Ecology and Environmental Sciences ›› 2026, Vol. 35 ›› Issue (4): 551-562.DOI: 10.16258/j.cnki.1674-5906.2026.04.006

• Research Article [Ecology] • Previous Articles     Next Articles

Spatiotemporal Dynamics and Scenario-Based Simulation of Ecosystem Health in the Yellow River Source Region

DU Jiarui(), SONG Qian*(), GAO Wenming   

  1. School of Geological Engineering, Qinghai University, Xining 810016, P. R. China
  • Received:2025-07-13 Revised:2025-10-30 Accepted:2025-12-22 Online:2026-04-18 Published:2026-04-14

黄河源区生态系统健康时空演变与多情景模拟研究

杜嘉睿(), 宋芊*(), 高文明   

  1. 青海大学地质工程学院青海 西宁 810016
  • 通讯作者: *E-mail: 2008990038@qhu.edu.cn
  • 作者简介:杜嘉睿(2002年生),男,硕士研究生,研究方向为生态环境遥感。E-mail: 19591504396@163.com
  • 基金资助:
    青海省基础研究计划项目(2024-ZJ-953);青海大学研究生科学研究与实践创新项目(qdkc-2554)

Abstract:

As the region serves as a critical ecological security barrier in China, the ecosystem health of the source region of the Yellow River directly influences the ecological stability and water resource security of the entire Yellow River Basin. To systematically reveal the spatiotemporal evolution characteristics and underlying mechanisms of ecosystem health in this region, this study established an ecosystem health assessment framework based on the Vigor-Organization-Resilience (VOR) model. Moran’s I spatial autocorrelation analysis was applied to identify clustering patterns of ecosystem health, and the Patch-generating Land Use Simulation (PLUS) model was employed to simulate future trends and potential impacts of ecosystem health under different development scenarios. The results show that: 1) From 2005 to 2020, the ecosystem health index (EHI) exhibited a fluctuating trend of “decline followed by recovery,” with the mean EHI decreasing from 0.477 in 2005 to 0.427 in 2015 and rebounding to 0.441 in 2020. The spatial pattern remained stable, characterized by “higher values in the east and lower values in the west,” with high-health areas concentrated in the southeastern river valley wetlands and low-health areas clustered in the ecologically fragile alpine zones in the northwest. 2) Spatial autocorrelation analysis revealed significant high-high and low-low clusters of ecosystem health, indicating a relatively stable spatial structure. Ecological connectivity in high-value areas has been enhanced, while degradation pressure in low-value areas remains prominent. 3) Scenario simulations suggest that under the cropland protection (GP) scenario in 2030, the mean EHI would increase to 0.454, and the area of high-health regions would expand to 9.31×103 km2, significantly exceeding the outcomes of the natural development (ND) and economic development (ED) scenarios. This highlights the positive effect of ecological conservation policies in improving ecosystem health. This study systematically elucidates the evolutionary patterns, spatial distribution, and driving mechanisms of ecosystem health in the source region of the Yellow River and underscores the critical role of ecological conservation policies in enhancing ecosystem resilience. The findings provide scientific and theoretical support for optimizing land use structures, formulating regional ecological conservation and management strategies, and promoting sustainable ecosystem development in the source region of the Yellow River.

Key words: ecosystem health, spatiotemporal distribution, PLUS model, multi-scenario prediction, source region of the Yellow River

摘要:

黄河源区作为国家生态安全的重要屏障,其生态系统健康直接关系到整个黄河流域的生态稳定与水资源保障能力。为系统揭示该区域生态系统健康的时空演变特征与演化机制,构建了以活力-组织-恢复力(VOR)为核心的生态系统健康评价体系,结合Moran’s I空间自相关分析方法识别健康聚集特征,并通过(PLUS)模型模拟不同发展情景下未来生态系统健康状态的变化趋势及潜在影响。结果表明,1)2005-2020年,黄河源区生态系统健康指数(EHI)呈“先降后升”的波动特征,EHI均值由2005年的0.477下降至2015年的0.427,后回升至2020年的0.441,空间格局长期稳定为“东高、西低”,高健康区域主要分布于东南部河谷湿地,低健康区集中于西北高寒脆弱区。2)空间自相关分析显示,生态健康存在显著的高-高和低-低聚集单元,表明健康水平空间结构趋于稳定,高值区生态连通性增强,低值区退化压力仍然突出。3)情景模拟表明,2030年耕地保护(GP)情景下EHI均值提升至0.454,健康区域面积增至9.31×103 km2,显著高于自然发展(ND)与经济发展(ED)情景,展示出生态保护政策对提升生态系统健康的积极作用。该研究系统揭示了黄河源区生态系统健康的演变规律、空间格局及其驱动机制,强调了生态保护政策在改善生态系统健康中的重要作用。研究成果为优化土地利用结构、制定区域生态保护和管理策略、推动黄河源区生态系统可持续发展提供了科学依据和理论支撑。

关键词: 生态系统健康, 时空演变, PLUS模型, 情景模拟, 黄河源区

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