Optimising marine protected area monitoring - a case study of the Isles of Scilly archipelago

We are increasingly reliant on marine protected areas (MPAs) to reverse biodiversity declines caused by human pressures across the world's oceans. However, MPAs are only effective as a conservation management tool if they are well-designed, properly enforced, and effectively monitored. With the growing push to designate more MPAs by 2030, research efforts are shifting toward improving MPA quality, particularly by addressing shortcomings in monitoring and management. This includes identifying key knowledge gaps, quantifying emerging pressures, and designing cost-effective, long-term monitoring programs.
This PhD explores these themes using the Isles of Scilly, a biologically distinct oceanic archipelago, as a case study. Through a collaborative partnership with the Inshore Fisheries and Conservation Authority and Natural England, this research specifically aims to: 1.Synthesize marine biodiversity knowledge in the Isles of Scilly to identify key knowledge gaps that could be addressed by this PhD and future research. 2. Use advancements in remote sensing vessel tracking technology to map fine-scale spatiotemporal patterns of ocean user activity and quantify how different maritime fleets interact with the archipelago's MPAs and their designated features. 3. Apply cutting-edge survey techniques, including spatially robust sampling and stereo baited remote underwater video systems, to survey fish assemblages within UK MPAs and establish benchmarks of marine health for the region. 4. Develop a framework for a more systematic approach to long-term ecological monitoring of UK MPAs by designing inter-annual survey programmes that balance statistical power with capacity constraints.
The findings of this thesis can provide direct conservation management benefits to local marine ecosystems and have wider application value for how we monitor the ecological value of, and threats to, marine protected areas in UK waters and coastal states more generally.