Network structure
We recorded 163 interactions between 62 snake species and 26 food
resources (Figure 1 and Supplementary material Appendix 1 Figure A6)
that were heterogeneously distributed among snake species, where most of
them had few interactions (56.45% snake species interacted with one or
two resource categories) and few species had many interactions (6.45%
interacted with more than five resources; Supplementary material
Appendix 1 Figure A1). The network structure show moderate connectance
(C = 0.101) (Table 1), indicating that, from the variety of food items
consumed by snakes, the species analysed use, on average, 2-3 resources.
The snake-resource network also show significant nestedness (N = 33.14,
p < 0.01), indicating that 1/3 of the interactions of the less
connected species represent a subset of the interactions of the most
connected species. Finally, the network also show significant modularity
(M = 0.51, p = 0.03), indicating that the number of interactions within
each modules is 51% larger than what is expected for a network with the
same number of modules, the same number of interactions per species, but
with random interactions between species.
Some snake species showed extreme specialisation, such as Dipsasspp., which feed exclusively on mollusks, and Drepanoides
anomalus that rely upon eggs of squamate reptiles. Other species, such
as Atractus spp., although specialist in the consumption of
earthworms, may also feed on insects. Similarly, Micrurus
surinamensis primarily consume fish but secondarily consume lizards and
snakes. On the other hand, we found very generalist species, such asBoa constrictor and Epicrates cenchria , which interacted
with six resource types, Corallus hortulanus , which interacted
with eight resources and Eunectes murinus , the largest species of
the network, which interacted with 11 resources. Among the food
resources consumed by many snake species were lizards (24% of all
interactions), anurans (16%), and small mammals (9%), comprising
rodents and marsupials. Among the least consumed resources were large
mammals (such as cervids), turtles and alligators, only consumed byEunectes murinus , onychophorans only consumed by Micrurus
hemprichii , gymnophiona only consumed by M. lemniscatus , and
salamanders, which were only consumed by Chironius fuscus(Supplementary material Appendix 2 Table A1).
To assess whether there was a difference in network structure based only
on the presence of primary resources in the snake diet, we removed all
non-primary resources and reanalysed the network. Even after removing
the secondary resources, network average degree and connectance remained
within the same range values (Table 1). The results also indicated that
there was no significant difference between the network nestedness
values with and without the presence of secondary resources (p = 0.147).
Even after the removal of non-primary items, the network remained
significantly nested (N = 29.46, p < 0.01). In contrast, the
modular structure was nonsignificant after removal of non-primary
resources (M = 0.47, p = 0.44). Similarity, to check if the type of food
resource categorization could affect the network patterns, we used the
same metrics to analyse the more specific and the less specific
networks. Our results hold even with different levels of detail on
resource description and all networks remained significantly nested and
modular (Supplementary material Appendix 1 Table A2).
Our results supported the prediction that there is a positive
association between the number of resources consumed and average body
size (slope = 1.41, R2 = 0.46, p < 0.01,
Figure 2), indicating that in general the largest species of snakes
showed a greater number of food interactions. Exceptions to this pattern
were Corallus caninus (k = 3) and Lachesis muta (k = 1),
both specialists in the consumption of mammals. Among the seven largest
snake species, five of them (Eunectes murinus, Boa constrictor,
Epicrates cenchria, Corallus hortulanus, and Corallus caninus )
belong to the family Boidae. Thus, this family is over-represented among
the set of heavier snakes in the network and our analysis may be biased
by the confounding factors generated by all other traits shared by boid
species. To circumvent this problem we explored if the correlation
between average body mass and degree holds within speciose snake
families. We performed correlation analyses between degree and average
body mass for species of the family Colubridae and for those of the
family Dipsadidae, the two largest snake families in the network. The
results indicated that a positive correlation between average body mass
and the number of resources consumed hold even for non-boid snakes and
partially controlling for phylogenetic effects, there was (see
Supplementary material Appendix 1 Figure A4 and A5).