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Record W3017682767 · doi:10.1016/j.heliyon.2020.e03805

Aboveground biomass allocation, additive biomass and carbon sequestration models for Pterocarpus erinaceus Poir. in Burkina Faso

2020· article· en· W3017682767 on OpenAlexfundno aff
Moussa Ganamé, Philippe Bayen, Kangbéni Dimobe, Issaka Ouédraogo, Adjima Thiombiano

Bibliographic record

VenueHeliyon · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicForest ecology and management
Canadian institutionsnot available
FundersMinistry of Environment - Saskatchewan
KeywordsAllometryBiomass (ecology)Tree allometryCarbon sequestrationDiameter at breast heightEnvironmental scienceContext (archaeology)ForestryEcologyAgroforestryBiologyBiomass partitioningGeographyCarbon dioxide

Abstract

fetched live from OpenAlex

Efforts to develop allometric models for accurate estimation of biomass and carbon sequestration in Sub-Saharan African savanna ecosystems remain inconclusive. Most available allometric models are not site-specific, and hence do not account for the effects of regional climate variabilities on tree growth and capacity to sequester carbon. In contrast, site-specific biomass allometric models constitute a robust tool for forest and carbon emission management in the context of the reducing emissions from deforestation and degradation program (REDD+). Although site-specific models have been developed for several tropical tree species, such models do not exist for Pterocarpus erinaceus in Burkina Faso. In this study, we investigated biomass fraction patterns and used a system of additive allometric models for predicting aboveground biomass and carbon stocks of P. erinaceus components. Thirty P. erinaceus trees were destructively sampled to estimate the biomass of their stems, branches and leaves. The biomass fraction of each component was assessed and its relationship with tree diameter at breast height (dbh) examined. The best allometric equations of the tree components, selected from three non-linear models with dbh, height (ht) and crown diameter (C d ) as predictors, were combined to develop an additive allometric model, using the Seemingly Unrelated Regressions (SUR) method. The Ash method was then used to estimate the carbon content of the different components. Leaf and stem biomass fractions decreased when the dbh increased, whereas a reverse trend was observed for branch biomass. Dbh was the most correlated independent variable with all biomass components. AGB=e −3.46 (dbh) 1.62 +e −2.45 (dbh) 2.31 +e −2.68 (dbh) was the most appropriate additive allometric equation for estimating the biomass of P. erinaceus trees. The carbon content of the leaves, branches and stems was 55.73%, 56.68% and 56.23%, respectively. The developed allometric equations can be used to accurately estimate the aboveground biomass of P. erinaceus in the savannas of Burkina Faso and other similar ecosystems in Sub-Saharan Africa.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.423
Threshold uncertainty score0.499

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 head0.017
GPT teacher head0.231
Teacher spread0.215 · 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

Citations22
Published2020
Admission routes1
Has abstractyes

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