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© The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Uhran, B., Windham-Myers, L., Bliss, N., Nahlik, A. M., Sundquist, E., & Stagg, C. L. Improved wetland soil organic carbon stocks of the conterminous U.S. through data harmonization. Frontiers in Soil Science, 1, (2021): 706701, https://doi.org/10.3389/fsoil.2021.706701., Wetland soil stocks are important global repositories of carbon (C) but are difficult to quantify and model due to varying sampling protocols, and geomorphic/spatio-temporal discontinuity. Merging scales of soil-survey spatial extents with wetland-specific point-based data offers an explicit, empirical and updatable improvement for regional and continental scale soil C stock assessments. Agency-collected and community-contributed soil datasets were compared for representativeness and bias, with the goal of producing a harmonized national map of wetland soil C stocks with error quantification for wetland areas of the conterminous United States (CONUS) identified by the USGS National Landcover Change Dataset. This allowed an empirical predictive model of SOC density to be applied across the entire CONUS using relational %OC distribution alone. A broken-stick quantile-regression model identified %OC with its relatively high analytical confidence as a key predictor of SOC density in soil segments; soils <6% OC (hereafter, mineral wetland soils, 85% of the dataset) had a strong linear relationship of %OC to SOC density (RMSE = 0.0059, ~4% mean RMSE) and soils >6% OC (organic wetland soils, 15% of the dataset) had virtually no predictive relationship of %OC to SOC density (RMSE = 0.0348 g C cm−3, ~56% mean RMSE). Disaggregation by vegetation type or region did not alter the breakpoint significantly (6% OC) and did not improve model accuracies for inland and tidal wetlands. Similarly, SOC stocks in tidal wetlands were related to %OC, but without a mappable product for disaggregation to improve accuracy by soil class, region or depth. Our layered harmonized CONUS wetland soil maps revised wetland SOC stock estimates downward by 24% (9.5 vs. 12.5Pg C) with the overestimation being entirely an issue of inland organic wetland soils (35% lower than SSURGO-derived SOC stocks). Further, SSURGO underestimated soil carbon stocks at depth, as modeled wetland SOC stocks for organic-r, This project was funded through the U.S. Geological Survey's Land Carbon Program and a grant to ES through the U.S. Geological Survey's Community for Data Integration Program for generating cross-agency assessments.

© The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Uhran, B., Windham-Myers, L., Bliss, N., Nahlik, A. M., Sundquist, E., & Stagg, C. L. Improved wetland soil organic carbon stocks of the conterminous U.S. through data harmonization. Frontiers in Soil Science, 1, (2021): 706701, https://doi.org/10.3389/fsoil.2021.706701., Wetland soil stocks are important global repositories of carbon (C) but are difficult to quantify and model due to varying sampling protocols, and geomorphic/spatio-temporal discontinuity. Merging scales of soil-survey spatial extents with wetland-specific point-based data offers an explicit, empirical and updatable improvement for regional and continental scale soil C stock assessments. Agency-collected and community-contributed soil datasets were compared for representativeness and bias, with the goal of producing a harmonized national map of wetland soil C stocks with error quantification for wetland areas of the conterminous United States (CONUS) identified by the USGS National Landcover Change Dataset. This allowed an empirical predictive model of SOC density to be applied across the entire CONUS using relational %OC distribution alone. A broken-stick quantile-regression model identified %OC with its relatively high analytical confidence as a key predictor of SOC density in soil segments; soils <6% OC (hereafter, mineral wetland soils, 85% of the dataset) had a strong linear relationship of %OC to SOC density (RMSE = 0.0059, ~4% mean RMSE) and soils >6% OC (organic wetland soils, 15% of the dataset) had virtually no predictive relationship of %OC to SOC density (RMSE = 0.0348 g C cm−3, ~56% mean RMSE). Disaggregation by vegetation type or region did not alter the breakpoint significantly (6% OC) and did not improve model accuracies for inland and tidal wetlands. Similarly, SOC stocks in tidal wetlands were related to %OC, but without a mappable product for disaggregation to improve accuracy by soil class, region or depth. Our layered harmonized CONUS wetland soil maps revised wetland SOC stock estimates downward by 24% (9.5 vs. 12.5Pg C) with the overestimation being entirely an issue of inland organic wetland soils (35% lower than SSURGO-derived SOC stocks). Further, SSURGO underestimated soil carbon stocks at depth, as modeled wetland SOC stocks for organic-r, This project was funded through the U.S. Geological Survey's Land Carbon Program and a grant to ES through the U.S. Geological Survey's Community for Data Integration Program for generating cross-agency assessments.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.

