Diversity of Arbuscular Mycorrhizal Fungi in Agroforestry, Conventional Plantations and Native Forests in Roraima State, Northern Brazil
Bibliographic record
Abstract
Arbuscular mycorrhizal fungi (AMF) are important components of the soil microbiota in terrestrial ecosystems, under the influence of various factors such as soil use and management, and can be adapted to a structure and diversity of fungal communities. The aim of this survey was to evaluate the influence of different systems of land use and management on AMF diversity in the Roraima State, Brazil. We collected soil samples in agroforestry, conventional soybean planting, conventional corn and native forest. After 150 days of incubation in a greenhouse, we extracted the spores in order to evaluate AMF, volume and to determine taxonomic identification. We found 16 species of AMF and the genus Acaulospora was the most frequent, followed by Glomus. Soil under agroforestry system had the highest species richness and the native forest, the lowest. On the other hand, soybean and corn areas presented greater density values than agroforestry system and native forest. In the agroforestry system, SOM attributes, Al3+ and H + Al had influence in AMF species richness. Thus, agroforestry constitute sustainable alternative influencing AMF communities in these ecosystems.
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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 | 0.001 | 0.001 |
| 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) | 0.000 | 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".