基于复杂网络分析法的空间生态网络结构研究

以荒漠绿洲区典型县域磴口县为研究区,将复杂网络分析方法中的点格局分析方法、网络骨架的提取算法和空间结构鲁棒性指标根据实际空间生态网络的特点进行改造,对研究区的空间复杂生态网络的结构进行分析。研究结果表明:7种类型的生态源地节点在较小尺度下均呈现聚集的空间分布格局,随着尺度的增大,逐渐呈现随机分布,最后呈现均匀分布,这种分布特征保证了小尺度和大尺度上生态网络的稳定。水网廊道的密度范围为0~1.46,路网廊道的密度范围为0~2.27,改造Kruskal算法识别出的骨架廊道符合实际情况。现状生态网络初始的连接鲁棒性仅为0.73,优化后生态网络的连接鲁棒性达到1。经过生态节点布局优化后的生态网络节点和边的抗打击破坏能力、恢复能力增强。

Investigation on Complex Spatial Ecological Network Structure Based on Complex Network Analysis Method

The study on the structure of complex space ecological network with spatial attribute information is a blank of the current research on complex network. Dengkou County, a typical county in the desert oasis area, was selected as the study area. The method of point pattern analysis in complex network analysis methods, the algorithm of extracting network skeletons and the robustness index of spatial structure were modified in accordance with the characteristics of the actual spatial ecological network, to analyze the structure of spatial complex ecological network in the study area. The results showed that the nodes of seven types of eco-sources exhibited aggregated spatial distribution pattern at a small scale, which was gradually distributed randomly as the scale increase, and finally distributed uniformly. This distribution feature ensured that ecological networks were stable at both small and large scales. The NDVI and MNDWI values of different types of ecological source had different distribution characteristics. The density of water corridors was ranged from 0 to 1.46, and the density of road corridors was ranged from 0 to 2.27. The framework corridor identified by Kruskal algorithm combined with the ecological network features was in accordance with the actual situation. The initial robustness of the current ecological network was only 0.73, and the robustness of the ecological network after optimization reached 1. Malicious attacks were more destructive than random attacks, but the optimized ecological networks showed stronger anti strike capability, stronger connectivity and stronger robustness of node and edge recovery. After optimization of the ecological node layout, the ecological network nodes and edges were more resistant to attack and destruction and more resilient.