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Morphological and genetic differentiation in <i>Isodon umbrosus</i> by altitudinal variation in bumblebee pollinator assemblages

2010· article· en· W2015976178 on OpenAlexaff
Ikumi Dohzono, Kazuo Suzuki

Bibliographic record

VenuePlant Species Biology · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsCegep de Sept Iles
FundersJapan Science Society
KeywordsBumblebeePollinatorBiologyRange (aeronautics)EcologyAltitude (triangle)Genetic variationProboscisEvolutionary biologyPollinationPollenGeneticsGene

Abstract

fetched live from OpenAlex

Abstract The corolla tube length of the bumblebee‐pollinated plant Isodon umbrosus shows conspicuous geographical variation, corresponding with the proboscis length of its bumblebee pollinators across its distributional range. We hypothesized that altitudinal variation in the pollinator assemblage is a principal factor mediating morphological and genetic differentiation among I. umbrosus populations. We examined determinants of the morphological and genetic differentiation of Isodon umbrosus by analyzing floral morphology and allozyme variation across the distributional range. A reanalysis of previous data confirmed that altitude was a good indicator of pollinator assemblages. Corolla tube length was highly variable among the 15 study populations, and genetic differentiation among the populations ( G ST = 0.360) was also highly significant. The differentiation in corolla tube length was explained by altitudinal difference, a proxy of the difference in pollinator assemblages. Genetic differentiation among populations also tended to be affected by the same factor, but statistical support was weak. To better understand the mechanisms responsible for morphological and genetic differentiation in I. umbrosus , we need to investigate altitudinally different populations over a narrower geographical scale.

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 score0.606
Threshold uncertainty score0.998

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 head0.022
GPT teacher head0.203
Teacher spread0.180 · 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

Citations13
Published2010
Admission routes1
Has abstractyes

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