UNIVERSITY OF CALGARY
Sibling Species and Secondary Contact: Habitat Use by Regionally Sympatric Alder
(Empidonax alnorum) and Willow Flycatchers (E. traillii) in Alberta
by
Sarah D. Hechtenthal
A THESIS
SUBMITTED TO THE FACULTY OF GRADUATE STUDIES
IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE
DEGREE OF MASTER OF SCIENCE
DEPARTMENT OF BIOLOGICAL SCIENCES
CALGARY, ALBERTA
APRIL, 2007
© Sarah Dawn Hechtenthal 2007
UNIVERSITY OF CALGARY
FACULTY OF GRADUATE STUDIES
The undersigned certify that they have read, and recommend to the Faculty of Graduate
Studies for acceptance, a thesis entitled “Sibling Species and Secondary Contact: Habitat
Use by Regionally Sympatric Alder (Empidonax alnorum) and Willow Flycatchers (E.
traillii) in Alberta” submitted by Sarah Dawn Hechtenthal in partial fulfilment for the
degree of Master of Science.
______Supervisor, M. Ross Lein, Department of Biological Sciences
______Steven M. Vamosi, Department of Biological Sciences
______Darren Bender, Department of Geography
______Steig Johnson, Department of Anthropology
______Date
ii ABSTRACT
Coexisting congeneric species often are segregated ecologically via resource partitioning. Sympatric sibling species provide the ideal situation for investigating resource partitioning and mechanisms of coexistence because of their recent common ancestry and great phenotypic similarity. Avian sibling species, such as Alder Flycatchers
(Empidonax alnorum) and Willow Flycatchers (E. traillii), are often segregated into
distinctive climate-vegetation zones, and are thus essentially allopatric during the
breeding season. However, secondary contact occurs where preferred habitats abut,
providing opportunities to study coexistence between recently-diverged species.
I quantified habitat use by Alder and Willow flycatchers in areas of local allopatry
and local sympatry in a region of secondary contact in southwestern Alberta. I measured
numerous variables pertaining to horizontal and vertical components of vegetation
structure and ground cover at three spatial scales on territories of each species. Using
both univariate and multivariate analyses, I tested for differences in habitat use between
the species within site types, and compared habitat use by each species between sites of
local sympatry and local allopatry to test for possible effects of coexistence.
I found numerous differences in habitat use between territories of each species in
local allopatry across all three spatial scales. They differed in the amount of water cover
and the structure and composition of vegetation on their territories. Alder Flycatcher
territories were located in dry areas and contained very tall, partially-dead bushes.
Willow Flycatcher territories were located in low-lying areas that always contained still or
moving water, saturated soil and mossy ground cover and low, wide, dense bushes. Local
iii coexistence of Alder and Willow flycatchers occurred only where environmental conditions produced a mosaic of habitats at the boundary of their respective ranges. When in local sympatry, the species vigorously defended interspecific territories. Although fewer significant differences in habitat use were detected than in allopatry, they remained microspatially segregated along the hydrological gradient at the sympatric sites.
Therefore, differential habitat use is probably the key factor in the ecological segregation of the species in areas of secondary contact.
Comparisons of habitat use between areas of local allopatry and areas of local sympatry revealed non-experimental evidence for an asymmetrical competitive relationship. Alder Flycatchers showed numerous differences in habitat use between the two site types at all scales of measurement, whereas Willow Flycatchers showed very little change in their habitat use whether in the presence of absence of their sibling species. The observed shift in habitat use by Alder Flycatchers in local sympatry may be the result of competitive displacement.
In the contact zone in eastern North America, Willow Flycatchers use dry, upland thickets and meadows and Alder Flycatchers use boggy to wet alder. My study suggests that the pattern of habitat use by the two species in their western range may be opposite to that shown by eastern populations. This is an unusual ecological and evolutionary phenomenon and is the first documentation of regional reversal of habitat use by sympatric species.
iv ACKNOWLEDGMENTS
I would like to thank M. Ross Lein, my supervisor, for his patience, scientific guidance, encouragement, and amazing editing expertise. I am also grateful to Steve
Vamosi and Darren Bender for serving on my thesis supervisory and examination committees and for adding many helpful comments and suggestions which improved my thesis. Steig Johnson also served on my thesis examination committee and offered useful comments.
This research was funded by the Challenge Grants in Biodiversity Program
(supported by the Alberta Conservation Association). Additional funding was provided by an operating grant from the Natural Sciences and Engineering Research Council of
Canada to MRL. I received support from the University of Calgary in the form of
Graduate Teaching Assistantships and Graduate Research Assistantships and was awarded a University of Calgary Graduate Entrance Scholarship, the Dennis Parkinson
Graduate Scholarship, and the Sharon Wilkens Teaching Excellence Award. I also received support from the Alberta government in the form of an Alberta Heritage
Graduate Scholarship and an Alberta Graduate Scholarship.
During my Master’s program, I presented my research at 123rd Stated Meeting of the American Ornithologists’ Union in Santa Barbara, CA in 2005, and the 4th North
American Ornithological Conference in Veracruz, Mexico in 2006. I received financial support to attend these meetings from the American Ornithologists’ Union, the North
American Ornithological Conference, the University of Calgary Graduate Student
Association , and University of Calgary Research Services.
v My field assistants (Jessie Malcolm, Erin Brock and Cecilia Kung) were
invaluable to this project, as were the numerous volunteers and friends who assisted me
in the field. Additional logistical support for field work was provided by the Kananaskis
Field Stations of the University of Calgary. The support staff at the research station,
especially Dave Billingham and Judy Buchanan-Mappin, were incredibly knowledgeable and helpful. I would also like to thank Alvin Kumlin and Terry Raymonds for allowing me to work on their private land.
I would very much like to acknowledge my academic peers for their comradery,
support, encouragement, and words of wisdom throughout my Master’s program. I feel
very fortunate to have worked with such intelligent, talented and fun-loving people.
Also, my phenomenal lab colleague, Scott Lovell, was a never-ending source of
knowledge and inspiration. My project was greatly improved by his comments and I will
miss our stimulating conversations about ornithology and life in general.
Finally, I am extremely grateful to all my friends and family who have spent hours
patiently listening to my musings about “my little green birds” and multivariate statistics.
I would especially like to thank my Mom. Her infinite courage and compassion has been
a constant source of inspiration to me. I thank her for her strength, support and love, and
for being a survivor.
vi TABLE OF CONTENTS
APPROVAL PAGE ...... ii ABSTRACT ...... iii ACKNOWLEDGMENTS ...... v TABLE OF CONTENTS ...... vii LIST OF TABLES ...... ix LIST OF FIGURES ...... xii
CHAPTER ONE: INTRODUCTION ...... 1 1. COEXISTENCE AMONG CONGENERIC SPECIES ...... 1 2. BIOLOGY OF EMPIDONAX FLYCATCHERS ...... 7 3. RESEARCH OBJECTIVES AND SCIENTIFIC SIGNIFICANCE ...... 10
CHAPTER TWO: METHODS ...... 12 1. BIOLOGY OF THE STUDY SPECIES ...... 12 A. Willow Flycatchers ...... 12 B. Alder Flycatchers ...... 20 2. STUDY AREAS ...... 25 A. 2004 Study Sites ...... 25 B. 2005 Study Sites ...... 28 3. BIRD-FOCUSED FIELD WORK ...... 30 A. Territory and Perch Assignment ...... 30 B. Nest Searching and Monitoring...... 31 4. HABITAT SAMPLING ...... 32 A. Sampling Methodology ...... 32 B. Habitat Variables ...... 37 i. Microplot...... 38 a. Song perch...... 38 b. Nest plant ...... 41 ii. Mesoplot...... 41 iii. Macroplot...... 44 5. DATA ANALYSIS ...... 45 A. Microplot...... 45 i. Song Perch...... 45 ii. Nest Plant...... 46 B. Mesoplot/Macroplot...... 47 i. Song Perch and Random Transects ...... 47 ii. Nest Plant...... 56
CHAPTER THREE: RESULTS ...... 57 1. ARRIVAL AND TERRITORIALITY ...... 57 2. SAMPLE SIZE ...... 59
vii 3. HABITAT USE AT THE MICROPLOT SCALE ...... 59 A. Song Perch...... 59 i. Differences Between Species in Allopatry ...... 62 ii. Differences Between Species in Sympatry ...... 67 iii. Differences Within Species Between Site Types ...... 68 B. Nest Plant...... 69 4. HABITAT USE AT THE MESOPLOT SCALE...... 71 A. Song Perch...... 71 i. Univariate Analyses...... 71 a) Differences between species in allopatry ...... 71 b) Differences between species in sympatry ...... 71 c) Differences within species between site types ...... 74 ii. Multivariate Analyses ...... 74 B. Nest Plant...... 83 5. HABITAT USE AT THE MACROPLOT SCALE ...... 84 A. Univariate Analyses...... 84 B. Multivariate Analyses ...... 87
CHAPTER FOUR: DISCUSSION ...... 96 1. HABITAT USE IN ALBERTA ...... 96 2. EFFECTS OF COEXISTENCE ...... 109 3. HABITAT USE ACROSS NORTH AMERICA ...... 118 4. CONSERVATION AND MANAGEMENT IMPLICATIONS ...... 122 5. SUGGESTIONS FOR FUTURE RESEARCH ...... 125 A. Hybridization Studies...... 125 B. Local Removal Experiments ...... 126 C. Ecological Niche Modelling ...... 126
BIBLIOGRAPHY ...... 128
APPENDIX 1: Summary of habitat variables measured at the microplot scale for song perches. Values shown as mean ± SE (top) and median in parentheses (below)...... 145
APPENDIX 2: Summary of habitat variables measured at the microplot scale for nest plants. Values shown as mean ± SE (top) and median in parentheses (below). Data for each species at the different site types were combined...... 146
APPENDIX 3: Summary of habitat variables measured at the mesoplot scale for song perches. Values shown as mean ± SE (top) and median in parentheses (below)...... 147
viii APPENDIX 4: Summary of habitat variables measured at the mesoplot scale for nest plants. Values shown as mean ± SE (top) and median in parentheses (below). Data for each species at the different site types were combined...... 149
APPENDIX 5: Summary of habitat variables measured at the macroplot scale for song perches. Values shown as mean ± SE (top) and median in parentheses (below)...... 150
ix LIST OF TABLES
TABLE TITLE PAGE
2.1. Microplot habitat features measured from the song perch or nest plant on individual bird territories...... 39
2.2. Habitat features measured on the 10-m transects centered around each song perch or nest plant (mesoplot) and on random transects (macroplot). Mean calculated from four transects (either mesoplot or macroplot transects)...... 42
2.3 Summary of original habitat variables measured around song perches at the mesoplot scale. A Pearson’s r > | 0.6 | between a pair of variables resulted in one variable being dropped from the analysis...... 48
2.4 Summary of original habitat variables measured around song perches at the macroplot scale. A Pearson’s r > | 0.6 | between a pair of variables resulted in one variable being dropped from the analysis...... 49
2.5 Summary of transformations on mesoplot song perch habitat variables. Results from test of normality (Shapiro-Wilk) and equal variances (Levene test) also shown. Variables meeting parametric requirements shown in bold face...... 51
2.6 Summary of transformations on macroplot song perch habitat variables. Results from test of normality (Shapiro-Wilk) and equal variances (Levene test) also shown. Variables meeting parametric requirements shown in bold face...... 52
3.1 Summary of study sites...... 61
3.2 Summary of univariate analyses examining differences between Alder Flycatcher and Willow Flycatcher song perches at the microplot scale. Parts (A) and (B) report differences in habitat use between the species at the different sites types, and parts (C) and (D) report differences in habitat use by each species between the different site types...... 63
3.3 Summary of univariate analyses examining differences between Alder Flycatcher and Willow Flycatcher nest plants at the microplot scale. Because of small sample sizes, data from both site types were combined for each species...... 70
x 3.4 Summary of univariate analyses (ANOVA and Kruskal-Wallis) on the transformed mesoplot habitat variables testing for differences among the four species/site type categories...... 72
3.5 Summary of multiple pairwise comparisons (with Dunn-Sidak corrections) of song perch variables at the mesoplot scale. Comparisons between the species at the different site types and between site types for each species are shown...... 73
3.6 Varimax rotated factor loadings for the ten song-perch habitat variables on the three principal components at the mesoplot scale. Eigenvalues and percentages of total variance explained by each principal component are shown...... 75
3.7 Summary of MANOVA analyses of the PC scores at the mesoplot scale. Results are reported for differences among all four species/site type categories (full dataset) in addition to differences between the species within a particular site type, and differences within a species between the site types...... 82
3.8 Summary of univariate analyses (ANOVA and Kruskal-Wallis) on the ten transformed macroplot habitat variables testing for differences among the four species/site type categories ...... 85
3.9 Summary of multiple pairwise comparisons (with Dunn-Sidak corrections) of song perch variables at the macroplot scale. Comparisons between the species at the different site types and between site types for each species are shown...... 86
3.10 Non-rotated factor loadings for the ten song-perch habitat variables on the three principal components at the macroplot scale. Eigenvalues and percentages of total variance explained by each principal component are also shown...... 88
3.11 Summary of MANOVA analyses of the PC scores at the macroplot scale. Results are reported for differences among all four species/site type categories (full dataset) in addition to differences between the species within a particular site type, and differences within a species between the site types...... 94
xi LIST OF FIGURES
FIGURE TITLE PAGE
2.1 Breeding distribution of Willow Flycatchers in North America (modified from Sedgwick 2000)...... 13
2.2 Breeding distribution of Willow Flycatchers (left) and Alder Flycatchers (right) in Alberta. Data points generated from Federation of Alberta Naturalists breeding database (1973 - present)...... 15
2.3 Breeding ranges of Willow Flycatcher subspecies: (A) E. t. brewsteri; (B) E. t. adastus; (C) E. t. extimus; (D) E. t. campestris; (E) E. t. traillii (modified from Browning 1993)...... 17
2.4 Breeding distribution of Alder Flycatchers in North America (modified from Lowther 1999)...... 22
2.5 Circled area indicates zone of regional sympatry between Alder and Willow flycatchers in southwestern Alberta. Data points generated from Federation of Alberta Naturalists breeding database (1973 - present). The City of Calgary is shown (hatched area), along with major rivers ...... 23
2.6 Map of all study sites used during the 2004 and 2005 breeding seasons. The City of Calgary is shown (hatched area) along with major roads. Lower map shows 2004 study sites along Sibbald Creek Trail ...... 26
3.1 Willow Flycatcher (line polygons) and Alder Flycatchers (dotted polygons) territories at the Bryant Creek site. Birds defended stable, exclusive territories that were generally non-overlapping. Habitat features, including beaver ponds, creeks, and forest boundaries are shown. Not all territories shown were sampled ...... 60
3.2 Mean scores (± SE) on the first three principal components for each species/site type category at the mesoplot scale. Y-axis labeled according to the highest component loadings for variables...... 77
3.3 Bivariate scatterplot of PC1 scores vs. PC2 scores at the mesoplot scale. Points for individual territories are indicated by symbols as follows: ALOALFL (circle); ALOWIFL (X); SYMALFL (triangle); and SYMWIFL (square). Group centroids for each species/site type category are indicated with a 95% confidence ellipse. Ellipses are identified by a two-letter
xii abbreviation as follows: ALOALFL (AA); ALOWIFL (AW); SYMALFL (SA); and SYMWIFL (SW)...... 79
3.4 Bivariate scatterplot of PC1 scores vs. PC3 scores at the mesoplot scale. Points for individual territories are indicated by symbols as follows: ALOALFL (circle); ALOWIFL (X); SYMALFL (triangle); and SYMWIFL (square). Group centroids for each species/site type category are indicated with a 95% confidence ellipse. Ellipses are identified by a two-letter abbreviation as follows: ALOALFL (AA); ALOWIFL (AW); SYMALFL (SA); and SYMWIFL (SW)...... 80
3.5 Mean scores (± SE) on the first three principal components for each species/site type category at the macroplot scale. Y-axis labeled according to the highest component loadings for variables...... 89
3.6 Bivariate scatterplot of PC1 scores vs. PC2 scores at the macroplot scale. Points for individual territories are indicated by symbols as follows: ALOALFL (circle); ALOWIFL (X); SYMALFL (triangle); and SYMWIFL (square). Group centroids for each species/site type category are indicated with a 95% confidence ellipse. Ellipses are identified by a two-letter abbreviation as follows: ALOALFL (AA); ALOWIFL (AW); SYMALFL (SA); and SYMWIFL (SW)...... 91
3.7 Bivariate scatterplot of PC1 scores vs. PC3 scores at the macroplot scale. Points for individual territories are indicated by symbols as follows: ALOALFL (circle); ALOWIFL (X); SYMALFL (triangle); and SYMWIFL (square). Group centroids for each species/site type category are indicated with a 95% confidence ellipse. Ellipses are identified by a two-letter abbreviation as follows: ALOALFL (AA); ALOWIFL (AW); SYMALFL (SA); and SYMWIFL (SW)...... 92
4.1 Resource utilization curves for the habitat variable SQRTSTEMS. Top graph shows resource curves for allopatric territories and bottom graph shows resource curves for sympatric territories...... 104
xiii 1
CHAPTER ONE
INTRODUCTION
1. COEXISTENCE AMONG CONGENERIC SPECIES
Coexisting congeneric species, which have been a major focus of community ecology for over half a century, often are ecologically segregated via resource partitioning
(MacArthur 1958, Catchpole 1973, Cody 1985, Rotenberry 1985, Price et al. 1997,
Tokeshi 1999, and see reviews by Schoener 1974 and Wiens 1989a). The ecological segregation of potentially-competing species along resource axes, usually involving several dimensions such as habitat, food and time, results in decreased overlap in resource use which is believed to provide a means for coexistence (Lack 1971, Jones et al. 2001, Naoki 2007). Members of bird assemblages (i.e., congeneric species occurring in the same place at the same time [Fauth et al. 1996]), typically show resource partitioning along habitat or foraging axes. Familiar examples include New World wood warblers (Dendroica), which coexist in spruce forests and partition their foraging niches by using different parts of the tree canopy and consuming different foods throughout the breeding season (MacArthur 1958, Lovette and Bermingham 1999). Similarly, sympatric
Mountain Chickadees (Poecile gambeli) and Black-capped Chickadees (P. atricapillus) in southern Alberta forage on different species of trees at different levels in the canopy and differ in their choice of nest sites (Hill and Lein 1988). Differences in morphology, especially in trophic structures, may also enable coexistence in congeneric avian species by allowing them to specialize on particular food resources. For example, species of 2
Galapagos ground finches (Geospiza spp.) consume seeds of different sizes and densities based on their beak morphology and segregate accordingly into different foraging niches
(Grant 1986). Other sympatric avian congeners that have been shown to partition resources in their shared habitat include New World orioles (Icterus, Omland 1999) and tanagers (Tangara, Burns 1997, Naoki 2007).
Resource partitioning among coexisting congeners has been demonstrated consistently for a range of taxa and is a widely-accepted ecological phenomenon.
However, attempts to identify the driving mechanisms involved in this partitioning of resources, especially understanding the role of interspecific competition, have been less straightforward. Two major processes that lead to resource partitioning among species have been identified: (1) interspecific competition either active at present or having played some role in the past (the “ghost of competition past” [Connell 1980]) or; (2) differential resource use as a result of independent evolutionary histories. Of course, these mechanisms are not mutually exclusive and can act together to shape geographic distribution patterns, regional distribution patterns, and local assemblages of closely- related species.
In the first case, ecological segregation is the result of competition for resources within a shared habitat. Here, coexisting congeners interact and influence each others’ patterns of resource use and acquisition, behaviours and/or interactions with other species such as predators and parasites. These interactions may have direct fitness consequences for individuals (Lenington and Scola 1982, Cody 1985, Block and Brennan 1993, Martin and Thibault 1996, Martin and Martin 2001b, Martin and Martin 2001a, Hofer et al. 3
2004, Sedlacek et al. 2004). Interspecific territorial exclusion at sites of sympatry commonly is viewed as a form of competition because it allows the species to partition resources spatially and, in extreme cases, can lead to competitive displacement (Schoener
1974, Prescott 1987, Sherry and Holmes 1988, Dhondt 1989, Wiens 1989a, Martin and
Martin 2001b, Martin and Martin 2001a). If interspecific competition is the primary mechanism driving differential resource use by sympatric species, then one species should expand or shift its range of resource use where the other is absent. It is believed that interspecific competition can shape the geographic distribution patterns of congeneric species by preventing species from occupying certain regions or habitats (Remsen and
Cardiff 1990).
In the second case, coexisting species use resources independent of any ecological interaction with congeners, and ecological segregation is the result of physiological, morphological, or behavioural differences among the species because of different evolutionary histories (Catchpole 1973, Rotenberry 1985, Rosenzweig 1991, Block and
Brennan 1993, Martin and Thibault 1996, Tokeshi 1999, Martin and Martin 2001b,
Sedlacek et al. 2004). In such cases, each species typically segregates spatially into different microhabitats (e.g., use different plant species for nesting, or plant structures for foraging). The use of specific resources by each species may have evolved as species- specific functional adaptations to different environments (Arlettaz 1999). If resource use and geographic distributions are shaped mainly by environmental factors, then resource use by one species should remain unchanged in the presence or absence of congeners. 4
The importance of both differential resource use and interspecific competition in
determining distribution patterns and abundance of coexisting congeneric species on a
local scale has been a controversial issue in ecology (Schoener 1974, Rotenberry 1981,
Schoener 1983, Alatalo et al. 1986, Wiens 1989a, Rosenzweig 1991, Remsen Jr. and
Graves 1995, Tokeshi 1999). In part, this is because experiments, such as removal
experiments, provide the most unambiguous evidence for the presence and effects of
interspecific competition between sympatric species, but are not often feasible or
permitted (in the case of endangered or threatened species). Consequently, comparative,
correlational studies based on observations, or “natural experiments”, are used commonly
in the study of species coexistence (Alatalo et al. 1986, Wiens 1989a, Arlettaz 1999).
Natural experiments comparing patterns of resource use between coexisting species are
most successful when conducted on closely-related and ecologically-similar species.
Therefore, studies on sympatric sibling species (i.e., biological species that are almost
indistinguishable phenotypically from their closest relatives) are of great interest. These
species pairs are expected to represent the extreme along a gradient of ecological
similarity because of their recent common ancestry and great phenotypic similarity.
