Revegetation of tailings sand without a soil cover in the Alberta oil sands
Bibliographic record
Abstract
Reclamation in the oil sands in Alberta is a high priority and can be challenging. Suncor Energy is in the process of reclaiming one of its consolidated tailings (CT) ponds (Pond 5). The CT is being capped with a layer of petroleum coke to accelerate the creation of a trafficable surface, and then with tailings sand. As these CT dewater, a temporary reclamation vegetative cover over the tailings sand was needed to stabilise the sand against water and wind erosion prior to final reclamation. Criteria for native plant species selection for the cover crop were based on their ability to grow rapidly, be drought and possibly salt tolerant and provide a vegetation cover for at least three years. This study aims to assess the potential of some native grasses to directly grow and stabilise tailings sand and to determine nutritional requirements for optimal growth. The study was initiated in 2010 (Woosaree et al., 2010). Year 2011 provided an opportunity to study how well these native species continued to adapt and grow on direct tailings sands and if the underlying coke layer from the tailings ponds, presented any limitation to plant growth and survival. Results indicated higher aboveground biomass and percent cover for the native grass seed mix than June grass or fringed brome grass alone. The higher biomass is most likely due to the nature of the species, with June grass being a low stature species compared to the native mix. Fringed brome plants were sparse within the plots, most likely as a result of low emergence in 2010. The greatest benefit of an organic amendment such as alfalfa pellet application appeared to be moisture retention, giving the seeded species a head start to germinate. Root depths measured ranged from 11 to 26 cm allowing the plants to tap deeper into below ground moisture. Plants in the control plots had less vigour, yet were still surviving despite no fertilisers or pellets being applied. A fertiliser rate above 50 kg N/ha did not have a positive effect on the plants. Soil available nitrogen measured in the fall of 2011 was below detectable level. However, plant tissue analysis showed total nitrogen of 1–2.3%. Atmospheric deposition of N and microbial association with the plant roots could contribute to N availability. Microbial analysis revealed six nitrogen fixing bacteria and one plant growth-promoting bacteria to be associated with the native species roots. This study will help to select suitable species for inclusion in seed mixtures for final reclamation.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".