Acoustic Indicators of Ecosystem Integrity: Developing Soundscape-Based Monitoring for West African Protected Areas

About the Project

Biodiversity monitoring underpins effective protected area management and international conservation reporting, yet West African nations face persistent capacity constraints -insufficient funding, limited field personnel, and taxonomic expertise gaps - that prevent adequate ecosystem assessment. Soundscape monitoring provides continuous biodiversity surveillance through automated acoustic recording, but methods remain research-focused rather than management-ready. The aim of this PhD is to 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.