Uncertainty in United States coastal wetland greenhouse gas inventorying

Abstract

Coastal wetlands store carbon dioxide (CO 2 ) and emit CO 2 and methane (CH 4 ) making them an important part of greenhouse gas (GHG) inventorying. In the contiguous United States (CONUS), a coastal wetland inventory was recently calculated by combining maps of wetland type and change with soil, biomass, and CH 4 flux data from a literature review. We assess uncertainty in this developing carbon monitoring system to quantify confidence in the inventory process itself and to prioritize future research. We provide a value-added analysis by defining types and scales of uncertainty for assumptions, burial and emissions datasets, and wetland maps, simulating 10 000 iterations of a simplified version of the inventory, and performing a sensitivity analysis. Coastal wetlands were likely a source of net-CO 2 -equivalent (CO 2 e) emissions from 2006-2011. Although stable estuarine wetlands were likely a CO 2 e sink, this effect was counteracted by catastrophic soil losses in the Gulf Coast, and CH 4 emissions from tidal freshwater wetlands. The direction and magnitude of total CONUS CO 2 e flux were most sensitive to uncertainty in emissions and burial data, and assumptions about how to calculate the inventory. Critical data uncertainties included CH 4 emissions for stable freshwater wetlands and carbon burial rates for all coastal wetlands. Critical assumptions included the average depth of soil affected by erosion events, the method used to convert CH 4 fluxes to CO 2 e, and the fraction of carbon lost to the atmosphere following an erosion event. The inventory was relatively insensitive to mapping uncertainties. Future versions could be improved by collecting additional data, especially the depth affected by loss events, and by better mapping salinity and inundation gradients relevant to key GHG fluxes. Social Media Abstract: US coastal wetlands were a recent and uncertain source of greenhouse gasses because of CH 4 and erosion.

Localized Scenarios and Latitudinal Patterns of Vertical and Lateral Resilience of Tidal Marshes to Sea‐Level Rise in the Contiguous United States

“…DEMs went through two transformations, from meters relative to current day NAVD88 to meters relative to MHHWS. We used a NAVD88 to MHHWS conversion layer used to determine the extent of 'coastal lands' for a U.S.-wide coastal wetland carbon inventory (Holmquist, Windham-Myers, Bernal, et al, 2018), and assumed an average 17.3 cm of positive elevation bias for wetland surfaces, introduced by dense vegetation interfering with Light Detection and Ranging penetration (Holmquist, Windham-Myers, Bernal, et al, 2018). The MHHWS line was also used to classify Palustrine Wetlands into finer tidal and non-tidal classifications using the elevation of MHHWS as a cutoff point, Palustrine wetlands below are classified as tidal, above MHHWSt=100 = NAVD88t=0 + MHHWSt=0 + SLR0:100 Eq.…”

Salt marsh ecosystem restructuring enhances elevation resilience and carbon storage during accelerating relative sea-level rise

“…Indeed, a recent review suggests that marsh vulnerability has been overstated and that many marshes continue to aggrade (Kirwan et al, 2016a). Both the loss of salt marsh area and the ecological shift to dominance of low marsh species across the marsh platform has raised the question of whether these societally important ecological systems will remain viable in the future and whether they will continue to serve as important carbon stores (Chmura, 2013;Crosby et al, 2016;Holmquist et al, 2018a). In an effort to answer these questions, numerous models have attempted to determine marsh plant response to relative sea-level rise, as well as the associated change in marsh platform accretion capacity (i.e.…”

Improved Wetland Soil Organic Carbon Stocks of the Conterminous U.S. Through Data Harmonization

“…Area and count distributions for assessing representation of data in NLCD-based extraction of SSURGO and NWCA data sets for all Inland values, for the Coastal Plains Region (CPL), for the Eastern Mountains and Upper Midwest Region (EMU), for the Interior Plains Region (IPL), and for The West Region (W). boundary of tidal hydrology (>1% probability of being below the Mean High High Water Spring Tide, MHHWS(33), available for download from the NASA Carbon Monitoring System at: https://daac.ornl.gov/CMS/guides/Uncertainty_US_ Coastal_GHG.html.…”