基于RPV模型的山西省生态系统健康评价及驱动因素分析

Ecosystem health evaluation and driving Force analysis based on RPV model in Shanxi Province

  • 摘要: 准确评估生态系统健康状况与驱动机制对区域生态安全具有重要意义。基于“风险-过程-价值” (RPV)评估模型,构建了包含生态风险、生态稳定性、水土流失和生态系统服务价值等多维度的生态系统健康评价体系,并结合地理探测器和结构方程模型(SEM),探究了山西省2000—2020年生态系统健康状况及驱动机制。结果表明:(1)2000—2020年间,山西省生态系统健康指数呈现稳定上升趋势,平均值由0.16上升至0.20,优、良等级区域显著增加;(2)优、良等级区域主要分布于山地及丘陵,差、较差等级区域主要位于平原及盆地。各等级区域表现为逐年逐级改善,并以相邻区域改善为主。(3)地理探测器与SEM分析表明,生态稳定性与土壤侵蚀量受地形、气候等受自然因素影响显著,生态风险与生态系统服务价值受人类活动影响显著。研究为理解黄土高原脆弱区生态系统健康状况提供了新的视角,并为生态环境修复和可持续管理提供科学参考。

     

    Abstract: Accurately assessing ecosystem health and its driving mechanisms is important for regional ecological security. Based on the "risk-process-value" evaluation framework, this study constructed a multi-dimensional ecosystem health assessment system. Using the geographical detector and structural equation modeling (SEM), this research explored the health status and driving mechanisms of ecosystems in Shanxi Province from 2000 to 2020. The results show that: (1) From 2000 to 2020, the ecosystem health index in Shanxi Province exhibited a stable upward trend, with the average value increasing from 0.16 to 0.20. Areas with excellent and good grades increased notably. (2) Regions with excellent and good health grades were mainly distributed in mountainous areas, whereas poor and relatively poor grades were primarily located in plains and basins. Transitional zones between these areas mostly exhibited moderate health grades. Improvement in health grades occurred progressively year by year, predominantly in adjacent regions. (3) Analyses using the geographical detector and SEM revealed that ecological stability and soil erosion were significantly influenced by natural factors such as topography and climate, whereas ecological risk and ecosystem service value were markedly affected by human activities. This study offers new insights into understanding ecosystem health and provides scientific references for ecological restoration and sustainable management.

     

/

返回文章
返回