Movement Rates and Distances of Wintering Harlequin Ducks: Implications for Population Structure
Bibliographic record
Abstract
Population structure of Harlequin Ducks (Histrionicus histrionicus) wintering in the Strait of Georgia, British Columbia, was evaluated by generating age, sex, paired status and distance-specific movement rates with multi-stratum mark-recapture analyses, and age and sex-specific movement distances through surveys of marked individuals. Annual movement distances and rates did not differ by sex, but only 2–4% of adults (third year and afterthird year) compared to 7–11% of subadults (hatch year and second year) moved among locations per year and distance moved decreased with age. Adults were highly site faithful regardless of sex and paired status. The stepping stone gene flow model estimated the among population component of genetic variance (FST) at 0.005, suggesting that winter movement by subadults was sufficient to explain results of previous genetic analyses that detected no fine scale genetic structuring. Seasonal movement rates indicated that at least 95% of individuals molt and winter in the same location, and that annual aggregation at Pacific Herring (Clupea pallasi) spawning sites facilitates demographic mixing and gene flow. Low annual movement rates (0.001) between the northern and southern Strait of Georgia and dispersal by both sexes suggest that a metapopulation distribution may function within the Pacific Coast range, which is relevant to the geographic scale of management. Movement rates and distances suggest that subadult survival rates are particularly vulnerable to underestimation.
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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 | 0.001 |
| 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".