Marine microbial communities capable of hydrocarbon biodegradation along shipping routes in the Kivalliq region of the Canadian Arctic
Bibliographic record
Abstract
The extreme cold and icy marine environment in the Canadian Arctic is not well understood regarding its potential for biodegradation of oil spills. Reduced ice cover due to climate change has led to increased human activities, with attendant risks of oil and fuel spills associated with shipping traffic. This threatens the marine ecosystem and well-being of Canadians living in Arctic communities that rely on the ocean for food and cultural livelihood. Naturally occurring hydrocarbon-degrading bacteria within the marine microbiome have the potential to catalyze biodegradation of crude oil compounds, with previous studies showing cold-adapted oil-degrading bacteria inhabiting different marine biomes in the Canadian Arctic. However, the Kivalliq region in Nunavut, Canada, which has been impacted by increased vessel traffic in Hudson Bay in recent decades, has not been investigated in this regard. Determination of the baseline microbiomes in pristine ice, seawater and surface sediment was complemented by mock oil spill microcosms in seawater and sediment to assess biodegradation potential in the Kivalliq marine environment. Incubations of seawater or sediment amended with crude oil were monitored over a 21-week period using 16S rRNA gene amplicon sequencing, metagenomics, cell counting and hydrocarbon geochemistry. Analysis of microbial baselines showed little variability in diversity or taxa in similar marine biomes apart from sites with fresher water. Seawater microcosms demonstrated growth from putative hydrocarbon-degrading organisms corresponding to losses in alkane hydrocarbons. Alkane and polycyclic aromatic hydrocarbon losses and detection of associated genes for hydrocarbon degradation corresponded with appearances of putative hydrocarbonoclastic taxa in sediment microcosms. The Kivalliq marine microbiome’s potential to mitigate pollution effects associated with oil spills suggests that incorporating microbial diversity and microbiome assessments into monitoring environmental change will lead to improved efficacy of spill bioremediation strategies and preparation measures in the Arctic.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 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) | 0.001 | 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".