Anthropogenic fire history and red oak forests in south-central Ontario
Bibliographic record
Abstract
The regeneration and dominance of northern red oak (Quercus rubra L.) has been associated with fire throughout eastern North America. Red oak in central Ontario grows near the northern edge of its distribution in mixed hardwood-coniferous forests under mesic conditions where it competes with more shade-tolerant species. We hypothesized that the abundance of red oak in these stands was largely the result of anthropogenic burning and natural fires, which would favor the regeneration and recruitment of northern red oak over such shade-tolerant species as sugar maple (Acer saccharum Marsh.). Fire histories dating from the mid-1600s were constructed by dendrochronological methods from fire scars on stumps, trees, and natural remnants of red pine (Pinus resinosa Ait.), white pine (Pinus strobus L.), and red oak at six sites in south-central Ontario. Fire histories of the sites are characterized by abrupt changes in fire interval. As much or more variance in fire interval is found within sites as is found among sites. Differences in the mean fire interval among sites are related to the density and migration of historic aboriginal and European populations. The mean fire interval varied from more than 70 years to six years depending on site location and historic period. The occurrence and abundance of red oak is linked to anthropogenic fire regimes. Key words: northern red oak, white pine, fire history, ecology, anthropogenic, fire regime, dendrochronology
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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 | 0.001 | 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".