Anthropogenic and natural disturbances increase local genetic diversity in an early spring geophyte (Ficaria verna Huds.)
Bibliographic record
Abstract
Tetraploid Ficaria verna is a common spring geophyte that forms large populations in central Europe and is considered invasive in northern USA and Canada. It is considered an almost seed-sterile taxon, relying on vegetative reproduction by underground tubers and aerial bulbils. Recent studies have revealed high levels of population genetic diversity in F. verna, raising the question of how genetic diversity is maintained and which factors may be responsible for the observed patterns. Polymorphic nuclear microsatellite markers were established to define multi-locus genotypes (MLGs), to analyze fine-scale spatial genetic structure (SGS) using grid and cross sampling schemes, and to quantify genetic diversity within and between nine populations with different disturbance regimes in central Germany. 115 MLGs were identified among a total of 347 samples. The G/N ratio varied between 0.16 and 0.70 among populations, and in each population a number of unique MLGs occurred. Genotypes were highly intermingled within populations, suggesting a ‘guerrilla’ dispersal strategy. Significant negative SGS was found in five out of nine populations in fine-scale cross sampling (up to 4 m) and in only one population in grid sampling (up to 14.6 m). No single MLG was found in more than one population, while many alleles were shared between populations. Within-population genetic diversity increased with greater exposure to both anthropogenic and natural disturbances. Regular gap openings, facilitated propagule establishment (vegetative and sexual), and propagule dispersal by water and mowing machines are likely important factors explaining the positive effects of disturbance on local genetic diversity of F. verna.
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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) | 0.000 | 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 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".