Document Type

Thesis - Open Access

Award Date


Degree Name

Master of Science (MS)


Natural Resource Management

First Advisor

Robert C. Lonsinger


bobcat, genetic diversity, harvest, Lynx rufus, population genetic structure, wildlife management


A primary objective of state wildlife management agencies is to establish sustainable harvest levels for game species. An important component of sustainable management practices is the identification of appropriate management units for monitoring and establishing defensible harvest levels. Across their range, bobcats (Lynx rufus) are an ecologically and economically important species. Despite their importance, little is known about the genetic structure of bobcat populations in South Dakota. We used tissue sampled from n = 1,215 bobcats harvested across the state from 2014–2019 to infer population genetic structure. We used 17 microsatellite loci and a sex identification marker to assign individuals to genetically discrete clusters (i.e., populations) using Bayesian clustering algorithms. Analyses were run to identify the most likely number of clusters (K), considering potential values of K from 1 to 20. We found strong support for hierarchical structure at K = 2 and K = 4, as well as evidence of finer-scale structure that we were not able to fully evaluate due to the spatial resolution of the data. We calculated standard measures of population genetic diversity (e.g., heterozygosity) and population differentiation (e.g., FST and G”ST). All pairwise measures of differentiation between identified clusters were found to be statistically significant (P ≤ 0.001). We identified the spatial configuration of inferred clusters by geographically plotting individuals assigned to each cluster. The inferred structure reduced linkage disequilibrium and deviations from Hardy-Weinberg Equilibrium as would be expected due to the Wahlund effect. For analyses supporting K = 2, the eastern and western clusters align closely with historical practices of managing bobcat harvest with 2 units in South Dakota, but our results suggest that shifting the boundary of the 2 units so the eastern unit includes counties immediately west of Missouri River and south of the Oahe Dam would better align management units with population boundaries. Alternatively, analyses supporting K = 4 provides a level of resolution that may benefit bobcat management if managers aim to conserve the uniqueness of bobcats in different regions (e.g., Black Hills).

Number of Pages



South Dakota State University



Rights Statement

In Copyright