove useful also include those between moisture, slope, and aspect, and
between light and aspect.

Decreases in soil moisture are known to inhibit the activity of both the
soil bacteria and fungi that mineralize nitrogen (Griffen 1972; Swift et al.
1979), thus supporting the positive correlation between these two variables
found in this study. Therefore, any species-dependent attribute or activity of

108

the overstory that is likely to reduce moisture levels may also decrease
nitrogen availability. Of the three groups of stands identified in the PCA
ordination, two groups were characterized as having low to moderate levels
of the two soil resources. The first group (RP1, RP2, SP2) also has generally
high light levels, strongly suggesting that high light can reduce soil moisture
through evaporation, thereby limiting both the microbial biomass and
nitrogen mineralization. This contention is supported by the strong negative
correlation found here between light and moisture. In particular, red pine
appears to allow more light to pass through its canopy than other species,
although plantation ages and spacings were relatively constant.

However, more moderate levels of mineralizable nitrogen were found
in the SP2 stand, the canopy of which was damaged in a 1982 ice storm. The
plot most affected by this damage probably had an increase in both litter and
light following the storm. More snow was likely to be captured in the new
small openings scattered about, leading to increases in available moisture in
the following spring. This moisture, combined with high light levels and
organic material, and a generally southwest exposure, may have boosted the
microbial population at this site and led to high rates of microbial activity and
mineralization of nitrogen (Swift et al. 1979). Although moisture levels have
since declined, higher soil temperatures are still likely in this high light plot,
and may counteract any low moisture effects on the rate at which the

microbial populations rnineralize nitrogen.

For the second PCA group with low soil moisture and mineralizable
nitrogen (DGF, EUL, WP1, WP2, RXW, SP1), the mechanism for reducing soil

moisture is less obvious, as these stands are also characterized as having low

109

light levels, although RXW has the highest light levels of the group and
tends to be dominated by red pine. These stands, with the exception of DGF,
have more available moisture than the previous three high light stands,
suggesting that increases in light only exacerbate an already poor situation.
The link between low moisture and low mineralization rates in these stands
may be related more to past history, erosion, and differences in the

underlying physical soil template, than to effects of species on moisture.

Stands having high moisture and mineralizable nitrogen levels (0H1,
OHZ, 0H3, LIR, POB, SXW), were found to have low to moderate light levels,
again reflecting the positive correlation between mineralizable nitrogen and
soil moisture, and suggesting deep shade as a mechanism for conserving soil
moisture. With the exception of 0H1 and P03, however, these stands were
characterized by low slopes, northeastern aspects, and / or low plateau
topographic positions, ie. having topographic characteristics that also tend to
conserve moisture (Spurr and Barnes 1980). In fact, the correlation between
moisture and topography (negative with slope, positive with transformed
aspect) was strong across these stands, as was the negative correlation between
transformed aspect and light at the ground. It appears that the effect of
different canopies on light penetration is complicated by topographic
variation among stands, which can vary moisture regimes independent of
stand composition. This can be done directly by altering the physical
characteristics of the soil, and indirectly by altering the light regime
experienced by the soil. For example, the stands P08 and OHI not only had
more moderate slopes, but also more westerly aspects (a low value
transformed). These two stands also tended to have moderate light levels

and lower moisture values than the other hardwood stands. The differences

110

between these two stands and the others in this group may reflect the
moderating influence of topography upon light and moisture holding

capacity.

The relationship found between pH and mineralizable nitrogen
appears to be less direct. PH is often used as an indicator of soil miggbial
activity: low pH's tend to inhibit soil bacteria but not soil fungi (Swift et al.
1979). As both groups mineralize nitrogen, the mineralization process
appears to be less sensitive to pH than nitrification (Paul and Clark 1989). As
microbial mineralization of nitrogen is more likely to be affected by litter
quality (eg. C:N ratio, lignin content, phenolics), and poor litter quality is
often correlated with low soil pH, the relationship between mineralizable
nitrogen and pH may be an indirect measure of the effect of litter quality on
mineralization by microbes (Swift et al. 1979). If this is the case, it is the
strongest argument for an overstory species-specific effect on soil resources, as
litter quality is directly linked to species composition; conifers are considered
to have more recalcitrant litter than hardwoods (Swift et al. 1979; Nadelhoffer
et al. 1983).

