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This is to certify that the
thesis entitled

EFFECTS OF LANDSCAPE CHANGE
ON GOLDEN-WINGED AND BLUE-WINGED WARBLERS
IN MICHIGAN

presented by

Katherine. J. Kahl

has been accepted towards fulfillment
of the requirements for the

MS. degree in Fisheries and Wildlife

 

Major Professor’s Signature

May 9, 2003

Date

MSU is an Affirmative Action/Equal Opportunity Institution

PLACE IN RETURN Box to remove this checkout from your record.
TO AVOID FINES return on or before date due.
MAY BE RECALLED with earlier due date if requested.

 

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6/01 c'JClRC/DatoDuopes-pJS

EFFECTS OF LANDSCAPE CHANGE ON GOLDEN-WINGED AND
BLUE-WINGED WARBLERS IN MICHIGAN

By

Katherine J. Kahl

A THESIS
Submitted to
Michigan State University
in partial fitlfillment of the requirements
for the degree of
MASTERS OF SCIENCE
Department of Fisheries and Wildlife

2003

ABSTRACT

EFFECTS OF LANDSCAPE CHANGE ON GOLDEN-WINGED AND BLUE-
WINGED WARBLERS IN MICHIGAN

By

Katherine J. Kahl

The objective of this research was to compare changes in landscapes over time where
Golden-winged and Blue-winged Warblers were present and absent in the lower
peninsula of Michigan. To do this, the landscape composition (land cover types within
the landscape) and landscape structure (degree of fragmentation of land cover types)
along Breeding Bird Survey (BBS) routes where both species were present were
examined and compared to routes where they were absent in 1978, 1993, and 2000.
Differences in landscape composition and structure around 46 BBS routes were
compared using classified land cover data from 1978, 1993, and 2000. A 018 was used
to create a 400-meter buffer around BBS routes. Total area and area-perimeter ratios for
12 landscape composition and 12 landscape structure variables were calculated within
each buffered area. Principal components analysis explained covariation patterns across
multiple landscape composition and structure variables. Analysis of variance was used to
test the significance of each principal component. Results show that both Golden-winged
and Blue-winged Warblers are moving northward. Potential causes of range shift for the
Golden-winged Warbler may be due to increased human influence and increased
fragmentation of land cover types they find favorable. Blue-winged Warblers may not be

as negatively affected by these factors.

ACKNOWLEDGEMENTS

This project has been one of endurance. I would like to thank my labmates, Genny
and Jennie, for enduring me and enduring with me in quarters big and small. Thanks to
my major advisor, Dr. Brian Maurer, who provided mentorship in the finer points of
statistical analysis and in project development. Thanks to my additional committee
members, Dr. Kelly Millenbah and Dr. Catherine Lindell. Kelly likely wondered if I
would ever finish asking GIS questions, among others, but was always there to help
untangle the web. Thanks to my friends for all the encouragement and being such nice
folks. So many thanks to my family for always being my cheering section and supporting
me in my endeavors. It means more than you know. Thank you Jody, for being my

friend, partner, and an unwavering source of strength in my life.

iii

TABLE OF CONTENTS

LIST OF TABLES .......................................................................................................... 4
LIST OF FIGURES .......................................................... . .............................................. 5
INTRODUCTION .......................................................................................................... 6
Bibliography ..................................................................................................... 9
Figures ............................................................................................................ 12

EFFECTS OF LAND COVER CHANGE ON GOLDEN-WINGED AND BLUE-

WINGED WARBLERS IN MICHIGAN ..................................................................... 14
Abstract .............................................................................................................. 14
Introduction ........................................................................................................ 1 5
Methods .............................................................................................................. 17
Statistical Analysis ............................................................................................. 20
Results ................................................................................................................ 23

Differences among routes with and without Golden-winged Warblers...23

Differences among routes with and without Blue-winged Warblers ....... 26

Discussion .......................................................................................................... 27
Future Research ................................................................................................. 29
BIBLIOGRAPHY ......................................................................................................... 3O
TABLES ....................................................................................................................... 32
FIGURES ...................................................................................................................... 34
APPENDIX A ............................................................................................................... 41

iv

LIST OF TABLES

Table - Page
1 Landscape Composition and Structure Classes ................................................... 32

LIST OF FIGURES

Liam » 1322:
INTRODUCTION
1.1 Golden-winged Warbler distribution map ....................................................... 12
1.2 Blue-winged Warbler distribution map ........................................................... 12
1.3 Golden-winged and Blue-winged Warbler range overlap map ....................... l3

EFFECTS OF LAND COVER CHANGE ON GOLDEN-WINGED AND BLUE-

WINGED WARBLERS IN MICHIGAN

1. Routes with and without Golden-winged and Blue-winged Warblers .............. 36
2. Landscape composition variables: Golden-winged Warbler ............................. 37
3. Univariate landscape composition variables ...................................................... 37
4. Landscape structure variables ............................................................................ 38
5. Landscape composition and structure variables ................................................ 38
6. Herbaceous landscape composition ................................................................... 39
7. Landscape composition variables: Blue-winged Warbler ................................. 39
8. Landscape composition and structure variables ................................................ 40

vi

INTRODUCTION

The Golden-winged Warbler (Vermivora chrysoptera) is among the highest-ranked
species for conservation in the Northeast, Southeast, and Midwest regions of the United
States (Barker and Rosenberg, 2000). Over the last three decades, the Golden-winged
Warbler has declined by 7.7% annually within its breeding range while the Blue-winged
Warbler (V. pinus), a congener, has only declined by 4.4% annually in the southern
portion of its range (Sauer er al., 1999). Both species are currently under United States
Fish & Wildlife Service contracted status assessment to determine whether they should
be Federally listed as threatened or endangered (Confer and Tupper, 2000; T. Will, Bird
Conservation Biologist, pers.comm.). There has been no published research on the status
of Michigan Golden-winged and Blue-winged Warbler populations since 1986 (Will,
1986).

The Golden-winged Warbler is an insectivorous, ground-nesting, Neotropical
migratory songbird that breeds in the northeastern United States and Canada, with its
largest populations concentrated in habitats along the Appalachian mountain range and
the U.S.-Canadian border. Michigan, Wisconsin, Minnesota, New York, Pennsylvania,
Vermont, West Virginia, and Ontario have some of the largest breeding populations
(National Geographic Society 1987; Brewer er (11.1991) (Fig. 1.1). Golden-winged
Warblers are associated with early successional patches of herbaceous cover, shrubs and
scattered trees that are often bordered by a forested edge. This habitat often results from
fire, logging, or abandoned farmland. They can also be found along marshes and bogs

with forested edge (Confer, 1992).

The Blue-winged Warbler is similar in behavior, vocalization, and body size, and is
known to compete with the Golden-winged Warbler for resources. Also a Neotropical
migratory songbird and a ground-nester, the Blue-winged Warbler breeding range lies
slightly southwest of the Golden-winged Warbler range (Fig. 1.2). Shrubby, early-
successional habitat is favored (Dunn and Garrett, 1997; Confer, 1992). Range
expansion for more than a century was aided by increased amounts of abandoned
farmland and forest clear-cuts providing the necessary early- to mid-successional habitat
(Berger, 1958; Confer and Knapp, 1981; Will, 1986). More recently, increased urban
sprawl and succession of abandoned farmland and old field cover types have resulted in
habitat loss for the species.

