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Discriminating between village and commercial hunting of apes
Authors:Hjalmar S Kuehl  Christian Nzeingui  Bas Huijbregts
Institution:a Max-Planck-Institute for Evolutionary Anthropology, Department of Primatology, Deutscher Platz 6, 04103 Leipzig, Germany
b World Wide Fund for Nature, WWF Gamba, P.O. Box 1944, Libreville, Gabon
Abstract:Hunting is the major driver of large mammal decline in Central African forests. In slowly reproducing species even low hunting pressure leaves spatial gradients with wildlife density increasing with distance from transport routes and human settlements. Park management can use this pattern formation to identify sources of threats, but also to discriminate between different threat scenarios, such as the impact of subsistence vs. commercial hunting. We conducted an ape survey in the mountainous Moukalaba Doudou National Park, Gabon, to evaluate whether potential population gradients would emanate from the three human population centers in the region or the villages surrounding the park. Using generalized linear modeling we found hill slope as a good predictor of ape nest occurrence probability and the distance to human population centers a better predictor of ape nest density and ape nest group size than distance to villages. In fact ape nest density was three times lower at the park borders close to the human population centers than in the park’s interior. The results indicate that Moukalaba’s ape population is more impacted by commercial than subsistence hunting and suggest that park management should focus conservation efforts on the human population centers. We conclude that in particular for slowly reproducing species geographic information on wildlife population gradients are of additional value for guiding protected area management. The hunting impact on those species might be easily underestimated, if derived only from market surveys or transport route controls, where they are only rarely found.
Keywords:Village  Human population center  Density  Park management  Population gradient  Survey
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