Quantifying spatiotemporal variability in zooplankton dynamics in the Gulf of Mexico with a physical–biogeochemical model

Shropshire, Taylor A.; Morey, Steven L.; Chassignet, Eric P.; Bozec, Alexandra; Coles, Victoria J.; Landry, Michael R.; Swalethorp, Rasmus; Zapfe, Glenn; Stukel, Michael R.

doi:https://doi.org/10.5194/bg-17-3385-2020

Articles | Volume 17, issue 13

https://doi.org/10.5194/bg-17-3385-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/bg-17-3385-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 17, issue 13

Research article

|

05 Jul 2020

Research article |

| 05 Jul 2020

Quantifying spatiotemporal variability in zooplankton dynamics in the Gulf of Mexico with a physical–biogeochemical model

Taylor A. Shropshire, Steven L. Morey, Eric P. Chassignet, Alexandra Bozec, Victoria J. Coles, Michael R. Landry, Rasmus Swalethorp, Glenn Zapfe, and Michael R. Stukel

Supplement

https://doi.org/10.5194/bg-17-3385-2020-supplement

Data sets

NEMURO-GoM model code along with configuration files to run with MITgcm T. Shropshire https://github.com/tashrops/NEMURO-GoM

Temporally averaged three-dimensional fields for all 11 state variables used in NEMURO-GOM along with surface chlorophyll T. Shropshire https://data.gulfresearchinitiative.org

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Short summary

Zooplankton are the smallest animals in the ocean and important food for fish. Despite their importance, zooplankton have been relatively undersampled. To better understand the zooplankton community in the Gulf of Mexico (GoM), we developed a model to simulate their dynamics. We found that heterotrophic protists are important for supporting mesozooplankton, which are the primary prey of larval fish. The model developed in this study has the potential to improve fisheries management in the GoM.