Synergistic optimization of ecological supply–demand: Integrating urban green space ecosystem services and dual ecological demands across multiple scenarios

• Developed a synergistic optimization framework integrating urban green space ecosystem service supply with dual ecological needs. • Revealed significant spatial mismatches between supply and demand, projected to intensify under future scenarios. • Identified four synergistic optimization area types and proposed targeted strategies for urban green space planning. • Offered a new perspective on rethinking urban green space to reconcile urban development with biodiversity conservation. Urban green space (UGS) is increasingly expected to deliver ecosystem services (ESs) while safeguarding biodiversity. But in dense cities, limited space and fragmented habitats tend to establish a disconnect between urban development and ecological needs, highlighting the necessity of rethinking green space through synergistic optimization. This research designed a synergistic optimization framework combining the supply of urban green space ecological services (UGS-ESs) and dual ecological requirements of humans and migratory birds. The Patch-generating Land Use Simulation (PLUS) model simulated and projected land use dynamics in Fuzhou’s central area from 2020 to 2030 under various SSP–RCP scenarios initially. The Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model then measured the supply of five prominent ESs from UGS: soil retention (SR), water purification (WP), habitat quality (HQ), carbon storage (CS) and water yield (WY). The demand side was calculated by combining human and migratory bird ecological requirements. Human ecological service demand was measured through two indicators: ecological scarcity and ecological-economic harmony (EEH). Migratory bird demand was determined through habitat suitability and habitat network analysis. Results indicated a great spatial disparity between UGS-ES and human-migratory bird habitat demand. While supply was broadly distributed across the north, south, and east of the city, demand was concentrated in the southwest and northeast, leading to persistent imbalances. The mismatch became more pronounced under different future scenarios. Under SSP1-2.6, surplus areas expanded due to ecological improvements in the north, but rapid demand growth on the urban fringe led to wider deficits. In contrast, under SSP5-8.5, limited demand growth was offset by continued ecological loss, sharply reducing surplus zones and weakening resilience. To address these spatial mismatches and guide targeted management strategies, four types of synergistic optimization areas were delineated based on cluster and overlay analysis, totaling 1,184.99 km 2 : the synergistic intensification area (SIA, 523.79 km 2 ), synergistic buffer area (SBA, 101.89 km 2 ), synergistic regulating area (SRA, 59.20 km 2 ), and synergistic potential area (SPA, 500.11 km 2 ). Restoration priorities, informed by benefit–cost ratio (BCR) analysis, were assigned as SIA > SRA > SPA > SBA, supporting the formulation of differentiated strategies for urban green space enhancement. Each area type reflects a distinct level of compatibility between urban development and biodiversity conservation, highlighting differences in ecological and spatial coordination. This framework provides a practical foundation for strengthening urban–ecology synergy and informing biodiversity-friendly planning and policy.