Non‐Lethally Produced Chemical Risk Cues Elicit Antipredator Responses in a Common Canadian Minnow
Bibliographic record
Abstract
ABSTRACT Predation risk exerts significant pressure on the survival of prey species and has many indirect impacts on their habitat use, energy allocation, and community dynamics. Prey must consistently assess their surroundings by using multiple information sources to monitor predation risk and respond accordingly. In aquatic environments, chemical signals (i.e., alarm cues, disturbance cues, and predator odors) play a crucial role in informing prey of predation risk. Here, we systematically assess the impact of two non‐lethal cues, disturbance cue and predator odor, on four aspects of prey fish behavior using the common blackchin shiner (Miniellus heterodon), a possible surrogate species for the Threatened pugnose shiner (Miniellus anogenus). In experiment 1, we found that conspecific disturbance cue elicited an increase in activity relative to the controls. However, there were no changes in area use, shoaling, or shelter use. In experiment 2, we found that predator odor elicited increased shelter use in blackchin shiner, consistent with an antipredator strategy, but no changes in activity, area use, or shoaling. Our two experiments suggest that disturbance cues and predator odors elicit different behavioral responses in blackchin shiner, perhaps since sources of risk information vary in their urgency and reliability. These results aimed to provide the baseline for future work on pugnose shiner, and demonstrate the value of using non‐lethal chemical cues, with standardized methods, to study antipredator behavior in threatened species.
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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 | 0.000 |
| 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) | 0.001 | 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".