Large fires as agents of ecological diversity in the North American boreal forest
Bibliographic record
Abstract
The present study undertook a hierarchical analysis of the variability within and among some individual fire events in the boreal ecozones of Canada and Alaska. When stratified by ecozone, differences in the spatial and temporal distribution of wildfires were observed in the Canadian Large Fire Data Base that reflect climatic, terrain and land-use differences across the country. Remote-sensing data collected before and after boreal forest fires permitted a rigorous analysis of the variability in burn severity within individual fire events, and the identification of certain fire-prone and more fire-resistant land-cover types. The occurrence of fire skips or islands was related to the distribution of those cover types, resulting in proportionally more unburned area within the perimeter of a burn for larger fires. Differences in burn severity led to differences in post-burn vegetation response of tree, shrub and moss layers that can persist for decades or even centuries. As a result, there can be considerable variability in the survival, density and distribution of residual biota and organic materials. This variability creates a range of post-fire vegetation patterns and contributes much to the habitat diversity of boreal landscapes.
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 | 0.001 | 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".