Can you hear me? Impacts of underwater noise on communication space of adult, sub-adult and calf contact calls of endangered St. Lawrence belugas (Delphinapterus leucas)
Bibliographic record
Abstract
Noise and anthropogenic disturbances from vessel traffic are an important threat to the recovery of the endangered St. Lawrence Estuary (SLE) beluga population. The consequences of acoustic masking could be particularly adverse in the case of critical vocalizations that maintain contact between mothers and their dependent but mobile calves. This study models the communication range of adults, sub-adults and newborn beluga contact calls in the presence and absence of vessels in an important summering area for this population. Ambient noise measurements, a composite beluga audiogram and apparent source levels of adult/sub-adult and newborn calls, informed the model. Apparent source levels were estimated from received levels of contact calls produced by four individuals carrying digital acoustic tags in the SLE, Canada, and from received levels of calls recorded from two adults and a newborn calf at an aquarium, at known distances from a calibrated hydrophone. The median communication ranges were over 18 times larger for SLE adult and sub-adult calls than for newborn calls, with a 57 and 53% reduction in range in the presence of vessel noise, respectively. For newborn calls, this results in a median range of 170 m in vessel noise. These first estimates of the communication range of beluga vocalizations with a known function suggest that masking of the quiet calls of newborns by anthropogenic noise could impair mother–calf contact.
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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 | 0.001 | 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".