Habitat‐specific behavioural thermoregulation by black rat snakes ( <i>Elaphe obsoleta obsoleta</i> )
Bibliographic record
Abstract
Thermoregulation is thought to be the most important factor influencing habitat selection by terrestrial ectotherms, at least in temperate climates. The cost‐benefit model of thermoregulation predicts that ectotherms should invest more in thermoregulation when the costs of doing so are low (when the thermal quality of the habitat is high). However, the extent to which ectotherms vary their thermoregulatory behaviour according to the thermal quality of habitats is currently unknown. We studied the relationship between habitat use and thermoregulation in 53 black rat snakes using temperature‐sensitive radio‐transmitters. Among the habitats available to black rat snakes, edges had the highest thermal quality, retreat sites and forest were intermediate, and open habitats had the lowest thermal quality. Black rat snakes experienced more favourable body temperatures while in barns (retreat sites) than in edges, and in edges than in forest. During the day, the effectiveness and the extent of thermoregulation by the snakes were equal in barns and forest, but much lower in edges. In fact, black rat snakes selected thermally favourable microhabitats less than their availability while in edges. Therefore, more favourable body temperatures were not necessarily achieved in thermally superior habitats by increased thermoregulation, but simply because favourable temperatures were encountered more often in those habitats. This result is contrary to the central prediction of the cost‐benefit model of thermoregulation and we suggest that this model should be modified to put more emphasis on other costs of thermoregulation, such as increased predation risk or lost foraging opportunities.
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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 | 0.000 |
| 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".