Ecological factors associated with hispid hare (Caprolagus hispidus) habitat use and conservation threats in the Terai Arc Landscape of Nepal
Bibliographic record
Abstract
The hispid hare (Caprolagus hispidus) is one of the most elusive mammals and is listed as an endangered species both globally by the International Union for Conservation of Nature (IUCN) and nationally by National Red list series, Nepal. The species is experiencing a continuous decline across its distribution range due to increasing anthropogenic activities in its habitats. Limited information on the species distribution and the factors affecting its habitat use have restricted site-specific conservation actions. In this study, we aim to identify the current distribution pattern, factors associated with the habitat use of the hispid hare, and prevalent conservation threats in Shuklaphanta National Park (ShNP) of Nepal. We conducted a strip transect-based survey in January and February 2021 across 12 sampling grids of 0.5 km × 0.5 km. The presence of hispid hare was assigned to 1 if any indirect sign of its presence was observed “used plots,” otherwise to 0 if any indirect sign of its presence was not observed (“habitat availability plot”). We next measured six habitat predictors (i.e., nearest distance to a water source, ground cover, ground condition, habitat type, dominant plant species, and presence/absence of anthropogenic disturbance) from both types of plots (“used” and “habitat availability plot”). We found that the overall distribution of hispid hare was clumped. Confirming a new distribution location around the Baba Tal area in ShNP will alert conservation managers to the need of a rapid assessment of its presence–absence across the lowlands of Nepal. Except for the nearest distance to a water source, all other five habitat factors influenced the probability of encountering a hispid hare. Out of six threats, four threats (i.e., grassland burning during the breeding season, grassland succession, habitat loss and fragmentation, and thatch collection from woodland) were determined as the most severe for the hispid hare. Our findings will enable park managers and local government to formulate and plan suitable conservation measures to protect this threatened and endangered species and its habitats. In addition, our results will act as a baseline for further research in ShNP and other similar regions.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".