Hybridization occurs where the two species breeding ranges overlap (Fig. 1.3)
producing a first cross (Fl) between the Golden-winged and Blue-winged Warbler called
the Brewster’s Warbler (V. Ieucobronchialis). The less common Lawrence’s Warbler,
(V. Iawrencii) is the second cross (F2) between either parent species and a Brewster’s
Warbler (Curseon et al., 1994; Dunn and Garrett, 1997). Both hybrids are fertile,
although their fitness may be low and potentially negatively affecting population sizes of
both species with increased hybridization (Confer, 1992). Both hybrids sing either parent
species song, or a garbled version of it, and have distinctive although variable plumage
markings. There is debate as to whether hybrids can accurately be visually differentiated
from Blue-winged Warblers (Parkes, 1951; Short, 1963; Ficken and Ficken 1968a,b; Gill
and Murray 1972; Gill 1980, 1997; Confer and Larkin, 1998).

Specific causes of Golden-winged Warbler decline within the breeding range are

often attributed to competition and hybridization with the Blue-winged Warbler.

However, the mechanism by which hybridization may favor the Blue-winged Warbler is
not yet understood (Confer, 1992). Arrival and expansion of the Blue-winged Warbler
in an area is frequently associated with the decline of the Golden-winged Warbler (Gill,
1980; Confer, 1992). However, they have not been proven to be the direct cause of the
extinction of local Golden-winged Warbler populations (Gill et al., 2001). Golden-
winged Warbler decline is known to be caused in large part by factors such as habitat loss
due to succession and human influences.

Behaviorally dominant Blue-winged Warblers may displace Golden-winged
Warblers from optimal habitat in central Michigan (Will, 1986). However, in other
geographic areas of the breeding range, Golden-winged Warblers dominate Blue-winged
Warblers (Confer, 1992) or Blue-winged Warblers do not exclude Golden-winged
Warblers from optimal nesting territories (Confer and Larkin, 1998).

Much of today’s research on Golden-winged and Blue-winged Warbler populations
focuses on hybridization of these two species and the potential negative effects on the
success of “true” populations of each species. Understanding how hybridization is
affecting population dynamics and therefore range shift must be explored to accurately
assess where species populations are located, in what abundance, and the patterns of
reproduction for each species and hybrids. The information needed first, however, relates
to understanding the particular habitat type characteristics that each species is selecting
for or against. Understanding the local and landscape-level patterns of habitat selection
within the possible matrix of habitat choices within the landscape is a necessary first step

for conservation agencies as well as for the knowledge base of avian ecology.

BIBLIOGRAPHY

Barker SA. and K.V. Rosenberg. 2000. The Golden-winged Warbler. Birdscope. Vol.1:
5-6.

Berger, AJ. 1958. The Golden-winged-Blue-winged Warbler complex in Michigan and
the Great Lakes area. Jack-Pine Warbler, 36237-71.

Brewer, R., G.A. McPeek, and R]. Adams Jr. 1991. The Atlas of Breeding Birds of
Michigan. Michigan State University Press, East Lansing, MI.

Confer, .1 .L., and K. Knapp. 1981. Golden-winged Warblers and Blue-winged Warblers:
the Relative Success of a Habitat Specialist and a Generalist. The Auk, 98: 108-
114.

Confer, J .L. 1992. Golden-winged Warbler. In The Birds of North America, No. 20 (A.
Poole, P. Stettenheim, and F. Gill, Eds.). Philadelphia: The Academy of Natural
Sciences; Washington DC: the American Ornithologists’ Union.

Confer, J .L. and J .L. Larkin. 1998. Behavioral Interactions Between Golden-winged and
Blue-winged Warblers. The Auk, 115(1): 209-214.

Confer, J.L. and SK. Tupper. 2000. A Reassessment of the Status of Golden-winged and
Blue-winged Warblers in the Hudson Highlands of Southern New York. The
Wilson Bulletin, 112(2): 544-546.

Curseon, J. D. Quinn, and D. Beadle. 1994. Warblers of the Americas. Houghton Mifflin,
NY, 22, 96-97.

Dunn, J. and K. Garrett. 1997. Peterson Field Guide to Warblers. Pages 125-145.

Houghton Mifflin, NY, 125-145.

Ficken, MS. and R.W. F icken. 1968a. Ecology of Blue-winged Warblers, Golden-
winged Warblers and Some Other Vermivora. American Midland Naturalist, Vol.
79, No. 2, 311-319.

Ficken, MS. and R.W. Ficken. 1968b. Reproductive Isolating Mechanisms in the Blue-
winged Warbler-Golden-Winged Warbler Complex. Evolution, Vol. 22, No. 1,
166-179.

Gill, F.B. 1998. Hybridization in Birds. The Auk, 1 15(2): 281-283.

Gill, F.B. 1980. Historical Aspects of Hybridization Between Blue-winged and Golden-
winged Warblers. The Auk, 97:1-18.

Gill, F.B. and B.G. Murray Jr. 1972. Discrimination Behavior and the Hybridization of
the Blue-winged and Golden-winged Warblers. Evolution, 26: 282-293

Gill, F.B. 1997. Local Cytonuclear Extinction of the Golden-Winged Warbler, Evolution,
Vol. 51, No. 2, 519-525.

Gill, F.B., R.A. Canterbury, and J .L. Confer. 2001. Blue-winged Warbler (Vermivora
pinus). In The Birds of North America, No. 584 (A. Poole and F. Gill, eds.) The
Birds of North America, Inc., Philadelphia, PA, 1-23.

National Geographic Society. 1987. Field Guide to the Birds of North America. Second
Edition. Washington, DC, 354.

Parkes, 1951. The Genetics of the Golden-winged Warbler x Blue-winged Warbler
Complex. The Wilson Bulletin, 63(1):5-15.

Short. L.L.1963. Hybridization of Wood Warblers Vermivora pinus and V. chrysoptera.
In Proceedings of the X111 International Ornithological Congress. Baton Rouge,

LA, 147-160.

Will, T.C. 1986. The Behavioral Ecology of Species Replacement: Blue-Winged and
Golden-Winged Warblers in Michigan. Ph.D. dissertation, University of

Michigan. Ann Arbor, MI.

FIGURES

     
    
    

a

’,. EZEIEB Iirriit

. t-lt
i,

 

101 and move
3110100
111030

4 to 10

2 to 3

One and below
I None Counted

  
  

 

 

 

Golden-winged Warbler

Vormivora chrysoptera

Figure 1.1 Golden-winged Warbler distribution map. Map taken from National
Breeding Bird Survey data results collected between 1985 and 1992.

1':

          

I

.9?

