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The structure and status of forest fragments outside protected areas in central Uganda

2009· article· en· W2033274370 on OpenAlexaff
Deborah Baranga, Colin A. Chapman, John Kasenene

Bibliographic record

VenueAfrican Journal of Ecology · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicConservation, Biodiversity, and Resource Management
Canadian institutionsMcGill University
FundersInternational Primate Protection League
KeywordsDeforestation (computer science)Basal areaForest structureAgroforestryGeographyForestryHabitatTree canopyHigh forestCanopyEcologyEnvironmental scienceBiology

Abstract

fetched live from OpenAlex

Abstract Given the extent of tropical forest deforestation and as a number of conservation programmes and local communities rely on forest fragments, it has become important to understand how fragment exploitation by local communities affects forest structure and function. The effects of forest exploitation on forest structure and status of forest fragments were investigated in 20 nonreserved forest fragments in central Uganda. Enumeration of plots showed that tree species composition of the forest fragments was 60.0%, 23.7% and 6.3% for under‐storey, middle and top canopy trees respectively. The major activity was fuel wood extraction (65%), followed by brick making (10%), cultivation and livestock paddocks (10%), charcoal burning (5%), local brew distillation and others (5%). These extractive processes caused drastic structural changes, habitat degradation and destruction. Tree stumps enumeration indicated that under storey trees formed the highest proportion for wood extraction. There was no significant difference in the level of forest exploitation (basal area loss) among forest patches of varying sizes.

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 score0.004
Threshold uncertainty score0.141

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)0.0000.000

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 head0.006
GPT teacher head0.189
Teacher spread0.183 · 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

Citations14
Published2009
Admission routes1
Has abstractyes

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