Consequences of being phenotypically mismatched with the environment: rapid muscle ultrastructural changes in cold-shocked black-capped chickadees (<i>Poecile atricapillus</i>)
Bibliographic record
Abstract
Phenotypic flexibility has received considerable attention in the last decade; however, whereas many studies have reported amplitude of variation in phenotypic traits, much less attention has focused on the rate at which traits can adjust in response to sudden changes in the environment. We investigated whole animal and muscle phenotypic changes occurring in black-capped chickadees ( Poecile atricapillus) acclimated to cold (−5°C) and warm (20°C) temperatures in the first 3 h following a 15°C temperature drop (over 3 h). Before the temperature change, cold-acclimated birds were consuming 95% more food, were carrying twice as much body fat, and had 23% larger pectoralis muscle fiber diameters than individuals kept at 20°C. In the 3 h following the temperature drop, these same birds altered their pectoralis muscle ultrastructure by increasing the number of capillaries per fiber area and the number of nuclei per millimeter of fiber by 22%, consequently leading to a 22% decrease in myonuclear domain (amount of cytoplasm serviced per nucleus), whereas no such changes were observed in the warm-acclimated birds. To our knowledge, this is the first demonstration of such a rapid adjustment in muscle fiber ultrastructure in vertebrates. These results support the hypothesis that chickadees maintaining a cold phenotype are better prepared than warm-phenotype individuals to respond to a sudden decline in temperature, such as what may be experienced in their natural wintering environment.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".