Multi-Millennial Fire History of the Giant Forest, Sequoia National Park, California, USA
Bibliographic record
Abstract
Giant sequoias ( Sequoiadendron giganteum [Lindl.] J. Buchholz) preserve a detailed history of fire within their annual rings. We developed a 3000 year chronology of fire events in one of the largest extant groves of ancient giant sequoias, the Giant Forest, by sampling and tree-ring dating fire scars and other fire-related indicators from 52 trees distributed over an area of about 350 ha. When all fire events were included in composite chronologies, the mean fire intervals (years between fires of any size) declined as a function of increasing spatial extent from tree, to group, to multiple groups, to grove scales: 15.5 yr (0.1 ha), 7.4 yr (1 ha.), 3.0 yr (70 ha), and 2.2 yr (350 ha), respectively. We interpreted widespread fires (i.e., fire events recorded on ≥2 trees, or ≥25% of all trees recording fires within composites) to have occurred in areas of 70 ha to 350 ha at mean intervals ranging from about 6 yr to 35 yr. We compared the annual, multi-decadal and centennial variations in Giant Forest fire frequency with those documented in tree-ring and charcoal-based fire chronologies from four other giant sequoia groves in the Sierra Nevada, and with independent tree-ring-based reconstructions of summer drought and temperatures. The other giant sequoia fire histories (tree rings and charcoal-based) were significantly ( P < 0.001) correlated with the Giant Forest fire frequency record and independent climate reconstructions, and confirm a maximum fire frequency during the warm and drought-prone period from 800 C.E. to 1300 C.E. (Common Era). This was the driest period of the past two millennia, and it may serve as an analog for warming and drying effects of anthropogenic greenhouse gases in the next few decades. Sequoias can sustain very high fire frequencies, and historically they have done so during warm, dry times. We suggest that preparation of sequoia groves for anticipated warming may call for increasing the rate of prescribed burning in most parts of the Giant Forest.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".