Examining the effect of intensive seismic surveys on abundance and behaviour of groundfish species along a continental slope of Newfoundland and Labrador, Canada
Bibliographic record
Abstract
This study investigated changes in the abundance and behaviour of groundfish species at a relatively deep-water site along the eastern continental slope of Canada, when exposed to a commercial seismic survey that lasted 100 consecutive days. Baited cameras were deployed at control and impact sites, before and after seismic exposure, consisting of 323, 5-h long, videos. Changes in abundance were not explained by seismic surveying noise for any of the five commonly observed fish species. However, Atlantic cod were found to have significantly longer arrival-times to baited camera stations and it took longer for available bait to be consumed immediately after seismic surveying occurred. This effect occurred when fish were exposed to a daily mean sound pressure level >120 dB re 1 μPa 2 prior to the experimental measurements. The study contributes towards a better ecological understating of noise-related impacts over a wide range of conditions where groundfish occur. • Seismic oil and gas exploration surveys raise concerns about the impact of ocean noise pollution on marine life, particularly for the fishing industry and general ocean health. • We incorporated a 100-day industry-based 3D seismic survey on commercial offshore fishing grounds into controlled field experiments, using baited cameras to study the impact on fish. • No significantly changes in estimated abundance were observed at our offshore study sites to suggest displacement effects, for either of five groundfish species considered, however changes in the foraging behaviour of Atlantic cod was detected. • Better understanding of noise-related impacts on fish behaviour contributes to improved ocean resource management and healthy oceans.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".