BBSBhnnt

 

101 and above
31t0100
111030
41010

i” '
‘53} i " x ' zto 3
.- '—'" one and below
d.‘ I None Counted
' ‘ Blue-winged Warbler

Vermivora pinus

 

 

 

Figure 1. 2. Blue-winged Warbler distribution map. Map taken from National Breeding
Bird Survey data results collected between 1985 and 1992.

 

  
  

Breeding Range

 
  

., W - _\
45,-.)
{v

3% D Goldeln-wingcd

Blue- -lwinged
I Warbler

Warbler

I Range overlap

Figure 1.3. Golden-winged and Blue-winged Warbler breeding range overlap. Map
taken from Golden-Winged Warbler Atlas Project results, 1992.

EFFECTS OF LAND COVER CHANGE ON GOLDEN-WINGED AND BLUE-

WINGED WARBLERS IN MICHIGAN

KATHERINE J. KAHL
Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI

48824 USA

Abstract. The objective of this research was to compare changes in landscapes over time
where Golden-winged and Blue-winged Warblers were present and absent in the lower
peninsula of Michigan. To do this, the landscape composition (land cover types within
the landscape) and landscape structure (degree of fragmentation of land cover types)
along Breeding Bird Survey (BBS) routes where both species were present were
examined and compared to routes where they were absent in 1978, .1993, and 2000.
Differences in landscape composition and structure around 46 BBS routes were
compared using classified land cover data from 1978, 1993, and 2000. A GIS was used
to create a 400-meter buffer around BBS routes. Total area and area-perimeter ratios for
12 landscape composition and 12 landscape structure variables were calculated within
each buffered area. Principal components analysis explained covariation patterns across
multiple landscape composition and structure variables. Analysis of variance was used to
test the significance of each principal component. Results show that both Golden-winged
and Blue-winged Warblers are moving northward. Potential causes of range shift for the

Golden-winged Warbler may be due to increased human influence and increased

fragmentation of land cover types they find favorable. Blue-winged Warblers may not be
as negatively affected by these factors.
Key words: Golden-winged Warbler, Blue-winged Warbler, landscape ecology, breeding

range, Michigan, area-perimeter ratio.

INTRODUCTION

Human alteration of land cover can cause changes in landscape composition and
structure that result in loss of biodiversity. For many Neotropical migratory songbird
species, loss in land cover diversity may lead to geographical shifts in their breeding
ranges. Globally, breeding ranges for many birds and mammals are beginning to shift to
the north (Parmesan and Yoke, 2003). These geographical changes in breeding range
location may be the result of shifts in the geographic locations of favorable habitats
within the landscape. Habitat is defined as the resources and conditions present in an
area that affect occupancy by a species (Morrison, 2002). Many different habitats may be
are contained within a landscape. Landscapes are defined as spatially heterogeneous
areas (Morrison, 2002). The term landscape will be discussed as a large-scale area, and
as perceived by Golden-winged and Blue-winged Warblers.

The boundaries of the Golden-winged Warbler (Vermivora chrysoptera) range are
shifting northeastward, abundance is decreasing within the breeding range, (Confer and
Larkin, 1998) and the total area of the geographic range is shrinking (Gill, 1980; Will,
1986; Brewer, 1991). Blue-winged Warbler (V. pinus) abundance is declining, although
not quite as sharply, and its breeding range is expanding as it spreads northeastward

(Short, 1962; Gill and Murray, 1972; Confer and Knapp, 1979). For the Golden-winged

10

Warbler and the Blue-winged Warbler, the cause of their northeastward shifts could be
one or a combination of the following: changes in landscape structure and composition of
breeding range, Golden-winged Warbler competition with the potentially dominant Blue-
winged Warbler for resources, or climate change.

If loss of suitable landscape composition and/or landscape structure is the reason
Golden-winged and Blue-winged Warblers are shifting north and becoming locally
extinct at the southern edges of the breeding range, what is happening at local and broad-
scale levels at those edges? Populations at the edges of the range may be especially
affected by human alteration of landscapes if they have already been reduced to low
numbers by previous environmental changes (Maurer and Taper, 2002). Loss of habitat
due to human alteration may be one of the main causes for overall population decline and
potentially for range shift. Therefore we need to consider the way in which species react
to their environment where increased human influence is present.

Population dynamics within a species geographic range are complex. Species are not
evenly distributed within their range. Rather, population abundance follows a spatial
pattern determined by availability of suitable habitat within a range (Brown, 1984;
Hengeveld, 1990; Maurer and Taper, 2002). Patches of high species abundance exist
where resources are most favorable and tend to be positioned toward the central part of
the range, with other localized patches of suitable habitat radiating around and away from
the central region until abundance declines to zero toward the edges of the range (Maurer
and Taper, 2002; Brown et al., 1995; Maurer and Villard, 1994; Lawton, 1993). As
increased anthropogenic disturbance affects the southern edges of the range boundaries,

species may tend to move northward into habitats that have not been as disturbed. These

11

northern landscapes may have slightly different habitat compositions, making large-scale
conservation efforts for the species difficult. Are individuals of each species choosing
these new areas because they prefer the habitat within the landscape(s), or are these new
areas of their ranges “second choice” because they have been pushed out of previous
areas of their range due to anthropogenic influences or competition?

Global climate change may be playing a role in these shifts (Root et al., 2003).
Global average temperatures have increased by approximately 06° C in the past decade
and already many birds and mammals have responded by changing their movement
patterns (Root et al., 2003, Parmesan et al., 2003). Paired with other ecological stressors,
the increased, rapid warming trend could completely change bird community dynamics
over time. However, this issue is not the focus of this study. Rather, examining how
landscapes have changed and consequently, how the species’ presence and absence have
changed within the landscape, is the focus at hand.

This said, studying areas and patterns of local abundance and local extinction allows
us to better understand how landscape structure and composition affect species habitat
selection and movement patterns. Proactively monitoring and correlating changes in
habitat with species abundance over time is an effective way to estimate the future
distribution of a species and in which geographic areas conservation efforts should be
focused.

The objective of this research is to compare changes in landscapes over time where
Golden-winged and Blue-winged Warblers are present and absent. To do this, landscape

structure and composition of BBS routes in the lower peninsula of Michigan that were

12

inhabited by these warblers during 1978, 1993, and 2000 were examined and compared
to similar BBS routes in all years that were not used by the species.
METHODS

To identify landscapes used by Golden-winged and Blue-winged Warblers in 1978,
1993, and 2000, standardized surveys conducted in each year were used. North
American Breeding Bird Surveys (BBS) are conducted during the peak of the nesting
season, primarily in June in Michigan. Each route is 39.4 km (24.5 miles) long, with 50
stops located at 0.8 km (0.5 mile) intervals along the route. A three-minute point count is
conducted at each stop, during which the observer records all birds heard or seen within a
0.4 km (0.25 mile) radius of the stop (USGS Patuxent Wildlife Research Center,
http://monitoring2.er.usgs.gov/bbs/).

