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    黄河流域生态系统服务价值时空异质性及驱动因素分析

    Spatiotemporal heterogeneity and driving factors of ecosystem service value in the Yellow River Basin

    • 摘要:
      目的 在黄河流域生态恢复背景下,研究生态系统服务价值(ESV)的时空动态演变特征及其驱动因素,为可持续发展提供理论参考。
      方法 基于2001—2020年20期的黄河流域土地利用数据,计算黄河流域ESV,利用空间自相关和探索性时空数据分析,揭示黄河流域ESV的时空分异动态特征,并引入时空地理加权回归模型探究黄河流域ESV时空分异的驱动因素。
      结果 (1)2001—2020年黄河流域ESV整体呈上升趋势,生态系统服务中调节服务价值所占比重最大。不同土地利用类型中,草地和林地所提供的生态服务价值最高。(2)黄河流域ESV空间上存在显著正相关。大多数地区,局部空间自相关指标时间路径的相对长度和弯曲度较小,结构比较稳定,但空间依赖效应较弱。ESV移动方向中负向协同增长占比最大,呈低速增长特征。2001—2020年ESV时空凝聚概率超过80%,说明黄河流域ESV局部空间格局呈现相对锁定状态。(3)流域ESV驱动因素中,年降雨量主要起负向作用,年均气温和植被覆盖则主要起正向作用,而人口密度与夜间灯光指数的影响作用相对较弱。
      结论 黄河流域ESV增长现状相对稳定,短期内较难改变,在影响ESV变化的因素中自然因素起主导作用。

       

      Abstract:
      Objective This paper aims to study the spatiotemporal dynamic evolution characteristics and driving factors of ecosystem service value (ESV) in the context of ecological restoration in the Yellow River Basin, and provide theoretical reference for sustainable development.
      Method Based on the land use data of the Yellow River Basin from 2001 to 2020, the ESV of the Yellow River Basin was calculated. Spatial autocorrelation and exploratory spatiotemporal data analysis (ESTDA) were used to reveal the dynamic characteristics of spatiotemporal differentiation of ESV in the Yellow River Basin. The spatiotemporal geographic weighted regression (GTWR) model was introduced to explore the driving factors of spatiotemporal differentiation of ESV in the Yellow River Basin.
      Result (1) From 2001 to 2020, the ESV of the Yellow River Basin showed an overall upward trend, and the value of regulation services accounted for the largest proportion of ecosystem services. Among different land use types, grassland and forest land provided the highest ecological service value. (2) There was a significant positive correlation in the spatial distribution of ESV in the Yellow River Basin. In most regions, the relative length and curvature of the local spatial autocorrelation index time path were relatively small, and the structure was relatively stable, but the spatial dependence effect was weak. The proportion of negative synergistic growth in the direction of ESV movement was the highest, showing a low-speed growth characteristics. The probability of spatiotemporal aggregation of ESV from 2001 to 2020 exceeded 80%, indicating that the local spatial pattern of ESV in the Yellow River Basin was in a relatively locked state. (3) Among the driving factors of watershed ESV, annual rainfall mainly played a negative role, while annual average temperature and vegetation cover mainly played a positive role, while the impact of population density and nighttime light index was relatively weak.
      Conclusion The current situation of ESV growth in the Yellow River Basin is relatively stable and difficult to change in the short term. Natural factors play a dominant role in influencing ESV changes.

       

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