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Record W4387059545 · doi:10.1242/jeb.246673

Cold comas could stop the spread of butterflies

2023· article· en· W4387059545 on OpenAlexaboutno aff
Jarren Kay

Bibliographic record

VenueJournal of Experimental Biology · 2023
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology and Insect Physiology Research
Canadian institutionsnot available
Fundersnot available
KeywordsComa (optics)ButterflyEcologyPredationBiologyZoologyPhysicsAstronomy

Abstract

fetched live from OpenAlex

As the planet warms, animals are leaving their usual homes and venturing closer to the poles or higher into the mountains to escape the heat. Normally, these areas are protected from many insects because becoming too cold leads to a coma as their central nervous system stops working. Although the insects can survive these comas for a limited amount of time, being unable to move leaves them at risk of becoming an easy meal for predators. With this in mind, Mads Andersen and Heath MacMillan of Carleton University, Canada, working with Quentin Willot of Aarhus University, Denmark, wanted to know if this cold-induced coma – and the events happening in the nervous system that cause it – are common among all insects. Perhaps surprisingly, they turned to several species of tropical butterfly to help them answer this intriguing question.Andersen and colleagues began the difficult task of recording the electrical activity in the brains of 12 different species of tropical butterflies while slowly cooling them down. As they got colder, every butterfly eventually lost brain function, suggesting they would fall into a coma. Surprisingly, the butterflies did so within a narrow range of temperatures between ∼3.0°C and ∼5.3°C, depending on the species. The researchers point out that cold coma has been linked to the temperature at which other insects, such as fruit flies and locusts, stop being able to coordinate their movements. In most insects, the coma is caused by an imbalance in the normal amounts of sodium and potassium ions inside and outside the nerve cells of the brain. Usually, there is more potassium inside the cells than outside, but the cold temperatures cause a rush of potassium to leave the cells, shutting them down until they can restore the usual balance of these ions. Although this happens slightly differently in butterflies, the team believe that existence of the cold-induced coma in such distantly related species suggests that this is what causes the loss of movement in all insects when the temperatures keep dropping. But can the researchers predict at what temperature the coma will start depending on the species?Andersen and colleagues constructed an evolutionary tree showing that related species of butterflies didn't necessarily fall into the coma at similar temperatures. However, when the researchers looked at where the butterflies originated, a pattern started to emerge. The temperature at which the coma would begin depended on how cold the coldest month was where the butterflies lived and the elevation they lived at. This means that the butterflies from the coldest climates or highest altitudes also had cold-induced comas beginning at the lowest temperatures. The researchers are quick to point out that the temperatures that cause these comas are 11.5°C below the average temperature of the coldest month that they would experience in the wild.While the team didn't find the differences that they were expecting, they suggest that the phenomenon of falling into a coma because you are too cold may exist in all insects since the butterflies in this study aren't closely related to either fruit flies or locusts. This also suggested that the temperature that causes the coma could predict where certain insects are able to survive. As the world gets warmer, animals are going to be found in new and unexpected places, but it might be the cold that stops them from going any further.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.009
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.002

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 head0.068
GPT teacher head0.371
Teacher spread0.303 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2023
Admission routes1
Has abstractyes

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