Torpor in Dark Times: Patterns of Heterothermy Are Associated with the Lunar Cycle in a Nocturnal Bird
Bibliographic record
Abstract
Many studies have shown that endotherms become more heterothermic when the costs of thermoregulation are high and/or when limited energy availability constrains thermoregulatory capacity. However, the roles of many ecological variables, including constraints on foraging opportunities and/or success, remain largely unknown. To test the prediction that thermoregulatory patterns should be related to foraging opportunities in a heterothermic endotherm, we examined the relationship between the lunar cycle and heterothermy in Freckled Nightjars (Caprimulgus tristigma), which are visually orienting, nocturnal insectivores that are dependent on ambient light to forage. This model system provides an opportunity to assess whether variation in foraging opportunities influences the expression of heterothermy. The nightjars were active and foraged for insects when moonlight was available but became inactive and heterothermic in the absence of moonlight. Lunar illumination was a much stronger predictor of the magnitude of heterothermic responses than was air temperature (T(a)). Our data suggest that heterothermy was strongly related to variation in foraging opportunities associated with the lunar cycle, even though food abundance appeared to remain relatively high throughout the study period. Patterns of thermoregulation in this population of Freckled Nightjars provide novel insights into the environmental and ecological determinants of heterothermy, with the lunar cycle, and not T(a), being the strongest predictor of torpor use.
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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 | 0.001 | 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".