Migration Patterns of Flammulated Owls (Psiloscops

MIGRATION PATTERNS OF FLAMMULATED OWLS (PSILOSCOPS

FLAMMEOLUS) USING LIGHT-LEVEL GEOLOCATORS

______

A Thesis

Presented

to the Faculty of

California State University, Chico

______

In Partial Fulfillment

of the Requirements for the Degree

Master of Science

Biological Sciences

______

Fall 2018

MIGRATION PATTERNS OF FLAMMULATED OWLS (PSILOSCOPS FLAMMEOLUS)

USING LIGHT-LEVEL GEOLOCATORS

A Thesis

Shannon Rich

Fall 2018

APPROVED BY THE INTERIM DEAN OF GRADUATE STUDIES:

______Sharon Barrios, Ph.D.

APPROVED BY THE GRADUATE ADVISORY COMMITTEE:

______Christopher T. Ivey, Ph.D. Colleen A. Hatfield, Ph.D., Chair Graduate Coordinator

______Donald G. Miller, Ph.D. Raymond J. Bogiatto II, M.S.

PUBLICATION RIGHTS

No portion of this thesis may be reprinted or reproduced in any manner unacceptable to the usual copyright restrictions without the written permission of the author.

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ACKNOWLEDGEMENTS

This project was a huge collaborative effort across four states that spanned multiple years and many dedicated field crews in order to learn more about this wonderful and elusive species.

This project would not have been possible without the funding by the U.S. Fish and Wildlife

Service and the mentorship of David H. Johnson, who worked as a technical advisor to teach me everything he knew about geolocators and catching owls. I am forever grateful for the knowledge given to us by Brian Linkhart, whose work with flammulated owls has spanned over

3 decades, and the use of his Colorado field site. I am grateful to the guidance of Markus Mika and his field crew in the use of his Utah study sites. David Oleyar came out to Washington to help us capture owls when all our trapping efforts were failing. I would like to thank David

Arsenault for the use of his Lake Davis, CA study site and use of his field crew to not only capture owls, but also to help with collection of vegetation sampling data. There were so many volunteers and field crew members who worked tirelessly throughout the field work portion of this project and since I could not be in four places at once, they stepped up and helped to collect the information that was needed for this project.

I would like to thank my committee Colleen Hatfield, Don Miller, and Jay Bogiatto, for sticking with me long after I should have been finished and contributing their years of experience to help me turn a lot of raw data into a cohesive narrative on the life history of these fascinating birds.

Lastly, I would like to thank my partner Julian for sticking by my side during the last 6 years and constantly giving me motivation and words of encouragement whenever I wanted to

give up. I want to thank my family for supporting me during my long summers camping out in the woods and searching for owls in the middle of the night, and trusting that I wasn’t going to get lost out in the woods.

TABLE OF CONTENTS

PAGE

Publication Rights ...... iii

Acknowledgements ...... iv

List of Tables ...... viii

List of Figures ...... ix

Abstract ...... xi

CHAPTER

I. Introduction ...... 1

Geolocator Background ...... 1 Flammulated Owl Life History ...... 4 Motivations for this Study ...... 7

II. Methods ...... 9

Study Site Selection ...... 9 Nighttime Surveys ...... 14 Nest Checking and Searching ...... 17 Mist-netting and Capture ...... 18 Geolocator Attachment ...... 19 Recapture ...... 21 Vegetation Measurement Methodology ...... 22 GIS Analysis ...... 27 Statistical Analysis ...... 29

III. Results ...... 30

Migration Patterns ...... 30 Estimation of Winter Habitat ...... 39 Breeding Habitat Characterization ...... 48 Vegetation Structure ...... 48 Species Composition ...... 51

IV. Discussion ...... 53

Geolocators ...... 53 Geolocator Routes ...... 54

Timing of Migration ...... 57 Winter Habitat Selection ...... 64 Breeding Habitat Selection ...... 64 Limitations ...... 67

References ...... 68

Appendix A ...... 79

Appendix B ...... 83

Appendix C ...... 100

vii

LIST OF TABLES

TABLE PAGE

1. Deployed and Recovered Geolocators from Each Study Site ...... 30

2. Departure and Arrival Dates for Recovered Flammulated Owls ...... 38

3. Means, Standard Error, and P-values for Used and Unused Vegetation ...... 49

viii

LIST OF FIGURES

FIGURE PAGE

1. Flammulated Owl Distribution Map ...... 11

2. Study Site Locations ...... 12

3. Overview of Individual Study Areas ...... 13

4. Overview of Lake Davis, CA Study Site ...... 16

5. Close-up of Geolocator Unit ...... 20

6. Example of Geolocator Attachment ...... 20

7. Geolocator Attachment on Flammulated Owl ...... 21

8. Overlap of Flammulated Owl Territories to Determine Sample Locations...... 24

9. Overview of all Used and Unused Vegetation Sampling Points ...... 25

10. Vegetation Sampling Plot Set-Up ...... 27

11. Estimated Migratory Routes for all Recovered Flammulated Owls ...... 34

12. Estimated Migratory Routes for Pair of CA Owls ...... 35

13. Estimated Migratory Routes for Recovered UT Owls ...... 36

14. Estimated Migratory Routes for Recovered CO Owls ...... 37

15. Kernel Density Polygons for Pair of CA Owls ...... 40

16. Kernel Density Polygons for UT Owls ...... 41

17. 50% Kernel Density Polygons for UT Owls ...... 42

18. Kernel Density Polygons for CO Owls ...... 43

19. Overlay of Land Use Categories on CA 50% Kernel Density Polygons ...... 45

20. Proportion of Vegetation Categories for CA 50% Kernel Density Polygons...... 45

21. Overlay of Land Use Categories on UT 50% Kernel Density Polygons ...... 46

22. Proportion of Vegetation Categories for UT 50% Kernel Density Polygons ...... 46

23. Overlay of Land Use Categories on CO 50% Kernel Density Polygons ...... 47

24. Proportion of Vegetation Categories for CO 50% Kernel Density Polygons...... 47

25. Mean Shrub Cover Count in Used and Unused Flammulated Owl Habitats...... 50

26. Average DBH in Used and Unused Flammulated Owl Habitats ...... 50

27. Mean Percent Shrub Cover in Used and Unused Flammulated Owl Habitats ..... 51

28. Importance Values of Canopy Species, Understory Composition, and

Topographic Position in Used and Unused Flammulated Owl Habitats ...... 52

ABSTRACT

MIGRATION PATTERNS OF FLAMMULATED OWLS (PSILOSCOPS FLAMMEOLUS)

USING LIGHT-LEVEL GEOLOCATORS

Master of Science in Biological Sciences

California State University, Chico

Fall 2018

Flammulated owls (Psiloscops flammeolus) are small nocturnal owls that are thought to migrate long distances every year from summer breeding grounds in the western United States and southern Canada to winter habitat in Mexico. They are cryptic and elusive cavity nesters and little is known about their migratory patterns or winter habitat. They have been named a Species of Concern by the U.S Fish and Wildlife Service because of potential habitat destruction. The goal of this research was to track the movements of these owls during their migratory season and over the winter using light-level geolocators, which records ambient light levels that correspond to sunrise and sunset times to determine specific bird locations. During 2012-2013, 60 geolocators were attached to male and female flammulated owls in breeding sites in Washington,

Colorado, Utah, and California. In 2013-2014, 16 of these geolocators were recovered from birds in California, Utah, and Colorado. The migratory routes of these birds were analyzed using GIS and further analysis was performed to determine habitat characteristics of their winter home ranges in Mexico. Consistencies in migratory routes and wintering areas between owls from

different breeding locations contributed to greater knowledge about the migratory ecology of this owl. Novel results for the migratory behavior of a mated pair from California who used comparable routes and wintering areas before returning to breed together the following year, as well as a female owl from Utah with multiple years of data that showed her using a very similar route and wintering area between years also provided new information that was not yet confirmed about female flammulated owls. This geolocator analysis along with additional research on habitat preferences of flammulated owls in California is the first step in assessing the current status of this species with the goal of a broader western U.S. effort in the future.

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CHAPTER 1

Introduction

The migratory behavior of small avian species has been a mystery and challenge for as long as birds have been studied. Scientists have been able to study almost all other aspects of an avian species’ ecology, from diet, to mating behavior, to habitat preferences. But the small size of many avian species has hindered tracking them during long distance migrations. There are many examples of scientists placing Global Positioning System (GPS) trackers on large birds, such as whooping cranes (Grus americana) and Canada geese (Branta canadensis), and even traveling alongside birds in ultralight aircraft. However, many species, such as songbirds, are too small for such trackers, and nocturnal species such as owls are not as visible. Without the capability to learn about a species’ migratory behavior, scientists are only able to study a fraction of a bird’s life history and thus miss out on important information such as wintering habitat and important staging locations. These pieces of information are integral to learning about the broader question of why the birds might make such long migrations in the first place, given their small size. The broadening of technological advances into avian biology has paved the way for answering many of these questions.

Geolocator Background

Prior to the use of geolocation technology in avian biology, researchers relied on band returns to track longevity, population size and for predicting migratory movements. Hochachka and Fiedler (2007) looked at banding data for three different passerine species between 1973 and

2003 from banding stations in Germany. They wanted to see how banding numbers over years of collection compared to actual population sizes. However, they found that changes in the ability

to perform trapping efforts varied based on weather, trapping site habitat changes, changes in staging site use, and arrival timing of birds all affected capture and recapture numbers even though populations appeared to remain stable. Thus banding has limitations because there was no way to tell what a bird was doing between the time it was banded and recaptured.

The implementation of GPS trackers and radio telemetry has allowed scientists to learn more about migration than ever before, as can be seen with Sooty Shearwater (Puffinus griseus) and Cory’s Shearwater (Calonectris diomedea) migration across open ocean, and radio tracking of black-bellied Plovers (Pluvialis squatarola) in England to determine nocturnal and diurnal territoriality (Wood 1986, Ristow et al. 2000, Shaffer et al. 2006). GPS trackers have decreased markedly in size, but have not become small enough for small birds because of the battery size that is required (Akesson et al. 2012, Lisovski et al. 2012). Radio telemetry allows for fine scale tracking of mammals and birds throughout their home ranges, but the units do not have a battery that lasts long enough to track an animal for extended periods of time (Takahashi et al. 2008). It also presents the challenge of researchers not being able to follow their study organism over hundreds or even thousands of kilometers to their summer or wintering grounds.

