Effects of evolutionary history and life form on extinction risk of Chinese flowering plants
Bibliographic record
Abstract
There has been much debate on what, including evolutionary history, ecological processes or environmental change, might contribute to species extinctions. In this study, we explored how evolutionary attributes and life forms were correlated with extinction risk of Chinese flowering plants. We defined genus-level extinction risk as the ratio of threatened species over all species in each plant genus. We compiled data on extinction risk for 2731 genera representing 27332 angiosperm species from the IUCN Red List threatened species assessments. We quantified the strength of phylogenetic signal in extinction risk and used phylogenetic generalized linear mixed models to test the effects of evolutionary age, genus size, and evolutionary distinctiveness on extinction risk. We found woody plants suffered greater extinction risk than herbs. There were significant phylogenetic signals in extinction risk, but the signal was stronger in herbaceous plants than in woody plants. Genus size and genus stem age were both negatively associated with extinction risk. In constrast, we found positive correlations between evolutionary distinctiveness and extinction risk. We further indentified many genera (e.g., Cynomorium, Mytilaria, Kingdonia, Scheuchzeria, Brasenia, and Manglietia) had both high evolutionary distinctiveness and high extinction risk. Our study shows that the extinction risk of Chinese flowering plant is not randomly distributed across genera but has strong evolutionary predisposition. We suggest information on life forms, genus size, genus stem age, and evolutionary distinctiveness be considered when making priority for the protection of Chinese flowering plants.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| 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".