Estimation of Inbuilt Age in Radiocarbon Ages of Soil Charcoal for Fire History Studies
Bibliographic record
Abstract
Radiocarbon age determinations of wood charcoal are commonly used to date past forest fire events, even though such ages should be greater than the fire event due to the age of the wood at the time of burning. The difference in the14C-derived age of charcoal and the time-since-fire (the “inbuilt age”) may be considerable in some vegetation types and thus must be estimated before interpreting fire dates. Two methods were used to estimate the potential range of inbuilt age of soil charcoal dated to determine ages of forest fires on the west coast of Vancouver Island (Canada). First, 2614C ages on charcoal in surficial soil were compared directly with ages of forest fire determined by tree-ring counts, suggesting inbuilt ages of 0–670 years. Second, a simulation model that uses estimated fuel loads, fuel consumption, charcoal production, and the ages of charred wood (time since wood formation), suggests that the combination of slow growth rates and slow decay rates of certain species can account for inbuilt ages of more than 400 years in this forest type. This level of inbuilt age is large enough such that the actual age of a fire may not occur within the 2σ confidence interval of a calibrated charcoal14C age determination, and thus significantly affect the interpretation of fire dates. A method is presented to combine the error of a calibrated14C age determination with the error due to inbuilt age such that the larger adjusted error encompasses the actual age of the 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".