A 1000-year record of forest fire, drought and lake-level change in southeastern British Columbia, Canada
Bibliographic record
Abstract
High-resolution charcoal analysis of lake sediments and stand-age information were used to reconstruct a 1000-year fire history around Dog Lake, which is located in the montane spruce zone of southeastern British Columbia. Macroscopic charcoal (>125,um) accumulation rates (CHAR) from lake sediment were compared with a modern stand-origin map and fire-scar dates in the Kootenay Valley to determine the relative area and proximity of fires recorded as CHAR peaks. Small fires close to the lake and larger more distant fires appear as similar-sized peaks in the record. This information reinforces previous findings where CHAR peaks represent a complex spatial aggregation of local to extra-local fires around a lake site. CHAR peaks indicate frequent stand-destroying fires during the 'Mediaeval Warm Period' (-AD 1000-1300), and other significant fires at c. 1360, 1500, 1610 and 1800. We also present a proxy measure of lake-level changes based on a comparison of accumulation rates of Chara globulanis-type oospores over the last millennium and the present distribution of charophytes in the lake basin. Lower water levels, represented by few or no Chara oospores, correspond to times of regional drought and large forest fires around the lake. Higher lake levels, represented by increased Chara oospore accumulation rates, correspond to wetter climate periods during the Oort, Wolf, Sporer and Maunder solar sunspot minima, when little or no fire activity occurs around the lake.
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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 | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 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) | 0.002 | 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".