develop the first soundscape-based monitoring system for tropical West Africa, using Guinea-Bissau's protected area network as a model system to generate transferable methods applicable across the region.

Using extensive acoustic data from Guinea-Bissau's protected area network, the research will identify robust acoustic metrics that track ecosystem condition across habitat types and disturbance gradients. Integration with freely available satellite data (e.g. vegetation indices, land cover, climate) will link soundscape patterns to environmental drivers, while machine learning algorithms will automate threat detection (e.g. poaching). Spatial analyses will identify high-conservation-value sites based on soundscape uniqueness.

The candidate will synthesize these components into a practical monitoring framework with validated acoustic indicators, optimal sampling protocols, and threat detection algorithms. Outputs will directly support Guinea-Bissau's government agency responsible for protected area management (Instituto da Biodiversidade e das Áreas Protegidas, IBAP) while providing replicable tools for resource-limited protected area agencies across West Africa.

develop the first soundscape-based monitoring system for tropical West Africa, using Guinea-Bissau's protected area network as a model system to generate transferable methods applicable across the region.

Using extensive acoustic data from Guinea-Bissau's protected area network, the research will identify robust acoustic metrics that track ecosystem condition across habitat types and disturbance gradients. Integration with freely available satellite data (e.g. vegetation indices, land cover, climate) will link soundscape patterns to environmental drivers, while machine learning algorithms will automate threat detection (e.g. poaching). Spatial analyses will identify high-conservation-value sites based on soundscape uniqueness.

The candidate will synthesize these components into a practical monitoring framework with validated acoustic indicators, optimal sampling protocols, and threat detection algorithms. Outputs will directly support Guinea-Bissau's government agency responsible for protected area management (Instituto da Biodiversidade e das Áreas Protegidas, IBAP) while providing replicable tools for resource-limited protected area agencies across West Africa.