洞庭湖流域生态系统服务的权衡效应和驱动分析
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作者单位:

1.南京信息工程大学遥感与测绘工程学院;2.自然资源部遥感导航一体化应用工程技术创新中心;3.中国科学院亚热带农业生态研究所;4.湖南省地质灾害调查监测所

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基金项目:

国家自然科学基金项目(42030111,U20A200110)


Analysis of trade-off effects and driving factors of ecosystem services in the Dongting Lake Basin
Author:
Affiliation:

1.School of Remote Sensing & Geomatics Engineering, Nanjing University of Information Science & Technology;2.Remote Sensing Navigation Integration Application Engineering Technology Innovation Center, ministry of Natural Resources;3.Institute of Subtropical Agriculture, Chinese Academy of Sciences;4.Hunan Institute of Geological Disaster Investigation and Monitoring

Fund Project:

National Natural Science Foundation of China (42030111, U20A200110)

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    摘要:

    全面了解生态系统服务(ES)的复杂相互作用及社会生态驱动因素,有助于促进生态管理决策的有效性。以往研究多集中于单一尺度的ES相互作用,忽视了多尺度下权衡与协同的特征。时空和跨尺度分析有助于揭示ES的空间分异规律,是提升大湖流域生态服务价值的关键。本研究以洞庭湖流域为例,基于InVEST模型量化了2000年、2010年和2020年间的5种关键ES,采用1km栅格和子流域尺度,分析了ES的权衡关系及其尺度特征,并运用SOM算法提取ES簇信息,结合最优参数地理探测器分析驱动因素。研究结果表明:1)粮食供给与其他ES在栅格和子流域尺度上均呈现显著的权衡关系。相比栅格尺度,子流域尺度上水源涵养与粮食供给间的权衡减弱,其他ES之间的权衡效应增强。2)在两个尺度上均识别出5个ES簇,子流域尺度的空间分布更为均匀,簇内聚集度更高。3)地形和气候是主要影响因素,且在子流域尺度上的影响较栅格尺度更为显著。本研究从栅格和子流域角度探讨了ES的相互作用特征和驱动机制,为洞庭湖流域生态管理策略的制定与调整提供了决策支持。

    Abstract:

    A comprehensive understanding of the complex interactions of ecosystem services and socio-ecological driving factors can help promote the effectiveness of ecological management decisions. Previous studies have mostly focused on the interactions of ecosystem services at a single scale, neglecting the characteristics of trade-offs and synergies at multiple scales. Spatiotemporal and cross-scale analysis helps reveal the spatial differentiation rules of ecosystem services, which is key to enhancing the value of ecological services in large lake basins. Taking the Dongting Lake Basin as an example, this study quantified 5 key ecosystem services from 2000, 2010, and 2020 based on the InVEST model, using a 1 km grid and sub-basin scale to analyze the trade-off relationships and their scale characteristics of ecosystem services. The SOM algorithm was used to extract ecosystem service cluster information, combined with the optimal parameter geographic detector to analyze driving factors. The results show that: 1) there is a significant trade-off relationship between food supply and other ecosystem services at both grid and sub-basin scales. Compared to the grid scale, the trade-off between water retention and food supply at the sub-basin scale weakens, while the trade-off effect between other ecosystem services strengthens. 2) Five ecosystem service clusters were identified at both scales, with the spatial distribution at the sub-basin scale being more uniform and the cluster concentration higher. 3) Terrain and climate are the main influencing factors, and their impact at the sub-basin scale is more significant than at the grid scale. This study explores the spatiotemporal characteristics and driving mechanisms of the interactions of ecosystem services from the perspectives of grid and sub-basin, providing decision-making support for the formulation and adjustment of ecological management strategies in the Dongting Lake Basin.

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引用本文

杜亚峰,刘 波,岳跃民,祁向坤,郑鹏飞. 洞庭湖流域生态系统服务的权衡效应和驱动分析[J]. 农业现代化研究, 2025, 46(3): 563-575
DU Yafeng, LIU Bo, YUE Yuemin, QI Xiangkun, ZHENG Pengfei. Analysis of trade-off effects and driving factors of ecosystem services in the Dongting Lake Basin[J]. Research of Agricultural Modernization, 2025, 46(3): 563-575

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  • 收稿日期:2024-12-17
  • 最后修改日期:2025-02-27
  • 录用日期:2025-03-04
  • 在线发布日期: 2025-06-18
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