Stand Structure, Allometric Equations, Biomass and Carbon Sequestration Capacity of <i>Acacia mangium</i> Wild. (Mimosaceae) in Côte d’Ivoire
Bibliographic record
Abstract
In addition to bioenergy production, Acacia magium, a fast growing species, plays a major role in climate change mitigation through carbon sequestration from the atmosphere. The objective of this study was to improve estimates of aboveground biomass of 3, 7 and 11 years old stands of Acacia mangium set up through natural regeneration at Anguédédou in C?te d’Ivoire. Tree measurements were done in circular plots of 615 m2 located at the center of each stand. 24 trees of circumference at breast height (cbh) between 31 and 116 cm were felled, weighed and measured. Multiple linear regressions were used to develop allometric equations linking aboveground biomass of trees to cbh and/or height. The carbon stock and sequestration capacity of each stand was assessed using these predictive models. The average cbh was 39.4 cm, 73.5 cm and 91.4 cm respectively for 3, 7 and 11 years old stands with a density ranging between 845 trees·ha-1 and 553 trees·ha-1. The allometric equations for biomass estimation were Btotal aboveground = exp(-3.455 + 2.081 × ln(C)), Btrunk = exp (-5.153 + 1.681 × ln(C) + 1.056 × ln(H)), Bbranches = exp(-2.005 + 0.498 × ln(C2 × H)), Bleaves = exp(-2.415 + 1.339 × ln(C)). Total height had no influence on total and leaf biomass but increased precision of trunk and branch biomass. The carbon sequestration capacity of aboveground biomass was highest in Acacia mangium stand of 7 years old with 45.14 teqCO2·ha-1·year-1 and lowest in the 3-year stand with 33.90 teqCO2·ha-1·year-1.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".