Investigations of resource-use patterns among sympatric sibling species are most likely to
reveal important aspects of species coexistence and to help to elucidate mechanisms of
coexistence (Tokeshi 1999, Naoki 2007).
Sibling species typically show one of two distinctive patterns of geographic
distribution. The species may coexist over much of their geographic ranges and live in direct contact with each other, or they may have largely non-overlapping geographic 5 distributions and coexist rarely within the same region. Several examples of the first distribution pattern come from sibling species of insectivorous bats. These bats have been studied intensively because they often occupy the same roosts and thus are likely to compete for resources. In these situations, each species exploits a distinctive trophic niche and is spatially segregated into a species-specific foraging habitat (Arlettaz et al.
1997, Arlettaz 1999, Davidson-Watts et al. 2006). Both dietary and habitat partitioning are believed to permit stable coexistence between sibling species at sympatric roost sites.
Inter-specific competition is not likely responsible for the observed resource partitioning because there is no evidence for any shifts in resource use between sympatric and allopatric populations. Instead, subtle differences in the auditory capabilities of each species may influence the prey items that are consumed and, subsequently, the microhabitats that are used for foraging (Arlettaz 1999).
The second distribution pattern is observed commonly among sibling species of ants (Dietrich and Wehner 2003), frogs (Graham et al. 2004), rodents (Anderson et al.
2002) and birds (Johnson and Cicero 2002, Cicero 2004). In these cases, the species tend to occupy distinctive climate-vegetation zones and thus have largely non-overlapping geographic distributions (Anderson et al. 2002, Johnson and Cicero 2002, Dietrich and
Wehner 2003). Avian sibling species typically have allopatric or parapatric breeding distributions and narrow zones of contact at the borders of their geographic ranges (i.e., where the distinctive climate-vegetation zones of each species abut) (Cicero 2004).
Examples include Baeolophus titmice (Cicero 2004), Empidonax flycatchers (Johnson
1978, Johnson and Cicero 2002), Calandrella larks (Serrano and Astrain 2005), and 6
Polioptila gnatcatchers (Atwood and Bontrager 2001). Sibling-species pairs in these avian genera show well-developed habitat specificity. Therefore, habitat, or microhabitat, partitioning would be expected to occur in areas of secondary contact as the result of different habitat requirements and evolutionary histories.
Studies of avian habitat use have been extremely useful for understanding the ecological and evolutionary factors that determine patterns of occurrence, distribution, and abundance of birds (Holmes 1981, Cody 1985, Wiens 1989a, Rosenzweig 1991,
Block and Brennan 1993). In this context, the term “habitat” refers to the set of biotic and abiotic factors in the environment of a species that it uses for its survival and reproduction (Karr 1981, Block and Brennan 1993). “Habitat use” is the way in which a species uses habitats to meet each of its life history needs such as foraging, nesting, predator avoidance, mate attraction, etc. (Jones 2001). Studies of habitat use in birds are often non-experimental and comparative. These studies examine broad-scale distribution patterns of congeners (Remsen and Cardiff 1990, Remsen and Graves 1995, Cintra 1997,
Peterson 2006), as well as patterns of habitat use by each species under sympatric and allopatric conditions. Comparative studies of sibling species in recent secondary contact require that two criteria to be met. First, a robust molecular phylogeny is needed to confirm sibling-species status of the study species. Second, these studies require that the species are locally sympatric in some areas (i.e., in direct contact). Often, when breeding ranges of sibling species overlap on a regional scale (i.e., regional sympatry), the species remain ecologically segregated in different habitats, and are thus not in direct contact. It is only in areas where the species coexist at a local scale (i.e., local sympatry) that 7 comparative studies on resource use and ecological interactions are possible. Sibling species in the genus Empidonax meet both of these criteria. A complete molecular phylogeny based on mitochondrial DNA is well-established for the genus Empidonax and indicates that this genus contains numerous pairs of sibling species that do occasionally breed in local sympatry (Cicero and Johnson 2002, Johnson and Cicero 2002).
2. BIOLOGY OF EMPIDONAX FLYCATCHERS
New World flycatchers of the genus Empidonax (Passeriformes: Tyrannidae) are well-known for their interspecific similarity in morphology and plumage and, hence, for their difficulty of identification. They are aerial insectivores and most species in this genus exhibit “striking ecological segregation into distinctive climate-vegetation zones”
(Johnson and Cicero 2002). Consequently, they have largely-allopatric or parapatric breeding distributions. Where species ranges do overlap with congeners, occupancy of the same habitat is rare. Local coexistence does occur where their preferred habitats abut and overlap. In these situations, coexistence has been explained by various mechanisms, including interspecific competition (Beaver and Baldwin 1975, Prescott 1987, Winker
1994), and differential use of habitats (Johnson 1966, 1978, Barlow and McGillivray
1983, Sakai and Noon 1991, Cicero and Johnson 2002, Johnson and Cicero 2002).
During the breeding season, five species of Empidonax flycatchers breed in southern Alberta, but most are segregated into distinctive breeding habitats. Least
Flycatchers (E. minimus) use deciduous or mixed woodland habitat, while Dusky
Flycatchers (E. oberholseri) use montane chaparral in open forests, and Cordilleran 8
Flycatchers (E. occidentalis) use shady canyons in coniferous or mixed forests. Alder
Flycatchers (E. alnorum) and Willow Flycatchers (E. traillii) are the exceptions. They
appear to use very similar habitats, and have been found breeding on contiguous
territories at several sites in southwestern Alberta.
Alder and Willow flycatchers exhibit remarkable phenotypic and ecological
similarity. They can be identified reliably in the field only by their distinctive
vocalizations. They were classified as two song forms of the same species until 1973
when they were recognized formally as sibling species (American Ornithologists' Union
1973). Their separation was based on behavioural and ecological differences (e.g.,
distinctive vocalizations and different geographic distributions, habitat use, and nesting
ecologies) (Stein 1958, 1963). Genetic analyses confirmed that they are sister species and
exhibit one of the lowest mtDNA sequence divergences in the genus Empidonax, along
with identical chromosomal morphology (Winker 1994, Johnson and Cicero 2002).
Alder and Willow flycatchers come into secondary contact during the breeding
season in several areas along the Canadian - United States border. The first documented
case of sympatry was in New York in 1931, then in Toronto in 1953 (Stein 1958, 1963).
In the west, there are no data about the timing of secondary contact although sympatric
populations were observed in British Columbia in the early 1960s (Stein 1963).
However, these dates are highly speculative because identification of these species in the field is difficult and many of the reports of sympatry occurred prior to the species being formally separated, and are thus not reliable. Recent studies from confirmed regions of secondary contact in eastern Canada have shown that, despite their phenotypic similarity, 9 the species remain reproductively isolated (Seutin and Simon 1988, Winker 1994). These studies found no evidence of hybridization and genetic isolation is believed to be maintained by interspecific territoriality and recognition of heterospecific song (Prescott
1987, Seutin and Simon 1988, Winker 1994).
In the eastern zone of sympatry, no significant interspecific differences in any aspect of foraging ecology, foraging behaviour, or foraging-related morphology have been reported (Barlow and McGillivray 1983, Seutin 1991). Because Alder and Willow flycatchers are both aerial insectivores, many aspects of their foraging ecologies are constrained by the specific requirements of this foraging mode and thus ecological overlap along this particular niche axis will be high (Hespenheide 1971, Beaver and
Baldwin 1975, Richman and Price 1992, Price et al. 1997). Consequently, differential habitat use is probably the key factor in the ecological segregation of the species in areas of recent secondary contact. Accordingly, the coexistence of these two sibling species can be explained best by differences in habitat composition or structure on their territories.
In the east, the preference of Willow Flycatchers for dry, upland willow (Salix spp.) thickets and meadows and of Alder Flycatchers for boggy to wet alder thickets is well-documented (Stein 1958, 1963, Zink and Fall 1981, Barlow and McGillivray 1983,
Cadman et al. 1987, Peck and James 1987, Lowther 1999, Sedgwick 2000). The few studies conducted on the species in the west show a pattern of habitat use different from that observed in the east. In Washington and British Columbia, Willow Flycatchers were found living under wet to very wet conditions (Frakes and Johnson 1982, Campbell et al. 10
1997). Little information is available for breeding habitats of Willow Flycatchers and
Alder Flycatchers in Alberta. Kulba and McGillivary (2001) found Willow Flycatchers breeding in wet, low-lying areas in Alberta and found no evidence of use of dry, upland habitats (see Kulba and McGillivray 2001 for full habitat description). Alder Flycatchers can be found in moderately moist habitats in Alberta but have been commonly observed using dryer sites than elsewhere in Canada (M.R. Lein, pers. comm.). This suggests that the pattern of habitat use by the two species in their western range may be reversed from that shown by eastern populations. If verified, this would be the first documentation of regional reversal of habitat use by sympatric species.
3. RESEARCH OBJECTIVES AND SCIENTIFIC SIGNIFICANCE
My first objective was to describe and quantify habitat use by Alder and Willow flycatchers in areas of local allopatry and local sympatry in the zone of secondary contact in southwestern Alberta. On breeding territories of each species, I quantified a number of biotic factors pertaining to the specific horizontal or vertical components of vegetation structure and ground cover (i.e., microhabitat) within the overall habitat types that were used by females for nesting and by males for foraging, mate attraction, territorial defense, etc. I predicted that, because the species use largely different climate-vegetation zones over most of their breeding ranges, in areas of regional sympatry the species would continue to use distinctive habitats.
My second objective was to compare habitat use by each species between areas of local allopatry and areas of local sympatry to investigate the effect of coexistence. My 11
null hypothesis was that there would be no effect of coexistence on either species and that
both species would show consistent species-specific patterns of habitat use whether
breeding in local allopatry or local sympatry. My alternative hypothesis was that, because
of recent common ancestry and thus very similar behaviour, morphology and physiology, the species would interact in local sympatry by aggressively defending interspecific territories. One (or both) species may undergo a change in habitat use in areas of local sympatry when compared to the habitat used in local allopatry as a result of competitive displacement.
My third objective was to compare the habitat use patterns by Alder and Willow flycatchers in Alberta to published descriptions of habitat use by these species in the eastern zone of secondary contact.
Research on Alder and Willow flycatchers in Canada, especially in their western ranges, is minimal. My study provides information on the habitats used by these species in Alberta and suggests a unique ecological and evolutionary relationship between sibling species that have undergone post-speciation secondary contact.
Additionally, Willow Flycatcher populations appear to be declining in Alberta
(Downes et al. 1999). Further research into the cause of this decline is important. My study contributes to what is known about the habitat requirements of Willow Flycatchers in Alberta and helps to elucidate some of the factors that are limiting their distribution in the province. 12
CHAPTER TWO
METHODS
1. BIOLOGY OF THE STUDY SPECIES
A. Willow Flycatchers
Willow Flycatchers are small flycatchers, but relatively large for the genus
Empidonax (mean mass ± SE = 14.0 ± 0.5 g, n = 6, Royal Alberta Museum Collections website: www.royalalbertamuseum.ca). Upon their arrival on the breeding grounds, their plumage is dark olive-green on the crown and back with a cream or white breast and wing bars. Later in the breeding season their plumage fades to a more drab greyish-olive and the wing bars become less distinctive (S. Hechtenthal, pers. obs.). Willow Flycatchers tend to be paler than Alder Flycatchers, with more gray and pale-olive in the upperparts and breast-band (Whitney and Kaufman 1986), although this distinction between the species becomes less evident late in the breeding season. Willow Flycatchers have a broad, flat bill with black upper mandible and an entirely yellow-orange or pinkish lower mandible. The species is sexually monomorphic in plumage. Willow Flycatchers have three distinctive advertising songs. The fitz-bew and fizz-bew are described as two- syllable songs, and the creet song is one syllable. Song performance is mostly by males and accounts of female song are uncommon (Sedgwick 2000). The typical location call is a soft whit that is used by both sexes.
Willow Flycatchers have a more southern breeding range than do Alder
Flycatchers (Fig. 2.1). Willow Flycatchers breed from southern British Columbia, east 13
Figure 2.1. Breeding distribution of Willow Flycatchers in North America
(modified from Sedgwick 2000). 14 across parts of the southern prairies to Quebec and Maine (Fig. 2.1). Their southern range limit is from the west coast of California to the east across the southern United States to
North Carolina and Virginia. The obvious gap in their breeding range from Montana south to Texas (Fig. 2.1) reflects the distinctive east/west split at the subspecies level
(discussed below). In Alberta, Willow Flycatchers breed along the Eastern Slopes of the
Rocky Mountains from Banff National Park south to Waterton Lakes National Park, with the majority of breeding records occurring south of the Bow Valley (Fig. 2.2) (Kulba and
McGillivray 2001, S. Hechtenthal, pers. obs.). Historical breeding records suggest that the range of this species extends north to Jasper National Park and south into southeastern
Alberta (Semenchuk 1992). Neither Kulba and McGillivray (2001) nor I found evidence of Willow Flycatcher populations breeding in these areas and I am reluctant to consider any breeding records outside of the Eastern Slopes region as confirmed. These extralimital records are certainly within the breeding range of their sister species, the
Alder Flycatcher, and lack of supporting evidence in the form of recorded vocalizations suggests that these records are likely cases of misidentification.
Willow Flycatchers winter in southern Mexico, Central America, and northwest
Columbia (Sedgwick 2000). Willow Flycatchers are believed to winter farther north than do Alder Flycatchers (Gorski 1969b, 1971, Sedgwick 2000, Lynn et al. 2003), and the southern limit of their winter range is unknown. Willow Flycatchers are late-spring migrants and typically travel a shorter distance to their breeding grounds than do Alder
Flycatchers. Figure 2.2. Breeding distribution of Willow Flycatchers (left) and Alder Flycatchers (right) in Alberta. Data points generated
from Federation of Alberta Naturalists breeding database (1973 - present). 15 16
Willow Flycatchers have been the focus of many recent studies because of a dramatic decline in population numbers across parts of their breeding range (Sedgwick
2000). The most notable decline has been in the southwestern subspecies (E. t. extimus), which is currently listed as endangered (Sedgwick 2000). As a result of increased research on this subspecies, much is known about this western population. Five Willow
Flycatcher subspecies are recognized (Fig. 2.3) and regional differences among populations in phenotype, vocalizations, habitat use, and behaviour are documented
(Unitt 1987, Browning 1993, Sedgwick 2001). Western subspecies (E. t. brewsteri, E. t. adastus, and E. t. extimus) can be distinguished from eastern subspecies (E. t. campestris and E. t. traillii) on basis of morphology, plumage pattern and coloration (Sedgwick
2000). The Alberta population remains largely unstudied, and it is unclear which subspecies breeds here. Based on the subspecies range map suggested by Browning (Fig.
2.3), I believe that the birds breeding in Alberta are a northerly population of E. t. adastus.
In Alberta, males typically arrive on the breeding grounds in late May or early
June and begin to establish territories upon arrival. Early in the breeding season, males defend their territories and advertise for mates with high rates of singing, starting prior to sunrise and often continuing into the afternoon. As the breeding season progresses and breeding pairs are established, daytime singing rapidly declines. Additionally, males arriving on the breeding grounds initially defend very large territories but, as the density of males increases at a site, territories become gradually smaller. Throughout the rest of 17
Figure 2.3. Breeding ranges of Willow Flycatcher subspecies: (A) E. t. brewsteri;
(B) E. t. adastus; (C) E. t. extimus; (D) E. t. campestris; (E) E. t. traillii (modified from Browning 1993). 18 the breeding season, males continue to defend their territories with daily bouts of dawn singing. Only unmated males continue with daytime singing throughout the breeding season. Males typically sing from exposed perches, often dead spruce snags or bare willow branches, that offer an unobscured view of their territory. These display perches are also used to initiate foraging sallies. Males tend to have several song perches in their territory, with one being used most frequently during their dawn singing throughout the breeding season (the primary perch). Females remain inconspicuous on the breeding grounds until nest building has commenced and, consequently, their exact arrival date often is difficult to determine (Hussell 1991b). In Alberta, females arrive 2 - 5 days after males, and mating pairs are established very quickly (S. Hechtenthal, pers. obs.).
Southwestern Willow Flycatchers are facultatively polygynous with up to 50% of males in a population having more than one reproductive female nesting within their territories (Pearson et al. 2006). In Alberta, Willow Flycatchers appear to be socially monogamous and there is no evidence of facultative polygyny (S. Hechtenthal, pers. obs.). Studies in Oregon found that banded individuals frequently returned to the same breeding site and rematings of the same male and female in successive years were not uncommon (Sedgwick 2000). The female selects the nest site, collects nest material, and builds the nest while the male perches nearby. In Alberta, Willow Flycatchers place their nests on the outer edge of a large willow bush, or occasionally in a small spruce tree that is embedded within a willow thicket (S. Hechtenthal, pers. obs.). Willow Flycatcher nests are generally placed higher (mean height ± SE = 114.8 ± 9.4 cm, range = 89.5 - 182 cm, n = 13; this study) than Alder Flycatcher nests. The nests are made of fine strands of 19 dried grasses and sedges and are usually more compact and less ragged than nests built by
Alder Flycatchers (Sedgwick 2000). The female lays 3 - 4 eggs (1 egg/day) early in the morning and incubates for 11 - 14 days (McCabe 1991, S. Hechtenthal, pers. obs.). The brood hatches over a period of 1 - 3 days and the subsequent feeding of the nestlings is done by both adults. The young remain in the nest for approximately 14 days and the fledglings remain on the natal territory for up to a week after leaving the nest (McCabe
1991, S. Hechtenthal, pers. obs.). Parents will continue to feed fledglings until they disperse from the territory (Sedgwick 2000). In Alberta, Willow Flycatchers are typically single-brooded because of the short breeding season. I observed re-nesting on three occasions in response to loss of nests resulting from flood damage or Brown-headed
Cowbird (Molothrus ater) parasitism. The re-constructed nests were within 10 m of the original nest and all were unsuccessful. Annual adult survival rate is unknown but life span is estimated to be 3 - 5 years (Sedgwick 2000).
There is little information on population trends for Willow Flycatchers in Alberta.
The Canadian Breeding Bird Survey reports that the Alberta Willow Flycatcher population experienced a 0.8 % mean annual decrease from 1966 - 1996 (Downes et al.
1999). This represents the highest provincial decline for the species in Canada.
Currently the species is listed as “status undetermined” in Alberta because its distribution and abundance are poorly known. Estimated population size is between 100 - 250 breeding pairs (Kulba and McGillivray 2001). The largest threat to the species in Alberta is believed to be anthropogenically-induced habitat loss and alteration. This has been the leading cause of the population decline in the United States. Cowbird parasitism and 20 competition with Alder Flycatchers in areas of sympatry are also possible limiting factors in Alberta .
B. Alder Flycatchers
In contrast to Willow Flycatchers, few studies of Alder Flycatchers exist, and relatively little is known about their biology. There are no recognized subspecies of
Alder Flycatcher and no quantitative work has been done on morphological or vocal differences among populations of Alder Flycatchers. Qualitative geographic variation between populations in the northwest part of the breeding range (Alaska, Yukon,
Northwest Territories) and more southern populations has been noted, with northern birds being larger and paler than southern ones (Phillips 1948).
Alder and Willow flycatchers are virtually indistinguishable, except by vocalizations. They are similar in size (Alder Flycatcher mean mass ± SE = 13.0 ± 0.2 g, n = 43, Royal Alberta Museum Collections website: www.royalalbertamuseum.ca), have similar bills, and differ very little in plumage. Like Willow Flycatchers, Alder
Flycatchers have dull, greenish-olive plumage on their upper parts, and a buffy or white breast and wing bars. However, Alder Flycatchers are typically darker and “contrastier” than Willow Flycatchers (Whitney and Kaufman 1986) and tend to have richer olive hues on their upperparts. Unlike Willow Flycatchers, a complete white eye-ring can be very prominent when Alder Flycatchers first arrive on the breeding grounds in spring, but fades as the summer proceeds (Whitney and Kaufman 1986, S. Hechtenthal, pers. obs.).
Like Willow Flycatchers, the sexes are sexually monomorphic in plumage. The 21
advertising song is described as a three-syllable fee-bee-o, but the third syllable often is difficult to hear and the song sounds more like a two-syllable free-beer. Alder
Flycatchers have a number of calls that are used by both sexes including a location call which is a dry, hard pit. Other calls including zwee-o, zwee, and churrr are believed to be used in territorial defense (Lowther 1999).
Their breeding range in Canada and northern United States is extensive (Fig. 2.4), ranging from Alaska, the Yukon and Northwest Territories, east through central and northern parts of Canada, including Newfoundland. They also breed in northeastern
United States, but generally farther north than do Willow Flycatchers. In Alberta, they breed throughout the province except for the most southern and south-eastern prairies, and the northwest corner (Fig. 2.2). They are most common in the foothills of the Rocky
Mountains west of Edmonton and north towards Slave Lake (Semenchuk 1992) (Fig.
2.2). They coexist with Willow Flycatchers at the southern edge of their range in Alberta
(Fig. 2.5).
Alder Flycatchers are long-distance Neotropical migrants. Their winter range and biology are poorly-known because they rarely vocalize in the winter and are virtually impossible to distinguish from their sister species in the field. They are thought to winter farther south than do Willow Flycatchers, mainly in the northern parts of South America.
The only confirmed winter records for Alder Flycatchers, on the basis of vocalizations, are from eastern Peru (Gorski 1971, M. S. Foster, pers. comm.), eastern Ecuador, and northern and eastern Bolivia (Lowther 1999). Qualitative descriptions of their winter 22
Figure 2.4. Breeding distribution of Alder Flycatchers in North America
(modified from Lowther 1999). 23
Figure 2.5. Circled area indicates zone of regional sympatry between Alder and
Willow flycatchers in southwestern Alberta. Data points generated from
Federation of Alberta Naturalists breeding database (1973 - present). The City of Calgary is shown (hatched area) along with major rivers. 24 habitat suggest a strong structural similarity to the habitat on the breeding grounds (M. S.
Foster, pers. comm.).
