MétaCan
Menu
Back to cohort

Reproductive interference between Nehalennia damselfly species

2007· article· en· W2173053806 on OpenAlexaffvenue
Hans Van Gossum, Kirsten Beirinckx, Mark R. Forbes, Thomas N. Sherratt

Bibliographic record

VenueEcoscience · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsCarleton University
Fundersnot available
KeywordsDamselflyBiologyAllopatric speciationOdonataMatingZoologyPopulationSympatryGracilis muscleEcologySympatric speciationDemographyAnatomy

Abstract

fetched live from OpenAlex

We tested the hypotheses that reproductive interference between 2 congeneric damselfly species influences their local population densities and the female morph ratios in one of the species. Nehalennia irene has 2 female types (andromorph and gynomorph), whereas N. gracilis exhibits only one female type. Andromorphic N. irene females not only resemble conspecific males in body coloration, but also resemble heterospecific females of N. gracilis. We predicted male N. irene to be most attracted to gynomorphs of N. irene and male N. gracilis to be least attracted to them. Further, if N. gracilis males harass andromorphic N. irene females excessively, then they may reduce andromorph frequencies of N. irene locally. Our results indicate hybridization to be prevented by a “lock-and-key” mechanism, but male N. irene often attempt mating with female N. gracilis. Contrary to prediction, andromorph frequency in N. irene did not depend on whether N. irene populations were in sympatry or allopatry with N.gracilis. As predicted, N. irene males attempted tandem formation most frequently with conspecific gynomorphs, while N. gracilis males made most heterospecific tandem attempts on N. irene andromorphs. Collectively, our results suggest that N. gracilis females may be frequently harassed by N. irene males, and that this may help explain the relative rarity of N. gracilis.Nomenclature: Walker, 1953.

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 score0.483
Threshold uncertainty score0.257

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)0.0000.000

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 head0.089
GPT teacher head0.235
Teacher spread0.147 · 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

Citations20
Published2007
Admission routes2
Has abstractyes

Explore more

Same venueEcoscienceSame topicPlant and animal studiesFrench-language works237,207