Multi-year acoustic tracking reveals transient movements, recurring hotspots, and apparent seasonality in the coastal-offshore presence of Greenland sharks (Somniosus microcephalus)
Bibliographic record
Abstract
Variable movement strategies can complicate the conservation and management of mobile species. Given its extreme life history traits as a long-lived, deep-water species, the Greenland shark ( Somniosus microcephalus ) is vulnerable to fisheries bycatch, but little is known over its long-term movements across a spatially and seasonally variable Arctic environment. To address this knowledge gap, the movements of Greenland sharks in coastal fjords and offshore waters of Baffin Bay were examined using seven years of acoustic telemetry data. Seasonal patterns in broad-scale movements and inshore-offshore connectivity were compared among 155 sharks (101 males, 54 females [mean LT = 2.65 ± 0.48 m, range 0.93-3.5 m]) tagged in 6 discrete coastal locations spanning from Grise Fiord to Cumberland Sound (Nunavut). Sharks exhibited transient movements throughout coastal and offshore regions with some evidence of seasonally recurring hotspots revealed by repeat detections of individuals at sites over multiple years. Shark presence in coastal fjords occurred exclusively during the coastal ice-free period (July to November), regardless of the location of tagging or detection, while presence in the offshore was recorded during the period of ice re-formation and cover (November to July). Through multi-year telemetry, it was possible to reveal repetitive patterns in broad-scale habitat use for a complex marine predator with direct relevance for understanding the seasonal distribution of mobile Arctic consumers and informing regional fisheries management.
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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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".