Hydrocarbon-degrading potential of microbial communities from Arctic plants
Bibliographic record
Abstract
AIMS: To explore rhizospheric microbial communities from Arctic native plant species evaluating their bacterial hydrocarbon-degrading capacities. METHODS AND RESULTS: Eriophorum scheuchzeri, Potentilla cf. rubricaulis, Oxyria digyna, Salix arctica and Puccinellia angustata plant species were collected at Eureka (Canadian high Arctic) along with their rhizospheric soil samples. Their bacterial community fingerprints (16S rRNA gene, DGGE) were distinctive encompassing members from the phyla: Bacteroidetes, Firmicutes, Actinobacteria and Proteobacteria. Isolated diesel-degrading bacteria belonged to the phyla Actinobacteria and Proteobacteria. Strains of Mycobacterium, Nocardia, Rhodococcus, Intrasporangiaceae, Leifsoni and Arthrobacter possessed alkB and Pseudomonas possessed both ndoB and xylE gene sequences. Two Rhodococcus strains mineralized [1-(14) C] hexadecane at 5 and -5°C. From the rhizosphere of P. angustata, larger numbers of hydrocarbon-degrading bacteria were isolated than from other plant rhizosphere samples and all three genes alkB (from Actinobacteria), ndoB and xylE (from Pseudomonas) were detected by PCR. CONCLUSIONS: (i) Arctic plants have unique rhizospheric bacterial communities. (ii) P. angustata has potential for phytoremediation research at high Arctic soils. (iii) Isolated bacteria mineralized hydrocarbons at ambient low temperatures. SIGNIFICANCE AND IMPACT OF THE STUDY: To the best of our knowledge, this is the first rhizospheric exploration examining the phytoremediation potential of five Arctic plants and evaluating their microbial hydrocarbon-degrading capacities.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".