Recommendations for interpreting zooplankton metabarcoding and integrating molecular methods with morphological analyses

Matthews, Stephanie A.; Goetze, Erica; Ohman, Mark D.

doi:10.1093/icesjms/fsab107

Cited by 16 publications

(26 citation statements)

References 51 publications

(65 reference statements)

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“…Bucklin et al (2019) reported significant positive correlations between V9 18S rRNA sequence numbers and microscopic counts for 7 taxonomic groups for which both types of data were available, with significant regressions for three groups: Calanoida, Gastropoda, and Chaetognatha. These results provided promising evidence that DNA metabarcoding using V9 18S rRNA can provide accurate classification and relative quantification for targeted zooplankton groups, which are important goals for applications for ecosystem monitoring (Lamb et al, 2018;Matthews et al, 2021).…”

Section: Integrative Morphological -Molecular Analysis Of Zooplankton...mentioning

confidence: 89%

“…The accuracy and reliability of metabarcoding for (semi)quantitative analysis, including abundance or biomass, of zooplankton has been evaluated in previous studies (Elbrecht and Leese, 2015;Thomas et al, 2016;Bucklin et al, 2019). A consistent finding has been that quantitative estimates are more accurate for highly abundant taxonomic groups or species (e.g., Matthews et al, 2021).…”

Section: S3mentioning

confidence: 98%

“…DNA metabarcoding of zooplankton samples has been used in association with ecosystem monitoring and management in recent years (Mohrbeck et al, 2015;Deagle et al, 2017;Djurhuus et al, 2018;Blanco-Bercial, 2020;Matthews et al, 2021). These efforts have used different molecular protocols and bioinformatics pipelines (Bucklin et al, 2021a).…”

Section: Introduction Metabarcoding Of Zooplankton Diversitymentioning

confidence: 99%

“…The potential of COI metabarcoding has been examined from many perspectives, including accuracy of species-level resolution of biodiversity (Brown et al, 2015;Leray and Knowlton, 2017;Schroeder et al, 2021), availability of reference sequence databases resulting from DNA barcoding efforts (Andújar et al, 2018;Porter and Hajibabaei, 2018;Bucklin et al, 2021b;Singh et al, 2021), and prospects for quantitative analysis related to species abundance and/or biomass (Lamb et al, 2018;Matthews et al, 2021). Challenges and disadvantages of COI as a metabarcode include lack of universal primers and missing groups due to primer-mismatch (Deagle et al, 2014;Clarke et al, 2017;Hajibabaei et al, 2019).…”

Section: Introduction Metabarcoding Of Zooplankton Diversitymentioning

confidence: 99%

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COI Metabarcoding of Zooplankton Species Diversity for Time-Series Monitoring of the NW Atlantic Continental Shelf

et al. 2022

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Marine zooplankton are rapid-responders and useful indicators of environmental variability and climate change impacts on pelagic ecosystems on time scales ranging from seasons to years to decades. The systematic complexity and taxonomic diversity of the zooplankton assemblage has presented significant challenges for routine morphological (microscopic) identification of species in samples collected during ecosystem monitoring and fisheries management surveys. Metabarcoding using the mitochondrial Cytochrome Oxidase I (COI) gene region has shown promise for detecting and identifying species of some – but not all – taxonomic groups in samples of marine zooplankton. This study examined species diversity of zooplankton on the Northwest Atlantic Continental Shelf using 27 samples collected in 2002-2012 from the Gulf of Maine, Georges Bank, and Mid-Atlantic Bight during Ecosystem Monitoring (EcoMon) Surveys by the NOAA NMFS Northeast Fisheries Science Center. COI metabarcodes were identified using the MetaZooGene Barcode Atlas and Database (https://metazoogene.org/MZGdb) specific to the North Atlantic Ocean. A total of 181 species across 23 taxonomic groups were detected, including a number of sibling and cryptic species that were not discriminated by morphological taxonomic analysis of EcoMon samples. In all, 67 species of 15 taxonomic groups had ≥ 50 COI sequences; 23 species had >1,000 COI sequences. Comparative analysis of molecular and morphological data showed significant correlations between COI sequence numbers and microscopic counts for 5 of 6 taxonomic groups and for 5 of 7 species with >1,000 COI sequences for which both types of data were available. Multivariate statistical analysis showed clustering of samples within each region based on both COI sequence numbers and EcoMon counts, although differences among the three regions were not statistically significant. The results demonstrate the power and potential of COI metabarcoding for identification of species of metazoan zooplankton in the context of ecosystem monitoring.

