Metabolic Fates of Evening Crop-Stored Sugar in Ruby-Throated Hummingbirds (Archilochus colubris)
Bibliographic record
Abstract
During the day, hummingbirds quickly metabolize floral nectar to fuel high metabolic demands, but are unable to feed at night. Though stored fat is the primary nocturnal metabolic fuel, it has been suggested that hummingbirds store nectar in their crop to offset fat expenditure in the night or to directly fuel their first foraging trip in the morning. We examine the use of crop-stored sugar in the nocturnal energy budget of ruby-throated hummingbirds (Archilochus colubris) using respirometry and 13C stable isotope analysis. Hummingbirds were fed a 13C-enriched sugar solution before lights-out and held in respirometry chambers overnight without food. Respirometry results indicate that the hummingbirds metabolized the sugar in the evening meal in less than 2 h, and subsequently primarily catabolized fat. Breath stable isotope signatures provide the key insight that the hummingbirds converted a substantial portion of an evening meal to fats, which they later catabolized to support their overnight metabolism and spare endogenous energy stores. These results show that the value of a hummingbird’s evening meal depends on how much of this energy was converted to fat. Furthermore, this suggests that evening hyperphagia is an important energy maximization strategy, especially during energetically expensive periods such as migration or incubation.
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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".