Geolocators present a solution to those problems because not only can they be lightweight, but they can also record migration movements over long distances and long periods of time (Hill 1994, Hill and Braun 2001). They work by measuring ambient light levels, using day length and timing of sunrise and sunset to determine latitude and longitude of a bird’s location (Hill 1994, Hill and Braun 2001). The geolocator units can be ultra-lightweight, for example, less than one gram, which makes tracking the movements of smaller birds such as songbirds and small owls possible.

Geolocators have been used successfully on many types of small passerine and pelagic birds in order to learn more about their movements, especially those that make long range migrations. A study using geolocators attached to Eurasian hoopoes (Upupa epops ) produced the first evidence of the migration patterns for several individual birds as well as evidence of birds from within the same breeding population migrating to different areas (Bachler et al. 2010).

Another study looked at bar-tailed godwits (Limosa lapponica), and using geolocators found that migration timing was linked to latitudes. These researchers found that this not only applied to the godwit breeding grounds in Alaska, but also to the wintering grounds in New Zealand, up to

18,000km away (Conklin et al. 2010).

Though geolocators have increased our understanding of bird migrations, they have limitations. Geolocator units are less accurate than GPS or radio telemetry for determining precise locations, but provide an excellent tool for determining routes taken by birds, and an overall area used during the breeding and wintering seasons (Ryder et al. 2011, Stanley et al.

2012). Another problem associated with geolocators is the inability to determine latitude during an equinox because of the angle of the sun relative to the earth (Hill 1994). Therefore, location during this time must be estimated based on a bird’s known locations prior to and after the equinox. Geolocators also present a unique challenge because they must be recovered to download data (Beason et al. 2012). Thus geolocators are most successful for birds that show high site fidelity to their capture location.

In spite of these limitations, geolocator technology can provide insights into different aspects of a species life history. For example, the flammulated owl (Psiloscops flammeolus) is a species that is well suited for the use of geolocators not only because its migratory behavior is relatively unknown, but it is small in size and shows a high level of site fidelity to its breeding

grounds as an adult (Linkhart et al. 2016). Because of their relatively cryptic nature, overall population numbers are not known across their breeding range. They have been designated a

Species of Special Concern in Canada (Cannings and van Woudenberg 2004) and a Sensitive

Species by the United States Forest Service (Verner 1994) and a Bird of Conservation Concern by the U.S. Fish and Wildlife Service (USFWS 2008). Further research on their migratory behavior would provide critical insight into areas along their migration pathway that are important for stopover and winter habitat use.

Flammulated Owl Life History

Flammulated owls are small insectivorous nocturnal owls that inhabit western North

America (Marshall 1939). The name flammulated refers to the orange “flame-like” markings on the owl’s wings and back. Several long term studies have been performed on breeding populations of flammulated owls, notably by Brian Linkhart in Colorado, Markus Mika in Utah, and David Arsenault in New Mexico. Collectively, these studies have provided much of what we currently know about the species. For example, flammulated owls are secondary cavity nesters that utilize previously excavated cavities or nestboxes (Marti 1994, Arsenault 2004,

Linkhart and Reynolds 2007). Flammulated owls primarily live and breed in mixed conifer forests dominated by ponderosa pine (Pinus ponderosa), fir (Abies spp.), and quaking aspen

(Populus tremuloides) at higher elevations across the western United States (Marshall 1939,

McCallum 1994, McCallum et al. 1995). These owls complete a long distance migration every fall when they leave their breeding grounds in the western United States and southern Canada and travel south to Mexico (Johnson 1963, Balda et al. 1975, McCallum 1994, Linkhart et al.

2016).

Other North American owls, like the snowy owl (Bubo scandiacus) and short-eared owl

(Asio flammeus) will stay in their breeding range unless there are food shortages, in which case they will look for areas that are similar to their preferred habitat in search of better food sources.

These types of migrations are often unpredictable and can be nomadic or irruptive in nature, and do not involve owls returning to the same wintering area year after year or even the same breeding area year after year (Clark 1975, Holt and Zetterberg 2008). Flammulated owls follow a migration strategy that is much closer to that of long-eared owls (Asio otus) and burrowing owls

(Athene cunicularia hypugaea), but on a much larger scale, especially relative to their body size.

Long-eared owls are secondary nesting birds and will use previously constructed nests rather than building their own (Marks 1986). They are known to migrate from the northern part of their range down into the southeastern United States and Mexico but will continually return to the same nesting area and even the same nest if they have been successful at nesting in the past

(Marks 1986). They will sometimes show nomadic behavior but it is unclear if this behavior is related to decline in available prey or unsuccessful nesting attempts (Marks 1986). Western burrowing owls are found throughout the western United States and it is believed that most will migrate south in the winter and then return to their breeding grounds the following year (Klute et al. 2003). From a 6 year study done by David H. Johnson on the Umatilla Chemical Depot in southeastern Oregon, burrowing owls with geolocators attached to them migrated south from their breeding grounds, sometimes not traveling far away, and other times venturing down into central California (unpublished communications 2018). These burrowing owls then returned to the breeding area to utilize the same burrow in successive years. Burrowing owls in the northern part of their range in southern Canada have been known to migrate south all the way to Texas

(Klute et al. 2003).

Flammulated owls are unique because not only do they show a high level of philopatry to their breeding grounds, but they complete a migration that is far greater than many owl species that are several times larger than them. Flammulated owls show a high level of site fidelity to their breeding grounds, with males having higher site fidelity than females (Reynolds and

Linkhart 1990, Linkhart and Reynolds 2004, 2007, Linkhart et al. 2016). This is most likely because males defend a territory in order to attract females. They therefore would return to a nesting site within a territory that was previously successful for them (Marshall 1939, Marti

1994, Linkhart and Reynolds 2004). However, philopatry is more pronounced in adult owls and almost nonexistent in juveniles (Linkhart and Reynolds 2004, Arsenault et al. 2005, Linkhart and

Reynolds 2007, Mika 2010). In most instances, juveniles disperse from natal sites and do not return, leading to an increase in gene flow among populations (Mika 2010). This lack of natal philopatry could explain why flammulated owls continue to constitute a single genetic population rather than distinct subspecies throughout their breeding range (Mika 2010).

Flammulated owls are also likely to display perennial monogamy among pairs (Linkhart and Reynolds 2004, 2007). It is thought that females are attracted to high quality territories when it comes to choosing a mate and so females will either mate with the same male if he continues to defend that high quality territory, or will pair with a new male with a higher quality territory

(McCallum 1994, Linkhart and Reynolds 2007). It is not fully known if this high quality habitat is related to cavity availability, vegetation diversity, or insect availability.

Motivation for this study

A major gap in our current knowledge of flammulated owls is the detailed migratory activity of these owls across their entire breeding range. It is not known if there are specific migratory pathways being used by owls and how these pathways vary between different breeding locations. We also do not know how migratory behavior varies between breeding pairs of owls.

There is also a lack of knowledge regarding the wintering areas that owls are traveling to and how those habitats compare to their breeding habitats. The goals of my study were to:

- Identify migration routes for flammulated owls

- Evaluate how migration routes and migration timing varies between flammulated owl

populations from different geographic regions

- Identify winter habitat for flammulated owls for different flammulated owl populations

My thesis used light-level geolocators to track the migratory movements of flammulated owls from their breeding grounds to and from their wintering grounds. Geolocators were lightweight enough to be attached safely and securely to flammulated owls, which have historically shown high return rates to their breeding grounds to ensure a high chance of geolocator recovery

(Linkhart and Reynolds 2007).

Flammulated owls from four different breeding locations, Washington, Colorado, Utah, and California, were fitted with geolocators in an attempt to learn more about the migration and habitats of these owls. Once geolocators were recovered, migration routes were estimated, and a kernel density analysis was performed in ArcGIS to analyze owl location data to estimate not only where each owl spent the winter, but also the type of habitat associated with that area.

Because territory quality seems to play an important role in the life history of these owls, a fourth goal of my study was to:

-Compare habitat characteristics on breeding grounds in northern California where

flammulated owl habitat has not previously been studied.

My thesis research is unique in that it examines migrations patterns for several flammulated owl populations spread across the entire breeding range to establish patterns and differences in the movement and winter habitat use of these owls. Though a previous study analyzed the migratory behavior of flammulated owls in a population in Colorado (Linkhart et al.

2016), this is the first large scale effort to understand migration patterns at a broad scale for this species.

In addition, an in-depth look at the features of the vegetation structure within used and unused habitat for the northern California population could provide insight on specific features that make some habitat conditions more attractive to the owl. This evaluation also allowed me to compare habitat selection in northern California to other studies that have characterized flammulated owls breeding habitat. Results from this study support a key role in determining flammulated owl life history. Conservation initiatives could also benefit from this information in order to determine the areas that are of most importance to flammulated owls throughout all stages of their life cycle.

CHAPTER 2

Methods

Study Site Selection

Study sites for this project were chosen to include a large subsample of the historic breeding range of flammulated owls in North America (Figures 1 and 2). Utah and Colorado already had long-term monitoring programs (Figure 3) sponsored by Hawkwatch International

(Markus Mika) and Colorado College (Brian Linkhart), respectively, and were ideal candidates for likelihood of capture and subsequent recapture of owls. The study site in Utah was comprised of four different locations; one near the Snow Basin Ski Resort near Huntsville, UT in Weber

County, another location south of the city of Mantua on the slopes of Black Mountain in Box

Elder County, a third location at Public Grove Hollow, north of Ogden in Weber County, and a fourth location at 3-Mile Canyon, north of Public Grove Hollow in Weber County (Markus

Mika, personal communication 2012). The Colorado study was located in the Manitou

Experimental Forest, west of Colorado Springs in El Paso County (Linkhart et al. 2016).

Washington was chosen based on previously recorded detections by the United States Forest

Service (USFS) during avian surveys in the Naches Ranger District, northwest of Yakima in

Yakima County (Figure 3). California had a relatively new monitoring program in place near

Lake Davis California in Plumas County through Plumas Audubon Society, and was added to the group of study sites in the second year (2013) of the project (Figure 3). This thesis research was a collaborative effort between a study sponsored and funded by the U.S. Fish and Wildlife

Service under the leadership of David H. Johnson of the Global Owl Project, as well as the

assistance of leaders of the California, Utah, and Colorado long term monitoring programs,

David Arsenault, Markus Mika, and Brian Linkhart, respectively.