Michigan BBS route data for 46 active routes in the lower peninsula were hand-
digitized by the Kalamazoo Nature Center research department using GPS points taken at
each stop by the individuals that survey these routes (Fig 1.a.). Michigan was in the
process of digitizing their BBS routes at the start of this research. At that time, 46 out of
the 57 routes in the lower peninsula were completed, therefore setting the number of
routes I was able to use. Changes in landscape composition and structure were analyzed
along these 46 routes using a classified land cover data source for each year: 1978, 1993,
and 2000. To assess change in land cover over time, classified images for 1978 were
compared to 1993 in the northern lower peninsula, and for 1978 and 2000 in the southern
lower peninsula. I calculated land cover change in the northern lower peninsula using 19

routes and in the southern lower peninsula using 27 routes. The decision to use two

13

different land cover classifications from two different years for the second time period
was brought about by the lack of a single, current, classified coverage of the entire state.

Michigan Resource Information System (MIRIS) images provided classified land
cover data for 1978. Coverages were derived by county from 124,000 scale color-
infrared and black-and-white aerial photographs and used to identify 52 land cover
classes (MIRIS, http://www.ciesin.org/datasets/mirisbase/mirisbase-home.htrnl).

Classified land cover data for the northern lower peninsula in 1993 and the southern
lower peninsula in 2000 were obtained from the Michigan Department of Natural
Resources (MDNR) and were developed for the Michigan Gap Analysis Project
(http://www.dnr.state.mi.us/spatialdatalibrarv/metadata/2000_slp_landcover.htm;
http://wwwdnnstate.mi.us/spatialdatalibrafl/metadata/lul993_nlj_;_nygr.htm). Land
cover for both 1993 and 2000 were derived from classification of Landsat Thematic
Mapper imagery and used to identify 32 land cover classes for 1993 and 30 classes for
2000. Data for these two years are in the Michigan Georef coordinate system with a 30-
meter resolution.

Since the original classifications for 1978, 1993, and 2000 coverages were each
categorized differently and each had a different number of classes, land cover
classification systems for each coverage were matched to MDNR “Current Use Inventory
Classification System Definitions” standards so that land cover change could be
unifome assessed between years (Michigan Department of Natural Resources, 1981;
http://www.crs.msu.edu/pdf/lclu/CUl.pdt). Matching classifications produced 20
common, aggregated land cover classes that were used for all years to note correlated

landscape composition and structure trends in the data and to recognize which cover

14

classes were pertinent to focus on for this study (Table 1). These 20 classes were further
aggregated to 12 classes, increasing the integrity of the data by merging similar classes
that had less data to those with sufficient data (Table 1). These classes were used for all
statistical analysis of landscape composition and structure variables. A variable
measuring diversity, or heterogeneity, of land cover types along BBS routes was
calculated using a Shannon-Weaver Index (Zar, 1996) with all 20 cover classes.

Using GIS, a 400-meter “buffer” was placed around each of the BBS routes (200
meters on each side of the route, ends of routes rounded). This buffer distance signified
the detectable range of birds from a BBS route. A distance of 400m is recommended by
the Golden-winged Warbler Atlas Project (which also studies Blue-winged Warblers) for
use in point count surveys designed to detect these species (S. Barker, Golden-winged
Warbler Project Coordinator, pers. comm). The buffer was used to clip out land cover
around BBS routes from classified coverages. Within each clip, I calculated the total area
and perimeter of each land cover class polygon. I dissolved common land cover class
boundaries so that a single, total area could be calculated for adjacent polygons of the
same cover class, for each cover class. Polygon areas and perimeters for each land cover
class were summed for each clipped BBS route for each time period.

For each landscape variable, two measurements were taken: landscape composition
(total area) and landscape structure (area-perimeter ratios). Landscape composition refers
to the different cover classes that make up the landscape. Landscape structure is defined
as the spatial configuration of land cover classes (i.e., size and shape of cover class
patches in relationship to each other on the landscape). Cover class refers to the

classification given to a particular land cover type; the land cover as interpreted by a

15

photo-interpreter. Land cover refers to what is interpreted to be on the ground, not
necessarily what the land is used for (by humans). Landscape composition was assessed
for the area of each land cover class around each BBS route per year using 1978, 1993,
and 2000 classified coverages. Landscape structure was assessed for each land cover
class in each time period by calculating the ratio of area to perimeter for every polygon of
each land cover class along a BBS route. When a cover class was not found along a
route, its area was entered as zero for that route, therefore making the area to perimeter
ratio equal to zero. I chose only non-zero area-perimeter ratios to use for structural
variable analysis. A high area to perimeter ratio for agricultural land would indicate
large, continuous tracts of agriculture around a route. A small area to perimeter ratio
would indicate smaller, more fragmented patches of agriculture around a route. An
additional landscape structure class, heterogeneity, was added to note diversity of land
cover along routes and used to see how it was associated with routes where species were
present and where they were absent.
STATISTICAL ANALYSIS

In addition to the univariate analysis described in the previous section, changes in the
landscape were also measured using multivariate analysis. Principal component analysis
(PCA) summarizes covariation among multiple variables (composition and structure) so
that patterns of covariation can be seen in the grouped land cover types that are
associated with the resulting principal components. Principal components analysis gave a
summary of the variance associated with landscape variables across BBS routes, whereas
correlations may have gone unseen using only univariate analysis. Instead of basing

conclusions on responses of single variables, PCA allows shows many factors responding

l6

to a combination of landscape composition and structure variables. It ranks variables on
a gradient of positive to negative scores so that response can be viewed in an ordered,
landscape context and more complete conclusions may be drawn.

Principal components analysis was run for all 12 landscape composition variables to
look for variance among habitat classes on routes where Golden-winged and Blue-
winged Warblers were present and where they were absent in 1978 and 1993 or 2000.
Each land cover type was scored and “ranked” along the positive to negative gradient.
For example, if a land cover class was positively associated with routes where species
were present, it was correlated with presence when all compositional variables were
analyzed for species presence-absence associations over time; that land cover class was
significantly associated with routes where the species was present in 1978 and/or 1993 or
2000.

Golden-winged and Blue-winged Warblers may not only be looking for a particular
habitat type while selecting a territory, they are also keying in on habitat structure.
Analysis of area-perimeter ratios for each cover type in 1978 and 1993 or 2000 examined
differences in patch size, or degree of fragmentation, along routes and how those
differences compared to where species were present and absent. Principal components
analysis was calculated for all non-zero habitat structure variables and heterogeneity to
examine how the variance between area-perimeter ratios for land cover classes, or the
degree of fragmentation for all land cover types, differed along routes between 1978 and
1993/2000 and where species were present and absent.

To see how both landscape composition and structure differed along routes over time

and how it affected where species were present and absent, the 12 composition classes,

17

five landscape structure variables that had non-zero area values, and heterogeneity were
analyzed together using PCA.

Analysis of variance (ANOVA) was performed on all univariate and multivariate
landscape variables. This test measured the relationships between all variables and the
two factors, year (1978 and 1993/2000) and species presence-absence (Golden-winged
and Blue-winged Warbler). This test was used to identify significant (p<0.05)
interactions or main effects between a landscape variable and one or both factors.
Significant univariate results were used to add support to significant findings in
multivariate relationships.

