Intra-hair stable isotope analysis implies seasonal shift to salmon in gray wolf diet
Bibliographic record
Abstract
Seasonal shifts in diet are widespread, but our ability to detect them can be limited. Comparisons of stable isotope signatures in metabolically inert tissue portions grown at different times are inadequately exploited in dietary reconstructions. We propose that segments of guard hair can index diet to periods of growth (i.e., seasons differing in resource availability). We examined inter-hair δ13C and δ15N signatures from gray wolves (Canis lupus) of British Columbia to test whether the bulk of enriched (marine-derived) nutrients was assimilated during fall, the peak of salmon (Onchorynchus spp.) migration. In five animals, we detected a seasonal dietary shift: relatively more13C and15N was assimilated during fall than during summer, suggesting use of salmon during fall. Twelve wolves and both controls showed no seasonal shift in diet. Using salmon when available may be adaptive, given its predictability, spatial constraint, caloric content, and lower potential to inflict injury relative to that imposed by large mammals. Our study complements others that also used novel and fine-scale isotope approaches and may permit the identification of otherwise undetectable niche differentiation among conspecifics or heterospecifics.
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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".