Rhizosphere effect is stronger than PAH concentration on shaping spatial bacterial assemblages along centimetre-scale depth gradients
Bibliographic record
Abstract
At centimetre scale, soil bacterial assemblages are shaped by both abiotic (edaphic characteristics and pollutants) and biotic parameters. In a rhizobox experiment carried out on planted industrial soil contaminated with polycyclic aromatic hydrocarbons (PAHs), we previously showed that pollution was distributed randomly with hot and cold spots. Therefore, in the present study, we investigated the effect of this patchy PAH distribution on the bacterial community assemblage and compared it with that of root depth gradients found in the rhizosphere of either alfalfa or ryegrass. Sequencing of 16S rRNA amplicons revealed a higher bacterial diversity in ryegrass rhizosphere and enrichment in specific taxa by the 2 plant species. Indeed, Bacteroidetes, Firmicutes, and Gammaproteobacteria were globally favored in alfalfa, whereas Acidimicrobiia, Chloroflexi, Alpha-, and Betaproteobacteria were globally favored in ryegrass rhizosphere. The presence of alfalfa created depth gradients of root biomass, carbohydrate, and pH, and actually shaped the bacterial assemblage, favoring Actinobacteria near the surface and Gemmatimonadetes and Proteobacteria at greater depths. Contrarily, the bacterial assemblage was homogeneous all along depths of the ryegrass root system. With both plant species, the PAH content and random distribution had no significant effect on bacterial assemblage. Globally, at centimeter scale, bacterial community assemblages were mostly shaped by soil physical and chemical depth gradients induced by root growth but not by patchy PAH content.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".