Implications of future disturbance regimes on the carbon balance of Canada’s managed forest (2010–2100)
Bibliographic record
Abstract
Recent increases in fire and insect disturbances have contributed to a transition of Canada’s managed forest carbon balance from sink to source. Further increases in area burned could contribute positive feedback to climate change. We made probabilistic forecasts of the recovery of C sinks in Canada’s managed forest between 2010 and 2100 under two assumptions about future area burned by wildfire: (1) no increase relative to levels observed in the last half of the 20th century and (2) linear increases by a factor of two or four (depending on region) from 2010 to 2100. Recovery of strong C sinks in Canada’s managed forest will be delayed until at least the 2030s because of insect outbreaks, even if predicted increases in area annually burned do not occur. After 2050, our simulations project an annual probability of a sink near 70% with no increase in area burned and 35% with increasing area burned. All simulations project a cumulative C source from 2010–2100, even if annual area burned does not increase. If the sink strength of terrestrial ecosystems is reduced because of increasing natural disturbances, then it will become more difficult to achieve global atmospheric CO2 stabilization targets.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".