[Spatio-temporal Evolution and Driving Force Analysis of Ecosystem Service Supply-demand in Zhejiang Province Based on InVEST-OPGD-RF Framework].

Authors

Yong-Hua Li, Zhe-Hui He, Song Yao, He-Zhou Jiang, Ju-Fang Song

Published in

Huan jing ke xue= Huanjing kexue. Volume 47. Issue 10. Pages 7163-7172. Oct 15, 2026.

Abstract

Ecosystem services are fundamental to sustainable human development， and understanding their spatiotemporal dynamics and driving mechanisms is crucial for regional ecological security. This study quantifies ecosystem service supply （water yield， carbon storage， soil conservation， and habitat quality） and demand （GDP per unit area， population density， and land-use intensity） in Zhejiang Province from 2000 to 2020. Using the InVEST model， we calculate the ecosystem service supply-demand ratio （ESDR） and analyze its spatiotemporal patterns. An optimal parameter-based geographical detector-random forest （OPGD-RF） framework is then applied to unravel driving mechanisms through single-factor， interactional， and multi-factor analyses. Key findings include： ① Ecosystem supply exhibited a southwest-high to northeast-low gradient， with water yield and soil conservation showing U-shaped trends while carbon storage and habitat quality declined continuously. Demand displayed the inverse pattern， with socioeconomic indicators （e.g.， GDP density） concentrated in urban clusters. ② ESDR followed a U-shaped trajectory over time. Spatially， deficits clustered in the Hangzhou-Jiaxing-Huzhou Plain and southeastern coast， while surpluses dominated southwestern mountainous regions. Ecological restoration policies facilitated recovery in some areas. ③ Population density and GDP emerged as core drivers， though NDVI's explanatory power rose significantly. Enhanced interactions between natural and socioeconomic factors jointly shaped ESDR differentiation. These conclusions directly support ecological zoning in territorial spatial planning for the Yangtze River Delta Integrated Demonstration Zone， providing scientific grounding for regional implementation of the Two Mountains theory.

PMID:
42935419
Bibliographic data and abstract were imported from PubMed on 27 Oct 2026.

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