Forest fires in Canadian permafrost region: the combined effects of fire and permafrost dynamics on soil organic matter quality
Bibliographic record
Abstract
Wildfires burn approximately 1% of boreal forest yearly, being one of the most significant factors affecting soil organic matter (SOM) pools. Boreal forests are largely situated in the permafrost zone, which contains half of global soil carbon (C). Wildfires advance thawing of permafrost by burning the insulating organic layer and decreasing surface albedo, thus increasing soil temperatures. Fires also affect SOM quality through chemical and physical changes, such as the formation of resistant C compounds. The long-term post-fire effects on SOM quality, degradability and isotopic composition are not well known in permafrost forests. We studied the effect of forest fires on the proportional sizes of SOM pools with chemical fractionation (extracting with water, ethanol and acid) of soil samples (5, 30 and 50 cm depths) collected from a fire chronosequence in the upland mineral soils of the Canadian permafrost zone. We also determined the 13C and 15N isotopic composition of soil after fire. In the topsoil horizon (5 cm) recent fire areas contained a smaller fraction of labile SOM and were slightly more enriched with 15N and 13C than older fire areas. The SOM fraction ratios reverted towards pre-fire status with succession. Changes in SOM were less apparent deeper in the soil. Best predictors for the size of recalcitrant SOM fraction were active layer depth, vegetation biomass and soil C/N ratio, whereas microbial biomass was best predicted by the size of the recalcitrant SOM fraction. Results indicated that SOM in upland mineral soils at the permafrost surface could be mainly recalcitrant and its decomposition not particularly sensitive to changes resulting from fire.
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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 | 0.000 | 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".