Examining the distributional equity of urban tree canopy cover and ecosystem services across United States cities

Abstract

Examining the distributional equity of urban tree canopy cover (UTCC) has increasingly become an important interdisciplinary focus of ecologists and social scientists working within the field of environmental justice. However, while UTCC may serve as a useful proxy for the benefits provided by the urban forest, it is ultimately not a direct measure. In this study, we quantified the monetary value of multiple ecosystem services (ESD) provisioned by urban forests across nine U.S. cities. Next, we examined the distributional equity of UTCC and ESD using a number of commonly investigated socioeconomic variables. Based on trends in the literature, we predicted that UTCC and ESD would be positively associated with the variables median income and percent with an undergraduate degree and negatively associated with the variables percent minority, percent poverty, percent without a high school degree, percent renters, median year home built, and population density. We also predicted that there would be differences in the relationships between each response variable (UTCC and ESD) and the suite of socioeconomic predictor variables examined because of differences in how each response variable is derived. We utilized methods promoted within the environmental justice literature, including a multi-city comparative analysis, the incorporation of high-resolution social and environmental datasets, and the use of spatially explicit models. Patterns between the socioeconomic variables and UTCC and ESD did not consistently support our predictions, highlighting that inequities are generally not universal but rather context dependent. Our results also illustrated that although the variables UTCC and ESD had largely similar relationships with the predictor variables, differences did occur between them. Future distributional equity research should move beyond the use of proxies for environmental amenities when possible while making sure to consider that the use of ecosystem service estimates may result in different patterns with socioeconomic variables of interest. Based on our findings, we conclude that understanding and remedying the challenges associated with inequities requires an understanding of the local social-ecological system if larger sustainability goals are to be achieved.

Associations between ultraviolet radiation, tree cover and adolescent sunburns

“…School neighborhood poverty level was used to control for neighborhood socio-economic status around schools that may be associated with tree cover, based on a study in one urban area [ 27 ]. While it is unknown whether the school neighborhood poverty level and tree cover is a generalizable relationship [ 33 ], we include it to test whether it is significant with a national sample. School neighborhood poverty was defined as the percent of persons living below the federal poverty line from the American Community Survey 2010–2014.…”

The tree cover and temperature disparity in US urbanized areas: Quantifying the association with income across 5,723 communities

“…Nesbit and colleagues found that across 10 incorporated cities, neighborhoods with lower education and income had less vegetation, a pattern that was most strongly apparent in large cities [ 28 ]. Riley and Gardiner studied 9 incorporated cities, examining tree cover and ecosystem service provision, which related to socioeconomic variables in different ways in each city [ 29 ]. A similar general trend for inequality in exposure to nature has been observed with remotely sensed measures of greenness [ 30 ], which have been used to analyze vegetation in cities globally [e.g., 31], and with exposure to heat risk due to lack of trees and high impervious cover [ 32 , 33 ].…”

“…Furthermore, socio-economic variables are themselves also correlated with aspects of urban form, such as the degree of sprawl and population density [ 43 , 44 ]. Second, some studies have found that the statistical significance of the relationship between tree cover and socioeconomic variables is different if spatial autocorrelation is accounted for [ 27 , 29 ], and one review study observed that studies that controlled for spatial autocorrelation generally found fewer statistically significant trends [ 23 ]. Therefore, one important question when quantifying patterns in tree inequality is whether relationships with socio-economic variables like income and race/ethnicity are statistically significant after accounting for covariates and spatial autocorrelation.…”

“…First, tree cover is also associated with other factors, including differences in climate, biome, neighborhood age, urban density, the intensity of urban settlement, and other aspects of urban form [34][35][36][37][38][39][40]. In some studies, covariates such as terrain, housing type and density explained part of the variation between tree cover and socio-economic variables [25,29,39,41,42]. Furthermore, socio-economic variables are themselves also correlated with aspects of urban form, such as the degree of sprawl and population density [43,44].…”

Green Apartheid: Urban green infrastructure remains unequally distributed across income and race geographies in South Africa

“…Whilst there are exceptions (e.g. Riley & Gardiner, 2020), several reviews (e.g. and empirical studies from different world regions have shown that lower income residential areas within towns and cities are more likely to have the least access to green infrastructure in the form of green spaces or street trees (Astell-Burt & Feng, 2019;McConnachie & Shackleton, 2010;Nero, 2017;Sathyakumar et al, 2019;Shen et al, 2017).…”