Analysis of variance was run separately for the first eight of 12 principal components
for the 12 composition variables, on the 5 landscape structure variables and
heterogeneity, and for the first eight of 12 combined composition and structure variables.
Results provided information on the statistical significance of each principal component
and therefore the “ranking” of land cover composition and structure variables associated
with routes where species were present and absent. Significant components were used to
make conclusions about how land cover around BBS routes differed over time and where
Golden-winged Warblers were present and absent.

For example, when a particular principal component for landscape structure variables
showed a statistically significant interaction between year and species presence, it was
implied that land cover on routes where the species was present was significantly
different for the two years and that therefore the structure of the land cover classes
positively associated with the component may have had a significant effect on the

presence of the species.

18

In 1978, Golden-winged Warblers were observed on BBS routes throughout the state,
although they were absent on many of the southern lower peninsula routes (Fig. lb). In
1993, Golden-winged Warblers were seen only in the northern lower peninsula and not at
all on southern lower peninsula routes, indicating a northward shift. Therefore a land
cover comparison for in the northern lower peninsula was made between routes in 1978
and 1993 (Fig. lb). Blue-winged Warblers were recorded on BBS routes throughout the
state in 1978, 1993, and in 2000. Although a northward shift in their occurrence can be
seen (Fig 1.c). Land cover comparison for Blue-winged Warblers was made between
1978 and 1993 in the northern lower peninsula and between 1978 and 2000 for the
southern lower peninsula.

Analyses were done in SAS (SAS Institute Inc., 1999). Mean total area and perimeter
of each landscape composition and structure class was calculated separately for all BBS
routes across years.

RESULTS
Differences among routes with and without Golden-winged Warblers

There was a significant interaction between year (1978, 1993) and Golden-winged
Warbler for compositional land cover variables along routes associated with principal
component 1 (Fig. 2). Noting the gradient of association on the y-axis and the
compositional land cover variables associated with it, routes with agriculture, open land,
and urban land covers were associated with absence of Golden-winged Warblers in 1978.
Routes with water and deciduous and coniferous forests were associated with presence in
1978. Note absence was associated with human-influenced land cover and presence was

associated with more “natural” land cover we would expect to find Golden-winged

l9

Warblers near. In 1993, routes where Golden-winged Warblers were present and absent
converged on the gradient; there were not distinguishable differences along the gradient
among land cover classes on routes where species were present and absent. Golden-
winged Warblers were just as likely to be on a route with agriculture, open land, and
urban land cover classes as on routes with more water, deciduous forest and coniferous
forest, suggesting that the landscape became more homogeneous over time. Data suggest
that in 1993 Golden-winged Warblers were present in landscapes with more agriculture
or open land or urban land cover and also on routes with less water, deciduous forest, and
coniferous forest. It is not possible to tell which land cover types are most “important” to
Golden-winged Warblers from this graph.

Total mean agricultural land cover on routes showed a significant main effect for
Golden-winged Warbler presence absence (Fig. 3). This graph indicates that Golden-
winged Warblers were not responding positively agricultural cover, with regard to the
convergence in figure 2. Golden-winged Warblers were found on routes with low areas
of agriculture regardless of year. There was a slight increase in presence, but it was not
significant. Therefore, because increased presence on routes in 1993 was likely not due
to agriculture cover, presence must have had more to do with the context of open land
and/or urban land cover classes were associated with on routes from 1978 to 1993.

Significant landscape structure variables for principal component 3 were different on
routes where Golden-winged Warblers were present and where they were absent (Fig. 4).
There was a significant main effect for Golden-winged Warbler presence-absence,
indicating only that there was a difference between GW presence and absence. Golden-

winged Warblers were found in landscapes with high area-perimeter ratios for agriculture

20

and deciduous forest and absent on routes with high area-perimeter ratios for shrub and
herbaceous covers. This suggests that they were present on routes with agriculture and
deciduous forest cover classes, but only if they were fragmented.

Landscape composition and structure associated with principal component 1 had a
significant interaction for Golden-winged Warbler presence and year (1978-1993)(Fig.
5). Agriculture composition as well as the area-perimeter ratios for agriculture, shrub and
herbaceous cover were high where on routes where Golden-winged Warblers were absent
in 1978. Coniferous and deciduous forest composition, nonforested wetland
composition, and heterogeneity classes had low principal component scores and were
associated with routes where Golden-winged Warblers were present in 1978. In 1993,
there was a convergence in composition and structure variables on routes where Golden-
winged Warblers were present and absent. Routes where Golden-winged Warblers were
present in 1993 had more heterogeneity associated with them than they did in 1978. This
may suggest that Golden-winged Warblers are choosing more heterogeneous landscapes.

In 1978, there was a distinct difference in presence-absence. In 1993, there was a
convergence toward more complex landscapes with less overall agriculture. Because
heterogeneity was the most heavily weighted variable in the PCA, this suggests that
Golden-winged Warblers were present in more complex landscapes in 1993 than in 1978.
However, Golden-winged Warblers were also absent in those same landscapes, but likely
for different reasons. Note that there was a bigger change in absence from 1978 tol 993
than in presence. The convergence in landscapes indicate that Golden-winged Warblers
were associated with low agriculture landscapes, but other human-related components in

the landscape may be part of the reason Golden-winged Warblers were choosing the

21

routes too. Agricultural land cover within the landscape may be undergoing increased
change due to other human-influenced uses (i.e. urban and open land increase).

In 1978, Golden-winged Warblers were present on routes in both the southern and
northern lower peninsula (Fig. lb). In 1993, they were only present in the northern
lower, but recorded throughout the northern region. However, in 2000, only one northern
route among the routes I sampled had Golden-winged Warblers present on it. My results
show that routes where Golden-winged Warblers were present consistently had little
agricultural land cover associated with them. When agriculture was present, it was often
highly fragmented. Routes in 1978 were less fragmented overall, and had more “natural”
cover classes associated with them.

Diflerences among routes with and without Blue-winged Warblers

There was a significant main effect for Blue-winged Warbler presence-absence on
routes with herbaceous land cover (Fig 6). Blue-winged Warblers were absent on routes
with large areas of herbaceous cover and present on routes with smaller areas of
herbaceous cover. The opposite would be expected since Blue-winged Warblers are
thought to use early successional classes like this one.

There was a significant interaction between year (1978 and 1993) and Blue-winged
Warbler presence-absence shown by principal component 2 for landscape composition
variables (Fig. 7). Routes that were positively associated with herbaceous, urban, and
nonforested wetland cover classes had Blue-winged Warblers on them in 1978. Routes
that had scrub-shrub wetland, deciduous forest, and agricultural land cover had few Blue-
winged Warblers present on them in 1978. Note that in 1993, Blue-winged Warblers

were present in landscapes that contained agriculture and absent on routes that did not.