Males typically arrive on breeding grounds prior to females and establish a breeding territory in a manner similar to Willow Flycatchers. They are believed to be socially monogamous but information on sex ratio, courtship displays, formation and duration of pair bonds, or extra-pair copulations is unavailable. There is some evidence of breeding site fidelity, especially in females (Gorski 1969a). Females are responsible for nest-site selection and nest building. Alder Flycatchers place their nests low in bushes
(mean height ± SE = 46.8 ± 5.1 cm, range = 25 - 67 cm, n = 8; this study), lower than do
Willow Flycatchers. In contrast to Willow Flycatchers, Alder Flycatchers make nests that are coarse and untidy, often with many loose strands of grass and sedge hanging from the bottom and sides (Lowther 1999, S. Hechtenthal, pers. obs.). All other aspects of the breeding phenology are similar to those of Willow Flycatchers. Alder Flycatchers are also single-brooded because of the extremely short breeding season. In fact, the period of breeding range occupancy of Alder Flycatcher populations in Alaska is the shortest yet documented for any population of migratory passerine (13% of annual cycle as compared to an average of 25 - 30 % for Neotropical migrant passerines) (Hussell 1991b, Hussell
1991a, Benson and Winker 2001). Re-nesting has been documented if the original nest is damaged, parasitized, or depredated (Lowther 1999).
Alder Flycatcher populations are considered to be stable across their breeding range (Lowther 1999). 25
2. STUDY AREAS
All of the study sites were located in the area of regional sympatry in the province
(Fig. 2.5). However, within this area, most sites had only one species present (local
allopatry). Sites where both species were present on contiguous territories (local
sympatry) were relatively uncommon. In 2004, I located study sites in the central area of
regional sympatry. In 2005, I chose sites that gave me a broader view of habitat use at
both the northern and southern borders of the area of regional sympatry (Fig. 2.6). I
selected sites when birds arrived in late May or early June on the basis of both species
composition and abundance at the sites. I designated a site as “locally allopatric” if a
minimum of five breeding pairs of a single species (and none of the other) were present.
A “locally sympatric” site required five breeding pairs of each species. This second type
of site was more difficult to locate. In both years, initial site designation followed these
species-abundance criteria. However, as the breeding seasons progressed, extrinsic factors such as snow, below-freezing temperatures, and flooding (especially in 2005) caused bird numbers at the study sites to decline as a result of death or abandonment.
Therefore, final species abundances do not reflect the initial selection criteria in all cases.
A. 2004 Study Sites
All study sites for the 2004 field season were located along Sibbald Creek Trail
(Highway 68), in the foothills of the Rocky Mountains, approximately 80 km west of
Calgary, Alberta. I chose five sites in this area (Fig. 2.6). 26 Forestry Hut
Cadet Camp Lochend
Cataract Creek
Indian Graves
SCT East SCT West Bryant Creek SCT Creek Sibbald Flats
Figure 2.6. Map of all study sites used during the 2004 and 2005 breeding seasons.
The City of Calgary is shown (hatched area) along with major roads. Lower map shows 2004 study sites along Sibbald Creek Trail. 27
The site named “SCT East” (51° 03' N, 114° 42' W) was located on the eastern section of Sibbald Creek Trail, just east of the Kananaskis Provincial Park boundary.
This site was used primarily for cattle grazing and the grazing pastures were bordered by dry, mature willow thickets and mixed forests, although stands of young poplar (Populus spp.) were also present. The only permanent body of water in the area was a small man- made livestock dugout. This site supported many Alder Flycatcher breeding pairs and was designated as allopatric for Alder Flycatchers (ALOALFL).
“Bryant Creek” (51° 02' N, 114° 47' W) was a large wetland area further west along Sibbald Creek Trail (both the north and south side of the road). It had a large sympatric population of Alder and Willow flycatchers (SYMALFL/SYMWIFL). This area had dense shrubby vegetation consisting mainly of willows, bog birch (Betula glandulosa), and shrubby cinquefoil (Potentilla fruticosa) bordering streams and beaver
(Castor canadensis) ponds. The wet meadows were bordered by dryer upland willow thickets and conifer forests (Picea and Pinus spp.). Bryant Creek is used annually for late-summer cattle grazing.
A second, smaller sympatric site was located further west along Sibbald Creek
Trail, called “SCT Creek” (51° 02' N, 114° 54' W). This site bordered Sibbald Creek, which typically flooded in the spring creating many small ponds and sedge marshes. The willow bushes were taller here than at Bryant Creek and poplar and spruce trees were abundant. To my knowledge, no cattle are permitted here.
I located two sites along Sibbald Creek Trail where only Willow Flycatchers bred
(ALOWIFL). The largest population of Willow Flycatchers was located at “Sibbald 28
Flats” (51° 02' N, 114° 52' W) where dense, tall willow bushes grew on the side of a busy gravel road. Beyond the willows, the habitat was a mosaic of small (< 3m) spruce trees, tall spruce snags, dense clumps of low willow bushes, and sedge marshes. Sibbald Creek snaked along the south side of the site. The birds defended long, narrow territories extending from the road back towards the creek. To my knowledge, no cattle are permitted at this site.
I located a smaller population of Willow Flycatchers at a site further west along
Sibbald Creek Trail called “SCT West” (51° 02' N, 114° 53' W). This site was extremely wet because Sibbald Creek was dammed by beavers at several locations, creating large ponds and deep trenches. The birds bred in the willow bushes that bordered the ponds, the creek, and the trenches. To my knowledge, no cattle are permitted at this site.
B. 2005 Study Sites
I located two ALOALFL sites in 2005 (Fig. 2.6). The “Lochend” site (51° 15' N,
114°20' W) was located approximately 25 km northwest of Calgary, immediately west of
Secondary Highway 766. This is privately-owned land used for seasonal cattle grazing.
Birds bred in the dense, mature, dry willow thickets that were located throughout the pastures and valleys. Stands of trembling aspen (Populus tremuloides) were often adjacent to breeding territories. The other ALOALFL site was adjacent to the Indian
Graves Provincial Recreation Area, approximately 120 km southeast of Calgary along
Secondary Highway 532. The “Indian Graves” site (50° 16' N, 114° 18' W) is also used for seasonal cattle grazing. Again, the area was dominated by dense, mature willow 29 thickets and poplar stands. A small creek ran around the periphery of the site, creating some sedge marshes and muddy areas intermixed with dry grass fields. This site was at the southern edge of the breeding range of Alder Flycatchers in Alberta.
It was a challenge to locate sites with adequate numbers of Willow Flycatchers in
2005. Many sites had large populations of Alder Flycatchers with only a few Willow
Flycatcher pairs present, or were inhabited solely by Alder Flycatcher pairs. I eventually located an ALOWIFL population at “Cataract Creek” (50° 16' N, 114° 36' W) along the
Forestry Trunk Road (Highway 940), approximately 12 km south of Highwood Junction.
The large, swift-moving Cataract Creek runs through the center of this site and the many beaver ponds, sedge marshes, small creeks, and trenches made this site very wet. This site was very different from all of the other sites in several ways. First, the area is not subjected to any anthropogenic modifications (i.e., no cattle grazing or busy roads).
Second, the tall dense willow thickets were surrounded in all directions by large sub- alpine meadows of low (< 50 cm), dense bushes. These meadows met with sub-alpine conifer forests at the perimeter of the site.
I located two sites in 2005 that were designated initially as sympatric. The “Cadet
Camp” site (51° 19' N, 114° 57' W) was located in the South Ghost Provincial Recreation
Area, 43 km northwest of Cochrane on the Forestry Trunk Road. On the east side of the road, Alder Flycatchers were breeding on a dry hillslope among mature, willow thickets.
On the west side of the road, approximately 500 m from the east-side territories, the habitat was a mosaic of beaver ponds and creeks alongside dryer upland areas. Both species were present on this side of the road with Willow Flycatchers breeding in the 30 bushes directly adjacent to the water, and Alder Flycatchers breeding in the dryer areas.
However, after extensive flooding and damage to the habitat in June 2005, only one
Willow Flycatcher pair remained. The Alder Flycatcher territories on the west side were located well away from the water, thus their territories remained unaltered. I decided that the Alder Flycatchers breeding on the east side of the road, “Cadet Camp East,” would be reassigned as allopatric, and the birds breeding on the west side of the road, “Cadet Camp
West,” would be reassigned as sympatric.
I located another sympatric site at the northern border of the range of Willow
Flycatchers in Alberta. “Forestry Hut” (51° 28' N, 114° 51' W) was located along
Highway 579, approximately 20 km west of Water Valley. The habitat at Forestry Hut was very similar to that of Bryant Creek, although cattle grazing occurred throughout the entire summer at this site.
3. BIRD-FOCUSED FIELD WORK
A. Territory and Perch Assignment
I began monitoring suitable breeding sites for the arrival of birds starting in the last week of May. Using vocalizations to identify the species, I noted the general arrival and settling pattern of Willow and Alder flycatchers at the various sites. Once population sizes were stable and males were advertising strongly for mates, I assigned sites to one of the three species-composition categories (i.e., ALOALFL, ALOWIFL, or SYMPATRIC).
I observed each male on its territory (i.e., the specific area within a suitable habitat that a bird chooses to defend) during pre-dawn and early morning singing bouts to determine 31 the primary song perch and territory boundaries. The pre-dawn song chorus commenced at approximately 04:00 MDT and the birds continued to sing strongly until 07:00 MDT.
The primary song perch was assigned based on the number of repeated visits to particular song perches during this 3-hour singing interval over an observation period of three days.
Without exception, each male in the study had a favorite song perch that was used > 75% of the time (S. Hechtenthal, pers. obs.). A second most-commonly used song perch was also identified in a similar manner.
I mapped the territory of each male by noting the location of counter-singing bouts and aggressive interactions between neighbors and using a modified version of the “flush method” (Reed 1985). This involved approaching a singing bird until he flew and noting the location where either he landed, or turned around and flew back across his territory.
This continued until a minimum of 4 boundary-points were noted. All boundaries and perches were flagged and subsequently plotted using a handheld Global Positioning
System (GPS) receiver. I am confident that song perches and territory boundaries were stable throughout the field season. Territorial males exhibit strong site fidelity and defend the same territory throughout the breeding season (Lovell and Lein 2004) and were observed singing from the same perches each morning (S. Hechtenthal, pers. obs.).
B. Nest Searching and Monitoring
I began to search for a nest on a territory after the presence of a female was confirmed. Because of the large number of territories and the time-consuming nature of nest searching, a maximum of 1 hour was allotted to nest searching on each territory. 32
Two searching methods were most successful. The first was to follow females that were carrying nesting materials during the nest building phase (early June). The second method involved moving slowly through the vegetation on the territory and attempting to flush the female off the nest during the incubation phase (mid-late June). When a nest was located, it was plotted with GPS and subsequent nest-monitoring continued throughout the entire breeding season using standard methods (Ralph et al. 1993).
Habitat sampling around the nest occurred only after the young had fledged in order to minimize the likelihood of abandonment or damage to the nest.
4. HABITAT SAMPLING
A. Sampling Methodology
There are regular, repeatable patterns of associations or correlations between birds and habitat variables (Rotenberry 1981) and various methods have been used to sample and test this nonrandom occupancy of habitat. However, the methods vary considerably in their accuracy and efficiency. The specific sampling strategy, spatial scale, and habitat variables need to be chosen carefully when designing a study of habitat use (Orians and
Wittenberger 1991, Pribil and Picman 1997, Jones 2001). All of my methods revolved around the concept of bird-centered habitat sampling in which the study species designates the focal sampling areas. This method ensures that the data acquired from the study correspond to the micro-habitat that is actually used by the study species (James
1971, Rotenberry 1985, Larson and Bock 1986) and also reduces the probability of 33
extraneous and irrelevant measurements being taken (Karr 1981, Whitmore 1981, Graves
2001).
The choice of the sampling strategy depends on the study objectives (Johnson
1981, Block and Brennan 1993). Since my objective was to quantify and compare the patterns of habitat use of Willow and Alder flycatchers, I needed to gather data from their territories that represented the micro-habitats that they used most often. The most common way in which habitat use is studied in breeding birds with territorial systems is to sample habitat that is being “used” by the birds for nesting, singing, foraging, etc., and habitat that is clearly unoccupied or “unused” (Jones 2001, Battin and Lawler 2006).
Habitat variables from the two areas are then compared and habitat preferences are inferred by demonstrating the disproportionate use of particular habitat features. This method can be misleading and uninformative, especially at coarser spatial scales, because areas may be unused or unoccupied by the birds for a variety of reasons other than habitat features (Jones 2001, Jones and Robertson 2001).
In order to avoid the problems associated with the “used” vs. “unused” method, and because I was interested in the habitat differences between Willow and Alder flycatchers (and not just the habitat preferences of individual species), I used a modified sampling method, recently named “constrained design” (Battin and Lawler 2006). This method gathers habitat information from an area within a territory that is being used for some specific purpose (e.g., singing, nesting, foraging) and from random areas, still within the known territory boundaries, that are being defended for an unknown purpose.
This way, the habitat sampling areas are “constrained” by boundaries that are set by the 34 focal species, and not by the researcher. Using this method, I obtained micro-habitat data on each territory that could be used to create overall quantitative and qualitative descriptions of habitat use by each species based on mean scores of the measured habitat variables. These descriptions could then be used to investigate differences between the species within a particular site type (e.g., ALOWIFL vs. ALOALFL and SYMWIFL vs.
SYMALFL) and differences between the site types within a species (e.g., ALOALFL vs.
SYMALFL and ALOWIFL vs. SYMWIFL). This sampling method has been shown to be a comprehensive, accurate, and informative way of describing specific aspects of habitat use by a species (Sedgwick and Knopf 1992, Jones and Robertson 2001).
Bird-centered sampling requires choosing specific features that are used by the birds on a territory to be the focal points for the habitat sampling. In studies of passerine habitat use, male song perches are used commonly as the central sampling points and are assumed to provide unbiased and representative locations from which to obtain a view of a species habitat (James 1971, Collins 1981, Barlow and McGillivray 1983, Sedgwick and Knopf 1992, Guilfoyle et al. 2002). This assumption is especially true for flycatchers because male song perches often have multiple functions (e.g., advertisement, defense, foraging). Nest sites also are used frequently as a sampling point and provide insight into female aspects of habitat use (Sedgwick and Knopf 1992). Interestingly, I observed that both species often place their nests < 10 m away from the primary song perch on a territory, indicating that sampling from either the nest or the song perch should yield similar information about the habitat used by the species. 35
Patterns of habitat use are affected strongly by the scale of the habitat sampling and consideration of scale becomes a necessary component of habitat studies (Wiens
1989b, Kristan 2006). In order to ensure valid results from a study of habitat use, both the ecology of the study species and the degree of heterogeneity in their habitat need to be considered carefully when choosing the sampling scale (Wiens 1989b, Sedgwick and
Knopf 1992, Pribil and Picman 1997, Jones 2001, Suorsa et al. 2005). Until recently, a standard practice was for researchers to obtain all of their habitat measurements from a single sampling scale - typically a 0.04-ha, circular plot centered around a censussing point such as a song perch (James and Shugart Jr. 1970, James 1971, Noon 1981).
However, because most passerine birds defend territories that are significantly larger than
0.04 ha, key micro-habitat variables that influence habitat use by a species can be missed or overlooked (Holmes 1981, Orians and Wittenberger 1991, Pribil and Picman 1997).
Additionally, for many passerines, the breeding territory encompasses all of the resources required during the breeding season, such as song perches, suitable foraging sites, nesting sites, and shelter from predators and inclement weather. Therefore, territories are likely to be highly heterogeneous in terms of physiognomy and floristic composition and multiscale sampling is required to account for this variation (Wiens 1989b, Sedgwick and
Knopf 1992, Matsuoka et al. 1997).
Based on the above considerations I sampled each territory at three different scales: (1) the song perch or nest plant itself (microplot); (2) the area directly surrounding the song perch or nest plant (10 m in each cardinal direction) (mesoplot) and; (3) the habitat characteristics on four randomly-chosen 10-m transects on each territory 36
(macroplot). This sampling method reflects the most common scale-dependent pattern in bird-habitat associations which assumes that birds choose the habitat features at the level of the territory (coarsest scale) first, followed by the choice of song perches by the male and a nest site by the female (finest scale) (Battin and Lawler 2006, Kristan 2006, Lawler and Edwards 2006). This assumption is supported in my study species because the males begin to defend territories prior to the arrival of the females and likely select areas with a number of possible nest sites (to be chosen by the females upon pairing). Females have been shown to be more discriminating in their habitat use than males and may pair with a male partially because of the nest site choices on the territory he is defending (Sedgwick and Knopf 1992).
A recent concern relating to the analysis of multiscale habitat studies involves the fact that because this system is inherently hierarchically-organized, the habitat variables will likely exhibit correlations across scales (Battin and Lawler 2006, Lawler and
Edwards 2006). When these cross-scale correlations exist within a multiscale habitat study, the habitat relationships identified at different scales are not likely to be independent and conclusions drawn about the relative strength of habitat associations at different spatial scales may be inaccurate. This problem has been explored only in very recent studies in which researchers have been focused on predicting species occurrence from hierarchical models of bird-habitat associations. My study makes no such attempt at modelling habitat relationships for either species, but rather focuses on differences between the species. Consequently, although I agree that cross-scale correlations exist, 37 for this study I will assume that they affect all of the territories equally and that the within-scale comparisons between species are still valid.
B. Habitat Variables
The premise behind choosing variables is obvious: sample only those habitat features that are of ecological importance to the study species. Establishing which factors are actually important to the species in question is the challenge. Additionally, in this study there were several factors involving the timing of the sampling that must be considered. The dramatic seasonal changes that occur during the breeding season in the amount of moisture and standing water on each territory have an impact on the results of the habitat sampling. At the start of the breeding season, numerous ephemeral pools of water existed on many territories (especially at the wetter sites). However, by the time the young had hatched and habitat sampling began (mid-late July), many of these pools had dried up. Thus, I found a tradeoff between sampling aspects of the vegetation and ground cover during the period when they were being used by the birds, and minimizing the impact on their breeding success. In order to account for these changes, I noted overall water cover on each territory around the primary song perch early in the breeding season (second week of June) in addition to recording this variable during the full habitat sampling in July. In the early-season sampling I assigned an overall water rank to each territory (PRERANK) based on a continuous scale of 1 - 5 (1 = entire territory dry; 5 = entire territory covered by water). I accounted for seasonal variation also by sampling all of the territories at approximately the same time in both years for both the early- and late- 38 season sampling. Within each breeding season I allocated a 20-day window to complete the full habitat sampling. All of the habitat sampling around the perches and on random transects took 18 days in 2004 (July 11 - July 29) and 20 days in 2005 (July 12 - August
2). Sampling at the nest sites occurred over a 5-day period in both years (August 2 - 7).
i. Microplot
At the microplot scale, I recorded detailed information about the primary song perch and nest plant (see Table 2.1 for list of variables).
a. Song perch
Two categories of song perch were possible: a tree or a bush (CPCATG). In the case of a bush, I used an extendable pole to measure exact height (CPHEIGHT). I used two perpendicular meter-sticks placed horizontally at the center of the bush to measure central stem density by counting the number of stems that made contact with the sticks
(CPSTEMS). If the song perch was a tree, I estimated the height using the pole. I recorded the overall vigor of the bush or tree (CPALIVE) using a categorical scale (Table
2.1) and type of ground cover immediately below the perch (CPGRCOV) using standardized codes (Table 2.1). I recorded the distance from the edge of the song perch to the nearest bush (> 1 m in height) in each cardinal direction and calculated the mean distance (CPNRBUSH). I also noted the distances from the song perch to the nearest
(CPNRWTR) and largest (CPLRGWTR) bodies of water on the territory as well as the Table 2.1. Microplot habitat features measured from the song perch or nest plant on individual bird territories.
Habitat variable Description CPCATG Type of song perch or nest plant (tree or bush)
CPHEIGHT Height of song perch or nest plant (m)
CPSTEMS Stem density of song perch or nest plant. Number of individual stems that make contact with a meter stick
placed at the center of the bush, averaged over North/South and East/West orientations
CPALIVE Categorical scale of vigor of the song perch or nest plant: 1 = all branches alive; 2 = most branches alive; 3 =
half the branches live and half dead; 4 = most branches dead; 5 = all branches dead CPGRCOV Categorical scale for the type of ground cover present under the song perch or nest plant: 1 = water; 2 = moss;
3 = dead sedge and grass; 4 = leaf litter and/or woody debris
CPNRBUSH Distance (m) from song perch or nest plant to neighboring bushes (> 1 m). Mean over the 4 cardinal directions
CPNRWTR Categorical scale for distance from song perch or nest plant to closest body of water: 1 = 0-5 m to closest
water; 2 = 5-10 m; 3 = 10-15 m; 4 = 15-20 m; 5 = 20-25 m; 6 = 25-30 m; 7 = 30 m + 39 Table 2.1. Continued
Habitat variable Description CPNRSIZE Categorical scale for the size of the body of water closest to the song perch or nest plant: 1 = Beaver pond or
large open body of still water; 2 = River, creek or stream; 3 = Grassy marsh with permanent water that is over
ankle; 4 = permanent grassy pools but not over ankle; 5 = damp moss or grass; 6 = damp leaf litter; 7 = dry CPLRGWTR Categorical scale for distance from song perch or nest plant to largest body of water on territory. Categories
same as CPNRWTR. CPLRGSIZE Categorical scale for the size of the largest body of water on the territory. Categories same as CPNRSIZE 40 41
standardized codes for these water features (CPNRSIZE and CPLRGSIZE, respectively)
(Table 2.1).
b. Nest plant
I used the same methods outlined above to measure the following microplot features of the nest plant: CPCATG, CPHEIGHT, CPALIVE, CPGRCOV, CPNRBUSH
(Table 2.1). Measurements on the nest plant were taken later in the season than those of the song perches (post-fledging). Consequently, no variables relating to water cover were included in the sampling because of extensive changes in the moisture gradient on the territories (drying).
ii. Mesoplot
At the mesoplot scale, I measured habitat variables within a 10-m radius around the song perch or nest plant. Song perches were often tall, dead spruce snags or tall, partially-dead willow bushes. In the case of a tree, the four 10-m transects ropes were centered at the base of the trunk and radiated outward in each cardinal direction. For bushes, the transect ropes were centered at the base of the branch used for perching and radiated outward through the bush. Nest-plant transects were centered on the main support branch for the nest. On each of the four transects I measured the number of meters of rope in contact with a deciduous bush (willow, bog birch, or cinquefoil) and this was converted into a percentage (BUSHCOV) (Table 2.2). I recorded visible water coverage along each transect in the same way (WTRCOV) and an overall water rank was Table 2.2. Habitat features measured on the 10-m transects centered around each song perch or nest plant (mesoplot) and on random transects (macroplot). Mean calculated from four transects (either mesoplot or macroplot transects).
