Nitrogen and carbon isotope values of individual amino acids: a tool to study foraging ecology of penguins in the Southern Ocean
Bibliographic record
Abstract
We determined the δ 15 N and δ 13 C values of individual amino acids (AAs) isolated from chick blood of 4 penguin species that forage in different oceanic regions (from the subtropics of the Indian Ocean to Antarctica) to test if: (1) the δ 15 N values of phenylalanine (δ 15 N phe ) revealed different foraging areas among the species; (2) the difference between glutamic acid and phenylalanine δ 15 N values (Δδ 15 N glu-phe ) accurately predicted trophic levels; and (3) the δ 13 C value of AAs could resolve species foraging locations, similar to bulk δ 13 C values.The δ 13 C values of all AAs decreased with latitude, were positively correlated with bulk δ 13 C data, and, therefore, tracked the isotopic baseline.However, we were not able to discern additional ecological information from these δ 13 C values.In contrast, the δ 15 N values of AAs distinguished the isotopic value of the nitrogen at the base of the food web from the trophic level of the consumer, providing new insight for the study of the trophic ecology of seabirds.The difference in the bulk δ 15 N values of northern and southern rockhopper penguins Eudyptes chrysocome ssp.was due to both a difference in their foraging location (different δ 15 N phe ) and their trophic levels (different Δδ 15 N glu-phe ).The δ 15 N phe values of king Aptenodytes patagonicus and Adélie penguins Pygoscelis adeliae were higher than those of rockhoppers, which could reflect a foraging on mesopelagic prey for king penguins and, in the highly productive Antarctic shelf waters, for Adelie penguins.The Δδ 15 N glu-phe accurately reflected the relative trophic level of penguins, but further work is required to determine the trophic enrichment factors for compound-specific isotope analysis.
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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 | 0.001 |
| 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".