Evolved reductions in body temperature and the metabolic costs of thermoregulation in deer mice native to high altitude
Bibliographic record
Abstract
The evolution of endothermy was instrumental to the diversification of birds and mammals, but the energetic demands of maintaining high body temperature could offset the advantages of endothermy in some environments. We hypothesized that reductions in body temperature help high-altitude natives overcome the metabolic challenges of cold and hypoxia in their native environment. Deer mice (Peromyscus maniculatus) from high-altitude and low-altitude populations were bred in captivity to the second generation and were acclimated as adults to warm normoxia or cold hypoxia. Subcutaneous temperature (Tsub, used as a proxy for body temperature) and cardiovascular function were then measured throughout the diel cycle using biotelemetry. Cold hypoxia increased metabolic demands, as reflected by increased food consumption and heart rate (associated with reduced vagal tone). These increased metabolic demands were offset by plastic reductions inTsub(approx. 2°C) in response to cold hypoxia, and highlanders had lowerTsub(approx. 1°C) than lowlanders in both environmental treatments. Empirical and theoretical evidence suggested that these reductions could together reduce metabolic demands by approximately 10–30%. Therefore, plastic and evolved reductions in body temperature can help mammals overcome the metabolic challenges at high altitude and may be a valuable energy-saving strategy in some non-hibernating endotherms in extreme environments.
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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".