Exploring red deer culling strategies using a population-specific calibrated management model

Wildlife management is generally carried out under conditions of uncertaint y. The exact population size is unknown, its future dynamics are uncertain and clear management objectives are often not formulated. In order to provi de management advice in this situation, a framework is presented for combin ing different sources of information using a Bayesian approach for calibrat ing a management model. Harvesting strategies can then be explored based on predictions of future populations size and structure which incorporate par ameter uncertainty. This method makes it possible to evaluate the probabili ty of achieving certain objectives with different management strategies. Th e advantage of the approach presented in this paper lies in that both the m odel and the harvesting strategies are adaptable to any particular populati on of interest The approach is illustrated for two Scottish red deer popula tions for which culling strategies corresponding to different management ob jectives are explored and their benefits evaluated. It is found that each p opulation requires different culling rates for keeping population number st able, demonstrating the benefits of the population specific calibration of the management model. (C) 2001 Academic Press.