A Research Associate Post in Marine Ecology and Conservation

A Research Associate post is available in the Marine Ecology and Conservation Group, led by Dr. Catharine Horswill, in the Department of Zoology at the University of Cambridge. Catharine is a quantitative marine ecologist with expertise in population modelling, demography, and the application of ecological evidence to conservation and management.

About the Role

Reliable stock assessments are essential for the sustainable management of tropical tuna fisheries worldwide. In representing complex population and fishery dynamics, assessment models rely on simplifying assumptions about biological processes, spatial structure, and fisheries data. Understanding how these assumptions affect model performance and management advice is critical for identifying key sources of uncertainty and determining where methodological advances or improvements in fisheries data could most effectively strengthen future assessments.

Responsibilities

The project will develop and apply high-resolution, simulation-based approaches to evaluate how assumptions about population biology and fisheries data influence stock assessment performance and management advice. The project will initially focus on Indian Ocean yellowfin tuna, with subsequent application to bigeye and skipjack tuna where appropriate.

• Initial Work: Building on an existing high-resolution, spatially explicit simulation framework developed using the Spatial Population Model (SPM). SPM will be used to generate population and fishery scenarios that incorporate key sources of structural uncertainty, including spatial variation in growth and fishery selectivity, alternative population structures, and differences in the weighting of fisheries data.
• Model Fitting: Assessment models, including Stock Synthesis (SS3) and next-generation platforms such as SPoRC (https://chengmatt.github.io/SPoRC/), will be fitted to these simulated datasets to evaluate how different sources of uncertainty influence assessment performance and management-relevant outputs.
• Methodological Advances: Identifying where methodological developments or improvements in the resolution of fisheries data could most effectively strengthen future tuna assessments.
• Monitoring and Data-Collection Approaches: Evaluating the potential of emerging monitoring and data-collection approaches to resolve key uncertainties and improve assessment performance, including genetic, age-composition, and fisheries-independent data.