Quantifying and mapping topsoil inorganic carbon concentrations and stocks: approaches tested in France
Marchant, B.P.; Villanneau, E.J.; Arrouays, D.; Saby, N.P.A.; Rawlins, B.G.. 2015 Quantifying and mapping topsoil inorganic carbon concentrations and stocks: approaches tested in France. Soil Use and Management, 31 (1). 29-38. 10.1111/sum.12158
Before downloading, please read NORA policies.Preview |
Text
Approaches_to_quantifying.pdf - Accepted Version Download (760kB) | Preview |
Abstract/Summary
Soils act as a sink or a source of atmospheric carbon, and great efforts are made to monitor soil organic carbon stocks, but soil inorganic carbon (SIC) stocks are not measured by many national- and continental-scale soil monitoring networks. Topsoil (0–30 cm) SIC concentrations were determined for > 2000 sites on a regular 16-km grid as part of the French, Réseau de Mesures de la Qualité des Sols (RMQS). We used design-based statistical methods to calculate unbiased estimates of the mean SIC concentration and total stocks across France. Model-based methods were used to determine the uncertainty of these estimates and to map the spatial distribution of these quantities. Observations of inorganic carbon were highly skewed and did not conform to standard statistical models. Data were normalized using a nonparametric transformation. The estimates and predictions of inorganic carbon are baselines against which the results of future phases of the network can be compared. We found that the total topsoil inorganic carbon stocks in France amount to 1070 ± 61 Tg, ca. one-third of the corresponding organic carbon stocks. Spatial distribution of SIC was strongly linked to the underlying geology. We tested the reliability of estimating SIC concentrations and stocks from the French Soil Test Database, which contains the results of 280 000 soil analyses requested by farmers between 1990 and 2004. A biased estimate of soil inorganic carbon concentrations resulted, presumably because soil samples were selected according to concerns of farmers rather than by a statistical design.
Item Type: | Publication - Article |
---|---|
Digital Object Identifier (DOI): | 10.1111/sum.12158 |
ISSN: | 02660032 |
Date made live: | 30 Mar 2015 15:00 +0 (UTC) |
URI: | https://nora.nerc.ac.uk/id/eprint/510510 |
Actions (login required)
View Item |
Document Downloads
Downloads for past 30 days
Downloads per month over past year