Habitat variable Description BUSHCOV Mean bush cover along transects (%)
WTRCOV Mean water cover along transects (%)
TRANSRANK Mean overall moisture scale on the transects. Continuous scale between 1 and 5: 1 = xeric (dry
over entire transect); 5 = hydric (entire transect covered by water)
VEGHT Mean height of vegetation along transects (m)
VEGALIVE Mean overall categorical scale of live versus dead vegetation along transects: 1 = all branches alive;
2 = most branches alive; 3 = half the branches live and half dead; 4 = most branches dead; 5 = all
branches dead
STEMHITLO Mean number of bush stems that make contact with measurement pole under 1 m
VIISALX Mean vegetation importance index for willow bushes along transects
VIISEDG Mean vegetation importance index for sedges along transects
VIIGRAS Mean vegetation importance index for grasses along transects 42 Table 2.2. Continued
Habitat variable Description VIIRUHT Mean vegetation importance index for rushes and horsetail along transects
VIIBETU Mean vegetation importance index for bog birch bushes along transects
VIITREE Mean vegetation importance index for trees along transects
VIIOTHR Mean vegetation importance index for other herbaceous vegetation along transects
VIINONE Mean vegetation importance index for unvegetated areas along transects
GIIMOSS Mean ground cover importance index for moss along transects
GIIWATR Mean ground cover importance index for water along transects
GIILLDB Mean ground cover importance index for leaf litter and woody debris along transects
GIIDGRAS Mean ground cover importance index for dead grass along transects
GIIDSEDG Mean ground cover importance index for dead sedge along transects
GIIOTHR Mean ground cover importance index for other types of ground cover along transects 43 44 assigned to the transect using a continuous scale of 1 - 5 (TRANSRANK). At each 1-m interval on a transect, I recorded height (VEGHT) and vigor (VEGALIVE) of the vegetation, and the number of bush stems that contacted a vertical pole below 1 m
(STEMHITLO). The type of vegetation was also noted at each 1-m interval and the proportion of each vegetation type on the transect (i.e., a vegetation importance index) was calculated. Vegetation-type categories included willow (VIISALX), sedge
(VIISEDG), grass (VIIGRAS), rushes and horsetail (VIIRUHT), bog birch (VIIBETU), trees (VIITREE), and other types of herbaceous vegetation (VIIOTHR). If no vegetation was present I recorded it as none (VIINONE). A ground cover importance index was recorded and calculated in the same way with the following categories: moss (GIIMOSS), water (GIIWATR), leaf litter and woody debris (GIILLDB), dead grass (GIIDGRAS), dead sedge (GIIDSEDG), and other (GIIOTHR) which included river rock, gravel, mud, or dirt.
iii. Macroplot
I generated random points on the territories of each bird using either a primary or secondary song perch as the starting point (determined by a coin toss), and then moved a random distance (0 - 30 m) and direction from that point. If the specified distance lead to an area outside of the territory boundaries, the distance was halved until the transect fell within the boundaries. The midpoint of the 10-m transect was centered on the random point and the transect was run perpendicular to the original direction of travel. On the 45 four 10-m random transects, the same variables were measured using the same methods as for the mesoplot transects (Table 2.2).
5. DATA ANALYSIS
The data analysis procedures for the microplot scale were very different from those of the mesoplot and macroplot scales and therefore will be discussed separately below. Significance was generally taken at the p < 0.05 level but, because a large part of this study is comparative, results will be considered marginally significant at p < 0.1. I used both SYSTAT 11.0 and SPSS 13.0 to conduct data analyses.
There were two types of comparisons that were of interest to me: (1) differences between the species within a particular site type (e.g., ALOWIFL vs. ALOALFL and
SYMWIFL vs. SYMALFL); and (2) differences within species between the site types
(ALOALFL vs. SYMALFL and ALOWIFL vs. SYMWIFL). The second type of test detected possible differences in habitat use by a species when breeding in the absence of their sibling species compared to breeding in areas of coexistence.
A. Microplot
i. Song Perch
I measured three continuous and seven categorical song perch variables. The continuous variables were tested for normality using exploratory data and graphical analysis techniques and appropriate univariate tests (parametric ANOVAs or non- parametric Mann-Whitney U tests) were run. I analyzed the categorical variables using 46 contingency tables. If a table had many low or zero frequencies (i.e., more than 20% of the categories had expected frequencies less than five), I collapsed several of the variables into new categories to increase the power of the statistical tests (Quinn and Keough
2002). The new categories were used throughout the entire microplot analysis. The original five CPALIVE categories were condensed to three new categories: 1 = vegetation mostly alive; 3 = vegetation half alive and half dead; 5 = vegetation mostly dead. The ground cover categories (CPGRCOV) were condensed into three new categories: 1 = majority of ground covered by water and/or moss; 2 = cover is mostly dead grass/sedge; 3
= cover is mostly leaf litter and/or woody debris. The categories for distance to nearest water (CPNRWTR) were condensed into three new categories (0-15m, 15-30m, 30m+).
Three new categories were also created for the size of water that was nearest to the song perch (CPNRSIZE) corresponding to: 1 = large open bodies of still or moving water; 2 = small pools of still water and small sedge marshes; 3 = damp or dry ground cover. I analyzed the categorical variables using Chi-squared tests. I tested both the continuous and categorical data for differences between the species within a particular site type and for differences between the site types within a species.
ii. Nest Plant
Sample sizes were too small to permit investigation of differences between all four species/site type categories. I combined ALOALFL with SYMALFL, and
ALOWIFL with SYMWIFL nest data and tested for differences only between the species.
The two continuous variables were tested for normality and appropriate univariate tests 47 were run. The three categorical variables were condensed into new categories and tested in the same manner as described above.
B. Mesoplot/Macroplot
i. Song Perch and Random Transects
The raw data collected from the transects at the mesoplot and macroplot scales first were averaged over the 10 sampling points on each transect. Then I averaged these values over the four mesoplot or macroplot transects to give a single value for each variable for each territory at each scale.
I conducted correlation analyses on all of the variables using both the Pearson correlation coefficient (parametric) and the Spearman rank correlation coefficient (non- parametric). Because both produced similar results, all decisions regarding retaining or discarding variables were based on the more powerful parametric test. Of the 20 original habitat variables that were measured on each mesoplot and macroplot transect, five were dropped from the analysis because they were highly correlated (r > | 0.6 |) with other variables or were rarely used (Tables 2.3 and 2.4). Eight variables were condensed to form new variables because the original categories were too restrictive and thus sparsely populated (Tables 2.3 and 2.4). Seven variables were retained without being condensed into new categories (Tables 2.3 and 2.4). The early-season water sampling variable
(PRERANK) was included initially in the analysis of the mesoplot variables (Table 2.3).
However, although the territories were significantly wetter during the early-season sampling (PRERANK) than during later-season sampling (TRANSRANK), the two 48
Table 2.3. Summary of original habitat variables measured around song perches at the mesoplot scale. A Pearson’s r > | 0.6 | between a pair of variables resulted in one variable being dropped from the analysis.
Original Retained? Notes
Variable BUSHCOV No Correlated with TRANSRANK, GIIWATR TRANSRANK Yes WTRCOV No Correlated with STEMHITLO, VIISALX, VIIHERB VEGHT Yes VEGALIVE Yes STEMHITLO Yes VIISALX Yes Part of new variable VIIBUSH VIISEDG Yes Part of new variable VIIHERB VIIGRAS Yes Part of new variable VIIHERB VIIRUHT Yes Part of new variable VIIHERB VIIBETU Yes Part of new variableVIIBUSH VIITREE No Correlated with VEGHT VIIOTHR Yes Part of new variable VIIHERB VIINONE No Correlated with GIIWATR GIIMOSS Yes GIIWATR Yes GIILLDB Yes GIIDGRAS Yes Part of a new variable GIIDHERB GIIDSEDG Yes Part of a new variable GIIDHERB GIIOTHR No < 10 territories had a value in this category PRERANK No Correlated with TRANSRANK 49
Table 2.4. Summary of original habitat variables measured around song perches at the macroplot scale. A Pearson’s r > | 0.6 | between a pair of variables resulted in one variable being dropped from the analysis.
Original variable Retained? Notes BUSHCOV No Correlated with VIISALIX, VIINONE, VIIGRAS,
STEMHITLO, VIISEDG TRANSRANK Yes WTRCOV No Correlated with GIIWTR, STEMHITLO, VIISALX VEGHT Yes VEGALIVE Yes STEMHITLO Yes VIISALX Yes Part of new variable VIIBUSH VIISEDG Yes Part of new variable VIIHERB VIIGRAS Yes Part of new variable VIIHERB VIIRUHT Yes Part of new variable VIIHERB VIIBETU Yes Part of new variableVIIBUSH VIITREE No Correlated with VEGHT VIIOTHR Yes Part of new variable VIIHERB VIINONE No Correlated with GIIWATR GIIMOSS Yes GIIWATR Yes GIILLDB Yes GIIDGRAS Yes Part of a new variable GIIDHERB GIIDSEDG Yes Part of a new variable GIIDHERB GIIOTHR No < 10 territories had a value in this category 50 variables were correlated (Table 2.3) and showed similar trends. For this reason,
PRERANK was dropped from all subsequent mesoplot analyses.
The 10 habitat variables that were retained for further analysis were assessed in each year independently using exploratory data analysis and graphical analysis techniques. I detected outliers using boxplots and tested the distribution of the data with graphical techniques (probability plots and histograms) as well as a formal significance test for normality (Shapiro-Wilk test) (Tables 2.5 and 2.6). Tests for homogeneity of variances included visual inspection with side-by-side boxplots, a formal significance test
(Levene test) (Tables 2.5 and 2.6), and plots of the residuals from an ANOVA model against predicted values (as suggested by Quinn and Keough, 2002). When necessary, I transformed the data to meet the distributional and variance assumptions required for linear and multivariate models (i.e., normality and homogeneity of variances). At the mesoplot scale, five of the ten variables showed equal variances and normal distributions after transformation and were tested under parametric conditions. The remaining five were tested using non-parametric statistics (Table 2.5). I used the same transformations on each macroplot variable as those used on each mesoplot variable with one exception.
The macroplot variable VEGALIVE was squared rather than cubed when transformed
(Table 2.6). Six of the ten macroplot variables showed equal variances after transformation and were tested under parametric conditions. The remaining four were tested using non-parametric statistics.
I used the transformed variables to test for differences between the two sampling years and among the study sites. Although I detected significant differences between the Table 2.5. Summary of transformations on mesoplot song perch habitat variables. Results from test of normality (Shapiro-Wilk) and equal variances (Levene test) also shown. Variables meeting parametric requirements shown in bold face.
Original habitat variable Transformation New habitat variable Shapiro-Wilk test Levene’s test
(p - value) (p - value) TRANSRANK Square root SQRTRANK 0.04 0.36
VEGHT Log LOGHEIGHT 0.62 0.90
VEGALIVE Cubed X3LIVEDEAD 0.24 0.00
STEMHITLO Square root SQRTSTEMS 0.77 0.88
VIIBUSH Squared X2BUSH 0.19 0.13
VIIHERB Root arcsine ASINHERB 0.02 0.01
GIIMOSS Square root SQRTMOSS 0.00 0.03
GIIWATR Square root SQRTWATER 0.00 0.00
GIILLDB Root arcsine ASINLITTER 0.05 0.41
GIIDHERB Square root SQRTDHERB 0.02 0.00 51 Table 2.6. Summary of transformations on macroplot song perch habitat variables. Results from test of normality (Shapiro-Wilk) and equal variances (Levene test) also shown. Variables meeting parametric requirements shown in bold face.
Original habitat variable Transformation New habitat variable Shapiro-Wilk test Levene’s test
(p - value) (p - value) TRANSRANK Square root SQRTRANK 0.06 0.19
VEGHT Log LOGHEIGHT 0.17 0.27
VEGLIVE Squared X2LIVEDEAD 0.24 0.00
STEMHITLO Square root SQRTSTEMS 0.06 0.13
VIIBUSH Squared X2BUSH 0.01 0.04
VIIHERB Root arcsine ASINHERB 0.39 0.03
GIIMOSS Square root SQRTMOSS 0.04 0.46
GIIWATR Square root SQRTWATER 0.00 0.00
GIILLDB Root arcsine ASINLITTER 0.12 0.13
GIIDHERB Square root SQRTDHERB 0.05 0.39 52 53 two years in several variables, most of the differences did not indicate year-effects.
Instead, because different study sites were used each year, they indicated strong differences between the habitat at the sites themselves. I confirmed this hypothesis when
I tested for differences among the study sites. Many of the study sites that I sampled in
2004 were significantly different from the sites that I sampled in 2005 on numerous variables that were not attributable to between-year effects (e.g., differences in stem densities and vegetation heights). Therefore, in order to include the full range of variation that existed at the breeding sites, I combined the data collected from 2004 and
2005 into single datasets. Once combined, I re-analyzed the variables to ensure they still met all the aforementioned assumptions.
I conducted univariate analyses (ANOVAs and non-parametric Kruskal-Wallis tests) on each variable to test for differences among the four species/site type categories.
If a significant difference was detected among the four categories, multiple pair-wise comparisons were performed with a Dunn-Sidak correction.
I used multivariate statistical techniques to investigate differences in habitat use between the species using multiple habitat variables simultaneously. I used a principal components analysis (PCA) to create a reduced set of uncorrelated variables, followed by a MANOVA and discriminant function analysis (DFA) on the principal components to test for differences among the four species/site type categories.
All 10 transformed habitat variables could be entered into a PCA because there are no distributional assumptions associated with the determination of component scores
(Tabachnick and Fidell 1996, Quinn and Keough 2002). I conducted the analysis using 54 the correlation matrix because the variables had different variances. Only principal components (PCs) with eigenvalues > 1 were retained for further analysis. Component loadings are simple correlations (using Pearson’s r) between the components and the original variables. High loadings, either positive or negative, indicate that a variable is strongly correlated with (i.e., strongly loads on) a particular component. I corrected for moderate principal component loadings (0.4 - 0.6) using a varimax rotation. Varimax is an orthogonal rotation that keeps the PCs uncorrelated and often increases the resolution and interpretability of the output (Quinn and Keough 2002). For each PC, I tested for significant differences among the four species/site type categories with an ANOVA, followed by multiple pairwise comparisons with a Dunn-Sidak correction.
The placement of each territory on each of the three PCs was shown using a series of bivariate scatterplots. The location of the group centroid for each species/site type category was indicated with a 95% Gaussian confidence ellipse. I plotted PC1 against
PC2 and PC1 against PC3. Plots of PC2 against PC3 revealed the same general patterns and were not included in the analysis. I used these graphs to examine visually the degree of overlap or separation among the multivariate confidence ellipses around each group centroid.
I ran the MANOVA and DFA on the PC scores of the individual territories instead of the transformed habitat variables for several reasons: (1) many of the habitat variables were highly correlated with each other, which is a severe problem in DFA (Klecka 1980); and (2) the assumptions of multivariate normality and equal group covariance matrices for MANOVA and DFA were not met by 50% of the transformed habitat variables. PC 55 scores were completely uncorrelated and, although they also deviated mildly from the assumptions, MANOVA and DFA are robust to mild deviations, especially when there are small numbers of variables (< 5) (Klecka 1980, Bray and Maxwell 1985, Quinn and
Keough 2002).
The mathematical goal of DFA is to weight and linearly combine a group of variables (i.e., the discriminating variables), which have been measured on two or more groups, in such a way as to ensure that the groups are as statistically distinct as possible
(Klecka 1980). It produces a decision rule (i.e., a classification function) that can be used to predict the group to which an observation belongs (Tabachnick and Fidell 1996). The rate of correct classification often is used as a measure of the success with which the discriminant function has separated the groups. The PC scores were used in a DFA to determine how well territories could be classified to the correct species/site type category, or how well territories within a site type could be classified to the correct species. All classifications were run with jackknifed cross-validations.
DFA has no direct calculation of error so the relevance of classification was derived from Wilk’s lambda, canonical correlations, and calculating a proportional reduction-in-error statistic, Cohen’s kappa (Titus et al. 1984, Tabachnick and Fidell
1996). A MANOVA was run on each discriminant function to test for differences between the group centroids. If the resulting Wilk’s lambda value was not significant, the discriminant functions would not be useful for separating the groups, or in classifying observations. The canonical correlation coefficient is a measure of association which summarizes the degree of relatedness between the groups and the discriminant function 56
(Klecka 1980). Cohen’s kappa (6) was calculated to give a standardized measure of improved ability to correctly classify the territories using the discriminating variables compared to random assignment (standardized by the number of groups). The significance of this improvement over chance was tested using a Z-statistic (Klecka 1980,
Titus et al. 1984).
ii. Nest Plant
Only very basic analyses could be run on the nest data because overall sample sizes were low in both years and the mesoplot transects around nests did not include a measure of ground cover or water rank. As was the case for the microplot scale, I combined ALOALFL with SYMALFL and ALOWIFL with SYMWIFL nest data and tested for differences between the species only. The mesoplot variables that I analyzed were average height of vegetation (VEGHT), average bush stem density < 1 m
(STEMHITLO), overall vigour of the vegetation (VEGALIVE), percent cover
(BUSHCOV), and percent herbaceous cover (HERBCOV). Continuous variables were tested for normality and appropriate univariate tests were run. The categorical variables were treated in the same manner as described for song perches. 57
CHAPTER THREE
RESULTS
1. ARRIVAL AND TERRITORIALITY
In both 2004 and 2005, I detected Willow Flycatchers at the study sites one day earlier than Alder Flycatchers. The first Willow Flycatcher was detected on June 1 in
2004 and May 28 in 2005. Males often did not commence pre-dawn singing until a few days after their arrival so initial identification was based on call notes given by the birds.
Once males started defending territories, there were regular interactions between neighboring birds. Intraspecific interactions often were intense and involved bouts of counter-singing which occasionally escalated into aggressive gesturing such as tail- flicking and crest-raising. On numerous occasions throughout the breeding season I observed a male (occasionally accompanied by a female) chasing an intruder off a territory. However, I rarely observed physical contact between a territory-holder and an intruder and, when this did occur, it was very brief. At sites where both species were breeding, the birds defended interspecific territories and interspecific interactions occurred with behaviours and intensities similar to those observed in intraspecific interactions.
Willow Flycatcher territories, and to a lesser extent Alder Flycatchers territories, overlapped partially or completely with Yellow Warbler (Dendroica petechia) and
Wilson’s Warbler (Wilsonia pusilla) territories. Flycatchers always displaced warblers in any interactions. Red-winged Blackbirds (Agelaius phoeniceus) consistently displaced 58
Willow Flycatchers in interactions around beaver ponds. Similarly, American Robins
(Turdus migratorius) displaced both species in all interactions.
At sites where Willow Flycatchers and Alder Flycatchers were breeding allopatrically, territories were either very close to one another or patchily distributed, depending on the arrangement of suitable habitat. For example, in areas where a narrow strip of suitable habitat was located between a road and a body of water (e.g., Sibbald
Flats and SCT West), territories were arranged into a linear row within this narrow strip, each bordered by another territory on either side. In areas where suitable habitat was patchily distributed, often with large open meadows separating each patch (e.g., Lochend and Cataract Creek) territories were placed within the suitable patches. At many of these sites, the territories were arranged with one territory per habitat patch.
In areas where the species were breeding sympatrically, there were two common distribution patterns. At sites where suitable habitat was arranged into a single, long, narrow strip (e.g., along roads), the birds placed their territories such that Willow
Flycatcher territories were at one end of the strip and Alder Flycatcher territories were at the other end. For example, at SCT Creek there were five flycatcher territories placed in the tall willow bushes along Sibbald Creek Trail. Three territories at one end of the site backed onto the creek and were defended by Willow Flycatchers. Immediately next to these territories there were two Alder Flycatcher territories. In this arrangement only one pair of each species shared a common territory boundary. The other common pattern occurred where suitable habitat was spread over a very large area, such as Bryant Creek and Forestry Hut. At these sites, the territories were not placed in a single row, but 59 instead were arranged around the habitat features present at the sites. The Willow
Flycatcher territories were often placed at edges of creeks and beaver ponds and the Alder
Flycatcher territories were placed in the dryer habitat (Fig. 3.1). Because both of these sites had almost twice as many Alder Flycatchers as Willow Flycatchers, Willow
Flycatchers usually shared a common territory boundary (usually the side furthest from the water) with neighboring Alder Flycatchers. However, many Alder Flycatcher pairs shared territory boundaries only with conspecifics.
2. SAMPLE SIZE
I sampled 97 territories at 11 sites during the 2004 and 2005 breeding seasons (see
Table 3.1 for summary). There were 23 ALOWIFL territories at 3 sites, and 29
ALOALFL territories at 4 sites. There were 17 SYMWIFL and 28 SYMALFL territories sampled at 4 sites. I also located a total of 20 nests. Six were located at sites designated as sympatric (4 Willow, 2 Alder) and 14 were at sites that were designated as allopatric (8
Willow, 6 Alder).
3. HABITAT USE AT THE MICROPLOT SCALE
A. Song Perch
A summary of habitat variables measured at the microplot scale for song perches
(mean ± SE and median) is given in Appendix 1.
Both Willow Flycatchers and Alder Flycatchers used tree and bush vegetation types as their primary song perches (CPCATG). Overall, 76 of 97 birds used a willow Figure 3.1. Willow Flycatcher (line polygons) and Alder Flycatcher (dotted polygons) territories at the Bryant
Creek site. Birds defended stable, exclusive territories that were generally non-overlapping. Habitat features, including beaver ponds, creeks and forest boundaries are shown. Not all territories shown were sampled. 60 61
Table 3.1. Summary of study sites.
