The Rhinoceros Relocation Mystery: Unraveling the Determinants of Habitat Use and Conservation Threats of Translocated Population in Nepal
Bibliographic record
Abstract
Due to the rapid decline of the Rhinoceros unicornis population during the 1960s, the Government of Nepal implemented several conservation measures, including translocation programs to various protected areas within the country. The program’s primary goal was to establish a founder population and lessen the risk of local extinction due to natural catastrophic events, disease, and poaching. However, there is a lack of comprehensive information regarding the relationships between the translocated R. unicornis population and their habitats, which is instrumental in planning and implementing conservation plans and policies. Thus, this study aimed to understand the factors affecting the habitat use of the translocated population of R. unicornis and the major existing conservation threats in Shuklaphanta National Park of Nepal. During the summer of 2022, we undertook a transect‐based habitat assessment over 15 sampling grids of size 4 × 4 km, encompassing a 246 km 2 area. Conservation threats were assessed through the combined approach of direct field visit, systematic literature reviews, and focus group discussions. Model‐averaged estimates of significant variables ( p < 0.05) indicate that R. unicornis detection is more likely in grasslands (low canopy cover) and in the proximity of water source and farther from roads. At the same time, the detection probability decreases with the presence of invasive species. In addition to this, our study ranked habitat loss, fragmentation, land degradation, and small population size as the severe threats to R. unicornis. These findings suggest that conservation efforts should prioritize preserving and restoring suitable grassland habitats and effective control measures to reduce invasive species. Additionally, population monitoring and management efforts should be strengthened to address the challenges posed by small population size and to support the long‐term persistence of R. unicornis in the region. We also recommend a similar study in a larger geographical setting, considering multiple seasons and assessing possible corridors and connectivity to link the local population with the Indian population to maintain genetic diversity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".