22

A significant interaction for year (1978, 2000) and Blue-winged Warbler presence-
absence on southern routes, (principal component 7, Fig. 8) showed some land cover
classes that were associated with presence on northern routes in 1978 (Fig.7) to be
associated with absence on southern routes in 1978. In both 1993 (north, Fig. 7) and
2000 (south, Fig. 8), there was a change on routes that Blue-winged Warbler presence
and absence were associated with. Blue-winged Warbler presence was associated with
agriculture in the south in 2000. However, it was associated with urban land cover as
well. In the north, presence was also associated with agriculture. This indicates that
Blue-winged Warblers did not seem to be as disturbed by human- influenced landscapes
as Golden-winged Warblers were. Landscapes seemed to be changing away from what
Golden-winged Warbler presence was associated with, but Blue-winged Warblers did not
seem to be affected in the same way by landscape changes.

When only looking at significant main effects for year, changes. in land cover between
1978 and 1993 or 2000 showed the most change on routes where Blue-winged Warblers
were present. Increases in urban landscapes and decreases in agricultural land in the
southern lower peninsula seem to have been the biggest changes on these routes.
DISCUSSION

This study shows that landscape characteristics associated with the presence and
absence of Golden-winged and Blue-winged Warblers were different in1978 and 1993 in
the northern lower peninsula BBS routes and in 1978 and 2000 in the southern lower
peninsula BBS routes.

Routes in the southern lower peninsula showed increased presence of Blue-winged

Warblers from 1978 to 1993 (Fig 1.c). By 2000 however, it appears that Blue-winged

23

Warblers had pushed northward slightly. The possibility that competition for territories
or mates with Golden-winged Warblers has caused Golden-winged Warblers to move
north is supported by the fact that in 2000 no Golden-winged Warblers were recorded on
BBS routes in the southern lower peninsula and only one route in the north had a Golden-
winged Warbler recorded on it. Routes in the southern lower peninsula are more heavily-
dominated by human-influenced land cover classes than in the northern regions. Golden-
winged Warblers may be retreating northward to find these more secluded and less
fragmented landscapes. Blue-winged Warblers may be benefiting from Golden-winged
Warblers deserting the southern edges of their range, and thus moving northward as well,
retracting the southern edges of their ranges too. These ideas give support to a human-
driven cause for northward range shift. It could also be true that Blue-winged Warblers
are out-competing Golden-winged Warblers for resources and pushing them northward.
Regardless, data from these routes, which may not be a complete representative sample
of the Michigan landscape, but is a good “first look”, suggest that both species are
moving northward.

With increased human-influenced land cover classes associated with absence of
Golden-winged Warblers, the idea that human alteration of landscapes in Michigan are at
least partially to blame for the decline of the species and the northward breeding range
shift toward more ideal land cover within landscapes is supported. Those landscapes
associated with Golden-winged Warbler presence have declined in the southern lower
peninsula from 1978 to 2000. This would help to explain a northward shifting of the

southern boundaries of the range. It is possible that these landscape changes could be

24

enhancing the ability for Blue-winged Warblers to move into northern areas. This in turn
could be increasing the opportunity for competition with the Golden-winged Warbler.

I previously stated that the Blue-winged Warbler was decreasing 4.4% within the
southern portion of its breeding range. Note that this statement is not necessarily
indicative of the entire breeding range. Populations in the southern portion of the range
may be declining, but if the range as a whole is indeed shifting northward, populations in
the northern portions of the range may be increasing. However, data to show this is not
available at this time. Michigan is within the central to northern portion of the Blue-
winged Warbler range. Populations may be, or may be becoming, larger here than we
realize. Consider too, that Michigan is within the central to southern portion of the
Golden-winged Warbler range, therefore it would make sense that populations are
smaller and may continue to get smaller if Michigan doesn’t have the quality of habitat
that northern regions may have. Golden-winged Warblers may be moving northward in
search of better quality habitat or it may be getting “pushed” northward by the Blue-
winged Warbler

Landscapes associated with Golden-winged Warbler presence in 1978 were more
indicative of landscapes one would expect to find them in than they were in 1993. This
suggests a degradation of landscape quality for the species over time. Although these
species may prefer cover types that indeed are present in the landscape in any given year,
the proximity to and context of the ideal cover types must be in “natural” mosaics for the
birds to find them favorable.

Factors such as the presence of Blue-winged Warblers, predation, and Brown-headed

Cowbird (Molothrus ater) parasitism are natural factors associated with Golden-winged

25

Warbler decline (Confer, 1992). These factors may be exacerbated in landscapes
subjected to increased human-alteration. Understanding the human-induced factors that
contribute to decline, such as habitat alteration and loss of landscape diversity, may allow
for more ecologically informed decisions in developing urban and suburban landscapes.
The more we knowledge we have on a local and state-wide levels, the more it can be
applied to the large scale picture of what is happening with these birds. Management
agencies need to be aware of the population dynamics and what may be causing decline
and range shift so that they can prepare management plans with this information in mind.
Global warming threatens to be a contributing factor to many changes in population
dynamics. Continued rates of consumption of ozone-depleting substances by our
increasing population will likely continue this warming trend. The consequences on
population dynamics, such as northward range shift, will heighten and make conservation
of important landscapes harder to predict as we become more unsure of species response
to changing plant and animal communities.

Land cover characteristics on routes where Golden-winged Warblers were present
and absent showed significant changes from 1978 to 1993 and 2000. Generally these
changes indicated that the large differences between where they were present and where
they were absent in 1978 had disappeared in 1993 or 2000; the routes with land cover
composition and structure their presence was associated with were just as likely to be
associated with their absence over time.

The landscapes occupied by Golden-winged Warblers in 1978 were much more
indicative of the “natural” landscapes we tend to associate them with than were the

landscapes occupied in 1993. This indicates that the quality of Michigan landscapes has

26

deteriorated for Golden-winged Warblers over time. However, Blue-winged Warblers
don’t seem to be as negatively affected by these changes as Golden-winged Warblers.
Future Research

Land cover changes along BBS routes analyzed in this study have provided a picture
of landscape change patterns on only a small portion of these species’ ranges in
Michigan. Additional contemporary data on the distribution of these species in
Michigan, as well as historic and current land cover data, are needed for a more thorough
analysis of effects of land cover change over time on patterns of Golden-winged and
Blue-winged Warbler distribution.

To supplement the spatial limitations of using BBS routes located along secondary
roads, as this is likely not the best place to survey for Golden-winged and Blue-winged
Warbler populations, it would be useful to have supplementary land cover data from
“control routes” in other parts of the state to be able to truly assessland cover change in
Michigan. The “control routes” would be the same geographic distance (25 miles) as
BBS routes, with random turns (i.e not straight lines) and would be located in randomly
selected geographic areas for example. Selecting areas that are not along secondary roads
may give a more diverse and realistic representation of Michigan land cover and thus
Michigan land cover change.

Each year, more Golden-winged Warblers are observed in the upper peninsula of
Michigan. Including BBS routes in the upper peninsula and/or other supplementary data
on these species would add greater understanding to both land cover change in Michigan

as well as Golden-winged and Blue-winged Warbler population dynamics.

27

A new state-wide land cover classification has been released by the MDNR (April,
2003). Classification of raw Landsat satellite imagery, or other finer-scaled types of
imagery, are other options that could be accessed for additional land cover information.
Both of these options will provide further opportunity to more uniformly assess land
cover change from 1978 to the present.

