Exploring the effects of forest management on tree diversity, community composition, population structure and carbon stocks in sudanian domain of Senegal, West Africa
Bibliographic record
Abstract
Human disturbances lead to forest degradation and a drastic reduction in forest area. In Africa, the most affected continent by this phenomenon, selective cutting of trees remains the main forest management strategy. However, the effects of management on biodiversity are insufficiently known, particularly in Africa. We investigated how forest management affects tree species diversity, composition, size structure and carbon biomass of mature and juvenile trees in the sudanian domain of Senegal by comparing unmanaged forests and three types of managed forests, while considering the disturbance level of each stand. We collected floristic data on five and fifteen unmanaged and managed forest stands, respectively. We calculated species richness, the Shannon-Wiener diversity Index (alpha, beta and gamma), as well as carbon stocks of trees for each forest stand. Then we fitted linear models to estimate the differences between forest types for each index. We also analyzed tree size structure and species composition of highly valuable species. In total, 26,009 mature and juvenile trees in 183 species were recorded. Our findings showed that management status and disturbance level affect tree species in different ways and that disturbance level explains a greater proportion of the variation in species diversity than management status. Considering alpha, beta and gamma diversity, we found no significant association between any of these metrics and management status, for either mature or juvenile trees. Disturbance level was only significantly associated with the gamma diversity of mature trees. Species composition of juvenile trees of highly valuable species was significantly associated with both management status and disturbance level, unlike mature tree species composition where the associations were not significant. The distribution of mature tree diameter forms an inverted J-shape for each management category and disturbance level. However, neither the median tree diameter nor the median absolute deviation presented significant differences as a function of management status or disturbance level. For carbon stocks, none of the differences observed by management status and disturbance level are statistically significant. Our findings indicated that forest management in the sudanian zone affects species composition more than diversity and that mature trees respond differently than juvenile trees. Disturbances more than forest management were the underlying process for biodiversity changes both in managed and unmanaged forests. These findings suggest a better protection of unmanaged forests, and also a development of specific conservation action plans for highly valuable species, especially for species that are threatened at national or global levels in order to minimize their risk of local extinction.
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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 | 0.000 | 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) | 0.000 | 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".