Scientific Data (Jan 2024)

A global dataset on phosphorus in agricultural soils

  • Bruno Ringeval,
  • Josephine Demay,
  • Daniel S. Goll,
  • Xianjin He,
  • Ying-Ping Wang,
  • Enqing Hou,
  • Sarah Matej,
  • Karl-Heinz Erb,
  • Rong Wang,
  • Laurent Augusto,
  • Fei Lun,
  • Thomas Nesme,
  • Pasquale Borrelli,
  • Julian Helfenstein,
  • Richard W. McDowell,
  • Peter Pletnyakov,
  • Sylvain Pellerin

DOI
https://doi.org/10.1038/s41597-023-02751-6
Journal volume & issue
Vol. 11, no. 1
pp. 1 – 34

Abstract

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Abstract Numerous drivers such as farming practices, erosion, land-use change, and soil biogeochemical background, determine the global spatial distribution of phosphorus (P) in agricultural soils. Here, we revised an approach published earlier (called here GPASOIL-v0), in which several global datasets describing these drivers were combined with a process model for soil P dynamics to reconstruct the past and current distribution of P in cropland and grassland soils. The objective of the present update, called GPASOIL-v1, is to incorporate recent advances in process understanding about soil inorganic P dynamics, in datasets to describe the different drivers, and in regional soil P measurements for benchmarking. We trace the impact of the update on the reconstructed soil P. After the update we estimate a global averaged inorganic labile P of 187 kgP ha−1 for cropland and 91 kgP ha−1 for grassland in 2018 for the top 0–0.3 m soil layer, but these values are sensitive to the mineralization rates chosen for the organic P pools. Uncertainty in the driver estimates lead to coefficients of variation of 0.22 and 0.54 for cropland and grassland, respectively. This work makes the methods for simulating the agricultural soil P maps more transparent and reproducible than previous estimates, and increases the confidence in the new estimates, while the evaluation against regional dataset still suggests rooms for further improvement.