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Record W2943711182 · doi:10.1139/cjb-2019-0022

Low levels of inbreeding depression and enhanced fitness in cleistogamous progeny in the annual plant <i>Triodanis perfoliata</i>

2019· article· en· W2943711182 on OpenAlexvenueno aff
Beth H. Ansaldi, Jennifer J. Weber, Carol Goodwillie, Steven J. Franks

Bibliographic record

VenueBotany · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsnot available
Fundersnot available
KeywordsInbreeding depressionSelfingBiologyOutcrossingInbreedingGenetic loadMating systemBotanyOutbreeding depressionZoologyMatingPopulationPollenDemography

Abstract

fetched live from OpenAlex

The maintenance of outcrossing in cleistogamous plants that produce both open, facultatively outcrossing chasmogamous (CH), and closed, obligate selfing cleistogamous (CL) flowers is puzzling because CL reproduction is thought to be more reliable and less costly. A possible explanation for the maintenance of CH flowers is the avoidance of inbreeding depression. However, inbreeding depression for cleistogamous species has rarely been quantified. In this study, we estimate levels of inbreeding depression in plants from three populations of Triodanis perfoliata (L.) Nieuwl., a dimorphic cleistogamous annual, under greenhouse conditions. Estimates of inbreeding depression at multiple life stages in all three populations were low and often not different from zero. Inbreeding depression at specific life stages varied, with two populations showing later-acting inbreeding depression, which is also found in other selfing species. In two of the study populations, selfed CL progeny outperformed selfed CH progeny, indicating a flower-type effect. The low levels of inbreeding depression and the superior fitness of CL compared with selfed CH flowers that we observed make the maintenance of CH flowers in this system surprising, and suggest that other advantages of outcrossing CH flowers are likely responsible for maintaining mixed mating in this 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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.706
Threshold uncertainty score0.129

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 head0.025
GPT teacher head0.211
Teacher spread0.185 · 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

Citations23
Published2019
Admission routes1
Has abstractyes

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