Convergent evolution of body color between sympatric freshwater fishes via different visual sensory evolution
Bibliographic record
Abstract
Abstract Although there are many examples of color evolution potentially driven by sensory drive, only few studies have examined whether distinct species inhabiting the same environments evolve similar body colors via shared sensory mechanisms. In this study, we tested whether two sympatric freshwater fish taxa, halfbeaks of the genus Nomorhamphus and ricefishes of the genus Oryzias in Sulawesi Island, converge in both body color and visual sensitivity. After reconstructing the phylogeny separately for Nomorhamphus and Oryzias using transcriptome‐wide sequences, we demonstrated positive correlations of body redness between these two taxa across environments, even after phylogenetic corrections, which support convergent evolution. However, substantial differences were observed in the expression profiles of opsin genes in the eyes between Nomorhamphus and Oryzias . Particularly, the expression levels of the long wavelength‐sensitive genes were negatively correlated between the taxa, indicating that they have different visual sensitivities despite living in similar light environments. Thus, the convergence of body colorations between these two freshwater fish taxa was not accompanied by convergence in opsin sensitivities. This system presents a case in which body color convergence can occur between sympatric species via different mechanisms.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 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".