Ecology, Morphology, and Behavior in the New World Wood Warblers

Home , Acrocephalidae, Altamira yellowthroat, Arrowhead warbler, Bahama yellowthroat, Basileuterus, Blackburnian warbler

A dissertation presented to

the faculty of

the College of Arts and Sciences of Ohio University

In partial fulfillment

of the requirements for the degree

Doctor of Philosophy

Brandan L. Gray

August 2019

This dissertation titled

Ecology, Morphology, and Behavior in the New World Wood Warblers

BRANDAN L. GRAY

has been approved for

the Department of Biological Sciences

and the College of Arts and Sciences by

Donald B. Miles

Professor of Biological Sciences

Florenz Plassmann

Dean, College of Arts and Sciences 3

ABSTRACT

GRAY, BRANDAN L., Ph.D., August 2019, Biological Sciences

Ecology, Morphology, and Behavior in the New World Wood Warblers

Director of Dissertation: Donald B. Miles

In a rapidly changing world, species are faced with habitat alteration, changing climate and weather patterns, changing community interactions, novel resources, novel dangers, and a host of other natural and anthropogenic challenges. Conservationists endeavor to understand how changing ecology will impact local populations and local communities so efforts and funds can be allocated to those taxa/ecosystems exhibiting the greatest need. Ecological morphological and functional morphological research form the foundation of our understanding of selection-driven morphological evolution. Studies which identify and describe ecomorphological or functional morphological relationships will improve our fundamental understanding of how taxa respond to ecological selective pressures and will improve our ability to identify and conserve those aspects of nature unable to cope with rapid change.

The New World wood warblers (family Parulidae) exhibit extensive taxonomic, behavioral, ecological, and morphological variation. Ever growing museum collections, life history data availability, citizen science-collected behavior data availability, advances in statistical techniques, and advances in Parulid warbler phylogenetic relationships prime the family for modern ecomorphological and functional morphological study. I combined morphological and migration distance data from museum specimens and ecological data from the literature to explore ecomorphological patterns in a phylogenetic 4 context at the level of the Parulidae. Morphological similarity among warblers mirrors genetic similarity except for traits associated with flight. Wing aspect and tail length have been shown to be influenced by both migration distance as well as foraging habitat structural openness. Selective pressures encountered during migration may drive a wing shape less suited for locomotion within the breeding and wintering environments and the shapes of modern migrant wings may represent functional trade-offs.

Many warbler species and subspecies are underrepresented in museum collections and ecological data are severely lacking for many taxa. Traditional ecomorphological ideology posits intraspecific phenotypic variation is minimal relative to interspecific phenotypic variation. However, the degree to which intraspecific variation in ecology and morphology varies among taxa and can be extensive. Studies which quantify the intraspecific variation in ecology and morphology for individual species will inform future ecomorphological study and inform conservation decisions by identifying those taxa with limited variation. The Hooded Warbler (Setophaga citrina) is considered a monotypic species within the Parulid family which exhibits well-characterized sex- specific habitat segregation. Using museum specimens, I explore the spatial and temporal variation in morphology across the species’ breeding range. Only males show a weak temporal shift in wing morphology with wing length increasing relative to wing width over the last century. The species exhibits age and sex-specific south to north, female to male, and young bird to old bird shifts in morphology consistent with migration distance, age, and sex patterns seen in other Parulid warblers and other small passerines. 5

Studies linking morphology and ecology with performance is crucial to our understanding of morphological evolution. Functional morphological relationships are rarely assessed in wild individuals due to temporal, financial, and practicality constraints.

However, captive performance studies may provide a biased view of functional morphological relationships. We used flight tunnel and video recording in the field to assess how wing size and shape influence flight speed in a wild population of Hooded

Warblers breeding near the northern limits of the species’ breeding range. Bird mass, wing area, and wing aspect interact to predict maximum takeoff flight speed attained during the first 2m of escape flight in the Hooded Warbler. For birds with low wing loading, wing aspect is positively related to maximum flight speed. At high wing loading, however, high aspect wings perform inferiorly to low aspect wings. This study supports a form-function relationship in the Hooded Warbler and provides a benchmark data set from wild, untrained individuals against which future captive and field-based studies can compare.

Results presented in this dissertation support individual-level, species-level, and family level ecomorphological and functional morphological patterns in a model avian system and expand our understanding of ecomorphological and functional morphological associations. Including a broader taxonomic and morphological sample of the warbler family has uncovered novel ecomorphological patterns in this well-studied avian system.

Additional fine-scale ecomorphological research is needed to better understand individual model taxa and to better understand discrepancies in ecomorphological patterns seen across taxonomic studies. 6

DEDICATION

For my family

ACKNOWLEDGMENTS

I thank my adviser, Donald Miles, for his mentorship and help developing my research and teaching interests; providing resources for my work; providing feedback for grant proposals; and for his patience, support, and advice regarding this dissertation. I also thank my dissertation committee members Kelly Williams, Viorel Popescu, and

Harvey Ballard for their patience and guidance. I thank Kelly Williams for teaching me the ways of the Hooded Warbler; for helping develop my field, lab, and statistical skillsets; for providing resources for this and other Hooded Warbler projects; and for collaborative support. I thank Michelle Ward, Ryan Dorkoski, Kelly Williams, Debbie

Walter, Kyle Brooks, Cassie Thompson, Derrick Gray, Linn Keyser, and Max Groff for countless hours of philosophical discussion and dissertation critique. Funding for these projects was provided by three Ohio University Graduate Student Senate Original Work

Grants, an Ohio University Student Enhancement Award, and a Kirtland Bird Club Ohio

Avian Project Initiative award. I thank Michelle Ward and Kelly Williams for assistance collecting museum and field morphological data. I thank the 2014-2017 Hooded Warbler field teams (the “chip chasers” and “HOWA hunters”) and HOWA lab members for field data collection assistance and data entry. Finally, I thank my family for supporting and encouraging my love of nature and pursuit of knowledge. 8

TABLE OF CONTENTS

Page

Abstract ...... 3 Dedication ...... 6 Acknowledgments...... 7 List of Tables ...... 11 List of Figures ...... 12 Chapter 1: Introduction ...... 14 Ecological Morphology ...... 14 Ecology, Morphology, and Performance ...... 15 Scale in Ecomorphological Studies ...... 16 Ecology and Avian Wing Morphology ...... 18 The New World Wood Warblers (Family Parulidae) ...... 22 Chapters ...... 25 Chapter 2: Ecology and Morphology of the New World Wood Warblers ...... 26 Abstract ...... 26 Introduction ...... 27 Migration...... 27 Functional Morphological Trade-offs ...... 31 Ontogenetic and Sex Polymorphism ...... 33 Parulidae ...... 34 Methods and Materials ...... 36 Specimen Selection ...... 36 Morphological Variables ...... 37 Ecological Variables ...... 39 Phylogenetic Signal in Morphological and Ecological variables ...... 40 Morphological and Ecological Trait Evolution ...... 42 Correlation between Ecology and Morphology in Parulidae ...... 43 Parulid Sexual Dimorphism ...... 44 Results ...... 45 Phylogenetic Signal and Evolutionary Model Selection ...... 45 Morphology and Ecology ...... 48 9

Covariation Between Morphology and Ecology...... 49 Sexual Dimorphism and Morphological Niche Breadth ...... 55 Group and Sex-Specific Differences in Morphology ...... 57 Discussion ...... 59 Morphological and Ecological Traits...... 60 Morphology and Migration Distance ...... 61 Sex, Morphology, Migration, and Habitat Structural Openness ...... 63 Chapter 3: Intraspecific Morphological Variation of the Hooded Warbler (Setophaga Citrina) ...... 66 Abstract ...... 66 Introduction ...... 67 Materials and Methods ...... 74 Results ...... 78 Morphological Change through Time ...... 81 Morphological Differences by Age and Sex ...... 83 Morphological Variation along a Latitudinal Gradient ...... 87 NMDS and PERMANOVA ...... 92 Discussion ...... 101 Interpreting Open Wing Shape from a Folded Dried Wing ...... 101 Descriptions of Wing Size and Shape ...... 102 Morphological Change through Time ...... 103 Morphological Differences by Age, Sex, and Breeding Location ...... 104 Chapter 4: Variation in Wing Shape and Flight Performance in Wild Hooded Warblers (Setophaga Citrina) ...... 110 Abstract ...... 110 Introduction ...... 111 Materials and Methods ...... 117 Capture, Handling, and Marking ...... 117 Wing Morphology ...... 118 Flight Performance...... 120 Statistical Analyses ...... 121 Results ...... 122 Body Condition ...... 124 10

Morphology...... 124 Flight Performance...... 127 Covariation between Morphology and Flight Performance ...... 131 Repeatability ...... 137 Discussion ...... 138 Morphology...... 138 Wing Morphology and Flight Performance ...... 140 Conclusion ...... 143 References ...... 147 Appendix A ...... 166 Appendix B ...... 174

LIST OF TABLES

Page

Table 1. Phylogenetic signal for 7 morphological traits among Parulid warblers...... 46 Table 2. Phylogenetic signal for ecological traits among Parulid warblers...... 46 Table 3. Morphological variables: Evolutionary model selection...... 47 Table 4. Ecological variables: Evolutionary model selection...... 47 Table 5. Correspondence analysis of ecological data ...... 49 Table 6. Summary of canonical correlation analysis between migratory habitat structural complexity and migratory ecological variables and Parulid morphological variables. .... 51 Table 7. Correlation between each morphological variable or correspondence axis and the canonical variables...... 51 Table 8. A canonical redundancy analysis...... 53 Table 9. Summary of phylogenetic canonical correlation analysis between migratory habitat structural complexity and migratory ecological variables and Parulid morphological variables...... 54 Table 10. Summary of phylogenetic canonical correlation analysis between migratory habitat structural complexity and migratory ecological variables and Parulid morphological variables...... 55 Table 11. Principal components analysis on 7 size corrected morphological variables. .. 56 Table 12. Results of morphospace occupancy analysis...... 56 Table 13. Means and standard errors for each morphological trait by Hooded Warbler breeding region, age, and sex...... 79 Table 14. Principal components analysis on size corrected flight feather measurements. 80 Table 15. Mean and standard error of each Hooded Warbler morphological, body condition, and performance variable by age and sex...... 123 Table 16. Principal components analysis on size corrected flight feather measurements...... 125 Table 17. Ten best AICc supported models and the full model...... 133

LIST OF FIGURES

Page

Figure 1. Bill and wing morphometric data collection ...... 38 Figure 2. Phylogenetic relationships among Parulidae. Adapted from Barker et al. 2015 41 Figure 3. Parulid taxa plotted in morphospace...... 58 Figure 4. Hooded Warbler breeding, migration, and wintering ranges...... 70 Figure 5. Hooded Warbler breeding density throughout its breeding...... 71 Figure 6. Right wing of a prepared Hooded Warbler indicating flight feather names and numbers...... 76 Figure 7. Size corrected Hooded Warbler wing chord by year...... 81 Figure 8. Change in wing morphology- represented by log10 and size corrected principal component 1- through time...... 82 Figure 9. Change in wing morphology- represented by log10 transformed and size corrected principal component 1- by sex through time...... 83 Figure 10. Total bill length in mm by age and sex...... 84 Figure 11. Wing chord length in mm by age and sex...... 85 Figure 12. Wing shape represented by mPC1 by age and sex...... 86 Figure 13. Wing shape represented by mPC2 by age and sex...... 87 Figure 14. SY male Hooded Warbler bill length along a latitudinal breeding gradient. .. 88 Figure 15. SY female Hooded Warbler bill width along a latitudinal breeding gradient. 89 Figure 16. SY male and ASY female Hooded Warbler tarsus length along a latitudinal breeding gradient...... 90 Figure 17. ASY male Hooded Warbler museum wing chord length along a latitudinal breeding gradient...... 91 Figure 18. Hooded Warbler wing shape represented by mPC1 wing chord length along a latitudinal breeding gradient...... 92 Figure 19. Morphological data ordinated with a non-metric multidimensional scale...... 93 Figure 20. Hooded Warbler specimens plotted in morphospace...... 94 Figure 21. Northern Hooded Warbler age and sex classes plotted in two dimensional morphospace...... 96 Figure 22. Southern Hooded Warbler age and sex classes plotted in two dimensional morphospace...... 97 Figure 23. Male Hooded Warbler population and age classes plotted in two dimensional morphospace...... 98 13

Figure 24. Female Hooded Warbler population and age classes plotted in two dimensional morphospace...... 99 Figure 25. SY Hooded Warbler population and sex classes plotted in two dimensional morphospace...... 100 Figure 26. ASY Hooded Warbler population and sex classes plotted in two dimensional morphospace...... 101 Figure 27. Field flight tunnel used to constrain Hooded Warbler flight in the field...... 114 Figure 28. Breeding and wintering distributions of the Hooded Warbler...... 116 Figure 29. Right wing of a prepared Hooded Warbler...... 119 Figure 30. Hooded Warbler hematocrit levels by age and sex...... 124 Figure 31. Representative Hooded Warbler wings shape as described by principal component scores 1 and 2...... 126 Figure 32. Comparison of wing loading values by age and sex classes...... 127 Figure 33. Maximum flight velocity of birds in the two study areas...... 128 Figure 34. Maximum flight velocity of all birds throughout the breeding season...... 129 Figure 35. Relationship between maximum flight velocity and body condition represented by hematocrit...... 130 Figure 36. Comparison of maximum flight velocity values attained during the first 2.7m of Hooded Warbler escape flight by age and sex...... 131 Figure 37. Model averaged importance of terms...... 134 Figure 38. Maximum flight velocity as a function of wingtip shape ...... 135 Figure 39. Maximum flight velocity as a function of wing loading...... 136 Figure 40. Surface plot showing the interaction between Hooded Warbler wing loading and wing shape on flight performance...... 137

CHAPTER 1: INTRODUCTION

Ecological Morphology

Local environmental conditions present organisms with unique habitat structure, climate, weather patterns, predation pressures, food resources, shelter, and community interactions. Each individual’s ability to navigate the environment, acquire resources, escape danger, and produce offspring is constrained by the individual’s phenotype.

Heritable aspects of morphology, physiology, and behavior which ultimately improve reproductive performance in the local environment increase in prevalence within the population with each successive generation; leading to local phenotypic adaptation.

While the mechanisms of selection and drift which dictate phenotypic expression by organisms are diverse, the selective pressures imposed on taxa by local ecology likely serve as major drivers of phenotypic diversity across life.

Selection may lead to phenotypic convergence when particular phenotypic traits provide a functional advantage under a particular set of ecological conditions and when taxonomically disparate groups are exposed to similar ecological conditions. Convergent morphology confused early taxonomists who relied on morphological similarity to classify organisms. Distantly related, morphologically convergent taxa were often assumed close relatives or the same species while individuals of the same species exhibiting sex or age class polymorphisms were assumed distinct species. As the concept of convergence gained support, studies seeking to elucidate patterns of morphological evolutionary responses to ecological selective pressures grew the fields of ecological and functional morphology. 15

Ecology, Morphology, and Performance

The fields of ecological morphology (ecomorphology) and functional morphology seek to better understand how ecological pressures shape morphological aspects of phenotype over time and to better understand how a taxon’s morphology constrains ecological function. Ecomorphological studies first describe patterns of correlation between aspects of morphology and aspects of ecology. Subsequent hypotheses regarding the mechanisms driving the ecomorphological relationships are informed by functional morphological studies. Individuals exhibiting different morphologies are subjected to some common test of performance designed to emulate challenges faced by individuals in the natural environment. Individuals which best perform under these emulated natural conditions may better acquire resources and avoid danger in nature. The results of functional performance trials inform specific “form-function” hypotheses by providing evidence for adaptive phenotypic variation. Tests of performance are sometimes used in lieu of more difficult-to-obtain measures of fitness.

Obtaining performance data from wild animals can be challenging and small passerines serve as prime examples of such difficulty. Small volant birds are highly mobile, difficult to capture, and often cannot safely be monitored remotely. Thus for small birds, field performance studies are uncommon. Functional morphological studies of flight conducted on small passerines often involve captive animals trained to fly through laboratory wind tunnels, making flight performance studies expensive and time consuming to perform (Hedenström and Lindström 2017). Further, unintentional effects of captivity, training, transport, and other variables inherently introduced by laboratory 16 conditions may skew our understanding of the relationship between morphology and performance in natural systems. Field-collected flight performance data outperform lab- collected flight performance data in hummingbirds (Segre et al. 2015). Whether such results are common among other avian groups is unknown, but studies like Segre et al.

(2015) highlight the importance of benchmark data obtained from field study (see also

Bäckman et al. 2017).

Scale in Ecomorphological Studies

Ecomorphological studies are generally categorized as broad-scale interspecific studies and fine-scale intraspecific studies. Studies at different taxonomic scales share many conceptual and statistical methodologies but differ by the specific ecological and morphological data which are collected and analyzed. Intraspecific studies typically focus on quantifying subtle differences in morphological traits among subspecies, populations, or individuals and attempt to elucidate the patterns of morphological adaptation to more local-scale ecology. Intraspecific studies are often performed on living individuals and sometimes incorporate aspects of behavioral performance to functionally link ecology and morphology. Intraspecific ecomorphological studies improve our understanding of fine scale ecomorphological relationships and trade-offs associated with local ecology or age and sex-specific selective pressures.

Sexually selected traits provide some of the most striking examples of intraspecific functional morphological trade-offs in natural systems. The elaborate display morphologies of male peafowl (Phasianidae: Pavo and Afropavo) or widow birds

(Ploceidae: Euplectes) drastically decrease predator avoidance performance and serving 17 as signals of male quality to females. More subtle functional trade-offs, such as the bite force or thermoregulation (ecological selection)/ bill closing speed (sexual selection) trade-off shaping the bill of the Large Ground Finch (Geospiza magnirostris) are less intuitive (Herrel et al. 2009). Failure to consider such functional trade-offs at the intraspecific scale may lead to erroneous or confusing ecomorphological conclusions at higher taxonomic scales.

Taxonomically diverse comparative studies often center on convergence to elucidate broad scale ecomorphological relationships and utilize species, genera, families, and sometimes higher classifications as the base units. In many comparative studies, the morphological variation of entire taxa are represented by measurements from a small sample or even single individuals under the assumption that intraspecific variation is small relative to interspecific variation. Although intraspecific studies would likely benefit from inclusion of genetic data, most do not take population-level or family-level relationships into consideration. However, comparative studies are rarely performed without an attempt to control for potential morphological similarity due to synapomorphy.

Methods for incorporating independently derived phylogenetic relationships into statistical models of phenotypic evolution have alleviated many of the issues associated with non-independence of sample taxa (i.e. Felsenstein 1985). Phylogenetic comparative methods thus permit statistically robust assessments of the strength of ecomorphological and functional morphological relationships. Comparative studies rarely incorporate the intraspecific variation highlighted in fine-scale studies. The field of ecomorphology is 18 slowly embracing the value of population, age, or sex-specific ecological and/or morphological variation in comparative studies (see for example summaries by Norberg et al. 1981, Norberg et al. 1990, and Bolnick et al. 2011). Lack of inclusion of phylogenetic information in intraspecific studies combined with a lack of consistency in the inclusion of intraspecific variation at broad ecomorphological scales may partially explain differences in ecomorphological patterns sometimes observed at different scales.

The local population, age, and sex-specific functional trade-offs detectable at fine scales may obscure some ecomorphological patterns at higher taxonomic scales. At the broad taxonomic scale, studies have described consistent patterns of wing shape correlation with migration distance across Aves (Vágási et al. 2016). At a fine taxonomic scale, the Yellow-rumped Warbler (Setophaga coronata) complex spans a migration distance gradient with some clades showing no migratory behavior to some clades migrating thousands of kilometers. Differences in wing shape among Yellow-rumped

Warbler populations mirror patterns observed across the rest of Aves (Milá et al. 2008).

However, repeated assessments at the intermediate scale of the avian family Parulidae which contains the Yellow-rumped Warbler complex have found no correlation between migration distance and wing morphology. Ecomorphological studies conducted at different scales will improve our understanding of the evolutionary morphological responses to different selective pressures.

Ecology and Avian Wing Morphology

Birds are popular model taxa in ecomorphological and functional morphological studies due to rich species diversity, extensive morphological and behavioral diversity, 19 and broad geographic and ecological distributions. Ecomorphological patterns observed throughout Aves have increased science’s understanding of morphological evolutionary responses to pressures associated with migration (Lockwood et al. 1998, Tellería et al.

2001, Bowlin and Wikelski 2008, Vágási et al. 2016, Grilli et al. 2017), breeding and wintering habitat use (Mérő et al. 2016), foraging ecology (Woodall 1991, Moreno and

Carrascal 1993, Moreno and Carrascal 1994, Miles and Ricklefs 1984), predator escape strategy (Kullberg et al. 2000, McFarlane et al. 2006), thermoregulation (Tattersall et al.

2009, Luther and Greenberg 2013) and reproduction (Hedenström and Möller 1992,

Nowakowski 2000). Continued exploration of ecomorphological and functional morphological relationships along a spectrum of taxonomic scales will improve our understanding of the environmental drivers of phenotypic evolution and better understand patterns of morphological and ecological trait covariation across life.

Along with the bill, the wing is one of the most actively studied aspects of avian morphology. For species which rely on flight for locomotion and display, wing morphology is likely under strong selective pressure. Interspecific and intraspecific studies regarding the avian wing have revealed strong functional and ecomorphological associations between wing shape and predator evasion strategies (Alatalo et al. 1984,

Kullberg et al. 2000; Burns and Ydenberg 2002, Metcalfe and Ure 1995), foraging strategies (Gustafsson 1988, Rayner 1988, Vágási et al. 2016), dispersal and migration strategies (Buerkle 2000, O’Brien and Dawson 2008, Dawideit et al. 2008), and reproductive success (Hedenström and Møller 1992, Blomqvist et al. 1997). Studies elucidating the functional link between wing shape and aspects of takeoff performance 20

(Swaddle et al. 1999, Labocha et al. 2015), maximum flight speed (Swaddle and

Lockwood 2003), aerial maneuverability (Swaddle and Lockwood 2003), and flight efficiency (Norberg 1995) provide a foundation for development of proximate hypotheses regarding the evolution of avian wing ecomorphological associations.

As one explores the ecomorphological literature regarding the wing, migration ecomorphology is popular. Migratory behavior allows organisms to capitalize on seasonally abundant resources as those resources become available in disparate parts of a species’ range or to avoid inhospitable seasonal variation. The resource benefits associated with migration are great and diverse but do not come without cost. The migratory route exposes migrants to unfamiliar, inhospitable, and dangerous environments (Lindström 1989, Sillett and Holmes 2002). Morphological or behavioral traits which allows migrants to reduce the overall duration of migration and thus limit exposure to one of the deadliest periods of the adult bird’s annual cycle may be beneficial and selected for.

Studies assessing the relationship between wing and tail morphology and migration distance or speed have uncovered varied relationships that seem constrained by aspects of life history (Hummel 1983, Hedenström 2007, Grilli et al. 2017). However, an overarching pattern across flap-powered migrants is one of increasingly high aspect and pointed wings and short tails among increasingly long-distance migrants (Alerstam 1991,

Winkler and Leisler 1992). Functional morphological studies show high aspect and pointed wings and short tails reduce the costs of drag associated with fast flight.

Migratory bird species possessing high aspect wings, pointed wings, and short tails may 21 experience improved flight speed performance and experience reduced exposure to a costly period of the annual cycle (see Ydenberg et al. 2007).

