A geographical approach to identifying vegetation-related environmental equity in Canadian cities

Where the not-so-wild things are in cities? The influence of social-ecological factors in urban trees at multiple scales

Green infrastructure plays an essential role in cities due to the ecosystem services it provides. However, these elements are shaped by social and ecological factors that influence their distribution and diversity, affecting ecological functions and human well-being. Here, we analyzed neighborhood tree distribution - trees in pocket parks, squares and along streets - in Lisbon (Portugal) and modelled tree abundance and taxonomic and functional diversity, at the parish and local scales, considering a comprehensive list of social and ecological factors. For the functional analyses, we included functional traits linked to dispersal, resilience to important perturbations in coastal Mediterranean cities, and ecosystem services delivery. Our results show not only that trees are unevenly distributed across the city, but that there is a strong influence of social factors on all biological indices considered. At the parish and local scales, abundance and diversity responded to different factors, with abundance being linked to both social and ecological variables. Although the influence of social factors on urban trees can be expected, by modelling their influence we can quantify how much humans modify urban landscapes at a structural and functional level. These associations can underlie potential biodiversity filters and should be analyzed over time to inform decisions that support long-term ecological resilience, maximize trait functional expression, and increase equity in ecosystem services delivery.

Insects in the city: Determinants of a contained aquatic microecosystem across an urbanized landscape

Cities can have profound impacts on ecosystems, yet our understanding of these impacts is currently limited. First, the effects of the socioeconomic dimensions of human society are often overlooked. Second, correlative analyses are common, limiting our causal understanding of mechanisms. Third, most research has focused on terrestrial systems, ignoring aquatic systems that also provide important ecosystem services. Here we compare the effects of human population density and low-income prevalence on the macroinvertebrate communities and ecosystem processes within water-filled artificial tree holes. We hypothesized that these human demographic variables would affect tree holes in different ways via changes in temperature, water nutrients, and the local tree hole environment. We recruited community scientists across Greater Vancouver (Canada) to provide host trees and tend 50 tree holes over 14 weeks of colonization. We quantified tree hole ecosystems in terms of aquatic invertebrates, litter decomposition, and chlorophyll a (chl a). We compiled potential explanatory variables from field measurements, satellite images, or census databases. Using structural equation models, we showed that invertebrate abundance was affected by low-income prevalence but not human population density. This was driven by cosmopolitan species of Ceratopogonidae (Diptera) with known associations to anthropogenic containers. Invertebrate diversity and abundance were also affected by environmental factors, such as temperature, elevation, water nutrients, litter quantity, and exposure. By contrast, invertebrate biomass, chl a, and litter decomposition were not affected by any measured variables. In summary, this study shows that some urban ecosystems can be largely unaffected by human population density. Our study also demonstrates the potential of using artificial tree holes as a standardized, replicated habitat for studying urbanization. Finally, by combining community science and urban ecology, we were able to involve our local community in this pandemic research pivot.

More than greening: Using a novel index to assess restorative nature and vulnerability relationships

Urban living limits access to nature yet spending time in nature is crucial for human health and well-being. To overcome this, urban planners and policymakers are actively looking for different ways to conserve and create more urban nature through parks, street trees, and other greening strategies. However, research shows that in most cities, these greening efforts are not equitably distributed, nor are they equal in terms of their quality or benefits they provide. Creating more equitable access to urban nature is a challenge and a priority in the next decade, and so is improving the quality of urban nature and associated benefits for urbanites. To address this challenge and contribute at both practical and conceptual levels, we propose a new Local Restorative Nature (LRN) index for geospatially assessing the "restorative quality" of urban nature that can support mental well-being. To contextualize the LRN index, we map the distribution of restorative nature in relation to social vulnerability in Vancouver, Canada. The novel LRN index provides critical insights showing that many neighborhoods with vulnerable populations in Vancouver have less exposure to restorative nature to support mental health and highlights where to strategically prioritize urban greening investment in areas that need it the most. The LRN index is scalable and can be used by urban planners in other cities and contexts to improve equitable distribution of restorative nature and better support urbanites' well-being.

