Using stable isotope (δ13C, δ15N) values from feces and breath to infer shorebird diets
Bibliographic record
Abstract
Abstract The use of stable isotopes of carbon (δ13C) and nitrogen (δ15N) from feces and breath offers potential as non-destructive tools to assess diets and nutrition. How stable isotope values derived from breath and feces compare with those from commonly used tissues, such as blood fractions and liver, remains uncertain, including understanding the metabolic routing of dietary nutrients. Here, we measured δ13C and δ15N from feces and δ13C of breath from captive Red-necked Stints (Calidris ruficollis) and 26 species of wild-caught migratory shorebirds (n = 259 individuals) and compared them against isotopic values from blood and feathers. For captive birds fed either cereal- or fish-based diets, differences in δ13C between feces and lipid-free diet were small, − 0.2 ± 0.5‰ and 0.1 ± 0.3‰, respectively, and differences in δ15N, − 0.7 ± 0.5‰ and − 0.5 ± 0.5‰, respectively. Hence, δ13C and δ15N values from feces can serve as proxies for ingested proteinaceous tissues and non-soluble carbohydrates because isotopic discrimination can be considered negligible. Stable isotope values in plasma and feces were strongly correlated in wild-caught shorebirds, indicating feces can be used to infer assimilated macronutrients. Breath δ13C was 1.6 ± 0.8‰ to 5.6 ± 1.2‰ lower than bulk food sources, and breath C derived from lipids was estimated at 47.5% (cereal) to 96.1% (fish), likely underlining the importance of dietary lipids for metabolism. The findings validate the use of stable isotope values of feces and breath in isotopic assays to better understand the dietary needs of shorebirds.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".