A floristic description and utilisation of two home ranges by vervet monkeys in Loskop Dam Nature Reserve, South Africa
Bibliographic record
Abstract
The plant communities occurring in the home ranges of two vervet monkey (Chlorocebus aethiops) troops (referred to as the Donga and Picnic troops) were investigated as part of a comprehensive research project on the spatial and temporal patterns in resource dispersion or distribution and range use. From two-way indicator species analysis (TWINSPAN) multivariate classifications refined by Braun-Blanquet procedures, seven plant communities that can be placed into three major groups were identified in the home range of the Donga troop, and eight plant communities that can be placed into four major groups were identified in the home range of the Picnic troop. Classifications and descriptions of the major groups, including vegetation maps, are presented. Diagnostic as well as prominent species of tree, shrub, forb and grass strata are outlined. Ordinations and floristic analyses were undertaken for the two home ranges to highlight vegetative differences between the areas. The phenology of vervet resources and the available resource energy were determined as a basis for the comprehensive study.Conservation implications: This vegetation description and phenology provide valuable information on the utilisation of home ranges by vervets and demonstrate how various management applications can affect the home range dependence of troops.
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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 | 0.001 |
| 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".