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Record W7162073043 · doi:10.82308/831

Ecology of American beech and sugar maple in an old-growth forest

2002· dissertation· en· W7162073043 on OpenAlexaboutno aff
Ken Arii

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsnot available
Fundersnot available
KeywordsEdaphicBeechInterspecific competitionFagaceaeForest dynamicsYellow birchDisturbance (geology)Fagus sylvaticaAceraceae

Abstract

fetched live from OpenAlex

The dynamics in Fagus-Acer forest have been frequently investigated, a particular interest being the replacement patterns and coexistence of the two dominant species, Fagus grandifolia Ehrh. and Acer saccharum Marsh. This thesis examines whether the community pattern and dynamics in a Fagus-Acer forest at Mont. St. Hilaire, Quebec, are consistent with predictions made by the disturbance hypothesis. This conceptual model explains the mechanisms underlying the coexistence and replacement patterns of the two dominant species. While the hypothesis suggests disturbance frequency and interspecific differences in growth under variable light conditions to be the key factors that determine the dynamics in Fagus-Acer forests, I demonstrate that edaphic factors and regeneration of Fagus by root sprouts can also play a significant role. Based on the findings, I propose an alternative model for the coexistence and replacement patterns in Fagus-Acer forest to better account for the influence of edaphic factors and of Fagus root sprouts.

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 score0.375
Threshold uncertainty score0.746

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.006
GPT teacher head0.236
Teacher spread0.230 · 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

Citations0
Published2002
Admission routes1
Has abstractyes

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