Disentangling the effects of urban form and socio-demographic context on street tree cover: A multi-level analysis from Montréal

Abstract

Street trees provide a wide range of benefits for cities. Street tree cover (STC) is explained by urban form, social stratification and lifestyle theories that operate at multiple scales. In this paper we examine how the urban form (street characteristics), social stratification and lifestyle (sociodemographics) account for variations of STC in Montréal. Tree cover was identified from Quickbird images and then overlaid on street segments to compute the STC. Each street segment was nested in a census tract. We used 2-level models with mixed effects and interactions (between street attributes and socio-demographic variables) while introducing a spatial term. Political, socioeconomic or other explanatory factors operating at the tract level can potentially explain 17.6% of the variation of STC. Overall, the street characteristics explained more variation in STC than the socio-demographic context. Lifestyle is less important than social stratification. Street length is positively associated with STC; street width and the percentage of duplexes and triplexes are negatively associated with STC, while construction age has a u-shaped effect on STC. Interactions show that STC is higher in expensive and highly-educated areas that have residential streets or streets with large setback (sidewalk). Areas predominantly comprised of low-income households could have higher or lower STC depending on the number of buildings and the percentage of duplexes and triplexes. Streetscape and socio-demographic contexts intertwine to create complex patterns of STC. Greening programs should be designed carefully according to local contexts since certain types of greening can lead to gentrification and displacement of low-income households.

Human and biophysical legacies shape contemporary urban forests: A literature synthesis

“…Troy et al (2007) detected a parabolic relationship between building age and the presence of vegetation in Baltimore, Maryland, where the positive association reaches a maximum cover at 40-50 years and then decreases; other studies have since corroborated those findings (Landry and Chakraborty, 2009;Locke et al, 2016;Pham et al, 2017). This relationship may reflect the normal life cycle of planted trees: growth followed by decline and removal (Roman et al, 2016).…”

“…The proliferation of single-family houses that dominated post-WWII altered the private land area available for tree planting. Larger lot sizes (Conway, 2009) and larger building set-backs (Pham et al, 2017) have been positively associated with vegetation cover. In both the US and Canada, urban areas with a higher proportion of single-family residential properties often have greater tree cover (Troy et al, 2007;Conway, 2009, Pham et al, 2017.…”

“…Larger lot sizes (Conway, 2009) and larger building set-backs (Pham et al, 2017) have been positively associated with vegetation cover. In both the US and Canada, urban areas with a higher proportion of single-family residential properties often have greater tree cover (Troy et al, 2007;Conway, 2009, Pham et al, 2017. Areas with more residential lands can also have high overall tree species diversity (Bourne and Conway, 2014), potentially related to homeowner choice in species selection.…”

The Relationship Between Urban Forests and Race: A Meta-Analysis

“…Findings suggest that features of the built environment such as terrain (Berland et al, 2015), street characteristics (Pham et al, 2017), construction age (Pham et al, 2017;Steenberg et al, 2015), vacant land (Nowak et al, 1996); or available planting space (Shakeel, 2012) help to explain urban forest distribution, and might explain variation better than social characteristics of a neighborhood (Berland et al, 2015;Pham et al, 2017; although see Melendez-Ackerman et al, 2014 for contrasting findings). Because features of the built environment are collinear with socio-demographic characteristics, we expect studies that control for built environment features to find weaker evidence of race-based urban forest inequity.…”

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

“…Findings suggest that features of the built environment such as terrain (Berland et al, 2015), street characteristics (Pham et al, 2017), construction age (Pham et al, 2017; Steenberg et al, 2015), vacant land (Nowak et al, 1996); or available planting space (Shakeel, 2012) help to explain urban forest distribution, and might explain variation better than social characteristics of a neighborhood (Berland et al, 2015; Pham et al, 2017; although see Melendez-Ackerman et al, 2014 for contrasting findings). Because features of the built environment are collinear with socio-demographic characteristics, we expect studies that control for built environment features to find weaker evidence of race-based urban forest inequity.…”