Assessing and mapping topsoil organic carbon stock at regional scale: A scorpan kriging approach conditional on soil map delineations and land use

In order to assess the potential of soils as C reservoir at regional scale, accurate estimates of soil organic carbon (SOC) are required, and different approaches can be used. This study presents a method to assess and map topsoil organic carbon stock (Mg ha−1) at regional scale for the whole Emilia Romagna plain in Northern Italy (about 12 000 km2). A Scorpan Kriging approach is proposed, which combines the trend component of soil properties as derived from the 1:50 000 soil map with geostatistical modeling of the stochastic, locally varying but spatially correlated component. The trend component is described in terms of varying local means, calculated taking into account soil type and dominant land use. The resulting values of SOC, sand, silt, and clay contents are retained for calculating topsoil SOC stocks, using a set of locally calibrated pedotransfer functions (PTFs) to estimate bulk density. The maps of each soil attribute are validated over a subset of 2000 independent and randomly selected observations. As compared to the standard approach based on the mean values for delineation, results show lower standard errors for all the variables used for SOC stock assessment, with a relative improvement (RI) ranging from 4 per cent for SOC per cent to 24 per cent for silt. The total C stock (0–30 cm) in the study area is assessed as 73·24 ± 6·67 M t, with an average stock of 62·30 ± 5·55 Mg ha−1. The SOC stock estimates are used to infer possible SOC stock changes in terms of carbon sequestration potential and potential carbon loss (PCL). Copyright © 2010 John Wiley & Sons, Ltd.

[1]  C. Calzolari,et al.  Quantifying spatial uncertainty of soil organic matter content using conditional sequential simulations: A case study in Emilia Romagna Plain (Northern Italy) , 2005 .

[2]  L. M. Vleeshouwers,et al.  Carbon emission and sequestration by agricultural land use: a model study for Europe , 2002 .

[3]  Budiman Minasny,et al.  On digital soil mapping , 2003 .

[4]  R. Lark,et al.  Carbon losses from all soils across England and Wales 1978–2003 , 2005, Nature.

[5]  R. Lal,et al.  Carbon emission from farm operations. , 2004, Environment international.

[6]  R. Lal Soil carbon sequestration to mitigate climate change , 2004 .

[7]  J. Rodríguez-Murillo Organic carbon content under different types of land use and soil in peninsular Spain , 2001, Biology and Fertility of Soils.

[8]  Y. Pachepsky,et al.  Effect of soil organic carbon on soil water retention , 2003 .

[9]  Pete Smith,et al.  Carbon losses from soil and its consequences for land-use management. , 2007, The Science of the total environment.

[10]  B. Minasny,et al.  Spatial prediction of soil properties using EBLUP with the Matérn covariance function , 2007 .

[11]  Pete Smith,et al.  Carbon sequestration in the agricultural soils of Europe , 2004 .

[12]  J. Deckers,et al.  World Reference Base for Soil Resources , 1998 .

[13]  Frank Canters,et al.  A multiple regression approach to assess the spatial distribution of Soil Organic Carbon (SOC) at the regional scale (Flanders, Belgium) , 2008 .

[14]  Y. Pachepsky,et al.  Use of soil penetration resistance and group method of data handling to improve soil water retention estimates , 1998 .

[15]  Mark Rounsevell,et al.  Carbon sequestration potential in European croplands has been overestimated , 2005, Global change biology.

[16]  J. Hammersley,et al.  Monte Carlo Methods , 1965 .

[17]  M. Meirvenne,et al.  Predictive Quality of Pedotransfer Functions for Estimating Bulk Density of Forest Soils , 2005 .

[18]  J. Fuhrer,et al.  Carbon stocks in Swiss agricultural soils predicted by land-use, soil characteristics, and altitude , 2005 .

[19]  Larry Boersma,et al.  A unifying quantitative analysis of soil texture: Improvement of precision and extension of scale , 1988 .

[20]  Xavier Emery Ordinary multigaussian kriging for mapping conditional probabilities of soil properties , 2006 .

[21]  J. J. Stoorvogel,et al.  A functional approach to soil characterization in support of precision agriculture , 2000 .

[22]  Dominique Arrouays,et al.  The carbon content of topsoil and its geographical distribution in France , 2001 .

[23]  Pete Smith,et al.  Climate change cannot be entirely responsible for soil carbon loss observed in England and Wales, 1978–2003 , 2007 .

[24]  Roland Hiederer,et al.  THE MAP OF ORGANIC CARBON IN TOPSOILS IN EUROPE , 2004 .

[25]  Andre G. Journel,et al.  The lognormal approach to predicting local distributions of selective mining unit grades , 1980 .

[26]  Rattan Lal,et al.  Relationships between surface soil organic carbon pool and site variables , 2004 .

[27]  Rattan Lal,et al.  Land Use, Land-Use Change and Forestry , 2015 .

[28]  Timothy C. Coburn,et al.  Geostatistics for Natural Resources Evaluation , 2000, Technometrics.

[29]  Walter J. Rawls,et al.  Accuracy and reliability of pedotransfer functions as affected by grouping soils , 1999 .

[30]  Reuven Y. Rubinstein,et al.  Simulation and the Monte Carlo Method , 1981 .