Genomic basis of the loss of diadromy in<i>Galaxias maculatus</i>: Insights from reciprocal transplant experiments
Bibliographic record
Abstract
Diadromy is known for having major effects on the distribution and richness of aquatic species, and so does its loss. The loss of diadromy has led to the diversification of many species, yet research focusing on understanding its molecular basis and consequences are limited. This is particularly true for amphidromous species despite being the most abundant group of diadromous species. Galaxias maculatus, an amphidromous species and one of the most widely distributed fishes in the Southern Hemisphere, exhibits many instances of nonmigratory or resident populations. The existence of naturally replicated resident populations in Patagonia can serve as an ideal system for the study of the mechanisms that lead to the loss of the diadromy and its ecological and evolutionary consequences. Here, we studied two adjacent river systems in which resident populations are genetically differentiated yet derived from the same diadromous population. By combining a reciprocal transplant experiment with genomic data, we showed that the two resident populations followed different evolutionary pathways by exhibiting a differential response in their capacity to survive in salt water. While one resident population was able to survive salt water, the other was not. Genomic analyses provided insights into the genes that distinguished (a) migratory from nonmigratory populations; (b) populations that can vs those that cannot survive a saltwater environment; and (c) between these resident populations. This study demonstrates that the loss of diadromy can be achieved by different pathways and that environmental (selection) and random (genetic drift) forces shape this dynamic evolutionary process.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".