The distribution of North Atlantic right whales in Canadian waters from 2015-2017 revealed by passive acoustic monitoring
Bibliographic record
Abstract
Northward range shifts are increasingly being identified in mobile animals that are responding to climate change. Range shifts are consequential to animal ecology, ecosystem function, and conservation goals, yet for many species these cannot be characterised without means of synoptically measuring their distribution. The distribution of critically endangered North Atlantic right whale ( Eubalaena glacialis; NARW) north of 45°N has been largely unknown due to a lack of systematic monitoring. The objectives of this study were to characterize the spatial and temporal variation in NARW acoustic occurrence in the northern portion of their foraging range. In addition, we sought to identify relevant NARW migratory corridors and explore potential previously unidentified high-use habitats beyond the highly surveyed Gulf of St. Lawrence (GSL). To achieve this, passive acoustic monitoring data were collected and analyzed from 67 moorings and 13 gliders deployed (across 38 recording stations) throughout the Atlantic Canadian continental shelf, between 42°N and 58°N during 2015 through 2017. The results support that while a portion of the population has moved northward into the GSL, this shift was constrained to temperate latitudinal ranges < 52°N during the study period. NARWs were not detected in the Labrador Sea and Newfoundland Shelf, despite their preferred prey occurring in those areas. NARWs were present on the Scotian Shelf (45°N) nearly year-round, but only from May through December in the Cabot Strait (50°N). These results indicate that the northern range of the population is probably influenced by energetic requirements to minimize the distance between suitable foraging habitat and low latitude calving grounds, rather than an absence of suitable foraging conditions in high latitude waters, or other environmental or physiological factors. This work provides critical information to conserve the species and mitigate human-induced risks.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".