Opposing macroevolutionary and trait‐mediated patterns of threat and naturalisation in flowering plants
Bibliographic record
Abstract
Due to expanding global trade and movement of people, new plant species are establishing in exotic ranges at increasing rates while the number of native species facing extinction from multiple threats grows. Yet, how species losses and gains globally may, together, be linked to traits and macroevolutionary processes is poorly understood. Here, we show that, adjusting for diversification rate and clade age, the proportion of threatened species across flowering plant families is negatively related to the proportion of naturalised species per family. Moreover, naturalisation is positively associated with range size, short generation time, autonomous seed production and interspecific hybridisation, but negatively with age and diversification, whereas threat is negatively associated with range size and hybridisation, and positively with biotic pollination, age and diversification rate. That we find such a pronounced signature of naturalisation and threat across plant families suggests that both trait syndromes have coexisted over deep evolutionary time and counter to intuition, that neither strategy is necessarily superior to the other over long evolutionary timespans.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".