Metabolic Rate and Climatic Fluctuations Shape Continental Wide Pattern of Genetic Divergence and Biodiversity in Fishes
Bibliographic record
Abstract
Taxonomically exhaustive and continent wide patterns of genetic divergence within and between species have rarely been described and the underlying evolutionary causes shaping biodiversity distribution remain contentious. Here, we show that geographic patterns of intraspecific and interspecific genetic divergence among nearly all of the North American freshwater fish species (>750 species) support a dual role involving both the late Pliocene-Pleistocene climatic fluctuations and metabolic rate in determining latitudinal gradients of genetic divergence and very likely influencing speciation rates. Results indicate that the recurrent glacial cycles caused global reduction in intraspecific diversity, interspecific genetic divergence, and species richness at higher latitudes. At the opposite, longer geographic isolation, higher metabolic rate increasing substitution rate and possibly the rapid accumulation of genetic incompatibilities, led to an increasing biodiversity towards lower latitudes. This indicates that both intrinsic and extrinsic factors similarly affect micro and macro evolutionary processes shaping global patterns of biodiversity distribution. These results also indicate that factors favouring allopatric speciation are the main drivers underlying the diversification of North American freshwater fishes.
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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 | 0.000 |
| 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".