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

Area of Science:

• Urban forestry
• Environmental planning
• Geographic Information Systems (GIS)

Background:

• Urban areas face challenges like pollution, stormwater runoff, and sedentary lifestyles.
• Trees offer solutions by absorbing pollutants and improving walkability.
• Optimizing tree benefits requires a multi-sectoral, systems approach.

Purpose of the Study:

• To develop a spatially-explicit method for optimizing urban tree planting in Durham, NC.
• To identify priority locations for planting 10,000 mid-sized deciduous trees.
• To evaluate tree planting strategies based on single and multiple objectives.

Main Methods:

• Utilized GIS data including landcover, demographics (U.S. Census), roads, and sidewalks.
• Employed a ranking approach for Census block groups (CBGs) based on objectives: stormwater reduction, emissions buffering, walkability, and vulnerable population protection.
• Compared outcomes of single-objective versus multiple-objective prioritization strategies.

Main Results:

• Single-objective prioritization yielded geographically dispersed planting locations.
• Multiple-objective prioritization favored historically disadvantaged CBGs.
• A four-objective strategy (including vulnerable populations) met the greatest regional need and showed that including vulnerable populations generated more benefits.

Conclusions:

• The City of Durham has implemented a seven-year plan to plant 10,000 trees based on this analysis.
• A multi-objective, spatially-explicit approach is effective for optimizing urban tree benefits.
• Prioritizing vulnerable populations in urban greening strategies enhances overall community well-being and resilience.