Nonconsumptive Effects of Predation and Impaired Chemosensory Risk Assessment on an Aquatic Prey Species
Bibliographic record
Abstract
Weak levels of acidity impair chemosensory risk assessment by aquatic species which may result in increased predator mortalities in the absence of compensatory avoidance mechanisms. Using replicate populations of wild juvenile Atlantic salmon (Salmo salar) in neutral and acidic streams, we conducted a series of observational studies and experiments to identify differences in behaviours that may compensate for the loss of chemosensory information on predation risk. Comparing the behavioural strategies of fish between neutral and acidic streams may elucidate the influence of environmental degradation on nonconsumptive effects (NCEs) of predation. Salmon in acidic streams are more active during the day than their counterparts in neutral streams, and are more likely to avoid occupying territories offering fewer physical refugia from predators. Captive cross-population transplant experiments indicate that at equal densities, salmon in acidic streams do not demonstrate relative decreases in growth rate as a result of their different behavioural strategies. Instead, altering diel activity patterns to maximize visual information use and occupying relatively safer territories appear sufficient to offset increased predation risk in acidic streams. Additional strategies such as elevated foraging rates during active periods or adopting riskier foraging tactics are necessary to account for the observed similarities in growth rates.
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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 | 0.001 |
| 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 | 0.001 |
| 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".