Management Impacts on Non-Native Smooth Brome (Bromus inermis Leyss.) Control in a Native Fescue Grassland in Canada
Bibliographic record
Abstract
Native fescue grassland degradation and reductions in plant species diversity due to smooth brome (Bromus inermis Leyss.) invasion and dominance have far ranging consequences for both human and ecological systems. A study was undertaken to reduce smooth brome which was invading foothills fescue grassland in Canada and displacing native species. Sheep and cattle grazing, mowing, glyphosate, and burning were applied to control smooth brome-dominant grasslands over three growing seasons. Defoliation (5 to 10 cm, 2 to 4 times) did not reduce smooth brome tiller density, etiolated regrowth, or total non-structural carbohydrates; however, the three heaviest defoliation treatments (sheep 3×, cattle 3×, mowing 4×) reduced smooth brome composition by year 3. Repeated glyphosate wicking (1× year 1, 2× year 2) was the most effective treatment and reduced smooth brome tiller density by 50% by year 3. Early-spring burning, as smooth brome began to grow, stressed the plants and reduced tiller density. Kentucky bluegrass (Poa pratensis L.), the subdominant species, increased in all treatments except the reference; thus, reducing smooth brome may result in another undesirable species becoming dominant.
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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 | 0.001 | 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".