Wildfire severity reduces richness and alters composition of soil fungal communities in boreal forests of western Canada
Bibliographic record
Abstract
Wildfire is the dominant disturbance in boreal forests and fire activity is increasing in these regions. Soil fungal communities are important for plant growth and nutrient cycling postfire but there is little understanding of how fires impact fungal communities across landscapes, fire severity gradients, and stand types in boreal forests. Understanding relationships between fungal community composition, particularly mycorrhizas, and understory plant composition is therefore important in predicting how future fire regimes may affect vegetation. We used an extreme wildfire event in boreal forests of Canada's Northwest Territories to test drivers of fungal communities and assess relationships with plant communities. We sampled soils from 39 plots 1 year after fire and 8 unburned plots. High-throughput sequencing (MiSeq, ITS) revealed 2,034 fungal operational taxonomic units. We found soil pH and fire severity (proportion soil organic layer combusted), and interactions between these drivers were important for fungal community structure (composition, richness, diversity, functional groups). Where fire severity was low, samples with low pH had higher total fungal, mycorrhizal, and saprotroph richness compared to where severity was high. Increased fire severity caused declines in richness of total fungi, mycorrhizas, and saprotrophs, and declines in diversity of total fungi and mycorrhizas. The importance of stand age (a surrogate for fire return interval) for fungal composition suggests we could detect long-term successional patterns even after fire. Mycorrhizal and plant community composition, richness, and diversity were weakly but significantly correlated. These weak relationships and the distribution of fungi across plots suggest that the underlying driver of fungal community structure is pH, which is modified by fire severity. This study shows the importance of edaphic factors in determining fungal community structure at large scales, but suggests these patterns are mediated by interactions between fire and forest stand composition.
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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 | 0.000 | 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 | 0.000 |
| 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 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".