An interesting phenomenon that should be noted here is that, when
samples were collected for N mineralization analysis in early July, few stands
possessed an 01 layer in their soil profiles. RP1, RP2, DGF, and RXW (which
was dominated by red pine) had distinct 01 layers < 2.5 cm in depth, but no
02 layer; SP2 had scattered debris from storm damage, but no distinct Ol layer.
The other stands varied from having pockets of litter accumulation to
virtually no litter present. N adelhoffer et a1. (1983) found the same situation
in 40 year old plantations on Alfisols in Wisconsin. They attributed the lack

111

of an 01 to earthworms fragmenting and incorporating the litter into mineral
soil by mid-July, and the lack of an 02 to fauna] mixing of the forest floor into
mineral soil directly. What this implies is that the mor soil typically
associated with coniferous forests has not yet developed in the conifer
plantations, and that this may be due to the presence of earthworms in these
former agricultural soils. The earthworms' apparent ability, in concert with
other soil fauna, to completely break down all but red pine and Douglas—fir
litter, suggests a more explicit mechanism for species-mediated effects on site
productivity through litter quality. In fact, N adelhoffer et al. (1983) go on to
suggest that red pine litter is of lower quality than either white pine litter or
combined white pine-red pine litter, thereby reducing net N mineralization

rates to the lowest found in their study.

From this discussion of relationships between resources and species-
specific effects on those resources, two general points can be made. First, the
strongest relationship which differentiates stands from one another appears
to be a contrast between light and soil resources, with both moisture and
nitrogen playing important roles. Although similar to Tilman's (1984, 1985,
1988) nitrogen-light resource gradient model, these data suggest a more
prominent role for soil moisture in these stands, and do in fact suggest
moisture as the driving variable. This makes sense biologically, as both
plants and the soil microorganisms that mineralize nitrogen depend upon
adequate soil moisture to survive and prosper. The role of species-specific
effects on the relationship between moisture and light is uncertain, as it
appears to be complicated by topography and other physical site and soil
characteristics not measured in this study.

112

The second point to be made comes as a result of the relationship
between pH and mineralizable nitrogen, and the stands SP2 and WP2, which
are exceptions to the general moisture-nitrogen relationship: SP2 has very
low soil moisture levels and moderate mineralizable nitrogen levels, while
WP2 has moderately high moisture levels and very low mineralizable
nitrogen. There appears to be an influence of other variables on nitrogen
availability, which act independently of soil moisture. It is likely that these
variables include soil temperature and litter quantity and quality, none of
which were measured in this study. Litter quality is indicated by the strong
relationship between mineralizable nitrogen and pH, and in WP2 where pH
was the lowest of the stands; soil temperature is implicated in SP2, where
light levels are very high, and in WP2, where light levels are very low; litter
quality may be implicated in SP2, where debris from ice storm damage is still
present. Other studies investigating plantation forests of similar age and
varying deciduous and coniferous compositions in the Midwest have also
found litter quality and quantity, and soil pH and temperature, to be
important variables in sorting stands along a site quality gradient
(Nadelhoffer et al. 1983; Artigas and Boerner 1989).

Species Distributions Among Plantations

Among the stands investigated, there did not appear to be any
distinguishable pattern of recruitment for any species in relation to stand
composition. However, differences among stands for total basal area of
saplings per hectare, and total number of seedlings per hectare, were quite
large. Of interest especially are the large basal areas associated with WP1 and
stands having a Scots pine component, and very small basal areas of saplings
but large numbers of seedlings under red pine dominated stands and DGF

113

(excluding the large aspen sapling). The resource data for the high basal area
stands suggest a relationship with mineralizable nitrogen, as this is the only
resource for which these four stands are not significantly different. In
addition, increased structural complexity in Scots pine stands may increase
bird dispersal of seeds (Smith 1975; Artigas and Boerner 1989), although the
mixed species stands, which tend also to be structurally diverse, show only a
slight trend towards higher densities for seedlings, but not saplings. In the
plantation study conducted by Artigas and Boerner (1989), they found higher
densities of seedlings and saplings under Virginia pine (Pinus virginiana), as
compared to white or red pine, which they did attribute to higher structural
complexity; Virginia pine is similar to Scots pine, as grown in the Northeast,
in having relatively short needles with two per fascicle, generally short
stature and scrubby form, and high susceptibility to ice, snow, and wind

damage to the crown.

