Background level of risk and the survival of predator-naive prey: can neophobia compensate for predator naivety in juvenile coral reef fishes?
Bibliographic record
Abstract
Neophobia--the generalized fear response to novel stimuli--provides the first potential strategy that predator-naive prey may use to survive initial predator encounters. This phenotype appears to be highly plastic and present in individuals experiencing high-risk environments, but rarer in those experiencing low-risk environments. Despite the appeal of this strategy as a 'solution' for prey naivety, we lack evidence that this strategy provides any fitness benefit to prey. Here, we compare the relative effect of environmental risk (high versus low) and predator-recognition training (predator-naive versus predator-experienced individuals) on the survival of juvenile fish in the wild. We found that juveniles raised in high-risk conditions survived better than those raised in low-risk conditions, providing the first empirical evidence that environmental risk, in the absence of any predator-specific information, affects the way naive prey survive in a novel environment. Both risk level and experience affected survival; however, the two factors did not interact, indicating that the information provided by both factors did not interfere or enhance each other. From a mechanistic viewpoint, this indicates that the combination of the two factors may increase the intensity, and hence efficacy, of prey evasion strategies, or that both factors provide qualitatively separate benefits that would result in an additive survival success.
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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 | 0.000 | 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".