<｜begin▁of▁sentence｜>### Instruction:
As a marine biologist deeply involved in ecosystem analysis and conservation efforts, you're engaged in deciphering the intricate relationships within marine communities. Imagine you're studying a vast coral reef ecosystem, brimming with diverse species interconnections. To aid in your research, you possess a comprehensive dataset encapsulating the network of interactions among various marine organisms, akin to the High-energy theory collaborations graph represented in a gml file named hep-th.gml.

In your quest to unveil the underlying structure of this ecosystem, you seek to employ advanced computational techniques. Leveraging the Lemon function from the Community Detection Library (cdlib), you aim to identify distinct communities within this complex network. Additionally, you possess a set of seed nodes, representing key species or habitat features whose influence you wish to explore further.

Your objective is clear: utilize the Lemon function from the cdlib API to conduct community detection on the provided network, utilizing the specified seed nodes as a starting point. Once the analysis is complete, you anticipate obtaining a detailed breakdown of the detected communities, shedding light on the intricate web of relationships within the marine ecosystem.
### Response:
import networkx as nx
from cdlib import algorithms

# Read the graph from the GraphML file
G = nx.read_gml('hep-th.gml')

# Define a list of seed nodes that will be used to find the community
seeds = [0, 1, 2]  # Replace with actual node identifiers from your graph

# Apply the LEMON community detection algorithm
coms = algorithms.lemon(G, seeds, min_com_size=2, max_com_size=5)

# Print the communities detected
for community in coms.communities:
    print(community)
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