Body temperature is a repeatable trait in a free-ranging passerine bird
Bibliographic record
Abstract
Body temperature (Tb) affects animal function through its influence on rates of biochemical and biophysical reactions, the molecular structures of proteins and tissues, and, ultimately, organismal performance. Despite its importance in driving physiological processes, there are few data on how much variation in Tb exists within populations of organisms, and whether this variation consistently differs among individuals over time (i.e. repeatability of a trait). Here, using thermal radio-frequency identification implants, we quantified the repeatability of Tb, both in the context of a fixed average environment (∼21°C) and across ambient temperatures (6-31°C), in a free-living population of tree swallows (Tachycineta bicolor, n=16). By experimentally trimming the ventral plumage of a subset of female swallows (n=8), we also asked whether the repeatability of Tb is influenced by the capacity to dissipate body heat. We found that both female and male tree swallow Tb was repeatable at 21°C (R=0.89-92), but female Tb was less repeatable than male Tb across ambient temperature (Rfemale=0.10, Rmale=0.58), which may be due to differences in parental investment. Trimmed birds had on average lower Tb than control birds (by ∼0.5°C), but the repeatability of female Tb did not differ as a function of heat dissipation capacity. This suggests that trimmed individuals adjusted their Tb to account for the effects of heat loss on Tb. Our study provides a first critical step toward understanding whether Tb is responsive to natural selection, and for predicting how animal populations will respond to climatic warming.
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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 | 0.000 |
| 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".