Title: Optimizing Ocean Acidification Observations for Model Parameterization in a Coupled Slope Water System of the US Northeast Large Marine Ecosystem
Funding Agency: NOAA OAR
Project Lead: Grace Saba
Partners: Stony Brook University, University of New Hampshire, University of Maine. MARACOOS, MERACOOS
Period of Performance: 9/1/2019 – 8/31/2022
Total Budget: $1,499,896
The U.S. Northeast Shelf Large Marine Ecosystem (NES LME), 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 the NES 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. We propose a multi-pronged approach to optimize 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.
The proposed effort represents a unique collaboration of partnerships under two Regional Associations of the Integrated Ocean Observing System (NERACOOS, MARACOOS) and their respective Coastal Acidification Networks (MACAN, NECAN). One of the great benefits of the work proposed here is that it brings together experts in the region to establish a regional network that will integrate new and existing OA coastal observation data on continuous or seasonal scales, and some in near-real-time for easier accessibility to benefit end users and modelers that would allow them to: 1) Address hypotheses related to identifying the drivers, and relative importance of the drivers, of acidification on various time scales in both the Mid-Atlantic Bight and Gulf of Maine; 2) Identify high-risk areas that are more prone to periods of reduced pH/ ΩArag and/or high pH/ ΩArag variability to enable better management of essential habitats in future, more acidic oceans; 3) Determine natural variability that will provide a framework to better study organism response and design more realistic experiments; and 4) Represent a step change in the independent data available for constraining BGC model rate constants and other parameterizations that will enhance model robustness. Through these efforts, the researchers will develop a mechanistic understanding of the physical and biological drivers of carbonate chemistry in order to design an optimal carbonate system sampling strategy for the NES.