Evaluation of assisted natural regeneration and stored carbon in Prioria balsamifera (Vermoesen) Bretteler plots of the Luki Biosphere Reserve in Central Kongo, Democratic Republic of Congo
Bibliographic record
Abstract
Extensive programs of enrichment through natural assisted regeneration were implemented between 1946 and 1959 by INEAC (Institute National pour étude Agronomique du Congo belge). He has conducted several studies for the implementation of silvicultural techniques in tropical environments, particularly in the Luki Biosphere Reserve (RBL) in the DRC. The Prioria balsamifera natural assisted regeneration (RNA) plots were part of the various silvicultural treatments implemented between 1956 and 1962 after clear-cutting. Five decades after their establishment, no evaluation has been undertaken. The objective of this study is to evaluate the natural assisted regeneration in the P. balsamifera plots and to account for the carbon sequestered in the P. balsamifera RNA after clear-cutting. The methodological approach to floristic, dendrometric and allometric inventories was used to determine the specific richness and diversity of the different study plots and to account for the carbon of the RNA biomass of the fifteen sampling plots of 0,25 ha each at three sites: Camp1; Camp2 and the RBL Post. The study revealed a higher density per hectare in the Camp1 plot, almost double the last two plots of the sampling. The density / ha varied between 380 to 980 stems / ha. The same trend was observed on the basal area (m2 / ha). This varied between 43 and 68 m2 / ha. The Shannon index used for the analysis of wealth and specific diversity varied between 0.8 and 1.6. The Camp1 plot showed little diversity compared to other plots of sampling. The mean téq CO2 / ha values in our fifteen sample plots (Camp1, amp2, RBL station) are estimated to be 1793.96 téq CO2 / ha, 985.28 teqCO2 / ha and 1305.8 téq CO2 / ha respectively for the three plots.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".