Fire and climate
Bibliographic record
Abstract
Fire has been an important component of ecosystems since the first terrestrial plants appeared, with fire records dating as far as to 420 million years ago. Fire is present in most of Earth’s ecosystems except in areas of sparse vegetation and near the poles. Human manipulation of fire for land-clearing and recreation, as well as fire suppression practices, has disrupted the natural pattern of fire activity in many forested regions. In addition, anthropogenic climate change is expected to further alter global fire occurrence, with important consequences for species distribution, ecosystem integrity and function, atmospheric greenhouse gas balance, and human safety. Characterizing the range of fire regime modifications remains a major challenge owing to the large interannual variability in area burned that tends to mask long-term and subtle changes. In this chapter, we outline the physical processes of fire in relation to the forest environment and climate. We also review the methods used in fire history reconstructions as well as results from fire history reconstructions and modeling. The best proxy records for longer term fire reconstructions are tree-ring and lake sediment records. Finally, our discussion focuses on fire history derived from these two proxy types at multiple sites in boreal, temperate, and tropical regions.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.004 |
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".