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The European mole Talpa europaea is common across much of Britain. It has a unique fossorial lifestyle, and evidence of its presence is readily identified through the presence of characteristic molehills. Although molehills are often a common sight in urban greenspaces, moles are remarkably understudied, with very few studies to date exploring the urban ecology of moles. Here, we investigate if factors such as greenspace (largely urban parks and playing fields) area, intensity of management, distance to nearest patch, amount of time the patch had been isolated from other green patches, and the amount of urbanization (constructed surfaces) surrounding the patch, influence the distribution and abundance of urban moles. Mole signs (hills and surface runs) were counted in all discrete urban greenspaces (excluding domestic gardens and one private golf course) within an 89.5 km2 area in the UK town of Reading. We found that 17 out of 59 surveyed sites contained moles, with their presence being recorded in greenspaces with a minimum patch area of approximately 0.1 km2 (10 ha). Where present, the abundance of mole territories in the greenspaces was associated with both the area of greenspace and degree of urbanization within 150 m of the patch boundary. While the former was not surprising, the latter outcome may be a consequence of sites with an increased risk of flooding being home to fewer moles, and the surrounding area is also less likely to be built upon. This case study highlights how choices made in designing urban green infrastructure will determine which species survive in urban areas long into the future.

Urban street greening structure plays a crucial role in promoting environmental justice and enhancing residents’ daily well-being, yet existing studies have primarily focused on vegetation quantity while neglecting how perception and governance interact to shape fairness. This study develops an integrated analytical framework that combines deep learning, machine learning, and spatial analysis to examine the impact of perceptual experience and socio-economic indicators on the equity of greening structure distribution in urban streets, and to reveal the underlying mechanisms driving this equity. Using DeepLabV3+ semantic segmentation, perception indices derived from street-view imagery, and population-weighted Gini coefficients, the study quantifies both the structural and perceptual dimensions of greening equity. XGBoost regression, SHAP interpretation, and Partial Dependence Plot analysis were applied to reveal the influence mechanism of the “Matthew effect” of perception and the Site governance responsiveness on the fairness of the green structure. The results identify two key findings: (1) perception has a positive driving effect and a negative vicious cycle effect on the formation of fairness, where positive perceptions such as beauty and safety gradually enhance fairness, while negative perceptions such as depression and boredom rapidly intensify inequality; (2) Site management with environmental sensitivity and dynamic mutual feedback to a certain extent determines whether the fairness of urban green structure can persist under pressure, as diverse Tree–Bush–Grass configurations reflect coordinated management and lead to more balanced outcomes. Policy strategies should therefore emphasize perceptual monitoring, flexible maintenance systems, and transparent public participation to achieve resilient and equitable urban street greening structures.

The urban forest is a green infrastructure system that delivers multiple environmental, economic, social and health services, and functions in cities. Environmental benefits of urban trees are well understood, but no review to date has examined how urban trees affect human health. This review provides a comprehensive summary of existing literature on the health impacts of urban trees that can inform future research, policy, and nature-based public health interventions. A systematic search used keywords representing human health, environmental health, and urban forestry. Following screening and appraisal of several thousand articles, 201 studies were conceptually sorted into a three-part framework. Reducing Harm, representing 41% of studies, includes topics such as air pollution, ultraviolet radiation, heat exposure, and pollen. Restoring Capacities, at 31%, includes attention restoration, mental health, stress reduction, and clinical outcomes. Building Capacities, at 28%, includes topics such as birth outcomes, active living, and weight status. The studies that were reviewed show substantial heterogeneity in purpose and method yet indicate important health outcomes associated with people’s exposure to trees. This review will help inform future research and practice, and demonstrates why urban forest planning and management should strategically promote trees as a social determinant of public health.

Summary The urban dimension of ecosystem services (ES) is underexposed, while the importance of ES for human well‐being is nowhere as evident as in cities. Urban challenges such as air pollution, noise and heat can be moderated by urban green space (UGS), simultaneously providing multiple other services. However, available methods to quantify ES cannot typically deal with the high spatial and thematic resolution land cover data that are needed to better understand ES supply in the urban context. This study derives methods to quantify and map a bundle of six ES as supplied by UGS, using land cover data with high spatial and thematic resolution, and applies these to the city of Rotterdam, the Netherlands. Land cover data comprise eight classes of UGS. Methods are derived from an evidence base on the importance of UGS types for the supply of each of the six ES that was built using literature review. The evidence base reveals that UGS types differ in their contribution to various ES, although the strength of the evidence varies. However, existing indicators for urban ES often do not discriminate between UGS types. To derive UGS‐specific indicators, we combined methods and evidence from different research contexts (ES, non‐ES, urban, non‐urban). Rotterdam shows high spatial variation in the amount of UGS present, and accounting for this in ES supply reveals that ES bundles depend on UGS composition and configuration. While the contribution of UGS types to ES supply differed markedly with UGS type and ES considered, we demonstrate that synergies rather than trade‐offs exist among the ES analysed. Synthesis and applications. Our findings underline the importance of a careful design of urban green space (UGS) in city planning for ecosystem services (ES) provision. Based on the latest insights on how different UGS provide ES, the methods presented in this study enable a more detailed quantification and mapping of the supply of ES in cities, allowing assessments of current supply of key urban ES and alternative urban designs. Such knowledge is indispensable in the quest for designing healthier and climate‐resilient cities. Our findings underline the importance of a careful design of urban green space (UGS) in city planning for ecosystem services (ES) provision. Based on the latest insights on how different UGS provide ES, the methods presented in this study enable a more detailed quantification and mapping of the supply of ES in cities, allowing assessments of current supply of key urban ES and alternative urban designs. Such knowledge is indispensable in the quest for designing healthier and climate‐resilient cities.

