Uncoupling Basal and Summit Metabolic Rates in White-Throated Sparrows: Digestive Demand Drives Maintenance Costs, but Changes in Muscle Mass Are Not Needed to Improve Thermogenic Capacity
Bibliographic record
Abstract
Avian basal metabolic rate (BMR) and summit metabolic rate (Msum) vary in parallel during cold acclimation and acclimatization, which implies a functional link between these variables. However, evidence suggests that these parameters may reflect different physiological systems acting independently. We tested this hypothesis in white-throated sparrows (Zonotrichia albicollis) acclimated to two temperatures (−8° and 28°C) and two diets (0% and 30% cellulose). We expected to find an uncoupling of Msum and BMR where Msum, a measure of maximal shivering heat production, would reflect muscle and heart mass variation and would respond only to temperature, while BMR would reflect changes in digestive and excretory organs in response to daily food intake, responding to both temperature and diet. We found that the gizzard, liver, kidneys, and intestines responded to treatments through a positive relationship with food intake. BMR was 15% higher in cold-acclimated birds and, as expected, varied with food intake and the mass of digestive and excretory organs. In contrast, although Msum was 19% higher in cold-acclimated birds, only heart mass responded to temperature (+18% in the cold). Pectoral muscles did not change in mass with temperature but were 8.2% lighter on the cellulose diet. Nevertheless, Msum varied positively with the mass of heart and skeletal muscles but only in cold-acclimated birds. Our results therefore suggest that an upregulation of muscle metabolic intensity is required for cold acclimation. This study increases support for the hypothesis that BMR and Msum reflect different physiological systems responding in parallel to constraints associated with cold environments.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".