Thermoregulatory trade-offs underlie the effects of warming summer temperatures on deer mice
Bibliographic record
Abstract
Climate warming could challenge the ability of endotherms to thermoregulate and maintain normal body temperature (Tb), but the effects of warming summer temperatures on activity and thermoregulatory physiology in many small mammals remain poorly understood. We examined this issue in deer mice (Peromyscus maniculatus), an active nocturnal species. Mice were exposed in the lab to simulated seasonal warming, in which an environmentally realistic diel cycle of ambient temperature (Ta) was gradually warmed from spring conditions to summer conditions (controls were maintained in spring conditions). Activity (voluntary wheel running) and Tb (implanted bio-loggers) were measured throughout, and indices of thermoregulatory physiology (thermoneutral zone, thermogenic capacity) were assessed after exposure. In control mice, activity was almost entirely restricted to the night-time, and Tb fluctuated ∼1.7°C between daytime lows and night-time highs. Activity, body mass and food consumption were reduced and water consumption was increased in later stages of summer warming. This was accompanied by strong Tb dysregulation that culminated in a complete reversal of the diel pattern of Tb variation, with Tb reaching extreme highs (∼40°C) during daytime heat but extreme lows (∼34°C) at cooler night-time temperatures. Summer warming was also associated with reduced ability to generate body heat, as reflected by decreased thermogenic capacity and decreased mass and uncoupling protein (UCP1) content of brown adipose tissue. Our findings suggest that thermoregulatory trade-offs associated with daytime heat exposure can affect Tb and activity at cooler night-time temperatures, impacting the ability of nocturnal mammals to perform behaviours important for fitness in the wild.
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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 | 0.001 |
| 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 | 0.001 |
| 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".