Spatial variation analysis of the effect of wheat and maize crop rotation on soil organic carbon in the Sushui River Basin

Objective: of investigation : Enhancing soil organic carbon (SOC) content in farmland is crucial for soil quality maintenance and food security. Crop rotation plays a significant role in this regard. However, the relationship between crop rotation and SOC sequestration remains unclear. This study focused on the effects of wheat − maize crop rotation on SOC in the Sushui River Basin in 2017–2021. Experimental material : soil organic carbon (SOC) content of monoculture wheat (47), monoculture maize (30), and wheat-maize rotation (35) sites in 2017 and 2021 cropland quality monitoring sites. Influencing factors were average temperature and rainfall during the study period, topographic factors, soil factors, and anthropogenic factors dominated by cropping systems. Method: of investigation : Geographically Weighted Regression and Geodetector were used to explore the spatial effects of major food cropping systems on SOC trends and their interactions with other factors. Data collection : Soil, climate, and terrain data were obtained from Shanxi Province Cropland Quality Monitoring Data, Yuncheng Meteorological Bureau, and the Geospatial Data Cloud website of the Computer Network Information Center of the Chinese Academy of Sciences, respectively. Results: : Analysis of variance (ANOVA) indicated significant differences only between wheat and maize monocrops. Altitude, temperature, rainfall, and pH were the main factors affecting SOC spatial heterogeneity. Although the impact of the cropping system alone on spatial heterogeneity was not significant, the influence increased after interactions with other factors. Concerning SOC variation, wheat–maize rotation had a trade-off effect with elevation and synergistic effects with rainfall and pH. It displayed a synergistic effect with temperature in the southwest and a trade-off effect in the northeast. Conclusions: : The degrees of trade-offs and synergy varied spatially among all interacting factors. Our results provide valuable insights that could facilitate optimization of planting layout and improvement of farmland management schemes.