Postfire Soil Carbon Accumulation Does Not Recover Boreal Peatland Combustion Loss in Some Hydrogeological Settings
Bibliographic record
Abstract
Abstract Deep peat burning at the interface between subhumid Boreal Plains (BP) peatlands and forestlands (margin ecotones) in some hydrogeological settings has brought into question the long‐term stability of these peatlands under current and future predicted climate. Small peatlands located at midtopographic positions on coarse sediments have been identified as hot spots for severe burning, as these peatland margins are not regularly connected to regional groundwater flow. The ability of these peatland systems to recover carbon lost from both the interior and margin within the fire return interval, however, has not yet been investigated. Here we examine peatland soil carbon accumulation along a chronosequence of time since fire for 26 BP ombrotrophic bogs located across a range of hydrogeological settings. Soil organic carbon accumulation following wildfire does not appear to be influenced by hydrogeological setting; however, the ability of a peatland to recover the quantity of carbon lost within the fire return interval is dependent on the amount of carbon that was released through smoldering, which is influenced by hydrogeological setting for peatland margins. Based on published measurements of organic soil carbon loss during wildfire and our soil carbon accumulation rates, we suggest that peatlands located at topographic lows on coarse‐grained glaciofluvial outwash sediments or on low‐relief, fine‐grained sediment deposits from glaciolacustrine or subglacial paleoenvironments are currently resilient to wildfire on the BP landscape. Peatlands that experience severe smoldering at the margins, such as ephemerally perched systems on glaciofluvial outwash sediments, will likely undergo permanent loss of legacy carbon stores.
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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 | 0.000 | 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) | 0.001 | 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".