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Record W2096909893 · doi:10.1139/x03-114

Gap characteristics in relation to forest structure and implications for southern beech forest dynamics

2003· article· en· W2096909893 on OpenAlexvenueno aff
Jaime G. Cuevas

Bibliographic record

VenueCanadian Journal of Forest Research · 2003
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsnot available
FundersComisión Nacional de Investigación Científica y Tecnológica
KeywordsSeedlingAltitude (triangle)BeechForest dynamicsElevation (ballistics)NothofagusTransectBiologyEffects of high altitude on humansDipterocarpaceaeEcologyAtmospheric sciencesEnvironmental scienceBotanyMathematicsGeology

Abstract

fetched live from OpenAlex

Gap characteristics, as well as forest structure, were investigated in Nothofagus pumilio (Poepp. et Endl.) Krasser stands on two slopes in Tierra del Fuego to test the following hypotheses: (i) there exists an altitudinal decline in tree height and stem diameter, (ii) this should result in gaps of decreasing size and abundance towards the upper forest, and (iii) this, in turn, should result in a longer suppressed growth of seedlings near the treeline (that is, an older seedling bank). Mean tree height on both slopes decreased significantly with increasing altitude from 21 to 11 m and from 13 to 8 m. Mean stem diameter declined with increasing altitude from 50 to 28 cm and from 19 to 16 cm, but this trend was only significant on one slope analyzed. Gap frequency declined with increased elevation from 33 to only 3 in 2-km transects. Mean gap size also decreased significantly with increased elevation from 91 to 11 m 2 . Mean seedling age varied with altitude, but the expected relationship was significant only when gap frequency was controlled. The best-fit model indicates a negative correlation between altitude and tree height and stem diameter, which are positively correlated and act indirectly on gap frequency via gap size. Although restrictions on seedling growth caused by small and infrequent gaps do not seem to be stronger at upper forest elevations, they may produce a bottleneck in the life cycle of the species in the long term. This phenomenon could be overcome either through faster seedling growth and higher survival at the treeline or through an episodic regeneration, as other research has documented previously.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.924
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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)0.0000.000

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 head0.045
GPT teacher head0.300
Teacher spread0.256 · 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

Citations15
Published2003
Admission routes1
Has abstractyes

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