Spatial patterns of forest fires in Canada, 1980–1999
Bibliographic record
Abstract
The present study characterized the spatial patterns of forest fires in 10 fire-dominated ecozones of Canada by using a database of mapped fires ≥200 ha from 1980 to 1999 (n = 5533 fires). Spatial metrics were used individually to compare measures of fire size, shape (eccentricity and complexity), clustering, and geographic orientation among ecozones and were used concurrently in a multivariate analysis. In addition, a set of factors that influence the fire regime at the ecozone level – topography, climate, fuels, and anthropogenic factors – was compared with the metric outputs. We found significant differences in all spatial metrics among ecozones. The multivariate analysis showed that the Montane Cordillera ecozone, which covers most of British Columbia, had the most distinctive fires: its fires were smaller, less complex, and had a more regular distribution. The fire regime descriptors of ecozones were useful to interpret the spatial variation of some spatial metrics, such as fire size, eccentricity, and clustering, but provided little insight into the mechanisms of patterns of fire complexity, which were shown to be sensitive to data quality. Our results provide additional information about the creation of spatially heterogeneous landscapes. Furthermore, they illustrate the potential use of spatial metrics for a more detailed characterization of fire regimes and provide novel information for ecosystems-based land management.
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".