Life history predicts flight muscle phenotype and function in birds
Bibliographic record
Abstract
1. Functional traits are the essential phenotypes that underlie an organism’s life history and ecology. Although biologists have long recognized that intraspecific variation is consequential to an animals’ ecology, studies of functional variation are often restricted to species-level comparisons, ignoring critical variation within species. In birds, interspecific comparisons have been foundational in connecting flight muscle phenotypes to species-level ecology, but intraspecific variation has remained largely unexplored. 2. We asked how age- and sex-dependent demands on flight muscle function are reconciled in birds. The flight muscle is an essential multifunctional organ, mediating a large range of functions associated with powered flight and thermoregulation. These functions must be balanced over an individual’s lifetime. 3. We leveraged within- and between-species comparisons in a clade of small passerines (Tarsiger bush-robins) from the eastern edge of the Qinghai-Tibet Plateau. We integrated measurements of flight muscle physiology, morphology, behavior, phenology, and environmental data, analyzing trait data within a context of three widespread, adaptive life-history strategies – sexual dichromatism, age and sex-structured migration, and delayed plumage maturation. This approach provides a framework of the selective forces that shape functional variation within and between species. 4. We found more variation in flight muscle traits within species than has been previously described between species of birds under 20 g. This variation was associated with the discovery of mixed muscle fiber types (i.e. both fast glycolytic and fast oxidative fibers), which differ markedly in their physiological and functional attributes. This result is surprising given that the flight muscles of small birds are generally thought to contain only fast oxidative fibers, suggesting a novel ecological context for glycolytic muscle fibers in small birds. Within each species, flight muscle phenotypes varied by age and sex, reflecting the functional demands at different life-history stages and the pressures that individuals face as a result of their multi-class identity (i.e. species, age, and sex). 5. Our findings reveal new links between avian physiology, ecology, behavior, and life history, while demonstrating the importance of demographic-dependent selection in shaping functional phenotypic variation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".