The Effects of Nutrient and Peat Amendments on Oil Sands Reclamation Wetlands: A Microcosm Study
Bibliographic record
Abstract
Oil sand mining operations in Alberta, Canada produce large quantities of process water and mature fine tailing (MFT) during the bitumen extraction process. Wet landscape reclamation is one of the reclamation strategies proposed to utilize process water and MFT in the creation of aquatic reclamation environments that are economically and environmentally acceptable. \n \nIn the interest of utilizing nutrient enrichment and peat amendment to improve aquatic flora and fauna colonization in new oil sands aquatic reclamation, this microcosm study was designed to assess the phytoplankton and periphyton growth (summer 2008), as well as benthic invertebrate colonization (summer 2009). Peat amendment significantly increased the growth of phytoplankton and periphyton by providing sufficient nutrients (total nitrogen, total phosphorus and dissolved organic carbon) to the system. In reference wetland, benthic invertebrate colonization was significantly increased by utilizing sand as bottom substrate and decreased by MFT/Sand mixture as bottom substrate. In OSPM-affected wetland, benthic invertebrate colonization was not affected by utilizing MFT/Sand as bottom substrate. In comparison to OSPM-affected wetlands, reference wetland had larger number of benthic invertebrate families and higher total abundance. \n \nIn this research, experimental microcosms were constructed in three reclamation wetlands with different types of reclamation materials as the bottom substrates (sand, MFT + sand) and amendments (nutrient and/or peat) added to optimize growing conditions for phytoplankton and periphyton, thus creating a biological detrital layer over unfavourable substrates to enhance benthic invertebrate colonization. The growth estimates of phytoplankton and periphyton on MFT + sand without amendment were low in comparison to the control (water only, no substrate). In comparison to sand, MFT + sand had higher growth estimates at OSPM-affected sites, but lower growth estimates at reference site. The growth estimates of phytoplankton and periphyton on MFT + sand were significantly increased with peat amendment. Nutrient (nitrogen and phosphorus) enrichment insignificantly improved the phytoplankton and periphyton growth. Peat amendments elevated the concentrations of nitrogen, phosphorus and dissolved organic carbon in the system and maintained these high concentrations throughout the experiment period. Nutrient enrichment only temporarily (less than 3 weeks) elevated nitrogen and phosphorus levels as the nutrients added were quickly utilized by the system. \n \nBenthic invertebrate colonization was assessed in the following year. Sand treatments had increased total abundance and numbers of families of benthic invertebrate compared to the mature sediments of the reference wetland. In oil sand process material (OSPM)-affected wetlands, sand treatments had slightly lower abundance and fewer numbers of families in comparison to the mature sediments. In comparison to sand treatments, MFT + sand treatments had decreased total abundance in the reference wetland but not in OSPM-affected wetlands that received MFT input during its construction. Peat amendment and nutrient enrichment had no impact on benthic invertebrate total abundance or composition.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".