A 700-year record of large fire years in northern Scandinavia shows large variability and increased frequency during the 1800 s
Bibliographic record
Abstract
Years with climatically mediated increases in boreal forest fire activity, referred to as large fire years (LFYs), contribute to a disproportionally large portion of the burned area over centuries, and are important drivers of ecosystem processes by affecting forest structure, biodiversity, and carbon balance at regional and continental scales. We analysed changes in LFY return intervals in northern Sweden (the area above 60 °N) over 1273–1960 using a network of 29 sites with dendrochronologically reconstructed fires, complemented by documentary records of fires available from forestry statistics. We observed large variability in return intervals of LFYs, an increase in LFY frequency during the 1800 s, and consistent associations between LFY occurrence and 500-hPa pressure anomalies over the European sub-continent over 1800xps2#1960. An increase in LFY frequency during the 1800 s might be climatically driven, and would thus long precede the period of likely human-induced climatic changes of the 1900 s. Long-term variability in climatically driven LFYs may present a challenge in partitioning the effects of human-related and human-independent components of climatic forcing upon forest fire activity.
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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 | 0.000 |
| 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 | 0.001 | 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".