In addition to long-distance travel, migrants often implement wing-powered locomotion strategies to navigate the breeding and wintering environments. Phenotypic traits, which facilitate individual survival during the migration period, may be at odds with phenotypic traits which facilitate survival, foraging success, improved body condition, parental care, and reproduction during the non-migratory period. The high aspect, pointed wing shape of migratory taxa which utilize open habitats at migratory stopover sites, on breeding grounds, and on wintering grounds may not present as great a hindrance to foraging and aerial locomotion (although see Lima 1993) as the same wing shape would for taxa which inhabit structurally closed environments where rapid takeoff or slow, maneuvered flight is critical.

Structural obstacles prevent direct flight patterns and taxa inhabiting closed and structurally complex environments rely on slow maneuvered flight, frequent short- distance flights, or hindlimb-driven locomotion to navigate the habitat (Savile 1957,

Robinson and Holmes 1982, Rayner 1988). Morphological features which facilitate efficient take-off performance, improve slow and maneuvered flight performance, or increased stride length may be advantageous to birds foraging in dense environments.

Long-distance migrants inhabiting dense foraging habitats may thus experience opposing selective pressures with rapid, forward flight performance favored during migration and slow, maneuvered flight favored outside migration. The wing shapes of migratory species 22 living in closed portions of the habitats may represent functional morphological trade- offs resulting from conflicting selective pressures.

The strength of migratory versus breeding/wintering selective pressures on wing shape may differ between sex classes or across age classes. The first male birds arriving to the breeding grounds may better acquire and defend high quality territories than males arriving later (Aebischer et al. 1996). Early arriving males may also be more likely to reproduce than males arriving later (Lozano et al. 1996). The reproductive benefits male birds may experience from rapid spring migration may lead to wing size and shape dimorphism among migrant taxa. Female birds may also experience fitness benefits from early arrival to the breeding or wintering grounds (Tarka et al. 2015); however, females may be less time constrained than males and/or may experience sex-specific benefits from increased maneuverability and take-off performance associated with more broad and rounded wings. As we continue to explore the patterns of ecological and morphological variation from the scale of individuals and populations to the scale of families and beyond, we improve our understanding of the evolution of shape.

The New World Wood Warblers (Family Parulidae)

The avian family Parulidae, collectively referred to as the New World wood warblers (hereafter ‘warblers’), is an ecologically and phenotypically diverse clade of oscine Passerines (songbirds). The family is comprised of 18 genera and 118 extant member species. Sixty-seven of the 118 species are monotypic. The remaining 51 species are formally divided into 238 distinct subspecies (Gill and Donsker 2018). The extensive 23 taxonomic diversity, in combination with equally extensive morphological and ecological diversity makes the warblers an excellent system for ecomorphological study.

Morphological diversity in the warblers led to confusion among early taxonomists regarding the evolutionary relationships among member species. Warblers in the genus

Vermivora, possess bills similar to wrens (Passeriformes: Troglodytidae). The American

Redstart (Setophaga ruticilla) and the tropical whitestarts (genus Myioborus) were thought to be flycatchers (Passeriformes, Tyrannidae) because of their shared aerial foraging behaviors and bill morphology (See Morse 1989). Only recently have incertae sedis taxa such as the Yellow-breasted Chat (Icteria virens, Passeriformes, Icteriidae) been moved to better resolved and supported branches. Advances in molecular phylogenetics have shifted our understanding of warbler evolutionary relationships

(Lovette et al. 2010, Barker et al. 2015) and the morphological similarities between warblers and other avian taxa, for example similarities between the redstarts and flycatchers, are now attributed to ecomorphological convergence (homoplasy) (Parkes

1961) and not shared derived characters (i.e. synapomorphies)

Intraspecific and paraphyletic interspecific warbler ecomorphological studies are common in the literature, however genera are not equally represented. Warbler species which migrate into or are resident within North America are popular study taxa while many Central and South American taxa are virtually unknown. The warbler genus

Setophaga contains 31% of all Parulid species and 33% of the recognized Parulid subspecies (Gill and Donsker 2018). Prevalence of the family and especially prevalence of the genus Setophaga in North American avian communities has led to an extensive 24 study bias of migratory, North American-breeding warbler taxa. Lack of life history data for sedentary tropical species make family-level analyses difficult and few studies have been performed at the level of Parulidae (but see Winger et al. 2011, Najar and Benedict

2015, Simpson et al. 2015, Gómez et al. 2016). Despite extensive variation in both wing morphology and migratory behavior, to my knowledge, no study has found a warbler family-wide correlation between migration distance and wing morphology.

Studies exploring population, age, and sex-specific differences in warbler ecology and morphology can be extensive. The Yellow-throated Warbler (Setophaga dominica) exhibits unique morphological features which facilitate novel foraging behavior performance in populations sympatric with the otherwise morphologically and ecologically similar Pine Warbler (Setophaga pinus) (Ficken et al. 1968). Avian sexual dimorphism and morphological changes during ontogeny may facilitate age and sex- specific differences in habitat use (Selander, 1966), foraging behavior (Gustafsson 1988,

Shaffer et al. 2001, Phillips et al. 2004, Carbodevilla et al. 2018) parental care (Bondel et al. 2002), and predator evasion strategies (Alatalo et al. 1984, Burs and Ydenberg, 2002).

The interspecific and intraspecific ecological and morphological variation across

Parulidae, combined with taxonomic diversity, historic (museum specimen) and modern morphological data availability, and well resolved phylogenetic relationships at the species level, primes the family for a modern assessment of ecomorphological pattern across taxonomic scales.

We can improve our understanding of fundamental principles of evolution by natural selection and the agents of selection on morphology through tests of functional 25 morphological and ecomorphological hypotheses across taxonomic groups and across taxonomic scales. For this dissertation, I explored ecomorphological relationships at two scales uncommon in the Parulid literature – a family-wide assessment and across the entire breeding range of a single species. I also sought to expand the body of literature linking ecology and morphology with performance assessments and explore individual- level relationships between wing shape and flight performance in a wild avian system.

Chapters

In chapter 2, I combine morphological data collected from 102 warbler species, ecological data gleaned from the literature, and modern warbler phylogenetic relationships (Lovette et al. 2010, Barker et al., 2015) to explore potential ecomorphological relationships among migration distance and breeding habitat use and species-specific and sex-specific morphological variation in bill, wing, tail, and hindlimb morphology at the family-level. In chapters 3 and 4, I characterize the ecomorphological and functional morphological variation in a single warbler taxon, the Hooded Warbler

(Setophaga citrina). In chapter 3, I use Hooded Warbler museum specimens across the species’ breeding range to explore spatial and temporal patterns of Hooded Warbler morphological variation across the breeding range, among age and sex classes, and compare the morphology of putative northern and southern Hooded Warbler breeding populations. In chapter 4, I explore the functional link between ecology and morphology of Hooded Warblers by quantifying the relationship between Hooded Warbler wing shape and flight performance in a monitored, wild population of Hooded Warblers breeding near the northern limit of the species’ breeding range. 26

CHAPTER 2: ECOLOGY AND MORPHOLOGY OF THE NEW WORLD WOOD

WARBLERS

Abstract

Migration is a costly but critical component of the annual cycle of many bird species. The migratory habitat entails surviving two major flights that expose individuals to a myriad of selective agents. Past studies of New World wood warblers have failed to demonstrate a relationship between morphology and migration. In this study, I combined museum morphological data, ecological data obtained from the literature, and modern warbler phylogenetic relationships from 102 warbler species to: 1) describe the strength and pattern of morphological and ecological evolution in the warblers; 2) elucidate the ecological variables which best correlate with variation in warbler morphology, and 3) explore the degree of warbler sexual dimorphism among ecological groups. Except the wing and tail, morphological and ecological variables were strongly influenced by phylogeny. While I expected flight morphology to correlate with migration distance, I found wing aspect tail length correlate with foraging habitat complexity. Sedentary taxa occupy a distinct region of morphospace relative to migrants characterized by short wings and long tails and hindlimbs relative to migrants. Among migrants, those migrating more than 2850km show the least overlap in morphospace by foraging openness group. Long- distance migrant taxa which utilize open habitats show the least overlap in morphospace by sex. Sexual dimorphism does not increase total morphospace occupancy of any tested ecological group. Results expand our understanding of the evolution of New World 27 warbler ecomorphological relationships, highlight the need for more warbler life history data, and confirm further, more fine scale ecomorphological study is needed.

Introduction

Migration

Approximately 20% of extant bird species exhibit some form of migratory behavior (Kirby et al. 2008). Migration allows organisms to capitalize on seasonally abundant resources as they become available in disparate parts of the organism’s geographic range (Hurlbert and Haskell 2003, Boucher-Lalonde et al. 2014, Dalby et al.

2014) or avoid harsh winters (Herrera 1978, Hurlbert and Haskell 2003). Many taxa have evolved reproductive strategies which coincide with seasonal abundance of resources in breeding grounds (van Noordwijk et al. 1995) and return to more equatorial wintering grounds before weather-driven reductions in available resources compromise future survival (Somveille et al. 2015). Migratory benefits, however, do not come without cost.

Migration is one of the most deadly periods of an adult bird’s annual cycle. Sillett and Holmes (2002) estimated 85% of annual mortality in Black-throated Blue Warblers

(Setophaga caerulescens) occurred during the relatively short annual migratory periods.

Raptor mortality can be as much as six times greater during migration than in sedentary periods (Klassen et al. 2014). Migrants are faced with pressures associated with physical exertion, high energetic demands, disease, pollution, dynamic temperature changes, collisions with anthropogenic structures, and predation as they travel between breeding and wintering habitats. 28

The energetic demands associated with long-distance travel are great

(Hedenström and Alerstam 1997, Alerstan and Hedenström 1998, Pennycuick 1998,

Aagaard et al. 2018). Some Catharus thrushes spend 4.6 total hours in active migratory flight per day during spring migration, however that 19% of the day devoted to migratory flight expends 55% of the total daily energy used by the bird (Wikelski et al. 2003).

Beyond the more straightforward costs of the physical exertion of flight, migration presents other costs to birds. During migration, pro-oxidant metabolic byproducts cause oxidative lipid damage and a compromised immune system (Eikenaar et al. 2017). As birds coalesce into large and mixed-species flocks or when large numbers of birds gather during stopover, close contact may facilitate the spread of disease and parasites

(Waldenström et al. 2002, Xu et al. 2016) among already immune-compromised individuals. In addition the physiological costs of migration, the migratory route itself can also be dangerous.

Flap-powered migratory taxa often migrate at night to better dissipate excess heat produced during exertion. Nocturnal migrants use geomagnetic as well as astrological cues to navigate at night (Cochran et al. 2004). General sources of anthropogenic light pollution may thus present a danger to migrants as light can reduce astrological navigational ability and increase the overall duration of migration. However high- intensity urban lighting installations present a true danger to nocturnal migrants. Van

Doren and colleagues found the “Tribute in Light” memorial installation in New York

City attracted passing migrants and accumulated densities of migrating birds to 20 times baseline densities. Further, many migrants became trapped within the light column until 29 lights were extinguished (Van Doren et al. 2017). Often powerful lighting installations are located in urban areas where they bring migrants into contact with buildings or other physical structures.

Anthropogenic structures are some of the most devastating causes of mortality to migrating birds. Each year millions of migrating birds collide with buildings, turbines, power lines, antennae, airplanes, helicopters, and increasingly with unmanned aerial vehicles (drones) (Lambertucci et al. 2015). The impact of wind turbines on migrating birds is still controversial, however as many as 2.1% of birds migrating within range of a wind turbine are struck (Aschwanden et al. 2018) and turbines may present an even more detrimental hazard to residents than migrants (Martín et al. 2018). Collisions with buildings, however, present one of the largest anthropogenic sources of migrating bird mortality (Machtans et al. 2013, Loss et al. 2014). Large buildings in urban areas and buildings with landscaping generate the greatest impact (Hager et al. 2017). While most studies have been done in North America, research abroad highlights the ubiquitously detrimental effects building windows have on nocturnal migrants (Low et al. 2017).

Few species embark on non-stop flights between breeding and wintering grounds.

Energetic demands are too great even for fat-loading to provide sufficient resources for most direct flights. The majority of time spent during migration is devoted to resting, re- supplying energy reserves (Wikelski et al. 2003, Smith and McWilliams, 2013, Gόmez et al. 2017), and possibly social learning (Németh and Moore 2014) at stopover sites. The length of time any given bird spends at a stopover site will be determined by individual condition, temperature, and food availability within the stopover habitat (Gόmez et al. 30

2017). Stopover refueling time may also increase as birds prepare to cross or recover after crossing functional deserts (see Spangler et al. 1995).

Birds rely on landscape-scale traits to locate stopover sites (Chernetsov 2006,

Butler et al. 2007), however assessing the quality of resources within the stopover habitat and level of predation danger must be assessed after birds have moved into the area.

Energetically expensive exploratory flights during stopover further increase metabolic demands and can increase overall migration duration (Schmaljohann et al. 2011). Some anthropogenically influenced habitats may appear attractive to passing birds, however hidden dangers render many of these environments ecological traps. For example, agricultural landscapes, especially cover crop fields in spring attract migrants (Wilcoxen et al. 2018). While agricultural fields allow birds to remain alert against predators, taxa using agricultural fields are often exposed to deadly levels of pesticide (Goulson 2014).

Causes of mortality experienced during migratory flights may also be encountered during foraging flights within stopover environments, but the highest rates of mortality during stopover arises from predation, both natural (McCabe and Olsen 2015) and anthropogenic (i.e. domestic cats (Loss et al. 2015)). For example, Lindström (1989) estimated predation pressure reduced the abundance of two migrant passerine species by approximately 10% at a single stopover site. Physical exertion, pollution, collisions, and predation make migration one of the most dangerous periods of a bird’s annual cycle.

Any morphological or behavioral traits which allow migrants to reduce the overall duration of migration, decrease time spent at stopover, or reduce exposure to predators may be beneficial and thus selected for. 31

Studies assessing the relationship between flight morphology and migration distance or migration speed across diverse avian taxonomic scales reveal varied trait associations that seem constrained by aspects of species-specific life history attributes.

These include flight style (i.e. flapping vs soaring; Grilli et al. 2017), flocking behavior

(i.e. loose flocking vs. formation flying; Hummel 1983) and body size (Hedenström

2007). However, a consistent pattern among migrants using powered (i.e. flapping) flight is one of increasingly high aspect wings, pointed wing tips, and short tails among increasingly long-distance migrants (Alerstam 1991, Winkler and Leisler 1992,

Lockwood et al. 1998, Peres-Tris et al. 2001, Bowlin and Wikelski 2008, Milá et al.

2008, Vágási et al. 2016; although see Huber et al. (2016) for a striking exception among the Hirundinidae (Swallows)). The wing and tail shape possessed by so many taxonomically diverse migrants is often interpreted as adaptation facilitating rapid migration (Mulvihill and Chandler 1990, Mönkkönen 1995, Nowakowski et al. 2014,

Vágási et al. 2016). Functional morphological studies show high aspect and pointed wings and short tails reduce the costs of drag associated with fast flight. Migratory bird species which possess high aspect wings, pointed wings, and short tails may experience reduced energetic costs associated with migration, experience reduced exposure to the migration route, or energetically compensate for long, circuitous migratory routes which avoid heavy predation risk (see Ydenberg et al. 2007).

Functional Morphological Trade-offs

The morphology exhibited by a taxon is driven by multiple selective forces and represents a trade-off of competing performance requirements. In addition to long- 32 distance travel, migrants may utilize their wings to implement wing-powered locomotion strategies as they navigate the breeding and wintering environments. Phenotypic traits which facilitate individual survival during the migration period may, at least for some taxa, entail trade-offs with other traits which facilitate survival, foraging success, or reproductive success during the non-migratory period.

Robinson and Holmes 1982, Rayner 1988). The high aspect, pointed wing shape of migratory taxa only generate sufficient lift to overcome gravity at high speeds making slow and maneuvered flight and repeated take-off flights costly. Migratory species which utilize structurally open habitats at migratory stopover sites, on breeding grounds, and on wintering grounds may not experience a great a hindrance to foraging and aerial locomotion (although see Lima 1993). However migrants inhabiting structurally closed environments would not be able to capitalize on forward momentum and experience increased energy requirements, relying on a greater wingbeat frequency to generate sufficient lift. Morphological features which facilitate efficient take-off performance, improve slow maneuvered flight performance, or increase stride length may be advantageous to birds foraging in dense and dangerous environments. Long-distance migrants inhabiting dense foraging habitats may thus experience opposing selective pressures with rapid, direct flight performance favored during migration and slow, maneuvered flight favored outside migration. 33

Ontogenetic and Sex Polymorphism

Unique ecology experienced by different age classes or sexes may drive sexual dimorphism and ontogenetic shifts in morphology. Many birds exhibit age and sex- specific differences in habitat use, foraging behavior, and morphology. Juvenile warblers possess low aspect, rounded wings relative to adults. This shape, according to flight biomechanics studies, permits rapid takeoff performance and maneuverability leading many to hypothesize the wing shape possessed by juveniles is shaped by predation pressures. Post-fledging juvenile birds often rely on cover provided by dense vegetation and rapid take-off escape behavior when concealment fails. Navigating the complex understory habitat with a wing shape that better permits predator escape is selected for.

In migratory taxa, males often exhibit a high aspect, pointed wing shape relative to females. This shape, according to functional morphological studies, permits fast flight leading many to hypothesize the wing shape possessed by males is shaped through fitness advantages for early arrival to summer breeding grounds. Males arriving sooner may establish and better defend high quality breeding territories (Aebischer et al. 1996) or produce more offspring than males arriving later (Lozano et al. 1996). The reproductive benefits male birds may experience from rapid spring migration may be a driver of wing size and shape dimorphism among migrant taxa.

Female birds may also experience fitness benefits from early arrival to the breeding grounds (Tarka and Hasselquist 2015), however females may be less time constrained than males and/or may experience sex-specific benefits from increased maneuverability and take-off performance associated with more broad and rounded 34 wings. During the breeding season when females experience mass gain associated with egg production, selection may favor females which are better able to escape predation. In taxa which implement female-dominated incubation or parental care strategies, females may further benefit from improved predator escape and maneuverability amongst the nest substrate. Differences in morphology between some male and female warblers facilitate reduced prey competition between the sexes on the breeding grounds. Experimental tail shape manipulation in the Hooded Warbler resulted in a decrease aerial foraging attack rates and a decrease in winged prey provisioned by females to chicks, while males showed no change in winged prey provisioned (Mumme 2014).

Parulidae

The New World wood warbler family Parulidae is comprised of 118 extant member species and one recently extinct species, Bachman’s Warbler (Setophaga bachmanii). Warbler species occupy a diversity of habitats and vegetation types including montane and sub-montane habitats, cloud forests, temperate and tropical rainforests, tropical and temperate forests, peatlands and marshes, scrublands, grasslands, and swamps. Lucy’s warbler (Leiothlypis luciae) breeds in the mesquite (genus Prosopis) thickets of the Sonora desert and forages by leaf and branch gleaning in the dense understory. The Black-and White Warbler (Mniotilta varia) forages by probing the bark of large tree branches and breeds in the structurally complex temperate deciduous forests of North America. The Slate-throated Whitestart (Myioborus miniatus) forages by flycatching in the mid canopy and breeds in the humid highland forests of Mexico, Central

America, and South America. The Louisiana Waterthrush (Parkesia motacilla) forages 35 by probing the leaf litter and stream banks in the temperate deciduous forests of the eastern United States.

Despite the migratory ancestral state of the warblers (Winger et al. 2011), 66 of the 119 warbler species are either non-migratory or perform only short (often altitudinal) annual movements. All other species have populations that perform annual migrations between northern breeding grounds and southern wintering grounds. The distance each species migrates varies interspecifically and intraspecifically. Florida-breeding populations of the Swainson’s Warbler (Limnothlypis swainsonii) are some of the shortest-distance migrant warblers with individuals wintering in the rainforests of the

Yucatán and Cuba and breeding in the southeastern United States (Meanley 1971).

Alaskan breeding populations of the Blackpoll Warbler (Setophaga striata) are some of the longest-distance migrant warblers with individuals wintering in the rainforests of northern and central South America and breeding throughout northern Alaska. The taxonomy of the Yellow Warbler is complex with as many as 43 distinct subspecies (Gill and Donsker 2018), and the species exhibits the greatest variation in migration of the warblers (Milot et al. 2001). Some populations are sedentary, breeding and wintering throughout the Caribbean islands; other populations are short-distance migrants wintering in Central America and breeding throughout Mexico; and some populations rival

Blackpoll Warblers as the longest-distance migrants wintering in northern South America and breeding in northwestern Alaska.

I explore the patterns of correlation between body shape and migration and foraging habitat structure within the taxonomically, behaviorally, and morphologically 36 diverse clade of birds; the New World wood warblers (Passeriformes: Parulidae).

Ecomorphological studies outside of the North American breeding warblers are uncommon. However considerable variation in ecology and morphology across

Parulidae, variation in age and sex dimorphism, growing museum collections, and advances in Parulid phylogenetics prime the warbler family for further ecomorphological study. I combine morphological data, migration distance data, and foraging habitat structural complexity data in a phylogenetic comparative context to explore broad ecomorphological relationships and degree of sexual dimorphism among migratory and non-migratory New World wood warblers.

Methods and Materials

Specimen Selection

We collected 7 morphological measurements representing bill, wing, hindlimb, and tail size and shape from 1,364 specimens representing 102 species of Parulid warbler

(Appendix A). The broad distribution of Parulidae and rarity of many taxa limited our morphological sampling to preserved museum skins. All specimens were obtained from the Smithsonian Institution (NMNH), The American Museum of Natural History

(AMNH), The Field Museum of Natural History (FMNH), the Carnegie Museum of

Natural History (CM), and the Ohio University Vertebrate Collection (OUVC). We attempted to measure 8 individuals per sex per species, but sample sizes ranged from 1 to

12 specimens per sex per species. I limited sampling to the longest distance migratory subspecies for polytypic species. 37

Morphological Variables

Morphological Measurements

We measured total bill length (from the naso-frontal hinge to the tip of the bill –

BL, Figure 1A), bill width (at the anterior of the nare - BW), bill height (at the anterior of the nare – BD, Figure 1B), tarsus length (from the intertarsal joint to the distal leg scale –

Tars (Pyle 1977)), wing chord length (Wing, Figure 1C), primary projection length

(distance from the tip of the longest secondary to the tip of the longest primary from a folded wing – PP; Figure 1D), and tail length (from pygostyle to the tip of the longest rectrix – TL (Pyle 1977) to the nearest 0.1mm using digital calipers. I reduced the effects of body size by subtracting a multivariate (Mosimann 1970, Mosimann and James 1979,

Freeman and Jackson 1990) proxy of body size (geometric mean of bill length, wing length, tail length, and tarsus length) from each morphological measurement (Mosimann

1970). All morphological data were log10 transformed prior to analyses. I assessed univariate and multivariate trait distributions and variance assumptions using the MVN package (Selcuc et al. 2018) in the R statistical program (R core team 2018). I used species averages in all analyses unless specified otherwise (species, not individuals, are replicates of ecological groups in phylogenetic analyses). I used internal functions from various packages in R to check the performance of statistical tests. 38

Figure 1. Bill and wing morphometric data collection A) Bill length measurement from naso-frontal hinge to the tip of the bill B) Bill height measurement at the anterior of the nare C) Museum wing chord length measurement and D) Primary projection length measurement

Sexual Dimorphism

Sexes sometimes experience different selective optima for shared traits, generating intralocus sexual conflict. One way sexual conflict is thought to be resolved is the evolution of sexual dimorphism. The sexual dimorphism equation I used was developed by Lovich and Gibbons (1992) and is the preferred metric of sexual dimorphism for morphological traits (Cox et al. 2003; Tarka et al. 2014). For each morphological trait I calculated sexual dimorphism (SD) as

푀푒푎푛 푡푟푎푖푡 푣푎푙푢푒 표푓 푙푎푟푔푒푟 푠푒푥 푆퐷 = − 1 푀푒푎푛 푡푟푎푖푡 푣푎푙푢푒 표푓 푠푚푎푙푙푒푟 푠푒푥

Ecological Variables

Fine scale habitat use data have not been collected for many sedentary warblers; particularly in the genera Basileuterus and Myioborus. Habitat type and foraging height data for rare taxa are limited to accounts of “presence” in certain habitat types. Thus, I used descriptions by Bent (1953), Curson et al. (1994), Hilty (2003), Post (1978), Ridgely

& Tudor (2009), and Vázquez (2008) to assign taxa to habitat type and foraging height categories (Appendix B). I assigned taxa to migration distance categories based on average migration distance of the measured specimens. I estimated migratory distance for each bird by subtracting the species’ average wintering latitude (Simpson et al. 2015) from the latitude in which each bird was collected and converted to kilometers.

