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Mobile Bay Fisheries

Full Title: Oyster, Blue Crab, Southern Flounder, and Spotted Seatrout Population Dynamics in Relation to Environmental Trends and Variability in Coastal Alabama

This project explores how oyster, blue crab, southern flounder, and spotted seatrout populations respond to human and environmental changes with the goal of improving the management of these economically and culturally important species.

The Team: John C. Lehrter*# (lead investigator, University of South Alabama, Dauphin Island Sea Lab jlehrter@southalabama.edu); Ronald Baker*# , Brian Dzwonkowski*# , Sean Powers*#  (University of South Alabama, Dauphin Island Sea Lab) Latif Kalin*# , Di Tian*#  (Auburn University); Ayoung Kim#, Dan Petrolia#, Seong Yun# (Mississippi State University);  Zhilong Liu# (University of South Alabama); Jeffrey David Plumlee# (Louisiana State University), Steven B. Scyphers# (University of South Alabama); Lisa Lowe* (North Carolina State University) Just Cebrian* (Mississippi State University, Northern Gulf Institute). *2019-2025  #2025-2029

Technical Monitors: Kelly Samek (kelly.samek@noaa.gov) and Eric Weissberger (eric.weissberger@noaa.gov)

Federal Program Officer: Frank Parker (frank.parker@noaa.gov)

Research Area: Multiple species, weather and climate, economic activity

Award Amount: $6,721,689

Award Period: September 2019 – August 2029

Why it matters: The abundance of oysters, blue crabs, southern flounder and spotted seatrout is rapidly declining in the Gulf. These species have provided valuable food, raw material, recreation, and cultural resources to humans since the Gulf was settled. Today, the ecosystem services provided by these species are threatened, or near collapse in Gulf estuaries. This is partially due to human activities and environmental trends such as fisheries harvest and changes in water and habitat quality. Many of the underlying mechanisms that relate long-term trends and short-term variability in the environment to changing populations of oyster, blue crab, southern flounder, and spotted seatrout are unquantified or unknown.

What the team is doing: This project continues to identify, measure, understand, and predict trends for four key estuarine species – oysters, blue crab, southern flounder, and spotted seatrout – and three stressors – elevated temperature, changing salinity (freshwater) patterns, and increasing low oxygen (hypoxia) events – in Mobile Bay, Alabama. Species’ thresholds will be quantified in lab experiments and field observations. Using a large time-series database of water quality, hydrology, climate, and species trends developed by the team, they will develop habitat suitability indices for the species across time. Next, the team will assess changes to ecosystem services by analyzing fishing behavior and management responses associated with the species. Finally, updated numerical models will be used to analyze environmental change and co-developed management scenarios. By linking multiple data sets of species recruitment, growth, and survival rates with natural and human induced environmental conditions across time, the project team seeks to improve the scientific foundation for ecosystem-based management of these populations in Mobile Bay. 

Expected Outcome:  This project will provide Mobile Bay decision-makers a process for evaluating various scenarios, management actions, and outcomes based on single and multiple thresholds for oyster, blue crab, southern flounder, and spotted seatrout populations. It will help identify what individual or combined stressors affect these economically and culturally important species plus evaluate how management actions may improve the resilience of these populations to environmental change.

Temperature, Salinity, pH, Oxygen, Inorganic and Organic Nitrogen, Phosphorus and Carbon, Suspended Sediments and Chlorophyll-a data for the Mobile Bay and Mississippi Sound from 2020-05-28 to present (NCEI Accession 0277234)

Li, Y., Tian, D., & Medina, H. (2021). Multimodel Subseasonal Precipitation Forecasts over the Contiguous United States: Skill Assessment and Statistical Postprocessing. Journal of Hydrometeorology, 22(10), 2581-2600. https://doi.org/10.1175/JHM-D-21-0029.1

Wang, F., Tian, D., Lowe, L., Kalin, L., & Lehrter, J. (2021). Deep Learning for Daily Precipitation and Temperature Downscaling. Water Resources Research, 57(4). https://doi.org/10.1029/2020WR029308

Haas, H., Dosdogru, F., Kalin, L., & Yen, H. (2021). Soft Data in Hydrologic Modeling: Prediction of Ecologically Relevant Flows with Alternate Land Use/Land Cover Data. Water, 13(21), 2947.

Haas, H., Kalin, L., & Srivastava, P. (2022). Improved forest dynamics leads to better hydrological predictions in watershed modeling. Science of The Total Environment, 153180.

Wang, F., & Tian, D. (2022). On deep learning-based bias correction and downscaling of multiple climate models simulations. Climate Dynamics, 1-18.

Takhellambam, B. S., Srivastava, P., Lamba, J., McGehee, R. P., Kumar, H., & Tian, D. (2022). Temporal disaggregation of hourly precipitation under changing climate over the Southeast United States. Scientific Data, 9(1), 211.

Domeisen, D. I. V., White, C. J., Afargan-Gerstman, H., Muñoz, Á. G., Janiga, M. A., Vitart, F., Wulf, C. O., Antoine, S., Ardilouze, C., Batté, L., Bloomfield, H. C., Brayshaw, D. J., Camargo, S. J., Charlton-Pérez, A., Collins, D., Cowan, T., del Mar Chaves, M., Ferranti, L., Gómez, R., González,P., Romero, C., Infanti, J., Karozis, S., Kim, H., Kolstad, E., LaJoie, E., Lledó, L., Magnusson, L., Malguzzi, P., Manrique-Suñén, A., Mastrangelo, D., Materia, S., Medina, H., Palma,L.,Pineda, L., Sfetsos, A., Son, S., Soret, A., Strazzo, S., & Tian, D. (2022). Advances in the subseasonal prediction of extreme events: relevant case studies across the globe. Bulletin of the American Meteorological Society, 103(6), E1473–E1501.