There are two possible explanations for the differences in sapling and
seedling biomass in DGF and the red pine dominated stands. First, the low
sapling and high seedling values could indicate that site conditions have
improved enough to allow seedlings to germinate and survive.
Alternatively, conditions may still be harsh enough that most of these
seedlings will die before reaching the sapling stage, and that this type of
mortality has been ongoing. This latter hypothesis is suggested for DGF,
where seedlings appeared to be in their first or second year with no
indications of survival beyond this age (personal observation). In the red
pine stands, the presence of older seedlings was variable by plot, and tended to
occur where plots were topographically sheltered from moisture loss,

suggesting improving site conditions there.

114

Red maple and black cherry are the dominant members of the
understory community in almost all stands, natural and planted. However,
dominance of red maple is greatest as a sapling and declines as a seedling,
while black cherry exhibits the opposite trend. A reasonable explanation for
this appears to be an initial floristics model (sensu Egler 1954) whereby an
increase in mortality of black cherry seedlings, relative to red maple of the
same age, occurs because shade tolerance of black cherry tends to decline with
age; light levels at 0 and 2.5 meters (the seedling stratum) tend to fall below
5% in these stands, which can inhibit the growth of black cherry (Fowells
1965; Auclair and Cottam 1971). The difference between an average potential
dispersal distance for black cherry of 46 m, compared to 89 m for red maple,
may also contribute to the dominance of black cherry as a seedling.

In addition to overall dominance, red maple and black cherry appear to
follow no particular pattern in relation to resource levels, and do not appear
to be limited by seed dispersal. The dominance of these two species in the
understory is consistent with the literature for both hardwood invasion of
plantations, and successional dynamics in oak forests of the Northeast. In 36-
64 year-old plantations in Northwestern Pennsylvania, Grisez (1968) found
that black cherry seedlings and saplings occurred in 76% of their plots, and red
maple in 65% of plots. Artigas and Boerner (1989) found a predominance of
red maple saplings and seedlings across their pine plantations in South-
central Ohio. Lorimer (1984) found red maple saplings dominating the
sapling layer in permanent plots established on four upland oak sites in New
York and Massachusetts. Auclair and Cottam (1971) found black cherry

115

seedlings and saplings to average 50% and attain 100% dominance in oak

forests of Southern Wisconsin.

The autecologies of red maple and black cherry, relative to other
hardwoods, appear to ensure the success of these species in invading
plantation forests, given adequate dispersal distances and numbers of seed
sources. Both species have excellent colonizing abilities: red maple is wind-
dispersed while black cherry has plentiful bird dispersal (Fowells 1965; Smith
1975). Neither species needs much light for germination, and both respond
vigorously to release from shade, although black cherry has a more limited
window for this release response (Fowells 1965; Smith 1975; Lorimer 1984). In
addition, both species are flexible in their requirements for moisture,
although red maple has a wider range of conditions over which it will

successfully germinate (Fowells 1965).

In addition to red maple and black cherry, white ash and American elm
are also important members of the sapling community, and with the former
two species comprise the bulk of the sapling biomass. American elm drops
out of the group in the seedling stratum. Wind-dissemination of seeds of
these two species may also provide them with an advantage over other
species in these stands, as it does for red maple. American elm and white ash
show slightly increased dominances in stands having high moisture and
nitrogen availability, although their presence still ranges broadly across all
resource gradients. In addition, dispersal distances appear to be a very
important factor for success of American elm, as measured in this study, and
may also be for white ash, which has the most peculiar relationship to
dispersal distance of the species examined. The largest numbers and basal

116

area of white ash were found within 150 m of a seed source, but on a site
(EUL) with somewhat lower soil fertility. Many of the ash in this plantation
were spindly, and there was considerable mortality. It may be that there was
enough moisture available for establishment, but not enough to maintain
good growth and that this dominance is short-lived.

Secondary mesic site species, including slippery elm, tulip tree,
shagbark hickory, and sugar maple, showed distinct associations as saplings or
seedlings with the mesic, fertile, shady ends of the resource gradients. Three
of these species are wind-disseminated, but potential seed sources tended to be
few and scattered, localized, or great distances from plots. This suggests both
resource and dispersal limitation for these species. Basswood and red oak,
also considered mesic species, did not consistently associate with the fertile
portion of the stand ordination with resources, and both ranged somewhat
widely across resource levels. Dispersal for both species occurs primarily by
animals. Therefore it appears likely that red oak and basswood may be more
limited by the vagaries of animal behavior and microsite variation rather

than by general resource levels in these stands.

