Fire history in relation to site type and vegetation in Vienansalo wilderness in eastern Fennoscandia, Russia
Bibliographic record
Abstract
A wildfire area in a boreal forest landscape dominated by Pinus sylvestris L., in the Vienansalo wilderness area in eastern Fennoscandia, was examined for its spatial characteristics and fire history. The boundaries of the 360-ha fire that occurred in 1969 were mapped, and the vegetation types of burnt and unburnt areas were inventoried. Fire history was investigated in 40 study plots, and fire scars, tree ages, and charcoal in peat or soil were used for evidence of past fires. The complex shape of the 1969 fire and the detected small-scale variation in past fire frequencies were concordant with the existing small-scale variation in site moisture and vegetation characteristics in the area. Moist depressions, swamps, and more fertile forest patches dominated by Picea abies (L.) Karst. often did not burn when the nearby dryish forest type did. There was also temporal variability in fire frequency. An abrupt increase in the number of fires occurred in the late 17th century. In the mid-19th century, both the number of fires and the annually burnt area in the region decreased. Our results show that in the examined wildfire area, there has been considerable and consistent small-scale spatial variation in fire frequency and that historical fire regime evidently has been strongly affected by human activity.
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 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 | 0.000 | 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 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".