Spatiotemporal Dynamics of Ecosystem Services and the Driving Factors in Urban Agglomerations: Evidence From 12 National Urban Agglomerations in China

The natural environment provides multiple ecosystem services for urban development and human quality of life. Given that current cities interact with each other and form urban agglomerations, understanding the spatiotemporal changes in ecosystem services and the driving forces is crucial for sustainable urban development. Using 12 national-level urban agglomerations as a case study, this paper quantifies the spatial patterns of multiple ecosystem service values from 2000 to 2015 and assesses how natural and socioeconomic factors contribute to such changes by using ordinary least squares (OLS) and geographically weighted regression (GWR). The results show the following: (1) spatial discrepancies of ecosystem services exist both in and between urban agglomerations, and ecosystem service values are reduced in more than 70% of urban agglomerations at a rate ranging from 0.02 to 4.27%; (2) elevation, precipitation, and fraction of woodland have positive impacts on ecosystem service values in urban agglomerations; while gross domestic product (GDP), population, and proportion of built-up area have negative effects; (3) both natural and social driving factors impact the ecosystem services of different urban agglomeration in different ways, according to the differences in their driving degrees. We categorized 12 urban agglomerations in China into six typical types: natural-factor dominated, socioeconomic-factor dominated, policy dominated, balanced, natural-factor inclined, and socioeconomic-factor inclined. Our results can be used to inform decision makers and urban planners to propose explicit location strategies to balance natural protection and socioeconomic development and ultimately promote sustainable urbanization across the nation.

Are street tree inequalities growing or diminishing over time? The inequity remediation potential of the MillionTreesNYC initiative

Most street tree inequality studies focus on examining tree abundance at single time point, while overlooking inequality dynamics measured based on a complete set of tree measures. Whether the severities of street tree inequalities vary with different tree structure measures, whether street tree inequalities are diminishing or growing over time, and how the inequality dynamics are affected by tree-planting programs remain largely unexplored. To fill these gaps, this study applied binned regression and cluster analyses to street tree census data of 1995-2015 in New York City. We investigated different structural measures of street tree inequalities pertaining to various aggregations of people, compared street tree inequalities over time, and revealed the inequity remediation role of the MillionTreesNYC initiative. We found that the underprivileged populations, characterized by higher percentages of the poor, racial minorities, young people, and less-educated people, are more likely to have lower tree abundance, less desired tree structure, poorer tree health condition, and more sidewalk damages. When disaggregating inequalities across various aggregations of people, income-based and education-based inequalities were the most severe, but the inequalities diminished over time. The race-based and age-based inequalities show mixed results that disfavor Hispanics, Blacks, and young people. The equity outcome of the MillionTreesNYC initiative is not ideal as the inequalities decrease when measured using tree count and species diversity, whereas they increase when measured using tree health and average diameter at breast height. The findings have important implications for more effective decision-making to balance resources between planting trees and protecting existing trees, and between increasing tree abundance and improving tree structure.

Does socioeconomic development lead to more equal distribution of green space? Evidence from Chinese cities

Despite the wide implementation of green spaces to mitigate the negative effects of urbanization, there is little evidence of how cities' socioeconomic development impacts the equality of urban green space (UGS) distribution. This paper addresses this knowledge gap. Employing longitudinal data analysis and the Gini index with various socioeconomic factors, we investigated potential driving factors for UGS equality at the prefectural city level (221 out of 341 cities in total) in China during the rapid urbanization from 2000 to 2015. Results indicated that 72% of Chinese cities (160 of 221) in our sample improved their UGS equality level from 2000 to 2015, whereas 14% of cities studied (31 out of 221) declined in both quantity and equality of green space. Nationwide, economic development levels reflected by gross domestic product per capita exerted a positive and significant impact on the equality of green space distributions. Urban afforestation-related policies in China were successful in promoting the equal distribution of green space. Regional analysis indicated divergent impacts of socioeconomic development and government policies on green space equality. Other institutional development factors, such as adopting a freer land market, might harm efforts toward equal green space distribution without appropriate safeguarding regulations and enforcement powers to ensure the implementation of an equal distribution of green spaces. These findings inform decision-makers about spatial variances in the equality of green space distribution in urban areas, which demand location-oriented interventions to promote inclusive urban afforestation in Chinese cities.

