Use of stable-carbon and -nitrogen isotopes to assess weaning and fasting in female polar bears and their cubs
Bibliographic record
Abstract
In some species, stable-isotope techniques can provide insights into dietary regimens where there are temporal shifts in trophic level or feeding frequency. We determined stable carbon (δ13C) and nitrogen (δ15N) isotope values for plasma and milk proteins and δ13C values for milk lipids from female polar bears (Ursus maritimus) and cubs to (i) ascertain whether cubs are at a higher trophic level than their mothers as a result of nursing and whether we can determine when weaning occurs, and (ii) determine the impact of seasonal fasting on δ13C and δ15N values. The plasma δ13C values for mothers and cubs were similar to milk-protein δ13C values and were significantly enriched in 13C compared with those for milk lipid. Plasma from cubs of the year (COYs) in spring, when milk was their only diet, was isotopically enriched in 15N by 1.0 over that of their mothers (δ15N = 21.5 ± 0.8 (mean ± SD) for cubs and 20.5 ± 0.5 for mothers) and depleted in 13C by 0.8 (δ13C = 19.6 ± 0.5 for cubs and 18.8 ± 0.8 for mothers). For bears who fasted between summer and fall (34 months), plasma became depleted in 13C by 0.5 and in 15N by 1. Plasma from females, who had fasted from summer to spring (78 months) and given birth to cubs, became enriched in 13C by 0.7 and in 15N by 2. By using stable-isotope analyses we were able to show that (i) young cubs were at a higher trophic level than their mother when milk was their only food source, and (ii) seasonal fasting influenced δ13C and δ15N values. However, we were not able to use stable-isotope analyses to determine the exact time of weaning.
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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 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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".