Use of amino acid isotope analysis to investigate capital versus income breeding strategies in migratory avian species
Bibliographic record
Abstract
Abstract Income and capital breeding represent opposing ends of a continuum of reproductive strategies. Quantifying nutrient allocation to reproduction is challenging, but recent advances in compound‐specific stable isotope analysis hold promise for tracing the source of individual compounds allocated to reproduction. Here, we describe a novel approach of using measured carbon (δ 13 C) and nitrogen (δ 15 N) isotope values of individual amino acids (AAs) in pectoral muscle of egg‐laying females and egg yolk as a useful tool to quantify the reliance on income versus capital breeding in migrating species. We used white‐fronted ( Anser albifrons frontalis ), lesser snow ( A. caerulescens caerulescens ) and black brant ( Branta bernicla nigricans ) geese breeding in tundra ecosystems of northern Alaska as model organisms. All three species relied on mixed capital–income breeding strategies, but models based on AA isotope data estimated higher proportional contributions of endogenous resources to yolk synthesis compared to results based on bulk tissue isotope analyses. Tracing income versus capital nutrient allocation in migratory species at the compound level is a major advance from the current ‘elemental’ perspective obtained from bulk tissue stable isotope analyses. Our framework is applicable to all taxonomic groups, as long as there is a sufficient spatial or temporal isotopic gradient between resources obtained during the breeding and non‐breeding periods.
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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) | 0.000 | 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".