Allometric Equations for Estimation of Below-ground Biomass of Two Dominants Shrub Species of Burkina Faso
Bibliographic record
Abstract
Deforestation leads to a significant loss of carbon and contributes indirectly to climate change. This study was carried out in four types of formations in the Sudanian zone of Burkina Faso to assess the contribution of plant species to climate change mitigation. The below-ground biomass of two species (Piliostigma reticulatum and Guiera senegalensis) was determined by the direct method. Three classes of subjects were determined and a total of 80 shrubs of P. reticulatum and 90 shrubs of G. senegalensis were completely excavated. The results showed that P. reticulatum measures about 0.49 to 2.10 m in height, 3.58 to 25 cm in circumference at the base of the trunk and stores 0.18 to 3.68 tC/ha in the root biomass (respectively after 3 years and 15 years) for a 3x3m plantation. In the 15-year fallow dominated by G. senegalensis stands, 3.93 tC/ha are stored by the underground biomass of G. senegalensis shrubs. Model fit showed that there is a good correlation between circumference at the base of the trunk and below-ground biomass for P. reticulatum. For G. senegalensis, it is the total height of the foot that is most correlated with the below-ground biomass. These results provide information on the carbon sequestration potential of these two species, and can thus help in the decision-making process for climate change adaptation and/or mitigation policies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".