Linking proximate drivers and fitness returns of vigilance in a large ungulate
Bibliographic record
Abstract
Vigilance allows animals to quickly detect threats from conspecifics and predators to avoid or minimize costly encounters. Time spent vigilant is usually traded‐off against other fitness‐enhancing activities, such that fitness returns are expected when allocation to vigilance increases. We assessed the proximate factors influencing vigilance and investigated whether vigilance correlates with fitness in wild mountain goats. We first studied which extrinsic and intrinsic factors influenced alert duration and frequency using focal observations recorded over 12 years on individually‐marked adult females. We found that females increased vigilance in forested areas compared with open areas and were less vigilant when they were surrounded by conspecific neighbours. Reproductive females were more frequently vigilant and for longer periods compared with females without offspring. Mothers also tended to perform longer alerts when their offspring was > 10 m away than at shorter distances, suggesting that variation in offspring's vulnerability to predation influences mother's vigilance. Thus, predation risk and offspring vulnerability were the main mechanisms driving variation in vigilance. To assess fitness returns, we then used a joint modelling framework to estimate the latent correlations at the individual level among vigilance traits (alert duration, alert frequency, and total time spent vigilant) and fitness components (adult female survival and offspring survival) while accounting for the drivers observed to influence vigilance. Contrary to expectations, we found no evidence that vigilance is associated with fitness returns, with only some traits being at best weakly positively correlated with survival of offspring and adult females. This might arise because vigilance incurs costs that outweighs its potential benefits, or because vigilance metrics are not repeatable due to their high plasticity, challenging the commonly assumed positive relationship between vigilance and fitness.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".