Use of GIS for a spatial and temporal analysis of Kenyan wildlife with generalised linear modelling

This paper applies generalised linear statistical techniques in a GIS to an alyse wildlife data from a Kenyan wildlife reserve and its surrounding area s. Attention focuses on the spatial distribution of elephant during nine su ccessive surveys, analysing their temporal and spatial relationship to 12 e nvironmental covariates. A principal component analysis identifies five maj or determining factors, thereby reducing dimensionality in the data, while a simple spatial analysis procedure, suitable for wildlife data obtained fr om airborne surveys, quantifies clustering for different animal species. Th e number of explanatory variables appearing in abundance models is found to be subject to large variations during successive surveys with a minimum an d maximum of four and eight variables, respectively. Species from highly cl ustered populations are found to have over 20 times more observations withi n short distances compared to the rest. The study concludes that a combinat ion of generalised linear modelling and GIS gives deeper insight into the d ynamics of wildlife species in and around well-defined nature reserves.