Landscape and Urban Planning 236 (2023) 104778 Contents lists available at ScienceDirect Landscape and Urban Planning journal homepage: www.elsevier.com/locate/landurbplan Socioeconomics explain tree diversity, abundance, and composition in the compact city of Barcelona, Spain Josep Padullés Cubino a, b, *, Javier Retana a, b a Autonomous University of Barcelona, 08193 Cerdanyola del Vallès, Spain b Centre for Ecological Research and Forestry Applications (CREAF), 08193 Cerdanyola del Vallès, Spain H I G H L I G H T S • In 2021, street trees represented 67% of the public trees in Barcelona. • Tree richness and abundance was positively related to life expectancy. • Wealthier neighborhoods had a lower tree species richness in public spaces. • Tree composition responded to demographic and socioeconomic gradients. A R T I C L E I N F O A B S T R A C T Keywords: Trees are frequently unevenly distributed in urban areas, and their diversity, abundance, and composition vary Beta-diversity spatially. Some studies have shown that the unequal distribution of urban trees can be associated with de­ Environmental justice mographic and socioeconomic factors. However, most studies have been conducted in diffuse urban systems Life expectancy using remotely-sensed tree cover within single or aggregated land-use types. We examined if the relationship Luxury effect between tree diversity, abundance, composition, and socioeconomic factors varied across land-use types (parks, Urban ecology Woody species streets, zonal areas, and total) in the compact city of Barcelona, Spain. We calculated tree species richness and abundance across 73 neighborhoods using 229,962 geo-referenced records of individual trees sampled in 2021. Life expectancy positively explained tree richness and abundance across land-use types, reinforcing that access to urban green infrastructure promotes longer life spans. In contrast, income did not positively explain tree richness or abundance, indicating that tree distribution does not directly result in biodiversity and green space in­ equalities for disadvantaged groups in terms of income. Total tree composition across neighborhoods responded to socioeconomic gradients, evidencing that neighborhood appearances are socially stratified. Street tree abundance increased in densely populated neighborhoods, possibly because intense street tree plantings in these neighborhoods compensate for the lack of other green infrastructure. Urban tree planting, particularly in streets, can be an effective strategy to increase green spaces in compact cities to overcome the disparities resulting from the unequal distribution of urban vegetation. Long-term data on socioeconomic factors and urban tree distri­ bution are necessary to determine how social stratification affects urban diversity. 1. Introduction (Kendal et al., 2012; Avolio et al., 2018), leading to inequality in the provision of tree-related ecosystem services and disservices. Govern­ Urban trees are the main component of urban vegetation and deliver ment policies, such as those that mandate the planting and removal of key ecosystem services, including several health, social, and economic trees in public open spaces and streetscapes, can determine the distri­ benefits to urban residents (Roy et al., 2012; Morgenroth et al., 2016; bution of urban trees (Conway & Urbani, 2007). Therefore, disen­ Salmond et al., 2016). Trees in cities can also result in ecosystem dis­ tangling the factors associated with urban tree distribution can support services causing harm, nuisances, and costs to urbanites (Lyytimäki, the creation and execution of appropriate strategies to promote the fair 2017). However, urban vegetation is not equally distributed in cities distribution of urban biodiversity and green space. * Corresponding author at: Centre for Ecological Research and Forestry Applications (CREAF), 08193 Cerdanyola del Vallès, Spain. E-mail addresses: padullesj@gmail.com (J. Padullés Cubino), Javier.Retana@uab.cat (J. Retana). https://doi.org/10.1016/j.landurbplan.2023.104778 Received 19 November 2022; Received in revised form 10 April 2023; Accepted 15 April 2023 Available online 22 April 2023 0169-2046/© 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). J. Padullés Cubino and J. Retana Landscape and Urban Planning 236 (2023) 104778 Theories to explain spatial patterns of urban tree distribution within (Baró et al., 2014) and showed that higher ecosystem service provision cities emphasize the relevance of socioeconomic and urban form factors. by street trees was linked to specific vulnerable groups, particularly Among the first group, income has been proposed as a key factor related elderly residents (Baró et al., 2019). We aim to answer three research