Identifying the scale-controlling factors of soil organic carbon in the cropland of Jilin Province, China

Abstract

Soil organic carbon (SOC) is the largest and most important terrestrial carbon pool, and it can influence global environmental management and food security. However, the spatial variability of SOC in cultivated areas and the relative controlling factors that drive the variations across different spatial scales are still not clear. On the basis of 2745 soil samples collected during 2006–2011, the spatial variability of SOC was first obtained from all of Jilin Province. Then, five categories of predictors, including climate, topography, soil, vegetation, and management practice, were selected to establish the environmental datasets at seven target scales (500 m, 1 km, 2.5 km, 5 km, 10 km, 25 km, and 50 km). Last, a machine learning method (random forest) was used to analyze the scale behaviors of these predictors on SOC variations. The results showed that the SOC content in Jilin Province had a moderate spatial dependence. Across all seven scales, elevation, precipitation, and temperature-related variables always had an important impact on SOC variation. Topography-related predictors had higher importance (relative importance (RI): 30.76%–44.20%) at the 1 km to 50 km scale, especially in the eastern humid mountainous ecoregion, while management practices had the largest importance (RI: 19%–29.20%) at the 500 m to 2.5 km scale in the central semihumid plain ecoregion. For the western semiarid plain, precipitation had higher importance (RI: 18.88%–23.68%) across all seven scales. Understanding the scale behaviors of environmental factors on SOC variations will be useful for improving soil health, food security and global environmental management.