Effect of weed control methods on growth of five temperate agroforestry tree species in Saskatchewan
Bibliographic record
Abstract
Most tree species in agroforestry plantings are intolerant to vegetative competition and sites must be intensively cultivated to eliminate weeds. Many studies have been conducted to investigate what factors limit seedling growth because of the presence of vegetative competition in forest environments; however on agricultural sites there are few studies on weed management options for tree planting. This research quantified and compared growth of Manitoba maple (Acer negundo), green ash (Fraxinus pennsylvanica), Colorado spruce (Picea pungens), Scots pine (Pinus sylvestris) and Walker poplar (Populus x Walker) in response to combinations of in-row and between-row weed control methods. The study was established on an agroforestry planting on agricultural soils in Saskatchewan. Treatments included in-row weed control using herbicides or plastic mulch and between-row weed control using tillage compared with a non-weeded control. Weed control positively affected annual height increment, basal diameter and height of the agroforestry species. The impacts of weed control versus no weed control were significant in almost all instances. However, tree species responded differently to the method of weed control. Weed control by herbicide and plastic mulch were not significantly different for four of the five species under investigation. This research will help with prescribing weed control methods for agroforestry and afforestation plantings on agricultural soils.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".