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Enregistrement W2147885818 · doi:10.1242/jeb.064410

LIZARD WITS INCREASE AS PLANET HEATS

2012· article· en· W2147885818 sur OpenAlexaff
Viviana Cadena

Notice bibliographique

RevueJournal of Experimental Biology · 2012
Typearticle
Langueen
DomainePsychology
ThématiqueAnimal and Plant Science Education
Établissements canadiensBrock University
Organismes subventionnairesnon disponible
Mots-clésLizardEcologyIncubationBiologyZoologyPsychology

Résumé

récupéré en direct d'OpenAlex

We all know an animal is the product of its genes and the influence of the environment. Humidity, food availability and parental care are just examples of factors that can have a strong impact on an animal's characteristics. This is certainly true in the case of reptiles, where incubation temperature can affect several of their physical and physiological characteristics. It is well known, for example, that sex, size and running speed can all be influenced by temperature in various lizard species. But what about other, less-obvious characteristics? It is harder to measure how incubation temperature affects different aspects of behaviour and intelligence. None the less, these are interesting questions and Joshua Amiel and Richard Shine from the University of Sidney, Australia, decided they were worth pursuing.They wanted to know whether incubation temperature affected young lizards' ability to learn. Moreover, they wanted to know whether an increased ability to learn would be relevant during a life-threatening situation. To do this, Amiel and Shine collected gravid three-lined skinks, which are lizards native to Australian forests. They took them back to their lab in Sidney and incubated their eggs at cold (16±7.5°C) and hot (22±7.5°C) regimes. When the babies hatched, it was time for their IQ tests inside their own homes so that they would not have to deal with the additional stress of learning in a strange environment. Each enclosure had two small hiding retreats but the entrance to one of them was blocked with a piece of Plexiglas. For each test a baby lizard was placed right in the middle between the two retreats under a little plastic cover. As soon as the experimenter lifted the cover, he tickled the lizard's tail with a paintbrush, scaring the poor lizard, which ran for a hiding place. The scientists then counted the number of times that the hatchling chose the wrong hide and the time it took to finally find the available retreat. They repeated these trials for 4 days, four times a day with each lizard and then compared the reptiles' success rates through time. Were they learning?All the babies were capable of learning and made fewer mistakes the more tests they performed, but as time went by, the hatchlings that had been incubated in the hot environment learned faster and made fewer mistakes than the cold-incubated ones. This was independent of sex, size or running speed.The fact that warm-incubated lizards turned out to be smarter than cold-incubated lizards gives a glimpse of what might happen during global warming. Amiel and Shine point out that this increased ability to learn will increase the lizard's capacity to respond in the face of environmental changes and therefore increase their chances of survival. The study does not dismiss the possibility that cold-incubated lizards may ‘catch up’ with their warm-incubated counterparts as they develop, or even compensate for their slower wits with other abilities such as locomotor speed. However, this does not negate the fact that lizards from hot eggs have the edge over their cool-egg friends.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesCharge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,543
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0050,001

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,046
Tête enseignante GPT0,379
Écart entre enseignants0,333 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2012
Routes d'admission1
Résumé présentoui

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