<｜begin▁of▁sentence｜>### Instruction:
Imagine we are studying a unique ecosystem of flowering plants, where each plant species (represented by numerical identifiers) has a symbiotic relationship with one or more other species. We have documented these connections as pairs: (1, 2), (1, 3), (2, 3), (3, 4), (4, 5), (5, 6), (4, 6). However, for our current experiment, we wish to focus on the peripheral species—those that are not as deeply connected in this web of interdependency as others. 

To simulate this in our botanical model, we're looking to create a subset of our ecosystem where we remove those species with primary importance in interconnectivity—who share connections with at least one other species—along with any species that might be left without a partnership as a result of this pruning.

Could you employ NetworkX to help us model this trimmed-down version of our ecosystem? This would involve excluding those key species and their direct connections, shedding light on the species that form the outermost layer of our symbiotic network.
### Response:
import networkx as nx

# Create a graph
G = nx.Graph()
G.add_edges_from([(1, 2), (1, 3), (2, 3), (3, 4), (4, 5), (5, 6), (4, 6)])

# Calculate the 1-crust of the graph
k = 1
crust = nx.k_crust(G, k)

# Print the edges of the 1-crust
print('Edges of the 1-crust:', list(crust.edges()))
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