Tree spacing effects on erosion of soil covered waste rock slopes
Bibliographic record
Abstract
The management of mine solid waste remains the most important environmental commitment for mine companies. This research project was carried out on the low sulphur waste rock of the Canadian Malartic mine, with the aim of assessing the erosion control effectiveness of different plantation designs on 33% slopes. Since the mine is located in the boreal forest, the purpose of the project is not only to define the design that provides best soil protection, but also to identify which one best promotes the establishment of trees. Fast growing poplar may prove to be effective in erosion control on the waste rock slopes because of its fine root development in dry soil and its effect on soil cohesion. The plantation was established in May 2013 and was monitored over two growing seasons with the aim of determining the effect of five treatments (planted trees at three different spacings without hydroseeding; planted trees with hydroseeding; and a control without trees or hydroseeding) on soil loss. Soil loss measurements were related to root morphology, canopy development and understory cover. In the centre of the plantations, soil loss occurred mainly during the spring snowmelt while soil deposition occurred during summer rainfall. During the first two years after planting, the combination of planted trees with hydroseeding showed the best erosion mitigation compared to the control because of its greater herbaceous cover and greater root length density which maximised soil protection. No difference in soil erosion rates was found between the tree spacing treatments. However, the 1 × 1 m tree spacing significantly increased root density and tree canopy cover in the second year after planting. Potentially this should be reflected in lower soil loss compared with the other treatments in the third year after planting.
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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 | 0.000 | 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) | 0.000 | 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".