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Record W2626050925 · doi:10.1111/aje.12427

Effects of anthropogenic disturbance on tree population structure and diversity of a rain forest biosphere reserve in Ghana, West Africa

2017· article· en· W2626050925 on OpenAlexaff
Emmanuel Morgan Attua, Louis Awanyo, Effah Kwabena Antwi

Bibliographic record

VenueAfrican Journal of Ecology · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsSpecies richnessEcologyDisturbance (geology)Abundance (ecology)Basal areaBiodiversityGeographyNature reserveBiosphereSpecies diversityIntermediate Disturbance HypothesisDiameter at breast heightForestryPopulationEnvironmental scienceBiology

Abstract

fetched live from OpenAlex

Abstract We evaluated the impacts of anthropogenic disturbance on community structure and diversity along three management zones of the Bia biosphere reserve in Ghana. Sixty sample plots were distributed among the core, buffer and transition zones. We estimated the degree of disturbances from discernible indicators on the field and satellite images. All tree species ≥10 cm dbh (diameter at breast height) were identified and enumerated. Inventory data were compared across the zones and related to intensity of disturbances. A total of 1176 individual trees from 108 species and 33 families were encountered. Number of species varied from 27 in the highly disturbed ( HD ) to 61 in the least disturbed ( LD ) zone. Mean basal area ( BA ) varied from 11.71 in the HD to 28.26 in the LD . Both Margalef's species richness and Shannon‐Weiner's α‐diversity were highest in the moderately disturbed ( MD ) than either the least and most disturbed zones. Our study revealed significant differences in tree abundance, stem density, BA and species diversity, attributable to differences in degree of anthropogenic disturbances among zones. Given the different levels of anthropogenic disturbance and corresponding impacts across the reserve, we recommend an integrated management strategy for the conservation of biodiversity in the Bia biosphere reserve.

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 score0.032
Threshold uncertainty score0.986

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 studies0.0000.001
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 head0.008
GPT teacher head0.227
Teacher spread0.219 · 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

Citations11
Published2017
Admission routes1
Has abstractyes

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