Considering Coasts: Adapting Terrestrial Models to Characterize Coastal Wetland Ecosystems

Incorporating coastal vegetation and hydrology in the E3SM Land Model to simulate salt marsh ecosystem responses to elevated CO2 and temperature.

Summary of updates to the E3SM Land Model to adapt the terrestrial forest model to simulate a coastal salt marsh.

[Reprinted with permission from O’Meara, T.A., et al. “Considering Coasts: Adapting Terrestrial Models to Characterize Coastal Wetland Ecosystems.” Ecological Modelling 450, 109561 (2021). [DOI:10.1016/j.ecolmodel.2021.109561] © 2022 Elsevier.]

The Science

Using the Energy Exascale Earth System Model (E3SM) Land Model as a base framework, researchers added plants, soil, and water flow to represent a coastal salt marsh. Once updated, they used the salt marsh model to simulate elevated carbon dioxide (CO2) and temperature treatments from the SMARTX experiment ( The researchers were more successful at predicting aboveground than belowground responses. Simulations of C3 species were more successful than those of C4 species. Similar to field data, simulations showed that CO2 increased plant growth for C3 plants and had little effect on C4 species, and that temperature responses for both plant functional types were nonlinear.

The Impact

Coastal wetlands are important carbon sinks but are missing from many models used for global-scale climate prediction. This work represents initial steps in incorporating coastal wetlands in global models by simulating tidal marsh plants, soils, and tides. The model was tested by comparing results to field data to pinpoint areas for future data collection. Targeted data collection can be used to improve model simulations and provide more accurate estimates of carbon cycling.


E3SM simulates the connections between plants, soil, and water and their interactions with climate. However, E3SM does not include systems at the terrestrial-aquatic interface (TAI), such as coastal wetlands. Since TAIs are important zones for carbon processing, including them in E3SM is key to improving climate predictions. Based on measurements from a field experiment in a well-studied coastal salt marsh, in which temperature and CO2 concentration were modified to represent potential future climate conditions, the team added new coastal vegetation types (high-elevation and low-elevation marsh) and new marsh hydrology processes (tides and interaction with tidal channels) into E3SM’s Land Model (ELM). The model was used to investigate the role of elevated CO2 and temperature on plant productivity. Results were compared to observed responses from the field-scale experiments. The updated model captures many aspects of the field experiments, showing that plant community responses to environmental change are nonlinear, and that differences between community responses can be explained by differences in plant physiology and hydrologic setting. The study was more successful at simulating aboveground than belowground processes. Additionally, simulations of a low-elevation marsh dominated by a C3 species were more closely aligned with field data than those for a high elevation dominated by C4 species. Next steps will include updates to key belowground parameters such as root:shoot carbon allocation and the addition of feedbacks between plants and nutrient processing.

Principal Investigator

J. Patrick Megonigal
Smithsonian Environmental Research Center
[email protected]

Program Manager

Daniel Stover
U.S. Department of Energy, Biological and Environmental Research (SC-33)
Environmental System Science
[email protected]


This work was supported by the Office of Biological and Environmental Research (grant numbers DE-SC0014413 and DE-SC0019110) within the U.S. Department of Energy Office of Science, the National Science Foundation Long-Term Research in Environmental Biology Program (grant numbers DEB-0950080, DEB-1457100, and DEB-1557009), and the Smithsonian Institution.


O’Meara, T.A., et al. "Considering Coasts: Adapting Terrestrial Models to Characterize Coastal Wetland Ecosystems." Ecological Modelling 450 109561  (2021).