The Effects of Increasing Grazing Height on Establishment of Pasture Weeds in Management-Intensive Rotationally Grazed Pastures
Bibliographic record
Abstract
Weeds can infest management-intensive grazed pastures and impact forage quantity, forage quality, and animal health. Common burdock, plumeless thistle, and Canada thistle are three common pasture weeds in the midwestern United States that are managed to avoid these impacts. Experiments were established at two sites to determine if increasing grazing heights from fall through summer would reduce emergence and survival of burdock, plumeless thistle, and Canada thistle seedlings. Five simulated grazing heights (5, 10, 15, and 20 cm and a not-clipped treatment) were implemented in October 2008 and repeated in May through August. Density of all species was reduced from May to September, with reductions ranging from 65 to 78%, regardless of treatment. Treatments that left at least 15 cm of residual grass had reduced densities of burdock and Canada thistle compared to the 10-cm treatment. Regression analysis demonstrated that reduction in burdock and summed planted weed density was related to increased intercepted photosynthetically active radiation from forage in April. However, total biomass yield was reduced up to 60% when grazing heights were increased from 5 to 20 cm, although differences were only observed at the fall and early spring grazing events. Relative forage quality (RFQ) was similar across treatments, except at the third grazing event for which the 15 and 20-cm treatments had reduced RFQ compared with other treatments. Results suggest that increasing grazing heights can reduce emergence and survival of burdock and Canada thistle but can also result in a reduction in forage quantity in the fall and early spring.
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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) | 0.001 | 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".