The sites in Colorado and Utah were ideal not only because they had long term monitoring programs but also because Colorado’s monitoring program included both historic and actively used nest sites (30 years of research) and the Utah study area had established nest boxes with high occupancy rates (approximately 180 nest boxes across four locations). These sites were ideal because owls using nests show a greater likelihood of return to that same territory than a male or female of unknown breeding status (Linkhart and Reynolds 2007). A nest box program in California was still in the early stages of establishment and thus additional nighttime surveys were needed to determine active territories (130 nest boxes across 10 locations). In contrast, at the Washington site, this study was the first to attempt to locate active nest sites. All field work was performed as a collaboration between the field crews performing ongoing research at each breeding location and the study being conducted by David H. Johnson, with my thesis research as an extension of that study.

Figure 1: Distribution of flammulated owls across their historic range. Map created for use by South Dakota Birds and Birding (2003) Reprinted with permission by Terry Sohl ([email protected]).

Figure 2: Banding locations of flammulated owls in Colorado, Utah, Washington, and California. Map created in ArcGIS 10.4 by Shannon Rich.

B A

C D

Figure 3: Overview of each study area: A) Four subareas in northeastern Utah, managed by Hawkwatch International (Markus Mika and David Oleyar) B) Boundary of study area in Manitou Experimental Forest, managed by Brian Linkhart (Colorado College) C) Boundary of study area in the Naches Ranger District in southcentral Washington D) Boundary of study area in northeastern California at Lake Davis, managed by David Arsenault (Plumas Audubon Society). Maps created in Arc GIS 10.4 by Shannon Rich.

Nighttime Surveys

Flammulated owls are strongly nocturnal, and nighttime surveys were conducted to determine presence of flammulated owls as well as territory boundaries of male owls. These surveys were conducted in Washington and California, using two different methodologies for route choice. Different methodologies were used at each of the sites because each individual site had its own ongoing research project. We used the method that was already established at each site because the overall goal was to detect owls, determine territories, and attempt capture of owls. Because this project was a collaborative effort between many people, it was important to have seamless integration with on-going research.

In Washington, USFS roads and trails were used as driving routes for the night surveys.

Roads were chosen that were close to where previous detections had been made during other surveys. David H. Johnson, various volunteers, and I walked the lengths of the roads, stopping approximately every 160 meters to listen for spontaneous calling and to do playback. Surveys would begin a 30 minutes after sunset and would continue until owl responses decreased or stopped altogether. Surveys would also stop early or were not performed if there were high winds, e.g. greater than 16kph that made it difficult to hear owls calling. The playback protocol consisted of recorded flammulated owl calls, including male broadcast calls, male territory calls, and in some cases female calls. These calls were played using a MP3 Western Rivers Predation

Call Box. Surveyors could also perform their own calls if there was no response to the playback.

For the most part, male broadcast calls were used most frequently, and nearby territorial males were likely to respond to these calls alone. Other calls could be used if surveyors were having trouble getting a response or were trying to determine if females were present in the area.

In Washington, at each survey point, the surveyor would begin the playback recording which consisted of a minute of silence and then alternating minutes of calling and silence. The first minute of silence was important to listen for any spontaneous calling. These spontaneous calls would be ideal because they could give an unbiased location of the owl without any outside interference. If at any time an owl responded, the surveyor would record a bearing using a compass and also an estimated distance of how far away the owl was located. The surveyor would record any and all responses that they heard from flammulated owls especially noting if an owl seemed to be moving closer. If multiple owls were recorded calling at the same time, it would potentially mean that surveyors were located along a territory boundary, and it would be the best way to determine how the owls were positioning themselves. Sometimes owls would silently come in close to the playback, so it was important to watch for owls flying in the vicinity. Surveyors would listen for the sounds of any female responses as these could be indicative of a nearby nest. All responses were recorded and mapped onto a large topographic map of the area to determine which areas were actively being used to maximize efficiency in capture attempts.

In California, the study area was divided into 10 subareas (Categorized A-J), each consisting of two paired 1 km x 1km squares, for a total of 20 1km squares (Figure 4). Within each square were a set of 5 points set up in an “X” pattern. This study design was set up by

David Arsenault for his ongoing research with the Plumas Audubon Society. The surveyor would choose a specific subarea to survey in a given night and would walk; visiting all 10 of the points within the two 1km x 1km squares and record bearings and distances of any responses heard. It was important to get as close to the designated survey points as possible to accurately map the

responses. The same 10 minute playback loop was used for all of the surveys conducted, as well as surveyor made calls.

Figure 4: Overview of Lake Davis study area and subareas. Yellow squares represent boundaries of subareas and red dots are set survey points. Map created in Arc Map 10.4 by Shannon Rich. Layers created by David Arsenault of Plumas Audubon Society.

Nest Checking and Searching

Locating nests was an integral part of the study because owls are most easily captured at their nest sites. In Colorado, previous research by Reynolds and Linkhart (1980-present) has revealed many of the possible locations of nests enabling investigators (Brian Linkhart and his field crew) to use cameras mounted on 18-m telescoping poles to check inside cavities and determine nest presence or absence. If nests were present, nestlings were monitored to determine when they would be old enough so that it would be safe to attempt capture of the adults.

In Utah, a long-term nest box program was in place that enabled the Hawkwatch

International field crew and me to check boxes periodically for presence or absence of a nest.

Owls using nest boxes were readily captured using a mist net because the boxes were low (2.5-

3m above the ground) and capture attempts could be easily performed. These nest boxes were checked periodically during the breeding season to track the progress of nests and determine the ideal time to attempt capture, i.e., when nestlings were big enough that both parent owls could leave the nest to hunt for food items.

In Washington, because there were no known nests, David H. Johnson, volunteers, and I had to rely on the results of the nighttime surveys to determine territories that might contain a nest. Strong, repeated male responses or any indication of a female response were given priority when choosing areas to focus on for nest searching. Investigators also went out during the day with telescoping poles with mounted cameras to check any tree cavities that had the potential to be used by a flammulated owl.

In California, the established nest boxes were checked first, using a telescoping pole with a mounted camera to determine occupancy. Results of the nighttime surveys were also used to

determine the highest probability areas to focus on in the event that nest boxes were not utilized.

Nest checking and nighttime surveys were conducted by David Arsenault and his Plumas

Audubon Society field crew and me.

Mist-netting and Capture

Once active nest sites were found, capture attempts of adult owls for geolocator attachment occurred after eggs had hatched and the young were old enough to thermoregulate.

Male owls were targeted because they typically show higher site fidelity (Linkhart and Reynolds

2007). In instances where there were fewer nests found, females were also targeted in order to gather data on pair behavior and site fidelity. After sunset, researchers watched owl behavior to determine flight patterns. One to two mist nets, depending on openness of the area, were then set up in front of a box or just off to the sides in order to capture owls as they attempted to enter or exit a box.

In areas where an active territory had been located, but no nest had been found, capture of male owls was attempted using mist nets and audio playback. In these instances, an area deemed suitable to attempt capture was located in the interior of the territory (determined by mapping of nighttime survey data) with smaller trees and surrounding vegetation to prevent owls from flying over and avoiding the nets. A small decoy owl was placed in the open space in the middle of the net array to make it seem like an intruding owl was inside the target owl’s territory. To avoid detection, the nets were set up prior to sunset and before the owls became active. An array of 4-6 nets was spread out across the chosen open area, attempting to cover openings in the trees and potential flight paths of incoming owls. Nets ranged in length from 2-12 m, and the top of the nets were often positioned 7 m off the ground. A key focus of net placement has to do with the

potential flight path of the owl. Playback would begin 45 minutes after sunset and researchers would stay nearby, out of sight but within hearing range, and preferably spread out to cover all directions to determine where owls might be coming from. One person would operate the playback and all would listen for owl responses or owls captured in the nets. This process typically took several hours per bird.

Geolocator Attachment

Once captured, owls were banded with USFWS size 3 bands, weighed, and their wing measurements were taken. The geolocators were manufactured by Migrate Technology, model

MK10B-S and had a 15-month battery with a 25mm stalk that was shrink-wrapped with a flexible plastic to protect from weather and exterior forces (Figure 5).These units were procured by David H. Johnson and he had received the necessary permits to attach leg bands and geolocators to adult owls. Geolocators weighed 1.0 gram with unit and harness material, which was less than 2% of body weight of any owl captured, as per standards of weight limitations for transmitters on birds (Caccamise and Hedin 1985).The harness was attached in a backpack design with 35 kg tensile strength Spectra braided fishing line.. The loops of the backpack were slid over the bird’s wings and attached with a metal jewelers crimp in the front at the sternum

(Figure 6). The geolocator was placed on the owl’s back and enough slack was given to be tight enough that it wouldn’t slide off the bird or become displaced but not too tight that it would injure the bird or impede its flight. Knots were tied at the base of the geolocator once the desired tightness was achieved and again fastened with a metal jewelers crimp (Figure 7). When the attachment was complete, the bird was held without any artificial light in open hand. After 5 min owls typically flew off all on their own. All owls were captured, handled, and released inside their own territory.

Figure 5: Underside of geolocator unit showing the individual identification number for future recapture and data analysis. Photo credit: David H. Johnson

Figure 6: Example of geolocator attachment as would be seen on flammulated owls. Photo credit: David H. Johnson.

Figure 7: Flammulated owl with geolocator attached prior to release in Washington. Photo credit: Danielle Munzing

Recapture

After birds were fitted with geolocators and released, (in 2012-13 for Washington and

Utah), 2012 in Colorado, and 2013 for California) recapture was attempted the following year to retrieve geolocators. This occurred in 2013-14 for Washington, Utah, and Colorado, and in 2014 for California. Additional capture efforts were undertaken in 2015-16 as part of the ongoing monitoring work in Colorado and Utah, with no additional geolocator marked birds recaptured.

For areas where birds were captured within territories lacking known nest site locations, such as

Washington and California, data from nighttime surveys was used to determine if birds were still using those territories. If a territory was still active, researchers attempted recapture using the same methods of mist net placement, lure decoy, and playback as with the initial capture. It was not possible to tell if the owls captured were the target owls until they were in hand. If a captured owl had a geolocator on it, the bird was weighed and the geolocator removed to be processed

later. Owls were also weighed to determine if there were any significant changes and then released. No owls were recaptured having lost their geolocator or harness during the study period.

