Soil organic matter (SOM) scale effects are critical for crop growth and food security, especially in coal–grain complexes. However, few studies describe the spatial variation in SOM and its influencing factors at different sampling scales. Here, geostatistical theory and mathematical statistical methods were adopted to analyze the spatial variation characteristics of and structural differences in SOM in the coal mining subsidence area at Zhaogu No. 2 Mine at different sampling scales. The results showed that SOM varied spatially at large, medium, and small scales, and the coefficients of variation were 28.07%, 14.93%, and 14.31%, respectively, which are moderate values. The characteristic functions of the SOM content at different sampling scales differed, and the spatial structure scale effect was obvious. The spatial distribution of the SOM content fitted by the multiscale fitting model method was generally the same as the spatial distribution law of the SOM content fitted by the single scale kriging interpolation method; however, in terms of the detailed expression and spatial distribution of small-scale SOM content, the fitting model method was more accurate, and the accuracy increased by 36%. At the different sampling scales, sample size and soil type had specific effects on the SOM spatial distribution. These results provide research concepts and technical countermeasures for improving food security and the ecological environment in the coal–grain complex and help ensure sustainable agricultural lands.

Soil nitrogen is very important for crop growth and development. However, the factors affecting the three-dimensional spatial distribution of soil total nitrogen (TN), particularly in coal mining subsidence areas, are unclear. In this study, Markov geostatistics was used to analyse the three-dimensional spatial distribution characteristics and influential factors of TN by examining 180 soil samples from the Zhaogu mine in China. The results showed that the TN content was significantly different at different soil depths (0–20, 20–40, 40–60 cm) and decreased with increasing soil depth. The variation coefficient of the TN content decreased gradually from top to bottom, ranging from 18.18 to 25.62%. In addition, the TN content was greatly affected by mining subsidence, rainfall, irrigation, fertilization and management mode. The factors that influenced the TN content also varied across different slope positions. The TN content of the upslope was the highest, and the TN content of the middle slope was the lowest. These results can provide research ideas and technical countermeasures for ecological environment improvement and sustainable land development in coal mining subsidence areas.