to urban tree diversity, with wealthier neighborhoods hosting land­ questions: (1) Does urban tree diversity, abundance, and composition scapes with more species (Talarchek, 1990; Avolio et al., 2015; 2018), a change between land-use types? (2) Are urban tree diversity, abun­ phenomenon commonly known as the “luxury effect” (Hope et al., 2003; dance, and composition related to neighborhood demographic and so­ Leong et al., 2018). Similarly, affluent neighborhoods frequently have cioeconomic factors? (3) Do these relationships vary between land-use more tree canopy cover (Gerrish & Watkins, 2018) and a higher abun­ types? dance of street trees (Anderson et al., 2023; Lin et al., 2021) than impoverished neighborhoods. Previous research has also found that tree 2. Materials and methods cover is negatively associated with population density (Clarke et al., 2013; Pham et al., 2013) and the proportion of minority residents 2.1. Study area (Watkins & Gerrish, 2018), and positively associated with education (Luck et al., 2009; Kendal et al., 2012; Threlfall et al., 2022) and This study focuses on the municipality of Barcelona (Spain). The city neighborhood age (Lowry et al., 2011). However, empirical studies have is located in the north-eastern Iberian Peninsula along the Mediterra­ also demonstrated that the direction and strength of the associations nean Sea shore (41◦ 23′ 3′′ N; 2◦ 10′ 34′′ E; Fig. 1a). Barcelona is the second between socioeconomic factors and tree cover vary amongst cities (Riley largest city by population in the country and one of the most densely & Gardiner, 2020). It is also unclear if tree composition in neighbor­ populated cities in Europe (~16,000 hab/km2). In recent decades, large- hoods with comparable socioeconomic characteristics remains similar scale development demands have forced the conversion of a large (but see Avolio et al., 2018). fraction of green and agricultural land. The rapid urbanization period Among the second group of urban form factors, land-use type ended with the Olympic Games’ urban development plans in 1992, strongly determines urban tree distribution (Bourne & Conway, 2013; which nearly completely depleted vacant open spaces (Huertas & Avolio et al., 2018). City landscapes frequently consist of a mosaic of Huertas, 2004). Barcelona has 73 neighborhoods distributed among ten several public and private land-use types with contrasting vegetation, districts (Fig. 1). resulting in differences in plant diversity, abundance, and composition Urban green space in Barcelona is not uniformly distributed (Fig. 1b; within urban areas (Aronson et al., 2017). These urban land-use types Barcelona City Council, 2017). The city has about 7 m2 of green space include streets, vacant lots, parks, or residential gardens. Because per resident (~1,100 ha). However, the high density of trees in the different land-use types provide various economic and social functions streets (~100 street trees per 1,000 residents) helps to offset this lack of and typically respond to multiple landscaping goals, they can be used as green space (Baró et al., 2014). With a few notable exceptions, including research units to examine how socioeconomic factors and public the city’s first urban park (Ciutadella Park, built in 1872), most of the decision-making affect urban tree distribution (Cheng et al., 2022). green infrastructure dates back to the 1980s. Most trees in city parks are, Moreover, environmental justice and political ecology research contend therefore, relatively young. that policies that frequently generate socioeconomic inequality impact Barcelona wants to expand the tree cover in the city by 5% before tree distribution. This inequality is more pronounced in public land­ 2037 while maximizing ecosystem service provision (Barcelona City scapes like streets or parks (Heynen et al., 2006; Landry & Chakraborty, Council, 2017). Furthermore, the city intends to increase urban green 2009). At the neighborhood scale, the unique set of street and park tree space by 1 m2 per resident and ensure that at least 40% of tree species drivers should translate into contrasting species compositions between will be climate-adapted through the climate action plan (Barcelona City these urban land-use types (Jim, 1993; Kirkpatrick et al., 2011). Council, 2018). Tree and shrub plantings are programmed in parks and While previous studies have shown that urban tree distribution is gardens to enrich the woody stratum, replace losses and increase associated with socioeconomic factors, the number of measures biodiversity (Barcelona City Council, 2021). employed to analyze this distribution and the variety of locations analyzed have been constrained (Kendal et al., 2012; Avolio et al., 2.2. Study