Aggregative response of Harlequin Ducks to herring spawning in the Strait of Georgia, British Columbia
Bibliographic record
Abstract
We determined the scale of aggregative response of Harlequin Ducks (Histrionicus histrionicus) to seasonally and locally superabundant prey at Pacific herring (Clupea pallasi) spawning sites in the northern Strait of Georgia, British Columbia, in 19952002. Aggregations of 34005500 birds gathered at a small number of sites along the same 8-km stretch of shoreline each year that spawn was available there. Aggregations occurred in only a small fraction of the habitat area where spawn was available. Duration of stay at spawning sites averaged 23 weeks and many birds returned to their wintering grounds afterwards. Birds moving to spawning sites represented 5587% of the total wintering population. The proportion of local wintering populations that moved to spawning sites was negatively related to the distance they had to travel, and few birds travelled farther than 80 km. The decline in proportions moving with increasing distance suggests that more distant individuals may be constrained by a lack of information or that there are trade-offs between the benefits of exploiting spawn and the costs of movement. This raises a conservation concern because the temporal and geographic range of herring spawning in British Columbia is contracting and some wintering waterbird populations may be losing access to this important late-winter food.
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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 | 0.001 | 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) | 0.001 | 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".