In this study, to comprehensively investigate the impact of garden plants on air quality, we measured the leaves of 18 common garden plants in three different areas, namely, Suzhou industrial parks (clean air area (CAA)), Xiangcheng district parks (lightly polluted area (LPA)), and Huqiu district parks (highly polluted area (HPA)). We also measured the leaf functional traits of different life-types of plants. To explore the trade-off strategies of the leaf traits of common garden plants in response to air pollution and to assess the adaptive capacity of different life types of plants to air pollution. The results show that plants in the polluted area had higher leaf dry matter content (LDMC) and leaf nitrogen content per unit mass (N_mass), and a lower specific leaf area (SLA), maximum net photosynthetic rate per unit area (A_area), transpiration rate (Tr), stomatal conductance (Gs), and chlorophyll value (SPAD). Pearson correlation analysis showed that SLA was significantly positively correlated with N_mass, Tr, photosynthetic use efficiency (PNUE), and SPAD, and significantly negatively correlated with LDMC, while A_area was significantly positively correlated with chlorophyll value. Redundancy analysis revealed that the correlation between each leaf functional trait and atmospheric pollution factors was as follows: LDMC > N_mass > SLA > LA > A_area > Tr > PNUE > SPAD. The results suggest that different plant types have varying levels of adaptability to environmental conditions. Trees were found to be the most adaptable, followed by shrubs, herbs, and lianas. Additionally, under the stress of air pollution, herbs and lianas exhibited characteristics of “fast investment-return” on the leaf economic spectrum, meaning they were able to quickly allocate resources to maximize their return. However, trees and shrubs displayed traits of “slow investment-return”, indicating a more conservative approach to resource allocation. These results provide valuable insights into the leaf trade-off strategies of plants in Suzhou Park under air pollution stress and can guide the selection of suitable plant species in similar environments.

Previous research has indicated that natural landscapes exhibit a greater capacity for ameliorating negative emotional states in individuals when compared to urban landscapes. Nevertheless, significant scientific inquiries, such as the uniformity of the rejuvenating effect across distinct categories of natural landscapes on college students and the choice of the optimal plant community for achieving the most potent restorative effect, remain unexplored. This study aimed to address these questions by selecting four plant communities (single-layer grassland, single-layer woodland, tree-grass composite woodland, tree-shrub-grass composite woodland) and using an electroencephalography method to capture the neuroelectric activity of the participants in combination with the Positive and Negative Affect Schedule score to explore the effects of plant community types on emotional recovery. The results showed that all four plant communities significantly increased positive emotions and significantly reduced negative emotions. There was no significant difference in the recovery effect of positive emotions among the four plant community types, but there was a significant difference in the recovery effect of negative emotions. The effect of tree-shrub-grass composite woodland on the negative emotion recovery effect is the best; the EEG results found that the alpha wave amplitude induced by the tree-shrub-grass composite woodland was significantly higher than that of the other three groups of plant communities, and the EEG and behavioral results were consistent. The results show that the tree-shrub-grass composite woodland has the best restoration effect and has stronger planning and design significance.

The accelerating urbanization has exacerbated mental health challenges faced across social groups. College students, as an important group in the society, often experience multiple pressures from academic demands, familial responsibilities, and career uncertainties, making their emotional states especially susceptible to environmental influences. This study investigated and sampled the colored-leaves plant communities in urban parks of Suzhou, selected redgreen palette, yellowgreen palette, and single green plant communities with varied color proportions, and combined psychological indicators (PANAS scale) and physiological indicators (EEG data) to scientifically examine the differences in the influence on college students emotional restoration. The results included: 1) all plant communities significantly increased respondents positive emotions and reduced negative emotions; 2) in the comparative experiment of redgreen plant communities, single green plant communities had the best effect on emotional restoration; 3) in the comparative experiment of yellowgreen plant communities, those with yellow color proportion of 75% 90% and 45% 60% had the best emotional restoration effect; and 4) when comparing the plant communities with the same red and yellow color proportion, the yellowgreen plant community performed better than the redgreen plant community. This study responds to the urgent need to pay attention to the mental health of the youth in the current urbanization process by exploring the differences of emotional restoration effects of colored-leaves plant communities. It aims to provide scientific vegetation planting and configuration suggestions for emotional restoration environments, as well as theoretical guidance for the construction of restorative landscapes.

Cultural ecosystem services (CESs) represent a critical link between ecosystems and human well-being and constitute a core foundation for regional sustainable development. The balance between CES supply and demand directly affects the coordination efficiency between ecological conservation and socio-economic development, making it a key prerequisite for ecosystem management, conservation planning, and policy formulation. This study focuses on the circum-Taihu region and integrates multi-source data to assess public perceived demand and spatial supply capacity of CESs. Supply–demand matching relationships are examined across three dimensions, namely, scenic beauty, cultural heritage, and recreation, through the construction of a region-specific CES quantitative indicator system. The impacts of multiple environmental factors on CES supply–demand dynamics are further explored to provide scientific support for coordinated ecological, cultural, and economic sustainability at the regional scale. The findings demonstrate the following: (1) the proposed methodology effectively quantifies CES perception and supply capacity in the circum-Taihu region. Scenic beauty exhibits the highest perception levels, whereas cultural heritage and recreation show lower perception. Cultural heritage displays the strongest supply capacity, whereas scenic beauty and recreation exhibit weaker supply. (2) Significant spatial imbalances exist between CES perception levels and supply capacity across the circum-Taihu region. Areas exhibiting mismatches constitute the largest proportion for cultural heritage CESs, followed by scenic beauty, with recreation displaying the smallest amounts of imbalance. (3) Environmental drivers exert differentiated effects on CES supply–demand relationships. Slope, road network density, and elevation have significant positive effects, whereas the normalized difference vegetation index (NDVI), distance to water bodies, and distance to roads exhibit significant negative effects. Distance to roads imposes the strongest inhibitory influence on CES perception, whereas elevation emerges as the most influential driver of public perceived CES levels.

Investigating the adaptive mechanisms of different plant growth forms to flooding gradients is essential for formulating scientific vegetation allocation models to support ecological restoration in aquatic–terrestrial ecotones and mitigate ecological risks associated with summer flooding. This study focused on 38 adaptable species under three flooding gradients in the Taihu Lake aquatic–terrestrial ecotone. We systematically measured leaf morphological traits, photosynthetic physiological parameters, and stoichiometric characteristics. Employing analysis of variance, correlation networks, and principal component analysis, we elucidated how flooding environments shape leaf functional trait patterns of woody and herbaceous plants. The results indicated the following. (1) With increasing flooding stress, herbaceous plants increase the leaf area (LA) and leaf dry weight (LDW), whereas woody plants decrease them, indicating that herbaceous plants demonstrate stronger adaptability than woody plants. (2) Woody plants constructed a leaf functional trait network centered on stomatal conductance (G_s), adopting a conservative resource-use strategy. In contrast, herbaceous plants formed a network centered on leaf nitrogen content (N_mass), employing a rapid resource acquisition strategy to adapt to the ecotone environment. (3) The synergistic changes in leaf traits of different growth forms were affected by flooding in distinct ways. Integrating the leaf economics spectrum and adaptive evaluation values for each species can further our understanding of plant adaptation strategies in different flooding environments and guide species selection and configuration for aquatic–terrestrial ecotone restoration.