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The role of area enclosures and fallow age in the restoration of plant diversity in northern Ethiopia

2006· article· en· W1985342539 on OpenAlexaff
Muluberhan Hailu Abebe, Gufu Oba, Ayana Angassa, Robert B. Weladji

Bibliographic record

VenueAfrican Journal of Ecology · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicRangeland Management and Livestock Ecology
Canadian institutionsCentre de Recherche Industrielle du QuébecNatural Sciences and Engineering Research Council of Canada
FundersSveriges Lantbruksuniversitet
KeywordsSpecies richnessForbSoil seed bankBiodiversityRangelandEcological successionSpecies diversityHerbaceous plantRestoration ecologyEcologyBiologyGeographyAgroforestryAgronomyGrasslandGermination

Abstract

fetched live from OpenAlex

Abstract This study investigated the roles played by area enclosures and fallow age in the restoration of plant species richness and soil seed bank species richness in degraded mountain rangelands in northern Ethiopia. Management types (enclosures versus grazed) influenced woody and herbaceous species richness, while fallow age showed no effect on the woody species. Management, age and the doubling of fallow age influenced the herbaceous species richness and species diversity. Management showed no effect on soil seed bank species richness. Fallow age and the doubling of fallow time also showed no influence on the soil seed bank of grass species, but they were influential on the forbs species soil seed bank. The trends for restoration of plant species richness and diversity and grass seed bank in response to fallow age were positive‐linear, but they declined when the fallow ages were doubled. The exception was the forbs seed bank showed linear trends when age of restoration was doubled. The data suggest that the restoration of degraded rangelands in the high mountain zones of northern Ethiopia was still in the weedy succession stages. Long‐term monitoring will be required to gain an informed understanding of the roles played by area enclosures and fallow age in the restoration of plant biodiversity.

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 score0.200
Threshold uncertainty score0.814

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.008
GPT teacher head0.184
Teacher spread0.176 · 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

Citations66
Published2006
Admission routes1
Has abstractyes

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