Movement Ecology and Stopover Duration of Northern Waterthrush and Yellow-rumped Warbler during Spring Migration along the Upper Mississippi River

Thesis

Presented in Partial Fulfillment of the Requirements for the Degree Master of Science in the Graduate School of The Ohio State University

By

David L. Slager, B.S.

Environment and Natural Resources Graduate Program

The Ohio State University

2011

Thesis Committee:

Dr. Paul G. Rodewald, Advisor

Dr. Robert J. Gates

Dr. Amanda D. Rodewald Copyright by

David L. Slager

2011 Abstract

Because distances traveled by Nearctic-Neotropical migratory songbirds are too great to cover in a single flight, birds must stop-over to rest and refuel along the way.

Migrant birds spend the majority of their time and energy at stopover sites, highlighting the importance of stopover to a successful migration. Since migrant songbirds stop-over at locations not previously encountered, their efficiency in exploring and exploiting unfamiliar locations should influence their rate of fat deposition. The decision of when to depart from a stopover site is central to maintaining a successful migratory schedule because early arrival on the breeding grounds is known to confer reproductive advantages to migratory songbirds. However, little is known about which intrinsic and extrinsic factors influence movement patterns and departure decisions of migratory birds during stopover.

My research objectives were to (1) describe the movement patterns of migrants during stopover, (2) determine the minimum stopover duration of migrants, (3) assess the influences of habitat, sex, energetic condition, and time of year on movements and stopover duration, and (4) examine relationships between weather conditions and the probability of migratory departure.

I examined fine-scale movement patterns and stopover duration of 43 Northern

Waterthrushes (Parkesia noveboracensis) and 30 "Myrtle" Yellow-rumped Warblers

(Setophaga coronata coronata) during migratory stopover at Trempealeau National

ii Wildlife Refuge in western Wisconsin during April-May of 2009 and 2010. I experimentally translocated and radio-tracked birds to investigate how migrants adjust movement patterns and stopover duration upon encountering unfamiliar environments.

To determine movement patterns of migrants during stopover, I radio-located birds every

30 min on the day of release and the day after release. I calculated daily movement rate

(m/hr) by dividing the total distance moved by the total time radio-tracked, daily displacement by taking the straight-line distance between the first point of the day (or release point) and the bird's location at 20:00, and daily linearity by dividing linear displacement by the total distance moved.

Yellow-rumped Warblers occupied a variety of habitats and moved at a rate of 157

± 54 m/hr (mean ± sd), showing no differences in movement metrics between the first and second days after release. An information theoretic approach using Akaike's

Information Criterion (AICc) revealed that ordinal date, energetic condition, sex, release point, and year explained no more variation in daily movement metrics for day 1 and day

2 than a null model. Energetic condition at capture and daily measures of movement rate, displacement, and linearity showed no change over the migratory period. Yellow-rumped

Warblers did not show a pronounced period of exploration followed by settling, a result contrasting with most studies of songbird movements during stopover. One possible explanation is that these generalist warblers find a wide variety of stopover habitats to be suitable, reducing the benefits of locating a particular habitat via exploration.

By contrast, Northern Waterthrushes moved at a median rate of 89 m/hr on day 1 and 64 m/hr on day 2, showing strong decreases in movement rate (43%), displacement

iii (71%), and linearity (55%) over the 2 days following release, a pattern consistent with exploration followed by settling. Waterthrushes released in upland forest habitat almost invariably moved to wetter habitats within a few hours of release. Most individual waterthrushes, regardless of release habitat, were fairly sedentary after the day of release.

Models best supported by Akaike's Information Criterion (AICc) revealed prominent differences in determinants of movement on day 1 and day 2. Waterthrushes released in upland forest habitat, at a later ordinal date, and in higher energetic condition had higher movement rates on day 1. In contrast, females and birds tracked in 2009 had higher movement rates on day 2. Northern Waterthrushes released in upland forest habitat and at later ordinal dates exhibited greater displacement on day 1; birds tracked in 2009 showed greater displacement on day 2. Birds released in upland forest habitat had increased linearity on day 1, whereas males and birds tracked in 2009 showed increased linearity on day 2. The fact that waterthrushes released in less suitable upland forest habitat showed movement characteristics on day 1 consistent with greater exploration than birds released in more suitable bottomland forest habitat suggests exploration as a method by which migrants locate suitable stopover microsites when encountering unfamiliar areas. Although waterthrushes with higher fat stores had higher movement rates on day 1, movements on day 2 were independent of energetic condition, suggesting that lean and fat birds explore habitat differently but converge on similar movement patterns after settling. A possible explanation for increased daily movement rates and displacement later in the spring is that urgency to arrive on the breeding grounds forces more rapid exploration. The fact that female waterthrushes had higher movement rates

iv and lower linearity than males on day 2 despite no inter-sexual differences in movements on day 1 is difficult to explain, but suggests males and females have a similar approach to initial exploration of habitat yet differ in movement patterns following settlement.

To investigate minimum stopover duration, I radio-located each bird at least once per day until departure. If a radio frequency was not detected for 7 days, I assumed the bird had departed on migration on the night of the last detection. Models best supported by Akaike's Information Criterion (AICc) indicated that Yellow-rumped Warblers with lower fat stores and those captured later in the season had longer stopover durations. The best-supported models for Northern Waterthrush showed that females released earlier in the season, in 2010, in bottomland forest habitat, and with lower fat stores had a longer minimum stopover duration. The negative relationship between energetic condition and stopover duration for both species studied matches the pattern emerging from other studies. Declining stopover duration over the season in Northern Waterthrushes is consistent with the idea that the primary constraints facing birds shift from energy to time as arrival timing on the breeding grounds becomes more urgent later in the spring. The tendency for Yellow-rumped Warblers to show shorter stopover durations earlier in the spring is more difficult to explain and underscores that spring migration is not a homogeneous period with regard to stopover decisions. Male Northern Waterthrushes had shorter stopover durations than females even after controlling for the earlier arrival dates of males, which may be explained in part by the need of males to arrive on the breeding grounds early to establish territories prior to the arrival of females.

Surprisingly, waterthrushes released in less suitable upland forest habitat had shorter

v stopover durations than those released in more suitable bottomland forest, despite the fact that all birds eventually settled in wet habitats. Most studies of songbirds indicate limited daily displacement of migrants at stopover sites, so it is possible that where a migrant makes landfall ultimately determines the extent of stopover resources available, due to an upper bound to exploratory movements.

To examine how weather conditions predicted the probability of migratory departure, I used Random Forests (an extension of classification trees) to determine how a suite of nightly weather variables predicted migrants' departure decisions after controlling for time of season. The Random Forests model predicted the highest probability of Yellow-rumped Warbler departure on nights with decreasing barometric pressure and a more easterly wind component. The model predicted Northern

Waterthrush departure on nights with a higher temperatures and more easterly winds.

After controlling for time of year, I found that departure in both species is predicted by conditions associated with passing warm fronts. My work suggests that energetic condition and date determine the duration of stopover whereas favorable weather conditions fine-tune the precise date of departure.

Overall, my results show that a diverse suite of factors including habitat, condition, sex, year, date, and weather mediates the movement patterns and stopover duration of migrants. I found that birds, especially in the case of Northern Waterthrushes, explore limited areas during stopover and that habitat and energetic condition may strongly influence stopover duration. Understanding inter-specific differences in stopover biology is an essential part of any holistic conservation strategy for migrants.

vi The fact that events during stopover can influence arrival timing and reproductive success on the breeding grounds highlights the importance of conserving high-quality stopover habitats for migratory birds.

vii Dedication

Dedicated to Emily

viii Acknowledgments

First of all, I need to thank my advisor, Paul Rodewald, for the opportunity and support to make this project possible. I also thank my committee members, Amanda

Rodewald and Bob Gates, for improving my research by offering critical comments and advice at many stages of the process.

This work was funded by a U.S. Fish and Wildlife Service Region 3 Challenge

Cost Share Grant, a University Fellowship from the Graduate School at The Ohio State

University, an Environmental Fellowship from the College of Food, Agriculture, and

Environmental Sciences at The Ohio State University, a Director's Associateship from the

Ohio Agricultural Research and Development Center, and a small grant from the

Wisconsin Society for Ornithology. I thank the American Ornithologists' Union, the

Wilson Ornithological Society, and the School of Environment and Natural Resources at

The Ohio State University for providing travel awards for attending scientific meetings.

I thank my field assistants Laura Jenkins, Jay Jordan, Adrienne Levoy, Will

Lewis, Frankie Nebenburgh, Gar Secrist, Ryan Trimbath, Julie Webber, and Darcie

Westerman for working long days and enduring ticks, mosquitoes, mud, weather, and contingency while maintaining a good sense of humor and a great work ethic. I thank

Patricia Heglund of the U.S. Fish and Wildlife Service for her strong support in developing and implementing the research project. I thank Upper Midwest

Environmental Sciences Center, Trempealeau National Wildlife Refuge, and Upper

ix Mississippi River National Wildlife Refuge for providing field vehicles, camping trailers, and other equipment. Kathy Bibby, Patricia Heglund, Steve Houdek, Melissa Meier,

Jennifer Sauer, and others showed unprecedented Wisconsin hospitality to me and my field crew. Among many other things, they helped with field work, logistics, plane flights, vehicles, campers, equipment, and supplies and allowed me to use their banding site. I am grateful to Vickie Hirschboeck and Trempealeau National Wildlife Refuge for granting access to refuge lands for study sites and refuge headquarters for office tasks. I also thank all but one adjacent landowner for kindly granting access to private property adjacent to the refuge. I wish to thank Joel Vonhaden, Hungry Point Bar and Grill, and the rest of the Trempealeau community for hosting me and my field crew at the Mulberry

Meadows River and Lakes RV Resort.

I thank the entire Rodewald lab group for friendship, support, and thoughtful suggestions for my research. I thank Dr. Steve Matthews and Matt Shumar for statistical advice. I thank Paul and Amanda for cultivating a positive atmosphere in the lab through weekly lab meetings and frequent get-togethers at their home. I also thank the administrators in the School of Environment and Natural Resources, particularly Olivia

Ameredes, Mary Capoccia, India Fuller, Dennis Hull, and Amy Schmidt for ensuring that my research, travels, purchase orders, and graduate program ran smoothly.

I am grateful to my parents for their acceptance and support of my ornithological pursuits over the years. And finally, I thank Emily for being the most loving and supportive spouse imaginable.

x Vita

Education

2005...... B.S., Biology, Biochemistry, Calvin College

Professional Experience

September 2008 - present...... Graduate Fellow and Research Associate,

The Ohio State University

June 2008 - July 2008...... Field Biologist, Ohio Breeding Bird Atlas II

April 2008 - May 2008...... Field Biologist, The Ohio State University

September 2006 - June 2007...... Teaching Assistant, University of Utah

May 2006 - July 2006...... Field Biologist,

Michigan Breeding Bird Atlas II

May 2005 - July 2005...... Field Biologist, University of Michigan

June 2004 - August 2004...... NSF Undergraduate Research Fellow,

University of Utah

May 2003 - July 2003...... NSF Undergraduate Research Fellow,

Mount Desert Island Biological Laboratory

May 2002 - July 2002...... Field Biologist, Michigan State University

xi Publications

Slager, D. L. 2011. Rufous-naped Greenlet (Hylophilus semibrunneus), Neotropical Birds

Online (T. S. Schulenberg, Editor). Ithaca: Cornell Lab of Ornithology.

http://neotropical.birds.cornell.edu/portal/species/overview?p_p_spp=512236

Bush, S. E., Harbison, C. W., Slager, D. L., Peterson, A. T., Price, R. D., and D. H.

Clayton. 2009. Geographic Variation in the Community Structure of Lice on

Western Scrub-Jays. Journal of Parasitology 95: 10-13.

Preston, R. L., Clifford, R. J., Thompson, J. A., Slager, D. L., Petersen, C. W., and G. W.

Kidder. 2004. CFTR mRNA expression in developing Fundulus heteroclitus

embryos. Bulletin of the Mount Desert Island Biological Laboratory 43: 25-27.

Field of Study

Major Field: Environment and Natural Resources

xii Table of Contents

Abstract...... ii

Dedication...... viii

Acknowledgments...... ix

Vita...... xi

List of Tables...... xv

List of Figures...... xvii

Chapter 1: Introduction...... 1

1.1. Introduction...... 1 1.2. Importance of the Migratory Period...... 2 1.3. Selection of Stopover Habitat...... 4 1.4. Energetics and Migratory Stopover...... 7 1.5. Predation...... 8 1.6. Competition...... 9 1.7. Stopover Duration...... 9 1.8. Study Area...... 10 1.9. Focal Species...... 11 1.10. References...... 12

Chapter 2: Habitat-dependent exploratory behavior and stopover duration in Northern Waterthrush (Parkesia noveboracensis): A translocation experiment during spring migration...... 18

2.1. Introduction...... 18 2.2. Methods...... 21 2.3. Results...... 30 2.4. Discussion...... 33 2.5. References...... 38

xiii Chapter 3: Movement ecology and stopover duration of the Yellow-rumped Warbler (Setophaga coronata) during spring migration...... 57

3.1. Introduction...... 57 3.2. Methods...... 60 3.3. Results...... 68 3.4. Discussion...... 71 3.5. References...... 74

Bibliography...... 92

Appendix A: Additional Information...... 102

xiv List of Tables

Table 2.1. Modeling the influence of ordinal date, energetic condition, sex, release point habitat, and year on day 1 movement rates of Northern Waterthrushes ...... 45

Table 2.2. Modeling the influence of ordinal date, energetic condition, sex, release point habitat, and year on day 2 movement rates of Northern Waterthrushes ...... 46

Table 2.3. Modeling the influence of ordinal date, energetic condition, sex, release point habitat, and year on day 1 displacement of Northern Waterthrushes ...... 47

Table 2.4. Modeling the influence of ordinal date, energetic condition, sex, release point habitat, and year on day 2 displacement of Northern Waterthrushes ...... 48

Table 2.5. Modeling the influence of ordinal date, energetic condition, sex, release point habitat, and year on day 1 linearity of Northern Waterthrushes...49

Table 2.6. Modeling the influence of ordinal date, energetic condition, sex, release point habitat, and year on day 2 linearity of Northern Waterthrushes...50

Table 2.7. Modeling the influence of ordinal date, energetic condition, sex, release point habitat, and year on minimum stopover duration of Northern Waterthrushes ...... 51

Table 2.8. Variable importance in the Random Forests model of departure probability for Northern Waterthrushes...... 52

Table 3.1. Modeling the influence of ordinal date, energetic condition, sex, release point, and year on day 1 movement rates of Yellow-rumped Warblers..80

Table 3.2. Modeling the influence of ordinal date, energetic condition, sex, release point, and year on day 2 movement rates of Yellow-rumped Warblers...81

xv Table 3.3. Modeling the influence of ordinal date, energetic condition, sex, release point, and year on day 1 displacement of Yellow-rumped Warblers...... 82

Table 3.4. Modeling the influence of ordinal date, energetic condition, sex, release point, and year on day 2 displacement of Yellow-rumped Warblers...... 83

Table 3.5. Modeling the influence of ordinal date, energetic condition, sex, release point, and year on day 1 linearity of Yellow-rumped Warblers...... 84

Table 3.6. Modeling the influence of ordinal date, energetic condition, sex, release point, and year on day 2 linearity of Yellow-rumped Warblers...... 85

Table 3.7. Modeling the influence of ordinal date, energetic condition, sex, release point, and year on minimum stopover duration of Yellow-rumped Warblers ...... 86

Table 3.8. Variable importance in the Random Forests model of departure probability for Yellow-rumped Warbler...... 87

Table A.1. Individual Northern Waterthrush data...... 103

Table A.2. Individual Yellow-rumped Warbler data...... 104

xvi List of Figures

Figure 2.1. Map showing location of Trempealeau National Wildlife Refuge ...... 53

Figure 2.2. Landcover and land use at Trempealeau National Wildlife Refuge in 1994 ...... 54

Figure 2.3. Northern Waterthrush capture locations and release sites at Trempealeau National Wildlife Refuge...... 55

Figure 2.4. Partial plots showing how the top three weather variables indicated by the Random Forests model predicted the probability of departure in Northern Waterthrushes...... 56

Figure 3.1. Map showing location of Trempealeau National Wildlife Refuge ...... 88

Figure 3.2. Landcover and land use at Trempealeau National Wildlife Refuge in 1994 ...... 89

Figure 3.3. Yellow-rumped Warbler capture locations and release sites at Trempealeau National Wildlife Refuge...... 90

Figure 3.4. Partial plots showing how the top three weather variables indicated by the Random Forests model predicted the probability of departure in Yellow- rumped Warblers...... 91

xvii Chapter 1: Introduction

1.1. Introduction

Hundreds of species of Nearctic-Neotropical migratory birds (hereafter

Neotropical migrants) depart tropical wintering areas each spring to breed in temperate and boreal areas of the United States and Canada (DeGraaf and Rappole 1995). This distance is too great to cover in a single flight for most migrants, and consequently birds must seek stopover habitat suitable for refueling, resting, and avoiding predation (Moore et al. 1995). Migrant landbirds typically stop-over in unfamiliar locations (Catry et al.

2004) and may not always find themselves in suitable stopover habitat. A bird's ability to efficiently exploit novel locations will, in part, determine the rate at which it replenishes energy reserves, its stopover duration, and its timing of arrival on the breeding grounds.

Upon making landfall at a stopover site, birds must balance the costs of habitat exploration with the benefits of finding more suitable stopover habitat (Jenni and Schaub

2003). Research on the movement patterns of migrant landbirds at stopover sites is relatively recent (Aborn and Moore 1997), and additional research is still badly needed to illuminate patterns and processes. Exploratory behavior is likely to be influenced by species-specific differences in ecology, such as the degree to which a species is a habitat specialist or generalist during stopover. Temporal and spatial patterns of exploratory

1 behavior during stopover are also likely to depend on sex and energetic condition of individuals as well as habitat availability and time of season (Paxton et al. 2008,

Seewagen et al. 2010). Since the magnitude of exploratory movements may be a proxy for the ability of a migratory bird to adapt to human-modified landscapes during stopover, patterns of exploratory movements will need to be better understood for successful acquisition and management of habitat for migrants en route (Buler et al.

2007).

My research examined the stopover ecology of two species of long-distance migrant wood warblers along the Upper Mississippi River in Wisconsin. I monitored fine-scale movement patterns and stopover duration of 43 Northern Waterthrushes

(Parkesia noveboracensis) and 30 "Myrtle" Yellow-rumped Warblers (Setophaga coronata coronata) during migratory stopover at Trempealeau National Wildlife Refuge during April-May of 2009-2010. I experimentally translocated and radio-tracked birds to investigate how migrants adjust movement patterns and stopover duration upon encountering unfamiliar environments. In addition, I examined how ordinal date, energetic condition, and sex might constrain movements and stopover duration, and how weather variables predicted the date of departure.

1.2. Importance of the Migratory Period

Populations of many Neotropical migrants have been declining for several decades (Robbins et al. 1989, Sauer and Link 2011). The primary hypotheses to explain

2 population declines have focused on events occurring on either breeding or wintering grounds, while migration has been relatively understudied (Hutto 2000, Mehlman et al.

2005). Nonetheless, events during the migratory period can contribute to population declines through direct mortality or via carry-over effects. The epic nature of intercontinental migration poses many hazards to migrant passerines during flight and may lead to extensive direct mortality. An estimated 85% of annual mortality in adult

Black-throated Blue Warblers is thought to occur during the migratory period (Sillett and

Holmes 2002). Among many potential causes of direct mortality during migration, poor weather during a migratory flight can disorient and ground an individual bird in inhospitable habitat. Headwinds or storms over water crossings may lead to exhaustion and drowning. Birds may collide with artificial structures such as communication towers, windows, wind turbines, or tall buildings (Veltri and Klem 2005, Drewitt and Langston

2008). Migrants also succumb to predation in the unfamiliar environments and novel predator landscapes at stopover sites (Cimprich et al. 2005, Ydenberg et al. 2007).

Birds that avoid direct mortality during migration and reach their ultimate destination may still need to cope with carry-over effects, i.e. non-lethal events in one season that influence fitness in a subsequent season (Norris and Taylor 2006, Harrison et al. 2011). In migratory birds, the currencies of carry-over effects can include arrival time or energetic condition, and may ultimately lower survival and/or reproduction during the following season (Newton 2004, Norris 2005). Several studies have documented carry- over effects in Neotropical migrant passerines. American Redstarts (Setophaga ruticilla) wintering in higher quality habitats maintained their body mass through the winter,

3 initiated spring migration earlier, and had a higher return rate the next winter compared to birds wintering in lower quality habitats (Marra et al. 1998, Studds and Marra 2005).

Migrating Black-throated Blue Warblers captured in the Bahamas that had previously wintered in higher quality habitats were in higher energetic condition than conspecifics that had wintered in lower quality habitats (Bearhop et al. 2004).

Events during spring migration can influence subsequent reproductive output on the breeding grounds through mechanisms such as arrival timing and body condition.

American Redstarts arriving on the breeding grounds with high fat loads had higher reproductive success than birds arriving in leaner condition (Smith and Moore 2003), whereas early-arriving redstarts had higher reproductive success than those arriving later

(Smith and Moore 2005). Northern Wheatears (Oenanthe oenanthe) that arrived earlier on the breeding grounds in Wales were more likely to pair successfully (Currie et al.

2000). American Redstarts occupying low-quality winter habitat were in poorer physical condition, departed wintering grounds later, and arrived on breeding grounds later and in poorer breeding condition than individuals that wintered in high-quality habitat (Marra et al. 1998).

1.3. Selection of Stopover Habitat

Long-distance migratory birds are highly mobile and can potentially select among a broad range of habitats. Research on stopover habitat associations of landbird migrants began several decades ago (Parnell 1969), yet the topic remains under-studied. Habitat

4 selection begins at the end of a nocturnal migratory flight for a typical migrant passerine.

Descending from cruising altitude during fair-weather nocturnal migration, an individual migrant selects a stopover site, followed by exploration and then settling (Chernetsov

2006). During landfall, visual cues and conspecific and heterospecific acoustic cues influence stopover site selection (Mukhin et al. 2008).

Several studies have reported that the highest density and diversity of migrant passerines occur in structurally heterogeneous woodlands such as mature edge-dominated forest (Rodewald and Brittingham 2002, 2004, 2007) and shrub-scrub (Moore et al.

1990). Food availability may be partially responsible for this pattern, as variety of studies have found greater arthropod abundance along forest edges (Bedford and Usher

1994, Jokimaki et al. 1998). Migrant abundance was positively associated with arthropod abundance across a variety of habitats in southeast Arizona (Hutto 1985). Moore et al.

(1995) provide a review of studies demonstrating correlations between food availability and migrant abundance.

Recent evidence suggests landscape effects are associated with migrant abundance and refueling rates, but little information is available. Migrant densities on the Gulf

Coast were correlated with amount of forest cover within 5 km (Buler et al. 2007).

Hourly mass gains in Willow Warblers (Phylloscopus trochilus) and European Redstarts

(Phoenicurus phoenicurus) were positively associated with percent forest cover within 5 km and 3 km, respectively (Ktitorov et al. 2008).

