<｜begin▁of▁sentence｜>### Instruction:
As a conservation scientist, you may be conducting a study to identify clusters within a network of interconnected natural habitats. Imagine you have collected data on the connectivity of different habitat patches, represented as edges between nodes. By utilizing community detection algorithms, such as edge betweenness based community detection provided by the networkx Python library, you can identify the first cluster of closely interconnected habitat patches. This knowledge may assist in determining effective conservation management strategies to protect and preserve biodiversity across the identified cluster.
### Response:
from igraph import Graph

# Define edges and create a graph
g = Graph(edges=[(0, 1), (1, 2), (2, 3), (3, 0), (1, 3)])

# Perform community detection to get a VertexClustering object
vc = g.community_edge_betweenness()

# Get the members of the first cluster
members_of_first_cluster = vc[0]

print(members_of_first_cluster)
<|EOT|>
