Skip to main content
Cornell University
We gratefully acknowledge support from
the Simons Foundation and member institutions.
arxiv logo > q-bio > arXiv:1505.04741

Help | Advanced Search

Quantitative Biology > Populations and Evolution

(q-bio)
[Submitted on 18 May 2015]

Title:Untangling the roles of parasites in food webs with generative network models

Authors:Abigail Z. Jacobs, Jennifer A. Dunne, Cristopher Moore, Aaron Clauset
Download PDF
Abstract: 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
Comments: 17 pages, 7 figures
Subjects: Populations and Evolution (q-bio.PE); Data Analysis, Statistics and Probability (physics.data-an); Quantitative Methods (q-bio.QM)
Cite as: arXiv:1505.04741 [q-bio.PE]
  (or arXiv:1505.04741v1 [q-bio.PE] for this version)
  https://doi.org/10.48550/arXiv.1505.04741
arXiv-issued DOI via DataCite

Submission history

From: Abigail Jacobs [view email]
[v1] Mon, 18 May 2015 18:01:59 UTC (5,684 KB)
Full-text links:

Download:

  • PDF
  • Other formats
(license)
Current browse context:
q-bio.PE
< prev   |   next >
new | recent | 1505
Change to browse by:
physics
physics.data-an
q-bio
q-bio.QM

References & Citations

  • INSPIRE HEP
  • NASA ADS
  • Google Scholar
  • Semantic Scholar
a export bibtex citation Loading...

Bookmark

BibSonomy logo Mendeley logo Reddit logo ScienceWISE logo

Bibliographic and Citation Tools

Bibliographic Explorer (What is the Explorer?)
Litmaps (What is Litmaps?)
scite Smart Citations (What are Smart Citations?)
Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)
  • About
  • Help
  • contact arXivClick here to contact arXiv Contact
  • subscribe to arXiv mailingsClick here to subscribe Subscribe
  • Copyright
  • Privacy Policy
  • Web Accessibility Assistance
  • arXiv Operational Status
    Get status notifications via email or slack