Ecological Management Zoning Based on the Supply–Demand Relationship and Synergies of Urban Forest Ecosystem Services: A Case Study from Fuzhou, China

Abstract

Urban forests, as vital components of green infrastructure, provide essential ecosystem services (ESs) that support urban sustainability. However, rapid urban expansion and increased density threaten these forests, creating significant imbalances between the supply and demand for these services. Understanding the characteristics of ecosystem services and reasonably dividing ecological management zones are crucial for promoting sustainable urban development. This study introduces an innovative ecological management zoning framework based on the matching degree and synergies relationships of ESs. Focusing on Fuzhou’s fourth ring road area in China, data from 1038 urban forest sample plots were collected using mobile LIDAR. By integrating the i-Tree Eco model and Kriging interpolation, we assessed the spatial distribution of four key ESs—carbon sequestration, avoided runoff, air purification, and heat mitigation—and analyzed their supply–demand relationships and synergies. Based on these ecological characteristics, we employed unsupervised machine learning classification to identify eight distinct ecological management zones, each accompanied by targeted recommendations. Key findings include the following: (1) ecosystem services of urban forests in Fuzhou exhibit pronounced spatial heterogeneity, with clearly identifiable high-value and low-value areas of significant statistical relevance; (2) heat mitigation, avoided runoff, and air purification services all exhibit synergistic effects, while carbon sequestration shows trade-offs with the other three services in high-value areas, necessitating targeted optimization; (3) eight ecological management zones were identified, each with unique ecological characteristics. This study offers precise spatial insights into Fuzhou’s urban forests, providing a foundation for sustainable ecological management strategies.