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Record W2978881162 · doi:10.1111/nph.16230

Defence compounds in pollen: why do they occur and how do they affect the ecology and evolution of bees?

2019· article· en· W2978881162 on OpenAlexaff
Sébastien Rivest, Jessica R. K. Forrest

Bibliographic record

VenueNew Phytologist · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPollenBiologyPollinatorPollen sourcePollinationPlant reproductionZoophilyEcologyPleiotropyBotany

Abstract

fetched live from OpenAlex

Pollen plays two important roles in angiosperm reproduction, serving as a vehicle for the plant's male gametes, but also, in many species, as a lure for pollen-feeding animals. Despite being an important food source for many pollinators, pollen often contains compounds with known deterrent or toxic properties, as documented in a growing number of studies. Here we review these studies and discuss the role of pollen defensive compounds in the coevolutionary relationship between plants and bees, the preeminent consumers of pollen. Next, we evaluate three hypotheses that may explain the existence of defensive compounds in pollen. The pleiotropy hypothesis, which proposes that defensive compounds in pollen merely reflect physiological spillover from other plant tissues, is contradicted by evidence from several species. Although plants may experience selection to defend pollen against poor-quality pollinators, we also find only partial support for the protection-against-pollen-collection-hypothesis. Finally, pollen defences might protect pollen from colonisation by antagonistic microorganisms (antimicrobial hypothesis), although data to evaluate this idea are scarce. Further research on the effects of pollen defensive compounds on pollinators, pollen thieves, and pollen-colonising microbes will be needed to understand why many plants have chemically defended pollen, and the consequences of those defences for pollen consumers.

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 score0.036
Threshold uncertainty score0.981

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 head0.027
GPT teacher head0.222
Teacher spread0.195 · 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

Citations87
Published2019
Admission routes1
Has abstractyes

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