units 2015). Most studies have been conducted in diffuse cities in North American cities using remote sensing data on tree cover within single or We considered all administrative city neighborhoods as study units aggregated land-use types (e.g., Riley & Gardiner, 2020; Locke et al., (Fig. 1). The administrative neighborhoods in Barcelona were estab­ 2021). However, diversity metrics, such as the number of species, can be lished in 2006 by grouping several smaller historical neighborhoods. unrelated to tree cover or abundance. The number of species (or species Barcelona has 73 neighborhoods ranging from 12 to 1,424 ha and a richness) is a key characteristic of ecosystems that can increase their mean size of 139 ± 208 ha. In 2021, the average population in the adaptability and resilience (Folke et al., 1996). Furthermore, neigh­ neighborhoods was 22,744 ± 14,735 (~257 inhabitants/hectare). borhoods with contrasting demographic and socioeconomic character­ Neighborhoods differed in residential occupancy (Appendix S1: istics probably have contrasting tree compositions independently of the Figure S1.2). Although neighborhoods in Barcelona are subdivided into number of species. Studies comparing complementary metrics of tree census tract units, some demographic and socioeconomic variables used diversity, abundance, and composition across land-use types and in this study, such as household income, were only available at the neighborhoods with different demographic and socioeconomic envi­ neighborhood level. ronments are necessary to determine whether generalizations can be made from the proposed theories to explain observed patterns, espe­ 2.3. Tree data cially in highly compact cities. In this study, we examined spatial patterns of tree diversity (tree We obtained tree occurrence data in public areas in Barcelona for the species richness), abundance, and composition (tree species dissimilar­ first trimester of 2021 from the City Council’s official website (https:// ities) in 73 neighborhoods in the municipality of Barcelona (Spain). We opendata-ajuntament.barcelona.cat/data/en/dataset?tags=Arbres). determined whether these patterns correlated with neighborhood de­ This database includes three datasets with tree occurrence data in three mographic and socioeconomic factors. We selected Barcelona because of land-use types: parks, streets, and zonal areas. Zonal areas include its highly compact urban matrix and because the city has ~ 230,000 geo- squares, flower beds, gazebos, or small garden spaces. Therefore, zonal referenced records of individual trees in parks, streets, and zonal areas areas should be considered a heterogeneous land-use type. Individual publicly available. We complement previous studies in Barcelona that tree occurrences in the datasets were originally geo-referenced and examined the regulating services of urban forests to reduce pollution localized in the city neighborhoods (N = 73). As a highly compact city, 2 J. Padullés Cubino and J. Retana Landscape and Urban Planning 236 (2023) 104778 Fig. 1. Location of the study area (Barcelona) in Spain and the Mediterranean Basin (a). Aerial picture of the compact city of Barcelona (image by Patrick Gautier from Pixabay) (b). Total tree species richness (tree diversity) (c) and abundance (d) in the 73 neighborhoods in Barcelona. most of the trees in the urbanized area of Barcelona occur in public 2.5.1. Tree diversity and abundance spaces. Only 3% of the houses in the city were single-family in 2001, the We conducted all analyses separately for parks, streets, and zonal last year with available data (INE, 2023). areas and then aggregated individual tree occurrences across all land- We standardized species nomenclature at the species level, thus use types (total). In each neighborhood, we calculated tree diversity as removing subspecies and cultivars. We assigned the epithet “hybrid” to the total number of tree species (hereafter tree species richness) and tree the hybrid cultivars that we could not assign to the species level (5 taxa). abundance as the total number of trees. Furthermore, we also calculated We removed undetermined species from the study. the Shannon diversity index in each neighborhood. Due to its partial overlap with species richness and the fact that it could only be calculated for a subset of neighborhoods with treed parks, we moved the methods 2.4. Demographic and socioeconomic data and results for Shannon diversity to Appendix S2. Therefore, we used Shannon diversity results to supplement the main findings from tree We obtained demographic and socioeconomic data at the neigh­ species richness and abundance. borhood level (N = 73) in Barcelona from the City Council’s official website (https://ajuntament.barcelona.cat/estadistica/angles/Estad 