Ecological categories used in the correspondence analysis include 5 descriptions of the habitat type ranging from structurally open to structurally complex: 1) grasslands, wetlands, and brushy fields. 2) scrublands, thickets, and early succession forest, 3) edge habitats and forest gaps, 4) mature broadleaf-dominated forest, and 5) mature softwood- dominated forest; 4 foraging height descriptions: 1) ground, 2) understory, 3) mid-story,

4) canopy; and 4 migration categories: 1) sedentary, 2) short-distance (up to 1700km), 3) medium distance (up to 3500km), 4) long-distance (more than 3500km).

Due to small sample size, ecological categories used in all other analyses include a more generalized assessment of habitat structural complexity and migration distance. I binned taxa into six broad migratory and habitat openness categories using species- specific accounts of breeding and wintering habitat structure from the literature (Bent

1953 and Curson et al. 1994) and migration categories with bin boundaries set using a 40 histogram of sample averaged migration distances. Ecological categories are LO (Long- distance migrants occupying Open habitats), LC (Long-distance migrants occupying

Closed habitats), ShO (Short-distance migrants occupying Open habitats, ShC (Short- distance migrants occupying Closed habitats), SeO (Sedentary taxa occupying Open habitats), and SeC (Sedentary taxa occupying Closed habitats). Sedentary taxa do not migrate or perform only limited seasonal movements, short-distance migrant taxa perform seasonal migrations up to 2750km, and long-distance migrant taxa migrate more than 2850km. Habitat openness refers to the structural complexity of a habitat in which the species is found with open habitats characterized by few structural obstacles and closed habitats characterized by numerous obstacles.

Phylogenetic Signal in Morphological and Ecological variables

Interspecific morphological studies cannot consider individual taxa as independent data points because the evolutionary relationships among taxa (Felsenstein

1985). The degree to which phylogenetic relationships explain patterns in phenotypic data are described with several methods (see Münkemüller et al. 2012). I trimmed the time-calibrated Emberizoid phylogeny by Barker et al. (2015) to include only the wood warbler taxa used in this study (Figure 2) and used the tree to test for phylogenetic signal in my morphological and ecological datasets, elucidate the evolutionary mechanism that best explains morphological and ecological change through warbler evolution, and to correct for phylogenetic interdependence of the data in statistical tests. Ultrametry of the tree was confirmed using the ape package (Paradis et al. 2018) in R.

Figure 2. Phylogenetic relationships among Parulidae. Adapted from Barker et al. 2015 Genera are indicated to the right. Tree generated with ‘ggtree’ package in R (Yu et al. 2017) I assessed phylogenetic signal using size corrected morphological variables as raw continuous variables are expected to be biased by phylogeny because of the inherent effects of body size (Motanu and Schmitz 2011). For each size corrected morphological variable and for each ecological variable, I estimated Pagel’s λ (Pagel 1999) and

Blomberg’s K (Blomberg et al. 2003). Lambda values can range from λ=0.0 (phylogeny explains none of the variation in the data; no phylogenetic bias) to λ=1.0 (data exhibit strong phylogenetic bias and follow a Brownian motion evolutionary model). To quantify phylogenetic covariance relative to that expected under the Brownian motion model (null model) expectation, I calculated Blomberg’s K statistic. Departures from Brownian motion are expected for convergence (Blomberg et al. 2003). Blomberg’s K statistic ranges from K=0.0 (low phylogenetic signal) to K>1.0 (indicates trait similarity among related taxa is greater than expected under a Brownian Motion model of evolution). I obtained λ and K values in the Phytools package (Revell 2017) in R.

Morphological and Ecological Trait Evolution

To identify the evolutionary process that best explains warbler morphological and ecological variation, I compared the morphological and ecological trait variables’ fit to predictions of common evolutionary models; a ‘random walk’ model (Brownian Motion,

BM), a random walk toward a selective optima, (multivariate) Ornstein-Uhlenbeck,

((MV)OU), and a model of decreasing evolutionary rate change through time (Early

Burst (EB)). I used the Rphylopars package (Goolsby et al. 2016) in R to calculate percent variance in morphology and ecology explained by phylogenetic relationships among taxa. Rphylopars uses a phylogenetic mixed model of phenotypic trait evolution while incorporating intraspecific variation (see Silvestro et al. 2015) and measurement 43 error. I used the size corrected data to estimate phylogenetic covariance given each model of evolution. The intraspecific covariance matrix can be fitted to either assume intraspecific measurements are correlated or uncorrelated. I ran each evolutionary model twice, once with intra-individual measurements assumed to be correlated (inter-individual variation drives intraspecific variation) and once with intra-individual measurements assumed to be uncorrelated (measurement error drives interspecific variation; Ives et al.

2007). I then assessed model fit with Bayesian information criterion (BIC; Luo et al.

2010) and Akaike Information Criterion corrected for sample size (AICc).

Correlation between Ecology and Morphology in Parulidae

Using data from migratory taxa, I looked for univariate and multivariate linear relationships between species-averaged morphological variables and species-averaged migration distance. I used phylogenetic generalized least squares (PGLS) to regress morphological variables against migration distance using the R packages nlme (Pearson et al. 2018) and Geiger (Harmon et al. 2015).

I ordinated migration categories and foraging habitat use data into a reduced set of dimensions using a correspondence analysis in the FactoMineR package (Husson et al.

2014) in R. I correlated species’ average positions in ecological space to species’ average positions in morphological space with a canonical correlation analysis (CCA). I performed CCA twice, once with size corrected morphological variables using the R package yacca (Butts 2009) and once with the size corrected morphological variables and incorporating phylogeny in the R package Phytools (Revell 2017). I tested whether each correlation differed from zero with Bartlett’s Chi-square tests (Butts 2009). 44

Parulid Sexual Dimorphism

The complete dataset violated assumptions of parametric multivariate tests. Using the complete, size corrected, morphological dataset I thus determined whether there were differences between sexes and among ecological groups with a permutational multivariate analysis of variance (PERMANOVA) in the R package vegan (Oksanen et al. 2018). I used morphological variables averaged by species and sex to create a

Euclidean-based distance matrix and incorporated a non-metric multidimensional scale. I plotted 95% confidence ellipses for each migration and habitat openness category by sex to visualize group position in morphospace. I made pairwise comparisons of group dispersion using Pillai-Bartlet statistic with 1,000, 10,000, and 20,000 permutations using the R package RVAideMemoir (Hervé 2018).

To determine whether sexual dimorphism within ecological groups increases the groups’ total morphospace occupancies, I implemented an analysis of morphospace packing following Butler et al. (2007). I reduced the dimensionality of the morphological dataset with a principal components analysis using the stats package in R (R core team

2018). I used principal component scores which explain more than 80% of the variation in the data (scores 1-3) to define morphospace and binned individual observations into cubes of 0.1 component units in length. I calculated the volume occupied by counting the number of cubes the group occupies by sex. I measured the total volume of morphospace occupied by male birds averaged by species in each group. I then measured the increase in morphospace volume occupied by each group when females averaged by species were added. I determined whether females increased the volume of morphospace occupied by 45 each group by randomizing the sex of samples in 20,000 permutations of the data using slicedice code by M Butler (Butler et al. 2007).

Results

Phylogenetic Signal and Evolutionary Model Selection

Phylogenetic relationships influence warbler body shape and ecological signal

(Table 1): Except wing chord length (λ = 0.36, P = 0.39, all morphological variables averaged by species show strong phylogenetic signal. When sexes were analyzed separately, I found males and female warblers showed strong phylogenetic signal in all morphological traits except wing chord length (male λ = 0.52, P = 0.10; female λ = 0.25

P = 0.48). Males showed low phylogenetic signal in tail length (λ = 0.24, P = 0.22) while females showed strong phylogenetic signal (female λ = 0.72, P<0.001). All ecological variables show strong phylogenetic signal (Table 2). Phylogenetic signal in most morphological and all ecological variables justify our use of phylogenetic comparative methods in further analyses. The best supported Rphylopars model by BIC (and AICc) for both morphological (Table 3) and ecological (Table 4) variables included simulated within-species phenotypic correlation (inter-individual variation drives intraspecific variation) and an Ornstein-Uhlenbeck (OU) model of evolution.

Table 1. Phylogenetic signal for 7 morphological traits among Parulid warblers. λ = Pagel’s Lambda, K= Blomberg’s K statistic. An ‘*’ indicates the observed λ or K is significantly different from λ=0.0 or K=0.0.

Table 2. Phylogenetic signal for ecological traits among Parulid warblers. λ = Pagel’s Lambda, K= Blomberg’s K statistic. An ‘*’ indicates the observed λ or K is significantly different from λ=0.0 or K=0.0. Ecological traits

Foraging Migration Habitat level λ 0.74* 0.38* 0.93* K 0.40* 0.24 0.88*

Table 3. Morphological variables: Evolutionary model selection. BM – Brownian Motion, OU – Ornstein-Uhlenbeck, mvOU – Multivariate Ornstein- Uhlenbeck, EB – Early Burst. The intraspecific covariance matrix can be fitted to either assume intraspecific measurements are correlated or uncorrelated. Corr = intra-individual measurements assumed to be correlated (inter-individual variation drives intraspecific variation) uncorr = intra-individual measurements assumed to be uncorrelated (measurement error drives interspecific variation).

Table 4. Ecological variables: Evolutionary model selection. BM – Brownian Motion, OU – Ornstein-Uhlenbeck, mvOU – Multivariate Ornstein- Uhlenbeck, EB – Early Burst. Morphology and Ecology

Bill: Setophaga warblers exhibit the proportionally longest, narrowest, and shallowest bills with the Vitelline Warbler (Setophaga vitelline) possessing the longest bills, the Cape May Warbler (S. tigrina) possessing the shallowest bills, and the Tropical

Parula (S. pitiayumi) possessing the narrowest bills of the taxa used in this study. The deepest and shortest bills belong to the Masked Yellowthroats (Geothlypis aequinocitalus) and Gray-crowned Yellowthroats (G. poliocephala) respectively. The widest bill belongs to the Rufous-capped Warbler (Basileuterus rufifrons). Wing: The

Cape May Warbler possesses the longest wing chord and the Blackpoll Warbler

(Setophaga striata) possesses the longest primary projection. Adelaide’s Warbler

(Setophaga adelaidae) possesses the shortest wing chord and Belding’s Yellowthroat

(Geothlypis beldingi) possesses the shortest primary projections. Tail: The Cerulean

Warbler (Setophaga cerulean) possesses the shortest tail and the Golden-browed Warbler

(Basileuterus belli) possesses the longest tail. Hindlimb: The Spectacled Whitestart

(Myioborus melanocephalus) possesses the shortest legs and Belding’s Yellowthroat possesses the longest legs.

Ecology: I retained the first five correspondence axes for use in the canonical correlation analysis based on a scree plot. Correspondence axis 1 captures a general habitat complexity and migration distance gradient ( Table 5 ). Structurally simple and open habitats and short migration categories load negatively on correspondence axis one.

Structurally complex and closed habitats and long distance migration categories load positively on correspondence axis 1. Correspondence axis 2 captures a migration axis and an open/closed habitat axis with ground and grassland habitats and medium and long 49 distance migration categories loading positively on correspondence axis 2 (Table 5). The first five axes represent 72.5% of the total ecological variation.

Table 5. Correspondence analysis of ecological data

Covariation Between Morphology and Ecology

Morphology and Migration Distance

Among migrants, I found no or weak univariate relationship between species’

2 average migration distance and species’ average bill depth (F1,47 = 2.71, r adj = 0.03, P =

2 0.11; phylogenetic P = 0.23), bill length (F1,47 = 0.70, r adj = -0.006, P = 0.41;

2 phylogenetic P = 0.22), tail length (F1,47 = 1.65, r adj = 0.01, P = 0.20; phylogenetic P = 50

2 0.14), primary projection length (F1,47 = 3.66, r adj = 0.05, P = 0.06, phylogenetic P =

2 0.11), wing length (F1,47 = 1.91, r adj = 0.02, P = 0.17; phylogenetic P = 0.09), body size

2 (F1,47 = 0.44, r adj = -0.01, P = 0.51; phylogenetic P = 0.08). hindlimb length (F1, 47 = 1.72,

2 2 r adj = 0.02, P = 0.20; phylogenetic P = 0.07) or bill width (F1, 47 = 5.11, r adj = 0.08, P =

0.03, phylogenetic P = 0.07). Among migrants, I found no multivariate relationship between species’ average migration distance and morphology. The best supported multivariate model included wing length, primary projection length, tail length, tarsus length, and all interactions (AICc = 517.0, LogLik = -237.8, model weight = .97) however the model was not significant (all coefficients P > 0.41). I found no relationship between sexual dimorphism for any trait and migration distance (all P>0.33, all phylogenetic P>0.13). Further breakdown of each species by sex does not reveal any morphological relationships with migration distance (all male P>0.23, all male phylogenetic P>0.17; all female P>0.40, all female phylogenetic P>0.11)

Covariation between Migration, Habitat, and Foraging Height Ecology and Bill, Wing,

Tail, and Hindlimb Morphology

I used species averages of each size corrected morphological variable and the first five correspondence analysis axis scores to represent the morphological and ecological variables. Only the first canonical correlation differed from zero (correlation= 0.59, P =

0.003; Table 6) and represents the relationship between morphological canonical variate

1 and ecological canonical variate 1. Morphological variables (Table 7): canonical variate

1 is primarily associated with primary projection length (r2 = 0.86) and wing length (r2 = 51

0.81) and to a lesser degree with tail length (r2 = 0.32). Canonical variate 2 is associated with tail length (r2 = 0.29), bill length (r2 = 0.24), and bill height (r2 = 0.23).

Table 6. Summary of canonical correlation analysis between migratory habitat structural complexity and migratory ecological variables and Parulid morphological variables.

. Table 7. Correlation between each morphological variable or correspondence axis and the canonical variables.

The first morphological canonical variate extracts 32% of the variation in the morphological variables and 11% of the variance in the ecological variables (Table 8).

The 5 morphological variates extract 77% of the variation in morphology and 14% of the variation in ecology. Thus 77% of the total variation in morphology explains 14% of the total variation in ecology. The 5 ecological variates collectively explain 12% of the total variation in morphology. Table 8. A canonical redundancy analysis. Within set comparisons are in the upper left and bottom right. Between set comparisons are in the top right and bottom left. Cumulative proportions of variance in either the morphological or ecological variables (correspondence axes) with morphological or ecological canonical variables.

After controlling for phylogeny, only the first canonical correlation differed from

0.0 (correlation 1= 0.77, P<0.001, correlation 2= 0.40, P=0.20; Table 9Error! Reference source not found.). Morphological phylogenetic canonical variate 1 is primarily associated with primary projection length (r2 = 0.14), tarsus length (r2 = 0.11), and wing length (r2 = 0.10; Table 10). Ecological phylogenetic canonical variate 1 is primarily associated with correspondence axis 1 (r2 = 0.04).

Table 9. Summary of phylogenetic canonical correlation analysis between migratory habitat structural complexity and migratory ecological variables and Parulid morphological variables.

Table 10. Summary of phylogenetic canonical correlation analysis between migratory habitat structural complexity and migratory ecological variables and Parulid morphological variables.

Sexual Dimorphism and Morphological Niche Breadth

I ordinated size corrected morphological variables averaged by species and sex with a principal components analysis. A scree plot indicated the first three component scores should be retained. The first three principal component scores explain 94.0% of the variation in morphological data ( Table 11 ). Principal component one was driven by primary projection length and to a lesser degree by wing length, component two was primarily driven by bill width and bill height, and component three was positively influenced by bill length and negatively influenced by tail length. Sedentary clades occupied the greatest breadth of morphospace and short-distance migrants utilizing closed habitats show the most restricted morphospace occupancy ( Table 12 ). Analysis 56 of morphospace packing with 20,000 permutations reveals no apparent increase in morphospace occupancy with sexual dimorphism in the new world warblers (P = 0.56).

Table 11. Principal components analysis on 7 size corrected morphological variables.

Table 12. Results of morphospace occupancy analysis.

Group and Sex-Specific Differences in Morphology

2 PERMANOVA revealed significant differences among groups (F5, 184 = 27.01, r

2 =0.42, P = 0.001) and between sexes within groups (F5, 184 = 12.54, r =0.44, P < 0.001).

Sedentary groups do not differ from one another (all Padj > 0.1) but each sedentary group differs from each migratory group (all Padj < 0.02). Each short and long-distance migrant group differed from one another (all Padj <0.03). Sexes do not differ within sedentary groups, short distance migrant groups, or long-distance migrants inhabiting closed habitats. Only long-distance migrants inhabiting open habitats show sex-specific segregation in morphospace (Padj = 0.01, Figure 3).

Figure 3. Parulid taxa plotted in morphospace. 95% confidence ellipses show position of each sex and ecological category in 2 dimentional morphospace represented by 2 non-metric multidimentional sclae axes. Axes include descriptions of morphospace.

Discussion

Patterns of correlation between flight morphology and migration distance have been described across taxonomic levels leading many to agree migration ecology is a driver of morphological evolution within Aves. Previous work has not detected morphology/ migration distance ecomorphological relationships at the family level within the avian family Parulidae despite the almost ubiquitous nature of the pattern at both higher taxonomic scales (the level of the emberizoids, the level of oscines, and the level of Aves) and lower taxonomic scales (individual Parulid genera and among populations of single species). I used size corrected measures of wing, bill, tail, and hindlimb morphology averaged by species and sex; ecological data taken from the literature; and modern phylogenetic relationships to further explore and describe the drivers of ecomorphological patterns at the family level in the Parulidae.

These results provide evidence within a phylogenetic context that 1) warbler wing and tail morphology show less phylogenetic signal than the other aspects of morphology collected for this study, possibly indicating flight-related traits are under stronger selection; 2) high aspect wings, short tails, and short legs are characteristic of long distance migratory warblers, but the drivers of morphological evolution are unknown; 3) warbler wing and tail morphology show weak correlation with a migration and habitat openness gradient, indicating a broader ecomorphological pilot study is needed to elucidate the drivers of morphological evolution within the Parulid model system; and 4) wing, tail, bill, and hindlimb sexual dimorphism is evident in some warbler species (long- distance migratory warbler taxa inhabiting open environments), highlighting the need to 60 control for intraspecific variation in broad phylogenetic comparative studies as patterns my differ among sex and perhaps age, body condition, etc. Similar to previous studies, I detected no linear relationship between morphology and migration distance. However, data support a weak pattern of increasing wing aspect and shortened tail and hindlimb length with migratory behavior within the New World wood warbler family.

Morphological and Ecological Traits

With the exception of wing length, primary projection length, and tail length, patterns of habitat use and patterns of morphological similarity among warbler species mirror patterns of genetic similarity. Moderate to high phylogenetic signal for morphological and ecological traits necessitate the use of phylogenetic comparative analytical methods. Morphological and ecological variation throughout the warbler clade best support an Ornstein-Uhlenbeck (OU) model of morphological and ecological evolution. The OU model of evolution is similar to the Brownian Motion (BM) model - a simple model in which trait variation accrues consistently with time. The OU model tends to outperform BM for small datasets (fewer than approximately 200 taxa (Cooper et al.

2016)). However, the Early Burst (EB) model was the second best-supported evolutionary model, not BM, which may highlight the rapid, allopatric speciation in the most species-rich Parulid genus, Setophaga, in scattered forest refugia during the late

Miocene or early Pliocene (Lovette and Bermingham 1999).

The OU evolutionary model is best supported when variables exhibit an evolutionary pull toward some optimum value in a clade-wide manner. Within the avian low-aspect and rounded wingtip shape to high aspect and pointed wingtip shape 61 spectrum, warblers possess an intermediate shape (Lockwood et al. 1998). While individual taxa will engage in diverse foraging behaviors and many will consume fruit or nectar, all taxa included in this study are predominantly insectivorous and all engage in branch and leaf gleaning foraging behaviors. Due to limited diet data availability, I did not include foraging ecology in these analyses. However, the generalization of warblers as gleaning insectivores and associated selection for a suite of morphological characters which facilitates a gleaning foraging lifestyle may drive patterns of wing, bill, tail, and hindlimb morphology in a clade-wide manner. More life history data are needed at the species, subspecies, and individual population scales to further elucidate the ecomorphological patterns in the Parulidae.

Morphology and Migration Distance

Among avian taxa which implement flap-style flight, wing size, wing aspect ratio, and tail length generally correlate with migration distance. High aspect wings promote fast flight by reducing the overall drag profile of the wing. The tail facilitates the efficient, long-range, fast flight of birds by reducing overall drag (Thomas 1996). While migrants with tails may be better suited than migrants without tails, increasing tail length reduces flight efficiency (Norberg 1995) by adding weight and increasing drag. Thus, I expected wing aspect to increase with migration distance and tail length to decrease with migration distance. Parulid migratiory ecomorphological relationships have been sought in the past, but no patterns have been detected (Keast in 1980). Similarly, I failed to detect linear relationships between migration distance and any aspect of flight morphology among migratory Parulid warblers despite a broader taxonomic sample, a 62 larger set of morphological features relative to previous studies, and inclusion of phylogenetic relationships.

Migratory warblers occupy breeding habitats similar to wintering habitats (niche tracking – a trait uncharacteristic of the Parulidae-containing clade of 9-primaried passerines (Emberizoids) (Laube et al. 2015)) and exhibit extensive sympatry throughout the northern breeding grounds (Gόmez et al. 2016). Patterns of morphological divergence which facilitate cohabitation among locally sympatric breeding warbler taxa or any species-specific combination of breeding habitat-related selective pressures may explain the apparent lack of migratory ecomorphological patterns expected at the scale of

Parulidae. A weak ecomorphological pattern emerged when I included both migration and foraging habitat structure together. Habitat structure and foraging location seem more important drivers of morphological evolution than does migration behavior as evident from the higher loading of habitat use and foraging height variables than migration variables on correspondence dimension 1.

I limited the resolution of ecological data used for this study to data available for those taxa with the least life history information available. While broad-scale ecomorphological patterns are often described with imprecise data, the local environment can affect morphological variation (Herrando and Brotons 2010). Johnson and Sherry

(2001) showed patterns of species distributions can be influenced by local microhabitat distribution, local food abundance, and local food distribution. Broad scale ecomorphological associations may be masked by traits associated with such taxon- specific differences in fine scale habitat use and food availability undetectable at scales of 63 habitat characterization available for many Parulid taxa. More data are needed regarding the life history of warblers, especially at the population level.

