Vegetation Management Using Polyethylene Mulch Mats and Glyphosate Herbicide in a Coastal British Columbia Hybrid Poplar Plantation: Four-Year Growth Response
Bibliographic record
Abstract
Abstract This study was initiated in 1995 to gather information on the effectiveness of opaque polyethylene mats and glyphosate herbicide treatment on growth and yield of hybrid poplar plantations on south coastal British Columbia. Immediately after planting 40 cm tall hybrid poplar cuttings, 60 × 60 cm opaque polyethylene mats were installed. All treatment plots were mechanically cultivated in one direction twice yearly from 1995 to 1997. This practice left an uncultivated strip between trees running in the same direction as the cultivation. The uncultivated strip was approximately 1 m wide, and represented approximately one-third (0.04 ha) of the total plot area (0.13 ha). Glyphosate was applied at a rate of 2.1 kg active ingredient (ai)/ha in water to the uncultivated strips in the herbicide treatment plots in midsummer of the second and third growing seasons. The opaque polyethylene mats significantly improved poplar height growth only for the first growing season. After four growing seasons, hybrid poplars treated with glyphosate were significantly taller (983 cm) than those in either the mat (915 cm) or control treated plots (902 cm). Diameter at breast height (dbh) was also significantly greater in the herbicide treated plots (88 mm) than in either the mat (78 mm) or control (77 mm) treated plots. Total volume was also significantly greater in herbicide plots (23 ³/ha) than in either the mat (17 m³/ha) or control (17 m³/ha) plots. Basal area and total volume were 14% and 37%, respectively, greater in the herbicide plots than in the mat and control plots following the fourth growing season. West. J. Appl. For. 16(1):26–30.
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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".