张亚丽, 黄柱军, 田义超, 等. 桂西南喀斯特峰丛洼地流域生境质量时空变化及驱动机制[J]. 生态与农村环境学报, 2024, 40(7): 877-887. DOI: 10.19741/j.issn.1673-4831.2023.0906
    引用本文: 张亚丽, 黄柱军, 田义超, 等. 桂西南喀斯特峰丛洼地流域生境质量时空变化及驱动机制[J]. 生态与农村环境学报, 2024, 40(7): 877-887. DOI: 10.19741/j.issn.1673-4831.2023.0906
    ZHANG Ya-li, HUANG Zhu-jun, TIAN Yi-chao, et al. Spatio-temporal Evolution Characteristics and Driving Mechanism of Habitat Quality in the Karst Peak Cluster Depression Basin of Southwestern Guangxi[J]. Journal of Ecology and Rural Environment, 2024, 40(7): 877-887. DOI: 10.19741/j.issn.1673-4831.2023.0906
    Citation: ZHANG Ya-li, HUANG Zhu-jun, TIAN Yi-chao, et al. Spatio-temporal Evolution Characteristics and Driving Mechanism of Habitat Quality in the Karst Peak Cluster Depression Basin of Southwestern Guangxi[J]. Journal of Ecology and Rural Environment, 2024, 40(7): 877-887. DOI: 10.19741/j.issn.1673-4831.2023.0906

    桂西南喀斯特峰丛洼地流域生境质量时空变化及驱动机制

    Spatio-temporal Evolution Characteristics and Driving Mechanism of Habitat Quality in the Karst Peak Cluster Depression Basin of Southwestern Guangxi

    • 摘要: 生境质量是区域生态系统生命有机体可持续发展的生存条件和基础, 更是区域生态环境保护和土地利用规划政策制定的重要理论基础。桂西南峰丛洼地流域是珠江流域重要的生态屏障, 也是我国重要的水源涵养区和生物多样性优先保护区。基于2000、2010和2020年土地利用及驱动力因子数据, 利用CA-Markov模型模拟预测2030年自然发展情景、粮食安全情景和生态保护情景下的土地利用格局, 并在此基础上, 基于InVEST模型对研究区2000-2020及2030年不同情景下生境质量进行评估。结果表明: (1)2000、2010和2020年生境质量平均指数分别为0.776、0.785和0.793, 生境质量水平整体较高。(2)2030年自然发展、粮食安全和生态保护情景下生境质量平均指数分别为0.798、0.779和0.807, 生态保护情景下高生境质量区域面积增加最多, 自然发展情景下次之, 耕地保护情景下高生境质量区域面积占比则低于2010和2020年。(3)土地利用类型是桂西南峰丛洼地流域生境质量空间分异的主导因素, 其后依次为NDVI、高程、坡度和石漠化程度, 气候环境的综合解释力较小。为了改善喀斯特区域生态环境, 应严格执行国土空间规划划定的各项保护边界, 合理控制建设用地发展规模, 优化生态补偿机制, 落实退耕还林、退耕还草等生态修复政策。

       

      Abstract: Habitat quality reflects the ecological status of a region, serving as the foundation for all ecosystem services and functions, and is crucial for formulating policies on regional ecological protection and land use planning. The peak cluster depression basin in southwest Guangxi is a vital ecological barrier within the Pearl River basin, and it is also a significant area for water conservation and biodiversity protection in China. This study utilizes land use data and driving factors from 2000, 2010, and 2020. The CA Markov model is employed to simulate and predict land use for 2030 under three scenarios: natural development, food security, and ecological protection. Subsequently, the InVEST model is used to assess habitat quality across these scenarios from 2000 to 2030. The findings reveal that: (1) The average habitat quality indices for 2000, 2010, and 2020 were 0.776, 0.785, and 0.793 respectively, indicating a generally high level of habitat quality. (2) For 2030, the average habitat quality indices under the natural development, food security, and ecological protection scenarios would be 0.798, 0.779, and 0.807 respectively. The ecological protection scenario showed the greatest increase in high-quality habitat area, followed by the natural development scenario. The high-quality habitat area under the food security scenario will be lower than in 2020, and even lower than in 2010. (3) Land use type was the primary factor influencing habitat quality spatial variation in the peaked depression watersheds of southwestern Guangxi, followed by NDVI, elevation, slope, and the degree of rocky desertification. The combined explanatory power of the climatic environment was relatively minor. To enhance the ecological environment in Karst Plateau areas, it is imperative to strictly enforce the protection boundaries defined in land use planning, reasonably control the development scale of construction land, optimize the ecological compensation mechanisms, and implement ecological restoration policies such as Grain for Green and grassland restoration.

       

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