Sex, Morphology, Migration, and Habitat Structural Openness

Both males and females of taxa which migrate more than 2,850km and forage in structurally open habitats possess high aspect wings and short tarsi. Only the long- distance migrant warbler taxa which breed in open habitats occupy distinct morphospace occupancy by the sexes. Male birds in this group possess the highest aspect wings, shortest tails, and shortest hindlimbs of the warblers. As this morphology is characteristic of long-distance migrant taxa in other avian clades, this is not unexpected. While females generally share this morphology with the males, males show the most extreme morphology. Male migrants have been shown to gain fitness advantages with early arrival (Lozano et al. 1996). While early spring arrival may allow early nesting or improved territory selection, selection for maneuverability in the nesting environment or selection for rapid takeoff performance while yolking eggs may drive a slower. but ultimately more maneuverable and more efficient female wing shape relative to males.

Regardless of the structural complexity of the foraging habitat, males and females of sedentary taxa occupy a broad region of morphospace characterized by long tarsi, long tails, and low aspect wings. Long hindlimbs benefit gleaning taxa which forage using hindlimb locomotion. Long hindlimbs increase stride length which facilitates faster and more efficient hindlimb-driven movement through the environment. Long hindlimbs also increase stretch length which allows individuals to forage a broader area without needing 64 to move the entire body through a gait cycle (Fitzpatrick 1978) and allows individuals to forage from branches that would otherwise require costly wing-powered movements.

Insect and plant diversity are greater in tropical environments relative to temperate environments (Novotny et al. 2006) and herbivorous insect-plant host interactions are more specialized in tropical environments relative to temperate environments (Forister et al. 2015). Such diverse and specialized prey-substrate interactions may prevent resident sedentary taxa from developing search images for prey taxa. Sedentary taxa may rely more heavily on slow, methodical search behaviors during periods of high prey demand (breeding season) than the most northerly breeding taxa which rely on comparatively few prey species (for example the Tennessee Warbler

(Leiothlypis peregrine), Cape May Warbler (Setophaga tigrina), and the Bay-breasted

Warbler (D. castanea) are spruce budworm (Choristoneura fumiferana) specialists during the breeding season (Patten and Burger 1998). Where spruce budworm specialists may be limited by their ability to reach new budworm patches and selection for a fast wing continues with the breeding ecology, wings continue to lengthen. Female budworm specialists and other northern species, however, may still rely on slow methodical searches as they seek the smallest prey for newly hatched young and may thus experience a functional wing shape tradeoff. Tropical taxa may be limited by prey detectability and wing, tail, and hinglimb morphology may respond to selection quickly in the more equatorial breeding habitats. High morphological overlap among ecological types and by sex further support a more consistently directional selective ecological pressure in the 65 sedentary taxa compared to a trade-off with migration selection in the longest distance migrants.

The truly interesting body shape-ecological patterns which require finer scale study lie with the intermediate distance migrants. These taxa, I imagine, are the reason family-wide correlations have not been found. When selective pressures driving contradictory morphological features differ along the same ecological gradient, perhaps the taxa with intermediate selection from both rather than strong selection for either can respond morphologically and behaviorally in a greater diversity of ways. Short and intermediate-distance migrants occupy a region of morphospace intermediate between sedentary taxa and long-distance migratory taxa and possess higher aspect wings, and shorter tarsi relative to sedentary taxa. Separation of foraging habitat structural groups and separation by sexes in morphospace becomes evident within the short and intermediate-distance migrants. However, the pattern is weak and does not follow the same patterns seen in the long-distance migrants.

CHAPTER 3: INTRASPECIFIC MORPHOLOGICAL VARIATION OF THE

HOODED WARBLER (SETOPHAGA CITRINA)

Abstract

Descriptions of morphological variation across widespread species’ ranges provide science with a holistic understanding of how selective pressures imposed on populations by the local environment shape the evolution of ecomorphological associations. The Hooded Warbler (Setophaga citrina) exhibits variation in ecology between sexes, across age classes, and across the species’ range. However, little is known about the morphological variation present within the species. Here, we expand the

Hooded Warbler ecomorphological literature by exploring variation in 16 measurements describing bill, wing, tail, and hindlimb morphology among age and sex classes across the species’ breeding range and through time. We observed a north to south, male to female, and old to young progression from long narrow wings and short tails to short wide wings and long tails. These data demonstrate aspects of Hooded Warbler body shape varies through time and wing shape, tail length, and hindlimb length differ among age and sex classes and between northerly breeding birds and southerly breeding birds.

Wing, hindlimb, and tail differences are consistent with other intraspecific morphological studies of migratory taxa conducted along latitudinal gradients. The Hooded Warbler is climate threatened and a northern shift in suitable breeding habitat may drive breeding

Hooded Warbler populations north. Understanding the morphological variation present across the species’ range and through time will inform conservation decisions and improve science’s understanding of morphological responses to ecological change. 67

Introduction

We improve our understanding of fundamental principles of evolution by natural selection and the selective drivers of morphology through tests of functional morphological and ecological morphological hypotheses conducted across taxonomic groups and across taxonomic scales. Morphological studies implementing an extensive taxonomic sampling often utilize species averages obtained from relatively few samples to represent the morphology of entire populations, or species; assuming intraspecific variation is small relative to interspecific variation. However, including intraspecific variation in comparative research promotes a more holistic understanding of ecomorphological patterns (Wiedenfeld 1991, Bolnick et al. 2002, Bolnick et al. 2011).

Descriptions of morphological variation across widespread species’ ranges continue to provide science with a more holistic understanding of how selective pressures imposed on populations by the local environment shape the evolution of ecomorphological associations. As intraspecific studies continue to reveal novel ecomorphological patterns, researchers will continue to advocate for the inclusion of intraspecific variation in ecological research.

Intraspecific morphological variation occurs among ecologically disparate populations, through ontogeny, and between sexes (see review by James 1982). Studies exploring intraspecific ecomorphological variation show population-specific differences in ecology and morphology can be extensive. Ficken et al. (1968) showed populations of

Yellow-throated Warblers (Setophaga dominica) have significantly longer bills than sympatric populations of Pine Warblers (Setophaga pinus). However, where the species 68 distributions do not overlap, populations of Yellow-throated warblers and Pine Warblers show no differences in bill length. The longer bill of Yellow-throated Warblers in areas of sympatry with Pine Warblers allowed Yellow-throated Warblers to probe conifer cones, a substrate inaccessible to the shorter-billed Pine Warblers, which forage for insects among conifer branches and fascicles Ficken et al. (1968). Whether the bill morphological differences between Pine Warblers and Yellow-throated Warblers sympatric on the Delmarva Peninsula were the result of natural selection acting on bill length was difficult to assess in the 1960s. Morphological differences in the wings of closely related populations of Yellow-rumped Warbler (Setophaga coronata) which differ in migration distance. Long-distance migrant populations of Yellow-rumped

Warblers including the Myrtle Warbler (Setophaga coronata coronata) and Audubon’s

Warbler (S. c. auduboni) possess longer, more pointed wings than sedentary populations such as the Black-fronted Warbler (S. c. nigrifrons) and Goldman’s Warbler (S.c. goldmani) (Milá et al. 2008). Intraspecific ecomorphological studies such as these highlight the importance of exploring morphological variation within individual warbler species across their breeding ranges, by sex, or through ontogeny. The idea that warbler morphology can respond quickly to changing ecological conditions continues to drive active research on the strength of selective ecological pressures and rates of morphological evolution.

The Hooded Warbler (Setophaga citrina Boddaert 1783) is a migratory, sexually dimorphic member of the New World wood warbler family Parulidae which exhibits ecological and behavioral variation between sexes and among age classes. Hooded 69

Warblers breed in mature mesic forests (James 1971) throughout the eastern United

States and in the Carolinian forests of southeastern Ontario, Canada (Whittam et al. 2002) and winter from central Mexico to Panama and throughout the Caribbean islands (Figure

4. Hooded Warbler breeding, migration, and wintering ranges.Figure 4). Breeding Bird

Survey data suggest northern and southern breeding concentrations of Hooded Warblers exist (Figure 5). Genetic studies have not been done to determine whether patterns of breeding concentration reflect genetically distinct populations, however differences in long and short distance populations of other Parulid warblers exhibit differences in wing and tail shape. Thus, in addition to describing morphological differences between age and sex classes, I compared the external morphology of northern and southern Hooded

Warbler “populations”. 70

Figure 4. Hooded Warbler breeding, migration, and wintering ranges.

Figure 5. Hooded Warbler breeding density throughout its breeding. Estimated number of breeding pairs per km2. Data from the North American Breeding Bird Survey.

In both the breeding grounds and wintering grounds, the Hooded Warbler displays strong sex-specific habitat segregation with males showing an innate preference (Morton

1990) for open mid-story habitat with vertically-oriented substrate structure. Females prefer dense understory habitat with an obliquely-oriented substrate structure (Lynch et al. 1985; Morton 1990). In addition to foraging in the understory, female Hooded

Warblers locate nests in the dense understory habitat associated with canopy gaps (Bisson and Stutchbury 2000; pers. obs.). Sexual habitat segregation has been documented in many Parulid warbler species including the American Redstart (Setophaga ruticilla),

Magnolia Warbler (S. magnolia), Black-throated Blue Warbler (S. caerulescens),

Common Yellowthroat (Geothlypis trichas), and Northern Parula (Setophaga americana) 72

(Ornat and Greenberg 1990; Marra et al. 1993; Spidal and Johnson 2016). However,

Hooded Warbler habitat segregation on the wintering grounds is more complete than the habitat segregation observed in any other Parulid species (Ornat and Greenberg 1990) and the degree of habitat segregation by sexes drove early Hooded Warbler research.

Lynch et al. (1985) proposed the sexual habitat segregation seen in sexually dimorphic, migratory Parulid warblers may be due to competitive exclusion of females from high quality habitat by more dominant males. While competitive exclusion explains sexual habitat segregation in the American Redstart (Marra et al. 1993), Morton et al.

(1987) showed competitive exclusion does not explain habitat segregation seen in

Hooded Warblers. Lynch et al. (1985) proposed the habitat segregation in the Hooded

Warbler may be ecomorphological; that the unique morphology of male and female

Hooded Warblers may be driven by unique selective pressures presented to each sex.

Morphological features which facilitate efficient take-off performance, improve slow maneuvered flight performance, or increased stride length may be advantageous to female and juvenile birds foraging in the dense understory habitats.

Lynch and colleagues measured exposed culmen length (the length of the bill from the tip of the bill to the first feathers of the head), wing length (museum wing chord length), and standard tarsus length (from the intertarsal joint to the distal leg scale) of 25 male and 25 female Hooded Warbler museum skins; mass from 89 male and 115 female

Hooded Warblers captured during migration; and female variation in melanism of the hood and bib plumage from 198 female museum skins. Briefly, they found males and females did not differ in exposed culmen length or tarsus length, but males had longer 73 wings and were heavier (Lynch et al. 1985). Lynch and colleagues proposed differences in wing length or mass may be due to sex-specific differences in foraging behavior observed on the breeding grounds (behavioral differences have not been found on the wintering grounds (Morton unpublished)).

Modern studies have also detected sex-specific differences in morphology and breeding grounds foraging ecology. Mumme and colleagues (2014) found differences in tail spot morphology between male and female Hooded Warblers are associated with sex- specific differences in foraging behavior. Experimental reductions in Hooded Warbler tail spot size resulted in a decrease aerial foraging attack performance in females and a decrease in winged prey provisioned by females to chicks (Mumme 2014). After the same tail spot reduction, males showed no change in foraging performance and showed no change in winged prey provisioned to chicks (Mumme 2014). Whether sex-specific differences in foraging behavior are consistent across the Hooded Warbler range is yet to be determined.

The Hooded Warbler exhibits considerable variation in migration distance; age and sex-specific differences in foraging ecology; and sex-specific habitat segregation.

The distance individual populations migrate may introduce another source of selective pressure on morphology. Wing and tail shape affect aspects of flight performance such as flight speed (Swaddle and Lockwood 2003), aerial maneuverability (Swaddle and

Lockwood 2003), and flight efficiency (Norberg 1995). Limited assessments explore whether such behavioral and ecological variation is associated with age, and sex-specific differences in morphology. The current understanding of Hooded Warbler 74 ecomorphological and functional morphological associations are founded on a limited pool of studies focusing on a few assessments of exposed culmen length and tarsus length, and crude assessments of wing size and shape. Here, we expand the current body of literature concerning the morphological variation in the Hooded Warbler by describing the morphological variation in wing, bill, tail, and hindlimb size and shape among

Hooded Warbler age and sex classes across the species’ breeding range.

Materials and Methods

To describe intraspecific morphological variation in the Hooded Warbler, I collected 16 linear measurements to represent bill, wing, tail, and hindlimb morphology from 150 Hooded Warbler museum skin specimens collected throughout the species’ breeding range. I selected specimens collected from late April to mid-July to increase the likelihood I sampled birds breeding at the latitude of capture. I collected data from museum specimens held at the Field Museum of Natural History (FMNH) and the

Carnegie Museum of Natural History (CM). I sexed each specimen based on plumage coloration and aged all specimens as either “second year” (SY – first breeding season) or

“after second year” (ASY) based on wing covert molt patterns and rectrix shape (Pyle

1997). Hooded Warblers cannot be aged beyond ASY based on external phenotype. I did not assess juvenile morphological variation due to limited availability of juvenile specimens in museum collections. I obtained specimen collection date and location, reproductive condition, fresh mass, and body fat information, when available, from museum tags. 75

I measured the lengths of each wing feather with digital calipers to the nearest 0.5 mm. I measured primary feathers 1-9 as the distance from the carpal joint to the tip of each flight feather on the closed right wing of each specimen (for wing feather numbering, see Figure 6); I measured the lengths of secondary feathers 1 and 3 as the distance from secondary feather insertion on the ulna to the tip of each secondary feather

(Evered 1990). I measured bill length from the naso-frontal hinge (where the nasal bones meet the skull) to the tip of the bill, bill width at the anterior of the external nare, bill height at the anterior of the external nare, tarsus length from the intertarsal joint to the distal leg scale (Pyle 1997), and tail length from pygostyle to the tip of the longest tail feather (rectrix). I measured each non-wing morphological variable with digital calipers to the nearest 0.1mm.

Figure 6. Right wing of a prepared Hooded Warbler indicating flight feather names and numbers.

I reduced the effects of body size by subtracting a multivariate (Freeman and

Jackson 1990) proxy of body size (geometric mean of bill length, wing length, tail length, and tarsus length) from each morphological measurement (Mosimann 1970, Mosimann and James 1979). I reduced the dimensionality of the wing morphological dataset with a principal components analysis on a covariance matrix of size corrected morphological measurements using the stats and FactoMineR (Husson et al. 2008) packages in R software 3.4.3 (R development core team 2017). I used the first two size free principal 77 components scores (mPC1 and mPC2) to represent size free wing shape in subsequent analyses.

I assessed univariate and multivariate trait distributions and variance using the

MVN package (Selcuc et al. 2018) in R to determine whether data met assumptions of each analysis and transformed as necessary. I compared bill, hindlimb, wing, and tail morphology among age and sex classes using one and two-way analysis of variance

(ANOVA) and Tukey’s honestly significant difference test for multiple comparisons. I tested whether Hooded Warbler morphology changed through time and along a latitudinal gradient using generalized linear models for each morphological variable and included date or latitude and age and sex as explanatory variables.

Finally, I assessed whether multivariate assessments of morphology differ between age and sex classes of Hooded Warblers from northern and southern populations. I assigned birds collected in TX, OK, LA, AR, MS, FL, coastal GA, and coastal SC to the southern breeding population and birds collected from inland GA, inland SC, TN, KY, IN, OH, WV, VA, MD, DE, NJ, CT, NY, and PA to the northern breeding population (Figure 5). I used the complete, size corrected morphological dataset to create a Euclidean-based distance matrix and incorporated a non-metric multidimensional scale. I plotted convex polygons (ordihull) and 95% confidence ellipses

(Ordiellipses) for each potential population, age, and sex group to visualize group position in morphospace. I compared age, sex, and population group centroids with a permutational multivariate analysis of variance (PERMANOVA) using the vegan package (Okansen et al. 2018) in R. I compared pairwise differences in group dispersion 78 using Pillai-Bartlet statistic with 999 permutations using the RVAideMemoir package

(Hervé 2018) in R.

Results

I analyzed morphological data obtained from 150 Hooded Warbler museum specimens (17 ASY females, 68 ASY males, 37 SY females, and 28 SY males; Table

13Table 13) collected during the breeding season across the species’ North American breeding range. Museum collections were biased toward Hooded Warbler specimens collected between the 1870s and 1940s. I found Hooded Warbler collections biased toward ASY male specimens and a general lack of intact ASY female specimens.

Apparent excessive use of available ASY females rendered many of the specimens with broken or missing feathers leading to limited ASY female specimen availability. Table 13. Means and standard errors for each morphological trait by Hooded Warbler breeding region, age, and sex. All measurements are in millimeters. Groups are N – northern birds and S – southern birds, ASY – old birds and SY – young birds, and M – males and F – females.

The first two principal component scores obtained from size corrected flight feather measurements explained 74% of the variation in flight feather data. Principal component one (mPC1) explained 54.9% of the variation in the flight feather data and was influenced positively by the distal-most primary feather lengths (P8 and P9) and negatively by the most proximal feather lengths (Table 14). Principal component two

(mPC2) explained 18.6% of the variation in the flight feather data and was influenced negatively by the distal-most primary and proximal secondary lengths and positively by primaries 4, 5, and 6 (Table 14).

Table 14. Principal components analysis on size corrected flight feather measurements. Coefficients, standard deviation, and cumulative percent variance explained.

Morphological Change through Time

I found no change in wing chord from the late 1870s to the late 2010s (F 1,148 =

2 0.56, P = 0.46, R adj=0.003, Figure 7). Only mPC1 showed a relationship (positive) with

2 year (F 1,148 = 5.18, P = 0.02, R adj=0.03, Figure 8). I found no changes in bill length, bill width, bill height, tail length, tarsus length, or mPC2 through time. When data for males and females were analyzed separately, again only mPC1 showed change through time

2 and the pattern was more prevalent for males (F 1, 94 = 3.84, P = 0.05, R adj=0.03) than females (F 1, 52 = 1.67, P = 0.20) (Figure 9).

Figure 7. Size corrected Hooded Warbler wing chord by year. 82

Figure 8. Change in wing morphology- represented by log10 and size corrected principal component 1- through time.

Figure 9. Change in wing morphology- represented by log10 transformed and size corrected principal component 1- by sex through time.

Morphological Differences by Age and Sex

I found no differences in bill width, bill height, tail length, or tarsus length by age or sex. ASY females possess longer bills than ASY males (Padj =0.01, Figure 10). SY females possess shorter wings than ASY males (Padj<0.001), and SY males (Padj<0.01,

Figure 11). ASY males exhibit higher mPC1 scores than SY males (Padj<0.001) and SY females (Padj=0.003) and ASY females exhibit higher mPC1 scores than SY males

(Padj=0.02, Figure 12). ASY females exhibit higher mPC2 scores than ASY males

(Padj=0.04), SY males exhibit higher mPC2 scores than ASY males (Padj=0.002) and SY females (Padj=0.006, Figure 13). 84

Figure 10. Total bill length in mm by age and sex. Significant differences indicated by an ‘*’

Figure 11. Wing chord length in mm by age and sex. Significant differences indicated by an ‘*’.

Figure 12. Wing shape represented by mPC1 by age and sex. Significant differences indicated by an ‘*’.

Figure 13. Wing shape represented by mPC2 by age and sex. Significant differences indicated by an ‘*’.

Morphological Variation along a Latitudinal Gradient

I found no relationships between bill height, tail length, or mPC2 and latitude.

SY males show a positive correlation between bill length and latitude (F 1, 26 = 21.9, P =

2 <0.001, R adj=0.44, Figure 14). SY females show a negative correlation between bill

2 width and latitude (F 1, 35 = 7.33, P = 0.01, R adj=0.15, Figure 15). ASY females show a

2 positive correlation between tarsus length and latitude (F 1, 15 = 5.62, P = 0.03, R adj=0.22)

2 as do SY males (F 1, 26 = 4.89, P = 0.04, R adj=0.13) (Figure 16). ASY males show a

2 positive correlation between wing length and latitude (F 1, 66 = 4.84, P = 0.03, R adj=0.05,

Figure 17). For the combined sample of all Hooded Warblers, mPC1 correlates positively

2 with latitude (F 1,148 = 6.01, P = 0.02, R adj=0.03, Figure 18). 88

Figure 14. SY male Hooded Warbler bill length along a latitudinal breeding gradient.

Figure 15. SY female Hooded Warbler bill width along a latitudinal breeding gradient.

Figure 16. SY male and ASY female Hooded Warbler tarsus length along a latitudinal breeding gradient.

Figure 17. ASY male Hooded Warbler museum wing chord length along a latitudinal breeding gradient.

Figure 18. Hooded Warbler wing shape represented by mPC1 wing chord length along a latitudinal breeding gradient.

NMDS and PERMANOVA

The morphological NMDS with two dimensions had a stress of 0.0907. The first

NMDS axis describes a wing shape continuum: axis 1 was positively correlated with proximal primary feather lengths (primaries 1, 2, and 3) and was negatively correlated with the distal primary feather lengths (primaries 6, 7, 8, and 9). The second NMDS axis describes a wing chord length/tail length continuum: axis 2 was positively correlated with wing size (wing chord) and negatively correlated with tail length. (Figure 19). I plotted convex polygons and 95% confidence ellipses to visualize group positions in morphospace (Figure 20). 93

Figure 19. Morphological data ordinated with a non-metric multidimensional scale.

Figure 20. Hooded Warbler specimens plotted in morphospace. Convex polygons and 95% confidence ellipses show position of each population, age, and sex category in 2 dimentional morphospace represented by two non-metric multidimentional scale axes.

I found significant morphological differences among ages, sexes, and populations of Hooded Warblers (PERMANOVA F 7,142 = 16.83, P = 0.001). Results of the

PERMANOVA and population, age and sex positions in morphospace mirror results of univariate ANOVAs and latitudinal relationships described previously, while providing a multivariate assessment of morphological variation among Hooded Warbler groups.

Wing and tail size and shape drive differences in group position in morphospace described by two NMDS axes. We observe a north to south, male to female, and ASY to

SY progression from long narrow wings and short tails (northern ASY males showing the 95 longest wings, shortest tails, and some of the narrowest wings) to short wide wings and long tails (southern SY females showing some of the shortest wings and longest tails and some of the widest wings).

Northern birds (Figure 21): Northern breeding ASY males differed from northern

ASY females (Padj=<0.01), SY females (Padj=<0.01), and SY males (Padj=<0.01).

Northern SY males differed from SY females (Padj=<0.01). Northern ASY females did not significantly differ from northern SY females or SY males. Southern birds (Figure

22): All southern groups differed in morphospace (all Padj=<0.01). Males (Figure 23):

Northern ASY males differed from southern ASY males (Padj=<0.01) and SY males

(Padj=<0.01). Northern SY males differed from southern ASY males (Padj=0.02), but not southern SY males. Females (Figure 24): Southern SY females differed from all other female groups (all Padj=<0.01). SY birds (Figure 25): Northern SY males differed from southern SY males (Padj=<0.01) but not southern SY females. Northern SY females differed from both southern SY males (Padj=<0.01) and southern SY females

(Padj=<0.01). ASY birds (Figure 26): Northern ASY males differed from southern ASY males (Padj=0.01) and southern ASY females (Padj=<0.01). Northern ASY females did not differ from southern ASY birds. 96

Figure 21. Northern Hooded Warbler age and sex classes plotted in two dimensional morphospace.

Figure 22. Southern Hooded Warbler age and sex classes plotted in two dimensional morphospace.

Figure 23. Male Hooded Warbler population and age classes plotted in two dimensional morphospace.

Figure 24. Female Hooded Warbler population and age classes plotted in two dimensional morphospace.

