A pilot whale mass stranding event, Sanday, 2024
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Deep-future predictions of the impact of climate on seabirds, based on century-long metapopulation data. Out today. #PopulationDynamics #seabirds #climate #metapopulation #ecology
onlinelibrary.wiley.com/doi/10.1111/...
Thank you to all co-authors, data collectors, institutions and funders, especially the DESNZ Offshore Energy Strategic Environmental Assessment OESEA programme.
We built mechanistic relationships with climate and demography into a flexible metapopulation model to accelerate progress in robust assessment of the multiple anthropogenic and natural threats to the gannet. We hope our work encourages similar mechanistic explorations for other colonial species.
Instead of standing out as clear climate change 'winners' or 'losers', gannet responses resemble a mosaic of colony-specific sensitivities to climate change varying across time and space with colonies in the southern and central part of the distribution increasingly smaller than they could be.
We found non stationarity in marine density dependent regulation, and forecast shifts from terrestrial to marine density dependent regulation as sea surface temperatures increase, more so under the severe climate change scenario SSP5.
We found that gannet metapopulation dynamics are driven by climatic covariates. Most importantly, we found a non-linear effect of near surface air temperature (A) and decreasing recruitments rates with increasing sea surface temperatures, for colonies under marine density dependent regulation (C).
Distribution of Northeast Atlantic gannet colonies and time series of near surface air temperature for example colonies.
We fit our expanded model to colony census data of the entire Northeast Atlantic metapopulation and climatic covariates spanning 1900 - 2100. We use two IPCC climate change scenarios for forecasts: moderate warming to below 2 degrees (SSP1) and very high emissions scenario (SSP5).
We built on our Bayesian metapopulation model for the Northern gannet published here ➡️ esajournals.onlinelibrary.wiley.com/doi/full/10....
Forecasting population responses to a rapidly changing climate is paramount, but we require mechanistic models with appropriate demographic complexity and population structure, flexibility in relationships between climate and demographic rates and variability across time and space.
