Island tameness and the repeatability of flight initiation distance in a large herbivore
Bibliographic record
Abstract
Antipredator behaviours can be lost relatively quickly in populations that are relieved of predation, as is known for several species inhabiting islands. Flight initiation distance (FID) is often studied in the context of island tameness; however, little is known about the factors that influence and maintain FID variation in predation-free populations. Here, we studied FID in foals of an isolated predator-free population of feral horses (Equus caballus L., 1758) on Sable Island, Canada, to determine if FID could be used for research on consistent individual differences in risk aversion and island tameness. In addition to testing for temporal, spatial, and sex effects on FID, we compared repeatability estimates at two temporal scales (within and among days). Similar FID for measurements obtained on the same day and for males and females indicated an absence of short-term desensitization and sex effects. In contrast, FID decreased for measurements made on subsequent days and from east to west, which could reflect habituation to human presence and (or) other temporal and spatial processes. Repeatability was high (0.42 ± 0.06), but tended to decrease with increasing time intervals. This study highlights the potential of FID for individual-based research on the ecology and evolutionary dynamics of risk aversion in predation-free populations.
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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 | 0.001 | 0.002 |
| 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 | 0.000 |
| 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".