Jeglinski & Matthiopoulos

Seabirds are important indicators of marine ecosystem health. A detailed understanding of seabird population dynamics is essential for their conservation and for decrypting early warning signals of changes in the marine environment. Although seabird colonies are increasingly recognized as metapopulation networks, we lack an in-depth understanding of the dynamics that establish and maintain these networks.

My work will address these knowledge gaps via an innovative approach that dovetails population- and individual-level processes using the iconic Northern gannet (Morus bassanus) as case study.

Firstly, I will apply advanced habitat modelling to identify suitable colony locations based on environmental variables.

Secondly, I will address colony dynamics at the population level by fitting a dynamic, state-space metapopulation model to a 100-year historical dataset of gannet colony censuses over their East Atlantic breeding range.

Complementarily, I will address breeding colony selection at the individual-level by equipping immature gannets with GPS tracking devices. Using the fully-fitted metapopulation model, I will then forecast the effects of scenarios of local and global (e.g. climate) environmental change.

These results will enhance our understanding of the long-term responses of important indicator species to anthropogenic environmental change and provide a broad scientific basis for the adaptive ecosystem management of seabirds.

First published: 10 August 2014

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