Diversity and function of fungi in peatlands: A carbon cycling perspective
Bibliographic record
Abstract
Peatlands are a dominant landform in the northern hemisphere, accumulating carbon in the form of peat due to an imbalance between decomposition and plant production rates. Decomposer (saprobes) and mycorrhizal fungi significantly influence carbon dynamics by degrading organic matter via the synthesis of extracellular enzymes. As organic matter decomposes, litter quality variables figure most prominently in the succession of fungi. Hence, litters composed primarily of complex polymers decompose very slowly. Surprisingly, recalcitrant polymer degraders (mostly basidiomycetes) are rarely isolated from peat, which may explain the accumulation of complex polymers in peat profiles. While enzymatic profiles of mycorrhizal fungi and other root endophytes may be more limited compared with saprobes, many of these fungi can degrade polymers of varying complexity as well and hence may also be significant decomposers of organic matter. To date, anamorphic ascomycetes and zygomycetes are the most frequently isolated fungi from peatlands (63 and 10% of all taxa, respectively), and chytridiomycetes, teleomorphic ascomycetes, and basidiomycetes appear to be less common (11% of all taxa). The remaining 16% of taxa remain unidentified or are sterile taxa. How disturbances affect peatland microbial communities and their roles is virtually unknown. This aspect of peatland microbial ecology requires immediate attention. The objective of this paper is to review the current state of knowledge of the diversity of fungi and their roles in carbon cycling dynamics in peatlands. Key words: Peatlands, fungi, carbon dynamics, diversity, functions, saprobes, mycorrhizas
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".