Identifying Important Areas for the Release of Five Endemic Species in a Mountainous Landscape: Inference from Spatial Modeling Techniques
Bibliographic record
Abstract
Efforts to release animals resulting from evacuation and rehabilitation into their natural habitats are important practices in wildlife conservation. Before releasing the animals, it is important to assess the habitat suitability of the areas to support the existence of the animals in the long run. Yet, there is limited study of habitat suitability assessment on national parks as release locations for wild animals. This study aimed to assess the suitable habitat of five charismatic animal species, i.e., Panthera pardus melas, Hylobates moloch, Prinonailurus bengalensis, Nycticebus javanicus, and Nisaetus bartelsi, in Gunung Halimun Salak National Park using Maxent, and to determine potential locations for releasing animal’s species. Models for the P. p. melas show 47,619 ha and 21,391 ha, respectively, suitable as habitat and potential release location, for H. moloch, each is 57,537 ha and 33,471 ha, for P. bengalensis, each is 25,460 ha and 17.189 ha, for N. javanicus, each is 29,848 ha and 15,578 ha, and for N. bartelsi, each is 44,426 ha and 25,660 ha. Our study shows that a suitable habitat can be critical in choosing a wildlife release site. Further consideration of conflict mitigation and practicalities is required to achieve the long-term existence of released species.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".