Using sonobuoys and visual surveys to characterize North Atlantic right whale (Eubalaena glacialis) calling behavior in the Gulf of St. Lawrence
Bibliographic record
Abstract
The appropriate use and interpretation of passive acoustic data for monitoring the Critically Endangered North Atlantic right whale Eubalaena glacialis (hereafter right whale) rely on knowledge of their calling behavior and how it varies with respect to time, space, demographics, and observed behavior. To assess such relationships in a habitat of increased management importance, sonobuoys (disposable drifting hydrophones) were deployed in the Gulf of St. Lawrence, Canada, to record sounds from aggregating right whales during visual aerial surveys in the summers (June through August) of 2017 (n = 8), 2018 (n = 13), and 2019 (n = 16). Upcalls, gunshots, and various mid-frequency (250-800 Hz) tonal calls were compared to demographics and observed behaviors of concurrently observed right whales using correlation matrices, linear regressions, and generalized linear models. Our results show that (1) call rates increased from June to August for all call types; (2) calling rates were associated negatively with observed foraging behavior and positively with observed socializing behavior; (3) upcalls were occasionally produced at higher rates (>20 calls h -1 ) when in association with gunshots and tonal calls; (4) acoustic monitoring did not always detect right whale presence at fine timescales (2-6 h), but presence estimates were improved when multiple calls types were considered; and (5) calling rates were too variable to provide reliable density estimates of observed right whales. These results have important implications for the interpretation of passive acoustic monitoring in this habitat and provide evidence that some whale behaviors (e.g. socializing) may be reliably inferred from acoustics alone.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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 teacher head, 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".