THE EVOLUTIONARY HISTORY OF BROWN TROUT (SALMO TRUTTA L.) INFERRED FROM PHYLOGEOGRAPHIC, NESTED CLADE, AND MISMATCH ANALYSES OF MITOCHONDRIAL DNA VARIATION
Bibliographic record
Abstract
Phylogeographic, nested clade, and mismatch analyses of mitochondrial DNA (mtDNA) variation were used to infer the temporal dynamics of distributional and demographic history of brown trout (Salmo trutta). Both new and previously published data were analyzed for 1,794 trout from 174 populations. This combined analysis improved our knowledge of the complex evolutionary history of brown trout throughout its native Eurasian and North African range of distribution in many ways. It confirmed the existence of five major evolutionary lineages that evolved in geographic isolation during the Pleistocene and have remained largely allopatric since then. These should be recognized as the basic evolutionarily significant units within brown trout. Finer phylogeographic structuring was also resolved within major lineages. Contrasting temporal juxtaposition of different evolutionary factors and timing of major demographic expansions were observed among lineages. These unique evolutionary histories have been shaped both by the differential latitudinal impact of glaciations on habitat loss and potential for dispersal, as well as climatic impacts and landscape heterogeneity that translated in a longitudinal pattern of genetic diversity and population structuring at more southern latitudes. This study also provided evidence for the role of biological factors in addition to that of physical isolation in limiting introgressive hybridization among major trout lineages.
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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) | 0.001 | 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".