Population genomic and historical analysis reveals a global invasion by bridgehead processes in <i>Mimulus guttatus</i>
Bibliographic record
Abstract
Abstract Humans are transforming species ranges worldwide. While artificial translocations trigger biological invasions with negative effects on biodiversity, invasions provide exceptional opportunities to generate ecological and evolutionary hypotheses. Unfortunately, imperfect historical records and exceedingly complex demographic histories present challenges for the reconstruction of invasion histories. Here we combine historical records, extensive worldwide and genome-wide sampling, and demographic analyses to investigate the global invasion of yellow monkeyflowers ( Mimulus guttatus ) from North America to Europe and the Southwest Pacific. By sampling 521 plants from 158 native and introduced populations genotyped at >44,000 loci, we determined that invasive North American M. guttatus was first likely introduced to the British Isles from the Aleutian Islands (Alaska), followed by rapid admixture from multiple parts of the native range. Populations in the British Isles then appear to have served as a bridgehead for vanguard invasions worldwide into the rest of Europe, New Zealand and eastern North America. Our results emphasise the highly admixed nature of introduced M. guttatus and demonstrate the potential of introduced populations to serve as sources of secondary admixture, producing novel hybrids. Unravelling the history of biological invasions provides a starting point to understand how invasive populations adapt to novel environments.
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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".