Urban Forest Research Articles

How do urban trees vary across the US? It depends on where and how you look

Urban forests provide ecosystem services important for regulating climate, conserving biodiversity, and maintaining human well‐being. However, these forests vary in composition and physiological traits due to their unique biophysical and social contexts. This variation complicates assessing the functions and services of different urban forests. To compare the characteristics of the urban forest, we sampled the species composition and two externally sourced traits (drought tolerance and water‐use capacity) of tree and shrub species in residential yards, unmanaged areas, and natural reference ecosystems within six cities across the contiguous US. As compared to natural and unmanaged forests, residential yards had markedly higher tree and shrub species richness, were composed primarily of introduced species, and had more species with low drought tolerance. The divergence between natural and human‐managed areas was most dramatic in arid climates. Our findings suggest that the answer to the question of “what is an urban forest” strongly depends on where you look within and between cities.

Changes in the soil microenvironment during ecological restoration of forest parks in megacities

Forest parks in megacities are pivotal in boosting biodiversity, purifying air, and offering essential green areas for community leisure and mental health amidst the hustle and bustle of cities. Yet, these vital oases encounter severe difficulties, including habitat degradation, contamination, and urbanization pressures, jeopardizing their preservation and the crucial ecological advantages they offer. The soil’s characteristics and its microbial inhabitants are fundamental in the cycling of nutrients and the well-being of plants, positioning them as central elements in restoration efforts. Nonetheless, the complex interplay among plant, soil, and microbial relationships during the restoration of forest ecosystems in megacities is still not well comprehended. This study aimed to investigate the interactions between plant-soil-microbial dynamics in different ecological restoration modes and construct assessment systems to evaluate the quality of restoration modes in the forest parks. The study identified a total of 25 distinct types of forests damaged by three main factors (farmland, highway, and quarrying) in Chongqing Taisiya Forest Park, and found that long-term natural restoration significantly increased soil properties in these forests. Additionally, an in-depth microbial sequencing analysis showed that Proteobacteria and Ascomycota were the major bacterial and fungal phyla dominant in the restoration process in the urban forests. Further correlation analysis showed that soil microbial diversity positively correlated with plant diversity, with a stronger correlation observed for bacterial communities compared to fungi. The comprehensive evaluation index results for the different forest types revealed varying degrees of restoration success. Collectively, our findings underscore the importance of forest attributes and soil microbial diversity in forest ecosystem restoration and provide valuable insights for designing effective restoration strategies in similar ecosystems.

A Hybrid Method for Individual Tree Detection in Broadleaf Forests Based on UAV-LiDAR Data and Multistage 3D Structure Analysis

Individual tree detection and segmentation in broadleaf forests have always been great challenges due to the overlapping crowns, irregular crown shapes, and multiple peaks in large crowns. Unmanned aerial vehicle (UAV)-borne light detection and ranging (LiDAR) is a powerful tool for acquiring high-density point clouds that can be used for both trunk detection and crown segmentation. A hybrid method that combines trunk detection and crown segmentation is proposed to detect individual trees in broadleaf forests based on UAV-LiDAR data. A trunk point distribution indicator-based approach is first applied to detect potential trunk positions. The treetops extracted from a canopy height model (CHM) and the crown segments obtained by applying a marker-controlled watershed segmentation to the CHM are used to identify potentially false trunk positions. Finally, the three-dimensional structures of trunks and branches are analyzed at each potentially false trunk position to distinguish between true and false trunk positions. The method was evaluated on three plots in subtropical urban broadleaf forests with varying proportions of evergreen trees. The F-score in three plots ranged from 0.723 to 0.829, which are higher values than the F-scores derived by a treetop detection method (0.518–0.588) and a point cloud-based individual tree segmentation method (0.479–0.514). The influences of the CHM resolution (0.25 and 0.1 m) and the data acquisition season (leaf-off and leaf-on) on the final individual tree detection result were also evaluated. The results indicated that using the CHM with a 0.25 m resolution resulted in under-segmentation of crowns and higher F-scores. The data acquisition season had a small influence on the individual tree detection result when using the hybrid method. The proposed hybrid method needs to specify parameters based on prior knowledge of the forest. In addition, the hybrid method was evaluated in small-scale urban broadleaf forests. Further research should evaluate the hybrid method in natural forests over large areas, which differ in forest structures compared to urban forests.