Migrants may find themselves in unsuitable stopover habitat for a variety of reasons including encountering bad weather (Moore and Kerlinger 1987), running out of

5 energy during a migratory flight, or making landfall in highly modified or fragmented stopover habitat. Migrants possess behavioral responses to make adjustments when they find themselves in unsuitable stopover habitat, but the nature of these behaviors and the scale of these adjustments are only recently coming to light.

Several recent studies suggest that birds explore locally upon landfall and then settle on a suitable stopover microsite (Aborn and Moore 2004, Chernetsov and Mukhin

2006). In parulid warblers, stopover movement patterns consistent with exploration followed by settling were also observed in Wilson’s Warblers in Arizona (Paxton et al.

2008) and Ovenbirds in New York (Seewagen et al. 2010). Summer Tanagers (Piranga rubra) newly arrived on the Gulf Coast after trans-gulf migration showed movements with higher linearity and lower turn bias than birds that had been present for more than 1 day, indicating initial exploratory behavior followed by more localized foraging (Aborn and Moore 1997). A similar pattern was observed in European Robins (Erithacus rubecula) in Russia (Chernetsov and Mukhin 2006).

It is not known whether migrants always explore a stopover area upon landfall, or whether they only explore when they find themselves in unsuitable habitat.

Understanding how migrants adjust their movements and refine their stopover location is critical to assessing how to conserve mosaics of stopover habitat suitable for migrants in fragmented and human-modified landscapes. The maximum distance a migrant explores upon making landfall at an unfamiliar stopover site can potentially serve as a recommendation to land managers for the minimum distance between suitable stopover habitats. Thus, the scale of migrants’ exploratory movements during stopover, in part,

6 can indicate the appropriate scale of stopover habitat patches to conserve and how much patch connectivity is required (Buler et al. 2007).

1.4. Energetics and Migratory Stopover

Migratory birds must maintain energy stores throughout migration and stay on schedule to increase the likelihood of survival and/or successful reproduction in subsequent seasons (Moore et al. 1995). During migration, songbirds spend their time either at a stopover location or flying between stopover locations. Migratory flight is the more energetically expensive activity per unit time, but over the course of the migratory period, up to 71% of a bird’s total energy use occurs during stopover (Wikelski et al.

2003), highlighting the central importance of quality stopover sites to successful migration.

Once a migrant locates stopover habitat, it must replenish fat stores lost during the previous night’s migratory flight. The rate of mass gain during stopover can vary dramatically among individuals, with several studies demonstrating relationships with age and sex. For example, Wilson’s Warblers (Cardellina pusilla) in New Mexico exhibited considerable variation in mass gain between sexes during spring migration and between age classes during fall migration (Yong et al. 1998). Males arrived earlier in spring, carried higher fat stores, and departed earlier than females. In fall, hatch-year birds tended to occupy suboptimal habitats, have lower fat stores and lower rates of mass gain, and remain at a stopover site longer than adults (Yong et al. 1998).

7 1.5. Predation

Avoiding predators at unfamiliar stopover sites is a major challenge for migrants because they are unfamiliar with local predator landscapes (Ydenberg et al. 2007).

Predation can be a major source of direct mortality during migration. In Sweden, an estimated 10% of a finch population (Fringilla spp.) succumbed to predation during a 45- day fall migration period, which represents a higher mortality rate than would be expected if mortality was uniformly distributed throughout the annual cycle (Lindström

1989). The physiological constraint of fuel storage may further add to the danger of predation during stopover. For example, when Blackcaps (Sylvia atricapilla) with high fat loads were exposed to artificial predators, their takeoff angle and velocity were lower relative to lean birds (Kullberg et al. 1996).

A tradeoff likely exists between predator avoidance and foraging. For example, migrant Blue-gray Gnatcatchers (Polioptila caerulea) and American Redstarts along the

Gulf Coast foraged deeper in foliage on days with more Sharp-shinned Hawks (Accipiter striatus) passing overhead (Cimprich et al. 2005). Moreover, Blue-gray Gnatcatchers had lower rates of movement and foraging after exposure to a Sharp-shinned Hawk model

(Cimprich et al. 2005). As further evidence for predation avoidance, migrant Bramblings

(Fringilla montifringilla) in Sweden chose stopover habitat with a lower ratio of predation to foraging success, even when foraging success was lower (Lindström 1990).

8 1.6. Competition

Migrant birds can compete for limited resources with conspecific or heterospecific birds at stopover sites. Evidence for intra-specific competition for food resources during stopover has been found in Goldcrests (Regulus regulus) in Sweden (Hansson and

Pettersson 1989), Wilson’s Warblers (Cardellina pusilla) in New Mexico (Kelly et al.

2002), and several species of passerine migrants along the Gulf of Mexico (Moore and

Yong 1991). Inter-specific competition among passerines has also been reported from a stopover site in the Sahara Desert (Salewski et al. 2007).

1.7. Stopover Duration

Migrant birds repeatedly face the tradeoff between remaining at a stopover site and departing to resume their migration. Migrants may take refueling rate into account when navigating this tradeoff. As evidence for this, fall migrant songbirds in Europe and

North Africa that gained body mass at a medium rate remained at a stopover site longer than migrants that either lost body mass or gained mass rapidly (Schaub et al. 2008).

Stopover duration in Old World warblers (Sylviidae) was negatively associated with both prey availability and rate of mass gain (Schaub and Jenni 2001). Several factors can influence rate of mass gain, including age, sex, competition, predation, and disturbance

(Newton 2006). As evidence for age affecting stopover duration, hatch-year Wilson’s

Warblers during fall migration in New Mexico had a longer mean stopover duration than

9 adults (Yong et al. 1998).

Weather can influence the date of departure from a stopover location independently of other factors (Matthews and Rodewald 2010). In Sweden, for example, night of departure during fall migration was positively correlated with a tail-wind

(Åkesson and Hedenström 2000). Small birds seldom initiate migratory flights in bad weather.

1.8. Study Area

Trempealeau National Wildlife Refuge (NWR) in western Wisconsin encompasses

2520 ha within the Upper Mississippi River alluvial valley. The refuge includes portions of Trempealeau and Buffalo counties, which have generally rolling terrain and are 25% and 43% forested, respectively (U.S. Fish and Wildlife Service 2008). The Mississippi

River valley is 4 to 9 km wide near the refuge. On the Minnesota side, steep forested bluffs abut the river. On the Wisconsin side, agricultural land (formerly the Trempealeau

Prairie), extends between the river and the bluffs for several kilometers. Trempealeau

NWR supports a heterogeneous mosaic of open aquatic habitats, emergent marshes, islands, shrub wetlands, and bottomland hardwood forest. Pockets of oak savanna, well- drained forests, and tall-grass prairie occur on sandy soil in the slightly higher elevations.

Overall, the refuge exhibits much variation in types of hydrology, stages of succession, and hardness of habitat edges. Forest cover on the refuge typically does not form discrete patches and is fragmented by natural habitat gradients, past agriculture, recent prairie

10 restorations, and natural and impounded bodies of water. The bluff faces flanking the alluvial valley support well-drained forest and steep prairie plant communities. The rolling upland hills of the Driftless area support a marbled mosaic of agriculture on flatter hilltops and valleys and well-drained forests on steeper terrain. Land use in the area surrounding Trempealeau NWR is primarily low-density residential and agricultural

(U.S. Fish and Wildlife Service 2008).

1.9. Focal Species

The Northern Waterthrush and Yellow-rumped Warbler were selected as the primary focal species for this study. Both species are common migrants in the study area and are readily captured by passive mist-netting. The species vary notably in their ecology during stopover: Northern Waterthrushes are habitat specialists and more sedentary during stopover, whereas Yellow-rumped Warblers are habitat generalists and more mobile.

The Northern Waterthrush breeds in Alaska, Canada, and the northern United

States and winters from northern Mexico and the West Indies to northern South America.

Northern Waterthrush is a common spring migrant in my western Wisconsin study area but does not breed or winter (Robbins 1991). Northern Waterthrushes inhabit dense understory near water, such as willow (Salix spp.), alder (Alnus spp.), and Rhododendron thickets during the breeding season (Eaton 1995). On the Neotropical wintering grounds it occurs in mangroves, gallery forest, and other mesic forest habitats (Eaton 1995).

11 During spring migratory stopover, the Northern Waterthrush has strong associations with habitats containing thick understory and wet substrate (Parnell 1969, Rappole and Warner

1976, Winker et al. 1992), often foraging on or near the ground near water and dense vegetation, where it consumes small arthropods (Eaton 1995). Intraspecific territoriality in Northern Waterthrush has been observed during spring migratory stopover in Texas

(Rappole and Warner 1976), and aggressive intraspecific chases into vegetation have been noted during morning flight in fall migration in New Jersey (Wiedner et al. 1992).

The Yellow-rumped “Myrtle” Warbler breeds in the boreal forests of Alaska,

Canada and the northern United States and winters from the southeastern United States through Mexico, Central America, and the West Indies (Hunt and Flaspohler 1998). In my western Wisconsin study area it occurs commonly as a migrant but does not breed and only rarely winters (Robbins 1991). The Yellow-rumped Warbler breeds in mature coniferous and mixed boreal forests, and during winter it occurs in a wide variety of habitats (Hunt and Flaspohler 1998). The species is also a habitat generalist during spring migration (Parnell 1969). During fall and winter, the Yellow-rumped Warbler is at least partially frugivorous, but during spring and summer it consumes mostly insects and other small invertebrates (Hunt and Flaspohler 1998).

1.10. References

Aborn, D. A., and F. R. Moore. 1997. Pattern of movement by Summer Tanagers (Piranga rubra) during migratory stopover: A telemetry study. Behaviour 134:1077-1100.

12 Aborn, D. A., and F. R. Moore. 2004. Activity budgets of Summer Tanagers during spring migratory stopover. The Wilson Bulletin 116:64-68.

Åkesson, S., and A. Hedenström. 2000. Wind selectivity of migratory flight departures in birds. Behavioral Ecology and Sociobiology 47:0140-0144.

Bearhop, S., G. M. Hilton, S. C. Votier, and S. Waldron. 2004. Stable isotope ratios indicate that body condition in migrating passerines is influenced by winter habitat. Proceedings of the Royal Society of London. Series B: Biological Sciences 271:S215 -S218.

Bedford, S. E., and M. B. Usher. 1994. Distribution of arthropod species across the margins of farm woodlands. Agriculture Ecosystems & Environment 48:295-305.

Buler, J. J., F. R. Moore, and S. Woltmann. 2007. A multi-scale examination of stopover habitat use by birds. Ecology 88:1789-1802.

Catry, P., V. Encarnação, A. Araújo, P. Fearon, A. Fearon, M. Armelin, and P. Delaloye. 2004. Are long-distance migrant passerines faithful to their stopover sites? Journal of Avian Biology 35:170-181.

Chernetsov, N. 2006. Habitat selection by nocturnal passerine migrants en route: mechanisms and results. Journal of Ornithology 147:185-191.

Chernetsov, N., and A. Mukhin. 2006. Spatial behavior of European Robins during migratory stopovers: A telemetry study. Wilson Journal of Ornithology 118:364- 373.

Cimprich, D. A., M. S. Woodrey, and F. R. Moore. 2005. Passerine migrants respond to variation in predation risk during stopover. Animal Behaviour 69:1173-1179.

Currie, D., D. Thompson, and T. Burke. 2000. Patterns of territory settlement and consequences for breeding success in the Northern Wheatear Oenanthe oenanthe. Ibis 142:389-398.

DeGraaf, R. M., and J. H. Rappole. 1995. Neotropical migratory birds: Natural history, distribution, and population change. Comstock Publishing Associates, Ithaca.

Drewitt, A., and R. Langston. 2008. Collision effects of wind-power generators and other obstacles on birds. Year in Ecology and Conservation Biology 2008 1134:233- 266.

13 Eaton, S. W. 1995. Northern Waterthrush (Seiurus noveboracensis). Page in A. Poole, editor. The Birds of North America Online. Cornell Lab of Ornithology, Ithaca, NY. Retrieved from http://bna.birds.cornell.edu.bnaproxy.birds.cornell.edu/bna/species/182.

Hansson, M., and J. Pettersson. 1989. Competition and fat deposition in Goldcrests (Regulus regulus) at a migration stop-over site. Die Vogelwarte 35:21-31.

Harrison, X. A., J. D. Blount, R. Inger, D. R. Norris, and S. Bearhop. 2011. Carry-over effects as drivers of fitness differences in animals. Journal of Animal Ecology 80:4-18.

Hunt, P. D., and D. J. Flaspohler. 1998. Yellow-rumped Warbler (Dendroica coronata). Page in A. Poole, editor. The Birds of North America Online. Cornell Lab of Ornithology, Ithaca, NY. Retrieved from http://bna.birds.cornell.edu.bnaproxy.birds.cornell.edu/bna/species/376.

Hutto, R. L. 1985. Seasonal changes in the habitat distribution of transient insectivorous birds in southeastern Arizona: Competition mediated? Auk 102:120-132.

Hutto, R. L. 2000. On the importance of en route periods to the conservation of migratory landbirds. Studies in Avian Biology 20:109-114.

Jenni, L., and M. Schaub. 2003. Behavioural and physiological reactions to environmental variation in bird migration: A review. Pages 155-171 in P. Berthold, E. Gwinner, and E. Sonnenschein, editors. Avian Migration. Springer- Verlag, Berlin and Heidelberg.

Jokimaki, J., E. Huhta, J. Itamies, and P. Rahko. 1998. Distribution of arthropods in relation to forest patch size, edge, and stand characteristics. Canadian Journal of Forest Research 28:1068-1072.

Kelly, J. F., L. S. DeLay, and D. M. Finch. 2002. Density-dependent mass gain by Wilson’s Warblers during stopover. Auk 119:210-213.

Ktitorov, P., F. Bairlein, and M. Dubinin. 2008. The importance of landscape context for songbirds on migration: body mass gain is related to habitat cover. Landscape Ecology 23:169-179.

Kullberg, C., T. Fransson, and S. Jakobsson. 1996. Impaired predator evasion in fat blackcaps (Sylvia atricapilla). Proceedings of the Royal Society of London Series B-Biological Sciences 263:1671-1675.

14 Lindström, Å. 1989. Finch flock size and risk of hawk predation at a migratory stopover site. Auk 106:225-232.

Lindström, Å. 1990. The role of predation risk in stopover habitat selection in migrating bramblings, Fringilla montifringilla. Behavioral Ecology 1:102-106.

Marra, P. P., K. A. Hobson, and R. T. Holmes. 1998. Linking winter and summer events in a migratory bird by using stable-carbon isotopes. Science 282:1884-1886.

Matthews, S. N., and P. G. Rodewald. 2010. Urban forest patches and stopover duration of migratory Swainson’s Thrushes. Condor 112:96-104.

Mehlman, D. W., S. E. Mabey, D. N. Ewert, C. Duncan, B. Abel, D. Cimprich, R. D. Sutter, and M. Woodrey. 2005. Conserving stopover sites for forest-dwelling migratory landbirds. Auk 122:1281-1290.

Moore, F., and P. Kerlinger. 1987. Stopover and fat deposition by North American wood- warblers (Parulinae) following Spring Migration over the Gulf of Mexico. Oecologia 74:47-54.

Moore, F., and W. Yong. 1991. Evidence of food-based competition among passerine migrants during stopover. Behavioral Ecology and Sociobiology 28:85-90.

Moore, F. R., S. A. Gauthreaux, P. Kerlinger, and T. R. Simons. 1995. Habitat requirements during migration: important link in conservation. Pages 121-144 in T. E. Martin and D. M. Finch, editors. Ecology and management of neotropical migratory birds: A synthesis and review of critical issues. Oxford University Press, New York.

Moore, F. R., P. Kerlinger, and T. R. Simons. 1990. Stopover on a Gulf Coast barrier island by spring trans-gulf migrants. The Wilson Bulletin 102:487-500.

Mukhin, A., N. Chernetsov, and D. Kishkinev. 2008. Acoustic information as a distant cue for habitat recognition by nocturnally migrating passerines during landfall. Behavioral Ecology 19:716-723.

Newton, I. 2004. Population limitation in migrants. Ibis 146:197-226.

Newton, I. 2006. Can conditions experienced during migration limit the population levels of birds? Journal of Ornithology 147:146-166.

Norris, D. R. 2005. Carry-over effects and habitat quality in migratory populations. Oikos 109:178-186.

15 Norris, D. R., and C. M. Taylor. 2006. Predicting the consequences of carry-over effects for migratory populations. Biology Letters 2:148 -151.

Parnell, J. F. 1969. Habitat relations of the Parulidae during spring migration. Auk 86:505-521.

Paxton, K. L., C. Van Riper III, and C. O’Brien. 2008. Movement patterns and stopover ecology of Wilson’s Warblers during spring migration on the Lower Colorado River in southwestern Arizona. Condor 110:672-681.

Rappole, J. H., and D. W. Warner. 1976. Relationships between behavior, physiology and weather in avian transients at a migration stopover site. Oecologia 26:193-212.

Robbins, C., J. Sauer, R. Greenberg, and S. Droege. 1989. Population declines in North- American birds that migrate to the neotropics. Proceedings of the National Academy of Sciences of the United States of America 86:7658-7662.

Robbins, S. D. 1991. Wisconsin Birdlife. University of Wisconsin Press, Madison.

Rodewald, P. G., and M. C. Brittingham. 2002. Habitat use and behavior of mixed species landbird flocks during fall migration. The Wilson Bulletin 114:87-98.

Rodewald, P. G., and M. C. Brittingham. 2004. Stopover habitats of landbirds during fall: Use of edge-dominated and early-successional forests. Auk 121:1040-1055.

Rodewald, P. G., and M. C. Brittingham. 2007. Stopover habitat use by spring migrant landbirds: The roles of habitat structure, leaf development, and food availability. Auk 124:1063-1074.

Salewski, V., B. Almasi, A. Heuman, M. Thoma, and A. Schlageter. 2007. Agonistic behaviour of Palaearctic passerine migrants at a stopover site suggests interference competition. Ostrich 78:349-355.

Sauer, J. R., and W. A. Link. 2011. Analysis of the North American Breeding Bird Survey using hierarchical models. Auk 128:87-98.

Schaub, M., and L. Jenni. 2001. Stopover durations of three warbler species along their autumn migration route. Oecologia 128:217-227.

Schaub, M., L. Jenni, and F. Bairlein. 2008. Fuel stores, fuel accumulation, and the decision to depart from a migration stopover site. Behavioral Ecology 19:657- 666.

16 Seewagen, C. L., E. J. Slayton, and C. G. Guglielmo. 2010. Passerine migrant stopover duration and spatial behaviour at an urban stopover site. Acta Oecologica 36:484- 492.

Sillett, T. S., and R. T. Holmes. 2002. Variation in survivorship of a migratory songbird throughout its annual cycle. Journal of Animal Ecology 71:296-308.

Smith, R. J., and F. R. Moore. 2003. Arrival fat and reproductive performance in a long- distance passerine migrant. Oecologia 134:325-331.

Smith, R. J., and F. R. Moore. 2005. Arrival timing and seasonal reproductive performance in a long-distance migratory landbird. Behavioral Ecology and Sociobiology 57:231-239.

Studds, C., and P. Marra. 2005. Nonbreeding habitat occupancy and population processes: An upgrade experiment with a migratory bird. Ecology 86:2380-2385.

U.S. Fish and Wildlife Service. 2008. Trempealeau National Wildlife Refuge Comprehensive Conservation Plan.

Veltri, C. J., and D. Klem. 2005. Comparison of fatal bird injuries from collisions with towers and windows. Journal of Field Ornithology 76:127-133.

Wiedner, D., P. Kerlinger, D. Sibley, P. Holt, J. Hough, and R. Crossley. 1992. Visible morning flight of neotropical landbird migrants at Cape May New Jersey. Auk 109:500-510.

Wikelski, M., E. M. Tarlow, A. Raim, R. H. Diehl, R. P. Larkin, and G. H. Visser. 2003. Avian metabolism: Costs of migration in free-flying songbirds. Nature 423:704.

Winker, K., D. W. Warner, and A. R. Weisbrod. 1992. The Northern Waterthrush and Swainson’s Thrush as transients at a temperate inland stopover site. Pages 384- 402 in J. M. Hagan and D. W. Johnston, editors. Ecology and conservation of Neotropical migrant landbirds. Smithsonian Institution Press, Washington, London.

Ydenberg, R. C., R. W. Butler, and D. B. Lank. 2007. Effects of predator landscapes on the evolutionary ecology of routing, timing and molt by long-distance migrants. Journal of Avian Biology 38:523-529.

Yong, W., D. Finch, F. Moore, and J. Kelly. 1998. Stopover ecology and habitat use of migratory Wilson’s warblers. Auk 115:829-842.

17 Chapter 2

Habitat-dependent exploratory behavior and stopover duration

in Northern Waterthrush (Parkesia noveboracensis):

A translocation experiment during spring migration

2.1. Introduction

Long-distance migration is among the most dangerous periods in the life cycle of migratory birds (Sillett and Holmes 2002) and may limit populations of some species

(Newton 2004). Migratory songbirds must repeatedly stop over to rest and refuel during migration (Moore et al. 1995), spending the majority of their time and energy in stopover habitats between migratory flights (Wikelski et al. 2003). Events during stopover can influence a migrant's time and energy budgets, and potentially carry-over to the breeding season by influencing survival and reproductive output (Harrison et al. 2011).

When a migratory songbird makes landfall after a migratory flight, it finds itself in an area not previously encountered (Catry et al. 2004). Migrants must efficiently exploit unfamiliar environments to increase fat stores and arrive at the breeding grounds early enough to obtain a high quality territory and maximize the probability of successful reproduction (Aebischer et al. 1996, Lozano et al. 1996, Smith and Moore 2005). Upon

18 arrival at a stopover site, migrants are expected to exhibit exploratory behavior, characterized by highly linear, long-distance movements through the site to acquire information about resources, predators, and habitat quality (Stamps 1995, Aborn and

Moore 1997, Paxton et al. 2008). As migrants encounter suitable habitat through exploration, they are expected to settle and confine their movements to more restricted microsites to feed or rest (Aborn and Moore 1997, Paxton et al. 2008). Recent studies have found that a variety of landbird migrants show a pattern of exploration followed by settling during stopover (Aborn and Moore 1997, Chernetsov 2005, Chernetsov and

Mukhin 2006, Paxton et al. 2008, Seewagen et al. 2010).

The frequently observed pattern of exploration followed by settling raises the question of whether exploratory behavior during stopover comes with costs such as increased predation risk (Cimprich et al. 2005) or delayed migration. Tradeoffs likely exist between exploring new areas and foraging in already-explored habitats within a heterogeneous stopover site (Charnov 1976) and between remaining at the current stopover site and resuming migration with the possibility of encountering more suitable stopover habitat elsewhere (Jenni and Schaub 2003). How birds make decisions to optimize these tradeoffs is unknown: In one scenario, birds might actively explore at a stopover site until the most suitable habitat for refueling is located. In another scenario, there may be an upper limit to time spent exploring, after which birds settle into the most suitable site encountered and resume migration when weather conditions permit. A variety of intrinsic (e.g. energetic condition, sex) and extrinsic (e.g. time of season, weather) factors may influence the tradeoffs associated with habitat exploration and

19 stopover duration (Schaub et al. 2008).

