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THESIS
i

2 C ET

This is to certify that the

thesis entitled

Lakes, Wetlands, and Streams as Dynamic Drivers of Land
Use/Cover Pattern and Change: A Unique View
of Aquatic Ecosystems in the Landscape

presented by

Sarah E. Walsh

has been accepted towards fulfillment
of the requirements for

M.S. Fish. & Wildl.

degree in

 

 

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Major professor

Date May 8, 2000

 

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6/01 cJCIRC/DatoDuo.p65-p.15

LAKES, WETLANDS, AND STREAMS AS DYNAMIC DRIVERS OF LAND
USE/COVER PATTERN AND CHANGE: A UNIQUE VIEW OF AQUATIC
ECOSYSTEMS IN THE LANDSCAPE
By

Sarah E. Walsh

A THESIS
Submitted to
Michigan State University
In partial fulfillment of the requirements
For the degree of

MASTER OF SCIENCE

Department of Fisheries and Wildlife

2000

ABSTRACT

LAKES, WETLANDS, AND STREAMS AS DYNAMIC DRIVERS OF LAND
USE/COVER PATTERN AND CHANGE: A UNIQUE VIEW OF AQUATIC
ECOSYSTEMS IN THE LANDSCAPE
By

Sarah E. Walsh

Most research linking aquatic ecosystems to their surrounding environment has
focused on how terrestrial processes affect lakes, wetlands, and streams. However, it is
equally as important to examine how aquatic ecosystems alter terrestrial systems. I
examined spatial patterns of rural residential development and land use/cover around
lakes, nonforested depressional wetlands, and streams in the Huron River watershed in
southeast Michigan, USA. Specifically, I found that urban land use/cover occurs closer
to lakes than depressional wetlands or streams compared to the watershed. Agriculture
occurs proportionally less around lakes and streams, but more around depressional
wetlands than in the watershed. Additionally, forested land is found proportionally more
often around all three types of aquatic ecosystems than watershed average. These
patterns are not static and show changes between 1938 and 1992. This research has
revealed that a more complete understanding of how aquatic ecosystems drive patterns in
landscape patterns is important and could potentially be useful to incorporate into

predictive models of land use/cover change.

ACKNOWLEDGEMENTS

This work was supported by the Michigan State University Agricultural
Experiment Station, College of Social Science, and College of Agriculture and Natural
Resources. I would like to thank the members of the Huron River human/land use project
(Jack Liu, Angela Merti g, Chris Lepczyk, and Mike Mascarenhas) for all their support
and encouragement, Daniel Rutledge for all his hard work in developing the Huron River
watershed land use/cover database, and Kendra Cheruvelil, Chris Lepczyk, Stacy Nelson,
and Daniel Rutledge for reviewing earlier drafts. I would also like to thank my
committee: Mike Jones for all his help with the buffer analysis and ratio data and Steve
Hamilton for his idea of using wells as an indicator of residential development. I would
also like to especially thank my advisor Pat Soranno for her help and patience working
with me in developing this project, and for all the opportunities and guidance she has

given me over the past 3 years.

TABLE OF CONTENTS

LIST OF TABLES ............................................................................ v
LIST OF FIGURES ........................................................................... vi
CHAPTER 1

LAKES, WETLANDS, AND STREAMS AS DYNAMIC DRIVERS OF LAND
USE/COVER PATTERN AND CHANGE: A UNIQUE VIEW OF AQUATIC

ECOSYSTEMS IN THE LANDSCAPE .................................................. 1

Introduction ........................................................................... 1

Study Site Description ............................................................... 6

Methods ............................................................................... 8

Landscape and Aquatic Ecosystem Data ................................ 8

Data Analysis ................................................................ 1 1

Results ................................................................................. 15

Buffers ........................................................................ 15

Spatial Pattern ............................................................... 16

Riparian land use/cover changes .......................................... 18

Effects of lake and wetland area .......................................... 20

Indicators of human use ................................................... 21

Discussion ............................................................................ 21

Spatial Pattern ............................................................... 22

Riparian land use/cover changes .......................................... 25

Effects of lake and wetland area .......................................... 28

Indicators of human use ................................................... 30

Conclusions ........................................................................... 31
APPENDD( l

TABLES AND FIGURES ................................................................... 33

LITERATURE CITED ...................................................................... 61

iv

LIST OF TABLES

Table 1. Summary characteristics of aquatic ecosystems in the Huron River watershed.

Table 2. Summary of wetlands in the Huron River watershed classified into forested and

nonforested classes. The number of wetlands that were removed from the nonforested

wetland group to create the depressional wetland group are also described.

Table 3. Wetland area and number of wetlands classified to depressional and forested

wetland types. The percent change is reported for a timestep from the previous timestep.

Table 4. Difference in percent of watershed land use from percent of riparian land use.

LIST OF FIGURES
Figure 1. Map of 1992 land use/cover (D. Rutledge unpublished data) in the subset of the
Huron River watershed and its location relative to other Michigan watersheds. Images in

this figure are presented in color.

Figure 2. Location of lakes, depressional wetlands, and streams in the Huron River

watershed. Images in this figure are presented in color

Figure 3. Land use/cover percentages of the dominant land use/cover types in the entire

watershed for all five timesteps (a) and the rates of change in hectares per year of all six

land use/cover types between each timestep along with the total rate of change between

1938 and 1992 (b).

Figure 4. Location of wells and towns in the Huron River watershed.

Figure 5. Distribution of wells around lakes (a), depressional wetlands (b), and streams

(c) in a subset of the Huron River watershed. Note that lakes along the stream system

interrupt the stream channel network.

Figure 6. Example of rules used to create buffers around two lakes.

Figure 7. Example of the final buffer coverage around lakes in a subset of the watershed.

vi

Figure 8. Frequency distribution of lake (a) and depressional wetland (b) areas placed in

10 and 5 hectare bins, respectively.

Figure 9. Area of land included in each buffer around lakes (a), depressional wetlands

(b), and streams (c) and the cumulative percent area of all buffers to a given distance.

Figure 10. Weighted mean well density (wells/kmz) and 95% confidence intervals for
each buffer distance around lakes (a), depressional wetlands (b), and streams (c). Dashed

line is the average well density in the watershed after removing lake, wetland, stream,

and towns from the area of the watershed.

Figure 11. Weighted means and 95% confidence intervals of the percentage of urban
land use/cover in 1992 for each buffer distance around lakes (a), depressional wetlands

(b), and streams (c). Dashed line is the percentage of urban land use/cover in the entire

watershed.

Figure 12. Weighted means and 95% confidence intervals of the percentage of

agricultural land use/cover in 1992 for each buffer distance around lakes (a), depressional

Wetlands (b), and streams (c). Dashed line is the percentage of agricultural land use/cover

in the entire watershed.

vii

Figure 13. Weighted means and 95% confidence intervals of the percentage of forest
land use/cover in 1992 for each buffer distance around lakes (a), depressional wetlands
(b), and streams (c). Dashed line is the percentage of forest land use/cover in the entire

watershed.

Figure 14. Weighted means and 95% confidence intervals of the percentage of urban
land use/cover in 1938 (grey bars) and 1992 (black bars) for each buffer distance around
lakes (a), depressional wetlands (b), and streams (c). Dashed lines are the percentages of

urban land use/cover in the entire watershed in 1938 and 1992.

Figure 15. Weighted means and 95% confidence intervals of the percentage of
agricultural land use/cover in 1938 (grey bars) and 1992 (black bars) for each buffer
distance around lakes (a), depressional wetlands (b), and streams (c). Dashed lines are the

percentages of agricultural land use/cover in the entire watershed in 1938 and 1992.

Figure 16. Weighted means and 95% confidence intervals of the percentage of forest
land use/cover in 1938 (grey bars) and 1992 (black bars) for each buffer distance around
lakes (a), depressional wetlands (b), and streams (c). Dashed lines are the percentages of

forest land use/cover in the entire watershed in 1938 and 1992.

Figure 17. Weighted mean percentage of urban (a), agricultural (b), and forest (c) land

use/cover in the 100 meter buffer around lakes, depressional wetlands, and streams for

each timestep. 95% confidence intervals are presented with the means, but are not visible

viii

because they are smaller than the data points. Note that forest (c) has a different scale on

the y-axis.

Figure 18. Box plots of well density in the 100 meter buffer around lakes (a) and

depressional wetlands (b) grouped into 10 and 5 hectare bins, respectively.

Figure 19. Box plots of percentage of urban, agriculture, and forest land use/cover in the
100 meter buffer around lakes (a) and depressional wetlands (b) grouped into 10 and 5

hectare bins, respectively.

Figure 20. Percentage of urban land use/cover in the 100 meter buffer around each lake

in 1992 as compared to 1938.

Figure 21. Lakes are shaded to represent the percentage of urban land use/cover in the
100 meter buffer around each lake in 1938 (a) and 1992 (b) in a subset of the watershed.

Images in this figure are presented in color.

Figure 22. Percentage of urban land use/cover in the 100 meter buffer around each lake
(a), depressional wetland (b), and stream (c) in 1992 compared to the well density
(wells/kmz) in the 100 m buffer around each lake. The R2 and p—value reported for

streams were calculated after removing one outlier.