Site name Year Site type Alder pairs Willow pairs Total SCT East 2004 ALOALFL 7 0 7 SCT West 2004 ALOWIFL 0 4 4 SCT Creek 2004 SYMPATRIC 2 3 5 Sibbald Flats 2004 ALOWIFL 0 12 12 Bryant Creek 2004 SYMPATRIC 15 8 23 Indian Graves 2005 ALOALFL 5 0 5 Lochend 2005 ALOALFL 9 0 9 Cataract Creek 2005 ALOWIFL 0 7 7 Forestry Hut 2005 SYMPATRIC 9 5 14 Cadet Camp East 2005 ALOALFL 8 0 8 Cadet Camp West 2005 SYMPATRIC 2 1 3
TOTALS 57 40 97 62
bush as a primary song perch and 21 of 97 used a tree (either spruce or poplar). Each species used trees as song perches in approximately equal proportions (12 of 57 Alder
Flycatchers and 9 of 40 Willow Flycatchers).
i. Differences Between Species in Allopatry
There was no significant difference between the species in song perch type
(CPCATG) in allopatry (Table 3.2A). When birds using trees as song perches were included in the analysis of song perch height (CPHEIGHT), the extreme range of heights required non-parametric analysis. Alder Flycatchers had significantly taller song perches than did Willow Flycatchers (Table 3.2A). When the song perch data were re-analyzed without trees, the data were normally distributed and showed the same difference (Table
3.2A). Central stem densities of song bushes (CPSTEMS) did not differ significantly between species and Alder Flycatcher song perches were marginally further from neighboring bushes (CPNRBUSH, p < 0.10). Willow Flycatchers used song perches that had significantly more live branches and stems than did Alder Flycatchers (CPALIVE).
Willow Flycatcher perches had significantly more water and moss as ground cover, and
Alder Flycatcher perches had significantly more dead sedge, dead grass, and woody debris and/or leaf litter (CPGRCOV) (Table 3.2A).
Willow Flycatcher song perches were significantly closer to water than were those of Alder Flycatchers (CPNRWTR). Willow Flycatchers also had a significantly larger areas of open water close to their song perches (CPNRSIZE) than did Alder Flycatchers
(Table 3.2A). The distance from the song perch to the largest body of water on the bird’s Table 3.2. Summary of univariate analyses examining differences between Alder Flycatcher and Willow Flycatcher song perches at the microplot scale. Parts (A) and (B) report differences in habitat use between the species at the different sites types, and parts (C) and (D) report differences in habitat use by each species between the different site types.
A. ALLOPATRY (differences between species)
Habitat variables Species differences Test Test statistic Significance CPCATG ALFL = WIFL Chi-square P2 = 0.029, df = 1 p > 0.85 CPHEIGHT (with trees) ALFL > WIFL Mann-Whitney U U = 486.00 p < 0.01 CPHEIGHT (no trees) ALFL > WIFL ANOVA F = 21.198, df = 1,37 p < 0.01 CPSTEMS ALFL = WIFL Mann-Whitney U U = 198.5 p > 0.70 CPALIVE ALFL > WIFL Chi-square P2 = 7.374, df = 2 p < 0.03 CPGRCOV ALFL WIFL Chi-square P2 = 7.216, df = 2 p < 0.03 CPNRBUSH ALFL . WIFL Mann-Whitney U U = 424.0 p < 0.10 * CPNRWTR ALFL > WIFL Chi-square P2 = 21.89, df = 2 p < 0.01 CPNRSIZE ALFL < WIFL Chi-square P2 = 21.88, df = 2 p < 0.01 CPLRGWTR ALFL = WIFL Chi-square P2 = 2.18, df = 2 p > 0.30 CPLRGSIZE ALFL < WIFL Chi-square P2 = 34.15, df=2 p < 0.01
* marginally significant 63 Table 3.2. Continued
B. SYMPATRY (differences between species)
Habitat variables Species differences Test Test statistic Significance CPCATG ALFL = WIFL Chi-square P2 = 0.00, df = 1 p > 0.99 CPHEIGHT (with trees) ALFL = WIFL Mann-Whitney U U = 294.00 p > 0.15 CPHEIGHT (no trees) ALFL > WIFL Mann-Whitney U U = 222.5 p < 0.05 CPSTEMS ALFL > WIFL Mann-Whitney U U = 237.5 p < 0.02 CPALIVE ALFL = WIFL Chi-square P2 = 2.458, df = 2 p > 0.25 CPGRCOV ALFL = WIFL Chi-square P2 = 2.52, df = 2 p > 0.25 CPNRBUSH ALFL = WIFL Mann-Whitney U U = 218.5 p > 0.60 CPNRWTR ALFL = WIFL Chi-square P2 = 1.69, df = 2 p > 0.40 CPNRSIZE ALFL = WIFL Chi-square P2 = 1.45 , df = 2 p > 0.45 CPLRGWTR ALFL . WIFL Chi-square P2 = 5.67, df = 2 p < 0.06 * CPLRGSIZE ALFL . WIFL Chi-square P2 = 5.69, df=2 p < 0.06 *
* marginally significant 64 Table 3.2. Continued
C. ALDER FLYCATCHER (differences between site types)
Habitat variables Site differences Test Test statistic Significance CPCATG ALLO = SYMP Chi-square P2 = 0.338, df = 1 p > 0.55 CPHEIGHT (with trees) ALLO > SYMP Mann-Whitney U U = 562.5 p < 0.02 CPHEIGHT (no trees) ALLO > SYMP ANOVA F = 10.057, df = 1,43 p < 0.01 CPSTEMS ALLO < SYMP Mann-Whitney U U = 116.5 P < 0.01 CPALIVE ALLO = SYMP Chi-square P2 = 0.866, df = 2 p > 0.65 CPGRCOV ALLO . SYMP Chi-square P2 = 4.95, df = 2 p < 0.09 * CPNRBUSH ALLO = SYMP Mann-Whitney U U = 472.0 p > 0.25 CPNRWTR ALLO > SYMP Chi-square P2 = 8.025, df = 2 p < 0.02 CPNRSIZE ALLO < SYMP Chi-square P2 = 14.85, df = 2 p < 0.01 CPLRGWTR ALLO . SYMP Chi-square P2 = 5.81, df = 2 p < 0.06 * CPLRGSIZE ALLO < SYMP Chi-square P2 = 15.45, df=2 p < 0.01
* marginally significant 65 Table 3.2. Continued
D. WILLOW FLYCATCHER (differences between site types)
Habitat variables Site differences Test Test statistic Significance CPCATG ALLO = SYMP Chi-square P2 = 0.399, df = 1 p > 0.50 CPHEIGHT (with trees) ALLO = SYMP Mann-Whitney U U = 207.5 p > 0.70 CPHEIGHT (no trees) ALLO = SYMP Mann-Whitney U U = 124.5 p > 0.80 CPSTEMS ALLO = SYMP Mann-Whitney U U = 115.5 p > 0.85 CPALIVE ALLO = SYMP Chi-square P2 = 2.899, df = 2 p > 0.20 CPGRCOV ALLO = SYMP Chi-square P2 = 1.965, df = 2 p > 0.35 CPNRBUSH ALLO = SYMP Mann-Whitney U U = 156.0 p > 0.25 CPNRWTR ALLO = SYMP Chi-square P2 = 4.365, df = 2 p > 0.10 CPNRSIZE ALLO = SYMP Chi-square P2 = 1.44, df = 2 p > 0.45 CPLRGWTR ALLO > SYMP Chi-square P2 = 6.892, df = 2 p < 0.04 CPLRGSIZE ALLO = SYMP Chi-square P2 = 0.162, df=2 p > 0.90 66 67 territory (CPLRGWTR) did not differ significantly between species. There was a significant difference in the size of the largest body of water on the territory
(CPLRGSIZE). Willow Flycatcher territories had significantly larger areas of open water
(including sedge marshes) present, and Alder Flycatcher territories had significantly more damp grass, leaf litter, or woody debris instead of open water (Table 3.2A).
ii. Differences Between Species in Sympatry
As in allopatry, there was no significant difference in song perch type (CPCATG) between species in sympatry (Table 3.2B). In contrast to the situation in allopatry, no significant difference was found in song perch heights when trees were included in the analysis (CPHEIGHT). However, when trees were removed from the analysis, there was a significant difference between the species, with Alder Flycatchers having taller song perches (Table 3.2B).
There was a significant difference in the central stem density (CPSTEMS) of the song perches between species, with Alder Flycatcher song perches having a higher stem density than Willow Flycatchers. There were no significant differences between species in vigor of song perches (CPALIVE), mean distance to nearest neighboring bush
(CPNRBUSH), or type of ground cover (CPGRCOV) under the song perches (Table
3.2B).
In contrast to the situation in allopatry, there were no significant differences between species in distance to nearest water (CPNRWTR), or in size of water that was nearest to the song perch (CPNRSIZE). The distance from the song perch to the largest 68 body of water on the territory (CPLRGWTR) and the size of that water (CPLRGSIZE) were marginally different between species (p < 0.06). Willow Flycatchers were marginally closer to the largest body of water on territory and were more likely to have large, open bodies of water present than were Alder Flycatchers.
iii. Differences Within Species Between Site Types
Alder Flycatchers showed a number of significant differences in habitat features of their song perches between allopatry and sympatry (Table 3.2C). ALOALFL perches were taller (CPHEIGHT - with or without trees), had lower stem densities (CPSTEMS), and were farther from the nearest body of water (CPNRWTR) than SYMALFL perches
(Table 3.2C). Ground cover differences (CPGRCOV) were marginally significant (p <
0.09), with SYMALFL perches having more water and moss as ground cover beneath the song perch, and ALOALFL perches having more leaf litter and dead grass and sedge as ground cover. The size of the water nearest to the perch (CPNRSIZE) also differed significantly between site types, with SYMALFL territories having larger and more open types of water close to the song perch than did ALOALFL territories. The difference in the distance from the perch to the largest body of water on the territory (CPLRGWTR) was marginally significant (p < 0.06), with SYMALFL perches being closer to large, open water than ALOALFL perches (Appendix 1). The size of water on the territories was more frequently a large, open body of water (including sedge marshes) in sympatry than in allopatry (CPLRGSIZE). 69
With one exception, Willow Flycatchers showed no significant differences in habitat features of song perches between allopatry and sympatry (Table 3.2D). The exception was distance from the song perch to the largest body of water on the territory
(CPLRGWTR), which was less in sympatry than in allopatry (Appendix 1).
B. Nest Plant
A summary of habitat variables measured at the microplot scale for nest plants
(mean ± SE and median) is given in Appendix 2.
Willow Flycatchers occasionally used small spruce trees as nest plants (3 of 12 nests) whereas Alder Flycatchers used only willow bushes. However, this differences was not significant (CPCATG) (Table 3.3). Willow Flycatchers used significantly taller nest bushes than did Alder Flycatchers (CPHEIGHT) (trees not included) and had marginally more live branches in the nest bush (p < 0.055) (CPALIVE). The species had significantly different types of ground cover under the nest plants (CPGRCOV). Willow
Flycatchers had damp, mossy ground cover and Alder Flycatchers had dry, dead sedge and dead grass. The distance to the nearest neighboring bush (CPNRBUSH) was also significantly less for Willow Flycatcher nests than Alder Flycatcher nests (Table 3.3).
Willow Flycatcher nests are placed higher than are Alder Flycatcher nests (t =
-5.23, df = 18, p < 0.000, this study). Because of this difference, and differences in nest construction, Alder Flycatcher nests were well concealed and more difficult to locate than were Willow Flycatcher nests. Table 3.3. Summary of univariate analyses examining differences between Alder Flycatcher and Willow Flycatcher nest plants at the microplot scale. Because of small sample sizes, data from both site types were combined for each species.
Habitat variable Species difference Test Test statistic Significance CPCATG ALFL = WIFL Chi-square P2 = 2.353, df = 1 p > 0.125 CPHEIGHT ALFL < WIFL Mann-Whitney U U = 21.00 p < 0.036 CPALIVE ALFL . WIFL Chi-square P2 = 5.859, df = 2 p < 0.055 * CPGRCOV ALFL WIFL Chi-square P2 = 16.212, df = 2 p < 0.001 CPNRBUSH ALFL > WIFL Mann-Whitney U U = 80.0 p < 0.005
* marginally significant 70 71
4. HABITAT USE AT THE MESOPLOT SCALE
A. Song Perch
i. Univariate Analyses
A summary of habitat variables measured at the mesoplot scale for song perches
(mean ± SE and median) is given in Appendix 3.
Parametric ANOVAs or non-parametric Kruskal-Wallis ANOVAs were run for each variable across the four species/site type categories. All variables showed significant differences among the categories (Table 3.4). Multiple pairwise comparisons were conducted on each habitat variable to test for differences between the species within a site type, and for differences between the site types within each species.
a) Differences between species in allopatry
Seven of ten habitat variables differed significantly between the species in allopatry (Table 3.5). The area around Alder Flycatcher song perches had taller vegetation (LOGHEIGHT), more herbaceous cover (ASINHERB), and significantly more leaf litter (ASINLITTER) and dead sedge/grass (SQRTDHERB) on the ground than did the area around Willow Flycatcher song perches. Willow Flycatchers had significantly wetter (SQRTRANK) and mossier (SQRTMOSS) habitat around their song perches, and had denser vegetation (SQRTSTEMS) than did Alder Flycatchers (Table 3.5).
b) Differences between species in sympatry 72
Table 3.4. Summary of univariate analyses (ANOVA and Kruskal-Wallis) on the transformed mesoplot habitat variables testing for differences among the four species/site type categories.
Habitat variables df Test statistic Significance
SQRTRANK 3, 93 F = 34.763 p < 0.001
LOGHEIGHT 3, 93 F = 6.583 p < 0.001
SQRTSTEMS 3, 93 F = 17.180 p < 0.001
X3LIVEDEAD 3 KW = 12.239 p < 0.01
X2BUSH 3, 93 F = 3.651 p < 0.02
ASINHERB 3 KW = 13.114 p < 0.005
SQRTMOSS 3 KW = 21.160 p < 0.001
SQRTWATER 3 KW = 25.896 p < 0.001
ASINLITTER 3, 93 F = 5.554 p < 0.005
SQRTDHERB 3 KW = 19.942 p < 0.001 Table 3.5. Summary of multiple pairwise comparisons (with Dunn-Sidak corrections) of song perch variables at the mesoplot scale.
Comparisons between the species at the different site types and between site types for each species are shown.
Species differences Site type differences Habitat variables Allopatry Sympatry ALFL WIFL LOGHEIGHT ALFL > WIFL* NONE SYM < ALLO* NONE SQRTRANK ALFL < WIFL* ALFL < WIFL* SYM > ALLO* SYM > ALLO* SQRTSTEMS ALFL < WIFL* NONE SYM > ALLO* NONE X3ALIVE NONE NONE NONE NONE X2BUSH NONE NONE SYM > ALLO* NONE ASINHERB ALFL > WIFL* NONE NONE NONE SQRTMOSS ALFL < WIFL* NONE SYM > ALLO* NONE SQRTWATER NONE ALFL < WIFL* NONE NONE ASINLITTER ALFL > WIFL* NONE NONE NONE SQRTDHERB ALFL > WIFL* NONE NONE NONE * p < 0.05 after Dunn-Sidak correction 73 74
Only two habitat variables differed between the species in sympatry. Both variables related to water cover (SQRTRANK and SQRTWATER), with Willow
Flycatchers having significantly wetter habitat around their song perches than did Alder
Flycatchers (Table 3.5).
c) Differences within species between site types
Alder Flycatchers showed more differences in habitat use between allopatric and sympatric sites than did Willow Flycatchers (Table 3.5). The areas around SYMALFL song perches had shorter vegetation (LOGHEIGHT), higher stem density
(SQRTSTEMS), more bush cover (X2BUSH), and mossier ground cover (SQRTMOSS) than did the areas around ALOALFL perches. The habitat around SYMALFL perches was also significantly wetter (SQRTRANK) than that around ALOALFL perches.
Willow Flycatchers showed only a single habitat difference between site types
(SQRTRANK), with the areas around SYMWIFL perches being much wetter than the areas around ALOWIFL perches (Table 3.5).
ii. Multivariate Analyses
In the PCA, the first three PCs had eigenvalues > 1 and explained > 74% of the total variance. Each variable loaded strongly on one of the PCs (Table 3.6).
PC1 explained > 32% of the variance, with ASINHERB and SQRTDHERB loading positively and SQRTSTEMS, X2BUSH, and SQRTMOSS loading negatively
(Table 3.6). Territories with positive scores on PC1 had herbaceous vegetation and dead 75
Table 3.6. Varimax rotated factor loadings for the ten song-perch habitat variables on the three principal components at the mesoplot scale. Eigenvalues and percentages of total variance explained by each principal component are shown.
Factor loadingsa Habitat variable PC1 PC2 PC3 SQRTRANK -0.290 0.683 -0.539 LOGHEIGHT -0.021 -0.688 -0.021 X3LIVEDEAD 0.024 0.138 0.832 SQRTSTEMS -0.795 0.416 -0.005 X2BUSH -0.860 -0.105 0.167 ASINHERB 0.870 0.208 0.043 SQRTMOSS -0.740 0.404 0.029 SQRTWATER 0.207 0.605 -0.650 ASINLITTER 0.038 -0.889 -0.099 SQRTDHERB 0.695 0.063 0.402 Total variance (%) 32.9 25.1 16.1 Eigenvalue 3.29 2.51 1.61 a Loadings with r > | 0.65 | are shown in bold face 76 sedge and grass as ground cover, and territories with negative scores had dense bushes and mossy ground cover. ALOALFL territory scores were highly positive and
ALOWIFL, SYMALFL, and SYMWIFL territory scores were negative (Fig. 3.2). Alder
Flycatcher territories showed a distinctive sign reversal from highly positive scores in allopatry to highly negative scores in sympatry (Fig. 3.2). PC1 scores differed
significantly among the four groups (ANOVA, F3, 93 = 9.259, p < 0.001). Post-hoc tests indicated that Alder and Willow Flycatcher territories differed significantly in allopatry
(ALOALFL vs. ALOWIFL, p < 0.001), but not in sympatry (SYMALFL vs. SYMWIFL, p > 0.9). In addition, Alder Flycatcher territories differed significantly between site types
(ALOALFL vs. SYMALFL, p < 0.01). Willow Flycatcher territories did not differ significantly between site types (ALOWIFL vs. SYMWIFL, p > 0.9).
PC2 explained > 25% of the variance, with SQRTRANK loading positively and
LOGHEIGHT and ASINLITTER loading negatively (Table 3.6). Positive scores on PC2 indicated wet territories and negative scores indicated tall vegetation and leaf litter/woody debris on the ground (this was often because of the presence of trees). ALOALFL and
SYMALFL territories had negative scores and ALOWIFL and SYMWIFL territories had positive scores (Fig. 3.2). PC2 scores differed significantly among the four groups
(ANOVA, F3, 93 = 9.125, p < 0.001). Post-hoc tests indicated significant differences between species in allopatry (ALOALFL vs. ALOWIFL, p < 0.01) and in sympatry
(SYMALFL vs. SYMWIFL, p < 0.04). The territories of neither species differed significantly between site types. 77
Figure 3.2. Mean scores (± SE) on the first three principal components for each species/site type category at the mesoplot scale. Y-axis labeled according to the highest component loadings for variables. 78
PC3 explained > 16% of the variance, with X3LIVEDEAD loading positively and
SQRTWATER loading negatively (Table 3.6). Positive scores on PC3 indicated territories with mostly dead vegetation and negative scores indicated very wet territories.
ALOALFL and SYMALFL territories had positive scores and ALOWIFL and SYMWIFL territories had negative scores (Fig. 3.2). PC3 scores differed significantly among the
four groups (ANOVA, F3, 93 = 9.304, p < 0.001). Post-hoc tests indicated significant differences between species in allopatry (ALOALFL vs. ALOWIFL, p < 0.02) and in sympatry (SYMALFL vs. SYMWIFL, p < 0.01). The territories of neither species differed significantly between site types.
Bivariate scatterplots of the PC scores showed that SYMWIFL territories and
ALOWIFL territories were scattered widely in the multivariate space defined by the PCs, whereas ALOALFL territories and SYMALFL territories formed generally more concentrated clusters (Figs. 3.3 and 3.4). The 95% confidence ellipses around the Willow
Flycatcher group centroids were larger than those around the Alder Flycatcher group centroids (Figs. 3.3 and 3.4). The confidence ellipses around the ALOALFL group centroids were consistently separated from the other three groups in both graphs. The
SYMALFL confidence ellipses overlapped broadly with ALOWIFL ellipses in both plots, and to a small extent with the SYMWIFL ellipse in the plot of PC1 against PC2 (Fig.
3.3). The ALOWIFL and SYMWIFL confidence ellipses overlapped broadly in both scatterplots (Figs. 3.3 and 3.4). 79
Figure 3.3. Bivariate scatterplot of PC1 scores vs. PC2 scores at the mesoplot scale.
Points for individual territories are indicated by symbols as follows: ALOALFL ( );
ALOWIFL (X); SYMALFL ( ); and SYMWIFL ( ). Group centroids for each species/site type category are indicated with a 95% confidence ellipse. Ellipses are identified by a two-letter abbreviation as follows: ALOALFL (AA); ALOWIFL (AW);
SYMALFL (SA); and SYMWIFL (SW). 80
Figure 3.4. Bivariate scatterplot of PC1 scores vs. PC3 scores at the mesoplot scale.
Points for individual territories are indicated by symbols as follows: ALOALFL ( );
ALOWIFL (X); SYMALFL ( ); and SYMWIFL ( ). Group centroids for each species/site type category are indicated with a 95% confidence ellipse. Ellipses are identified by a two-letter abbreviation as follows: ALOALFL (AA); ALOWIFL (AW);
SYMALFL (SA); and SYMWIFL (SW). 81
MANOVA of the PC scores of all territories (full dataset) showed significant differences among the four species/site type categories (Table 3.7). DFA of the full dataset generated one significant canonical discriminant function that explained 95% of the variance (canonical correlation = 0.782, p < 0.001). Jackknifed DFA of the full dataset assigned 54% of the territories to the correct category. ALOALFL territories had the highest rate of correct classification (79%), followed by SYMWIFL territories (53%),
SYMALFL territories (46%), and ALOWIFL territories (30%). For the analysis of the full dataset, classification based on DFA made 37% fewer errors than would be expected by random assignment (6 = 0.37, p < 0.001).
