Interactive effects of temperature acclimation and dietary fatty acids on metabolic rate and body composition of zebra finches ( <i>Taeniopygia guttata</i> )
Bibliographic record
Abstract
Abstract Climate change is contributing to geographic range shifts in many bird species, with possible exposure to novel diets. How individuals respond physiologically across chronic time frames to the interacting effects of diet and environmental temperature has been little explored. We acclimated zebra finches to either cool (20-24°C) or thermoneutral (35°C) temperatures over 6-months and provided them with diets enriched in either unsaturated or saturated fatty acids. We measured body mass throughout the study, and basal metabolic rate (BMR) and body composition at 3- and 6-months, respectively. Individuals held in cool conditions and fed a diet enriched with unsaturated fatty acids lost mass initially relative to the other groups, however, effects were reversible, and all individuals had a similar mass at 6- months. Chronic exposure to cool conditions increased BMR and the mass of the pectoral muscle and visceral organs. However, we could detect no long-term effect of diet on any physiological parameter. Our results contrast with those of birds studied over acute time frames, in which diet and temperature interact to determine energy expenditure. Over chronic time frames individuals appear to reach a new steady-state, with long-term physiological responses driven primarily by thermoregulatory responses to environmental temperature. Research Highlights: With climate change, birds may encounter novel diets and temperatures In zebra finches we show that chronic acclimation to cool temperatures increased energy expenditure and changed body composition. Dietary fatty acid content had little long-term impact on the physiological parameters we measured.
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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 | 0.001 |
| 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".