Effect of age and ration on diet-tissue isotopic (Δ<sup>13</sup>C, Δ<sup>15</sup>N ) discrimination in striped skunks (<i>Mephitis mephitis</i>)
Bibliographic record
Abstract
An important prerequisite for the effective use of stable isotopes in animal ecology is the accurate assessment of isotopic discrimination factors linking animals to their diets for a multitude of tissue types. Surprisingly, these values are poorly known in general and especially for mammalian carnivores and omnivores in particular. Also largely unknown are the factors that influence diet-tissue isotopic discrimination such as nutritional quality and age. We raised adult and juvenile striped skunks (Mephitis mephitis) in captivity on a constant omnivore diet (Mazuri Omnivore A 5635). Adults (n=6) and juveniles (n=3) were kept for 7 months and young (n=7) to the age of 50 days. We then examined individuals for stable carbon (δ(13)C) and nitrogen (δ(15)N) isotope values of hair, nails, lipid, liver, muscle, bone collagen and the plasma, and cellular fractions of blood. Discrimination values differed among age groups and were significantly higher for young compared with their mothers, likely due to the effects of weaning. Δ(15)N isotopic discrimination factors ranged from 3.14 (nails) to 5.6‰ (plasma) in adults and 4.3 (nails) to 5.8‰ (liver) for young. For Δ(13)C, values ranged from-3.3 (fat) to 3.0‰ (collagen) in adults and from-3.3 (fat) to 2.0‰ (collagen) in young. Our data provide an important tool for predicting diets and source of feeding for medium-sized mammalian omnivorous adults integrated over short (e.g. liver, plasma) through long (e.g. collagen) periods and underline the potential effects of age on isotopic values in omnivore diets.
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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 | 0.000 | 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 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".