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Integrating InVEST and MaxEnt Models for Ecosystem Service Network Optimization in Island Cities: Evidence from Pingtan Island, China

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  • Jinyan Liu

    (College of Landscape Architecture and Art, Fujian Agriculture and Forestry University, 63 Xiyuangong Rd., Fuzhou 350002, China
    College of Resource and Environmental Sciences, Quanzhou Normal University, 398 Donghai Rd., Quanzhou 362000, China
    These authors contributed equally to this work.)

  • Bowen Jin

    (College of Landscape Architecture and Art, Fujian Agriculture and Forestry University, 63 Xiyuangong Rd., Fuzhou 350002, China
    These authors contributed equally to this work.)

  • Jianwen Dong

    (College of Landscape Architecture and Art, Fujian Agriculture and Forestry University, 63 Xiyuangong Rd., Fuzhou 350002, China)

  • Guochang Ding

    (College of Landscape Architecture and Art, Fujian Agriculture and Forestry University, 63 Xiyuangong Rd., Fuzhou 350002, China)

Abstract

As unique geographical entities, island cities boast abundant ecological resources and profound cultural values, serving as critical hubs for maintaining ecosystem services in coastal transition zones. Ensuring the stability of ecosystem services is strategically significant for sustainable urban development, while the construction of Ecosystem Service Networks (ESNs) has emerged as a core strategy to enhance ecological functionality and mitigate systemic risks. Based on current research gaps, this study focuses on three key questions: (1) How to construct a Composite Ecosystem Service Index (CESI) for island cities? (2) How to identify the Ecosystem Service Networks (ESNs) of island-type cities? (3) How to optimize the ecosystem service networks of island cities? This study selects Pingtan Island as a representative case, innovatively integrating the InVEST and MaxEnt models to conduct a comprehensive assessment of ecological and cultural services. By employing Principal Component Analysis (PCA), a Composite Ecosystem Service Index (CESI) was established. The research follows a systematic technical approach to construct and optimize the ESN: landscape connectivity indices were applied to identify ecological source areas based on CESI outcomes; multidimensional resistance factors were integrated into the Minimum Cumulative Resistance (MCR) model to develop the foundational ecological network; gradient buffer zone analysis and circuit theory were sequentially employed to refine the network structure and evaluate ecological efficacy. Key findings reveal: (1) Landscape connectivity analysis scientifically delineated 20 ecologically valuable source areas; (2) The coupled MCR model and circuit theory established a hierarchical ESN comprising 45 corridors (12 Level-1, 14 Level-2, and 19 Level-3), identifying 5.75 km 2 of ecological pinch points, 7.17 km 2 of ecological barriers, and 84 critical nodes—primarily concentrated in cultivated areas; (3) Buffer zone gradient analysis confirmed 30 m as the optimal corridor width for multi-scale planning; (4) Circuit theory optimization significantly enhanced network current density (1.653→8.224), demonstrating a leapfrog improvement in ecological service efficiency. The proposed “assessment–construction–optimization” integrated methodology establishes an innovative paradigm for deep integration of ecosystem services with urban spatial planning. These findings provide practical spatial guidance for island city planning, supporting corridor design, conservation prioritization, and targeted restoration, thereby enhancing ecosystem service efficiency, biodiversity protection, and resilience against coastal ecosystem fragmentation.

Suggested Citation

  • Jinyan Liu & Bowen Jin & Jianwen Dong & Guochang Ding, 2025. "Integrating InVEST and MaxEnt Models for Ecosystem Service Network Optimization in Island Cities: Evidence from Pingtan Island, China," Sustainability, MDPI, vol. 17(18), pages 1-28, September.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:18:p:8470-:d:1754484
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    References listed on IDEAS

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