A Needs-Driven, Multi-Objective Approach to Allocate Urban Ecosystem Services from 10,000 Trees

Abstract

Urban areas face challenges including vehicular emissions, stormwater runoff, and sedentary lifestyles. Communities recognize the value of trees in mitigating these challenges by absorbing pollution and enhancing walkability. However, siting trees to optimize multiple benefits requires a systems approach that may cross sectors of management and expertise. We present a spatially-explicit method to optimize tree planting in Durham, NC, a rapidly growing urban area with an aging tree stock. Using GIS data and a ranking approach, we explored where Durham could augment its current stock of willow oaks through its plans to install 10,000 mid-sized deciduous trees. Data included high-resolution landcover metrics developed by the U.S. Environmental Protection Agency (EPA), demographics from the U.S. Census, an attributed roads dataset licensed to the EPA, and sidewalk information from the City of Durham. Census block groups (CBGs) were ranked for tree planting according to single and multiple objectives including stormwater reduction, emissions buffering, walkability, and protection of vulnerable populations. Prioritizing tree planting based on single objectives led to four sets of locations with limited geographic overlap. Prioritizing tree planting based on multiple objectives tended to favor historically disadvantaged CBGs. The four-objective strategy met the largest proportion of estimated regional need. Based on this analysis, the City of Durham has implemented a seven-year plan to plant 10,000 trees in priority neighborhoods. This analysis also found that any strategy which included the protection of vulnerable populations generated more benefits than others.

US EPA EnviroAtlas Meter-Scale Urban Land Cover (MULC): 1-m Pixel Land Cover Class Definitions and Guidance

“…In Portland, Oregon, city planners have used MULC to design street tree planting and green infrastructure for urban heat island mitigation [24]. In Durham, North Carolina, EnviroAtlas has been used to identify census block groups with low tree cover and vulnerable populations to explore how tree planting might benefit child development, overall public health, and environmental quality [25,26]. In Tampa Bay, Florida, a Health Impact Assessment (HIA) has demonstrated how MULC and EnviroAtlas metrics, tools, and data can assist decision makers in a health and wellness application [27].…”

A Community EcoHealth Index from EnviroAtlas Ecosystem Services Metrics

“…Correlations are weak, insignificant or negative in more agricultural communities in semi-arid and grassland ecoregions such as Fresno, CA, Des Moines, IA, and Brownsville, TX as well as in cities with high amounts of impervious surface like New York City, NY and Paterson, NJ. These findings need further investigation considering urban vegetation inequity, where neighborhoods with higher levels of income and education often have more woody and mixed vegetation and parks [55]. Though CEHI favors communities and neighborhoods with greater tree cover and greenspace, both ecoregion and urban vegetation inequity need to be taken into account.…”

Disambiguating Concepts of Fairness in Stormwater Management: A Review of Economic Efficiency and Equity

“…They manuscript submitted to Water Resources Research suggest a method for including multi-aspects of vulnerability to prioritize green infrastructure projects to provide multi-benefits to underserved communities. Almeter et al (2018) developed a semi-quantitative prioritization scheme to identify a tree planting strategy based on maximizing multi-benefits. They found that multi-objective benefits favored planting in historically disadvantaged U.S. Census block groups in Durham, North Carolina, compared to single objectives.…”