Can species climate niche predict canopy growth, functional traits and phenotypic plasticity in urban trees?

There is much uncertainty in how climate change will impact the performance of urban trees. Climate niche modelling predicts that many urban tree species may become unsuitable in future climates, but this has rarely been tested in cities. Broad planting of diverse tree species in different cities provides the opportunity to test climate niche predictions. Here we investigated if the climate of origin of 14 urban tree species influenced tree growth, trait expression, and phenotypic plasticity. We determined climate niche limits for all species and measured canopy growth rates of individual trees from 2013 to 2021 in the two largest Australian cities: subtropical Sydney, and temperate Melbourne. Six functional traits including leaf water potential at turgor loss point (TLP), wood density (WD), leaf dry matter content (LDMC), specific leaf area (SLA), carbon isotope composition (δ13C) and Huber value (HV) were measured in both cities. Trees planted outside their climate niche limits had lower growth than trees planted inside their climate niche in the temperate but not subtropical city. Species with lower MAP of origin (i.e., drier) had faster canopy growth in both cities. Species with low MAP and high heat moisture index (HMI) at their origin had more negative TLP and greater WD, indicating species from drier environments maintain their high drought tolerance in cities. Trees planted in drier Melbourne had more negative TLP, higher WD and higher LDMC than in Sydney, demonstrating phenotypic plasticity in urban trees. Wetter origin species showed greater phenotypic plasticity in TLP, WD and δ13C. Canopy RGR was negatively related with δ13C reflecting a strong impact of stomatal behaviour on urban tree growth. Our study provides limited support that species climate niche limits reliably predict urban tree growth, so we caution against solely using climate niche matching and advocate for inclusion of functional traits when selecting urban tree species.

The Added Value of Urban Trees (Tilia tomentosa Moench, Fraxinus excelsior L. and Pinus nigra J.F. Arnold) in Terms of Air Pollutant Removal

The serious densification of human settlements necessitates an increase in the role and importance of green infrastructures in the overall functioning of urban ecosystems. Accordingly, the aim of the present study was to (1) assess the efficiency of air pollutant removal (potentially toxic elements) of three common ornamental trees (Tilia tomentosa Moench, Fraxinus excelsior L. and Pinus nigra J.F. Arnold) and (2) model the air quality regulatory services (removal of PM10, PM2.5 and NO2). Three different approaches were applied—enrichment factor (EF) and metal accumulation factor (MAI) per tree species, as well as simulation modeling for the whole urban forest. The MAI values of the three studied species were found to be very similar, in the range of 22.35 to 23.08, which suggests that these species could be a good choice for planting in urban areas with worsened air quality. The highest EF values were observed for U (3–18), followed by As (1.6–2.56) and Sr (0.87–2.46). The potential of urban forests in countering air pollution was highlighted by three simulated scenarios for PM10, PM2.5 and NO2 removal. The highest removal efficiency was calculated for evergreen species, followed by the mixed composition of deciduous (90%) and evergreen trees (10%), and the scenario with wholly deciduous trees had the lowest one. The contribution of nature-based solutions in meeting air quality standards and enhancing resilience in urban areas was clearly demonstrated. The functional complementarity of the different functional tree groups (coniferous, evergreen and deciduous broad-leaved species) was proven to be crucial for the support of both functional stabilities of the phytocenosis under diverse climatic conditions and during the change of seasonal cycles in the vegetation.

