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TESTING MODELS OF SEX RATIO EVOLUTION IN A GYNODIOECIOUS PLANT: FEMALE FREQUENCY COVARIES WITH THE COST OF MALE FERTILITY RESTORATION

2012· article· en· W2015619957 on OpenAlexaff
Christina M. Caruso, Andrea L. Case

Bibliographic record

VenueEvolution · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsGynodioecyBiologyHermaphroditePollenCytoplasmic male sterilityFertilitySterilityPopulationDioecyFrequency-dependent selectionEvolutionary biologySex allocationEcologyGeneticsDemographyOffspring

Abstract

fetched live from OpenAlex

In many gynodioecious species, cytoplasmic male sterility genes (CMS) and nuclear male fertility restorers (Rf) jointly determine whether a plant is female or hermaphrodite. Equilibrium models of cytonuclear gynodioecy, which describe the effect of natural selection within populations on the sex ratio, predict that the frequency of females in a population will primarily depend on the cost of male fertility restoration, a negative pleiotropic effect of Rf alleles on hermaphrodite fitness. Specifically, when the cost of restoration is higher, the frequency of females at equilibrium is predicted to be higher. To test this prediction, we estimated variation in the cost of restoration across 26 populations of Lobelia siphilitica, a species in which Rf alleles can have negative pleiotropic effects on pollen viability. We found that L. siphilitica populations with many females were more likely to contain hermaphrodites with low pollen viability. This is consistent with the prediction that the cost of restoration is a key determinant of variation in female frequency. Our results suggest that equilibrium models can explain variation in sex ratio among natural populations of gynodioecious species.

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 score0.189
Threshold uncertainty score0.432

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 head0.070
GPT teacher head0.219
Teacher spread0.150 · 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

Citations26
Published2012
Admission routes1
Has abstractyes

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