Enhanced biodegradation of petroleum hydrocarbons in the mycorrhizosphere of sub‐boreal forest soils
Bibliographic record
Abstract
Petroleum hydrocarbon (PHC) contamination is becoming more common in boreal forest soils. However, linkages between PHC biodegradation and microbial community dynamics in the mycorrhizosphere of boreal forest soils are poorly understood. Seedlings (lodgepole pine, paper birch, lingonberry) were established in reconstructed soil systems, consisting of an organic layer (mor humus, coarse woody debris, or previously oil-contaminated mor humus) overlying mineral (Ae, Bf) horizons. Light crude oil was applied to the soil surface after 4 months; systems were destructively sampled at 1 and 16 weeks following treatment. Soil concentrations of four PHC fractions were determined using acetone-hexane extraction followed by gas chromatography - flame ionization detection analysis. Genotypic profiles of root-associated bacterial communities were generated using length heterogeneity-PCR of 16S rDNA. Most plant-soil treatments showed significant loss in the smaller fraction PHCs indicating an inherent capacity for biodegradation. Concentrations of total PHCs declined significantly only in planted (pine-woody debris and birch-humus) systems (averaging 59% and 82% loss between 1 and 16 weeks respectively), reinforcing the importance of the mycorrhizosphere for enhancing microbial catabolism. Bacterial community structure was correlated more with mycorrhizosphere type and complexity than with PHC contamination. However, results suggest that communities in PHC-contaminated and pristine soils may become distinct over time.
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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".