Effects of marine diesel on microbial diversity and activity in high Arctic beach sediments
Bibliographic record
Abstract
Global warming induced sea ice loss increases Arctic maritime traffic, enhancing the risk of ecosystem contamination from fuel spills and nutrient loading. The impact of marine diesel on bacterial metabolic activity and diversity, assessed by colorimetric assay, 16S rRNA and metagenomic sequencing, of Northwest Passage (Arctic Ocean) beach sediments was assessed with nutrient amendment at environmentally relevant temperatures (5 and 15 °C). Higher temperature and nutrients stimulated microbial activity, while diesel reduced it, with metabolism inhibited at and above 0.01 % (without nutrients) and at 1 % (with nutrients) diesel inclusions. Diesel exposure significantly decreased microbial diversity and selected for Psychrobacter genus. Microbial hydrocarbon degradation, organic compound metabolism, and exopolysaccharide production gene abundances increased under higher diesel concentrations. Metagenomic binning recovered nine MAGs/bins with hydrocarbon degradation genes. We demonstrate a nutrients' rescue-type effect in diesel contaminated microbial communities via enrichment of microorganisms with stress response, aromatic compound, and ammonia assimilation metabolisms.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".