Notice bibliographique
Résumé
Oxygen is essential for life, providing the energy needed for surviving and thriving in our world. However, animals that live in aquatic habitats have their work cut out for them. Not only is oxygen less freely available in water than in terrestrial environments but also, with climate change, bouts of low oxygen (hypoxia) are becoming more and more common in these habitats. For decades, scientists have been studying and categorizing how well fish can handle low oxygen (or not) to understand who the ‘winners’ and ‘losers’ would be in an oxygen-limited world. The ultimate goal for many scientists is to create rules that allow us to predict which species are more vulnerable to changing environments and whether this vulnerability will change their current distributions around the globe.Until recently, scientists have been studying how one or two environmental factors in isolation can affect oxygen limitation – but many factors can conspire to impact a fish's oxygen supply or demand. For example, low oxygen levels in water frequently occur when temperatures are elevated. This increases a fish's demand for oxygen and effectively makes it worse at dealing with limited oxygen availability. However, there's conflicting evidence for how other factors that influence oxygen demand, such as body size, affect a fish’s tolerance of low-oxygen scenarios within and across species.To approach this in a more holistic manner, Wilco Verberk from Radbound University, The Netherlands, and colleagues from Chile, the UK and France, searched the literature and an existing database of limiting oxygen levels for what factors might influence fishes’ ability to withstand low oxygen. Compiling traits for 195 fish species, they took into account the many physical factors that relate to the fishes’ oxygen supply or demand and investigated whether these factors work separately or together to explain why some fishes are better than others at dealing with low oxygen.Verberk and colleagues found that the relatedness of species heavily influences their ability to tolerate low oxygen. For example, sharks and rays are more sensitive to low oxygen than their distantly related ‘cousins’ goldfish, which are renowned low-oxygen champions. Salinity is also a predictor of how well fishes deal with limited oxygen availability, wherein freshwater fishes are less sensitive to hypoxia than marine fishes. This is unsurprising as freshwater habitats tend to have more intense fluctuations in oxygen and temperature than marine habitats and so species that live in freshwater need to be better prepared to withstand frequent bouts of low oxygen.The scientists’ most interesting finding was that bigger fishes and fishes with bigger cell sizes are more vulnerable to low oxygen, specifically in warm habitats. At higher temperatures, their demand for oxygen is high but they might be limited by the flow of oxygen into the blood, making them more sensitive to low-oxygen situations. In cooler environments, fishes with larger bodies and bigger cell sizes are actually less vulnerable to low oxygen than their small counterparts. Colder water has a higher viscosity – it's thicker and stickier – which would make it more difficult for small fishes to breathe, giving larger fishes the leg (or fin?) up.Low oxygen and warmer temperatures are predicted to work together to limit desirable habitats and reshape species distribution. Yet, other environmental and biological factors can impact oxygen supply or demand. By including body size in their considerations, Verberk and colleagues were able to resolve how body mass impacts hypoxia tolerance and add to the growing body of work seeking to predict fishes’ vulnerability in a changing world.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,013 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,003 | 0,006 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,044 | 0,008 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».