Year of Award

2013

Document Type

Thesis - Campus Access Only

Degree Type

Master of Science (MS)

Degree Name

Wildlife Biology

Department or School/College

College of Forestry and Conservation

Committee Chair

Mike Mitchell

Commitee Members

Pete Zager, Lisette Waits, Paul Krausman, Scott Mills

Keywords

Genetic Relatedness, Multi-State Models, Connectivity, Bighorn Sheep

Publisher

University of Montana

Abstract

Identification of population structure and connectivity is important for understanding and managing animal populations, in part, because they can influence spread of disease. Respiratory disease is one of the most important factors affecting populations of bighorn sheep and transmission of disease is believed to occur via direct contact. Therefore, risk of disease spread is related to the level of connectivity in bighorn sheep populations. We investigated population subdivision and connectivity of bighorn sheep across central Idaho at behavioral (fine) and genetic (broad) scales. We assessed fine-scale connectivity within a bighorn sheep population using radio telemetry data from 56 individuals from 2007-2013. We defined social groups of bighorn sheep using cluster analysis and estimated connectivity between these groups using a multi-state mark-recapture model. We evaluated the effects of sex, age, and season on the probability that an individual from one social group would transition into the area of another social group. We found that social groups of bighorn sheep along the lower Salmon River were well connected. While males were the primary source of connectivity between social groups, ewes also transitioned into other social groups but to a lesser degree. Rams had a 3 times higher probability of moving during the winter associated with the rut than during the summer. We employed genetic techniques to assess broad-scale connectivity across a metapopulation of bighorn sheep in Idaho using nuclear and mitochondrial DNA from 410 and 206 individuals, respectively. We defined subpopulations of bighorn sheep using a Bayesian clustering program and examined connectivity between these subpopulations using measures of genetic differentiation. We also looked at the contribution of males and females to connectivity. We found evidence for 4 subpopulations of bighorn sheep where 3 of those subpopulations were well connected. We observed some connectivity due to females but population connectivity was largely the result of male movements and dispersal. If contact is sufficient for disease transmission, then males are the most likely vector of disease spread given an outbreak at each scale.

Download

This record is only available
to users affiliated with
the University of Montana.

Request Access

Share

COinS
 

© Copyright 2013 Nathan Jeffery Borg