Publication: Skillful prediction of tropical Pacific fisheries provided by Atlantic Niños
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2021-05
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IOP Publishing Ltd
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Abstract
Tropical Pacific upwelling-dependent ecosystems are the most productive and variable worldwide, mainly due to the influence of El Niño Southern Oscillation (ENSO). ENSO can be forecasted seasons ahead thanks to assorted climate precursors (local-Pacific processes, pantropical interactions). However, due to observational data scarcity, little is known about the importance of these precursors for marine ecosystem prediction. Previous studies based on Earth System Model simulations forced by observed climate have shown that multiyear predictability of tropical Pacific marine primary productivity is possible. With recently released global marine ecosystem simulations forced by historical climate, full examination of tropical Pacific ecosystem predictability is now feasible. By complementing historical fishing records with marine ecosystem model data, we show herein that equatorial Atlantic sea surface temperatures (SSTs) constitute a valuable predictability source for tropical Pacific fisheries, which can be forecasted over large-scale areas up to three years in advance. A detailed physical-biological mechanism is proposed whereby equatorial Atlantic SSTs influence upwelling of nutrient-rich waters in the tropical Pacific, leading to a bottom-up propagation of the climate-related signal across the marine food web. Our results represent historical and near-future climate conditions and provide a useful springboard for implementing a marine ecosystem prediction system in the tropical Pacific.
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© 2021 The Author(s). This research was funded by the EU H2020 project TRIATLAS (No. 817578), the Universidad Complutense de Madrid project FEI-EU-19-09 and the Spanish Ministry of Economy and Competitiveness project PRE4CAST (CGL2017-86415-R). This work also acknowledges the ‘Severo Ochoa Centre of Excellence’ accreditation by the Spanish Ministry of Science and Innovation (CEX2019-000928- S) to the Institute of Marine Science (ICM-CSIC). We thank Derek Tittensor (UNEP-WCMC) and Iliusi Vega (PIK-Postdam) for help with FishMIP data extraction. We thank Roberto Suárez-Moreno (LDEO-Columbia University), Jeroen Steenbeek (ICM-CSIC) and Charles Stock (NOAA-GFDL) for their cooperation and help during the progress of this study. Finally, we would like to thank the two anonymous reviewers for their helpful comments and suggestions, which contributed to improve this manuscript.