Establishing road shelter forests is a key method to reduce traffic noise pollution. However, the characteristics of various types of road shelter forests and their effectiveness in reducing traffic noise remain extensively unexplored. This study focused on five types of pure road shelter forests (PFs) and one type of mixed coniferous broad-leaved forest (MCBLF). By conducting field noise monitoring and spectrum simulations, we analyzed average mass density, additional noise reduction and economic benefits. With a forest belt width of 60 m, the MCBLF reduced additional noise by 6.6 dB(A). Additionally, Forest height, crown shape, average mass density and noise frequency were all positively linked to noise reduction. The width of shelter forests was the main factor affecting noise reduction. Linear regression analysis results showed that cumulative mass surface density was a significant factor in noise reduction (p < 0.01, R² = 0.93). Furthermore, the type and composition of the shelter forest had indirect effects on noise reduction. The MCBLF had better noise-reducing effects compared to both broad-leaved PFs and needle-leaved PFs due to its more complex structure. Interestingly, as the forest belt became wider, the noise reduction benefits per unit area decreased, implying that a 10 m wide forest belt offered higher economic returns. Considering that a 10 m wide shelter forest belt did not meet noise reduction requirements. This study suggested that the 20 m wide MCBLF was an optimal choice as an urban road shelter forest, providing both effective noise reduction and maximized economic benefits. Our findings provide a basis for the construction and sustainable development of road shelter forests with noise reduction functions.

Clarifying ecosystem service interactions under urbanization facilitates integrated ecological governance. This study took the rapidly urbanizing Su-Xi-Chang agglomeration in the Yangtze River Delta as the research area and applied the InVEST model to evaluate spatiotemporal variations in carbon storage, soil retention, water yield, and habitat quality from 2000 to 2023. The coupling coordination degree model and self-organizing map model were adopted to analyze urbanization–ecosystem interactions and the evolution of ecosystem service bundles, while the GeoDetector model was used to identify key socio-ecological drivers. The results reveal significant spatiotemporal divergences among the four ecosystem services. Carbon storage and habitat quality declined, while water yield and soil retention increased. Carbon storage and soil retention hotspots were persistently concentrated in the Yixing–Liyang Mountainous Area. Pairwise correlations further show that the synergy between water yield and soil retention strengthened over time, whereas their trade-offs with habitat quality intensified. The coupling coordination between urbanization and ecosystem services remained at a primary level yet exhibited a clear trajectory from imbalance toward optimization after 2010. Four ecosystem service bundles were identified, among which the urban-function-dominated bundle expanded by 190.39% from 2000 to 2023, indicating progressive spatial lock-in of urban land use. Differentiated zoning and targeted restoration strategies are proposed to reconcile urban development and ecological conservation. This study offers scientific references for ecological spatial optimization and refined ecological management in the Yangtze River Delta.

Warming profoundly influences soil respiration in terrestrial ecosystems, thereby altering global carbon cycling. Understanding the trends and drivers of soil respiration changes in forest ecosystems under warming is essential for assessing regional carbon budgets and ecosystem carbon sink/source dynamics. In this study, a one-year warming experiment was conducted using open-top chambers in a Taxodium hybrid (Zhongshanshan) ecosystem in the northern Jiangsu coastal area, China. Treatments included control (CK) and warming (W), focusing on soil respiration components (soil respiration, Rs; heterotrophic respiration, Rh; autotrophic respiration, Ra) and associated soil hydrothermal and nutrient factors. Results showed that both warming and season significantly affected Rs, Rh, and Ra, all exhibiting a unimodal seasonal pattern peaking in summer. Warming increased winter Ra by 117.39% (p < 0.001). Bivariate models (temperature and moisture) explained more variation in respiration (R² = 0.720–0.893) than univariate models. Correlation analysis indicated that under control conditions, Rs components were significantly positively correlated with microbial biomass carbon (MBC), ammonium nitrogen (NH₄⁺-N), and available phosphorus (AP). After warming, these positive correlations with MBC and AP persisted; however, negative correlations emerged with soil organic carbon (SOC) and its stoichiometric ratios (C:N, C:P). Additionally, Ra showed negative correlations with easily oxidizable carbon (EOC), total nitrogen (TN), and N:P. Overall, these findings suggest that climate warming may enhance soil respiration in the Taxodium hybrid (Zhongshanshan) ecosystem by altering soil thermal-hydrological and nutrient factors, although further validation is needed.