Tracing the Origin of Dietary Protein in Tropical Dry Forest Birds<sup>1</sup>
Bibliographic record
Abstract
ABSTRACT Fundamental to our understanding of the ecology of animal communities in the tropics is knowledge of the effect of seasonal changes in the abundance of food sources in consumer diets. We determined stable‐isotope composition ( 13 C/ 12 C and 15 N/ 14 N) in whole blood of 14 resident avian species in a tropical dry forest to quantify the origin of their assimilated protein. We used a probabilistic approach (IsoSource) to estimate the relative contribution of C 3 plants, CAM‐C 4 plants, C 3 insects, and CAM‐C 4 insects during the dry and rainy seasons. IsoSource iteratively creates each possible combination of source contribution and produces a distribution of all feasible combinations that adequately predict the observed isotopic signature of the consumer. Granivore–frugivores and granivore–frugivore–insectivores were modeled as predominantly dependent upon plants whereas insectivorous birds were modeled to derive protein almost exclusively from insects. Between these extremes there were several species using mixed diets such as insectivore–frugivores or insectivore–granivores. In most species, virtually all assimilated food was of C 3 origin with the exception of Ruddy Ground‐Doves ( Columbina talpacoti ) in which CAM or C 4 plants contributed significantly. Seasonal changes in relative food source contribution were followed in eight species of birds. Of these species, White‐tipped Doves ( Leptotila verreauxi ), Grayish Saltators ( Saltator coerulescens ), and Social Flycatchers ( Myiozetetes similis ) increased their use of insects in the rainy season, in contrast to Great Kiskadees ( Pitangus sulphuratus ), which decreased their use of insects. Our study suggests that that diverse strategies are used by various avian species to obtain dietary proteins within seasonal habitats.
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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".