CAS-Climate: Acquisition of Eddy Covariance Towers for Assessing Spatial and Temporal Variability in Greenhouse Gas Emissions from Coastal Wetlands in California

This award will support the acquisition of eddy covariance towers and carbonate chemistry sensors to continuously monitor greenhouse gas emissions and lateral carbon fluxes at Elkhorn Slough – a National Estuarine Reserve site and the largest coastal tidal wetland in California outside the San Francisco Bay-Delta. The eddy covariance method is the preferred technique today for estimating gas fluxes which permits calculation of seasonal and annual emissions and inventories. Data obtained will be deposited in the AmeriFlux database and will contribute to better constrain the carbon budget in these systems and allow for extrapolation to other coastal wetlands. The outcomes will also enable coupling of Earth System Models with realistic predictions emissions from coastal/tidal wetlands based on reliable emission data. This project will provide quantitative information that will enable local communities and policy managers to understand the cost-benefits of restoring wetlands to sequester carbon and enhance other ecosystem services. It will improve our understanding on the processes that control greenhouse gas emissions from coastal wetlands, information that will help decision-making and the financing and methodological guidance for introducing coastal wetland management projects into carbon markets. The project also will provide summer internship opportunities for local under-represented students to work at the site using authentic data directly relevant to them and hence expanding their climate and data literacy. In addition, we will develop and offer a course on data literacy in which students will use authentic data from the towers (and other sites) to hone their data and modeling skills.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.