Historically, researchers investigating the stopover duration and movements of individual migrants have faced many challenges. For example, dense vegetation and active movements can make small passerines difficult or impossible to continuously track, even when color-marked. Local emigration can lead to underestimates of stopover duration in mark-recapture studies (Bachler and Schaub 2007). Radio-telemetry, by contrast, enables collection of more continuous data and documentation of fine-scale movements and departure dates of individual migrants.

I used an experimental approach to investigate how spring migrants adjust exploratory movements and stopover duration in response to encountering different habitat types in unfamiliar environments. I focused specifically on fine-scale movement patterns and stopover duration of individual Northern Waterthrushes (Parkesia noveboracensis). In addition, I examined how ordinal date, energetic condition, and sex might constrain movements and stopover duration, and how weather variables predicted the date of departure. A more complete understanding of how migrants navigate the tradeoffs associated with exploring unfamiliar habitats during stopover and how these are mediated by intrinsic and extrinsic factors is needed to effectively manage and restore quality stopover habitats (Ewert and Hamas 1995, Buler et al. 2007).

20 2.2. Methods

Study area

I conducted my study in western Wisconsin, USA at Trempealeau National

Wildlife Refuge (NWR, N 44.05°, W 91.53°), which encompasses 2520 ha within the

Upper Mississippi River alluvial valley (Figure 2.1). The refuge includes portions of

Trempealeau and Buffalo counties, which have generally rolling terrain and are 25% and

43% forested, respectively (U.S. Fish and Wildlife Service 2008). The Mississippi River valley is 4 to 9 km wide near the refuge. Steep, forested bluffs abut the river on the

Minnesota side, whereas the former Trempealeau Prairie, now mostly agricultural land, extends between the river and the bluffs for several kilometers on the Wisconsin side.

The rolling upland hills of the surrounding Driftless Area are characterized by a mosaic of agriculture on flatter hilltops and valleys and well-drained forests on steeper terrain.

Land use in the area surrounding Trempealeau NWR is primarily low-density residential and agricultural (U.S. Fish and Wildlife Service 2008). Trempealeau NWR supports a heterogeneous mosaic of open aquatic habitats, emergent marshes, islands, shrub wetlands, and bottomland hardwood forest (Figure 2.2). Pockets of oak savanna, upland forest, and tall-grass prairie occur on sandy soil in the slightly higher elevations. Overall, the refuge exhibits much variation in types of hydrology, stages of succession, and hardness of edges. Forest cover on the refuge typically does not occur in discrete patches and is fragmented by natural habitat gradients, past agriculture, prairie restorations, and water bodies. The bluff faces flanking the alluvial valley support well-drained forest and prairie plant communities.

21 Study species

The Northern Waterthrush breeds in Alaska, Canada, and the northern United

States and winters from northern Mexico and the West Indies to northern South America

(Eaton 1995). In my study area it occurs only as a non-breeding transient, with the nearest location of confirmed breeding 140 km to the north (Wisconsin Breeding Bird

Atlas 2003). All radio-tagged Northern Waterthrushes departed by May 25 and no

Northern Waterthrushes were seen or heard in the study area after May 26. The Northern

Waterthrush inhabits dense understory vegetation near water during the breeding season, and on the Neotropical wintering grounds it occurs in mangroves, gallery forest, and other mesic forest habitats (Eaton 1995). During spring migratory stopover, the Northern

Waterthrush has strong associations with habitats containing thick understory and wet substrate (Parnell 1969, Rappole and Warner 1976, Winker et al. 1992). The Northern

Waterthrush typically forages near water and dense vegetation, where it consumes small arthropods (Eaton 1995). Intra-specific competition has been observed during spring migratory stopover in Texas (Rappole and Warner 1976), and aggressive intra-specific chases into vegetation have been noted during diurnal morning flight in fall migration in

New Jersey (Wiedner et al. 1992).

Capture and processing of focal individuals

I passively mist-netted transient Northern Waterthrushes during mid-April to late

May 2009 and 2010 between 06:00 and 11:40. When personnel were available for radio- tracking, I selected the most recently captured Northern Waterthrush as a focal individual.

22 For each individual I measured unflattened wing chord to the nearest millimeter using a wing ruler, tarsus length to the nearest 0.1 mm using calipers, mass to the nearest 0.1 g using a digital scale, and visible fat on a scale of 0-7 (DeSante et al. 2011). I banded each individual with a U.S. Geological Survey aluminum leg band and a unique combination of Darvic plastic colored leg bands. Since spring transient male and female Northern

Waterthrushes are morphologically similar and do not exhibit cloacal protuberances or brood patches, I sampled a rectrix from each individual for molecular sexing. Feather samples were analyzed at an external laboratory (Avian Biotech International,

Tallahassee, FL), where conclusive sex determinations were obtained for 33 of 40 individual Northern Waterthrush samples submitted. I did not age the birds because aging criteria based on plumage alone are unreliable for Northern Waterthrush in spring

(Pyle 1997). I placed each focal individual into a cloth bag during the translocation process after processing at the banding station.

Translocation experiment and radio-tagging

I translocated all birds so that upon release, each would presumably be forced to explore habitat not previously encountered. Although releasing non-translocated

“control” birds at the capture site is conceptually attractive (Matthews and Rodewald

2010a), arrival dates of individuals were unknown and releasing birds at the capture location would not have controlled for differences in knowledge of the habitat surrounding the capture site. I selected two release sites in each of the two major forest types present in the study area. The four release sites were 0.7 to 5.4 km from the

23 banding sites (Figure 2.3). I selected two bottomland forest release sites and two upland forest release sites. The bottomland sites were characterized by swamp white oak

(Quercus bicolor), box elder (Acer negundo), silver maple (Acer saccharinum), and ash

(Fraxinus spp.), whereas the upland sites were characterized by trees favoring sandier soils such as black locust (Robinia pseudoacacia) and northern pin oak (Quercus ellipsoidalis). Northern Waterthrushes strongly favor wet substrates for foraging, so these release sites formed a continuum of presumably suitable to less suitable habitat based on published descriptions of stopover habitat relationships (Parnell 1969, Rappole and Warner 1976, Winker et al. 1992). I randomly assigned birds to these release sites while maintaining balanced sample sizes at each site and assigning no more than one

Northern Waterthrush per day to each release site.

I translocated birds via automobile to within 200 m of the release site and verified whether the focal individual was stressed (e.g., bill open, eyelids partly shut, less alert) before proceeding with radio-transmitter attachment. Since no birds showed visible signs of stress, I proceeded with radio-transmitter attachment in all cases. I attached a radio- transmitter to back feathers using LashGrip eyelash cement (Kenward 2001). I fitted all

Northern Waterthrushes in 2010 with a 0.39 g Holohil Systems transmitter (BD-2N, Carp,

Ontario, Canada). In 2009, I fitted 5 waterthrushes with a 0.39 g Holohil Systems transmitter (BD-2N) and 16 waterthrushes with a 0.65 g (mean; range 0.56 g to 0.73 g)

Wildlife Materials transmitter (SOM-2007, Murphysboro, IL). The transmitters on each waterthrush averaged 2.6% of body mass (range 1.7% to 4.0%). After attachment I placed a cloth bag over my hand gripping the bird and walked the remaining distance to

24 the release point. Upon arrival at the release point, I randomly oriented the bird so that microhabitat features at the release point would not cause systematic bias in the initial flight direction and behavior of the bird upon release. I oriented each bird at a random compass direction and a random distance between 0 and 50 m from the release point prior to removing the bag and releasing the bird. Time elapsed between capture and release averaged 37 min (range 25 to 64 min).

Radio telemetry

Movement ecology is increasingly gaining recognition as a key component of the biology of all organisms (Nathan et al. 2008). In studies of avian movement ecology, radio-telemetry has a long history of use and wide acceptance for studying small birds inside and outside the migratory period (Cochran et al. 1967, Wikelski et al. 2003,

Robinson et al. 2010, Whitaker and Warkentin 2010). Although radio-transmitters can sometimes affect the behavior of animals (Millspaugh and Marzluff 2001, Barron et al.

2010), radio-telemetry remains the only way to accurately determine fine-scale movement and stopover duration of small migratory songbirds (Bachler and Schaub

2007). Moreover, a number of studies on passerines have found no adverse effects of transmitters on avian behavior. Wood Thrushes (Hylocichla mustelina) carrying transmitters weighing 4% of body mass showed no decrease in return rates or body mass compared to banded-only birds (Powell et al. 1998). Female Hooded Warblers

(Setophaga citrina) carrying radio-transmitters and harnesses weighing 7% to 8.5% of body mass showed equal nest provisioning rates, brooding time, and time spent perched

25 on the edge of the nest as untagged birds (Neudorf and Pitcher 1997). In my study, radio- tagged Northern Waterthrushes appeared to forage normally, and the only individual recaptured with a radio-transmitter had gained body mass. Most importantly, all individuals in my study received a radio-transmitter and similar treatment, so any differences among individuals in movement behavior and stopover duration should not be attributable to the presence of radio-transmitters.

I radio-located birds every 30 min until 20:00 on the day of release and every 30 min from 06:00 to 20:00 on the day after release to investigate fine-scale movement patterns of birds soon after encountering unfamiliar environments. Since birds were often hidden by vegetation and direct observation was usually not feasible, I approached as closely as possible without disturbing the bird (but no closer than 25 m) and located the individuals via homing (White and Garrott 1990) using a R4000 receiver (Advanced

Telemetry Systems, Isanti, MN) and a 3-element Yagi antenna. I marked the observer location with a GPS (Garmin, Olathe, KS) to a precision of 0.00001 latitude/longitude degrees and recorded the distance and bearing from this point to the bird (Smith et al.

2010).

After the first 2 days of radio tracking, I verified whether each bird remained in the study area once per day in 2010 and twice per day in 2009. I searched daily for radio frequencies of birds presumed to have departed the study area using ground-based radio- telemetry. Additionally, I scanned for signals throughout the study area 1-2 times per week using a small airplane. If a radio frequency was not detected for 7 days, I assumed the bird had departed on migration on the night of the last detection. I removed birds

26 from movement analyses if the transmitter detached during the first 2 days of tracking; I omitted birds from analyses of stopover duration if the transmitter detached at any time during stopover. The manufacturer-specified nominal battery life was 12 days for the

Holohil Systems transmitters and 14 days for the Wildlife Materials transmitters.

Movement characteristics and home range estimation

I excluded two birds from movement analysis due to transmitter failure and one bird because its radio-transmitter detached on day 1. Individual relocation points were excluded if time/location data were missing or if the observer estimated the bird to be more than 100 m away at the time the location was recorded. I considered daily movement data to be complete if gaps in tracking data did not exceed 2 hours and there were at least 10 relocation points, a sampling frequency consistent with other published studies of fine-scale movement behavior during stopover (Paxton et al. 2008, Seewagen et al. 2010).

I calculated measures of movement following Aborn and Moore (1997), Paxton et al. (2008), and Seewagen et al. (2010). I calculated daily movement rate (m/hr) by dividing total distance moved (sum of distances between all successive movements) by the length of time radio-tracked. I calculated daily displacement by determining the straight-line distance between the first point and the last point on a given day. I calculated daily linearity by dividing displacement by the total distance moved.

I used Home Range Tools (Rodgers et al. 2007) in ArcMap (ESRI 2011) to estimate fixed-kernel home range size for all birds (n = 30) radio-tracked for at least 2

27 days and with ≥ 10 locations per day (Seewagen et al. 2010). I calculated home ranges using 50, 90, and 95% isopleths using Href smoothing parameters. Isopleth areas were strongly negatively correlated with the original sample size (Seaman et al. 1999), indicating significant temporal autocorrelation between successive locations (Swihart and

Slade 1985). Swihart and Slade (1985) described how to determine time to independence among successive locations, but such methods assume a constant center of movement activity, an assumption unlikely met by migrants during stopover (Whitaker and

Warkentin 2010). Nonetheless, I still present kernel isopleth results here for general descriptive and comparative purposes following Buler (2006), Chernetsov and Mukhin

(2006), and Seewagen et al. (2010).

Energetic condition

To obtain an index of energetic condition, I computed the first principal component of unflattened wing chord (mm) and tarsus length (mm) as an index of body size. I calculated energetic condition index as the residuals of a linear regression of bird mass (g) on the body size index. I made these calculations using program R (R

Development Core Team 2011). The energetic condition index was strongly positively correlated with scores of visible fat deposits (regression, p < 10-5).

Statistical analyses

I used a model-selection procedure to determine the variables most closely associated with stopover duration, daily movement rate, daily displacement, and daily

28 linearity. I selected 32 candidate models a priori. These models included the explanatory variables ordinal date, energetic condition, sex, year, and release point habitat. The models included a null model, a saturated model (all 5 variables), and 30 other models comprising all possible combinations of the 5 variables. I fitted generalized linear models in program R (R Development Core Team 2011) and ranked them in package bbmle using Akaike's information criterion with a correction for small sample size (AICc) (Anderson and Burnham 2002). I fitted these models to the log-transformed response variables movement rate, displacement, and linearity, and the untransformed response variable minimum stopover duration. I considered the model with the lowest

AICc value to be the best and models with ΔAICc < 2 as equally supported given the data

(Anderson and Burnham 2002). For response variables with models that were equally competitive, I obtained averaged parameter estimates and standard errors by calculating a weighted average of the parameter estimates and standard errors for all best-ranked models and normalizing according to the total weight of all best-ranked models. When the confidence interval for a parameter overlapped with zero, I considered that parameter uninformative.

To examine the influence of weather on departure, I obtained quality-controlled hourly weather data (National Climatic Data Center 2011) for the Winona Municipal

Airport, located 7 to 16 km from stopover locations of focal birds. I aggregated weather data from the end of astronomical twilight in the evening to the beginning of astronomical twilight in the morning to create nightly weather variables. I used Random

Forests (an extension of classification trees, Cutler et al. 2007) to examine how departure

29 decisions were predicted by a suite of nightly weather variables (mean barometric pressure, change in barometric pressure, mean temperature, mean southerly component wind speed, mean westerly component wind speed, and total precipitation). I evaluated the importance of each variable in predicting departure decisions by calculating the mean decrease in the Gini index (a splitting criterion for classification trees), with and without permuting the variable of interest (Breiman et al. 1984).

2.3. Results

I radio-tracked 43 Northern Waterthrushes during spring 2009-2010. I tracked 21 birds (6 female, 6 male, 9 sex unknown) in 2009 between April 24 and May 25 and 22 birds (9 female, 12 male, 1 sex unknown) in 2010 between April 29 and May 24. On average, I captured males 7 days earlier than females (t-test, n = 33, p < 0.001). Males

(19.4 g, 76.3 mm) tended to be heavier (t-test, n = 33, p = 0.07) and were longer-winged

(t-test, n = 33, p < 0.002) than females (18.0 g, 74.1 mm) but similar in energetic condition (t-test, n = 33, p = 0.14).

My two-year dataset includes 1859 radio-locations, an average of 43 radio- locations per individual. The sample size was higher on day 1 than on day 2 in part because 6 birds initiated a migratory flight the night after release, and 2 birds left the study area on the night after release or early the next morning. Complete daily movement data were available for 34 birds for day 1, 30 birds on day 2, 37 birds for at least one day, and 27 birds for both days.

30 Home range size varied greatly by individual and by the size of the isopleth used.

At the 95% isopleth, median home range size was 13 ha (range 0.3 to 110 ha). At 90% the median home range size was 10 ha (range 0.2 to 89 ha). At 50% the median home range size was 2.4 ha (range 0.04 to 30 ha).

The daily movement rate was 74 ± 32 m/hr (mean ± sd) for Northern

Waterthrushes with complete radio-tracking data for the first 2 days after release (n = 27).

Mean daily displacement, describing the distance between a bird's first location of the day and its location at 20:00, was 280 ± 188 m (mean ± sd). Mean daily linearity, with 0 reflecting meandering movements and 1 reflecting perfectly linear movement, was 0.30 ±

0.16 (mean ± sd).

Movements of individual Northern Waterthrushes decreased over the 2 days following release for all 3 calculated measures of movement (paired t-tests, n = 27).

Movement rate decreased 43% from a median of 89 m/hr on day 1 to 61 m/hr on day 2 (p

< 0.001). Displacement decreased 71% from a median of 314 m on day 1 to 90 m on day

2 (p < 0.001). Linearity decreased 55% from a median of 0.35 on day 1 to 0.16 on day 2

(p < 0.005). Waterthrushes released in upland forest habitats almost invariably moved to wetter habitats within a few hours of release. Most individuals, regardless of release habitat, were fairly sedentary after the day of release.

Competing models and their model-averaged parameter estimates revealed prominent differences between determinants of movement on day 1 (n = 34) and day 2 (n

= 30). Top-ranked candidate models showed that birds released in upland forest habitat

(β = -0.371 ± 0.146), at a later ordinal date (β = 0.016 ± 0.008), and in higher energetic

31 condition (β = 0.107 ± 0.037) had higher movement rates on day 1 (Table 2.1). In contrast, females (β = -0.581 ± 0.244) and birds tracked in 2009 (β = -0.250 ± 0.157) had higher movement rates on day 2 (Table 2.2). Top-ranked models showed that birds released in upland forest habitat (β = -1.322 ± 0.271) and at later ordinal dates (β = 0.011

± 0.009) exhibited greater daily displacement on day 1 (Table 2.3); birds tracked in 2009

(β = -1.729 ± 0.611) showed greater daily displacement on day 2 (Table 2.4). Further, top-ranked models revealed that birds released in upland forest habitat (β = -0.857 ±

0.243) exhibited increased linearity on day 1 (Table 2.5), whereas males (β = 0.774 ±

0.449) and birds tracked in 2009 (β = -1.340 ± 0.481) showed increased linearity on day 2

(Table 2.6).

Minimum stopover duration for Northern Waterthrushes was 4.0 ± 0.4 days (n =

31, mean ± SE) with a range of 1 to 10 days. When I modeled the determinants of stopover duration, the 3 top-ranked models contained the majority of the model weight

(w1 to 3 = 0.77) and indicated that birds released in bottomland forest habitat (β = 1.463 ±

0.573), on earlier ordinal dates (β = -0.208 ± 0.056), in lower energetic condition (β =

-0.194 ± 0.100), sexed as females (β = -0.831 ± 0.735), and in 2010 (β = 0.304 ± 0.200) had a longer minimum stopover duration (Table 2.7).

During spring 2009-2010, there were 48 nights when at least one radio-tagged waterthrush remained in the study area or departed on a migratory flight. The Random

Forests model correctly classified 63% of nights as departure or non-departure nights for

Northern Waterthrush. The top 3 variables in the model indicated a higher probability of waterthrush departure on nights with a later ordinal date, a warmer mean temperature,

32 and more easterly winds (Table 2.8, Figure 2.4). Although energetic condition at capture was not included in the model, it was not associated with ordinal date and thus should not have confounded results (regression, p = 0.35).

2.4. Discussion

Migratory songbirds arrive at stopover areas with little or no prior information about how to best exploit these unfamiliar environments (Catry et al. 2004, Nemeth and

Moore 2007). How efficiently spring migrants familiarize themselves with stopover areas and replenish their energy reserves can influence migratory timing, energetic condition, and ultimately reproductive success (Smith and Moore 2003, 2005). In my study, Northern Waterthrushes settled into more defined microsites following a period of wider exploration and exhibited decreases in movement rate, displacement and linearity of movement between the 1st and 2nd days after release. On a finer time scale, waterthrushes released in upland forest habitat almost invariably moved to wetter habitats within 3 hours of release, indicating that rapid exploration can help to accommodate their narrow stopover habitat preferences (Parnell 1969). My study corroborates an emerging pattern in stopover research in which landbird migrants explore widely early in stopover and subsequently settle on a smaller microsite. This pattern has now been found across multiple species and families, in different migration systems on different continents, and in both rural and urban stopover habitats (Aborn and Moore 1997, Chernetsov 2005,

Chernetsov and Mukhin 2006, Paxton et al. 2008, Seewagen et al. 2010).

33 Randomized translocation of radio-tagged birds to unfamiliar stopover habitats provides a unique opportunity to assess how migrants adjust their spatial behavior upon encountering novel environments, but such studies have rarely been conducted. The

Northern Waterthrushes I released in upland forest habitat explored more widely on day 1 than birds released in more suitable bottomland forest habitat. By day 2, movement metrics did not differ with respect to release point habitat, suggesting that Northern

Waterthrushes had largely completed the exploratory phase of their movements and settled into a stopover microsite. Using a similar approach, Cohen and Moore (2011) translocated migrant Red-eyed Vireos (Vireo olivaceus) to 3 habitats differing in quality, birds released in low quality habitats showed greater displacement and almost invariably moved into higher quality habitats.

Two separate lines of reasoning might be used to predict the relationship between a migrant's energetic condition upon arrival and its patterns of movement during a stopover event. In one scenario, migrants arriving with remaining fat stores explore more widely for food resources at a stopover site while lean birds, having a lower safety margin, settle in the first suitable habitat located (Chernetsov 2006). In another scenario, lean birds are forced to forage over large areas despite increased predation risk while fat birds move less and simply await favorable conditions for the next migratory flight

(Chernetsov 2006). Northern Waterthrushes captured in higher energetic condition showed greater movement rates on the day of release than lean birds, a pattern opposite that found in other studies (Aborn and Moore 1997, Buler 2006, Seewagen et al. 2010,

Matthews and Rodewald 2010b). Movement rate of waterthrushes did not vary with

34 energetic condition by the 2nd day after release, a finding consistent with the idea that fat and lean birds explore habitat differently but converge on similar movement strategies after settling.

Important inter-sexual differences in the spatial ecology of long-distance migrants have been observed in other seasons (e.g. Marra et al. 1993), yet the vast majority of stopover studies have not examined how movement patterns may differ between males and females (Seewagen et al. 2010, Matthews and Rodewald 2010a). In this study I found no inter-sexual differences in the movements of Northern Waterthrushes on the day of release, but on the 2nd day female waterthrushes showed higher movement rate and lower linearity compared to males. This pattern is difficult to explain but suggests males and females have a similar approach to initial exploration of habitat, yet differ in movement patterns following settlement. In Arizona, Paxton et al. (2008) examined the influence of sex on movements of Wilson's Warblers (Cardellina pusilla), but found no differences between males and females.

Spring in temperate zones is characterized in part by phenological changes in vegetation structure and arthropod abundance, so it is perhaps not surprising that movement patterns of migrants during stopover can change as the season progresses. In spring migrant Wilson's Warblers in Arizona, Paxton et al. (2008) documented seasonal increases in movement rate, displacement, and linearity, attributing the pattern to increased habitat exploration as food resources became increasingly dispersed with changing flowering phenology. I also detected seasonal increases in movement rate and displacement, but only on the day of release, suggesting seasonal changes in food

35 distribution may not be the primary cause.

For a migratory songbird, deciding when to depart a stopover site is central to maintaining a successful migratory schedule (Schaub et al. 2008) because early arrival on the breeding grounds can confer reproductive advantages (Smith and Moore 2005). My results support the view that stopover duration represents an optimization of many different intrinsic and extrinsic factors.

