Understanding the social and ecological dynamics of illegal bushmeat in villages near Serengeti National Park through community-based modeling

Abstract

Lack of coordinated understanding of the social and ecological dynamics of bushmeat trade limits the ability of conservation policies to be matched with local environmental conditions. Through Fuzzy-logic cognitive Mapping (FCM), the similarities and differences of social-ecological components of bushmeat trade were analyzed of by comparing assumptions driving externally generated bushmeat management policies with the understanding about the dynamics of the bushmeat trade from local community members currently or formerly engaged in the bushmeat trade (e.g. hunters, consumers, sellers). Results indicated that there was an agreement of 58% across community models about the most central factors important to understanding the bushmeat trade, and this agreement matched policy assumptions. However, community models demonstrated a high degree of local-scale complexity and factors perceived to drive social-ecological bushmeat trade dynamics varied considerably across communities. Comparison of bushmeat management policies indicated that providing income alternatives was most effective at decreasing bushmeat consumption, while Community Wildlife Management (CWM) was most effective in increasing wildlife populations. Additionally, protein alternatives were useful in both reducing bushmeat consumption and illegal hunting. Our results suggest that the general knowledge of participants about the components that comprise the bushmeat trade is similar, but perceptions of bushmeat trade dynamics are largely heterogeneous .These heterogeneous perceptions are seen mainly in communities engaged in bushmeat trade which suggests that conservation policies should not be applied uniformly.