Date of Award:

5-2017

Document Type:

Thesis

Degree Name:

Master of Science (MS)

Department:

Wildland Resources

Committee Chair(s)

Thomas Edwards, Jr

Committee

Thomas Edwards, Jr.

Committee

David Koons

Committee

Kari Veblen

Abstract

Wildlife species distributed over large areas of land inhabiting varying environments are experiencing shifts in their home ranges due to human expansion and climate change. As these species home ranges shifts out of familiar, critical habitat they are forced to interact with novel environments, which in turn affects the species population demographics. In order to manage and conserve these species accordingly, specifically in a time of large-scale change, it is imperative that we add to current understandings of how they interact with various environments. Furthermore, frequently generating short-term predictions of demographic drivers will allow for conservation and management insight that is temporally relative to the current changes a population is experiencing. In this study we provide an example of this framework by investigating relationships between mule deer (Odocoileus hemionus) survival, a widely distributed ungulate, and varying environment variables. The survival dataset we utilized was collected from 7 different zones distributed across the three major ecoregions within Utah. We investigated the ability to estimate survival and generate short-term predictions of survival through the use of weather metrics and satellite-derived vegetation data. As expected, young had lower survival than adults. Survival decreased as you moved north and up in elevation. Consistently, increased precipitation in the winter months resulted in lower overwinter survival as well as survival in the following year. We found that increased forage availability during the summer months had a positive effect on survival. Our research provides an example of how survival of a widely distributed species interacts with varying environments. Coupling the analysis performed in this study with adaptive modelling techniques could guide conservation and management of widely distributed species facing large-scale change.

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