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Fisheries Ecosystem Models

Full Title: Ecosystem Modeling to Improve Fisheries Management in the Gulf of Mexico

This project integrated 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, dchagaris@ufl.edu), Skyler Sagarese (NOAA), Matthew Lauretta (NOAA), Kim de Mutsert (University of Southern Mississippi), and Rob Ahrens (NOAA)

Technical Monitor: Nick Farmer (nick.farmer@noaa.gov)

Federal Program Officer/Point of Contact: Frank Parker (frank.parker@noaa.gov)

This project began in June 2017 and ended 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 did: This project worked to 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 adapted 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 developed new model features and procedures to represent lethal and sublethal effects of red tides. The team 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 aligned model development and outputs to coincide with the requirements and timing of the stock assessment and management process.

Summary of Outcome: The overall goal of this project was to formally integrate information on ecosystem stressors and predator-prey interactions into the fisheries assessment and management process of the Gulf of Mexico, with a focus on red tide impacts on gag grouper and ecosystem-based management of Gulf menhaden. The objectives to achieve this goal consisted of end user engagement, model development, application to stock assessment and management, and training. The project included 5 investigators, 2 post-docs, and 2 PhD students as well as over a dozen collaborators (e.g. data providers, stock assessment analysts) and end users (i.e. fisheries managers). The work plans included end user engagement, updating and advancing existing Gulf of Mexico ecosystem models, providing outputs for fisheries stock assessment, providing outputs to inform decision making. End user engagement was conducted throughout the project via dedicated workshops as well as opportunistically at routine stock assessment and management meetings. Three ecosystem models were updated as part of the project, including a model for West Florida Shelf (WFS), the entire U.S. Gulf of Mexico, and the Northern Gulf of Mexico. These models were designed with the intention of informing stock assessment and management. This required 1) updating and integrating data on fishing effort, fishing mortality, biomass, landings, bycatch, life history, stock assessments, and food habits; 2) time-dynamic modeling of marine species population trends as driven by fishing, primary production, and other environmental drivers; and 3) development of fine-scale and spatially-explicit ecosystem components for the West Florida Shelf and Louisiana continental shelf. Outputs from the models and associated analyses were provided for use in stock assessments and management of gag and Gulf menhaden. The project resulted in or contributed to seven peer-reviewed publications (2 published, 3 under review, and 2 in preparation), four SEDAR working papers, two PhD dissertations, six presentations to managers, four workshops, three data submissions, and two web applications.

Primary accomplishments include:

  1. The development and application of the West Florida Shelf Ecospace model to estimate red tide mortality, inform stock assessment, and provide near-real time advice for management of gag
  2. The development and application of the U.S. Gulf-wide model to estimate ecological reference points (ERPs) for Gulf menhaden. Red tide was estimated to cause substantial mortality on gag grouper, especially juveniles that are distributed closer to shore, with 2005 being the most severe year in our analysis.

The Gulf menhaden tradeoff analysis and resulting ERPs indicated that the fishery was likely ‘ecosystem overfishing’ during the 1980s and 1990s, but current fishing mortality rates are within the range of our estimated ERPs. We highlight the utility of the WFS ecosystem model to inform acceptable biological catch determination of gag grouper, which marks the first time an ecosystem model has been integrated into management advice in the Gulf of Mexico.

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

Other Resources

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. 2021. West Florida Shelf Ecosystem Model. Ecopath model database file. University of Florida Institutional Repository. http://ufdc.ufl.edu/IR00011604/00001. Accessed 9/19/2022.

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.

Vilas, D. 2022. Spatiotemporal ecosystem dynamics on the West Florida Shelf: Prediction, validation, and application to red tides and stock assessment. PhD Dissertation, University of Florida. Available: http://ufdc.ufl.edu/UFE0058578/00001.

Berenshtein, I., Sagarese, S., Lauretta, M., Nuttall, M., Chagaris, 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.

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.

Chagaris, D. and Vilas, D. (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.

Vilas, D., Buszowski, J., Sagarese, S. , Steenback, J., Siders, Z., and Chagaris, D. (2023). Evaluating red tide effects on the West Florida Shelf using a spatiotemporal ecosystem modeling framework. Sci Rep 13, 2541. https://doi.org/10.1038/s41598-023-29327-z

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.

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.