Lakes, wetlands, and streams as dynamic drivers of land use/cover spatial pattern
and change: a unique view of aquatic ecosystems in the landscape

Introduction

Aquatic ecosystems are strongly linked to the surrounding landscape and cannot
be studied in a vacuum set apart from their environmental setting (Hynes 1975; Karr and
Schlosser 1978; Malanson 1993; Allan and Johnson 1997). Over the past several
decades, scientists from many different disciplines have increasingly studied how human
modification of the landscape affects aquatic ecosystems. For streams, land use/cover
has been correlated to many chemical (Osborne and Wiley 1988; Johnson et al. 1997,
Herlihy 1998), physical (Kuhnle et al. 1996), and biological (Steedman 1988, Schlosser
1995) factors. In lakes, land use/cover has been shown to cause physical (Christensen
1996; France 1997), chemical and nutrient (Eilers et al. 1989; Field et al. 1996; Siver
1996), and possibly biological (Stemberger and Lazorchek 1994; Allen et al. 1999)
changes. The little research that has been done on wetlands has mainly examined effects
of land use/cover on biological features of wetlands (Mensing 1998; Euliss 1999;
Anderson and Vondracek 1999). However, despite these examples, the major focus of
research on land-water interactions has been on how land use/cover affects streams and
far fewer studies have been conducted on wetlands or lakes with the exception of those
studies focusing on nutrient loading in lakes (Dillon and Kirchner 1975).

In addition, few studies have examined a specific function or process in lakes,
wetlands, and streams together (Gorham 1996). Although some studies have linked two
systems, for example when examining the effects of wetlands on water quality in lakes

(Detenbeck et al. 1993) or streams (Johnston et al. 1990; Weller et al. 1996), rarely have

all three been examined. Examining how land use/cover affects multiple aquatic systems
together might greatly improve our understanding of the complex interaction between
terrestrial and aquatic ecosystems.

To fully understand the interactions between aquatic and terrestrial ecosystems,
aquatic ecosystems must also be seen as more than receptors of human modification of
the landscape, but also as potential drivers of these modifications. The distribution and
location of aquatic ecosystems may actually influence how humans use the land. For
example, forested riparian buffers are often left around streams to filter upland sediment
and nutrients before they reach streams (Peterjohn and Correll 1984; Osborne and
Kovacic 1993). Because human use of the landscape has been shown to be so important
to aquatic ecosystems it is important to examine how aquatic ecosystems might in turn
affect human use of the land.

Researchers have examined the pattern of rural residential development and land
use/cover change for some time (Burgess 1967, Hart 1976), but they have generally come
from disciplines such as geography, rural sociology, and urban and regional planning.
Only recently have ecologists begun to include human modifications in research on
ecological systems at larger scales (Vitousek 1994; Dale et al. 1998). From an ecological
point of view, there is still more to learn about land use/cover pattern and change. In
particular, we have gained many new insights from studies that describe land use/cover
pattern and change at specific places around the country (Simpson et al. 1994;
Silbemagel et al. 1997). These studies have revealed some broad generalizations about
land use/cover change (Medley et al. 1995; Bradshaw and Muller 1998). For example,

the conversion of agricultural land to other land use/cover types (i.e. converted to

residential uses or left to return to forest land cover) has been seen as a problem for
decades in the US. (Furuseth 1982). The loss of American farms is a very complex
phenomenon that we do not yet completely understand (Galston and Baehler 1995).
Another general pattern in land use/cover change is increased urbanization, which can be
found throughout the country (Befort et al. 1998).

Human utilization of the land does not occur randomly across the landscape.
There are social, economic, political, and physical drivers of land use/cover change that
range from the reigning political party to local landscape features (Cronon 1983). For
example, land cover change has been found to depend on the land ownership in the
southern Appalachian highlands and the Olympic peninsula (Turner et al 1996).
Similarly, natural features on the landscape have the potential to affect land use/cover
change (Pan et al. 1999) or rural population growth (McGranahan 1999). Pan et al.
(1999) found that the physical landscape in Quebec, Canada constrained land use changes
which were triggered by socioeconomic forces. Other studies have found a weaker
relationship between landscape attributes and land use change (Iverson 1988; LaGro
1998). This relationship may be weaker in some areas due to specific conditions in the
region. For example, Iverson (1988) found that in southern Illinois most soils are suitable
for crop production so changes in agriculture were unrelated to physical conditions of the
landscape. LaGro (1998) found little relationship between development and physical
landscape attributes because improved technology in private on-site sewage systems
allowed their placement in areas that used to be constrained by slope, soil permeability,

depth to bedrock, or depth to water. The results of all of these studies suggest that

including natural features may be important variables to consider when trying to predict
how land use/cover is going to change in a region.

Several models have been developed to predict future land use/cover in various
areas of the country (Pijanowski et al. 1995, Turner 1996) and have included predictor
variables such as distance to employment, land use regulations, elevation, and age of
farmer. The extent to which natural features are included in the models varies, but very
few studies have explicitly included aquatic ecosystems. Lakes, wetlands, and streams are
sometimes mentioned (for example the Great Lakes shoreline or stream riparian buffers
in Pijanowski et al. (1995)), but rarely included as key parameters in land use/cover
change models, suggesting that they do not play important roles in land use/cover pattern
and change. However, other studies that found correlations between landscape features
and development show this assumption may not be valid (Orr 1997; McGranahan 1999;
Pan et al. 1999).

Aquatic ecosystems may not have been included in many models simulating
future land use/cover scenarios because we do not know the role that lakes, wetlands, and
streams play in influencing land use/cover in the immediate region surrounding these
important ecosystems. Nonetheless, we do know that lakes attract people for their
aesthetic and recreational values (Orr 1997). In some regions, especially in the Upper
Great Lakes region, this relationship is due to retirement communities or second home
growth (Hunt et al. in press; Green et al. 1996). Streams have been included as a variable
in some land use/cover change models by leaving a buffer around streams where
development is not allowed to occur (Pijanowski et al. 1995). This conservation of

stream riparian zones is opposite that of lakes (where people tend to build in riparian

zones rather than preserve them) and is supported in some literature on perceptions and
urban growth in river corridors. For example, Ryan (1998) and Bollens (1990) state that
it is important to maintain natural corridors around streams. Bollens (1990) examined the
effect of floodplain management programs on the development of river floodplains and
Ryan ( 1998) examined preferences and attitudes of rural residents toward riparian
landscapes. In both studies, the goal was to maintain natural vegetation near rivers. This
conservation attitude appears to not have not been transferred to lakes or wetlands.

Given the importance of aquatic ecosystems, coupled with our lack of knowledge
of how they drive human modification of the landscape, a basic question that needs to be
addressed is whether the presence of aquatic ecosystems on the landscape predictably
alters land use/cover in surrounding land. The specific questions I address are:

1) Do aquatic ecosystems correlate to spatial patterns of rural residential

development and land use/cover?

2) How has both the total amount and spatial pattern of riparian land use/cover

changed through time?

3) Does lake or wetland area affect riparian land use/cover?

4) How do different indicators of human use/development compare (i.e. land

use/cover and well density)?

I answer the above questions by analyzing spatial patterns in rural residential
development and land use/cover around lakes, depressional wetlands, and streams using a
conceptually simple buffer analysis. I conducted this research in the Huron River
watershed in southeastern Michigan using data from five time steps between 1938-1992.

I examined whether the location of aquatic ecosystems are correlated to spatial patterns

on the landscape by using land use/cover and well density as indicators of human
modification of the landscape. To assess spatial pattern, I compared well density and
land use/cover percent in several buffers around aquatic ecosystems to the average
watershed well density and land use/cover percentage. The location of drinking water
wells were chosen as an indicator of rural residential development in that they represent a
single household. Although I am not aware of any other research that has used wells as
an indicator of development, septic tanks have been effectively used in a similar fashion
(LaGro 1998) and wells are likely to be highly correlated to septic tanks. I hypothesized
that the location of aquatic ecosystems would influence the spatial patterns of how

humans use the land in the Huron River watershed.

Study site description

The Huron River watershed drains 2300 km2 in southeast Michigan (Figure 1).
The river and its tributaries flow approximately 800 km into the northwest comer of Lake
Erie, carrying a mean annual discharge of approximately 90 m3/s. The surface
topography of the watershed is characteristic of a glaciated landscape. The northern
region makes up the majority of the watershed area and contains a dendritic pattern of
tributaries, lakes connected by the rivers, and extensive wetland areas (Figure 2).
Geologically, the watershed is largely comprised of glacial moraines, till plains, and
outwash deposits (Hay-Chmielewski et al. 1995). Both outwash and moraine geologies
contain sand and gravel deposits that are conducive to groundwater — surface water
exchanges, however, the till plains consist of sorted fine sediments that are more

conducive to surface runoff (Hay-Chmielewski et al. 1995).

