Salt tolerance as a factor in determining suitability of northern grasses for revegetation of oil sands sites affected by tailings release water
Bibliographic record
Abstract
We compared the effects of release water from the enhanced non‐segregating oil sands mining tailings (eNST) on the growth and physiological responses of three grass species varying in salt tolerance: a relatively salt‐sensitive Kentucky bluegrass ( Poa pratensis ), a moderately salt‐tolerant Alkali bluegrass ( P. juncifolia ), and a highly salt‐tolerant halophytic Nuttall's alkali grass ( Puccinellia nuttalliana ). Since salt concentrations vary in tailings depending on manufacturing technology and environmental factors, we also examined plant responses to eNST release water that was supplemented with 60 and 120 mM NaCl. The study demonstrated that the responses of P. pratensis , P. juncifolia , and P. nuttalliana to eNST varied according to their salt tolerance level, pointing to salinity as the major factor detrimental to plants. The eNST water severely reduced growth, chlorophyll concentrations, and gas exchange in P. pratensis , and the addition of NaCl aggravated the effects of eNST. The treatment with 50%‐diluted eNST water did not affect the growth of P. juncifolia . However, the 100% eNST and 50% eNST + NaCl treatments exceeded the tolerance threshold of P. juncifolia and decreased the growth and physiological parameters. Poa pratensis and P. juncifolia accumulated high levels of leaf Na in all treatments. Puccinellia nuttalliana showed little or no effects of the applied treatments on the growth and physiological parameters. It also excluded Na from the leaves and maintained low leaf Na/K and Na/Ca ratios. We recommend considering plants with superior salt tolerance levels for the revegetation of sites where roots may come in contact with oil sands tailings release water.
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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 | 0.001 |
| 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".