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Partial local mate competition in the wasp <i>Trichogramma euproctidis</i> : the role of emergence sex ratio on female mating behaviour

2010· article· en· W2038107894 on OpenAlexaff
Véronique Martel, Josée Doyon, Guy Boivin

Bibliographic record

VenueEcological Entomology · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsMcGill UniversityAgriculture and Agri-Food Canada
FundersUniversité de Rennes 1
KeywordsBiologyMatingSex ratioCompetition (biology)ParasitoidSex allocationParasitoid waspHymenopteraTrichogrammaZoologyEcologyDemographyPopulationGenetics

Abstract

fetched live from OpenAlex

1. Parasitic wasps with structured populations are generally assumed to follow the local mate competition (LMC) model: females lay only the minimal number of sons necessary to inseminate all daughters in the emergence patch, and increase this number when faced with additional broods from unrelated females. After emergence, daughters mate with local males before dispersing for host location and oviposition. The main predictions from the model have been verified for many species. 2. Conflicting evidence exists on the status of the egg parasitoids Trichogramma regarding their on‐patch versus off‐patch mating. Although the life‐history traits of several species indicate that mating must occur on the emergence patch, recent data suggest that mating could occur outside the natal patch. 3. In this study, we measured the level of off‐patch mating in the egg parasitoid Trichogramma euproctidis using two isofemale lines in a greenhouse experiment. The impact of the sex ratio on the level of off‐patch mating was also tested. 4. The overall off‐patch mating proportion was 40.5% with a range between 0 and 85.7%, and was influenced by the sex ratio on the emergence patch: the more males available at emergence, the less off‐patch mating occurring. 5. The mating structure of this species can be described as partial LMC.

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)0.001
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 score0.232
Threshold uncertainty score0.684

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.000

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 head0.228
Teacher spread0.206 · 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

Citations16
Published2010
Admission routes1
Has abstractyes

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