Local adaptation to climate facilitates a global invasion
Bibliographic record
Abstract
), native to Eurasia and Africa, has invaded globally, with severe impacts in western North America. We aimed to identify mechanisms and consequences of local adaptation in the North American cheatgrass invasion. We sequenced 307 range-wide genotypes and conducted controlled experiments. We found that diverse lineages invaded North America, where long-distance gene flow is common. Nearly half of North American cheatgrass comprises a mosaic of ~19 locally adapted, near-clonal genotypes, each seemingly very successful in a different part of North America. Additionally, ancestry, phenotype, and allele frequency-environment clines in the native range predicted those in the invaded range, indicating pre-adapted genotypes colonized different regions. Common gardens showed directional selection on flowering time that reversed between warm and cold sites, potentially maintaining clines. In the USA Great Basin, genomic predictions of strong local adaptation identified sites where cheatgrass is most dominant. Our results indicate that multiple introductions and migration within the invaded range fueled local adaptation and success of cheatgrass in western North America. Understanding how environment and gene flow shape adaptation and invasion is critical for managing ongoing invasions.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".