Listening to Life: Acoustic and AI Technologies for Tracking Freshwater Biodiversity Recovery

Freshwater ecosystems are among the most threatened habitats on Earth due to multiple anthropogenic pressures. Protecting them requires novel monitoring solutions that are both low-cost and highly sensitive to change. Such tools will enable large-scale, real-time data generation to inform conservation and restoration efforts (e.g., assessing river restoration or Nature-based Solutions). Integrating big data with Artificial Intelligence (AI) can reveal environmental trends, support policy development, and provide essential evidence to national policymakers, international bodies, and the public.

This project will build on ongoing freshwater ecological restoration in the UK, investigating multiple species groups. Cutting-edge technologies (e.g., passive acoustic monitoring, mini drones, camera traps) will produce extensive datasets from chalk stream restoration projects in Southern Hampshire and from the emerging field of ghost pond resurrection (capturing fish, invertebrate, amphibian, mammal, and bird activity) within the Brecks Fen Edge and Rivers landscape area of West Norfolk. The approach will deliver real-time insights into biological recovery that traditional methods cannot achieve, while detecting elusive species with irregular or crepuscular behaviours. It will also contribute to global aquatic sound databases, with potential to detect the return of rare species post-restoration.

This interdisciplinary PhD bridges environmental and data sciences, involving deployment of in-river and in-pond sensors and the development of AI-based systems for real-time biodiversity monitoring and management. The student will gain expertise in bioacoustics, environmental sampling, water quality assessment, quantitative statistics, camera trapping, machine learning, big data analytics, and GIS—preparing them to pioneer innovative approaches in freshwater conservation.