Accuracy and precision of tidal wetland soil carbon mapping in the conterminous United States

James R. Holmquist, Lisamarie Windham-Myers, Norman Bliss, Stephen Crooks, James T. Morris, J. Patrick Megonigal, Tiffany Troxler, Donald Weller, John Callaway, Judith Drexler, Matthew C. Ferner, Meagan E. Gonneea, Kevin D. Kroeger, Lisa Schile-Beers, Isa Woo, Kevin Buffington, Joshua Breithaupt, Brandon M. Boyd, Lauren N. Brown, Nicole DixLyndie Hice, Benjamin P. Horton, Glen M. Macdonald, Ryan P. Moyer, William Reay, Timothy Shaw, Erik Smith, Joseph M. Smoak, Christopher Sommerfield, Karen Thorne, David Velinsky, Elizabeth Watson, Kristin Wilson Grimes, Mark Woodrey

Research output: Contribution to journalArticlepeer-review

91 Scopus citations


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.

Original languageEnglish (US)
Article number9478
JournalScientific reports
StatePublished - 2018

All Science Journal Classification (ASJC) codes

  • General


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