Reconstructing fire history in central Mongolia from tree-rings
Bibliographic record
Abstract
Rising temperatures are expected to increase wildfire activity in many regions of the world. Over the last 60 years in Mongolia, mean annual temperatures have increased ~2°C and the recorded frequency and spatial extent of forest and steppe fires have increased. Few long records of fire history exist to place these recent changes in a historical perspective. The purpose of this paper is to report on fire history research from three sites in central Mongolia and to highlight the potential of this region as a test case for understanding the relationships between climate change, fire and land use. We collected partial cross-sections from fire-scarred trees and stumps at each site using a targeted sampling approach. All three sites had long histories of fire ranging from 280 to 450 years. Mean Weibull fire return intervals varied from 7 to 16 years. Fire scars at one protected-area site were nearly absent after 1760, likely owing to changes in land use. There is limited synchrony in fire occurrence across sites, suggesting that fire occurrence, at least at annual time scales, might be influenced by local processes (grazing, human ignitions, other land-use factors) as well as regional processes like climate. Additional data are being collected to further test hypotheses regarding climate change, land use and fire.
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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) | 0.000 | 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".