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Ocean warming drives abrupt declines in fish productivity at global scale
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Abstract
Marine life is under multiple pressures, including climate change and overfishing. Environmental change and variability can threaten fishery sustainability, especially when it results in large, abrupt and persistent shifts in productivity of fish stocks. Reports of abrupt shifts in marine systems are not uncommon, but a global assessment of their occurrence and drivers is seriously lacking. Here, we systematically classified the temporal dynamics of fish stock productivity from agency-assessed fisheries worldwide. Among the 315 fish stocks with time series available, we detected at least one productivity abrupt shift for more than a quarter of the stocks. Using an integrative modeling approach including life history, environmental conditions, and fishing intensity variables, we showed that abrupt declines are over-represented in stocks where sea surface temperature increases have been larger during the period covered by fish stock monitoring, while abrupt increases are more likely under lower fishing intensity. We investigated the link between productivity abrupt shifts and stock collapses. We found that abrupt declines in productivity preceded stock collapses by ten to twenty years in 25% of the cases, suggesting that some major stock collapses could be anticipated if abrupt shift were more systematically detected and examined. Overall, our results highlight the importance of considering productivity abrupt shifts to prevent a pervasive risk of fish population collapse in warming oceans.
DOI
https://doi.org/10.32942/X22S86
Subjects
Life Sciences
Keywords
abrupt shift, Fisheries, nonlinear dynamics, stock assessment, warming temperatures
Dates
Published: 2025-05-22 13:50
Last Updated: 2025-05-22 13:50
License
CC-By Attribution-NonCommercial-NoDerivatives 4.0 International
Additional Metadata
Conflict of interest statement:
None.
Data and Code Availability Statement:
All analyses were conducted using R software (version 4.3.3). The R script to replicate all analyses is available on Github (https://anonymous.4open.science/r/ocean_warming_fisheries).
Language:
English
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