Effects of biotic feedback and harvest management on boreal forest fire activity under climate change
Bibliographic record
Abstract
Predictions of future fire activity over Canada's boreal forests have primarily been generated from climate data following assumptions that direct effects of weather will stand alone in contributing to changes in burning. However, this assumption needs explicit testing. First, areas recently burned can be less likely to burn again in the near term, and this endogenous regulation suggests the potential for self-limiting, negative biotic feedback to regional climate-driven increases in fire. Second, forest harvest is ongoing, and resulting changes in vegetation structure have been shown to affect fire activity. Consequently, we tested the assumption that fire activity will be driven by changes in fire weather without regulation by biotic feedback or regional harvest-driven changes in vegetation structure in the mixedwood boreal forest of Alberta, Canada, using a simulation experiment that includes the interaction of fire, stand dynamics, climate change, and clear cut harvest management. We found that climate change projected with fire weather indices calculated from the Canadian Regional Climate Model increased fire activity, as expected, and our simulations established evidence that the magnitude of regional increase in fire was sufficient to generate negative feedback to subsequent fire activity. We illustrate a 39% (1.39-fold) increase in fire initiation and 47% (1.47-fold) increase in area burned when climate and stand dynamics were included in simulations, yet 48% (1.48-fold) and 61% (1.61-fold) increases, respectively, when climate was considered alone. Thus, although biotic feedbacks reduced burned area estimates in important ways, they were secondary to the direct effect of climate on fire. We then show that ongoing harvest management in this region changed landscape composition in a way that led to reduced fire activity, even in the context of climate change. Although forest harvesting resulted in decreased regional fire activity when compared to unharvested conditions, forest composition and age structure was shifted substantially, illustrating a trade-off between management goals to minimize fire and conservation goals to emulate natural disturbance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".