Post-fire development of canopy structure and composition in black spruce forests of Abitibi, Québec: a landscape scale study
Bibliographic record
Abstract
Fire reconstruction and forest inventory maps provided an opportunity to study changes in stand-level characteristics following fire using a data set comprised of all forest stands of fire origin in an area of over 10 000 km2. We assigned the date of the most recent fire occurrence to over 31 000 forest stands in an ecoforestry database. We categorized stands on different substrates into age classes to investigate differences in canopy composition, cover and height, and incidence of secondary disturbance. Stands with over 75% Picea mariana (Mill.) BSP dominated all age classes on organic sites. On other substrates, there was a change in canopy composition from deciduous stands and stands dominated by Pinus banksiana Lamb. to Picea mariana stands after about 100 yr. This transition was later for xeric sites. After a peak in canopy cover and height at about 100 yr, there was a decrease in the area occupied by stands with dense, tall canopies. Structural development was slower on less productive sites. There was little incidence of spruce budworm outbreaks. Partial disturbance by windthrow coincided with canopy break-up at 100 yr, but appeared to have little effect on overall canopy structure in later stages. Structural diversity was independent of compositional diversity; on organic sites, stands with similar composition had different canopy structure. Diversity of stands with different composition and structure was greatest in the first 150 yr following fire. Maintaining stands in different stages of structural development on the landscape would serve to maintain regional biodiversity.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".