Abstract
Phosphorus (P) availability in soils limits crop yields in many regions of the World, while excess of soil P triggers aquatic eutrophication in other regions. Numerous processes drive the global spatial distribution of P in agricultural soils, but their relative roles remain unclear. Here, we combined several global data sets describing these drivers with a soil P dynamics model to simulate the distribution of P in agricultural soils and to assess the contributions of the different drivers at the global scale. We analysed both the labile inorganic P (PILAB), a proxy of the pool involved in plant nutrition and the total soil P (PTOT). We found that the soil biogeochemical background corresponding to P inherited from natural soils at the conversion to agriculture (BIOG) and farming practices (FARM) were the main drivers of the spatial variability in cropland soil P content but that their contribution varied between PTOT vs. PILAB. When the spatial variability was computed between grid cells at half-degree resolution, we found that almost all of the PTOT spatial variability could be explained by BIOG, while BIOG and FARM explained 38% and 63% of PILAB spatial variability, respectively. Our work also showed that the driver contribution was sensitive to the spatial scale characterizing the variability (grid cell vs. continent) and to the region of interest (global vs. tropics for instance). In particular, the heterogeneity of farming practices between continents was large enough to make FARM contribute to the variability in PTOT at that scale. We thus demonstrated how the different drivers were combined to explain the global distribution of agricultural soil P. Our study is also a promising approach to investigate the potential effect of P as a limiting factor for agroecosystems at the global scale.
Original language | English |
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Pages (from-to) | 3418-3432 |
Number of pages | 15 |
Journal | Global Change Biology |
Volume | 23 |
Issue number | 8 |
DOIs | |
State | Published - Aug 2017 |
Funding
This research was supported by the ‘Institut National de la Recherche Agronomique’ (INRA) and the Environnement et Agronomie (EA) division. We are grateful to Mark Irvine for help with the computing aspects. We thank Christophe Nguyen, Christian Morel, André Schneider, Pascal Denoroy, Alain Mollier, Benjamin Nowak, Corina Buendia, Axel Kleidon, Adrien Rusch and Noémie Schaller for helpful discussions about the phosphorus cycle, farming practices or statistics. Finally, we would like to thank Aldyth Nys for her assistance with the linguistic aspects of this paper. Modelling of the soil P dynamics model and analysis were performed in using Python (Python Software Foundation. Python Language Reference, version 2.7. Available at http://www.python.org). The authors declare no conflict of interest.
Funders | Funder number |
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Environnement et Agronomie | |
Institut National de la Recherche Agronomique |
Keywords
- agricultural soils
- biogeochemical cycles
- global scale
- modelling
- phosphorus