Diversity of endolithic fungal communities in dolomite and limestone rocks from Nanjiang Canyon in Guizhou karst area, China
Bibliographic record
Abstract
The endolithic environment, the tiny pores and cracks in rocks, buffer microbial communities from a number of physical stresses, such as desiccation, rapid temperature variations, and UV radiation. Considerable knowledge has been acquired about the diversity of microorganisms in these ecosystems, but few culture-independent studies have been carried out on the diversity of fungi to date. Scanning electron microscopy of carbonate rock fragments has revealed that the rock samples contain certain kinds of filamentous fungi. We evaluated endolithic fungal communities from bare dolomite and limestone rocks collected from Nanjiang Canyon (a typical karst canyon in China) using culture-independent methods. Results showed that Ascomycota was absolutely dominant both in the dolomite and limestone fungal clone libraries. Basidiomycota and other eukaryotic groups (Bryophyta and Chlorophyta) were only detected occasionally or at low frequencies. The most common genus in the investigated carbonate rocks was Verrucaria. Some other lichen-forming fungi (e.g., Caloplaca, Exophiala, and Botryolepraria), Aspergillus, and Penicillium were also identified from the rock samples. The results provide a cross-section of the endolithic fungal communities in carbonate rocks and help us understand more about the role of microbes (fungi and other rock-inhabiting microorganisms) in rock weathering and pedogenesis.
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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 | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 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".