Heavy Metal‐Driven Land Degradation in Apple Orchards: Geospatial Controls and Sustainable Zoning Management

ABSTRACT In orchard systems, sustained agrochemical inputs drive progressive heavy metal accumulation in soils, posing threats to ecosystem security and potential human health risks. This study integrates ecological risk models, partial correlation analysis, random forest algorithms, and regression analysis methods to systematically investigate the characteristics, spatial heterogeneity patterns, and driving mechanisms of heavy metal pollution and risks under distinct management regimes in apple orchards of the Chinese Weibei Upland, while unraveling their multi‐scale driving mechanisms. The findings indicate that: (1) Geographical background primarily governs the differentiation pattern of ecological risks. The soil heavy metal pollution load of apple orchards in Qianyang was significantly higher than that of Baishui and Luochuan. (2) There was no significant effect of management practices on soil heavy metal content, ecological, and health risks in the area ( p > 0.199). (3) Random forest analysis and partial correlation analysis showed that the distribution of arsenic and lead was dominated by parent material factors, cadmium and mercury showed significant associations with microbial activities, chromium was strongly associated with organic carbon, and copper accumulation was dominated by exogenous inputs. These findings provide a mechanistic basis for developing targeted management strategies for orchards in the Weibei Upland and similar ecologically fragile areas.