Impact of Soil Development and Land Use on Concentrations of Potentially Toxic Elements in Soils: Insights from a Multi-Scale Study

Soil potentially toxic elements (PTEs) are crucial indicators of soil quality and ecological risk, especially in areas with complex pedogenesis and intensive anthropogenic activities. However, how soil development and land use jointly shape PTEs’ distribution across multiple scales remains unclear. A multi-scale framework encompassing catchment, sub-catchment, and regional scales was employed to examine the impacts of soil development and land use on PTEs’ (Cr, Ni, Cu, Zn, Pb, Cd, As, and Hg) distribution and their dominant drivers in the lower Yangtze River basin’s alluvial soils. Results showed significant scale-dependent variations in PTEs, with concentrations being highest on the regional scale. During pedogenesis, PTEs exhibited distinct evolutionary patterns across scales: Ni, Cu, Zn, and Cd decreased significantly at both the catchment and sub-catchment scales, whereas Cr, Ni, and As showed increasing trends at the regional scale. Land use also demonstrated scale-dependent effects, with drylands exhibiting PTEs’ enrichment at larger scales but significantly lower concentrations compared to woodlands and paddy-dryland rotation (paddies) at the regional scale. The mechanisms through which the Chemical Index of Alteration (CIA) influences PTE concentrations varied across scales, with metal oxide alteration as a key common pathway. Mantel tests showed that PTE distributions are governed by pH and total phosphorus (TP) at larger scales but by organic carbon (OC) and total nitrogen (TN) regionally. These cross-scale insights reveal how pedogenesis and human activity jointly shape HM patterns, highlighting the potential for scale-appropriate sustainable soil management—for instance, regionally tailored adjustments of pH and organic matter can mitigate metal risks while maintaining soil health. Future studies can build on this multi-scale framework by integrating long-term monitoring with predictive models to assess adaptive strategies under land-use change, thereby advancing sustainability in alluvial agroecosystems.