2.5.2. Models for tree diversity and abundance istiques_per_territori/Barris/index.htm). Specifically, we retrieved data Poisson regression is frequently used to model discrete data such as for four demographic and socioeconomic variables: household dispos­ tree species richness and abundance (Agresti, 2015). This type of able income per capita (HDIpc; €/person); population density (in­ generalized linear model (GLM) assumes a Poisson error distribution habitants/ha); mean population age (hereafter ‘age’; years); and mean and includes the natural logarithm as the link function. However, two life expectancy (hereafter ‘life expectancy’; years) (see further details in attributes of discrete variables induce problems for Poisson regressions: Appendix S1). All variables were recorded in 2021, except HDIpc, which overdispersion (i.e., variance largely exceeding the mean); and a large was recorded in 2019. proportion of zero values (Agresti, 2015). Although only a small pro­ portion of neighborhoods had zeros for tree species richness and abun­ dance (32%), most response variables exhibited overdispersion. 2.5. Statistical analyses Therefore, we used quasi-Poisson regressions. In this extension of the Poisson model, the dispersion parameter is not fixed but estimated from We conducted statistical analyses in R v. 4.2.0 () and established significance at α < 0.05 throughout all standard Poisson regression, but the inference is adjusted for over­ tests. The core code for the analyses is available at: https://github.com/ dispersion (Agresti, 2015). padullesj/bcn_trees. 3 J. Padullés Cubino and J. Retana Landscape and Urban Planning 236 (2023) 104778 We created several GLMs with tree species richness and abundance in 3. Results each land-use type as response variables and the four demographic and socioeconomic variables (i.e., HDIpc [loge-transformed]; population 3.1. Urban tree diversity and abundance across land-use types density; mean age; and life expectancy) as predictors. We included neighborhood area (loge-transformed) in the GLMs as a covariate. We The datasets collectively included 229,962 tree occurrences from interpreted the neighborhood area as the potential area that could be 371 species. The majority of trees occurred in streets (67%), followed by used for planting trees in each neighborhood. We also included the zonal areas (18%) and parks (15%). Parks consistently had more tree proportion of residential land in the neighborhoods as a covariate. species (319) than zonal areas (243) or streets (208). On average, streets However, this variable showed no significant effects on tree species and zonal areas had a higher tree species richness than parks across richness and abundance and was finally discarded. neighborhoods (Fig. 2a). Streets also had a higher tree abundance than We centered and standardized predictors before introducing them to zonal areas and parks across neighborhoods (Fig. 2b). Shannon diversity the models to make their coefficients comparable (Zuur et al., 2007). We was higher in zonal areas than in parks or streets (Appendix S2). Spatial used diagnostic plots to check model assumptions (i.e., normally patterns in tree diversity across land-use types can be found in Appendix distributed errors with a constant variance; homogeneity of variance; S3. and independence of residuals) (Zuur et al., 2007). We also tested for spatial autocorrelation in the models’ residuals with Moran’s I in the 3.2. Demographic and socioeconomic factors related to urban tree “ape” R package (Paradis & Schliep, 2019). These tests revealed no diversity and abundance significant spatial autocorrelation in the models’ residuals. For each GLM, we report McFadden’s pseudo R2 as a metric of the goodness of fit GLMs explained tree abundance better than tree species richness (McFadden, 1977). (Fig. 3). Tree species richness and abundance in parks, streets, zonal areas, and across all land-use types were significantly positively related 2.5.3. Tree composition and demographic and socioeconomic correlates to life expectancy in the neighborhoods. Furthermore, tree species To examine tree composition across neighborhoods, we created a richness and abundance in zonal areas were significantly positively site-by-site pairwise dissimilarity matrix using Bray Curtis distances and related to mean population age. Tree abundance in streets also respon­ tree abundance data (i.e., the number of tree occurrences per species ded positively to population density. In contrast, tree species richness divided by the total number of tree occurrences) within each neigh­ and abundance were significantly negatively related to population borhood in the “vegan” R package (Oksanen et al., 2022). Then, we