Bridging the ecosystem service supply-demand imbalance: Spatial flow patterns and driving forces in the Yangtze River midstream urban agglomeration, China
Xiaowen Zhou, Xuesong Zhang, Hongjie Peng, Wei Ren, Qiuyu Zou
Abstract
• Develops integrated ES assessment framework with spatial flows and drivers. • Reveals ES deficits (2000–2020): 82% imbalances in urban cores. • FPF outperforms WYF and CSF in optimizing supply–demand imbalance. • Identifies ESF drivers: FPF (multidimensional), WYF (socioeconomic), CSF (natural). • Strongest ES interlinkages emerge at county level. Rapid urbanization has intensified ecosystem service (ES) supply–demand imbalances in urban agglomerations, particularly for food production (FP), water yield (WY), and carbon sequestration (CS). This study analyzes spatial flow patterns and driving forces of these critical services in China’s Yangtze River Midstream Urban Agglomeration (YRMA, 2000–2020). Using Integrated Valuation of Ecosystem Services and Trade-offs model (InVEST) for supply–demand quantification and spatial models (Gaussian Two-Step Floating Catchment Area, Breakpoint-Field Strength model) for ecosystem service flows (ESF) simulation. The Geo-Detector model was applied to identify key drivers of flow volume and direction from natural conditions, landscape characteristics, and socio-economic perspectives. We identified three key findings: (1) Temporal analysis of the supply–demand balance index (SDI) revealed divergent trends, with FP showing steady growth, WY demonstrating fluctuating increases, and CS experiencing continuous decline. Spatially, 82 % of supply–demand imbalances concentrated in core urban areas, with spatial extents progressively expanding. (2) FP flow (FPF) initial flows mitigated local deficits (77,100 t max), enhanced by cross-regional transfers (270,500 t max), while WY flow (WYF) covered 48 % of the entire study area and CS flow (CSF) served only 37 % of imbalanced zones, both limited by non-selective flows. (3) Driving forces displayed specific patterns: FPF was influenced by multiple factors, WYF was primarily socio-economically driven, and CSF was mainly determined by natural conditions. These findings offer critical insights for balancing ESs and guiding ecological policies in urban agglomerations.