These datasets represent a revised national scale estimate of wetland soil carbon stock assessments by improving representation of soil organic carbon densities. This assessment is based on a three-step approach to harmonize survey and point-based data for predicting soil organic carbon density from percent organic carbon alone (or percent organic matter, with conversion), when reliable dry bulk density information is not available. Given issues with survey-level extrapolation of soil pedons into discontinuous hydric soils, quantile, segmented data analysis provides a more accurate spatially explicit soil organic carbon density product. These modeled data leverage spatial and statistical distributions of soil organic carbon percent data of the conterminous United States (CONUS) for two national-scale soil datasets: a wetland-specific field campaign, the EPA National Wetland Condition Assessment, and the USDA NRCS SSURGO survey. See https://doi.org/10.3389/fsoil.2021.706701 for details.

This dataset provides estimates of soil organic carbon (SOC) in tidal wetlands for the northeastern United States. The data cover the period 1998-2018. Northeastern U.S. tidal wetlands and bordering areas were harmonized from government agencies [U.S. Department of Agriculture - Natural Resources Conservation Service (USDA-NRCS), National Cooperative Soil Survey (NCSS), USDA-NRCS - Rapid Carbon Assessment (RaCA), U.S. Environmental Protection Agency - National Wetland Condition and Assessment (EPA-NWCA)] and published studies. Point data for carbon stocks (in kg m-2) at four soil depths (0-5, 0-30, 0-100, and 0-200 cm) are included. SOC for the four depths was predicted for eight regional zones using regression models driven by environmental covariates. Two methods were used to estimate parameters for these models, a Random Forest (RF) Ranger method and a Quantile Regression Forest (QRF) model. The distribution of SOC was predicted for tidal wetland cover types mapped by Correll et al. (2019). Predictions and uncertainties are available at a 3 m resolution.

Public data used for data harmonization. This dataset is associated with the following publication: Uhran, B., L. Windham-Myers, N. Bliss, A. Nahlik, E. Sundquist, and C. Stagg. Improved Wetland Soil Organic Carbon Stocks of the Conterminous U.S. Through Data Harmonization. Frontiers in Soil Science. Frontiers, Lausanne, SWITZERLAND, 1: 706701, (2021).

Public data used for data harmonization. This dataset is associated with the following publication: Uhran, B., L. Windham-Myers, N. Bliss, A. Nahlik, E. Sundquist, and C. Stagg. Improved Wetland Soil Organic Carbon Stocks of the Conterminous U.S. Through Data Harmonization. Frontiers in Soil Science. Frontiers, Lausanne, SWITZERLAND, 1: 706701, (2021).

This dataset provides modeled estimates of soil carbon stocks for tidal wetland areas of the Conterminous United States (CONUS) for the period 2006-2010. Wetland areas were determined using both 2006-2010 Coastal Change Analysis Program (C-CAP) raster maps and the National Wetlands Inventory (NWI) vector data. All 30 x 30-meter C-CAP pixels were extracted that are coded as estuarine emergent, scrub/shrub, or forested in either 2006 or 2010. A soil database for model fitting and validation was compiled from 49 different studies with spatially explicit empirical depth profile data and associated metadata, totaling 1,959 soil cores from 18 of the 22 coastal states. Reported estimates of carbon stocks were derived with modeling approaches that included (1) applying a single average carbon stock value from the compiled soil core data, (2) applying models fit using the empirical data and applied spatially using soil, vegetation and salinity maps, (3) relying on independently generated soil carbon maps from The United States Department of Agriculture (USDA)'s Soil Survey Geographic Database (SSURGO), and the NWI that intersected with mapped tidal wetlands, and (4) using a version of SSURGO bias-corrected for bulk density. Comparisons of uncertainty, precision, and accuracy among these four approaches are also provided.

NWCA 2011 Soil Chemistry Data. This dataset is associated with the following publication: Nahlik, A., and M.S. Fennessy. Carbon storage in US wetlands. Nature Communications. Nature Publishing Group, London, UK, 7: 1-9, (2016).

NWCA 2011 Soil Chemistry Data. This dataset is associated with the following publication: Nahlik, A., and M.S. Fennessy. Carbon storage in US wetlands. Nature Communications. Nature Publishing Group, London, UK, 7: 1-9, (2016).

This dataset provides estimates of carbon pools, fluxes, and associated uncertainties across the contiguous USA (CONUS) at 0.5-degree resolution for all terrestrial land cover types. Carbon pools include labile carbon, foliar carbon, fine root, woody carbon, litter carbon, and soil organic carbon. Carbon fluxes include gross primary production (GPP), net primary production (NPP), net biome exchange, autotrophic respiration, and heterotrophic respiration. The modeled estimates are provided as monthly averages over the 16-year period, 2001 through 2016. The data were derived from the CARbon DAta MOdel fraMework (CARDAMOM) that included climate data, and above and below ground biomass maps of CONUS for the years 2005, 2010, 2015 and 2016 as input data sources to this model-data fusion framework. The input data were integrated into the CARDAMOM model to constrain on the terrestrial carbon and to specifically attribute changes of forest carbon stocks and spatial distributions of carbon emissions and removals across forested lands. United States Forest Service's Forest Inventory and Analysis (FIA) plot data were used to train models for the prediction of forest above-ground biomass (AGB).

This data release presents data that were collected as part of a larger effort to assess the carbon balance of recently exposed (i.e., no vegetation cover) wetland sediments. This work was part of an international collaborative effort associated with the Dryflux II project. During June and July 2021, data were collected from three artificial ponds located near Jamestown, North Dakota, to estimate carbon dioxide flux, vegetation characteristics, and soil properties. Numerous covariates related to atmospheric and soil conditions also were measured. Water levels of the artificial ponds, which are managed by the U.S. Geological Survey Northern Prairie Wildlife Research Center, were manipulated to mimic the natural drying cycle of prairie wetlands. This management resulted in exposed sediments where samples were collected. Data from this collaborative study will be used to better understand the carbon balance of wetland soils associated with fluctuating wet and dry conditions, and to refine global estimates of carbon dioxide emissions from dry inland waters.

This data release presents data that were collected as part of a larger effort to assess the carbon balance of recently exposed (i.e., no vegetation cover) wetland sediments. This work was part of an international collaborative effort associated with the Dryflux II project. During June and July 2021, data were collected from three artificial ponds located near Jamestown, North Dakota, to estimate carbon dioxide flux, vegetation characteristics, and soil properties. Numerous covariates related to atmospheric and soil conditions also were measured. Water levels of the artificial ponds, which are managed by the U.S. Geological Survey Northern Prairie Wildlife Research Center, were manipulated to mimic the natural drying cycle of prairie wetlands. This management resulted in exposed sediments where samples were collected. Data from this collaborative study will be used to better understand the carbon balance of wetland soils associated with fluctuating wet and dry conditions, and to refine global estimates of carbon dioxide emissions from dry inland waters.