Pacific herring respond to simulated odontocete echolocation sounds
Bibliographic record
Abstract
There has been a long-running debate as to if and how clupeoid fish, such as herring (Clupea sp.), respond to anthropogenic sound. Anatomical and physiological investigations have shown that members of the clupeoid suborder have highly developed hearing extending into ultrasonic frequencies and behavioural studies suggest that they respond to many sounds. However, only recently have the selective forces that have driven the evolution of this keen sense and behavioural repertoire played a major part in the debate. One explanation is the adaptation to predation from echolocating cetaceans. In this study, we investigate the responses of adult Pacific herring (Clupea pallasii) to broadband biosonar-type sounds with high-frequency similarities to those produced by odontocete cetaceans. Exposures to these sounds in an indoor tank and sea cage caused feeding fish to cease, drop in the water column, and begin to school actively. Fish already schooling dropped in the water column and increased their swimming speed. Exposures to electronic silence and an acoustic deterrent device for marine mammals did not elicit such responses. We discuss the potential suitability of the observed manoeuvres for avoidance of foraging odontocetes and consider their relevance for human-related fishing activities.
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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".