CONSERVATION OF HARVESTED POPULATIONS IN FLUCTUATING ENVIRONMENTS - THE CASE OF THE SERENGETI WILDEBEEST

1. In this paper we examine the effects of alternative harvesting strategies on the wildebeest (Connochaetes taurinus) population in Serengeti National Park, Tanzania, within a Bayesian decision setting. 2. A wildebeest population dynamics model is constructed where mortality and recruitment are driven by environmental conditions. The applicability of the model is explored by fitting it to historical abundance data. 3. The uncertainty about the true dynamics of the population is represented by different degrees of rainfall-dependence in the recruitment of new individuals to the population. The likelihood of alternative recruitment scenarios is estimated within a Bayesian statistical framework. 4. The implications of different harvesting strategies for conservation, harvest productivity and harvest variability are evaluated using a Monte Carlo simulation of the population dynamics and harvest process. 5. The risk of collapse of the unexploited population is found to be higher for more rainfall-dependent recruitment scenarios. A clear trade-off exists between maximizing average harvest and minimizing the risk of population collapse. Constant harvest rate exploitation regimes produce similar average harvests to constant quota regimes and at the same time significantly reduce the risk of collapse. 6. The fastest way to determine the intensity of rainfall-dependence in the recruitment process is to eliminate all exploitation.