Tidal wetlands produce long-term soil organic carbon (C) stocks. Thus for carbon accounting purposes, we need accurate and precise information on the magnitude and spatial distribution of those stocks. We assembled and analyzed an unprecedented soil core dataset, and tested three strategies for mapping carbon stocks: applying the average value from the synthesis to mapped tidal wetlands, applying models fit using empirical data and applied using soil, vegetation and salinity maps, and relying on independently generated soil carbon maps. Soil carbon stocks were far lower on average and varied less spatially and with depth than stocks calculated from available soils maps. Further, variation in carbon density was not well-predicted based on climate, salinity, vegetation, or soil classes. Instead, the assembled dataset showed that carbon density across the conterminous united states (CONUS) was normally distributed, with a predictable range of observations. We identified the simplest strategy, applying mean carbon density (27.0 kg C m-3), as the best performing strategy, and conservatively estimated that the top meter of CONUS tidal wetland soil contains 0.72 petagrams C. This strategy could provide standardization in CONUS tidal carbon accounting until such a time as modeling and mapping advancements can quantitatively improve accuracy and precision.

© The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Scientific Reports 8 (2018): 15219, doi:10.1038/s41598-018-33283-4., This Article corrects an error in Equation 1

© The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Scientific Reports 8 (2018): 9478, doi:10.1038/s41598-018-26948-7., Tidal wetlands produce long-term soil organic carbon (C) stocks. Thus for carbon accounting purposes, we need accurate and precise information on the magnitude and spatial distribution of those stocks. We assembled and analyzed an unprecedented soil core dataset, and tested three strategies for mapping carbon stocks: applying the average value from the synthesis to mapped tidal wetlands, applying models fit using empirical data and applied using soil, vegetation and salinity maps, and relying on independently generated soil carbon maps. Soil carbon stocks were far lower on average and varied less spatially and with depth than stocks calculated from available soils maps. Further, variation in carbon density was not well-predicted based on climate, salinity, vegetation, or soil classes. Instead, the assembled dataset showed that carbon density across the conterminous united states (CONUS) was normally distributed, with a predictable range of observations. We identified the simplest strategy, applying mean carbon density (27.0 kg C m−3), as the best performing strategy, and conservatively estimated that the top meter of CONUS tidal wetland soil contains 0.72 petagrams C. This strategy could provide standardization in CONUS tidal carbon accounting until such a time as modeling and mapping advancements can quantitatively improve accuracy and precision., Synthesis efforts were funded by NASA Carbon Monitoring System (CMS; NNH14AY67I), USGS LandCarbon and the Smithsonian Institution. J.R.H. was additionally supported by the NSF-funded Coastal Carbon Research Coordination Network while completing this manuscript (DEB-1655622). J.M.S. coring efforts were funded by NSF (EAR-1204079). B.P.H. coring efforts were funded by Earth Observatory (Publication Number 197).

© The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Scientific Reports 8 (2018): 15219, doi:10.1038/s41598-018-33283-4., This Article corrects an error in Equation 1

© The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Scientific Reports 8 (2018): 9478, doi:10.1038/s41598-018-26948-7., Tidal wetlands produce long-term soil organic carbon (C) stocks. Thus for carbon accounting purposes, we need accurate and precise information on the magnitude and spatial distribution of those stocks. We assembled and analyzed an unprecedented soil core dataset, and tested three strategies for mapping carbon stocks: applying the average value from the synthesis to mapped tidal wetlands, applying models fit using empirical data and applied using soil, vegetation and salinity maps, and relying on independently generated soil carbon maps. Soil carbon stocks were far lower on average and varied less spatially and with depth than stocks calculated from available soils maps. Further, variation in carbon density was not well-predicted based on climate, salinity, vegetation, or soil classes. Instead, the assembled dataset showed that carbon density across the conterminous united states (CONUS) was normally distributed, with a predictable range of observations. We identified the simplest strategy, applying mean carbon density (27.0 kg C m−3), as the best performing strategy, and conservatively estimated that the top meter of CONUS tidal wetland soil contains 0.72 petagrams C. This strategy could provide standardization in CONUS tidal carbon accounting until such a time as modeling and mapping advancements can quantitatively improve accuracy and precision., Synthesis efforts were funded by NASA Carbon Monitoring System (CMS; NNH14AY67I), USGS LandCarbon and the Smithsonian Institution. J.R.H. was additionally supported by the NSF-funded Coastal Carbon Research Coordination Network while completing this manuscript (DEB-1655622). J.M.S. coring efforts were funded by NSF (EAR-1204079). B.P.H. coring efforts were funded by Earth Observatory (Publication Number 197).

