Host traits associated with species roles in parasite sharing networks

Published

Journal Article

© 2018 The Authors The community of host species that a parasite infects is often explained by functional traits and phylogeny, predicting that closely related hosts or those with particular traits share more parasites with other hosts. Previous research has examined parasite community similarity by regressing pairwise parasite community dissimilarity between two host species against host phylogenetic distance. However, pairwise approaches cannot target specific host species responsible for disproportionate levels of parasite sharing. To better identify why some host species contribute differentially to parasite diversity patterns, we represent parasite sharing using ecological networks consisting of host species connected by instances of shared parasitism. These networks can help identify host species and traits associated with high levels of parasite sharing that may subsequently identify important hosts for parasite maintenance and transmission within communities. We used global-scale parasite sharing networks of ungulates, carnivores, and primates to determine if host importance – encapsulated by the network measures degree, closeness, betweenness, and eigenvector centrality – was predictable based on host traits. Our findings suggest that host centrality in parasite sharing networks is a function of host population density and range size, with range size reflecting both species geographic range and the home range of those species. In the full network, host taxonomic family became an important predictor of centrality, suggesting a role for evolutionary relationships between host and parasite species. More broadly, these findings show that trait data predict key properties of ecological networks, thus highlighting a role for species traits in understanding network assembly, stability, and structure.

Full Text

Duke Authors

Cited Authors

  • Dallas, TA; Han, BA; Nunn, CL; Park, AW; Stephens, PR; Drake, JM

Published Date

  • January 1, 2019

Published In

Volume / Issue

  • 128 / 1

Start / End Page

  • 23 - 32

Electronic International Standard Serial Number (EISSN)

  • 1600-0706

International Standard Serial Number (ISSN)

  • 0030-1299

Digital Object Identifier (DOI)

  • 10.1111/oik.05602

Citation Source

  • Scopus