Movement and Occurrence of Two Elephant Herds in a Human-Dominated Landscape, the Bénoué Wildlife Conservation Area, Cameroon
Bibliographic record
Abstract
Increasing human settlement and disturbance adjacent to protected areas have intensified competition between people and wildlife for resources and living space. In northern Cameroon, over 60,000 people live in villages surrounding Bénoué National Park. In that same area, as in other parts of Africa, savanna elephants damage crops, homes, water provision infrastructures, and grain stores. Using almost 1000 satellite-derived positions for two matriarch female elephants from 2007 to 2009, movement patterns were analyzed with respect to a highway, secondary roads, unpaved park roads, rivers, and villages through the use of log linear modeling. More than half of all locations and core areas occurred outside the park, while seasonal and individual differences in home range size and distribution were found within the protected area. Elephant occurrence within approximately 7 to 9 km of villages showed a decreasing trend with proximity. The highway appeared to act as a barrier to movement for one elephant herd, while the other did not come within 11 km of it. On the other hand, elephants remained close to the Bénoué River and secondary roads. Our findings show that in the Bénoué Wildlife Conservation Area, perennial water availability and human disturbance from the presence of villages can influence elephant spatial distribution in the protected area, and overlap of villages with elephant home range indicates a high potential for human-elephant conflict. This highlights the need for more effective land use planning to reduce such conflict and for additional research into movement patterns of the Bénoué National Park elephant population.
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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 | 0.001 |
| 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".