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Enregistrement W4247905118 · doi:10.1242/jeb.135855

Striped catfish lose the plot in low CO2 water

2016· article· en· W4247905118 sur OpenAlexaboutno aff

Notice bibliographique

RevueJournal of Experimental Biology · 2016
Typearticle
Langueen
DomaineEarth and Planetary Sciences
ThématiqueOcean Acidification Effects and Responses
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésCatfishPlot (graphics)Environmental scienceFisheryBiologyFish <Actinopterygii>MathematicsStatistics

Résumé

récupéré en direct d'OpenAlex

As the politicians keep on squabbling over the best ways to alleviate climate change, and CO2 emissions continue rising, much of the gas ends up in our oceans and rivers. At first glance, it didn't seem as if this gradual acidification was going to pose a problem for the planet's fishy residents. Matthew Regan from the University of British Columbia, Canada, says, ‘They are well prepared physiologically and biochemically to tolerate even the most depressing of future CO2 projections’. However, more recently it has become apparent that fish that have been exposed to future levels of CO2 experience behavioural problems: in addition to becoming hyperactive and bolder, they also suffer visual disturbance and anxiety, and are attracted to predators. The associated mild chemical imbalances in the fish's bodies affect their inhibitions. Following on from this discovery, Sjannie Lefevre and Göran Nilsson from the University of Oslo, Norway, wondered how fish that already reside in water with high CO2 would cope if the situation was reversed and they were transferred into normal (low CO2) water?Teaching at a graduate course on air-breathing fish in 2014 organised by Mark Bayley at Can Tho University, Vietnam, Lefevre and Nilsson had the ideal opportunity to address the conundrum. The Mekong Delta is home to the striped catfish (Pangasianodon hypophthalmus), which thrives in high-CO2 water. So, with a flourishing aquaculture industry on hand to supply the fish and a team of enthusiastic students available to run the experiments, they were in the perfect place to test the fish's reactions to low-CO2 water.Collecting fish provided by Do Thi Thanh Huong and Nguyen Thanh Phuong from a nearby farm, Regan and his fellow students Andy Turko, Joe Heras and Mads Kuhlmann Andersen transferred some of the animals into low-CO2 water, while the rest remained in high-CO2. Then, with the help of Colin Brauner and Tobias Wang, they began testing the fish's reactions to a range of situations, from the arrival of an unfamiliar object (a brick) in their surroundings to how much time they spent schooling with their own kind, to find out how the water conditions had affected their behaviour.Not surprisingly, striped catfish that resided in their habitual high-CO2 conditions showed all of the usual reactions to unfamiliar situations, avoiding the frightening brick and remaining out of reach of a threatening predator. However, the fish that had been held in freshwater began behaving strangely. Not only were they unalarmed by the presence of the predator but also they were unfazed by the arrival of the brick. In addition, they were less attracted to a school of their own species and were much more active. However, when the team gave the low-CO2 catfish a dose of a drug that counteracts the effects of the GABA neurotransmitter – the neurotransmitter that malfunctions and triggers bold behaviour when fish that normally reside in low CO2 are exposed to high CO2 – the emboldened catfish lost their courage and began behaving normally.So, the GABA neurotransmitter had lost its inhibitory effects in the catfish that had been transferred to low-CO2 water because of the subtle chemical changes in their brains caused by the alteration in their surrounding water. And Regan suggests that other species may be able to adapt their brains to the brave new world that striped catfish already survive in, provided they can keep pace with change.

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 consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,012
Score d'incertitude au seuil0,999

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)0,0020,000

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 Opus0,014
Tête enseignante GPT0,251
Écart entre enseignants0,237 · 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; un appel candidat d’une seule tête enseignante, pas un consensus.

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
Publié2016
Routes d'admission1
Résumé présentoui

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