October 12, 2022

Drivers and demographic consequences of seabird foraging strategies in a changing environment

Coastal marine ecosystems are undergoing rapid change due to multiple anthropogenic impacts including overfishing, climate change, pollution and renewable energy generation. These changes have important impacts on marine organisms, including top predators such as seabirds, leading to increased concern for protected populations. Understanding how seabirds adjust their behaviour with respect to spatio-temporal variation in their environment and food resources to shape energetics and demography is crucial for predicting their ability to cope with future environmental change, and for devising effective conservation measures. However, robust understanding of how key drivers shape responses to environmental change is lacking which hinders our ability to quantify and predict impacts of anthropogenic activities on protected species.

This project will use one of the most extensive datasets on seabird at-sea activity, location and demography in the world, spanning 35 years, as well as additional targeted data collection to: (1) identify drivers of foraging behaviour across a range of environmental conditions; (2) determine the consequences of foraging strategies for productivity and survival; (3) forecast impacts of change in productivity and survival on population trajectories under different scenarios of future human activity in an inshore, benthic-foraging species, the European shag.

The student will be based at UKCEH Edinburgh and will be co-supervised at Bangor University, where they will be registered, with further training provided by collaborators at the University of Highlands and Islands. The student will develop skills in (1) processing and integration of large, complex datasets, (2) designing field studies aimed at testing effects of environmental and intrinsic factors on individual performance, (3) field techniques including deployment of bio-logging devices, (4) advanced statistical analyses including hierarchical Bayesian modelling, mixed modelling, integrated population modelling and stochastic population viability analysis. The student will receive further training in transferable skills from all partner institutions and within the Envision DTP.

Applicants must have or expect to have, a First or Upper Second Class UK Honours degree or the equivalent qualification gained outside the UK, in a relevant subject to the project applied for. We welcome applications from all suitably qualified candidates. Our graduates will come from a diverse range of backgrounds and ethnicities, and Envision strives to ensure that no applicant/student shall experience prejudice at admissions or during their studies, related to their sexuality, disability or any other protected characteristic.

For more information please contact Maria Bogdanova (