Postfire carbon balance in boreal bogs of Alberta, Canada
Bibliographic record
Abstract
Abstract Boreal peatland ecosystems occupy about 3.5 million km 2 of the earth's land surface and store between 250 and 455 Pg of carbon (C) as peat. While northern hemisphere boreal peatlands have functioned as net sinks for atmospheric C since the most recent deglaciation, natural and anthropogenic disturbances, and most importantly wildfire, may compromise peatland C sinks. To examine the effects of fire on local and regional C sink strength, we focused on a 12 000 km 2 region near Wabasca, AB, Canada, where ombrotrophic Sphagnum ‐dominated bogs cover 2280 km 2 that burn with a fire return interval of 123±26 years. We characterized annual C accumulation along a chronosequence of 10 bog sites, spanning 1–102 years‐since‐fire (in 2002). Immediately after fire, bogs represent a net C source of 8.9±8.4 mol m −2 yr −1 . At about 13 years after fire, bogs switch from net C sources to net C sinks, mainly because of recovery of the moss and shrub layers. Subsequently, black spruce biomass accumulation contributes to the net C sink, with fine root biomass accumulation peaking at 34 years after fire and aboveground biomass and coarse root accumulation peaking at 74 years after fire. The overall C sink strength peaks at 18.4 mol C m −2 yr −1 at 75 years after fire. As the tree biomass accumulation rate declines, the net C sink decreases to about 10 mol C m −2 yr −1 at 100 years‐since‐fire. We estimate that across the Wabasca study region, bogs currently represent a C sink of 14.7±5.1 Gmol yr −1 . A decrease in the fire return interval to 61 years with no change in air temperature would convert the region's bogs to a net C source. An increase in nonwinter air temperature of 2 °C would decrease the regional C sink to 6.8±2.3 Gmol yr −1 . Under scenarios of predicted climate change, the current C sink status of Alberta bogs is likely to diminish to the point where these peatlands become net sources of atmospheric CO 2 ‐C.
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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 | 0.000 | 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".