Cryptic phylogeographic history sheds light on the generation of species diversity in sky-island mountains
Bibliographic record
Abstract
ABSTRACT Biodiversity hotspots should be given high priority for conservation under the situation of global climate change. The sky islands in southwestern China are characterized by extraordinarily high species diversity and are among one of the world’s top biodiversity hotspots. However, neither the actual species diversity in this region or mechanisms generating this diversity are well explored. Here, we report on the phylogeographic analysis of the long-tailed mole ( Scaptonyx fusicaudus ), a semi-fossorial mammal that inhabits the montane cool forests across the Chinese sky islands and is considered to represent one species divided into two subspecies. Analyses using DNA sequence data from one mitochondrial and six nuclear genes revealed that populations inhabiting different mountains exhibited exceptionally strong geographic structure. The lowlands and large rivers act as “soft” and “hard” barriers to dispersal, respectively, isolating evolutionary lineages for up to 11 million years. Our results suggest that the mountain ranges act as interglacial refugia buffering populations from climate fluctuations, further facilitating allopatric diversification. Strikingly, species delimitation analyses suggests that the long-tailed mole may comprise 18 operational taxonomic units and 17 putative species. Our results suggest that for low-vagility species, the complex topography of the Chinese sky islands has shaped genetic diversity and structure and promoted exceptional diversification through a combination of eco-environmental stability as well as geographic fragmentation. The patterns observed in S. fusicaudus may be representative for other cold- adapted species, reflecting the generation of mammalian faunal diversity in the sky-island mountains of southwestern China.
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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 | 0.001 | 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".