• Bahn, Volker
  University of Maine Graduate School
  

Modeling the geographical distributions of wildlife species is important for ecology and conservation biology. Spatial autocorrelation in species distributions poses a problem for distribution modeling because it invalidates the assumption of independence among sample locations. I explored the prevalence and causes of spatial autocorrelation in data from the Breeding Bird survey, covering the conterminous United States, using Regression Trees, Conditional Autoregressive Regressions (CAR), and the partitioning of variance. I also constructed a simulation model to investigate dispersal as a process contributing to spatial autocorrelation, and attempted to verify the connection between dispersal and spatial autocorrelation in species' distributions in empirical data, using three indirect indices of dispersal.