Amino Acid Specific Stable Nitrogen Isotope Values in Avian Tissues: Insights from Captive American Kestrels and Wild Herring Gulls
Bibliographic record
Abstract
Through laboratory and field studies, the utility of amino acid compound-specific nitrogen isotope analysis (AA-CSIA) in avian studies is investigated. Captive American kestrels ( Falco sparverius ) were fed an isotopically characterized diet and patterns in δ 15 N values of amino acids (AAs) were compared to those in their tissues (muscle and red blood cells) and food. Based upon nitrogen isotope discrimination between diet and kestrel tissues, AAs could mostly be categorized as source AAs (retaining baseline δ 15 N values) and trophic AAs (showing 15 N enrichment). Trophic discrimination factors based upon the source (phenylalanine, Phe) and trophic (glutamic acid, Glu) AAs were 4.1 (muscle) and 5.4 (red blood cells), lower than those reported for metazoan invertebrates. In a field study involving omnivorous herring gulls ( Larus argentatus smithsonianus ), egg AA isotopic patterns largely retained those observed in the laying female’s tissues (muscle, red blood cells, and liver). Realistic estimates of gull trophic position were obtained using bird Glu and Phe δ 15 N values combined with β values (difference in Glu and Phe δ 15 N in primary producers) for aquatic and terrestrial food webs. Egg fatty acids were used to weight β values for proportions of aquatic and terrestrial food in gull diets. This novel approach can be applied to generalist species that feed across ecosystem boundaries.
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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 | 0.001 | 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".