MANOVA of the PC scores of allopatric territories showed significant differences between species (Table 3.7). DFA of the PC scores of allopatric territories identified one canonical discriminant function that explained 100% of the variance
(canonical correlation = 0.822, p < 0.001). Jackknifed DFA correctly assigned 89% of the territories to the correct species (91% Willow Flycatcher, 86% Alder Flycatcher).
DFA made 77% fewer errors than would be expected by chance (6 = 0.77, p < 0.001).
MANOVA of the PC scores of sympatric territories showed significant differences between species (Table 3.7). DFA of the PC scores of sympatric territories identified one canonical discriminant function that explained 100% of the variance
(canonical correlation = 0.666, p < 0.001). Jackknifed DFA correctly assigned 80% of the territories to the correct species (89% Alder Flycatchers, 65% Willow Flycatchers).
DFA made 57% fewer errors than would be expected by chance (6 = 0.57, p < 0.001). 82
Table 3.7. Summary of MANOVA analyses of the PC scores at the mesoplot scale.
Results are reported for differences among all four species/site type categories (full dataset) in addition to differences between the species within a particular site type, and differences within a species between the site types.
Wilks’ lambda Approximate F df Significance Full Dataset 0.358 12.879 9, 221 p < 0.001 Allopatric 0.325 33.229 3, 48 p < 0.001 Sympatric 0.556 10.915 3, 41 p < 0.001 Alder Flycatcher 0.633 10.253 3, 53 p < 0.001 Willow Flycatcher 0.816 2.699 3, 36 p > 0.060 83
To determine whether territories of each species could be classified to the correct site type, I ran MANOVA and DFA on the within-species datasets. MANOVA of the PC scores of Alder Flycatcher territories showed significant differences between site types
(Table 3.7). DFA of the PC scores of Alder Flycatcher territories identified one canonical disciminant function that explained 100% of the variance (canonical correlation = 0.606, p < 0.001). Jackknifed DFA correctly assigned 77% of the territories to the correct site type (83% allopatry, 71% sympatry). DFA made 54% fewer errors than would be expected by chance (6 = 0.54, p < 0.001).
MANOVA of the PC scores of Willow Flycatcher territories showed only a marginally significant difference between site types (Table 3.7). DFA of the PC scores of
Willow Flycatcher territories identified one marginally significant canonical disciminant function (canonical correlation = 0.429, p > 0.06). Jackknifed DFA correctly assigned
73% of the territories to the correct site type (83% allopatry, 53% sympatry).
B. Nest Plant
A summary of habitat variables measured at the mesoplot scale for nest plants
(mean ± SE and median) is given in Appendix 4.
No significant differences in nesting habitat were noted between the species
(Mann-Whitney U, all p > 0.05). However, Willow Flycatchers had marginally denser bushes around the nest than did Alder Flycatchers (Mann-Whitney U, p < 0.08). 84
5. HABITAT USE AT THE MACROPLOT SCALE
A. Univariate Analyses
A summary of habitat variables measured at the macroplot scale for song perches
(mean ± SE and median) is given in Appendix 5.
Parametric ANOVAs or non-parametric Kruskal-Wallis ANOVAs were run for each variable across the four species/site type categories. All but one of the variables showed significant differences among categories (Table 3.8) and were analyzed further using multiple pairwise comparisons. The variable X2BUSH was marginally different among the categories (p < 0.06) and was included in subsequent analyses.
Fewer multiple comparisons were significant at the macroplot scale (Table 3.9) than at the mesoplot analysis (compare with Table 3.5). Significant differences were noted between species in allopatry with Alder Flycatcher territories having taller vegetation (LOGHEIGHT) and more dead sedge/grass as ground cover (SQRTDHERB) than did Willow Flycatcher territories (Table 3.9). Willow Flycatcher territories were significantly wetter (SQRTRANK), with denser bushes (SQRTSTEMS) and mossier ground cover (SQRTMOSS) than those of Alder Flycatchers. Differences between the species in sympatry were the same as those at the mesoplot scale, with Willow
Flycatchers having significantly wetter territories than did Alder Flycatchers
(SQRTRANK and SQRTWATER) (Table 3.9).
Alder Flycatchers showed fewer differences in habitat use between allopatric and sympatric sites at the macroplot scale (Table 3.9) than they did at the mesoplot scale 85
Table 3.8. Summary of univariate analyses (ANOVA and Kruskal-Wallis) on the ten transformed macroplot habitat variables testing for differences among the four species/site type categories.
Habitat variables df Test statistic Significance
SQRTRANK 3, 93 F = 21.46 p < 0.001
LOGHEIGHT 3, 93 F = 5.78 p < 0.001
SQRTSTEMS 3, 93 F = 12.18 p < 0.001
X2LIVEDEAD 3 KW = 19.71 p < 0.001
X2BUSH 3 KW = 7.57 p < 0.060*
ASINHERB 3 KW = 8.64 p < 0.040
SQRTMOSS 3, 93 F = 10.00 p < 0.001
SQRTWATER 3 KW = 25.21 p < 0.001
ASINLITTER 3, 93 F = 3.70 p < 0.020
SQRTDHERB 3, 93 F = 11.22 p < 0.001
* marginally significant and included in subsequent analyses. Table 3.9. Summary of multiple pairwise comparisons (with Dunn-Sidak corrections) of song perch variables at the macroplot scale.
Comparisons between the species at the different site types and between site types for each species are shown.
Species differences Site type differences Habitat variables Allopatry Sympatry ALFL WIFL LOGHEIGHT ALFL > WIFL* NONE NONE NONE SQRTRANK ALFL < WIFL* ALFL < WIFL* SYM > ALLO* NONE SQRTSTEMS ALFL < WIFL* NONE SYM > ALLO* NONE X2ALIVE NONE NONE NONE NONE X2BUSH NONE NONE NONE NONE ASINHERB NONE NONE NONE NONE SQRTMOSS ALFL < WIFL* NONE SYM > ALLO* NONE SQRTWATER NONE ALFL < WIFL* NONE NONE ASINLITTER NONE NONE NONE NONE SQRTDHERB ALFL > WIFL* NONE NONE NONE * p < 0.05 after Dunn-Sidak correction 86 87
Table 3.5). In sympatry, Alder Flycatcher territories were wetter (SQRTRANK) and had higher stem densities (SQRTSTEMS) and mossier ground cover (SQRTMOSS) than did territories in allopatry. Willow Flycatchers showed no significant differences at this scale between allopatric and sympatric sites (Table 3.9).
B. Multivariate Analyses
In the PCA, the first three PCs had eigenvalues > 1 and explained > 76% of the total variance. Each variable loaded strongly on one of the PCs (Table 3.10).
PC1 explained > 36% of the variance, with ASINHERB and SQRTDHERB loading negatively and SQRTSTEMS, X2BUSH, and SQRTMOSS loading positively
(Table 3.10). Territories with negative scores on PC1 had herbaceous vegetation and dead sedge/grass as ground cover. Territories with positive scores had dense bushes and mossy ground cover. ALOALFL territory scores were highly negative and ALOWIFL,
SYMALFL, and SYMWIFL territory scores were positive (Fig. 3.5). Alder Flycatcher territories showed a distinctive sign reversal from highly negative scores in allopatry to positive scores in sympatry (Fig. 3.5). PC1 scores differed significantly among the four
groups (ANOVA, F3,93 = 13.383, p < 0.001). Post-hoc tests indicated Alder and Willow
Flycatcher territories differed significantly in allopatry (ALOALFL vs. ALOWIFL, p <
0.001), but not in sympatry (SYMALFL vs. SYMWIFL, p > 0.9). In addition, Alder
Flycatcher territories differed significantly between site types (ALOALFL vs. 88
Table 3.10. Non-rotated factor loadings for the ten song-perch habitat variables on the three principal components at the macroplot scale. Eigenvalues and percentages of total variance explained by each principal component are also shown.
Factor loadingsa Habitat variables PC1 PC2 PC3 SQRTRANK 0.616 -0.687 -0.099 LOGHEIGHT 0.121 0.686 -0.049 X2LIVEDEAD -0.180 0.192 0.674 SQRTSTEMS 0.789 0.102 0.400 X2BUSH 0.741 0.577 0.056 ASINHERB -0.846 -0.349 0.168 SQRTMOSS 0.790 -0.134 0.406 SQRTWATER 0.254 -0.817 -0.315 ASINLITTER -0.003 0.661 -0.649 SQRTDHERB -0.797 0.142 0.338 Total variance (%) 36.38 25.88 14.58 Eigenvalue 3.638 2.588 1.458 a Loadings with r > | 0.65 | are shown in bold face 89
Figure 3.5. Mean scores (± SE) on the first three principal components for each species/site type category at the macroplot scale. Y-axis labeled according to the highest component loadings for variables. 90
SYMALFL, p < 0.01). Willow Flycatcher territories did not differ significantly between site types (ALOWIFL vs. SYMWIFL, p > 0.9).
PC2 explained > 25% of the variance, with SQRTRANK and SQRTWATER loading negatively and LOGHEIGHT and ASINLITTER loading positively (Table 3.10).
Negative scores on PC2 indicated very wet territories, and positive scores indicated tall vegetation and leaf litter/woody debris on the ground. ALOALFL and SYMALFL territories had positive scores and ALOWIFL and SYMWIFL territories had negative
scores (Fig. 3.5). PC2 scores differed significantly among the four groups (ANOVA, F3,93
= 13.035, p < 0.001). Post-hoc tests indicated significant differences between species in allopatry (ALOALFL vs. ALOWIFL, p < 0.001) and in sympatry (SYMALFL vs.
SYMWIFL, p < 0.001). The territories of neither species differed significantly between site types.
PC3 explained > 14% of the variance, with X2LIVEDEAD loading positively
(Table 3.10). Territories with a positive score on PC3 had largely dead vegetation.
ALOALFL, ALOWIFL, and SYMALFL territories had slightly positive scores and
SYMWIFL territories had slightly negative scores (Fig. 3.5). PC3 scores did not differ
significantly among the four groups (ANOVA, F3,93 = 1.266, p > 0.20).
Bivariate scatterplots of the PC scores showed that SYMWIFL territories,
ALOWIFL territories and, SYMALFL territories were scattered widely in the multivariate space defined by the PCs (Figs. 3.6 and 3.7). As was the case for the mesoplot scale,
ALOALFL territories formed generally more concentrated clusters and the 95% confidence ellipses around the ALOALFL group centroids were consistently separated 91
Figure 3.6. Bivariate scatterplot of PC1 scores vs. PC2 scores at the macroplot scale.
Points for individual territories are indicated by symbols as follows: ALOALFL ( );
ALOWIFL (X); SYMALFL ( ); and SYMWIFL ( ). Group centroids for each species/site type category are indicated with a 95% confidence ellipse. Ellipses are identified by a two-letter abbreviation as follows: ALOALFL (AA); ALOWIFL (AW);
SYMALFL (SA); and SYMWIFL (SW). 92
Figure 3.7. Bivariate scatterplot of PC1 scores vs. PC3 scores at the macroplot scale.
Points for individual territories are indicated by symbols as follows: ALOALFL ( );
ALOWIFL (X); SYMALFL ( ); and SYMWIFL ( ). Group centroids for each species/site type category are indicated with a 95% confidence ellipse. Ellipses are identified by a two-letter abbreviation as follows: ALOALFL (AA); ALOWIFL (AW);
SYMALFL (SA); and SYMWIFL (SW). 93 from the other three groups in both graphs (Figs. 3.6 and 3.7). In Figure 3.6, the
SYMALFL confidence ellipse was completely separated from the other three groups, and the ALOWIFL and SYMWIFL ellipses overlapped broadly with each other. In Figure
3.7, SYMWIFL and SYMALFL confidence ellipses were almost completely contained within the ALOWIFL ellipse.
MANOVA of the PC scores of all territories (full dataset) showed significant differences among the four species/site type categories (Table 3.11). DFA of the full dataset generated one significant canonical discriminant function that accounted for 94% of the variance (canonical correlation = 0.748, p < 0.001). Jackknifed DFA of the full dataset assigned 57% of the territories to the correct category. ALOALFL territories had the highest rate of correct classification (76%), followed by SYMALFL territories (61%),
SYMWIFL territories (53%), and ALOWIFL territories (30%). For the analysis on the full dataset, classification based on DFA made 44% fewer errors than would be expected by random assignment (6 = 0.44, p < 0.001).
MANOVA of the PC scores of allopatric territories showed significant differences between species (Table 3.11). DFA of the PC scores of allopatric territories identified one canonical discriminant function that explained 100% of the variance (canonical correlation = 0.788, p < 0.001). Jackknifed DFA correctly assigned 83% of the territories to the correct species (83% Willow Flycatchers, 83% Alder Flycatchers). DFA made
65% fewer errors than would be expected by chance (6 = 0.65, p < 0.001).
MANOVA of the PC scores of sympatric territories showed significant differences between species (Table 3.11). DFA of the PC scores of sympatric territories 94
Table 3.11. Summary of MANOVA analyses of the PC scores at the macroplot scale.
Results are reported for differences among all four species/site type categories (full dataset) in addition to differences between the species within a particular site type, and differences within a species between the site types.
Wilks’ lambda Approximate F df Significance Full Dataset 0.406 10.999 9, 221 p < 0.001
Allopatric 0.379 26.275 3, 48 p < 0.001 Sympatric 0.584 9.730 3, 41 p < 0.001 Alder Flycatcher 0.636 10.095 3, 53 p < 0.001 Willow Flycatcher 0.881 1.626 3, 36 p > 0.200 95 identified one canonical discriminant function that explained 100% of the variance
(canonical correlation = 0.645, p < 0.001). Jackknifed DFA correctly assigned 82% of the territories to the correct species (93% Alder Flycatchers, 65% Willow Flycatchers).
DFA made 62% fewer errors than would be expected by chance (6 = 0.62, p < 0.001).
To determine whether territories of each species could be classified to the correct site type, I ran MANOVA and DFA on the within-species datasets. MANOVA of the PC scores of Alder Flycatcher territories showed significant differences between site types
(Table 3.11). DFA of the PC scores of Alder Flycatcher territories identified one canonical disciminant function that explained 100% of the variance (canonical correlation
= 0.603, p < 0.001). Jackknifed DFA correctly assigned 75% of the territories to the correct site type (76% allopatry, 75% sympatry). DFA made 51% fewer errors than would be expected by chance (6 = 0.51, p < 0.001).
MANOVA on the PC scores of Willow Flycatcher territories showed no significant differences between site types (Table 3.11) and no significant canonical discriminant function was identified (canonical correlation = 0.345, p > 0.2). 96
CHAPTER FOUR
DISCUSSION
1. HABITAT USE IN ALBERTA
Most breeding sites in the area of regional sympatry in southwestern Alberta have either Alder or Willow flycatchers present, and local sympatry is not a widespread phenomenon. The rarity of local coexistence in the province is largely because each species is associated with different environmental conditions, mainly along hydrological and vegetation gradients, and the two species are thus spatially segregated by differential habitat use. The species were found in direct contact only where environmental conditions produced a mosaic of habitats at the boundary of their respective breeding ranges. When in local sympatry, the species showed microspatial segregation along habitat gradients and vigorously defended interspecific territories.
Prominent qualitative differences in habitat use were visible on the territories of each species in local allopatry, including the amount of water cover (especially in the early part of the breeding season) and the structure and composition of the vegetation.
ALOALFL territories often were located in dry, hilly areas adjacent to open meadows, and contained willow bushes that were very tall (3 - 4 m), and which looked like small, divaricately-branching trees. These arborescent willows formed thickets that were partially dead and were patchily distributed in meadows and pastures. In contrast,
ALOWIFL territories were located in flat, low-lying areas that always contained still or moving water and had saturated soil and mossy ground cover. The willow bushes on 97
ALOWIFL territories were lower (1 - 3 m), wider, denser, and mostly alive (Appendices
1, 3, 5). These bushes grew as isolated clumps along edges of streams, beaver ponds, and sedge marshes, or as long, narrow thickets in roadside ditches.
These qualitative differences in habitat use by locally allopatric Alder and Willow flycatchers were reflected in the quantitative habitat data at all three scales of measurement. Significant, or marginally significant, differences were found between the species on all but three microplot variables (Table 3.2A) and all but one mesoplot variable (Table 3.5). Fewer habitat variables differed significantly between species at the macroplot scale (Table 3.10). However, differences were present at all sampling scales for the variables relating to water cover, ground cover, and vegetation structure, indicating that these differences were present over entire territories at sites of local allopatry. Multivariate analyses showed that PC scores for ALOALFL and ALOWIFL territories differed significantly on all three principal components at the mesoplot scale and on PC1 and PC2 at the macroplot scale (Figs. 3.2 and 3.5). All bivariate scatterplots on PC scores showed consistent separation between the confidence ellipses for the
ALOALFL and ALOWIFL group centroids (Figs. 3.3, 3.4, 3.6 and 3.7). Additionally,
DFA of the PC scores classified territories of each species in allopatry with a high rate of success (89% correct classification at the mesoplot scale; 83% at the macroplot scale) indicating distinctive habitat use by each species in allopatry.
Local sympatry occurred at sites where various habitat gradients overlapped, creating a mixture of wet and dry areas, as well as heterogeneous vegetation structure and composition. Coexistence at these sites was accompanied by microspatial segregation 98 along the visible hydrological gradient, with SYMWIFL territories located in the wetter areas and SYMALFL territories located in the dryer patches (e.g., Bryant Creek, see Fig.
3.1). Quantitative habitat data reflected the segregation of the species along the hydrological gradient in local sympatry. Significant or marginally significant differences were found between the species on all habitat variables relating to water cover at all scales of measurement (Tables 3.2B, 3.5 and 3.10). However, fewer habitat variables relating to vegetation structure differed between species in local sympatry than in local allopatry at all scales (Tables 3.2B, 3.5 and 3.10). This result is in part because of the close proximity of territories at sympatric sites (i.e., a SYMALFL perch could be < 50 m from a SYMWIFL perch), thus increasing the possibility that transects on different territories may have been only a few meters apart.
Multivariate analyses showed that PC scores for SYMALFL and SYMWIFL territories did not differ significantly on PC1 at any scale, but did differ significantly on
PC2 and PC3 at the mesoplot scale and PC2 on the macroplot scale (Figs. 3.2 and 3.5).
Because water cover is an important segregating factor for the species in sympatry, PCs that are not correlated with habitat variables relating to water cover would not be expected to show significant differences between the species. PC1 does not contain a measure of water cover at either scale (Tables 3.6 and 3.10), and so it is not surprising that no significant difference was detected. Habitat variables relating to water cover loaded strongly on PC2 and PC3 at the mesoplot scale, and PC2 at the macroplot scale, resulting in significant differences being detected between species on these PCs.
Similarly, all of the bivariate scatterplots showed consistent overlap between SYMALFL 99 and SYMWIFL confidence ellipses on PC1 (x-axes), but separation was observed on PC2 and PC3 (y-axes) (Figs. 3.3, 3.4, 3.6 and 3.7). Classification success using DFA for territories of each species in sympatry was only slightly lower than that for territories in allopatry (80% correct classification at the mesoplot scale; 82% at the macroplot scale).
Classification success likely remained high because of strong discriminating power of the
PCs that contained measures of water cover.
I also found that Alder and Willow flycatchers used different microhabitats for nesting. Willow Flycatchers placed their nests over wetter ground than did Alder
Flycatchers, and Willow Flycatcher nest plants were significantly taller, closer to neighboring bushes, and had more live stems than did Alder Flycatcher nest plants (Table
3.3). The difference in height of the nest plants between the species (WIFL > ALFL) is opposite to that seen for the song perches (ALFL > WIFL). Although Willow Flycatcher territories tended to have shorter vegetation overall than did Alder Flycatcher territories, female Willow Flycatchers appear to have used tall bushes preferentially for nesting
(Appendix 2). This preference is not surprising because Willow Flycatchers place their nests significantly higher than do Alder Flycatchers and thus require taller bushes for nest building. In contrast, Alder Flycatcher females placed their nests very low to the ground and tended to use low bushes for nesting if they were present on the territory. Nest height and vegetation density have consequences for nest concealment and nests that are placed higher up in a bush may be more visible to predators and nest parasites (Holway 1991,
Sedgwick and Knopf 1992, Cain et al. 2003). Therefore, Willow Flycatchers may place their nests preferentially in very dense, live willow thickets to maximize nest concealment 100 at the higher heights. I also found that song perches of both species were taller than nest plants, which is expected considering the different functional requirements for nest plants
(female-selected) and song perches (male-selected) (Sedgwick and Knopf 1992).
Although most nesting-habitat variables differed between the species at the microplot scale (Table 3.3), no differences were detected between any of the five mesoplot variables. This is unexpected because differences were detected at the mesoplot scale for the song perches, and nests were often constructed < 10 m from the song perches. This result could be attributable to the fact that no ground or water cover variables were measured at the mesoplot scale for nests, and these were key differentiating variables noted around the song perches. Additionally, small sample sizes may have made any differences present between the species harder to detect.
The greatest number of differences in habitat use between species at both site types occurred at the finest scales of sampling and fewest differences occurred at the coarsest scale. This is not surprising because the finer sampling scales were designed to detect subtle differences in habitat use on each territory, whereas macroplot transects were placed at random points throughout the territories and captured coarser habitat features. The number of habitat differences detected between the territories of the two species using the different sampling scales highlights the importance of multiscale sampling. Territories are highly heterogeneous in terms of physiognomy and floristic composition and multiscale sampling is required to account for this variation (Wiens
1989b, Matsuoka et al. 1997). 101
I detected fewer differences in habitat use between Alder and Willow flycatchers where they bred in sympatry than in allopatry at all sampling scales. This pattern of differential resource use in allopatry and more similar resource use in sympatry has been noted in several other studies of coexisting congeneric flycatchers. These studies compared the foraging ecologies of locally-allopatric and locally-sympatric tyrant flycatchers in areas of recent contact (Frakes and Johnson 1982, Blancher and Robertson
1984). The species pairs in both studies were rarely sympatric because of strong habitat differences, but they coexisted in areas where their preferred habitats met. The authors predicted that, because the species were very similar morphologically and behaviourally, they would compete for food where they came into contact. They proposed that interspecific competition would be the most important segregating factor for the species in sympatry and that this would be reflected by divergent foraging ecologies and possibly character displacement at the sites of contact. The results of both studies were contrary to the predictions, and neither study found evidence of divergent foraging ecologies, character displacement, or direct competition. Instead they found that the species appeared to undergo convergence in their resource use in areas of local sympatry. They suggested several possible explanations for this pattern, still within the context of competition theory. These included the presence of ephemeral and superabundant food resources, population sizes that were below the environmental carrying capacity, and effects of limiting resources other than food (Frakes and Johnson 1982, Blancher and
Robertson 1984). 102
I agree with the authors of the above-mentioned studies that ephermeral and highly-mobile flying insects are difficult to defend as a food resource (Sherry 1984) and that species often occur in reduced densities at the edges of their distributions because of marginal habitat conditions (Cicero 2004). However, there are other possible explanations for this observed pattern of resource use that do not involve competition theory. A study of the foraging ecologies of Alder and Willow flycatchers breeding in southern Ontario also found more similar habitat use in sympatry than in allopatry
(Barlow and McGillivray 1983). In local allopatry the species bred in distinctive habitats and foraged from significantly different types of vegetation, but otherwise showed similar foraging behaviours. In local sympatry the species bred in highly heterogeneous habitats and showed no differences in any aspect of their foraging behaviour, including the type of vegetation that was used for foraging. Barlow and McGillivray (1983) suggested that the foraging behaviours of these species were not habitat specific, and the observed overlap in foraging ecologies in sympatry was because of similarities in the habitat at these sites.
