Evidence for within-individual energy reallocation in cold-challenged, egg-producing birds
Bibliographic record
Abstract
Recent studies have shown that the metabolic cost of avian egg production involves a 16-27% increase in metabolic rate (MR) above non-reproductive basal or resting values (BMR and RMR, respectively). To determine how the metabolic cost of egg production interacted with the costs of other essential processes (such as cold acclimation and active heat production), we measured the MR of non-breeding and egg-producing zebra finches (Taeniopygia guttata) while (a) warm-acclimated (to 19-21 degrees C) and measured within their thermoneutral zone (at 35 degrees C), (b) cold-acclimated (to 7 degrees C) and measured at thermoneutrality (at 35 degrees C, i.e. not actively producing heat), and (c) cold-acclimated and measured below thermoneutrality (at 7 degrees C) (i.e. during active heat production). The metabolic cost of egg production was small (24% above BMR) compared with the additive costs of cold acclimation and active heat production (224% above BMR). Exposure to low ambient temperatures was accompanied by an increase in seed consumption (by 72%) and a decrease in locomotor activity (by 72%) compared with warm-acclimated, non-breeding values. By contrast, egg production in heat-producing females was associated with an 11% decrease in MR and a 22% decrease in seed consumption compared with non-breeding thermoregulating values. Our data suggest that while the increase in MR associated with egg production is small in relation to the birds' capacity to increase MR in response to other energetically demanding processes, the addition of egg production to these metabolically costly activities may be enough to necessitate the use of energy-saving strategies, such as internal energy reallocation, to cope with the additional energetic demands.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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".