Preprints
https://doi.org/10.5194/bg-2023-22
https://doi.org/10.5194/bg-2023-22
24 Feb 2023
 | 24 Feb 2023
Status: a revised version of this preprint was accepted for the journal BG and is expected to appear here in due course.

Global patterns and drivers of phosphorus pools in natural soils

Xianjin He, Laurent Augusto, Daniel S. Goll, Bruno Ringeval, Ying-Ping Wang, Julian Helfenstein, Yuanyuan Huang, and Enqing Hou

Abstract. Most phosphorus (P) in soils is unavailable for direct biological uptake as it is locked within primary or secondary mineral particles, adsorbed to mineral surfaces, or immobilized inside of organic material. Deciphering the composition of different P pools in soil is critical for understanding P bioavailability and its underlying dynamics. However, widely used global estimates of different soil P pools are based on a dataset containing few measurements in which many regions or soil types are unrepresented. This poses a major source of uncertainty in assessments that rely on these estimates to quantify soil P constraints on biological activity controlling global food production and terrestrial carbon balance. To address this issue, we consolidated a database of six major soil P pools containing 1857 entries from globally distributed (semi-)natural soils and 11 related environmental variables. The P pools (labile inorganic P (Pi), labile organic P (Po), moderately labile Pi, moderately labile Po, primary mineral P, and occluded P) were measured using a sequential P fractionation method. Using the database, we trained random forest regression models for each of the P pools and captured observed variation with R2 higher than 60 %. We identified total soil P concentration as the most important predictor of all soil P pool concentrations, except for primary mineral P concentration, which is primarily controlled by soil pH. When expressed in relative concentrations (i.e., as a proportion of total P), the model showed that soil pH is the most important predictor for proportions of all soil P pools, except for labile Pi proportion, which is primarily controlled by soil depth. Using the trained random forest models, we predicted soil P pools’ distributions in natural systems at a resolution of 0.5° × 0.5°. Our global maps of different P pools in soils as well as the pools’ underlying drivers can inform assessments of the role of natural P availability for ecosystem productivity, climate change mitigation, and the functioning of the Earth system.

Xianjin He et al.

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on bg-2023-22', Anonymous Referee #1, 07 Mar 2023
    • AC3: 'Reply on RC1', xianjin He, 22 May 2023
  • RC2: 'Comment on bg-2023-22', Anonymous Referee #2, 22 Apr 2023
    • AC1: 'Reply on RC2', xianjin He, 22 May 2023
  • RC3: 'Comment on bg-2023-22', Anonymous Referee #3, 23 Apr 2023
    • AC2: 'Reply on RC3', xianjin He, 22 May 2023

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on bg-2023-22', Anonymous Referee #1, 07 Mar 2023
    • AC3: 'Reply on RC1', xianjin He, 22 May 2023
  • RC2: 'Comment on bg-2023-22', Anonymous Referee #2, 22 Apr 2023
    • AC1: 'Reply on RC2', xianjin He, 22 May 2023
  • RC3: 'Comment on bg-2023-22', Anonymous Referee #3, 23 Apr 2023
    • AC2: 'Reply on RC3', xianjin He, 22 May 2023

Xianjin He et al.

Data sets

Global patterns and drivers of phosphorus pools in natural soils Xianjin He, Laurent Augusto, Daniel S. Goll, Bruno Ringeval, Ying-Ping Wang, Julian Helfenstein, Yuanyuan Huang, Enqing Hou https://doi.org/10.6084/m9.figshare.16988029

Xianjin He et al.

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Short summary
We identified total soil P as the most important predictor of all soil P pool concentrations, except for primary mineral P concentration, which is primarily controlled by soil pH. We found soil pH is the most important predictor for proportions of all soil P pools, except for labile Pi proportion, which is primarily controlled by soil depth. We predicted soil P pools’ distributions in natural systems at a resolution of 0.5° × 0.5°.
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