Approaching merchant ships elicit behavioral changes in Atlantic sturgeon (<scp><i>Acipenser oxyrinchus</i></scp>) in the St. Lawrence River, Canada
Bibliographic record
Abstract
There are gaps in our understanding of sturgeon's response to anthropogenic sounds and the spatial scales at which they occur. We measured spatial displacement of Atlantic sturgeon in the St. Lawrence River at various distances of approaching merchant ships. This fish population is designated as "threatened," although anthropogenic noise is not currently considered a direct threat. For several years, Atlantic sturgeon migrations have been monitored by the Quebec government using acoustic transmitters and a network of telemetry receivers in the St. Lawrence River. We combined fish telemetry data with merchant ship positions to detect co-occurrences between Atlantic sturgeons that remained in the vicinity of the receivers and approaching ships. Numerical simulations reveal that the probability of masking of transmitters (69 kHz) by ship noise was infinitesimal and that the disappearance of the transmitter signal was related to fish movement. When the ships approached, a significant spatial displacement was detected with ships at distances between 0.5 and 5 km from the receivers. After emitter signal loss, over 61% of sturgeons took at least 30 min to be detected again or did not return at all in the vicinity of the receivers. Furthermore, the median time to redetection after a ship transit was longer than when no ship was approaching (31 vs. 18 min). Our results show that sturgeons alter their position due to approaching ships at greater trigger distances than previously documented, which are too far away to be attributed to visual cues alone. We also found that the long-distance propagation of low-frequency sounds from large ships through water should not be heard by Atlantic sturgeon at distances of 1 km and longer based on current knowledge of sturgeons hearing. These results suggest that behavioral responses in Atlantic sturgeons are modulated not only by visual cues but can also be triggered by underwater sounds at relatively long distances, although the precise mechanism is still unknown.
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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".