BIBLIOGRAPHY

Brewer, R., GA. McPeek, R.J. Adams Jr. 1991. The Atlas of Breeding Birds of
Michigan. Michigan State University Press, East Lansing, MI

Brown, J. H. 1984. On the Relationship between Abundance and Distribution of Species.
American Naturalist 1242255-279.

Brown, J. H., D. W. Mehlman, and G. C. Stevens. 1995. Spatial variation in abundance.
Ecology 76:2028-2043.

Confer, J. L., and K. Knapp. 1979. The changing proportion of Blue-winged and Golden-
winged Warblers in Tompkins County and their habitat selection. The Kingbird:8-
l4.

Confer, J. L., and J. L. Larkin. 1998. Behavioral interactions between Golden-winged and
Blue-winged Warblers. Auk 1 15:209-214.

Confer, J.L. 1992. Golden-winged Warbler. In The Birds of North America, No. 20 (A.
Poole, P. Stettenheim, and f. Gill, Eds.) Philadelphia: The Academy of Natural
Sciences; Washington DC: the American Omithologists’ Union.

Gill, F. B., and B. G. J. Murray. 1972. Song variation in sympatric Blue-winged and
Golden-winged Warblers. The Auk 89:625-643.

Gill, F. B. 1980. Historical aspects of hybridization between Blue-Winged and Golden-

28

Winged Warblers. The Auk: A Quarterly Journal of Ornithology 97: 1-17.

Hengeveld, R. 1990. Dynamic biogeography. Cambridge University Press, Cambridge
[England] ; New York.

Lawton, J. H. 1993. Range, Population Abundance and Conservation. Trends in Ecology
& Evolution 8:409-413.

Maurer, B. A., and M. L. Taper. 2002. Connecting geographical distributions with
population processes. Ecology Letters 5:223-231.Maurer, 1994

Maurer, B. A., and M. A. Villard. 1994. Geographic variation in abundance of North
American birds. Research & Exploration 10:306-317.

Michigan Department of Natural Resources. 1981. Current use inventory classification
system definitions http://wwwcrsmsu.edu/pdf/lclu/CUI.pdf.

Michigan Gap Analysis Project. http://www.msu.edu/user/skillen1/MIGAP.htm

MIRIS. Michigan Resource Information System Base Maps.
http://www.ciesin.org/datasets/mirisbase/mirisbase-home.html

Morrison, ML. 2002. Wildlife Restoration Techniques for Habitat Analysis and Animal
Monitoring. Island Press. Washington, DC, 41-70.

Parmesan, C. and G. Yoke. 2003. A Globally Coherent Fingerprints of Climate Change
Impacts Across Natural Systems. Nature, 421 :37-42

Root, T.R., J .T. Price, K.R. Hall, S.H. Schneider, C. Rosennzweig, J .A. Pounds. 2003.
Fingerprints of Global Warming on Wild Animals and Plants. Nature 421257-60.

Will, T. C. 1986. The behavioral ecology of species replacement: Blue-Winged and
Golden-Winged Warblers in Michigan. Page 126. Biological Sciences. University

of Michigan, Ann Arbor, MI.

29

Short, L. L. J. 1962. The Blue-winged Warbler and Golden-winged Warbler in Central
New York. The Kingbird 12:59-67.

USGS Patuxent Wildlife Research Center, httpfl/monitoringZer.usgsgov/bbs/

Zar, J.H. 1996. Biostatistical Analysis, Third Edition. Prentice Hall. New Jersey, 39-42.

30

LIST OF TABLES

Table 1. Landscape Composition and Structure Classes.

Original (19 + heterogeneity) and aggregated (12 + heterogeneity) land cover class
descriptions for 1978, 1993, and 2000 images using MIRIS codes. Classes used to
analyze structure and composition of the landscape associated with differences in

Golden-winged and Blue-winged Warbler presence-absence.

31

TABLES

Table 1. Landscape Composition and Structure Classes.
Original (19 + heterogeneity) and aggregated (12 + heterogeneity) land cover class
descriptions for 1978, 1993, and 2000 images using MIRIS codes. Classes used to
analyze structure and composition of the landscape associated with differences in

Golden-winged and Blue-winged Warbler presence-absence.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

MIRIS Class Label Aggregated
Code Class
1100 Urban (residential) 1100
1200 Commercial, service, industrial, transportation, institutional 1100
1700 Extractive (mining, quarry) 1100
1900 Open land, outdoor recreation, parks, cemeteries 1900
2100 Agriculture (cropland, confined feeding, permanent pasture) 2100
2200 Vineyard, orchard ornamental 2100
3100 Herbaceous cover 3100
3200 Shrub cover 3200
41 10 Northern hardwoods 41 10
4120 Dominant oak/hickory 4110
4130 Dominant aspen, white birch and associates 4110
4140 Lowland hardwoods (ash, elm, soft maple, cottonwood, balm- 4110

of-Gilead, aspen, birch)
4210 Pine (white, red, jack, scotch, white spruce, black spruce, 4210
balsam fir, Douglas fir, larch, hemlock, managed Christmas
tree plantations (scotch, Douglas fir, blue spruce, white pine)
4230 Lowland conifers (cedar, black spruce, tamarack, balsam fir- 4210
white spruce, balsam fir, jack pine)
5000 Water (stream, lake, reservoir, Great Lakes) 5000
6110 Wooded wetlands 6110
6120 Scrub, shrub wetland 6120
6220 Nonforested wetland (aquatic bed, emergent, mud flats) 6220
7000 Barren (beach, riverbank, sand dune, exposed rock) 7000

 

 

 

32

 

LIST OF FIGURES

Figure l. Routes with and without Golden-winged and Blue-winged Warblers

l.a. Total BBS routes surveyed in 1978, 1993, and 2000.

lb. Golden-Winged Warblers were present throughout the state in 1978, recorded on
some routes in the northern lower peninsula in 1993, and not found on southern lower
peninsula routes in 2000. Land cover data was analyzed around routes for 1978 and 1993
to look at differences where Golden-winged Warblers were and were not present.

l.c. Blue-winged Warblers present on routes for 1978, 1993, and 2000. Land cover was
analyzed around routes for 1978 and 2000 to look at differences where Blue-winged
Warblers were and were not present

Figure 2. Landscape composition variables: Golden-winged Warbler. Significant
interaction between year and Golden-winged Warbler occurrence: 1978-1993 (F =6.00,
dfi=l, df2=37,p=0.0192)

Figure 3. Univariate landscape composition variables. Significant main effect for
Golden-winged Warbler: 1978-1993 (F=7.52, df1=l , df2=38, p=0.009)

Figure 4. Landscape structure variables. Note significant main effect for Golden-winged
Warbler: 1978-1993 (F=4.60, df,=1, df2=36, p=0.0387)

Figure 5. Landscape composition and structure variables. Note significant interaction
between Golden-winged Warbler and year: 1978-1993 (F =60, df1=1, df2=37, p=0.0192)
Figure 6. Herbaceous landscape composition. Significant main effect for Blue-winged

