Professor Zoe Davies (School of Anthropology and Conservation – DICE, University of Kent)
Dr Cleo Cunningham (UN Environment Programme World Conservation Monitoring Centre)
Professor Neil Burgess (UN Environment Programme World Conservation Monitoring Centre)
Conservation areas are vital for conserving biodiversity and ecosystem services but research on their effectiveness typically only focuses on state-managed protected areas (Butchart et al, 2015). This is changing, with several case-studies showing that privately- and community-managed conservation areas can play a key role. However, we lack spatial data (e.g. accurate locations, boundaries) on these non-state conservation areas, so cannot fully measure how well global biodiversity is conserved or monitor progress towards meeting international targets (Dinerstein et al, 2019). Collecting such data for every country is a long-term process (Bingham et al, 2019), so DICE-led research has developed a sampling methodology from a representative subset of countries. This studentship will strengthen and refine this new approach, producing results that will inform international conservation research and policy.
The new methodology uses spatial conservation prioritisation software (Smith et al, 2019) to identify an ecologically and socio-politically representative subset of countries, collect all their conservation area data and calculate conservation area coverage within this sample area (Sykes et al, 2020). This studentship will: (1) investigate the robustness of the sample selection approach by comparing results from different software packages; (2) produce statistical models to understand what best predicts the actual and recorded coverage of state, private and community-managed conservation areas per country; (3) measure the extent to which the different conservation areas types meet global protection targets for terrestrial species; (4) modify this approach to identify a sample of marine areas for future research.
The candidate will be based at DICE and UNEP-WCMC and receive additional training through Kent Graduate School workshops. They will develop spatial databases using ArcGIS/QGIS, identify the representative samples using the Marxan, prioritizr and Zonation software packages, work with partners to collect conservation area data and analyse the results using R. They will also learn academic skills such as academic writing, giving conference presentations and time management.
A highly motivated candidate interested in combining biogeography with conservation science to produce high-impact, policy-relevant research. The candidate should have a degree in conservation, ecology or environmental sciences, strong analytical skills and, ideally, GIS expertise.