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Record W2127876815 · doi:10.1139/x01-079

A 400-year history of fire and oak recruitment in an old-growth oak forest in western Maryland, U.S.A.

2001· article· en· W2127876815 on OpenAlexvenueno aff
Durland L. Shumway, Marc D. Abrams, Charles M. Ruffner

Bibliographic record

VenueCanadian Journal of Forest Research · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsnot available
Fundersnot available
KeywordsFire historyGeographyBasal areaForestryRidgeDendrochronologyFire ecologyArchaeologyEcologyBiologyClimate changeCartographyEcosystem

Abstract

fetched live from OpenAlex

We document the fire history and associated ecological changes of an old-growth forest stand in western Maryland, U.S.A. The study area is located on the side slopes of a ridge system (Savage Mountain). Twenty basal cross sections were obtained from old trees cut in 1986, which provided evidence of 42 fires from 1615 to 1958. Nine fires were recorded in the sample trees in the 17th century, 13 in the 18th century, 12 in the 19th century, and eight in the early to mid-20th century. However, there were no major fire years after 1930. The Weibull modal fire interval was 7.6 years. Oaks recruited consistently from the early 1600s to the early 1900s, but there was increased Acer rubrum L. and Betula lenta L. recruitment with fire suppression after 1930. Species recruitment patterns and long-term fire history reported in this study offer important direct support for the hypothesis that periodic fire played an important role in the historical development and perpetuation of oak forests of the mid-Atlantic region before and after European settlement.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.083
Threshold uncertainty score0.165

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.056
GPT teacher head0.292
Teacher spread0.236 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations153
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Forest ResearchSame topicFire effects on ecosystemsFrench-language works237,207