Coastal wetlands are critical components of both land and ocean carbon (C) budgets at global scales. Accounting for C import and export is particularly difficult in these dynamic habitats due to complex and competing processes across time and space. Despite the extreme heterogeneity within wetlands, large-scale datasets serve an essential in developing C and greenhouse gas monitoring approaches for coastal wetlands. These include at least 3 major types of data: 1) synoptic and historic imagery through remote sensing, 2) national scale inventories of soil, water levels and land use categorization, and 3) community-initiated databases on field-specific structure and processes to validate models. Integration of these data using both a GIS-model and a process-based model are currently being tested for the continental U.S. within the framework of developing a C monitoring approach for changes in C stocks for coastal “blue carbon" pools, applicable at annual timesteps from 10 to 50 to 100 years. The goal of the framework is to determine the relative value of each dataset in reducing uncertainty in C accounting for tidal wetlands at a national, regional, and project scales. More information can be found at the website: http://water.usgs.gov/nrp/blue-carbon/nasa-blue-cms/
At least 3 primary findings can be reported for this ongoing project. One, of the 2.74 million hectares of inter-tidal wetlands documented – from freshwater to saline, and from emergent (e.g. marsh) to forested habitats – NOAA’s C-CAP documents only 2% loss of tidal wetland habitat from 1996-2010, 94% of which occurred in coastal Louisiana as loss to open water habitats. Two, USDA’s soil mapping products (e.g. SSURGO) coupled with NOAA long-term tide gauge records of sea level rise provide a mechanism to constrain regional C accretion rates, but within-wetland variability is often greater than between-wetland variability. Three, a growing database (>1500 spatially-explicit datapoints on soil carbon profiles, elevation change, vegetation biomass, etc) from the field-science community has generated ranges and relationships that can be used to refine remotely-sensed and modeled estimates of changes in C stocks through time. We suggest that key variables for IPCC-relevant C accounting – such as elevation, tidal restrictions, and intermediate salinities – may be identified through novel remote-sensing techniques and targeted gap-filling field measurements on soil C accretion, vegetation stocks, and methane emissions.