100

Figure 25. SY Hooded Warbler population and sex classes plotted in two dimensional morphospace.

101

Figure 26. ASY Hooded Warbler population and sex classes plotted in two dimensional morphospace.

Discussion

These data demonstrate aspects of Hooded Warbler wing size and shape vary through time, along a breeding latitudinal gradient, and between age and sex classes while most other morphological variables did not. Wing and tail differences are consistent with other intraspecific morphological studies looking at population, age, and sex-specific differences in small migratory passerines (Gaston 1974, Senar et al. 1994,

Copete et al. 1999, Pérez-Tris et al. 2001, Pérez-Tris et al. 2003, Milá et al. 2008).

Interpreting Open Wing Shape from a Folded Dried Wing

Accuracy of open wing shape descriptions derived from closed museum wing data differ by species. Aspects of open wing shape are driven not only by feather lengths, but also musculoskeletal elements (Hieronymus 2015). Manus length is incorporated into 102 museum wing chord measurements, and proportional distances between tips of distal primaries do not change with museum skin preparation in small passerines (Jenni and

Winkler 1989). Secondary feathers to not show such consistency upon wing drying.

Secondary feather length measurements taken on a closed wing are affected by soft tissue contraction during drying. However, Jenni and Winkler (1989) found, in small passerines, differences between museum specimen wing feather lengths and live bird wing feather lengths were smaller than rounding errors. Evered (1990) showed methodological adjustments made while taking secondary feather length measurements result in assessments of wing size and shape comparable to those found in live birds.

I propose the descriptions of wing shape described here serve as acceptable proxies for natural open wing shape in the Hooded Warbler. Hooded Warblers are 1) small passerines, 2) I rounded feather lengths to the nearest .5 mm, 3) I measured secondary feathers from insertion to the feather tip instead of from the wrist to the feather tip, and 4) when I performed principal components on a reduced wing feather dataset limited to primaries 3-9 only, I found loadings on PC1 axis 1 and NMDS axis 2 to still describe a distal wing pointedness/high wing aspect continuum and loadings on PC2 to still describe a wingtip convexity continuum.

Descriptions of Wing Size and Shape

Proportionately long distal primaries and short proximal primaries and secondaries result in a high aspect, pointed wingtip shape in live Hooded Warblers (Per sobs.). Proportionately short primaries 8 and 9, long middle primaries, and short proximal primaries and secondaries correspond to a wing characterized by a rounded convex wing 103 tip in live Hooded Warblers. Thus, I interpret wing mPC1 (and NMDS axis 1) as an index of wing aspect and wingtip pointedness. I interpret wing mPC2 as an index of wingtip concavity. I interpret NMDS axis 2 as a wing and tail length continuum. Hooded

Warblers with high mPC1 scores and low NMDS 1 scores possess a high aspect wing with a pointed wingtip. Hooded Warblers with high mPC2 scores possess a wing with a convex wing tip shape. Hooded Warblers with high NMDS 2 scores possess long wings and short tails.

Morphological Change through Time

I tested whether wing length, wing shape, and other aspects of morphology changed since the 1870s and included age and sex in models. Increasing wing length relative to wing width (increased wing aspect) and wingtip pointedness improve rapid migratory performance. As rapid migration performance improves male fitness (Lozano et al. 1996) in many songbirds, I expected any wing size and shape variation patterns would be most prevalent for male birds. I found no change in wing chord length or any non-wing morphological traits through time. Despite small modern sample sizes, wing aspect and pointedness showed a positive change through time for male warblers. The

Hooded Warbler has shown a northerly shift in breeding distribution over the last 100 years (Jones 1903, Hicks 1937, Bent 1953, Rodewald et al. 2016). Hooded Warblers at the front of the northern expansion may benefit from improved migration flight performance and morphological traits which facilitate efficient long-distance flight may be selected for. 104

Morphological Differences by Age, Sex, and Breeding Location

The Bill

Across populations of Hooded Warblers, ASY females possess longer bills than

ASY males. Female Hooded Warblers may engage in more flush-pursuit foraging behaviors than males (Mumme 2013). Aspects of tail morphology exhibited by females facilitate winged prey capture performance as females flush winged insect prey from the understory. Bill length correlates with bill-closing velocity in birds (Corbin et al. 2014). It is possible morphological traits which facilitate rapid bill closing velocity may improve foraging performance for female Hooded Warblers relative to males. The length of SY male bills increases along a northerly latitudinal gradient. Second year males do not forage differently from ASY males in southeastern Ohio (pers. obs.), however little is known about differences in foraging behavior between age and sex classes of Hooded

Warblers throughout the breeding range. Further study is needed to elucidate any latitudinal, age, and sex-specific ecomorphological patterns associated with bill length in the Hooded Warbler.

Bill width increases with prey size and foraging mode. Aerial insectivores possess short, wide bills (Keast 1972) and often functionally increase gape width further with long bristle-like feathers at the sides of the mouth (rictal bristles). Increased bill width in aerial insectivores facilitates aerial prey capture by directing escaping prey into the mouth. As male Hooded Warblers are thought to perform more aerial prey capture behaviors than females, I expected males would possess wider bills than females, however I found no differences. Second year females show bill narrowing along a 105 northerly latitudinal gradient. Whether southern SY females implement more flycatching foraging behaviors is unknown.

The Hindlimb

Long hindlimbs benefit perch gleaning birds by increasing stride length and increasing stretch length. Increased stride length facilitates more rapid hindlimb-driven locomotor performance allowing birds to explore an area more rapidly. Birds which forage by scanning close, dense foliage benefit from long tarsi which allow the bird to stretch taller; thus permitting the bird to search more area from a single perch (Fitzpatrick

1978) and glean prey from more distant substrates without utilizing more costly wing- powered locomotion behaviors. After second year females and SY males show increasing hindlimb length along a northerly latitudinal gradient. Females would benefit from long tarsi as females forage by flush-chasing prey and leaf and branch glean in close, dense understory habitats. That ASY females show a latitudinal increase in hindlimb length may be the result of subtle wing shape trade-offs between foraging and migration. While

I did not detect a latitudinal change in wing shape for ASY females, northern ASY females show greater variation along NMDS axis 1. Northern females with wing morphologically similar to males likely experience decreased slow maneuvered flight performance and may compensate by relying more heavily on hindlimb locomotion relative to southern females. Because we are unable to age birds accurately past their second year, increased wing shape variation in older northern females may be resolved with long-term banding studies which track annual changes in female wing morphology among birds of known age. 106

Second year males also show a tarsus length increase along a northerly latitudinal gradient. Perhaps SY males implement more branch and leaf gleaning behaviors in northern latitudes and would thus benefit form longer tarsi in the north. Often sit-and- wait avian predators possess short tarsi which improve balance; bringing the bird’s center of gravity closer to the perch. Perhaps differences in avian communities, habitat structure, or foraging differences between northern and southern populations drive the latitudinal increase in hindlimb length for SY males. Young males may not be as able to compete for territories as ASY males. Young males not holding defined territories often sneak copulations with females by lurking in the understory singing quietly while the territory- holding male is singing in the canopy. In more northerly habitats, SY males which can better maneuver the dense understory can better stay hidden and thus exhibit greater fitness. More field study is needed.

The Wing and Tail

In the northern Hooded Warbler population, male birds differ from females along the second NMDS axis with males occupying morphospace characterized by long wings and short tails. Northern SY males differ from northern ASY males along NMDS axis 1 with ASY males showing longer distal primaries and SY males showing longer proximal primaries. In the potential southern population, we see a similar pattern of morphological distinction between males and females along NMDS axis 2. We also see greater morphological differentiation between ASY and SY birds’ morphology along NMDS axis 1; indicating southern SY birds mirror northern SY patterns and possess wings with 107 short distal primary feathers and long proximal primary feathers relative to ASY males and females.

For male Hooded Warblers, from north to south and ASY to SY, we see a progression from long narrow wings and short tails to short wide wings and long tails.

Females to not show the same pattern. Only SY females from the southern population occupy distinct morphospace. Females occupy space characterized by short wide wings and long tails. Southern SY females occupy the most extreme position in this low aspect long tailed region of morphospace. The remaining female groups cluster closer to the males, but still exhibit shorter wider wings and longer tails relative to most male groups.

In SY Hooded Warblers, males and females differ primarily along NMDS axis 2.

SY males possess longer wings and shorter tails than SY females. From north to south,

SY birds differ along NMDS axis 2. Northern SY birds possess higher aspect wings than southern birds. In ASY Hooded Warblers, we see differences along NMDS axis 2. Wing length, wing aspect, wingtip pointedness, and wing convexity differences observed in this study may be driven by differences in the strength of selective pressures imposed by migration (Lozano et al. 1996), foraging (Mumme 2014), and habitat use (Lynch 1985) on males relative to females. However wing aspect and wingtip pointedness seem linked to migration performance as patterns follow a latitudinal gradient and are more pronounced in northern breeding birds than southern breeding birds.

Ecomorphological studies associated with migration often find differences in tail morphology in addition to differences in wing morphology. Tail length seems to be an important morphological trait associated with migration in the Hooded Warbler. During 108 fast flight, drag induced by the body (profile drag) increases. The drag experienced by a biplane with a wing-tail combination is lower than the drag experienced by a biplane with wings alone (Thomas 1996). Thus, the avian tail may serve as an important morphological character which facilitates the efficient, long-range, fast flight of birds.

While migrants with tails may be better suited than migrants without tails, increasing tail length reduces flight efficiency (Norberg 1995) by adding weight and increasing drag.

The long tails of females and short tails of males makes functional sense given females rely more heavily on the tail for foraging performance (Mumme 2014) and males likely migrate more quickly than females as indicated by earlier spring arrival dates.

The patterns of wing and tail variation present in the Hooded Warbler emulate the morphological patterns exhibited by other small, migratory passerines. Further, known differences in behavior and life history among Hooded Warbler age and sex classes generate functional explanations for observed differences in morphology. Descriptions of wing and tail morphology from museum specimens may correlate with broad scale aspects of ecology and behavior. However, isolated external morphological studies cannot incorporate constraints imposed by internal anatomy (Hieronymus 2015), physiology (Segre et al. 2015), behavioral wing shape modification (Lentink 2007), or flight style (Rayner 1985) on migration performance, foraging performance, and predator escape performance in the wild. Subsequent functional morphological studies will improve our understanding of the form-function dynamic and help elucidate the proximate mechanisms driving morphological change. 109

The Audubon Society’s climate report (Langham et al. 2015) indicates the

Hooded Warbler is climate threatened and predicts a 63% loss of breeding habitat availability within the modern species range over the next 65 years. A northern shift in suitable habitat may drive Hooded Warbler populations north. Understanding the morphological variation present across the species’ range and through time will inform conservation decisions concerning the Hooded Warbler and its relatives and improve science’s understanding of morphological responses to ecological change.

110

CHAPTER 4: VARIATION IN WING SHAPE AND FLIGHT PERFORMANCE IN

WILD HOODED WARBLERS (SETOPHAGA CITRINA)

Abstract

Traditional laboratory-acquired performance assessments may fail to capture natural behaviors and thus may skew our understanding of the relationship between morphology and performance in natural systems. Field-collected benchmark performance data are needed. I used linear regression to assess the extent to which variation in field- collected maximum flight velocity can be explained by a combination of wing morphological traits collected from 48 wild Hooded Warblers (Setophaga citrina). These data demonstrate wing shape interacts with wing size and bird mass to predict maximum flight velocity attained during the first 3.0m of escape flight in wild Hooded Warblers.

Individual birds with high aspect wings flew faster than individuals with low aspect wings and individuals with low wing loading flew faster than individuals with high wing loading. Wing shape and wing loading further interact to predict flight speed. At high wing loading values, birds with low aspect wings outperform birds with high aspect wings, while at low wing loading valued, birds with high aspect wings outperform birds with low aspect wings. To my knowledge, this study provides the first quantitative assessment of the relationship between morphology and flight performance in the

Hooded Warbler. Further, this study provides a benchmark data set from wild, untrained individuals against which future, more controlled, captive studies can compare. 111

Introduction

Research in aeronautics and flight biomechanics has shown the surface area, relative length, width, and convexity of an airfoil constrain aerial performance by affecting properties of lift and drag (see Rayner, 1988). Aspects of airfoil shape which increase efficiency in one aspect of aerial performance often come at the cost of another aspect of aerial performance (Ray et al. 2016). For example, high aspect (relatively long and narrow) and pointed airfoils reduce the costs of drag and improve fast flight performance. However, high aspect and pointed airfoils only generate sufficient lift to allow forward flight at high speed making slow, maneuvered flight energetically costly.

Alternately, a low aspect (relatively short and wide) and rounded airfoil generates high lift at low speed which improves slow maneuvered flight performance, however large rounded airfoils generate high induced drag making fast flight energetically costly. Bird wings act as airfoils and the functional relationships between airfoil morphology and flight performance obtained from classical aeronautic and flight biomechanics studies are foundational to understanding functional morphological relationships between flight performance and the avian wing.

Avian wing morphology is influenced by forelimb musculoskeletal morphology

(Calmaestra and Moreno 2000, Hieronymus 2015), flight feather morphology (Swaddle et al. 1999, Swaddle and Lockwood 2003), flight feather condition (Swaddle et al. 1996), and behavior (Parrott 1970, Combes and Daniel 2001, Rosén and Hedenström 2001,

Lentink et al. 2007). Studies conducted at both interspecific (Yong and Moore 1994,

Marchetti et al. 1995) and intraspecific (Senar, Lleonart and Metcalfe, 1994; Gyurácz & 112

Bank, 1995) levels link the interaction between wing shape and flight performance.

Functional morphological studies have revealed how avian wing shape constrains aspects of takeoff performance (Swaddle et al. 1999, Labocha et al. 2015), maximum flight speed

(Swaddle and Lockwood 2003), aerial maneuverability (Swaddle and Lockwood 2003), and flight efficiency (Norberg 1995). In nature, such performance measures translate to predator evasion (Alatalo et al. 1984, Kullberg et.al. 2000; Burns and Ydenberg 2002,

Metcalfe and Ure 1995), resource acquisition (Gustafsson 1988, Rayner 1988, Vágási et al. 2016), dispersal (O’Brien and Dawson 2008, Dawideit et al. 2008), migration

(Buerkle 2000), and reproductive success (Hedenström and Møller 1992, Blomqvist et al.

1997). Thus, avian wing morphology should be under strong selective pressure from numerous, perhaps opposing forces.

When individual populations or age and sex classes interact with distinct ecological features, novel performance traits may be adaptive and any morphological traits which increase performance may drive intraspecific variation in morphology. For example, Alatalo et al. (1984) posited the lower aspect and more rounded wings of juvenile passerines relative to adult passerines improves predator evasion performance in young birds by facilitating greater lift at low speed (more efficient and faster takeoff performance). As young birds mature, the strength of selection for a round wing shape by predators may decrease relative to the strength of selection for a pointed wing by pressures imposed by resource acquisition or reproduction. During spring migration, the first male birds returning to the breeding grounds may better acquire and defend high quality territories than males arriving later (Aebischer et al. 1996) and may be more 113 likely to produce offspring than males arriving later (Lozano et al. 1996). Thus, selection for a fast wing during migration may strengthen with age and may be stronger for males than for females. Further, taxa which rely on greater maternal care of the young may experience selection for efficient take-off or maneuverability in the nesting environment and may explain the more rounded wings of females relative to males. Hypotheses regarding the proximate mechanisms behind ecomorphological correlations, such as early spring arrival to the breeding grounds by males or improved maneuverability in the nesting environment, are informed by tests of functional performance.

Studies linking avian morphology and ecology with performance are crucial to our understanding of the evolution of trait size and shape. Obtaining performance data from small wild birds is challenging because wild birds are highly mobile, difficult to capture (especially multiple times for repeatability assessments) and cannot be fitted with heavy remote tracking devices such as radio transmitters and geolocators. Most functional morphological studies of avian wing shape thus involve captive individuals trained to fly through laboratory wind tunnels or involve the transport of wild individuals to laboratory wind tunnels for performance trials. Thus, flight performance studies are often expensive and time consuming to perform (Hedenström and Lindström 2017).

Wind tunnels are an incredible asset to flight studies, however unintentional effects of captivity, training, transport, and other variables inherently introduced by laboratory conditions which affect body condition, behavior, or otherwise alter flight performance skew our understanding of the relationship between morphology and performance in natural systems. Segre et al. (2015) found maximum velocity and acceleration values 114 exhibited by hummingbirds in flight chambers were lower than velocity and acceleration values exhibited by hummingbirds in the field. Segre and colleagues propose the lower levels of performance in captivity are due to the size of captive enclosures, but such studies highlight the importance of benchmark data obtained from field study (see also

Bäckman et al. 2017). We implemented a portable and inexpensive field flight tunnel design (Figure 27) introduced by Corbin et al. (2015) to explore the relationship between wing morphology and flight performance in a wild population of Hooded Warblers

(Setophaga citrina) as part of a larger study on Hooded Warbler ecology.

Figure 27. Field flight tunnel used to constrain Hooded Warbler flight in the field. Tunnel is an “Institutional I See U” padded 9ft tunnel from Pacific Play Tents Inc. Tunnel model 20408. Dimensions are 274cm x 56cm.

The Hooded Warbler is a migratory, sexually dimorphic New World wood warbler (Family Parulidae), which breeds in mature mesic forests throughout the eastern

United States and southeastern Canada (James 1971). The species over-winters from 115 central Mexico to Panama and the Caribbean islands (Figure 28). Age and sex classes show differences in breeding site arrival dates and in breeding and wintering habitat use.

Males arrive to southern Ohio breeding territories up to two weeks before females

(Personal observation) and young birds (first breeding season) arrive to northwestern

Pennsylvania breeding sites 7-10 days after old birds (at least second breeding season)

(Stutchbury et al. 1997). In both the breeding grounds (although see Williams and Miles

2016) and wintering grounds, Hooded Warblers exhibit sexual habitat segregation (Lynch et al. 1985; Morton 1990). Males prefer open mid-story habitat with vertically-oriented substrate structure whereas females prefer dense understory habitat with an obliquely- oriented substrate structure (Lynch et al. 1985; Morton 1990). Some posit age and sex- specific ecological variation may be a driver of morphological variation in the Hooded

Warbler (Lynch et al. 1985). However, few studies have examined whether the differences in habitat selection between male and female Hooded Warblers are associated with sex-specific variation in morphology and, to my knowledge, none have quantified the relationship between morphology and flight performance for this species. 116

Figure 28. Breeding and wintering distributions of the Hooded Warbler. Figure from Cornell Lab of Ornithology.

Lynch and colleagues (1985) found male Hooded Warblers possess higher aspect wings and were heavier than females and posited these morphological differences may be driven by ecological differences (habitat use). However, the morphological traits used by

Lynch were confined to closed wing chord length from a small sample of birds and the study was not designed to evaluate functional consequences, i.e., flight performance, of wing size and shape. This work on birds breeding in southern Ohio reveals age and sex- 117 specific differences in Hooded Warbler wing shape. Male Hooded Warblers and Female

Hooded Warblers in at least their second breeding season (ASY) possess longer wings

(wing chord) than females in the first breeding season (SY); ASY Hooded Warblers possess wings with a more pointed wingtip shape (long primary feathers 8 and 9 relative to primaries 6 and 7) relative to SY Hooded Warblers; and ASY male Hooded Warblers and SY female Hooded Warblers possess wings with a more convex trailing edge shape

(short primary feathers 1-3 and short secondary feathers relative to the more distal primaries) relative to SY male and ASY female Hooded Warblers (Chapter 3). To my knowledge no previous study has assessed the functional relationship between wing size and shape and flight speed performance in wild Hooded Warblers.

Materials and Methods

Capture, Handling, and Marking

We assessed whether body mass and wing size and shape predicts variation in maximum post take-off flight velocity. The study incorporated individuals captured from a population of Hooded Warblers breeding near the northern limit of the species’ breeding range. During April – July 2015 – 2017 we captured and marked wild adult

Hooded Warblers breeding in three, 20ha sites in SE Ohio; two sites located in Tar

Hollow State Forest (39.33 N 82.77 W) and one site in Zaleski State Forest (39.36 N

82.37 W). We lured adult birds into mist nets with a mounted decoy Hooded Warbler and/or conspecific playback calls. We weighed individuals to the nearest 0.1g using a

Pesola® spring scale; banded individuals with a USGS aluminum band and three plastic color bands for individual identification; and collected morphometric and body condition 118 data. We aged each bird as “second year” (SY – first breeding season) or “after second year” (ASY – at least second breeding season) based on primary covert/greater covert color and rectrix shape (Pyle 1997). We collected approximately 50 µl of blood from a brachial vein to assess hematocrit- a proxy of body condition- and ensured the wound had clotted before we conducted flight performance trials.

Wing Morphology

We measured the right, un-flattened wing chord length (from the carpal joint to the tip of the longest flight feather) to the nearest 0.5mm using a straight wing ruler. As many birds were nesting and we were also monitoring Hooded Warbler breeding ecology in our sites, we chose to forego measuring each primary and secondary feather in the field to reduce handling time (for wing terminology and flight feather numbering, see Figure

29A). Instead, we photographed the fully extended right wing against a white, 5x5mm gridded board (Chai and Dudley 1995). I quantified total wing length, wing area, and each primary and secondary feather’s length from wing photographs using ImageJ (NIH

2016) software. I recorded primary feather lengths as the distance from the carpal joint to each primary feather tip. I recorded secondary feather lengths as the distance from the leading edge of the wing directly radial to the base of each secondary feather to the tip of each secondary feather (Figure 29B). Due to inconsistency in photographs, I was unable to quantify secondaries 4, 5, and 6 consistently and I did not include these proximal secondaries in analyses. 119

A B

Figure 29. Right wing of a prepared Hooded Warbler. A) flight feather names and numbers B) Chord measurements for primaries 5, 7, and 9 (yellow) and secondaries 2 and 4 (blue).

I reduced the effects of body size by subtracting a multivariate (Freeman and

Jackson 1990) proxy of wing size (geometric mean of flight feather lengths) from each log10 transformed morphological measurement (Mosimann 1970; Mosimann and James

1979). I reduced the dimensionality of flight feather data with a principal components analysis on a covariance matrix of size free flight feather values using the princomp function in the ‘stats’ package (R core team 2018) in the statistical program R (R core team 2018). I retained principal component scores which explain >5% of the variation in the data to represent size-free wing shape. A scree plot and an average-eigenvalue test

(Kaiser-Guttman test) confirm the retention of the first two principal components scores 120 for use in subsequent analyses. In addition to wing shape, I calculated wing loading (WL) as

0.5 × 퐵푀 푊퐿 = 푊퐴

where BM = body mass and WA = wing area of the right wing. In addition, I calculated the wing aspect ratio (AR) as

푊퐿2 퐴푅 = 푊퐴

where WL = the extended right wing length, and WA = wing area of the right wing. Both formulae are based on Pennycuick (1978).

Flight Performance

We released each bird through an Institutional See-Thru 9ft Tunnel (Figure 27) from Pacific Play Tents, Inc. to constrain flight path (minimize y and z-axis movements) according to methods outlined in Corbin et al. (2015). Birds were not trained to fly through the tunnel. An individual positioned at one opening of the tunnel held the bird approximately 10cm off the ground and allowed the bird to view the escape path through the tunnel (Corbin et al. 2015). Individual take-off performance is affected by motivation

(Tobalske et al. 2004). We assume the individual releasing each bird elicited predator evasion behavior and motivated all birds to escape as quickly as possible (Berns and

Ydenberg 2002).

