Arbuscular mycorrhizal fungal diversity associated with Eleocharis obtusa and Panicum capillare growing in an extreme petroleum hydrocarbon-polluted sedimentation basin
Bibliographic record
Abstract
Arbuscular mycorrhizal fungi (AMF) have been extensively studied in natural and agricultural ecosystems, but little is known about their diversity and community structure in highly petroleum-polluted soils. In this study, we described an unexpected diversity of AMF in a sedimentation basin of a former petrochemical plant, in which petroleum hydrocarbon (PH) wastes were dumped for many decades. We used high-throughput PCR, cloning and sequencing of 18S rDNA to assess the molecular diversity of AMF associated with Eleocharis obtusa and Panicum capillare spontaneously inhabiting extremely PH-contaminated sediments. The analyses of rhizosphere and root samples over two years showed a remarkable AMF richness comparable with that found in temperate natural ecosystems. Twenty-one taxa, encompassing the major families within Glomeromycota, were detected. The most abundant OTUs belong to genera Claroideoglomus, Diversispora, Rhizophagus and Paraglomus. Both plants had very similar overall community structures and OTU abundances; however, AMF community structure differed when comparing the overall OTU distribution across the two years of sampling. This could be likely explained by variations in precipitations between 2011 and 2012. Our study provides the first view of AMF molecular diversity in soils extremely polluted by PH, and demonstrated the ability of AMF to colonize and establish in harsh environments.
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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 | 0.001 | 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".