| Soil organic carbon (soil organic carbon, SOC) play an important role in conserving soil fertility, improve soil quality, and changing global climate. SOC stocks and carbon fixation is a global environmental problem which has been given wide attention. Paddy soil is hydroponic natural soil in the artificial aging process of the formation of a special man-made wetland soil, is a Chinese Soil Taxonomy. In a unique man-made hydroponics soil subclass, is internationally recognized as the soil with Chinese characteristics. According to the second national soil survey data, the Chinese water organic carbon content of cultivated soil is dry an average of 137% of cultivated land, paddy soil during the maturation hydroponics organic carbon accumulation is a common trend. In the agricultural soil carbon sequestration potential in paddy soil significantly higher share of the total. Therefore, accurately quantifying SOC stock and describing its spatial distribution in large regional-scale is considered essential to modeling the global carbon cycle and helpful to slow the pace of climate change.The precision of spatial characterization of soil attribute is commonly affected by the map scale. Spatial patterns of SOC can be captured by assigning soil attribute data to polygons of a digital soil map. However, the specific influences of map scale on SOC estimates remain unclear. And the interpolation method as another possible way of scale transfer from discrete sampling points to regional scale that needs to be considered when making decisions. In this study, effects of soil mapping scale on the estimates of SOC storage (to a depth of 100 cm) in taihu region were discussed based on 1107 soil profiles and soil maps with six scales ranging from 1:50,000 to 1:14,000,000. Moreover, universal kriging (UK), ordinary kriging (OK), pedological professional knowledge-based (PKB) method along with the auxiliary topographic factors extracted from geographic coordinates were applied to predict the spatial patterns of SOC density (to a depth of 100 cm) for changxing county.Digital soil map of different mapping scale had different influence on the estimation of SOC storage. And SOC density values of the main soil types had fundamental influences on the SOC storage estimates. From the point of view of soil region, the SOC stocks increased at first then fell at 1:1,000,000 soil map, then decreased as the map scale decreased.From the point of view of soil terrain, in different mapping scales, four soil area in the study area of paddy soil organic carbon storage in the order:polder soil region> alluvial plain soil region> Taihu lake plain soil region>Low mountain and hilly soil region.Estimates of SOC stock should consider not only the total SOC stock but also the SOC stock at different spatial locations; from this point of view, the 1:50,000 scale soil map has the most detailed spatial information of SOC among the five soil map scales considered in this study, and the PKB method can reflect the spatial variability of SOCD within a map unit to some degree.Therefore, the 1:50,000 soil map combined with the PKB method is probably the best one for SOC stock estimates in Taihu Lake region.The total SOC storage of the Taihu Lake region was mainly controlled by the hydromorphic paddy soil, the gleyed paddy soil, the degleyed paddy soil and the percolated paddy soil, for the SOC storage of these four paddy soil subtypes accounted for more than 83% of the total SOC storage under each mapping scale. The gleyed paddy soil and the hydromorphic paddy soil had the greatest influence on different mapping scale and their SOC storage under the 1:14,000,000 mapping scale was apparently higher than any other scale. Such influence of soil map scale on estimation of SOC stocks in taihu region is resulted mainly from the map generalization process.After three methods were applied to predict the spatial patterns of SOC density (to a depth of 100 cm), the results showed that mean absolute error (MAE) and root mean square error (RMSE), is the smallest and 87% of the total variation can be explained by PKB method, it is the best one for predicting the spatial patterns of SOC density in taihu region.The OK method resulted in a lower MAE, RMSE and a wider range of SOC density compared with UK method. Moreover, the SOC density map can reflect not only the differences between the peaks and river valleys, but also the variations among different land use types. |
