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Record W2016755120 · doi:10.1139/x10-242

Sapling age structure and growth series reveal a shift in recruitment dynamics of sugar maple and American beech over the last 40 years

2011· article· en· W2016755120 on OpenAlexaffvenueabout
Dominique Gravel, Marilou Beaudet, Christian Messier

Bibliographic record

VenueCanadian Journal of Forest Research · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicForest ecology and management
Canadian institutionsUniversité du Québec à RimouskiUniversité du Québec à Montréal
Fundersnot available
KeywordsBeechMapleYellow birchBiologyForest dynamicsStand developmentBotanyEcologyForestryGeography

Abstract

fetched live from OpenAlex

Northern hardwoods have undergone a marked change in their dynamics, with American beech ( Fagus grandifolia Ehrh.) increasing in abundance relative to sugar maple ( Acer saccharum Marsh.). This study aims to better understand this sudden shift in recruitment dynamics. We performed an extensive analysis of the age structure, radial growth pattern, and release history on >700 saplings from 34 mature maple–beech stands of southern Quebec. We found (i) that the sapling age structures showed a progressive decrease in the establishment of maple relative to beech starting about 40 years ago, (ii) a change in the species growth hierarchy that started in the 1980s due to increasing radial growth of beech, (iii) that this growth trend is negligible for both maple and beech when we account for size and suppression status, and finally (iv) that the growth trend appears to be independent of present soil conditions. These results contrast with previous studies conducted at the adult stage that reported a growth decline for maple. We conclude that this change in recruitment dynamics is not related to growth, and consequently, further studies investigating this phenomenon should concentrate on establishment and survival.

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 score0.281
Threshold uncertainty score0.559

Distilled classifier scores by category (both heads)

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

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 head0.032
GPT teacher head0.272
Teacher spread0.240 · 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

Citations31
Published2011
Admission routes3
Has abstractyes

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