Vegetation Measurement Methodology

For the California study site, a vegetation analysis was performed to look at habitat selection and hypothesized differences between habitat that was occupied or “used” by owls and habitat that was unoccupied or “unused” by owls. Used habitat was characterized as areas where owls had been detected over the course of the nighttime surveys performed in 2012-2014, and unused habitat was characterized as habitat where owl detections had not occurred. For all further data analysis, those territories that were occupied by owls will be referred to as used and areas where owls were not detected will be referred to as unused. Owl detections from the nighttime surveys heard within approximately 200 meters (these detections were more likely to be from an owl that was displaying strong territorial behavior and actively defending a territory, rather than just responding to the playback) of the surveyor, were entered into ArcMap 10.4, and

120m buffers were added around each point to account for the size of a territory (274 M) that a flammulated owl is known to utilize (Figure 8) (Reynolds and Linkhart 1984, 1987). The random point generator tool (ArcMap 10.4) was used to randomly place sample points within the “used” boundaries to establish vegetation plots to be sampled (Figure 9). Areas outside of the used boundaries but still inside the boundaries of each subarea were then used to generate random points to survey for vegetation in the unused habitat. There were 10 individual subareas in total

(Figure 9) and a total of 40 points each were chosen for both used and unused territories from the combined study areas. The number of sample points was chosen in order to give a large enough sample size to be able to analyze for trends. Ideally, there would be an average of four points per

subarea but for a few areas with less than four owl detections, points were chosen from subareas that had more than four detections. Four unused points were chosen from within each of the 10 A study areas.

A B

Figure 8: A) Individual territories mapped for male flammulated owls (FLOW in this graphic) in one subarea of the California study area from 2012-14. Large outer boxes represent the boundaries of the subarea and colored polygons represent mapped territories in each year and B) Overlapping areas of the territories used to randomly choose “Used” and “Unused” survey sample points. Areas that overlapped for at least two of three years were used to choose the “Used” points and “Unused” points were randomly generated in the area that fell outside of the territories but inside the of study area boundary. The “Unused” points had to be far enough away from territories for the vegetation sampling protocol to be carried out without overlapping. Initial territory boundaries were created by David Arsenault and overlap layers were created by Shannon Rich.

Figure 9: Overview of vegetation sampling points in “Used” and “Unused” habitats across the ten subareas of the Lake Davis study area. The same protocol displayed in Figure 8 was used for each of the ten subareas in the study area. Map created in ArcMap 10.4, layers created by David Arsenault and Shannon Rich.

The protocol used for the vegetation analysis followed that of Groves et al. (1997) in which researchers studied the density, distribution, and habitat use of flammulated owls in Idaho.

In my study, each vegetation sampling plot was a 3.1 hectare circular plot that was further divided into five 0.04 hectare subplots with one subplot located at the center of the sampling plot and the other four subplots located 50 meters away at each of the cardinal directions (Figure 10).

Researchers used a Garmin 72H GPS unit to navigate to each subplot center point and established the subplot with an 11.3 meter radius. Each of the five subplots had several measurements taken, including topographic position (such as directional slope), aspect (using a clinometer), dominant tree cover species and understory species, number of canopy layers, stand age (classified as young, mature, old, or mixed), and percent canopy cover (using a densiometer).

A compass was used to randomly choose a direction, and an 11.3 meter transect was measured out from the center of each subplot. Along the established line, percent ground cover of woody

(such as woody debris) and non-woody vegetation (herbaceous vegetation) was measured as a percentage of the transect line that intersected some type of ground cover divided by the total length of the transect. This same method was used to measure percent shrub cover along another

11.3 meter transect radiating out from the subplot center and a randomly chosen in another direction. At each subplot, tree density and DBH (diameter at breast height) were measured using the point quarter center method (Cottam and Curtis 1956, and Groves et al. 1997) where the nearest tree within the 11.3 m radius within each of the four quadrants was measured for distance from the center point, DBH, and tree species. This methodology for vegetation sampling was completed for all subplots within the main sampling point.

Figure 10: Vegetation sampling plot showing sub-plot set-up for each used and random point to record all vegetation measurements (left). The point-quarter center method was used in each subplot to measure the nearest tree distance, DBH, and tree species (right).

GIS Analysis

Once geolocator data were recovered from the units, date and location were converted from a text file into a usable shape file that could be viewed and edited in ArcGIS 10.4 software (see Appendix A for full protocol). All points that had a latitude and longitude coordinate were displayed on the map to perform editing. Points that were deemed obviously incorrect (such as located in the ocean) or too far away from the majority of the points (too far away for the bird to physically travel in the given period of time), were deleted to provide a more fine-tuned route of bird movement (Stutchbury et al. 2009). This was performed for both points along the migratory route and the points around the estimated winter location. Using the drawing tool in ArcGIS, a line was drawn following the route that the points followed to provide an estimate of the route that the bird took after leaving its breeding ground and then again after it left its wintering ground (Heckscher et al. 2011). A kernel density analysis was performed on the points estimated to be those on the wintering location (Eraud et al. 2013) (see Appendix A for full protocol). The ArcGIS kernel density tool was used to draw 50, 75, and 90% confidence

interval polygons to provide a probability estimate based on the point densities of recorded locations of where the bird spent its time during the nonbreeding months. The 50% confidence interval polygon was overlaid on a 250m resolution raster map of the 2010 North American Land

Cover Data Set Map (CEC 2013)) and the raster map was clipped for each individual owl’s polygon to display the different land cover types and proportions for the area that the owl was predicted to have spent the winter. Land use categories that were deemed more likely to be suitable habitat for a flammulated owl (i.e., forest compared to urban) provided a more accurate estimate of where the owl might have actually been located. I compared the proportions of the appropriate land use categories to the overall total land use within the polygon. After removing those categories that would be unlikely for flammulated owl use, such as grasslands, wetland, cropland, barren lands, and urban, the habitat types with the strongest representation were tropical/subtropical deciduous forest, temperate shrubland, and mixed forest. In some categories, sub-polar was used to describe the habitat associated with the area that the owl wintered in, but this classification refers to higher elevation forests where snow is likely but temporary, and is still indicative of acceptable habitat for the owls. The resulting land use categories are indicative of the types of habitats that are suitable to flammulated owls based on the types of habitat that they use during their breeding season and based on winter habitat use research by Linkhart et al.

(2016). I focused on the 50 percent kernel polygons because these polygons represented the core areas that the owls were more frequently located based on the geolocator data. I merged all 50 percent overlapping polygons together for the owls from each respective breeding location when calculating the proportion of each potential land use type. The final proportion of the estimated wintering area had the highest likelihood of occupation by owls.

Statistical Analysis

Vegetation data were analyzed to look for differences between used and unused habitat.

The five subplots from each vegetation point were averaged together for 40 used and 40 unused data points. F-tests were performed to determine equal or unequal variances, and which type of t- test should be performed. Each individual characteristic was compared using a standard t-test and graphed to show statistical significance with error bars. Species composition comparisons were made between the overstory species and understory species found in the used and unused habitat.

I calculated importance values to determine which overstory species from the nearest tree sampling data were of most importance in the used compared to unused habitats. I did this by calculating relative density of each tree species, relative frequency or each tree species, and relative dominance of each tree species, and then adding them together.

CHAPTER 3

Results

Migration Patterns

Of the 60 geolocators that were placed on adult male and female owls in Washington,

Colorado, Utah, and California in 2012-2013, 16 were recovered in 2013-2014 (Table 1). One geolocator from this study and three geolocators from a complementary study by Brian Linkhart from Colorado College were also recovered in Colorado on male owls. We used these complementary geolocators because they were put on owls during the same breeding season as our geolocators, and bolstered our sample size, allowing us to make comparisons between the different sites. Ten geolocators were recovered from nine males and one female in Utah. Two geolocators from a pair of owls were recovered in California. None of the geolocators put on owls in Washington were recovered.

Table 1: Total deployed and recaptured owls with geolocators across all four breeding locations

California Utah Colorado Washington

Deployed Recaptured Deployed Recaptured Deployed Recaptured Deployed Recaptured Males 5 1 22 9 8 1 13 0 Females 5 1 7 1 0 0 0 0 Totals 10 2 29 10 8 4 13 0

Analysis of the recovered geolocators allowed me to map the migration routes from breeding to winter grounds and back for the 16 owls from Utah, Colorado and California over a two year period (Figure 11). Of the owls recovered, both California owls, nine of ten Utah owls,

and two of four Colorado owls (for a total of 13 of the 16 recaptured owls) took southwestern fall migrations and northeastern spring migrations.

The breeding pair of California owls nested successfully in both 2013 and 2014 and were recaptured together (Figure 12). The male appeared to have a more direct migration route in both directions compared to the female. The pair varied in their time of fall departure, with the female leaving earlier than the male, but arrived on their wintering grounds in southwest Mexico at almost the same time (Table 2 and Appendix B). Their departure dates from the wintering grounds and arrival dates at the breeding grounds varied as well, with the male departing sooner from the wintering grounds and arriving sooner at the breeding grounds compared to the female.

The collective migratory routes for the 10 Utah owls can be seen in Figure 13 and show that the majority of these owls wintered in southern Mexico. These Utah owls were all banded in a relatively small geographical area within northern Utah, but took a variety of routes and wintered in different geographical areas. Some owls, (e.g., B891 and F707) took narrow, western routes and wintered on the west coast of southern Mexico. B921 and B914 took more centralized routes but still wintered on the west coast of southern Mexico. B912 and B726 took central fall routes and eastern spring routes, while wintering on the southwest coast and in central Mexico, respectively. F715 and B911 took central migratory routes, while wintering on the eastern coast of southern Mexico. The geolocator failed before F715 could return to the breeding grounds and thus I only have the first half of the migration information available. B904 and B900 took eastern migratory routes but wintered on the east coast and in central Mexico, respectively. B891, B900,

B914, and F715 were all banded at the area known as Snow Basin, and all of these owls wintered in the southwestern coast and southcentral portions of Mexico. B726 was the only owl to be banded and recovered from the Public Grove study site, and this owl was the only owl to winter

in the central region of Mexico. B904, B911, B912, B921, and F707 were all banded at the

Mantua location and all of these owls wintered along the southwestern coast of Mexico, with the exception of B904, which was the only Utah owl to winter along the mid-eastern coast of

Mexico.

