Your browser doesn't support javascript.
loading
Replicate DNA metabarcoding can discriminate seasonal and spatial abundance shifts in river macroinvertebrate assemblages.
Bush, A; Compson, Z; Rideout, N K; Levenstein, B; Kattilakoski, M; Hajibabaei, M; Monk, W A; Wright, M T G; Baird, D J.
Afiliação
  • Bush A; Lancaster Environment Centre, University of Lancaster, Lancaster, UK.
  • Compson Z; Environment and Climate Change Canada @ Canadian Rivers Institute, Department of Biology, University of New Brunswick, Fredericton, New Brunswick, Canada.
  • Rideout NK; Environment and Climate Change Canada @ Canadian Rivers Institute, Department of Biology, University of New Brunswick, Fredericton, New Brunswick, Canada.
  • Levenstein B; Department of Biological Sciences, Advanced Environmental Research Institute, University of North Texas, Denton, Texas, USA.
  • Kattilakoski M; Environment and Climate Change Canada @ Canadian Rivers Institute, Department of Biology, University of New Brunswick, Fredericton, New Brunswick, Canada.
  • Hajibabaei M; Environment and Climate Change Canada @ Canadian Rivers Institute, Department of Biology, University of New Brunswick, Fredericton, New Brunswick, Canada.
  • Monk WA; Environment and Climate Change Canada @ Canadian Rivers Institute, Department of Biology, University of New Brunswick, Fredericton, New Brunswick, Canada.
  • Wright MTG; Department of Microbiology, University of Helsinki, Helsinki, Finland.
  • Baird DJ; Centre for Biodiversity Genomics and Department of Integrative Biology, University of Guelph, Guelph, Ontario, Canada.
Mol Ecol Resour ; 23(6): 1275-1287, 2023 Aug.
Article em En | MEDLINE | ID: mdl-36999614
ABSTRACT
The 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.
Assuntos
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Rios / Código de Barras de DNA Taxonômico Tipo de estudo: Prognostic_studies Limite: Animals Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Rios / Código de Barras de DNA Taxonômico Tipo de estudo: Prognostic_studies Limite: Animals Idioma: En Ano de publicação: 2023 Tipo de documento: Article