Interactions within the climate-vegetation-fire nexus may transform 21st century boreal forests in northwestern Canada
Bibliographic record
Abstract
Dry and warm conditions have exacerbated the occurrence of large and severe wildfires over the past decade in Canada's Northwest Territories (NT). Although temperatures are expected to increase during the 21st century, we lack understanding of how the climate-vegetation-fire nexus might respond. We used a dynamic global vegetation model to project annual burn rates, as well as tree species composition and biomass in the NT during the 21st century using the IPCC's climate scenarios. Burn rates will decrease in most of the NT by the mid-21st century, concomitant with biomass loss of fire-prone evergreen needleleaf tree species, and biomass increase of broadleaf tree species. The southeastern NT is projected to experience enhanced fire activity by the late 21st century according to scenario RCP4.5, supported by a higher production of flammable evergreen needleleaf biomass. The results underlie the potential for major impacts of climate change on the NT's terrestrial ecosystems.
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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 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".