Developmental Dynamics of Gilbertiodendron dewevrei (Fabaceae) Drive Forest Structure and Biomass in the Eastern Congo Basin
Bibliographic record
Abstract
Patterns of structural change associated with monodominant tropical forest complexes have remained enigmatic for decades. Here, we extend previous efforts in presenting a longitudinal, local-scale analysis of forest dynamics in central Africa. Using four 10-ha census plots measured across three time periods (959,312 stems ≥1 cm DBH), we analyzed changes in a number of biometrical attributes for four distinct forest types capturing the developmental gradient from mixed species forest to Gilbertiodendron dewevrei-dominated forest. We modeled above-ground biomass (AGB), basal area (BA), and stem density across all species, and diameter at breast height (DBH), recruitment, and mortality for Gilbertiodendron dewevrei. We hypothesized that trends in these attributes are consistent with a slow spread of Gilbertiodendron dewevrei into adjacent mixed species forest. We identified statistically significant increases in AGB and BA across sites and positive, though nonsignificant, increases in AGB and BA for most forest types. DBH and relative recruitment increased significantly for Gilbertiodendron dewevrei stems, while relative mortality did not. When looking from mixed species to transitional to monodominant forest types, we found a statistically significant pattern of developmental aggradation and net expansion of monodominant forest. We do not attribute this to atmospheric forcing but to a combination of (a) landscape-scale recovery or response to widespread disturbance (primarily historical fires), (b) Gilbertiodendron dewevrei’s ectomycorrhizal association, and (c) Gilbertiodendron dewevrei’s exceptional stress tolerance traits.
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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 | 0.000 |
| 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".