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Reproductive consequences of interactions between clonal growth and sexual reproduction in <i>Nymphoides peltata</i>: a distylous aquatic plant

2004· article· en· W2092330839 on OpenAlexafffund
Yong Wang, Qingfeng Wang, You‐Hao Guo, Spencer C. H. Barrett

Bibliographic record

VenueNew Phytologist · 2004
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaWuhan University
KeywordsBiologySexual reproductionReproductionPlant reproductionBotanyAquatic plantEcologyPollinationPollen

Abstract

fetched live from OpenAlex

Distyly is a sexual polymorphism in which plant populations contain two floral morphs differing in morphology and physiology. The dimorphism serves to promote animal-mediated cross-pollination between the floral morphs. Clonal propagation can interfere with the functioning of distyly by compromising intermorph pollinations, resulting in reduced fertility. Here, we investigate the relations between clonal growth and sexual reproduction in the aquatic macrophyte Nymphoides peltata (Menyanthaceae). Surveys of morph representation in 30 populations from five regions of China revealed that most populations exhibited strongly biased morph ratios and 30% contained a single floral morph. Experimental pollinations indicate that N. peltata possesses a strong dimorphic incompatibility system preventing self and intramorph fertilizations. An experiment involving the manipulation of morph ratios in an experimental population and an investigation in a natural population with strong morph substructure both provided evidence that compatible pollen dilution limits fertility. Despite constraints on the functioning of distyly in N. peltata we found no evidence for evolutionary changes to the heterostylous syndrome, as reported in Nymphoides, including populations of N. peltata in other parts of its geographical range.

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 score0.307
Threshold uncertainty score0.995

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 head0.060
GPT teacher head0.254
Teacher spread0.194 · 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

Citations62
Published2004
Admission routes2
Has abstractyes

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