European human settlement began in the 1700’s and by the 1800’s agriculture
was the dominant land use in the watershed (Hay-Chmeilewski et al. 1995). Since then
however, extensive land conversion within the watershed has produced a mixture of
urban, agricultural, and natural land use/covers today (Figure 1). Urban growth and
development extending from the Detroit metropolitan area (southeast of the Huron
watershed) and Ann Arbor (in the southeast portion of the watershed) drive much of the
land conversion in the watershed. The watershed used in all of my analyses in Figure 1 is
a subset of the entire watershed (see below for details). The large urban center in the
southern comer of the watershed is the city of Ann Arbor, around which occurs extensive
agricultural development. By 1992, approximately 25% of the watershed was classified
as urban land use/cover, 28% as agricultural land use/cover and 18% as forested land
(Figure 1; data sources given in methods). These land use/cover percentages within the
watershed subset have not been constant throughout time however (Figure 3a). Over the
last 55 years, there have been marked decreases in agriculture and increases in urban land
use/cover, but little change in the area covered by forests (Figure 3a). The average
annual rates of change in ha/year of all six land use/cover types between each timestep
for this watershed subset are shown in Figure 3b. Although the wetland loss occurred
through all 5 timesteps in the Huron River watershed, the rate of change is much lower in
recent timesteps than it was between early timesteps (Figure 3b). This result is to be
expected given legislation that has been passed to prevent wetland loss (Zedler et al.
1998). The majority of wetland loss in Michigan occurred before 1930 and was the result

of installing drains to create agricultural fields (Fretwell et al. 1996).

Methods
Landscape and aquatic ecosystem data

All data were compiled in a geographic information system (GIS) database. The
landscape and aquatic ecosystem data were obtained from the Michigan Resource
Information Service (MIRIS). These data included coverages of land use/cover, county
boundaries, watershed boundaries, waterways, and water well locations. The land
use/cover data is classified in a hierarchical 5-step scheme using the Anderson
Classification scheme (Anderson et al. 1976). The most general level of classification
used in this study includes the following land use/cover types: urban, agricultural,
nonforested vegetation (i.e. scrubs and shrubs), forest, water, and wetlands. Land
use/cover data for the watershed are based on a 1985 digital base map (note that the rest
of the state of Michigan in the MIRIS database are based on 1978 data). Historical land
use/cover coverages were created from aerial photographs taken in three timesteps
previous to 1985. The aerial photographs were taken for the following years for each
timestep: Step 1 (1937, 1940), Step 2 (1955, 1957), Step 3 (1969, 1970, 1972, 1973), and
Step 4 (1985). I will refer to each timestep by the average year of the aerial photos
(1938, 1956, 1971, 1985, and 1992). The digital 1938, 1956, and 1971 land use/cover
coverages were created chronologically going back through time beginning with the 1971
layer. The 1971 layer was created by overlaying the 1985 land use/cover data layer on
the 1971 photographs and editing the land use/cover data layer to match the photos (D.
Rutledge, unpublished data). The same methods were used to create the 1938 and 1956

land use/cover layers overlaying the preceding data layer on the photos for each timestep.

The 1992 land use/cover coverage was obtained from the Huron River Watershed
Council, which was created from classification of color aerial photographs in addition to
ground truthing. All coverages were edited to obtain maximum accuracy and continuity
between the five timesteps (D. Rutledge, unpublished data). The minimum resolution of
the original MIRIS land use/cover data is approximately 1 hectare. For the purpose of this
research, I reduced the watershed’s extent (Figure l). I excluded areas where there was
not enough information on wells, where there was a low number of wells, or a known
public water supply in an area not within town boundaries (as determined from public
water supply maps and personal communication with township public works
departments).

The drinking well coverage contains the location of each well indicated by a point
(Figure 4). The original drinking well data were compiled from the Water Well and
Pump Records of the Michigan Department of Public Health. Because wells were chosen
as an indicator of rural residential development, any wells located within the boundary of
towns were excluded from analyses. The rationale for this decision is that if public
drinking water supply became available to a town after private wells had been drilled,
they would have remained in the dataset, but would be no longer in use. Only 200 out of
over 17,000 wells were located in towns and subsequently removed from the analysis.
The town coverage was obtained by selecting the delineated towns from the county
coverage (as shown by the dark polygons in Figure 4). Figure 5 shows the distribution of
wells around lakes, nonforested wetlands, and streams for a Subset of the watershed.

Creating the GIS coverages of the aquatic ecd'systems involved several additional

steps of data manipulation. All of the aquatic coverages came from the 1992 land

use/cover coverage and were assumed not to change through time. In building a lake
coverage, any body of water coded as a lake and greater than 1 ha was included in the
lake coverage because 1 ha is the minimum resolution of the data of the original MIRIS
database. The final lake coverage contained 453 lakes (Table 1).

The wetland coverage created for all spatial analysis includes a subset of the total
number of polygons classified as wetlands in the 1992 land use/cover coverage. In the
wetland coverage I only included wetlands classified as nonforested wetlands because
they are more likely to have standing water. Nonforested wetlands made up 75% of the
total wetlands in the watershed (Table 2). Similar to lakes, all nonforested wetlands
under 1 ha in area were not included in the wetland coverage. In addition, I removed
those nonforested wetlands that were directly contiguous to lakes and streams (riparian
wetlands), which ended up being 29% of the nonforested wetlands. Thus, I restricted my
analysis to those nonforested depressional wetlands that would not be confounded by the
presence of a lake or stream immediately adjacent to that nonforested wetland. The same
was not done for lakes and streams because approximately 40% of lakes and 60% of
streams had wetlands adjacent to them. Reducing the number of lakes and streams by
that much would have lowered the sample size too much. Because keeping the lakes and
streams with adjacent wetlands in the final coverages confounds the interpretation, my
analysis is likely to be conservative. The final depressional wetland coverage contained
1296 waterbodies (Table 1).

The 1985 MIRIS land use/cover coverage served as the starting point for the
creation of the stream coverage rather than the 1992 coverage. The land use/cover

coverage was edited using an additional stream layer from MIRIS and aerial photographs

10

from the first three timesteps to include small order streams (down to approximately 3rd
order (Strahler 1964)) than were available in the original coverage. Very short stream
segments that were not ultimately connected to the tributaries or the mainstem of the river
were deleted from the stream coverage, but not the land use/cover coverage. 1 divided
the stream coverage into 110 segments following an approximate stream order
classification (Table 1).

These three aquatic ecosystem coverages were used for analyses in all timesteps.
Thus, I assumed that there were no changes in the location and the spatial pattern of
aquatic ecosystems across the 55 years. There were only minor changes in the number,
size, and distribution of lakes and streams relative to overall land use/cover (Figure 3b).
Overall, the total area of depressional wetlands decreased by 32% from 1938 to 1992. For
the depressional wetlands, it is important to note that only the depressional wetlands
remaining in 1992 were included in the spatial pattern analyses. I examined how
depressional wetlands correlated to land use/cover change around them, but the total
extent of all wetlands in the land use/cover coverage also changed due to the conversion
or creation of new wetlands through time (Table 3). For all three aquatic ecosystems it
was important to use a consistent set of waterbodies throughout the analysis that were
present in all timesteps.
Data analysis

Creating Buffers: For all analyses, 1 created 20 concentric 100 meter buffers
around the separate coverages of lakes, depressional wetlands, and streams. Using
ArcView the following operations were performed to make three coverages that each

contained twenty 100 m buffers around each aquatic ecosystem type. First, for the lake

coverage a 100 m buffer was created around each lake (Figure 6). If lakes were closer
than 200 m to each other, the overlapping area of the two buffers was randomly assigned
to one of the two lakes. This step was necessary as there was no analytical way to split
the overlapping buffer area in two. By assigning the overlapping area randomly, there
should have been no systematic bias introduced into the analysis, only extra variation, or
noise. After the 100 m buffers were created, the 200 m buffers were added as a 100 m
wide buffer beginning at the end of the first 100 m buffer. As with the 100 m buffer, if
the 200 m buffer intersected another 200 m buffer, then the same rules were applied as
for the 100 m buffer. The 200 m buffer of one lake was not allowed to overlap a 100m
buffer around another lake. Thus, buffers with the shortest distance from a lake were
always given preference over buffers further away. This buffer creation continued until
20 buffers were made around each lake (Figure 7). Lake identification numbers were
assigned to each buffer so that buffers could be connected with lake attribute information
(i.e. surface area). The final data file contained buffers, buffer areas and the lake that
they were assigned to. These steps were repeated for streams and wetlands, resulting in
three separate coverages used to describe the spatial pattern of rural residential
development and land use/cover patterns around lakes, depressional wetlands, and
streams. Because of the complexity of the spatial patterning of lakes, wetlands, and
streams, it was not possible in this study to examine the possible correlations among all
ecosystems types and land use/cover pattern combined.