The Legacy Effects of Colonial and Apartheid Imprints on Urban Greening in South Africa: Spaces, Species, and Suitability

Colonialism is a significant legacy across most aspects of urban form, the nature and distribution of public green spaces, and tree species composition in many cities of the Global South. However, the legacy effects of colonialism on urban green infrastructure and the uses thereof have only recently come under scrutiny. Here we collate information from South Africa on urban greening and interpret it through a colonial and apartheid legacy lens in relation to the distribution and types of urban nature found and their resonance with contemporary needs as an African country. The analysis indicates marked inequalities in public green space distribution and quality between neighborhoods designated for different race groups during the colonial and apartheid periods, which continues to be reproduced by the post-colonial (and post-apartheid) state. Additionally, in the older, former colonial neighborhoods non-native tree species dominate in parks and streets, with most of the species having been introduced during the colonial period. Such colonial introductions have left a burdensome legacy of invasive species that costs billions of Rands annually to keep in check. Lastly, the forms of nature and activities provided in public urban green spaces remains reminiscent of the colonial norm, with little recognition of African worldviews, identity and needs. We conclude in emphasizing the necessity for urban authorities and planners to address these anachronistic legacies through adopting a more inclusive and co-design approach with respect to the extent, location and types of urban nature provided, as well as the types of cultural symbols and activities permitted and promoted.

The relationship between urban forests and race: A meta-analysis

There is ample evidence that urban trees benefit the physical, mental, and social health of urban residents. The environmental justice hypothesis posits that environmental amenities are inequitably low in poor and minority communities, and predicts these communities experience fewer urban environmental benefits. Some previous research has found that urban forest cover is inequitably distributed by race, though other studies have found no relationship or negative inequity. These conflicting results and the single-city nature of the current literature suggest a need for a research synthesis. Using a systematic literature search and meta-analytic techniques, we examined the relationship between urban forest cover and race. First, we estimated the average (unconditional) relationship between urban forest cover and race across studies (studies = 40; effect sizes = 388). We find evidence of significant race-based inequity in urban forest cover. Second, we included characteristics of the original studies and study sites in meta-regressions to illuminate drivers of variation of urban forest cover between studies. Our meta-regressions reveal that the relationship varies across racial groups and by study methodology. Models reveal significant inequity on public land and that environmental and social characteristics of cities help explain variation across studies. As tree planting and other urban forestry programs proliferate, urban forestry professionals are encouraged to consider the equity consequences of urban forestry activities, particularly on public land.

The relationship between urban forests and income: A meta-analysis

Urban trees provide substantial public health and public environmental benefits. However, scholarly works suggest that urban trees may be unequally distributed among poor and minority urban communities, meaning that these communities are potentially being deprived of public environmental benefits, a form of environmental injustice. The evidence of this problem is not uniform however, and evidence of inequity varies in size and significance across studies. This variation in results suggests the need for a research synthesis and meta-analysis. We employed a systematic literature search to identify original studies which examined the relationship between urban forest cover and income (n=61) and coded each effect size (n=332). We used meta-analytic techniques to estimate the average (unconditional) relationship between urban forest cover and income and to estimate the impact that methodological choices, measurement, publication characteristics, and study site characteristics had on the magnitude of that relationship. We leveraged variation in study methodology to evaluate the extent to which results were sensitive to methodological choices often debated in the geographic and environmental justice literature but not yet evaluated in environmental amenities research. We found evidence of income-based inequity in urban forest cover (unconditional mean effect size = 0.098; s.e. = .017) that was robust across most measurement and methodological strategies in original studies and results did not differ systematically with study site characteristics. Studies that controlled for spatial autocorrelation, a violation of independent errors, found evidence of substantially less urban forest inequity; future research in this area should test and correct for spatial autocorrelation.

Remote sensing-based measurement of Living Environment Deprivation: Improving classical approaches with machine learning

This paper provides evidence on the usefulness of very high spatial resolution (VHR) imagery in gathering socioeconomic information in urban settlements. We use land cover, spectral, structure and texture features extracted from a Google Earth image of Liverpool (UK) to evaluate their potential to predict Living Environment Deprivation at a small statistical area level. We also contribute to the methodological literature on the estimation of socioeconomic indices with remote-sensing data by introducing elements from modern machine learning. In addition to classical approaches such as Ordinary Least Squares (OLS) regression and a spatial lag model, we explore the potential of the Gradient Boost Regressor and Random Forests to improve predictive performance and accuracy. In addition to novel predicting methods, we also introduce tools for model interpretation and evaluation such as feature importance and partial dependence plots, or cross-validation. Our results show that Random Forest proved to be the best model with an R2 of around 0.54, followed by Gradient Boost Regressor with 0.5. Both the spatial lag model and the OLS fall behind with significantly lower performances of 0.43 and 0.3, respectively.