Warbler: 1978-1993 (F: 5.02, (If/=1, df2=38,p=0.0310)

33

Figure 7. Landscape composition variables: Blue-winged Warbler. Significant
interaction between year and Blue-winged Warbler: 1978-1993 (F = 4.63, df1=1 , df2=36,
p= 0.03 82)

Figure 8. Landscape composition and structure variables. Significant interaction

between year and Blue-winged Warbler: 1978-2000 (F=4.63, df1= l, df2=36, p=0.03 82)

34

FIGURES

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

1?! [I I l I! II I

i i
it . ir-
IfTri-ll III I ll Til

£5 ‘ flfltfif

l.a 1978 Routes 1993 NLP Routes 2000 SLP routes

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

44V"

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

{Til (E711 (ELI
Iii? 21335 413%

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

1.b 1978 GW present 1993 GW present 2000 GW present
I 3 ’ j l‘" i
i I I UT

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

vflrllll iE711 I
11 A]: I_I./ fl
I _I__L_L/

1.0 1978 BW present 1993 BW present 2000 BW present

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Figure l. Routes with and without Golden-winged and Blue-winged Warblers

l.a. BBS routes surveyed in 1978, 1993, and 2000.

lb. Golden-Winged Warblers were present in the northem- and southern lower
peninsulas in 1978, recorded on some routes in the northern lower peninsula in 1993, and
not found on any southern lower peninsula routes in 2000. Land cover change was
assessed between 1978 and 1993 on routes in the northern lower peninsula where
Golden-winged Warblers were present and absent.

l.c. Blue-winged Warblers present on routes for 1978, 1993, and 2000. Land cover was
analyzed between routes for 1978 and 1993 on routes in the northern lower peninsula
where Blue-winged Warblers were present and absent and around routes for 1978 and
2000 for the southern lower peninsula where Blue-winged Warblers were present and

absent.

35

 

Agriculture n=23
Open land 1 ~
Urban

Prin 1

-21

 

Water
Deciduous Forest
Coniferous Forest 1973

 

 

 

1993
Year

 

—O— GW Absent
+ Gw Present

 

 

 

Figure 2. Landscape composition variables: Golden-winged Warbler. Significant
interaction between year and Golden-winged Warbler occurrence: 1978-1993 (F =6.00,
df1=l , df2=3 7, p=0.0192). Sample sizes (number of routes sampled) are shown for each
year for all graphs.

1800

 

n=23
1600 -

1400 -

1200 -
n:
1000 -

aoo -
n=6
600 J

400 - "=3

200 ~

 

 

O

 

Mean Agricultural Land Cover on Routes (ha)

1978 1993

Year

 

—0— GW Absent
—o— GW Present

 

 

 

Figure 3. Univariate landscape composition variables. Significant main effect for
Golden-winged Warbler: 1978-1993 (F=7.52, df1=1, df2=38, p=0.009).

36

2.0

 

Agriculture A/P

 

 

 

 

 

 

Deciduous Forest NP 1 5 0724
1.0 -
0')
.E
d”.
0.5 -
n=3 --
0.0 ~
Shrub A/P i
Herbaceous A/P -045
1978 1993

Year

 

—0- GW Absent
+ GW Present

 

 

 

Figure 4. Landscape structure variables. Note significant main effect for Golden-winged
Warbler: 1978-1993 (F=4.60, dfi=1, df2=36, p=0.0387)

 

Agriculture

Agriculture A/P
Shrub NP 2 ‘
Herbaceous A/P

n=24

 

 

 

 

.E o -
i
.1 -4
Coniferous Forest _2 ,
Deciduous Forest
Nonforested Wetland
Heterogeneity '3
1978 1993
Year

 

—0— BW Absent
+ BW Present

 

 

 

Figure 5. Landscape composition and structure variables. Note significant interaction
between Golden-winged Warbler and year: 1978-1993 (F =6.0, df,=l, df2=3 7, p=0.0192)

37

Mean Herbaceous cover along routes(ha)

 

400

300 <

200 <

100 -I

 

 

n=1

 

1978 1
Year

 

—o— BWAbsent
+ BW Present

 

 

 

993

Figure 6. Herbaceous landscape composition. Significant main effect for Blue-winged
Warbler: 1978-1993 (F= 5.02, df1=1, df2=38, p=0.0310)

Herbaceous
Urban
Nonforested wetland

Scrub-shrub wetland
Deciduous Forest
Agriculture

Prin 2

 

0.5 ~

0.0 ~

-0.5 ~

-1.0 *

 

 

 

-2.0

1978 1993
Year

 

—0— BW absent
+ BW present

 

 

 

Figure 7. Landscape composition variables: Blue-winged Warbler. Significant
interaction between year and Blue-winged Warbler: 1978-1993 (F = 4.63, dfl=l , dfg=36,

p= 0.0382)

38

 

 

 

 

 

 

 

Open land
Scrub-shrub wetland 1.0 4
Wooded wetland o a ,
Shrub
06
04
[x
.g 0 2
a.
00
02
04
Agriculture .06 ,
Nonforested wetland
than '08
Herbaceous 1 978 2000

Year

 

—O— BW Absent
+ 8W Present

 

 

 

Figure 8. Landscape composition and structure variables. Significant interaction
between year and Blue-winged Warbler: 1978-2000 (F=4.63, df;= 1, df2=36, p=0.0382)

39

 

APPENDIX A

40

 

 

APPENDIX A. PCA eigenvector values for significant results

 

Figure 5. PC 1

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Landscape Structure and Eigenvector
Composition Variables Value
Heterogeneity 0458
Urban 0.012
Openland 0.160
Agriculture 0.373
Herbaceous -0.087
Shrub 0.121
Deciduous -0.237
Coniferous forest -0.319
Water -0.126
Wooded wetland 0.146
Scrub-shrub wetland -0.032
Nonforested wetland 0146
Urban AP 0.297
Agriculture AP 0.401
Deciduous AP 0.162
Herbaceous AP 0.302
Shrub AP 0.330
Figure 7: PC 2
Landscape Composition Eigenvector
Value
Urban 0.471
Open land 0.151
Agriculture -0.29l
Herbaceous 0.048
Shrub 0.089
Deciduous forest -0.058
Coniferous forest 0.181
Water 0.059
Wooded wetland 0.191
Scrub-shrub wetland 0.025
Nonforested wetland 0.450
Barren 0.391

 

 

 

41

 

Figure 2: PC 1

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Landscape Eigenvector
Composition Variable Value
Urban 0.471
Open land 0.150
Agriculture -0.29l
Herbaceous 0.480
Shrub 0.089
Deciduous forest -0.058
Coniferous forest 0.181
Water 0.059
Wooded wetland 0.191
Scrub-shrub wetland 0.025
Nonforested wetland 0.450
Barren 0.391
flure 4: PC 4
Landscape Structure Eigenvector
Variables (area- Value
perimeter ratios; AP)
Heterogeneity AP -0.197
Urban AP 0.453
Agriculture AP 0.398
Deciduous forest AP 0.428
Herbaceous AP 0.451
Shrub AP 0.460

 

 

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