Whole‐genome resequencing reveals complex effects of geographical–palaeoclimatic interactions on diversification of moustache toads in East Asia
Bibliographic record
Abstract
Geographical features and palaeoclimatic fluctuations are two classical evolutionary forces that shape genetic diversification within species. Fine-grained analysis of the mechanisms involved through population demographic processes, however, remains limited. Taking advantage of two recently published reference genomes, we resequenced the genomes and examined the evolutionary history of the moustache toads, a group endemic to East Asia where complex topography and fluctuating palaeoclimate are known to have had profound impacts on organisms. Moustache toads probably originated in southeast Yunnan, China, and diversified towards the northwestern of Yunnan, as well as central and eastern China. Further exploration based on three widespread species (Leptobrachium ailaonicum, L. boringii and L. liui) using demographic modelling and species distribution models revealed that mountains and river valleys in East Asia not only functioned as geographical barriers, but also provided dispersal corridors and facilitated continuous migration or post-glacial secondary contact among moustache toad populations. Furthermore, periodic oscillation of effective population sizes accompanying fluctuations of historical temperature and population contraction at the Last Glacial Maximum support the widespread impact of climatic changes of the Pleistocene on species diversification in East Asia. This impact was moderate for populations of L. ailaonicum and L. boringii in the southwestern mountains but severe for populations of L. liui in the eastern lowland regions of continental East Asia, which is supported by different degrees of change of their effective population sizes. Our findings reveal mechanisms underlying genetic diversification among moustache toads, and highlight the power of genomic data and demographic modelling for examining complex historical population-level processes and for understanding how geographical and palaeoclimatic factors interactively shape current intraspecific diversity.
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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 | 0.001 |
| 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".