Trees grow on money: urban tree canopy cover and environmental justice

This study examines the distributional equity of urban tree canopy (UTC) cover for Baltimore, MD, Los Angeles, CA, New York, NY, Philadelphia, PA, Raleigh, NC, Sacramento, CA, and Washington, D.C. using high spatial resolution land cover data and census data. Data are analyzed at the Census Block Group levels using Spearman's correlation, ordinary least squares regression (OLS), and a spatial autoregressive model (SAR). Across all cities there is a strong positive correlation between UTC cover and median household income. Negative correlations between race and UTC cover exist in bivariate models for some cities, but they are generally not observed using multivariate regressions that include additional variables on income, education, and housing age. SAR models result in higher r-square values compared to the OLS models across all cities, suggesting that spatial autocorrelation is an important feature of our data. Similarities among cities can be found based on shared characteristics of climate, race/ethnicity, and size. Our findings suggest that a suite of variables, including income, contribute to the distribution of UTC cover. These findings can help target simultaneous strategies for UTC goals and environmental justice concerns.

Toward improved public health outcomes from urban nature

There is mounting concern for the health of urban populations as cities expand at an unprecedented rate. Urban green spaces provide settings for a remarkable range of physical and mental health benefits, and pioneering health policy is recognizing nature as a cost-effective tool for planning healthy cities. Despite this, limited information on how specific elements of nature deliver health outcomes restricts its use for enhancing population health. We articulate a framework for identifying direct and indirect causal pathways through which nature delivers health benefits, and highlight current evidence. We see a need for a bold new research agenda founded on testing causality that transcends disciplinary boundaries between ecology and health. This will lead to cost-effective and tailored solutions that could enhance population health and reduce health inequalities.

A spatially explicit approach to the study of socio-demographic inequality in the spatial distribution of trees across Boston neighborhoods

The racial/ethnic and income composition of neighborhoods often influences local amenities, including the potential spatial distribution of trees, which are important for population health and community wellbeing, particularly in urban areas. This ecological study used spatial analytical methods to assess the relationship between neighborhood socio-demographic characteristics (i.e. minority racial/ethnic composition and poverty) and tree density at the census tact level in Boston, Massachusetts (US). We examined spatial autocorrelation with the Global Moran's I for all study variables and in the ordinary least squares (OLS) regression residuals as well as computed Spearman correlations non-adjusted and adjusted for spatial autocorrelation between socio-demographic characteristics and tree density. Next, we fit traditional regressions (i.e. OLS regression models) and spatial regressions (i.e. spatial simultaneous autoregressive models), as appropriate. We found significant positive spatial autocorrelation for all neighborhood socio-demographic characteristics (Global Moran's I range from 0.24 to 0.86, all P=0.001), for tree density (Global Moran's I=0.452, P=0.001), and in the OLS regression residuals (Global Moran's I range from 0.32 to 0.38, all P<0.001). Therefore, we fit the spatial simultaneous autoregressive models. There was a negative correlation between neighborhood percent non-Hispanic Black and tree density (rS=-0.19; conventional P-value=0.016; spatially adjusted P-value=0.299) as well as a negative correlation between predominantly non-Hispanic Black (over 60% Black) neighborhoods and tree density (rS=-0.18; conventional P-value=0.019; spatially adjusted P-value=0.180). While the conventional OLS regression model found a marginally significant inverse relationship between Black neighborhoods and tree density, we found no statistically significant relationship between neighborhood socio-demographic composition and tree density in the spatial regression models. Methodologically, our study suggests the need to take into account spatial autocorrelation as findings/conclusions can change when the spatial autocorrelation is ignored. Substantively, our findings suggest no need for policy intervention vis-à-vis trees in Boston, though we hasten to add that replication studies, and more nuanced data on tree quality, age and diversity are needed.