Semiarid bunchgrasses accumulate molybdenum on alkaline copper mine tailings: assessing phytostabilization in the greenhouse
Bibliographic record
Abstract
Abstract Phytostabilization is the use of plants and soil amendments to physically stabilize and remediate contaminated mine wastes and to control wind and water erosion in semiarid environments. The aim of this study was to evaluate two native bunchgrass species’ ( Pseudoroegneria spicata and Festuca campestris ) biomass accumulation and metals uptake response to locally available soil amendments (compost, wood ash and wood chips) to determine their suitability for phytostabilization at an alkaline copper mine tailings site in British Columbia, Canada. In the greenhouse, bunchgrasses important as forage for livestock and wildlife were grown in tailings with various ash–compost–wood chip combinations and evaluated using a randomized complete block design with 13 treatments and 10 replicates. Plants were harvested after 90 d, and tissues were analyzed for root and shoot biomass. Tissue samples ( n = 3) from three treatment subsets (ash, compost, blend) were selected for elemental analysis. Biomass increased with increasing compost applications, and the response was greatest for P. spicata . Shoot molybdenum exceeded the maximum tolerable level for cattle and was significantly higher when grasses were grown on the ash treatment (183–202 mg kg −1 ) compared to the others (19.7–58.3 mg kg −1 ). Translocation and root bioconcentration factors were highest on the ash treatment (2.53–12.5 and 1.75–7.96, respectively) compared to the other treatments (0.41–3.43 and 1.47–4.79, respectively) and indicate that both species are ‘accumulators.’ The findings suggest that these bunchgrasses were not ideal candidates for phytostabilization due to high shoot tissue molybdenum accumulation, but provide important considerations for mine restoration in semiarid grassland systems.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".