Fungal Community Analysis by Large-Scale Sequencing of Environmental Samples
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Fungi are an important and diverse component of soil communities, but these communities have proven difficult to study in conventional biotic surveys. We evaluated soil fungal diversity at two sites in a temperate forest using direct isolation of small-subunit and internal transcribed spacer (ITS) rRNA genes by PCR and high-throughput sequencing of cloned fragments. We identified 412 sequence types from 863 fungal ITS sequences, as well as 112 ITS sequences from other eukaryotic microorganisms. Equal proportions of Basidiomycota and Ascomycota sequences were present in both the ITS and small-subunit libraries, while members of other fungal phyla were recovered at much lower frequencies. Many sequences closely matched sequences from mycorrhizal, plant-pathogenic, and saprophytic fungi. Compositional differences were observed among samples from different soil depths, with mycorrhizal species predominating deeper in the soil profile and saprophytic species predominating in the litter layer. Richness was consistently lowest in the deepest soil horizon samples. Comparable levels of fungal richness have been observed following traditional specimen-based collecting and culturing surveys, but only after much more extensive sampling. The high rate at which new sequence types were recovered even after sampling 863 fungal ITS sequences and the dominance of fungi in our libraries relative to other eukaryotes suggest that the abundance and diversity of fungi in forest soils may be much higher than previously hypothesized. All sequences were deposited in GenBank, with accession numbers AY 969316 to AY 970290 for the ITS sequences and AY 969135 to AY 969315 for the SSU sequences.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.005 | 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 it