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Record W2129067507 · doi:10.1111/btp.12218

Age‐related Crown Thinning in Tropical Forest Trees

2015· article· en· W2129067507 on OpenAlexafffund
Eadaoin Maria Ines Quinn, Sean C. Thomas

Bibliographic record

VenueBiotropica · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaSmithsonian Tropical Research Institute
KeywordsLianaCanopyCrown (dentistry)UnderstoryBiologyThinningDiameter at breast heightForest dynamicsTemperate rainforestEcologyTree canopyForestryGeographyEcosystem

Abstract

fetched live from OpenAlex

Abstract Gap dynamics theory proposes that treefall gaps provide high light levels needed for regeneration in the understory, and by increasing heterogeneity in the light environment allow light‐demanding tree species to persist in the community. Recent studies have demonstrated age‐related declines in leaf area index of individual temperate trees, highlighting a mechanism for gradual changes in the forest canopy that may also be an important, but less obvious, driver of forest dynamics. We assessed the prevalence of age‐related crown thinning among 12 tropical canopy tree species sampled in lowland forests in Panama and Puerto Rico (total N = 881). Canopy gap fraction of individual canopy tree crowns was positively related to stem diameter at 1.3 m (diameter at breast height) in a pooled analysis, with 10 of 12 species showing a positive trend. Considered individually, a positive correlation between stem diameter and canopy gap fraction was statistically significant in 4 of 12 species, all of which were large‐statured canopy to emergent species: Beilschmiedia pendula, Ceiba pentandra, Jacaranda copaia, and Prioria copaifera . Pooled analyses also showed a negative relationship between liana abundance and canopy gap fraction, suggesting that lianas could be partially obscuring age‐related crown thinning. We conclude that age‐related crown thinning occurs in tropical forests, and could thus influence patterns of tree regeneration and tropical forest community dynamics.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.735

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)0.0000.001

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 head0.018
GPT teacher head0.243
Teacher spread0.225 · 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.

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

Citations5
Published2015
Admission routes2
Has abstractyes

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