Methanotrophic bacteria in oilsands tailings ponds of northern Alberta
Bibliographic record
Abstract
We investigated methanotrophic bacteria in slightly alkaline surface water (pH 7.4-8.7) of oilsands tailings ponds in Fort McMurray, Canada. These large lakes (up to 10 km(2)) contain water, silt, clay and residual hydrocarbons that are not recovered in oilsands mining. They are primarily anoxic and produce methane but have an aerobic surface layer. Aerobic methane oxidation was measured in the surface water at rates up to 152 nmol CH4 ml(-1) water d(-1). Microbial diversity was investigated via pyrotag sequencing of amplified 16S rRNA genes, as well as by analysis of methanotroph-specific pmoA genes using both pyrosequencing and microarray analysis. The predominantly detected methanotroph in surface waters at all sampling times was an uncultured species related to the gammaproteobacterial genus Methylocaldum, although a few other methanotrophs were also detected, including Methylomonas spp. Active species were identified via (13)CH4 stable isotope probing (SIP) of DNA, combined with pyrotag sequencing and shotgun metagenomic sequencing of heavy (13)C-DNA. The SIP-PCR results demonstrated that the Methylocaldum and Methylomonas spp. actively consumed methane in fresh tailings pond water. Metagenomic analysis of DNA from the heavy SIP fraction verified the PCR-based results and identified additional pmoA genes not detected via PCR. The metagenome indicated that the overall methylotrophic community possessed known pathways for formaldehyde oxidation, carbon fixation and detoxification of nitrogenous compounds but appeared to possess only particulate methane monooxygenase not soluble methane monooxygenase.
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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 | 0.001 | 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".