Características de dormideros comunales de Loros Habladores (<i>Amazona aestiva</i><i></i><i></i>) en la Ciudad Autónoma de Buenos Aires, Argentina: una población fuera de su rango de distribución natural

Psittacines are often illegally captured and sold as pets. The historical capture of specimens and the deforestation of the native forest have had negative consequences on psittacine species at a global level. Locally, individuals retained as pets and subsequently released have been able to establish outside their native range, and may even become invasive. The Turquoise-fronted Parrot (Amazona aestiva) is wanted as a pet for its ability to imitate sounds. Specimens released in the 1980s and 1990s in the City of Buenos Aires, established a population 750 km of the limit of their natural range. In 2015 and 2018, we detected roosts in the neighborhood of Saavedra and Parque Chas-Agronomía respectively. In this work we aimed to gain new knowledge about this population, its feeding sites, roosts and behavior. The two roosts studied were located on urban trees (mainly Platanus acerifolia), and are the only ones recorded so far in Buenos Aires. We recorded an average of 243 individuals in 2021 and 180 in 2022. We recorded 12 sites within a 20 km radius of the active roost where the Turquoise-fronted Parrot was observed. Parrots leave the roost at dawn and return at dusk. They consume fruits of Platanus acerifolia, Melia azedarach, Eriobotrya japonica, Styphnolobium japonicum, among others. These roosts may constitute a new resource for urban ecotourism, giving value to this species that persists outside its natural range where it is threatened.

Local climate, air quality and leaf litter cover shape foliar fungal communities on an urban tree

Foliar fungi on urban trees are important for tree health, biodiversity and ecosystem functioning. Yet, we lack insights into how urbanization influences foliar fungal communities. We created detailed maps of Stockholm region’s climate and air quality and characterized foliar fungi from mature oaks (Quercus robur) across climatic, air quality and local habitat gradients. Fungal richness was higher in locations with high growing season relative humidity, and fungal community composition was structured by growing season maximum temperature, NO2 concentration and leaf litter cover. The relative abundance of mycoparasites and endophytes increased with temperature. The relative abundance of pathogens was lowest with high concentrations of NO2 and particulate matter (PM2.5), while saprotrophs increased with leaf litter cover. Our findings show that urbanization influences foliar fungi, providing insights for developing management guidelines to promote tree health, prevent disease outbreaks and maintain biodiversity within urban landscapes.

Risk of wind destruction to urban trees: Prediction workflow and relative importance of influencing factors

During typhoons, risk of wind destruction to trees is harder to predict for trees in urban areas than for those in plains, and the influencing factors are more intricate. This study integrated a simplified HWIND mechanistic model for trees, computational fluid dynamics simulations for airflow, and quantified tree morphology indicators to predict the risk of wind destruction to urban trees. The workflow was demonstrated using three typical streets in Guangzhou, China. The workflow was verified based on the observed damage states of case trees in the study areas after Typhoon Mangkhut. Original critical wind speed in plains (CWSP(10)) and urban regions (CWS(10)) at a height of 10 m were introduced to evaluate the wind resistance and destruction risk to urban trees. The relative influence of various factors on CWS(10) and CWSP(10) was evaluated through Relative Weight Analysis and Random Forest. For urban trees with uprooting as the primary destruction mode, wind resistance is mainly influenced by tree height and total root-soil length in terms of tree morphology indicators, while the decisive factor affecting wind destruction risk is the “built environment indicator,” defined as BEI=CWS(10)/CWSP(10).

Variability of Concentrations of Potentially Toxic Metals in the Topsoil of Urban Forest Parks (Southern Poland)

