Spatial prediction of soil organic carbon from data on large and variable spatial supports. II. Mapping temporal change

Abstract

We calculate statistical predictions of changes in soil organic carbon (SOC), and attendant uncertainty from areal data across a region of France. The data consist of measurements of SOC from farms across the region collected in two time periods: 1995–1999, and 2000–2004. To protect the anonymity of farms that contributed, the data were summarised by commune; we were only able to use the average value, sample variance and number of observations from each commune. We consider how we can use data of this form to map temporal changes in SOC. We account for the dependence between data from the two surveys through a linear model of coregionalization. Cross‐validation shows that by using the linear model of coregionalization to model inter‐survey dependence, we obtain better estimates of SOC changes and better uncertainty assessments. We compare maps produced using the approaches showing the estimated SOC changes and probabilities of SOC decrease between the times of the two surveys. Copyright © 2012 John Wiley & Sons, Ltd.