Behavioural and Growth Responses of a Territorial Fish (Atlantic Salmon, <i>Salmo salar,</i> L.) to Multiple Predatory Cues
Bibliographic record
Abstract
Abstract Antipredatory behaviours are important fitness components. The probability of survival decreases if animals fail to respond to signs of danger, but in contrast, energetic costs increase if the response to the threat is exaggerated. We conducted a laboratory experiment designed to examine the behavioural and growth responses of a territorial fish (Atlantic salmon fry, Salmo salar , L.) to different predatory cues (no predatory cues, chemical cues alone, physical cues alone and combined chemical and physical cues). We evaluated the response of Atlantic salmon, focussing on behaviours linked to predator avoidance and to other fitness‐enhancing activities (territory defence and energy acquisition) both during the day and the night. The cost of such responses in terms of growth was assessed and we compared the relative contributions of behaviours in explaining individual growth rate, according to each predation treatment. We demonstrated that the magnitude and nature of behavioural modification varied according to the response variables we considered. An index of predator avoidance and the distance from the food source were affected in an additive fashion by predatory cues (interaction term, p = 0.469 and p = 0.888 for the index of predator avoidance and the distance from the food source respectively); the effect of physical cues was stronger than the effect of chemical cues and the effect of the combined cues was highest. An index of territoriality was affected in a threshold‐like fashion (interaction term, p = 0.040); chemical or physical cues alone had no effect but when both cues were combined, Atlantic salmon significantly reduced their territorial defence. An index of foraging activity was not significantly affected by predatory cues (alone or combined). We detected no effect on the growth rate of Atlantic salmon (p = 0.328). Finally, we found that the relative contribution of behaviours in explaining individual growth rate changed according to the treatments we considered. Overall, these results demonstrated that fish were able to accurately integrate multiple predatory cues and that this information was used to modulate their antipredatory response. Behaviours involved in the response were relatively independent of each other, allowing fish to adopt behavioural tactics that maximized the ratio of net energy gain to predator avoidance.
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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 | 0.001 | 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".