The Utah owls had a high degree of variation in the departure timing from their breeding grounds, but showed less variation in the timing of arrival to the wintering grounds, departure from the wintering grounds, and arrival to the breeding grounds (Table 2, Appendix B). The female B911 departed and arrived to the wintering and breeding grounds in comparable timing to the male owls that were recaptured. What was of most interest about B911 was how similar the timing was between the two years before B911 was recaptured (Appendix B). The departure from the wintering area and arrival on the breeding area were within days of each other, and the wintering areas from both years were closely lined up with one another (Appendix B). The geolocator battery failed before B911 could reach the breeding grounds the second year.

The collective routes taken by male owls in Colorado marked variation in the winter migration routes and/or wintering areas (Figure 14). In contrast, the spring migration route for two of the males (BG4 and B721) did overlap for much of the spring migration, though they wintered in different regions, i.e. the southeastern coast of Mexico and south central Mexico, respectively (Figure 14). Other patterns of interest include BG1 who was the only Colorado male to take a more easterly route through central Texas. This particular owl also had the most northerly winter habitat of all owls in the study, wintering just south the US border, in the northeastern coast of Mexico. BG5 took a westerly fall migration and an easterly spring migration, wintering in central Mexico. The Colorado owls also showed variation in their departure dates, ranging from early September to early October, but generally arrived at about

the same time on the wintering grounds, late October and early November (Table 2 and

Appendix B). Their date of departure from the wintering grounds again varied, and their arrival on the breeding area showed slight variation across the month of May (Table 2).

The duration of the migration of the Colorado owls also showed some interesting differences. The amount of time that it took for the owls to travel from their breeding grounds to their wintering area ranged from about 2 months for BG4 and BG5, to about 6 weeks for B721, to about 4 weeks for BG1 (Table 2). The spring migration was timed to about 5 weeks for BG4,

BG5, and B721, but BG1 was an outlier in that the time from the departure of the wintering grounds to the arrival at the breeding grounds was about 12 weeks. This is markedly different from any of the other owls because it left the wintering ground around late February while the other owls did not leave until late March or early April. Because of the problem that an equinox plays in determining parts of the migratory pathway, it is unclear if BG1 made a stopover before returning to the breeding area.

Figure 11: Estimated fall and spring migratory routes for 16 recovered owls with geolocators. Each code of a letter and three numbers represents the code on the physical geolocator unit. Map created in ArcMap 10.4 by Shannon Rich. See Appendix B for individual owl migratory paths.

Figure 12: Estimated migratory routes of the pair of California owls recovered with geolocators. Each code of a letter and numbers represents the code on the geolocator. Map created in ArcMap 10.4 by Shannon Rich.

Figure 13: Estimated migratory routes of ten Utah owls recovered with geolocators. Codes of a letter and numbers represent the codes on the individual geolocators. Map created in ArcMap 10.4 by Shannon Rich.

Figure 14: Estimated migratory routes of the four Colorado owls recovered with geolocators. Codes with a letter and numbers represent the code on the individual geolocators. Map made in ArcMap 10.4 by Shannon Rich

Table 2: Departure and arrival dates for recovered geolocators on flammulated owls from each breeding location with standard error in days. The standard error was calculated for owls that we were unable to determine a specific departure date based on the equinox timing. The terms pre-migration and total migration refer to owls that were determined to have left their breeding grounds on a certain day but then made a stopover before finishing their migration. Note: there are multiple seasons of data for female B911 for she made migrations to Mexico in two consecutive years.

Geolocator Tag Location Fall Departure Fall Arrival Spring Departure Spring Arrival F712 CA 9/3/2013 11/4/2013 3/28/2014 5/3/2014 depart breeding 8/09/13 premigration #1 8/09/2013 F721 CA 11/3/2013 4/23/2014 5/25/2014 premigration #2 8/30/13 total 9/17/13 +/-10 days B726 UT 8/27/2012 10/25/2012 3/25/13 5/11/2013 B891 UT 9/28/2012 11/09/12 3/28/2013 5/14/2013 B900 UT 10/7/2012 11/11/2012 4/12/2013 5/12/2013 depart breeding 8/8/12 B904 UT premigration 8/08/12 12/09/2012 4/15/2013 5/16/2013 total migration 10/06/12 B911 UT 9/22/2012 11/8/2012 4/4/2013 5/15/2013 B911 UT 9/24/2013 11/9/2013 3/28/2014 unit malfunction B912 UT 9/4/2012 10/26/2012 4/12/2013 5/5/2013 B914 UT 10/8/2012 11/12/2012 Est 3/24/2013 5/11/2013 B921 UT 10/6/2012 11/8/2012 DJ Est. 3/26/2013 +/- 5 days 5/19/2013 depart breeding 8/17/13 F707 UT premigration 8/20/2013 12/6/2013 3/26/2014 5/16/2014 total migration 10/01/13 +/- 5 days F715 UT 10/10/2013 11/25/2013 unit malfuntion unit malfunction BG1 CO 10/2/2012 11/6/2012 2/28/2013 5/26/2013 B721 CO Est 09/17/2012 +/- 10 11/4/2012 3/26/2013 5/6/2013 BG4 CO 9/2/2012 10/26/2012 4/8/2013 5/19/2013 BG5 CO 9/1/2012 10/31/2012 4/7/2013 5/16/2013

Estimation of winter habitat

The geolocators provided data on each of the owls during the wintering season. Using this information, the kernel density analysis allowed me to estimate the geographic area where the owls spent the winter. This in turn allowed me to determine land use patterns and the associated habitat types within that area to provide an estimation of the owl wintering habitat.

The 50, 75 and 90% kernel density polygons for each of the owls from each state can be seen in figures 15, 16, and 18 for California, Utah and Colorado, respectively.

The kernel density polygons for the California owls show extensive overlap, and while the female owl has a larger overall polygon, the core habitat within the 50% polygon, that is, the polygon that represents the densest accumulation of data points, is the same for the two owls

(Figure 15). The kernel density polygons of the Utah owls show a great deal of variation, especially when they are all displayed together on one map (Figure 16). They range from coast to coast across southern Mexico. When all kernel density polygons are incorporated, it is difficult to discern the differences in the wintering areas of the Utah owls, but when just the 50% polygons are displayed, the variation is much more apparent (Figure 17). Of notable importance is the female owl with a year and a half of data, whose kernel density polygons overlapped almost entirely between the two years. The Colorado owls showed the most variation in their kernel density polygons, with each owl wintering in a different location, with the exception of BG4

(green) and B721 (orange) who had a partial overlap of their habitat (within the 50% polygon)

(Figure 18).

Figure 15: The 50, 75, and 90 percent kernel density polygons for the pair of California flammulated owls on their wintering area in Mexico. Map created in ArcMap 10.4 by Shannon Rich.

Figure 16: The 50, 75 and 90 percent kernel density polygons for the ten Utah flammulated owls on their wintering area in Mexico. Map created in ArcMap10.4 by Shannon Rich.

Figure 17: The map of 50 percent kernel density polygons of Utah flammulated owls to better distinguish differences in winter ranges. Note differences in scale between Figures 16 and 17. Map created in ArcMap 10.4 by Shannon Rich.

Figure 18: The 50, 75 and 90% kernel density polygons for the four Colorado flammulated owls on their wintering area in Mexico Map created in ArcMap 10.4 by Shannon Rich.

For the two California owls, the selected habitat categories (see Methods) accounted for

60 percent of the coverage of the 50 percent kernel density polygons (Figures 19 and 20). The predominant land use cover types were broadleaf deciduous forests and shrubland followed by mixed forest (Figure 20).

For the Utah owls, the most likely habitat categories accounted for 54 percent of the coverage of the 50 percent kernel density polygons (Figures 21 and 22). There was overlap in the types of habitats that were most common for both the California and Utah owls; several of the

Utah owls wintered on the western coast of Mexico as did the California owls. However, for the

Utah owls, temperate shrubland was the most common land cover type followed by tropical/subtropical deciduous forest, and mixed forest.

The land use classifications with the highest densities in Mexico for the Colorado owls were temperate shrubland, tropical/subtropical shrubland, and mixed forest, and accounted for

46 percent of the land use within the 50 percent kernel density polygons (Figures 23 and 24). The most common vegetation types found within this polygon were somewhat different from the habitat types that were found within the wintering areas of the California and Utah owls, with shrubland showing dominance.

Figure 19: The 50 percent kernel density polygon map with probable land use categories shown for wintering habitat in Mexico of California flammulated owls. Smaller inset shows inclusion of all land use categories.

25 Temperate or sub-polar needleleaf forest

Tropical or sub-tropical broadleaf 20 evergreen forest Tropical or sub-tropical broadleaf 15 deciduous forest Temperate or sub-polar broadleaf deciduous forest 10 Mixed forest

Tropical or sub-tropical shrubland Land Use Percentage 5 Temperate or sub-polar shrubland 0 Figure 20: Proportion of probable vegetation categories in 50 percent kernel density polygons of wintering areas for two California flammulated owls.

Figure 21: The 50 percent kernel density polygon map with probable vegetation categories shown for wintering habitat of Utah flammulated owls wintering in Mexico. Smaller inset map shows land use when all categories are present.

20 Temperate or sub-polar needleleaf forest Tropical or sub-tropical broadleaf 15 evergreen forest Tropical or sub-tropical broadleaf deciduous forest 10 Temperate or sub-polar broadleaf deciduous forest Mixed forest 5

Land Use LandPercentageUse Tropical or sub-tropical shrubland

Temperate or sub-polar shrubland 0

Figure 22: Proportion of probable vegetation categories in 50 percent kernel density polygons for 9 nesting Utah flammulated owls wintering in Mexico.

Figure 23: The 50 percent kernel density polygon map with only probable vegetation categories displayed for four nesting Colorado flammulated owls in Mexico. Inset map shows polygon map with all vegetation categories.

20 Temperate or sub-polar needleleaf forest

Tropical or sub-tropical broadleaf 15 evergreen forest Tropical or sub-tropical broadleaf deciduous forest 10 Temperate or sub-polar broadleaf deciduous forest Mixed forest

5 Tropical or sub-tropical shrubland Land Use Percentage

Temperate or sub-polar shrubland 0

Figure 24: Proportion of vegetation categories for 50 percent kernel density polygons for the four nesting Colorado flammulated owls wintering in Mexico.

Breeding Habitat Characterization

The goal of the vegetation characterization study in California was to evaluate if there were certain habitat features that flammulated owls were selecting for within the study area and how this compared with habitat features in other flammulated owl breeding habitat studies (See

Methods).

