Natural populations are often difficult and costly to study, due to the plethora of confounding processes and variables present. This is of particular importance when dealing with managed species. Ungulates, for example, act as both consumers and prey sources; they also provide economic benefit through harvest, and as such, are of high ecological and economic value. I addressed conservation and management concerns by quantifying subdivision in wild populations and combined movement with non-invasive sampling to provide novel insight on the physiological drivers of space use in multiple species. This thesis explored biological patterns in ungulates using two distinct approaches: the first used molecular genetics to quantify gene flow, while the second examined the relationship between movement and the gut microbiome using high-throughput sequencing and GPS tracking. The goal of the first chapter was to quantify gene flow and assess the population structure of mountain goats (Oreamnos americanus) in northern British Columbia (BC) to inform management. I used microsatellites to generate genotype data and used a landscape genetics framework to evaluate the possible drivers behind genetic differentiation. The same analyses were performed at both a broad and fine scale, assessing genetic differentiation between populations in all of northern BC and in a case management study area northeast of Smithers BC. The results indicated panmixia among mountain goats regardless of scale, suggesting distance and landscape resistance were minimally inhibiting gene flow. Therefore, management at local scales can continue with little need for genetically informed boundaries, but regulations should be tailored to specific regions incorporating data on local access and harvest pressure. My second chapter aimed to determine the extent to which the gut microbiome drives space-use patterns in a specialist (mountain goat) and generalist (white-tailed deer, Odocoileus virginianus) ungulate. Using fecal samples, we generated genomic data using 16S rRNA high-throughput sequencing to evaluate gut diversity and gut microbiome characteristics. Additionally, individuals were fitted with GPS collars so that we could gain insight into movement patterns. Gut microbiome metrics were stronger predictors of space use and movement patterns with respect to home range size, whereas they were weaker predictors of habitat use. Notably, factors of both the gut microbiome and age of a given species were correlated with changes in space use and habitat use. Ultimately, this research linked high-throughput sequencing and GPS data to better understand ecological processes in wild ungulates.
Author Keywords: gene flow, genomics, gut microbiome, home range, population genetic structure, ungulates