Estimating the energetic significance of basking behaviour in a temperate-zone turtle
Bibliographic record
Abstract
Basking is a common thermoregulatory behaviour in many ectotherms, including reptiles. Because the key physiological processes affecting net energy retention (NER) are temperature dependent, ectotherms have the potential to modulate their energy budget by using basking behaviour. Many aquatic chelonians bask extensively. The energetic significance of basking is, however, largely unknown. We used biologging to measure the body temperature of free-ranging juvenile northern map turtles in Ontario, Canada. We measured the contribution of basking behaviour to the ability of turtles to reach their optimal body temperature for NER. We also used the predicted standard metabolic rate as a proxy to estimate the effects of basking on NER. Our results show that basking is essential for turtles to reach the optimal temperature for NER and suggest that basking behaviour allows turtles to increase their metabolic rate by 17.2 to 30.1%, which should translate into an even greater increase in NER. In addition, our results show that basking behaviour allows turtles to buffer the effects of climatic variations on their Tb and thus potentially on their energy budget. Collectively, our results suggest that basking behaviour has important ramifications for the energy budget, and by extension the fitness, of temperate-zone turtles.
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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 | 0.000 |
| 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".