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Record W4361296978 · doi:10.1098/rsbl.2022.0555

Butterfly foraging is remarkably synchronous in an experimental tropical macrocosm

2023· article· en· W4361296978 on OpenAlexafffundabout
Federico Riva, André‐Philippe Drapeau Picard, Maxim Larrivée

Bibliographic record

VenueBiology Letters · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsCarleton UniversityEspace pour la vie
FundersMitacs
KeywordsForagingBiologyEctothermEcologyButterflyAbiotic componentEcosystemNicheClimate change

Abstract

fetched live from OpenAlex

Diel patterns in foraging activity are dictated by a combination of abiotic, biotic and endogenous limits. Understanding these limits is important for insects because ectotherm taxa will respond more pronouncedly to ongoing climatic change, potentially affecting crucial ecosystem services. We leverage an experimental macrocosm, the Montreal Insectarium Grand Vivarium, to test the importance of endogenous mechanisms in determining temporal patterns in foraging activity of butterflies. Specifically, we assessed the degree of temporal niche partitioning among 24 butterfly species originating from the Earth's tropics within controlled environmental conditions. We found strong niche overlap, with the frequency of foraging events peaking around solar noon for 96% of the species assessed. Our models suggest that this result was not due to the extent of cloud cover, which affects radiational heating and thus limits body temperature in butterflies. Together, these findings suggest that an endogenous mechanism evolved to regulate the timing of butterfly foraging activity within suitable environmental conditions. Understanding similar mechanisms will be crucial to forecast the effects of climate change on insects, and thus on the many ecosystem services they provide.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.720
Threshold uncertainty score0.185

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 head0.042
GPT teacher head0.255
Teacher spread0.212 · 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

Citations4
Published2023
Admission routes3
Has abstractyes

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