Alteration of microbial community structure affects diesel biodegradation in an Arctic soil
Bibliographic record
Abstract
A wide range of microbial taxa are active in hydrocarbon-contaminated Arctic soils, and many are capable of hydrocarbon metabolism. The most effective hydrocarbon degraders may not naturally dominate following contamination events, so shifts in microbial abundance could potentially increase hydrocarbon biodegradation. In this study, we contaminated an Arctic soil with diesel and used gentamicin and vancomycin to inhibit distinct portions of the microbial community. We measured diesel loss using gas chromatography, bacterial and fungal abundance with qPCR, and assessed bacterial diversity and community composition through Ion Torrent sequencing of 16S rRNA gene amplicons. The combined addition of both antibiotics increased diesel biodegradation significantly relative to the no-antibiotic treatment, despite reduced bacterial and fungal abundance; however, this effect was not observed when nutrients were also added. All treatments produced unique bacterial communities, and both Xanthomonadaceae and Micrococcineae were dominant in the dual antibiotic treatment. The bacterial communities resulting from dual gentamicin and vancomycin addition were similar both with and without nutrients, although nutrient addition produced a much larger fungal population, which may partly explain the differences in biodegradation between these two treatments. These results suggest that the most efficient hydrocarbon-degrading community may not always be promoted naturally in contaminated soils.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".