Forest ecosystems and urban parks are an integral part of the natural environment and the natural system of a city, where they form a mosaic of habitats resulting from the variation in soil cover due to human activities. The study was conducted in urban forests in five urban parks in Upper Silesia (southern Poland) and investigated the chemical properties and content of potentially toxic metals (PTMs) in the topsoil, which had an average thickness of 15 cm for all samples. The soil reaction ranged from acidic (pH = 4.7–5.1, in KCl) to slightly acidic (pH = 5.6, to neutral—6.6–7.2) at most sites. The organic carbon (OC) content was relatively high at all sites, ranging from 1.19 to 14.3%, with the highest total nitrogen (Nt) content being 0.481%. The average total phosphorus (Pt) content in the parks ranged from 310 mg kg−1 to 684 mg kg−1, while the highest values were 1840 mg kg−1. The total Cr, Cu, Co and Ni content was within acceptable limits, while the Zn, Pb, Cd, As, Sr and Ba exceeded acceptable standards. In terms of content, Zn dominated the PTMs at each site (Zn > Pb > Ba > Sr > Cu > Cr > As > Ni > Cd > Co), while Ba and Pb alternated in taking second place (Zn > Ba > Pb > Sr > Cu > Cr > Ni > As > Co > Cd). Environmental indicators, such as the geoaccumulation index (Igeo), enrichment factor (EF) and potential ecological risk index (RI), showed that the analyzed soils are highly contaminated with PTMs. Among the sources of pollution in the urban forest are low emissions from coal combustion, industrial activities, water runoff from streets and proximity to transportation routes. Identification of PTM levels in urban parks will provide valuable information on the behavior of these metals, which is important in sustainable development and can help evaluate the local spatial development plans of urbanized areas.

How Social Media Data Mirror Spatio-Temporal Behavioral Patterns of Tourists in Urban Forests: A Case Study of Kushan Scenic Area in Fuzhou, China

Exploring the spatial distribution of tourist attractions and comprehending the spatio-temporal behaviors of tourists within tourist attractions can provide local planning agencies, destination marketing organizations, and government departments with essential evidence for decision-making processes. This study examines the spatio-temporal behavior patterns of tourists in the Kushan Scenic Area by analyzing GPS trajectory data acquired from social media platforms. The investigation primarily utilizes three research methodologies: grid analysis, Markov chain, and K-means clustering. The grid analysis results reveal three spatial distribution patterns within the scenic area, while the outcomes from the Markov chain and K-means clustering delineate six tourist movement patterns, along with three choices regarding travel time. This finding holds significant practical implications for enhancing the attractiveness of scenic areas, optimizing spatial layout, and improving tourists’ experiences.

Soil respiration across a variety of tree-covered urban green spaces in Helsinki, Finland

Abstract. As an increasing share of the human population is being clustered in cities, urban areas have swiftly become the epicentres of anthropogenic carbon (C) emissions. Understanding different parts of the biogenic C cycle in urban ecosystems is needed in order to assess the potential to enhance their C stocks as a cost-efficient means to balance the C emissions and mitigate climate change. Here, we conducted a field measurement campaign over three consecutive growing seasons to examine soil respiration carbon dioxide (CO2) fluxes and soil organic carbon (SOC) stocks at four measurement sites in Helsinki, representing different types of tree-covered urban green space commonly found in northern European cities. We expected to find variation in the main drivers of soil respiration – soil temperature, soil moisture, and SOC – as a result of the heterogeneity of urban landscape and that this variation would be reflected in the measured soil respiration rates. In the end, we could see fairly constant statistically significant differences between the sites in terms of soil temperature but only sporadic and seemingly momentary differences in soil moisture and soil respiration. There were also statistically significant differences in SOC stocks: the highest SOC stock was found in inactively managed deciduous urban forest and the lowest under managed streetside lawn with common linden trees. We studied the impacts of the urban heat island (UHI) effect and irrigation on heterotrophic soil respiration with process-based model simulations and found that the variation created by the UHI is relatively minor compared to the increase associated with active irrigation, especially during dry summers. We conclude that, within our study area, the observed variation in soil temperature alone was not enough to cause variation in soil respiration rates between the studied green space types, perhaps because the soil moisture conditions were uniform. Thus, irrigation could potentially be a key factor in altering the soil respiration dynamics in urban green space both within the urban area and in comparison to non-urban ecosystems.

