COS 141-1
Untangling the roles of parasites in food webs with generative network models

Friday, August 14, 2015: 8:00 AM
323, Baltimore Convention Center
Abigail Z. Jacobs, Department of Computer Science, University of Colorado Boulder, Boulder, CO
Jennifer A. Dunne, Santa Fe Institute, Santa Fe, NM
Cristopher Moore, Santa Fe Institute, Santa Fe, NM
Aaron Clauset, BioFrontiers Institute, University of Colorado Boulder, Boulder, CO

Food webs represent the set of consumer-resource interactions among 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. Furthermore, interactions such as concomitant predation and predation on parasites have unknown impacts on the structure of food webs, further obscuring the roles that parasites play in this context. Here we introduce 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. Using the well-studied Flensburg Fjord food web, we apply this method to investigate the role of parasites on food web structure. 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 found that there is effectively no structural distinction between parasites and free-living species with respect to the model’s representation of predation in a real food web. The probabilistic niche model accurately represented predation among free-living species, predation on parasites, concomitant predation, and parasitic intraguild trophic predation. Conversely, parasite-host interactions were not well captured by the probabilistic niche model. Interestingly, concomitant predation links followed similar patterns to other types of predation on parasites. Observing concomitant links made predation on parasites easier to predict, which suggests that the model is well aligned with the ecological context. Furthermore, concomitant links did not obscure the niche structure of either free-living species or parasites, and concomitant links led to no significant decrease in model fit. The novel discovery that concomitant links, parasitic intraguild trophic interactions and predation on parasites are well-represented by niche structure, but that parasite-host interactions are not naturally recovered by the niche model, sheds new light on the roles of parasite interactions. This work provides a powerful new tool for evaluating hypotheses about the impact of previously underresolved classes of species and interactions on food web structure.