Predictors for digital mapping of forest soil organic carbon stocks in different types of landscape

Forest soils have a high potential to store carbon and thus mitigate climate change. The information on spatial distribution of soil organic (SOC) stocks is very important. This study aims analyse the importance environmental predictors for forest SOC stock prediction at regional national scale in Czech Republic. A big database data more than 7 000 sites was compiled from several surveys. were calculated content bulk density topsoil mineral layer 0-30 cm. Spatial models developed separately individual natural areas four subsets with different altitude range, using random method. strongly differs between regions altitudes. At lower altitudes, edaphic series classes are strong predictors, while higher altitudes related topography become depends pedodiversity level difference classes. contribution types as limited when one (mostly coniferous) type dominates. Better results can be obtained smaller, but consistent regions, like some areas.