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Record W6931427742 · doi:10.5281/zenodo.5598297

Data from: Does pollen limitation limit plant ranges? Evidence and implications

2021· other· en· W6931427742 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2021
Typeother
Languageen
FieldMathematics
TopicStatistical Methods and Bayesian Inference
Canadian institutionsMcGill University
Fundersnot available
KeywordsPollenPollinationRange (aeronautics)Plant reproductionPollen sourceSexual reproductionPlant speciesLeverage (statistics)

Abstract

fetched live from OpenAlex

Sexual reproduction often declines towards range edges, reducing fitness, dispersal, and adaptive potential at range edges. For plants, sexual reproduction is frequently limited by inadequate pollination. While case studies show that pollen limitation can limit plant distributions, the extent to which pollination commonly declines toward plant range edges is unknown. Here, we leverage global databases of pollen-supplementation experiments and plant occurrence data to test whether pollen limitation increases toward plant range edges, using a phylogenetically controlled meta-analysis. While there was significant pollen limitation across studies, we found little evidence that pollen limitation increases toward plant range edges. Pollen limitation was not stronger toward the tropics, nor at species' equatorward vs poleward range limits. Meta-analysis results are consistent with results from targeted experiments, in which pollen limitation increased significantly toward only 14% of 14 plant range edges, suggesting that pollination contributes to range limits less often than do other interactions. Together, these results suggest pollination is one of the rich variety of potential ecological factors that can contribute to range limits, rather than a generally important constraint on plant distributions.

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)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.409
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0380.001

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 head0.292
GPT teacher head0.385
Teacher spread0.093 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreMethods

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

Citations0
Published2021
Admission routes1
Has abstractyes

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