Date of Award:

5-2024

Document Type:

Dissertation

Degree Name:

Doctor of Philosophy (PhD)

Department:

Wildland Resources

Committee Chair(s)

Kezia Manlove

Committee

Kezia Manlove

Committee

Susannah French

Committee

Tal Avgar

Committee

Dan McNaulty

Committee

Paul Cross

Abstract

Movement is a fundamental component of animal ecology. Animals move in order to access resources and avoid risk. Movement decisions aggregated across time determine how individuals use space, contact dynamics between individuals within a population, and connectivity across a species range. These patterns that emerge from movement decisions have downstream implications for many ecological processes and a mechanistic understanding of movement can help answer broader questions about ecology.

Disease dynamics are intrinsically tied to movement. Understanding the mechanisms that drive movement can elucidate how disease will spread and impact host populations. In this vein, I employed a suite of movement analyses to understand how an individual’s social and environmental context affects movement, population connectivity, and disease dynamics in bighorn sheep populations living along a latitudinal and precipitation cline. Bighorn sheep are currently threatened by an infectious bacterial pneumonia that can have catastrophic outcomes on infected populations. The ultimate goal of this study was to understand how different patterns of movement affect disease transmission and population growth. Using location data collected from bighorn sheep spanning a variety of environmental conditions across the state of Nevada, I identified long-distance foray behaviors that lead to connectivity between populations based on movement characteristics, modeled the effect of social and environmental factors, as well as disease, on the probability of rams making foray movements, modeled seasonal connectivity between populations, and, finally, incorporated the results of the movement and connectivity models into a realistic model of metapopulation dynamics in the presence of disease. an important role in determining how populations are ultimately affected by disease. The probability of rams making foray movements is temporally dynamic, responding to seasonal pressures and local population demography. Connectivity between populations is also temporally dynamic, with the highest rates of contact during the breeding season. When incorporated into a disease simulation model, I found that the ultimate effect of disease on population dynamics can depend on the timing of connectivity between populations in relation to its ability to provide gene flow or disease transmission.

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