袁文华, 范文君, 李建春, 刘黎明. 黄河流域典型县域生境质量的时空分异特征及影响因素研究[J]. 生态与农村环境学报, 2024, 40(5): 622-633. DOI: 10.19741/j.issn.1673-4831.2023.0741
    引用本文: 袁文华, 范文君, 李建春, 刘黎明. 黄河流域典型县域生境质量的时空分异特征及影响因素研究[J]. 生态与农村环境学报, 2024, 40(5): 622-633. DOI: 10.19741/j.issn.1673-4831.2023.0741
    YUAN Wen-hua, FAN Wen-jun, LI Jian-chun, LIU Li-ming. Research on the Spatiotemporal Differentiation Characteristics and Influencing Factors of Ecological Quality in Typical Counties in the Yellow River Basin[J]. Journal of Ecology and Rural Environment, 2024, 40(5): 622-633. DOI: 10.19741/j.issn.1673-4831.2023.0741
    Citation: YUAN Wen-hua, FAN Wen-jun, LI Jian-chun, LIU Li-ming. Research on the Spatiotemporal Differentiation Characteristics and Influencing Factors of Ecological Quality in Typical Counties in the Yellow River Basin[J]. Journal of Ecology and Rural Environment, 2024, 40(5): 622-633. DOI: 10.19741/j.issn.1673-4831.2023.0741

    黄河流域典型县域生境质量的时空分异特征及影响因素研究

    Research on the Spatiotemporal Differentiation Characteristics and Influencing Factors of Ecological Quality in Typical Counties in the Yellow River Basin

    • 摘要: 通过探索黄河流域山东段县域生境质量时空分异特征与影响因素, 以便从县域尺度为地方生态环境保护与社会经济高质量发展提供政策建议。基于2000、2010和2020年3期土地利用数据, 采用InVEST模型解析生境质量的时空分布格局与演变特征, 结合空间自相关模型对其空间分异特征进行探测, 并采用地理加权回归(GWR)模型分析社会、经济与自然影响因素在空间维度上对生境质量的影响。结果表明: (1)2000-2020年, 黄河流域山东段平均生境质量指数为0.448, 空间上表现出中段、上段低和下段高的分布格局, 生境质量整体呈先快速下降后缓慢下降趋势, 中段生境质量下降趋势最为显著; (2)生境质量变化在空间分布上呈显著集聚性特征, 会受到邻近区域的影响, 且总体集聚态势不断增强, 高-高型集聚区面积明显大于低-低型集聚区, 在流域下段范围连片分布; (3)土地开发强度是影响生境质量时空分布的首要因素, 城市化水平、人口密度和NDVI对生境质量有重要影响, 社会、经济和自然因素共同影响生境质量时空变化, GWR回归分析结果表明生境质量具有空间差异性。识别这些时空差异对推动该区域生态高质量发展具有重要意义。

       

      Abstract: This paper explores the spatio-temporal characteristics and influencing factors of habitat quality along the Yellow River in Shandong Province. It aims to furnish direct policy recommendations that are tailored towards enhancing ecological environmental protection and fostering high-quality socio-economic development at the county level. Using land use data in 2000, 2010 and 2020, the spatio-temporal distribution patterns and evolution characteristics of habitat quality were analysed by InVEST model. On this basis, the spatial autocorrelation model was employed to further explore the spatial differentiation of habitat quality, and subsequently the impact of social, economic, and natural factors on habitat quality were investigated by using the geographically weighted regression (GWR) model. The analysis reveals three results: (1) From 2000 to 2020, the average habitat quality index along the Yellow River in Shandong Province was 0.448, with a spatial distribution pattern where the middle and upper reaches exhibited lower quality, while the lower reaches showed higher quality. The habitat quality in the basin exhibited a decreasing trend with diminishing pace, particularly noting a pronounced downward trend in the middle reaches. (2) Spatially, habitat quality variation displays significant agglomeration, influenced by adjacent regions, and the overall agglomeration trend is consistently increasing. The area of HH-type agglomeration is notably larger than that of LL-type agglomeration, predominantly distributed in the lower reaches of the basin. (3) Land development intensity emerges as the primary factor influencing the spatio-temporal distribution of habitat quality. Population density, urbanization level, and NDVI also play important roles. The GWR model reveals that social, economic, and natural factors together contribute to significant spatial heterogeneity in the temporal and spatial variations of habitat quality. Identifying these spatiotemporal disparities is key to advancing high-quality ecological development in the area.

       

    /

    返回文章
    返回