Explaining and mapping total phosphorus content in French topsoils

• Published in: Soil use and management Vol. 31; no. 2; pp. 259 - 269
• Main Authors: Delmas, M, Saby, N, Arrouays, D, Dupas, R, Lemercier, B, Pellerin, S, Gascuel‐Odoux, C, Withers, Paul
• Format: Journal Article
• Language: English
• Published: Bedfordshire Published for the British Society of Soil Science by Blackwell Scientific Publications 01.06.2015; Blackwell Publishing Ltd; Wiley Subscription Services, Inc; Wiley
• Subjects: agricultural soils; aluminum; aquatic ecosystems; calcium; carbon; clay fraction; controlling factors; crop production; data collection; iron; Life Sciences; linear models; Mapping; Materials selection; Mathematical models; monitoring; multiple linear regression model; nitrogen content; Origins; Phosphorus; regression analysis; Scale (ratio); Soil (material); soil sampling; spatial analysis; surface water; Topsoil; Total phosphorus; watersheds; France; mapping; total phosphorus; spatial analysis; multiple linear regression model; controlling factors
• ISSN: 0266-0032; 1475-2743
• DOI: 10.1111/sum.12192

Total phosphorus (TP) build‐up in agricultural soils represents both a threat to aquatic ecosystems and a valuable resource for future crop production, given the context of increasing food demand combined with the rapid depletion of the world's phosphate reserves. Therefore, it is crucially important (i) to identify the main factors controlling topsoil TP and (ii) to develop methods for mapping its spatial distribution. Multiple linear regression models were used with two distinct approaches to calculate TP and covariates linked to the P cycle. Firstly, covariates were selected from the Réseau de Mesures de la Qualité des Sols database, the French soil monitoring network, which consists of soil samples collected from 2158 sites on a 16‐km regular grid. Secondly, covariates were selected to map TP from spatially exhaustive datasets in France. The first approach explains 80% of variability in topsoil TP. The variables selected are linked to the autochthonous origin of P (parent material), to allochthonous origin (organic carbon and nitrogen contents) and to the retention capacity of soil (Al, Fe, Ca and clay contents). The predicted map obtained from the second approach provides a mean TP of 0.76 g/kg. This study demonstrates that creating national scale maps of TP, based on detailed soil sampling and many variables, is feasible and can be used to model the P cycle and P transfer processes. Such maps can be used in P erosion and transfer models over river basins, and therefore to predict P exports to surface waters.