(Canon U.S.A Inc.) placed perpendicular to the tunnel and set to record at 30fps (Burns and Ydenberg 2002; Swaddle and Lockwood 2003). We set the camera approximately 121

2m from the tunnel which placed the 2.2m of see-through mesh section of the tunnel in the center of the camera’s viewing area, thus minimizing parallax distortion (Berns and

Ydenberg 2002). Using a known scale in the flight performance video, we digitized position points into metric coordinates frame-by-frame as the bird flew through the flight tunnel and plotted position as a function of time, fitted the data with a curve, and used the fitted curve to calculate the bird's maximum velocity and acceleration. Maximum velocity scores were obtained through internal functions in the Logger Pro® version 3.8.6 software (Vernier Software & Technology, LLC 2018). I did not include data from any bird which landed anywhere in the tunnel or from any bird which ascended or descended more than 10cm. during the flight across the field of view (Swaddle and Lockwood

2003).

We attempted to describe variation in flight performance within and among individuals. Recapture of the same individual was difficult and occurred rarely. Any recaptured bird’s bands were checked, the birds were re-weighed, fat and breeding condition was re-assessed, and the birds were released through the flight tunnel and recorded. If more than 15 days separated capture events, we re-drew blood for hematocrit before the second release. Due to small sample size, we were unable to incorporate presence or absence of a blood draw in describing variation in maximum flight velocity.

Statistical Analyses

I used the R package ‘MVN’ (Selcuk and Korkmaz 2018) to assess multivariate normality and transformed data as necessary. Wing loading increases power requirements for flight and thus constrains flight performance. Because wing load and condition vary 122 throughout the annual cycle in some avian taxa (Lehikoinen 1987, Lindström and

Piersma 1993, Segre et al. 2015), we tested for temporal changes in wing loading throughout the breeding season in our population of Hooded Warblers. I tested the relationship between maximum fight velocity and each morphological trait (wing aspect ratio, wing loading, wing size, and size free wing shape represented by principal component scores 1 and 2) and determined whether Julian date, study site, body condition (hematocrit), and age and sex impacted maximum flight velocity. Aside from extracting maximum flight velocity values from Logger Pro, I conducted all analyses in R

(Version 3.4.1, R core team 2018). I used linear regression in the ‘stats’ package (R core team 2018) to assess the extent to which variation in maximum flight velocity can be explained by a combination of traits. I compared the full model which included each variable and limited interactions to all subsequent models using the ’MuMln’ (Bartoń

2018) and ‘glmulti’ (Calcagno, 2013) packages in R. I chose the best supported model based on AICc.

Results

I collected body condition, wing morphology, and successful flight performance trial data from 48 adult Hooded Warblers during the 2015-2017 breeding seasons; 6 ASY females, 9 ASY males, 13 SY females, and 20 SY males (Table 15).

Table 15. Mean and standard error of each Hooded Warbler morphological, body condition, and performance variable by age and sex. Mass is in grams, hematocrit is percent of whole blood volume comprised of packed erythrocytes, right wing length and the lengths of each flight feather (P9-S3) are in millimeters, and maximum velocity is in meters per second. SY indicates birds in their first breeding season, ASY indicates birds in at least their second breeding season, M indicates male birds and F indicates female birds.

Body Condition

I found no age or sex-specific differences in the Hooded Warbler body condition proxy hematocrit (F 3, 44 = 0.55, P = 0.65, Figure 30). I found no differences in hematocrit among birds breeding in each study sites (F 2, 45 = 1.10, P = 0.34). I found hematocrit did not change throughout the breeding season for any age or sex class (F 7, 40 = 0.64, P =

2 0.72, r adj = -0.06).

Figure 30. Hooded Warbler hematocrit levels by age and sex.

Morphology

I retained the first two size free principal components scores to represent wing shape based on a scree plot. The first two size corrected principal component scores explained

86.3% of the variation in flight feather data. Principal component one explained 69.4% of 125 the variation in the flight feather data and was influenced negatively by the distal-most primary feather lengths and positively by the most proximal feather lengths (Table 16. and Figure 31). Principal component two explained 16.9% of the variation in the flight feather data and was influenced positively by the distal primaries and secondaries and negatively by the proximal primaries (Table 16 and Figure 31).

Table 16. Principal components analysis on size corrected flight feather measurements. Coefficients, standard deviation, and cumulative percent variance explained.

126

Figure 31. Representative Hooded Warbler wings shape as described by principal component scores 1 and 2. A) Hooded Warbler wing that represents a small PC1 score and an intermediate PC2 score. B) Hooded Warbler wing that represents a high PC1 score and a low PC2 score. C) Hooded Warbler wing that represents a high PC1 and a high PC2.

I found no age or sex-specific difference in wing size (F 3, 44 = 1.48, P = 0.23); wing aspect (F 3, 44 = 1.51, P = 0.23); or size free wing shape as portrayed by mPC1 (F 3,

44 = 0.14, P = 0.94) or mPC2 (F 3, 44 = 2.42, P = 0.08). I found a difference in wing loading by age and sex (F 3, 44 = 5.34, P = 0.003) with female Hooded Warblers exhibiting higher wing loading than SY males but not ASY males. SY males had lower wing loading than both SY females (Padj = 0.03) and ASY females (Padj = 0.004, Figure

32). I found no relationships between aspect ratio, mPC1, or mPC2 and covariates body condition, Julian day, or study site (all Padj >0.1). 127

Figure 32. Comparison of wing loading values by age and sex classes. Asterisks indicate differences of P <0.05. SY indicates birds in their first breeding season, ASY indicates birds in at least their second breeding season, M indicates male birds and F indicates female birds.

Flight Performance

I found no differences in maximum flight velocity among individuals among study sites (F2, 45 = 0.57, P = 0.57; Figure 33). In addition, variation in maximum flight

2 velocity was unrelated with Julian date (F1, 46 = 0.07, P = 0.79, r adj = -0.02; Figure 34),

2 hematocrit (F1, 46 = 1.99, P = 0.17, r adj = 0.02; Figure 35), or age (F1, 44 = 1.34, P = 0.25).

I found differences maximum flight velocity between males and females (F1, 44= 5.53, P

= 0.02; Figure 36) with males flying 0.34 (0.05-0.64)m/s faster than females. 128

Figure 33. Maximum flight velocity of birds in the two study areas. TT – Tar Hollow State Forest’s Fire and Fire Surrogacy selectively harvested research plot, TC – Tar Hollow State Forest’s Fire and Fire Surrogacy control research plot, ZT – Zaleski State Forest’s Fire and Fire Surrogacy selectively harvested research plot.

129

Figure 34. Maximum flight velocity of all birds throughout the breeding season.

130

Figure 35. Relationship between maximum flight velocity and body condition represented by hematocrit.

131

Figure 36. Comparison of maximum flight velocity values attained during the first 2.7m of Hooded Warbler escape flight by age and sex. Asterisk symbols indicate differences of P <0.05. SY indicates birds in their first breeding season, ASY indicates birds in at least their second breeding season, M indicates male birds and F indicates female birds.

Covariation between Morphology and Flight Performance

The best fit regression model based on AICc scores (Table 17) predicting maximum flight velocity included mPC1, wing loading, and their interaction. While we found significant differences in maximum flight velocity attained by males and females, sex was not an important term in model selection (Figure 37). Maximum flight velocity correlates with wing shape, wing loading, and their interaction (F3, 44 = 10.64, P < 0.001,

2 r adj = 0.38). Individuals with low mPC1 scores - pointed wingtip shape - flew faster than individuals with high mPC1 scores - rounded wingtip shape - (t = -3.55, P < 0.001, 132

Figure 38) and birds with low wing loading flew faster than individuals with high wing loading (t = -3.23, P = 0.002) (Figure 39). We found a significant interaction between wing loading and shape in explaining maximum flight velocity (t = 3.035, P = 0.004)

(Figure 40).

Table 17. Ten best AICc supported models and the full model. LL= Log Likelihood, AICc= Akaike’s Information Criterion corrected for small sample size, ΔAICc= difference in AICc between model and highest ranked model, w= AIC weight.

Figure 37. Model averaged importance of terms.

135

Figure 38. Maximum flight velocity as a function of wingtip shape as interpreted from principal components ordination of log10-transformed, size corrected flight feather length measurements.

136

Figure 39. Maximum flight velocity as a function of wing loading.

137

Figure 40. Surface plot showing the interaction between Hooded Warbler wing loading and wing shape on flight performance.

Repeatability

Capturing the same individual multiple times was difficult and we were only able to obtain a successful repeated flight tunnel trials for one ASY male which was captured three times in the 2016 breeding season and one SY female which was captured twice during the 2017 breeding season. Maximum flight velocity attained during the ASY male’s first trial (in which a blood sample was taken) was 5.18m/s. Nine days later, we recaptured the bird and immediately released it through the flight tunnel. Maximum flight velocity during this second trial was 5.13m/s. Maximum flight velocity attained during the SY female’s first trial was 5.49m/s. Twenty days later, we recaptured, assessed, drew 138 blood and released the female through the flight tunnel. Maximum flight velocity during the female’s second trial was 5.31m/s.

Discussion

Our data demonstrate wing shape interacts with wing size and bird mass to predict maximum flight velocity attained during the first 3m of escape flight in a wild population of Hooded Warblers. Contrary to expectation, we found few morphological differences among Hooded Warbler age and sex classes and incorporating age and sex class does not improve a multivariate predictive model of maximum flight velocity. Variation in wing morphology in the Hooded Warbler explains variation in maximum flight velocity in a way predicted by aerodynamic theory with increasingly pointed wings seemingly permitting faster flight. High levels of wing loading hinder fast flight as expected, although a rounded, convex wing shape may improve takeoff flight performance at heavy wing loads.

Morphology

Proportionally short distal primaries and long proximal primaries and secondaries results in a rounded wing shape. Proportionally long distal primaries and long secondaries in combination with short proximal primaries results in a concave wing shape. Thus, I interpret mPC1 as an index of wing pointedness/roundedness and mPC2 as an index of wing concavity/convexity; an interpretation consistent with other studies of avian wing morphology (Swaddle and Lockwood 2003; Milá et al. 2008). Hooded

Warblers with low mPC1 scores possess relatively pointed wings and individuals with high scores for mPC1 possess relatively round wings. Hooded Warblers with low mPC2 139 scores possess a convex wing and Hooded Warblers with high mPC2 scores possess a concave wing.

Comparisons of wing shape across all Hooded Warblers captured in our study sites during the 2014-2017 breeding seasons show ASY males exhibit the highest aspect, most pointed, and most concave wings, SY females exhibit the lowest aspect, most rounded, and most convex wings, and SY males and ASY females exhibit intermediate morphologies. Hooded Warblers exhibit the same differences in wing shape by age and sex across the species’ breeding range (see chapter 3). However, we did not detect differences in aspect ratio, wing pointedness, or concavity by age or sex in our sample from southeastern Ohio.

We found female Hooded Warblers exhibit higher wing loading than young males. The difference is due to mass and not wing size and the difference may reflect reproductive condition. Male Hooded Warblers were actively defending territories and caring for young and female Hooded Warblers were laying and incubating eggs and caring for chicks while we conducted this study. While we found no relationship between wing loading and hematocrit by age or sex, low wing loading observed in young male

Hooded Warblers may be due to lower body condition of young males relative to older males. Female Hooded Warblers may have been in various stages of egg production when captured. Increased weight imposed by egg production may have contributed to increased wing loading exhibited by female Hooded Warblers relative to young males.

We assess subcutaneous fat deposits at the furcula and/or axillary regions of each bird based on a standard scale when banding, however this scale was not fine enough to test 140 whether variation in subcutaneous fat score explained variation in wing loading through the breeding season.

Wing Morphology and Flight Performance

Maximum flight velocity attained in the first three meters after takeoff through the field flight tunnel is here considered a proxy of maximum flight velocity possible in the wild. Power needed for forward flight is high at slow speeds gradually reducing as speed increases up to a certain point then it begins to increase again. Thus, rapid acceleration to maximum flight velocity should be expected (Rayner 1988, Tobalske et al. 2003). Birds with proportionately long and pointed wings flew faster than birds with relatively short and rounded wings. Birds with low wing loading flew faster than birds with high wing loading. We did not detect any differences in maximum fight velocity between male and female Hooded Warblers or between SY and ASY Hooded Warblers as expected. While flight performance sample size for this study is large (Segre et al. 2015), the sample was unable to detect known morphological differences among age and sex classes. Female

Hooded Warblers showed larger variance in wing loading and flight speed compared to other groups and lack of statistical differences in maximum flight velocity between age and sex may be due to a small ASY female sample size in addition to variation in wing loading in females due to egg production.

We found wing loading and wing shape interact to explain maximum flight velocity in the Hooded Warbler. Rounded, convex wings generate greater lift than pointed, convex wings and permit greater takeoff burst speed (Alatalo et al. 1984).

Females with developing eggs exhibit some of the highest wing loading scores of the 141 birds in our study and females possess the roundest and most convex wings. Female wing roundness and convexity do not differ from juvenile male and female Hooded Warblers in northern populations (Chapter 3). Perhaps female wing shape is constrained by high wing loading during egg production on the breeding grounds or by any excess fat and protein reserves sometimes carried by migrating female birds; a behavior which has been shown to increased clutch size in some species (Jones and Ward 1976, Klaassen et al.

2017).

We did not assess Flight muscle morphology and physiology, wingbeat frequency, implementation of bounding flight, or behavioral modifications to wing shape in our flight tunnel trials. Forward flight requires thrust provided through power generation by the flight muscles. Flight muscle morphology, muscle fiber type, and metabolic rates affect acceleration and maximum flight velocity by constraining down stroke speed and wingbeat frequency (Segre et al. 2015). Bounding flight is thought to be a behavioral strategy implemented to maximize flight efficiency at a range of loadings experienced during migration (Alerstam et al. 2007). Wing orientation during flight and potential differences in wing flexibility (see Mountcastle and Combes 2013) may also affect flight performance by allowing birds to behaviorally modify airfoil properties during flight. Further studies are needed to determine the contributions of these and other behavioral, morphological, and physiological traits on flight performance.

This study provides the first assessment of flight performance in the Hooded

Warbler and the first intraspecific study to implement the field flight tunnel method designed by Corbin et al. (2015). Captive wind tunnel studies, flight cage studies, and 142 geolocator studies will improve our understanding of fine scale differences in acceleration, wingbeat kinematics, maneuverability, and intra-individual variation in flight performance of the Hooded Warbler. This study supports a form-function relationship in the Hooded Warbler and provides a benchmark data set from wild, untrained individuals against which future captive studies can compare.

143

CONCLUSION

The selective pressures driving avian body shape have been a focus of ornithologists. Studies seeking to elucidate morphological features associated with migration are popular. Wing size and shape-migration distance and tail length and shape- migration distance relationships are popular, especially among the migrant Old World warblers (Passeriformes: Sylviidae, Acrocephalidae, and Phylloscoidae). Among the New

World warblers, however, modern ecomorphological studies are uncommon at the family level. Early work did not find patterns of wing shape change with migration distance in the Parulidae, but lack of pattern in previous work may be due to limited taxonomic, ecological, or morphological sampling; poorly supported phylogenetic relationships; small sample sizes; or a real lack of ecomorphological pattern within the family. I sought to expand the current body of literature regarding Parulid-scale ecomorphological relationships and to explore novel ecomorphological and functional morphological relationships at the family, species, and individual scales by expanding the number of taxa sampled, increasing the number of morphological and ecological traits measured, incorporating modern phylogenetic relationships to correct or non-independence of the datapoints, and using moderate to large sample sizes. This dissertation work will also expand the body of literature describing functional morphological relationships with wild subjects. Broadening the search for ecomorphological patterns, incorporating phylogenetic relationships, and supporting ecomorphological associations with field- collected functional morphological performance data allow for new insights into the poorly understood morphological evolution of a model clade. 144

Despite the generalized nature of this comparative study, warbler species which exhibit similar migration behaviors and utilize breeding habitats with similar structural openness share aspects of wing, tail, and hindlimb shape- thus reinforcing a form- function link in the Parulid system. Findings suggest the selective pressures experienced during migration may drive a fast flight morphology, but also suggest other aspects of ecology may also play a role in shaping flight morphology. Low phylogenetic signal in the wing and tail coupled with high loading of breeding and wintering habitat characteristics in the canonical correlation analysis seem to indicate the foraging environment my also play a role in wing shape evolution in warblers.

Across science, variation within species is often reduced to the averaged traits of a few individuals. These averaged behavioral, ecological, and morphological traits of these averaged individuals may or may not represent the variation that exists within the species.

Functional and ecological morphological patterns can shift depending on age, sex, body condition, molt, the list goes on. Why intraspecific variation is not embraced among morphological study is likely an unfortunate product of the intensive effort required for the necessary field study to quantify the intraspecific variation. Despite extensive sex- specific ecological segregation, age and sexual morphological change, age and sex- specific differences in foraging behavior, broad breeding distribution with localized breeding centers, occupancy of a wide range of habitat types, and localized differences in foraging behavior, the Hooded Warbler is often simply categorized as a monotypic intermediate distance migrant which breeds in canopy gaps of mature forest, and forage by gleaning and hawking. 145

Data from this study indicate morphological differences among age and sex classes and between the more northerly breeding group and the more southern breeding group. This work not only highlights the wealth of ecomorphological and functional morphological information that could be gained by further exploration of the Hooded

Warbler system, but also highlights the caution necessary when making assumptions about the degree of intraspecific variation. Considering morphology alone, the longest

Hooded Warbler wing (an ASY male) measured in this study was almost 130% the length of the shortest (an SY female). Specimen selection is important and most strive to find good representatives for comparative study, but for taxa in which specimen availability is limited, age and sex cannot be controlled for, when research funding only permits specimen sampling from limited localities, or where specimen availability is limited to particularly old or poorly prepared skins, morphological bias can easily introduced.

Further, the interaction between the chosen model specimen’s morphology and the species’ averaged ecology, behavior, performance may skew the patterns derived from such datapoints.

Flight morphology functionally constrains flight performance in a northern breeding population of the Hooded Warbler, a monotypic and broadly distributed member of the Parulidae. Individual birds with longer and more pointed wing shapes can fly faster than birds with proportionally shorter and more rounded wings. While more work is needed, this (previously assumed) functional morphological relationship which forms the basis for the expected wing shape-migration distance ecomorphological pattern in the warblers seems to be affected by bird mass. Such results highlight the importance 146 of quantifying and incorporating intraspecific variation in ecomorphological and functional morphological studies rather than make assumptions. In addition to body mass body condition my prove another factor influencing functional performance in the

Hooded Warbler. Further functional morphological works are needed to improve the power of analyses presented here and to explore other potential sources of individual variation that influence flight performance in Hooded Warblers as well as other members of the warbler clade.

In addition to broadening our understanding of wing shape evolution in the New

World warblers and more generally our understanding of wing shape evolution, these results bring new insight into the study of form-function across different scales. Because the patterns derived from ecological and functional morphological studies form the foundational assumptions for so much ecological, conservation, restoration, behavioral, and evolutionary study, ecomorphologists and functional morphologists must strive to understand the drivers of the patterns seen throughout life. I hope this work will inspire others to incorporate more life history data and functional morphological data into their own research. Doing such will improve the interpretability of any patterns by viewing patterns in a more holistic context and will provide science with more intraspecific form- function data that will continue to strengthen our foundational understanding of evolution by natural selection.

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APPENDIX A

Appendix A. Means and (standard errors) for each morphological measurement; Bill length (BL), bill width (BW), bill height (BD), wing length (WL), primary projection length (PP), tail length (Tail L), and tarsus length (Tars L). All measurements are in millimeters. Species Name Common Name Sex n BL (se) BW (se) BD (se) WL (se) PP (se) Tail L (se) Tars L (se) Basileuterus belli Golden-browed Warbler M 10 13.1 (0.18) 3.3 (0.03) 3.4 (0.08) 56.8 (1.13) 8.4 (0.45) 59.9 (1.19) 21.6 (0.36) F 10 12.9 (0.20) 3.1 (0.05) 3.3 (0.06) 58.4 (0.97) 7.8 (0.34) 59.5 (1.05) 21.2 (0.53) Basileuterus culicivorus Golden-crowned Warbler M 9 14.3 (0.18) 4.1 (0.09) 4.0 (0.10) 62.0 (0.94) 7.7 (0.37) 53.6 (0.87) 21.7 (0.35) F 9 15.0 (0.17) 4.1 (0.04) 4.0 (0.09) 65.3 (1.10) 9.4 (0.46) 55.5 (1.23) 21.4 (0.55) Basileuterus hypoleucus White-bellied Warbler M 4 13.8 (0.28) 4.1 (0.13) 3.8 (0.05) 55.6 (1.56) 8.4 (0.52) 47.8 (0.25) 20.2 (0.80) F 3 13.2 (0.21) 3.7 (0.17) 3.6 (0.19) 53.6 (0.20) 7.6 (0.77) 49.2 (1.33) 17.7 (0.26) Basileuterus lachrymosus Fan-tailed Warbler M 6 14.5 (0.34) 4.1 (0.07) 3.9 (0.06) 58.2 (1.44) 9.2 (0.42) 57.1 (2.68) 20.3 (0.56) F 7 14.9 (0.24) 3.8 (0.11) 4.0 (0.10) 64.0 (0.47) 10.1 (0.66) 62.9 (0.87) 21.7 (0.25) Basileuterus melanogenys Black-cheeked Warbler M 10 15.8 (0.21) 3.9 (0.08) 4.0 (0.11) 67.7 (1.44) 10.9 (0.56) 64.5 (1.15) 21.9 (0.38) F 10 14.8 (0.16) 4.0 (0.06) 3.8 (0.06) 61.9 (0.43) 9.9 (0.53) 61.1 (0.76) 21.2 (0.23) Basileuterus rufifrons Rufous-capped Warbler M 10 13.1 (0.14) 4.0 (0.07) 4.0 (0.04) 66.0 (0.71) 10.7 (0.44) 65.0 (0.86) 21.3 (0.37) F 10 13.1 (0.10) 3.9 (0.09) 3.6 (0.08) 55.4 (0.42) 7.9 (0.49) 46.4 (0.50) 19.3 (0.22) Basileuterus trifasciatus Three-banded Warbler M 1 13.5 4.0 3.6 58.2 9.6 59.4 20.1 F 1 13.4 3.6 3.5 58.5 9.1 58.7 20.4 Basileuterus tristriatus Three-striped Warbler M 10 13.8 (0.31) 3.7 (0.10) 3.6 (0.10) 59.2 (0.64) 7.7 (0.25) 52.8 (1.63) 21.6 (0.43) F 10 14.8 (0.15) 3.9 (0.13) 3.7 (0.07) 63.4 (0.43) 8.2 (0.54) 57.7 (0.76) 22.4 (0.43) Cardellina canadensis Canada Warbler M 9 15.0 (0.19) 3.8 (0.07) 3.7 (0.07) 64.9 (1.55) 9.7 (0.59) 60.3 (1.51) 22.3 (0.50) F 8 13.9 (0.15) 3.9 (0.07) 3.6 (0.11) 57.7 (0.95) 9.1 (0.54) 62.0 (0.70) 20.4 (0.70) Cardellina pusilla Wilson's Warbler M 8 14.7 (0.15) 3.4 (0.06) 3.5 (0.06) 63.5 (0.52) 11.2 (0.57) 65.4 (1.50) 24.1 (0.52) F 7 14.8 (0.17) 3.5 (0.15) 3.7 (0.09) 64.8 (0.99) 12.7 (0.79) 63.0 (2.22) 23.7 (0.76) Cardellina rubra Red Warbler M 8 14.2 (0.16) 3.6 (0.12) 3.6 (0.09) 65.8 (1.25) 8.5 (0.44) 61.5 (1.25) 23.1 (0.51) F 8 13.6 (0.10) 3.7 (0.06) 3.4 (0.06) 58.9 (0.50) 7.7 (0.33) 56.4 (0.92) 22.9 (0.29) Cardellina rubrifrons Red-faced Warbler M 10 13.3 (0.14) 3.6 (0.08) 3.5 (0.05) 61.1 (0.66) 8.1 (0.57) 56.8 (0.82) 23.1 (0.27) F 10 14.4 (0.19) 3.8 (0.08) 3.5 (0.06) 58.6 (1.23) 7.0 (0.62) 55.6 (0.81) 23.5 (0.21) 167

Appendix A cont.

