The ability to predict spatial distributions of marine species has advanced rapidly in recent years. Benefits include extrapolating habitat maps when data are sparse, thus improving our ability to quantify shifts in species ranges seasonally and over past decades, understanding the ocean conditions that drive these shifts, and projecting spatial redistribution due to climate change. Efforts have begun to couple these spatial distributions to complex multispecies and end-to-end-ecosystem models. The resulting integration of distributions, stock size, trophic interactions, and fishing effects allows for more realistic dynamics than what either model type is likely to attain alone. Coupling species distribution models to multispecies and ecosystem models is intuitively attractive, yet presents us with multiple decisions and approximations. Here we identify best practices for the detailed decisions (“the devil’s in the details”) required for such coupling. We summarize lessons learned from five case studies in the California Current and Peru Current ecosystems, the Celtic Sea, and the Gulf of Alaska, with a focus on examples regarding small pelagic fish.
Kaplan I., Hazen E.L., Koenigstein S., Lezama- Ochoa N., Hill M., Hernvann P.-Y., Liu O.R., Gomes D.G., Vásquez S.I., Luján C., Green S., Baker M.R., Oliveros-Ramos R., Rovellini A., Asch R. and Muhling B. (2026) The devil's in the details when using correlative and mechanistic species distribution models to inform multispecies and ecosystem models. Canadian Journal of Fisheries and Aquatic Sciences 83: 1-27. 10.1139/cjfas-2025-0419
@article{Kaplan2026,
Title = {The devil's in the details when using correlative and mechanistic species distribution models to inform multispecies and ecosystem models},
Author = {Kaplan, Isaac and Hazen, Elliott L and Koenigstein, Stefan and Lezama- Ochoa, Nerea and Hill, Mariana and Hernvann, Pierre-Yves and Liu, Owen R and Gomes, Dylan G and Vásquez, Sebastián I. and Luján, Criscely and Green, Stephanie and Baker, Matthew R and Oliveros-Ramos, Ricardo and Rovellini, Alberto and Asch, Rebecca and Muhling, Barbara},
Journal = {Canadian Journal of Fisheries and Aquatic Sciences},
Year = {2026},
Pages = {1-27},
Volume = {83},
Doi = {10.1139/cjfas-2025-0419},
Abstract = {The ability to predict spatial distributions of marine species has advanced rapidly in recent years. Benefits include extrapolating habitat maps when data are sparse, thus improving our ability to quantify shifts in species ranges seasonally and over past decades, understanding the ocean conditions that drive these shifts, and projecting spatial redistribution due to climate change. Efforts have begun to couple these spatial distributions to complex multispecies and end-to-end-ecosystem models. The resulting integration of distributions, stock size, trophic interactions, and fishing effects allows for more realistic dynamics than what either model type is likely to attain alone. Coupling species distribution models to multispecies and ecosystem models is intuitively attractive, yet presents us with multiple decisions and approximations. Here we identify best practices for the detailed decisions (“the devil’s in the details”) required for such coupling. We summarize lessons learned from five case studies in the California Current and Peru Current ecosystems, the Celtic Sea, and the Gulf of Alaska, with a focus on examples regarding small pelagic fish.},
}
TY - JOUR
AU - Kaplan, Isaac
AU - Hazen, Elliott L
AU - Koenigstein, Stefan
AU - Lezama- Ochoa, Nerea
AU - Hill, Mariana
AU - Hernvann, Pierre-Yves
AU - Liu, Owen R
AU - Gomes, Dylan G
AU - Vásquez, Sebastián I.
AU - Luján, Criscely
AU - Green, Stephanie
AU - Baker, Matthew R
AU - Oliveros-Ramos, Ricardo
AU - Rovellini, Alberto
AU - Asch, Rebecca
AU - Muhling, Barbara
TI - The devil's in the details when using correlative and mechanistic species distribution models to inform multispecies and ecosystem models
T2 - Canadian Journal of Fisheries and Aquatic Sciences
PY - 2026
SP - 1-27
VL - 83
DO - 10.1139/cjfas-2025-0419
AB - The ability to predict spatial distributions of marine species has advanced rapidly in recent years. Benefits include extrapolating habitat maps when data are sparse, thus improving our ability to quantify shifts in species ranges seasonally and over past decades, understanding the ocean conditions that drive these shifts, and projecting spatial redistribution due to climate change. Efforts have begun to couple these spatial distributions to complex multispecies and end-to-end-ecosystem models. The resulting integration of distributions, stock size, trophic interactions, and fishing effects allows for more realistic dynamics than what either model type is likely to attain alone. Coupling species distribution models to multispecies and ecosystem models is intuitively attractive, yet presents us with multiple decisions and approximations. Here we identify best practices for the detailed decisions (“the devil’s in the details”) required for such coupling. We summarize lessons learned from five case studies in the California Current and Peru Current ecosystems, the Celtic Sea, and the Gulf of Alaska, with a focus on examples regarding small pelagic fish.
ER -
