Reducing uncertainty on the Grand Bank: tracking and vessel surveys indicate mortality risks for common murres in the North-West Atlantic
Bibliographic record
Abstract
Seabirds and other marine animals are at risk from anthropogenic activities that target them directly and those that can harm them incidentally. We integrate year-round tracking and vessel studies to assess risks for a globally important seabird population in the North-West Atlantic. The eastern Canadian Grand Bank has a rich and diverse food web that supports an abundance of apex predators. Major resource extraction industries (hydrocarbon production and fisheries) operate in the area, and, in addition to shipping and hunting, pose risks for marine birds. Understanding the relative risks has been hampered by poor information on bird distribution at sea. Here, we deployed global location sensors (loggers or geolocators) on common murres Uria aalge at Funk Island, the species' largest North American breeding colony. Adults (n=10) were resident on the Grand Bank and in adjacent pelagic waters year round. Within 10 days of leaving the colony, males dispersed offshore (<50°W), south–south-east of Funk Island. Females departed later and spent 10–47 days in coastal waters before moving offshore. All birds were in the vicinity of offshore oil platforms during November and December, but remained outside the area of the coastal Newfoundland and Labrador murre hunt. Three of six tracked females, but only one of four tracked males moved closer to shore during January and February where vulnerability to the hunt may have increased. Vessel-based surveys confirmed the importance of offshore, shelf-edge habitats for murres in winter. Our results highlight the relative risk to wintering murres from different human activities, providing a sound scientific rationale for focusing conservation and management actions. This information is particularly timely given the continued expansion of deep-water drilling in the North-West Atlantic and increasing risk of oil pollution for seabirds attracted to platforms.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 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".