Spatial pattern: I examined the spatial pattern of rural residential development
and land use/cover by analyzing both the well density (as an indicator of rural residential

development) and 1992 land use/cover data (urban, agriculture, and forest) in buffers

12

around lakes, depressional wetlands, and streams. Urban land use/cover is a composite of
many types of development, but is dominated by residential use (70%) in the Huron
River watershed. I calculated the weighted mean well density and land use/cover
percentages for each buffer and compared it to the average watershed value. I weighted
each observation (buffer polygon) by buffer area because there was a wide range of
buffer areas. Using 95% confidence intervals (based on an estimate of variance for ratio
data (Cochran 1953; Lockwood et al. 1999)), I determined if there was a significant
difference between each buffer mean and the overall watershed average value by
determining whether the watershed value was found outside the 95% confidence interval.
If, for example, the percentage of urban land use/cover was significantly higher in a
buffer near lakes compared to the watershed average, I concluded that lakes M
human development. If, on the other hand, the percentage of urban land use/cover was
significantly lower than the watershed average, I concluded that lakes r_epgl human
development. These words (attract and repel) do not necessarily claim a causal
relationship, but only a positive or negative correlation between the location of aquatic
ecosystems and rural residential development or land use/cover. For the well analysis I
used all twenty concentric 100 meter buffers, and for the land use/cover analysis I used a
subset of ten of the buffer distances (100-400, 700, 1000, 1100, 1500, 1800, 1900).
Riparian land use/cover changes: To examine if the spatial patterns in land
use/cover changed through time I also analyzed urban, agricultural, and forested land
use/cover for 1938 in the same subset of buffers around lakes, depressional wetlands, and
streams as the 1992 analysis. In addition, I examined the changes in patterns of the

riparian zone in more detail because I expected this area to show the greatest difference

from the overall watershed. To address how riparian land use/cover spatial pattern
changed through time, I analyzed land use/cover percentage for three land use/cover
types (urban, agriculture, and forest) in the 100 m buffer around lakes, depressional
wetlands, and steams for the five timesteps (1938, 1956, 1971, 1985, 1992). I define
riparian as the first 100 meters away from a water body. Although this definition is not
hydrologically accurate because it is not based on hydrology or topography, it was
selected because of the limitations of data resolution, to ensure that at least one entire
property width was included in the riparian buffer, and because many previous studies
define it as such. The spatial pattern in riparian land use/cover was analyzed through
time for lakes, depressional wetlands, and streams by comparing weighted means to the
estimate of watershed land use/cover percentage as described above.

Effects of lake and wetland area: To test for the effects of lake and wetland area
on the spatial patterns of well density and land use/cover percentage, I created groups
(bins) of lakes and wetlands based on area, using of 10 and 5 ha intervals, respectively
(Figure 8). I performed regression analyses on the binned data to examine whether there
was a significant relationship between area and either well density or land use/cover
percentage. For these analyses, I did not weight the data by buffer area because it was
necessary to treat the lakes as individual sample points of a population (each with their
own area), therefore I used traditional statistical methods in my regression analysis
instead of using the estimate of variance for ratio data. The regressions were done on the
full group of data, not the mean value for each buffer distance because of the large
amount of variance in well density and land use/cover percentage. These data do not

have a normal distribution partly due to the large number of zeros (for both land

14

use/cover percentage and well density). To improve the normality of the data, I
performed power and log transformations on the well density and lake or wetland areas,
and I transformed the land use/cover percentages with an arcsine transformation
(Wilkinson 1996).

Indicators of human use: I used the riparian well density and percentage of
riparian urban land use/cover for each lake, depressional wetland, and stream to compare
the similarity of two different indicators of human use and residential development. I
plotted the riparian well density for each waterbody against the percentage of riparian
urban land use/cover and calculated the significance of the regression and correlation
coefficients. This analysis was performed independently for lakes, depressional

wetlands, and streams.

Results
Buffers

Creating 20 concentric 100 meter buffers around separate coverages of lakes,
depressional wetlands, or streams results in three buffer coverages. The area that each
buffer distance represents varies with distance from the water body and aquatic
ecosystem type (Figure 9). The total buffer area for each distance increases further away
from lakes and wetlands for the first three to five 100 m buffers (as would be expected
from basic geometric properties of the area of circles). However, after the first 3-5
buffers, the area of each buffer decreases as you move away from the lakes or wetlands.
This spatial pattern occurs because the buffers begin to overlap other buffers that are

closer to another lake or are at the edge of the watershed. Unlike lakes and wetlands,

streams do not show an initial increase in buffer area because they are more linear in
shape and thus do not share the same geometric properties. Stream buffers show a steady
decrease in area as they increase in distance from the stream and overlap buffers that are
closer to another stream or reach the edge of the watershed. Because the analyses are
corrected for areal expect these buffer area patterns will not influence the following
results. The twenty 100 m buffers around each aquatic ecosystem type cover
approximately 80% of the total watershed for lakes, 90% for depressional wetlands, and
75% for streams (Figure 9). I analyzed the proportion of urban, agriculture, and forest
land use/cover in these buffers and found that these three land use/cover types make up
between 60 and 80% of the total area for each buffer distance around all systems.
Although they were not analyzed, the other land use/cover types do not change much
through time in the watershed (Figure 3b) and should not have much of an influence on
other land use spatial patterns observed in this study.
Spatial pattern

It appears that aquatic ecosystems are strongly correlated to spatial patterns in
rural residential development and urban, agricultural, and forested land use/cover (Figure
10-13). The confidence intervals presented in these figures are very small because of the
high number of individual waterbodies in each group. In general, the first two to four
100 m buffers around lakes, depressional wetlands, and streams are most dramatically
influenced by the presence of the aquatic ecosystem. The buffers farther away from the
lake, depressional wetland, or stream often show significant differences from overall
watershed well density or land use/cover (dotted line). Additionally, buffers further away

from waterbodies typically show the opposite relationship to the watershed average as

16

buffers close to the system, possibly because if the well density is higher than average
near lakes it has to be lower than the watershed average somewhere else.

Well density in the first 2-3 buffers around lakes, depressional wetlands, and
streams, and therefore rural residential development, differs from the overall watershed
well density (Figure 10). Lakes show the greatest difference from the overall watershed
well density in the first 100m buffer where the density of wells is 2.5 times greater than
the watershed as a whole (Figure 10a). Although lakes appear to attract rural residential
development, depressional wetlands do the opposite and repel development (Figure 10b).
Streams attract rural residential development beyond the first 100 meter buffer (Figure
10c). The first 100 meters adjacent to streams and the first 300 meters around wetlands
have less development than the watershed as a whole and show similar degrees of
development repulsion in the first 100 meters.

Land use/cover percentages show attraction and repulsion (i.e. positive and
negative correlations) from aquatic ecosystems similar to spatial patterns of wells. Urban
land use/cover shows trends almost identical to rural residential development trends,
which I expected since they measure similar human modifications. Urban land use/cover
is attracted to lakes and repelled from depressional wetlands and streams in the first few
100 m buffers (Figure 11). Lakes and streams strongly repel agricultural land use/cover,
whereas wetlands attract it (Figure 12). All aquatic ecosystems have higher percentages
of forest near them compared to the rest of the watershed (Figure 13). Streams only have
an increase in forest in the first 100 meters, whereas lakes and depressional wetlands
have higher percentage of forest in the first four to five 100 m buffers. Lakes also show a

smaller attraction of forest compared to wetlands and streams, especially in the first

17

buffer. Overall, lakes, depressional wetlands, and streams do alter the spatial pattern of
development and land use/cover on the landscape.
Riparian land use/cover changes

This study shows that there have been some changes in the spatial patterns of
rural residential development and land use/cover over 55 years. By comparing the most
recent to the oldest coverage, I found the magnitude of the difference between riparian
and watershed urban land use/cover percentage was more extreme for all systems in 1992
than it was in 1938 (Figure 14). The spatial pattern of agriculture around lakes does not
change much with time, streams show a little less repulsion, and depressional wetlands
show attraction more distinctly in 1992 than in 1938 (Figure 15). Forested land use/cover
shows different changes in spatial pattern depending on the aquatic ecosystem. In 1992,
there is slightly more forest in the watershed, but the amount of forest in the 100 in buffer
around lakes decreased from 1938 to 1992 (Figure 16a). The other lake buffers increase
in forest at a rate similar to the increase in forest in the watershed as a whole.
Depressional wetlands show an overall increase in the magnitude of the difference
between forest in the proximate buffers and entire watershed (Figure 16b). Stream
buffers show little change in the spatial pattern of forested land use/cover over time,
except an overall increase in percent forest in all buffers (Figure 16c).

Because riparian areas showed the most change, I examined the first 100 m buffer
in greater detail. Spatial patterns in lake, depressional wetland, and stream riparian land
use/cover percentages in the Huron River watershed have changed over the five timesteps
between 1938-1992. In general, the percentage of urban in the riparian buffer increased

in all timesteps for all systems (Figure 17a) and the percentage of agriculture decreased

18

(Figure 17b). Forest land use/cover in the riparian buffer showed less absolute change
(Figure 17c). Because the confidence intervals are actually smaller than the data point in
almost all cases, almost all of the observed changes are significant.

Riparian urban land use/cover around lakes changed from under 7% to over 35%
over the 55 years, with the highest rate of increase between 1956 and 1971 (1265 ha/year)
(Figure 17a). The percentage of urban land use/cover around streams is much smaller
than around lakes and slightly less than is in the watershed for every timestep (except
1956 when there was a slightly higher amount of urban around streams than there was in
the watershed) (Figure 17a and Table 4). Although depressional wetlands repel urban
land use/cover even more than streams do, the difference between watershed and wetland
riparian land use/cover percentages has been decreasing over the 55 year period (Figure
17a and Table 4). As was the case at the watershed scale, the urban land use/cover
category is mainly comprised of residential uses in the areas riparian to lakes,
depressional wetlands, and streams (64-76%). Other types of urban uses that were
common (IO-15%) around the waterbodies were extractive, industrial, and
openland/outdoor recreation urban land use/cover classes.

Agricultural land use/cover has been decreasing around lakes, depressional
wetlands, and streams and at the watershed scale across the study period. In 1938, the
percentage of riparian area around lakes that was agricultural land use/cover was very
similar to the percentage around streams (Figures 17b). Through time, the amount of
riparian agriculture around streams decreased at a rate very similar to the watershed’s
decrease, but lakes lost much more agricultural land from their riparian zones.

