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.