Carbon isotopic fractionation in eider adipose tissue varies with fatty acid structure: implications for trophic studies
Bibliographic record
Abstract
Carbon isotopic fractionation was investigated in fatty acids (FA) of adipose tissue and blood serum of threatened Steller's eiders (Polysticta stelleri) and spectacled eiders (Somateria fischeri) relative to the FA in their diets. Captive eiders were fed a known diet for 180 days with serum sampled at 60, 120 and 180 days immediately after a 12 fast; adipose was collected at 180 days. Essential FA (EFA) in the adipose showed varying degrees of isotope fractionation (0-4‰), depending on FA structure. The δ(13)C values of long-chain FA 20:5n-3 and 22:6n-3 did not differ from those in the diet, while those of 18:2n-6 and 18:3n-3 were ∼2‰ greater than in the diet. The δ(13)C values of free FA (FFA) in serum were not consistent within individuals or sampling dates; fractionation varied randomly, suggesting that FFA were arising from diet, rather than mobilization from adipose tissue. Discrimination factors were used in combination with a mixing model incorporating FA and lipid concentrations to estimate the diet of eiders fed a binary mixture with contrasting isotopic signatures. Diet estimates varied with FA but mean values closely approximated the actual proportions consumed. By tracking EFA, this study avoided the complications in interpretation arising from isotopic routing of carbon in bulk isotope analyses and serves as a basis for the development of compound-specific isotopic methods to trace dietary input in wild eiders. However, our understanding of the processes contributing to the variation in isotopic signatures of FA in nature is currently limited, and we recommend that future research directions focus on elucidating these mechanisms.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".