Islet tameness: escape behavior and refuge use in populations of the Balearic lizard (Podarcis lilfordi) exposed to differing predation pressure
Bibliographic record
Abstract
Prey often exhibit reduced escape behavior on islands where predators are absent or scarce. Models of escape and refuge use predict that prey from populations having lower predation pressure have shortened flight initiation distance (FID; distance between a predator and a prey when escape begins), reduced distance fled and tendency to enter refuge, and shortened hiding time before emerging from refuge. By ourselves simulating approaching predators, we tested these predictions for two populations of the Balearic lizard, Podarcis lilfordi (Müller, 1927), on the islets of Rei (higher predation pressure) and Aire (lower) adjacent to Menorca. FID, distance fled, and hiding time were shorter and probability of entering refuge was lower on Aire than on Rei, confirming all predictions. All effect sizes were large, indicating major differences in antipredatory behavior between islets. These findings are consistent with data for other lizards on FID and limited data on distance fled and refuge entry. The effect of predation pressure on hiding time is a novel finding. Our results and those of previous studies suggest that relaxation of predation pressure leads to reduced natural selection for maintenance of antipredatory behavior at all stages of predator–prey interactions over a relatively short time span.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 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".