For the first time, an international work with Bastien MÉRIGOT (UM, MARBEC) led by Jim THORSON with the NOAA Fisheries Alaska Fisheries Science Center, takes a “Robin Hood” approach to provide missing information on data-poor fish species for more effective ecosystem based fisheries management. This work is part of the FISHGLOG project co-led by Bastien MÉRIGOT and Deng PALOMARES (UBC, IOF).
Scientists can now predict growth, survival, and reproductive strategies for all known fish in the world. The combination of traits a given species has developed to adapt to its niche and environment makes up its life history strategy. The new model uses 33 traits—describing size, growth, reproduction, parental care, lifespan and more— to classify more than 34,000 fish species among three dominant strategy types.
The results will inform ecosystem-based fisheries management, help forecast consequences of climate change, and advance our understanding of evolutionary relationships.
"Because of limited scientific resources, we can assess only a fraction of the fish species we catch around the world. Now we have a model that can predict traits and strategies for all the rest,” Thorson said. “That information is essential to set sustainable fishing limits and prepare for future change."
Jim THORSON, NOAA Fisheries Alaska Fisheries Science Center
To know more
Thorson, J. T., Maureaud, A. A., Frelat, R., Mérigot, B., Bigman, J. S., Friedman, S. T., Palomares, M. L. D., Pinsky, M. L., Price, S. A., Wainwright, P. (2023). Identifying direct and indirect associations among traits by merging phylogenetic comparative methods and structural equation models. Methods in Ecology and Evolution. https://doi.org/10.1111/2041-210X.14076
https://www.fisheries.noaa.gov/feature-story/first-time-scientists-can-predict-traits-all-fish-worldwide