Linking forest fires to lake metabolism and carbon dioxide emissions in the boreal region of Northern Québec
Bibliographic record
Abstract
Abstract Natural fires annually decimate up to 1% of the forested area in the boreal region of Québec, and represent a major structuring force in the region, creating a mosaic of watersheds characterized by large variations in vegetation structure and composition. Here, we investigate the possible connections between this fire‐induced watershed heterogeneity and lake metabolism and CO2 dynamics. Plankton respiration, and water–air CO2 fluxes were measured in the epilimnia of 50 lakes, selected to lie within distinct watershed types in terms of postfire terrestrial succession in the boreal region of Northern Québec. Plankton respiration varied widely among lakes (from 21 to 211 μg C L−1 day−1), was negatively related to lake area, and positively related to dissolved organic carbon (DOC). All lakes were supersaturated in CO2 and the resulting carbon (C) flux to the atmosphere (150 to over 3000 mg C m2 day−1) was negatively related to lake area and positively to DOC concentration. CO2 fluxes were positively related to integrated water column respiration, suggesting a biological component in this flux. Both respiration and CO2 fluxes were strongly negatively related to years after the last fire in the basin, such that lakes in recently burnt basins had significantly higher C emissions, even after the influence of lake size was removed. No significant differences were found in nutrients, chlorophyll, and DOC between lakes in different basin types, suggesting that the fire‐induced watershed features influence other, more subtle aspects, such as the quality of the organic C reaching lakes. The fire‐induced enhancement of lake organic C mineralization and C emissions represents a long‐term impact that increases the overall C loss from the landscape as the result of fire, but which has never been included in current regional C budgets and future projections. The need to account for this additional fire‐induced C loss becomes critical in the face of predictions of increasing incidence of fire in the circumboreal landscape.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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".