Depressional wetlands had slightly more agriculture in their riparian zones than found at

the watershed scale and the difference increased over the five timesteps (Figure 17b and
Table 4).

Overall, forested land use/cover increased in the watershed from 1938 to 1992,
with the peak of the increase between 1938 and 1971 (Figure 17c). Since 1971, forest
area has been decreasing in the watershed. Riparian forest shows similar trends of
peaking in the middle of the five time periods and then showing some decreases more
recently (Figure 17c). During the first time period, lakes had more riparian forest than
streams or wetlands (which were all higher than the percentage in the watershed), but by
1971 lakes had the least amount of riparian forest of the three systems. Wetlands started
out with the least amount of forest around them and in 1992 had the highest percentage.
In the last three timesteps, lakes show a faster rate of forest loss than the watershed.
Riparian forests around streams have mirrored the changes in forest at the watershed
scale very closely and the magnitude of the difference between watershed and riparian
has changed very little over time (Table 4).

Eflects of lake and wetland area

Lake area (in 10 ha bins) had a very small, but significant and positive
relationship with riparian well density (Figure 18a; p < 0.001, R2 = 0.079). Wetland area
(in 5 ha bins) also had a significant and positive relationship with well density using a log
transformation on well density and a power transformation on wetland area (Figure 18b;
p = 0.037, R2 = 0.003).

The percentage of each land use/cover type in the riparian zone around lakes and
wetlands showed that some land use/cover types correlated with lake and wetland area

(Figure 19). Lake area had a significant relationship with both urban (positive, p = 0.005,

20

R2 = .018) and agriculture land use/cover (negative, p = 0.065, R2 = 0.008). Wetland area
had a significant positive relationship with agricultural land use/cover (p = 0.043, R2 =
0.003). However, all relationships explain a very small amount of the variation between
lakes in riparian well density and land use/cover percentages.
Indicators of human use

Comparing the percentage of urban land use/cover to well density in the riparian
areas around each lake, depressional wetland, and stream showed that these two
indicators of human use or residential development are not highly correlated although the
regressions for lakes and depressional wetlands were significant (p = 0.001 and 0.005
respectively). The regression of riparian well density and urban land use/cover
percentage for each stream was not significant after removing one outlier (p = 0.253).
Although the regressions were significant, very little of the variation in riparian well
density for each waterbody is explained by the percentage of the riparian buffer classified

as urban land use/cover.

Discussion

The goal of this research was to gain a better understanding of land use/cover
spatial pattern and change in relation to aquatic ecosystems and to help improve our
understanding of aquatic-terrestrial linkages. Riparian areas play a proportionally greater
role in influencing aquatic ecosystems than any other part of the watershed and yet also
appear to be highly valued areas by humans. Therefore, understanding more about
riparian land use/cover and the spatial pattern of land use/cover to aquatic systems should

be important for land use/cover planning and management. We measured spatial pattern

21

by measuring the magnitude of the difference between the land use percentage in buffers
around each type of waterbody and the watershed. There are two important outcomes of
this research. First, the presence of lakes, depressional wetlands, and streams are
correlated to spatial patterns in rural residential development and urban, agricultural, and
forested land use/cover. Second, the area closest to waterbodies (up to 500 m away) is
most dramatically affected by the presence of the aquatic ecosystem.

Predicting land use/cover change is useful, but inherently difficult. One way to
improve our understanding of land use/cover change is to ensure that the most significant
variables are included as predictors of future land use/cover. Typically, natural features
on the landscape, especially aquatic ecosystems, have not been used to predict land
use/cover change. This study has revealed that lakes, depressional wetlands, and streams
may be useful to include in predictive models because they are highly correlated to some
spatial patterns of human use of the landscape.

Spatial pattern

Using well density as an indicator of rural residential development, I found rural
residential development was strongly attracted to lakes and repelled (less strongly
though) from depressional wetlands and streams (in the first 100 meters). I found strong
correlations between the location of aquatic ecosystems and rural residential development
and land use/cover supporting my hypothesis that in fact lakes, depressional wetlands,
and streams may drive spatial patterns on the landscape. The percentage of urban land
use/cover showed very similar spatial patterns to well density (attraction to lakes and
repulsion from depressional wetlands and streams in the riparian buffer). Beyond 100

meters, streams did attract urban land use/cover, which suggests that depressional

22

wetlands may be the only type of aquatic ecosystem that truly repels urban development.
Depressional wetlands were also the only aquatic ecosystem to attract agriculture and
showed the largest difference in the percent of forest compared to the entire watershed.
For depressional wetlands, as well as lakes and streams, the attraction or repulsion of
certain land use/cover types may be due in part to the spatial distribution of other land
use/cover types. Specifically, depressional wetlands may have had more agriculture and
forest around them because the percent of urban land use/cover in the first several buffers
away from depressional wetlands was lower than for lakes or streams.

The increase in proportion of urban land use/cover around aquatic ecosystems is
ecologically important. The processes through which land use/cover affects aquatic
ecosystems likely occur at different scales for different variables and are still not well
understood. These relationships have been examined mainly for streams (Roth et a1.
1996; Allan et a1 1997). Although there is still some debate over what scale aquatic
ecosystems respond most closely to human modifications, it is clear that the spatial
pattern of land use/cover on the landscape is important to ecosystems. These
discrepancies are due in part to the scale and focus of each study (Lammert and Allan
1999). Depending on the study, either the entire watershed (Omemik et al. 1981;
Hunsaker and Levine 1995; Roth et al. 1996) or only riparian land use/cover (Richards et
al. 1996; Soranno et al. 1996; Lammert and Allan 1999) has been found to be a better
predictor of aquatic conditions. The importance of the spatial pattern of land use/cover to
aquatic ecosystems makes it more important that we understand how lakes, wetlands, and

streams drive those spatial patterns.

23

The strong attraction of human residential development to areas around lakes, and
to a lesser extent streams, may mean that urban land use/cover may be influencing the
relationship with other land use types around lakes. Lakes attract urban land use/cover
within the first three hundred meters which likely raises property values and decreases
the likelihood of agriculture and forests occurring in this area (Orr 1997). Land use/cover
in the first 100 m buffer around streams may be driven in part by the hazard of occasional
flooding (Bollens 1990) and because of public education on the importance of forested
riparian buffer strips around streams. The increase in urban proportion in the near-stream
buffers (beyond the first 100 m buffer) may be indicative of a general trend of rural
residential development that is occurring in southeastern Michigan (Erickson 1995). For
example, in the River Raisin watershed between 1968 and 1988 there was an overall
increase in urban land use/cover and decrease in agriculture. Erickson (1995) expected
forested land to also decrease in this time period, but actually found that it in fact
increased.

Similar to the potential effects of floods on streamside development, the
geomophology that creates wetlands most likely has an effect on how the land is
modified by humans. The lower percent urban land use/cover near depressional wetlands
may lead to the higher percentage of forest around depressional wetlands than in the
watershed as a whole. I found that wetlands slightly attract agriculture, but I had not
expected to see a positive correlation between the location of wetlands and agricultural
land use/cover. However, because agricultural land in southeastern Michigan is often
created by draining wetlands (Erickson 1995), these two land use/cover types may be

more likely to occur in close proximity to each other.

24

Riparian land use/cover changes

The spatial pattern of land use/cover around aquatic ecosystems in the Huron
River watershed has not changed between 1938 and 1992. For example, in all timesteps
urban land use/cover was attracted to lakes and forest was attracted to all three types of
aquatic ecosystems. The absolute amount of each land use/cover type has changed
through time. One of the components of land use/cover spatial pattern that has changed
around aquatic ecosystems in the magnitude of the difference between each land
use/cover type in the riparian zone and at the watershed scale. For example, for wetlands
the magnitude of the difference of urban land use/cover was higher for the first three to
four 100 meter buffers in 1992 than in 1938, but in both timesteps, depressional wetlands
repelled urban land use/cover. This change in magnitude may indicate a change in the
way wetlands are viewed by society (i.e. less likely to build within 100 meters of them in
1992). Lakes showed an increased magnitude of urban attraction through time. This
result suggests that lakes increasingly attract people to develop in the riparian area as
both the population in the watershed increases and possibly as lakes become more
developed. From 1938 to 1992, there was an increase in the number of buffers around
lakes (beginning from the shoreline) with higher percentages of urban land use/cover than
the watershed average, as well as an increase in the magnitude of the difference. This
result is likely due partly to the overall low percentage of urban land in the watershed in
1938, but could also show that the distance from lakes that attracts development is
growing. In 1938 it was only in the first 100 meters that had a higher percentage of urban
than the watershed, but in 1992 four 100 meter buffers showed an increase in human

residential development.

25

One of the more extreme changes in land use/cover around aquatic ecosystems
that has occurred in the Huron River watershed is the change in the total percentage of
urban land use/cover around lakes through time. In 1938, ~6% of the 100 m riparian
buffer around lakes was urban. In 1992 the percentage was ~35%. Urban land use/cover
also increased around depressional wetlands and streams, but neither increase was as
extreme as lakes. There are important implications for lake ecosystems of the increase in
the percent of urban land use/cover around lakes from 6% to 35% (NRC 1992; Smith
1998). On average increasing the percentage of urban land in a watershed increases
nitrogen and phosphorus load to aquatic ecosystems (Omemik 1976). This can have
dramatic impacts on chlorophyll concentrations and percent of nuisance algae species in
lakes (Smith 1998).

