浙江省生态保护修复优先区识别
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国家社会科学基金重大项目“研究阐释党的二十大精神”(23ZDA105)


Identification of priority areas for ecological protection and restoration in Zhejiang Province based on ecosystem service bundles
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    摘要:

    生态保护修复是维持和提升生态系统稳定性和可持续性的重要举措。识别生态保护修复优先区并进行有规划的生态保护修复能够达到抑制生态环境退化的目的。以浙江省为研究对象,运用生态系统服务价值计算模型、神经网络自组织映射(SOM)聚类分析法、空间统计、Spearman非参数相关性分析等方法,识别生态系统服务簇,分析生态系统服务簇演化和人类活动强度变化特征,识别生态保护修复优先区,探讨不同生态系统服务价值的权衡/协同关系,提出生态保护修复优先区规划策略。结果表明:(1)2000-2021年浙江省生态系统服务空间分布逐渐趋于均衡,生态系统服务价值总量由7279.73亿元降低至6980.28亿元;(2)2000-2021年浙江省人类活动强度显著增加,呈现由西到东、由南到北的递增趋势;(3)2000-2021年浙江省生态系统服务与人类活动强度变化Moran's I指数呈现显著负相关性,说明人类活动强度与生态服务价值两者空间上处于相互制约状态;(4)2000-2021年浙江省 90 县(区)可划分为4类生态系统服务簇,包括:城市中心簇、农业生产簇、核心生态簇和生态保育簇;(5)基于2021年双变量Moran's I指数聚类结果将研究区划分的5种类型分区作为生态保护修复一级分区,以区域内主导生态系统服务簇作为生态保护修复二级分区划分依据。浙江省生态保护修复优先区划分为4个类型,即面积占比14.83%的生态预防治理区、面积占比19.94%的生态调控建设区、面积占比50.23%的核心生态保护区和面积占比15.00%的生态综合提升区。据此,提出不同类型优先分区实施生态保护修复的规划策略。

    Abstract:

    Ecosystem restoration is an important measure to maintain and enhance the stability and sustainability of ecosystems. Identifying priority areas for ecological protection and restoration and conducting planned ecological protection and restoration can achieve the goal of suppressing ecological degradation. Taking Zhejiang Province as the research area, the ecosystem service value calculation model, neural network self-organizing mapping (SOM) cluster analysis method, spatial statistics, Spearman non parametric correlation analysis, and other methods are used to identify ecosystem service clusters, analyze the evolution of ecosystem service bundles and changes in human activity intensity, identify priority areas for ecological protection and restoration, explore the trade-off/synergistic relationship between different ecosystem service values, and propose priority area planning strategies for ecological protection and restoration. The results indicate that: (1) From 2000 to 2021, the spatial distribution of ecosystem services in Zhejiang Province gradually tended to be balanced, and the total value of ecosystem services decreased from 727.973 billion yuan to 698.028 billion yuan; (2) From 2000 to 2021, the intensity of human activities in Zhejiang Province significantly increased, showing an increasing trend from west to east and from south to north; (3) From 2000 to 2021, the Moran's I index showed a significant negative correlation between ecosystem services and changes in human activity intensity in Zhejiang Province, indicating that the intensity of human activity and the value of ecological services are spatially interdependent; (4) From 2000 to 2021, 90 counties in Zhejiang Province can be divided into four types of ecosystem service clusters, including urban center clusters, agricultural production clusters, core ecological clusters, and ecological conservation clusters; (5) Based on the clustering results of the bivariate Moran index in 2021, the five types of zoning in the study area will be classified as the primary zoning for ecological protection and restoration, and the dominant ecosystem service cluster in the region will be used as the basis for the secondary zoning for ecological protection and restoration. The priority areas for ecological protection and restoration in Zhejiang Province were divided into four types, namely the ecological prevention and control area accounting for 14.83%, the ecological regulation and construction area accounting for 19.94%, the core ecological protection area accounting for 50.23%, and the ecological comprehensive improvement area accounting for 15.00%. Based on this, the priority strategies for implementing ecological protection and restoration planning in different types of priority zones were proposed.

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徐彩瑶,崔铭烨,王宁,孔凡斌.浙江省生态保护修复优先区识别.生态学报,2024,44(8):3223~3240

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