Dissertation Research: Catch-per-unit-effort as an indicator of "bushmeat" sustainability

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Wildlife hunting for human consumption and use is a major threat to global biodiversity and, paradoxically, to the very people who depend on it. While fisheries research has a long history of investigating maximum sustainable yields and methods for monitoring fisheries stock population status, research in bushmeat (wild meat) sustainability and management is still relatively nascent. This project will examine wildlife utilization in the Congo Basin of Africa, which has traditionally been approached from a conservation perspective, rather than a utilitarian perspective. Wildlife populations in the Congo Basin are notoriously difficult to monitor due to remoteness and dense tropical forest canopy, precluding aerial surveys. The main objective of this research project is to determine if hunter catch-per-unit-effort indices, commonly used in fisheries management, can be used as indicators of the status of harvested wildlife populations in Central Africa. This project will test whether the harvest system for African bushmeat is influenced by factors such as gear-type, vegetation, season, and hunter experience, and will also investigate whether ancillary data of harvested population structure (e.g. age and sex) can serve as a proxy for wildlife abundance or harvested population status.This project addresses a major gap in current management of wildlife harvesting in Central Africa, a resource that is currently under threat of unsustainable harvests. Millions of people across Africa rely on wildlife as a primary source of protein, and alternative protein sources are difficult, if not impossible, to access. Hence, it is imperative that cost-effective, technologically feasible, and socially acceptable methods for monitoring harvested wildlife populations are identified. Results from this project will be provided to stakeholders in conservation and government agencies in the Congo Basin to better inform management strategies. This project will support the doctoral dissertation research of a graduate student.