Temporal Trends in the Acoustic Occurrence of Baleen Whales in the Bay of Fundy, Canada: Observations from Passive Acoustic Monitoring
Bibliographic record
Abstract
The outer Bay of Fundy supports 6 baleen whale species seasonally and year–round, but multi-species passive acoustic monitoring efforts are lacking in this region. This area also experiences significant activity from fishing, commercial shipping, and tourism, all of which contribute to underwater anthropogenic noise. We report on the minimum acoustic occurrence of baleen whales and ambient sound levels in the Bay of Fundy from a multi-year passive acoustic dataset. We took acoustic recordings opportunistically at 5 sites from 2015 to 2022 using a single archival bottom-mounted hydrophone and the bottom hydrophone from a 3-channel vertical array. We processed the data with automated detectors and manual validation to identify and confirm baleen whale vocalizations and calculated average ambient sound pressure levels as broadband and within the 100-Hz band level. Balaenoptera physalus (Fin Whale), Megaptera novaeangliae (Humpback Whale), and Eubalaena glacialis (North Atlantic Right Whale) were the predominant baleen whale species detected. Fin Whales were detected year–round, Humpback Whale detections peaked from July to October, and Right Whales were detected from July into October. Balaenoptera borealis (Sei Whale) were detected in June, July, and August in 2015, Balaenoptera acutorostrata (Minke Whale) were detected only minimally despite numerous visual sightings in this region, and no Balaenoptera musculus (Blue Whale) were detected. The Grand Manan site had the highest average broadband and band-level ambient sound-pressure levels. These observations highlight the area's importance for baleen whales and contribute underwater soundscape data for past and future monitoring comparisons.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".