Estimating, monitoring, and modeling elk population growth rates and densities in northcentral Idaho at multiple spatial and temporal scales /by Brian Gilbert.

We investigated the effect of spatial and temporal scale on the ability to model elk density and population growth rates in the Clearwater Basin of northcentral Idaho. We used an information theoretic approach to determine best model sets to predict density and population growth rates of different sex and age classes of elk at annual and decadal time scales over herd and population sized units. Spatial and temporal scale did not dramatically affect our ability to predict elk density for all classes of elk, however there were some important repercussions related to choosing a scale of analysis. Larger spatial scales and longer temporal scales resulted in reduced variation in population growth rate (PGR), while assessment at the herd unit (HU) scale was dramatically better at predicting PGR, especially for the bull segment of the population. Modeling PGR at the HU and annual scale was most effective for cows, all bulls, and adult bulls. However, the best model for total PGR, with the best correlation coefficient of all models except adult bulls, was at the GMU and decadal scale. In order to assess effects of forage on elk density and PGR, predictive models from satellite imagery were developed to assess potential forage availability remotely. Finally, we used stochastic stage-structured projection models to simulate elk populations within the study area. Our objective was to investigate our ability to detect the influence of projection covariates on the density and annual growth rate of various segments of the elk population. Sampling intensity had dramatic effects on our ability to detect covariate influences, although not consistently across population segments. Habitat variables such as forage availability and snow accumulation were found to be most correlated with population metrics, while harvest variables were poorly correlated.Thesis (Ph. D., Natural Resources)--University of Idaho, May 2008