Exploring forest productivity at an early age after fire: a case study at the northern limit of commercial forests in Quebec
Bibliographic record
Abstract
Interest in northern forests is increasing worldwide for both timber production and climate change mitigation. Studies exploring forest productivity at an early age after fire and its determining factors are greatly needed. We studied forest productivity, defined as the combined quality of stocking and growth, of 116 10- to 30-year-old postfire sites. The sites were spread over a 90 000 km 2 area north of the Quebec commercial forestry limit and were dominated by Picea mariana (Mill.) B.S.P. and Pinus banksiana Lamb. Seventy-two percent of our sites were classified as unproductive, mainly because of poor growth. Because growth was mostly determined by climatic factors, afforestation alone may not be sufficient to increase stand productivity in our study area. In addition, our results suggest that P. banksiana on dry sites may be less resilient to fire than previously thought, presumably because of poor site quality and climate. Overall, this is one of the first studies to explore productivity issues at an early age in natural northern forests, and the analysis scheme that defines forest productivity as the result of growth and stocking could provide a useful tool to identify similar issues elsewhere.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".