Challenges faced in the conservation of rare antelope: a case study on the northern basalt plains of the Kruger National Park
Bibliographic record
Abstract
The conservation of rare antelope has long been one of the goals of the Kruger National Park. The roan antelope Hippotragus equinus, and to a lesser extent the tsessebe Damaliscus lunatus, represent low-density species or rare antelope in the park. Specific management approaches representing the older equilibrium approach, have been employed to conserve these antelope. Of these, the supply of artificial water over many decades was the most resource intensive. The sudden, severe drop in the roan antelope population towards the end of the 1980s was unexpected and, retrospectively, attributed to the development of a high density of perennial waterpoints. The postulated mechanism was that the perennial presence of water allowed Burchell’s zebra Equus burchelli to stay permanently in an area that was previously only seasonally accessible. The combined effect of a long, dry climatic cycle, high numbers of zebra and their associated predators was proposed to be the cause of this decline. As part of the new nature evolving or ecosystem resilience approach, twelve artificial waterpoints were closed in the prime roan antelope habitat in 1994 in an attempt to move the zebra out of this area. The zebra numbers declined as the rainfall increased. Closure of waterholes clearly led to redistribution of zebra numbers on the northern plains, zebra tending to avoid areas within several kilometres of closed waterpoints. However, at a larger scale, regional densities appeared similar in areas with and without closed waterpoints. There was an initial drop in the lion numbers in 1995, after which they stabilised. In spite of an improvement in the grass species composition and an increase in biomass the roan antelope population did not increase. The complexity of maintaining a population at the edge of their distribution and the problems associated with the conservation of such populations are discussed in terms of management options and monitoring approaches that may be employed in this process.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".