Trait evolution during a rapid global weed invasion despite little genetic differentiation
Bibliographic record
Abstract
Abstract Invasive species often possess a great capacity to adapt to novel environments in the form of spatial trait variation, as a result of varying selection regimes, genetic drift, or plasticity. We explored the geographic differentiation in several phenotypic traits related to plant growth, reproduction, and defense in the highly invasive Centaurea solstitialis by measuring neutral genetic differentiation (FST), and comparing it with phenotypic differentiation (PST), in a common garden experiment in individuals originating from regions representing the species distribution across five continents. Native plants were more fecund than non‐native plants, but the latter displayed considerably larger seed mass. We found indication of divergent selection for these two reproductive traits but little overall genetic differentiation between native and non‐native ranges. The native versus invasive PST–FST comparisons demonstrated that, in several invasive regions, seed mass had increased proportionally more than the genetic differentiation. Traits displayed different associations with climate variables in different regions. Both capitula numbers and seed mass were associated with winter temperature and precipitation and summer aridity in some regions. Overall, our study suggests that rapid evolution has accompanied invasive success of C. solstitialis and provides new insights into traits and their genetic bases that can contribute to fitness advantages in non‐native populations.
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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 | 0.000 |
| 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".