Context-Driven Optimization of Ecological and Socioeconomic Benefits through Urban Forest Expansion

The expansion of global forest cover is a critical component of preserving biodiversity, promoting climate resilience, and improving community well-being worldwide. Yet, the benefits that forests provide vary significantly depending on factors such as structural complexity, species composition, and geographic context. Forest restoration and tree-planting programs therefore present a unique opportunity to intentionally shape the forest's future conditions to achieve target management objectives and deliver specific ecosystem services. However, implementing such programs at the landscape-scale becomes more complicated, and requires balancing the needs of diverse stakeholders and competing management goals. Urbanizing landscapes introduce additional layers of complexity in the form of high population densities and heterogenous land use mosaics, which intensify trade-offs between ecological and socioeconomic priorities. Furthermore, the inherent variability in each landscape's spatial configuration may present unique challenges or opportunities to balance these trade-offs, which may affect the benefits generated by planted forests. The difficulty in balancing this multitude of context-specific factors emphasizes the need for a systematic, data-driven approach which identifies strategic locations for increasing forest cover.

In this study, we present a spatial decision support system (SDSS) designed to locate optimal planting sites within urbanizing landscapes for strategically increasing tree cover and ecosystem service provisioning. The SDSS analyzes high-resolution geospatial data to identify and rank available planting locations, simulate potential implementation strategies, and integrate external models to quantify potential outcomes. Upon completion, a detailed inventory of identified sites is generated, which provides actionable information including the size and geographic coordinates of each site. The inventory also provides a concrete foundation for quantifying specific ecosystem services, such as carbon sequestration and storage potential or pollution removal. These estimates can then be evaluated alongside stakeholder priorities and management goals to identify areas where forest expansion will yield the greatest benefits. Overall, the SDSS's scalable nature aids decision-making by considering services generated locally by individual trees as well as collectively by entire forests—thus offering comprehensive, actionable insights for sustainable and effective landscape management.

This presentation will highlight a case study from the United States that explores the impacts of different forest expansion scenarios, and the SDSS's capacity to strategically inform forest restoration and expansion efforts and enhance ecosystem service provisioning worldwide.