As cities attempt to ameliorate urban green inequities, a potential challenge has emerged in the form of green gentrification. Although practitioners are central to urban greening and associated gentrification, there has yet to be an exploration of practitioner perspectives on the phenomenon. We fill this gap with an online survey of 51 urban greening practitioners in Metro Vancouver and the Greater Toronto Area. Most respondents defined green gentrification as the displacement of vulnerable residents due to the installation or improvement of green space that attracts wealthy in-movers and increases property values. They were most likely to identify greening as driving green gentrification, with a minority identifying other systemic drivers with greening in a secondary role. Although 39 of 51 participants had some familiarity with green gentrification, most reported low confidence in their understanding of the concept, little evidence of using the concept in their work, and moderate concern that their work is implicated in green gentrification. The gentrification issues most encountered by practitioners were changes to neighbourhood character and uneven investment in public infrastructure, and those working in domains linked to planning, equity, and engagement were most likely to encounter gentrification issues. Practitioners experienced multiple barriers to addressing green gentrification, including limited institutional capacity, limited access to data and relevant information, policy/mandate restriction, and lack of engagement tools. Results indicate that practitioners have a moderate understanding of green gentrification but do not often use the concept in their work, despite their potential to contribute to or exacerbate it. This suggests some resistance to critiques of urban greening practice, a failure of scholarly critiques of urban greening to influence policy change, and the need for stronger research theory and research co-creation involving practitioners and academia.

Urban green spaces have many vital ecosystem services such as air cleaning, noise reduction, and carbon sequestration. Amid these great benefits from urban green spaces, the cooling effects via shading and evapotranspiration can mitigate the urban heat island effect. The impact of urban green spaces (UGSs) on the urban thermal environment in Beijing was quantified as a case study of metacities using four metrics: Land surface temperature (LST), cooling intensity, cooling extent, and cooling lapse. Three hundred and sixteen urban green spaces were extracted within the 4th ring road of Beijing from SPOT 6 satellite imagery and retrieved LST from Landsat 8 remote sensing data. The results showed that the cooling intensity of green spaces was generally more prominent in the areas with denser human activities and higher LST in this metacity. Vegetation density is always the dominant driver for the cooling effect indicated by all of the metrics. Furthermore, the results showed that those dispersive green spaces smaller than 9 ha, which are closely linked to the health and well-being of citizens, can possess about 6 °C of cooling effect variability, suggesting a great potential of managing the layout of small UGSs. In addition, the water nearby could be introduced to couple with the green and blue space for the promotion of cooling and enhancement of thermal comfort for tourists and residents. As the severe urban heating threatens human health and well-being in metacities, our findings may provide solutions for the mitigation of both the urban heat island and global climate warming of the UGS area customized cooling service.

Vitoria-Gasteiz has taken several urban greening actions such as the introduction of a ring of parks that connect the city’s surroundings, a sustainable mobility plan, and urban green structure strategies. Previous studies establish a connection to the importance of greening to mitigate the surface urban heat island (SUHI) and evaluate the effectiveness of these measures on urban climate. In this study, land surface temperature (LST), a remote sensing (RS) parameter, recorded by Landsat satellites (5, 7, and 8) was used to evaluate the effect of SUHI in Vitoria-Gasteiz between 1985–2021. The aim was to evaluate whether the urban greening actions influenced the local thermal conditions and, consequently, helped minimize the SUHI. Thirty sampling locations were identified, corresponding to different local climate zones (LCZ), at which LST data were extracted. A total of 218 images were processed and separated into summer and winter. Four of the 30 locations had, since 2003, on-site meteorological stations with regular air temperature (Tair) measurements which were used to validate the LST data. The results showed that Spearman’s correlation between Tair and LST was higher than 0.88 in all locations. An amount of 21 points maintained the same LCZ classification throughout the analysed period and nine underwent a LCZ transformation. The highest average temperature was identified in the city centre (urbanized area), and the lowest average was in a forest on the outskirts of the city. SUHI was more intense during the summer. A significant increase in SUHI intensity was identified in areas transformed from natural to urban LCZs. However, SUHI during satellite data acquisition periods has shown a minimal change in areas where sustainable practices have been implemented. RS was valuable for analysing the thermal behaviour of the LCZs, despite the limitation inherent in the satellite’s time of passage, in which the SUHI effect is not as evident.

