Trophy hunting in<scp>A</scp>frica: long‐term trends in antelope horn size
Bibliographic record
Abstract
Abstract Trophy hunting in ungulates may favour individuals with smaller horns. A decrease in horn/antler size may jeopardize the conservation potential of hunting areas, which would be a major concern inAfrica where hunting zones represent over half of the total area of protected lands. We investigated horn length trends of harvested male impalasAepyceros melampus, greater kudusTragelaphus strepsicerosand sable antelopesHippotragus niger, from 1974 to 2008 inMatetsiSafariArea,Zimbabwe. Horn length declined by 4% in impalas, partly because male harvest age decreased. In greater kudus, surprisingly, horn length increased by 14%, while mean age of harvested male greater kudus increased during the study period. Reduced hunting pressure on this species during the study may have allowed males to live longer and to grow longer horns before being harvested. Horn length declined by 6% in sable antelopes, independent of age, suggesting that trophy hunting selected male sable antelopes with smaller horns through time, provided that horn length is heritable. Hunting pressure and trophy value were higher for sable antelopes than for impalas and greater kudus. Accordingly, the decline of horn length in this species was more pronounced. More valuable trophy species, such as sable antelopes, require special attention because they may be exposed to higher hunting pressure, and are therefore more likely to experience a decrease in horn size.
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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".