Landscape and Biogeochemical Controls of Methylmercury in Watersheds
In the Northeastern U.S., mercury has built up in watershed soils and sediments from long range atmospheric transport and deposition and point source contamination. Mercury is released to aquatic environments through dissolution of organic matter, and once mobilized, anaerobic microbial communities convert inorganic mercury to methylmercury under appropriate biogeochemical conditions. Methylmercury is a potent neurotoxin that bioaccumulates through aquatic foodwebs, posing a significant exposure risk to humans and wildlife that consume fish. Loading of mercury and organic matter to aquatic ecosystems is predicted to increase under global climate change due to decreased retention in soils from land disturbances and acid rain, and from increased episodes of high runoff. An understanding of the landscapes and processes that drive methylmercury transport in watershed streams, which connect terrestrial sources to larger bodies of water, are needed to predict the fate of mercury under different environmental scenarios.
Landscape, particularly wetland density and forest cover, plays a strong role in predicting the mobility and cycling of mercury and organic matter in watersheds. Once released, the transport and fate of mercury and organic carbon remain strongly tied. Different organic carbon structures have been related to landscape sources, where microbially-mediated components of organic matter are, like methylmercury, associated with wetland inputs, whereas terrestrial, protein-like components are highest during high flow conditions. In this study, we will model the interactive effects of organic carbon compounds and landscape parameters to understand methylmercury loading and bioavailability in streams. We will combine data on methylmercury and organic carbon parameters collected from streams in watersheds across the Northeastern U.S. (Lake Sunapee, NH, Hubbard Brook Experimental Forest, NH; Sleeper’s River, VT; and Arbutus Lake, NY) and obtain landscape parameters (eg. land cover, canopy cover and type) using remote sensing tools. These will be applied to establish a predictive model of methylmercury in streams across watersheds in the Northeast, and provide a framework for investigating the controls on methylmercury levels in streams across different spatial scales.