Plant Community Diversity and Tree Growth Following Single and Repeated Glyphosate Herbicide Applications to a White Spruce Plantation
Bibliographic record
Abstract
Glyphosate herbicide is widely used to control bluejoint reedgrass (Calamagrostis canadensis (Michx.) Beauv.), trembling aspen (Populus tremuloides Michx.), and other competing species in regenerating white spruce (Picea glauca (Moench) Voss) plantations in Alberta, Canada. In 2004, we initiated a study to examine the effects of the aerial application of glyphosate herbicide on plant community diversity and tree growth near Calling Lake, Alberta. Four treatments were applied: (a) no treatment (control); (b) herbicide application in the first growing season after harvesting; (c) herbicide application in the third growing season after harvesting; and (d) herbicide application in the second and fourth growing seasons after harvesting (two treatments). After 11 growing seasons, species richness was not significantly affected by treatment, while Shannon and Simpson index values were highest in areas treated with herbicide in the first growing season. Herbicide treatment did not have a significant effect on the cover of bluejoint reedgrass after 11 growing seasons, but did significantly reduce trembling aspen and paper birch cover and height. Application of glyphosate in the second and fourth growing seasons resulted in the greatest reductions to aspen cover and height, as well as significant increases in spruce diameter at age 11. Simulations with the Mixedwood Growth Model indicate that all tested herbicide treatments will reduce aspen volume while increasing spruce volume at age 90, with the largest impacts evident where two treatments were applied.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".