Temporal and spatial changes in soil organic carbon and soil inorganic carbon stocks in the semi-arid area of northeast China

Soil organic carbon (SOC) and soil inorganic carbon (SIC) has important effects on soil physical, chemical and biological properties. They play an important role in coordinating the relationship between soil water and air, increasing soil water holding capacity and improving plant productivity. In this study, a boosted regression trees (BRT) model was developed to map the spatial distribution carbon stocks in the semi-arid region of Northeast China in 1990 and 2015. During the two periods, 10-fold cross-validation technology was used to test the performance and uncertainty of BRT model. In order to construct the model, 9 environmental variables (derived from climate, topography and biology) and 173 (1990) and 223 (2015) topsoil (0-30 cm) samples were used. The comparison between estimated and observed data shows that the RMSE of SOC and SIC stocks were 0.53 kgm(-2) and 0.19 kgm(-2) in 1990, and 0.65 kgm(-2) and 0.20 kgm(-2) in 2015, respectively. Elevation, normalized difference vegetation index, mean annual precipitation and Landsat band 3 were identifies as critical environmental factors for simulating the spatial distribution of SOC, accounting for 76.6 % and 70.3 % of the total relative importance in 1990 and 2015, respectively. Mean annual precipitation, mean annual temperature and topographic wetness index were the critical environmental factors for simulating the spatial variation of SIC during the two periods. Land use change also played an important role in the spatial variability of SOC and SIC stocks. In the past 25 years, soil carbon stocks decreased from 6.2 kg m(-2) in 1990 to 5.9 kg m(-2) in 2015. The spatial distribution pattern of SOC was high in northeastern area and low in southwestern area during the two periods, while the spatial distribution pattern of SIC was opposite to that of SOC stocks. The mapped soil carbon stock distribution is fundamental to future study of soil carbon cycle and regional carbon balance in semi-arid regions.

Automated summary

Soil organic carbon (SOC) and soil inorganic carbon (SIC) have significant effects on soil properties and plant productivity. A boosted regression trees (BRT) model was developed to map the carbon stocks in Northeast China's semi-arid region from 1990 to 2015. Environmental variables and soil samples were used to construct the model, and the comparison between estimated and observed data showed good performance. The spatial distribution pattern of SOC and SIC stocks and their changes over time were influenced by environmental factors and land use change.