Passive acoustic detection of North Atlantic Right Whales in the Cabot Strait : ambient noise analysis and detection range modelling
Bibliographic record
Abstract
North Atlantic right whales (NARWs) occur throughout most of the Northwest Atlantic from Florida to Newfoundland, with aggregations documented in the Gulf of St. Lawrence in spring, summer and fall in recent years. As they migrate between southern breeding grounds and northern feeding areas, the Cabot Strait serves as a critical movement corridor. This study examines the feasibility of using Passive Acoustic Monitoring (PAM) to detect NARWs as they traverse this high-traffic shipping corridor, with a focus on detecting their contact calls (upcalls). A sparse array of PAM systems was deployed at six mooring stations across the 110 km-wide Cabot Strait from October 2022 to August 2023. Detection distances for NARW upcalls were estimated by using in situ ambient noise level measurements with integrated ocean-acoustic modelling. Detection modeling, based on a 155 dB source level and a 3 dB Signal-to-Noise Ratio (SNR) threshold, was conducted using both quantile and logarithmic regression methods, with quantile regression proving to be the more robust approach. The findings reveal substantial variation in ambient noise levels among the stations. Notably, stations CS2 and CS3, located closest to a shipping lane, exhibited the shortest median detection ranges (5 to 6 km), whereas station CSE achieved the longest median detection range (20 to 25 km), attributable to its generally lower ambient noise levels. The high volume of vessel traffic, with over 20 ships traversing the strait daily, contributes to continuous low-frequency noise in this area, which can propagate up to 100 km, complicating detection efforts. Additionally, seasonal sound channels were observed to enhance sound propagation, but their transient nature underscores the need for adaptive deployment strategies. This study provides a preliminary estimate of NARW detection distances in a complex ocean-acoustic environment, emphasizing the impact of shipping noise on detection effectiveness and highlighting the need for further research to refine PAM-based NARW monitoring strategies in the Cabot Strait.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".