Estimating habitat selection when GPS fix success is less than 100

摘要: Inferences about habitat selection by animals derived from sequences of relocations obtained with global positioning system (GPS) collars can be influenced GPS fix success. Environmental factors such as dense canopy cover or rugged terrain reduce success, making subsequent modeling problematic if success depends on the selected habitat. Ignoring failed attempts may affect estimates model coefficients and lead to incorrect conclusions selection. Here, we present a that accounts for missing locations due habitat-induced data losses, called resource function (RSF) The model's formulation is similar adjusting probability occupancy when detection less than 100% in patch sampling. We demonstrate use collected an adult female mule deer (Odocoileus hemionus) discuss how analyze multiple animals. In simulations presented, our was generally unbiased sets up 50% locations.