Microorganisms are critical in forest ecosystems, where they secrete soil ecological enzymes and mediate nutrient cycling. These processes are essential in determining how these ecosystems respond to nitrogen (N) addition inputs. In this study, an N addition experiment was conducted with three levels of N addition treatments in a subtropical evergreen broad-leaved forest in southwest China. The aim was to identify the effects of low (LN: 10 g m^− 2 year⁻¹), medium (MN: 20 g m^− 2 year^− 1), and high N addition (HN: 25 g m^− 2 year^− 1) on soil microbial community structure, diversity, ecological enzyme activities, and nutrient content, and to explore whether and how soil microorganisms influence ecological enzyme activity and nutrient cycling. Our observations indicated that surface soil exhibited the highest microbial diversity, ecological enzyme activities, and nutrient contents. N addition led to a reduction in soil bacterial and fungal diversity, with bacterial diversity consistently higher than fungal diversity. Moreover, bacterial community structures were generally more diverse and complex compared to fungal communities. The study emphasized that bacteria were relatively enriched under LN treatment, while fungi exhibited higher relative abundance under control conditions. Different soil microbial groups exhibited distinct responses to N addition, with an inhibitory effect on enzyme activities such as invertase (Inv), urease (Ure), and acid phosphatase (ACP), and an enhancement of catalase (CAT) activity. With increasing N addition levels, soil organic carbon (SOC), total N (TN), and total phosphorus (TP) contents decreased, whereas total potassium (TK), nitrate N (NO₃⁻-N), and ammonium N (NH₄⁺-N) exhibited the opposite trend. Co-linearity network analysis revealed stronger interactions among soil bacteria compared to fungi. The dominant bacterial phyla Pseudomonadota and Verrucomicrobiota showed stronger correlations with Ure and ACP, respectively, while Acidobacteriota exhibited a higher correlation with TP. Among the dominant fungal phyla, Basidiomycota had stronger correlations with CAT, NO₃⁻-N, and NH₄⁺-N, while Ascomycota was notably associated with Inv. The results showed that soil bacteria had a strong correlation with ecological enzymes, while soil fungi had a strong correlation with nutrients. This implies that bacteria and fungi have distinct advantages in enzyme secretion and nutrient mediation, leading to a trend of nutritional complementarity.

Risk assessment related to heavy metals in mining areas is crucial to ensuring the sustainable development of regional ecosystems and protecting human health. However, almost all research on the impact of mining activities on environmental quality entails field monitoring of surface soils or soil profiles. Here, to compare the variety of heavy metal concentrations in the geological profile, 39 samples (including soil, rock, and coal gangue) were collected and analyzed from hundreds of meters underground in the Pingshuo coal mine (Anjialing coal mine, Antaibao coal mine, and Donglutian coal mine), which is the largest open-pit coal mine in China. The mean heavy metal concentrations of Cd, Hg, As, Pb, Cr, Cu, Zn, and Ni in soils were 0.15 mg/kg, 0.02 mg/kg, 13.70 mg/kg, 27.12 mg/kg, 70.89 mg/kg, 26.10 mg/kg, 79.88 mg/kg, and 37.68 mg/kg, respectively; most of these metals were more concentrated in the soil samples than in the rock and coal gangue samples. A potential ecological risk assessment indicated that As, Pb, Cr, Cu, Zn, and Ni in all samples showed low risk, while the ecological risk degrees of Cd and Hg were higher and contributed most to the total risk index (RI). The highest E_r^i value (92.94) for Cd was found in rock samples, contributing to approximately 55.18% of the to tal RI. For Hg, four rock sampling sites had the highest E_r^i values (427.70, 270.78, 198.96, and 188.70), contributing approximately 68.36–88.07% of the total RI. Ranked after soil (0.15 mg/kg), limestone and shale showed high mean Cd concentrations (both 0.13 mg/kg). The highest mean concentration was found in coal gangue samples (0.1 mg/kg). Compared with the other types of samples, the mean concentrations of Cr, Cu, and Ni in soils, limestone, and mudstone were relatively higher. At different sites, heavy metal concentrations varied greatly at different depths, owing to diverse sample types and rock types. Correlations between heavy metals and soil nutrients indicated that N and P were closely correlated with heavy metals. Comparing the proportions of different heavy metals in various types of samples showed that heavy metals in soils were extremely similar to those in limestone, mudstone, and shale, implying that soils might indirectly inherit their features from their parent material.

