Decadal‐Scale Recovery of Carbon Stocks After Wildfires Throughout the Boreal Forests
Bibliographic record
Abstract
Abstract Boreal forests store 30% of the world's terrestrial carbon (C). Consequently, climate change mediated alterations in the boreal forest fire regime can have a significant impact on the global C budget. Here we synthesize the effects of forest fires on the stocks and recovery rates of C in boreal forests using 368 plots from 16 long‐term (≥100 year) fire chronosequences distributed throughout the boreal zone. Forest fires led to a decrease in total C stocks (excluding mineral soil) by an average of 60% (range from <10% to >80%), which was primarily a result of C stock declines in the living trees and soil organic layer. Total C stocks increased with time since fire largely following a sigmoidal shape Gompertz function, with an average asymptote of 8.1 kg C m −2 . Total C stocks accumulated at a rate of 2–60 g m −2 yr −1 during the first 100 years. Potential evapotranspiration (PET) was identified as a significant driver of C stocks and their post‐fire recovery, likely because it integrates temperature, radiation, and the length of the growing season. If the fire return interval shortens to ≤100 years in the future, our findings indicate that many boreal forests will be prevented from reaching their full C storage potential. However, our results also suggest that climate warming‐induced increases in PET may speed up the post‐fire recovery of C stocks.
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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".