Ecology of cultivable yeasts in pristine forests in northern Patagonia (Argentina) influenced by different environmental factors
Bibliographic record
Abstract
Environmental factors influencing the occurrence and community structure of soil yeasts in forests are not well studied. There are few studies dedicated to Southern Hemisphere soil yeasts populations and even fewer focused on temperate forests influenced by volcanic activity. The present work aimed to study the ecology of soil yeast communities from pristine forests influenced by different environmental factors (precipitation, physicochemical properties of soil, tree species, soil region, and season). The survey was performed in 4 northern Patagonian forests: 2 dominated by Nothofagus pumilio and 2 by Nothofagus antarctica. Yeast communities were described with ecological indices and species accumulation curves, and their association with environmental characteristics was assessed using multivariate analysis. Each forest site showed a particular arrangement of species as a result of environmental characteristics, such as dominant plant species, nutrient availability, and climatic characteristics. Cryptococcus podzolicus was most frequently isolated in nutrient-rich soils, Trichosporon porosum dominated cold mountain forests with low nutrient and water availability in soil, and capsulated yeasts such as Cryptococcus phenolicus dominated forest sites with low precipitation. The present work suggests that environmental factors affecting yeast communities may not be the current soil characteristics but the result of complex interactions of factors including natural disturbances like volcanic activity.
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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".