Effects of diurnal temperature variation on microbial community and petroleum hydrocarbon biodegradation in contaminated soils from a sub‐ <scp>A</scp> rctic site
Bibliographic record
Abstract
Contaminated soils are subject to diurnal and seasonal temperature variations during on-site ex-situ bioremediation processes. We assessed how diurnal temperature variations similar to that in summer at the site from which petroleum hydrocarbon-contaminated soil was collected affect the soil microbial community and the extent of biodegradation of petroleum hydrocarbons compared with constant temperature regimes. Microbial community analyses for 16S rRNA and alkB genes by pyrosequencing indicated that the microbial community for soils incubated under diurnal temperature variation from 5°C to 15°C (VART5-15) evolved similarly to that for soils incubated at constant temperature of 15°C (CST15). In contrast, under a constant temperature of 5°C (CST5), the community evolved significantly different. The extent of biodegradation of C10-C16 hydrocarbons in the VART5-15 systems was 48%, comparable with the 41% biodegradation in CST15 systems, but significantly higher than CST5 systems at 11%. The enrichment of Gammaproteobacteria was observed in the alkB gene-harbouring communities in VART5-15 and CST15 but not in CST5 systems. However, the Actinobacteria was abundant at all temperature regimes. The results suggest that changes in microbial community composition as a result of diurnal temperature variations can significantly influence petroleum hydrocarbon bioremediation performance in cold regions.
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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".