Fluvial CO<sub>2</sub> and CH<sub>4</sub> patterns across wildfire‐disturbed ecozones of subarctic Canada: Current status and implications for future change
Bibliographic record
Abstract
Abstract Despite occupying a small fraction of the landscape, fluvial networks are disproportionately large emitters of CO2 and CH4, with the potential to offset terrestrial carbon sinks. Yet the extent of this offset remains uncertain, because current estimates of fluvial emissions often do not integrate beyond individual river reaches and over the entire fluvial network in complex landscapes. Here we studied broad patterns of concentrations and isotopic signatures of CO2 and CH4 in 50 streams in the western boreal biome of Canada, across an area of 250,000 km2. Our study watersheds differ starkly in their geology (sedimentary and shield), permafrost extent (sporadic to extensive discontinuous) and land cover (large variability in lake and wetland extents). We also investigated the effect of wildfire, as half of our study streams drained watersheds affected by megafires that occurred 3 years prior. Similar to other boreal regions, we found that stream CO2 concentrations were primarily associated with greater terrestrial productivity and warmer climates, and decreased downstream within the fluvial network. No effects of recent wildfire, bedrock geology or land cover composition were found. The isotopic signatures suggested dominance of biogenic CO2 sources, despite dominant carbonate bedrock in parts of the study region. Fluvial CH4 concentrations had a high variability which could not be explained by any landscape factors. Estimated fluvial CO2 emissions were 0.63 (0.09–6.06, 95% CI) and 0.29 (0.17–0.44, 95% CI) g C m−2 year−1 at the landscape scale using a stream network modelling and a mass balance approach, respectively, a small but potentially important component of the landscape C balance. These fluvial CO2 emissions are lower than in other northern regions, likely due to a drier climate. Overall, our study suggests that fluvial CO2 emissions are unlikely to be sensitive to altered fire regimes, but that warming and permafrost thaw will increase emissions significantly.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| 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".