Humidity, huddling & the hibernation energetics of big brown bats (Eptesicus fuscus)
Bibliographic record
Abstract
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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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".