Humidity, huddling & the hibernation energetics of big brown bats (Eptesicus fuscus)
Notice bibliographique
Résumé
During winter, many mammals hibernate and lower their body temperature and metabolic rate (MR) in prolonged periods of torpor. Hibernators will use energetically expensive arousals (i.e., restore body temperature and MR) presumably to re-establish water balance. Some hibernating mammals however will huddle in groups, possibly to decrease energetic costs and total evaporative water loss (EWL), although the benefit is not fully understood. Research on the relationship between behaviour, physiology, water loss, and energy expenditure of bats during hibernation is especially important because of a fungal disease called white-nose syndrome (WNS). To date, 12 North American bat species are affected by WNS, however big brown bats (Eptesicus fuscus) appear resistant, although the underlying mechanism is poorly understood. The overall objective of my thesis was to understand the influence of humidity and huddling on the behavioural and physiological responses of hibernating big brown bats. To test my hypotheses, I used a captive colony of hibernating big brown bats (n = 20). Specifically, for Chapter 2, I first tested the hypothesis that big brown bats adjust huddling and drinking behaviour depending on humidity, to maintain a consistent pattern of periodic arousals, and therefore energy balance during hibernation. I found that bats hibernating in a dry environment did not differ in arousal/torpor bout frequency, or torpor bout duration throughout hibernation but drank at twice the rate as bats in a humid environment. Bats in the dry treatment also had shorter arousals, and huddled in a denser huddle, potentially to reduce rates of total EWL. During late hibernation, for Chapter 3, I used open-flow respirometry to test two additional hypotheses, first that phenotypic flexibility in total EWL helps explain the tolerance of hibernating big brown bats for a wide range of humidity relative to other bat species. I found that dry-acclimated bats had lower rates of total EWL, compared to bats acclimated to humid conditions. I then tested the second hypothesis that big brown bats can use huddling to mitigate the challenge of dry conditions. I found that, for humid-acclimated bats, rates of total EWL were reduced with huddling bats but there was no effect of huddling on EWL for bats acclimated to dry conditions. These results suggest that the ability of big brown bats to reduce rates of total EWL through acclimation may reduce the need to huddle with conspecifics to avoid water loss and thus dehydration. Overall, my thesis suggests that big brown bats use both behavioural and physiological mechanisms to reduce water loss which could allow them to exploit habitats for hibernation that are unavailable to other bat species and could also help explain their apparent resistance to WNS.
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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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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.
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 ».