Background Response and adaptation strategies of plants to the environment have always been the core issues in ecological research. So far, relatively little study exists on its functional traits responses to warming, especially in an urban environment. This information is the key to help understand plant responses and trade-off strategy to urban warming. Results We chose the common greening trees of mature age in Beijing ( Fraxinus pennsylvanica, Koelreuteria paniculata, and Sophora japonica ) as the research subjects, and used infrared heaters to simulate warming for three gradients of natural temperature (CK), moderate warming (T1) and severe warming (T2). Results showed that:(1) Leaf dry matter content (LDMC), chlorophyll content (CHL), leaf tissue density (LTD), and stomatal density (SD) all increased with temperature warming. Specific leaf area (SLA), stomatal size (SS), and stomatal aperture (SA) decreased with simulated warming. (2) SLA was extremely significantly negatively correlated with CHL, LDMC, LTD and SD ( P  < 0.01), and was extremely significantly positively correlated with SS ( P  < 0.01). SA was extremely negatively correlated with SD ( P  < 0.01), and was extremely significantly positively correlated with SS ( P  < 0.01). There was a significant positive correlation between LDMC and LTD ( P  < 0.01). This showed that urban greening trees adapted to the environment by coordinating adjustment among leaf functional traits. (3) Under the T1 treatment, the R 2 and slope among the leaf traits were higher than CK, and the significance was also enhanced. The correlation between leaf traits was strengthened in this warming environment. Conversely, it will weaken the correlation between leaf traits under the T2 treatment. Conclusion Our study demonstrated that there was a strong trade-off between leaf functional traits in the urban warming environment. Plants in the warming environment have adopted relatively consistent trade-offs and adaptation strategies. Moderate warming was more conducive to strengthening their trade-off potential. It is further verified that the global leaf economics spectrum also exists in urban ecosystems, which is generally tend to a quick-investment return type with the characteristics of thick leaves, strong photosynthetic capacity, low transpiration efficiency and long life in urban environments.

Significant differences in urban greening have occurred in Chinese cities, accompanied by China’s rapid urbanization. However, there are relatively few studies on the spatial differentiation of urban greening in China at the city level. In addition, there is no unanimous conclusion on the main factors influencing the spatial differentiation of urban greening. Based on 2014 emission inventory data from 289 cities, the spatial differentiation pattern and spatial correlation characteristics of the urban green space ratio, urban green coverage rate, and public green area per capita were calculated and analyzed using global and local Moran’s I . We then used ordinary least squares, spatial error model, spatial autoregression, and geographically weighted regression to quantify the impact and spatial variations of China’s economy on urban greening. The results showed (1) a significant spatial dependence and heterogeneity existed in urban greening values, and the patterns showed influences of both the stage of economic development and spatial agglomeration; (2) regression models revealed per capita GDP had a positive effect on the urban green space ratio and public green area per capita while the urbanization rate, secondary industry, urban land, and population density had opposite effects on these two greening indexes; and (3) geographically weighted regression revealed per capita GDP had a greater influence on urban greening in the northwestern region than in the southeastern region. The study could constitute a valuable reference for mid-to-long-term green space planning policy in diverse parts of China and could further assist in coordinating the development of urban greening and economic growth.

Street greening is widely recognized as influencing resident well-being and housing prices, and street-view imagery provides a fine-grained data source for quantifying urban microenvironments. However, existing research predominantly relies on single indicators such as the Green View Index (GVI) and overall green coverage/volume lacking a systematic analysis of how the hierarchical structure of trees, shrubs, and grass relates to housing prices. This study examines the high-density block context of Tianjin’s six urban districts. Using the Street Greening Space Structure (SGSS) dataset to construct greening structure configurations, we integrate housing-price data, neighborhood attributes, and 13,280 street-view images from the study area. We quantify how “visibility and hierarchical ratios” are capitalized on in the housing market and identify auditable threshold ranges and contextual gating. We propose an urban–forest structural system centered on visibility and hierarchical ratios that links street-level observability to ecosystem services. Employing an integrated framework combining Geographical-XGBoost (G-XGBoost) and SHapley Additive exPlanations (SHAP), we move beyond average effects to reveal structural detail and contextual heterogeneity in capitalization. Our findings indicate that tree visibility G_TVI is the most robust and readily capitalized price signal: when G_TVI increases from approximately 0.06 to 0.12–0.16, housing prices rise by about 8%–10%. Hierarchical structure is crucial: balanced tree–shrub ratios and moderate shrub–grass ratios translate “visible green” into functional green. Capitalization effects are environmentally conditioned—more pronounced along corridors with high centrality and accessibility—and are likewise common in dense East Asian metropolises (e.g., Beijing, Shanghai, Seoul, and Tokyo) and rapidly motorizing cities (e.g., Bangkok and Jakarta). These patterns suggest parametric prescriptions that prioritize canopy-corridor continuity and keep ratios within actionable threshold bands. We translate these findings into urban greening strategies that prioritize canopy continuity, under-canopy permeability, and maintainability, providing sustainability-oriented, parameterized guidance for converting urban greening structure into ecological capital for sustainable cities.