Epsilon Open Archive

Abstract

Genomic tools can greatly facilitate our understanding of wild populations. For the purposes of ecology and conservation, the most pertinent insights into wild populations are those that are contemporary. Much of the genetic-based research on wild populations has been derived from a population genetic framework resulting in historically derived summary statistics. These statistics are undoubtedly useful for understanding things such as effective dispersal and population structuring. However, they provide little indication to processes affecting populations within existing generations. One way to overcome this is to work at the individual level and consolidate the findings to improve understanding at the population level. For individual-based genetic studies, it is essential to be able to identify unique individuals and obtain reliable inferences of relatedness. Molecular markers must therefore possess qualities that make them suitable for identifying individuals and inferring relatedness between them.

This dissertation first describes the development of a set of 96 single nucleotide polymorphisms (SNPs) designed to infer relatedness between individuals in the Scandinavian brown bear population. The SNPs were used to study three contemporary features through relatedness inferences and pedigree reconstruction based on noninvasively collected samples: population size, natal dispersal distances, and fine-scale spatial structuring. These three studies are all based on new methods, one developed by Creel and Rosenblatt (2013) but empirically tested here, and the other two first developed for this dissertation. Using these methods, I successfully identified contemporary characteristics of a wild population. These methods can easily be applied to other species of ecological and conservation interest.