## 3 Results
### Results of Topological Indicators  
#### 3.3.1. Results of the Topological Indicators Describing the Ecological Nodes  
The degree of an ecological node indicates the number of ecological corridors it is connected to. In order to more clearly represent the difference in degrees between nodes, we present the results of degrees in the network (Figure 8). The remaining topological indicators of the ecological nodes had values between 0 and 1, as presented in Figure 9. Node 18 had a degree of 13 and was the node with the largest degree. On the other hand, Node 1 and Node 27, which were at the edge of the network, both had a degree of 1 and were the nodes with the smallest degree. In an ecological context, the degree describes the connectivity between ecological nodes. Node 18 was the alpine meadow located in  
Figure 6: Cumulative resistance surface distribution map.  
Qinghai province, which had the highest connectivity in this network. According to its degree, Node 18 had an important position in the network. Node 1 and Node 27 were deciduous broadleaf forest and temperate steppe located in Shandong and Qinghai, and they had the lowest connectivity in the network.  
The clustering coefficient reflects the proportion of connections between the neighboring nodes of the ecological nodes. Node 15 was the node with the largest clustering coefficient in the ecospatial network, and its clustering coefficient was 1. This indicated that all neighboring nodes around Node 15 were connected to each other. Node 21, Node 25, Node 26, and Node 27 were the four ecological nodes with a clustering coefficient of 0. This showed that none of their neighboring nodes were connected to each other.  
Closeness centrality describes the shortest path from a node to all other nodes: the higher the closeness centrality, the more the node is located at the topological center of the network. In this study, the node with the highest closeness centrality was Node 18 and the node with the lowest closeness centrality was Node 27, which means that Node 18 was at the topological center of the network and Node 27 was at the topological edge of the network.  
Betweenness centrality describes the proportion of a node that is located between any two nodes in a network. Nodes with high betweenness centrality play the role of a \"bridge\" in the ecospatial network. In this study, the node with the highest betweenness centrality was Node 20, and the node with the lowest betweenness centrality was Node 27. Thus, if Node 20 is lost, all nodes with a number greater than 20 would be disconnected from the main body of the network (Figure 8). Therefore, Node 20 represented the \"stepping stone\" of the ecospatial network.  
Figure 7: The result map of the ecospatial network of the Yellow River Basin.  
The core purpose of eigenvector centrality is to evaluate a node by the number and importance of its neighboring nodes, and it is a comprehensive indicator to measure the transmission effect and connectivity between nodes. Ecological nodes with high eigenvector centrality are usually surrounded by neighboring nodes that also occupy an important position in escaptial network. Similar to the results of closeness centrality, the nodes with the highest and lowest eigenvector centrality in this study were still Node 18 and Node 27. PageRank is a variant of the eigenvector centrality, and the difference between them is the algorithm for the weight of important nodes. The node with the highest PageRank was still Node 18, while the node with the lowest PageRank was Node 1. It is not difficult to find that the results of the above different topological indicators overlapped. For example, Node 18 was evaluated as the most important node by multiple indicators.