An isotopic assessment of protein from diet and endogenous stores: Effects on egg production and incubation behaviour of geese
Bibliographic record
Abstract
Little empirical information exists to assess to what degree geese use a capital versus income breeding strategy for investing nutrients into eggs. We used stable isotope methods to directly estimate the sources of protein deposited into egg yolks of Brent Branta bernicla and Emperor Geese Anser canagicus on the Yukon-Kuskokwim Delta, Alaska, USA. Approximately 59 and 45% of protein in egg yolks of Brent and Emperor Geese, respectively, was derived from exogenous sources (i.e. food plants on the local breeding area). Within clutches of Brent Goose eggs, first-laid eggs exhibited slightly higher contributions from endogenous reserves than last-laid eggs. This pattern was less clear for Emperor Geese, which may have been a consequence of possibly analysing eggs that were laid by intraspecific nest parasites rather than by hosts. For both these species, individuals exhibited large variability in the percent contribution of exogenous versus endogenous stores to eggs, and future studies should identify ecological factors related to this variation. Those Emperor Geese in poor body condition incubated their nests less constantly, and based on δ 13 C values, they fed on terrestrial foods while off their nests. Although not a pure capital breeder, Emperor Geese used nutrients garnered on spring staging areas to fuel virtually all their own maintenance during incubation and to contribute half or more of the nutrients in eggs. These results highlight the ecological importance of these spring staging habitats to geese.
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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 | 0.000 | 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".