Conservation Status of the African Buffalo: A Continent-Wide Assessment
Bibliographic record
Abstract
This chapter presents the distribution, abundance patterns and trends of African buffalo in the 38 countries of its distribution area based on recent aerial and ground census data and feedback from field experts. For the period 2001–2021, we collected abundance data from 163 protected areas or complexes of protected areas and presence data from 711 localities. The savanna buffalo population is estimated in 2022 at over 564,000 individuals, after deduction of the 75,000 buffalo under intensive private management in South Africa. Its abundance is roughly equivalent to that estimated 25 years ago (625,000). The subspecies conservation status is highly unbalanced. The Cape buffalo is by far the most abundant, representing 90 per cent of the total estimated population (510,000 individuals). The West and Central subspecies respectively represent 4 and 6 per cent (>20,000 individuals and >34,000 individuals). The conservation status of the Central African savanna buffalo, whose abundance has been nearly halved over the last 25 years, is worrisome, with exception of the steadily increasing populations of Zakouma NP (Chad) and Garamba NP (DRC). Estimating the abundance of forest buffalo is challenging, as is establishing a trend. Our investigations showed that the forest buffalo is still well represented in Central Africa in areas with low human density. The forest buffalo’s most important stronghold in Central Africa is probably the Greater TRIDOM/TNS (Tri-National Dja-Odzala-Minkébé / Trinational Sangha), a vast contiguous block of mainly pristine moist forest covering 250,000 km2 and straddling Cameroon, Congo, Gabon and Central African Republic (11 per cent of the Central African forest block). In West Africa, we obtained very little information on the presence of the forest buffalo in the residual forest block, suggesting that the conservation status of the forest buffalo in this region is very worrisome.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".