density and household disposable income per capita (HDIpc) in zonal performed an ordination on the site-by-site pairwise dissimilarity matrix areas and across all land-use types. Tree species richness and abundance with principal coordinates analysis (PCoA). We fitted demographic and were significantly negatively related to population density and HDIpc socioeconomic vectors to the ordination with the envfit function in the across all land use types, respectively. “vegan” R package. The explanatory power of demographic and socioeconomic variables was consistently lower for Shannon diversity than for species richness 2.5.4. Differences in tree diversity, abundance, and composition between (Appendix S2). The Shannon diversity across all land use types was land-use types positively related to life expectancy in the neighborhoods but negatively To examine differences in diversity, abundance, and composition in related to HDIpc and population density. the neighborhoods between land-use types, we used non-parametric Kruskal-Wallis tests. When the result was significant, we performed 3.3. Demographic and socioeconomic factors related to urban tree post hoc paired comparisons following Dunn (1964). We adjusted P- composition values with the Holm method (Holm, 1979). Tree composition was more homogeneous (i.e., had lower mean Bray Curtis distances) in streets than in zonal areas and, especially, parks (Fig. 4). Tree composition also varied widely across land-use types (Fig. 5). Variation in tree composition amongst neighborhoods was significantly related to HDIpc and life expectancy in streets and to Fig. 2. Patterns of tree species richness (a) and abundance (b) in parks, streets, zonal areas, and across all land-use types (total) in neighborhoods in Barcelona. The black line and the boxes within each violin plot show the median values and the 95% confidence intervals, and the whiskers in each violin plot represent the range. Different lower-case letters on top of the violin plots show a significant difference (P < 0.05) among other groups based on Kruskal-Wallis multiple comparisons. 4 J. Padullés Cubino and J. Retana Landscape and Urban Planning 236 (2023) 104778 Fig. 3. Estimated coefficients (±95% confidence in­ tervals) for all variables included in GLMs of tree species richness (a) and abundance (b) in parks, streets, zonal areas, and across all land-use types (total) in neighborhoods in Barcelona. Confidence intervals that do not overlap zero indicate signifi­ cance. The dashed horizontal line separates focal predictors (demographic and socioeconomic vari­ ables) from the covariate (neighborhood area). For each model, McFadden’s pseudo R2 is also shown. population density in zonal areas and across all land-use types. pollution (Tzoulas et al., 2007; Correia et al., 2013; Heaviside et al., 2016). However, we are cautious when interpreting our results as causal 4. Discussion effects. It is possible that socioeconomic variables do not adequately capture other confounders and selection effects. For instance, the lasting This study shows that the demographic and socioeconomic factors impacts of historical or past events on the present urban ecosystem, such related to tree diversity, abundance, and composition vary between as changes in land use, past human activities, or species introduction, land-use types within a compact city. The direction and magnitude of can shape tree species distribution in cities (Clarke et al., 2013; Larson these relationships do not always coincide with those reported in other et al., 2017). Recognizing the combined influence of legacy effects and cities, indicating that distinct factors may be at work in other locations. socioeconomic factors on the current tree diversity patterns can help In the highly compact city of Barcelona, tree abundance responded more urban planners develop more effective strategies for promoting and strongly to the variation in the social environment than tree diversity. sustaining plant diversity in cities. Taken together, our findings support the notion that urban tree distri­ In contrast to life expectancy, income was negatively related to tree bution varies across social strata (Riley & Gardiner, 2020). diversity in zonal areas and unrelated to tree diversity in the other land- Given that a significant fraction of urban trees are planted, particu­ use types. Therefore, this finding contradicts the idea that affluent res­ larly in compact cities, it seems plausible to assume that demographic idents live in more diverse neighborhoods (i.e., luxury effect; Hope et al., and socioeconomic factors should relate to tree diversity and abundance 2003; Leong et al., 2018), a pattern commonly reported in more diffuse and that tree composition