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Large Herbivore Nemabiomes: Patterns of Diversity and Sharing

Citation

Titcomb, Georgia et al. (2022), Large Herbivore Nemabiomes: Patterns of Diversity and Sharing, Dryad, Dataset, https://doi.org/10.25349/D96P6K

Abstract

Amidst global shifts in the distribution and abundance of wildlife and livestock, we have only a rudimentary understanding of ungulate parasite communities and parasite-sharing patterns. We used qPCR and DNA metabarcoding of fecal samples to characterize gastrointestinal nematode (Strongylida) community composition and sharing among 17 sympatric species of wild and domestic large mammalian herbivore in central Kenya. We tested a suite of hypothesis-driven predictions about the role of host traits and phylogenetic relatedness in describing parasite infections. Host species identity explained 27-53% of individual variation in parasite prevalence, richness, community composition, and phylogenetic diversity. Host and parasite phylogenies were congruent, host gut morphology predicted parasite community composition and prevalence, and hosts with low evolutionary distinctiveness were centrally positioned in the parasite-sharing network. We found no evidence that host body size, social-group size, or feeding height were correlated with parasite composition. Our results reflect the interwoven evolutionary and ecological histories of large herbivores and their gastrointestinal nematodes and suggest that host identity, phylogeny, and gut architecture—a phylogenetically conserved trait related to parasite habitat—are the overriding influences on parasite communities. These findings have implications for wildlife management and conservation as wild herbivores are increasingly replaced by livestock.

Methods

We performed DNA metabarcoding for strongylid DNA in fecal samples from a community of large mammalian herbivores in Kenya. 

Usage Notes

Analyses presented in the paper can be reproduced using these files and the scripts provided here and at https://github.com/gtitcomb/nemabiome_herbivores/tree/master/scripts.

The README.txt file describes the scripts and data in the project folder needed to replicate the analyses presented in the paper.

Funding

National Science Foundation, Award: DEB-1556786

National Science Foundation, Award: DEB-1930820

National Science Foundation, Award: IOS-1656527

National Geographic Society, Award: EC-33R-18

National Science Foundation, Award: 1650114