孟凡迪, 周智, 张贵军, 焦翠丽, 阚瑶川, 赵丽. 基于生态系统服务供需与生态恢复力的国土空间生态修复分区−以京津冀为例[J]. 中国生态农业学报 (中英文), 2023, 31(9): 1496−1510. DOI: 10.12357/cjea.20230010
引用本文: 孟凡迪, 周智, 张贵军, 焦翠丽, 阚瑶川, 赵丽. 基于生态系统服务供需与生态恢复力的国土空间生态修复分区−以京津冀为例[J]. 中国生态农业学报 (中英文), 2023, 31(9): 1496−1510. DOI: 10.12357/cjea.20230010
MENG F D, ZHOU Z, ZHANG G J, JIAO C L, KAN Y C, ZHAO L. Land space ecological restoration zoning based on ecosystem service supply and demand and ecological resilience: a case study in the Beijing-Tianjin-Hebei region[J]. Chinese Journal of Eco-Agriculture, 2023, 31(9): 1496−1510. DOI: 10.12357/cjea.20230010
Citation: MENG F D, ZHOU Z, ZHANG G J, JIAO C L, KAN Y C, ZHAO L. Land space ecological restoration zoning based on ecosystem service supply and demand and ecological resilience: a case study in the Beijing-Tianjin-Hebei region[J]. Chinese Journal of Eco-Agriculture, 2023, 31(9): 1496−1510. DOI: 10.12357/cjea.20230010

基于生态系统服务供需与生态恢复力的国土空间生态修复分区以京津冀为例

Land space ecological restoration zoning based on ecosystem service supply and demand and ecological resilience: a case study in the Beijing-Tianjin-Hebei region

  • 摘要: 探究生态系统服务供需匹配特征与生态恢复力属性的耦合关系, 科学划分国土空间生态修复分区, 对生态安全与区域可持续发展具有重要意义。本研究以京津冀区县为研究单元, 基于多源数据, 运用食物产量模型、InVEST模型、CSLE模型等方法测算食物供给、产水、碳固持、土壤保持、休闲游憩等5项生态系统服务的供需量, 构建生态恢复力评价指标体系测算县(区)生态恢复力; 基于“生态系统服务供需+生态恢复力”划定生态修复分区, 并根据分区内部自然和社会经济现状及发展特征提出相应优化策略。结果表明: 1)京津冀生态系统服务供给高值区主要分布在承德市北部、秦皇岛市和唐山市区县, 中部县(区)有零星分布; 需求高值区主要集中在发展较好的京津冀中部及东南部城市, 而北部山区及高原生态系统服务需求较低; 研究区供需关系表现为空间负相关。2)各区县生态恢复力区域性差异明显, 高值区主要聚集在京津冀的东北部。3)研究区生态系统服务综合供需无高度盈余区域, 赤字区域占总面积的42.26%, 主要原因为城市与工业的发展导致系统功能衰退, 生态服务需求难以得到满足。4)结合生态系统服务供需匹配特征和生态恢复力空间分布格局, 将研究区划分为高供给-高需求-高恢复力区(13.68%)、低供给-高需求-低恢复力区(0.51%)、低供给-高需求-高恢复力区(10.54%)、低供给-低需求-低恢复力区(12.07%)、低供给-低需求-高恢复力区(20.22%)、高供给-低需求-高恢复力区(42.98%) 6类, 同时针对不同分区提出差异化的生态修复策略, 为生态修复工程的系统布局提供指引, 为国土空间综合整理方案的科学编制提供方法参考。

     

    Abstract: It is important to explore the coupling relationship between the supply and demand characteristics of ecosystem services and the attributes of ecological resilience, and to scientifically delineate the ecological restoration zones in the national land space for ecological security and regional sustainable development. This study took districts and counties of Beijing, Tianjin, and Hebei as the study unit. Based on multi-source data, the food production model, InVEST model, CSLE model, and other methods were used to measure the supply and demand of five ecosystem services, including food supply, water yield, carbon storage, soil conservation, and recreation supply. An ecological resilience evaluation index system was constructed to measure the ecological resilience of counties (districts). Based on the ecosystem service supply and demand as well as ecological resilience, the ecological restoration zones were delineated, and the corresponding optimization strategies were proposed according to the natural and socio-economic status and development characteristics within the zones. The results showed that: 1) the high-value areas of the ecosystem service supply in the Beijing-Tianjin-Hebei region were mainly distributed in the northern part of Chengde City, Qinhuangdao City, and Tangshan City, and scattered in the central counties (districts) of the region. The high-value areas of ecosystem service demand were mainly concentrated in the well-developed cities in the central and southeastern Beijing-Tianjin-Hebei region, whereas the demand for ecosystem services in the mountainous areas and plateaus in the northern Beijing-Tianjin-Hebei region was low. The supply and demand of ecosystem services in the study area were spatially negatively correlated. 2) The ecological resilience of each district and county had noticeable regional differences, and the high-value areas were mainly concentrated in the northeast of the Beijing-Tianjin-Hebei region. 3) There was no high surplus area in the comprehensive supply and demand of ecosystem services in the study area. The deficit area accounted for 42.26% of the total area, mainly resulting from the decline in system function caused by urban and industrial development, and the demand for ecological services was challenging to meet. 4) Based on the matching characteristics of the supply and demand of ecosystem services and the spatial distribution pattern of ecological resilience, the study area was divided into high supply-high demand-high resilience (13.68%), low supply-high demand-low resilience (0.51%), low supply-high demand-high resilience (10.54%), low supply-low demand-low resilience (12.07%), low supply-low demand-high resilience (20.22%), and high supply-low demand-high resilience (42.98%) areas. At the same time, different ecological restoration strategies were proposed for different areas. This study provides guidance for the systematic layout of ecological restoration projects and a methodological reference for the scientific preparation of comprehensive land space consolidation plans.

     

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