Kieran Hyder, Cefas
Professor Tom Cameron, University of Essex, School of Life Sciences
Dr Joe Bailey, University of Essex, School of Mathematics, Statistics and Actuarial Science
Dr Nicola Walker, Cefas
Marine fishes exhibit complex life cycles, featuring discrete spawning, nursery and feeding areas that confer different benefits to the stock. Identifying the ‘Essential Fish Habitats’ supporting our fisheries, and the connectivity pathways linking them, is critical for performing effective spatial management and conservation. European sea bass are an ideal model species to implement a lifecycle management approach as they support important inshore and offshore fisheries, and rely on estuarine nursery areas that are particularly vulnerable to human impacts . However, estimating the importance of specific areas and habitats remains an ongoing challenge, particularly in the face of rapid global change.
You will use machine learning classification models to improve movement reconstructions using biogeochemical “fingerprints” recorded in bass otoliths (earstones) and eye lenses . You will also validate biogeochemical tracers in archived otoliths using existing tagging data from the same individuals, perform additional fish sampling, and explore whether environmental proxies (e.g. salinity, temperature) help to reduce uncertainty around unsampled areas. You will then integrate these results with other existing datasets (genetics, tagging, modelling [3,4]) to build network models that describe the spatial structure and connectivity of UK bass populations and to predict the outcome of different climate and management scenarios (e.g. MPAs, altered fishing pressure).
You will be trained in a range of transferable skills, building on the expertise of the supervisory team in fisheries ecology, modelling and biogeochemical tracers. While focused on modelling, you will also be trained in laboratory and field techniques (mass spectrometry, fish sampling). You will also spend three months at Cefas learning additional modelling techniques and best practices to link science, management and policy, and gain access to Cefas’ extensive student networks and professional development activities.
Individuals with an interest in fisheries and conservation ecology, and a degree in ecology, mathematics, environmental science or related fields, are encouraged to apply. Quantitative skills will be important, but there will be considerable training provided. Students with numerical skills but no degree-level exposure to environmental sciences (e.g. Mathematics, Physics, Chemistry, Engineering) may apply for additional support for training in environmental sciences (https://www.aries-dtp.ac.uk/supervisors/additional-funding/).