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<p>Understanding ecosystem service supply-demand (ESSD) relationships is essential for optimizing resource allocation, supporting land-use planning, and advancing adaptive environmental governance. However, regional heterogeneity and scale effects associated with ESSD mismatches remain insufficiently explored, which constrains their application in spatial governance. This study focused on the Chengdu–Chongqing Urban Agglomeration (CCUA) to elucidate multi-scale ESSD mismatch mechanisms and to inform zonal governance strategies. A self-organizing map was applied to identify ESSD bundles, while redundancy analysis and generalized additive models were used to investigate the underlying drivers of each bundle. The findings revealed that: (1) ESSD mismatches exhibited pronounced spatial heterogeneity across the CCUA. Urban centers were characterized by demand hotspots coinciding with supply cold spots, whereas urban fringes and ecologically rich areas displayed supply surpluses under relatively low demand. (2) Seven ESSD bundles were identified at both scales. At the county level, fewer drivers with stronger explanatory power reflected the aggregation effect, whereby a limited number of dominant factors captured broader spatial patterns. Socio-economic factors dominated ESSD mismatches in urbanized regions, while natural factors influenced mismatches in remote areas. (3) ESSD ratios exhibited nonlinear and scale-dependent responses to key drivers, revealing critical thresholds that could support precision governance. This study provides an integrated analytical framework for diagnosing ESSD mismatches and offers practical insights for multi-level spatial planning and sustainable ecosystem governance.</p>

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Understanding ecosystem service mismatches and their scale-dependent drivers for zoning governance in the Chengdu-Chongqing urban agglomeration

  • 期刊论文

  • 发表日期：

    2026年1月12日

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  • Rou Zhang,
  • Zhanqi Wang,
  • Haiyang Li,
  • Wenyu Lyv

摘要

Understanding ecosystem service supply-demand (ESSD) relationships is essential for optimizing resource allocation, supporting land-use planning, and advancing adaptive environmental governance. However, regional heterogeneity and scale effects associated with ESSD mismatches remain insufficiently explored, which constrains their application in spatial governance. This study focused on the Chengdu–Chongqing Urban Agglomeration (CCUA) to elucidate multi-scale ESSD mismatch mechanisms and to inform zonal governance strategies. A self-organizing map was applied to identify ESSD bundles, while redundancy analysis and generalized additive models were used to investigate the underlying drivers of each bundle. The findings revealed that: (1) ESSD mismatches exhibited pronounced spatial heterogeneity across the CCUA. Urban centers were characterized by demand hotspots coinciding with supply cold spots, whereas urban fringes and ecologically rich areas displayed supply surpluses under relatively low demand. (2) Seven ESSD bundles were identified at both scales. At the county level, fewer drivers with stronger explanatory power reflected the aggregation effect, whereby a limited number of dominant factors captured broader spatial patterns. Socio-economic factors dominated ESSD mismatches in urbanized regions, while natural factors influenced mismatches in remote areas. (3) ESSD ratios exhibited nonlinear and scale-dependent responses to key drivers, revealing critical thresholds that could support precision governance. This study provides an integrated analytical framework for diagnosing ESSD mismatches and offers practical insights for multi-level spatial planning and sustainable ecosystem governance.