Release point habitat type strongly affected stopover duration of Northern

Waterthrushes, with birds initially released in more suitable habitat staying longer. Such habitat-dependent stopover duration was unexpected because waterthrushes released in unsuitable habitat had almost invariably moved to more suitable habitat within a few hours of release, and by day 2, movement patterns were no longer associated with release point habitat type. Rate of mass gain was considered the main factor determining optimal fuel stores at departure under time-minimizing optimal migration theory (Alerstam and

Lindström 1990, Hedenström and Alerstam 1997, Jenni and Schaub 2003), suggesting that the waterthrushes released in more suitable habitats and stopping over longer were gaining mass faster. Habitat-dependent differences in mass gain would not be expected under an ideal free distribution (Fretwell and Lucas 1969), but perhaps migrants at stopover sites are not “free” to select habitats of highest quality. Indeed, an upper bound on exploratory movements (Paxton et al. 2008) may preclude waterthrushes from conforming to an ideal free distribution upon settling. Northern Waterthrushes encountering unsuitable habitat with patches of suitable habitat within their range of exploration, such as my upland release sites, may concentrate their activity within

36 suitable patches of habitat and experience increased intra-specific competition (Rappole and Warner 1976), which has been linked to lower rates of mass gain (Bibby and Green

1980, Moore and Yong 1991, Kelly et al. 2002). Conversely, waterthrushes encountering homogenous areas of suitable habitat such as my bottomland release sites (Parnell 1969,

Winker et al. 1992), may experience less inter-specific competition and higher rates of mass gain, and consequently may opt for longer stopovers.

Northern Waterthrushes in my study area decreased their stopover duration as the spring season progressed, a result similar to that of Matthews and Rodewald (2010b) for

Swainson's Thrushes (Catharus ustulatus). Possible explanations for this pattern include a decrease in food availability over the spring season or a shift from an energy-limited to a time-limited schedule as arrival timing on the breeding grounds becomes more urgent.

My study along with a number of others (e.g. Cherry 1982, Yong and Moore 1993,

Goymann et al. 2010, Seewagen et al. 2010) have found a negative relationship between stopover duration and energetic condition. I also found males to have shorter stopover duration than females, even after controlling for day of year. Yong et al. (1998) predicted that males should have shorter stopover duration in spring because the sexes have different seasonal “goals”. Presumably the idea is that males have a faster migratory pace because of the need to arrive early on the breeding grounds and establish territories prior to females' arrival, but this pattern could also arise if males depart the wintering grounds earlier or make shorter, more frequent stopovers and shorter migratory flights.

Weather may influence departure decisions independently of other factors

(Matthews and Rodewald 2010b). I found that departure probability on a given night

37 increased with ordinal date and weather conditions characteristic of a passing warm front, such as higher temperature and more easterly winds (Table 2.8, Figure 2.4). Taken together, these results for Northern Waterthrush indicate that energetic condition and ordinal date determined the duration of stopover whereas favorable weather conditions fine-tuned the precise date of departure, a pattern also found in Swainson's Thrushes

(Matthews and Rodewald 2010b). In modeling departures of European Robins

(Erithacus rubecula), Schaub et al. (2004) observed that wind conditions on the ground mostly failed to predict the night of departure. By contrast, both my study and that of

Åkesson and Hedenström (2000) found that surface conditions were valuable for predicting departure.

The Northern Waterthrushes in this study settled into more defined microsites following a period of wider exploration. The degree of exploration differed by release habitat, showing that waterthrushes adjusted their spatial ecology during stopover to accommodate their narrow habitat preferences. Nonetheless, birds also adjusted stopover duration in response to release habitat, highlighting the potential importance of conserving quality stopover habitats for migratory landbirds (Ewert and Hamas 1995).

2.5. References

Aborn, D. A., and F. R. Moore. 1997. Pattern of movement by Summer Tanagers (Piranga rubra) during migratory stopover: A telemetry study. Behaviour 134:1077-1100.

38 Aebischer, A., N. Perrin, M. Krieg, J. Studer, and D. R. Meyer. 1996. The role of territory choice, mate choice and arrival date on breeding success in the Savi’s Warbler Locustella luscinioides. Journal of Avian Biology 27:143-152.

Åkesson, S., and A. Hedenström. 2000. Wind selectivity of migratory flight departures in birds. Behavioral Ecology and Sociobiology 47:0140-0144.

Alerstam, T., and Å. Lindström. 1990. Optimal bird migration: The relative importance of time, energy, and safety. Pages 331-351 in E. Gwinner, editor. Bird migration: physiology and ecophysiology. Springer-Verlag, Berlin and New York.

Anderson, D. R., and K. P. Burnham. 2002. Model selection and multimodel inference : A practical information-theoretic approach. Springer, New York.

Bächler, E., and M. Schaub. 2007. The effects of permanent local emigration and encounter technique on stopover duration estimates as revealed by telemetry and mark-recapture. Condor 109:142-154.

Barron, D. G., J. D. Brawn, and P. J. Weatherhead. 2010. Meta-analysis of transmitter effects on avian behaviour and ecology. Methods in Ecology and Evolution 1:180- 187.

Bibby, C., and R. Green. 1980. Foraging behavior of migrant Pied Flycatchers, Ficedula hypoleuca, on temporary territories. Journal of Animal Ecology 49:507-521.

Breiman, L., J. H. Friedman, R. A. Olshen, and C. J. Stone. 1984. Classification and regression trees. Wadsworth and Brooks/Cole, Monterey, CA.

Buler, J. J. 2006. Understanding habitat use by landbirds during migration along the Mississippi Gulf Coast using a scale-dependent approach. Ph.D. Dissertation, University of Southern Mississippi.

Buler, J. J., F. R. Moore, and S. Woltmann. 2007. A multi-scale examination of stopover habitat use by birds. Ecology 88:1789-1802.

Catry, P., V. Encarnação, A. Araújo, P. Fearon, A. Fearon, M. Armelin, and P. Delaloye. 2004. Are long-distance migrant passerines faithful to their stopover sites? Journal of Avian Biology 35:170-181.

Charnov, E. L. 1976. Optimal foraging, the marginal value theorem. Theoretical Population Biology 9:129-136.

39 Chernetsov, N. 2005. Spatial behavior of medium and long-distance migrants at stopovers studied by radio tracking. Annals of the New York Academy of Sciences 1046:242- 252.

Chernetsov, N. 2006. Habitat selection by nocturnal passerine migrants en route: mechanisms and results. Journal of Ornithology 147:185-191.

Chernetsov, N., and A. Mukhin. 2006. Spatial behavior of European Robins during migratory stopovers: A telemetry study. Wilson Journal of Ornithology 118:364- 373.

Cherry, J. D. 1982. Fat deposition and length of stopover of migrant White-crowned Sparrows. Auk 99:725-732.

Cimprich, D. A., M. S. Woodrey, and F. R. Moore. 2005. Passerine migrants respond to variation in predation risk during stopover. Animal Behaviour 69:1173-1179.

Cochran, W. W., G. G. Montgomery, and R. R. Graber. 1967. Migratory Flights of Hylocichla Thrushes in Spring: A Radiotelemetry Study. The Living Bird 6:213- 225.

Cohen, E., and F. Moore. 2011. Predicting successful stopover: Individual based models of Red-eyed Vireos (Vireo olivaceus) in a heterogeneous landscape. Chattanooga, TN. Retrieved May 28, 2011, from http://citation.allacademic.com/meta/p_mla_apa_research_citation/2/4/4/0/7/p244 072_index.html.

Cutler, D. R., T. C. Edwards, K. H. Beard, A. Cutler, K. T. Hess, J. Gibson, and J. J. Lawler. 2007. Random forests for classification in ecology. Ecology 88:2783- 2792.

DeSante, D. F., K. M. Burton, P. Velez, D. Froehlich, and D. Kaschube. 2011. MAPS Manual. Institute for Bird Populations.

Eaton, S. W. 1995. Northern Waterthrush (Seiurus noveboracensis). Page in A. Poole, editor. The Birds of North America Online. Cornell Lab of Ornithology, Ithaca, NY. Retrieved from http://bna.birds.cornell.edu.bnaproxy.birds.cornell.edu/bna/species/182.

ESRI. 2011. ArcMap 9.3. Environmental Systems Research Institute, Redlands, CA.

40 Ewert, D. N., and M. J. Hamas. 1995. Ecology of migratory landbirds during migration in the midwest. Pages 200-208 in F. R. I. Thompson, editor. Management of midwestern landscapes for the conservation of neotropical migratory birds. North Central Forest Experiment Station USDA Forest Service, Detroit, MI. Retrieved from http://www.nrs.fs.fed.us/pubs/gtr/gtr_nc187.pdf.

Fretwell, S. D., and H. L. Lucas. 1969. On territorial behavior and other factors influencing habitat distribution in birds. Acta Biotheoretica 19:16-36.

Goymann, W., F. Spina, A. Ferri, and L. Fusani. 2010. Body fat influences departure from stopover sites in migratory birds: evidence from whole-island telemetry. Biology Letters 6:478 -481.

Harrison, X. A., J. D. Blount, R. Inger, D. R. Norris, and S. Bearhop. 2011. Carry-over effects as drivers of fitness differences in animals. Journal of Animal Ecology 80:4-18.

Hedenström, A., and T. Alerstam. 1997. Optimum fuel loads in migratory birds: Distinguishing between time and energy minimization. Journal of theoretical biology 189:227-234.

Jenni, L., and M. Schaub. 2003. Behavioural and physiological reactions to environmental variation in bird migration: A review. Pages 155-171 in P. Berthold, E. Gwinner, and E. Sonnenschein, editors. Avian Migration. Springer- Verlag, Berlin and Heidelberg.

Kelly, J. F., L. S. DeLay, and D. M. Finch. 2002. Density-dependent mass gain by Wilson’s Warblers during stopover. Auk 119:210-213.

Kenward, R. 2001. A manual for wildlife radio tagging. Academic Press, San Diego, CA; London.

Lozano, G. A., S. Perreault, and R. E. Lemon. 1996. Age, arrival date and reproductive success of male American Redstarts Setophaga ruticilla. Journal of Avian Biology 27:164-170.

Marra, P. P., T. W. Sherry, and R. T. Holmes. 1993. Territorial Exclusion by a Long- Distance Migrant Warbler in Jamaica: A Removal Experiment with American Redstarts (Setophaga ruticilla). The Auk 110:565-572.

Matthews, S. N., and P. G. Rodewald. 2010a. Movement behaviour of a forest songbird in an urbanized landscape: the relative importance of patch-level effects and body condition during migratory stopover. Landscape Ecology 25:955-965.

41 Matthews, S. N., and P. G. Rodewald. 2010b. Urban forest patches and stopover duration of migratory Swainson’s Thrushes. Condor 112:96-104.

Millspaugh, J. J., and J. M. Marzluff. 2001. Radio tracking and animal populations. Academic Press, San Diego.

Moore, F., and W. Yong. 1991. Evidence of food-based competition among passerine migrants during stopover. Behavioral Ecology and Sociobiology 28:85-90.

Moore, F. R., S. A. Gauthreaux, P. Kerlinger, and T. R. Simons. 1995. Habitat requirements during migration: important link in conservation. Pages 121-144 in T. E. Martin and D. M. Finch, editors. Ecology and management of neotropical migratory birds: A synthesis and review of critical issues. Oxford University Press, New York.

Nathan, R., W. M. Getz, E. Revilla, M. Holyoak, R. Kadmon, D. Saltz, and P. E. Smouse. 2008. A movement ecology paradigm for unifying organismal movement research. Proceedings of the National Academy of Sciences 105:19052 -19059.

National Climatic Data Center. 2011. National Climatic Data Center. Retrieved March 24, 2011, from http://www.ncdc.noaa.gov/oa/ncdc.html.

Nemeth, Z., and F. R. Moore. 2007. Unfamiliar stopover sites and the value of social information during migration. Journal of Ornithology 148:S369-S376.

Neudorf, D. L., and T. E. Pitcher. 1997. Radio transmitters do not affect nestling feeding rates by female Hooded Warblers. Journal of Field Ornithology 68:64-68.

Newton, I. 2004. Population limitation in migrants. Ibis 146:197-226.

Parnell, J. F. 1969. Habitat relations of the Parulidae during spring migration. Auk 86:505-521.

Paxton, K. L., C. Van Riper III, and C. O’Brien. 2008. Movement patterns and stopover ecology of Wilson’s Warblers during spring migration on the Lower Colorado River in southwestern Arizona. Condor 110:672-681.

Powell, L. A., D. G. Krementz, Jason D. Lang, and M. J. Conroy. 1998. Effects of radio transmitters on migrating Wood Thrushes. Journal of Field Ornithology 69:306- 315.

Pyle, P. 1997. Identification guide to North American birds, Part I. Slate Creek Press, Bolinas, California.

42 R Development Core Team. 2011. R: A language andenvironment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.

Rappole, J. H., and D. W. Warner. 1976. Relationships between behavior, physiology and weather in avian transients at a migration stopover site. Oecologia 26:193-212.

Robinson, W. D., M. S. Bowlin, I. Bisson, J. Shamoun-Baranes, K. Thorup, R. H. Diehl, T. H. Kunz, S. Mabey, and D. W. Winkler. 2010. Integrating concepts and technologies to advance the study of bird migration. Frontiers in Ecology and the Environment 8:354-361.

Rodgers, A. R., A. P. Carr, H. L. Beyer, L. Smith, and J. G. Kie. 2007. HRT: Home Range Tools for ArcGIS. Version 1.1. Ontario Ministry of Natural Resources, Centre for Northern Forest Ecosystem Research, Thunder Bay, Ontario, Canada.

Schaub, M., L. Jenni, and F. Bairlein. 2008. Fuel stores, fuel accumulation, and the decision to depart from a migration stopover site. Behavioral Ecology 19:657- 666.

Schaub, M., F. Liechti, and L. Jenni. 2004. Departure of migrating European robins, Erithacus rubecula, from a stopover site in relation to wind and rain. Animal Behaviour 67:229-237.

Seaman, D. E., J. J. Millspaugh, B. J. Kernohan, G. C. Brundige, K. J. Raedeke, and R. A. Gitzen. 1999. Effects of sample size on kernel home range estimates. Journal of Wildlife Management 63:739-747.

Seewagen, C. L., E. J. Slayton, and C. G. Guglielmo. 2010. Passerine migrant stopover duration and spatial behaviour at an urban stopover site. Acta Oecologica 36:484- 492.

Sillett, T. S., and R. T. Holmes. 2002. Variation in survivorship of a migratory songbird throughout its annual cycle. Journal of Animal Ecology 71:296-308.

Smith, J. A. M., L. R. Reitsma, and P. P. Marra. 2010. Moisture as a determinant of habitat quality for a nonbreeding Neotropical migratory songbird. Ecology 91:2874-2882.

Smith, R. J., and F. R. Moore. 2003. Arrival fat and reproductive performance in a long- distance passerine migrant. Oecologia 134:325-331.

Smith, R. J., and F. R. Moore. 2005. Arrival timing and seasonal reproductive performance in a long-distance migratory landbird. Behavioral Ecology and Sociobiology 57:231-239.

43 Stamps, J. 1995. Motor Learning and the Value of Familiar Space. The American Naturalist 146:41-58.

Swihart, R. K., and N. A. Slade. 1985. Testing for independence of observations in animal movements. Ecology 66:1176-1184.

U.S. Fish and Wildlife Service. 2008. Trempealeau National Wildlife Refuge Comprehensive Conservation Plan.

Whitaker, D. M., and I. G. Warkentin. 2010. Spatial Ecology of Migratory Passerines on Temperate and Boreal Forest Breeding Grounds. Auk 127:471-484.

White, G. C., and R. A. Garrott. 1990. Analysis of wildlife radio-tracking data. Academic Press, San Diego, CA.

Wiedner, D., P. Kerlinger, D. Sibley, P. Holt, J. Hough, and R. Crossley. 1992. Visible morning flight of neotropical landbird migrants at Cape May New Jersey. Auk 109:500-510.

Wikelski, M., E. M. Tarlow, A. Raim, R. H. Diehl, R. P. Larkin, and G. H. Visser. 2003. Avian metabolism: Costs of migration in free-flying songbirds. Nature 423:704.

Winker, K., D. W. Warner, and A. R. Weisbrod. 1992. The Northern Waterthrush and Swainson’s Thrush as transients at a temperate inland stopover site. Pages 384- 402 in J. M. Hagan and D. W. Johnston, editors. Ecology and conservation of Neotropical migrant landbirds. Smithsonian Institution Press, Washington, London.

Wisconsin Breeding Bird Atlas. 2003. WBBA Northern Waterthrush Map. Retrieved from http://www.uwgb.edu/birds/wbba/species/maps/NOWA.htm.

Yong, W., D. Finch, F. Moore, and J. Kelly. 1998. Stopover ecology and habitat use of migratory Wilson’s warblers. Auk 115:829-842.

Yong, W., and F. R. Moore. 1993. Relation between Migratory Activity and Energetic Condition among Thrushes (Turdinae) Following Passage across the Gulf of Mexico. The Condor 95:934-943.

44 Table 2.1. Competing models examining the influence of ordinal date, energetic condition, sex, release point habitat (upland [R1 and R2] or bottomland [R3 and R4]), and year on day 1 movement rates of Northern Waterthrushes experimentally translocated to 4 forested release points at Trempealeau National Wildlife Refuge, Wisconsin in April-May 2009-2010. I ranked 32 candidate models by AICc. Bold text indicates the models with the most support.

Model K AICc ΔAICc wi Date + Condition + Sex + Release 6 30.8 0.0 0.43 Condition + Sex + Release 5 32.1 1.3 0.23 Date + Condition + Sex + Release + Year 7 33.9 3.0 0.10 Condition + Sex + Release + Year 6 34.3 3.5 0.08 Date + Condition + Sex 5 34.8 4.0 0.06 Condition + Sex 4 36.2 5.3 0.03 Date + Sex + Release 5 36.3 5.5 0.03 Date + Condition + Sex + Year 6 37.7 6.9 0.01 Condition + Sex + Year 5 38.4 7.6 0.01 Sex + Release 4 38.5 7.7 0.01 Date + Sex + Release + Year 6 39.2 8.4 0.01 Date + Sex 4 40.3 9.5 0.00 Sex + Release + Year 5 41.2 10.4 0.00 Sex 3 42.7 11.9 0.00 Date + Sex + Year 5 42.9 12.1 0.00 Sex + Year 4 45.3 14.5 0.00 Date + Condition + Release 5 49.2 18.4 0.00 Date + Condition + Release + Year 6 52.1 21.2 0.00 Date + Release 4 53.9 23.1 0.00 Date + Condition 4 54.0 23.1 0.00 Condition + Release 4 54.5 23.7 0.00 Date + Release + Year 5 56.0 25.2 0.00 Date + Condition + Year 5 56.5 25.7 0.00 Condition + Release + Year 5 57.3 26.4 0.00 Date 3 58.9 28.0 0.00 Release 3 59.1 28.3 0.00 Condition 3 59.3 28.4 0.00 Date + Year 4 60.5 29.7 0.00 Release + Year 4 61.7 30.8 0.00 Condition + Year 4 61.9 31.0 0.00 null 2 64.3 33.4 0.00 Year 3 66.5 35.7 0.00

45 Table 2.2. Competing models examining the influence of ordinal date, energetic condition, sex, release point habitat (upland [R1 and R2] or bottomland [R3 and R4]), and year on day 2 movement rates of Northern Waterthrushes experimentally translocated to 4 forested release points at Trempealeau National Wildlife Refuge, Wisconsin in April-May 2009-2010. I ranked 32 candidate models by AICc. Bold text indicates the models with the most support.

Model K AICc ΔAICc wi Sex 3 39.3 0.0 0.23 Sex + Year 4 39.3 0.0 0.22 Sex + Release + Year 5 41.1 1.8 0.09 Sex + Release 4 41.4 2.1 0.08 Condition + Sex 4 41.5 2.2 0.08 Date + Sex 4 41.9 2.6 0.06 Condition + Sex + Year 5 42.0 2.7 0.06 Date + Sex + Year 5 42.0 2.7 0.06 Condition + Sex + Release 5 43.8 4.5 0.02 Condition + Sex + Release + Year 6 44.0 4.7 0.02 Date + Sex + Release + Year 6 44.0 4.7 0.02 Date + Sex + Release 5 44.3 5.0 0.02 Date + Condition + Sex 5 44.3 5.0 0.02 Date + Condition + Sex + Year 6 45.0 5.7 0.01 Date + Condition + Sex + Release 6 46.8 7.5 0.01 Date + Condition + Sex + Release + Year 7 47.3 8.0 0.00 Date + Release 4 81.5 42.2 0.00 Date 3 82.2 42.9 0.00 null 2 83.0 43.6 0.00 Release 3 83.2 43.9 0.00 Date + Condition + Release 5 83.9 44.6 0.00 Date + Release + Year 5 84.3 45.0 0.00 Date + Condition 4 84.5 45.2 0.00 Date + Year 4 84.8 45.4 0.00 Condition 3 85.3 46.0 0.00 Year 3 85.4 46.1 0.00 Condition + Release 4 85.7 46.4 0.00 Release + Year 4 85.8 46.5 0.00 Date + Condition + Release + Year 6 86.8 47.5 0.00 Date + Condition + Year 5 87.1 47.8 0.00 Condition + Year 4 87.9 48.6 0.00 Condition + Release + Year 5 88.6 49.3 0.00

46 Table 2.3. Competing models examining the influence of ordinal date, energetic condition, sex, release point habitat (upland [R1 and R2] or bottomland [R3 and R4]), and year on day 1 displacement of Northern Waterthrushes experimentally translocated to 4 forested release points at Trempealeau National Wildlife Refuge, Wisconsin in April-May 2009-2010. I ranked 32 candidate models by AICc. Bold text indicates the models with the most support.

Model K AICc ΔAICc wi Sex + Release 4 62.9 0.0 0.38 Date + Sex + Release 5 64.0 1.1 0.22 Condition + Sex + Release 5 65.0 2.1 0.13 Sex + Release + Year 5 65.5 2.6 0.10 Date + Condition + Sex + Release 6 66.6 3.7 0.06 Date + Sex + Release + Year 6 66.9 4.0 0.05 Condition + Sex + Release + Year 6 67.6 4.7 0.04 Date + Condition + Sex + Release + Year 7 69.7 6.8 0.01 Sex 3 79.1 16.2 0.00 Date + Release 4 79.8 16.9 0.00 Date + Sex 4 80.0 17.1 0.00 Condition + Sex 4 80.5 17.6 0.00 Date + Release + Year 5 80.9 18.0 0.00 Sex + Year 4 81.7 18.8 0.00 Date + Condition + Sex 5 81.9 19.0 0.00 Date + Condition + Release 5 82.3 19.4 0.00 Date + Sex + Year 5 82.7 19.8 0.00 Release 3 82.9 20.0 0.00 Condition + Sex + Year 5 83.1 20.2 0.00 Release + Year 4 83.2 20.3 0.00 Date + Condition + Release + Year 6 83.4 20.5 0.00 Date + Condition + Sex + Year 6 84.9 22.0 0.00 Condition + Release + Year 5 85.1 22.2 0.00 Condition + Release 4 85.1 22.2 0.00 Date 3 94.6 31.7 0.00 Date + Condition 4 96.6 33.7 0.00 Date + Year 4 96.8 33.9 0.00 null 2 97.4 34.5 0.00 Date + Condition + Year 5 98.7 35.8 0.00 Condition 3 98.9 36.0 0.00 Year 3 98.9 36.0 0.00 Condition + Year 4 100.2 37.3 0.00

47 Table 2.4. Competing models examining the influence of ordinal date, energetic condition, sex, release point habitat (upland [R1 and R2] or bottomland [R3 and R4]), and year on day 2 displacement of Northern Waterthrushes experimentally translocated to 4 forested release points at Trempealeau National Wildlife Refuge, Wisconsin in April-May 2009-2010. I ranked 32 candidate models by AICc. Bold text indicates the model with the most support.

