Annual cycle of White-winged Scoters (<i>Melanitta fusca</i>) in eastern North America: migratory phenology, population delineation, and connectivity
Bibliographic record
Abstract
Understanding full annual cycle movements of long-distance migrants is essential for delineating populations, assessing connectivity, evaluating crossover effects between life stages, and informing management strategies for vulnerable or declining species. We used implanted satellite transmitters to track up to 2 years of annual cycle movements of 52 adult female White-winged Scoters (Melanitta fusca (Linnaeus, 1758)) captured in the eastern United States and Canada. We used these data to document annual cycle phenology; delineate migration routes; identify primary areas used during winter, stopover, breeding, and molt; and assess the strength of migratory connectivity and spatial population structure. Most White-winged Scoters wintered along the Atlantic coast from Nova Scotia to southern New England, with some on Lake Ontario. White-winged Scoters followed four migration routes to breeding areas from Quebec to the Northwest Territories. Principal postbreeding molting areas were in James Bay and the St. Lawrence River estuary. Migration phenology was synchronous regardless of winter or breeding origin. Cluster analyses delineated two primary breeding areas: one molting area and one wintering area. White-winged Scoters demonstrated overall weak to moderate connectivity among life stages, with molting to wintering connectivity the strongest. Thus, White-winged Scoters that winter in eastern North America appear to constitute a single continuous population.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 source (direct Gemma or distilled Codex), 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".