Genetic uniformity characterizes the invasive spread of water hyacinth (<i>Eichhornia crassipes</i>), a clonal aquatic plant
Bibliographic record
Abstract
Aquatic plant invasions are often associated with long-distance dispersal of vegetative propagules and prolific clonal reproduction. These reproductive features combined with genetic bottlenecks have the potential to severely limit genetic diversity in invasive populations. To investigate this question we conducted a global scale population genetic survey using amplified fragment length polymorphism markers of the world's most successful aquatic plant invader -Eichhornia crassipes (water hyacinth). We sampled 1140 ramets from 54 populations from the native (South America) and introduced range (Asia, Africa, Europe, North America, Central America and the Caribbean). Although we detected 49 clones, introduced populations exhibited very low genetic diversity and little differentiation compared with those from the native range, and approximately 80% of introduced populations were composed of a single clone. A widespread clone ('W') detected in two Peruvian populations accounted for 70.9% of the individuals sampled and dominated in 74.5% of the introduced populations. However, samples from Bangladesh and Indonesia were composed of different genotypes, implicating multiple introductions to the introduced range. Nine of 47 introduced populations contained clonal diversity suggesting that sexual recruitment occurs in some invasive sites where environmental conditions favour seedling establishment. The global patterns of genetic diversity in E. crassipes likely result from severe genetic bottlenecks during colonization and prolific clonal propagation. The prevalence of the 'W' genotype throughout the invasive range may be explained by stochastic sampling, or possibly because of pre-adaptation of the 'W' genotype to tolerate low temperatures.
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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 | 0.001 |
| 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".