Rich and cold: diversity, distribution and drivers of fungal communities in patterned‐ground ecosystems of the <scp>N</scp>orth <scp>A</scp>merican <scp>A</scp>rctic
Bibliographic record
Abstract
Fungi are abundant and functionally important in the Arctic, yet comprehensive studies of their diversity in relation to geography and environment are not available. We sampled soils in paired plots along the North American Arctic Transect (NAAT), which spans all five bioclimatic subzones of the Arctic. Each pair of plots contrasted relatively bare, cryoturbated patterned-ground features (PGFs) and adjacent vegetated between patterned-ground features (bPGFs). Fungal communities were analysed via sequencing of 7834 ITS-LSU clones. We recorded 1834 OTUs - nearly half the fungal richness previously reported for the entire Arctic. These OTUs spanned eight phyla, 24 classes, 75 orders and 120 families, but were dominated by Ascomycota, with one-fifth belonging to lichens. Species richness did not decline with increasing latitude, although there was a decline in mycorrhizal taxa that was offset by an increase in lichen taxa. The dominant OTUs were widespread even beyond the Arctic, demonstrating no dispersal limitation. Yet fungal communities were distinct in each subzone and were correlated with soil pH, climate and vegetation. Communities in subzone E were distinct from the other subzones, but similar to those of the boreal forest. Fungal communities on disturbed PGFs differed significantly from those of paired stable areas in bPGFs. Indicator species for PGFs included lichens and saprotrophic fungi, while bPGFs were characterized by ectomycorrhizal and pathogenic fungi. Our results suggest that the Arctic does not host a unique mycoflora, while Arctic fungi are highly sensitive to climate and vegetation, with potential to migrate rapidly as global change unfolds.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".