Response of forest productivity to changes in growth and fire regime due to climate change
Bibliographic record
Abstract
Climate change is having complex impacts on the boreal forest, modulating both tree growth limiting factors and fire regime. However, these aspects are usually projected independently when estimating climate change effect on the boreal forest. Using a combination of three different methods, our goal is to assess the combined impact of changes in growth and fire regime due to climate change on the timber supply at the transitions from closed to open boreal coniferous forests in Québec, Canada. To identify the areas that are likely to be the most sensitive to climate change, we projected climate-induced impacts on growth and fire activity at three different time periods: 2011–2040 RCP 8.5 for low growth change and minimum fire activity, 2071–2100 RCP 4.5 for moderate growth change and medium fire activity, and 2071–2100 RCP 8.5 for high growth change and maximum fire activity. Our study shows the importance of incorporating fire in strategic forest management planning especially in a context of climate change. Under the most extreme scenarios, the negative impact of fire activity on productive area and total volume mostly offsets the positive effects of climate change via improved tree growth.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".