Effects of wildfire and harvest disturbances on forest soil bacterial communities
Bibliographic record
Abstract
Little attention has been paid to the effects of wildfires on soil bacterial communities. The opposite is true for the effects of harvest treatments on soil bacterial communities. This scarcity of microbiological research post wildfire may be because of the unpredictability of such events or because of a focus on other fire-induced changes such as soil chemistry. In this study, Boreal forest soil bacterial communities were assessed post disturbance in four treatments: control, harvest, burn and burn-salvage. The burn treatments were areas affected by the wildfire near Chisholm, Alberta in May, 2001. Changes in these microbial communities occurred as a consequence of the wildfire or harvest treatment disturbance, with greater effects in the burn treatments. Significant decreases in microbial biomass carbon (C[sub mic]) were seen as a result of the burn or harvest treatments. Microbial biomass nitrogen (N[sub mic]) decreased in the harvest treatment, but increased in the burn treatments, probably because of microbial assimilation of the increased amounts of available NH₄⁺ and NO₃⁻ due to burning. The C[sub mic]:N[sub mic] decreased in the harvest, burn and burn-salvage treatments, indicating a probable decrease in fungal biomass. Nonparametric ordination of molecular fingerprint data (ribosomal intergenic spacer analysis and rRNA gene denaturing-gradient gel electrophoresis) of 119 samples indicated clear distinctions between community composition in the burned and unburned treatments. Differences between control versus harvest and between burn versus burn-salvage treatments were less obvious, but multi-response permutation procedures demonstrated statistically significant separations between the two. Sequencing of bands from fingerprints uncovered interesting patterns of bacterial divisions specific to treatment type, y- and α-Proteobacteria were highly characteristic of the unburned treatments, while β-Proteobacteria and members of Bacillus were highly characteristic of the burned treatments. Biomass determinations confirmed general trends observed in past literature, while relatively new molecular methods unveiled new and interesting effects to bacterial communities in Boreal forest soils impacted by human and natural disturbances.
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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 | 0.001 | 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".