Cardellina versicolor Pink-headed Warbler M 5 14.5 (0.40) 3.9 (0.13) 3.4 (0.10) 61.6 (1.02) 7.9 (0.81) 57.6 (1.32) 23.2 (0.38) F 5 15.0 (0.14) 3.8 (0.08) 3.5 (0.07) 65.5 (1.43) 8.7 (0.50) 57.2 (2.19) 23.6 (1.02) Catharopeza bishopi Whistling Warbler M 2 13.7 (0.80) 3.8 (0.01) 3.5 (0.30) 56.9 (3.95) 7.3 (0.20) 47.9 (3.15) 22.9 (0.60) F 4 14.0 (0.31) 3.9 (0.03) 3.9 (0.15) 59.7 (2.26) 9.0 (1.46) 53.5 (3.2) 21.9 (1.08) Geothlypis aequinoctialis Masked Yellowthroat M 8 13.0 (0.11) 3.9 (0.03) 3.7 (0.08) 56.0 (1.13) 7.0 (0.48) 46.7 (0.84) 21.9 (0.48) F 8 13.4 (0.16) 4.0 (0.05) 3.8 (0.03) 57.2 (0.95) 7.0 (0.69) 50.0 (1.05) 21.3 (0.55) Geothlypis beldingi Belding's Yellowthroat M 3 13.7 (0.25) 3.9 (0.15) 3.7 (0.25) 60.5 (0.88) 7.8 (1.15) 53.9 (2.14) 21.8 (1.25) F 3 14.4 (0.47) 4.1 (0.22) 3.4 (0.12) 59.5 (0.74) 7.4 (0.44) 54.3 (1.01) 23.7 (0.26) Geothlypis flavovelata Altamira Yellowthroat M 1 14.9 4.2 4.1 58.8 7.3 53.6 22.5 F 2 14.1 (0.05) 4.3 (0.10) 3.5 (0.06) 59.6 (0.65) 6.2 (0.25) 55.4 (2.2) 23.5 (0.10) Geothlypis formosa Kentucky Warbler M 9 13.6 (0.15) 3.4 (0.08) 3.6 (0.09) 59.1 (0.82) 7.9 (0.33) 54.9 (1.17) 21.3 (0.55) F 8 13.4 (0.15) 3.7 (0.07) 3.7 (0.06) 61.7 (0.84) 9.0 (0.57) 57.5 (0.76) 20.1 (0.34) Geothlypis nelsoni Hooded Yellowthroat M 1 13.6 3.7 3.3 63.2 8.3 59.4 19.5 F 1 13.5 4 4.1 64.2 8 60.5 20.6 Geothlypis philadelphia Mourning Warbler M 8 13.5 (0.13) 3.6 (0.09) 3.8 (0.10) 65.8 (0.35) 9.8 (0.84) 62.5 (1.31) 20.3 (0.44) F 8 11.9 (0.04) 3.0 (0.05) 3.6 (0.08) 65.4 (0.73) 14.1 (0.65) 65.2 (1.32) 17.1 (0.16) Geothlypis poliocephala Gray-crowned Yellowthroat M 10 12.4 (0.16) 2.9 (0.04) 3.4 (0.06) 68.5 (0.66) 14.5 (0.45) 62.1 (1.23) 17.4 (0.26) F 6 16.4 (0.13) 3.9 (0.11) 4.0 (0.05) 68.3 (2.12) 16.1 (0.67) 57.8 (1.00) 22.4 (0.43) Geothlypis rostrata Bahama Yellowthroat M 4 12.9 (0.21) 3.1 (0.09) 3.0 (0.13) 46.4 (0.51) 8.3 (0.60) 45.6 (1.49) 17.7 (0.64) F 6 11.7 (0.19) 3.0 (0.08) 3.0 (0.08) 47.7 (0.66) 7.3 (0.58) 46.4 (1.16) 17.0 (0.30) Geothlypis semiflava Olive-crowned Yellowthroat M 6 12.8 (0.11) 3.0 (0.07) 3.0 (0.12) 48.8 (0.73) 9.6 (0.66) 49.5 (1.33) 17.0 (0.14) F 7 12.9 (0.24) 3.1 (0.09) 2.8 (0.09) 52.4 (0.70) 8.6 (0.65) 46.4 (1.25) 16.8 (0.57) Geothlypis speciosa Black-polled Yellowthroat M 2 12.8 (0.15) 3.9 (0.01) 3.6 (0.05) 59.3 (0.45) 12.3 (0.45) 46.2 (1.95) 19.2 (0.65) F 4 12.2 (0.16) 3.7 (0.05) 3.0 (0.08) 60.9 (0.53) 14.0 (0.43) 48.1 (1.21) 17.9 (0.23) Geothlypis tolmiei MacGillivray's Warbler M 8 12.6 (0.07) 3.8 (0.07) 3.3 (0.05) 63.4 (0.57) 15.2 (0.38) 47.6 (0.53) 18.6 (0.11) F 8 13.3 (0.22) 3.6 (0.09) 3.4 (0.10) 68.9 (0.79) 19.1 (1.30) 46.8 (0.59) 18.7 (0.29) 168

Appendix A cont.

Geothlypis trichas Common Yellowthroat M 9 13.5 (0.17) 3.4 (0.09) 3.5 (0.06) 72.3 (0.40) 20.2 (0.57) 45.4 (1.44) 18.0 (0.55) F 9 13.4 (0.21) 3.4 (0.06) 3.5 (0.07) 66.7 (2.57) 19.1 (1.16) 43.9 (2.03) 17.9 (0.45) Helmitheros vermivorum Worm-eating Warbler M 8 13.7 (0.20) 3.3 (0.10) 3.7 (0.05) 60.7 (0.33) 12.6 (0.38) 52.9 (1.79) 19.8 (0.38) F 7 13.6 (0.08) 3.3 (0.08) 3.3 (0.07) 66.3 (0.61) 21.0 (0.74) 42.2 (0.75) 16.9 (0.18) Leucopeza semperi Semper's Warbler M 3 13.5 (0.20) 3.2 (0.23) 3.7 (0.03) 63.2 (0.12) 13.0 (0.50) 58.2 (1.11) 18.2 (0.22) F 2 13.7 (0.05) 3.0 (0.20) 3.7 (0.15) 63.5 (0.05) 14.1 (0.75) 58.8 (1.60) 18.1 (0.30) Limnothlypis swainsonii Swainson's Warbler M 5 13.9 (0.22) 3.0 (0.05) 3.6 (0.08) 64.6 (0.28) 14.7 (0.67) 62.6 (0.44) 18.8 (0.42) F 8 12.8 (0.17) 3.0 (0.08) 3.3 (0.06) 68.9 (0.59) 15.9 (0.67) 53.2 (1.15) 18.5 (0.17) Mniotilta varia Black-and-white Warbler M 9 13.0 (0.19) 3.1 (0.07) 3.2 (0.03) 60.2 (0.69) 17.3 (0.41) 54.6 (0.65) 19.2 (0.33) F 11 13.5 (0.08) 3.1 (0.05) 2.9 (0.03) 60.4 (0.71) 10.1 (0.19) 48.4 (0.41) 18.2 (0.21) Myioborus brunniceps Brown-capped Whitestart M 8 12.7 (0.25) 2.6 (0.13) 2.6 (0.06) 52.9 (0.67) 10.2 (0.63) 46.3 (0.79) 18.1 (0.46) F 6 12.2 (0.13) 2.7 (0.15) 2.6 (0.09) 55.4 (0.60) 11.6 (0.58) 45.9 (1.63) 18.9 (0.44) Myioborus cardonai Guaiquinima Whitestart M 1 13.5 3.1 3.2 56.9 10 48.9 19.3 F 1 12.7 2.7 2.8 56.2 10.9 48.8 16.4 Myioborus castaneocapilla Tepui Whitestart M 1 13.1 2.6 2.9 57.8 11 48.4 16.6 F 2 13.9 (0.25) 2.6 (0.15) 2.9 (0.10) 61.7 (1.90) 15.7 (0.30) 49.1 (0.20) 18.1 (0.45) Myioborus flavivertex Yellow-crowned Whitestart M 6 16.6 (0.07) 2.9 (0.11) 3.2 (0.09) 64.2 (0.21) 17.0 (0.41) 50.1 (1.09) 17.2 (0.36) F 8 16.6 (0.13) 3.7 (0.07) 3.4 (0.13) 64.9 (1.04) 19.6 (0.48) 48.5 (1.79) 17.5 (0.20) Myioborus melanocephalus Spectacled Whitestart M 10 12.7 (0.07) 4 (0.04) 3.6 (0.04) 65.2 (0.56) 20.6 (0.59) 46.3 (0.73) 17.6 (0.07) F 7 13.3 (0.12) 3.2 (0.08) 3.1 (0.07) 64.5 (0.88) 16.1 (1.17) 46.3 (0.93) 16.6 (0.18) Myioborus miniatus Slate-throated Whitestart M 8 13.3 (0.12) 2.9 (0.08) 2.9 (0.06) 63.2 (0.40) 15.9 (0.37) 48.0 (0.89) 16.2 (0.15) F 8 14.0 (0.23) 3.2 (0.15) 3.5 (0.17) 67.1 (0.82) 13.6 (0.78) 53.7 (1.27) 17.9 (0.33) Myioborus ornatus Golden-fronted Whitestart M 9 11.8 (0.09) 2.5 (0.09) 2.6 (0.06) 56.6 (0.93) 11.2 (0.30) 49.8 (0.68) 17.8 (0.28) F 7 12.3 (0.11) 2.4 (0.07) 2.7 (0.05) 58.9 (0.74) 12.3 (0.29) 51.0 (0.96) 17.5 (0.32) Myioborus pariae Paria Whitestart M 1 12.1 2.5 2.7 62.5 13.3 54 18.7 F 1 12.6 2.7 2.9 60.6 11.9 51.3 17.8 169

Appendix A cont.

Myioborus pictus Painted Whitestart M 8 13.1 (0.07) 3.1 (0.08) 3.2 (0.10) 58.5 (0.65) 13.1 (0.45) 50.4 (0.95) 17.2 (0.34) F 8 12.6 (0.13) 3.1 (0.10) 3.4 (0.06) 62.5 (0.55) 14.2 (0.46) 50.5 (1.24) 17.7 (0.27) Myioborus torquatus Collared Whitestart M 5 12.9 (0.15) 3.0 (0.07) 3.1 (0.03) 64.5 (0.80) 17.8 (0.46) 47.3 (1.02) 18.6 (0.31) F 6 12.9 (0.10) 3.0 (0.07) 3.2 (0.04) 66.0 (0.41) 18.0 (0.45) 48.0 (0.55) 18.3 (0.22) Myiothlypis bivittata Two-banded Warbler M 9 12.3 (0.09) 4.2 (0.07) 3.6 (0.05) 60.3 (0.37) 15.4 (0.49) 42.2 (1.04) 18.1 (0.26) F 7 12.7 (0.06) 4.0 (0.07) 3.7 (0.08) 63.5 (0.73) 17.3 (0.45) 43.7 (0.94) 18.4 (0.43) Myiothlypis chrysogaster Cuzco Warbler M 6 12.4 (0.11) 3.7 (0.15) 3.5 (0.14) 59.8 (0.46) 14.2 (0.76) 40.1 (0.36) 18.9 (0.43) F 7 12.8 (0.16) 3.7 (0.05) 3.6 (0.09) 61.6 (0.73) 15.8 (0.43) 42.4 (0.42) 18.2 (0.20) Myiothlypis cinereicollis Gray-throated Warbler M 8 13.9 (0.19) 3.0 (0.08) 3.3 (0.08) 61.8 (0.69) 10.5 (0.97) 46.9 (1.92) 19 (0.41) F 9 13.2 (0.11) 4.3 (0.15) 3.8 (0.07) 65.2 (0.61) 18.2 (0.42) 47.8 (0.96) 17.9 (0.35) Myiothlypis conspicillatus White-lored Warbler M 1 13.3 4.2 4.3 66.2 16.9 51.0 18.0 F 1 13.1 4.3 4.5 69.7 16.8 49.0 18.2 Myiothlypis coronata Russet-crowned Warbler M 8 13.2 (0.07) 3.9 (0.07) 3.8 (0.10) 57.9 (0.25) 13.6 (0.56) 50.8 (1.09) 18.1 (0.37) F 10 13.9 (0.19) 3.4 (0.09) 3.2 (0.05) 57.1 (0.74) 12.9 (0.55) 48.6 (0.74) 18.3 (0.57) Myiothlypis flaveola Flavescent Warbler M 10 14.1 (0.12) 3.5 (0.08) 3.3 (0.05) 63.7 (0.69) 13.3 (0.17) 52.4 (0.44) 19.9 (0.25) F 10 13.2 (0.13) 3.0 (0.04) 3.2 (0.06) 71.7 (0.42) 21.8 (0.50) 53.8 (1.61) 18.4 (0.47) Myiothlypis fraseri Gray-and-gold Warbler M 1 12.1 3.2 3.2 69.6 21.5 45.8 18.3 F 2 13.4 (0.30) 3.1 (0.15) 3.3 (0.05) 76.5 (0.60) 23.5 (1.30) 53.0 (1.5) 19.1 (0.40) Myiothlypis fulvicauda Buff-rumped Warbler M 5 13.0 (0.04) 2.9 (0.18) 2.6 (0.09) 62.8 (0.35) 14.4 (0.54) 43.7 (2.39) 18.8 (0.70) F 6 12.4 (0.13) 2.8 (0.05) 2.6 (0.07) 63.7 (0.68) 15.9 (0.99) 42.9 (0.41) 18.2 (0.49) Myiothlypis leucoblephara White-rimmed Warbler M 8 12.7 (0.18) 2.8 (0.17) 2.8 (0.10) 63.7 (0.45) 17.3 (0.56) 50.0 (2.42) 17.6 (0.35) F 8 12.9 (0.13) 2.7 (0.10) 3.0 (0.12) 65.0 (0.75) 17.6 (0.43) 44.7 (1.58) 18.4 (0.48) Myiothlypis luteoviridis Citrine Warbler M 4 12.8 (0.12) 3.3 (0.14) 3.2 (0.23) 62.2 (1.17) 17.1 (0.75) 50.9 (1.75) 18.1 (0.77) F 5 12.6 (0.19) 3.0 (0.11) 3.2 (0.04) 60.8 (2.46) 15.8 (1.19) 47.6 (2.05) 18.1 (0.52) Myiothlypis nigrocristata Black-crested Warbler M 10 12.6 (0.09) 3.1 (0.06) 3.3 (0.03) 60.1 (0.54) 14.5 (0.33) 46.1 (0.47) 17.9 (0.18) F 10 13.8 (0.18) 2.7 (0.06) 3.0 (0.10) 55.2 (1.10) 9.4 (0.47) 50.3 (0.94) 17.5 (0.37) 170

Appendix A cont.

Myiothlypis rivularis River Warbler M 4 13.3 (0.21) 2.4 (0.11) 2.8 (0.17) 57.9 (0.74) 9.0 (1.01) 57.1 (3.18) 17.8 (0.61) F 4 11.8 (0.06) 2.7 (0.24) 2.9 (0.09) 61.1 (1.15) 10.4 (0.20) 59.7 (3.75) 18.3 (0.13) Myiothlypis roraimae Roraiman Warbler M 1 11.0 2.4 2.9 59.6 11.0 61.0 18.4 F 1 11.3 2.3 2.8 59.9 11.3 58.4 18.1 Myiothlypis signata Pale-legged Warbler M 3 11.3 (0.12) 2.4 (0.12) 3 (0.18) 65.8 (1.00) 12.2 (0.49) 66.1 (0.70) 18.5 (0.28) F 7 11.4 (0.09) 2.3 (0.08) 2.9 (0.06) 61.7 (0.53) 12.1 (0.65) 61.4 (0.54) 18.6 (0.24) Oporornis agilis Connecticut Warbler M 6 11.4 (0.04) 3.1 (0.08) 3.2 (0.03) 59.3 (0.64) 10.5 (0.59) 53.5 (0.71) 18.8 (0.15) F 6 11.9 (0.16) 3.1 (0.08) 3.4 (0.09) 65.5 (3.48) 14.6 (2.81) 49.6 (0.91) 19.7 (0.67) Oreothlypis celata Orange-crowned Warbler M 7 12.8 (0.22) 2.8 (0.06) 3.0 (0.05) 59.2 (0.62) 12.6 (0.18) 45.2 (0.66) 18.0 (0.17) F 6 12.7 (0.21) 2.7 (0.07) 3.1 (0.06) 59.2 (0.84) 12.4 (0.66) 45.9 (0.35) 17.8 (0.35) Oreothlypis crissalis Colima Warbler M 3 14.1 (0.39) 2.6 (0.07) 3.1 (0.19) 61.1 (0.33) 10.4 (0.60) 56.4 (2.49) 18.4 (0.26) F 5 14.1 (0.06) 2.8 (0.07) 3.0 (0.15) 63.8 (0.60) 11.8 (0.81) 58.6 (0.87) 18.5 (0.20) Oreothlypis gutturalis Flame-throated Warbler M 9 13.8 (0.22) 2.8 (0.10) 3.3 (0.08) 62.1 (0.86) 13.3 (0.51) 47.2 (1.07) 17.8 (0.29) F 10 14.0 (0.29) 2.7 (0.08) 3.3 (0.09) 64.7 (0.81) 13.6 (0.70) 49.2 (1.02) 17.4 (0.17) Oreothlypis luciae Lucy's Warbler M 7 11.0 (0.11) 2.5 (0.08) 2.8 (0.08) 53.5 (0.59) 11.2 (0.35) 44.7 (1.22) 15.2 (0.20) F 7 11.3 (0.12) 2.6 (0.07) 2.8 (0.03) 55.6 (0.53) 11.4 (0.10) 45.3 (0.91) 16.2 (0.27) Oreothlypis peregrina Tennessee Warbler M 8 12.8 (0.09) 2.7 (0.06) 3.0 (0.04) 62.2 (0.82) 17.4 (0.56) 39.7 (0.53) 16.4 (0.17) F 9 12.4 (0.17) 2.8 (0.04) 3.1 (0.04) 63.9 (0.67) 17.3 (0.51) 40.8 (0.60) 16.3 (0.28) Oreothlypis ruficapilla Nashville Warbler M 7 12.1 (0.10) 2.6 (0.04) 3.0 (0.03) 57.0 (0.71) 12.5 (0.33) 39.6 (0.93) 16.3 (0.22) F 7 12.0 (0.09) 2.7 (0.06) 3.0 (0.05) 59.5 (0.69) 13.5 (0.46) 42.1 (1.04) 16.9 (0.14) Oreothlypis superciliosa Crescent-chested Warbler M 6 13.2 (0.19) 2.9 (0.18) 3.0 (0.17) 58.2 (0.44) 13.4 (0.33) 45.1 (1.26) 15.6 (0.24) F 9 13.0 (0.09) 2.8 (0.12) 3.1 (0.12) 60.4 (1.26) 14.6 (0.62) 48.0 (0.97) 16.5 (0.27) Oreothlypis virginiae Virginia's Warbler M 5 12.6 (0.27) 2.7 (0.06) 2.9 (0.05) 58.2 (0.70) 10.8 (0.60) 45.1 (0.66) 17.1 (0.34) F 8 12.2 (0.12) 2.7 (0.07) 2.9 (0.06) 62.3 (0.32) 12.3 (0.50) 46.6 (0.51) 17.3 (0.20) Parkesia motacilla Louisiana Waterthrush M 9 17.6 (0.15) 3.4 (0.08) 3.9 (0.05) 77.4 (1.19) 21.9 (0.67) 54.0 (1.53) 22.6 (0.27) F 8 17.7 (0.11) 3.4 (0.06) 4.1 (0.05) 80.2 (0.50) 23.6 (0.47) 51.5 (0.97) 22.3 (0.29) 171

Appendix A cont.

Parkesia noveboracensis Northern Waterthrush M 9 15.0 (0.21) 3.9 (0.05) 3.7 (0.08) 70.8 (0.61) 17.8 (0.61) 48.7 (0.28) 21.1 (0.28) F 9 14.9 (0.23) 3.8 (0.09) 3.6 (0.06) 73.0 (0.84) 19.5 (0.80) 49.0 (0.76) 21.2 (0.23) Protonotaria citrea Prothonotary Warbler M 2 16.1 (0.06) 4.0 (0.04) 4.1 (0.15) 68.7 (0.44) 16.6 (1.78) 42.6 (0.58) 19.4 (1.27) F 9 16.3 (0.19) 3.3 (0.07) 3.6 (0.07) 70.1 (0.69) 19.1 (0.72) 46.7 (1.10) 20.0 (0.48) Seiurus aurocapilla Ovenbird M 9 14.3 (0.14) 3.9 (0.09) 4.1 (0.06) 70.5 (0.84) 16.5 (0.48) 46.3 (0.69) 21.3 (0.27) F 8 14.2 (0.16) 4.0 (0.12) 4.0 (0.09) 73.5 (0.34) 18.0 (0.58) 51.4 (0.71) 21.2 (0.20) Setophaga adelaidae Adelaide's Warbler M 10 13.0 (0.18) 3.0 (0.08) 3.0 (0.07) 47.2 (0.48) 7.8 (0.38) 46.1 (0.87) 17.0 (0.44) F 10 12.8 (0.20) 3.0 (0.08) 3.0 (0.07) 49.8 (0.59) 9.6 (0.48) 48.9 (1.02) 16.7 (0.28) Setophaga americana Northern Parula M 8 12.0 (0.16) 2.3 (0.04) 2.5 (0.04) 55.1 (0.69) 13.4 (0.51) 43.5 (0.94) 16.9 (0.21) F 8 12.3 (0.18) 2.4 (0.09) 2.5 (0.06) 60.0 (0.53) 15.2 (0.28) 48.0 (0.54) 16.8 (0.46) Setophaga angelae Elfin-woods Warbler M 1 11.3 2.2 2.6 51.7 8.4 39.6 15.5 F 1 12.1 2.6 2.7 54.2 7.2 43.7 18.2 Setophaga caerulescens Black-throated Blue Warbler M 8 12.4 (0.15) 3.7 (0.14) 3.2 (0.09) 60.2 (0.84) 13.8 (0.42) 47.4 (0.74) 18.5 (0.20) F 9 12.6 (0.06) 3.8 (0.08) 3.3 (0.05) 63.9 (0.63) 15.4 (0.32) 47.7 (0.48) 18.7 (0.09) Setophaga castanea Bay-breasted Warbler M 7 13.6 (0.24) 3.5 (0.08) 3.5 (0.05) 70.1 (0.53) 20.7 (0.44) 46.4 (0.58) 18.7 (0.37) F 8 13.6 (0.16) 3.6 (0.05) 3.6 (0.04) 73.5 (0.62) 21.4 (0.66) 49.4 (0.45) 18.9 (0.27) Setophaga cerulea Cerulean Warbler M 8 13.2 (0.22) 3.3 (0.07) 3.3 (0.06) 61.4 (0.58) 18.0 (1.00) 39.4 (0.49) 16.5 (0.15) F 8 13.5 (0.15) 3.3 (0.07) 3.3 (0.06) 65.6 (0.87) 20.9 (0.65) 41.6 (0.90) 16.9 (0.16) Setophaga chrysoparia Golden-cheeked Warbler M 10 13.7 (0.16) 3.3 (0.08) 3.7 (0.04) 60.7 (0.38) 12.4 (0.32) 51.4 (1.12) 19.5 (0.35) F 10 13.8 (0.17) 3.0 (0.05) 3.6 (0.05) 64.2 (0.30) 14.4 (0.41) 61.3 (0.81) 18.0 (0.35) Setophaga citrina Hooded Warbler M 6 13.4 (0.24) 3.6 (0.11) 3.3 (0.10) 61.5 (0.77) 13.1 (0.40) 54.2 (0.61) 19.4 (0.28) F 12 14.2 (0.09) 3.7 (0.05) 3.5 (0.03) 64.9 (0.63) 14.3 (0.43) 53.6 (0.38) 19.3 (0.10) Setophaga coronata Yellow-rumped Warbler M 7 12.7 (0.09) 3.1 (0.11) 3.2 (0.05) 70.7 (1.15) 16.9 (0.87) 52.8 (0.81) 18.7 (0.18) F 9 12.8 (0.18) 3.1 (0.06) 3.2 (0.03) 72.6 (0.74) 17.0 (0.38) 54.1 (0.72) 19.1 (0.30) Setophaga delicata St. Lucia Warbler M 6 13.6 (0.08) 3.1 (0.06) 2.9 (0.05) 53.7 (0.83) 9.4 (0.52) 48.1 (0.51) 18.3 (0.33) F 7 13.5 (0.10) 3.2 (0.06) 3.0 (0.04) 54.5 (0.93) 9.7 (0.53) 48.0 (0.72) 18.2 (0.19) 172

Appendix A cont.

