Full Title: Ecosystem Modeling to Improve Fisheries Management in the Gulf of Mexico
This project is integrating information on ecosystem stressors and predator-prey interactions into the fisheries assessment and management process in the Gulf of Mexico.
The Team: David Chagaris (Lead Investigator, University of Florida, firstname.lastname@example.org), Skyler Sagarese (NOAA), Matthew Lauretta (NOAA), Kim de Mutsert (University of Southern Mississippi), and Rob Ahrens (NOAA)
Technical Monitor: Nick Farmer (email@example.com)
Federal Program Officer/Point of Contact: Frank Parker (firstname.lastname@example.org)
This project began in June 2017 and will end in May 2022.
Award Amount: $1,167,586
Why it matters: The population of a recreationally or commercially important fish species can be influenced by several factors such as harvest, the abundance of its prey, the abundance of its predators, mortality events, and ocean conditions. Understanding how these factors interact and quantifying the effects is not easy. Advances in ecosystem simulation models in the Gulf of Mexico is making it possible to incorporate these factors into the assessment of valuable fishery species and improve our ability to manage.
What the team is doing: This project will further refine Gulf of Mexico ecosystem models to address questions and develop outputs that are relevant to the decisions managers face. Working with input from managers and stock assessment scientists, the model development team will adapt existing ecosystem models to quantify the impacts of red tides and explore effects and tradeoffs in Gulf fisheries such as grouper and menhaden. In addition, the model development team has developed new model features and procedures to represent lethal and sublethal effects of red tides. The team has also improved model accuracy to better represent spatial processes and stressors such as habitat preferences, red tides, and fish migration patterns. The model development team will align model development and outputs to coincide with the requirements and timing of the stock assessment and management process.
Expected Outcome: This project will integrate fisheries managers into the continued development of computer-based ecosystem models for the Gulf of Mexico and produce model outputs that are necessary for stock assessment and relevant to the decisions managers face. This project is expected to improve stock assessment and inform catch limits for gag grouper by providing historical and near-real time estimates of red tide impacts. This project will also evaluate tradeoffs associated with menhaden harvest and develop new management reference points that take into account their important role in the ecosystem.
From the seminar “Ecosystem Modeling to Improve Fisheries Management in the Gulf of Mexico”
Presenter: Dr. David Chagaris, University of Florida, and Dr. Igal Berenshtein, University of Miami
Berenshtein, I., S. Sagarese, M. Lauretta, M. Nuttall, and D. Chagaris. 2021. NOAA RESTORE Science Program: ecosystem modeling to improve fisheries management in the Gulf of Mexico: model inputs and outputs for the US Gulf-wide model, 1980-01-01 to 2016-12-31 (NCEI Accession 0243116). NOAA National Centers for Environmental Information. Dataset.
Chagaris, D., and D. Vilas. 2022. NOAA RESTORE Science Program: Ecosystem modeling to improve fisheries management in the Gulf of Mexico: model inputs and outputs for the West Florida Shelf, 1985-01-01 to 2018-12-31 (NCEI Accession 0242339). NOAA National Centers for Environmental Information. Dataset.
Chagaris, D., Sagarese, S., Farmer, N., Mahmoudi, B., de Mutsert, K., VanderKooy, S., Patterson III, W.F., Kilgour, M., Schueller, A., Ahrens, R. and Lauretta, M. (2019). Management challenges are opportunities for fisheries ecosystem models in the Gulf of Mexico. Marine Policy, 101, 1-7.
Berenshtein, Igal, Sagarese, Skyler R, Lauretta, Matthew V, Nuttall, Matthew A, Chagaris, David D. 2021. Technical documentation of a U.S. Gulf of Mexico-wide Ecosystem model. NOAA Technical Memorandum. NMFS-SEFSC-751, 229 p. https://doi.org/10.25923/zj8t-e656
Berenshtein, I., Sagarese, S. R., Lauretta, M. V., Schueller, A. M., & Chagaris, D. D. (2023). Identifying trade-offs and reference points in support of ecosystem approaches to managing Gulf of Mexico menhaden.
Vilas, D., Fletcher Jr, R. J., Siders, Z. A., & Chagaris, D. (2022). Understanding the temporal dynamics of estimated environmental niche hypervolumes for marine fishes. Ecology and Evolution, 12(12), e9604.
Vilas, D., Buszowski, J., Sagarese, S. et al. Evaluating red tide effects on the West Florida Shelf using a spatiotemporal ecosystem modeling framework. Sci Rep 13, 2541 (2023). https://doi.org/10.1038/s41598-023-29327-z
Red Tide RShiny App. This tool represents predicted biomass, biomass loss due to red tide, and annual red tide mortality rate from the year 2002 to 2018 from the West Florida Shelf (WFS) spatiotemporal ecosystem model. It allows the exploration of predictions for multiple groups/species and multiple model configurations.