Staying warm is not always the norm: behavioural differences in thermoregulation of two snake species
Bibliographic record
Abstract
Thermal biology research compares field with laboratory data to elucidate the evolution of temperature-sensitive traits in ectotherms. The hidden challenge of many of these studies is discerning whether animals actively thermoregulate, since motivation is not typically assessed. By studying the behaviours involved in thermoregulation, we can better understand the mechanisms underlying body temperature control. Using an integrative approach, we assessed the thermoregulatory and thermotactic behaviours of two sympatric snake species with contrasting life histories: the generalist Eastern Garter Snake (Thamnophis sirtalis sirtalis ( Linnaeus, 1758 )) and the semi-fossorial Northern Red-bellied Snake (Storeria occipitomaculata occipitomaculata ( Storer, 1839 )). We expected that thermoregulatory behaviours would be optimized based on life history, in that T. s. sirtalis would show higher evidence for thermally oriented behaviours than S. o. occipitomaculata due to its active nature. Thamnophis sirtalis sirtalis actively thermoregulated, had higher thermal preferences (29.4 ± 2.5 vs. 25.3 ± 3.6 °C), and was more active than S. o. occipitomaculata, which showed relatively low evidence for thermotaxis. Our results build on the notion that evaluating movement patterns and rostral orientation towards a heat source can help ascertain whether animals make thermally motivated choices. Our data provide insight into the thermoregulatory strategies used by snakes with different life histories and maximize the information provided by behavioural thermoregulation experiments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".