Results from my quantitative analysis of habitat use by Alder and Willow flycatchers in
Alberta supports this hypothesis. I believe the apparent convergence in resource use by sympatric flycatchers is largely a result of differences in the habitats at sites of allopatry and sympatry.
The species-specific habitats used by ecologically-similar flycatchers comprise various environmental gradients (e.g., vegetation structure and composition gradients, hydrological gradients, elevational gradients, etc.), and each species has a different distribution of habitat usage along these gradients. Distribution of usage along the 103 gradients can be visualized as distinctive resource utilization curves which are centered around points on each gradient that are used most often by the species. Differences between species in their utilization of various habitat resources can result in broadly allopatric or parapatric geographic distributions. However, in areas where species- specific habitat gradients meet, habitat usage by each species would be expected to overlap to a greater degree.
An example of this from my study was the difference between Alder and Willow flycatchers in their usage of habitat along a gradient relating to bush density
(SQRTSTEMS) at the mesoplot scale. In allopatry, bush density differed significantly between the species, with the areas around Alder Flycatcher song perches having lower stem densities than the areas around Willow Flycatcher song perches (Table 3.5). The utilization curves for each species along this habitat gradient in local allopatry are shown in the top panel of Figure 4.1. Two distinctive curves with non-overlapping peaks of maximal habitat use are observed, with moderate overlap between one tail of each curve
(Fig. 4.1). In sympatry, bush density on territories did not differ significantly between the species (Table 3.5) and complete overlap between the curves is observed (Fig. 4.1). Note that the habitats used by each species in sympatry are still within the range of habitats used in allopatry. However, the SYMALFL curve is located within the area of the right tail of the ALOALFL curve, indicating that the bushes around SYMALFL perches were denser than those around ALOALFL perches (Fig. 4.1). This shift by Alder Flycatchers in sympatry into slightly different habitats from those used in allopatry demonstrates a shows resourcecurvesfor sympatric territories. Top graphshowsresource curvesforallopatricterritoriesandbottom graph Figure 4.1.Resourceutilizationcurvesforthehabitat variableSQRTSTEMS. FREQUENCY ALOALFL ALOALFL SYMALFL SYMWIFL ALOWIFL 104 105
degree of flexibility in habitat use in terms of vegetation structure that is not apparent in
the utilization curves for Willow Flycatchers.
Habitat use by each species is somewhat flexible, but the degree of flexibility
appears to differ among habitat variables, and between the species. I found several
habitat features that were associated consistently with Willow Flycatcher territories
whether breeding in local allopatry or in local sympatry (i.e., water cover at all scales and
vegetation structure at the microplot scale). The only habitat feature that was consistently
associated with Alder Flycatcher territories, whether in local allopatry or in local
sympatry, was tall song perches (microplot scale). This indicates that Willow Flycatchers
may have a higher degree of habitat-specificity than Alder Flycatchers. Interestingly,
Willow Flycatchers use habitats on their wintering grounds that are very similar to those
used on their breeding grounds (Gorski 1969a ,Gorski 1969b, Lynn et al. 2003,
Koronkiewicz et al. 2006). Willow Flycatchers in El Salvador, Costa Rica, and Panama defended territories that always contained standing or slow-moving freshwater and/or saturated soil, woody shrub thickets, and open areas (Lynn et al. 2003, Koronkiewicz et al. 2006). Alder Flycatchers on their wintering grounds in Peru used a range of habitats, from early successional forests in dry, upland areas to mixed stands of trees and woody
“willow-like” shrubs next to rivers (M. S. Foster, pers. comm.).
Consistency in habitat use patterns by the two species throughout the year, especially by Willow Flycatchers, provides evidence of possible innate differences in
habitat use. However, some degree of plasticity in habitat use is an obvious requirement
for Neotropical migrants that defend territories in very different geographic regions 106 throughout the year (Block and Brennan 1993). Similarly, because some foraging behaviours are influenced by habitat use, such as choice of pre-foraging perches for aerial insectivores, foraging ecologies must also be moderately flexible to accommodate the use of sightly different habitats. There is evidence that flycatchers change certain aspects of their foraging ecologies from one habitat to another, suggesting a degree of flexibility in their behaviours (Frakes and Johnson 1982, Barlow and McGillivray 1983, Sherry 1984,
Lovette and Holmes 1995, Whelan 2001). This flexible relationship between habitat use and foraging ecology may explain why many studies looking specifically at differences in foraging ecologies between flycatchers in local allopatry and local sympatry found apparent convergence in sympatry (e.g., Alder and Willow flycatchers in southern Ontario
[Barlow and McGillivray 1983]). Clearly, if the birds are using habitats that are more similar when breeding in local sympatry than in local allopatry, then foraging behaviours would also be expected to be more similar in sympatry. This demonstrates the fact that differential foraging ecologies may not provide a means for ecological segregation between sympatric flycatchers and that differential habitat use is likely the key factor in the ecological segregation of the species in areas of recent secondary contact.
Differential habitat use can also explain the observed differences in the relative abundances of sibling species in areas of recent secondary contact (Johnson 1966, Beaver and Baldwin 1975, Johnson and Cicero 2002, Cicero 2004). Sites where sibling species come into direct contact contain a heterogeneous mosaic of habitats and it is likely that the proportion of suitable habitat for each species would vary among sites. The more- abundant species would be the one for which the majority of the habitat is suitable, or the 107 species that has the greatest degree of flexibility in its habitat use. The less-abundant species is likely restricted by specific habitat requirements, and consequently limited by the small proportion of suitable habitat. Depending on the level of flexibility in habitat use of the less abundant species, a few individuals may breed in marginal habitat. In my study, the two largest sympatric sites, Bryant Creek and Forestry Hut, supported almost twice as many Alder Flycatcher pairs as Willow Flycatcher pairs. The majority of the habitat at these sites ranged from moist to dry and had vegetation that was more typical of
Alder Flycatcher habitat. Because Willow Flycatchers use substantially wetter territories than do Alder Flycatchers, they were restricted to using the habitat closest to the beaver ponds and streams (Fig. 3.1). Therefore, the uneven spatial distribution of habitat gradients at these sites, along with the higher habitat specificity of Willow Flycatchers, led to the observed difference in species abundance.
Distinctive species-specific habitat use and occasional coexistence where preferred habitats overlap have been documented for other closely-related Empidonax species (Johnson 1966, Beaver and Baldwin 1975, Johnson 1978, Frakes and Johnson
1982, Prescott 1987, Sakai and Noon 1991, Winker 1994, Johnson and Cicero 2002).
Johnson and Cicero (2002) found patterns of geographic parapatry or disjunct allopatry among the most closely-related Empidonax species, and noted that the degree of sympatry increased among more distantly-related species. They noted that, in areas where closely- related species were in contact during the breeding season, the species typically showed strong differences in either preferred habitat and/or abundance. For example, the breeding ranges of Dusky Flycatchers (E. oberholseri), Gray Flycatchers (E. wrightii), 108 and Hammond’s Flycatchers (E. hammondii) are broadly allopatric because of altitudinal separation of preferred habitats. But in certain areas where their distinctive breeding habitats are intermixed creating a mosaic of vegetation, the species occur in local sympatry. In such areas, the species defend interspecific territories in appropriate patches of habitat (Johnson 1966, Johnson and Cicero 2002). Likewise, locally-sympatric
Hammond’s Flycatchers and Pacific-slope Flycatchers (E. difficilis) have slightly different habitat preferences which ultimately limit their coexistence (Beaver and
Baldwin 1975, Sakai and Noon 1991). Where Hammond’s Flycatchers co-occur with either Pacific-slope Flycatchers (E. difficilis) or Cordilleran Flycatchers (E. occidentalis), differences in the abundance of each species are noted, with one species usually common and the other uncommon or rare (Johnson 1978).
Two sibling-species pairs in other taxa show distribution and habitat use patterns similar to those of Empidonax flycatchers. The Oak Titmouse (Baeolophus inornatus) and Juniper Titmouse (B. ridgwayi) were recently separated as sibling species, based on distinctive vocalizations and habitat use, and have essentially non-overlapping geographic distributions (Cicero 2000, 2004). Similarly, the California Gnatcatcher (Polioptila californica) and the Black-tailed Gnatcatcher (P. melanura) were recently recognized as sibling species because of distinctive vocalizations and habitat use and they have parapatric breeding distributions (Weaver 1998, Atwood and Bontrager 2001). Like the genus Empidonax, members of each of these closely-related pairs are behaviourally and morphologically similar to one another and have very distinctive species-specific habitat use. Local sympatry is rare and occurs only in areas where their preferred habitats abut. 109
Unfortunately no studies on habitat use or coexistence have been conducted on these
species.
For members of the genus Empidonax, species-specific differences in habitat use may have evolved during periods of historical geographic separation during the glaciation cycles of the Pleistocene when each species would have adapted to distinctive vegetation- climate zones. This hypothesis coincides with the divergence time of 2.3 Mya for Alder and Willow flycatchers as estimated by mitochondrial DNA (Johnson and Cicero 2004).
Considering that at least 20 glacial cycles have occurred over the past 2 million years, these species have been exposed to several glacial-interglacial cycles during and after their speciation. Similarly, the divergence times of 2.1 Mya for the Oak and Juniper titmice and 2.0 Mya for the California and Black-tailed gnatcatchers as estimated by mitochondrial DNA (Johnson and Cicero 2004), along with their patterns of geographic separation and differential habitat use, indicate that they may have evolutionary histories similar to those of Empidonax species.
2. EFFECTS OF COEXISTENCE
Interspecific territoriality and aggressive interactions commonly are reported in studies of closely-related Empidonax species breeding in sympatry (Johnson 1966, Gorski
1969a, Johnson 1978, Prescott 1987, Sakai 1988, Sakai and Noon 1991, Johnson and
Cicero 2002). In many cases this type of behaviour has been taken as evidence of interspecific competition between coexisting species, but this remains a controversial topic (Murray Jr. 1971, Murray Jr. 1976, Cody 1985, Prescott 1987, Wiens 1989a, 110
Robinson and Terborgh 1995, Martin and Thibault 1996, Martin and Martin 2001a). I did not design this study to test directly for the presence of interspecific competition between Alder and Willow flycatchers, but I did detect aggressive interactions between the two flycatchers in areas of secondary contact. Whether these interactions impact either species negatively, and are thus of a competitive nature, has yet to be determined.
I observed that both species aggressively defended non-overlapping interspecific territories in local sympatry and I observed numerous behavioural interactions throughout the breeding season. Interactions were noticeable especially when territories were being established and during the earliest part of the nesting period. Locally-sympatric populations of Alder and Willow flycatchers in southern Ontario also show interspecific territoriality and both species respond aggressively to heterospecific song playback
(Prescott 1987). Not surprisingly, Prescott found that aggressive responses to heterospecific song occurred more frequently where both species bred in local sympatry than in local allopatry, suggesting that they learned, through coexistence, to recognize heterospecific song. This learned aggressive behaviour in sympatry is possibly a response to a potential competitor (Prescott 1987).
Competition between locally-sympatric Alder and Willow flycatchers probably would be for breeding territories, which are related directly to food and nesting resources.
The differences in habitat use between the species that were described in the previous section probably reduce the severity of any competition for territories. However, in areas where they are regionally sympatric, species-specific habitats overlap and both species likely defend areas that could be used by the other. It is in these areas, which are 111 presumably suitable for either species, where competition might occur (Johnson 1966,
Beaver and Baldwin 1975).
I looked for empirical evidence of interspecific competition using a non- experimental approach in which the habitat data for a species in local allopatry were compared quantitatively to data for that species in local sympatry. The number of intraspecific differences in habitat use between the two site types was noted for each species. An unequal number of differences (i.e., one species uses different habitat when sympatric with its sister species than when breeding in allopatry) could indicate competitive displacement in local sympatry. Because I did not measure any direct consequences of coexistence for fitness-related traits such as individual reproductive success or survival, I cannot comment on the definitive existence of interspecific competition, nor on the effects of competition on either species. However, differential patterns of habitat use at the different site types, in addition to observed aggressive interactions between the species and interspecific territoriality in sympatry, may offer circumstantial evidence of at least moderate levels of competition and provide a basis for future studies aimed at testing specific predictions of alternative hypotheses for how these species may interact and coexist (Alatalo et al. 1986, Remsen Jr. and Graves 1995, Martin and Martin 2001b, Anderson et al. 2002, Oppel et al. 2004).
The number of intraspecific differences in habitat use between the two site types was highly unequal. Willow Flycatchers showed little change in their habitat use between local allopatry and local sympatry, with the exception that ALOWIFL song perches were significantly closer to large bodies of water than were SYMWIFL perches (Table 3.2D) 112 and SYMWIFL territories were significantly wetter than were ALOWIFL territories
(Table 3.5). There was extensive overlap between confidence ellipses for ALOWIFL and
SYMWIFL group centroids in all of the bivariate scatterplots (Figs. 3.3, 3.4, 3.6 and 3.7).
Additionally, the MANOVA on the PC scores showed only marginal significant differences between Willow Flycatcher territories in allopatry and in sympatry at the mesoplot scale and no significant differences between the site types at the macroplot scale
(Tables 3.7 and 3.11). This indicates that Willow Flycatchers used generally similar types of habitat whether breeding in the presence or absence of their sibling species.
In contrast, Alder Flycatchers showed numerous significant differences in habitat use between local allopatry and local sympatry at all scales of measurement. ALOALFL song perches were taller, had lower stem densities, and were placed in drier habitat than
SYMALFL perches (Table 3.2C). All bivariate scatterplots show consistent separation between multivariate ellipses for ALOALFL and SYMALFL territories (Figs. 3.3, 3.4,
3.6 and 3.7), and the MANOVA on the PC scores indicated significant differences between ALOALFL and SYMALFL territories at the mesoplot and macroplot scales
(Tables 3.7 and 3.11). Additionally, at both the mesoplot and macroplot scales, the mean score for ALOALFL territories on PC1 was positive, which is opposite to the scores for the other species/site type categories (which were all negative) (Figs. 3.2 and 3.5). This indicates that ALOALFL territories were distinctive from all other species/site type categories because they had abundant herbaceous vegetation and dead grass/sedge as ground cover, in contrast to dense bushes and mossy ground cover. 113
This marked discrepancy between the species in the number of differences in habitat use between the site types may be explained by my choice of sample sites, at least in part. ALOALFL sites were easy to locate because Alder Flycatchers are abundant in the province and they often breed in habitats that have a distinctive vegetation structure
(i.e., tall, partially-dead willow thickets in open meadows). Because I had a narrow window of time at the start of the breeding season to locate study sites, these conspicuous sites were quick and easy to find. The distinctive nature of ALOALFL territories is demonstrated by the high rate of correct DFA classification of this site type at both the mesoplot and macroplot scales and the consistent separation of the ALOALFL multivariate ellipses in the scatterplots (Figs. 3.3, 3.4, 3.6 and 3.7). My study sites represented the drier end of the range of habitats used by locally-allopatric Alder
Flycatchers in Alberta. Alder Flycatchers were observed breeding in slightly wetter habitats, especially at the northern border of regional sympatry in Alberta, but these areas were not included in my study because of time and logistical constraints. The habitat that was used by Alder Flycatchers at these northern sites ranged from dry to moderately wet, and resembled the habitat that was used by Alder Flycatchers at locally-sympatric sites such as Bryant Creek. If I had been able to sample from a larger range of ALOALFL breeding sites, some of the observed differences between Alder Flycatcher territories in local allopatry and local sympatry may have decreased.
The habitat sampling for Willow Flycatchers better represents the full range of habitats used by the species in the province. Willow Flycatchers are not abundant in
Alberta, and sites where they bred in sufficient numbers were very difficult to locate. As 114 a consequence, I searched a large geographic area in order to find ALOWIFL breeding sites that met my sampling criteria. This may explain the visibly greater variation in the habitats used by Willow Flycatcher and the scattered nature of the ALOWIFL and
SYMWIFL territories in the bivariate scatterplots (Figs. 3.3, 3.4, 3.6 and 3.7). As mentioned previously, Willow Flycatcher territories always had either standing or running water present. The only significant differences in habitat use detected among site types include the distance from the song perch to the largest body of water on the territory
(CPLRGWTR) being significantly reduced in sympatry (Table 3.2D), and both mesoplot and macroplot transects being generally wetter in sympatry than in allopatry. This is because many SYMWIFL territories were directly adjacent to beaver ponds and creeks, resulting in large portions territories being completely, or almost completely, covered by water (e.g., Bryant Creek and Cadet Camp). In contrast, numerous ALOWIFL breeding sites had a creek or river present on the territories, but these habitat features were localized to a small area of the territory and were often not sampled (e.g., Cataract Creek and Sibbald Flats).
Surprisingly, ALOWIFL territories had the lowest rate of correct DFA classification at the mesoplot and macroplot scales. Almost half of ALOWIFL territories were incorrectly classified as SYMALFL territories, suggesting that some Willow
Flycatchers in allopatry were occupying habitat similar to that used by Alder Flycatchers in sympatry. The ALOWIFL territories at Cataract Creek were largely responsible for this result. The bushes at Cataract Creek were very tall and there were numerous mature spruce trees, which were often used as song perches, on each territory. Although this area 115 was generally very wet and had numerous beaver ponds and several large creeks, the song perches were located in the dry to moderately wet areas of each territory so that the habitat that was sampled closely resembled that used by of Alder Flycatchers in sympatry.
Studies conducted in the contact zone in eastern North America suggest that there is an asymmetrical competitive relationship between Alder and Willow flycatchers, with
Willow Flycatchers being more aggressive and behaviourally dominant to Alder
Flycatchers (Stein 1963, Gorski 1969a, Barlow and McGillivray 1983, Prescott 1987,
Sedgwick 2000). This suggestion comes from the observation that, in the contact zone in eastern North America, Willow Flycatchers appear to occupy habitats more similar to those chosen by Alder Flycatchers in allopatry (Barlow and McGillivray 1983, Prescott
1987, Sedgwick 2000). I found no evidence to suggest that SYMWIFL territories resembled ALOALFL territories. In fact, SYMWIFL territories were consistently very different from ALOALFL territories. The possible bias in my sampling of ALOALFL sites may play a role in this result, but even if I had been able to include the moderately wet ALOALFL sites in my study, the SYMWIFL territories were still wetter than anything I had seen any Alder Flycatcher using in allopatry.
However, there is some evidence in support of an asymmetrical competitive relationship between the species in Alberta. I observed several interspecific encounters that resulted in the displacement of an Alder Flycatcher by a Willow Flycatcher, suggesting that Willow Flycatchers may be more aggressive. Other studies have noted that Willow Flycatchers appear to be generally more aggressive in defending their territories against both conspecifics and heterospecifics than are Alder Flycatchers (Stein 116
1958, Barlow and McGillivray 1983, Prescott 1987, Sedgwick 2000). Additionally, the distribution and abundance of the species at the breeding sites may provide evidence of asymmetrical competition. The habitat at several of the ALOWIFL breeding sites appeared to be well within the range of ecological tolerance for Alder Flycatchers, as evidenced by the similarity of the habitat used by Willow Flycatchers at Cataract Creek and that used by Alder Flycatchers in sympatry. Yet, with very few exceptions, there are no records of Alder Flycatchers breeding at sites where large numbers of Willow
Flycatchers are present. At Sibbald Flats there are records of a single Alder Flycatcher territory being located in the dryer habitat on the opposite side of the creek from where the Willow Flycatchers breed (M. R. Lein, pers. comm.). I regularly checked a breeding site along the Bow River that was not included in my study but which has a long history of Willow Flycatcher occupancy. I found 10-12 Willow Flycatcher territories in the tall, dense willow bushes adjacent to the river. In 2004 there was a single Alder Flycatcher territory at the east end of the site in the dryer, more open habitat. These distribution patterns may indicate that Willow Flycatchers are more aggressive and are able to displace Alder Flycatchers in any disputes over breeding territories that contain habitat this is suitable to either species. In contrast, the habitat at the ALOALFL breeding sites
(i.e., SCT East, Lochend, or Indian Graves) was distinctly outside the range of ecological tolerance for Willow Flycatchers. As mentioned previously, Willow Flycatcher territories consistently have large bodies of water present and there are no records of Willow
Flycatchers in Alberta breeding in xeric habitats (Kulba and McGillivray 2001). 117
If there is a competitive relationship between Willow and Alder flycatchers, it is likely asymmetrical. Complex asymmetrical competitive relationships are common among groups of related species that share common resources (Alatalo et al. 1986,
Robinson and Terborgh 1995, Torok and Toth 1999, Martin and Martin 2001b, Serrano and Astrain 2005). Willow Flycatchers may be the dominant competitor but are likely restricted by their specific habitat requirements, and thus limited in their distribution by the availability of suitable breeding sites in Alberta. Alder Flycatchers appear to use a broader range of habitats, but may be restricted by interactions with Willow Flycatchers in areas where both species occur. This type of asymmetrical competitive relationship between species with differential ecological tolerances has been found between narrowly- sympatric Ficedula flycatchers in Europe (Saetre et al. 1999), between coexisting sibling species of Calandrella larks (Serrano and Astrain 2005), and may occur between locally- sympatric populations of Hammond’s and Pacific-slope flycatchers (Sakai and Noon
1991). The best way to evaluate alternative hypotheses about ecological interactions between species is to conduct reciprocal removal experiments and to include a measure of the ecological consequences of coexistence (i.e., fitness consequences for individuals).
