Reflecting on research produced after more than 60 years of exclosures in the Kruger National Park
Bibliographic record
Abstract
Herbivores are a main driver of ecosystem patterns and processes in semi-arid savannas, with their effects clearly observed when they are excluded from landscapes. Starting in the 1960s, various herbivore exclosures have been erected in the Kruger National Park (KNP), for research and management purposes. These exclosures vary from very small (1 m2) to relatively large (almost 900 ha), from short-term (single growing season) to long-term (e.g. some of the exclosures were erected more than 60 years ago), and are located on different geologies and across a rainfall gradient. We provide a summary of the history and specifications of various exclosures. This is followed by a systematic overview of mostly peer-reviewed literature resulting from using KNP exclosures as research sites. These 75 articles cover research on soils, vegetation dynamics, herbivore exclusion on other faunal groups and disease. We provide general patterns and mechanisms in a synthesis section, and end with recommendations to increase research outputs and productivity for future exclosure experiments.Conservation Implications: Herbivore exclosures in the KNP have become global research platforms, that have helped in the training of ecologists, veterinarians and field biologists, and have provided valuable insights into savanna dynamics that would otherwise have been hard to gain. In an age of dwindling conservation funding, we make the case for the value added by exclosures and make recommendations for their continued use as learning tools in complex African savannas.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".