Biodegradable plastic exposure enhances microbial functional diversity while reducing taxonomic diversity across multi-kingdom soil microbiota in cherry tomato fields
Bibliographic record
Abstract
Plastic films are extensively utilized in agroecosystems, and their residues are accumulating in global soil at a worrying rate. Biodegradable films are employed as a substitute for polyethylene (PE) films due to their rapid degradation rate. Although the taxonomic diversity of soil microbiome in response to biodegradable films has been studied, its alterations in functional diversity remain unexplored. Here, we conduct a two-year field experiment in cherry tomato to address how PE and poly (butylene adipate-co-terephthalate) (PBAT) influences soil microbiota across multi-kingdom (bacteria, fungi, and protists) regarding its taxonomic and functional diversity. The results show that PBAT exposure reduces the taxonomic diversity while increasing functional diversity across multi-kingdom domains compared to PE exposure. We further find that the decreased taxonomic diversity under PBAT exposure reduces the complexity of microbial inter-kingdom and internal-kingdom networks. Conversely, PBAT exposure enhances microbial functional diversity (Shannon index) and average genome size, accompanied by elevated abundances of plastic-degrading genes as well as carbon, nitrogen, phosphorus, and sulphur cycling functional genes. Overall, our study indicates that environmental filtration induced by PBAT exposure changes the microbial life adaptive strategies and leads to a decoupling between taxonomic diversity and functional diversity.
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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 | 0.000 |
| 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".