Setophaga discolor Prairie Warbler M 8 12.5 (0.23) 2.5 (0.10) 2.6 (0.07) 53.7 (0.81) 11.1 (0.58) 46.9 (1.03) 18.5 (0.35) F 8 12.7 (0.23) 2.8 (0.10) 2.7 (0.10) 55.8 (0.53) 11.0 (0.31) 46.2 (1.12) 18.3 (0.51) Setophaga dominica Yellow-throated Warbler M 6 15.4 (0.29) 2.5 (0.08) 3.0 (0.07) 63.2 (0.68) 17.0 (0.72) 49.4 (1.02) 17.2 (0.32) F 6 16.7 (0.13) 2.7 (0.06) 3.3 (0.11) 67.1 (0.90) 18.5 (0.47) 52.4 (0.75) 17.6 (0.34) Setophaga fusca Blackburnian Warbler M 7 12.4 (0.13) 3.8 (0.10) 3.5 (0.12) 63.0 (0.38) 20.8 (0.55) 44.5 (0.46) 17.2 (0.27) F 10 12.8 (0.20) 3.9 (0.09) 3.5 (0.07) 66.6 (0.60) 20.9 (0.17) 46.1 (0.43) 17.5 (0.20) Setophaga graciae Grace's Warbler M 7 13.4 (0.20) 2.7 (0.05) 2.8 (0.03) 62.6 (0.44) 15.5 (0.32) 47.4 (0.49) 16.1 (0.10) F 7 13.3 (0.11) 2.9 (0.08) 2.9 (0.06) 63.8 (0.73) 16.5 (0.56) 48.8 (1.04) 16.1 (0.14) Setophaga kirtlandii Kirtland's Warbler M 3 13.7 (0.38) 3.3 (0.16) 3.4 (0.14) 66.2 (0.68) 12.8 (0.47) 54.3 (1.58) 20.3 (0.48) F 4 14.4 (0.20) 3.4 (0.18) 3.8 (0.22) 68.2 (1.33) 12.0 (0.56) 56.5 (0.78) 21.2 (0.16) Setophaga magnolia Magnolia Warbler M 9 12.1 (0.22) 2.5 (0.06) 2.6 (0.06) 56.2 (0.72) 11.4 (0.35) 49.6 (0.71) 17.6 (0.26) F 8 12.2 (0.14) 2.4 (0.06) 2.7 (0.06) 59.6 (0.82) 12.7 (0.43) 51.5 (0.85) 17.7 (0.32) Setophaga nigrescens Black-throated Gray Warbler M 7 13.1 (0.07) 3.1 (0.09) 3.3 (0.08) 58.3 (0.71) 13.1 (0.52) 49.6 (0.61) 17.1 (0.38) F 7 12.7 (0.18) 3.1 (0.11) 3.4 (0.06) 62.5 (0.66) 13.7 (0.46) 52.3 (1.23) 17.6 (0.29) Setophaga occidentalis Hermit Warbler M 7 12.7 (0.18) 3.0 (0.06) 3.1 (0.03) 63.3 (0.67) 17.5 (0.64) 46.6 (0.42) 18.3 (0.28) F 7 12.8 (0.15) 3.0 (0.08) 3.2 (0.05) 66.7 (0.56) 17.8 (0.44) 49.0 (0.71) 18.6 (0.10) Setophaga palmarum Palm Warbler M 6 13.7 (0.16) 2.6 (0.09) 2.9 (0.11) 61.4 (0.79) 10.6 (0.91) 51.3 (0.80) 19.5 (0.29) F 6 13.2 (0.05) 2.4 (0.06) 2.9 (0.07) 64.5 (0.70) 12.0 (0.80) 52.9 (0.61) 19.0 (0.31) Setophaga pensylvanica Chestnut-sided Warbler M 8 12.2 (0.06) 4.3 (0.05) 3.6 (0.06) 59.6 (0.33) 15.3 (0.55) 41.4 (0.62) 17.9 (0.27) F 8 12.7 (0.09) 4.0 (0.06) 3.7 (0.06) 63.4 (0.48) 17.0 (0.49) 44.9 (1.20) 18.6 (0.28) Setophaga petechia Yellow Warbler M 7 12.4 (0.17) 3.8 (0.10) 3.6 (0.13) 59.8 (0.39) 14.4 (0.69) 40.2 (0.31) 18.0 (0.19) F 10 13.4 (0.23) 3.6 (0.06) 3.5 (0.08) 62.0 (0.55) 15.9 (0.44) 41.9 (0.51) 18.3 (0.22) Setophaga pharetra Arrowhead Warbler M 4 13.9 (0.27) 3.1 (0.12) 3.4 (0.12) 62.0 (0.20) 9.3 (0.38) 50.5 (0.90) 19.2 (0.64) F 3 13.8 (0.38) 3.1 (0.09) 3.4 (0.09) 60.4 (2.02) 9.0 (1.11) 51.2 (1.47) 19.9 (0.15) Setophaga pinus Pine Warbler M 8 13.3 (0.11) 4.5 (0.06) 3.9 (0.07) 65.4 (0.68) 18.3 (0.55) 47.0 (0.67) 17.6 (0.21) F 8 13.1 (0.09) 4.0 (0.06) 4.0 (0.09) 70.6 (0.25) 18.1 (0.55) 50.9 (0.98) 18.3 (0.27) 173

Appendix A. cont.

Setophaga pitiayumi Tropical Parula M 9 12.2 (0.18) 2.3 (0.07) 2.6 (0.08) 51.8 (0.70) 10.9 (0.61) 41.4 (0.80) 16.9 (0.34) F 9 12.1 (0.13) 2.2 (0.05) 2.6 (0.08) 53.7 (0.56) 10.8 (0.43) 42.8 (0.46) 17.1 (0.33) Setophaga pityophila Olive-capped Warbler M 3 13.5 (0.17) 2.7 (0.03) 2.9 (0.03) 57.1 (0.41) 13.3 (0.55) 50.1 (1.53) 17.5 (0.60) F 6 13.8 (0.07) 2.9 (0.06) 2.9 (0.06) 57.5 (0.80) 14.0 (0.58) 47.3 (0.76) 17.0 (0.12) Setophaga plumbea Plumbeous Warbler M 6 14.3 (0.20) 3.5 (0.11) 3.4 (0.07) 59.1 (1.52) 12.0 (0.40) 51.3 (0.84) 20.4 (0.37) F 6 14.1 (0.17) 3.5 (0.09) 3.3 (0.06) 63.2 (0.64) 13.2 (0.21) 52.5 (0.53) 20.0 (0.20) Setophaga ruticilla American Redstart M 8 12.0 (0.11) 4.2 (0.09) 3.2 (0.10) 61.0 (0.72) 14.9 (0.67) 52.0 (0.73) 16.9 (0.24) F 9 12.1 (0.11) 4.4 (0.07) 3.2 (0.07) 63.7 (0.59) 16.8 (0.23) 54.6 (0.92) 18.2 (0.23) Setophaga striata Blackpoll Warbler M 7 13.3 (0.24) 3.1 (0.07) 3.2 (0.07) 70.0 (0.82) 20.8 (0.41) 50.9 (0.50) 18.4 (0.51) F 9 13.5 (0.17) 3.0 (0.08) 3.3 (0.07) 74.1 (1.00) 23.2 (0.37) 53.3 (1.13) 18.7 (0.36) Setophaga tigrina Cape May Warbler M 10 12.7 (0.13) 2.8 (0.06) 2.6 (0.06) 63.3 (0.46) 15.6 (0.57) 42.3 (0.44) 18.2 (0.35) F 9 12.5 (0.21) 2.5 (0.11) 2.7 (0.09) 65.5 (0.29) 17.5 (0.49) 42.9 (0.72) 17.9 (0.51) Setophaga townsendi Townsend's Warbler M 6 12.8 (0.23) 3.0 (0.12) 3.2 (0.09) 62.7 (0.48) 17.3 (0.37) 51.4 (0.95) 18.7 (0.32) F 6 12.9 (0.16) 3.2 (0.10) 3.2 (0.05) 64.2 (0.86) 18.2 (0.54) 54.4 (1.64) 18.2 (0.38) Setophaga virens Black-throated Green Warbler M 6 12.6 (0.18) 3.1 (0.06) 3.3 (0.04) 57.9 (0.96) 14.8 (0.34) 45.5 (0.72) 17.5 (0.40) F 9 12.6 (0.13) 3.1 (0.06) 3.3 (0.04) 60.4 (0.63) 15.2 (0.52) 45.6 (0.52) 17.8 (0.18) Setophaga vitellina Vitelline Warbler M 6 13.7 (0.23) 2.7 (0.06) 2.8 (0.05) 53.2 (1.08) 9.5 (0.36) 50.0 (1.13) 16.9 (0.38) F 6 14.2 (0.30) 2.6 (0.07) 3.0 (0.12) 57.3 (0.82) 10.0 (0.66) 51.5 (0.85) 18.2 (0.38) Vermivora bachmanii Bachman's Warbler M 4 13.0 (0.21) 2.8 (0.05) 3.2 (0.04) 56.4 (0.35) 12.1 (0.54) 40.9 (0.54) 16.8 (0.12) F 4 13.5 (0.20) 2.9 (0.08) 3.2 (0.04) 61.7 (0.51) 14.7 (0.26) 43.9 (1.05) 16.7 (0.18) Vermivora chrysoptera Golden-winged Warbler M 9 14.0 (0.18) 3.0 (0.05) 3.4 (0.06) 59.3 (0.25) 15.0 (0.55) 43.4 (0.52) 16.9 (0.23) F 9 14.0 (0.14) 3.1 (0.06) 3.3 (0.06) 62.9 (0.57) 16.7 (0.59) 46.6 (0.47) 17.3 (0.10) Vermivora cyanoptera Blue-winged Warbler M 7 13.5 (0.26) 3.1 (0.09) 3.4 (0.08) 56.8 (0.82) 13.1 (0.29) 42.8 (0.58) 16.9 (0.28) F 9 13.2 (0.13) 3.0 (0.05) 3.3 (0.05) 60.0 (0.52) 14.6 (0.45) 44.1 (0.72) 17.0 (0.27)

174

APPENDIX B

Appendix B. Ecological data for each warbler species used. Migration distances are distance between the species’ average wintering latitude and each specimen’s captured latitude. Distances are in kiloimeters. Average sample migration Species Name Common Name distance (km) Habitat Foraging Height General Habitat Openness Basileuterus belli Golden-browed Warbler 0 Mixed Forest Understory Closed Basileuterus culicivorus Golden-crowned Warbler 0 Hardwood Forests, Edges and Gaps Understory through Midstory Open Basileuterus hypoleucus White-bellied Warbler 0 Thickets, Edges, Gaps, and Hardwood Forests Understory Open Basileuterus lachrymosus Fan-tailed Warbler 0 Hardwood Forests, Edges and Gaps Ground and Understory Open Basileuterus melanogenys Black-cheeked Warbler 0 Hardwood Forest Understory Closed Basileuterus rufifrons Rufous-capped Warbler 0 Thickets and Softwood Forests Understory Open Basileuterus trifasciatus Three-banded Warbler 0 Thickets, Edges, Gaps, and Hardwood Forests Understory through Midstory Open Basileuterus tristriatus Three-striped Warbler 0 Hardwood Forests, Edges and Gaps Understory Closed Cardellina canadensis Canada Warbler 4580 Thickets and Hardwood Forests Understory through Midstory Closed Cardellina pusilla Wilson's Warbler 1676 Fields, Gaps, Thickets, Mixed Forest Understory through Midstory Open Cardellina rubra Red Warbler 0 Mixed Forest Understory through Midstory Open Cardellina rubrifrons Red-faced Warbler 1899 Thickets and Mixed Forests Midstory Open Cardellina versicolor Pink-headed Warbler 0 Softwood Forest, Edges, and Gaps Understory Open Catharopeza bishopi Whistling Warbler 0 Hardwood Forests, Edges and Gaps Understory through Midstory Closed Geothlypis aequinoctialis Masked Yellowthroat 0 Fields, Gaps, Thickets, Mixed Forest Ground and Understory Open Geothlypis beldingi Belding's Yellowthroat 0 Grasslands and Brushy Fields Understory Open Geothlypis flavovelata Altamira Yellowthroat 0 Grasslands and Brushy Fields Understory Open Geothlypis formosa Kentucky Warbler 2681 Hardwood Forest Ground and Understory Closed Geothlypis nelsoni Hooded Yellowthroat 0 Thickets and Softwood Forests Understory Closed Geothlypis philadelphia Mourning Warbler 3686 Thickets, Edges, Gaps, and Hardwood Forests Ground and Understory Open Geothlypis poliocephala Gray-crowned Yellowthroat 0 Fields, Gaps, Thickets, Mixed Forest Ground and Understory Open

175

Appendix B cont.

Geothlypis rostrata Bahama Yellowthroat 0 Thickets and Softwood Forests Understory Closed Geothlypis semiflava Olive-crowned Yellowthroat 0 Brushy Fields, Edges, and Gaps Understory Open Geothlypis speciosa Black-polled Yellowthroat 0 Grasslands and Brushy Fields Understory Open Geothlypis tolmiei MacGillivray's Warbler 2681 Thickets, Edges, Gaps, and Hardwood Forests Understory Open Geothlypis trichas Common Yellowthroat 2457 Fields, Gaps, Thickets, Hardwood Forest Understory Open Helmitheros vermivorum Worm-eating Warbler 2904 Hardwood Forest Understory through Midstory Closed Leucopeza semperi Semper's Warbler 0 Hardwood Forest Ground and Understory Closed Limnothlypis swainsonii Swainson's Warbler 782 Thickets, Edges, Gaps, and Hardwood Forests Ground Closed Mniotilta varia Black-and-white Warbler 3016 Thickets and Hardwood Forests Understory through Canopy Closed Myioborus brunniceps Brown-capped Whitestart 0 Hardwood Forest Understory through Midstory Closed Myioborus cardonei Guaiquinima Whitestart 0 Hardwood Forests, Edges and Gaps Understory through Midstory Open Myioborus castaneocapilla Tepui Whitestart 0 Hardwood Forests, Edges and Gaps Understory through Midstory Open Myioborus flavivertex Yellow-crowned Whitestart 0 Thickets, Edges, Gaps, and Hardwood Forests Midstory through Canopy Closed Myioborus melanocephalus Spectacled Whitestart 0 Thickets, Edges, Gaps, and Hardwood Forests Understory through Canopy Closed Myioborus miniatus Slate-throated Whitestart 0 Mixed Forest Midstory through Canopy Closed Myioborus ornatus Golden-fronted Whitestart 0 Hardwood Forests, Edges and Gaps Midstory through Canopy Open Myioborus pariae Paria Whitestart 0 Hardwood Forests, Edges and Gaps Understory through Midstory Open Myioborus pictus Painted Whitestart 1340 Mixed Forest Understory Closed Myioborus torquatus Collared Whitestart 0 Fields, Gaps, Thickets, Hardwood Forest Understory through Canopy Open Myiothlypis bivittata Two-banded Warbler 0 Hardwood Forests, Edges and Gaps Understory Closed Myiothlypis chrysogaster Cuzco Warbler 0 Hardwood Forest Midstory through Canopy Closed Myiothlypis cinereicollis Gray-throated Warbler 0 Hardwood Forests, Edges and Gaps Understory Closed Myiothlypis conspicillatus White-lored Warbler 0 Hardwood Forests, Edges and Gaps Understory through Midstory Closed Myiothlypis coronata Russet-crowned Warbler 0 Hardwood Forests, Edges and Gaps Understory through Midstory Closed Myiothlypis flaveola Flavescent Warbler 0 Thickets, Edges, Gaps, and Hardwood Forests Ground and Understory Open Myiothlypis fraseri Gray-and-gold Warbler 0 Mixed Forest Understory through Midstory Closed 176

Appendix B cont.

Myiothlypis fulvicauda Buff-rumped Warbler 0 Hardwood Forest Ground Open Myiothlypis leucoblephara White-rimmed Warbler 0 Hardwood Forests, Edges and Gaps Ground and Understory Closed Myiothlypis luteoviridis Citrine Warbler 0 Thickets, Edges, Gaps, and Hardwood Forests Understory through Midstory Closed Myiothlypis nigrocristata Black-crested Warbler 0 Thickets, Edges, Gaps, and Hardwood Forests Understory Open Myiothlypis rivularis River Warbler 0 Hardwood Forest Ground Open Myiothlypis roraimae Roraiman Warbler 0 Hardwood Forest Midstory through Canopy Closed Myiothlypis signata Pale-legged Warbler 0 Hardwood Forests, Edges and Gaps Ground and Understory Closed Oporornis agilis Connecticut Warbler 5362 Fields, Gaps, Thickets, Mixed Forest Ground Open Oreothlypis celata Orange-crowned Warbler 1564 Thickets, Edges, Gaps, and Hardwood Forests Understory through Canopy Open Oreothlypis crissalis Colima Warbler 670 Mixed Forest Understory Closed Oreothlypis gutturalis Flame-throated Warbler 0 Thickets, Edges, Gaps, and Hardwood Forests Midstory through Canopy Open Oreothlypis luciae Lucy's Warbler 1340 Fields, Gaps, Thickets, Mixed Forest Understory through Midstory Open Oreothlypis peregrina Tennessee Warbler 4133 Thickets, Edges, Gaps, and Mixed Forests Canopy Open Oreothlypis ruficapilla Nashville Warbler 2234 Thickets, Edges, Gaps, and Hardwood Forests Understory through Midstory Open Oreothlypis superciliosa Crescent-chested Warbler 0 Mixed Forest Midstory through Canopy Open Oreothlypis virginiae Virginia's Warbler 1899 Thickets and Mixed Forests Understory Open Parkesia motacilla Louisiana Waterthrush 3128 Hardwood Forests, Edges and Gaps Ground Open Parkesia noveboracensis Northern Waterthrush 4133 Fields, Gaps, Thickets, Hardwood Forest Ground Open Protonotaria citrea Prothonotary Warbler 3016 Hardwood Forest Ground and Understory Closed Seiurus aurocapilla Ovenbird 3016 Hardwood Forest Ground Closed Setophaga adelaidae Adelaide's Warbler 0 Thickets, Edges, Gaps, and Hardwood Forests Canopy Open Setophaga americana Northern Parula 2346 Mixed Forest Canopy Closed Setophaga angelae Elfin-woods Warbler 0 Hardwood Forest Canopy Closed Setophaga caerulescens Black-throated Blue Warbler 3016 Thickets and Hardwood Forests Understory through Midstory Closed Setophaga castanea Bay-breasted Warbler 3574 Thickets, Edges, Gaps, and Softwood Forests Midstory through Canopy Open Setophaga cerulea Cerulean Warbler 4356 Hardwood Forest Canopy Open 177

Appendix B cont.

Setophaga chrysoparia Golden-cheeked Warbler 1720 Mixed Forest Midstory through Canopy Closed Setophaga citrina Hooded Warbler 2011 Hardwood Forests, Edges and Gaps Understory through Midstory Closed Setophaga coronata Yellow-rumped Warbler 2681 Mixed Forest Midstory through Canopy Open Setophaga delicata St. Lucia Warbler 0 Thickets, Edges, Gaps, and Hardwood Forests Understory through Midstory Closed Setophaga discolor Prairie Warbler 2011 Fields, Gaps, Thickets, Softwood Forest Ground through Midstory Open Setophaga dominica Yellow-throated Warbler 1787 Mixed Forest, Edges and Gaps Canopy Open Setophaga fusca Blackburnian Warbler 5362 Softwood Forest Canopy Open Setophaga graciae Grace's Warbler 1564 Softwood Forest Canopy Closed Setophaga kirtlandii Kirtland's Warbler 2457 Thickets and Mixed Forests Ground through Midstory Closed Setophaga magnolia Magnolia Warbler 2904 Thickets, Edges, Gaps, and Softwood Forests Understory through Midstory Closed Setophaga nigrescens Black-throated Gray Warbler 2681 Thickets and Mixed Forests Understory Open Setophaga occidentalis Hermit Warbler 1787 Softwood Forest Canopy Closed Setophaga palmarum Palm Warbler 2569 Fields, Gaps, Thickets, Mixed Forest Ground Open Setophaga pensylvanica Chestnut-sided Warbler 2904 Thickets, Edges, Gaps, and Hardwood Forests Understory through Midstory Open Setophaga petechia Yellow Warbler 3910 Thickets, Edges, Gaps, and Hardwood Forests Understory through Midstory Open Setophaga pharetra Arrowhead Warbler 0 Hardwood Forest Understory through Canopy Closed Setophaga pinus Pine Warbler 1340 Softwood Forest Ground, midstory, canopy Open Setophaga pitiayumi Tropical Parula 0 Thickets, Edges, Gaps, and Hardwood Forests Canopy Closed Setophaga pityophila Olive-capped Warbler 0 Softwood Forest Canopy Open Setophaga plumbea Plumbeous Warbler 0 Thickets and Hardwood Forests Understory Open Setophaga ruticilla American Redstart 3574 Thickets and Hardwood Forests Midstory through Canopy Open Setophaga striata Blackpoll Warbler 5362 Softwood Forest Midstory through Canopy Open Setophaga tigrina Cape May Warbler 3574 Thickets, Edges, Gaps, and Softwood Forests Canopy Open Setophaga townsendi Townsend's Warbler 2569 Softwood Forest Canopy Closed Setophaga virens Black-throated Green Warbler 1787 Thickets, Edges, Gaps, and Mixed Forests Midstory through Canopy Open Setophaga vitellina Vitelline Warbler 0 Thickets, Edges, Gaps, and Hardwood Forests Understory through Midstory Closed 178

Appendix B cont.

Vermivora bachmanii Bachman's Warbler 670 Hardwood Forest Canopy Closed Vermivora chrysoptera Golden-winged Warbler 3351 Brushy Fields, Edges, and Gaps Understory through Midstory Open Vermivora cyanoptera Blue-winged Warbler 3128 Thickets and Softwood Forests Midstory Open

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