An experimental study of carbon-isotope fractionation between diet, hair, and feces of mammalian herbivores
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Bibliographic record
Abstract
The carbon-isotope composition of hair and feces offers a glimpse into the diets of mammalian herbivores. It is particularly useful for determining the relative consumption of browse and graze in tropical environments, as these foods have strongly divergent carbon-isotope compositions. Fecal δ 13 C values reflect the last few days consumption, whereas hair provides longer term dietary information. Previous studies have shown, however, that some fractionation occurs between dietary δ 13 C values and those of hair and feces. Accurate dietary reconstruction requires an understanding of these fractionations, but few controlled-feeding studies have been undertaken to investigate these fractionations in any mammalian taxa, fewer still in large mammalian herbivores. Here, we present data from the first study of carbon-isotope fractionation between diet, hair, and feces in multiple herbivore taxa. All taxa were fed pure alfalfa (Medicago sativa) diets for a minimum period of 6 months, at which point recently grown hair was shaved and analyzed for carbon isotopes. The mean observed diethair fractionation was +3.2, with a range of +2.7 to +3.5. We also examined dietfeces fractionation for herbivores on alfalfa and bermudagrass (Cynodon dactylon) feeds. The mean dietfeces fractionation for both diets was 0.8, with less fractionation for alfalfa (0.6) than bermudagrass (1.0). Fecal carbon turnover also varies greatly between taxa. When diets were switched, horse (Equus caballus) feces reflected the new diet within 60 h, but alpaca (Lama pacos) feces did not equilibrate with the new diet for nearly 200 h. Thus, fecal carbon isotopes provide far greater dietary resolution for hindgut-fermenting horses than foregut-fermenting alpacas.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it