Bushmeat and food security in the Congo Basin: linkages between wildlife and people's future
Why this work is in the frame
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Bibliographic record
Abstract
Tropical moist forests in Africa are concentrated in the Congo Basin. A variety of animals in these forests, in particular mammals, are hunted for their meat, termed bushmeat. This paper investigates current and future trends of bushmeat protein, and non-bushmeat protein supply, for inhabitants of the main Congo Basin countries. Since most bushmeat is derived from forest mammals, published extraction ( E ) and production ( P ) estimates of mammal populations were used to calculate the per person protein supplied by these. Current bushmeat protein supply may range from 30 g person −1 day −1 in the Democratic Republic of Congo, to 180 g person −1 day −1 in Gabon. Future bushmeat protein supplies were predicted for the next 50 years by employing current E : P ratios, and controlling for known deforestation and population growth rates. At current exploitation rates, bushmeat protein supply would drop 81% in all countries in less than 50 years; only three countries would be able to maintain a protein supply above the recommended daily requirement of 52 g person −1 day −1 . However, if bushmeat harvests were reduced to a sustainable level, all countries except Gabon would be dramatically affected by the loss of wild protein supply. The dependence on bushmeat protein is emphasized by the fact that four out of the five countries studied do not produce sufficient amounts of non-bushmeat protein to feed their populations. These findings imply that a significant number of forest mammals could become extinct relatively soon, and that protein malnutrition is likely to increase dramatically if food security in the region is not promptly resolved.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 it