Structure and Function of Urban Forests and Green Spaces in a Changing World

Green infrastructures (e.g., forests, parks, and other types of green spaces) in urban areas provide people with a huge volume of ecosystem benefits. However, the quality of urban green infrastructure varies among cities in different countries/regions, and key ecological processes, maintaining mechanisms, and policy decision routes remain unclear. Here, we recognize four themes that link studies from the Asia-Pacific and European regions presented in this Editorial: (1) indicators and services of urban green spaces; (2) assembly of and changes in diverse plant communities; (3) utilization and evaluation of urban forest landscape; and (4) patterns and drivers of urban agro-forestry systems. These investigations enlarge our understanding on the theoretical exploration and methodological innovation of urban forestry studies in response to the changing environment, and shed some light on routes to achieve sustainable development goals in the context of rapid urbanization.

Comparison of biogenic volatile organic compounds emissions from representative urban tree species in South Korea and evaluation of standard emission rate models

Although trees generally help alleviate global warming, they generate biogenic volatile organic compounds (BVOCs) that may contribute to air pollution and exacerbate climate change. To estimate BVOCs emission rates, several models have been widely used to calculate the standard emission rate (ERs) that takes temperature and light intensity into account. In this study, the effects of temperature and light intensity on the isoprene and monoterpene emissions from various tree species were investigated. Four broad-leaved trees (Platanus occidentalis, Quercus mongolica, Zelkova serrata, and Acer palmatum) and three coniferous trees (Pinus densiflora, Metasequoia glyptostroboides, and Pinus koraiensis) were investigated in August 2022 for the comparison by the species. Emissions from Pinus densiflora were also measured in May for comparison with different climate conditions. Platanus occidentalis revealed the highest emission of isoprene, followed by Quercus mongolica, Zelkova serrata, and Acer palmatum. It was found that the isoprene emissions from Zelkova serrata and Quercus mongolica had a stronger correlation with light intensity than those from Platanus occidentalis. In contrast, the isoprene emissions from Platanus occidentalis exhibited the strongest correlation with temperature compared to other trees concerned. The monoterpene emission from Metasequoia glyptostroboides showed the highest correlation with light intensity (r2 = 0.662). Among the monoterpenes, α-pinene was the most affected by light intensity. Pinus densiflora was affected more by light intensity in May. The ERs estimation using the G93 model confirmed this pattern. Therefore, this study suggests that both light and temperature be taken into account in order to obtain more reliable ERs data of monoterpenes.

Phytoremediating the air down under: Evaluating airborne particulate matter accumulation by 12 plant species in Australia

AbstractAtmospheric particulate matter (PM) is the most inhaled hazardous air pollutant that can cause adverse health impacts. Plants can remove such contaminants and act as biological filters through phytoremediation. In this study, we screened 12 Australian native species (two deciduous trees, three evergreen shrubs, and seven evergreen trees) growing in three regions to determine their potential in accumulating leaf surface (SPM) and in‐wax PM (WPM). Among the screened species, Lagunaria patersonia (139.22 μg cm−2) was the most effective PM accumulator, followed by Ficus obliqua (131.02 μg cm−2). L. patersonia is an Australian native tree with a dense crown that can efficiently trap PM due to air turbulence between its leaves and branches; broad leaves with a rough texture enhance the plant's ability to trap PM. On the contrary, morphological characteristics like evergreen leaves with hairy appendages may act as an efficient trap for PM in F. obliqua. Due to smoother leaves, the least effective species were F. rubignosa and Eucalyptus saligna. In addition to leaf shape, leaf structures and micromorphology influence PM accumulation. For instance, Pittosporum undulatum accumulated more PM due to its wrinkled and folded leaf structures despite a significantly lower waxes layer. The findings highlight the importance of planting efficient PM accumulator species to shield vulnerable areas from pollution and decrease human exposure to pollutants. The sink capacity of these species can be used in urban tree planning to combat air pollution and improve air quality.

