MétaCan
Menu
Back to cohort
Record W2581321796 · doi:10.1111/ele.12738

Global biogeography of mating system variation in seed plants

2017· article· en· W2581321796 on OpenAlexaff
David A. Moeller, Ryan D. Briscoe Runquist, Annika M. Moe, Monica A. Geber, Carol Goodwillie, Pierre‐Olivier Cheptou, Christopher G. Eckert, Elizabeth Elle, Mark O. Johnston, Susan Kalisz, Richard H. Ree, Risa D. Sargent, Mario Vallejo‐Marín, Alice A. Winn

Bibliographic record

VenueEcology Letters · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of OttawaDalhousie UniversitySimon Fraser UniversityQueen's University
FundersNational Science Foundation
KeywordsOutcrossingBiomeBiogeographyEcologyBiologyMating systemLatitudeBiodiversityMatingPollinatorTaxonPollinationEcosystemGeographyPollen

Abstract

fetched live from OpenAlex

Latitudinal gradients in biotic interactions have been suggested as causes of global patterns of biodiversity and phenotypic variation. Plant biologists have long speculated that outcrossing mating systems are more common at low than high latitudes owing to a greater predictability of plant-pollinator interactions in the tropics; however, these ideas have not previously been tested. Here, we present the first global biogeographic analysis of plant mating systems based on 624 published studies from 492 taxa. We found a weak decline in outcrossing rate towards higher latitudes and among some biomes, but no biogeographic patterns in the frequency of self-incompatibility. Incorporating life history and growth form into biogeographic analyses reduced or eliminated the importance of latitude and biome in predicting outcrossing or self-incompatibility. Our results suggest that biogeographic patterns in mating system are more likely a reflection of the frequency of life forms across latitudes rather than the strength of plant-pollinator interactions.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.083
Threshold uncertainty score0.532

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 head0.020
GPT teacher head0.199
Teacher spread0.179 · 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

Citations106
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueEcology LettersSame topicPlant and animal studiesFrench-language works237,207