Botswana’s wildlife losing ground as Kalahari Wildlife Management Areas (WMAs) are dezoned for livestock expansion
Bibliographic record
Abstract
Abstract Botswana is rightfully lauded for maintaining 42% of its land base for conservation, and ranking top in the world for effort to conserve megafauna. Yet during the recent preservationist political climate characterized by a hunting moratorium and deterioration of CBNRM, changes to the national land use map suggest Botswana is losing grip on its lofty status. While conservation attention is turned to elephants and KAZA, discussion about the official dezoning of 8,268 km 2 of free-ranging wildlife estate in the Kalahari ecosystem has been notably absent. Using track-based methods we quantified wildlife populations inhabiting this relinquished wilderness now awaiting imminent conversion to fenced and private livestock holdings. We find that the affected areas contain approximately 3,900 free-ranging large herbivores and 50 large carnivores, all of which will become consumed, displaced or potential conflict animals. Erstwhile publicly-owned wildlife particularly important for local communities will effectively become de facto private property for an elite minority. The land use changes spell negative consequences for wildlife not only via mechanisms of habitat loss and edge effects but also reduced landscape connectivity between protected areas that limits seasonal movements and gene flow thus eroding long-term population resilience in a drought-prone environment. As Botswana’s agricultural lobby continues to exert pressure on the Kalahari ecosystem, we suggest that ground surveys conducted by Kalahari trackers be implemented to inform decision-making rather than relying on the inadequate coarse-grained aerial survey record only.
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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".