The driving factors affecting soil quality were identified to evaluate the effect of vegetation on soil quality in coal mine reclamation areas with various restoration durations. This study used Hippophae rhamnoides subsp.sinensis Rousi with different reclamation durations (3, 4, 5, 6, and 7 years) in the abandoned land area of the Juxinlong coal mine in Ordos as the research subject. Artificial and abandoned grasslands were selected as the study’s controls. A soil quality evaluation model was constructed to assess the soil quality in the reclamation area. A structural equation model was used to thoroughly analyze the driving factors affecting soil quality in the study area. The findings show that: (1) Reclamation duration significantly affected the physicochemical characteristics of the soil. As the reclamation duration increased, soil nutrients such as organic carbon accumulated while the bulk density index (BD) decreased. (2) The soil quality index of Hippophae rhamnoides forest land in China was the highest after 6 years of reclamation. The Hippophae rhamnoides forest land with the lowest soil quality index after 4 years of reclamation differed significantly from that after 6 years (p < 0.05). The soil quality index (SQI) of 6a (years) significantly increased by 67.44% compared to 4a. (3) By constructing a structural equation model, it was found that physical indicators (saturated water content and silt) and reclamation durations were the main drivers of soil quality. SQI had a strong interaction with organic matter (OM) and different restoration durations. The findings of this study will serve as important guidelines for future quantitative evaluation of soil quality following land reclamation and management during the ecological restoration process.

Choosing economically important trees and establishing planting patterns can improve soil quality in economic forests. To clarify the soil quality status of the main economic forest land distributed in northern Shaanxi, the research object in this study was jujube and apple economic forests, and the control was grassland. By evaluating 17 soil indicators, the minimum data set (MDS) and structural equation model (SEM) were used to analyze the soil quality status and its dominant factors under different economic forests and land preparation methods. The results showed that (1) compared with grassland, the economic forest has a certain improvement and promotion in soil’s properties, mainly in the water-holding capacity and available nutrients. Compared to the undisturbed slope, the level bench had better physical and chemical properties. (2) Six indicators were identified as the minimum data set for assessing soil quality, including the soil organic carbon, saturated water content, bulk density, alkaline nitrogen, sand, and total capillary porosity. In addition, structural equation model analysis showed that the soil organic carbon, saturated water content, alkaline nitrogen, and capillary porosity were the dominant factors affecting soil quality in the study area. (3) Jujube trees exhibited the highest soil quality and the best restoration effect, followed by apple trees, while grassland had the poorest restoration effect. The soil quality of undisturbed slopes under different land preparation methods was lower than that of the level bench land preparation. The outcomes of this study are to provide data support and a theoretical basis for improving soil quality, enhancing ecological benefits, and selecting and managing economic forest species, in the study area and similar regions in the future.

To investigate the distribution characteristics and driving factors of soil potentially toxic elements after land reclamation in a mining area, this study focused on the soil potentially toxic elements distribution in a Hippophae rhamnoides plantation within the Juxinlong Coal Mine reclamation area in Ordos, Inner Mongolia. Soil sampling gradients were established at distances of 1/8 (0.25 m), 1/4 (0.5 m), and 1/2 (1 m) of the inter-tree distance from the standard tree. Abandoned grassland was used as a control group. The contents and distribution characteristics of potentially toxic elements including Cadmium (Cd), Copper (Cu), Lead (Pb), Chromium (Cr), and Arsenic (As) in the soil were analyzed to assessed their potential ecological risks, and identified the driving factors. The results showed that the contents of Pb, Cu, Cr, Cd, and As in the study area increased as the distance from the tree trunk decreased. The contents of Pb, Cu, Cr, and Cd in the abandoned grassland were generally higher than those in the Hippophae rhamnoides treatment groups, while As showed significant enrichment at the 1/8 plant spacing distance, with its content increasing from 4.03 mg·kg⁻¹ to 9.35 mg·kg⁻¹.The comprehensive potential ecological risk index (RI) increased as the distance decreased, reaching an extremely high-risk level near the standard trees (1/8 plant spacing), with RI values ranging from 434.58 to 581.17, and Cr was identified as the key risk factor. Soil moisture indicators (field water-holding capacity, CWC; saturated water content, SW) were the core driving factors regulating the contents of As, Cd, and Cu, exerting significant negative direct effects (with path coefficients of -0.84, -0.80, and -0.50, respectively). Furthermore, soil moisture indirectly influenced potentially toxic elements distribution by affecting soil pH, available potassium, organic matter, and bacterial community diversity. This study elucidates the distribution pattern of soil potentially toxic elements and their main influencing factors in a coal mine reclamation area, providing a theoretical basis for risk identification and precise management in mining area ecological restoration.

To assess soil quality in micro-topographic units of loess hilly regions, this study selected five typical micro-landforms (shallow gully, collapse, steep slope, gentle terrace, cut gully) along with the original slope as a control. We measured 23 indicators covering soil physicochemical properties, enzyme activities, and plant diversity. A soil quality evaluation model was constructed using principal component screening combined with fuzzy comprehensive evaluation, and structural equation modeling was applied to identify driving factors. The results showed that the first five principal components had a cumulative contribution rate of 79.915%. The SQI values ranked as follows: collapse (0.604) > gentle terrace (0.550) > cut gully (0.538) > shallow gully (0.530) > original slope (0.527) > steep slope (0.466), with the collapse micro-landform consistently ranking first across the physical, chemical, enzymatic, and plant diversity indicators. The structural equation models further showed that soil moisture had the strongest association with soil quality in collapses, shallow gullies, and the original slope, whereas soil organic matter showed the strongest association in steep slopes, gentle terraces, and cut gullies. These findings provide a scientific basis for precision soil quality management and ecological function enhancement based on micro-topographic units in the implementation of the Grain-for-Green program.