Toluene biodegradation in the vadose zone of a poplar phytoremediation system identified using metagenomics and toluene-specific stable carbon isotope analysis
Bibliographic record
Abstract
Biodegradation is an important mechanism of action of phytoremediation systems, but performance evaluation is challenging. We applied metagenomic molecular approaches and compound-specific stable carbon isotope analysis to assess biodegradation of toluene in the vadose zone at an urban pilot field system where hybrid poplars were planted to remediate legacy impacts to an underlying shallow fractured bedrock aquifer. Carbon isotope ratios were compared spatio-temporally between toluene dissolved in groundwater and in the vapor phase. Enrichment of 13C from toluene in the vapor phase compared to groundwater provided evidence for biodegradation in the vadose zone. Total bacterial abundance (16S rRNA) and abundance and expression of degradation genes were determined in rhizosphere soil (DNA and RNA) and roots (DNA) using quantitative PCR. Relative abundances of degraders in the rhizosphere were on average higher at greater depths, except for enrichment of PHE-encoding communities that more strongly followed patterns of toluene concentrations detected. Quantification of RMO and PHE gene transcripts supported observations of active aerobic toluene degradation. Finally, spatially-variable numbers of toluene degraders were detected in poplar roots. We present multiple lines of evidence for biodegradation in the vadose zone at this site, contributing to our understanding of mechanisms of action of the phytoremediation system.
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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".