The thermoregulatory strategy of two sympatric colubrid snakes affects their demography
Bibliographic record
Abstract
Abstract Population dynamics of terrestrial vertebrates are affected by climatic fluctuations, notably in ectotherms. An understanding of the interaction between physiology and demographic processes is necessary to predict the impacts of climate change. Reptiles are particularly sensitive to temperature, but only a few studies have explored the relationship between thermoregulatory strategy and demography in these animals. Using 12 years of mark‐recapture data on two sympatric colubrid snakes ( Hierophis viridiflavus and Zamenis longissimus ), we tested whether demographic parameters are influenced by contrasted thermoregulatory strategies. The thermophilic and conspicuous species ( H. viridiflavus ) grew faster than the thermoconforming and secretive species ( Z. longissimus ), and this difference was most pronounced in open habitats, suggesting that the metabolic benefits associated with high thermal preferences depend on environmental factors at small spatial scales. Survival varied annually in both species, but was not lower in H. viridiflavus despite a higher degree of exposure. In Z. longissimus , survival was negatively affected by low temperatures during the active season, possibly underlying an exposure trade‐off.
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 | 0.000 |
| 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 | 0.000 |
| 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".