Secondary dry-mesic _to xeric site species, including white pine and
black oak, also demonstrated affinities for the appropriate dry, sunny, and
more or less fertile portions of the stand ordination. Black oak was only
prevalent in SPZ, where it was within an easy 72 m from the nearest potential
seed source. The one plot in SP2 with high available light conditions has
seen an explosion of black oak regeneration. What is unclear about this
phenomenon is whether the black oak seeds had already established and
germinated before the disturbance and were simply responding to the

117

increase in light, or if seedling germination and establishment occurred de
nova after light levels were increased. Determining the ages of the
reproduction would provide an answer to this question. Although black oak
is characterized as moderately tolerant, it has the lowest tolerance of shade of
the oaks in this area, and, as with many oaks, can respond quite vigorously to
disturbance. The addition to this situation of a southwest exposure for the
plot, and the relatively high frequency of good seed years as compared to
other oaks, appears to have given a boost to the successful establishment of
black oak on this particular site.

The case of white pine is also interesting because, although it was
heavily planted in the forest, and its seeds are wind-dispersed, it was only
prevalent in RXW, and only as a seedling. The moderately high light
conditions in this stand at ground level are a general requirement for
successful germination and establishment of white pine, although Fowells
(1965) states that dry mineral soil or thick pine litter do not provide favorable
seed beds for this species. This suggests that the plots in which white pine
was prevalent at this site may not have had as dense a pine litter layer as
other red pine stands in the area. White pine's absence from SP2 may be
explained either by competition or by a dry mineral soil seed bed.

Pignut hickory, although also considered a dry-mesic species, appeared
to show no correspondence to resource levels, and did not appear to be
dispersal limited. This hickory tended towards low frequency and constancy
among stands, although it was found in 6 of 15 stands and ranged widely over
the full range of resource levels available. Pignut hickory is also intermediate

in tolerance, and can exist on sites of varied fertility. It's range in site

118

tolerance and lack of exact requirements for light seem to suggest that success
of pignut hickory in these stands depends upon the behavior of the animal
vectors that disperse its seed, and the frequency of mast years.

Long-term Community Development

Speculating into the future concerning the development of the
hardwood understory of these stands, it appears that black cherry and red
maple may become the most important members of the overstory as the
plantations senesce. Both species can disseminate propagules over long
distances, and are common in fencerows, as members of the natural forest
community, and as old field "standards". Their lack of exacting site
requirements and their fast growth makes them superior colonizers, and
perhaps competitors, in these plantations. The continuation of natural
disturbance in the form of ice and wind storms is likely to help cherry
maintain its presence, as its requirement for light increases with age. These
speculations appear to be consistent with hypotheses presented by Lorimer
(1984) and Auclair and Cottam (1971). Lorimer (1984) has advanced a red
maple dominance hypothesis, suggesting that the invasion of red maple into
old-growth oak forests with sparse oak sprouts will continue and lead to a
new forest type in the Northeast dominated by red maple, although
uncertainties still exist about its lifespan. Auclair and Cottam (1971) suggest
that because black cherry and sugar maple tend to favor the mesic, fertile,
well-drained sites, black cherry may replace sugar maple in succeeding into
these sites in fragmented landscapes with few sugar maple seed sources; they
argue that higher degrees of fragmentation in the landscape tend to favor

colonization by pioneers.

119

These results are different than those obtained by Artigas and Boerner
(1989) who argue that in their forests, the sapling and seedling species
assemblages generally resemble those found in second growth xeric forests of
that region, and that if plantations are allowed to senesce, the advanced
hardwood regeneration would dominate and quickly blend into the
surrounding forest matrix. This present study suggests that the advanced
hardwood regeneration present in the understory is dominated by species
which are not common in the surrounding oak-hickory matrix, and that
initially these new stands may remain distinctly different from the typical
oak-hickory forest of this landscape. The rate at which these senescing
plantations will blend into the surrounding forested landscape, and the
degree to which this type of succession may or may not result in an
accelerated conversion of the natural oak-hickory forests to a different

hardwood ecosystem is unknown.

