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Record W2126791719 · doi:10.5558/tfc76339-2

Anthropogenic fire history and red oak forests in south-central Ontario

2000· article· en· W2126791719 on OpenAlexfundvenueaboutno aff
Daniel C. Dey, Richard P. Guyette

Bibliographic record

VenueThe Forestry Chronicle · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsnot available
FundersMinistry of Natural Resources
KeywordsEcologyGeographyFire regimeAbundance (ecology)ForestryDominance (genetics)Red pineEnvironmental scienceBiologyEcosystemPinus <genus>Botany

Abstract

fetched live from OpenAlex

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

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.194
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.001

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.

Opus teacher head0.007
GPT teacher head0.192
Teacher spread0.185 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations69
Published2000
Admission routes3
Has abstractyes

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