Behavioural and morphological changes in fish exposed to ecologically relevant boat noises
Bibliographic record
Abstract
There is increasing concern about the effect of underwater noise on fish due to rising levels of anthropogenic noise. We performed experiments on the black bullhead (Ameiurus melas), a species with known hearing specializations and located within the Laurentian Great Lakes where there is considerable commercial and recreational boat traffic. We tested and compared physiology (baseline cortisol), behaviour (activity, sheltering), and morphology (ciliary bundles of hair cells) of bullhead to boat noise. At 140 dB re 1 μPa (−54.84 dB re 1 m·s−2), we saw clear behavioural effects in terms of both activity and sheltering levels despite no obvious morphological or physiological stress. Following both short- and long-period acute exposure to higher — but environmentally relevant — noise levels, bullhead were less active and sheltered more and also exhibited a decrease in ciliary bundles. These results suggest that there are sublethal effects of anthropogenic noise on fish behaviour and ciliary bundles, which may have direct implications on population health. Moreover, commonly used metrics such as stress hormones may not always offer the most relevant biomarker of the response to anthropogenic boat noise.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".