What’s happening with Harlequin ducks in the Salish Sea?
Bibliographic record
Abstract
White Rock B.C. supports a relatively small population of Harlequin ducks during the non-breeding period. From the 1980s to the mid-2000s, males consistently returned to White Rock during June-July to complete their body and wing molts, followed by females 1-2 months later. However, by 2006 all males stopped molting at White Rock, returning instead 2+ months later in pre-alternate plumage. Associated with this change in behavior the number of overwintering males declined and this contributed to a local population level effect. Causal factors are unknown but the following are suspected: 1) increasing levels of disturbance from kayakers and paddle-boarders, and/or 2) increasing levels of predation risk from river otters and bald eagles. Surveys were initiated at two nearby sites (Point Roberts and Birch Bay in WA State) to determine if the same pattern of delayed return is occurring, and that definitely seems to be the case. In spring 2015 we marked Harlequin ducks at White Rock (7M/7F) and Hornby Island (14M/8F) with satellite transmitters to describe winter-breeding affiliations and site-fidelity, and to track male molt migration patterns. The resulting Argos data showed that the large majority of the tagged birds bred in the Rocky Mountain-Kootenay Mountain region, all signaling birds returned to their capture sites by the end of October indicating a high level of site-fidelity, and the males migrated north of the Salish Sea to molt, from northern Vancouver Island to Prince Rupert BC. This large-scale molt migration was unexpected and raises the following questions: Why is it occurring? Is it happening throughout the Salish Sea? Is this a recent phenomenon or has it always occurred? Finally, what are the population implications for Harlequin ducks and other marine birds in the Salish Sea? Plans are to mark breeding birds in Alberta and northern US Sates to further describe connectivity and migration patterns.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".