Computer models based on satellite and climate data could warn scientists early on about the decline in coastal wetlands.
Using this model, scientists detected a decline in underground plant biomass in most coastal wetlands in Georgia between 2014 and 2023. Critical, this loss thrived on the surface despite the grass of the wetlands thriving in greenery.
Survey results released last month Proceedings of the United States Academy of Scienceshelps land managers identify targets for recovery before more serious damage is retained.
The roots of concern
Wetlands are “a place of cultural and entertainment importance not only economically but also for those who live along the coast and visit the coast.”
Kyle Lannion, a study co-author who is a landscape ecologist at the University of Georgia, said: They help to control flooding, sequestering carbon and provide space for hunting, fishing and wildlife spots.
However, rapid sea level rise threatens coastal marsh grasses as higher waters and more frequent floods flood the soil and suffocate the supply of oxygen at the roots. In healthy ecosystems, underground plant biomass stops erosion and ultimately breaks down into more soil, increasing Marsh's resilience to sea level rise, and a decline in the root system can be an early sign of Marshland.
Wetlands can sometimes appear healthy even when their roots are dying, said Bernard Wood, a wetland ecologist with the Louisiana Department of Coastal Conservation and Restoration, who was not involved in the study.
But a trip to the wetlands itself tells a different story. “I just pick up this huge chunk of grass with one hand and there's very little that has it on the ground,” Wood said.
BERM and Biomass
To understand how Georgia's wetlands respond to changing conditions, researchers developed and tested the Underground Ecosystem Resilience Model (BERM) in 2021. Spartina alternifloraor smooth corded glass from coastal areas.
In the 2021 survey, the team gathered information on environmental conditions for Georgia Salt Marsh from Landsat 8, Daymet Climate Summaries, and other public data sets. They built machine learning models that could predict underground biomass and trained them with field data from four MARSH sites. Researchers found that some of the most important variables in predicting root biomass are the frequency and depth of rise, vapor pressure, and flooding.
How a salt marsh looks on the surface is not necessarily an indicator of how it actually operates.
In a new study, Runion and his colleagues applied the model, S. Alterniflora Between 2014 and 2023, root biomass spans approximately 700 square kilometers of the Georgia coast.
Meanwhile, the team found that underground biomass on average fell by about 1% per year. Approximately 72% of the salt marsh areas had reduced subterranean plant mass. At the same time, ground biomass, a visible part of the marsh grass, was attacked by most of the study areas.
Ground biomass is less sensitive to floods than root systems, so disparities between the top and bottom biomass can occur. Alternatively, the increase may be temporary, as floods provide nutrients initially, but ultimately own the plants. In either case, what the salt marsh looks like on the surface doesn't necessarily indicate that it is truly being carried.
Tools for Maintenance
The early warning signs of wetland decline provided by the model are essential for conservation. “one time [marsh] Runion said: “By getting signs of deterioration before the loss occurs, you can step in and do something much easier about this.”
Mapping which areas of the wetland are the most vulnerable could combat the tendency for the wetland to be “undoomed” or “undoomed” and could target conservation efforts to the most needy areas, said Dennis Reid, a New Orleans University coastal geologist who is not involved in the study. Underground biomass is on average decreasing, but some areas of the coast change less than others.
“There are some complicated patterns going on, and it's probably great to understand it a little better,” Reed said. But “this idea that we can detect areas in worse condition against areas in better condition from a soil perspective is really helpful.”
For now, BERM can only predict underground biomass in the swamps of Georgia. Other regions have different plant species and flood dynamics that can alter the relationships that BERM depends on. However, additional calibration data from other salt marsh can allow the team to make the model more widely applicable, Runion said.
“We are trying to expand this species' modeling framework to include a variety of species along the Gulf and East Coast,” Runion says.
—Skyler Ware (@skylerdware), science writer
