Trade-offs in the choice of refuges by common wall lizards: do thermal costs affect preferences for predator-free refuges?
Bibliographic record
Abstract
Prey often respond to predator presence by increasing refuge use. However, some types of refuges may expose prey to other types of predators. In addition, in selecting refuges ectothermic animals may have a conflict between safety and thermal suitability. In this paper we examined in the laboratory whether common wall lizards, Podarcis muralis (Laurenti, 1768), (i) prefer to use warm refuges to cold ones, (ii) prefer safe refuges to those with chemical cues of a saurophagous snake, and (iii) whether lizards face a trade-off between using a warm but snake-scented refuge or a cold but odorless one. Results did not show differences in refuge use in relation to refuge temperature, because common wall lizards only entered to investigate it, but they were not forced to hide. So, common wall lizards did not have to be at suboptimal temperatures for longer times. Common wall lizards avoided the use of predator-scented refuges, regardless of thermal conditions, and they also increased their movement rate, trying to escape from the terrarium. Because snakes are inconspicuous inside refuges, an avoidance response to their chemicals may enhance the survival possibilities of common wall lizards. We conclude that in common wall lizards, predation-risk costs are more important than thermal costs in determining refuge use.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".