Variation in body mass and foraging effort of Barrow’s Goldeneyes (<i>Bucephala islandica</i>) during remigial molt
Bibliographic record
Abstract
ABSTRACT. Molt is a metabolically demanding process in the annual cycle of birds, particularly for species that undergo simultaneous remigial molt because nutritional and energetic costs occur during a short period. Birds that molt remiges simultaneously utilize many different body-mass and foraging strategies to meet the nutritional and energetic costs of remigial molt, and documentation of interspecific variation has contributed to understanding species-specific risks associated with molt. However, little is known about intraspecific variation in body-mass and foraging strategies among birds that molt remiges simultaneously. We documented body-mass dynamics and foraging effort of Barrow's Goldeneyes (Bucephala islandica) during simultaneous remigial molt at two important postbreeding sites, including a large, hypereuthrophic lake and a small, mesotrophic lake in Alberta, to determine whether strategies for meeting nutritional costs of remigial molt varied across sites, years, and cohorts. Average body mass of all age and sex cohorts on both lakes increased during remigial molt in both 2009 and 2010. Birds were heavier on the smaller lake, and heavier in 2010 than in 2009, and adult males were heavier than subadult males. Radiomarked adult males exhibited similar foraging effort on each lake in each year (approximately 120–140 min day-1); however, birds foraged primarily diurnally on the large lake and nocturnally on the small lake. We conclude that Barrow's Goldeneyes exhibit considerable intraspecific variation in body-mass and foraging dynamics during remigial molt across sites, years, and cohorts, which suggests that these components of molt strategy are plastic and responsive to local environmental conditions.
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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 | 0.000 |
| 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) | 0.001 | 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".