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Reproductive ageing and sexual selection on male body size in a wild population of antler flies (<i>Protopiophila litigata</i>)

2005· article· en· W2151791056 on OpenAlexaff
Russell Bonduriansky, Chad E. Brassil

Bibliographic record

VenueJournal of Evolutionary Biology · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsToronto ZooUniversity of Toronto
Fundersnot available
KeywordsBiologySexual selectionAntlerLongevityAgeingMatingReproductionSelection (genetic algorithm)Life history theoryPopulationTrade-offReproductive successSexual reproductionZoologyLife historyEcologyDemographyGenetics

Abstract

fetched live from OpenAlex

Little is known about the importance of trade-offs between ageing and other life history traits, or the effects of ageing on sexual selection, particularly in wild populations suffering high extrinsic mortality rates. Life history theory suggests that trade-offs between reproduction and somatic maintenance may constrain individuals with higher initial reproductive rates to deteriorate more rapidly, resulting in reduced sexual selection strength. However, this trade-off may be masked by increased condition dependence of reproductive effort in older individuals. We tested for this trade-off in males in a wild population of antler flies (Protopiophila litigata). High mating rate was associated with reduced longevity, as a result of increased short-term mortality risk or accelerated ageing in traits affecting viability. In contrast, large body size was associated with accelerated ageing in traits affecting mating success, resulting in reduced sexual selection for large body size. Thus, ageing can affect sexual selection and evolution in wild populations.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.015
GPT teacher head0.248
Teacher spread0.234 · 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 source (direct Gemma or distilled Codex), 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

Citations83
Published2005
Admission routes1
Has abstractyes

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