Does the proportion of arthropods versus fruit in the diet influence overwintering condition of an omnivorous songbird?
Bibliographic record
Abstract
Many migratory songbirds switch from a primarily insectivorous diet during the breeding season to either a mixed diet or fruit diet during the non-breeding season. However, for species with mixed diets, arthropods may be superior food items because of their higher protein content and easier digestibility. We tested this hypothesis by analyzing the diet and body condition of omnivorous Wood Thrushes (Hylocichla mustelina) at a non-breeding site in tropical forest in Belize, Central America. We used analysis of stable isotopes δ15N and δ13C in the blood to measure diet. Our objective was to determine if a higher dietary proportion of arthropods relative to fruit (i.e., higher δ15N and δ13C) was associated with better body condition. We also examined the possible effect of age, sex, and habitat type on Wood Thrush diets, as well as any changes in diet through the overwintering period. We used a hierarchical Bayesian mixing model (MixSIAR) to estimate the proportion of different prey items in the diet of overwintering Wood Thrushes overall, in each habitat type, and over time during the non-breeding period. From January to April, we found a significant decline in δ15N in forest habitats, whereas δ15N increased in scrub habitat. There was no significant seasonal change in δ13C. Birds with higher δ15N or δ13C values were not in better body condition. Females in dry-scrub habitat consumed more fruit than males, but this did not affect body condition. Mixing model results indicated that most Wood Thrushes at our study sites consumed primarily arthropods, even during the driest times of the non-breeding season and in the driest habitat. Overall, our results suggest that the diet of Wood Thrushes varies with habitat and during the overwintering period, but diet alone was not a predictor of body condition. Wood Thrushes, and possibly other omnivorous migratory songbirds, are apparently flexibly able to meet their wintering and pre-migration nutritional demands with a variety of diets.
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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 | 0.000 | 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".