Predicting occupancy for the Siberian flying squirrel in old-growth forest patches

Management and conservation efforts necessitate the understanding, of species' habitat requirements at the local scale. Population processes. however, often operate at larger scales than a single habitat patch and therefore. attention should be given to species' landscape responses in a network of habitat patches, The aim of this study was to determine important landscape characteristics associated with patch occupancy of the Siberian flying squirrel in northern Finnish forest landscapes, Landscape data were derived from satellite images and analyzed in GIS. Having landscape measures as independent explanatory variables, we developed a predictive landscape model using logistic regression analysis. Our model pointed out the relative importance of landscape characteristics such as the amount and quality of preferred habitat and the degree of structural connectivity at a local scale. Our landscape model was correct in predicting 80% of species occupancy.. We further tested model predictions with an independent data set for another landscape in northern Finland. The model did not predict occupied habitat patches as accurately as unoccupied ones in this test area. suggesting limitations and the need for caution in the application of the model elsewhere in northern Finland. This may be due to inherent landscape patterns and/or population processes that vary amount study areas in the region. This finding suggests that predictive models should he constructed for spatially explicit domains where the changes in, for instance, soil characteristics and topography vary within certain limits and can be controlled. Nevertheless, our model provides a useful tool for landscape ecological forest planning to locate potential habitat patches and assess the quality and spacing of connecting habitat in the matrix.