Model K AICc ΔAICc wi Sex + Year 4 73.8 0.0 0.46 Condition + Sex + Year 5 76.3 2.5 0.13 Date + Sex + Year 5 76.3 2.6 0.13 Sex + Release + Year 5 76.7 2.9 0.11 Date + Condition + Sex + Year 6 78.8 5.0 0.04 Sex 3 78.8 5.1 0.04 Condition + Sex + Release + Year 6 79.4 5.7 0.03 Date + Sex + Release + Year 6 79.5 5.7 0.03 Date + Sex 4 81.2 7.5 0.01 Sex + Release 4 81.4 7.7 0.01 Condition + Sex 4 81.5 7.7 0.01 Date + Condition + Sex + Release + Year 7 82.2 8.4 0.01 Date + Sex + Release 5 84.1 10.3 0.00 Date + Condition + Sex 5 84.1 10.4 0.00 Condition + Sex + Release 5 84.3 10.6 0.00 Date + Condition + Sex + Release 6 87.2 13.5 0.00 Year 3 103.5 29.7 0.00 null 2 104.6 30.8 0.00 Date + Year 4 105.9 32.2 0.00 Condition + Year 4 106.1 32.3 0.00 Release + Year 4 106.1 32.3 0.00 Date 3 106.3 32.5 0.00 Condition 3 107.1 33.3 0.00 Release 3 107.1 33.3 0.00 Date + Release + Year 5 108.8 35.0 0.00 Date + Condition + Year 5 108.8 35.0 0.00 Date + Condition 4 108.9 35.1 0.00 Condition + Release + Year 5 108.9 35.2 0.00 Date + Release 4 109.0 35.2 0.00 Condition + Release 4 109.7 36.0 0.00 Date + Condition + Release 5 111.8 38.0 0.00 Date + Condition + Release + Year 6 111.9 38.1 0.00

48 Table 2.5. Competing models examining the influence of ordinal date, energetic condition, sex, release point habitat (upland [R1 and R2] or bottomland [R3 and R4]), and year on day 1 linearity of Northern Waterthrushes experimentally translocated to 4 forested release points at Trempealeau National Wildlife Refuge, Wisconsin in April-May 2009-2010. I ranked 32 candidate models by AICc. Bold text indicates the models with the most support.

Model K AICc ΔAICc wi Sex + Release 4 56.6 0.0 0.44 Condition + Sex + Release 5 58.4 1.8 0.18 Sex + Release + Year 5 59.1 2.5 0.13 Date + Sex + Release 5 59.4 2.8 0.11 Condition + Sex + Release + Year 6 61.2 4.6 0.04 Date + Condition + Sex + Release 6 61.3 4.7 0.04 Date + Sex + Release + Year 6 62.1 5.5 0.03 Date + Condition + Sex + Release + Year 7 64.4 7.8 0.01 Sex 3 65.2 8.6 0.01 Date + Sex 4 67.6 11.0 0.00 Condition + Sex 4 67.7 11.0 0.00 Sex + Year 4 67.7 11.1 0.00 Date + Condition + Sex 5 70.2 13.6 0.00 Date + Sex + Year 5 70.3 13.7 0.00 Condition + Sex + Year 5 70.4 13.8 0.00 Release + Year 4 71.2 14.6 0.00 Condition + Release + Year 5 73.0 16.4 0.00 Release 3 73.1 16.4 0.00 Date + Condition + Sex + Year 6 73.1 16.5 0.00 Date + Release + Year 5 73.9 17.3 0.00 Condition + Release 4 74.1 17.4 0.00 Date + Release 4 75.4 18.8 0.00 Date + Condition + Release + Year 6 75.9 19.3 0.00 Date + Condition + Release 5 76.5 19.9 0.00 Year 3 79.0 22.4 0.00 null 2 79.2 22.6 0.00 Condition 3 81.1 24.5 0.00 Date 3 81.2 24.5 0.00 Condition + Year 4 81.3 24.7 0.00 Date + Year 4 81.3 24.7 0.00 Date + Condition 4 83.0 26.4 0.00 Date + Condition + Year 5 83.8 27.2 0.00

49 Table 2.6. Competing models examining the influence of ordinal date, energetic condition, sex, release point habitat (upland [R1 and R2] or bottomland [R3 and R4]), and year on day 2 linearity of Northern Waterthrushes experimentally translocated to 4 forested release points at Trempealeau National Wildlife Refuge, Wisconsin in April-May 2009-2010. I ranked 32 candidate models by AICc. Bold text indicates the models with the most support.

Model K AICc ΔAICc wi Sex + Year 4 63.6 0.0 0.40 Condition + Sex + Year 5 65.4 1.8 0.16 Date + Sex + Year 5 66.1 2.5 0.12 Sex + Release + Year 5 66.3 2.7 0.10 Date + Condition + Sex + Year 6 67.5 3.9 0.06 Sex 3 68.3 4.7 0.04 Condition + Sex + Release + Year 6 68.4 4.8 0.04 Date + Sex + Release + Year 6 69.1 5.5 0.03 Sex + Release 4 70.5 6.9 0.01 Date + Condition + Sex + Release + Year 7 70.7 7.1 0.01 Condition + Sex 4 70.8 7.2 0.01 Date + Sex 4 70.8 7.2 0.01 Condition + Sex + Release 5 73.2 9.6 0.00 Date + Sex + Release 5 73.2 9.7 0.00 Date + Condition + Sex 5 73.5 9.9 0.00 Date + Condition + Sex + Release 6 76.2 12.6 0.00 Year 3 87.9 24.3 0.00 Release + Year 4 88.8 25.2 0.00 Date + Year 4 89.6 26.0 0.00 Condition + Year 4 90.1 26.5 0.00 Date + Release + Year 5 90.3 26.7 0.00 Condition + Release + Year 5 91.2 27.6 0.00 null 2 91.4 27.9 0.00 Date + Condition + Year 5 91.7 28.1 0.00 Release 3 91.9 28.4 0.00 Date + Condition + Release + Year 6 92.6 29.0 0.00 Date 3 93.9 30.3 0.00 Condition 3 93.9 30.3 0.00 Date + Release 4 94.4 30.8 0.00 Condition + Release 4 94.6 31.0 0.00 Date + Condition 4 96.5 32.9 0.00 Date + Condition + Release 5 97.3 33.7 0.00

50 Table 2.7. Competing models examining the influence of ordinal date, energetic condition, sex, release point habitat (upland [R1 and R2] or bottomland [R3 and R4]), and year on minimum stopover duration of Northern Waterthrushes experimentally translocated to 4 forested release points at Trempealeau National Wildlife Refuge, Wisconsin in April-May 2009-2010. I ranked 32 candidate models by AICc. Bold text indicates the models with the most support.

Model K AICc ΔAICc wi Date + Condition + Sex + Release 6 92.1 0.0 0.32 Date + Condition + Sex + Release + Year 7 92.6 0.5 0.25 Date + Sex + Release 5 93.0 0.9 0.20 Date + Sex + Release + Year 6 94.3 2.2 0.10 Date + Condition + Sex 5 95.2 3.1 0.07 Date + Condition + Sex + Year 6 97.2 5.1 0.03 Date + Sex 4 97.6 5.5 0.02 Date + Sex + Year 5 100.1 8.0 0.01 Sex + Release 4 101.9 9.8 0.00 Condition + Sex + Release 5 102.3 10.1 0.00 Condition + Sex 4 102.8 10.7 0.00 Condition + Sex + Release + Year 6 103.2 11.1 0.00 Sex + Release + Year 5 103.3 11.2 0.00 Sex 3 103.8 11.7 0.00 Condition + Sex + Year 5 104.6 12.5 0.00 Sex + Year 4 106.0 13.8 0.00 Date + Condition + Release 5 124.6 32.5 0.00 Date + Condition 4 125.8 33.7 0.00 Date + Condition + Release + Year 6 126.8 34.7 0.00 Date + Condition + Year 5 128.1 36.0 0.00 Date + Release 4 128.6 36.5 0.00 Date 3 130.6 38.5 0.00 Date + Release + Year 5 131.2 39.1 0.00 Date + Year 4 133.2 41.1 0.00 Condition 3 135.3 43.2 0.00 Condition + Release 4 135.5 43.4 0.00 Condition + Year 4 137.2 45.0 0.00 Condition + Release + Year 5 137.3 45.1 0.00 Release 3 137.6 45.4 0.00 null 2 138.2 46.1 0.00 Release + Year 4 139.7 47.6 0.00 Year 3 140.4 48.3 0.00

51 Table 2.8. Variable importance in the Random Forests model of departure probability for Northern Waterthrushes. Variable importance is based on the mean decrease in the Gini index for model iterations without the variable, indicating the importance of the variable for predicting departure from the study area.

Variable name Mean decrease in GINI index Ordinal date 3.6 Mean temperature 3.55 Westerly wind component 3.52 Southerly wind component 3.22 Mean pressure 3.18 Change in pressure 2.9 Mean wind speed 1.82 Precipitation amount 0.74 Year 0.3

52 Figure 2.1. Map showing location of Trempealeau National Wildlife Refuge (U.S. Fish and Wildlife Service 2008).

53 Figure 2.2. Landcover and land use at Trempealeau National Wildlife Refuge in 1994 (U.S. Fish and Wildlife Service 2008).

54

d d e n s a u

l 3 e t a i R n

s

o . i g s t n e a i t i d N s

n u e a a s b e a l e y a l r e e a r p d

t n m s o e e r c r e o T

s f t

a a d

n ) s a a d l e p w r

( u

2 s e B e

h t

t i . s s e

r r e a e s e a w y e

l 2 h e t r R

o d b d n n n a a i

) 1 d w e R s o l u . l

0 e n 1 y o ( 0 i

t s 2 a n c n o i o i

l t

d a g e c s n o i . u l

s

d e e e n t t r i i a u s s b t

e g p y s a n r i a c a

e d l h m n e i s a r r u

b t p r

s h y e t e r r r h a t e o t d f s a n a d o W n w c

a e n l 1 s r e B m a

h

o . t s t r t e a o o g w b u

N

f

3 e

e . h B 3 t R

.

. e 2 e

r 9 f i e e 0 l r 0 d w u l

2 i g

4 i n F W i R

55 Figure 2.4. Partial plots showing how the top three weather variables indicated by the Random Forests model predicted the probability of departure in Northern Waterthrushes.

56 Chapter 3

Movement Ecology and Stopover Duration

of the Yellow-rumped Warbler (Setophaga coronata) during Spring Migration

3.1. Introduction

Migratory birds face serious challenges during migration that can result in disproportionately higher rates of mortality (Sillett and Holmes 2002) and possibly population limitation (Newton 2006). Songbirds engaged in migration spend the majority of their time and energy in stopover habitats (Wikelski et al. 2003) where they must rest and refuel between flights (Moore et al. 1995). Events during stopover can alter a migrant's time and energy budgets, and may subsequently influence reproductive output or survival during the breeding season (Harrison et al. 2011).

Following migratory flights, migrants typically land in locations not previously encountered (Catry et al. 2004). How efficiently migrants are able to explore and exploit novel environments during stopover and deposit fat stores can influence whether they arrive at the breeding grounds early enough to obtain a high quality territory and maximize the probability of successful reproduction (Aebischer et al. 1996, Lozano et al.

1996, Smith and Moore 2005). Upon arrival at a stopover site, migrants are expected to exhibit exploratory behavior, characterized by highly linear, long-distance movements

57 through the site to acquire information about resources, predators, and habitat quality

(Stamps 1995, Aborn and Moore 1997, Paxton et al. 2008). As migrants encounter suitable habitat through exploration, they are expected to settle and confine their movements to more restricted microsites to feed or rest (Aborn and Moore 1997, Paxton et al. 2008). Recent studies have found that a variety of passerine migrants show a pattern of exploration followed by settling during stopover (Aborn and Moore 1997,

Chernetsov 2005, Chernetsov and Mukhin 2006, Paxton et al. 2008, Seewagen et al.

2010).

Exploration provides a means for migrants to rapidly locate a microsite with adequate resources. However, settling into a small area may have costs, including local resource depletion by a single individual (Bibby and Green 1980), intra-specific competition (Kelly et al. 2002), or inter-specific competition (Salewski et al. 2007).

Exploration can also be costly because it is energetically expensive (Zach and Falls 1976) and may expose migrants to increased predation risk (Cimprich et al. 2005) or delay their migration timing due to lower foraging efficiency.

The typically observed pattern of exploration followed by settling during stopover may be more likely to break down in a species that is both abundant and a habitat generalist. The per capita cost of settling in a localized area may be high in numerically abundant migrants due to density-dependent resource depletion. In addition, a habitat generalist may also be less likely to benefit from habitat exploration, since locating a particular habitat type would not confer much of an advantage.

Migrants must also face the tradeoff between remaining at a current stopover site

58 and resuming migration with the possibility of encountering more suitable stopover habitat elsewhere (Charnov 1976, Jenni and Schaub 2003). How birds make decisions to optimize stopover duration is unknown (Erni et al. 2002). A variety of intrinsic (e.g. energetic condition, sex) and extrinsic (e.g. time of season, weather) factors may further drive the tradeoffs associated with habitat exploration and stopover duration (Matthews and Rodewald 2010b).

Researchers investigating the movements and stopover duration of individual migrants have faced many challenges. For example, dense vegetation and rapid movements can make small migrant passerines difficult or impossible to continuously track. Local emigration can cause measures of stopover duration based on mark- recapture to under-estimate the true length of stopover (Bächler and Schaub 2007).

Radio-telemetry, by contrast, enables recording the fine-scale movements and accurate departure date of individual migrants.

I examined fine-scale movement patterns and stopover duration of individual

“Myrtle” Yellow-rumped Warblers (Setophaga coronata coronata) during spring migratory stopover, using a translocation approach to observe how migrants respond to encountering unfamiliar environments. In addition, I examined how ordinal date, energetic condition, and sex are associated with movement metrics and stopover duration, and examined how weather variables predicted the date of departure. Understanding how intrinsic and extrinsic factors mediate exploratory movements and stopover duration in migrants will be necessary to effectively manage and restore en route habitats for migratory birds (Ewert and Hamas 1995, Buler et al. 2007).

59 3.2. Methods

Study area

I conducted this study in western Wisconsin, USA at Trempealeau National

Wildlife Refuge (NWR, N 44.05°, W 91.53°), which encompasses 2520 ha within the

Upper Mississippi River alluvial valley (Figure 3.1). The refuge includes portions of

Trempealeau and Buffalo counties, which have generally rolling terrain and are 25% and

43% forested, respectively (U.S. Fish and Wildlife Service 2008). The Mississippi River valley is 4 to 9 km wide near the refuge. The bluff faces flanking the alluvial valley support well-drained forests and steep prairies. The rolling upland hills of the Driftless

Area are characterized by a mosaic of agriculture on flatter hilltops and valleys and well- drained forests on steeper terrain. Steep, forested bluffs abut the river on the Minnesota side, whereas the former Trempealeau Prairie, now mostly agricultural land, extends between the river and the bluffs for several kilometers on the Wisconsin side.

Trempealeau NWR supports a heterogeneous mosaic of open aquatic habitats, emergent marshes, islands, shrub wetlands, and bottomland hardwood forest (Figure 3.2). Pockets of oak savanna, upland forest, and tall-grass prairie occur on sandy soil in the slightly higher elevations. Overall, the refuge exhibits much variation in hydrology, stages of forest succession, and hardness of edges. Forest cover on the refuge typically does not form discrete patches and is fragmented by natural ecotones and successional gradients, past agriculture, prairie restorations, and water bodies. Land use surrounding the refuge is primarily light residential and agricultural (U.S. Fish and Wildlife Service 2008).

60 Study species

The “Myrtle” Yellow-rumped Warbler, perhaps the most abundant parulid in the world (Dunn and Garrett 1997, Rich et al. 2004), breeds in the boreal forests of Alaska,

Canada and the northern United States and winters primarily in the southeastern United

States, Mexico, Central America, and the West Indies (Hunt and Flaspohler 1998). In the study area it occurs as an abundant non-breeding transient (Dunn and Garrett 1997) and a very rare overwintering species. Between 2000-2010, only 0.004 Yellow-rumped

Warblers per party-hour were recorded on the Winona Christmas Bird Count, which circumscribes the study area (National Audubon Society 2011). The closest confirmed breeding area to my study site is 80 km to the northeast, with no breeding records for

Trempealeau or Buffalo counties (Wisconsin Breeding Bird Atlas 2003). During the breeding season the Yellow-rumped Warbler nests in mature coniferous and mixed boreal forests, and during winter it occurs in a variety of different habitats (Hunt and Flaspohler

1998). During spring this species migrates primarily nocturnally (Hunt and Flaspohler

1998) and occurs abundantly in many different stopover habitats (Parnell 1969).

Foraging behavior of this generalist parulid may be more varied than in any other warbler

(Dunn and Garrett 1997); it is at least partially frugivorous during fall and winter, but during spring and summer it consumes mostly insects and other small invertebrates (Hunt and Flaspohler 1998).

61 Capture and processing of focal individuals

I passively mist-netted transient Yellow-rumped Warblers during mid-April to late

May 2009 and 2010 between 06:50 and 11:50. When personnel were available for radio tracking, I selected the most recently captured Yellow-rumped Warbler as a focal individual. For each individual I measured unflattened wing chord to the nearest millimeter using a wing ruler, tarsus length to the nearest 0.1 mm using calipers, mass to the nearest 0.1 g using a digital scale, and visible fat on a scale of 0-7 (DeSante et al.

2011). I banded each individual with a U.S. Geological Survey aluminum leg band and a unique combination of darvic plastic colored leg bands. I sexed individuals in the hand using plumage criteria (Pyle 1997) and photographed each individual. I placed each focal individual into a cloth bag during the translocation process after processing at the banding station.

Translocation and radio-tagging

I translocated all birds so that upon release, each would presumably be forced to explore habitat not previously encountered. Although releasing non-translocated

“control” birds at the capture site can be conceptually attractive (Matthews and Rodewald

2010a), birds' arrival dates were unknown and releasing birds at the capture location would not have controlled for differences in knowledge of the habitat surrounding the capture site. I released birds at 3 forested sites which included a range of forested habitats available in the study area. The release sites were 0.7 to 2.2 km from the banding sites (Figure 3.3). I randomly assigned birds to these release sites while

62 maintaining balanced sample sizes at each site, releasing no more than one individual

Yellow-rumped Warbler per day at a release site.

I translocated birds via automobile to within 200 m of the release site and verified that the focal individual was not stressed (e.g., bill open, eyelids partly shut, less alert) before proceeding with radio-transmitter attachment. I attached a radio-transmitter to back feathers using LashGrip eyelash cement (Kenward 2001). I fitted Yellow-rumped

Warblers with a 0.39 g Holohil Systems transmitter (BD-2N). The transmitters were

3.3% of the lean body mass (11.7 g) of Yellow-rumped Warbler. After attachment I placed a cloth bag over my hand gripping the bird and walked the remaining distance to the release point. Upon arrival at the release point, I randomly oriented the bird so that microhabitat features at the release point would not cause systematic bias in the initial flight direction and behavior of the bird upon release. I oriented each bird at a random compass direction and a random distance between 0 and 50 meters from the release point prior to removing the bag and releasing the bird. Time elapsed between capture and release averaged 40 min (range of 22 to 66 min) for 29 of 30 birds but was 103 min for 1 bird.

Radio telemetry

Movement ecology is increasingly gaining recognition as a key component of the biology of all organisms (Nathan et al. 2008). In avian movement ecology, radio- telemetry has enjoyed a long and productive history (Cochran et al. 1967) of use and wide acceptance for study of small birds during the migratory period (Wikelski et al.

63 2003, Robinson et al. 2010, Whitaker and Warkentin 2010). Although transmitters can sometimes affect the behavior of animals (Millspaugh and Marzluff 2001, Barron et al.

2010), radio-telemetry remains the only way to accurately determine fine-scale movement and stopover duration of small migratory songbirds (Bächler and Schaub

2007). Moreover, a number of studies on passerines have found no adverse effects of transmitters on avian behavior. Wood Thrushes (Hylocichla mustelina) carrying transmitters weighing 4% of body mass showed no decrease in return rates or body mass compared to banded-only birds (Powell et al. 1998). Female Hooded Warblers

(Setophaga citrina) carrying radio-transmitters and harnesses weighing 7% to 8.5% of body mass showed equal nest provisioning rates, brooding time, and time spent perched on the edge of the nest as untagged birds (Neudorf and Pitcher 1997). In my study,

Yellow-rumped Warblers with radio-tags appeared to flock with conspecifics and forage normally. Most importantly, all individuals received the same radio-transmitter treatment, so any differences observed in movement behavior and stopover duration among individuals should not be attributable to the presence of radio-transmitters.

I radio-located birds every 30 min until 20:00 on the day of release and every 30 min from 06:00 to 20:00 on the day after release to investigate fine-scale movement patterns of birds soon after encountering unfamiliar environments. Since birds were often hidden by vegetation and direct observation was difficult, I approached as closely as possible without disturbing the bird (to 25 m unless the bird was high in the canopy) and located the individuals via homing (White and Garrott 1990) using a R4000 receiver

(Advanced Telemetry Systems, Isanti, MN ) and a 3-element Yagi antenna. I marked the

64 observer location with a GPS (Garmin, Olathe, KS) to a precision of 0.00001 latitude/longitude degrees and recorded the estimated distance and bearing from this point to the bird (Smith et al. 2010).

After the first 2 days of radio tracking, I verified that each bird remained in the study area twice per day in 2009 and once per day in 2010. I searched daily for radio frequencies of departed birds using ground-based radio-telemetry. Additionally, I overflew the study area in a small airplane 1-2 times per week to search for radio frequencies of birds presumed to have departed from the study area. If a radio frequency was not detected for 7 days, I assumed the bird had departed on migration on the night following the last detection. I removed birds from movement analyses if the transmitter detached during the first 2 days of tracking; I omitted birds from analyses of stopover duration if the transmitter detached at any time during stopover. The manufacturer- specified nominal battery life for the transmitters was 12 days, with a range of 8-15 days.

Movement characteristics and home range estimation

I excluded 1 bird from movement analyses due to failure of receiving equipment,

1 bird because its radio-transmitter detached on the day of release, and 1 bird because it was depredated within seconds of release by a Sharp-shinned Hawk (Accipiter striatus).

Individual relocation points were excluded if time/location data were missing or if the bird was more than 100 m from the observer at the time the location was recorded. I considered daily movement data complete if gaps in tracking data did not exceed 2 hours and at least 10 relocation points were present, which is consistent with the number of

65 daily radio locations used in other studies (Paxton et al. 2008, Seewagen et al. 2010).

