Evidence map›Paper›PMID 38564614›Full record

ArticlePloS one2024

Comparing modern identification methods for wild bees: Metabarcoding and image-based morphological taxonomic assignment.

Cassandra D Smith, Robert S Cornman, Jennifer A Fike, Johanna M Kraus, Sara J Oyler-McCance, Carrie E Givens, Michelle L Hladik, Mark W Vandever, Dana W Kolpin, Kelly L Smalling

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
4.1field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 4 citations in OpenAlex.

  1. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 1 institution in 1 country.

Cassandra D SmithOregon Water Science Center, U.S. Geological Survey, Bend, Oregon, United States of America.ORCID 0000-0003-1088-1772
Robert S CornmanFort Collins Science Center, U.S. Geological Survey, Fort Collins, Colorado, United States of America.
Jennifer A FikeFort Collins Science Center, U.S. Geological Survey, Fort Collins, Colorado, United States of America.
Johanna M KrausColumbia Environmental Research Center, U.S. Geological Survey, Columbia, Missouri, United States of America.ORCID 0000-0002-9513-4129
Sara J Oyler-McCanceFort Collins Science Center, U.S. Geological Survey, Fort Collins, Colorado, United States of America.ORCID 0000-0003-1599-8769
Carrie E GivensUpper Midwest Water Science Center, U.S. Geological Survey, Lansing, Michigan, United States of America.
Michelle L HladikCalifornia Water Science Center, U.S. Geological Survey, Sacramento, California, United States of America.ORCID 0000-0002-0891-2712
Mark W VandeverFort Collins Science Center, U.S. Geological Survey, Fort Collins, Colorado, United States of America.
Dana W KolpinCentral Midwest Water Science Center, U.S. Geological Survey, Iowa City, Iowa, United States of America.
Kelly L SmallingNew Jersey Water Science Center, U.S. Geological Survey, Lawrenceville, New Jersey, United States of America.ORCID 0000-0002-1214-4920
United States Geological Survey · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the decline of bee populations worldwide, studies determining current wild bee distributions and diversity are increasingly important. Wild bee identification is often completed by experienced taxonomists or by genetic analysis. The current study was designed to compare two methods of identification including: (1) morphological identification by experienced taxonomists using images of field-collected wild bees and (2) genetic analysis of composite bee legs (multiple taxa) using metabarcoding. Bees were collected from conservation grasslands in eastern Iowa in summer 2019 and identified to the lowest taxonomic unit using both methods. Sanger sequencing of individual wild bee legs was used as a positive control for metabarcoding. Morphological identification of bees using images resulted in 36 unique taxa among 22 genera, and >80% of Bombus specimens were identified to species. Metabarcoding was limited to genus-level assignments among 18 genera but resolved some morphologically similar genera. Metabarcoding did not consistently detect all genera in the composite samples, including kleptoparasitic bees. Sanger sequencing showed similar presence or absence detection results as metabarcoding but provided species-level identifications for cryptic species (i.e., Lasioglossum). Genus-specific detections were more frequent with morphological identification than metabarcoding, but certain genera such as Ceratina and Halictus were identified equally well with metabarcoding and morphology. Genera with proportionately less tissue in a composite sample were less likely to be detected using metabarcoding. Image-based methods were limited by image quality and visible morphological features, while genetic methods were limited by databases, primers, and amplification at target loci. This study shows how an image-based identification method compares with genetic techniques, and how in combination, the methods provide valuable genus- and species-level information for wild bees while preserving tissue for other analyses. These methods could be improved and transferred to a field setting to advance our understanding of wild bee distributions and to expedite conservation research.

Indexed as

DNA Barcoding, TaxonomicAnimalsBeesDatabases, FactualIowa

Identifiers

PMID38564614
PMCPMC10986983
OpenAlexW4393715748

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.