| 基于InVEST-OPGD-RF框架的浙江省县域生态系统服务供需时空演变及驱动力分析 |
| 摘要点击 308 全文点击 7 投稿时间：2025-08-19 修订日期：2025-11-16 |
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| 中文关键词 生态系统服务（ESs） 供需平衡 机器学习 驱动因素 浙江省 县域水平 |
| 英文关键词 ecosystem services（ESs） supply-demand balance machine learning driving factors Zhejiang Province county level |
| DOI 10.13227/j.hjkx.202508174 |
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| 中文摘要 |
| 生态系统服务是支撑人类可持续发展的基础，揭示生态系统服务供需格局的时空演变及深层次驱动机制是保障区域生态安全的关键. 浙江省作为经济发达省份，兼具“七山一水二分田”地理特性，生态系统服务供需矛盾突出. 选取2000~2020年浙江省产水、固碳、土壤保持、生境质量为供给指标，地均GDP、人口密度和土地利用强度为需求指标，结合InVEST模型探究生态系统服务供需比（ESDR）的时空演变特征；再构建地理探测器与随机森林（OPGD-RF）分析框架，从单因子、双因子和多因子这3个视角全面解析其驱动机制. 结果表明：①浙江省生态系统服务供给呈西南高、东北低梯度趋势，产水与土壤保持量呈倒U型变化，碳储量与生境质量持续递减；需求呈东北高、西南低分布，地均GDP等经济社会指标的高值区显著集中于中心城市群. ②ESDR时序呈正U型变化，空间上赤字区集中于杭嘉湖平原及东南沿海，盈余区分布于西南山地，生态修复政策促使部分区域回归盈余. ③人口密度与GDP为核心驱动因子，NDVI解释力持续提升，自然与社会经济因素交互效应增强，共同影响ESDR空间分异. 研究结论可支撑长三角一体化示范区国土空间规划生态专项编制，为区域践行“两山”理念提供科学依据. |
| 英文摘要 |
| 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. |
