Fungal community turnover along steep environmental gradients from geothermal soils in Yellowstone National Park
Bibliographic record
Abstract
Abstract Geothermal soils offer unique insight into the way extreme environmental factors shape communities of organisms. However, little is known about the fungi growing in these environments and in particular how localized steep abiotic gradients affect fungal diversity. We used metabarcoding to characterize soil fungi surrounding a hot spring-fed thermal creek with water up to 84 °C and pH 10 in Yellowstone National Park. We found a significant association between fungal communities and soil variable principal components, and we identify the key trends in co-varying soil variables that explain the variation in fungal community. Saprotrophic and ectomycorrhizal fungi community profiles followed, and were significantly associated with, different soil variable principal components, highlighting potential differences in the factors that structure these different fungal trophic guilds. In addition, in vitro growth experiments in four target fungal species revealed a wide range of tolerances to pH levels but not to heat. Overall, our results documenting turnover in fungal species within a few hundred meters suggest many co-varying environmental factors structure the diverse fungal communities found in the soils of Yellowstone National Park.
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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 | 0.001 |
| 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".