Emergence of the Introduced Grass <i>Agropyron cristatum</i> and the Native Grass <i>Bouteloua gracilis</i> in a Mixed‐grass Prairie Restoration
Bibliographic record
Abstract
Abstract Prairie restoration at the northern edge of the Great Plains can be frustrated by previously established non‐native perennial grasses. We compared the emergence of a widely introduced grass, Agropyron cristatum , and a common native grass, Bouteloua gracilis , in a 4‐year‐old field experiment in which the Agropyron ‐dominated vegetation had either been left intact or treated annually with herbicide. This was done at two levels of water supply, reflecting conditions expected in wet and dry years, to examine the effects of among‐year variability in precipitation. Water addition significantly increased the emergence of both surface‐sown and buried (1 cm deep) seeds. Herbicide treatment of neighbors did not increase the emergence of experimentally added seeds. Emergence was much greater for buried (80%) than surface‐sown seeds (20%). Significantly more Bouteloua than Agropyron germinated from experimentally buried seeds. Whereas only a single seedling of Bouteloua emerged from the existing seed bank, the mean density of Agropyron seedlings emerging from the seed bank was 930/m 2 (range, 0 to 6,455/m 2 ). Surprisingly, the emergence of Agropyron from the seed bank was not decreased by 4 years of herbicide treatment, possibly because herbicide may release Agropyron from intraspecific competition and allow increased seed production to compensate for decreased plant abundance. In summary, we found few differences between Agropyron and Bouteloua in spring and summer emergence at high or low water availability. The persistence of Agropyron stands despite repeated herbicide application may be partly due to increased seed production.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".