Farmer–African wild dog (<i>Lycaon pictus</i>) relations in the eastern Kalahari region of Botswana
Bibliographic record
Abstract
African wild dogs (Lycaon pictus) are the most endangered large carnivores in southern Africa. Direct and indirect persecution by farmers causes significant conservation challenges. Farmer– wild dog conflict in Botswana commonly occurs as a result of cattle and stocked game depredation by wild dogs, affecting farmer livelihood and causing economic and emotional distress. Although wild dogs predate livestock at lower levels than other carnivores, they continue to be killed both indiscriminately and in retaliation for incidents of depredation. Investigating farmer–wild dog conflict is a necessary step towards establishing appropriate conflict mitigation strategies. Eighty livestock and game farmers were interviewed in order to examine farmers’ value of, perceptions of and experiences with wild dogs as well as their insights on wild dog impacts and conservation in the eastern Kalahari region of Botswana. Interviews were semi-structured and used open-ended questions to capture complexities surrounding farmer–wild dog relations. This research contributes baseline data on wild dogs in understudied tribal land and commercial livestock and game farms in eastern Kalahari. It confirms the presence of wild dogs, livestock and stocked game depredation by wild dogs and negative perspectives amongst farmers towards wild dogs and their conservation. Mean losses were 0.85 livestock per subsistence farmer, 1.25 livestock per commercial livestock farmer, while game farmers lost 95.88 game animals per farmer during January 2012 through June 2013. Proportionally, more subsistence farmers than commercial livestock farmers and game farmers held negative perspectives of wild dogs (χ ² = 9.63, df = 2, p < 0.05). Farmer type, education level, socioeconomic status and land tenure, as well as positive wild dog characteristics should be considered when planning and operationalising conflict mitigation strategies. As such, conservation approaches should focus on conservation education schemes, improved wild prey base for wild dogs, poverty alleviation, and community engagement in order to offer long-term opportunities for addressing farmer–wild dog conflict in Botswana.Conservation implications: Our research contributes to wild dog conservation in Botswana by confirming the presence of wild dogs and the occurrence of livestock and stocked game depredation in previously understudied tribal land and commercial livestock and game farms in eastern Kalahari. To improve predominately negative perceptions of wild dogs and reduce conflict, practitioners should focus their efforts on conservation education schemes, improved wild prey base for wild dogs, poverty alleviation, and community engagement.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".