Long-term forage dynamics in pastures sprayed with residual broadleaf herbicide: A test of legume recovery
Bibliographic record
Abstract
Miller, A. J., Bork, E. W., Hall, L. M. and Summers, B. 2015. Long-term forage dynamics in pastures sprayed with residual broadleaf herbicide: A test of legume recovery. Can. J. Plant Sci. 95: 43–53. Legumes such as alfalfa (Medicago sativa L.) and white clover (Trifolium repens L.) are important components of northern temperate pastures where they increase forage productivity and quality, but are susceptible to decline when exposed to broadleaf herbicides. Little is known about the long-term sward responses following herbicide use in northern temperate pastures, including the recovery of legumes and their subsequent contribution to forage production. We established five field sites over 2 yr to assess changes in grass, legume, total forage (grass+legume) and other forb biomass, as well as the recovery of a common weed, dandelion (Taraxacum officinale Weber), for up to 3 yr following a single application of two broad leaf herbicides with residual properties (aminopyralid and aminocyclopyrachlor). The importance of defoliation and the legume seed bank in facilitating legume biomass recovery were also evaluated with mowing and legume overseeding, respectively, in a strip/split-split design. Both herbicides had similar functional impacts on sward composition based on peak annual biomass, reducing legume biomass by an average of 71–100% across the 3 yr, equivalent to 63.4–22.6 g m−2 from year 1 to year 3, respectively. Although grass biomass did not change significantly with herbicides, net reductions in total forage were limited to 6.8% (28 g m−2) over the study, suggesting at least some ability of grasses to compensate for legume removal. Legume biomass was greater following overseeding and only in non-sprayed controls, but then decreased over time. Conversely, biomass of other forbs and cover of dandelion were lower shortly following herbicide application, only to reach levels similar to non-sprayed controls by the second growing season. Defoliation also influenced sward composition, favoring dandelion recovery following herbicide application. As both weed control and legume re-establishment are important objectives for livestock producers, the result of this study provides useful insight into the long-term impact of broad-leaf weed control on forage production in mixed swards of northern temperate pastures.
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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 | 0.001 |
| 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".