Carbon–nitrogen (C-N) coupling is a fundamental concept in ecosystem ecology. Long-term excessive fertilization in tea plantations has caused soil C-N imbalance, leading to ecological issues. Understanding soil C-N coupling under nitrogen loading is essential for sustainable management, yet the mechanisms remain unclear. This study examined C-N coupling in tea plantation soils under five fertilization regimes: no fertilization, chemical fertilizer, chemical + organic cake fertilizer, chemical + microbial fertilizer, and chemical + biochar. Fertilization mainly increased particulate organic carbon (POC) and inorganic nitrogen, driven by changes in bacterial community composition and function. Mixed fertilization treatments enhanced the association between bacterial communities and soil properties, increasing ecological complexity without altering overall trends. Fungal communities had a minor influence on soil C-N dynamics. Microbial necromass carbon (MNC) and microbial carbon pump (MCP) efficacy, representing long-term carbon storage potential, showed minimal responses to short-term fertilization. However, the microbial necromass accumulation coefficient (NAC) was nitrogen-sensitive, indicating short-term responses. PLS-PM analysis revealed consistent C-N coupling across the treatments, where soil nitrogen influenced carbon through enzyme activity and MCP, while bacterial communities directly affected carbon storage. These findings provide insights for precise soil C-N management and sustainable tea plantation practices under climate change.

With the expansion of pure forest planting area and the increase in the number of rotations used, soil activity and plant productivity have significantly reduced. The functional diversity of soil microorganisms plays a vital role in forest health and the long-term maintenance of productivity. Though the optimization of forest cutting and regeneration methodologies is necessary to improve the functional diversity of soil microorganisms, the effects of harvest residual treatment on the functional diversity of soil microorganisms remain unclear. During the period 2018–2020, we designed four harvest residual treatments—reference (RF), residual burning (RB), crushing and mulching (MT), and no residuals (NR)—to determine soil physical and chemical properties. We also used microbial biomass (MB) to evaluate the diversity in carbon source metabolism of soil microorganisms through Biolog microplate technology, and discussed the response mechanism of microbial functional diversity to the different forest cutting and regeneration methodologies used in Chinese fir plantations. The results indicated that RB significantly increased the carbon metabolic capacity of the microbial community, the community richness, and its dominance compared to RF, MT, and NR; however, they also showed that it decreased the uniformity of the soil microbial community. NR showed a poor carbon utilization capacity for microorganisms compared to RF and MT, while MT significantly increased the utilization capacity of carbohydrate and amino acid carbon compared with RF. Soil nutrients were the main driving factors of soil microbial carbon metabolic activity, and the different responses of microbial functional diversity to various forest cutting and regeneration methodologies were mainly due to the variation in the nutrient inputs of harvest residues. This study provides a practical basis for enhancing the functional diversity of soil microorganisms in plantations through the management of harvest residues.

As a key part of the forest ecosystem, soil microorganisms play extremely important roles in maintaining the ecological environment and the security of water quality in reservoir areas. However, it is not clear whether there are differences in the functional diversity of soil microorganisms in different types of water-conservation forests in reservoir areas, and which factors affect the functional diversity of soil microorganisms. In our study, the Biolog-Eco microplate technique was used to analyze the carbon source metabolic characteristics of soil microbial communities in three typical water-conservation forests and a non-forest land: Pinus massoniana-Quercus variabilis mixed forest (MF), Pinus massoniana forest (PF), Quercus variabilis forest (QF) and non-forest land (CK). The results showed that the average well color development (AWCD), the Shannon diversity index (SDI) and the richness index (S) of the three forest lands was significantly greater than that of the non-forest land (p < 0.05). The mean values of AWCD, SDI and S of the three forests had the same order (QF > PF > MF), but there was no significant difference among different types of forests. The microbial biomass carbon (MBC) and microbial biomass nitrogen (MBN) of QF and PF were higher than those of MF and CK, but the microbial biomass C/N ratio (MBC/MBN) was lower. The variance partitioning analysis (VPA) showed that 86.4% of the variation was explained by plant (community) diversity, soil physical and chemical properties and soil microbial biomass, which independently explained 10.0%, 28.9%, and 14.9% of the variation, respectively. The redundancy analysis (RDA) showed that total phosphorus (TP), microbial biomass carbon (MBC), total nitrogen (TN), number of plant species (N_um) and alkali-hydro nitrogen (W_n) were the key factors affecting the functional diversity of soil microorganisms. This study confirmed that forest ecosystem is better than non-forest land in maintaining soil microbial function diversity. Moreover, Quercus variabilis forest may be a better stand type in maintaining the diversity of soil microbial functions in the study area.

Urbanization has profoundly reshaped ecosystem services (ESs), yet how diverse urbanization drivers interact with land use and land cover (LULC) changes to influence ESs remains insufficiently studied. To address these gaps, this study offers a comprehensive assessment of urbanization induced ESs transformations across Anhui Province, China. We selected five key regulating and provisioning services closely linked to LULC dynamics, revealing that southern mountainous areas consistently supported higher ES levels, whereas central and northern urbanizing zones experienced severe ES degradation. By using random forest ensemble learning and Partial Least Square Path Modeling, we identified population density, urban construction proportion, and agricultural intensification as key urbanization drivers shaped LULC changes and indirectly influenced ES distributions. Notably, we also found that urbanization drivers and land use transitions did not act independently but interacted to jointly affect ES dynamics. These findings underscored the critical role of land use changes in mediating the impacts of urbanization on ESs and highlighted the importance of integrating land use management with urban planning to support sustainable regional development.