I calculated measures of movement following Aborn and Moore (1997), Paxton et al. (2008), and Seewagen et al. (2010). I calculated daily movement rate (m/hr) by dividing total distance moved (sum of distances between all successive movements) by the length of time radio-tracked. I calculated daily displacement by determining the straight-line distance between the first point and the last point on a given day. I calculated daily linearity by dividing displacement by the total distance moved.

I used Home Range Tools (Rodgers et al. 2007) in ArcMap (ESRI 2011) to estimate fixed-kernel home range size for all birds (n = 16) radio-tracked for at least 2 days and with ≥ 10 locations per day (Seewagen et al. 2010). I calculated home ranges using 50, 90, and 95% isopleths using Href smoothing parameters. Isopleth areas were strongly negatively correlated with the original sample size (Seaman et al. 1999), indicating significant temporal autocorrelation between successive locations (Swihart and

Slade 1985). Swihart and Slade (1985) described how to determine time to independence among successive locations, but such methods assume a constant center of movement activity, an assumption unlikely met by migrants during stopover (Whitaker and

Warkentin 2010). Nonetheless, I still present kernel isopleth results here for general descriptive and comparative purposes following Buler (2006), Chernetsov and Mukhin

(2006), and Seewagen et al. (2010).

66 Energetic condition

To obtain an index of energetic condition, I computed the first principal component of unflattened wing chord (mm) and tarsus length (mm) as an index of body size. I calculated energetic condition index as the residuals of a linear regression of bird mass (g) on the body size index. I made these calculations using program R (R

Development Core Team 2011). The energetic condition index was strongly positively correlated with scores of visible fat deposits (regression, p < 10-4).

Statistical analyses

I used a model-selection procedure to determine the variables most closely associated with stopover duration, daily movement rate, daily displacement, and daily linearity. I selected 32 candidate models a priori. These models included the explanatory variables ordinal date, energetic condition, sex, year, and release point. The models included a null model, a saturated model (all 5 variables), and 30 other models comprising all possible combinations of the 5 variables. I fitted generalized linear models in program R (R Development Core Team 2011) and ranked them in package bbmle using Akaike's information criterion with a correction for small sample size (AICc)

(Anderson and Burnham 2002). I fitted these models to the log-transformed response variables movement rate, displacement, and linearity, and the untransformed response variable stopover duration. I considered the model with the lowest AICc value to be the best and models with ΔAICc < 2 as equally supported given the data (Anderson and

Burnham 2002). For response variables with models that were equally competitive, I

67 obtained averaged parameter estimates and standard errors by calculating a weighted average of the parameter estimates and standard errors for all best-ranked models and normalizing according to the total weight of all best-ranked models. When the confidence interval for a parameter overlapped with zero, I considered that parameter uninformative.

To examine the influence of weather on departure, I obtained quality-controlled weather data (National Climatic Data Center 2011) for the Winona Municipal Airport, located 7 to 16 km from stopover locations of focal birds. I aggregated weather data from the end of astronomical twilight in the evening to the beginning of astronomical twilight in the morning to create nightly weather variables. I used Random Forests (an extension of classification trees, Cutler et al. 2007) to examine how departure decisions were predicted by a suite of nightly weather variables (mean barometric pressure, change in barometric pressure, mean temperature, mean southerly component wind speed, mean westerly component wind speed, and total precipitation). I evaluated the importance of each variable in predicting departure decisions by calculating the mean decrease in the

Gini index (a splitting criterion for classification trees), with and without permuting the variable of interest (Breiman et al. 1984).

3.3. Results

I radio-tracked 30 Yellow-rumped Warblers (15 females and 15 males) during spring 2009-2010. In 2009 I tracked 13 birds (4 females and 9 males) between April 18

68 and May 18. In 2010 I tracked 17 birds (11 females and 6 males) between April 25 and

May 11. My two-year dataset included 1139 radio-locations averaging 38 locations per individual. Complete daily movement data were available for 21 birds for day 1, 11 birds for day 2, 24 birds on at least 1 day, and 8 birds for both days. The sample size was considerably lower on day 2 than day 1 because 7 birds initiated a migratory flight the night after release and 1 additional bird departed the study area the night after release or early in the morning on day 2.

Home range size varied greatly by individual and by the size of the isopleth used.

At 95% the median home range size was 121 ha (range of 27 to 1389 ha). At 90% the median home range size was 85 ha (range of 21 to 1120 ha). At 50% the median home range size was 24 ha (range of 6 to 342 ha).

The average daily movement rate of Yellow-rumped Warblers was 157 ± 54 m/hr

(mean ± sd) during the first two days after release (n = 8). Average daily displacement, which describes the distance between a bird's first location of the day and its location at

20:00, was 511 ± 269 m (mean ± sd). Average daily linearity, with 0 reflecting meandering movements and 1 reflecting a perfectly linear movement, was 0.31 ± 0.13

(mean ± sd). Neither average daily movement rate (p = 0.91), average daily displacement

(p = 0.74), nor linearity index (p = 0.93) changed over the course of the migratory season

(regressions, n = 8). Energetic condition at capture also did not change over the course of the season (regression, n = 30, p = 0.79).

Individual Yellow-rumped Warblers showed no difference between the first and second days after release for any of the 3 movement metrics I calculated (paired t-tests, n

69 = 8). Median movement rate was 150 m/hr on day 1 and 155 m/hr on day 2 (p = 0.48).

Median displacement was 497 m on day 1 and 415 m on day 2 (p = 0.40). The median linearity was 0.29 on day 1 and 0.27 on day 2 (p = 0.21).

Competing models revealed that date, condition, sex, release point, and year, and combinations of these variables explained no more variation in daily movement metrics of Yellow-rumped Warblers for day 1 (n = 21) and day 2 (n = 11) than the null model

(Tables 3.1-3.6).

Minimum stopover duration for Yellow-rumped Warblers was 4.0 ± 0.5 d (n = 25, mean ± se). The two top-ranked models describing stopover duration (Table 3.7) encompassed the majority of the model weight (w1 to 2 = 0.51) and indicated that energetic condition (β = -0.402 ± 0.160 se) was negatively related to stopover duration. After controlling for energetic condition, ordinal date was positively correlated with stopover duration (β = 0.014 ± 0.012 se).

During spring 2009-2010, there were 26 nights when at least one radio-tagged

Yellow-rumped Warbler remained in the study area or departed on a migratory flight.

The Random Forests model correctly classified 58% of nights as departure or non- departure nights. The top 3 variables in the model indicated a higher probability of departure on nights with decreasing barometric pressure, a more southerly wind component, and a lower mean temperature (Table 3.8, Figure 3.4). Although energetic condition at capture was not included in the model, it was not associated with ordinal date and thus should not have confounded the analysis (regression, p = 0.80).

70 3.4. Discussion

The Yellow-rumped Warblers I studied did not show a pronounced period of exploration followed by settling, unlike most other migrant songbirds studied to date. A potential explanation is that generalist Yellow-rumped Warblers find a wide diversity of stopover habitats to be suitable for foraging (Parnell 1969), so the costs of exploration outweigh the potential benefit of locating other habitats. Another possiblity is that settling in Yellow-rumped Warblers largely happened after my two-day sampling window. Regardless, the apparent consistency in movement metrics of Yellow-rumped

Warblers from day 1 to day 2 warrants further research.

The Yellow-rumped Warblers I studied were quite mobile during the first 2 days of stopover and showed a high degree of variation in their movement patterns. The average daily movement rate of 157 m/hr at my inland site is comparable to a rate of 210 m/hr rate reported for the species in a coastal Ohio stopover study (Buchanan 2008).

Assessing movement patterns of a single species across its migratory range (Buler 2006,

Seewagen et al. 2010) is important for identifying landscape-specific or region-specific en route management needs.

I detected no difference in movement patterns between fat and lean birds.

Chernetsov (2006) presented two different hypotheses to explain the relationship between a migrant's energetic condition and movement patterns during stopover. In one scenario, fat migrants use their energy stores to explore widely for food resources at a stopover site while lean birds, lacking a safety margin, settle in to the first area of possibly suitable

71 habitat they can find (Chernetsov 2006). In another scenario, lean birds are forced to forage over large areas despite increased predation risk while fat birds simply take cover awaiting favorable conditions for the next migratory flight (Chernetsov 2006). In my study, the lack of a clear relationship between energetic condition and movement patterns suggests that both scenarios may be operating simultaneously (Chernetsov 2006,

Seewagen et al. 2010).

I found no evidence of differences in movement patterns between males and females. A plausible explanation for this lack of a relationship is that Yellow-rumped

Warblers are rather social during migration and often occur in mixed-sex flocks at stopover sites. Sexes may segregate spatially within flocks, but this would not necessarily result in changes in movement patterns. Most studies to date of movement ecology during stopover have omitted sex as an explanatory variable (Seewagen et al.

2010, Matthews and Rodewald 2010a, but see Paxton et al. [2008]), despite the fact that males and females can show important differences in spatial ecology at other seasons

(Marra et al. 1993).

For a migratory songbird, deciding when to depart a stopover site is central to maintaining a successful migratory schedule (Schaub et al. 2008) because early arrival on the breeding grounds can confer reproductive advantages (Smith and Moore 2005). My results are consistent with the idea that stopover duration represents an optimization of both intrinsic and extrinsic factors. Many studies (listed in Seewagen et al. 2010, see also

Goymann et al. 2010) have identified a negative relationship between stopover duration and energetic condition, and my results for Yellow-rumped Warbler are no exception.

72 Furthermore, after controlling for sex and energetic condition, I found that stopover duration increased as the spring season progressed. This pattern is difficult to explain, but underscores the fact that spring migration is not a homogenous period; migrants may optimize stopover duration differently at different stages of the migratory period.

Weather may influence departure decisions independently of other factors. I found that departure probability in Yellow-rumped Warblers increased with weather conditions characteristic of a passing warm front, such decreasing barometric pressure and a more southerly wind vector. Taken together, these results are consistent with the idea that energetic condition and ordinal date determine the duration of stopover whereas favorable weather conditions fine-tune the precise date of departure (Matthews and

Rodewald 2010b).

Understanding the stopover ecology of migratory birds is an essential part of any holistic strategy for their conservation. As more data become available, land managers will need to consider spatial behaviors such as exploration when designing and implementing conservation plans for migrant birds en route. Further, the fact that energetic condition was closely tied to stopover duration in Yellow-rumped Warblers, which in turn can influence arrival timing and reproductive success on the breeding grounds, emphasizes the importance of conserving high quality stopover habitats for migratory birds.

73 3.5. References

Aborn, D. A., and F. R. Moore. 1997. Pattern of movement by Summer Tanagers (Piranga rubra) during migratory stopover: A telemetry study. Behaviour 134:1077-1100.

Aebischer, A., N. Perrin, M. Krieg, J. Studer, and D. R. Meyer. 1996. The role of territory choice, mate choice and arrival date on breeding success in the Savi’s Warbler Locustella luscinioides. Journal of Avian Biology 27:143-152.

Anderson, D. R., and K. P. Burnham. 2002. Model selection and multimodel inference : A practical information-theoretic approach. Springer, New York.

Bächler, E., and M. Schaub. 2007. The effects of permanent local emigration and encounter technique on stopover duration estimates as revealed by telemetry and mark-recapture. Condor 109:142-154.

Barron, D. G., J. D. Brawn, and P. J. Weatherhead. 2010. Meta-analysis of transmitter effects on avian behaviour and ecology. Methods in Ecology and Evolution 1:180- 187.

Bibby, C., and R. Green. 1980. Foraging behavior of migrant Pied Flycatchers, Ficedula hypoleuca, on temporary territories. Journal of Animal Ecology 49:507-521.

Breiman, L., J. H. Friedman, R. A. Olshen, and C. J. Stone. 1984. Classification and regression trees. Wadsworth and Brooks/Cole, Monterey, CA.

Buchanan, A. A. 2008. Movements, Habitat Use, and Stopover Duration of Migratory Songbirds in the Western Lake Erie Basin of Northern Ohio. Master’s Thesis, The Ohio State University.

Buler, J. J. 2006. Understanding habitat use by landbirds during migration along the Mississippi Gulf Coast using a scale-dependent approach. Ph.D. Dissertation, University of Southern Mississippi.

Buler, J. J., F. R. Moore, and S. Woltmann. 2007. A multi-scale examination of stopover habitat use by birds. Ecology 88:1789-1802.

Catry, P., V. Encarnação, A. Araújo, P. Fearon, A. Fearon, M. Armelin, and P. Delaloye. 2004. Are long-distance migrant passerines faithful to their stopover sites? Journal of Avian Biology 35:170-181.

74 Charnov, E. L. 1976. Optimal foraging, the marginal value theorem. Theoretical Population Biology 9:129-136.

Chernetsov, N. 2005. Spatial behavior of medium and long-distance migrants at stopovers studied by radio tracking. Annals of the New York Academy of Sciences 1046:242- 252.

Chernetsov, N. 2006. Habitat selection by nocturnal passerine migrants en route: mechanisms and results. Journal of Ornithology 147:185-191.

Chernetsov, N., and A. Mukhin. 2006. Spatial behavior of European Robins during migratory stopovers: A telemetry study. Wilson Journal of Ornithology 118:364- 373.

Cimprich, D. A., M. S. Woodrey, and F. R. Moore. 2005. Passerine migrants respond to variation in predation risk during stopover. Animal Behaviour 69:1173-1179.

Cochran, W. W., G. G. Montgomery, and R. R. Graber. 1967. Migratory Flights of Hylocichla Thrushes in Spring: A Radiotelemetry Study. The Living Bird 6:213- 225.

Cutler, D. R., T. C. Edwards, K. H. Beard, A. Cutler, K. T. Hess, J. Gibson, and J. J. Lawler. 2007. Random forests for classification in ecology. Ecology 88:2783- 2792.

DeSante, D. F., K. M. Burton, P. Velez, D. Froehlich, and D. Kaschube. 2011. MAPS Manual. Institute for Bird Populations.

Dunn, J. L., and K. L. Garrett. 1997. A field guide to warblers of North America. Houghton Mifflin Company, Boston and New York.

Erni, B., F. Liechti, and B. Bruderer. 2002. Stopover strategies in passerine bird migration: A simulation study. Journal of Theoretical Biology 219:479-493.

ESRI. 2011. ArcMap 9.3. Environmental Systems Research Institute, Redlands, CA.

Ewert, D. N., and M. J. Hamas. 1995. Ecology of migratory landbirds during migration in the midwest. Pages 200-208 in F. R. I. Thompson, editor. Management of midwestern landscapes for the conservation of neotropical migratory birds. North Central Forest Experiment Station USDA Forest Service, Detroit, MI. Retrieved from http://www.nrs.fs.fed.us/pubs/gtr/gtr_nc187.pdf.

75 Goymann, W., F. Spina, A. Ferri, and L. Fusani. 2010. Body fat influences departure from stopover sites in migratory birds: evidence from whole-island telemetry. Biology Letters 6:478 -481.

Harrison, X. A., J. D. Blount, R. Inger, D. R. Norris, and S. Bearhop. 2011. Carry-over effects as drivers of fitness differences in animals. Journal of Animal Ecology 80:4-18.

Hunt, P. D., and D. J. Flaspohler. 1998. Yellow-rumped Warbler (Dendroica coronata). Page in A. Poole, editor. The Birds of North America Online. Cornell Lab of Ornithology, Ithaca, NY. Retrieved from http://bna.birds.cornell.edu.bnaproxy.birds.cornell.edu/bna/species/376.

Jenni, L., and M. Schaub. 2003. Behavioural and physiological reactions to environmental variation in bird migration: A review. Pages 155-171 in P. Berthold, E. Gwinner, and E. Sonnenschein, editors. Avian Migration. Springer- Verlag, Berlin and Heidelberg.

Kelly, J. F., L. S. DeLay, and D. M. Finch. 2002. Density-dependent mass gain by Wilson’s Warblers during stopover. Auk 119:210-213.

Kenward, R. 2001. A manual for wildlife radio tagging. Academic Press, San Diego, CA; London.

Lozano, G. A., S. Perreault, and R. E. Lemon. 1996. Age, arrival date and reproductive success of male American Redstarts Setophaga ruticilla. Journal of Avian Biology 27:164-170.

Marra, P. P., T. W. Sherry, and R. T. Holmes. 1993. Territorial Exclusion by a Long- Distance Migrant Warbler in Jamaica: A Removal Experiment with American Redstarts (Setophaga ruticilla). The Auk 110:565-572.

Matthews, S. N., and P. G. Rodewald. 2010a. Movement behaviour of a forest songbird in an urbanized landscape: the relative importance of patch-level effects and body condition during migratory stopover. Landscape Ecology 25:955-965.

Matthews, S. N., and P. G. Rodewald. 2010b. Urban forest patches and stopover duration of migratory Swainson’s Thrushes. Condor 112:96-104.

Millspaugh, J. J., and J. M. Marzluff. 2001. Radio tracking and animal populations. Academic Press, San Diego.

76 Moore, F. R., S. A. Gauthreaux, P. Kerlinger, and T. R. Simons. 1995. Habitat requirements during migration: important link in conservation. Pages 121-144 in T. E. Martin and D. M. Finch, editors. Ecology and management of neotropical migratory birds: A synthesis and review of critical issues. Oxford University Press, New York.

Nathan, R., W. M. Getz, E. Revilla, M. Holyoak, R. Kadmon, D. Saltz, and P. E. Smouse. 2008. A movement ecology paradigm for unifying organismal movement research. Proceedings of the National Academy of Sciences 105:19052 -19059.

National Audubon Society. 2011. CBC Historical Results Count Table. Retrieved from http://audubon2.org/cbchist/count_table.html.

National Climatic Data Center. 2011. National Climatic Data Center. Retrieved March 24, 2011, from http://www.ncdc.noaa.gov/oa/ncdc.html.

Neudorf, D. L., and T. E. Pitcher. 1997. Radio transmitters do not affect nestling feeding rates by female Hooded Warblers. Journal of Field Ornithology 68:64-68.

Newton, I. 2006. Can conditions experienced during migration limit the population levels of birds? Journal of Ornithology 147:146-166.

Parnell, J. F. 1969. Habitat relations of the Parulidae during spring migration. Auk 86:505-521.

Paxton, K. L., C. Van Riper III, and C. O’Brien. 2008. Movement patterns and stopover ecology of Wilson’s Warblers during spring migration on the Lower Colorado River in southwestern Arizona. Condor 110:672-681.

Powell, L. A., D. G. Krementz, Jason D. Lang, and M. J. Conroy. 1998. Effects of radio transmitters on migrating Wood Thrushes. Journal of Field Ornithology 69:306- 315.

Pyle, P. 1997. Identification guide to North American birds, Part I. Slate Creek Press, Bolinas, California.

R Development Core Team. 2011. R: A language andenvironment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.

77 Rich, T. D., C. J. Beardmore, H. Berlanga, P. J. Blancher, M. S. W. Bradstreet, G. S. Butcher, D. W. Demarest, E. H. Dunn, W. C. Hunter, E. E. Iñigo-Elias, J. A. Kennedy, A. M. Martell, A. O. Panjabi, D. N. Pashley, K. V. Rosenberg, C. M. Rustay, J. S. Wendt, and T. C. Will. 2004. Partners in Flight North American Landbird Conservation Plan. Retrieved from http://www.partnersinflight.org/cont_plan/default.htm.

Robinson, W. D., M. S. Bowlin, I. Bisson, J. Shamoun-Baranes, K. Thorup, R. H. Diehl, T. H. Kunz, S. Mabey, and D. W. Winkler. 2010. Integrating concepts and technologies to advance the study of bird migration. Frontiers in Ecology and the Environment 8:354-361.

Rodgers, A. R., A. P. Carr, H. L. Beyer, L. Smith, and J. G. Kie. 2007. HRT: Home Range Tools for ArcGIS. Version 1.1. Ontario Ministry of Natural Resources, Centre for Northern Forest Ecosystem Research, Thunder Bay, Ontario, Canada.

Salewski, V., B. Almasi, A. Heuman, M. Thoma, and A. Schlageter. 2007. Agonistic behaviour of Palaearctic passerine migrants at a stopover site suggests interference competition. Ostrich 78:349-355.

Schaub, M., L. Jenni, and F. Bairlein. 2008. Fuel stores, fuel accumulation, and the decision to depart from a migration stopover site. Behavioral Ecology 19:657- 666.

Seaman, D. E., J. J. Millspaugh, B. J. Kernohan, G. C. Brundige, K. J. Raedeke, and R. A. Gitzen. 1999. Effects of sample size on kernel home range estimates. Journal of Wildlife Management 63:739-747.

Seewagen, C. L., E. J. Slayton, and C. G. Guglielmo. 2010. Passerine migrant stopover duration and spatial behaviour at an urban stopover site. Acta Oecologica 36:484- 492.

Sillett, T. S., and R. T. Holmes. 2002. Variation in survivorship of a migratory songbird throughout its annual cycle. Journal of Animal Ecology 71:296-308.

Smith, J. A. M., L. R. Reitsma, and P. P. Marra. 2010. Moisture as a determinant of habitat quality for a nonbreeding Neotropical migratory songbird. Ecology 91:2874-2882.

Smith, R. J., and F. R. Moore. 2005. Arrival timing and seasonal reproductive performance in a long-distance migratory landbird. Behavioral Ecology and Sociobiology 57:231-239.

78 Stamps, J. 1995. Motor Learning and the Value of Familiar Space. The American Naturalist 146:41-58.

Swihart, R. K., and N. A. Slade. 1985. Testing for independence of observations in animal movements. Ecology 66:1176-1184.

U.S. Fish and Wildlife Service. 2008. Trempealeau National Wildlife Refuge Comprehensive Conservation Plan.

Whitaker, D. M., and I. G. Warkentin. 2010. Spatial Ecology of Migratory Passerines on Temperate and Boreal Forest Breeding Grounds. The Auk 127:471-484.

White, G. C., and R. A. Garrott. 1990. Analysis of wildlife radio-tracking data. Academic Press, San Diego, CA.

Wikelski, M., E. M. Tarlow, A. Raim, R. H. Diehl, R. P. Larkin, and G. H. Visser. 2003. Avian metabolism: Costs of migration in free-flying songbirds. Nature 423:704.

Wisconsin Breeding Bird Atlas. 2003. WBBA Yellow-rumped Warbler Map. Retrieved from http://www.uwgb.edu/birds/wbba/species/maps/YRWA.htm.

Zach, R., and J. B. Falls. 1976. Foraging behavior, learning, and exploration by captive ovenbirds (Aves: Parulidae). Canadian Journal of Zoology 54:1880-1893.

79 Table 3.1. Competing models examining the influence of ordinal date, energetic condition, sex, release point (R1, R2, or R3), and year on day 1 movement rates of Yellow-rumped Warblers experimentally translocated to 3 forested release points at Trempealeau National Wildlife Refuge, Wisconsin in April-May 2009-2010. I ranked 32 candidate models by AICc. Bold text indicates the models with the most support.

