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Record W2060151033 · doi:10.1111/1365-2656.12373

Flowering time of butterfly nectar food plants is more sensitive to temperature than the timing of butterfly adult flight

2015· article· en· W2060151033 on OpenAlexafffundabout
Heather M. Kharouba, Mark Vellend

Bibliographic record

VenueJournal of Animal Ecology · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversité de SherbrookeUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsButterflyPhenologyBiologyNectarAdaptation (eye)Climate changeEcologyGlobal warmingPollen

Abstract

fetched live from OpenAlex

1. Variation among species in their phenological responses to temperature change suggests that shifts in the relative timing of key life cycle events between interacting species are likely to occur under climate warming. However, it remains difficult to predict the prevalence and magnitude of these shifts given that there have been few comparisons of phenological sensitivities to temperature across interacting species. 2. Here, we used a broad-scale approach utilizing collection records to compare the temperature sensitivity of the timing of adult flight in butterflies vs. flowering of their potential nectar food plants (days per °C) across space and time in British Columbia, Canada. 3. On average, the phenology of both butterflies and plants advanced in response to warmer temperatures. However, the two taxa were differentially sensitive to temperature across space vs. across time, indicating the additional importance of nontemperature cues and/or local adaptation for many species. 4. Across butterfly-plant associations, flowering time was significantly more sensitive to temperature than the timing of butterfly flight and these sensitivities were not correlated. 5. Our results indicate that warming-driven shifts in the relative timing of life cycle events between butterflies and plants are likely to be prevalent, but that predicting the magnitude and direction of such changes in particular cases is going to require detailed, fine-scale data.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.807
Threshold uncertainty score0.202

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 head0.031
GPT teacher head0.222
Teacher spread0.192 · 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 designBench or experimental
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

Citations67
Published2015
Admission routes3
Has abstractyes

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