Acidification in brackish estuarine environments, such as the Chesapeake Bay, is intensified by coastal inputs such as runoff, atmospheric pollution and freshwater sources. The Chesapeake Bay is home to commercial shellfish hatcheries that supply seed that is sold to and planted in hundreds of shellfish farms within the Chesapeake. A great deal of research has been dedicated to understanding the impact of acidification on shellfish, and has shown even greater impacts to shellfish growth and survival in lower salinity and nutrient-rich environments. The shellfish industry relies on consistent hatchery production to sustain and expand operations that could greatly benefit from regional OA forecasts and metrics. This project will synthesize recent CO2 system observations with long-term water quality parameters and combine observations an existing baywide, high-resolution 3D model. The proposed research will develop forecasts of acidification and develop acidification metrics tailored to support decision-making needs of commercial shellfish hatchery and nursery operators.

The U.S. Northeast Shelf Large Marine Ecosystem, supports some of the nation’s most economically valuable coastal fisheries, yet most of this revenue comes from shellfish that are sensitive to ocean acidification (OA). Furthermore, the weakly buffered northern region of this area is expected to have greater susceptibility to OA. Existing OA observations in the NES do not sample at the time, space, and depth scales needed to capture the physical, biological, and chemical processes occurring in this dynamic coastal shelf region. Specific to inorganic carbon and OA, the data available in the region has not been leveraged to conduct a comprehensive regional-scale analysis that would increase the ability to understand and model seasonal-scale, spatial-scale, and subsurface carbonate chemistry dynamics, variability, and drivers in the NES. This project optimizes the NES OA observation network encompassing the Mid-Atlantic and Gulf of Maine regions by adding seasonal deployments of underwater gliders equipped with transformative, newly developed and tested deep ISFET-based pH sensors and additional sensors (measuring temperature, salinity for total alkalinity and aragonite saturation [ΩArag] estimation, oxygen, and chlorophyll), optimizing existing regional sampling to enhance carbonate chemistry measurements in several key locations, and compiling and integrating existing OA assets. The researchers will apply these data to an existing NES ocean ecosystem/biogeochemical (BGC) model that resolves carbonate chemistry and its variability.