Soil fauna-microbial interactions shifts fungal and bacterial communities under a contamination disturbance
Bibliographic record
Abstract
The aim of this study was to determine whether the soil faunal-microbial interaction complexity (SFMIC) is a significant factor influencing the soil microbial communities and the willow growth in the context of PAH contamination. The SFMIC treatment had eight levels: just the microbial community, or the microbial community with nematodes, springtails, earthworms and all the possible combinations. SFMIC affected the height and biomass of willows after eight weeks or growth. SFMIC affected the structure and the composition of the bacterial, archaeal and fungal communities, with significant effects of SFMIC on the relative abundance of fungal genera such as Sphaerosporella, a known willow symbiont during phytoremediation, and bacterial phyla such as Actinobacteriota, containing many polycyclic aromatic hydrocarbons (PAH) degraders. These SFMIC effects on microbial communities were not clearly reflected in the community structure and abundance of PAH degraders, even though some degraders related to Actinobacteriota and the diversity of Gram-negative degraders were affected by the SFMIC treatments. Over 95% of PAH was degraded in all pots at the end of the experiment. Overall, our results suggest that, under our experimental conditions, SFMIC changes willow phytoremediation outcomes.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".