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Record W2138639041 · doi:10.1098/rspb.2010.0501

Floral colour versus phylogeny in structuring subalpine flowering communities

2010· article· en· W2138639041 on OpenAlexafffund
Jamie R. McEwen, Jana C. Vamosi

Bibliographic record

VenueProceedings of the Royal Society B Biological Sciences · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyPhylogenetic treePollinatorAttractionTraitPopulationBotanyEcologyPhylogeneticsPollinationPollenDemography

Abstract

fetched live from OpenAlex

The relative number of seeds produced by competing species can influence the community structure; yet, traits that influence seed production, such as pollinator attraction and floral colour, have received little attention in community ecology. Here, we analyse floral colour using reflectance spectra that include near-UV and examined the phylogenetic signal of floral colour. We found that coflowering species within communities tended to be more divergent in floral colour than expected by chance. However, coflowering species were not phylogenetically dispersed, in part due to our finding that floral colour is a labile trait with a weak phylogenetic signal. Furthermore, while we found that locally rare and common species exhibited equivalent floral colour distances from their coflowering neighbours, frequent species (those found in more communities) exhibited higher colour distances from their coflowering neighbours. Our findings support recent studies, which have found that (i) plant lineages exhibit frequent floral colour transitions; and (ii) traits that influence local population dynamics contribute to community structure.

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)0.001
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 score0.516
Threshold uncertainty score0.525

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.059
GPT teacher head0.228
Teacher spread0.169 · 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

Citations105
Published2010
Admission routes2
Has abstractyes

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