Model K AICc ΔAICc wi Year 3 25.9 0.0 0.24 Sex + Year 4 27.0 1.1 0.14 Sex 3 27.3 1.4 0.12 null 2 27.6 1.8 0.10 Date + Year 4 28.0 2.1 0.08 Condition + Year 4 28.9 3.0 0.05 Date + Sex + Year 5 29.1 3.2 0.05 Condition 3 30.1 4.2 0.03 Date + Sex 4 30.1 4.2 0.03 Condition + Sex + Year 5 30.2 4.3 0.03 Date 3 30.3 4.5 0.03 Condition + Sex 4 30.4 4.5 0.03 Date + Condition + Year 5 31.5 5.6 0.01 Release + Year 5 32.3 6.5 0.01 Release 4 32.4 6.5 0.01 Date + Condition + Sex + Year 6 32.8 7.0 0.01 Sex + Release 5 33.0 7.1 0.01 Date + Condition 4 33.1 7.2 0.01 Date + Condition + Sex 5 33.6 7.7 0.01 Sex + Release + Year 6 34.3 8.4 0.00 Date + Release + Year 6 35.5 9.6 0.00 Condition + Release 5 35.7 9.8 0.00 Date + Release 5 35.8 9.9 0.00 Condition + Release + Year 6 36.3 10.4 0.00 Date + Sex + Release 6 36.8 10.9 0.00 Condition + Sex + Release 6 37.0 11.1 0.00 Date + Sex + Release + Year 7 37.7 11.8 0.00 Condition + Sex + Release + Year 7 38.7 12.8 0.00 Date + Condition + Release 6 39.7 13.8 0.00 Date + Condition + Release + Year 7 40.0 14.2 0.00 Date + Condition + Sex + Release 7 41.4 15.5 0.00 Date + Condition + Sex + Release + Year 8 42.8 16.9 0.00

80 Table 3.2. Competing models examining the influence of ordinal date, energetic condition, sex, release point (R1, R2, or R3), and year on day 2 movement rates of Yellow-rumped Warblers experimentally translocated to 3 forested release points at Trempealeau National Wildlife Refuge, Wisconsin in April-May 2009-2010. I ranked 32 candidate models by AICc. Bold text indicates the model with the most support.

Model K AICc ΔAICc wi null 2 13.6 0.0 0.48 Condition 3 15.9 2.3 0.15 Year 3 16.8 3.3 0.09 Sex 3 17.4 3.9 0.07 Date 3 17.5 3.9 0.07 Release 4 17.6 4.1 0.06 Date + Condition 4 20.6 7.0 0.01 Condition + Year 4 20.6 7.0 0.01 Condition + Sex 4 21.1 7.6 0.01 Date + Year 4 21.9 8.4 0.01 Sex + Year 4 22.0 8.4 0.01 Condition + Release 5 22.4 8.8 0.01 Date + Sex 4 22.7 9.1 0.01 Date + Release 5 24.3 10.7 0.00 Sex + Release 5 24.7 11.1 0.00 Release + Year 5 24.8 11.2 0.00 Date + Condition + Year 5 26.7 13.1 0.00 Date + Condition + Sex 5 27.8 14.2 0.00 Condition + Sex + Year 5 27.9 14.4 0.00 Date + Condition + Release 6 28.5 15.0 0.00 Date + Sex + Year 5 29.2 15.7 0.00 Condition + Release + Year 6 33.3 19.8 0.00 Condition + Sex + Release 6 33.4 19.8 0.00 Date + Release + Year 6 34.8 21.2 0.00 Date + Sex + Release 6 35.1 21.5 0.00 Sex + Release + Year 6 35.5 21.9 0.00 Date + Condition + Sex + Year 6 37.3 23.7 0.00 Date + Condition + Release + Year 7 45.5 31.9 0.00 Date + Condition + Sex + Release 7 46.2 32.6 0.00 Condition + Sex + Release + Year 7 51.6 38.1 0.00 Date + Sex + Release + Year 7 53.0 39.4 0.00 Date + Condition + Sex + Release + Year 8 81.2 67.6 0.00

81 Table 3.3. Competing models examining the influence of ordinal date, energetic condition, sex, release point (R1, R2, or R3), and year on day 1 displacement of Yellow-rumped Warblers experimentally translocated to 3 forested release points at Trempealeau National Wildlife Refuge, Wisconsin in April-May 2009-2010. I ranked 32 candidate models by AICc. Bold text indicates the models with the most support.

Model K AICc ΔAICc wi Date + Sex 4 39.3 0.0 0.17 Sex 3 39.4 0.2 0.16 null 2 40.0 0.8 0.12 Date 3 41.0 1.8 0.07 Date + Sex + Year 5 41.7 2.4 0.05 Condition + Sex 4 41.8 2.5 0.05 Year 3 42.1 2.8 0.04 Date + Condition + Sex 5 42.2 3.0 0.04 Date + Year 4 42.3 3.0 0.04 Sex + Year 4 42.3 3.1 0.04 Sex + Release 5 42.4 3.1 0.04 Condition 3 42.7 3.4 0.03 Release 4 42.7 3.5 0.03 Date + Sex + Release 6 43.2 3.9 0.02 Date + Condition 4 44.1 4.8 0.02 Date + Condition + Sex + Year 6 44.5 5.2 0.01 Date + Release 5 44.6 5.3 0.01 Condition + Sex + Year 5 44.7 5.5 0.01 Condition + Year 4 44.8 5.6 0.01 Condition + Sex + Release 6 45.4 6.1 0.01 Date + Condition + Year 5 45.5 6.2 0.01 Release + Year 5 46.1 6.8 0.01 Condition + Release 5 46.1 6.8 0.01 Sex + Release + Year 6 46.4 7.1 0.00 Date + Condition + Sex + Release 7 47.0 7.7 0.00 Date + Sex + Release + Year 7 47.4 8.1 0.00 Date + Release + Year 6 47.7 8.4 0.00 Date + Condition + Release 6 48.5 9.3 0.00 Condition + Release + Year 6 49.7 10.5 0.00 Condition + Sex + Release + Year 7 49.9 10.6 0.00 Date + Condition + Sex + Release + Year 8 51.6 12.3 0.00 Date + Condition + Release + Year 7 52.0 12.8 0.00

82 Table 3.4. Competing models examining the influence of ordinal date, energetic condition, sex, release point (R1, R2, or R3), and year on day 2 displacement of Yellow-rumped Warblers experimentally translocated to 3 forested release points at Trempealeau National Wildlife Refuge, Wisconsin in April-May 2009-2010. I ranked 32 candidate models by AICc. Bold text indicates the model with the most support.

Model K AICc ΔAICc wi null 2 41.7 0.0 0.48 Condition 3 43.9 2.2 0.16 Date 3 45.2 3.6 0.08 Release 4 45.6 3.9 0.07 Sex 3 45.6 3.9 0.07 Year 3 45.6 3.9 0.07 Condition + Sex 4 49.1 7.4 0.01 Date + Condition 4 49.2 7.5 0.01 Condition + Year 4 49.2 7.5 0.01 Condition + Release 5 49.9 8.2 0.01 Date + Release 5 50.2 8.5 0.01 Date + Sex 4 50.4 8.7 0.01 Date + Year 4 50.5 8.8 0.01 Sex + Year 4 50.8 9.1 0.01 Sex + Release 5 52.0 10.3 0.00 Release + Year 5 52.8 11.1 0.00 Date + Condition + Sex 5 56.5 14.8 0.00 Condition + Sex + Year 5 56.5 14.8 0.00 Date + Condition + Year 5 56.5 14.8 0.00 Condition + Sex + Release 6 57.6 15.9 0.00 Date + Sex + Year 5 57.7 16.0 0.00 Date + Condition + Release 6 59.8 18.1 0.00 Date + Sex + Release 6 60.5 18.8 0.00 Condition + Release + Year 6 60.9 19.2 0.00 Date + Release + Year 6 61.1 19.4 0.00 Sex + Release + Year 6 62.9 21.2 0.00 Date + Condition + Sex + Year 6 67.5 25.8 0.00 Date + Condition + Sex + Release 7 75.7 34.0 0.00 Condition + Sex + Release + Year 7 75.9 34.2 0.00 Date + Condition + Release + Year 7 78.1 36.4 0.00 Date + Sex + Release + Year 7 78.8 37.1 0.00 Date + Condition + Sex + Release + Year 8 112.3 70.6 0.00

83 Table 3.5. Competing models examining the influence of ordinal date, energetic condition, sex, release point (R1, R2, or R3), and year on day 1 linearity of Yellow-rumped Warblers experimentally translocated to 3 forested release points at Trempealeau National Wildlife Refuge, Wisconsin in April-May 2009-2010. I ranked 32 candidate models by AICc. Bold text indicates the models with the most support.

Model K AICc ΔAICc wi Date 3 27.4 0.0 0.35 null 2 29.3 1.9 0.14 Date + Sex 4 30.2 2.8 0.09 Date + Year 4 30.4 3.0 0.08 Date + Condition 4 30.4 3.1 0.08 Year 3 31.3 3.9 0.05 Condition 3 32.0 4.6 0.03 Sex 3 32.0 4.6 0.03 Date + Release 5 32.2 4.8 0.03 Release 4 33.2 5.8 0.02 Date + Sex + Year 5 33.6 6.2 0.02 Date + Condition + Sex 5 33.7 6.3 0.01 Date + Condition + Year 5 33.8 6.5 0.01 Sex + Year 4 34.3 6.9 0.01 Condition + Year 4 34.4 7.0 0.01 Condition + Sex 4 35.1 7.7 0.01 Release + Year 5 35.4 8.0 0.01 Date + Sex + Release 6 35.9 8.5 0.01 Date + Release + Year 6 35.9 8.6 0.00 Date + Condition + Release 6 36.2 8.8 0.00 Sex + Release 5 36.7 9.3 0.00 Condition + Release 5 36.7 9.3 0.00 Date + Condition + Sex + Year 6 37.5 10.2 0.00 Condition + Sex + Year 5 37.8 10.4 0.00 Sex + Release + Year 6 39.2 11.8 0.00 Condition + Release + Year 6 39.3 11.9 0.00 Date + Sex + Release + Year 7 40.1 12.7 0.00 Date + Condition + Release + Year 7 40.4 13.0 0.00 Date + Condition + Sex + Release 7 40.5 13.1 0.00 Condition + Sex + Release 6 40.7 13.3 0.00 Condition + Sex + Release + Year 7 43.8 16.4 0.00 Date + Condition + Sex + Release + Year 8 45.4 18.0 0.00

84 Table 3.6. Competing models examining the influence of ordinal date, energetic condition, sex, release point (R1, R2, or R3), and year on day 2 linearity of Yellow-rumped Warblers experimentally translocated to 3 forested release points at Trempealeau National Wildlife Refuge, Wisconsin in April-May 2009-2010. I ranked 32 candidate models by AICc. Bold text indicates the models with the most support.

Model K AICc ΔAICc wi null 2 41.7 0.0 0.45 Condition 3 43.1 1.4 0.22 Date 3 45.3 3.6 0.07 Sex 3 45.5 3.8 0.07 Year 3 45.6 3.9 0.06 Release 4 46.2 4.6 0.05 Date + Condition 4 48.3 6.6 0.02 Condition + Sex 4 48.3 6.6 0.02 Condition + Year 4 48.3 6.6 0.02 Condition + Release 5 49.3 7.6 0.01 Date + Sex 4 50.4 8.7 0.01 Date + Year 4 50.5 8.9 0.01 Sex + Year 4 50.7 9.1 0.00 Date + Release 5 51.8 10.1 0.00 Sex + Release 5 52.9 11.2 0.00 Release + Year 5 53.5 11.9 0.00 Date + Condition + Sex 5 55.6 13.9 0.00 Date + Condition + Year 5 55.6 13.9 0.00 Condition + Sex + Year 5 55.6 13.9 0.00 Condition + Sex + Release 6 56.9 15.2 0.00 Date + Sex + Year 5 57.7 16.0 0.00 Date + Condition + Release 6 60.0 18.3 0.00 Condition + Release + Year 6 60.3 18.6 0.00 Date + Sex + Release 6 62.4 20.7 0.00 Date + Release + Year 6 62.7 21.0 0.00 Sex + Release + Year 6 63.9 22.2 0.00 Date + Condition + Sex + Year 6 66.5 24.8 0.00 Date + Condition + Sex + Release 7 75.2 33.6 0.00 Condition + Sex + Release + Year 7 75.2 33.6 0.00 Date + Condition + Release + Year 7 78.3 36.6 0.00 Date + Sex + Release + Year 7 80.6 38.9 0.00 Date + Condition + Sex + Release + Year 8 111.9 70.2 0.00

85 Table 3.7. Competing models examining the influence of ordinal date, energetic condition, sex, release point (R1, R2, or R3), and year on minimum stopover duration of Yellow-rumped Warblers experimentally translocated to 3 forested release points at Trempealeau National Wildlife Refuge, Wisconsin in April-May 2009-2010. I ranked 32 candidate models by AICc. Bold text indicates the models with the most support.

Model K AICc ΔAICc wi Condition 3 115.7 0.0 0.34 Date + Condition 4 117.1 1.4 0.17 Condition + Year 4 118.4 2.7 0.09 Condition + Sex 4 118.5 2.8 0.08 null 2 119.4 3.7 0.05 Date + Condition + Year 5 119.6 3.9 0.05 Date 3 120.0 4.3 0.04 Date + Condition + Sex 5 120.1 4.4 0.04 Condition + Sex + Year 5 121.5 5.8 0.02 Condition + Release 5 121.5 5.8 0.02 Sex 3 121.7 6.0 0.02 Year 3 121.7 6.0 0.02 Date + Sex 4 122.7 7.0 0.01 Date + Year 4 122.8 7.1 0.01 Date + Condition + Sex + Year 6 123.1 7.4 0.01 Date + Condition + Release 6 123.5 7.9 0.01 Release 4 124.2 8.6 0.00 Sex + Year 4 124.4 8.7 0.00 Condition + Release + Year 6 124.8 9.1 0.00 Condition + Sex + Release 6 124.9 9.2 0.00 Date + Release 5 125.4 9.7 0.00 Date + Sex + Year 5 125.8 10.1 0.00 Date + Condition + Release + Year 7 126.8 11.1 0.00 Sex + Release 5 127.2 11.5 0.00 Release + Year 5 127.2 11.5 0.00 Date + Condition + Sex + Release 7 127.3 11.6 0.00 Condition + Sex + Release + Year 7 128.7 13.0 0.00 Date + Sex + Release 6 128.8 13.1 0.00 Date + Release + Year 6 128.9 13.2 0.00 Sex + Release + Year 6 130.6 14.9 0.00 Date + Condition + Sex + Release + Year 8 131.1 15.4 0.00 Date + Sex + Release + Year 7 132.7 17.0 0.00

86 Table 3.8. Variable importance in the Random Forests model of departure probability for Yellow-rumped Warblers. Variable importance is based on the mean decrease in the Gini index for model iterations without the variable, indicating the importance of the variable for predicting departure from the study area.

Variable name Mean decrease in GINI index Change in pressure 3.64 Southerly wind component 3.04 Mean temperature 2.66 Mean pressure 2.47 Ordinal date 2.42 Westerly wind component 2.19 Mean wind speed 2.17 Precipitation amount 0.43 Year 0.30

87 Figure 3.1. Map showing location of Trempealeau National Wildlife Refuge (U.S. Fish and Wildlife Service 2008).

88 Figure 3.2. Landcover and land use at Trempealeau National Wildlife Refuge in 1994 (U.S. Fish and Wildlife Service 2008).

89

n i

d e

s l u a n e t o i i t s a g N n

i u d a n e a l b a e y p r a m d e n r o . T

s c t e e a t s

i

) s a d

e e s s r a ( a

w e s

l e e 2 t r i

B s

e

r . e e s s r a w a e l e 3 e y r R

h d t d n o n a b a

) , n i 2 w o R d l e , l s e 1 u y

R (

n

. s o i 0 n t 1 o a i 0 t c 2 a o

l c

n o i g l

n d e i e r d s u n t u

a p e b a t

i c y

s r r a e g l n m b i i r d r a n p

a W e

b

h d t y e r s p a a d m w n u r o 1 - c B e w

s o . l e a l

g e s u a Y f

e w .

3 R 3 .

3 e B

f

i e . l r 9 d u l 0 i g i 0 F W 2

90 Figure 3.4. Partial plots showing how the top three weather variables indicated by the Random Forests model predicted the probability of departure in Yellow-rumped Warblers.

91 Bibliography

Aborn, D. A., and F. R. Moore. 1997. Pattern of movement by Summer Tanagers (Piranga rubra) during migratory stopover: A telemetry study. Behaviour 134:1077-1100.

Aborn, D. A., and F. R. Moore. 2004. Activity budgets of Summer Tanagers during spring migratory stopover. The Wilson Bulletin 116:64-68.

Aebischer, A., N. Perrin, M. Krieg, J. Studer, and D. R. Meyer. 1996. The role of territory choice, mate choice and arrival date on breeding success in the Savi’s Warbler Locustella luscinioides. Journal of Avian Biology 27:143-152.

Åkesson, S., and A. Hedenström. 2000. Wind selectivity of migratory flight departures in birds. Behavioral Ecology and Sociobiology 47:0140-0144.

Alerstam, T., and Å. Lindström. 1990. Optimal bird migration: The relative importance of time, energy, and safety. Pages 331-351 in E. Gwinner, editor. Bird migration: physiology and ecophysiology. Springer-Verlag, Berlin and New York.

Anderson, D. R., and K. P. Burnham. 2002. Model selection and multimodel inference : A practical information-theoretic approach. Springer, New York.

Bächler, E., and M. Schaub. 2007. The effects of permanent local emigration and encounter technique on stopover duration estimates as revealed by telemetry and mark-recapture. Condor 109:142-154.

Barron, D. G., J. D. Brawn, and P. J. Weatherhead. 2010. Meta-analysis of transmitter effects on avian behaviour and ecology. Methods in Ecology and Evolution 1:180- 187.

Bearhop, S., G. M. Hilton, S. C. Votier, and S. Waldron. 2004. Stable isotope ratios indicate that body condition in migrating passerines is influenced by winter habitat. Proceedings of the Royal Society of London. Series B: Biological Sciences 271:S215-S218.

Bedford, S. E., and M. B. Usher. 1994. Distribution of arthropod species across the margins of farm woodlands. Agriculture Ecosystems & Environment 48:295-305.

92 Bibby, C., and R. Green. 1980. Foraging behavior of migrant Pied Flycatchers, Ficedula hypoleuca, on temporary territories. Journal of Animal Ecology 49:507-521.

Breiman, L., J. H. Friedman, R. A. Olshen, and C. J. Stone. 1984. Classification and regression trees. Wadsworth and Brooks/Cole, Monterey, CA.

Buchanan, A. A. 2008. Movements, Habitat Use, and Stopover Duration of Migratory Songbirds in the Western Lake Erie Basin of Northern Ohio. Master’s Thesis, The Ohio State University.

Buler, J. J. 2006. Understanding habitat use by landbirds during migration along the Mississippi Gulf Coast using a scale-dependent approach. Ph.D. Dissertation, University of Southern Mississippi.

Buler, J. J., F. R. Moore, and S. Woltmann. 2007. A multi-scale examination of stopover habitat use by birds. Ecology 88:1789-1802.

Catry, P., V. Encarnação, A. Araújo, P. Fearon, A. Fearon, M. Armelin, and P. Delaloye. 2004. Are long-distance migrant passerines faithful to their stopover sites? Journal of Avian Biology 35:170-181.

Charnov, E. L. 1976. Optimal foraging, the marginal value theorem. Theoretical Population Biology 9:129-136.

Chernetsov, N. 2005. Spatial behavior of medium and long-distance migrants at stopovers studied by radio tracking. Annals of the New York Academy of Sciences 1046:242- 252.

Chernetsov, N. 2006. Habitat selection by nocturnal passerine migrants en route: mechanisms and results. Journal of Ornithology 147:185-191.

Chernetsov, N., and A. Mukhin. 2006. Spatial behavior of European Robins during migratory stopovers: A telemetry study. Wilson Journal of Ornithology 118:364- 373.

Cherry, J. D. 1982. Fat deposition and length of stopover of migrant White-crowned Sparrows. Auk 99:725-732.

Cimprich, D. A., M. S. Woodrey, and F. R. Moore. 2005. Passerine migrants respond to variation in predation risk during stopover. Animal Behaviour 69:1173-1179.

Cochran, W. W., G. G. Montgomery, and R. R. Graber. 1967. Migratory Flights of Hylocichla Thrushes in Spring: A Radiotelemetry Study. The Living Bird 6:213- 225.

93 Cohen, E., and F. Moore. 2011. Predicting successful stopover: Individual based models of Red-eyed Vireos (Vireo olivaceus) in a heterogeneous landscape. Chattanooga, TN. Retrieved May 28, 2011, from http://citation.allacademic.com/meta/p_mla_apa_research_citation/2/4/4/0/7/p 244072_index.html.

Currie, D., D. Thompson, and T. Burke. 2000. Patterns of territory settlement and consequences for breeding success in the Northern Wheatear Oenanthe oenanthe. Ibis 142:389-398.

Cutler, D. R., T. C. Edwards, K. H. Beard, A. Cutler, K. T. Hess, J. Gibson, and J. J. Lawler. 2007. Random forests for classification in ecology. Ecology 88:2783- 2792.

DeGraaf, R. M., and J. H. Rappole. 1995. Neotropical migratory birds: Natural history, distribution, and population change. Comstock Publishing Associates, Ithaca.

DeSante, D. F., K. M. Burton, P. Velez, D. Froehlich, and D. Kaschube. 2011. MAPS Manual. Institute for Bird Populations.

Drewitt, A., and R. Langston. 2008. Collision effects of wind-power generators and other obstacles on birds. Year in Ecology and Conservation Biology 2008 1134:233- 266.

Dunn, J. L., and K. L. Garrett. 1997. A field guide to warblers of North America. Houghton Mifflin Company, Boston and New York.

Eaton, S. W. 1995. Northern Waterthrush (Seiurus noveboracensis). Page in A. Poole, editor. The Birds of North America Online. Cornell Lab of Ornithology, Ithaca, NY. Retrieved from http://bna.birds.cornell.edu.bnaproxy.birds.cornell.edu/bna/species/182.

Erni, B., F. Liechti, and B. Bruderer. 2002. Stopover strategies in passerine bird migration: A simulation study. Journal of Theoretical Biology 219:479-493.

ESRI. 2011. ArcMap 9.3. Environmental Systems Research Institute, Redlands, CA.

Ewert, D. N., and M. J. Hamas. 1995. Ecology of migratory landbirds during migration in the midwest. Pages 200-208 in F. R. I. Thompson, editor. Management of midwestern landscapes for the conservation of neotropical migratory birds. North Central Forest Experiment Station USDA Forest Service, Detroit, MI. Retrieved from http://www.nrs.fs.fed.us/pubs/gtr/gtr_nc187.pdf.

94 Fretwell, S. D., and H. L. Lucas. 1969. On territorial behavior and other factors influencing habitat distribution in birds. Acta Biotheoretica 19:16-36.

Goymann, W., F. Spina, A. Ferri, and L. Fusani. 2010. Body fat influences departure from stopover sites in migratory birds: evidence from whole-island telemetry. Biology Letters 6:478 -481.

Hansson, M., and J. Pettersson. 1989. Competition and fat deposition in Goldcrests (Regulus regulus) at a migration stop-over site. Die Vogelwarte 35:21-31.

Harrison, X. A., J. D. Blount, R. Inger, D. R. Norris, and S. Bearhop. 2011. Carry-over effects as drivers of fitness differences in animals. Journal of Animal Ecology 80:4-18.

