The influence of biopsy site and pregnancy on stable isotope ratios in humpback whale skin
Bibliographic record
Abstract
Abstract Rationale Stable isotope analysis (SIA) of free‐swimming mysticetes using biopsies is often limited in sample size and uses only one sample per individual, failing to capture both intra‐individual variability and the influence of demographic and physiological factors on isotope ratios. Methods We applied SIA of δ 13 C and δ 15 N to humpback whale ( Megaptera novaeangliae ) biopsies taken during the foraging season along the western Antarctic Peninsula to quantify intra‐individual variation from repeatedly sampled individuals, as well as to determine the effect of biopsy collection site, sex, and pregnancy on isotope ratios. Results There was substantial variability in δ 13 C from multiple biopsies taken from the same individuals, though δ 15 N was much more consistent. Side of the body (left versus right) and biopsy location (dorsal, anterior, ventral, and posterior) did marginally affect the isotopic composition of δ 15 N but not δ 13 C. Pregnancy had a significant effect on both δ 13 C and δ 15 N, where pregnant females were depleted in both when compared to non‐pregnant females and males. Conclusions These results indicate that isotopic signatures are influenced by multiple endogenous and exogenous factors and emphasize value in accounting for intra‐individual variability and pregnancy status within a sampled population. Placed within an ecological context, the endogenous variability in δ 13 C observed here may be informative for future isotopic analyses.
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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 | 0.001 | 0.001 |
| 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".