should reflect the management considerations cities (Schwarz et al., 2015; Avolio et al., 2015; 2018). Nonetheless, of the actors who choose trees (Aronson et al., 2017; Avolio et al., 2015). luxury effects may become more evident in private landscapes where Accordingly, we found that tree diversity and abundance increased with owners’ preferences and choices have greater effects on tree distribution life expectancy across all land-use types when controlling for neigh­ (Martin et al., 2004). Our study also did not account for peri-urban borhood area and other socio-demographic variables. A growing body of vegetation. Private landscapes and peri-urban areas make up a signifi­ research shows that access to green spaces can have numerous benefits cant portion of the urban matrix and play an essential role in the dis­ for mental and physical health, social cohesion, and overall quality of tribution of trees. Combining the existing data with information on tree life (Takano et al., 2002; Jonker et al., 2014). These benefits are usually occurrences in private landscapes and residents’ access to peri-urban related to the fact that urban green spaces lower stress levels, promote areas would enable us to further support our conclusions. This would physical activity, enhance local climates, and lower ambient air provide a more comprehensive and accurate representation of the state 5 J. Padullés Cubino and J. Retana Landscape and Urban Planning 236 (2023) 104778 street tree plantings in densely populated areas likely compensate for the lack of other green infrastructure. Accordingly, tree abundance in zonal areas, representing a variety of land cover, such as squares, flower beds, gazebos, or small garden spaces, decreased with population density. Furthermore, street trees were more diverse and compositionally ho­ mogenous than in parks. Because street trees are usually exposed to high-stress levels, their lifespan is generally lower than that of park trees (Sæbø et al., 2003), and street trees are more frequently replanted with similar sets diverse species throughout the city than those in parks. In contrast, large, old trees are keystone structures in urban parks (Stagoll et al., 2012), likely reinforcing parks’ distinctive landscape designs. Because many ecosystem services depend on urban tree abundance (Morgenroth et al., 2016), street trees may provide a broader range of ecosystem services than trees in other land-use types. Our findings highlight the importance of discriminating between trees in parks, streets, and zonal areas and identifying rules for removing and planting trees when evaluating urban tree diversity. For instance, while tree monocultures have traditionally been planted for aesthetic reasons, more diverse tree assemblages are encouraged to provide a broader range of ecosystem services (McPherson et al., 2016) and Fig. 4. Bray Curtis distances between neighborhoods considering tree species greater stability and resilience to global change drivers (Morgenroth composition in parks, streets, zonal areas, and across all land-use types (total) in et al., 2016). Local authorities can use online resources like Citree (Vogt Barcelona. The black line and the boxes within each violin plot show the me­ dian values and the 95% confidence intervals, and the whiskers in each violin et al., 2017) to support multicriteria tree selection. Our study also em­ plot represent the range. Different lower-case letters on top of the violin plots phasizes that street trees significantly contribute to tree abundance in indicate a significant difference (P < 0.05) among other groups based on densely populated cities such as Barcelona. Streets are at the interface of Kruskal-Wallis multiple comparisons. private and public landscapes and reflect political influences more strongly than parks or zonal areas as they are more directly tied to in­ of tree populations in the study region. dividual dwellings. Street tree planting schemes can help urban planners Total tree abundance in Barcelona also decreased with income across handle mismatches between social groups and plant diversity caused by neighborhoods, further demonstrating the positive relationship between the generally uneven distribution of urban green spaces like private wealth and urban tree canopy cover (Gerrish & Watkins, 2018) and gardens, parks, or urban forests (Nielsen et al., 2017). Even though the street tree abundance (Anderson et al., 2023; Lin et al., 2021) may not expansion of street trees may be physically limited in highly compact hold in highly compact cities. Accordingly, Anguelovski et al. (2018) cities, transforming the street network, for example, by reducing the found that urban green areas in Barcelona were not associated with