Influence of tea-<i>Pleurotus ostreatus</i> intercropping on soil fungal diversity and community structure
Bibliographic record
Abstract
Understanding the relationship between soil fungal communities and soil function is vital to establish a sustainable and ecologically friendly tea (Camellia sinensis L.) cultivation. However, there is limited research on the response of soil fungal communities to tea-fungus intercropping, particularly how it is related to soil biodiversity and fertility. Here, we assessed and compared the fungal communities using a metabarcoding technique, soil properties in three plantations (1, 2, and 5 yr of tea-Pleurotus intercropping plantations), and a 5 yr chemically fertilized monoculture plantation. We obtained a total of 3493 operational taxonomic units (OTUs) from four tea plantations. Five hundred and ninety-three fungal OTUs are shared by all plantations, and the other 471 fungal OTUs are shared by three plantations. The largest number of OTUs was recorded in 5 yr tea-Pleurotus intercropped plantations (N = 2040), followed by 2 yr (N = 2024) and then 1 yr (N = 1471), while the chemically fertilized plantation recorded 1823 OTUs. Tea-Pleurotus intercropping showed a significant effect on the increased diversity of soil fungal diversity compared with the monoculture tea cultivations. Fungal groups Basidiomycota, Ascomycota, and Mortierellomycota were the most abundant taxonomic groups recorded in all soil samples. Principal coordinate analysis revealed that fungal community composition in tea-Pleurotus intercropped plantations and monoculture tea plantations was significantly different. Besides, redundancy analysis revealed that soil nutrients significantly influence soil fungal community composition. Our results demonstrate that tea-Pleurotus intercropping may offer long-term benefits to soil biodiversity and sustainable benefits in the tea plantations.
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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".