We can also examine trends in individual lakes through time to understand how
changes in land use/cover affects an individual lake, wetland, or stream. Of the 453 lakes
in this study, 324 increased in the percentage of urban from 1938 to 1992, 128 remained
the same, and only 1 decreased (the decrease was a 5% reduction in urban percentage
which is within the possible measurement error) (Figure 20). Sixty percent of
depressional wetlands and 106 of the 110 stream segments had an increase in the
percentage of riparian urban land use/cover. These relationships between percent urban
in 1938 and 1992 show that it is unlikely that any waterbody will become less developed
through time. For example, the lakes with very low urban land use/cover percentages in
1938 showed the full range of development in 1992 which suggests that lakes with low
development are not likely to remain that way in the future unless zoning or other

planning measures are put into place. In addition, there were very few lakes with high

26

development in 1938 (Figure 20). In 1938 there were very few lakes with more than 50%
of their riparian zone classified as urban land use/cover, however, by 1992 many lakes
had more than 50% of their riparian buffer in urban land use/cover. This result can have
important implications for lake ecosystems because lakes with changes in residential
development have been shown to have larger changes in conductivity, alkalinity, calcium,
and pH over a 50 year period (Eilers et al. 1989).

It is interesting to note that while most of the research on the effects of land
use/cover on aquatic ecosystems has focused on streams, while my study revealed there is
proportionally less urban development in the 100 meters closest to streams than in the
watershed as a whole. Notably, there is also much less urban riparian land use/cover
around streams compared to lakes. This result is supported by other reports of riparian
land use where urban land use/cover was also found to be proportionally less in riparian
buffers around streams (Tufford et al. 1998). Tufford et al. (1998) also found smaller
percentages of agriculture and higher percentages of forest around streams that an the
watershed scale. Similarly, a study in the River Raisin watershed, just south of the Huron
River watershed, found that between 1968 and 1988 there had been an increase in
riparian forests next to streams (Kleiman and Erickson 1996). In the River Raisin the
number of acres being farmed and the number of farms have both decreased resulting in
the removal of marginal land from farming which may have influenced the increase in
riparian forest in both their and my studies. The majority of research on the effects of
riparian buffers has also been conducted primarily on streams. These studies have shown
that forested buffers are important in streams ecosystems because they help regulate

water quantity and quality. Presently, many studies have shown an increase in the

27

percentage of stream channel lined by riparian forest, suggesting a conservation of land to
preserve streams. There has been less focus on the use of riparian areas around lakes and
wetlands however, and in fact lakes attract development into the riparian areas. A
thorough and complete understanding of why these spatial patterns occur and why they
change was beyond the scope of this research, but it is likely that legislative, social, and
economic factors interact to change both human behavior and the role that lakes, streams,
and wetlands play in determining land use spatial pattern.
Efi‘ects of lake and wetland area

Because strong relationships were found between aquatic ecosystems and land
use/cover spatial patterns, I examined how this relationship varied across lakes and
depressional wetlands with different surface areas. My results show that both
depressional wetland and lake area have positive and significant relationships with well
density which means that larger bodies of water have higher well densities around them,
although the variance in well density explained by lake or wetland area was very low.
Intuitively, this relationship makes sense for lakes because larger lakes may attract more
people for the increased opportunities for recreation. The relationship with wetland area
is less intuitive, no relationship was expected to be found between well density and
wetland area. The percentage of urban land use/cover was also significant with lake area
which corroborates the finding of a significant relationship with well density and lake
area. Urban land use/cover percentage was not found to have a significant relationship
with depressional wetlands, although well density was significant, suggesting that this is
not a strong relationship. In addition to urban land use/cover, agricultural land use/cover

was found to be significant to both lake (negative) and depressional wetland area

28

(positive). A possible explanation of these results is that because of the positive
relationship with urban land use/cover, larger lakes are less likely to have agriculture
around them. The positive relationship between depressional wetlands and agriculture is
more difficult to explain and may be specific to this watershed. However, the topography
and hydrology around depressional wetlands may vary with wetland size and result in
better-suited conditions around larger depressional wetlands for agriculture.

For all of the surface area analyses, it is important to keep in mind that although
these relationships were found to be significant, a very small amount of the variance in
well density and land use/cover percentage is explained by surface area. These
relationships may be weak partly because the range in lake and depressional wetland
surface area is not very wide. The smallest waterbodies (< 2 ha) were removed from the
analysis and the upper range was not very large (maximum: ~400 ha lake and ~80 ha
depressional wetland). A wider range in sizes may have resulted in stronger
relationships.

One of the factors not explicitly examined in this study that may affect the percent
of riparian urban land use/cover around a lake is the distribution of lakes on the landscape
and the relative locations of large urban centers. In the Huron River watershed, the
natural distribution of lakes results in an uneven scattering of lakes and lake sizes within
the watershed. The northern part of the watershed has more and larger lakes than the
southern portion. Figure 22 shows that lakes with higher percentages of urban land
use/cover in the 100 m riparian zone are somewhat clumped together in 1992. This
suggests that the distance from one lake to another may be important in determining how

developed a lake will become. In 1938, there also seems to be some spatial pattern

29

between distance to other lakes and shoreline development. Therefore, the distribution of
lakes on the landscape appears to play a role in determining urban riparian development,
although it would be necessary to analyze this pattern more quantitatively in a variety of
watersheds to conclude if this is an ecologically significant spatial pattern.
Indicators of human use

I examined how aquatic ecosystems drive spatial patterns on the landscape by
using well density and land use/cover as indicators of human modification of the
landscape. I expected to find a similarity between the spatial pattern of well density and
urban land use/cover because they indicate similar human modification of the landscape.
However, they result in slightly different conclusions about the magnitude of the
difference between the riparian and watershed averages. For example, for lakes the first
100 m buffer had a well density 2.5 times higher than the watershed, while the urban
percentage in that buffer was only 1.3 times higher. Urban land use/cover indicates when
an area of land is being used for residential, commercial, or industrial purposes. It does
not reveal anything about the intensity of that use. Well densities can only be used in
areas without public water supplies (i.e. rural) and is therefore most useful for examining
rural residential development. Unlike urban land use/cover, wells can give you
information about the density of development which may be ecologically important
(Dillon and Rigler 1975; Hutchinson et al. 1991). In fact, well density and the percent of
urban land use/cover for the first 100 m buffer around each lake, depressional wetland,
and stream are not strongly correlated, although the regression is statistically significant
(p < 0.001) (Figure 22). As the percent of urban land use/cover increases in the buffers,

there is an overall increase in well density, but there is a great deal of variation around

30

this relationship. In fact, eighty percent of the wells were in land use/cover classified as
urban, 6% in agriculture, 5% in forest, and 9% in other land use/cover types, suggesting
that there is also slight variation in the land use/cover category associated with a given
well. This result suggests that well density and urban proportion reflect different features
of human use and that well density can provide more of an indicator of the intensity of
human use. Depending on the question, it is important to carefully choose which

indicator of development is used.

Conclusions

In this study, I examined if rural residential development and land use/cover
showed any spatial patterns in relation to aquatic ecosystems in the Huron River
watershed. My results show that urban, agricultural, and forested land use/cover types
have different distributions in riparian zones than in the watershed as a whole and show
different rates of change through time. My results may be typical for the North temperate
glaciated landscapes in regions with a large human population, but warrant further
research in other watersheds and regions.

A complete understanding of how natural features on the landscape affect land
use/cover spatial pattern and change will add to our ability to predict land use change in
the future and help better manage land use in environmentally sensitive and highly valued
areas such as riparian zones. Although riparian areas do play a proportionally greater
role in influencing aquatic ecosystems than other parts of the watershed, riparian areas
' cannot be expected to mitigate the effects of uncontrolled modification of the landscape,

especially when they are also under development pressure.

31

APPENDIX 1

TABLES AND FIGURES

32

Table 1. Summary characteristics of aquatic ecosystems in the Huron River watershed.

Lake Wetland Stream
Number of polygons 453 1296 110 segments
Total area or length 6249 ha 5455 ha 553 km
Area or length range 1 — 412 ha 1-77 ha 0.6 — 24.7 km
Mean area or length 13.8 ha 4.2 ha 5.0 km
Median area or length 3.4 ha 2.4 ha 4.0 km

Table 2. Summary of wetlands in the Huron River watershed classified into forested and
nonforested classes. The number of wetlands that were removed from the nonforested
wetland group to create the depressional wetland group are also described.

Area (ha) Number
Forested wetlands 3296 662
Nonforested wetlands 8796 1840
Depressional 5574 1312
Nonforested riparian 3222 528

Table 3. Wetland area and number of wetlands classified to nonforested and forested
wetland types. The percent change is reported for a timestep from the previous timestep.

