Semester

Spring

Date of Graduation

2014

Document Type

Thesis

Degree Type

MS

College

Davis College of Agriculture, Natural Resources and Design

Department

Wildlife and Fisheries Resources

Committee Chair

Todd E. Katzner

Committee Co-Chair

David C. Brandes

Committee Member

Adam E. Duerr

Committee Member

George T. Merovich, Jr.

Abstract

Understanding animal movements is fundamental to ecology and conservation, yet direct measurement of movements of birds is both challenging and costly. Raptor populations are especially difficult to monitor, but movement models can provide information toward this goal. The golden eagle (Aquila chrysaetos canadensis) in eastern North America is a species of regional conservation concern, and little is known about its population ecology, movements, or behavior. Because of their rarity and role as apex predators, improving monitoring of this small population is of great importance. Similar to using movement models to help improve monitoring, developing new methods to estimate the size of wildlife populations is also important to ecology and conservation.;In my first chapter, I simulated autumn migration of golden eagles in Pennsylvania, USA based on regional topography, eagle flight behaviors, estimated uplift, and a principal axis of migration. In total, I modeled 6,094 flight routes, averaging 2,191 (+/- 1,281; +/- SD; range: 3 - 5,373) moves. I found that 71% of my simulations intersected the Ridge and Valley physiographic province of the central Appalachians. Simulations were spatially comparable to historic, flight route data collected via telemetry. In my model, orographic uplift was significantly stronger and more frequently occurring than thermal uplift (Welch's two-sample t = -560.13, df = 43,059,702, p < 0.0001), and uplift values were not correlated with the number of simulated movements (orographic, Pearson's r = -0.015 and thermal, r = 0.003). I used output from my simulations to select sites and collect field data in new areas concentrating golden eagles on migration. This not only preliminarily verified my modeled predictions, but it also allowed me to locate new, potential monitoring sites for migrant golden eagles. I also compared output from my migration model to that of another model, to evaluate the influence of topography, spatial relationships with hawk-count sites, and role of scale in modeling migration.;In my second chapter, I evaluated the utility of hawk-count data for population size estimation of golden eagles migrating in eastern North America. I used my computer model from the first chapter to simulate migratory flights of eagles to assess what proportion of the population is available to be counted at hawk-counts in Pennsylvania, USA. I then conducted a mark-recapture analysis to estimate mean detectability of migrating eagles and mean local abundance along an important migration corridor. Finally, I used estimates of availability and detectability to adjust data from hawk-count sites to derive regional estimates of population size. Mean (+/- SD) availability of golden eagles to hawk-count sites was 0.240 (+/- 0.140; range: 0.040 - 0.440). I estimated mean detectability as 0.073 (+/- 0.010; range: 0.048 - 0.109). Previous estimates of population size for golden eagles in eastern North America were 1000 - 5000.;All of my population estimates far exceeded that of previous approximations. When using detection rates from recent literature, only then were my estimates < 5,000 individuals. Using my estimates of availability and detectability, mean population size was more than five times larger than the maximum previous estimate. My smallest estimate was three times larger than the previous maximum estimate. Larger estimates were driven by the low availability and detectability of birds passing by hawk-counts. Overall, this work suggests that (a) detection estimates need to be improved, (b) the majority of migrating golden eagles in eastern North America are not counted at hawk-count sites, and (c) previous population estimates for this species are likely low--possibly, greatly so. This exercise demonstrates the utility of using citizen-science data in concert with movement models to address a pressing conservation goal: estimating population size for species of regional concern. My research contributes to current scientific knowledge through development of a novel, cost-effective method for modeling migration patterns and abundance of a rare, low-density raptor species. (Abstract shortened by UMI.).

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