Introduction history and population genetics of the invasive grass <i>Bromus tectorum</i> (Poaceae) in Canada
Bibliographic record
Abstract
The invasive annual Bromus tectorum (cheatgrass) is distributed in Canada primarily south of 52° N latitude in two diffuse ranges separated by the extensive coniferous forest in western Ontario. The grass was likely introduced independently to eastern and western Canada post-1880. We detected regional variation in the grass's genetic diversity using starch gel electrophoresis to analyze genetic diversity at 25 allozyme loci in 60 populations collected across Canada. The Pgm-1a & Pgm-2a multilocus genotype, which occurs in the grass's native range in Eastern Europe, is prevalent in eastern Canada but occurs at low frequency in western Canada. In contrast, the Got-4c multilocus genotype, found in the native range in Central Europe, is widespread in populations from western Canada. Overall genetic diversity of B. tectorum is much higher in eastern Canada than in the eastern U.S., while the genetic diversity in populations in western North America is similar between Canada and the U.S. The distribution of genetic diversity across Canada strongly suggests multiple introduction events. Heterozygous individuals, which are exceedingly rare in B. tectorum, were detected in three Canadian populations. Formation of novel genotypes through occasional outcrossing events could spark adaptive evolution and further range expansion across Canada of this exceedingly damaging grass.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".