Patterns of distribution of microfungi in decomposing bog and fen plants
Bibliographic record
Abstract
The microfungal assemblages from the litter of the dominant vegetation of a forested bog and a riverine, sedge-dominated fen in southern boreal Alberta, Canada, were investigated over a 2-year period. Canonical correspondence analyses showed distinctly different fungal communities associated with litter of the dominant plant species of this bog (Sphagnum fuscum (Schimp.) Klinggr.) and fen (Carex aquatilis Wahlenb. leaves and rhizomes and Salix planifolia Pursh leaves and roots). Plant tissue quality variables, including total phosphorus and total nitrogen tissue concentrations, correlated most strongly with the fungal communities. In contrast, site-specific environmental (surface water chemical variables) and physical (peat and water temperatures, water level) variables were not correlated with the fungal communities of these five decomposing fen and bog plant litters. Of 93 identified fungal taxa, 25% occurred exclusively in the bog and 56% occurred exclusively in the fen. Eighteen species (19%) were common to the materials examined from both peatlands. Several species of (i) Aspergillus, Mortierella, and Oidiodendron were restricted to the Sphagnum litter in the bog, and species of (ii) Phialophora, Phialocephala, Fusarium, Dimorphospora foliicola, Monocillium constrictum, and several basidiomycetes were restricted to the Carex and Salix plant litters in the fen. These taxa constitute components of the bog and fen fungal communities, respectively.Key words: fungal communities, decomposition, bog, fen, canonical correspondence analysis (CCA).
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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 | 0.000 |
| 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".