Behavioural effects of temperature on ectothermic animals: unifying thermal physiology and behavioural plasticity
Bibliographic record
Abstract
Temperature imposes significant constraints on ectothermic animals, and these organisms have evolved numerous adaptations to respond to these constraints. While the impacts of temperature on the physiology of ectotherms have been extensively studied, there are currently no frameworks available that outline the multiple and often simultaneous pathways by which temperature can affect behaviour. Drawing from the literature on insects, we propose a unified framework that should apply to all ectothermic animals, generalizing temperature's behavioural effects into: (1) kinetic effects, resulting from temperature's bottom-up constraining influence on metabolism and neurophysiology over a range of timescales (from short to long term), and (2) integrated effects, where the top-down integration of thermal information intentionally initiates or modifies a behaviour (behavioural thermoregulation, thermal orientation, thermosensory behavioural adjustments). We discuss the difficulty in distinguishing adaptive behavioural changes from constraints when observing animals' behavioural responses to temperature. We then propose two complementary approaches to distinguish adaptations from constraints, and categorize behaviours according to our framework: (i) 'kinetic null modelling' of temperature's effects on behaviour; and (ii) behavioural ecology experiments using temperature-insensitive mutants. Our framework should help to guide future research on the complex relationship between temperature and behaviour in ectothermic animals.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".