No Signs of Adaptations for High Flight Intensity in the Mitochondrial Genome of Birds
Bibliographic record
Abstract
Mitochondrial genomes are expected to show adaptations for optimizing aerobic respiration in birds that make intense use of flight. However, there is limited empirical evidence of such a relationship. We here examine correlates of several mitochondrial genome characteristics and flight use across a diverse sample of 597 bird species. We developed an index of flight use intensity that ranged from 0 in flightless species to 9 in migratory hummingbirds and examined its association with nucleobase composition, amino acid class composition, and amino acid site allelic variation using phylogenetic comparative methods. We found no evidence of mitochondrial genome adaptations to flight intensity. Neither nucleotide composition nor amino acid properties showed consistent patterns related to flight use. While specific sites in mitochondrial genes exhibited variation associated with flight intensity, there was limited association between specific amino acid residues and flight intensity levels. Our findings suggest a complex genetic architecture for aerobic performance traits, where multiple genes in both mitochondria and the nucleus may contribute to overall performance. Other factors, such as gene expression regulation and anatomical adaptations, may play a more significant role in influencing flight performance than changes in mitochondrial genes. These findings highlight the need for comprehensive genomic analyses to unravel the intricate relationship between genetic variants and aerobic performance in birds.
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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 | 0.001 |
| 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".