Most other species important in the natural oak-hickory communities
of the Kellogg Forest and KBS do not appear in dominant roles in the
understory. American elm does well in a few places, but its future is far from
secure due to Dutch elm disease. White ash is present in a number of stands,
but is dominant in only one and is senescing in that stand, either from
rigorous self-thinning or poor site conditions. White ash is not a long-lived
species as well, so its role in the new developing hardwood forest is not likely
to be one of importance. There also does not appear to be an imminent, or
even threatening, invasion of more mesic hardwoods into the Kellogg Forest
area. However, because sugar maple and beech are already established in the
forest as a small stand and a few individuals, respectively, these species may
become more important in the distant future.

120

Dominance, and possibly presence, of oaks and hickories in these
stands without some form of disturbance or human intervention (eg.
prescribed burning) is unlikely, except perhaps in SP2. These species tend to
be at a competitive disadvantage when compared to red maple and black
cherry; they are species with heavy seeds, sporadic mast years, often
unpredictable animal vectors, widespread predation of seeds and sprouts, and
slower growth. The fact that periodic fires no longer occur to eliminate
competition and stimulate oak sprouts has further endangered the survival
of the oak-hickory ecosystem as it presently exists at the Kellogg Forest and
KBS. However, the phenomenon occurring in SP2 does indicate that under
certain conditions, black oak has the capacity to establish dominance in the
understory of these plantations and successfully, at least in the short-term,

coexist with red maple and black cherry.

SUMMARY AND CONCLUSIONS

The general objective of this study was to characterize patterns of
variation in tree establishment and recruitment within plantation forests,
and to relate these patterns to gradients in light, nitrogen and moisture, and
to topographic variation, disturbance history, and distance to potential seed
sources. The first hypothesis tested suggested that resource levels varied
significantly across plantations and forests of different compositions, but
which occurred on similar soils. There does indeed appear to be substantial
and significant variation in resource availability among these stands, and
some of this appears to be attributable to species-specific effects of the
overstory brought about either by changing the light regime received in the
understory, or by litter quality and quantity effects. However, it was apparent
that the stands sampled were more physically heterogeneous, primarily in
topography, than first supposed. This heterogeneity manifested itself both as
interactions between topography and stand composition as they affected
resource levels, and effects of topography directly on moisture availability.

The second and third hypotheses deal with sapling and seedling species
distributions relative to stands and their resource levels. It was found that
red maple and black cherry are the predominant recruits in these plantation
and natural forests, and that neither species appeared to be limited by either
resource levels or dispersal distances. Nor were these species associated in

any way with a stand type. These species are aggressive colonizers, have

121

122

flexible resource tolerances, and have plentiful vectors for seed dispersal, the
sources for which are on average within 100 m of any given plot sampled.
Secondary sapling and seedling species appear to be limited by a combination
of resource availability and dispersal distance, although again there did not
appear to be any distinct association with stand type. Scots pine stands appear
to offer suitable habitat for the establishment of a number of different species,
which possibly is related to an increase in structural diversity in these stands
due to susceptibility to crown damage. Stands dominated by Douglas-fir or
red pine appear to offer the least hospitable environments for tree
establishment, and were also the only stands having a well-defined forest
floor layer.

In conclusion, while it does appear that planting different species will
have different effects upon the soil resources that tend to limit tree
establishment and growth, the types of conifers planted, per se, do not appear
to influence current successional trends in these forests. Effects of conifers
upon resource levels may only slow down the incursions of black cherry and
red maple into these stands, but are unlikely to prevent the ultimate success

of these two species.

As this is one of only two studies explicitly looking at successional
trends in plantation forests, the need for further research is quite clear. More
detailed soil sampling to characterize litter quality and quantity, populations
of soil microorganisms, soil temperature, nitrification rates, exchangeable
cations, soil texture, and small scale spatial heterogeneity in forest soils are
needed in order to test hypotheses concerning the mechanisms by which the
different plantation species surveyed affect soil resources. Tests for dispersal

123

limitations (seed traps and seed bank analysis) and herbivory limitations to
the success of various sapling and seedling tree species are also needed to
characterize the roles of these factors in successional development.
Competition experiments on sapling/ seedling species combinations would be
useful for predicting the future success of the sapling species found, and for
testing hypotheses concerning early development of these understories.
Research focusing on the effects of disturbance, and on various silvicultural
manipulations that could be performed to encourage the successful
establishment of oak species in these plantation understories, could also be
very important, especially in those areas where future forests dominated by
oaks are desired.

