Soil heavy metal (HM) contamination has become a critical global environmental issue, predominantly caused by industrial and agricultural operations. This study focuses on Mount Wuyi, a UNESCO biodiversity hotspot and major tea production base, to examine vegetation-mediated soil HM accumulation under anthropogenic impacts. We analyzed nine HMs (Mn, Cu, Zn, Cd, Hg, As, Pb, Cr, Ni) across diverse vegetation types using geochemical indices and Positive Matrix Factorization (PMF) modeling. The findings revealed Mn and Zn were dominant elements, and Cr and Pb concentrations exceeded regional background values by 3.47 and 1.26 times, respectively. Cr, Cd, and Pb demonstrated significant pollution levels, while Cd and Hg posed the highest ecological risks. Vegetation type significantly influenced HM distribution patterns, with cultivated areas and shrublands (including tea gardens) accumulating higher concentrations of Cu, Cd, Pb, and Hg from agricultural and transportation sources. Notably, bamboo forests exhibited natural resistance to HM contamination. PMF analysis identified four primary pollution sources: urbanization (27.94%), transport–agriculture activities (21.40%), agricultural practices (12.98%), and atmospheric deposition (12.96%). These results underscore the need for implementing clean energy solutions, phytoremediation strategies, and tea-specific detoxification measures to maintain ecological security and agricultural sustainability in this ecologically significant region.

Soil heavy metal (HM) control has become a pressing global ecological and environmental issue, with a significant focus on the western Dabie Mountain in China, a region that is recognized for its ecological barriers and water sources. We analyzed the concentrations, pollution status, and potential ecological risks of 10 HMs (i.e., Cu, +Pb, Zn, Cr, Ni, Co, Cd, As, Hg, and Mn) in the topsoil of different ecosystems in this region. The effects of four soil groups (Anthrosol, Fluvisols, Gleysol, and Alisols) and three soil texture types (sandy, clayey, and loamy soils) on the above aspects were also analyzed. Positive Matrix Factorization (PMF) models were performed to identify and quantify the potential sources and contribution rates of these HMs. Results showed that the level of HM pollution may be negligible, and there was no potential ecological risk. Of all metals, Pb and Cd exhibited the highest levels of pollution. The potential ecological risk associated with soil HMs decreased from croplands to urban and further to forests. Cu and Co were more likely to accumulate in Anthrosols, while Alisols were more likely to accumulate Pb, Cd, and Hg and had a higher overall potential ecological risk. The overall risk in clayey and loamy soils is both higher than in sandy soils. The HM accumulation in topsoil was closely related to the soil organic matter and clay contents. The potential main sources of HMs in this region can be agricultural activities, soil parent material, mining, industrial activities, and vehicle emissions. These findings suggest that special attention should be paid to soil Pb and Cd in western Dabie Mountain. Future efforts can focus on reducing mining, smelting, and industrial emissions, as well as strengthening the research on the migration patterns and mechanisms of HMs.

Converting monoculture forests into mixed forests is a widely adopted strategy to enhance forest ecosystem quality. Soil enzyme activities and their stoichiometric ratios are acknowledged as critical indicators of nutrient cycling and ecosystem multifunctionality, with microbial nutrient limitation (particularly C, N, and P) being strongly influenced by forest management practices. However, the effects of this conversion on soil enzyme activities and stoichiometric ratios remain inconclusive, and the impacts of forest conversion on soil C, N, and P dynamics require further clarification. To address these uncertainties, a meta-analysis of 2113 paired observations was conducted to assess the impacts of forest conversion on soil enzyme activities, stoichiometric ratios, and microbial nutrient limitations. The activities of four key enzymes, including β-1,4-glucosidase (BG), β-1,4-N-acetylglucosaminidase (NAG), leucine aminopeptidase (LAP), and phosphatase (ACP) were examined. It was found that mixed forests exhibited significantly higher C-, N-, and P- enzyme activities than monocultures (increases of 36.23%, 9.85%, and 11.07%, respectively). Additionally, soil C, N, and P contents were generally enhanced following the conversion from monocultures to mixed forests. Elevated enzyme C:P and N:P ratios were observed in mixed forests, while C:N ratios were reduced. Microbial C limitation was alleviated, though C&P co-limitation remained prevalent. Notably, greater effects on enzyme activities were observed when conifer monocultures (particularly those introduced with broadleaf species) were converted, compared with conversions of broadleaf monocultures. In contrast, the introduction of additional conifer species into existing conifer stands exacerbated C limitation. These results suggest that conversion of monocultures to mixed-species forests can mitigate microbial C limitation in soils while improving soil nutrient availability. Furthermore, for conifer plantation conversion, selecting functionally complementary broadleaf species yields greater benefits than introducing additional conifer species.

Soil microbial carbon use efficiency (CUE) is a pivotal determinant of soil carbon sequestration, yet how forest quality gradients regulate CUE through the interplay of mineral-microbial interactions in subtropical conifer ecosystems remains poorly understood. To address this, we examined the CUE response and its drivers across a forest quality gradient (high-quality to poor-quality stands) in subtropical coniferous forests in China. Soil mineral composition (including soil texture and the contents of Fe₂O₃, CaO, and MgO), physicochemical properties, microbial community diversity, and CUE were quantified. The results showed that CUE decreased by 2.7%, from 0.533 in high-quality stands to 0.519 in low-quality stands. Concurrently, soil organic carbon (SOC), nutrient availability, and microbial diversity exhibited consistent declining trends along the forest quality gradient. The CUE showed a significant positive correlation with SOC (r > 0.90, p < 0.001). Structural equation modeling and random forest revealed that microbial diversity was the most dominant correlated factor of CUE (the total effects on CUE = 0.932), followed by SOC. However, soil minerals indirectly influenced CUE via SOC. These findings highlight microbial diversity as the dominant observed correlate of CUE across forest quality gradients. This study not only deepens the understanding of the microbial mechanisms underlying soil carbon dynamics in subtropical forests but also provides key scientific basis for ecological restoration of poor-quality forests and nature-based climate solutions.