Preferential use of space tells us important information about animal ecology and how they might respond to changing environments. Statistical analysis of point location data typically involves point process models of spatial intensity, and observed use locations are typically considered to be independent.
I am interested in extending current point process models for use-availability studies to account for potential autocorrelation in the data. Location data are often collected sequentially in time, and unless the times between location fixes on an individual are very large, sequential locations are likely to be correlated.
Additionally, interactions between individuals could cause autocorrelation in the observed use locations, as animals cluster together in social groups or seek to be isolated from other conspecifics.