Methanogenic Biodegradation of iso-Alkanes by Indigenous Microbes from Two Different Oil Sands Tailings Ponds
Bibliographic record
Abstract
iso-Alkanes, a major fraction of the solvents used in bitumen extraction from oil sand ores, are slow to biodegrade in anaerobic tailings ponds. We investigated methanogenic biodegradation of iso-alkane mixtures comprising either three (2-methylbutane, 2-methylpentane, 3-methylpentane) or five (2-methylbutane, 2-methylpentane, 2-methylhexane, 2-methylheptane, 2-methyloctane) iso-alkanes representing paraffinic and naphtha solvents, respectively. Mature fine tailings (MFT) collected from two tailings ponds, having different residual solvents (paraffinic solvent in Canadian Natural Upgrading Limited (CNUL) and naphtha in Canadian Natural Resources Limited (CNRL)), were amended separately with the two mixtures and incubated in microcosms for ~1600 d. The indigenous microbes in CNUL MFT produced methane from the three-iso-alkane mixture after a lag of ~200 d, completely depleting 2-methylpentane while partially depleting 2-methylbutane and 3-methylpentane. CNRL MFT exhibited a similar degradation pattern for the three iso-alkanes after a lag phase of ~700 d, but required 1200 d before beginning to produce methane from the five-iso-alkane mixture, preferentially depleting components in the order of decreasing carbon chain length. Peptococcaceae members were key iso-alkane-degraders in both CNUL and CNRL MFT but were associated with different archaeal partners. Co-dominance of acetoclastic (Methanosaeta) and hydrogenotrophic (Methanolinea and Methanoregula) methanogens was observed in CNUL MFT during biodegradation of three-iso-alkanes whereas CNRL MFT was enriched in Methanoregula during biodegradation of three-iso-alkanes and in Methanosaeta with five-iso-alkanes. This study highlights the different responses of indigenous methanogenic microbial communities in different oil sands tailings ponds to iso-alkanes.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".