33

Wetland N onforested Forested Total
area
Wetland area % Wetland area % Wetland area %
(ha) change (ha) change (ha) change
1938 13199 4534 17733
1956 10072 -24% 3534 -22% 13606 -23%
1971 9063 - 10% 3376 -4% 12439 -9%
1985 8912 -2% 3336 -1% 12248 -2%
1992 8796 - l % 3296 - l % 12092 -1%
Number of Nonforested Forested Total
wetlands
Number % Number % Number %
change change change
1938 4296 1386 5682
1956 2598 -40% 850 -39% 3448 -39%
1971 2061 -21% 742 -13% 2803 -19%
1985 1979 -4% 716 -4% 2695 -4%
1992 1 840 -7% 662 -8% 2502 -7%

Table 4. Difference in percent of watershed land use from percent of riparian land use

URBAN Year Lake Wetland Stream
1938 2.1 -2.9 -0.6
1956 7.4 -4.6 1
1971 11.3 -7.9 -1.2
1985 11.7 -8.3 -2.3
1992 9.8 -9.0 -3.3

AGRICULTURE Lake Wetland Stream
1938 -24.8 0.1 -23.9
1956 -24.3 3.1 -21.4
1971 -23.7 3.0 -16.3
1985 -22.6 3.8 - 14.4
1992 -20.7 4.5 -13.3

FOREST Lake Wetland Stream
1938 6.8 2.3 4.8
1956 6.3 4.0 7.1
1971 3.7 6.2 5.0
1985 3.2 6.3 5.1

1992 2.5 5.9 5.1

34

LIST OF FIGURES

Figure 1. Map of 1992 land use/cover (D. Rutledge unpublished data) in the subset of the

Huron River watershed and its location relative to other Michigan watersheds. Images in

this figure are presented in color.

Figure 2. Location of lakes, depressional wetlands, and streams in the Huron River

watershed. Images in this figure are presented in color

Figure 3. Land use/cover percentages of the dominant land use/cover types in the entire

watershed for all five timesteps (a) and the rates of change in hectares per year of all six

land use/cover types between each timestep along with the total rate of change between

1938 and 1992 (b).

Figure 4. Location of wells and towns in the Huron River watershed.

Figure 5. Distribution of wells around lakes (a), depressional wetlands (b), and streams

(c) in a subset of the Huron River watershed. Note that lakes along the stream system

interrupt the stream channel network.

Figure 6. Example of rules used to create buffers around two lakes.

Figure 7. Example of the final buffer coverage around lakes in a subset of the watershed.

35

Figure 8. Frequency distribution of lake (a) and depressional wetland (b) areas placed in

10 and 5 hectare bins, respectively.

Figure 9. Area of land included in each buffer around lakes (a), depressional wetlands

(b), and streams (c) and the cumulative percent area of all buffers to a given distance.

Figure 10. Weighted mean well density (wells/kmz) and 95% confidence intervals for
each buffer distance around lakes (a), depressional wetlands (b), and streams (c). Dashed
line is the average well density in the watershed after removing lake, wetland, stream,

and towns from the area of the watershed.

Figure 11. Weighted means and 95% confidence intervals of the percentage of urban
land use/cover in 1992 for each buffer distance around lakes (a), depressional wetlands
(b), and streams (c). Dashed line is the percentage of urban land use/cover in the entire

watershed.

Figure 12. Weighted means and 95% confidence intervals of the percentage of
agricultural land use/cover in 1992 for each buffer distance around lakes (a), depressional
wetlands (b), and streams (c). Dashed line is the percentage of agricultural land use/cover

in the entire watershed.

36

Figure 13. Weighted means and 95% confidence intervals of the percentage of forest
land use/cover in 1992 for each buffer distance around lakes (a), depressional wetlands
(b), and streams (c). Dashed line is the percentage of forest land use/cover in the entire

watershed.

Figure 14. Weighted means and 95% confidence intervals of the percentage of urban
land use/cover in 1938 (grey bars) and 1992 (black bars) for each buffer distance around
lakes (a), depressional wetlands (b), and streams (c). Dashed lines are the percentages of

urban land use/cover in the entire watershed in 1938 and 1992.

Figure 15. Weighted means and 95% confidence intervals of the percentage of
agricultural land use/cover in 1938 (grey bars) and 1992 (black bars) for each buffer
distance around lakes (a), depressional wetlands (b), and streams (c). Dashed lines are the

percentages of agricultural land use/cover in the entire watershed in 1938 and 1992.

Figure 16. Weighted means and 95% confidence intervals of the percentage of forest
land use/cover in 1938 (grey bars) and 1992 (black bars) for each buffer distance around
lakes (a), depressional wetlands (b), and streams (c). Dashed lines are the percentages of

forest land use/cover in the entire watershed in 1938 and 1992.

Figure 17. Weighted mean percentage of urban (a), agricultural (b), and forest (c) land

use/cover in the 100 meter buffer around lakes, depressional wetlands, and streams for

each timestep. 95% confidence intervals are presented with the means, but are not visible

37

because they are smaller than the data points. Note that forest (c) has a different scale on

the y-axis.

Figure 18. Box plots of well density in the 100 meter buffer around lakes (a) and

depressional wetlands (b) grouped into 10 and 5 hectare bins, respectively.

Figure 19. Box plots of percentage of urban, agriculture, and forest land use/cover in the
100 meter buffer around lakes (a) and depressional wetlands (b) grouped into 10 and 5

hectare bins, respectively.

Figure 20. Percentage of urban land use/cover in the 100 meter buffer around each lake

in 1992 as compared to 1938.

Figure 21. Lakes are shaded to represent the percentage of urban land use/cover in the
100 meter buffer around each lake in 1938 (a) and 1992 (b) in a subset of the watershed.

Images in this figure are presented in color.

Figure 22. Percentage of urban land use/cover in the 100 meter buffer around each lake
(a), depressional wetland (b), and stream (c) in 1992 compared to the well density
(wells/kmz) in the 100 m buffer around each lake. The R2 and p-value reported for

streams were calculated after removing one outlier.

38

 

   
 
 

1992 Land Use/Cover in the
Huron River watershed

 

 

 

 

- Urban
- Agriculture

V " ‘ Nonforested vegetation
__+__ - Forest
0 5 10 - Water

Kilometers Wetland

Figure 1

39

 

“.61 We; 3‘:

    

 

 

0 Lake
9 Depressional Wetland
’U Stream

5 Kilometers

 

 

 

Figure 2

40

A. Land use percentages

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

60 ‘
1: a
Q)
E 50 ‘ _.
8
‘° 40 ‘
3. 'Urban
3 30 DAgriculture
3’ 'Forest
‘5 20 ‘
§
g: 10 ‘
0.
1938 1956 1971 1985 1992
Year
B. Rate of land use change
11%
‘5
a 600-
t. 31938-1956
§ 100: . .1956-1971
fi 41971-1985
30 “400 01985-1992
.5 300‘ ITotal change
U
-l400-
Urban Agriculture NonforestVeg. Forest Water Wetland
Land use/cover type
Figure 3

41

 

 

 

- Town

5 Kilometers - Well

 

 

 

 

Figure 4

42

 

A. Lakes

 

 

B. Depressional
Wetlands

 

 

C. Streams

5 Kilometers

 

 

 

 

Figure 5

43

100 and 200 m buffers assigned to lakes A
& B resulting in three overlapping polygons.

 

Randomly assign
overlapping buffers
of same distance

 

Cg? 200m buffer overlap
l: Lake A. buffers
Lake B. buffers

Figure 6

44

I x, \ll/led... \

., - - QC
. r ,. :2 ,fl_m__ammo@
... ., fiflwfimaaé
. @WWrflg/ an
«W)&_.®@fi.©n / Kl

)

.Waée -
@QrWfl
my. £6

@Aflm

J

.3
NJ 1 )I/x/llx

,, NWW A ire/ct »/ WU \\l

l -w as t

//
.//

.WQ

AA. @txms . W ,,

 

0
. 1v \ .2
W \xlfiyll/ \JR

-3
”J /\
we. 9

\ > . % fi/wmln/FKAWM/

{W fills w; ._
N o a» xm/VQJ/ \rflx afifiwuy/ ./
3m amouifiUc

l/

97% 9 .W. / \s/W
or. 1%”fo ”WNW/.l, .

5 Kilometers

m
x
W

,
»

Figure7

45

A. Lake areas

 

 

 

 

 

 

 

 

1000

3 o

x

.‘3 Dos

“5 l o

.8 o

E 104 . .

o ’09 o
o o
1 1 ¢ 3 1 ¢ 1 1 ‘fi 1
O 100 200 300 400 500
Lake area (10 ha bins)

B. Depressional wetland areas

_8 10001 ’

t:

(6
u. E ’
3 3 100-
0 —— O
‘13 § .
:1 --~ _
Z g 10 o o . °

:2.

g o o

1 1 1 c 1 ¢ ¢ 1
0 20 40 60 80 100
Wetland area (5 ha bins)
Figure8

46

A. Lake buffers

 

 

 

 

 

 

 

 

Distance from water body (m)

47

 

200
A l “>- 0.9
. A ‘1
E150 ~ 1. .1 .1 1. i
A
£2 ,, A —— 0.6
:3 100 r O . O 9 Q ‘
.o z e ,
.E ’ ° 0
350- *‘A .00, «0'3
E A ‘ . ° 0
A
0 ‘ 1 1 1 0
0 500 1000 1500 2000
B. Depressional wetland buffers
200 1
(GR .0. “A“A“FO.9
E O 1‘ A ‘
{2.1150 7 . . ‘ ‘
H . -—
3“; A . 0.6
B 100 - g .
.E A o
8 SO _ ‘ . ..._ 0.3
E A °
° 0
O A Q Q . . ‘ 0
0 500 1000 1500 2000
C. Stream buffers
200}
c? d” 0.9
g 150 ‘ A 11
1... ‘ A ‘
. é’ A 11 ‘ “r 0.6
-5 100 a A ‘
u: 0 O 0 Q . . O . ‘
.3 ‘ O O . .
0 SO __‘ ‘ . O . . d” 0.3
:2 ‘ ‘ o ’ 0 0
‘ A
O l r 1 O
0 500 1000 1500 2000

Cumulative % of Cumulative % of

Cumulative % of

watershed area

watershed area

watershed area

 

 

0 Buffer Area

Cumulative % of
watershed area

 

 

Figure 9

A. Lake well density
30

 

NN
CU!

