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Author ORCID Identifier



Open Access Dissertation

Document Type


Degree Name

Doctor of Philosophy (PhD)

Degree Program

Environmental Conservation

Year Degree Awarded


Month Degree Awarded


First Advisor

Toni Lyn Morelli

Subject Categories

Ecology and Evolutionary Biology | Genetics | Population Biology


This dissertation research focuses on the ecology of the Arctic ground squirrel (Urocitellus parryii) in Denali National Park and Preserve, AK. The Arctic ground squirrels is a species of interest for monitoring efforts under the National Park Services’ Vital Signs Monitoring Program under the Vital Signs Monitoring program. The focus of this program is to monitor what is considered to be the most significant indicators of ecological conditions of the specific park resources that are of the greatest concern. The CAKN designated the Arctic ground squirrel (Urocitellus parryii) as one indicator species of park ecosystems. Despite being easy to observe and having a geographic range larger than most other ground-dwelling species, the ecology of Arctic ground squirrels and their potential vulnerability to climate change is not well studied.

This study aimed at collecting baseline information about the species status in the park by estimating the spatial distribution and density of Arctic ground squirrels and their environmental correlates, assessing the genetic diversity and population structure, and predict their occurrence and abundance in the future with respect to climate change to fill in critical information gaps relative to future management concerns.

In Chapter 2, I analyzed data collected on Arctic ground squirrels during three seasons of monitoring to generate estimates of the probability of occupancy, density, and other demographic parameters of interest of Arctic ground squirrels in DENA using hierarchical occupancy and distance transect models. The distance-transect surveys results suggest an estimated density of 19.5 individuals/ha. For Arctic ground squirrels, slope and mean precipitation was an important positive predictor, while sampling year was also predictive. Occupancy models predicted an 0.54 occupancy probability across surveyed sites in the park. The five-year temperature mean was a negative predictor of occupancy.

In Chapter 3, I used single nucleotide polymorphisms (SNPs) to delineate genetic structure and assess genetic diversity to guide future monitoring efforts. I identified three major genetic clusters across the five populations, with low genetic diversity and genetic differentiation among the populations and clusters.

In Chapter 4, I make use of presence-absence, abundance, and genetic data previously collected in this study to assess potential conservation implications of climate change on the distribution of Arctic ground squirrels using the Random Forest algorithm. The results indicate that regions of predicted high occurrence and abundance showed similar patterns where high concentrations are mainly in the mid to southern portion of the administrative boundaries of the park. The maps of predicted spatial distribution with projected climate predictions here represent an initial attempt to capture the geographical and temporal range of the species and may be useful for identifying potential areas of conservation concern and improving sampling for future studies.