Fung, M. S., Phipps, S. W., & Lehrter, J. C. (2022). Abrupt chlorophyll shift driven by phosphorus threshold in a small subtropical estuary. Frontiers in Marine Science, 1949.

Dzwonkowski, B., Fournier, S., Lockridge, G., Coogan, J., Liu, Z., & Park, K. (2022). Hurricane Sally (2020) shifts the ocean thermal structure across the inner core during rapid intensification over the shelf. Journal of Physical Oceanography, 52(11), 2841-2852.

Liu, Z., Lehrter, J., Dzwonkowski, B., Lowe, L. L., & Coogan, J. (2022). Using dissolved oxygen variance to investigate the influence of nonextreme wind events on hypoxia in Mobile Bay, a shallow stratified estuary. Frontiers in Marine Science, 9.

Wang, F., Tian, D., & Carroll, M. (2022). Customized Deep Learning for Precipitation Bias Correction and Downscaling. Geoscientific Model Development, 16, 535–556

Isik, S., Haas, H., Kalin, L., Hantush, M. M., & Nietch, C. (2023). Nutrient Removal Potential of Headwater Wetlands in Coastal Plains of Alabama, USA. Water, 15(15), 2687.

Haas, H., Kalin, L., & Baltaci, E. (2024). How wide is the problem? Leveraging alternative data sources to enhance channel width representation in watershed modeling. Environmental Modelling & Software, 172, 105935.

Haas, H., Kalin, L., & Yen, H. (2024). Improved forest canopy evaporation leads to better predictions of ecohydrological processes. Ecological Modelling, 489, 110620.

Cebrian, J., Gilpin, R., Alberti, J., West, L., Moody, R., McDonald, R., Lau, Y. & Scheffel, W. (2024). Comparing shallow seagrass versus fringing marsh habitat use by nekton juvenile recruits with “incomparable” fishing gear in the northern Gulf of Mexico. Estuaries and Coasts, 1-12.

Plumlee, J. D., Powers, S. P., Kimbro, D. L., Lehrter, J. C., Herrmann, J., & Mareska, J. (2024). Increasing duration of heatwaves poses a threat to oyster sustainability in the Gulf of Mexico. Ecological Indicators, 162, 112015.

Jarvis, B. M., Lehrter, J. C., Lowe, L., Penta, B., Wan, Y., Duvall, M., Melendez, W. & Ko, D. S. (2024). Coastal generalized ecosystem model (CGEM) 1.0: Flexible model formulations for simulating complex biogeochemical processes in aquatic ecosystems. Ecological Modelling, 496, 110831.

Sreeshylam, H., Liu, Z., Dzwonkowski, B., & Lehrter, J. (2024). Enhancing model temperature estimations in shallow, turbid, coastal regions: Mobile Bay, Alabama. Ocean Modelling, 102455.

Haas, H., Kalin, L., Sun, G., & Kumar, S. (2024). Understanding the effects of afforestation on water quantity and quality at watershed scale by considering the influences of tree species and local moisture recycling. Journal of Hydrology, 640, 131739.

Wang, F., & Tian, D. (2024). Multivariate bias correction and downscaling of climate models with trend-preserving deep learning. Climate Dynamics, 62(10), 9651-9672.

Oxford, C., Dzwonkowski, B., & Goff, J. (2024). Observations of Lateral Salinity Variability at a Deltaic-Bay Transition Zone, Mobile Bay, Alabama. Gulf and Caribbean Research, 35(1), SC31-SC35.

Clemo, W. C., Dorgan, K. M., Wallace, D. J., & Dzwonkowski, B. (2024). Spatially and temporally variable impacts of hurricanes on shallow sediment structure. Journal of Geophysical Research: Oceans, 129(7), e2023JC020820.

Petrolia, D. R., Enyetornye, F., Chen, Z., & Yun, S. (2025). The value of oyster reef restoration. Marine Resource Economics, 40(1), 45-64.

Clark, A., Ellis, W. T., Rodriguez, A. R., & Baker, R. (2025). Dissolved Oxygen May Limit the Suitability of Salt Marsh as Nekton Habitat. Estuaries and Coasts, 48(4), 1-8.

Clemo, W. C., Dorgan, K. M., Dzwonkowski, B., & Wallace, D. J. (2025). Repeated hurricane disturbance has minimal impact on shallow coastal infaunal communities. Ecosphere, 16(7), e70341.

Haas, H., Kalin, L., Tian, D., & Lehrter, J. (2025). Dynamic land-use/cover improves simulations of long-term watershed-scale streamflow and water quality trends. Journal of Hydrology, 133744.

Categorical Exclusion Addendum for RESTORE Act Science Program Project Renewal: “Oyster, Blue Crab, Southern Flounder, and Spotted Seatrout Population Dynamics in Relation to Environmental Trends and Variability in Coastal Alabama: Phase II, Years 6-10”

Categorical Exclusion for RESTORE Science Program Project NA19NOS4510194, “Building Resilience for Oysters, Blue Crabs, and Spotted Seatrout to Environmental Trends and Variability in the Gulf of Mexico”

Not applicable