Vulnerability of African Rosewood (Pterocarpus erinaceus, Fabaceae) natural stands to climate change and implications for silviculture in West Africa
Bibliographic record
Abstract
Pterocarpus erinaceus is a native tree species of the Guineo-Sudanian and Sudano-Sahelian zones where natural stands are under constant pressure and heavily exploited for timber, animal feeding and others uses. A part from the overexploitation, climate change could also become a serious threat to the species natural distribution. For that purposes, this study aims to assess the vulnerability of P. erinaceus potential niche to climate change within its natural distribution area in West Africa. Niche predictions are based on 6,981 natural occurrence of the species and 19 global bioclimatic variables available through WorldClim. The future niche of the species is predicted according to three concentration pathways (RCPs 2.6, 4.5 and 8.5) of BC model for 2050 and 2070, thanks to Maxent software. P. erinaceus is currently reported from Senegal to Cameroon. Its potential niche covers the Sudano-Sahelian zone and the Dahomey gap on approximately 17.42% of the total area of these countries. In general, the niche of the species is not sensitive to climate change, regardless of the climate scenario and the year. Compared to its initial niche, the niche of the species will increase from 22.33% to 43.61% in 2050 and from 27.12% to 53.61% in 2070. However, this ecological expansion observed mainly in the Gulf of Guinea, will be associated with a considerable decrease in the Sahel and central Nigeria. This study shows the importance of promoting the development of innovative silvicultural strategies for the extension and restoration of natural stands of P. erinaceus in order to meet sustainably the timber needs of the West African region. It helps also to strengthening the roles of natural forests in providing ecosystem services and mitigating climate change effects.
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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".