Mapping surface soil organic carbon in the coal–grain composite area: threshold and interaction effects of coal mining activities

Abstract

Background

In China, the coal–grain composite area accounts for more than 40% of the total cultivated land area, and its soil organic carbon (SOC) content profoundly impacts soil health and food security. However, underground coal mining causes surface subsidence, farmland degradation, and a decline in the SOC pool, severely threatening soil security and long-term crop productivity. Accurately mapping SOC in the coal–grain composite areas is crucial for assessing soil quality and estimating carbon emissions. However, existing studies rarely consider the adverse impacts of mining activities, and the threshold and interaction effects of environmental variables have not been thoroughly investigated. Using 294 samples collected in Peixian county, a typical coal–grain composite area, this study aimed to apply the gradient boosting decision tree (GBDT) model and partial dependence plot to explore the threshold and interaction effects between environmental variables and SOC content, and obtain a spatial map of SOC content.

Results

The results of the GBDT model showed that SOC content was high in the eastern part and low in the western part, which was mainly influenced by land use, mean annual precipitation, distance from the lake, and distance from mining land. Environmental variables exhibited threshold effects on SOC. For instance, the SOC content increased with distance from the mining area, and increased significantly beyond 15.9 km, indicating that the average effective influence range of mining land was 15.9 km. Similarly, the effective influence ranges of the lake, and irrigated ditch were 23.4 km and 0.2 km, respectively. The interaction effect plots showed that environmental variables were not independent but had complex interactions.

Conclusions

These results highlight the importance of introducing mining activities and considering threshold and interaction effects, which help to understand the spatial pattern of SOC in the coal–grain composite areas.