Tidal wetlands produce long-term soil organic carbon (C) stocks. Thus for carbon accounting purposes, we need accurate and precise information on the magnitude and spatial distribution of those stocks. We assembled and analyzed an unprecedented soil core dataset, and tested three strategies for mapping carbon stocks: applying the average value from the synthesis to mapped tidal wetlands, applying models fit using empirical data and applied using soil, vegetation and salinity maps, and relying on independently generated soil carbon maps. Soil carbon stocks were far lower on average and varied less spatially and with depth than stocks calculated from available soils maps. Further, variation in carbon density was not well-predicted based on climate, salinity, vegetation, or soil classes. Instead, the assembled dataset showed that carbon density across the conterminous united states (CONUS) was normally distributed, with a predictable range of observations. We identified the simplest strategy, applying mean carbon density (27.0 kg C m-3), as the best performing strategy, and conservatively estimated that the top meter of CONUS tidal wetland soil contains 0.72 petagrams C. This strategy could provide standardization in CONUS tidal carbon accounting until such a time as modeling and mapping advancements can quantitatively improve accuracy and precision.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.

Land–atmosphere interactions play a critical role in the Earth system, and a better understanding of these interactions could improve weather and climate models. The interaction among drought, vegetation productivity, and land cover is of particular significance. In a semiarid environment, such as the U.S. Great Plains, droughts can have a large influence on the productivity of agriculture and grasslands, with serious environmental and economic impacts. Here, we used the vegetation drought response index (VegDRI) drought indicator to investigate the response of vegetation to weather and climate for landcover types in the Great Plains in the United States from 1989 to 2012. We found that analysis that focused on land-cover types within ecoregion divisions provided substantially more and land-cover-based detail on the timing and intensity of drought than did summarizing across the entire Great Plains region. In the northern Great Plains, VegDRI measured more frequent drought impacts on vegetation in the western ecoregions than in the eastern ecoregions. Across the ecoregions of the Great Plains, drought impacts on vegetation were more commonly found in grassland than in cropland. For example, in the ‘‘Northwestern Great Plains’’ ecoregion (which encompasses areas of Montana, Wyoming, North Dakota, South Dakota, and Nebraska), grassland and nonirrigated cropland were observed in VegDRI to have historical fractional drought coverages in the growing season of 17% and 11%, respectively.

This paper is not subject to U.S. copyright. The definitive version was published in Applied Geochemistry 26 (2011): S259, doi:10.1016/j.apgeochem.2011.03.118., The documented history of US soil and water management provides a unique opportunity to examine soil and sediment C storage under conditions of changing management practices. Historical acceleration of erosion due to cultivation has been moderated by improved soil management. Increased construction of dams and locks has expanded areas of aquatic sedimentation in reservoirs and ponds. Enhanced historical sediment deposition rates have been documented in lakes and estuaries. All of these changes have an impact on terrestrial C storage and turnover. The present-day C budget associated with erosion and burial cannot be determined without quantifying the time-dependent changes due to past and present soil and water management.

This paper is not subject to U.S. copyright. The definitive version was published in Applied Geochemistry 26 (2011): S259, doi:10.1016/j.apgeochem.2011.03.118., The documented history of US soil and water management provides a unique opportunity to examine soil and sediment C storage under conditions of changing management practices. Historical acceleration of erosion due to cultivation has been moderated by improved soil management. Increased construction of dams and locks has expanded areas of aquatic sedimentation in reservoirs and ponds. Enhanced historical sediment deposition rates have been documented in lakes and estuaries. All of these changes have an impact on terrestrial C storage and turnover. The present-day C budget associated with erosion and burial cannot be determined without quantifying the time-dependent changes due to past and present soil and water management.