Optimizing urban tree species composition to maximize nature-based solutions

Abstract Nature-based Solutions (NbS) are vital for achieving sustainable urban development. While urban tree planting is one of the most important approaches to enhance NbS, current practices often concentrate on tree quantity or green coverage targets. NbS planning studies are also limited to priority identification, revealing a notable gap in both study and practice. This study presents a tree species composition optimization-based framework for maximizing regional NbS by linking local demands and the effectiveness of tree species through a multi-objective optimization algorithm. A case study was designed in Philadelphia, and the optimal tree species composition was explored on 0.25 km 2 grids. The spatial heterogeneity of local demands and the varying effectiveness of tree species highlight the significance of strategic tree placement. The current tree species composition in Philadelphia is suboptimal for achieving NbS. Future greening efforts should increase the proportion of advantageous species, such as Acer saccharinum , Acer rubrum , and Liquidambar styraciflua . Compared with the baseline, the optimized species composition can provide substantially greater ecosystem services, for instance, about 20% more in stormwater management and up to 80% more in microclimate regulation. Two general planning recommendations are proposed: (1) maximize carbon sequestration capacity in areas with insignificant urban hazards; and (2) strategically place trees with specific advantages in targeted response to specific urban hazards. The developed framework provides guidance for efficient urban greening projects, enabling maximization of NbS under given greening quantity targets.