Genetic variation and clonal diversity in floating aquatic plants: Comparative genomic analysis of water hyacinth species in their native range
Bibliographic record
Abstract
Many eukaryotic organisms reproduce by sexual and asexual reproduction. Genetic diversity in populations can be strongly dependent on the relative importance of these two reproductive modes. Here, we compare the amounts and patterns of genetic diversity in related water hyacinths that differ in their propensity for clonal propagation - highly clonal Eichhornia crassipes and moderately clonal E. azurea (Pontederiaceae). Our comparisons involved genotype-by-sequencing (GBS) of 137 E. crassipes ramets from 60 locations (193,495 nucleotide sites) and 118 E. azurea ramets from 53 locations (198,343 nucleotide sites) among six hydrological basins in central South America, the native range of both species. We predicted that because of more prolific clonal propagation, E. crassipes would exhibit lower clonal diversity than E. azurea. This prediction was supported by all measures of clonal diversity that we examined. Eichhornia crassipes also had a larger excess of heterozygotes at variant sites, another signature of clonality. However, genome-wide heterozygosity was not significantly different between the species. Eichhornia crassipes had weaker spatial genetic structure and lower levels of differentiation among hydrological basins than E. azurea, probably because of higher clonality and more extensive dispersal of its free-floating life form. Our findings for E. crassipes contrast with earlier studies from the invasive range which have reported very low levels of clonal diversity and extensive geographic areas of genetic uniformity.
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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 | 0.001 |
| 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".