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

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

5 Citations (Scopus)

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.

Original languageEnglish
Article number17
JournalScientific Data
Volume11
Issue number1
DOIs
Publication statusPublished - 2 Jan 2024

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