Simulating the effects of future fire regimes on western Canadian boreal forests
Bibliographic record
Abstract
Abstract.Effects of future fire regimes on boreal tree species and plant functional types were studied in W Canada using a simulation approach. Present (1975–1990) and future (2080–2100) fire regimes were simulated using data from the Canadian Global Coupled Model (CGCM1). The long‐term effects of these fire regimes were simulated using a stand level, boreal fire effects model (BORFIRE) developed for this study. Changes in forest composition and biomass storage due to future altered fire regimes were determined by comparing the effects of present and future fire regimes on forest stands over a 400‐yr period. Differences in the two scenarios after 400 yr indicate shifting trends in forest composition and biomass that can be expected as a result of future changes in the fire regime. The ecological impacts of altered fire regimes are discussed in terms of general plant functional types. The Canadian Global Coupled Model showed more severe burning conditions under future fire regimes including fires with greater intensity, greater depth of burn and greater total fuel consumption. Shorter fire cycles estimated for the future generally favoured species which resprout (fire endurers) or store seed (fire evaders). Species with no direct fire survival traits (fire avoiders) declined under shorter fire cycles. The moderately thick barked trait of fire resisters provided little additional advantage in crown fire dominated boreal forests. Many species represent PFTs with multiple fire survival traits. The fire evader and avoider PFT was adaptable to the widest range of fire cycles. There was a general increase in biomass storage under the simulated future fire regimes caused by a shift in species composition towards fast‐growing re‐sprouting species. Long‐term biomass storage was lower in fire exclusion simulations because some stands were unable to reproduce in the absence of fire.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".