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Record W2556556285 · doi:10.26786/1920-7603(2016)4

Pollination ecology of <i>Oreocallis grandiflora</i> (Proteaceae) at the northern and southern ends of its geographic range

2016· article· en· W2556556285 on OpenAlexvenueno aff
Jenny Hazlehurst, Santiago Cárdenas, Boris A. Tinoco, Jordan Karubian

Bibliographic record

VenueJournal of Pollination Ecology · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsnot available
Fundersnot available
KeywordsPollinatorBiologyNectarPollinationProteaceaeEcologyRange (aeronautics)Abiotic componentPollenEvolutionary ecologyOrchidaceae

Abstract

fetched live from OpenAlex

Geographic variation in pollination ecology is poorly documented, if at all, in many plant-pollinator systems. Great insights could be gained into the abiotic and biotic factors which impact the evolution of floral properties and their potential to lead to speciation by doing so, as both can vary naturally over the geographic range of a plant species. We characterized the pollination ecology of the Andean tree Oreocallis grandiflora (Family: Proteaceae) at the northern and southern ends of its range in Ecuador and Peru in terms of flower morphology, nectar properties, pollinators and plant reproduction. We found significant divergence in the two populations in terms of style length and flower openness, nectar standing crop and secretion rate, and pollinator community. We did not find a significant difference in the length of the pollen presenter or in nectar sucrose concentration by weight (% Brix). The observed divergence in floral traits between the two study populations may be related to a combination of factors, including genetic drift and isolation by distance, distinctive suites of pollinators, or heterospecific pollen competition, which future studies should further investigate. This study demonstrates that pollination ecology can vary substantially across the geographic range of a species, with implications for delimiting species and subspecific taxa.

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 score0.604
Threshold uncertainty score0.997

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 studies0.0000.000
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 head0.017
GPT teacher head0.202
Teacher spread0.186 · 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

Citations8
Published2016
Admission routes1
Has abstractyes

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