Short- to medium-term effects of crown and surface fires on soil respiration in a Canadian boreal forest
Bibliographic record
Abstract
Fires are an important perturbation for the carbon (C) dynamics of boreal forests, especially when they are stand-replacing. In North American boreal forests, crown fires are predominant and, therefore, the most studied. However, surface fires can also lead to major tree mortality with substantial implications for the C balance. Here, we assess the short- (hours to days) to medium-term (1–3 years) effects of the different fire types (surface vs. crown) on the postfire soil C effluxes in jack pine (Pinus banksiana Lamb.) and black spruce (Picea mariana (Mill.) BSP) forest stands in the Northwest Territories, Canada. We found that while trees were instantly killed by the four crown fires studied, trees also died within 1 year after two of three surface fires studied. Associated with this tree mortality, soil autotrophic respiration decreased after both fire types, although at different timings. The soil heterotrophic respiration was either lower or unchanged when measured 1–3 years after either fire type but was increased when measured immediately after a surface fire, possibly due to the interaction between ash generation and wetting performed to suppress the fire. Our results suggest that both fire types can thus substantially alter C fluxes in the short to medium term, both through changes in vegetation and the soil environment.
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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 | 0.000 | 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) | 0.001 | 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".