Foraging Effort and Pre-Laying Strategy in Breeding Common Eiders
Bibliographic record
Abstract
To face energetic demands of reproduction, female birds need to build up body reserves before breeding and/or feed while producing eggs and incubating. Five female Common Eiders were implanted with data loggers that recorded flying and diving activity for a year. The pre-laying period, defined as the interval between the end of spring migration and laying of the first egg, extended over eleven to 27 days and represented a period of intense foraging activity. Daily time spent diving (DTSD) during the pre-laying period averaged 159.6 ± 16.0 min compared to an annual average of 91.4 ± 37.8 min. Diving decreased to 69.8 ± 7.4 min during laying and became almost negligible at the onset of incubation. Females showed hyperphagic behavior during follicular growth, suggesting that they may directly utilize ingested food for egg production and laying. Given the small number of instrumented females, available evidence was reviewed on foraging and time of arrival in various populations and subspecies. Despite large variations in migration distance, the pre-laying period was similar to other populations (16–28 days), as well as DTSD (160–211 min). Reduced take-off capability may constrain the timing of accumulation of body reserves and foraging effort. Further, the level of body mass required for nesting (laying and incubation) was estimated to be 543 g higher than in winter, of which about 41–72% would be accumulated on the breeding grounds. Protection of foraging areas during the pre-breeding period is important to maintain healthy populations.
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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".