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 (https://serc.si.edu/gcrew/warming). 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.

Summary

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
megonigalp@si.edu

Program Manager

Daniel Stover
U.S. Department of Energy, Biological and Environmental Research (SC-33)
Environmental System Science
daniel.stover@science.doe.gov

Funding

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.

References