Theses and Dissertations

ORCID

0009-0001-1590-3961

Advisor

Morin, Dana

Committee Member

Brzeski, Kristin

Committee Member

Sandel, Michael

Date of Degree

8-12-2026

Original embargo terms

Immediate Worldwide Access

Document Type

Graduate Thesis - Open Access

Major

Wildlife, Fisheries & Aquaculture

Degree Name

Master of Science (M.S.)

College

College of Forest Resources

Department

Department of Wildlife, Fisheries and Aquaculture

Abstract

American black bear (Ursus americanus) monitoring programs often use minimally invasive genetic monitoring techniques (hair snares) to estimate abundance and density. Historically, microsatellites have been used to identify individuals from hair samples and create mark-recapture histories to estimate population size. However, microsatellite-based genotyping requires multiple replicates and visual confirmation of consensus genotypes. Advances in genetic sequencing technology have led to methods like Genotyping-in-Thousands by sequencing (GT-seq), which allow automated genotyping using bioinformatic pipelines, thereby reducing the number of replicate samples required to confirm genotypes and increasing data portability. We developed a GT-seq panel for individual identification of black bears using genomic data from three disparate populations. To evaluate the panel’s utility as a range-wide monitoring tool we sequenced 3,412 samples from 23 populations obtained from 19 states across the United States. We also conducted a population genetic assessment of black bears across the Coastal Bear Management Unit in North Carolina.

Sponsorship (Optional)

Funding: North Carolina Wildlife Resources Commission; Pittman-Robertson Wildlife Restoration Act - In collaboration with North Carolina State University - Project: WM-0369

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