What makes the Sino‐Himalayan mountains the major diversity hotspots for pheasants?
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Aim The Sino‐Himalayas have higher species richness than adjacent regions, making them a global biodiversity hotspot. Various mechanisms, including ecological constraints, energetic constraints, diversification rate (DivRate) variation, time‐for‐speciation effect and multiple colonizations, have been posited to explain this pattern. We used pheasants (Aves: Phasianidae) as a model group to test these hypotheses and to understand the ecological and evolutionary processes that have generated the extraordinary diversity in these mountains. Location Sino‐Himalayas and adjacent regions. Taxon Pheasants. Methods Using distribution maps predicted by species distribution models ( SDM s) and a time‐calibrated phylogeny for pheasants, we examined the relationships between species richness and predictors including net primary productivity ( NPP ), niche diversity (NicheDiv), DivRate, evolutionary time (EvolTime) and colonization frequency using Pearson's correlations and structural equation modelling ( SEM ). We reconstructed ancestral ranges at nodes and examined basal/derived species patterns to reveal the mechanisms underlying species richness gradients in the Sino‐Himalayas. Results We found that ancestral pheasants originated in Africa in the early Oligocene (~33 Ma), and then colonized the Sino‐Himalayan mountains and other regions. In the Sino‐Himalayas, species richness was strongly related to DivRate, NPP , NicheDiv and colonization frequency, but weakly correlated with EvolTime. The direct effects of NicheDiv and DivRate on richness were stronger than NPP and EvolTime. NPP indirectly influenced species richness via DivRate, but its effect on richness via NicheDiv was relatively weak. Main conclusions Higher species diversity in the Sino‐Himalayas was generated by both ecological and evolutionary mechanisms. An increase in available niches, rapid diversifications and multiple colonizations was found to be key direct processes for the build‐up of the diversity hotspots of pheasants in the Sino‐Himalayan mountains. Productivity had an important but indirect effect on species richness, which worked through increased DivRate. Our study offers new insights on species accumulation in the Sino‐Himalayas and provides a useful model for understanding other biodiversity hotspots.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it