This experimental approach has been very successful in elucidating mechanisms of coexistence (see review by Schoener 1983) but has yet to be attempted for sympatric
Empidonax flycatchers.
The importance of both environmental conditions and species interactions in determining distribution patterns and abundance of coexisting congeneric species has been a controversial issue in ecology for many years, especially when using non- 118 experimental observations for testing of causal processes (Alatalo et al. 1986, Wiens
1989a, Remsen Jr. and Cardiff 1990, Remsen Jr. and Graves 1995, Tokeshi 1999). Many recent studies have shown both factors to be important but acting on different spatial scales (Chesson and Huntly 1997, Saetre et al. 1999, Serrano and Astrain 2005, Lovette and Hochachka 2006). I believe that underlying factors that are unrelated to interspecific interactions, namely differential use of habitat, largely shape the distribution of Alder and
Willow flycatchers on broad geographic and regional scales, but that interspecific ecological interactions may play a role at local scales in shaping the community structure at sites of secondary contact.
3. HABITAT USE ACROSS NORTH AMERICA
I conducted a literature review of habitat use by Alder and Willow flycatchers across their North American breeding range. I tried to limit my search to studies conducted after the species were separated in 1973 and to areas that are within the zones of regional secondary contact. Because the zones of sympatry are not well-defined, and there are few papers with detailed accounts of habitat use by these species (especially for
Alder Flycatchers), some studies conducted prior to 1973 and some that may be from outside the zones of sympatry were included in the review.
In the east, the presence of Willow Flycatchers in dry, upland thickets and meadows and of Alder Flycatchers in boggy to wet alder thickets is well-documented
(Stein 1958, Zink and Fall 1981, Barlow and McGillivray 1983, Lowther 1999, Sedgwick
2000). Descriptions from areas of regional sympatry in Ohio, Massachusetts, Vermont 119 and New Hampshire state that Alder Flycatchers are found at higher elevations and in wetter, swampier habitats than are Willow Flycatchers (Robbins 1974, Lowther 1999,
Sedgwick 2000). In Michigan, Alder Flycatcher nests are placed in shrubs “growing in knee-deep water and muck” (Payne 1991). Breeding bird surveys in Ontario and Quebec found Alder Flycatchers in wet areas more often than in dry areas, with Willow
Flycatchers showing the opposite pattern (Cadman et al. 1987, Peck and James 1987,
Gauthier and Aubry 1996).
Studies conducted on the species in the west are scarce but do show a pattern of habitat use that is different from that observed in the east. In Washington and British
Columbia Alder and Willow flycatchers breed in moist to dry shrubby thickets, with
Willow Flycatchers being found most often in riparian areas near small streams and lakes
(Frakes and Johnson 1982, Campbell et al. 1997). In southern Alberta, both Kulba and
McGillivary (2001) and I found Willow Flycatchers breeding in wet, low-lying areas and found no evidence of use of dry, upland habitats. Alder Flycatchers in my study used dryer habitats than described elsewhere.
This literature, along with the results from my study, confirm an overall reversal in habitat use by each species between the eastern and western regions of secondary contact. This is an unusual ecological and evolutionary phenomenon. As a result of this finding, numerous questions relating to the processes that would produce this switch in habitat use, and the factors that maintain the present patterns of habitat use, have arisen.
Biogeographic and evolutionary questions are difficult to answer because the historical processes that may be responsible for this pattern could never be ascertained completely, 120 leaving inference as the primary methodology. There are certainly a number of historical scenarios that could account for the present-day distribution of these species, but the data presented here are not sufficient to differentiate between the alternatives. Also, experiments to test hypotheses concerning large scale distribution patterns are usually logistically intractable, especially for birds.
I propose the following explanation for the observed pattern of habitat use in regions of sympatry. The distribution of Alder and Willow flycatchers on broad geographic and regional scales is shaped largely by adaptations to very different climate- vegetation zones. For Alder Flycatchers, over 63% of their total population breeds in
Canada’s boreal forest (Blancher 2003) and they are well-adapted to the cool, damp climactic conditions of this ecoregion. Boreal habitat is highly heterogeneous, and Alder
Flycatcher habitat ranges from white spruce bogs, muskegs, and fens, to dryer alder thickets along the coast, and early successional hardwood forests (Lowther 1999, Benson and Winker 2001). Where they have come into contact with Willow Flycatchers in
Alberta, they appear to breed in areas that are dryer than what is seen elsewhere across their range, although they continue to use moist areas in many cases (e.g., Bryant Creek).
In contrast, Willow Flycatchers breed in much warmer climates and are adapted to a very different suite of environmental conditions than are Alder Flycatchers. Significant differences between the eastern and western forms of Willow Flycatchers (refer to the distinctive split in breeding distribution Fig. 2.1) and among the 5 subspecies (Fig. 2.3) have been shown to exist (Sedgwick 2000, Sedgwick 2001, Johnson and Cicero 2002)
Western subspecies (E. t. brewsteri, E. t. adastus, and E. t. extimus) can be distinguished 121 from the eastern subspecies (E. t. campestris and E. t. traillii) on basis of morphology, plumage pattern and coloration (Sedgwick 2000). Some differences in song and habitat use have been noted among Willow Flycatcher subspecies (Sedgwick 2001). The western subspecies often occupy riparian corridors and are described as riparian-habitat specialists
(Knopf et al. 1988, Sedgwick 2001), whereas habitat data available for the eastern subspecies indicate that they use slightly dryer habitats for breeding than the western subspecies (Sedgwick 2000).
Habitat differences among the subspecies could explain the observed reversal in habitat use by Willow Flycatchers. If, as many researchers have claimed, Willow
Flycatchers were the dominant competitor and have more specialized habitat use, then regionally-sympatric Alder Flycatchers in the west may be displaced into dryer habitats.
Similarly, in the east, Alder Flycatchers may be displaced into wetter habitats because
Willow Flycatchers in the east use the dryer areas. Further habitat data are required along with removal experiments in order to test this hypothesis.
The observed reversal in habitat use could also be a result of inadequate habitat descriptions for each species across their breeding range, especially in the east. The literature contains a wide range of habitat descriptions for both species and this may be the result of incomplete sampling and confusion between the species in areas where they are sympatric. My study provides the first quantitative analysis of habitat use by a regionally sympatric population of Alder and Willow flycatchers and it is clear that similar research needs to be conducted in other regions of sympatry in order to improve our understanding of the effects of secondary contact between these sibling species. 122
4. CONSERVATION AND MANAGEMENT IMPLICATIONS
Willow Flycatcher populations in Alberta are experiencing a higher rate of decline than any other Canadian population (Downes et al. 1999) and are classified as “Status
Undetermined” by the Alberta Wildlife Management Division (Kulba and McGillivray
2001). Detailed and accurate quantitative studies of habitat use are an essential step in the development of management strategies for species at risk. The lack of information about Willow Flycatchers in Alberta has been the greatest weakness in assessing its status in the province. My research contributes to what is known about the habitat requirements of Willow Flycatchers in Alberta and indicates that the loss of suitable habitat, often because of anthropogenic activity, probably is the largest threat to this species.
Additionally, my research shows that it is necessary for conservation planners to consider fully the significant differences in habitat use among Willow Flycatcher subspecies to ensure effective management strategies. Strategies based on data collected from the populations in eastern North America would be inappropriate for the western populations and vice versa.
Alberta is at the northern border of the breeding range for Willow Flycatchers and probably supports only a small breeding population of Willow Flycatchers (< 200 pairs)
(Kulba and McGillivray 2001). My research indicates that Willow Flycatchers in southern Alberta, like those in other areas of western North America, are habitat specialists and consistently use riparian areas that have dense willow thickets and standing or running water present. Their distribution in the province appears to be limited by the availability of suitable riparian habitat which tends to be uncommon, 123
isolated, and widely dispersed. Also, riparian habitat is subject to periodic natural
disturbances, such as flooding, which drastically reduce the availability of breeding
habitat. Flooding in southern Alberta during the 2005 breeding season destroyed several
Willow Flycatcher breeding sites. These sites were subsequently abandoned by the birds
and likely will not be occupied for several years as a result of the damage to the
vegetation. Willow Flycatchers in Alberta also experience stochastic environmental
events (e.g., summer snowstorms) with severe consequences for the population.
Willow flycatchers are most vulnerable to changes in their riparian habitat that
lead to desiccation (Green et al. 2003). The loss and alteration of riparian habitats
because of road expansion, wetland drainage, and livestock grazing are the greatest
threats to Willow Flycatchers in Alberta because these activities result in more xeric
conditions within traditional Willow Flycatcher breeding habitat. Willow Flycatchers are
strongly impacted by summer-grazing practices (Knopf et al. 1988) because cattle affect
the structure, spacing, and density of vegetation in riparian areas and increase stream-
bank erosion (Knopf et al. 1988). Accordingly, none of my study sites that supported
larger numbers of Willow Flycatchers were heavily grazed. Another limiting factor for
Willow Flycatchers in Alberta may be cowbird parasitism (Kulba and McGillivray 2001).
I found cowbird eggs in 2 of 12 Willow Flycatcher nests. Both of these nests were subsequently abandoned. Rates of cowbird parasitism in Willow Flycatcher populations are highly variable, ranging from 0 - 88%, depending on the geographic location
(Sedgwick 2000). A more detailed study of nest parasitism rates in Alberta is necessary to assess this threat adequately. 124
Because there are many Willow Flycatcher breeding sites in southern Alberta with small populations (< 5 pairs) and only a few sites with larger populations (> 10 pairs), I think that protecting specific breeding sites would be challenging. Instead, overall conservation and restoration strategies for riparian habitats, like those implemented for the Southwestern Willow Flycatcher (see Finch and Stoleson 2000), would be more effective. Also, Willow Flycatcher breeding sites in Alberta are not well-documented and are somewhat transient because of natural disturbances. Therefore, broad-scale conservation of riparian habitats would reduce the possibility that significant amounts of
Willow Flycatcher habitat would be destroyed unknowingly. It would also be beneficial to determine which subspecies of Willow Flycatcher breeds in Alberta. Data about population trends, nest success, and survivorship for the species in Alberta would be useful in identifying other potential limiting factors in the province.
Alder Flycatchers in Alberta are well-adapted to northern environmental conditions and their population appears to be stable (Lowther 1999). They appear to breed successfully in areas where livestock grazing occurs and many of the Alder
Flycatcher breeding sites that I sampled were located in grazing pastures. My data suggest that Alder Flycatchers may be less affected by grazing because they can tolerate lower stem densities and xeric breeding conditions. There are very few data on cowbird nest parasitism rates for this species and none of the Alder Flycatcher nests in my study were parasitized. 125
5. SUGGESTIONS FOR FUTURE RESEARCH
My study has revealed several interesting patterns that provide a foundation for investigating the degree of ecological interaction, and mechanisms of coexistence, between Alder and Willow flycatchers in areas of secondary contact. In order to confirm the observed reversal in habitat use between the eastern and western contact zones in
North America, a study using habitat sampling techniques similar to mine needs to be conducted in areas of regional sympatry in eastern North America. It would also be beneficial to conduct this type of study at sites of local sympatry in British Columbia in order to fully assess habitat use in the western zone of contact. In addition to research on habitat use, there are several specific areas that I suggest merit further investigation, as listed below.
A. Hybridization Studies
Seutin and Simon (1988) and Winker (1994) found no conclusive evidence of hybridization between Alder and Willow flycatchers in the eastern zone of contact, but both studies used very small sample sizes and suggested that further examination was warranted. There has been no genetic work done on either species in the area of regional sympatry in western North America, although there are several accounts of territorial males with unusual songs that sound intermediate between typical Alder and Willow flycatcher song (Stein 1963, Sedgwick 2000, S. Hechtenthal, pers. obs.). Further genetic research using larger sample sizes in both eastern and western contact zones would provide important information about whether these species are hybridizing. This is key 126 information to acquire in order to fully assess the degree of interaction between Alder and
Willow flycatchers in areas where they have come into secondary contact.
B. Local Removal Experiments
Reciprocal removal experiments are useful for examining the potential ecological and fitness consequences of coexistence for ecologically-similar species (Alatalo et al.
1986, Torok and Toth 1999, Martin and Martin 2001b). A reciprocal removal experiment with Alder and Willow flycatchers could be used to examine: (1) whether coexistence results in ecological consequences for either species with respect to access to nest sites, access to food resources, nest predation, and adult female predation; and (2) whether these ecological consequences result in fitness consequences with respect to reproductive success (clutch size, number of young fledged per nest), or adult female survival within a breeding season. In either the eastern or western zones of contact, breeding pairs on control plots where both Alder and Willow flycatchers coexist in local sympatry could be compared to experimental plots where one species had been removed. Although this would be a logistically-difficult experiment to conduct, it would help to clarify whether there are any effects of coexistence on either species and might possibly confirm the presence of an asymmetrical competitive relationship.
C. Ecological Niche Modelling
Ecological niche models have been used recently to make predictions about geographic distributions of individual species in relation to environmental factors. Such 127
models have been applied to a variety of organisms to address questions of ecology,
biogeography, geographic variation, systematics, evolution, conservation biology and
climate change (Cicero 2004, Graham et al. 2004, Peterson 2006, Ruegg et al. 2006,
Swenson 2006) and can be used to predict past, current, and future distributions.
Bioclimatic modelling was used recently to test specific hypotheses about barriers to
sympatry between avian sibling species in the genus Baeolophus where they approach and contact each other at range margins (Cicero 2004). Similar techniques could be used to investigate geographic range limits for Alder and Willow flycatchers across North
America and to predict areas of secondary contact based on current habitat and environmental data. Future geographic distributions resulting from climate change could also be investigated (Hijmans and Graham 2006). Ecological niche models have also been used to test hypotheses about past geographic distributions for species during
Pleistocene glaciation cycles (Ruegg et al. 2006). This could help to clarify the dynamics of post-glacial range expansions that may have led to recent secondary contact between
Alder and Willow flycatchers. 128
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Appendix 1. Summary of habitat variables measured at the microplot scale for song perches. Values shown as mean ± SE (top) and median in parentheses (below).
Habitat variables ALOALFL ALOWIFL SYMALFL SYMWIFL
(n = 29) (n = 23) (n = 28) (n = 17) CPHEIGHT (m) 4.93 ± 0.53 4.10 ± 0.56 4.02 ± 0.50 4.92 ± 1.25
(with trees) (4.1) (3.0) (3.1) (2.8) CPHEIGHT (m) 3.75 ± 0.15 2.79 ± 0.13 3.09 ± 0.14 2.76 ± 0.14
(no trees) (3.55) (2.75) (3.0) (2.75) CPSTEMS 6.47 ± 0.88 5.89 ± 1.36 11.09 ± 1.38 6.85 ± 1.47
(7.5) (6.0) (12.5) (7.0) CPALIVE 1.62 ± 0.14 2.13 ± 0.19 1.57 ± 0.12 1.82 ± 0.20
(1.00) (2.00) (1.50) (2.00) CPGRCOV 2.21 ± 0.15 1.61 ± 0.18 1.71 ± 0.15 1.35 ± 0.15
(2.0) (1.0) (1.5) (1.0) CPNRBUSH (m) 1.21 ± 0.28 0.76 ± 0.23 0.74 ± 0.24 1.32 ± 0.47
(0.68) (0.35) (0.26) (0.53) CPNRWTR 2.31 ± 0.17 1.22 ± 0.09 1.61 ± 0.17 1.29 ± 0.17
(3.0) (1.0) (1.0) (1.0) CPNRSIZE 2.55 ± 0.12 1.78 ± 0.09 1.82 ± 0.13 1.82 ± 0.13
(3.0) (2.0) (2.0) (2.0) CPLRGWTR 2.38 ± 0.16 2.26 ± 0.17 2.00 ± 0.15 1.77 ± 0.24
(3.0) (2.0) (2.0) (1.0) CPLRGSIZE 2.55 ± 0.12 1.17 ± 0.10 1.71 ± 0.14 1.24 ± 0.14
(3.0) (1.0) (2.0) (1.0) 146
Appendix 2. Summary of habitat variables measured at the microplot scale for nest plants. Values shown as mean ± SE (top) and median in parentheses (below). Data for each species at the different site types were combined.
Habitat variables Alder Flycatcher Willow Flycatcher
(n = 8) (n = 12) CPHEIGHT (m) 1.64 ± 0.15 2.14 ± 0.16
(1.53) (1.98) CPALIVE 2.25 ± 0.16 1.58 ± 0.19
(2.0) (1.5) CPGRCOV 1.88 ± 0.13 1.33 ± 0.23
(2.0) (1.0) CPNRBUSH (m) 0.95 ± 0.36 0.078 ± 0.05
(0.85) (0.0) Appendix 3. Summary of habitat variables measured at the mesoplot scale for song perches. Values shown as mean ± SE
(top) and median in parentheses (below).
Habitat variables ALOALFL ALOWIFL SYMALFL SYMWIFL Transformation
TRANSRANK 1.53 ± 0.08 2.44 ± 0.12 2.09 ± 0.11 3.21 ± 0.16 Square root
(1.5) (2.5) (2.06) (3.25) VEGHT (m) 2.12 ± 0.11 1.49 ± 0.12 1.61 ± 0.13 1.52 ± 0.19 Log
(2.21) (1.39) (1.45) (1.32) VEGALIVE 2.69 ± 0.04 2.38 ± 0.11 2.53 ± 0.03 2.39 ± 0.08 Cubed
(2.75) (2.48) (2.51) (2.43) STEMHITLO 1.52 ± 0.19 4.01 ± 0.34 3.26 ± 0.29 3.50 ± 0.45 Square root
(1.15) (4.08) (3.27) (2.90) VIIBUSH (%) 68.81 ± 2.26 78.13 ± 3.74 78.89 ± 2.42 74.97 ± 4.78 Squared
(73.0) (82.5) (79.0) (80.0) VIIHERB (%) 26.31 ± 2.18 15.46 ± 2.95 16.09 ± 1.90 16.85 ± 4.27 Root arcsine
(25.0) (10.0) (14.0) (12.50) 147 Appendix 3. Continued
Habitat variables ALOALFL ALOWIFL SYMALFL SYMWIFL Transformation
GIIMOSS (%) 9.57 ± 2.44 40.98 ± 7.13 25.98 ± 3.98 29.56 ± 5.51 Square root
(5.0) (30.0) (22.50) (22.50) GIIWATR (%) 2.42 ± 1.12 6.130± 1.57 2.35 ± 1.00 19.88 ± 5.08 Square root
(0) (2.5) (0) (12.5) GIILLDB (%) 34.66 ± 3.50 18.91 ± 4.34 27.77 ± 3.59 16.77 ± 4.93 Root arcsine
(37.5) (10.0) (25.0) (10.0) GIIDHERB (%) 51.21 ± 4.22 25.54 ± 3.44 41.96 ± 4.91 29.12 ± 2.61 Square root
(47.5) (20.0) (37.50) (27.50) 148 149
Appendix 4. Summary of habitat variables measured at the mesoplot scale for nest plants. Values shown as mean ± SE (top) and median in parentheses (below). Data for each species at the different site types were combined.
Habitat variables Alder Flycatcher Willow Flycatcher
(n = 8) (n = 12) VEGHT (m) 1.63 ± 0.22 1.30 ± 0.08
(1.66) (1.37) VEGALIVE 2.55 ± 0.07 2.38 ± 0.11
(2.52) (2.50)
STEMHITLO 5.26 ± 2.5 8.51 ± 1.79
(1.99) (8.25) BUSHCOV (%) 76.56 ± 5.99 79.58 ± 5.11
(71.25) (83.75) HERBCOV (%) 21.25 ± 6.05 15.00 ± 4.11
(21.25) (10.0) Appendix 5. Summary of habitat variables measured at the macroplot scale for song perches. Values shown as mean ± SE
(top) and median in parentheses (below).
Habitat variable ALOALFL ALOWIFL SYMALFL SYMWIFL Transformation TRANSRANK 1.63 ± 0.10 2.52 ± 0.12 2.14 ± 0.10 3.11 ± 0.22 Square root
(1.5) (2.5) (2.190) (3.130) VEGHT (m) 1.57 ± 0.10 0.98 ± 0.06 1.28 ± 0.13 1.21 ± 0.27 Log
(1.55) (0.98) (1.11) (0.9) VEGALIVE 2.71 ± 0.04 2.36 ± 0.11 2.48 ± 0.04 2.35 ± 0.05 Squared
(2.7) (2.5) (2.51) (2.38) STEMHITLO 1.33 ± 0.14 3.31 ± 0.38 3.02 ± 0.28 2.70 ± 0.39 Square root
(1.13) (2.77) (2.74) (2.23) VIIBUSH (%) 58.15 ± 3.02 62.45 ± 5.04 70.36 ± 2.78 58.82 ± 4.95 Squared
(56.25) (65.0) (71.25) (55.0) VIIHERB (%) 38.06 ± 3.03 29.24 ± 4.85 26.88 ± 2.83 24.56 ± 4.09 Root arcsine
(40.0) (23.75) (25.0) (25.0) 150 Appendix 5. Continued
Habitat variable ALOALFL ALOWIFL SYMALFL SYMWIFL Transformation GIIMOSS (%) 9.10 ± 2.21 34.62 ± 5.68 26.38 ± 3.79 25.07 ± 4.68 Square root
(5.0) (30.0) (26.25) (20.0) GIIWATR (%) 2.32 ± 0.83 8.92 ± 2.45 3.87 ± 1.15 27.09 ± 5.67 Square root
(0.0) (4.0) (0.25) (22.5) GIILLDB (%) 25.60 ± 3.19 15.16 ± 3.95 19.55 ± 2.04 14.19 ± 3.82 Root arcsine
(25.0) (7.5) (17.5) (7.5) GIIDHERB (%) 59.31 ± 3.92 32.07 ± 4.75 46.30 ± 4.19 27.43 ± 3.31 Square root
(60.0) (23.75) (43.75) (27.5) 151