Spatial and temporal population dynamics of an elk metapopulation in Idaho: Demography, genetics, and environmental factors

The metapopulation approach explicitly incorporates spatial context, which focuses on spatially structured populations distributed broadly across the landscape. Metapopulation dynamics are influenced by the amount and variability of synchrony among populations. Multiple years of data are needed to gauge how elk populations respond to environmental factors. I used genetic, demographic, and environmental data to describe population and metapopulation dynamics of elk in Idaho.;I found the distribution of genetic variation was consistent among elk populations. A patchy metapopulation structure described the distribution of genetic variation among Idaho elk populations implying enough interchange of individuals occurred that only slight differences in genetic variation were detected.;Genetic population structure can be influenced by harvest via changes in gene flow among populations within a metapopulation, loss of genetic variation, and nonrandom selection of genotypes. I used a landscape genetics approach to evaluate influence of harvest on elk genetic population structure. Population growth rate, cow abundance, bull harvest rate, and bulls! 100 cows most influenced elk genetic population structure.;I delineated populations within an elk metapopulation based on demographic characteristics and measured population synchrony. Elk populations were synchronized, but the degree and magnitude of synchrony varied widely. Overall, elk populations in Idaho suggested a moderate amount of synchrony, meaning populations were balanced between being independently- or dependently-influenced by similar population and environmental factors.;For environmental factors, I modeled the response of elk population growth rates to density dependence, harvest, wolf population estimates, precipitation, snow depth, and estimates of vegetation productivity. Population growth rate decreased as total elk, cow, and calf densities increased indicating negative density dependence. Overall, density dependence, weather, and habitat covariates appeared in models that best fit the data more often than mortality covariates. Density dependence was contained in all the most supported models. My time series analysis of elk population growth rates and environmental factors revealed that multiple factors with complex relationships were acting on elk populations. My data and analysis can provide a baseline for genetic and demographic monitoring from which to measure future genetic variation and gauge the influence of environmental factors, including harvest, on elk populations.