International trade in wildlife is a complex multi-million dollar industry. To supply it, many animals are extracted from the wild, sourced from biodiversity-rich, developing countries. Whilst the trade has far-reaching implications for wildlife protection, there is limited information regarding the socio-economic implications in supply countries. Consequently, a better understanding of the costs and benefits of wildlife supply chains, for both livelihoods and conservation, is required to enhance wildlife trade management and inform its regulation. Using Madagascar as a case study, we used value chain analysis to explore the operation of legal wildlife trade on a national scale; we estimate the number of actors involved, the scale, value and profit distribution along the chain, and explore management options. We find that the supply of wildlife provided economic benefits to a number of actors, from local collectors, to intermediaries, exporters and national authorities. CITES-listed reptiles and amphibians comprised a substantial proportion of the quantity and value of live animal exports with a total minimum export value of 230,795USD per year. Sales prices of reptiles and amphibians increased over 100-fold between local collectors and exporters, with exporters capturing ~92% of final export price (or 57% when their costs are deducted). However, exporters shouldered the largest costs and financial risks. Local collectors obtained ~1.4% of the final sales price, and opportunities for poverty alleviation and incentives for sustainable management from the trade appear to be limited. Promoting collective management of species harvests at the local level may enhance conservation and livelihood benefits. However, this approach requires consideration of property rights and land-use settings. The complex and informal nature of some wildlife supply chains make the design and implementation of policy instruments aimed at enhancing conservation and livelihoods challenging. Nevertheless, value chain analysis provides a mechanism by which management actions can be more
precisely targeted.