Spatial and temporal patterns of wildfires in the Northern Alps
Bibliographic record
Abstract
In the surrounding of the Karwendel, Wetterstein and Mieminger Mountains we have identified c. 400 forest fires to date. The earliest detected fire dates to more than 2900 years; the largest one (in 1705) affected an area of several thousand hectares. Approximately 90% of the fires are man-made (negligence, arson, railway) which explains the concentration on the south-exposed slopes of the densely populated Inn valley. Most of the larger fires take place in the altitudinal belt between 1400 and 1900 m a.s.l.; apart from very few exceptions, they are restricted to southerly orientations. Locally, mean recurrence intervals of 200-300 years occur which is similar to e.g. boreal forests in Canada. We observed a strong seasonality with 40% of the fires occurring in spring and 30% in summer. There is a weak correlation with the weather conditions in the one or two weeks before the fire with dry periods promoting wildfire ignition and burnt area size; however, there are many exceptions from the rule. The 1940ies stands out for more than twice as much fires than in all other decades which is both due to climatic and anthropogenic causes. Today, there is an apparent trend towards more frequent and smaller fires. The frequency is biased by the multitude of available documentation today (e.g. websites of fire brigades), while the decreasing size is due to improved fire fighting. Additional first results of the charcoal records in soils and mires will be presented at the meeting.
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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 | 0.001 | 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 | 0.001 | 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".