Arctic herbivore diet can be inferred from stable carbon and nitrogen isotopes in C<sub>3</sub> plants, faeces, and wool
Bibliographic record
Abstract
The use of stable isotopes in diet analysis usually relies on the different photosynthetic pathways of C3 and C4 plants, and the resulting difference in carbon isotope signature. In the Arctic, however, plant species are exclusively C3, and carbon isotopes alone are therefore not suitable for studying arctic herbivore diets. In this study, we examined the potential of both stable carbon and nitrogen isotopes to reconstruct the diet of an arctic herbivore, here the muskox ( Ovibos moschatus (Zimmermann, 1780)), in northeast Greenland. The isotope composition of plant communities and functional plant groups was compared with those of muskox faeces and shed wool, as this is a noninvasive approach to obtain dietary information on different temporal scales. Plants with different root mycorrhizal status were found to have different δ15N values, whereas differences in δ13C, as expected, were less distinct. As a result, our examination mainly relied on stable nitrogen isotopes. The interpretation of stable isotopes from faeces was difficult because of the large uncertainty in diet–faeces fractionation, whereas isotope signatures from wool suggested that the muskox summer diet consists of around 80% graminoids and up to 20% willows. In conclusion, the diet composition of an arctic herbivore can indeed be inferred from stable isotopes in arctic areas, despite the lack of C4 plants.
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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) | 0.001 | 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".