n the wet, muddy places where America’s rivers and lands meet the sea, scientists from the Department of Energy’s Oak Ridge National Laboratory are unearthing clues to better understand how these vital landscapes are evolving under climate change.

Around 40% of the nation’s population live in coastal counties. The coasts are a linchpin of the economy, hosting the nation’s ports, key energy infrastructure, fisheries and tourism centers, producing $10 trillion in goods and services a year. Coastal wetlands serve as an effective barrier to absorb flooding impacts and guard against property damage. However, severe storms, chronic sea level rise and increasing infrastructure, plus other stressors present unique challenges for coastal ecosystems. 

ORNL researchers gather and analyze data about how water, soils, plants and microbes interact and influence the cycling of carbon and nutrients in these environments. They collect samples in biomes as varied as the coastal marshes of Louisiana, the mangrove swamps of Texas and the coastal wetlands of the Chesapeake Bay and Lake Erie. Their goal is to improve the nation’s premier Earth system simulations that help decision-makers prepare for the future.

Elizabeth Herndon, senior staff scientist in ORNL’s Environmental Sciences Division, is leading a project examining how water level fluctuations along the Louisiana coastline translate into changes in biogeochemical processes, or the natural cycles of life, earth and chemistry in the environment. The study involves two sites – one in which a delta is actively growing after part of a river was diverted to reduce urban flooding. The other site is where land is submerging as the sediment supply has been cut off, with soils increasingly inundated and subject to salinization — where soluble salts accumulate — from sea level rise. 

The research is part of Herndon’s DOE Early Career Award project focused on how flooding by freshwater and seawater affect interactions between the nutrient phosphate and the elements iron and manganese in coastal ecosystems. The findings will improve predictive modeling capabilities.