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Record W2178598536 · doi:10.5539/jsd.v8n9p281

Agroecological Niches as Ecosystem-Based Adaptive Option to Environmental Change in the Forest-Savanna Transition Zone of Ghana

2015· article· en· W2178598536 on OpenAlexvenueno aff
Benjamin D. Ofori, Jesse Ayivor, Opoku Pabi, Christopher Gordon

Bibliographic record

VenueJournal of Sustainable Development · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Rural Development Research
Canadian institutionsnot available
Fundersnot available
KeywordsAgroecologyAgricultureFood securityAgroforestryProduction (economics)Adaptive strategiesGeographyEcosystemBusinessAgricultural economicsEcologyEnvironmental scienceEconomicsForestry

Abstract

fetched live from OpenAlex

<p>Generally, local farmers are able to adapt to environmental change (and developments in socio-economic conditions) by engaging in a range of creative practices of on-farm management, use of improved crop varieties and adoption of new technologies. However in the past few decades, there has been growing interest in other adaptive options with the potential of addressing household food security and the multiple dimensions of sustainable agriculture. This study therefore examined the use of niche environments in the agricultural landscape as ecosystem-based adaptive strategy to environmental change among 102 farmers of 9 fringe communities of the Kogyae Strict Nature Reserve of the forest-savanna transition zone in Ghana. The study noted the increasing shift from maize cultivation to rice production using marshy areas and low-lying parts of farm fields and farms. The farmers mentioned climatic, ecological and other socio-economic reasons for this trend. They cited growing insecurity associated with maize production due to changing rainfall pattern and reduction in rainfall amounts, and changes in land cover and soil conditions. Additionally, they emphasized the relative ease with which they are able to store rice and the willingness of padi buyers to visit the villages in spite of the poor nature of the roads. The study advocated for greater institutional support to boost local rice production in order to reduce the country’s heavy dependence on imports.</p>

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.705
Threshold uncertainty score0.184

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 head0.033
GPT teacher head0.240
Teacher spread0.206 · 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

Citations4
Published2015
Admission routes1
Has abstractyes

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