Projections of future forest age class structure under the influence of fire and harvesting: implications for forest management in the boreal forest of eastern Canada
Bibliographic record
Abstract
In northeastern Canadian boreal forests, a coarse-filter approach was adopted to provide sustainable ecosystem services in order to maintain a balance between biodiversity, ecosystem function and timber production. An old forest (>100 years) maintenance target was established considering the range of historical variability in the proportion of this forest stage. However, the estimation of the harvesting rate that maintains the target level in old forests did not consider explicitly the impact of current and future, i.e. possibly higher, fire frequency. In this context, we compared historical, current, and future age structures according to recorded or projected fire activity and the current level of harvesting in western Quebec's boreal forest. Results show that under the current rates of harvesting and fire, the proportion of old forests could reach a minimum level rarely seen in the natural landscape in the past. The situation could become even more critical with the projected increase in fire activity under climate change. Numerous forest and fire management solutions exist, such as increasing rotation length, implementing a diversified silviculture, using a fire-smart approach or reaching a better balance between intensive management and conservation. We advocate their rapid implementation to reverse the projected decrease in the proportion of old forests.
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 | 0.002 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".