Environmental niche and flight intensity are associated with molecular evolutionary rates in a large avian radiation
Bibliographic record
Abstract
BACKGROUND: Metabolic activity and environmental energy are two of the most studied putative drivers of molecular evolutionary rates. Their extensive study, however, has resulted in mixed results and has rarely included the exploration of interactions among various factors impacting molecular evolutionary rates across large clades. Taking the diverse avian family Furnariidae as a case study, we examined the association between several estimates of molecular evolutionary rates with proxies of metabolic demands imposed by flight (wing loading and wing shape) and proxies of environmental energy across the geographic ranges of species (temperature and UV radiation). RESULTS: We found weak evidence of a positive effect of environmental and morphological variables on mitochondrial substitution rates. Additionally, we found that temperature and UV radiation interact to explain molecular rates at nucleotide sites affected by selection and population size (non-synonymous substitutions), contrary to the expectation of their impact on sites associated with mutation rates (synonymous substitutions). We also found a negative interaction between wing shape (as described by the hand-wing index) and body mass explaining mitochondrial molecular rates, suggesting molecular signatures of positive selection or reduced population sizes in small-bodied species with greater flight activity. CONCLUSIONS: Our results suggest that the demands of flight and environmental energy pose multiple evolutionary pressures on the genome either by driving mutation rates or via their association with natural selection or population size. Data from whole genomes and detailed physiology across taxa will bring a more complete picture of the impact of metabolism, population size, and the environment on avian genome evolution.
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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 | 0.001 | 0.002 |
| 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".