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应用生态学报 ›› 2026, Vol. 37 ›› Issue (7): 2293-2304.doi: 10.13287/j.1001-9332.202607.022

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上海市生态系统服务格局演变、权衡协同关系与服务簇特征的多情景模拟

田峰1,2, 胡宇霞3*, 余兆武3   

  1. 1上海市建设用地和土地整理事务中心, 上海 200003;
    2自然资源部大都市区国土空间生态修复工程技术创新中心, 上海 200003;
    3复旦大学环境科学与工程系, 上海 200438
  • 收稿日期:2026-03-13 接受日期:2026-05-20 出版日期:2026-07-18 发布日期:2027-01-18
  • 通讯作者: *E-mail: 24110740052@m.fudan.edu.cn
  • 作者简介:田 峰, 男, 1976年生, 博士, 高级工程师。主要从事国土空间规划、国土整治和生态保护修复研究。E-mail: tfdy@21cn.com
  • 基金资助:
    国家重点研发计划项目(2024YFF1307000)、国家自然科学基金项目(42571103)、国家自然科学基金委国际合作项目(4251101264)和上海市科技计划项目(25692112600)资助。

Multi-scenario simulation of ecosystem service pattern evolution, trade-off and synergy relationships, and service cluster characteristics in Shanghai, China

TIAN Feng1,2, HU Yuxia3*, YU Zhaowu3   

  1. 1Shanghai Land Consolidation and Rehabilitation Center, Shanghai 200003, China;
    2Technology Innovation Center for Land Spatial Eco-restoration in Metropolitan Area, Ministry of Natural Resources, Shanghai 200003, China;
    3Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China
  • Received:2026-03-13 Accepted:2026-05-20 Online:2026-07-18 Published:2027-01-18

摘要: 在全球气候变化与快速城市化叠加背景下,厘清多情景下城市生态系统服务格局演变及其权衡协同关系,对构建功能分区和空间治理具有重要意义。本研究以上海市为研究区,基于2020年土地利用数据、气象数据和土壤数据,采用intPLUS模型模拟2050年3种共享社会经济路径(SSP)情景下(低排放、生态保护路径,SSP126;中等排放、适度发展路径,SSP245;高排放、高经济增长路径,SSP585)生境质量、碳储量、土壤保持和水源涵养4项生态系统服务,分析其演变特征,并开展像元尺度权衡协同识别和自组织映射服务簇划分。结果表明:2020年,上海市生态系统服务表现出外围高、中心低的空间特征,高值区主要集中于崇明、西部农业空间及外围生态空间,中心建成区普遍较低。2050年,3种情景下的生态系统服务总体上延续“外围高、中心低”的空间格局,其中,与2020年相比,生境质量和碳储量空间格局总体稳定;土壤保持和水源涵养功能对情景较敏感,土壤保持在SSP126、SSP245、SSP585情景下依次增加(增幅分别为56.7%、58.8%、61.6%),水源涵养在SSP126情景下不显著减少(减幅83.1%)、在SSP245和SSP585情景下不显著增加(增幅分别为72.8%、73.9%)。权衡协同分析表明,生境质量与碳储量保持稳定协同,生境质量与水源涵养、土壤保持总体表现为权衡关系,水源涵养与土壤保持则由SSP126下的权衡主导转向SSP245和SSP585下的协同主导。生态系统服务簇分析将研究区划分为碳汇调节区、生态保育区、产水优势区和水土保持区4类功能区,为面向未来不确定性的分区管控提供了空间框架。研究结果有助于深化对超大城市生态系统服务多功能耦合及其情景响应机制的认识,并可为上海及类似高密度城市的生态空间优化和差异化治理提供科学依据。

关键词: 生态系统服务簇, 生态功能分区, 多情景模拟, 自组织映射, 权衡协同

Abstract: Under the dual pressures of global climate change and rapid urbanization, clarifying the evolution of urban ecosystem service patterns and their trade-off and synergy relationships under multiple scenarios is important for constructing functional zoning and spatial governance frameworks. We used land use data, meteorological data, and soil data of 2020 to simulate four ecosystem services in Shanghai, namely habitat quality, carbon storage, soil conservation, and water conservation, under three shared socioeconomic pathway scenarios (SSP126, representing a low-emission and ecological protection pathway; SSP245, representing a medium-emission and moderate development pathway; and SSP585, representing a high-emission and high-economic-growth pathway) in 2050 using the intPLUS model. Then, we analyzed the evolutionary characteristics, and identified pixel-scale trade-off and synergy relationship and conducted self-organizing map-based service cluster classification. The results showed that Shanghai's ecosystem services in 2020 showed a spatial pattern characterized by higher values in peripheral areas and lower values in the urban center. High-value areas were mainly concentrated in Chongming, western agricultural areas, and peripheral ecological spaces, whereas the central built-up area generally showed lower values. By 2050, ecosystem services under the three scenarios generally continued the spatial pattern of high at the periphery and low in the center. Compared with 2020, the spatial patterns of habitat quality and carbon storage remained generally stable, whereas soil conservation and water conservation were more sensitive to scenario changes. Soil conservation showed increases under SSP126, SSP245, and SSP585, with proportions of 56.7%, 58.8%, and 61.6%, respectively. Water conservation mainly showed decrease under SSP126, with a proportion of 83.1%, but showed increases under SSP245 and SSP585, with proportions of 72.8% and 73.9%, respectively. The trade-off/synergy analysis showed that habitat quality and carbon storage maintained a stable synergistic relationship, while habitat quality generally exhibited trade-off relationships with water conservation and soil conservation. The relationship between water conservation and soil conservation shifted from trade-off dominance under SSP126 to synergy dominance under SSP245 and SSP585. The ecosystem service cluster analysis classified the study area into four functional zones: carbon sink regulation zone, ecological conservation zone, water yield advantage zone, and soil conservation zone, providing a spatial framework for zoning management under future uncertainty. The results would help deepen the understanding of multifunctional coupling and scenario-response mechanisms of ecosystem services in megacities, and provide a scientific basis for ecological spatial optimization and differentiated governance in Shanghai and other high-density cities.

Key words: ecosystem service cluster, ecological functional zoning, multi-scenario simulation, self-organizing map, trade-off and synergy