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Lookup NU author(s): Dr Jordan CuffORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
Dietary analysis using DNA metabarcoding is a powerful tool that is increasingly being used to further our knowledge of trophic interactions in highly complex food webs but is not without limitations. Omnivores, the most generalist of consumers, pose unique challenges when using such methods. Here, we provide the rationale to understand the problems associated with analysing the complex diets of omnivores. By reviewing existing metabarcoding studies of omnivorous diet, and constructing hypothetical scenarios arising from each, we outline that great caution is required when interpreting sequencing data in such cases. In essence, the problems of accidental consumption and secondary ingestion are significant sources of error when investigating omnivorous diets. The integration of multiple high throughput sequencing markers increases the taxonomic breadth of taxa detected but we reveal how some detections may be misleading. Disentangling which taxa have been deliberately or accidentally consumed by the focal omnivore is challenging and can falsely emphasise those that were not intentionally consumed, obscuring biologically meaningful interactions. Although we suggest ways to disentangle these issues, we urge that the results of such analyses should be interpreted with caution and all possible scenarios for the presence of biota within omnivores given due consideration.
Author(s): Tercel MPTG, Symondson WOC, Cuff JP
Publication type: Article
Publication status: Published
Journal: Molecular Ecology
Year: 2021
Volume: 30
Issue: 10
Pages: 2199-2206
Print publication date: 09/05/2021
Online publication date: 27/03/2021
Acceptance date: 22/03/2021
Date deposited: 03/11/2023
ISSN (print): 0962-1083
ISSN (electronic): 1365-294X
Publisher: Wiley-Blackwell Publishing Ltd.
URL: https://doi.org/10.1111/mec.15903
DOI: 10.1111/mec.15903
Data Access Statement: Data sharing not applicable to this article as no data sets were generated or analysed during the current study.
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