Linking tree rings, summer aridity, and regional fire data: an example from the boreal forests of the Komi Republic, East European Russia
Bibliographic record
Abstract
To evaluate the potential use of tree-ring data as a proxy for fire activity at the scale of a large boreal region, we analyzed a set of regional tree-ring chronologies of Siberian larch (Larix sibirica L.), a spatially implicit annual fire record, and monthly climate data for the Komi Republic for the period 19501990. In most years, annually burned area was below 0.001% of the republic's forested area and reached up to 0.7% during fire-prone years. Principal components (PC) of summer aridity resolved 64.2% of the annual variation in the number of fires, 12.2% in the average fire size, and 59.2% in the annually burned area. In turn, tree-ring PCs explained 65.2% of variation in fire-related weather PCs. Dendrochronological reconstruction of the annual number of fires and of the log-transformed annually burned area predicted 27.0% and 40.1% of the high-frequency variance of these variables, respectively. Coefficient of efficiency, a measure of reconstruction usefulness, reached 0.081 (number of fires) and 0.315 (annual area burned), supporting the obtained index as a realistic proxy for regional fire activity. Decadal variation in coefficient of efficiency values suggested improved monitoring accuracy since 1960 and more effective fire suppression during the last studied decade (19801990).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".