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Record W4410248100 · doi:10.3389/fsufs.2025.1457055

A research hotspot for Microgastrinae parasitoid wasps (Hymenoptera, Braconidae) in North America: DNA barcoding reveals the need for increased taxonomic efforts in dark taxa

2025· article· en· W4410248100 on OpenAlexafffundabout
Melanie Beaudin, Amelie Höcherl, Caroline Boudreault, Catherine I. Cullingham, David R. Lapen, José Fernández-Triana

Bibliographic record

VenueFrontiers in Sustainable Food Systems · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicHymenoptera taxonomy and phylogeny
Canadian institutionsAgriculture and Agri-Food CanadaCarleton University
FundersAgriculture and Agri-Food Canada
KeywordsBraconidaeHymenopteraDNA barcodingParasitoidTaxonBiologyEcologyParasitoid waspTaxonomy (biology)Hotspot (geology)

Abstract

fetched live from OpenAlex

Microgastrinae parasitoid wasps (Hymenoptera: Braconidae) were studied in the St. Lawrence Lowlands ecoregion (~14,100 km 2 ) in Ontario, Canada. This subfamily is one of (if not the) most species-rich clades of Lepidoptera parasitoids and has important applications in the biological control of agricultural pests. The St. Lawrence Lowlands ecoregion is one of the nine southern Canadian ecoregions to be identified as a “crisis ecoregion,” having high biodiversity, high risk of biodiversity loss, and low proportion of land included in protected areas. A total of 3,481 specimens collected from 1905 to 2021 within the region were studied. Two species are recorded for the first time in the Nearctic: Apanteles minornavarroi Fernandez-Triana, 2014 and Protapanteles anchisiades (Nixon, 1973); two species are recorded for the first time in Canada: Promicrogaster virginiana Fernandez-Triana, 2019 and Protapanteles immunis (Haliday, 1834); and two are recorded for the first time in Ontario: Cotesia plathypenae (Muesebeck, 1921) and Alphomelon winniewertzae Deans, 2003. DNA-barcode sequences for 2,173 specimens and 66% of the formally described species were successfully recovered. Using a combination of DNA barcodes and morphological assessment, we document herein a minimum putative species count of 228 and a maximum count of 304. We assess the accuracy of species identification in the ecoregion through DNA barcodes and discuss the use of Barcode Index Numbers (BINs) for species discovery in this taxon. Using BINs, 83% of the formally described species with molecular data can be successfully discriminated. The incredible diversity revealed by DNA-barcoding and the high risk of biodiversity loss in the ecoregion highlight the need for increased taxonomic efforts in this taxon to catalog species before they are potentially lost. Several species are present solely in unique habitats within the study area, such as Sphagnum bogs and wetlands. Other (semi) natural features important for these beneficial insects include hedgerows, riparian zones, ditch banks, and wooded areas. Enrichment of these habitats in proximity to field crops could help maintain microgastrine populations and control Lepidoptera crop pests.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.721
Threshold uncertainty score0.755

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.022
GPT teacher head0.252
Teacher spread0.230 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2025
Admission routes3
Has abstractyes

Explore more

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