Correlates and consequences of heterothermy in mammals
Bibliographic record
Abstract
Endotherms are capable of using internal heat to precisely regulate body temperature at an elevated level, yet there is considerable variation in the range of body temperatures (heterothermy) expressed by an endotherm. In this thesis, I exploit two different approaches to address the causes and consequences of heterothermy in mammals, reflective of an underlying trade-off between the functional benefits and energetic costs of endothermy. I first conduct an inter-specific, empirical analysis of mammalian body temperatures reported in the literature, treating heterothermy as a continuous variable spanning all endotherms, to examine factors that predict the degree of body temperature fluctuation observed in different species. Across mammals, body temperature variation decreased with body mass and increased with proximity to the poles, and food hoarders were less heterothermic than non-hoarders. Further, with these allometric, latitudinal, and behavioural effects included, phylogeny still had a strong influence on the degree of body temperature variation in a given species. In my second chapter, I examine potential behavioural consequences of torpor, a special case of heterothermy involving a pronounced reduction in body temperature and metabolism. This research was conducted in captivity on eastern chipmunks (Tamias striatus), which exhibit deep torpor and show extreme individual variation in heterothermy that spans most of the heterothermic continuum expressed by mammals in general. To test the hypothesis that torpor impairs exploration and spatial memory, individual performance was assessed in an open field and a radial arm maze prior to and during hibernation. Results showed that habituation in the open field was negatively impacted by torpor, particularly prolonged torpor, however performance in the radial maze, tested later in the arousal period, was less affected. Thus, torpor expression clearly affects behaviour, but these effects are very transient and therefore unlikely to have long-term fitness consequences. Mammals overall are characterized by extensive variability, both among and within species, in the degree of body temperature variation, with species occupying cold climates and relying on ephemeral food being characterized by the most heterothermy. As to why more individuals and species do not exploit the energetic savings of high-amplitude heterothermy, captive research suggests the immediate costs of reduced body temperature on endotherm function may be more important than its long-term effects.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".