Implementation of Ecotourism in PIK Mangrove to Improving the Interest Tourism of Urban Society

Implementation of the ecotourism concept that is appropriate to carry ecological and socio-economic functions that can be applied in the tourist destination area. This is inseparable from the interference from the tour, the government, the private sector that manages tourism and the surrounding community. One of the uses of ecotourism in urban areas can be applied by utilizing the maximum lakes, situ, urban forests, mangrove forests and various enriched areas that are suitable for use as ecotourism locations. Mangrove tourism in Pantai Indah Kapuk (PIK) has been included in nature tourism, it's just that if it has to do with tourism defense, the maximum concept of ecotourism can be applied to PIK mangrove forests. The research method used was case study with documentation consisting of data obtained from related parties and reporting used in the community while the method of data analysis was carried out using qualitative descriptive methods that describe and explain in full the ones explained and explained. Urban areas that appear to be busy and full of complexity save tourism with an interesting concept of ecotourism and will be maximized if it gets convenience from the government and the private sector.

Meteorological, chemical and biological evaluation of the coupled chemistry-climate WRF-Chem model from regional to urban scale. An impact-oriented application for human health

Extreme climatic conditions, like heat waves or cold spells, associated to high concentrations of air pollutants are responsible for a broad range of effects on human health. Consequently, in the recent years, the question on how urban and peri-urban forests may improve both air quality and surface climate conditions at city-scale is receiving growing attention by scientists and policymakers, with previous studies demonstrating how nature-based solutions (NBS) may contribute to reduce the risk of population to be exposed to high pollutant levels and heat stress, preventing, thus, premature mortality. In this study we present a new modeling framework designed to simulate air quality and meteorological conditions from regional to urban scale, allowing thus to assess the impacts of both air pollution and heat stress on human health at urban level. To assess the model reliability, we evaluated the model's performances in reproducing several relevant meteorological, chemical, and biological variables. Results show how our modeling system can reliably reproduce the main meteorological, chemical, and biological variables over our study areas, thus this tool can be used to estimate the impact of air pollution and heat stress on human health. As an example of application, we show how common heat stress and air pollutant indices used for human health protection change when computed from regional to urban scale for the cities of Florence (Italy) and Aix en Provence (France).

Application of multi-temporal satellite imagery for urban tree species identification

Accurate tree inventories are critical for urban forest management but challenging to obtain, as many urban trees are on private property (backyards, etc.) and are excluded from public inventories. Here, we examined the feasibility of tree species identification in a large heterogenous urban area (>850 km2) by using multi-temporal PlanetScope images (3.2 m resolution, multi-spectral) and inventory data from more than 20,000 ground observations within the urban forest of the Greater Chicago area. Our approach achieved an overall classification accuracy of 0.60 and 0.71 for 18 species and ten genera, respectively, but varied from moderate to high for certain species (0.59–0.92) and genera (0.61–0.91). In particular, we identified key host tree species (Fraxinus americana, F. pennsylvanica, and Acer saccharinum) for two damaging invasive insects, emerald ash borer (EAB, Agrilus planipennis) and Asian longhorn beetle (ALB, Anoplophora glabripennis), with over 0.80 accuracies. In addition, we demonstrated that including images from the autumn months (September–November), either for a single-season model or a combined multiple-season model, improved the identification accuracy of temperate deciduous trees. Further, the high classification accuracy of support vector machine (SVM) over random forest (RF) and neural network (NN) approaches suggests that future work might benefit from comparing multiple classification methods to select the approach that maximizes species classification accuracy. Our study demonstrated the potential for applying multi-temporal high-resolution images in urban tree classification, which can be used for urban forest management at a large spatial scale.

Synthesis and evaluation of seamless, large-scale, multispectral satellite images using Generative Adversarial Networks on land use and land cover and Sentinel-2 data

