Contrasting evolutionary trajectories of terrestrial vertebrates in the Hengduan Mountains hotspot
Bibliographic record
Abstract
ABSTRACT The Hengduan Mountains (HDM) harbor the richest temperate diversity in the Northern Hemisphere, yet our understanding of how this exceptionally diverse biota evolved remains obscure. Large-scale historical biogeographic analyses of 851 terrestrial vertebrate species and their relatives (totaling 4862 species) reveal that multiple evolutionary pathways formed this biodiversity hotspot. Whereas in situ speciation dominates in amphibians and non-avian reptiles, near-equal in situ speciation and colonization occurs in mammals, and colonization happens primarily in birds. HDM are a ‘cradle’ for neo-endemics and a ‘sink’ receiving surrounding biotas, mostly (>30%) coming from the Indo-Malay region. Orogenesis and monsoon intensification triggered in situ speciation initiated in the early Oligocene and peaking around 7–8 Ma. Analyses of different taxonomic groups reveal contrasting evolutionary processes and how major geo-climatic events override taxon-specific attributes. Results highlight the need to incorporate taxon-specific traits into future conservation planning to effectively address the unique needs and challenges of different groups.
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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".