Land use, rangeland degradation and ecological changes in the southern Kalahari, Botswana
Bibliographic record
Abstract
Abstract Dual‐scale analyses assessing farm‐scale patterns of ecological change and landscape‐scale patterns of change in vegetation cover and animal distribution are presented from ecological transect studies away from waterpoints, regional remotely sensed analysis of vegetation cover and animal numbers across the southern Kalahari, Botswana. Bush encroachment is prevalent in semi‐arid sites where Acacia mellifera Benth. is widespread in communal areas and private ranches, showing that land tenure changes over the last 40 years have not avoided rangeland degradation. Herbaceous cover is dominated in intensively grazed areas by the annual grass Schmidtia kalahariensis Stent and in moderately grazed areas by the perennial grass Eragrostis lehmanniana Nees. Nutritious perennial grass species including Eragrostis pallens Hack. Ex Schinz remain prevalent in Wildlife Management Areas. Other ecological changes include the invasion of the exotic Prosopis glandulosa Torr. and dense stands of Rhigozum trichotomum Kuntze. in the arid southwest. Regional patterns of wildlife species show that the expansion of cattleposts and fenced ranches has led to large areas of low wildlife conservation value even in areas where cattle production is not practiced. Findings show the need for integrated landscape‐scale planning of land use if the ecological value and biodiversity of the southern Kalahari is to be retained.
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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".