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Record W3199416649 · doi:10.4039/tce.2021.43

The impact of parasitoids on diamondback moth in Europe: a life table approach

2021· article· en· W3199416649 on OpenAlexafffundabout
Tim Haye, Tina Dancau, Andrew M. R. Bennett, Peter G. Mason

Bibliographic record

VenueThe Canadian Entomologist · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect-Plant Interactions and Control
Canadian institutionsAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food CanadaLeibniz-GemeinschaftGottfried Wilhelm Leibniz Universität Hannover
KeywordsDiamondback mothPlutellaPlutellidaeParasitismBiologyBraconidaeLepidoptera genitaliaPupaParasitoidEcologyLarvaHost (biology)

Abstract

fetched live from OpenAlex

Abstract Diamondback moth, Plutella xylostella (Linnaeus) (Lepidoptera: Plutellidae), was first recorded in North America from Europe about 150 years ago and can be a significant pest of canola in Western Canada. Because parasitism of P. xylostella in Canada is generally low, the introduction of one or more additional exotic parasitoids from Europe is being considered to increase the suppression of P. xylostella populations. Life table studies to determine the impact of parasitoids on diamondback moth populations in Europe were conducted in northwestern Switzerland in 2014–2016. Net reproductive rates were found to be less than one in seven out of eight life tables, suggesting that P. xylostella populations in Switzerland are mostly driven by immigration and recolonisation. In total, seven primary parasitoid species and one hyperparasitoid were associated with diamondback moth. Pupal parasitism by D. collaris reached up to 30%, but because generational mortality was mainly driven by abiotic mortality factors and predation of larvae, the overall contribution of pupal parasitism was low (< 6%). In regions of Canada, where P. xylostella may have increasing populations and low larval mortality, the addition of D. collaris may be a promising approach. Life table studies across Canada are necessary to determine the need for such intervention.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.412
Threshold uncertainty score0.471

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.021
GPT teacher head0.240
Teacher spread0.219 · 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

Citations4
Published2021
Admission routes3
Has abstractyes

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