Yeasts from tropical forests: Biodiversity, ecological interactions, and as sources of bioinnovation
Bibliographic record
Abstract
Tropical rainforests and related biomes are found in Asia, Australia, Africa, Central and South America, Mexico, and many Pacific Islands. These biomes encompass less than 20% of Earth's terrestrial area, may contain about 50% of the planet's biodiversity, and are endangered regions vulnerable to deforestation. Tropical rainforests have a great diversity of substrates that can be colonized by yeasts. These unicellular fungi contribute to the recycling of organic matter, may serve as a food source for other organisms, or have ecological interactions that benefit or harm plants, animals, and other fungi. In this review, we summarize the most important studies of yeast biodiversity carried out in these biomes, as well as new data, and discuss the ecology of yeast genera frequently isolated from tropical forests and the potential of these microorganisms as a source of bioinnovation. We show that tropical forest biomes represent a tremendous source of new yeast species. Although many studies, most using culture-dependent methods, have already been carried out in Central America, South America, and Asia, the tropical forest biomes of Africa and Australasia remain an underexplored source of novel yeasts. We hope that this review will encourage new researchers to study yeasts in unexplored tropical forest habitats.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".