Context-dependent effects of thermal acclimation on physiological correlates of animal personality in Asiatic toads
Bibliographic record
Abstract
Persistent individual variation in behaviour, or ‘personality’, is a widespread phenomenon in animals, and understanding the evolution of animal personality is a key task of current biology. Natural selection has been proposed to promote the integration of personality with animal ‘intrinsic states’, such as metabolic or endocrine traits, and this integration varies with ecological conditions. However, these external ecological modulatory effects have rarely been examined. Here, we investigate the effects of thermal acclimation on between-individual covariations between physiology and behaviour in Asiatic toads ( Bufo gargarizans ) along an altitudinal gradient. Our results reveal that the thermal modulatory effects on the covariations depend on the altitudinal population. Specifically, at low altitudes, between-individual covariations are highly plastic, with risk-taking behaviour covarying with baseline glucocorticoids (GCs) under warm acclimation, but risk-taking and exploration behaviour covarying with resting metabolic rate (RMR) under cold acclimation. In contrast, between-individual covariations are relatively fixed at high altitudes, with risk-taking behaviour consistently covarying with baseline GCs. Furthermore, at low altitudes, changes in covariations between RMR and personality are associated with adjustment of energy management models. Evidently, animal physiological states that determine or covary with personality can adapt according to the seasonal thermal environment and the thermal evolutionary background of populations. Our findings highlight the importance of a multi-system physiological approach to understand the evolution of animal personality.
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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 | 0.001 |
| 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".