Can small wildlife conservancies maintain genetically stable populations of large mammals? Evidence for increased genetic drift in geographically restricted populations of Cape buffalo in East Africa
Bibliographic record
Abstract
The Cape buffalo (Syncerus caffer caffer) is one of the dominant and most widespread herbivores in sub-Saharan Africa. High levels of genetic diversity and exceptionally low levels of population differentiation have been found in the Cape buffalo compared to other African savannah ungulates. Patterns of genetic variation reveal large effective population sizes and indicate that Cape buffalos have historically been interbreeding across considerable distances. Throughout much of its range, the Cape buffalo is now largely confined to protected areas due to habitat fragmentation and increasing human population densities, possibly resulting in genetic erosion. Ten buffalo populations in Kenya and Uganda were examined using seventeen microsatellite markers to assess the regional genetic structure and the effect of protected area size on measures of genetic diversity. Two nested levels of genetic structure were identified: a higher level partitioning populations into two clusters separated by the Victoria Nile and a lower level distinguishing seven genetic clusters, each defined by one or two study populations. Although relatively small geographic distances separate most of the study populations, the level of genetic differentiation found here is comparable to that among pan-African populations. Overall, correlations between conservancy area and indices of genetic diversity suggest buffalo populations inhabiting small parks are showing signs of genetic erosion, stressing the need for more active management of such populations. Our findings raise concerns about the future of other African savannah ungulates with lower population sizes and inferior dispersal capabilities compared with the buffalo.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| 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".