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Record W4309915217 · doi:10.1111/een.13211

Pollen specialisation is associated with later phenology in <i>Osmia</i> bees (Hymenoptera: Megachilidae)

2022· article· en· W4309915217 on OpenAlexafffund
Daniel Pelletier, Jessica R. K. Forrest

Bibliographic record

VenueEcological Entomology · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsGeneralist and specialist speciesPhenologyBiologyMegachilidaeHerbivoreEcologyPollinationPollenHost (biology)HymenopteraPollinatorHabitat

Abstract

fetched live from OpenAlex

Abstract Species exhibit a range of specialisation in diet and other niche axes, with specialists typically thought to be more efficient in resource use but more vulnerable to extinction than generalists. Among herbivorous insects, dietary specialists seem more likely to lack acceptable host plants during the insect's feeding stage, owing to fluctuations in host‐plant abundance or phenology. Like other herbivores, bee species vary in host breadth from pollen specialisation (oligolecty) to generalisation (polylecty). Several studies have shown greater interannual variation in flowering phenology for earlier‐flowering plants than later‐flowering plants, suggesting that early‐season bees may experience substantial year‐to‐year variation in the floral taxa available to them. It was therefore reasoned that, among bees, early phenology could be a more viable strategy for generalists, which can use resources from multiple floral taxa, than for specialists. Consequently, it was expected that the median dates of collection of adult specimens to be earlier for generalist species than for specialists. To test this, phenology data and pollen diet information on 67 North American species of the bee genus Osmia was obtained. Controlling for latitude and phylogeny, it was found that dietary generalisation is associated with significantly earlier phenology, with generalists active, on average, 11–14 days earlier than specialists. This result is consistent with the generalist strategy being more viable than the specialist strategy for species active in early spring, suggesting that dietary specialisation may constrain the evolution of bee phenology—or vice versa.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.994

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)0.0070.000

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 head0.029
GPT teacher head0.205
Teacher spread0.176 · 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.

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

Citations7
Published2022
Admission routes2
Has abstractyes

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