Coastal marshes support communities and economies by providing protection from storm surge and habitat for valuable species and recreation. To preserve these benefits, managers need short- and long-term estimates of marsh changes in response to rising sea levels. There are many models of future marsh conditions available, and the project team will offer insights on the differences between models and clarify how they might best be used.
Why We Care
Multiple models predict future coastal marsh conditions, with new and enhanced models appearing every year. The number of available models and the substantial differences in their functionalities can lead to discordant predictions of future marsh extent and health. Understanding the implications of differences in model functionality is often confusing but is critical for accurately using marsh model predictions to inform management decisions, such as land acquisition and development.
This project aims to reduce model confusion. By comparing model results from similar sea level rise scenarios and time steps, we can highlight areas of agreement and disagreement. Understanding where there is cross-model consensus on the extent of future habitat helps minimize uncertainty and improve confidence in the planning and validity of management decisions related to sea level rise.
What We Are Doing
In 2018, we compared marsh model results in three regions along the Northern Gulf of Mexico coast (Apalachicola Florida, Grand Bay Mississippi, and all of coastal Louisiana) for two different sea level rise scenarios at various time steps to determine:
- Agreement of marsh predictions between marsh models; we re-classified model outputs as ‘marsh,’ ‘water,’ or ‘other’ (e.g., dry land, swamp, beach)
- Agreement of land and water classifications between marsh models; we re-classified model outputs simply as ‘water’ or ‘land’ (i.e., ‘marsh’ + ‘other’ classifications from the marsh predictions above)
We worked closely with model developers and coastal natural resource managers to review model comparisons to better understand how that information could be expanded or repackaged to support management actions. In the Northern Gulf of Mexico our project is the result of a diverse team of modelers and managers, and is co-led by the Northern Gulf of Mexico Sentinel Site Cooperative coordinator, Renee Collini. Collaborators included over 30 organizations, including state, federal, and academic organizations in Florida, Alabama, Mississippi, Louisiana, and Texas. A complete list is provided at the end of this project description.
In 2020, funding from the Southeast Climate Adaptation Science Center (SECASC) is expanding this effort to explore conducting marsh model output comparisons elsewhere around the United States, and to work with marsh modelers to develop an approach for a retrospective analysis. A retrospective analysis will compare outputs of marsh model runs to historical data, allowing us to further understand the strengths and limitations of each model and the implications for model application. The project with SECASC will be conducted through 2021.
What We Found
In the Gulf of Mexico 2018 marsh model comparison, across the three examined regions (LA, MS, FL), we found varying levels of marsh classification agreement between models (18–67%) in the initial timesteps (~c. 2000). Marsh classification agreement broadly declined over time. Further, in most cases, agreement declined faster over time for higher sea level rise scenarios. When model results were re-classified and compared for land-water agreement, we found higher agreement than for the marsh classification (agreement ranges for the initial timesteps (c. 2000) are land: 38–65%; water: 32–43%). These levels of agreement mostly held constant over time and trended slightly lower for higher sea level rise scenarios.
Because the input data sets for these models varied greatly it is difficult to understand why marsh extents were different between these models. In the 2020 study, we will dive deeper into this next step. We will identify data sets and new study areas where marsh models can be run with a standardized set of input data to better understand these output differences.
Benefits of Our Work
Our data and products are essential tools for local managers charged with restoring and conserving these valuable resources in a changing climate. Our workshop products (report and online mapping application) provide a systematic review of marsh model agreement and disagreement under future sea level rise conditions and can be combined with or compared to existing efforts in the regions. These marsh model comparison results can be used to:
- Inform future land acquisition
- Define areas of model improvement
- Identify regions of high vulnerability
- Highlight valuable restoration locations (e.g. beneficial use sites)
Complete List of Our Project Partners:
Alabama: Alabama Department of Conservation and Natural Resources (AL DCNR), AL DCNR – Marine Resources Division, Geological Survey of Alabama.
Florida: Florida Department of Environmental Protection, Florida International University, Florida Fish and Wildlife Conservation Commission (FWC), FWC – Fish and Wildlife Research Institute, University of Central Florida.
Louisiana: Louisiana Department of Wildlife and Fisheries, Louisiana State University.
Mississippi: Mississippi-Alabama Sea Grant, Mississippi Department of Environmental Quality, Mississippi Department of Marine Resources, Mississippi State University, Southern Mississippi Planning & Development District.
Texas: Harte Research Institute, Texas Parks & Wildlife Department, Texas General Land Office.
Gulf-wide / Cross-state Organizations: Coastal Protection and Restoration Authority, Gulf of Mexico Alliance, Northern Gulf Institute, Northern Gulf of Mexico Sentinel Site Cooperative, The Water Institute of the Gulf.
Federal Agencies: National Oceanic and Atmospheric Administration (NOAA), NOAA Office for Coastal Management, NOAA Fisheries, U.S. Environmental Protection Agency, U.S. Department of the Interior, U.S. Fish and Wildlife Service, U.S. Geological Survey (USGS), USGS Southeast Climate Adaptation Science Center.