Predicting spatiotemporal changes of surface soil organic carbon in China

Evaluating the spatiotemporal dynamics of soil organic carbon (SOC) is essential for better understanding the role of SOC in global C cycling. In this study, we report on the application of a two-compartment model for mapping and examining SOC changes in China. We develop a SOC change prediction model combined with an environmental stratification approach and map SOC changes for the top 20-cm soil depth in China at a grid resolution of 1 km. We perform a model comparison to quantify the effects of environmental stratification on model performance. A mean SOC increase of 0.63 kg m(-2) was observed over the past 40 yr. Compared to the model without environmental stratification (the concordance correlation coefficient [CCC]: 0.34-0.40; RMSE: 2.16-2.33 kg m(-2)), we found that the models incorporating spatial or temporal stratification provide better performance. Notably, the model with spatiotemporal stratification achieved the better performance compared with results without stratification, with the prediction accuracy improved up to 57% in terms of CCC. Our results suggest that both the spatial- and temporal-scale effects of environmental heterogeneity on SOC processes need to be accounted for in the prediction of SOC changes. Furthermore, the results indicate that the developed approach can be used to map SOC changes over large regions. This study also emphasizes that to achieve accurate predictions, it is necessary to choose the proper environmental stratification method to refine the study unit.