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    杨林哲, 牛腾, 于强, 岳德鹏, 马骏, 裴燕如. 基于复杂网络理论的生态空间优化以松花江流域为例[J]. 北京林业大学学报, 2022, 44(9): 91-103. DOI: 10.12171/j.1000-1522.20210475
    引用本文: 杨林哲, 牛腾, 于强, 岳德鹏, 马骏, 裴燕如. 基于复杂网络理论的生态空间优化以松花江流域为例[J]. 北京林业大学学报, 2022, 44(9): 91-103. DOI: 10.12171/j.1000-1522.20210475
    Yang Linzhe, Niu Teng, Yu Qiang, Yue Depeng, Ma Jun, Pei Yanru. Ecological spatial optimization based on complex network theory: a case study of Songhua River Basin of northeastern China[J]. Journal of Beijing Forestry University, 2022, 44(9): 91-103. DOI: 10.12171/j.1000-1522.20210475
    Citation: Yang Linzhe, Niu Teng, Yu Qiang, Yue Depeng, Ma Jun, Pei Yanru. Ecological spatial optimization based on complex network theory: a case study of Songhua River Basin of northeastern China[J]. Journal of Beijing Forestry University, 2022, 44(9): 91-103. DOI: 10.12171/j.1000-1522.20210475

    基于复杂网络理论的生态空间优化以松花江流域为例

    Ecological spatial optimization based on complex network theory: a case study of Songhua River Basin of northeastern China

    • 摘要:
        目的  快速的城市化发展导致景观破碎化和生态空间网络的破坏,因此合理构建生态空间网络可以促进生态源地之间能量的流动,有效缓解生态环境的恶化。
        方法  以松花江流域为研究对象,基于土地利用数据提取生态源地,运用GIS空间分析技术和MCR模型,筛选生态源地及潜在生态廊道;其次,基于复杂网络方法计算生态源地“度”,运用引力模型计算松花江流域潜在生态廊道“边权”,依据复杂网络中“边权”和“度”得到研究区生态源地“权重”;最后,通过权−度相关性对研究区生态空间网络进行模拟增边优化,分析生态空间网络鲁棒性。
        结果  (1)松花江流域生态空间网络由450个生态源地和1 019条潜在生态廊道组成。(2)在松花江流域生态空间网络中,齐齐哈尔市、大庆市、松原市生态源地斑块聚集度低,生态廊道结构简单,呼伦贝尔市、牡丹江市斑块聚集度高,生态空间网络错综复杂。研究区生态空间网络出现两极分化,生态环境亟需优化。(3)基于复杂网络理论,对松花江流域进行模拟增边优化。共识别增边节点20个,模拟增边24条,模拟增边优化后,网络连接鲁棒性有了明显的增强,松花江流域生态空间网络连通性以及抗干扰能力有很大提升。
        结论  基于MCR模型构建生态空间网络,运用复杂网络理论对松花江流域进行增边优化,提升生态空间网络的鲁棒性,为松花江流域生态空间格局优化奠定了理论基础。

       

      Abstract:
        Objective  Rapid urbanization leads to fragmentation of the landscape and destruction of ecological spatial networks, so the reasonable construction of ecological spatial networks can promote the flow of energy between ecological sources and effectively mitigate the deterioration of the ecological environment.
        Method  Taking the Songhua River Basin as the research object, present study firstly extracted the ecological source area from the land use data, and screened the ecological sources and potential ecological corridors by employing GIS spatial analysis and MCR model. Then, present research calculated the degree of ecological sources based on the complex network method, and calculated the frontier rights of potential ecological corridors in the Songhua River Basin using the gravity model, and then whereby the frontier rights and degree of ecological corridors in the complex network, the weight of the Songhua River Basin can be obtained. Finally, the robustness of the ecological space network in the Songhua River Basin was analyzed by simulating the increased edge optimization through the weight-degree correlation.
        Result  (1) The ecological space network of the Songhua River Basin was composed of 450 ecological sources and 1 019 potential ecological corridors. (2) In the ecological space network of the Songhua River Basin, the ecological source patches in Qiqihar, Daqing and Songyuan were low in aggregation and the ecological corridor structure was simple, while the patches in Hulunbeier and Mudanjiang were high in aggregation and the ecological space network was intricate and complex. Accordingly, the ecological space network in the study area was polarized, and the ecological environment needs to be optimized urgently. (3) Based on the complex network theory, 20 increased edge nodes were identified and 24 increased edges were simulated through simulating the increased edge optimization of the Songhua River Basin. Simultaneously, the network connectivity robustness had been significantly enhanced after the increased edge optimization, and the connectivity and anti-disturbance ability of the ecological space network in the Songhua River Basin had been greatly improved.
        Conclusion  The ecological space network is constructed based on the MCR model, and the complex network theory is applied to increase edge optimization of the Songhua River Basin, which improves the robustness of the ecological space network and lays a theoretical foundation for the optimization of the ecological space pattern for Songhua River Basin.

       

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