Modelling seabird breeding habitat selection

Seabirds breed on offshore islands and/ or coastal cliffs to reduce exposure to terrestrial predators and be close to feeding areas. Nonetheless, for cliff nesting species, it is clear that not all cliffs are equal: Birds crowd into some areas at densities of over 70 nests per metre squared, while other cliffs are left empty, even when they apparently contain ledges suitable for nesting. Exposure to wind is likely to be a key factor due to its impact on thermoregulation, flight capacity and the ability of strong winds to displace birds from the nest, with the importance of wind varying between species according to body mass and flight style, for instance. In support of this, a recent study has shown that large breeding colonies of common guillemots (hereafter guillemots) can be predicted from simple proxies for shelter on two small, neighbouring islands. Nonetheless, the links between airflows and fitness have yet to be tested, and whether shelter can predict breeding distributions at a regional scale, including in colonies that vary in their exposure to strong winds, remains unknown. These represent important knowledge gaps because (i) colonies can represent the nexus of reproductive activity for tens of thousands of individuals and (ii) wind regimes are changing.

We will establish the impact of wind on population level processes in cliff-nesting seabirds, taking common guillemots (Uria aalge), hereafter guillemots, razorbills (Alca torda), black-legged kittiwakes (Rissa tridactyla) and northern fulmars (Fulmarus glacialis) as our study systems. We focus on cliff-nesting species as these will be the most exposed to the wind. They also represent over 75% of the seabirds breeding in the UK (over 6 million of the approximately 8 million recorded by the JNCC Seabird 2000 report). The influence of wind seabirds is therefore of interest both from a conservation perspective and from the wider impact on marine communities.

A key constraint in the ability to study the impact of wind at the nest site has been the difficulties of measuring wind over steep and inaccessible terrain, such as nesting cliffs. We will take an ambitious, interdisciplinary approach using computational fluid dynamics software (CFD) to characterise the airflows that birds select and avoid at their breeding cliffs in 9 areas of the UK. CFD is widely used in other disciplines (e.g. in the wind energy industry) and has proved pivotal for understanding the impact of currents on the behaviour and ecology of riverine fish. However, wider applications in animal ecology are lacking. We will use supercomputing facilities to model the wind in our study areas, which represents an increase in 3 orders of magnitude in the scale at which such models have been used in avian ecology. This will allow us to establish (i) whether birds select their breeding habitat in relation to the shelter it provides, whether shelter can predict (ii) differences in breeding success between sub-colonies, and (iii) the population trend over a decadal scale. Finally, we will test whether simple measures of cliff orientation can be used as a proxy for shelter, which would allow our approach to be applied to even larger areas without the associated computational cost.

Our project capitalises on the rich data available for breeding seabirds across the UK, including at least a decade of count and breeding success data from 9 areas that vary in their exposure to strong winds, and that represent a substantial proportion of the total UK breeding populations of our study species. The outputs will include the first regional-scale habitat selection model for seabirds, as well as novel insight into the mechanisms by which wind impacts wider population-level processes.