Hedenström, A., and T. Alerstam. 1997. Optimum fuel loads in migratory birds: Distinguishing between time and energy minimization. Journal of theoretical biology 189:227-234.

Hunt, P. D., and D. J. Flaspohler. 1998. Yellow-rumped Warbler (Dendroica coronata). Page in A. Poole, editor. The Birds of North America Online. Cornell Lab of Ornithology, Ithaca, NY. Retrieved from http://bna.birds.cornell.edu.bnaproxy.birds.cornell.edu/bna/species/376.

Hutto, R. L. 1985. Seasonal changes in the habitat distribution of transient insectivorous birds in southeastern Arizona: Competition mediated? Auk 102:120-132.

Hutto, R. L. 2000. On the importance of en route periods to the conservation of migratory landbirds. Studies in Avian Biology 20:109-114.

Jenni, L., and M. Schaub. 2003. Behavioural and physiological reactions to environmental variation in bird migration: A review. Pages 155-171 in P. Berthold, E. Gwinner, and E. Sonnenschein, editors. Avian Migration. Springer- Verlag, Berlin and Heidelberg.

Jokimaki, J., E. Huhta, J. Itamies, and P. Rahko. 1998. Distribution of arthropods in relation to forest patch size, edge, and stand characteristics. Canadian Journal of Forest Research 28:1068-1072.

Kelly, J. F., L. S. DeLay, and D. M. Finch. 2002. Density-dependent mass gain by Wilson’s Warblers during stopover. Auk 119:210-213.

Kenward, R. 2001. A manual for wildlife radio tagging. Academic Press, San Diego, CA; London.

95 Ktitorov, P., F. Bairlein, and M. Dubinin. 2008. The importance of landscape context for songbirds on migration: body mass gain is related to habitat cover. Landscape Ecology 23:169-179.

Kullberg, C., T. Fransson, and S. Jakobsson. 1996. Impaired predator evasion in fat blackcaps (Sylvia atricapilla). Proceedings of the Royal Society of London Series B-Biological Sciences 263:1671-1675.

Lindström, Å. 1989. Finch flock size and risk of hawk predation at a migratory stopover site. Auk 106:225-232.

Lindström, Å. 1990. The role of predation risk in stopover habitat selection in migrating bramblings, Fringilla montifringilla. Behavioral Ecology 1:102-106.

Lozano, G. A., S. Perreault, and R. E. Lemon. 1996. Age, arrival date and reproductive success of male American Redstarts Setophaga ruticilla. Journal of Avian Biology 27:164-170.

Marra, P. P., T. W. Sherry, and R. T. Holmes. 1993. Territorial Exclusion by a Long- Distance Migrant Warbler in Jamaica: A Removal Experiment with American Redstarts (Setophaga ruticilla). The Auk 110:565-572.

Marra, P. P., K. A. Hobson, and R. T. Holmes. 1998. Linking winter and summer events in a migratory bird by using stable-carbon isotopes. Science 282:1884-1886.

Matthews, S. N., and P. G. Rodewald. 2010a. Movement behaviour of a forest songbird in an urbanized landscape: the relative importance of patch-level effects and body condition during migratory stopover. Landscape Ecology 25:955-965.

Matthews, S. N., and P. G. Rodewald. 2010b. Urban forest patches and stopover duration of migratory Swainson’s Thrushes. Condor 112:96-104.

Mehlman, D. W., S. E. Mabey, D. N. Ewert, C. Duncan, B. Abel, D. Cimprich, R. D. Sutter, and M. Woodrey. 2005. Conserving stopover sites for forest-dwelling migratory landbirds. Auk 122:1281-1290.

Millspaugh, J. J., and J. M. Marzluff. 2001. Radio tracking and animal populations. Academic Press, San Diego.

Moore, F. R., S. A. Gauthreaux, P. Kerlinger, and T. R. Simons. 1995. Habitat requirements during migration: important link in conservation. Pages 121-144 in T. E. Martin and D. M. Finch, editors. Ecology and management of neotropical migratory birds: A synthesis and review of critical issues. Oxford University Press, New York.

96 Moore, F. R., and P. Kerlinger. 1987. Stopover and fat deposition by North American wood-warblers (Parulinae) following Spring Migration over the Gulf of Mexico. Oecologia 74:47-54.

Moore, F. R., P. Kerlinger, and T. R. Simons. 1990. Stopover on a Gulf Coast barrier island by spring trans-gulf migrants. The Wilson Bulletin 102:487-500.

Moore, F. R., and W. Yong. 1991. Evidence of food-based competition among passerine migrants during stopover. Behavioral Ecology and Sociobiology 28:85-90.

Mukhin, A., N. Chernetsov, and D. Kishkinev. 2008. Acoustic information as a distant cue for habitat recognition by nocturnally migrating passerines during landfall. Behavioral Ecology 19:716-723.

Nathan, R., W. M. Getz, E. Revilla, M. Holyoak, R. Kadmon, D. Saltz, and P. E. Smouse. 2008. A movement ecology paradigm for unifying organismal movement research. Proceedings of the National Academy of Sciences 105:19052 -19059.

National Audubon Society. 2011. CBC Historical Results Count Table. Retrieved from http://audubon2.org/cbchist/count_table.html.

National Climatic Data Center. 2011. National Climatic Data Center. Retrieved March 24, 2011, from http://www.ncdc.noaa.gov/oa/ncdc.html.

Nemeth, Z., and F. R. Moore. 2007. Unfamiliar stopover sites and the value of social information during migration. Journal of Ornithology 148:S369-S376.

Neudorf, D. L., and T. E. Pitcher. 1997. Radio transmitters do not affect nestling feeding rates by female Hooded Warblers. Journal of Field Ornithology 68:64-68.

Newton, I. 2004. Population limitation in migrants. Ibis 146:197-226.

Newton, I. 2006. Can conditions experienced during migration limit the population levels of birds? Journal of Ornithology 147:146-166.

Norris, D. R. 2005. Carry-over effects and habitat quality in migratory populations. Oikos 109:178-186.

Norris, D. R., and C. M. Taylor. 2006. Predicting the consequences of carry-over effects for migratory populations. Biology Letters 2:148 -151.

Parnell, J. F. 1969. Habitat relations of the Parulidae during spring migration. Auk 86:505-521.

97 Paxton, K. L., C. Van Riper III, and C. O’Brien. 2008. Movement patterns and stopover ecology of Wilson’s Warblers during spring migration on the Lower Colorado River in southwestern Arizona. Condor 110:672-681.

Powell, L. A., D. G. Krementz, Jason D. Lang, and M. J. Conroy. 1998. Effects of radio transmitters on migrating Wood Thrushes. Journal of Field Ornithology 69:306- 315.

Pyle, P. 1997. Identification guide to North American birds, Part I. Slate Creek Press, Bolinas, California.

R Development Core Team. 2011. R: A language andenvironment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.

Rappole, J. H., and D. W. Warner. 1976. Relationships between behavior, physiology and weather in avian transients at a migration stopover site. Oecologia 26:193-212.

Rich, T. D., C. J. Beardmore, H. Berlanga, P. J. Blancher, M. S. W. Bradstreet, G. S. Butcher, D. W. Demarest, E. H. Dunn, W. C. Hunter, E. E. Iñigo-Elias, J. A. Kennedy, A. M. Martell, A. O. Panjabi, D. N. Pashley, K. V. Rosenberg, C. M. Rustay, J. S. Wendt, and T. C. Will. 2004. Partners in Flight North American Landbird Conservation Plan. Retrieved from http://www.partnersinflight.org/cont_plan/default.htm.

Robbins, C., J. Sauer, R. Greenberg, and S. Droege. 1989. Population declines in North-American birds that migrate to the neotropics. Proceedings of the National Academy of Sciences of the United States of America 86:7658-7662.

Robbins, S. D. 1991. Wisconsin Birdlife. University of Wisconsin Press, Madison.

Robinson, W. D., M. S. Bowlin, I. Bisson, J. Shamoun-Baranes, K. Thorup, R. H. Diehl, T. H. Kunz, S. Mabey, and D. W. Winkler. 2010. Integrating concepts and technologies to advance the study of bird migration. Frontiers in Ecology and the Environment 8:354-361.

Rodewald, P. G., and M. C. Brittingham. 2002. Habitat use and behavior of mixed species landbird flocks during fall migration. The Wilson Bulletin 114:87-98.

Rodewald, P. G., and M. C. Brittingham. 2004. Stopover habitats of landbirds during fall: Use of edge-dominated and early-successional forests. Auk 121:1040-1055.

Rodewald, P. G., and M. C. Brittingham. 2007. Stopover habitat use by spring migrant landbirds: The roles of habitat structure, leaf development, and food availability. Auk 124:1063-1074.

98 Rodgers, A. R., A. P. Carr, H. L. Beyer, L. Smith, and J. G. Kie. 2007. HRT: Home Range Tools for ArcGIS. Version 1.1. Ontario Ministry of Natural Resources, Centre for Northern Forest Ecosystem Research, Thunder Bay, Ontario, Canada.

Salewski, V., B. Almasi, A. Heuman, M. Thoma, and A. Schlageter. 2007. Agonistic behaviour of Palaearctic passerine migrants at a stopover site suggests interference competition. Ostrich 78:349-355.

Sauer, J. R., and W. A. Link. 2011. Analysis of the North American Breeding Bird Survey using hierarchical models. Auk 128:87-98.

Schaub, M., and L. Jenni. 2001. Stopover durations of three warbler species along their autumn migration route. Oecologia 128:217-227.

Schaub, M., L. Jenni, and F. Bairlein. 2008. Fuel stores, fuel accumulation, and the decision to depart from a migration stopover site. Behavioral Ecology 19:657- 666.

Schaub, M., F. Liechti, and L. Jenni. 2004. Departure of migrating European robins, Erithacus rubecula, from a stopover site in relation to wind and rain. Animal Behaviour 67:229-237.

Seaman, D. E., J. J. Millspaugh, B. J. Kernohan, G. C. Brundige, K. J. Raedeke, and R. A. Gitzen. 1999. Effects of sample size on kernel home range estimates. Journal of Wildlife Management 63:739-747.

Seewagen, C. L., E. J. Slayton, and C. G. Guglielmo. 2010. Passerine migrant stopover duration and spatial behaviour at an urban stopover site. Acta Oecologica 36:484- 492.

Sillett, T. S., and R. T. Holmes. 2002. Variation in survivorship of a migratory songbird throughout its annual cycle. Journal of Animal Ecology 71:296-308.

Smith, J. A. M., L. R. Reitsma, and P. P. Marra. 2010. Moisture as a determinant of habitat quality for a nonbreeding Neotropical migratory songbird. Ecology 91:2874-2882.

Smith, R. J., and F. R. Moore. 2003. Arrival fat and reproductive performance in a long- distance passerine migrant. Oecologia 134:325-331.

Smith, R. J., and F. R. Moore. 2005. Arrival timing and seasonal reproductive performance in a long-distance migratory landbird. Behavioral Ecology and Sociobiology 57:231-239.

99 Stamps, J. 1995. Motor Learning and the Value of Familiar Space. The American Naturalist 146:41-58.

Studds, C., and P. Marra. 2005. Nonbreeding habitat occupancy and population processes: An upgrade experiment with a migratory bird. Ecology 86:2380-2385.

Swihart, R. K., and N. A. Slade. 1985. Testing for independence of observations in animal movements. Ecology 66:1176-1184.

U.S. Fish and Wildlife Service. 2008. Trempealeau National Wildlife Refuge Comprehensive Conservation Plan.

Veltri, C. J., and D. Klem. 2005. Comparison of fatal bird injuries from collisions with towers and windows. Journal of Field Ornithology 76:127-133.

Whitaker, D. M., and I. G. Warkentin. 2010. Spatial Ecology of Migratory Passerines on Temperate and Boreal Forest Breeding Grounds. Auk 127:471-484.

White, G. C., and R. A. Garrott. 1990. Analysis of wildlife radio-tracking data. Academic Press, San Diego, CA.

Wiedner, D., P. Kerlinger, D. Sibley, P. Holt, J. Hough, and R. Crossley. 1992. Visible morning flight of neotropical landbird migrants at Cape May New Jersey. Auk 109:500-510.

Wikelski, M., E. M. Tarlow, A. Raim, R. H. Diehl, R. P. Larkin, and G. H. Visser. 2003. Avian metabolism: Costs of migration in free-flying songbirds. Nature 423:704.

Winker, K., D. W. Warner, and A. R. Weisbrod. 1992. The Northern Waterthrush and Swainson’s Thrush as transients at a temperate inland stopover site. Pages 384- 402 in J. M. Hagan and D. W. Johnston, editors. Ecology and conservation of Neotropical migrant landbirds. Smithsonian Institution Press, Washington, London.

Wisconsin Breeding Bird Atlas. 2003. WBBA Northern Waterthrush Map. Retrieved from http://www.uwgb.edu/birds/wbba/species/maps/NOWA.htm.

Wisconsin Breeding Bird Atlas. 2003. WBBA Yellow-rumped Warbler Map. Retrieved from http://www.uwgb.edu/birds/wbba/species/maps/YRWA.htm.

Ydenberg, R. C., R. W. Butler, and D. B. Lank. 2007. Effects of predator landscapes on the evolutionary ecology of routing, timing and molt by long-distance migrants. Journal of Avian Biology 38:523-529.

100 Yong, W., D. Finch, F. Moore, and J. Kelly. 1998. Stopover ecology and habitat use of migratory Wilson’s warblers. Auk 115:829-842.

Yong, W., and F. R. Moore. 1993. Relation between Migratory Activity and Energetic Condition among Thrushes (Turdinae) Following Passage across the Gulf of Mexico. The Condor 95:934-943.

Zach, R., and J. B. Falls. 1976. Foraging behavior, learning, and exploration by captive ovenbirds (Aves: Parulidae). Canadian Journal of Zoology 54:1880-1893.

101 Appendix A

Additional Information

102 Table A.1. Individual Northern Waterthrush data. Wing = unflattened wing chord (mm), tarsus given in mm, fat given on scale of 0-7, masses given in g, HSL = Holohil Systems Ltd. model BD-2N, WMI = Wildlife Materials Inc. model SOM-2007, hab = habitat (U = upland forest, B = bottomland forest), NA = unknown.

Bird Capture Transmitter Release Stopover ID sex fat wing tarsus mass date time site make mass site hab time duration 12 NA 0 77 22.5 17.8 2009-04-24 09:30 B2 HSL 0.39 R2 U 10:34 5 15 NA 0 77 22.7 17.1 2009-04-28 07:00 B2 HSL 0.39 R3 B 07:40 NA 25 NA 0 77 21.7 15.5 2009-04-30 11:40 B1 WMI 0.62 R1 U 12:07 NA 26 M 4 72 21.5 18.4 2009-05-06 07:40 B1 WMI 0.73 R4 B 08:28 NA 22 NA 4 72 22.2 18.6 2009-05-06 07:50 B2 WMI 0.73 R2 U 08:33 6 33 M 3 75 20.8 18.5 2009-05-06 09:20 B1 WMI 0.67 R3 B 10:00 4 2 M 3 76 21.6 15.9 2009-05-06 11:10 B1 HSL 0.39 R4 B 11:44 NA 28 F 2 75 20.8 16.4 2009-05-08 09:00 B1 WMI NA R1 U 09:30 NA 6 NA 4 77 22.3 21.7 2009-05-11 06:30 B1 HSL 0.39 R4 B 07:15 2 7 M 2 75 22.0 18.3 2009-05-11 07:30 B1 HSL 0.39 R2 U 08:08 1 32 M 4 75 21.9 21.6 2009-05-13 07:40 B1 WMI 0.56 R1 U 08:11 NA 30 F 1 74 21.0 17.6 2009-05-14 07:00 B1 WMI 0.57 R4 B 07:40 5 34 NA 4 73 21.0 17.6 2009-05-14 07:50 B1 WMI 0.56 R3 B 08:17 4 29 F 5 75 20.6 22.0 2009-05-14 08:30 B1 WMI 0.56 R1 U 09:02 1 16 F 4 73 21.8 18.6 2009-05-17 08:20 B1 WMI 0.72 R3 B 08:57 4 27 NA 4 69 20.4 18.6 2009-05-17 09:50 B1 WMI 0.72 R2 U 10:15 6 31 F 3 76 20.0 15.6 2009-05-19 07:00 B2 WMI 0.56 R4 B 07:45 4 24 M 1 75 21.6 17.7 2009-05-21 06:20 B1 WMI 0.70 R1 U 06:47 NA 21 NA 3 75 21.7 18.4 2009-05-21 07:00 B1 WMI 0.71 R3 B 07:33 5 5 F 3 72 20.7 17.1 2009-05-21 07:40 B1 WMI 0.68 R2 U 08:30 3 23 NA 3 68 21.2 16.6 2009-05-24 06:00 B2 WMI 0.67 R4 B 06:33 NA 43 M 1 77 21.4 17.6 2010-04-29 07:30 B3 HSL 0.39 R3 B 08:01 NA 47 M 0 74 20.5 15.9 2010-04-30 06:20 B1 HSL 0.39 R2 U 06:51 7 53 NA 0 78 20.2 15.7 2010-04-30 06:50 B3 HSL 0.39 R4 B 07:27 10 44 M 0 78 22.7 18.6 2010-05-02 06:30 B1 HSL 0.39 R1 U 07:02 NA 49 M 2 76 21.7 21.3 2010-05-02 09:00 B1 HSL 0.39 R4 B 09:38 5 54 M 0 78 20.7 17.2 2010-05-04 06:10 B1 HSL 0.39 R3 B 06:46 6 58 M 4 78 20.2 22.9 2010-05-06 06:30 B1 HSL 0.39 R2 U 07:00 5 57 F 4 73 20.8 22.7 2010-05-09 06:50 B1 HSL 0.39 R1 U 07:17 1 60 M 3 79 20.9 22.2 2010-05-09 07:00 B1 HSL 0.39 R4 B 07:52 6 52 F 1 75 21.1 16.0 2010-05-09 08:00 B1 HSL 0.39 R2 U 08:56 NA 63 M 1 79 20.5 20.2 2010-05-09 09:40 B1 HSL 0.39 R3 B 10:24 NA 64 F 1 73 21.6 17.6 2010-05-10 07:10 B1 HSL 0.39 R1 U 07:42 6 62 F 0 76 21.4 16.8 2010-05-10 08:50 B1 HSL 0.39 R2 U 09:24 5 65 M 4 74 20.7 20.5 2010-05-12 07:10 B1 HSL 0.39 R4 B 07:46 4 66 M 2 77 21.2 19.2 2010-05-12 08:30 B1 HSL 0.39 R3 B 09:05 4 61 M 5 79 21.8 22.5 2010-05-13 10:50 B3 HSL 0.39 R1 U 11:17 2 68 F 1 73 21.6 18.5 2010-05-16 06:10 B1 HSL 0.39 R2 U 06:42 4 73 F 4 72 20.7 18.6 2010-05-20 07:10 B3 HSL 0.39 R4 B 07:47 5 69 F 3 74 21.3 18.7 2010-05-20 08:00 B3 HSL 0.39 R2 U 08:32 1 71 F 1 73 21.5 15.8 2010-05-20 08:00 B3 HSL 0.39 R3 B 08:55 3 70 M 3 76 21.1 20.7 2010-05-20 09:00 B3 HSL 0.39 R1 U 09:40 1 72 F 0 77 21.5 18.2 2010-05-22 10:00 B3 HSL 0.39 R1 U 10:30 1

103 Table A.2. Individual Yellow-rumped Warbler data. Wing = unflattened wing chord (mm), tarsus given in mm, fat given on scale of 0-7, masses given in g, HSL = Holohil Systems Ltd. model BD-2N, NA = unknown.

Bird Capture Transmitter Release Stopover ID sex fat wing tarsus mass date time site make mass site time duration 13 M 3 72 17.2 12.9 2009-04-25 09:30 B1 HSL 0.39 R3 10:36 NA 14 M 4 79 18.8 15.0 2009-04-26 07:20 B1 HSL 0.39 R3 08:00 NA 17 M 2 74 19.5 13.5 2009-04-28 07:30 B1 HSL 0.39 R3 08:35 7 8 M 0 73 19.7 11.8 2009-04-28 07:00 B1 HSL 0.39 R2 08:43 2 18 M 3 75 18.1 13.5 2009-04-28 10:10 B1 HSL 0.39 R1 11:08 5 19 M 2 75 18.9 13.2 2009-04-30 10:10 B1 HSL 0.39 R2 10:45 5 20 F 4 72 18.5 14.9 2009-05-02 08:10 B1 HSL 0.39 R1 08:43 3 9 F 3 69 18.4 13.7 2009-05-02 09:10 B1 HSL 0.39 R3 09:45 9 10 F 5 72 18.6 16.7 2009-05-04 07:40 B1 HSL 0.39 R2 08:07 1 11 M 4 73 17.8 14.2 2009-05-04 08:10 B1 HSL 0.39 R3 08:54 1 3 M 3 74 18.3 13.7 2009-05-06 11:50 B1 HSL 0.39 R2 12:29 6 1 F 4 72 18.4 16.0 2009-05-08 07:10 B1 HSL 0.45 R1 08:00 NA 4 M 3 77 18.0 13.4 2009-05-08 07:10 B1 HSL 0.39 R3 08:05 4 35 M 4 76 19.9 16.0 2010-04-18 08:50 B1 HSL 0.39 R1 09:23 2 36 F 4 70 18.4 14.3 2010-04-18 09:20 B1 HSL 0.39 R2 10:05 5 37 F 4 70 17.7 14.1 2010-04-18 10:10 B1 HSL 0.39 R3 10:48 1 39 F 3 75 18.6 14.8 2010-04-22 07:00 B1 HSL 0.39 R1 07:25 NA 40 F 0 72 18.5 14.5 2010-04-22 08:00 B1 HSL 0.39 R2 08:22 6 38 F 3 73 19.0 14.2 2010-04-22 08:10 B1 HSL 0.39 R3 08:51 NA 45 F 3 74 18.2 14.2 2010-04-26 08:20 B1 HSL 0.39 R3 08:50 3 41 F 5 70 18.9 17.6 2010-04-27 07:20 B1 HSL 0.39 R2 07:43 1 42 F 4 72 17.1 16.4 2010-04-27 10:00 B1 HSL 0.39 R1 10:34 1 46 M 3 72 17.2 15.0 2010-04-28 08:40 B3 HSL 0.39 R1 09:15 1 48 M 3 72 17.6 13.3 2010-04-30 07:30 B1 HSL 0.39 R2 08:26 5 50 M 2 76 17.8 13.9 2010-05-02 07:00 B1 HSL 0.39 R3 07:36 5 55 M 4 75 18.2 15.4 2010-05-04 06:50 B1 HSL 0.39 R2 07:31 6 56 M 4 74 17.8 16.0 2010-05-04 06:50 B1 HSL 0.39 R3 07:50 6 59 F 4 69 17.5 15.0 2010-05-06 07:00 B1 HSL 0.39 R1 07:27 5 51 F 3 70 18.1 15.4 2010-05-06 07:30 B1 HSL 0.39 R2 08:01 1 67 F 3 66 16.9 11.8 2010-05-11 11:50 B1 HSL 0.39 R1 12:26 8

104