Can diet composition estimates using stable isotope analysis of feathers predict growth and condition in nestling mountain bluebirds (<i>Sialia currucoides</i>)?
Bibliographic record
Abstract
Abstract Insectivorous birds breeding in seasonal environments provision their dependent young during periods when prey diversity and abundance vary. Consequently, the composition and nutritional value of diets parents feed to their offspring may differ within and among broods, potentially affecting the condition of nestlings. In a population of mountain bluebirds (Sialia currucoides), we used two methods to estimate diet composition for individual nestlings: direct observation of provisioning using video recordings at 5 and 9 days post‐hatch, and stable isotopes of the δ13C and δ15N in nestling feathers and prey followed by analysis with mixing models. We determined the macronutrient content (% fat and lean mass) and estimated the metabolized energy from each type of prey. We evaluated whether different methods of estimating diet composition would produce similar results, and whether the types of prey nestlings ate at one or both ages affected their morphology, growth rates, or blood ketone concentration. We found that bluebirds fed their young 5 main types of prey: beetles, cicadas, grasshoppers, insect larvae, and spiders. Both observational and mixing model estimates of diet composition indicated that larvae are traded off with grasshoppers and that fewer larvae are provided to nestlings as the season progresses. In evaluating how diet influences individual growth and condition, estimates from direct observations had greater explanatory power than those from mixing models, indicating that diets rich in the most energy‐dense prey (greatest fat content; cicadas and larvae) were associated with larger size and higher body condition, and faster rate of mass gain and growth of tarsus. Lower value prey had more limited, specific effects on nestlings, but may still be important dietary components. While isotopic methods produced estimates of diet composition that were generally informative, when applied to explain the growth and condition of nestlings they proved less useful.
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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 | 0.001 |
| 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".