Variability in stable isotopes of snowy owl feathers and contribution of marine resources to their winter diet
Bibliographic record
Abstract
The snowy owl is an elusive arctic predator known for its nomadic behaviour. Satellite tracking has revealed that some adult snowy owls could make an extensive use of the marine environment during the non‐breeding season. However, the relative contribution of marine resources to their diet is unknown. Stable isotope analyses can be useful to document the diet of mobile animals during periods of the year when individuals are less accessible. This study aimed to assess variation in isotopic values (δ 13 C and δ 15 N) of various feather types, and the usefulness of feathers to determine the contribution of the marine environment to the winter diet of snowy owls captured in summer. We sampled feathers coming from 6 body regions of 18 breeding females at two sites in the eastern Canadian Arctic in 2013 and 2014. Prior to analyses, diet‐tissue discrimination factors of snowy owl feathers were established in captivity. Variability in isotopic values among feather types was relatively low and pairwise correlations in isotopic values between feathers on the same individual were variable and often low, which suggests differences in the diet at the time when various feathers were synthesized. Diet reconstruction models detected a contribution of marine sources to snowy owl feathers ranging from 4 to 19% among feather types. However, the marine contribution was highly variable when single feathers were examined within individuals, ranging from 3 to 71%. This indicated that no single feather type could be used alone to reliably infer the contribution of marine resources to the winter diet of owls, possibly due to a high variability in the timing and sequence of molt. For asynchronous molters like snowy owls, we recommend sampling multiple feathers from various body regions, excluding wing feathers, to investigate winter diet or habitat use.
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How this classification was reachedexpand
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 | 0.002 | 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 teacher head, 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".