Replicate DNA metabarcoding can discriminate seasonal and spatial abundance shifts in river macroinvertebrate assemblages

Author:

Bush A.12ORCID,Compson Z.23,Rideout N. K.2,Levenstein B.2,Kattilakoski M.24,Hajibabaei M.5,Monk W. A.6,Wright M. T. G.5,Baird D. J.2ORCID

Affiliation:

1. Lancaster Environment Centre University of Lancaster Lancaster UK

2. Environment and Climate Change Canada @ Canadian Rivers Institute, Department of Biology University of New Brunswick Fredericton New Brunswick Canada

3. Department of Biological Sciences, Advanced Environmental Research Institute University of North Texas Denton Texas USA

4. Department of Microbiology University of Helsinki Helsinki Finland

5. Centre for Biodiversity Genomics and Department of Integrative Biology University of Guelph Guelph Ontario Canada

6. Environment and Climate Change Canada @ Canadian Rivers Institute, Faculty of Forestry and Environmental Management University of New Brunswick Fredericton New Brunswick Canada

Abstract

AbstractThe delivery of consistent and accurate fine‐resolution data on biodiversity using metabarcoding promises to improve environmental assessment and research. Whilst this approach is a substantial improvement upon traditional techniques, critics note that metabarcoding data are suitable for establishing taxon occurrence, but not abundance. We propose a novel hierarchical approach to recovering abundance information from metabarcoding, and demonstrate this technique using benthic macroinvertebrates. To sample a range of abundance structures without introducing additional changes in composition, we combined seasonal surveys with fish‐exclusion experiments at Catamaran Brook in northern New Brunswick, Canada. Five monthly surveys collected 31 benthic samples for DNA metabarcoding divided between caged and control treatments. A further six samples per survey were processed using traditional morphological identification for comparison. By estimating the probability of detecting a single individual, multispecies abundance models infer changes in abundance based on changes in detection frequency. Using replicate detections of 184 genera (and 318 species) from metabarcoding samples, our analysis identified changes in abundance arising from both seasonal dynamics and the exclusion of fish predators. Counts obtained from morphological samples were highly variable, a feature that limited the opportunity for more robust comparison, and emphasizing the difficulty standard methods also face to detect changes in abundance. Our approach is the first to demonstrate how quantitative estimates of abundance can be made using metabarcoding, both among species within sites as well as within species among sites. Many samples are required to capture true abundance patterns, particularly in streams where counts are highly variable, but few studies can afford to process entire samples. Our approach allows study of responses across whole communities, and at fine taxonomic resolution. We discuss how ecological studies can use additional sampling to capture changes in abundance at fine resolution, and how this can complement broad‐scale biomonitoring using DNA metabarcoding.

Publisher

Wiley

Subject

Genetics,Ecology, Evolution, Behavior and Systematics,Biotechnology

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