Risk of natural disturbances makes future contribution of Canada's forests to the global carbon cycle highly uncertain
Bibliographic record
Abstract
A large carbon sink in northern land surfaces inferred from global carbon cycle inversion models led to concerns during Kyoto Protocol negotiations that countries might be able to avoid efforts to reduce fossil fuel emissions by claiming large sinks in their managed forests. The greenhouse gas balance of Canada's managed forest is strongly affected by naturally occurring fire with high interannual variability in the area burned and by cyclical insect outbreaks. Taking these stochastic future disturbances into account, we used the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) to project that the managed forests of Canada could be a source of between 30 and 245 Mt CO(2)e yr(-1) during the first Kyoto Protocol commitment period (2008-2012). The recent transition from sink to source is the result of large insect outbreaks. The wide range in the predicted greenhouse gas balance (215 Mt CO(2)e yr(-1)) is equivalent to nearly 30% of Canada's emissions in 2005. The increasing impact of natural disturbances, the two major insect outbreaks, and the Kyoto Protocol accounting rules all contributed to Canada's decision not to elect forest management. In Canada, future efforts to influence the carbon balance through forest management could be overwhelmed by natural disturbances. Similar circumstances may arise elsewhere if global change increases natural disturbance rates. Future climate mitigation agreements that do not account for and protect against the impacts of natural disturbances, for example, by accounting for forest management benefits relative to baselines, will fail to encourage changes in forest management aimed at mitigating climate change.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".