Chital's call: An appeal for conservation strategies in the forest of the Institute of Forestry, Hetauda, Nepal
Bibliographic record
Abstract
The chital, Axis axis, constitutes one of Nepal's six deer species and maintains a closed population within the forest of the Institute of Forestry, Hetauda Campus. Presently, the chital population faces a range of challenges, prompting a comprehensive study encompassing population status, habitat preference analysis, and threat assessment. We utilized the pellet group count method on 74 systematic random sample plots (4×4m) within a 100×100 m grid for population estimation. Pellet presence/absence in predetermined habitat characteristics was analyzed to assess habitat preferences. Concurrently, a relative threat ranking method from household interviews was employed to evaluate existing threats. The study revealed a total chital population estimate of approximately 141 individuals, with a population density of 190 individuals per km2. Their habitat preference showed an affinity towards areas abundant in Sal and riverine forests, along with an inclination towards locations further from roads within the forested areas. Primary threats to the chital population encompassed attacks from feral dogs, illegal hunting, and habitat degradation mainly due to invasive alien plant species. This study shows that with effective management of the feral dogs, mitigation strategy to control illegal hunting with the help of local authorities, and improving the habitat conditions concerning their preferences, the chital population has the potential to continue growing in the coming years.
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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 | 0.001 | 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".