Convergence in form and function overcomes non-parallel evolutionary histories in a Holarctic fish
Bibliographic record
Abstract
Abstract Understanding the extent to which evolution is predictable under multifarious selection is a longstanding question in evolutionary biology. However, the interplay of stochastic and contingent factors influencing the extent of parallelism in nature is not well understood. To test the predictability of evolution, we studied a ‘natural experiment’ on different organismal levels across lakes and evolutionary lineages of a freshwater salmonid fish, Arctic charr (Salvelinus alpinus). We identified significant phenotypic parallelism between Arctic charr ecotype pairs within a continuum of parallel evolution and highly parallel adaptive morphological traits. Variability in phenotypic predictability was explained by complex demographic histories, differing genomic backgrounds and genomic responses to selection, variable genetic associations with ecotype, and environmental variation. Remarkably, gene expression was highly similar across ecotype replicates, and explained the observed parallelism continuum. Our findings suggest that parallel evolution by non-parallel evolutionary routes is possible when the regulatory molecular phenotype compensates for divergent histories.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".