Vegetation Structure

Of the vegetation characteristics that were measured (Table 3), average shrub species count was significantly higher (p = 0.01, Figure 25) in used habitat (1.0 shrubs ± 0.1) compared to unused habitat (0.7 shrubs±0.01). Average tree DBH was also significantly different (p = 0.03,

Figure 26) between used and unused habitat. The trees in used habitat were significantly smaller

(mean dbh = 89.1 cm ± 4.4 cm) compared to the unused habitat (mean dbh = 103.7 cm ±4.6 cm).

Percent shrub cover was marginally insignificant (p=.06) and was greater in used habitats (15.0 ±

1.1) compared to unused habitats (11.0 ± 1.7) (Figure 27). Even though the majority of the vegetation characteristics were not significantly different between the used and unused habitats

(Appendix C), overall, data indicated that the used habitats displayed a more diverse understory while the unused habitats displayed a more developed canopy layer.

Table 3: Means, standard error, and p values for t-tests between used and unused vegetation characteristics in Lake Davis, California. Highlighted areas indicate significance.

Std. Vegetation Characteristic Mean p value Error

Average dominant Unused 1.4 0.1 0.48 tree species count Used 1.4 0.1 Average dominant Unused 1.4 0.1 0.91 understory species count Used 1.4 0.1

Average number Unused 2.4 0.1 0.55 canopy layers Used 2.5 0.1 Unused 2.0 0.1 0.41 Average stand age Used 1.9 0.1

Average percent Unused 54.9 1.9 0.19 canopy cover Used 51.4 1.9 Average percent Unused 15.6 1.3 0.31 “Non-Woody” ground cover Used 17.5 1.3

Average percent Unused 8.8 1.0 0.86 “Woody” ground cover Used 9.1 0.6

Average percent Unused 11.0 1.7 0.06 shrub cover Used 15.0 1.1 Average shrub Unused 0.7 0.1 0.01 species count Used 1.0 0.1 Unused 11.0 0.9 0.17 Average slope Used 12.9 1.0

Average tree Unused 5.0 0.2 0.34 distance (m) Used 4.7 0.2 Unused 103.7 4.6 0.03 Average dbh (cm) Used 89.1 4.4

Average basal area Unused 25.2 1.9 0.26 2 (cm ) Used 22.5 1.5

Shrub Cover Count in Used and Unused Habitat

1.20 p=0.01

1.00

0.80 Used 0.60 Unused 0.40

0.20 Average Average shrubcovercountshrubs) (#

0.00

Figure 25: Mean shrub cover count in Used and Unused flammulated owl habitats at the Lake Davis, CA study site, with standard error bars and p-value. Shrub cover count refers to the number of different species of shrubs within the sample plot. This measurement is meant to give insight into diversity of understory species within the sample plot.

Average DBH in Used and Unused Habitats 120

110 p=0.03

100

90 Used

80 Unused

Average Average DBH (cm) 70

Figure 26: Mean diameter at breast height (DBH) in Used and Unused habitats at the Lake Davis, CA study site, with standard error bars and p-value.

Percent Shrub Cover in Used versus Unused Habitats 18.00 p=0.06 16.00

14.00 12.00 10.00 Used 8.00 Unused 6.00

PercentShrubCover 4.00 2.00 0.00

Figure 27: Mean percent shrub cover in Used versus Unused habitats at the Lake Davis, CA study site with standard error bars and p-value.

Species Composition

In terms of species dominance, “Used” habitats showed higher values for incense cedar

(Calocedrus decurrens), western juniper (Juniperus occidentalis), and white fir (Abies concolor) while Unused habitats showed higher values for douglas fir (Pseudotsuga menziesii) jeffrey pine

(Pinus jeffreyi), and sugar pine (Pinus lambertiana) (Figure 28). Overall, there didn’t seem to be much difference between the importance values of the dominant canopy species in “Used” and

“Unused” plots. Common snowberry (Symphoricarpos albus) was the most dominant understory species in “Used” habitats and mule’s ear (Wyethia mollis) was the most dominant understory species in “Unused” habitats (Figure 28). North facing, southwest facing, and southeast facing slopes were the most common in “Used habitats”, while east facing slopes and flat areas were the most common in “Unused habitats” (Figure 28).

Importance Value for Dominant Canopy Species

120

100 80 60 Used 40 Unused

20 ImportanceValue 0 Incense Cedar Douglas Fir Jeffrey Pine Juniper White Fir

15 Used 10 Unused

PercentCoverage 5

0 Buckbrush Grass species Mules Ear Mt. Pine Needles Sagebrush Snowberry Woody debris Mahagony

25 20 15 10 5 Used Proportion 0 Unused

Figure 28: Top: Canopy species in Used versus Unused habitats in the Lake Davis study area in California. Middle: Comparison of understory composition using line-intercept method for Used and Unused habitats in the Lake Davis study area in California. Bottom: Topographic position from each sampling point in used and unused habitats in the Lake Davis study area in California.

CHAPTER 4

Discussion

The understanding of flammulated owl migration is very limited, especially across their entire breeding range. It is generally understood that they perform a long distance migration to

Mexico from across the western United States and southwestern Canada, but for most locations throughout their breeding range, this is based solely on absence from breeding locations during the winter and capture of owls at banding sites during the months of September and October when owls would most likely to be migrating. The lack of detail in migratory routes and location of wintering area limits the ability to learn more about the complete ecological picture of this owl’s life history.

Geolocators

The use of geolocators with flammulated owls provided insight into their migratory movements and behavior that would not have been otherwise possible. This technology has allowed a major question to begin to be answered about an important aspect of this bird’s life history. Prior to this study, the only information that was available for the migration of flammulated owls was anecdotal in nature and a study of one breeding population in Colorado

(Linkhart et al. 2016). While the study in Colorado using geolocators produced the first evidence of migration routes, timing, and wintering areas, there are still many questions to be answered in terms of the rest of the breeding populations of flammulated owls across the western United

States.

This study employed geolocators across four different breeding locations, and recovered geolocators from three of those locations. This allowed for the analysis of routes taken by individual owls as well as distinguishable patterns in the migratory movements of owls within a breeding location and between different breeding locations. I was also able to determine information about the wintering locations of each owl and was able to do a more in depth analysis of habitat types within each wintering area.

Geolocator Routes

Sixteen owls were recovered with geolocators over a two year period across Colorado,

Utah and California. Several patterns were discernable when analyzing the migration routes taken by the owls. Utah had the highest number of geolocator recoveries, and of the ten owls that produced data, nine used a southwestern route along the Rocky and Sierra Madre Occidental mountain ranges to reach their wintering grounds and a northeastern route along the Sierra

Madre Oriental and Rocky Mountains to reach their breeding grounds the following year. For the most part, these owls traveled to southern regions of Mexico, but were still significantly dispersed upon arrival. Because of the inability to get exact locations for the owls, it is unclear if any of these owls wintered in the immediate vicinity of one another, but the overlap of their wintering core areas (50% polygons) provides some evidence that they could at least be using the same habitat types. Utah owls wintered within the states of Michoacán, Guerrero, Oaxaca,

Veracruz, Puebla, and Guanajuato. What does seem clear is that mountain ranges seem to play a role in the routes used by these owls. Banding stations in New Mexico and Nevada were set up in the Manzano and Goshute Mountains, respectively, and captured many owls flying through open meadow areas in mixed conifer forests parallel to ridgelines (Smith 2008, Delong 2002).

This could be attributed to the habitat within the mountain ranges providing ample resources for

them to make the journey down to their wintering grounds (Linkhart et al. 2016). Flammulated owls are known to stage as they travel between their breeding and wintering grounds, sometimes just short stops and other times for longer periods of time, (Linkhart et al. 2016). According to thesis research by P. J. Thomas (2008), diurnal raptor migrants seem to be utilizing topography more than nocturnal raptor species, traveling parallel along ridgelines and utilizing favorable wind conditions. Nocturnal raptor species were only greatly affected by topography at high elevations (Thomas 2008). For the most part, calm to low winds seemed to provide the best conditions for capture of owls at banding sites (Smith 2008). If there are stronger winds, birds will be more likely to use tail winds to conserve energy and increase flight efficiency (Thomas

2008).

The Colorado owls were all banded within a small geographic breeding area and yet displayed a high level of variation in their migratory routes. The Colorado owls also displayed a pattern that was notably different from that of the Utah owls in that their migratory routes varied and were less restricted by geographic landmarks such as large mountain ranges than the Utah owls. Two of the four owls (BG4 and B721) took very narrow routes, with southwestern fall migrations and northeastern spring migrations also along the Rocky and Sierra Madre Oriental mountain ranges. The other two owls took migration routes that were markedly separated geographically from the other owls. One of these two owls (BG5) seemed to follow the Rockies and Sierra Madre Occidental on the southern journey and then the Sierra Madre Oriental and

Rockies on the northern migration. The fourth owl (BG1) had the most distinctive route, apparently migrating eastward through Texas before wintering near the eastern side of the Sierra

Madre Oriental near the Texas/ Mexico border. McCallum (1994) noted that flammulated owls have been documented near the Gulf Coast and in central Texas, suggesting that some

individuals might migrate east of their breeding range and then winter in Mexico in the Sierra

Madre Oriental, the eastern most mountain range in Mexico. The return journey of BG1 was more straightforward, traveling northwest along the same mountain range through western Texas and eastern New Mexico. Colorado only has mountains bordering one side of it and thus owls could use varying routes to reach their wintering areas based on which areas provide resources for stopovers. The states where the Colorado owls wintered were Tamaulipas, Zacatecas,

Aguascalientes, Jalisco, Oaxaca, and Puebla.

The California owls had the most distinctive migration pattern. This study was the first to put geolocators on female flammulated owls, and even though only two females were recovered, they both provided information that was novel to the study of flammulated owls. The California female (F721) had a geolocator attached along with her mate in 2013 and both were recaptured in 2014. When their geolocators were analyzed, both took southwestern fall migrations and northeastern spring migrations along the west coasts of California and Mexico and Sierra Nevada and Sierra Madre Occidental mountain ranges. Not only did they take very similar routes, but their wintering areas overlapped in the region of Jalisco, Mexico, showing that they potentially could have spent the winter together. The second female owl (B911) was originally captured in

Utah and was recaptured two years later in the same general breeding territory. B911 used almost identical routes for both fall migrations and wintered in the same area each year. The geolocator unit failed before B911 could return to the breeding area, so we were unable to determine the second spring migration route. Linkhart et al. (2016) had one male owl that also had a year and half worth of data and that owl also took a second fall migratory route that was similar to the previous year, as well as the same wintering area in both years.

