Chemical fumigation combined with soil amendments of contrasting carbon availability alters soil bacterial and fungal community diversity
Bibliographic record
Abstract
Chemical fumigation is used to reduce soil-borne diseases in agricultural production systems; however, non-targeted soil microorganisms may also be affected. This study investigated the effects of chemical fumigation and substrate carbon (C) availability on the soil bacterial and fungal community diversity under controlled conditions over 128 days. This study consisted of a 3 × 3 factorial arrangement of three fumigant treatments (fumigation with chloropicrin [CP], metam sodium [MS], or no fumigation) and three soil amendment treatments (amendment with young barley, mature barley, or no amendment). MS fumigation transiently decreased bacterial species evenness when combined with young barley residues; however, it did not affect fungal diversity indices. CP fumigation, regardless of soil amendment or substrate C availability, decreased bacterial species evenness and richness that did not recover over time. However, CP fumigation only decreased fungal species evenness and richness when combined with young or mature barley residues. Although all treatments resulted in a bacterial and fungal community that was significantly dissimilar to the non-fumigated unamended soil, CP fumigated soils had the most dissimilar bacterial and fungal β-diversity after 128 days. This study demonstrated that the addition of young or mature barley residues to chemically fumigated soil did not recover microbial diversity. Instead, the addition of plant residues to chemically fumigated soil had a greater impact on microbial diversity and community composition compared to chemical fumigation used alone, subsequently promoting a less diverse and selective community for both fumigation and organic C additions.
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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) | 0.001 | 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".