Age and Sex Ratios of Sea Ducks Wintering in the Strait of Georgia, British Columbia: Implications for Monitoring
Bibliographic record
Abstract
In research on sea ducks, winter age and sex ratios provide valuable demographic data that are difficult to obtain by other means.Our objectives were to determine spatial, temporal, and density-related variability in (1) age and sex ratios for five sea duck species and (2) proportions of adult males for eight species that winter in the Strait of Georgia, British Columbia, Canada.Kilometre-long shoreline sections (n = 49-62) were surveyed in early February in three years : 2003, 2004, and 2014.Annual estimates for male age ratio (first year:adult male) varied significantly for Black Scoter Melanitta americana (0.071 to 0.170), Surf Scoter M. perspicillata (0.064 to 0.101) and Harlequin Duck Histrionicus histrionicus (0.068 to 0.138).Regional differences in male age ratio were found for Barrow's Goldeneye Bucephala islandica (0.034 to 0.197) and Common Goldeneye B. clangula (0.033 to 0.165), and more complex interactions were found between regions by year for Surf Scoter.Sex ratios were less variable than age ratios and varied consistently by year and region only for Common Goldeneye.Adult male proportions were correlated with but varied more than sex ratios and showed significant differences by year for Surf Scoter, Common Goldeneye and Bufflehead B. albeola and by region for Surf Scoter, Common Goldeneye, Bufflehead and Red-breasted Merganser Mergus serrator.Based on previous research that calculated expected confidence limits from different numbers of occupied survey sections, the sampling intensity for each species obtained in this study provided age ratio estimates with 95% confidence limits likely within ± 5% for Surf Scoters and ± 3% for Harlequin Ducks.Regional and density-related differences in age ratios, sex ratios and adult male proportions indicated segregation and emphasize the need for broad-scale sampling to achieve representativeness.Inter-annual differences may indicate demographic changes, but few comparative data exist, and several consecutive years of surveys are needed to provide baseline data.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".