Abstract
Dietary DNA metabarcoding enables researchers to identify and characterize trophic interactions with a high degree of taxonomic precision. It is also sensitive to sources of bias and contamination in the field and laboratory. One of the earliest and most common strategies for dealing with such sensitivities has been to remove all low-abundance sequences and conduct ecological analyses based on the presence or absence of food taxa. Although this step is now often perceived to be necessary, evidence of its sufficiency is lacking and more attention to the risk of introducing other errors is needed. Using computer simulations, we demonstrate that common strategies to remove low-abundance sequences can erroneously eliminate true dietary sequences in ways that impact downstream inferences. Using real data from well-studied wildlife populations in Yellowstone National Park, we further show how these strategies can markedly alter the composition of dietary profiles in ways that scale-up to obscure ecological interpretations about dietary generalism, specialism, and composition. Although the practice of removing low-abundance sequences may continue to be a useful strategy to address research questions that focus on a subset of relatively abundant foods, its continued widespread use risks generating misleading perceptions about the structure of trophic networks. Researchers working with dietary DNA metabarcoding data—or similar data such as environmental DNA, microbiomes, or pathobiomes—should be aware of drawbacks and consider alternative bioinformatic, experimental, and statistical solutions.
Original language | English |
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Pages (from-to) | 1615-1626 |
Journal | Molecular Ecology |
Volume | 31 |
Issue number | 6 |
Early online date | 18 Jan 2022 |
DOIs | |
Publication status | Published - 31 Mar 2022 |
Data Availability Statement
Illumina sequence read data and sample metadata have been made available at NCBI (BioProject accession no.: PRJNA780500; Littleford-Colquhoun et al., 2021). Unrarefied/rarefied sequence read tables and plant taxonomy information have been made available at Dryad (https://doi.org/10.5061/dryad.kwh70rz4s). All bioinformatic scripts are available at Zenodo (10.5281/zenodo.5703310).Acknowledgements
We would like to thank the National Park Service, Ecology Project International, and Yellowstone Forever for their help collecting wildlife fecal samples; Brown University students in BIOL 1515/2015 in 2018 and 2020 for their course-based participation in this research; The Howard Hughes Medical Institute and The Sheridan Center for Teaching and Learning for financially supporting student participation; the Brown Multidisciplinary Teaching Laboratory staff; Bruce Davitt for performing microhistological analyses; Douglas Frank for sparking this collaboration on Yellowstone food webs.Funding
Funding was provided by NSF DEB-2046797, DEB-2026294, DEB-1930820, and OIA-2033823.