Ren‐Min Yang

There is a need for accurate estimate of soil organic carbon (SOC) stocks for understanding the role of alpine soils in the global carbon cycle. We tested a method for mapping digitally the continuous distribution of the SOC stock in three dimensions in the northeast of the Tibetan Plateau. The approach integrated the spatial distribution of the mattic epipedon which is a special surface horizon widespread and rich in organic matter in Tibetan grasslands. Prediction models resulted in high prediction accuracy. An average SOC stock in the mattic epipedon was estimated to be 4.99 kg m(-2) in a mean depth of 14 cm. The amounts of SOC in the mattic epipedon, the upper 30 cm and 50 cm accounted for about 21%, 80% and 89%, respectively, of the total SOC stock in the upper 1 m depth. Compared with previous estimates, our approach resulted in more reliable predictions. The mattic epipedon was proven to be an important factor for modelling the realistic distribution of the SOC stock in Tibetan grasslands. Vegetation-related covariates have the most important influence on the distribution of the mattic epipedon and the SOC stock in the alpine grassland soils of northeast Tibetan Plateau.

The evaluation of soil organic carbon (SOC) dynamics and its driving factors is important for developing sustainable soil C sequestration practices. A key challenge is the lack of a time series of spatially explicit SOC estimates; most previous SOC estimates are static. In this study, we applied a digital soil mapping framework to model the relationship between SOC and environmental factors based on a combined dataset of 4695 soil samples collected in China from the early 1980 s and during the 2000–2014 period. We predicted the annual SOC distribution at a depth of 0–100 cm at a 1 km resolution for China between 1982 and 2019. We mapped trends of SOC change and identified change hotspots. To obtain the pixel-level association between SOC change and environmental factors, we used a linear function to quantify the contribution of individual predictors to SOC change. The results show that the accuracy of SOC prediction is acceptable, with a mean R2 value of 0.58 for validation. SOC storage in China was estimated to range from 89.03 to 97.41 Pg C and showed a slight increase (slope = 0.024 Pg C/yr) from 1982 to 2019. Specifically, two distinct phases of SOC were identified as follows: (1) from 1982 to 2004, a considerable decline occurred, which was mainly driven by increased temperature; (2) from 2004 to 2019, SOC increased slowly, resulting from the contribution of greening to sustaining C sequestration in soils under warming conditions. Approximately 17 % of all areas have been characterized by a significant decrease in SOC since 1982, predominantly in central and western China. Environmental controls exhibited large spatial variation, where approximately 69 % of all areas were predominantly controlled by climate factors. For grasslands, the SOC losses in northern China were largely driven by temperature and precipitation, while the SOC losses were primarily attributed to decreased organic inputs driven by grassland degradation on the Tibetan Plateau. Policy-driven land use change has led to an increase in SOC in some cropland areas (e.g., northeast and east China). The implementation of ecological restoration has shown a positive influence on SOC sequestration. This study highlights the diverse spatial patterns and heterogeneity of SOC changes and their controls. Given this spatial differentiation, spatially explicit assessments of soil C dynamics are important for the formulation of regional soil-based mitigation strategies and guidance for effective restoration interventions based on geographic location.