Using camera traps to enhance community-based management of subsistence hunting in the Amazon.

Community-based management and monitoring of biodiversity has emerged as a cost-effective strategy for providing credible data, informing decision-making, and empowering local communities in resource governance and management. However, the establishment of community-based management of subsistence hunting in the Brazilian Amazon has been hampered by legal uncertainty. Local regulations, such as the restriction or banning of mixed-breed dogs in hunting, have been strengthened to address social conflicts and improve wildlife management, but the conservation effectiveness of such regulations has been questioned. We conducted a case study of community-based decision-making in a human community in the Riozinho da Liberdade Extractive Reserve in the southwestern Brazilian Amazon. This community established an informal agreement to limit the use of hunting dogs along one of the banks of the Liberdade River. After analyzing the results of 20 camera traps (CTs) placed in areas with and without the use of hunting dogs, the community strengthened their hunting agreement and decided to reinforce the agreement and ban this type of hunting completely. Subsequent to this decision, we analyzed the CT data and verified the negative effects of hunting with dogs on site-level species richness, aggregate abundance and biomass, and the relative abundance and individual detection of some species. To strengthen community-based subsistence hunting strategies in the Amazon and tropical forests in general, we suggest that camera trapping sampling of sites with different hunting management strategies and subsequent presentation to communities can facilitate local engagement, strengthen social and management rules, increase the decolonization of wildlife management, and ultimately expedite decision-making processes to avoid the tragedy of the commons in similar tropical forest socioecological systems.