Transpiration measurements on vegetated soil layers over waste rock and tailings
Bibliographic record
Abstract
Numerous large-scale hard rock mines operate in Canada and will need to be reclaimed. The water balance of the reclaimed sites needs to be measured regularly to assess the reclamation performance and prevent environmental contamination from mining wastes. Transpiration is an important component of the water balance. However, it is rarely directly measured and is typically deduced from the measurement of other water balance components. This study used non-destructive sap flow sensors to evaluate transpiration rates of willow cuttings (Salix miyabeana clone sx64) planted in 2017 on experimental cells (ECs) composed of tailings and waste rock covered with overburden and topsoil layers. Data were collected in late summer 2020 and 2021. Consistently low transpiration rates of 0.76 mm and 0.8 mm per day were measured for waste rock ECs in 2020 and 2021, and 0.63 mm per day for tailings ECs in 2021. Transpiration accounted for almost one-third of the cumulative precipitation on the tailings and waste rock ECs (varying from 16% to 32%). Such high values demonstrate the importance of measuring the transpiration component of the water balance and its evolution in relation to vegetation development in the mining reclamation context to improve post-closure water management.
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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) | 0.000 | 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 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".