Mixed‐severity fire history at a forest–grassland ecotone in west central British Columbia, Canada
Bibliographic record
Abstract
. We documented historical chronologies of widespread fires and localized grassland fires between AD 1600 and 1900. Relationships between fire events, reconstructed values of the Palmer Drought Severity Index, and annual precipitation were examined using superposed epoch and bivariate event analyses. Widespread fires occurred during warm, dry years and were preceded by multiple anomalously dry, warm years. Localized fires that affected only grassland-proximal forests were more frequent than widespread fires. These localized fires showed a lagged, positive relationship with wetter conditions. The landscape pattern of forest structure provided further evidence of complex fire activity with multiple plots shown to have experienced low-, mixed-, and/or high-severity fires over the last four centuries. We concluded that this forest-grassland ecotone was characterized by fires of mixed severity, dominated by frequent, low-severity fires punctuated by widespread fires of moderate to high severity. This landscape-level variability in fire-climate relationships and patterns in forest structure has important implications for fire and grassland management in west central British Columbia and similar environments elsewhere. Forest restoration techniques such as prescribed fire and thinning are oftentimes applied at the forest-grassland ecotone on the basis that historically high frequency, low-severity fires defined the character of past fire activity. This study provides forest managers and policy makers with important information on mixed-severity fire activity at a low elevation forest-grassland ecotone, a crucial prerequisite for the effective management of these complex ecosystems.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".