  Food webs represent the set of consumer-resource interactions among a set of
species that co-occur in a habitat, but most food web studies have omitted
parasites and their interactions. Recent studies have provided conflicting
evidence on whether including parasites changes food web structure, with some
suggesting that parasitic interactions are structurally distinct from those
among free-living species while others claim the opposite. Here, we describe a
principled method for understanding food web structure that combines an
efficient optimization algorithm from statistical physics called parallel
tempering with a probabilistic generalization of the empirically well-supported
food web niche model. This generative model approach allows us to rigorously
estimate the degree to which interactions that involve parasites are
statistically distinguishable from interactions among free-living species,
whether parasite niches behave similarly to free-living niches, and the degree
to which existing hypotheses about food web structure are naturally recovered.
We apply this method to the well-studied Flensburg Fjord food web and show that
while predation on parasites, concomitant predation of parasites, and parasitic
intraguild trophic interactions are largely indistinguishable from free-living
predation interactions, parasite-host interactions are different. These results
provide a powerful new tool for evaluating the impact of classes of species and
interactions on food web structure to shed new light on the roles of parasites
in food webs
