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Record W1976333825 · doi:10.1093/forestry/cpu026

Changes in the tree and shrub layer of Wytham Woods (Southern England) 1974–2012: local and national trends compared

2014· article· en· W1976333825 on OpenAlexaff
K. J. Kirby, Dawn R. Bazely, E. A. Goldberg, Jeanette Hall, R. Isted, Suzy Perry, R.C. Thomas

Bibliographic record

VenueForestry An International Journal of Forest Research · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicForest Ecology and Biodiversity Studies
Canadian institutionsYork University
Fundersnot available
KeywordsShrubWoodlandFraxinusEcological successionBasal areaAcer pseudoplatanusDisturbance (geology)National parkForestryGeographyCanopyQuercus roburEcologyAgroforestryEnvironmental scienceBiology

Abstract

fetched live from OpenAlex

Changes in the woody composition of Wytham Woods since 1974 are described, related to national trends in broadleaved woodland, and used to suggest the impact of future changes such as from ash dieback disease (Chalara fraxinea). Data on the tree and shrub layer from 164 permanent 10 × 10 m plots distributed in a grid across the Woods are presented from 1974, 1991, 1999 and 2012, on species occurrence, regeneration, contribution to the canopy and basal area. Variations in the current and past composition and structure of the Woods are related to past forestry management and natural succession/disturbance processes. These largely mirror changes shown by other surveys at a national level. Fraxinus excelsior has been increasing in prominence across the Woods since 1974, but its future is uncertain because of disease. The species most likely to increase if there is a severe decline in F. excelsior at Wytham appear to be Acer pseudoplatanus, Corylus avellana and Quercus robur. There are benefits from linking long-term studies at one site to wider less detailed surveys in order to explore the general applicability of the results.

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)0.002
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 score0.022
Threshold uncertainty score0.553

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.078
GPT teacher head0.326
Teacher spread0.248 · 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

Citations36
Published2014
Admission routes1
Has abstractyes

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