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Record W4307731498 · doi:10.26786/1920-7603(2022)671

By land and by tree: Pollinator taxa diversity of terrestrial and epiphytic orchids

2022· article· en· W4307731498 on OpenAlexvenueno aff
Haleigh A. Ray, Jennifer L. Gillett‐Kaufman

Bibliographic record

VenueJournal of Pollination Ecology · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsnot available
Fundersnot available
KeywordsPollinatorEpiphyteBiologyPollinationOrchidaceaeEcologyTaxonSpecies richnessPollen

Abstract

fetched live from OpenAlex

There are approximately 30,000 species in the family Orchidaceae, with some species growing terrestrially and others growing as epiphytes. Though the pollination biology of many of these species is not well known, there has been a diversity of taxa recorded as orchid pollinators. Insects, birds, and even a record of a mammal species have been documented as successful pollinators, while some orchids are able to reproduce without the use of a pollen vector. The goal of this review is to provide an overview of orchid pollination tactics, with references to more specific studies of each, and to analyze a large subset of publications to determine differences in pollinator taxa and specificity between epiphytic and terrestrial orchid genera. This review examines pollination data from over 400 orchid species, including 74 epiphytic and 83 terrestrial orchid genera. Two pollinator taxa, Coleoptera and Hymenoptera (Class: Insecta), were found to pollinate significantly more terrestrial than epiphytic orchid genera, while other taxa showed no significant differences. Hymenoptera were the dominant taxa of pollinator in regards to the overall number of species recorded; however, based on species interaction webs that were built, the Lepidoptera (Class: Insecta) have stronger interactions with the orchid species they pollinate, suggesting a more specific relationship between the two.

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 score0.066
Threshold uncertainty score0.220

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 head0.019
GPT teacher head0.201
Teacher spread0.182 · 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
Published2022
Admission routes1
Has abstractyes

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