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Record W2586880078 · doi:10.1139/cjfr-2016-0497

Variation in fuelwood properties and correlations of fuelwood properties with wood density and growth in five tree and shrub species in Niger

2017· article· en· W2586880078 on OpenAlexvenueno aff
Carmen Sotelo Montes, John C. Weber, Tougiani Abasse, Dimas A. Silva, Sandra Lúcia Soares Mayer, Carlos Roberto Sanquetta, Graciela Inês Bolzón de Muñiz, R. Á. Garcia

Bibliographic record

VenueCanadian Journal of Forest Research · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAfrican Botany and Ecology Studies
Canadian institutionsnot available
FundersInternational Fund for Agricultural DevelopmentUniversidade Federal do Paraná
KeywordsShrubEnvironmental scienceSoil waterHeat of combustionBulk densityAfforestationWater contentForestryAgroforestryBotanyAgronomyBiologyGeographySoil scienceChemistry

Abstract

fetched live from OpenAlex

Information about variation and correlations of fuelwood properties and growth is needed in order to recommend species and sites for fuelwood production in a changing climate in Africa. We investigated the effects of site variables (land use, soil, terrain), geographical coordinates, and mean annual rainfall on fuelwood properties (volatile matter, fixed carbon, ash content, moisture content, gross calorific value, gross calorific value per cubic metre, and fuel value index) of Combretum glutinosum Perr., Combretum micranthum G. Don., Combretum nigricans Lepr. ex Guill. & Perr., Guiera senegalensis J.F. Gmel., and Piliostigma reticulatum (DC.) Hochst. and correlations of fuelwood properties with wood density and growth (height, stem diameter, and ring width) in Niger. We hypothesized that wood density, fixed carbon, and gross calorific value were positively correlated with one another and that fixed carbon and gross calorific value were positively correlated with growth. Most effects of site variables, geographical coordinates, and mean annual rainfall on fuelwood properties differed among species. Fuel value index was greater on rocky soils than on sandy soils. Wood moisture content of three species was greater in drier locations than in more humid ones. Correlations of fuelwood properties with wood density and growth differed among species. Based on this and previous research, we recommend parkland agroforests and sites with rocky soils and higher mean annual rainfall for fuelwood production.

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)0.001
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 score0.885
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.074
GPT teacher head0.238
Teacher spread0.165 · 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

Citations7
Published2017
Admission routes1
Has abstractyes

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