Spatio-Temporal Simulation of the Field-Scale Evolution of Organic Carbon over the Landscape

and biological condition of soil (Oades, 1993; Stevenson, 1994). To maintain SOC in agricultural fields, we need The spatial or temporal variability of soil has been extensively to consider its local and global evolution. With respect considered in the literature using either experimental or modeling approaches. However, only a few studies integrate both spatial and to the latter, global warming and the potential release temporal dimensions. The aim of this paper is to present a method or sequestration of C into or from the atmosphere must for field-scale simulations of the spatio-temporal evolution of topsoil be considered. Intermediate spatial scales such as variaorganic C (OC) at the landscape scale over a few decades and under tions along slopes are also important as they contribute different management strategies. A virtual landscape with characteristo soil diversity, which impacts biodiversity (Ibáñez et tics matching part of Brittany (France) was considered for the study. al., 1995). Stochastic simulations and regression analysis were used to simulate The spatial or temporal variability of soil organic matspatial fields with known spatial structures: short-range, mediumrange, and long-range variability. These were then combined using an ter has been extensively considered by experimental or additive model of regionalization. Agricultural land use was simulated modeling approaches (Balabane and Balesdent, 1995; considering four different land uses: permanent pasture, temporary Bernoux et al., 1998; Smith et al., 1997; Six et al., 1999; pasture, annual cereal crops, and maize (Zea mays L.). Land use Collins et al., 2000; Arrouays et al., 2001), but only few evolution over time was simulated using transition matrices. Evolution studies integrate both spatial and temporal dimensions of soil organic matter was estimated each year for each pixel through (Jolivet et al., 1997; Papritz and Webster, 1995). The a rudimentary balance model that accounts for land use and the ones that do, neglect shortand medium-range spatial influence of soil waterlogging on mineralization rates. This spatiotemporal simulation approach at the landscape level allowed the simuvariability and consider only mean values (Smith et al., lation of several scales of soil variability including within-field variabil1997; Nieder and Richter, 2000). Thus the impact of ity. Spatial variability decreased drastically over time when only the management strategies on soil, at both the field and influence of land use was considered. This effect on soil variability landscape scales, cannot be adequately evaluated. Furover the landscape may have implications for site-specific soil managethermore, the design of soil monitoring networks cannot ment and precision agriculture. The presence of redoximorphic condibe tested a priori for their ability to detect the evolution tions was found to maintain soil spatial variability. of selected soil properties in a given region (Mol et