13,000 years of fire history derived from soil charcoal in a British Columbia coastal temperate rain forest
Bibliographic record
Abstract
Abstract Little is known regarding the fire history of high‐latitude coastal temperate rain forests in the Pacific Northwest ( PNW ) of North America. While reconstructing historical fire regimes typically requires dendrochronological records from fire‐scarred trees or stratigraphically preserved lake sediment data, this type of information is virtually non‐existent in this region. To describe the long‐term fire history of a site on the central coast of British Columbia, Canada, we radiocarbon‐dated 52 pieces of charcoal. Charcoal ages ranged from 12,670 to 70 yr BP . Fires occurred regularly since 12,670 yr BP , with the exception of a distinct fire‐free period at 7500–5500 yr BP . Time since fire ( TSF ) estimates from soil charcoal and fire‐scarred trees ranged from 12,670 to 100 yr BP (median = 327 yr), and 70% of the sites examined had burned within the past 1000 yr. An increase in fire frequency in the late Holocene is consistent with the widely held hypothesis that anthropogenic fires were common across the PNW . We evaluate TSF distributions and discuss the difficulties in assigning actual fire dates from charcoal fragments with large inbuilt ages in a coastal temperate rain forest setting. We determine that a comprehensive approach using soil charcoal and fire scar analyses is necessary to reconstruct general trends in fire activity throughout the Holocene in this region.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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".