Novel chytrid lineages dominate fungal sequences in diverse marine and freshwater habitats
Bibliographic record
Abstract
In aquatic environments, fungal communities remain little studied despite their taxonomic and functional diversity. To extend the ecological coverage of this group, we conducted an in-depth analysis of fungal sequences within our collection of 3.6 million V4 18S rRNA pyrosequences originating from 319 individual marine (including sea-ice) and freshwater samples from libraries generated within diverse projects studying Arctic and temperate biomes in the past decade. Among the ~1.7 million post-filtered reads of highest taxonomic and phylogenetic quality, 23,263 fungal sequences were identified. The overall mean proportion was 1.35%, but with large variability; for example, from 0.01 to 59% of total sequences for Arctic seawater samples. Almost all sample types were dominated by Chytridiomycota-like sequences, followed by moderate-to-minor contributions of Ascomycota, Cryptomycota and Basidiomycota. Species and/or strain richness was high, with many novel sequences and high niche separation. The affinity of the most common reads to phytoplankton parasites suggests that aquatic fungi deserve renewed attention for their role in algal succession and carbon cycling.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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 teacher head, 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".