number of private traffic lanes, may open up new opportunities for gentrification processes in historically impoverished neighborhoods. increased tree planting. This has important social implications because it suggests that urban planners and policymakers should not assume that increasing income 5. Conclusions levels alone will lead to an increase in tree cover or green spaces. Instead, they need to take a more targeted approach that focuses on Our research shows that while total tree diversity and abundance identifying and addressing the barriers that prevent particular social were positively related to life expectancy, it was neither positively groups from accessing trees and green spaces. related to income nor population age. Therefore, as reported for tree- Street tree composition across neighborhoods responded to income related ecosystem services (Baró et al., 2019), tree distribution in Bar­ and life expectancy. This finding is in line with the theory of the ecology celona does not directly result in biodiversity inequalities for low- of prestige, which posits that urban vegetation gives locals a way to income or elderly groups. Furthermore, our study demonstrates that flaunt their socioeconomic status and support neighborhood identity the relationship between socioeconomic factors and urban biodiversity through unique neighborhood appearance (Grove et al., 2014). These varies across land-use types. Specifically, tree diversity and abundance landscape identities probably play a part in how trees shape people’s responded more strongly to residents’ demographic and socioeconomic sense of place (Dwyer et al., 1991; Pearce et al., 2015), wherein residents characteristics in streets and zonal areas than in parks. We conclude that develop a connection to particular trees and the qualities of an area that tree planting, particularly in streets, can be an effective greening strat­ trees contribute to. Although the ecology of prestige is often more egy for compact cities to overcome the disparities resulting from the prominent in private urban landscapes, it can still be present in public typically unequal distribution of urban vegetation. Long-term data on urban landscapes. While people may have limited decision-making alternative socioeconomic factors and urban tree change are required to power regarding the trees planted in public areas, the competition for reveal social stratification’s impact on urban diversity. status and recognition within a social context can still influence the development of public urban areas, leading to the gentrification of Declaration of Competing Interest certain neighborhoods or the implementation of policies that prioritize the landscaping interests of powerful or influential groups (Molotch, The authors declare that they have no known competing financial 1996; Bryson, 2013). Future research should assess how residents’ interests or personal relationships that could have appeared to influence connections to specific vegetation and locations in cities affect public the work reported in this paper. decisions on tree plantings and removals. We found street tree abundance in Barcelona was positively related Data availability to population density, in contrast to similar studies conducted in diffuse cities in Australia and the US (Grove et al., 2006; Iverson & Cook, 2000; All datasets are publicly available and referenced in the Materials Kendal et al., 2012). This finding, combined with a higher tree abun­ and methods. dance in streets than in parks or zonal areas, indicates that more intense 6 J. Padullés Cubino and J. Retana Landscape and Urban Planning 236 (2023) 104778 Fig. 5. Results from principal coordinates analyses (PCoA) showing tree composition in parks, streets, zonal areas, and across all land-use types (total). Red arrows indicate demographic and socioeconomic gradients significantly (P < 0.05) related to tree composition. The length of the arrow is positively related to the strength of the gradient. The colors are only for visualization purposes to connect points in the ordinations (left column) to their respective neighborhoods in the city (right column). Appendix A. Supplementary data Anderson, E. C., Locke, D. H., Pickett, S. T. A., & LaDeau, S. L. (2023). Just street trees? Street trees increase local biodiversity and biomass in higher income, denser neighborhoods. Ecosphere, 14, e4389. Supplementary data to this article can be found online at https://doi. Anguelovski, I., Connolly, J. J. T., Masip, L., & Pearsall, H. (2018). Assessing green org/10.1016/j.landurbplan.2023.104778. gentrification in historically disenfranchised neighborhoods: A longitudinal and spatial analysis of Barcelona. 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