4.8 Article

The age distribution of global soil carbon inferred from radiocarbon measurements

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NATURE GEOSCIENCE
卷 13, 期 8, 页码 555-+

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NATURE PORTFOLIO
DOI: 10.1038/s41561-020-0596-z

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  1. European Research Council [695101]
  2. US DOE Office of Science Biological and Environmental Research RUBISCO Science Focus Area
  3. NASA Earth and Space Science Fellowship
  4. [DE-SC0014374]
  5. European Research Council (ERC) [695101] Funding Source: European Research Council (ERC)

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Soils contain more carbon than the atmosphere and vegetation combined. An increased flow of carbon from the atmosphere into soil pools could help mitigate anthropogenic emissions of carbon dioxide and climate change. Yet we do not know how quickly soils might respond because the age distribution of soil carbon is uncertain. Here we used 789 radiocarbon ( increment C-14) profiles, along with other geospatial information, to create globally gridded datasets of mineral soil increment C-14 and mean age. We found that soil depth is a primary driver of increment C-14, whereas climate (for example, mean annual temperature) is a major control on the spatial pattern of increment C-14 in surface soil. Integrated to a depth of 1 m, global soil carbon has a mean age of 4,830 +/- 1,730 yr, with older carbon in deeper layers and permafrost regions. In contrast, vertically resolved land models simulate increment C-14 values that imply younger carbon ages and a more rapid carbon turnover. Our data-derived estimates of older mean soil carbon age suggest that soils will accumulate less carbon than predicted by current Earth system models over the twenty-first century. Reconciling these models with the global distribution of soil radiocarbon will require a better representation of the mechanisms that control carbon persistence in soils. Soils may accumulate less carbon and with a slower turnover than Earth system models predict, according to analysis of the age distribution of global soil carbon, which finds that the mean age of soil carbon is older than that in simulated in models.

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