Effects of acid rainfall on juvenile Atlantic salmon (Salmo salar) antipredator behaviour: loss of chemical alarm function and potential survival consequences during predation
Bibliographic record
Abstract
Many organisms rely on chemosensory cues to mediate predation risks. Recent studies have demonstrated impaired chemosensory detection ability under weak acidification. Because rainfall may lead to episodic acidification of surface water, we assessed the effects of acid rain on chemosensory alarm functions. Under natural conditions, we quantified alarm behaviour of juvenile Atlantic salmon (Salmo salar) exposed to conspecific chemical alarm cues before and following rainfall. Before rainfall, salmon were capable of an alarm response in the study streams. After rainfall, salmon from Devil’s Brook did not respond to the alarm cues whereas the detection of salmon from Catamaran Brook (a comparable stream having higher acid neutralising capacity) was maintained. To relate these findings to predator–prey encounters, we performed a second experiment where we staged encounters between prey (rainbow trout, Oncorhynchus mykiss) and predator (largemouth bass, Micropterus salmoides) exposed to acidified and unacidified rainbow trout chemical alarm cues. Trout exposed to acidified alarm cues survived for a significantly shorter amount of time than trout exposed to unacidified alarm cues, whereas no difference in overall predator behaviour was observed. Our results suggest that episodic acidification in small nursery streams may disrupt the chemical information mediated by the chemical alarm cues that can translate into higher survival costs for prey.
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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".