Regional relationships between climate and wildfire-burned area in the Interior West, USA
Bibliographic record
Abstract
Recent studies have linked the Atlantic Multidecadal Oscillation (AMO) and the Pacific Decadal Oscillation (PDO) with drought occurrence in the interior United States. This study evaluates the influence of AMO and PDO phases on interannual relationships between climate and wildfire-burned area during the 20th century. Palmer's Drought Severity Index (PDSI) is strongly related to burned area at both regional and subregional scales. In the southern Interior West, PDSI is most strongly related to yearly burned area during warm-phase AMO, while for the same period no significant relationships exist between PDSI and burned area in the central Interior West. During cool-phase PDO, interannual climate has little influence on burned area in either the northern or the central Interior West. The opposite is true for the southern Interior West and the eastern slope of the Colorado Rockies using the Southern Oscillation Index and PDSI, respectively. The western slope of the Colorado Rockies is the only climate division or region in which burned area is not related to preceding PDSI. During warm-phase PDO, current PDSI explains 67% of the interannual variance in burned area on the western slope. These regional and temporal differences are most likely governed by variations in fuel dynamics associated with dominant regional and subregional vegetation types.
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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 | 0.000 | 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) | 0.001 | 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".