ABSTRACT Artificial intelligence (AI) began to make its way into geoinformation science several decades ago and since then has constantly brought forth new cutting-edge approaches for diverse geographic use cases. AI and deep learning methods have become essential approaches for land use and land cover (LULC) classifications, which are important in urban planning and regional management. While the extraction of LULC information from multispectral satellite images has been a well-studied part of past and present research, only a few studies emerged about the recovery of spectral properties from LULC information. Estimates of the spectral characteristics of LULC categories could enrich LULC forecasting models by providing necessary information to delineate vegetation indices or microclimatic parameters. We train two identical Conditional Generative Adversarial Networks (CGAN) to synthesize a multispectral Sentinel-2 image based on different combinations of open-source LULC data sets. Large-scale synthetic multispectral satellite images of the administrative region of Bonn and Rhein-Sieg in Germany are generated with a Euclidean distance-based patch-fusion method. The approach generated a realistic-looking satellite image without noticeable seams between patch borders. Based on several metrics, such as difference calculations, the spectral information divergence (SID), and the Fréchet inception distance (FID), we evaluate the resulting images. The models reach mean SIDs as low as 0.026 for urban fabrics and forests and FIDs below 90 for bands B2 and B5 showing that the CGAN is capable of synthesizing distinct synthetic features matching with features typical for respective LULC categories and manages to mimic multispectral signatures. The method used in this paper to generate large-scale synthetic multispectral satellite images can be used as an approach to support scenario-oriented sustainable urban planning.

A study of street trees and their effects on pedestrians’ perceptions during summer

Poor thermal and light climates can have significant negative effects on human living qualities. Exploring sustainable ways to address these issues is an urgent task, and at the street level, trees pose a potential solution. This study aimed to determine the effect of street trees on pedestrians’ physiological comfort under different conditions. This was accomplished by field surveys, including questionnaires distributed at several forested streets in the Qingbaijiang District (QBD), a suburban area of Chengdu, China. Data analysis showed that people had different responses towards either physical or meteorological factors. They responded differently to various environmental factors, and the responses varied over physical and meteorological contexts. It was found that pedestrians’ neutral temperature and lighting levels were 28.64 °C, as indicated by physiologically equivalent temperature (PET, °C), and 0.91 klx, as indicated by illumination (klx). The percentage of people in favor of larger tree crowns increased considerably for PET (from 60 % at 30 °C to 90 % at 45 °C) and illumination (from 30 % at 0 klx to 100 % at 20 klx) elevations under small-sized trees. People preferred larger crowns and shorter trunks as they made them more comfortable. Their responses were also different for various PETs and daily periods. This is evident from the change in either thermal sensation vote (TSV) or overall comfort vote (OCV). The increase of either PET or illumination might result in TSV increase and OCV decrease. In relative terms, tree crown sizes (diameter, TCD) had a significant influence on pedestrians’ comfort. Increasing TCD by 1 m resulted in a TSV reduction of 0.449 and/or an OCV increase of 0.475 (sig. < 0.001). Results from this study may aid in future urban design and forestation works with the goal of improving pedestrians’ comfort.

Centering Community Perspectives to Advance Recognitional Justice for Sustainable Cities: Lessons from Urban Forest Practice

Cities worldwide are grappling with complex urban environmental injustices. While environmental justice as a concept has gained prominence in both academia and policy, operationalizing and implementing environmental justice principles and norms remains underexplored. Notably, less attention has been given to centering the perspectives and experiences of community-based actors operating at the grassroots level, who can inform and strengthen urban environmental justice practice. Through ethnographic, participant-as-observer methods, interviews, and geovisualizations, this study explores the perspectives, experiences, knowledge, and practices of community-based urban forest stewards in Philadelphia, Pennsylvania (United States) who are invested in addressing environmental injustices through urban tree-planting and stewardship. Interviewees were asked how they were addressing issues of distribution, procedure, and recognition in urban forest planning and practice, as well as the socio-political and institutional factors that have influenced their perspectives and practices. Particular attention is given to how urban forest stewards implement recognitional justice principles. Findings from this study exposed several complex socio-political challenges affecting steward engagement in community-led tree initiatives and the broader pursuit of environmental justice, including discriminatory urban planning practices, gentrification concerns, underrepresentation of Black and Latinx voices in decision-making, volunteer-based tree-planting models, and tree life cycle costs. Nevertheless, urban forest stewards remain dedicated to collective community-building to address environmental injustices and stress the importance of recognizing, listening to, dialoguing with, and validating the perspectives and experiences of their neighbors as essential to their process.