Woody Vegetation Utilisation in Tembe Elephant Park, Kwazulu-Natal, South Africa
Bibliographic record
Abstract
A survey of woody plant species utilisation by large (excluding elephants), medium and small browsers,man and “natural damage”, was conducted in nine vegetation units of Tembe Elephant Park, KwaZulu-Natal, South Africa. Woody species use and canopy removal were evaluated within two age ranges, (a) recent, ? 12 months prior to study and (b) old, > 12 months prior to the study. The results show that recent canopy removal by medium and small browsers was intensive and generally represented one third of height classes available to the agents which were consistently used withinall vegetation types. The overall utilisation pattern indicated that medium and small browsers may be removing the regeneration classof the woody plants layer. Natural damage was found to be considerable and it was hypothesized that it may be linked and possibly amplified by prior elephant utilisation. In conclusion, it is possible to suggest that the regular use of the sapling level by small and medium browsers could promote woodland to grassland retrogression, as was found in east Africa under high densities of animals.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.001 | 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".