Declining population of Harlequin Duck (<i>Histrionicus histrionicus</i>) on the Bow River, Alberta, Canada: 25 years of monitoring
Bibliographic record
Abstract
Harlequin Duck (Histrionicus histrionicus) is a small sea duck that winters in coastal waters and breeds on fast-movingmountain streams in western North America. Because of its dependency on streams and coastal near-shore habitat with healthy macroinvertebrate populations, population trends of this species can be used as an indication of healthy freshwater and marine ecosystems. From 1995 to 2020 we conducted roadside surveys for Harlequin Ducks on the Bow River in Banff National Park, Alberta. We calculated the population’s trend by modelling maximum annual count, which showed a population decline over the 25 years of 3.3% per year. The trajectory varied over time: a relatively stable population from 1995 to 2005, a steep decline until 2011, then stabilising at a much lower level with a slight rebound in recent years. The predicted number of ducks from our state-space model closely tracked the maximum number of ducks observed in annual counts. During stable or slightly increasing population estimates the male:female (M:F) ratio fluctuated considerably but stayed high (1.4:1 and 1.3:1, respectively), and during the period of steep population decline the M:F ratio was at its lowest (1.1:1). This declining population trend is concerning because it is occurring in a protected area, but it is similar to data from other studies in the Rocky Mountains and at the coastal wintering area, suggesting that causes may not be solely due to issues on the breeding streams.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".