基于图斑尺度的秦岭陕西段生态保护红线区人为干扰风险评估与溯源分析

A Patch-scale Anthropogenic Disturbance Risk Assessment and Traceability Analysis within Ecological Conservation Redlines in the Qinling Mountains of Shaanxi Province

  • 摘要: 开展生态保护红线内人为干扰的定量评估与诊断研究, 对优化红线管理效能、保障区域生态安全具有重要的理论与实践意义。本文以秦岭陕西段生态保护红线区为研究对象, 以生态破坏图斑为切入点, 基于贝叶斯网络, 开展生态破坏风险评估与诊断分析, 重点探究图斑危险性、图斑可达性与生态敏感性之间的因果传递路径, 旨在定量识别关键胁迫因子并划定风险分区, 以提出差异化的风险调控策略。结果表明: (1)秦岭陕西段生态破坏风险整体处于中等水平, 呈现"整体中度、局部集聚高风险"的空间格局, 高风险区主要位于北麓水源涵养型生态保护红线范围内; (2)图斑危险性、图斑可达性与生态敏感性共同导致生态破坏风险, 其中图斑可达性是驱动空间分异的核心因素, 其对生态敏感性中受体质量的影响尤为直接且显著; (3)生态保护红线内图斑面积占比是首要结构性风险因子, 占比越高则人类活动与生态核心区重叠度越大, 风险水平越显著; 同时图斑形状复杂度越高, 边缘效应越强, 生态稳定性越低。研究揭示了图斑尺度的风险传递机制, 可为该区域生态保护红线差异化管控与风险精准治理提供科学依据。

     

    Abstract: Conducting quantitative assessments and diagnostic research on anthropogenic disturbances within ecological conservation redlines (ECRs) is critical for optimizing the effectiveness of redline management and ensuring regional ecological security. This study focuses on the ECR areas in the Qinling Mountains of Shaanxi Province, adopting ecological damage patches to carry out a preliminary ecological damage risk assessment and traceability analysis. The study aims are to quantitatively identify key stress factors, delineate risk zones, and propose differentiated risk regulation strategies. The results indicate the following: (1) The Shaanxi section of the Qinling Mountains exhibits a spatial pattern characterized by overall moderate risk with localized high-risk clusters. These high-risk clusters are primarily located within the ECR water conservation areas on the northern slopes. (2) Patch hazards, patch accessibility, and ecological sensitivity jointly contribute to ecological damage risk. Among these, patch accessibility is the core factor driving spatial heterogeneity, with a particularly direct and significant impact on ecological receptor quality. (3) The proportion of the ECR areas that overlap with patch areas is the primary structural risk factor. When this proportion is higher, it indicates greater overlap between human activities and ecological core areas, and thus a higher level of risk. Furthermore, greater patch shape complexity results in stronger edge effects and lower ecological stability. In summary, this study clarifies the driving mechanisms of ecological risk through nonlinear quantitative assessment, providing a scientific basis for the differentiated management, source-specific risk prevention and control, and sustainable development of the ECRs in the Qinling Mountains of Shaanxi Province.

     

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