Abundance and diversity of fungi in relation to chemical changes in arctic moss profiles
Bibliographic record
Abstract
Mosses are a dominant component of high-arctic terrestrial ecosystems, yet little is known regarding the abundance and diversity of fungi associated with these abundant plants. We investigated vertical patterns of abundance and diversity of fungi and their relationship with chemical properties within profiles of Hylocomium splendens and Racomitrium lanuginosum collected in the Oobloyah Bay area on Ellesmere Island, Canada. The moss profiles were divided into 6 (H. splendens) and 5 (R. lanuginosum) layers according to the color and texture, and hyphal length, fungal assemblages, and contents of organic chemical components (acid-unhydrolyzable residues, total carbohydrates, extractives) and nutrients (N, P, K, Ca, Mg) were measured. Total hyphal length was greatest at the middle layers of H. splendens and at the deepest layers of R. lanuginosum and was significantly affected by moss species and nutrient contents. A total of 18 and 19 fungal taxa was isolated from the profiles of H. splendens and R. lanuginosum, respectively, with 11 taxa being common to both moss species. Moss species significantly affected the species distribution of fungi. Individual fungal taxa showed patterns of vertical distribution within the moss profiles. The contents of acid-unhydrolyzable residues and nutrients increased and the content of total carbohydrates decreased down the profile, which was attributable to the ability of fungi to decompose carbohydrates selectively and to immobilize nutrients in decomposed moss residues.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".