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    内蒙古防沙带生态空间网络结构演变

    Evolution of ecological spatial network structure in sand-prevention belts of Inner Mongolia, northern China

    • 摘要:
        目的  生态空间网络具有保障生态过程、维护生态安全、提升生态系统服务的作用,当前有关研究多针对潜在生态空间网络展开,对现状生态空间网络的研究较少。基于长时间序列土地利用数据,提取现状生态空间网络,分析其结构的演变特征,为优化网络结构、构建区域生态安全格局、提升区域生态服务功能提供重要依据。
        方法  以内蒙古防沙带为研究区,首先以空间形态学分析方法分析研究区1990、1995、2000、2005、2010、2015和2020年多种景观组分的空间分布特征,进而以核心区为节点,以连接桥为边构建了研究区实际生态空间网络,利用复杂网络分析中的度、度分布、直径、平均路径长度、聚类系数等多种拓扑结构指标研究了实际生态空间网络的结构演变特征。
        结果  研究区景观组分以核心区和连接桥为主,30年间分别占研究区面积的32.13%和28.72%,其次为边缘、孤岛和环,其中核心区在不断减少,孤岛逐渐增多。30年间研究区生态空间网络平均度在20.01至39.98范围内波动,度分布幂律特征明显,幂函数指数呈上升趋势。网络直径从1990年的24下降到2020年的17,平均路径长度从1990年的4.20上升到2020年的5.14。30年间连通子图平均数量为61个,且呈现增加趋势,连通子图规模平均为33.35,呈下降趋势。网络具有极强的度度相关性,度与聚类系数之间没有明显的数量关系。
        结论  30年间各指标的变化趋势表明,研究区生态空间网络为无标度非层次同配小世界网络。网络不均匀性较强但有降低趋势,网络局部连接紧密,社团结构明显,但跨社区的长距离连接正在减少,网络正逐渐分裂为互相孤立的多个子图,网络整体连通性有所下降。研究区景观格局的优化可通过建设跨区域的生态廊道、增加各个社团间的连接等措施进行。

       

      Abstract:
        Objective  Ecological spatial networks play an important role in safeguarding ecological processes, maintaining ecological security, and enhancing ecosystem services. Currently, most of the research on ecological spatial networks focuses on potential networks, with relatively little attention paid to the study of existing ecological spatial networks. Based on long-term land use data, the extraction of existing ecological spatial networks and analysis of their structural evolution characteristics provides an important basis for optimizing network structure, constructing regional ecological security patterns, and enhancing regional ecosystem service functions.
        Method  Taking the Inner Mongolia sand-prevention belt as the research area, this study first used spatial morphological analysis method to analyze the spatial distribution characteristics of multiple landscape components in 1990, 1995, 2000, 2005, 2010, 2015, and 2020. Then, using the core area as the node and bridges as edges, the existing ecological spatial network of the research area was constructed. The structural evolution characteristics of the existing ecological spatial network were studied using various topological structure indicators, such as degree, degree distribution, diameter, average path length, and clustering coefficient in complex network analysis.
        Result  The landscape components in the research area were mainly core areas and connecting bridges, which accounted for 32.13% and 28.72% of the research area, respectively, followed by edges, islands and rings. The core area had been decreasing continuously, while the number of islands had been gradually increasing. The average degree of the ecological spatial network in the research area fluctuated between 20.01 and 39.98 over the past 30 years, and the power-law characteristics of degree distribution were obvious, with the power-law index showing an upward trend. The network diameter decreased from 24 in 1990 to 17 in 2020, and the average path length increased from 4.20 in 1990 to 5.14 in 2020. The average number of connected subgraphs was 61 over the past 30 years, showing an increasing trend, while the average size of connected subgraphs was 33.35, showing a decreasing trend. The network had a strong degree-degree correlation, and there was no obvious quantitative relationship between degree and clustering coefficient.
        Conclusion  The trend of various indicators over the past 30 years indicates that the ecological spatial network in the research area is a scale-free, non-hierarchical, assortative small-world network. The network has strong heterogeneity but shows a decreasing trend, with local connections being dense and community structure being obvious. However, long-distance connections across communities are decreasing, and the network is gradually splitting into multiple isolated subgraphs, resulting in a decrease in overall connectivity. Optimization of the landscape pattern in the research area can be achieved through measures such as building cross-regional ecological corridors and increasing connections between different communities.

       

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