Year-round movements of Northern Common Eiders Somateria mollissima borealis breeding in Arctic Canada and West Greenland followed by satellite telemetry
Bibliographic record
Abstract
We implanted satellite transmitters to track Northern Common Eiders Somateria mollissima borealis from breeding grounds in West Greenland and eastern Arctic Canada, and from their wintering grounds in SW Greenland. We compared distances moved, timing, duration, and patterns of movement between migration flyways and between spring and autumn migration. Common Eiders used two wintering areas linked by three routes. Eiders tracked from a NW Greenland breeding colony (n = 10) migrated south along the coast to winter exclusively in west and southwest Greenland. Breeders from Arctic Canada wintered in two distinct areas with a tendency to segregate by sex. Some eastern Canadian Arctic Eiders from a colony near Southampton Island, migrated through Hudson Strait along the Labrador and Newfoundland coasts, to winter in Atlantic Canada. However, 60% (n = 25) originating from this colony crossed the Davis Strait to winter in SW Greenland, returning in spring to breed in Canada, linking the two north-south flyways. Seven of 8 Eiders implanted in SW Greenland in winter crossed the Davis Strait into Arctic Canada in spring to breed. Apparently more females than males from the Canadian colony (14/18 females and 1/6 males) followed the shorter east-west flyway in fall. Spring migration was initiated later in the Canadian Arctic. Tracked movements ranged from sedentary birds that nested within 45 km of their wintering area in SW Greenland, to migration routes that exceeded 2000 km. Spring migration speeds averaged c. 60 km d -1 , less than half that during moult migration (142 km d -1 ) and autumn migration (190 km d -1 ). This suggests that Eiders must stop to feed whilst travelling to breed, are constrained by sea ice conditions, or both. Climatic and sea ice conditions differ between the eastern Arctic Canada and west Greenland which influence wintering sites, timing and routes of spring migration.
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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 | 0.000 | 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".