<｜begin▁of▁sentence｜>### Instruction:
In the context of forest management and ecological data analysis, imagine we have two distinct representations of ecosystems, which we will refer to as 'Forest Network A' and 'Forest Network B.' Forest Network A has connections representing pathways between Sample Zones 1, 2, and 3, specifically the connections (1, 2), (1, 3), and (2, 3), indicating interlinked ecological zones. On the other hand, Forest Network B consists of Sample Zones labeled 'a', 'b', and 'c' with pathways ('a', 'b'), ('a', 'c'), and ('b', 'c') signifying similar interconnections between these zones.

We seek to understand if these two forest networks represent fundamentally the same underlying structure of ecological connections, which is critical for developing consistent conservation strategies. To determine this, we wish to employ a method akin to the vf2pp_isomorphism algorithm from the NetworkX toolkit in forest management. How can we accurately ascertain if Forest Networks A and B are isomorphic—that is, structurally identical in terms of their connectivity and interrelation of zones—using this advanced algorithm in NetworkX?
### Response:
import networkx as nx

# Create two graphs
G1 = nx.Graph()
G2 = nx.Graph()

# Add some nodes and edges, each graph representing the same structure
G1.add_edges_from([(1, 2), (1, 3), (2, 3)])
G2.add_edges_from([('a', 'b'), ('a', 'c'), ('b', 'c')])

# Call vf2pp_isomorphism to verify if G1 and G2 are isomorphic
iso_mapping = nx.algorithms.isomorphism.vf2pp_isomorphism(G1, G2)

if iso_mapping:
    print('The graphs are isomorphic with the following mapping:', iso_mapping)
else:
    print('The graphs are not isomorphic')
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