Soil temperature regime (STR) is important for soil classification and land use.  Generally, STR is delineated by estimating the mean annual soil temperature at a depth of 50 cm (MAST50) according to the Chinese Soil Taxonomy (CST).  However, delineating the STR of China remains a challenge due to the difficulties in accurately estimating MAST50.  The objectives of this study were to explore environmental factors that influence the spatial variation of MAST50 and generate an STR map for China.  Soil temperature measurements at 40 and 80 cm depth were collected from 386 National Meteorological Stations in China during 1971–2000.  The MAST50 was calculated as the average mean annual soil temperature (MAST) from 1971–2000 between 40 and 80 cm depths.  In addition, 2 048 mean annual air temperature (MAAT) measurements from 1971 to 2000 were collected from the National Meteorological Stations across China.  A zonal pedotransfer function (PTF) was developed based on the ensemble linear regression kriging model to predict the MAST50 in three topographic steps of China.  The results showed that MAAT was the most important variable related to the variation of MAST50.  The zonal PTF was evaluated with a 10% validation dataset with a mean absolute error (MAE) of 0.66°C and root mean square error (RMSE) of 0.78°C, which were smaller than the unified model with MAE of 0.83°C and RMSE of 0.96°C, respectively.  This study demonstrated that the zonal PTF helped improve the accuracy of the predicted MAST50 map.  Based on the prediction results, an STR map across China was generated to provide a consistent scientific base for the improvement and application of CST and land use support.

Crop modelling can facilitate researchers’ ability to understand and interpret experimental results, and to diagnose yield gaps. In this paper, the Decision Support Systems for Agrotechnology Transfer 4.6 (DSSAT) model together with the CENTURT soil model were employed to investigate the effect of low nitrogen (N) input on wheat (Triticum aestivum L.) yield, grain N concentration and soil organic carbon (SOC) in a long-term experiment (19 years) under a wheat-maize (Zea mays L.) rotation at Changping, Beijing, China.  There were two treatments including N0 (no N application) and N150 (150 kg N ha^–1) before wheat and maize planting, with phosphorus (P) and potassium (K) basal fertilizers applied as 75 kg P₂O₅ ha^–1 and 37.5 kg K₂O ha^–1, respectively.  The DSSAT-CENTURY model was able to satisfactorily simulate measured wheat grain yield and grain N concentration at N0, but could not simulate these parameters at N150, or SOC in either N treatment.  Model simulation and field measurement showed that N application (N150) increased wheat yield compared to no N application (N0).  The results indicated that inorganic fertilizer application at the rates used did not maintain crop yield and SOC levels.  It is suggested that if the DSSAT is calibrated carefully, it can be a useful tool for assessing and predicting wheat yield, grain N concentration, and SOC trends under wheat-maize cropping systems.

    Reliable prediction of soil organic carbon (SOC) density and carbon sequestration potential (CSP) plays an important role in the atmospheric carbon dioxide budget. This study evaluated temporal and spatial variation of topsoil SOC density and CSP of 21 soil groups across Hebei Province, China, using data collected during the second national soil survey in the 1980s and during the recent soil inventory in 2010. The CSP can be estimated by the method that the saturated SOC content subtracts the actual SOC associated with clay and silt. Overall, the SOC density and CSP of most soil groups increased from the 1980s to 2010 and varied between different soil groups. Among all soil groups, Haplic phaeozems had the highest SOC density and Endogleyic solonchaks had the largest CSP. Areas of soil groups with the highest SOC density (90 to 120 t C ha^–1) and carbon sequestration (120 to 160 t C ha^–1carbon sequestration, SOC density, spatial variation, topsoil
) also increased over time. With regard to spatial distribution, the north of the province had higher SOC density but lower CSP than the south. With respect to land-use type, cultivated soils had lower SOC density but higher CSP than uncultivated soils. In addition, SOC density and CSP were influenced by soil physicochemical properties, climate and terrain and were most strongly correlated with soil humic acid concentration. The results suggest that soil groups (uncultivated soils) of higher SOC density have greater risk of carbon dioxide emission and that management should be aimed at maximizing carbon sequestration in soil groups (cultivated soils) with greater CSP. Furthermore, soils should be managed according to their spatial distributions of SOC density and carbon sequestration potential under different soil groups.