Can we project changes in fish abundance and distribution in response to climate?

• Published in: Global Change Biology
• Main Authors: Fernandes, Jose A., Rutterford, Louise, Simpson, Stephen D., Butenschön, Momme, Frölicher, Thomas L., Yool, Andrew, Cheung, William W. L., Grant, Alastair
• Other Authors: Horizon 2020 Framework Programme, Seventh Framework Programme, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, Natural Environment Research Council
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2020
• Subjects: North East Atlantic
• Online Access: http://dx.doi.org/10.1111/gcb.15081; https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Fgcb.15081; https://onlinelibrary.wiley.com/doi/pdf/10.1111/gcb.15081; https://onlinelibrary.wiley.com/doi/full-xml/10.1111/gcb.15081

Abstract Large‐scale and long‐term changes in fish abundance and distribution in response to climate change have been simulated using both statistical and process‐based models. However, national and regional fisheries management requires also shorter term projections on smaller spatial scales, and these need to be validated against fisheries data. A 26‐year time series of fish surveys with high spatial resolution in the North‐East Atlantic provides a unique opportunity to assess the ability of models to correctly simulate the changes in fish distribution and abundance that occurred in response to climate variability and change. We use a dynamic bioclimate envelope model forced by physical–biogeochemical output from eight ocean models to simulate changes in fish abundance and distribution at scales down to a spatial resolution of 0.5°. When comparing with these simulations with annual fish survey data, we found the largest differences at the 0.5° scale. Differences between fishery model runs driven by different biogeochemical models decrease dramatically when results are aggregated to larger scales (e.g. the whole North Sea), to total catches rather than individual species or when the ensemble mean instead of individual simulations are used. Recent improvements in the fidelity of biogeochemical models translate into lower error rates in the fisheries simulations. However, predictions based on different biogeochemical models are often more similar to each other than they are to the survey data, except for some pelagic species. We conclude that model results can be used to guide fisheries management at larger spatial scales, but more caution is needed at smaller scales.