Long-term biodegradation of crude oil in high-arctic backshore sediments: The Baffin Island Oil Spill (BIOS) after nearly four decades
Bibliographic record
Abstract
With an on-going disproportional warming of the Arctic Ocean and the reduction of the sea ice cover, the risk of an accidental oil spill from ships or future oil exploration is increasing. It is hence important to know how crude oil weathers in this environment and what factors affect oil biodegradation in the Arctic. However, this topic is currently poorly studied. In the 1980s, the Baffin Island Oil Spill (BIOS) project carried out a series of simulated oil spills in the backshore zone of beaches located on Baffin Island in the Canadian High Arctic. In this study two BIOS sites were re-visited, offering the unique opportunity to study the long-term weathering of crude oil under Arctic conditions. Here we show that residual oil remains present at these sites even after almost four decades since the original oiling. Oil at both BIOS sites appears to have attenuated very slowly with estimated loss rates of 1.8-2.7% per year. The presence of residual oil continues to significantly affect sediment microbial communities at the sites as manifested by a significantly decreased diversity, differences in the abundance of microorganisms and an enrichment of putative oil-degrading bacteria in oiled sediments. Reconstructed genomes of putative oil degraders suggest that only a subset is specifically adapted for growth under psychrothermic conditions, further reducing the time for biodegradation during the already short Arctic summers. Altogether, this study shows that crude oil spilled in the Arctic can persist and significantly affect the Arctic ecosystem for a long time, in the order of several decades.
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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 | 0.000 | 0.001 |
| 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".