Fire is the predominant natural disturbance that influences the community structure as well as ecosystem function in forests. This study was conducted to examine the soil properties, loss of aboveground biomass, and understory plant community in response to an anthropogenic fire in a coniferous (Pinus massoniana Lamb.) and broadleaf (Quercus acutissima Carruth.) mixed forest in a subtropical–temperate climatic transition zone in Central China. The results showed that soil pH, NO₃⁻-N concentration, and microbial biomass carbon (C) increased three months after the fire; however, there were no significant differences in soil organic C, total nitrogen (N), NH₄⁺-N concentration, or microbial biomass N between the burned and unburned observed plots. The total aboveground biomass was 39.0% lower in the burned than unburned plots four weeks after fire. Direct biomass combustion (19.15 t ha⁻¹, including understory shrubs and litters) was lower than dead wood biomass loss (23.69 t ha⁻¹) caused by the fire. The declining trends of tree mortality with increasing diameter at breast height for both pine and oak trees suggest that small trees are more likely to die during and after fires due to the thinner bark of small trees and tree and branch fall. In addition, burning significantly stimulated the density of shrub (160.9%) and herb (88.0%), but it also affected the richness of shrub and herb compared with that in the unburned plots two months after the fire. The rapid recovery of understory plants after fires suggest that the diversity of understory species could benefit from low-severity fires. Our findings highlight that the decomposition of dead wood and understory community recovery should be considered for offsetting C emissions after fires for further research.

To investigate the impact of periodic water-level fluctuations on soil microbial community structure in the riparian zone of the Three Gorges Reservoir Area, this study focused on the riparian zone at Zhangjiawan near the dam. Surface soil samples (0–20 cm) were collected in spring, summer, and autumn from three elevation gradients: below 160 m, 160–170 m, and above 170 m. Phospholipid fatty acid (PLFA) was employed to characterize the microbial community structure. The results indicated that microbial community distribution was significantly influenced by both elevation and season, with bacteria dominating community variations. In terms of elevation, the total microbial biomass and bacterial abundance were highest at the 160–170 m gradient, followed by the area above 170 m, and lowest below 160 m. Season and elevation exhibited a significant interactive effect on fungi. Seasonal patterns showed that total microbial biomass and bacterial abundance peaked in summer, whereas fungal abundance and the fungi-to-bacteria ratio were higher in autumn. In contrast, actinobacterial abundance remained stable across seasons. Soil organic carbon (SOC; 60.3%) was identified as the predominant environmental factor influencing microbial community structure, followed by total nitrogen (TN; 13.9%) and pH (2.4%). SOC was identified as the key driver of microbial community dynamics. These findings clarify the respective roles of water level fluctuation, seasonal variation, and environmental factors in shaping riparian microbial communities, providing critical baseline data and theoretical support for ecological protection and scientific management of the Three Gorges Reservoir Area.

Soil organic carbon (SOC) and its active fractions—labile organic carbon (Lab-C), dissolved organic carbon (DOC), and microbial biomass carbon (MBC)—govern soil carbon stability and climate feedback mechanisms. To investigate the distribution patterns and regulatory mechanisms of SOC and those active fractions along elevational gradients in the riparian zone of the Three Gorges Reservoir Area (subjected to intense waterlogging stress), soil sampling and analysis were conducted across four zones of the Longtanping: below 160 m, 160–170 m, 170–180 m, and above 180 m in early September 2021. Results indicated that as elevation increases, the content of SOC and active components exhibited a unimodal distribution pattern showing initial increases followed by decreases; moreover, this pattern can be attributed to the pH-riven changes in bacterial abundance under varying inundation stress conditions. The peak values occurred at elevations of 160–170 m, with the overall distribution pattern being as follows: 160–170 m > 170–180 m > above 180 m > below 160 m. Correlation analysis revealed significant positive correlations among SOC, DOC, MBC, Lab-C, pH, TN, and bacterial abundance (p < 0.05). Lab-C demonstrated the strongest explanatory power for SOC variations, serving as a sensitive indicator of SOC turnover and persistence dynamics. This study provides critical insights into the carbon cycling mechanism and regional carbon sink assessment in reservoir riparian ecosystems.

Conventional physicochemical parameter-based monitoring fails to provide real-time early warning of microbial risks in drinking water sources, highlighting the critical necessity to unravel the inherent associations between microbial activity and water quality dynamics. This study integrated a domestically developed microbial enzymatic analyzer with multivariate analyses to assess real-time microbial activity in a complex reservoir. Measurements of microbial indicators and physicochemical parameters were conducted at eight sites during dry and wet seasons, plus six months of continuous monitoring at a polluted tributary site. Key findings: (1) Water quality showed clear spatiotemporal variation, worse in the wet season than the dry season, with tributaries more polluted than mainstream, and downstream better than upstream; (2) Microbial activity exhibited spatial heterogeneity, with a significant positive correlation between E. coli and Enterococcus (EC); (3) Microbial activity responded to key water quality indicators, and both E. coli and EC correlated positively with NH₃-N. EC also correlated positively with TP. In summary, this study reveals a mechanism-based link between microbial activity and key water quality parameters, providing a theoretical foundation for a microbial-response-centered early warning model. This marks a shift from conventional reactive monitoring to proactive risk management for drinking water safety, offering a new paradigm with ecological indication and practical value.