The routes taken by all of the owls show that there isn’t one necessary pathway that must be taken every year. There are many different routes that eventually lead to many different regions in Mexico. This behavior is different from many other migratory species, such as the

Egyptian Vulture (Neophron percnopterus) that migrates at a consistent time each year, while utilizing different routes and different wintering areas (Lopez-Lopez et al. 2014). A study by

Stanley et al. (2012) tracked repeated migrations of wood thrushes (Hylocichla mustelina) and found that migration routes were variable from year to year, even when the birds were returning to the same wintering area from the previous year. They were able to vary their routes depending on the weather conditions that they encountered and availability of stopover locations along the way. Male wood thrushes arrived earlier to breeding locations than female wood thrushes, and birds that had already performed at least one migration arrived earlier than birds that were completing their first migration (Stanley et al. 2012).

Timing of Migration

The timing of the migrations was derived from the geolocator data. According to van

Woudenberg et al. (2008), flammulated owls in British Columbia have been known to start migrating as early as late August, whereas Reynolds and Linkhart 1987 and Linkhart and

Reynolds 2007 have found owls staying on their breeding range in Colorado until mid-October, showing that there is variation in migration timing of owls. The banding stations in Nevada and

New Mexico both had the highest capture rates during the month of September with a smaller number of captures occurring in early October (Delong 2003, Smith 2008). Besides these captures being much earlier than was expected, the majority of the owls captured were hatch years. One explanation of this timing was postulated to be young owls leaving earlier than adult owls as they venture from their nest and learn to fend for themselves (Smith 2008). Some of the

owls were recaptured a few days to a few weeks after their initial capture and it was believed that these owls were either using the banding site for a staging area or were possible local owls that had not departed for their migration yet (Smith 2008). Because banding efforts did not go past mid-October, it is unclear if more owls were traveling through the banding sites later into

October. But the presence of some adult owls captured in mid-September does agree with the timing of migration that I determined for the owls from my study. The California male and female had a difference in timing between departures, but arrived at the wintering grounds at almost the same time. I estimated the female performing a stopover period before her actual migration based on the geolocator data points and a lack of change in latitude of the female for an extended period of time that could not be attributed to normal shading events. There was also significant variation in the data points from her geolocator before she left her breeding area in early August, which could have been caused by increased movement after her young had fledged. Both owls arrived on their wintering grounds around 3 November 2013. There was a much larger difference in the departure dates from the wintering grounds, with the male leaving almost three weeks earlier than the female owl, 28 March 2014 compared to 23 April 2014. The male arrived earlier than the female, 3 May 2014 compared to 25 May 2014 respectively, and this could reinforce the idea that males will arrive earlier on the breeding grounds to reclaim their territory before their prospective partners arrive (Reynolds and Linkhart 1987a). The male returned to the same nesting territory of the previous year before the female, who arrived on the same territory where the pair successfully paired and bred in 2014.

The Utah owls had a later departure date from their breeding grounds relative to the

California pair, with most leaving between late September (9/22) and early October (10/10).

There were a few owls that were estimated to have left in late August and early September (8/27

and 9/4). These were determined by analyzing geolocator data points and basing the departure dates on a significant change in latitude. The migrating owls all arrived on the wintering grounds timed relatively close together in mid-November and departed at the end of March and beginning of April. There were two other owls that arrived around 26 October and two owls arriving around 6-9 December 2012. The two owls that arrived in early December appeared to both make stopovers soon after leaving their breeding grounds before making their final migration down to the wintering area. This could explain why they arrived later than most of the other owls if they had spent extended time on stopovers. Owl arrivals onto their respective breeding territories in the spring were still very closely timed, with most arriving in mid-May (5/5-5/19).

One female from Utah was captured after two years and the timing of the departure from the breeding grounds was almost identical for both years, as well as the arrival to the wintering grounds and departure from the wintering grounds The female also returned to the same general wintering area and the movements could provide evidence for potential site fidelity to wintering grounds in addition to breeding grounds. This is the first direct evidence we have of females demonstrating site fidelity at both breeding and wintering grounds. Linkhart et al. (2016) found similar results for one of their male owls recaptured after two years in that the owl utilized a similar route for multiple seasons as well as a similar wintering area. The timing of the migration of this owl was also comparable between years.

The Colorado owls departed their breeding grounds from the first week of September (1

September) to early October (2 October), and all arrived in the last week of October (26-31

October) to the first days of November (4-6 November). They showed a high level of variation in their departure dates from the wintering grounds, departing late February to early April (28

February. 26 March, 7 April, 8 April), and arrived on their breeding grounds throughout May (6-

26 May). These patterns are informative in that they show the importance of males arriving to their breeding grounds in a timely manner in order to be competitive in reclaiming their territory to attract a female partner (Reynolds and Linkhart 1987a, 1990).

The results from this study can be compared to the geolocator research that was performed by Brian Linkhart in Colorado between 2009 and 2011 (Linkhart et al. 2016). He attached geolocators to male flammulated owls and was able to retrieve four geolocators during his study. These males were from the same Colorado breeding population that we put out our geolocators on in 2012, and therefore were extremely useful in comparing migratory routes, timing, and wintering areas over a longer time period. The most notable similarities between the two studies were the comparable wintering area regions that both sets of owls traveled to.

Notable differences mostly related to a difference in departure timing from the breeding grounds between the two sets of owls.

All of the owls, regardless of breeding location, seemed to follow a migration pattern in terms of when they left their breeding grounds and when they returned. They all departed from their breeding grounds in early fall, most likely as resources became scarce due to seasonal changes. Their primary diet consists of nocturnal insects (McCallum 1994), which become less available during the winter months when vegetation is scarce and temperatures are cold. All of the areas where the flammulated owls are known to breed are at elevations that experience decreased temperatures and food availability during the winter; these owls must move to areas that are more stable because they are not able to hibernate or drastically change their diet in order to adjust to changing conditions (McCallum 1994). When they migrate to Mexico, they are traveling to latitudes that display warmer climates with the foraging habitat and prey base that

they require year round and they are able to refuel before they make the migration back to their breeding grounds.

An interesting question one might ask is why these owls migrate when they have a steady food source and favorable climate and habitat in Mexico. There are resident populations of flammulated owls that reside in southern Mexico during the breeding and nonbreeding season, with some even completing a much shorter migration down to Central America during the winter

(Mika 2010). However, because territory and access to resources are so important to the life history and breeding success of these owls, it could be postulated that they would move northward to similar habitats in order to reduce competition for resources during the breeding season (McCallum 1994). An increase in wing length the further north that birds are found has enabled them to make longer migrations (McCallum 1994). Birds will also engage in pre- migratory hyperphagia and weight gain in order to prepare for the migration after the breeding season (McCallum 1994, Delong 2006, and Stock et al. 2006). These owls are not nomadic in nature and thus would not simply move to any available habitat they might find (Stock et al.

2006). The study done by Stock et al. (2006) in the southern Boise Mountains in southwestern

Idaho compared the migratory strategies of flammulated owls to northern saw-whet owls, and found that flammulated owls displayed proportionately greater weight gain and body condition than saw-whets, and arrived earlier to the netting stations than saw-whets in order to avoid the cold temperatures in the later months. Data from banding stations in the Goshute Mountains in northeastern Nevada (Smith and Neri 2004, Smith 2005, 2006, 2008, 2009) and the Manzano

Mountains in central New Mexico (DeLong 2000, 2001, 2002) found similar results with flammulated owls arriving at netting stations in mid-September, compared to saw-whets that mostly arrived in mid-October. While flammulated owls rely on a diet of only invertebrates, saw-

whets consume a diet of small mammals and do not have the same restrictions in access to resources as temperatures decrease. Flammulated owls are found to perform longer migrations in the fall because they have been able to increase their fat reserves and energy to make the trip to their wintering area or a suitable stopover area (McCallum 1994, Delong 2006, Linkhart et al.

2016). The return journey to their breeding grounds in the spring is much quicker and more direct in order to reclaim territories and resources (Linkhart et al. 2016).

Over time, flammulated owls have been able to expand their range into what it is today because they have been able to use the large patches of suitable habitat across the western United

States and southwestern Canada (Mika 2010). According to Pulido (2007), birds have been able to colonize new areas by using them during the times of year when they are most favorable, and then retreating to an area that is favorable during the off season. This phenomenon can be referred to as migratory connectivity, and according to Webster et al. (2002), the different periods of their annual cycle are “biologically linked” in terms of the successful life history of the species, and form a set of complex interactions across space and time. The birds have evolved the ability to detect when conditions are becoming less favorable and when they need to move to a habitat that will support them. With site fidelity playing such an important role in flammulated owl breeding ecology, the strong migratory connectivity that they exhibit could lead to a decreased ability to respond to selective pressures (Webster et al. 2002), particularly in terms of climate change and habitat loss. They are able to move across a large patchwork network of favorable habitat in order to get them to their final destination, but as those patches get smaller, it could disrupt their ability to move and disperse (Mika 2010).

Even though flammulated owls are spread out geographically across North America, studies done by Mika (2010) and Arsenault et al. (2005) found that genetically, the breeding

populations of flammulated owls across the United States are still closely related, and are collectively less related to the resident population in Mexico. Studies done on breeding populations in Colorado by Reynolds and Linkhart (1990), Linkhart and Reynolds (2004) and in

New Mexico by Arsenault et al. (2005) found that there is a low level of natal philopatry to the nesting area, with most nestlings not returning in subsequent years. The authors found only one instance of a nestling returning to its natal territory. The study by Arsenault et al. (2005) found that of 26 juveniles that were banded, only two were recaptured. This could be an important reason why different populations are so genetically similar and perhaps why populations can continually be sustained by an influx of new owls (Mika 2010).