APPENDIX

APPENDIX

DIRECTIONS TO PLOTS IN THE 15 STANDS SURVBYED

m: Tulip tree (LIR)

W: Compartment 22C, east of Augusta Road, W. K. Kellogg Forest

2135521219115:

0 From center line of intersection of main woods road and forest trail, along
northern edge of Compartment 22C, proceed South 0° and 208.5 ft to
Plot 1.

0 From Plot 1, proceed South 26° West and 187 ft to Plot 2.

0 From Plot 2, proceed South 47° West and 140 ft to Plot 3.

m: Scots pine 2 (SP2)

W: Compartment 22A, east of Augusta Road, W. K. Kellogg Forest

W5:

0 From the northwest corner of a sign titled "Spruce Christmas Tree
Demonstration Area", in the northeast corner of the demonstration
area, along the southern side of main woods road in Compartment
22A, proceed North 39° East and 184 ft to Plot 3.

0 From Plot 3, proceed North 0° and 115 ft to Plot 2

0 From Plot 2, proceed North 90° East and 106.5 ft, then South 0° and 33 ft to
Plot 1.

124

125

SLANJQ: Oak-hickory 2 (OHZ)
LEATTQN: Compartment 228, east of Augusta Road, W. K. Kellogg Forest
IRE NS:

0 From center line of intersection of main woods road and forest trail, along
northern edge of Compartment 22C, proceed North 40° East and 137 ft
to Plot 1.

0 From Plot 1, proceed North 40° East and 200 ft, then North 29° East and 60 ft
to Plot 2.

0 From Plot 2, proceed North 90° West and 251 ft to Plot 3.

STAND: Douglas-fir (DGF)

LOCATTON: Compartment 22A, east of Augusta Road, W. K. Kellogg Forest

DIRECTIONS:

0 From intersection of main woods road and forest trail bisecting
Compartment 22A north to south, proceed North on forest trail to first
intersection with another trail bearing East. From center line of this
intersection, proceed South 9° East and 86 ft to Plot 1.

0 From Plot 1, proceed South 50° East and 63.5 ft to Plot 2.

0 From Plot 2, proceed South 31° East and 61 ft to Plot 3.

126

511.112: Oak-hickory 1 (0H1)

LQQAJJQN: Compartment 10, east of Augusta Road, W. K Kellogg Forest

W:

0 From southwest corner of sub-compartment 12 of Compartment 10, from a
stake painted red north of the trail that passes this corner, proceed
North 34° East and 154 ft to Plot 1.

0 From southeast corner of sub-compartment 15 of Compartment 10, proceed
N 51° West and 59.1 ft to Plot 2.

0 From the southeast corner post of the lookout building, located south of the
main woods road at the boundary between Compartments 9 and 10,
proceed North 41° East and 207 ft to Plot 3.

w: Red pine 2 (RP2)

LQQATIQN: Compartment 9, east of Augusta Road, W. K. Kellogg Forest

DIRE N :

0 From the southeast corner post of the lookout building, located south of the
main woods road at the boundary between Compartments 9 and 10,
proceed South 83° West and 104.3 ft to Plot 1.

0 From Plot 1, proceed South 56° West and 187 ft to Plot 2.

0 From Plot 2, proceed North 0° and 200 ft, then North 70° West and 34 ft to
Plot 3.

127

M: Red pine-White pine (RXW)

W: Compartment 7, east of Augusta Road, W. K. Kellogg Forest

W:

0 From the northwest corner post of Compartment 7-plot F5, proceed South
58° East and 49 ft to Plot 3.

0 From the northwest corner post of Compartment 7-plot D1, proceed South
22° EastandSOfttoPlotz.

0 From the northwest corner post of Compartment 7-plot B4, proceed South
52° East and 28.4 ft to Plot 1.

M: Scots pine-White pine (SXW)

LSEAT’IQN: Compartment 4A, east of Augusta Road, W. K Kellogg Forest

DIREQI IONS:

0 From the center line of main woods road at intersection at the northwest
corner of Compartment 7, proceed North 6° East and 200 ft along
northern extension of main woods road. Then continue North 4° East
and 123 ft along road. Then turn and proceed North 86° West and 138
ft to Plot 1.

