## 3 Results and Discussion
### Complex Ecospatial Networks Evaluation
#### 3.2.4 Ecological Node Clustering Coefficient  
The distribution of clustering coefficients in the study area is shown in Figure 9.  
The average clustering coefficient of the ecospatial network in the study area is 0.2174, indicating that the small-world property of the ecospatial network is low. This may be due to the fact that more than 75% of the nodes in the network are connected to a small number of corridors, which are only between 0 and 5. Figure 9b shows that about 41% of the nodes have a clustering coefficient in the range 0-0.1, which is the range with the largest number of nodes, and most of them have a clustering coefficient of 0. The ecological source patches represented by these nodes have very low or do not have clustering features. About 4% of nodes have clustering coefficients in the range 0.9-1, and these nodes have obvious clustering features; 93% of nodes have low clustering coefficients below 0.5, indicating that this ecospatial network does not show obvious clustering properties on the whole. Overall, the value of the clustering coefficient of each node is not concentrated in a specific value range but is relatively scattered in each interval, which also indicates that the network has the property of inhomogeneity; that is, the ecological source patches are unevenly distributed in location, and the network density varies significantly in different regions, which leads to high instability of the ecospatial network structure.  
Figure 10b was also obtained by using the kriging method to predict the distribution of clustering coefficients. On the whole, the clustering coefficients on each land cover type were mainly concentrated in the range of 0-0.08, 0.09-0.20, and 0.21-0.63, and there is no obvious regularity between the land cover types and the clustering coefficient. For nodes on different land cover types, the interval covered by the clustering coefficient is basically the same, indicating that the land cover type does not have a significant effect on the clustering coefficients of the nodes.  
Figure 9: (a) Distribution of clustering coefficient; (b) clustering coefficient distribution histogram.  
The clustering coefficient-degree correlation indicates the relationship between the clustering coefficient and the degree of the node in the ecos spatial network. In order to get a more distinct rule between the two, this paper performed logarithmic processing on the clustering coefficient and the degree, as shown in Figure 11. It shows that with the increase in degree, most of the clustering coefficient tends to increase slowly first and then decrease rapidly, which indicates that most of the nodes that tend to cluster in the network have a smaller degree; that is to say, the average number of corridors connected by the nodes distributed in clusters is often relatively small, while those distributed in fragments are larger, and the nodes bear more responsibility in the network. Once such nodes are destroyed, the impact on the ecos spatial network will be more serious. On the whole, the clustering coefficient of the nodes in the network does not have an obvious reciprocal relation with the degree of the nodes, and there is no obvious linear relationship after the logarithm processing, indicating that the network is a non-hierarchical network.  
Figure 11: (**a**) Clustering coefficient–degree correlation distribution; (**b**,**c**) logarithmic distribution.  
Figure 10: (**a**) Spatial distribution of node clustering coefficient; (**b**) spatial distribution prediction.