Soil construction and revegetation are essential for ecological restoration in mining areas. The influence of vegetation on the horizontal and vertical distribution patterns of soil properties should be fully understood. However, most studies on reconstructed soils in mining areas only concentrate on the surface soil, without exploring the vertical variations in soil properties. Overall, this study aims to explore the potential mechanisms by which surface vegetation exerts some influence on the spatial distribution of soil physicochemical properties, and to provide some insight into revegetation and soil reclamation in mining areas. Descriptive statistics and one-way analysis of variance (one-way ANOVA) were employed to evaluate the differences in the soil physicochemical properties in horizontal and vertical directions under different land-use types in the south dump of Antaibao opencast mine in Pingshuo, Shanxi Province, China. The main results of this study are as follows: (1) In the horizontal direction, except for the strong variation (variation coefficient ≥ 100%) in soil organic matter (SOM) content at some depths, the degree of variation in other soil physicochemical properties at various depths was moderate or weak (variation coefficient < 100%). The soil physicochemical properties gradually remained constant after years of reclamation. In the vertical direction, the soil bulk density (SBD), soil porosity, SOM content, soil C/N ratio, soil total nitrogen (STN) content, soil available phosphorus (SAP) content, and soil available potassium (SAK) content showed significant variations (p < 0.05) between soil depths. In contrast, no significant difference was found for other physicochemical properties. (2) The SBD, STN, SAK, soil porosity, and soil clay content were significantly different (p < 0.05) under different vegetation cover types, but the influence of vegetation on other soil physicochemical properties seemed to be limited. The results reveal that trees have a stronger ability to reduce soil grain sizes and enhance SAP contents than shrubs or herbs; however, the beneficial effects of herbs on the physicochemical properties of shallow soil are more obvious than those of trees and shrubs. (3) This study indicates that more shrubs and trees should be planted in the areas with low vegetation coverage, and more measures should be taken to improve soil physicochemical properties in order to prevent the occurrence of large-scale degradation. The reconstruction of soil structure should be preferentially considered in the process of soil reconstruction and revegetation in areas under similar conditions. Herbs should first be planted in the early reclamation stage. At the same time, shrubs or trees can be adopted in the middle and late stages of vegetation reconstruction in order to achieve comprehensive revegetation.

The prioritization of energy policies by local governments represents a process of competitive attention allocation among various policy tools, and its outcomes significantly influence the ultimate effectiveness of the low-carbon transformation of energy. Building on the theoretical framework of governmental attention allocation, the research first analyzes how internal–external governmental relations shape policy tool prioritization through comparative case studies, followed by a discrete choice experiment (DCE) to empirically examine local governments’ preferences for policy tool attributes under different relational conditions. The findings reveal that county governments (CGs) dominated by intergovernmental relationships tend to align their priorities with the governance requirements of higher-level authorities and emphasize clarity, operability, economic attributes, and political considerations in policy tool selection. In contrast, governments dominated by government–enterprise relationships place greater emphasis on the impact of policy tools on enterprise production and focus primarily on economic attributes and operability. The study demonstrates that under different internal–external government relations, CGs prioritize distinct attributes of policy tools, which leads to varied rankings of energy policy tools. Building effective incentive and constraint mechanisms on the basis of rationalizing vertical intergovernmental and government–enterprise relationships, while optimizing energy policy supply to guide local governments in selecting context-appropriate energy policy tools, serves as a crucial approach to advancing urban low-carbon energy transitions and achieving sustainable socioeconomic development.