Next‐Generation Sequencing Assessment of Eukaryotic Diversity in Oil Sands Tailings Ponds Sediments and Surface Water
Bibliographic record
Abstract
Tailings ponds in the Athabasca oil sands (Canada) contain fluid wastes, generated by the extraction of bitumen from oil sands ores. Although the autochthonous prokaryotic communities have been relatively well characterized, almost nothing is known about microbial eukaryotes living in the anoxic soft sediments of tailings ponds or in the thin oxic layer of water that covers them. We carried out the first next-generation sequencing study of microbial eukaryotic diversity in oil sands tailings ponds. In metagenomes prepared from tailings sediment and surface water, we detected very low numbers of sequences encoding eukaryotic small subunit ribosomal RNA representing seven major taxonomic groups of protists. We also produced and analysed three amplicon-based 18S rRNA libraries prepared from sediment samples. These revealed a more diverse set of taxa, 169 different OTUs encompassing up to eleven higher order groups of eukaryotes, according to detailed classification using homology searching and phylogenetic methods. The 10 most abundant OTUs accounted for > 90% of the total of reads, vs. large numbers of rare OTUs (< 1% abundance). Despite the anoxic and hydrocarbon-enriched nature of the environment, the tailings ponds harbour complex communities of microbial eukaryotes indicating that these organisms should be taken into account when studying the microbiology of the oil sands.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".