Flammulated owls are unique in relation to other raptor species because they perform such a long distance migration in relation to their body size. They are unique in relation to the migratory habits of other North American owls in that they show such a high site fidelity to their breeding grounds. Many other species of owls, such as snowy owls, boreal owls (Aegolius funereus) and northern hawk owls (Surnia ulula) base their migrations on the abundance of prey

(Cheveau et al. 2004). They will leave higher latitudes during the winter months and migrate to areas that provide them with ample resources. Smaller species such as boreal owls are hindered by their small size in the types of prey items that they can eat. Small mammal populations, such as the red-backed vole (Clethrionomys gapperi), are subject to cyclic fluctuations in population size, and some owls, e.g. great gray owl, northern hawk owl, have adopted a nomadic lifestyle in order to better follow prey populations (Cheveau et al. 2004). Whalen and Watts (2002) found similar results with northern saw-whet owls and their adoption of a nomadic lifestyle to follow stable populations of mammal prey items. This species is prone to irruptive population densities that are related to the densities of their prey items.

Winter Habitat Selection

Very little is actually known about the wintering habitat of flammulated owls. Previous authors have stated that owls winter in Mexico, but have not given evidence for the types of habitat that they might be using when they are there (Johnson 1963, McCallum 1994, McCallum et al. 1995). Land use categories for the winter habitat provide insight into differences that might occur between the wintering areas used by the owls from the different breeding locations.

Breeding Habitat Selection

While Utah and Colorado had long-term monitoring programs that were decades old, the study site at Lake Davis, California was in its second and third year of study during my thesis project. Extensive vegetation and flammulated owl ecology had been studied in Utah and

Colorado, and I investigated what was contributing to the success of flammulated owl nesting occupancy at Lake Davis.

Using the protocol outlined in Groves et al. 1997, I hypothesized that certain vegetation factors contributed to diversity in the habitat of used territories that made these areas better foraging sites compared to those that were unused. Factors such as plant understory diversity and tree overstory diversity and composition could contribute to an increase in prey availability.

Goggans (1986) found that flammulated owls used habitats that occurred along forest/ grassland edges with a mix of lower ground cover with multiple species and a multistoried canopy.

Flammulated owls use a balance of diverse ground cover because it leads to a higher diversity of prey organisms and, canopy cover composition in order to be able to safely perch to catch prey and avoid predators (Goggans 1986). In contrast, Reynolds and Linkhart (1992) found that flammulated owls were mainly using the interior tree crowns of old growth ponderosa pine

stands. These habitat types are different from one another, and yet owls will use both because they are opportunistic in the type of prey they will take (McCallum 1994). Because I was not able to locate the exact nest sites, I chose to look at the overall territory characteristics which, according to previous literature, would be one of the first factors used by a male in selecting an area that would make him attractive to an available female (Linkhart et al. 1998). Of the 13 factors that I measured, I was only able to find significant differences in three of them, including percent shrub cover, average shrub species count, and average DBH of nearest measured trees.

Shrub count and shrub percent cover were both higher in occupied habitats, which would make sense according to previous literature that found that a diverse ground cover was conducive to more diverse prey community (Goggans 1985, Linkhart et al. 1998). Linkhart et al. (1998) also found that flammulated owls favored old growth ponderosa pine/ douglas-fir stands, which were similar to the jeffrey pine/ white fir dominated habitats present in occupied habitats. In my study site, DBH was significantly lower in used habitats, which was different than what I would have expected based on the literature.

According to van Woudenberg (1992), the characteristics of the individual nest tree used by the owls may be of more importance than overall habitat quality, because habitat characteristics may be more indicative of the needs of the original cavity nesting species.

Previous studies that assessed habitat characteristics at nest sites of flammulated owls found that those sites were usually dominated by yellow pine species in old growth stands with open understories and canopies that would allow for ease of foraging and flight path to the nest during feeding of nestlings (Marshall 1939, Reynolds and Linkhart 1992, McCallum 1994, and Marti

1997). Since I did not have specific information on actual nest locations, I was not able to assess whether these characteristics were relevant in my Lake Davis study site.

Flammulated owls have been found to be fairly flexible in terms of the specific tree species within the habitats across their range, as long as the general structure fits with their foraging and nesting preferences (McCallum 1994). The wintering habitat seemed to share the same level of differences among the habitat types that the owls were using, potentially opening up more habitat than was once thought available. Dunham et al. (1996) found that small patches of conifer forests dominated by white fir were able to support small breeding populations of flammulated owls. Similarly, yellow pine species such as ponderosa pine and jeffrey pine are not common in Utah, but work done by Marti (1997), found flammulated owls nesting in habitats dominated by deciduous forests of quaking aspen with some douglas-fir and white fir mixed in.

Studies conducted by Marshall (1939), Winter (1974), Marcot and Hill (1980), and

Bloom (1983) found that flammulated owls were most common in habitats dominated by yellow pine species at elevations between 350 to 2800 m. Owls have been found nesting not only in old growth yellow pine forests, but also secondary growth yellow pine forests as well (e.g. Nelson et al. 2009). Flammulated owls have been found throughout the entire range of ponderosa pine and jeffrey pine within California, including along the Pacific Coast Range. The study by Marcot and

Hill (1980) conducted surveys in Humboldt and Trinity Counties in northern California and found that territory sites had variable canopy cover, ranging from low to high, with at least two canopy layers being present, and at least some level of understory cover. Tree density and basal area of trees was also quite variable. They found that the characteristics of territories were closely related to those territories that had been studied in Oregon by Bull and Anderson (1978).

These characteristics included stands of tall, mature trees with at least some open canopy and open understory. These characteristics are present within the Lake Davis study area.

Limitations

While this study provided additional information about the migratory activity of flammulated owls, it was not without its limitations. Future studies could look at expanding to other parts of the flammulated owl breeding range, as well as increasing the number of geolocators put out to increase chances of recovery. It would also be interesting to determine if there are areas that are consistently being used as stopover locations among many different individuals. Because of the limited number of females that had geolocators put on them, it would be very helpful to add more females in the future to see if the behavior of the Utah female and the California pair of owls were the norm or an anomaly. The methods associated with capturing and recapturing the owls are labor intensive and so increasing the number of people attempting recapture would also go a long way to increasing recapture efforts. The geolocators, themselves, have some challenges, particularly not being able to get any information off of them until they are recovered as well as the loss of latitude data during spring and fall equinoxes. As for the vegetation study, a major limitation was only finding a limited number of nests, which really hindered my ability to accurately detect those differences that might make one area of that field site more preferential than other areas.

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APPENDIX A

Appendix A

IntiProc Geolocator Methodology- Step by Step

 Lux (light) files were opened in IntiProc.

 Markup function was chosen, which draws lines where changes in light that represent

potential sunrises and sunsets occur.

 User can scroll through markups and eliminate sets that are completely wrong or those

that do not show a definitive change in light.

 User can then use the generate function to produce a set of coordinates that are displayed

on a map.

 The calibrate function can be used by entering known coordinates on known dates to

create more accurate coordinate locations.

 This set of coordinates can be saved as a text file that can then be opened in excel to

make the data importable into GIS.

GIS Methodology- Step by Step

 The excel file made from the IntiProc data can be imported into GIS and the XY

coordinates can be displayed. This layer cannot be edited so the points must be exported

to a new layer.

 When this new layer is displayed on a base map, the points that are incorrect or obviously

wrong, specifically those that are dated around the time of the fall or spring equinoxes or

fall into the ocean can be eliminated.

 At this point a “Week” column can be added to create a way to categorize the coordinates

according to time. This can allow the user to see the movements of the owl through time

as well as space.

 The table can be exported as a dbf file and opened in Excel. A new column is created and

coded to show a period of 7 days. A code that says 7_1_7_12 would mean July 1-7, 2012.

All points are coded in this way using 7 day increments. This excel file can then be

brought back into GIS.

 The points in this file are symbolically categorized so that each week is represented by a

different color. The user can see the change in color which shows the change in location

over time.

 A kernel density estimation can be run using the “kernel density” tool found in the GIS

toolbox. Before this tool is run, it is useful to export the points as a new layer so that the

original layer will remain unchanged.

 Kernel density can only be run using UTM so if the points are in any other coordinate

system, they must be transformed using the transformation tool from the toolbox. The

new layer can then be edited and all points except those of interest, in this case the

wintering location points, can be deleted.

 To run the kernel density tool, there are a series of parameters that need to be filled in in

the pop up window. From previous geolocator papers, the search radius has been set to

200km and the grid size set to 2km. In the window, these are entered in meters as

200,000m and 2000m, respectively. The unit is set to square kilometers and under the

environments tab, the processing extent is set can be set to a smaller square area that will

encompass all of the points and the accompanying polygon rather than having the entire

frame be processed (which could take longer).

 Once the kernel density is run, the output will be a rounded polygon that can then be

changed to show different layers depending on what is wanted. For this project, 50, 75,

and 90% contours were desired to show the different proportions of points. There is no

tool for this so it has to be done manually. This initial layer is a raster layer so there are

no values associated with points, so the “extract values to points” tool from the

Extraction toolbox can be used. The 50, 75, and 90% values can be looked up in the

attribute table and then those values can be used as the break values in the symbology tab

in the raster layer. The outer edge of the polygon can be found by using the smallest point

value as this is the point that is furthest from the center of the polygon. There should be

four category levels and the outside level can be set to display no color so that there are

only the three contours of interest displayed.

 The “reclassify” tool was used to separate the 50 percent polygon from the larger kernel

density polygon. The “extract by mask” tool was then used to extract the shape of the 50

percent polygon from the Mexican land use map in order to determine the land use by

each owl within their estimated wintering areas.

APPENDIX B

Appendix B- Migration Routes for Individual Owls

Depart 3 September 2013

APPENDIX C

100

Appendix C- Vegetation Comparisons for Lake Davis Study Site

Understory Composition: Used vs Unused Territories 25.00

20.00

15.00 Used

10.00 Unused PercentCoverage 5.00

0.00

Importance Value of Overstory Species

120.00 100.00 80.00 60.00 40.00 20.00 0.00 Used

Unused ImportanceValue

Overstory Species

101

Understory Composition: Used vs Unused Territories 25.00

20.00

15.00 Used

Unused

10.00 PercentCoverage

5.00

0.00

Vegetative Characteristics in Used vs Unused Territories 3

2.5

1.5 Used

1 Unused

0.5

0 Dominant tree Dominant Canopy layers Stand age Shrub cover cover understory count

102

Percent Canopy Cover 58.00 56.00 54.00 52.00 Used 50.00 Unused 48.00 46.00 44.00 % Canopy cover

Comparison of Percent Coverage 20.00 18.00 16.00 14.00 12.00 10.00 Used 8.00 Unused 6.00 4.00 2.00 0.00 % NW ground cover % W ground cover % Shrub cover

103