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Record W4406288043 · doi:10.70880/001c.128231

Effect of Stand Density on Growth and Allometry of Marri (<i>Corymbia Calophylla</i>) in the High Rainfall Zone of Southwest Western Australia

2023· article· en· W4406288043 on OpenAlexaff
Shes Kanta Bhandari, Erik J. Veneklaas, W. L. McCaw, Richard Mazanec, Michael Renton

Bibliographic record

VenueJournal of the Royal Society of Western Australia · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPasture and Agricultural Systems
Canadian institutionsUniversity of Alberta
FundersSwan River Trust
KeywordsAllometryBiologyGeographyEcology

Abstract

fetched live from OpenAlex

Marri ( Corymbia calophylla ), an endemic and keystone tree species of southwest Western Australia (SWWA), provides significant environmental, conservation, economic and cultural values. This study aims to analyse the effect of stand density, manipulated through thinning, on growth and allometry of marri-dominated forest. Although individual tree diameter (DHBUB, diameter at breast height under bark), basal area, height and crown-width (CW) growth was stimulated by thinning, stand basal-area growth was highest in denser (less thinned) stands. Stand density had a significant effect on the allometry between DBHUB and each of height and height-diameter ratio (HDR). Height and CW increased with an increase in DBHUB although the relationship with CW was not statistically significant; HDR was inversely related to DBHUB. Thinning has the potential to increase yields of merchantable timber, firewood, and enhance ecological values including tree hollows for arboreal fauna and marri-fruit production (important for cockatoos) that depend on retention of sufficient large old trees. Reduction of stand density through thinning reduces inter-tree competition and may help in reducing the risk of marri canker disease.

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)0.000
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 score0.133
Threshold uncertainty score0.441

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.021
GPT teacher head0.250
Teacher spread0.229 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

Explore more

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