Diversity of arbuscular mycorrhizal fungi in soil from the Pampa Ondulada, Argentina, assessed by pyrosequencing and morphological techniques
Bibliographic record
Abstract
The aim of this study was to assess the effects of agronomic practices on the arbuscular mycorrhizal (AM) fungal community in soils from the Pampa Ondulada region (Argentina), and to compare conclusions reached when using pyrosequencing or a morphological approach. The AM fungal diversity of 3 agricultural exploitations located in the Pampa Ondulada region (Argentina) was assessed by using 454 amplicon pyrosequencing and morphological (based on spore traits) approaches. Two kinds of soil managements are found in these sites: agronomic and non-agronomic. A total of 188 molecular operational taxonomic units and 29 morphological species of AM fungi were identified. No effect of soil management on AM richness was detected. AM fungal communities were more diverse and equitable in the absence of agronomic management. In contrast, the results on β-diversity varied according to the methodology used. We concluded that agronomic management of soil has a negative effect on AM fungal community biodiversity in the Pampa Ondulada region. We also conclude that both methodologies complement each other in the study of AM fungal ecology. This study greatly improved the knowledge about AM fungi in South America where the molecular diversity of AM fungi was practically unknown.
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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".