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Loss of floral polymorphism in heterostylous <i>Luculia pinceana</i> (Rubiaceae): a molecular phylogeographic perspective

2012· article· en· W2164583374 on OpenAlexaff
Wei Zhou, Spencer C. H. Barrett, Hong Wang, Li D

Bibliographic record

VenueMolecular Ecology · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Diversity and Evolution
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBiologyEvolutionary biologyLineage (genetic)PhylogeographyPopulationHeterostylyCoalescent theoryEcologyPollenPhylogeneticsPollinationGeneticsGene

Abstract

fetched live from OpenAlex

Both deterministic and stochastic forces determine the representation and frequency of floral morphs in heterostylous plant populations. Phylogeographic analysis of molecular variation can provide information on the role of historical factors, including founder events, in affecting population morph structure. Here, we investigate geographical patterns of floral morph variation in a distylous shrub Luculia pinceana (Rubiaceae) by examining the relations between floral polymorphism and molecular (cpDNA and microsatellite) variation in 25 populations sampled throughout the distribution of the species in southwest China and adjacent countries. In 19 of the 25 populations, the frequency of floral morphs was not significantly different from the expected 1:1 ratio. The remaining populations were either L-morph biased (2) or monomorphic (4) for this form and were morphologically differentiated from the remaining populations in several floral traits, that is, corolla tube length, sex organ position and stigma-anther separation. Phylogeographic analysis supports the hypothesis that L. pinceana was initially split into west-central and eastern lineages in the Early Pleistocene (~1.982 Mya). A centrally located lineage composed of morph-biased and monomorphic populations appears to have been subsequently derived from the west-central lineage, perhaps by a founder event after the last glacial maximum. Hypotheses to explain why these populations have not returned to equilibrium morph frequencies are considered.

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 score0.590
Threshold uncertainty score0.357

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 head0.008
GPT teacher head0.191
Teacher spread0.183 · 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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