Travel tales of a worldwide weed: genomic signatures reveal colonial trade routes and prior adaptation are key to the success of Plantago major
Bibliographic record
Abstract
Retracing pathways of historical species introductions is fundamental to understanding the factors involved in the successful colonization and spread, centuries after a species’ establishment in an introduced range. Numerous plants are thought to have been introduced to regions outside their native ranges by European voyagers and early colonists making transoceanic journeys; however, records are scare to document this. We use genotyping-by-sequencing and genotype-likelihood methods on the selfing, global weed, Plantago major, collected from 50 populations worldwide to test hypotheses that the plant was brought to new regions during colonial times. We further investigate how patterns in genomic diversity facilitate the success of this global weed. Although genomic differentiation among populations is found to be low, we identify six unique ecotypes showing very little sign of admixture. Three of the most prevalent of these ecotypes present in the native range gave rise to introduced populations in the Americas, Africa, Australia and New Zealand, indicating that more than one successful ecotype colonized and spread. The distribution of ecotypes is found to have links to colonial history, and ecotypes are further found to be restricted by latitude. Dispersal of multiple successful ecotypes and prior adaptation in the native range to latitudinally dependent environmental factors (such as climate) are likely reasons for the success of this prolific, global weed. Genomic signatures can provide new perspectives on the drivers behind the historic introductions and the successful colonization of introduced species in an era of global change.
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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 | 0.000 | 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".