 

Average #wells/km2
5 G
I

I

I

I
I

I

 

 

 

CM

0 500 1000 1500 2000
B. Depressional wetland well density
14~
12 ‘ - ' 1:
10 ‘

 

Average #wells/km2
I
H
H
H

 

 

 

0 w . 1 1
0 500 1000 1500 2000

C. Stream well density
16 *

 

 

Averagey#wells/km2
00
H
H
H
II
H
H
H

 

 

 

.1

O 500 1000 1500 2000
Distance to water body (m)

FigurelO

48

 

.1!
"1.1-.

A. Lake - urban

Percentage of buffer

 

50

A
O

U»)
C
I

N
O

5

 

 

 

O 1 1 1
0 500 1000 1500

B. Depressional wetland - urban

Percentage of buffer

2000

 

50

4:.
O

M
O
I

N

o

I
I

O

 

II

 

 

o 1 . 1
0 500 1000 1500

C. Stream - urban

Percentage of buffer

50

2000

 

A
O

U)
C
1
I
I
I

 

 

O I I I
0 500 1000 1500
Distance to waterbody (m)

49

 

2000

Figure 1 1

A. Lake -agriculture

Percentage of buffer

Percentage of buffer

Percentage of buffer

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

6O 4
40 -1 . _ _ _
20 a -

0 1 1 1

0 500 1000 1500 2000
B. Depressional wetland -agriculture

60 ~
40 _
20 a :1: :1:
0 l I r

0 500 1000 1500 2000

C. Stream - agriculture
60 -
4O .1
a: I: t
= I
20 1 " '
o 1 1 1
O 500 1000 1500 2000
Distance to waterbody (m)

50

Figure 12

 

A. Lake - forest

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

51

30
5
a - -
a: 20 “ - -
“It - -
° - I
Q I
DO
8
5
E 10 r
a.
0 l l l
0 500 1000 1500 2000
B. Depressional wetland - forest
30
11"»
8‘:
3 - -
“5 2O 1 1..
o ' - I- I
3 I I
G
21‘: 10 ~
0
n-
0 1 fl 1
0 500 1000 1500 2000
C. Stream - forest
30
3'3
8:
=
“a 20 7 I _ I I I I
a 11 ‘ 1
8
=
id: 10 1
a.
0 . 1 , ,
O 500 1000 1500 2000
Distance to waterbody (m)

Figure 13

A. Lake - urban

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

50
3
8; 40
.1: ..
6.1
o -
g», 30 - _
s """"""""""" ‘- """"" -'- """"""" - ------- ‘--
fl
0
8 20 ‘
Q)
a.
10 ‘ ~
0 1 1 1
500 1000 1500 2000
B. Depressional wetland - urban
50
a 1: I
’i 40‘
.1: z
“-1
c -
311 30 ‘ -
s ................................................. ,_...
1:
0 -
8 20* - "
u -
m -
10 ~ _ "
0 — 1 1 1
0 500 1000 1500 2000
C. Stream - urban
50
3
lg 40
.n-
"5
8’» 30‘ ...r..'.'..'. ....... '. = .
5 """"""""""""" i; """" if}
g I:
3 20 ~ 1
5'3 1938 buffer mean
9‘ I 1992 buffer mean
10 ‘ ' " "1938 watershed mean
,...—...:....-. ............ —...._,_ “"1992watershedmcan
O l I 1 .
500 1000 1500 2000
Distance to waterbody (m) Figure 14

52

A. Lake -agriculture

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

60 — - 7 ’ ‘ h
3 .................................................................................
3:: g -
5
.9 _
“5 40 - _ _
Q - - I
60 ...
S --------------- .; --------------------------------
5
§ 20 1 _ -
m —
0 1 1 1
0 500 1000 1500 2000
B. Depressional wetland «agriculture
g 60 d “...-...-..7 ............ 2': ............ 11..."? .............................. -...
5
1f
3 40 ~
OD
3 " " - - _
g ...................................................
0 - - I
0
2'3 20 1 z r
11..
0 I l l
0 500 1000 1500 2000
C. Stream - agriculture
3 60 ~ -~ ................ “I...
E - _
“5
o 40 ‘
NJ
‘3 '.' ....................................... .=. ....... i.”
0 I I
a _ _ - - I I 1938 buffer mean
g 20 _ I 1992 buffer mean
' ' 1938 watershed mean
““1992 watershed mean
0 T r 1
0 500 1000 1500 2000
Distance to waterbody (m) Figure 15

53

A. Lake - forest

Percentage of buffer

Percentage of buffer

Percentage of buffer

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

3O
20 a "' _ - -
....- ................... II ............ -........-...
10 ~
0 I r 1
0 500 1000 1500 2000
B. Depressional wetland - forest
30
20 ~ ' - -
'..'..".‘..'.E.’..'-f.'.If..'.if.'..'.i.'..'f.'.:f.E.f.'..°..'.f.'..°f.’..'f.°.1111.1: '
I - I
10 a
o l l T
0 500 1000 1500 2000
C. Stream - forest
30
I
20 ~ - I I
. .1: . .......§.: .......... 1.5 ...........
__ :I: r I .. __ - ..
10 4 I 1938 buffer mean
I 1992 buffer mean
' 1938 watershed mean
“"1992 watershed mean
0 w I r
0 500 1000 1500 2000

Distance to waterbody (m)

54

Figure 16

Percentage of buffer

A. Urban riparian land use/cover

 

60‘
50‘
401
30‘
20‘
10‘

  

 

  

 

 

          

 

 

O . . , . v v
1935 1945 1955 1965 1975 1985

B. Agricultural riparian land use/cover

Percentage of buffer

Percentage of buffer

1 995

 

60‘
50‘
40W
30‘
20*
10‘

 

 

 

 

0 - C . . .
1935 1945 I955 I965 1975 1985

C. Forested riparian land use/cover

I995

 

30
25 .
20 .
15 J G/W’” _ ,
10 .

 

5 4
O

 

 

 

1935 1945 1955 1965 1975 1985
Timestep

55

1995

 

 

-°- Ifiake . al
e ressnon

+w§1and

--«— Stream

-°-- Watershed

 

Figure 17

 

A. Lake area - well density

 

300 Ill]

MW 1 l
x°° m®s°°u$ps°°
Lake area (10 ha bins)

Wells / km2
N

8
r

4

§

Woo oomo
:j——‘<IGH c o

 

 

 

B. Depressional Wetland area - well density
6 l l l

 

S— —.

 

 

Wetland density ( log(x+1))
W
l
_}_———-
l

 

 

 

 

 

 

 

 

 

 

l l l

-0.20 -0.15 -0.10 -0.05 0.00
Wetland area (ha) (- l/area)

 

Figure 18

56

A. Lake area - land use percentage

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Urban Agricultural Forest

U T l l I l l I I I l I
DO
.2 100’ ' ‘ Lii ‘ “I . ‘
d.) _ F‘ _ E ° _¢ 3
i 80 _ - ' ‘ “
o 60 " [ ‘ H ‘ “E o '4 ' ‘
'U 40 ‘1 LE ‘ L 6 _
g . - . H -

20 J i: it ~ - ~

0 a . 1 l J I I‘ll EA °° ,, -1—1 1 , .1": 1

a a §§§ a a ag e a §§§
Lake area (ha) Lake area (ha) Lake area (ha)
B. Depressional Wetland area - land use percentage
Urban Agricultural Forest

0 [mp U - I. c
g 80 ~ " 1 r 1
223 i‘
a 60 - - ~ ;1
3 40 r ‘ ‘
53‘ fl _ D
g 20 F B _ ‘ H i _ ._

O U — l- l l L... l L L 1 l

0 30 60 9d) 30 60
Wetland area (ha) Wetland area (ha) Wetland area (ha)
Figure 19

57

Riparian urban % ( 1992)

 

 

 

 

 

 

 

 

 

 

’/ -
o ’
to" '
O O /
9 on V
. ,»’
2/
O //‘
20 4O 60 8O

Riparian urban % (1938)

58

100

Figure 20

 

A. 1938

 

 

 

B. 1992

 

 

 

1 , . ‘
ck ‘

 

Percentage of
urban land use
in 100 m buffer
m o - 5 —
5 - 25 5 Kilometers
fig. 1; 25 - 50

' 50-75
75-100

 

Figure 21

59

1992 Well density (# / kmz)

A. Lakes
250

200

 

B. Depressional Wetlands

250

R2 = .072
200 p = 005 .
150

r o ’ . o

 

 

 

 

C. Streams
250
i R2=.01
200 ‘ p=.293
150 -
100 -
50 1 °
0 4 1w 5% 3 _v . ‘3 .
0 20 4o 60 80 100

Riparian urban % ( 1992)

Figure 22

60

LITERATURE CITED

61

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