Diseases affecting livestock production mediate landscape scale of a changing pasture regime in Lake Mburo Conservation Area, Uganda
Bibliographic record
Abstract
This study investigated whether spatial disparities in pastoral herd sizes across rangelands from Lake Mburo National Park (LMNP) boundary was responsible for a changing pasture regime. A midst growing concern that cattle diseases associated with wild ungulates outside the protected areas impose limitations on pastoralist household income, the affected communities respond by overstocking as an adaption to disease risks. Therefore, increasing cattle stock holding among pastoralists living at the park boundary was suspected to be facilitating the disappearance of forests in Lake Mburo Conservation Area (LMCA). We applied ecosystem approach in a cross-sectional survey design to assess whether impact of diseases transmitted at the nexus of wildlife and livestock play intermediary role in the emerging spatial pattern of pasture regimes in LMCA. Paired sample t-test was used to examine the mean differences of animal populations between managed and unmanaged pasture and interpreted with Geo-eye satellite data of a typical landscape of savanna ecosystem of LMCA. The results revealed a significant difference (p < 0.05) in the distribution of wild species of animals between managed and unmanaged pasture. Spatial variation in population abundance of wild animals between distance zones was also reflected in the distribution of average household stockholding as well as cattle mortalities along a distance gradient from LMNP boundary. These findings could guide evidence based monitoring of long term effects of changing pasture regimes on pastoralist livelihood systems around LMCA. For example, future research should consider complementarities and overlap of the diets of wild ungulates and cattle at the nexus of wildlife and livestock interface. This will provide an understanding of how wildlife presence in rangelands can lead to either favorable or adverse changes in the fauna as far as the domestic livestock species of cattle and small ruminants are concerned.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".