Seasonal changes of stable isotope signals in the primary feathers of plains sharp‐tailed grouse
Bibliographic record
Abstract
Abstract Stable isotopes of a consumer organism can be used to estimate the proportional utilization of food items that have different isotopic signals to estimate changes in diet over time. Using stable isotopes as biotracers has become a useful tool for investigating trophic dynamics in ecosystems. Recent advances in the theory of stable isotope dynamics and food web modeling have extended the utility of natural variations in stable isotope abundance. However, as a growing field, some potentially useful approaches to using stable isotopes remain untested. Here, we used stable isotopes of nitrogen (δ 15 N) and carbon (δ 13 C) to validate their utility in examining the feeding relationships of plains sharp‐tailed grouse ( Tympanuchus phasianellus jamesi ; hereafter sharp‐tailed grouse) in southern Alberta, Canada. Sharp‐tailed grouse are known to consume mostly plants and opportunistically utilize insects and spiders as a high protein food source between May and October. Primary feathers obtained from hunter harvested grouse were analysed and used to estimate diet proportions of vegetation and arthropods during this time frame. Stable isotope measurements of primary feathers were able to show seasonal changes in sharp‐tailed grouse diet. Our results indicated that sharp‐tailed grouse may primarily utilize nutrients obtained from insect prey (mainly grasshoppers) for feather synthesis during molt, and that the isotope signals found in primary feathers may be a result of isotopic routing. Stable isotope data also reflected known differences among adult female and male, and juvenile grouse feeding ecology. However, model uncertainty existed due to isotopic similarity of some plant and animal food sources.
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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 | 0.000 | 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".