0 From Plot 1, proceed North 42° West and 87.5 ft to Plot 3.

0 From Plot 1, proceed North 0° and 116 ft to Plot 2.

128

w: Red pine 1 (RP1)

LmATIQN: Compartment 8A, east of Augusta Road, W. K. Kellogg Forest

W:

0 From center line of main woods road at intersection with power line (poles)
on northern borders of Compartments 8A and 9, proceed on road
South 7° East and 200 ft, then South 4° West and 139 ft. Turn and
proceed North 85° West and 93 ft to Plot 2.

0 From Plot 2, proceed South 70° West and 179 ft to Plot 3.

0 From Plot 3, proceed South 70° West and 65 ft, then North 41° West and 131
ft to trail. Turn and proceed North 12° East and 157 ft to Plot 1.

film: European larch (EUL)

LQATIQN: Compartment 9, east of Augusta Road, W. K. Kellogg Forest

W:

0 From center line of main woods road and forest trail with oak leak emblem
and the number ”19", along the western border of Compartment 9,
proceed South 60° East and 98 ft to Plot 1.

0 From Plot 1, proceed North 0° and 180 ft to Plot 2.

0 From Plot 2, proceed North 75° West and 56 ft to Plot 3.

129

m: White pine-Red oak-Basswood (WOB)

LQXATION: Compartment 13C, east of Augusta Road, W. K. Kellogg Forest

W:

0 From the southern post of the Kellogg Forest sign at junction of entrance
road and main woods road, in the northwest corner of Compartment
13C, proceed South 22° East and 200 ft, then North 58° East and 38 ft to
Plot 1.

0 From Plot 1, proceed South 56° East and 155 ft to Plot 2.

0 From Plot 2, proceed South 64° West and 200 ft, then South 31° West and 24
ft to Plot 3.

m2: \Nhite pine 1 (WP 1)

LQQTIQN: Compartment 18, west of Augusta Road, W. K. Kellogg Forest

DIRE N :

0 At gate to entrance to western portion of forest, proceed along forest trail
that bears north parallel to Augusta Road (just inside the fenceline) to
the first forest trail on the left (bearing west). From center line of the
intersection of the two trails, proceed South 81° West and 96 ft to Plot 3.

0 From Plot 3, proceed North 2° East and 345 ft to Plot 2.

0 From Plot 2, proceed North 44° West and 248.5 ft to Plot 1.

130

SLLNQ: INhite pine 2 (WP2)

LQQATTQN: Compartment 20A, west of Augusta Road, W. K Kellogg Forest

DIRE N :

0 Proceed west along the forest trail bordering the southern edge of
Compartment 20A until it intersects a forest trail bearing north at the
southwest corner of this compartment (where C. 20A, C. 21, and C. 24I
meet). From a 7-inch Sassafras albidum at this corner of Compartment
20A, proceed North 25° East and 126 ft to Plot 1.

0 From Plot 1, proceed South 71° East and 98.5 ft to Plot 2.

0 From Plot 2, proceed North 71° East and 86 ft to Plot 3.

gm: Scots pine 1 (SP1)

LxATIQN: Compartment 21, west of Augusta Road, W. K. Kellogg Forest

was:

0 At the intersection of trails located at the northwest corner of Compartment
20A, proceed along the trail that bears due west, up the hill, until it
intersects a trail bearing north-south that divides Compartment 21
from 29. Go to the southwest corner of the stand occupying the
northeast quadrant of this intersection (in Compartment 21). Proceed
North 43° East and 63 ft to Plot 3.

0 From Plot 3, proceed North 10° East and 208 ft to Plot 1.

0 From Plot 3, proceed North 44° East and 170 ft to Plot 2.

131

M: Long Woods (0H3)

LOCATION: W. K Kellogg Biological Station

was:

0 Proceed through gate and east along road that borders the southern edge of
Cantlon Fields, until the road turns a corner to the south. At this
corner, to the south and west is a young stand of Iuglans nigra. From a
I. nigra having a circumference of 2.2 ft at the corner of this stand,
proceed North 90° East and 288 ft to Plot 1.

0 From Plot 1, proceed North 17° East and 87 ft, then North 0° and 400 ft to
Plot 2.

0 From Plot 2, proceed North 47° East and 50 ft, then North 56° East and 400 ft
to Plot 3.

COMPARTMENT MAP OF THE W. K. KELLOGG FOREST

W. K. KELLOGG FOREST

AUGUSTA . MICHIGAN

aura-area couuvv
cross 7" - fl! “I

     

LEGEND

- WW”? Ln,
. m "'° 7”? ”Y“, 0-- m.

m-=—=—

4/89

132

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