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Section: Integrative Morphological -Molecular Analysis Of Zooplankton...mentioning

confidence: 89%

Section: S3mentioning

confidence: 98%

Section: Introduction Metabarcoding Of Zooplankton Diversitymentioning

confidence: 99%

Section: Introduction Metabarcoding Of Zooplankton Diversitymentioning

confidence: 99%

See 2 more Smart Citations

COI Metabarcoding of Zooplankton Species Diversity for Time-Series Monitoring of the NW Atlantic Continental Shelf

et al. 2022

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“…There might also be biases in our relative prey contributions resulting from PCR, because we did not use PCR replicates. Although PCR biases can be problematic, especially in detecting rare OTUs 34,35 , more reliable results for major mesozooplankton prey could be obtained by using replicate samples. In addition, there is a potential risk of contamination in metabarcoding analysis, such as the inclusion of non-food DNA, laboratory contamination, symbionts of prey, and secondary predation 36 .…”

Section: Discussionmentioning

confidence: 99%

Metabarcoding analysis of trophic sources and linkages in the plankton community of the Kuroshio and neighboring waters

Kobari

Tokumo

Sato

et al. 2021

Sci Rep

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Trophic sources and pathways supporting early life stages are crucial for survival of forage fishes recruiting around the oligotrophic and unproductive Kuroshio. However, information is limited for the Kuroshio planktonic food web and its trophodynamics because of its high biodiversity. Here, we explore trophic sources and linkages in the Kuroshio plankton community using metabarcoding analysis of gut-content DNA for 22 mesozooplankton groups. The major prey was dinoflagellates and calanoids for omnivorous groups, and calanoids and gelatinous organisms for carnivorous groups. Larvaceans and hydrozoans were the most frequently appeared prey for both omnivores and carnivores, whereas they were minor constituents of the available prey in water samples. Although calanoids overlapped as major prey items for both omnivores and carnivores because they were the most available, contributions from phytoplankton and gelatinous prey differed among taxonomic groups. Further analysis of the metabarcoding data showed that in addition to omnivorous copepods like calanoids, gelatinous groups like larvaceans and hydrozoans were important hubs in the planktonic food web with their multiple trophic linkages to many components. These findings suggest that gelatinous organisms are important as supplementary prey and provide evidence of niche segregation on trophic sources among mesozooplankton groups in the Kuroshio.

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Divergent patterns of zooplankton connectivity in the epipelagic and mesopelagic zones of the eastern North Pacific

Matthews,

Blanco‐Bercial

2023

Ecology and Evolution

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Due to historical under‐sampling of the deep ocean, the distributional ranges of mesopelagic zooplankton are not well documented, leading to uncertainty about the mechanisms that shape midwater zooplankton community composition. Using a combination of DNA metabarcoding (18S‐V4 and mtCOI) and trait‐based analysis, we characterized zooplankton diversity and community composition in the upper 1000 m of the northeast Pacific Ocean. We tested whether the North Pacific Transition Zone is a biogeographic boundary region for mesopelagic zooplankton. We also tested whether zooplankton taxa occupying different vertical habitats and exhibiting different ecological traits differed in the ranges of temperature, Chl‐a, and dissolved oxygen conditions inhabited. The depth of the maximum taxonomic richness deepened with increasing latitude in the North Pacific. Community similarity in the mesopelagic zone also increased in comparison with the epipelagic zone, and no evidence was found for a biogeographic boundary between previously delineated mesopelagic biogeochemical provinces. Epipelagic zooplankton exhibited broader temperature and Chl‐a ranges than mesopelagic taxa. Within the epipelagic, taxa with broader temperature and Chl‐a ranges also had broader distributional ranges. However, mesopelagic taxa were distributed across wider dissolved oxygen ranges, and within the mesopelagic, only oxygen ranges covaried with distributional ranges. Environmental and distributional ranges also varied among traits, both for epipelagic taxa and mesopelagic taxa. The strongest differences in both environmental and distributional ranges were observed for taxa with or without diel vertical migration behavior. Our results suggest that species traits can influence the differential effects of physical dispersal and environmental selection in shaping biogeographic distributions.

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Recommendations for interpreting zooplankton metabarcoding and integrating molecular methods with morphological analyses

Cited by 16 publications

References 51 publications

COI Metabarcoding of Zooplankton Species Diversity for Time-Series Monitoring of the NW Atlantic Continental Shelf

COI Metabarcoding of Zooplankton Species Diversity for Time-Series Monitoring of the NW Atlantic Continental Shelf

Metabarcoding analysis of trophic sources and linkages in the plankton community of the Kuroshio and neighboring waters

Divergent patterns of zooplankton connectivity in the epipelagic and mesopelagic zones of the eastern North Pacific

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