Can the Provision of Alternative Livelihoods Reduce the Impact of Wild Meat Hunting in West and Central Africa?

As threats to the world's ecosystems continue to escalate, the demand for evidence-based conservation approaches from conservation scientists, practitioners, policy-makers and donors is growing. Wild meat hunting represents one of the biggest threats to tropical forest ecosystems and various conservation strategies have been employed with the aim of reducing hunting impacts. Alternative livelihood projects have been implemented at the community level to reduce hunting through the provision of protein and income substitutes to wild meat. However, there is scant evidence of these projects' impact on hunting practices and wildlife populations. This study addresses this knowledge gap, focusing on alternative livelihood projects in West Africa and Central Africa. A comprehensive literature review and call for information identified 155 past and current projects, of which 19 were analysed in detail through key informant interviews. The study found that a range of different livelihood alternatives are being offered. Most projects are run by local and national non-governmental organisations, and project managers acknowledged the importance of involving communities in project decision-making; however, many projects are funded through small, short-term grants and struggle to meet their objectives with the available time, funding and capacity. Given these constraints, few projects monitor their outcomes and impacts. Projects also seldom implement conditionalities and sanctions, which may lead to the alternatives offered becoming additional rather than substitutional activities. Applying currently available best-practice guidelines for Integrated Conservation and Development Project design and implementation, including the use of simple monitoring methods for evaluating outcomes and impact, would greatly increase the chances of success for alternative livelihood projects, along with a restructuring of current funding models