Vultures, their population status and some ecological aspects in an Indian stronghold
Bibliographic record
Abstract
Indian vultures have important ecological and socio-economic functions and are increasingly studied, per their ecological role and recently, their catastrophic populations’ decline. However, there are few studies of vultures in central India, a vulture stronghold. The present paper examined the presence, distribution per landcover variation, roosting and nesting habits of vultures in this region. Both quantitative (total count) and qualitative (questionnaire survey) methods of research were applied. The hypotheses were that vulture presence is higher in forested areas, unaffected by agricultural development (excepting the Egyptian vulture); as well as that vultures are more likely to roost and nest in large trees and on cliffs in open landcover. Vulture species recorded in summer and winter counts were the Long-billed vulture (Gyps indicus, Scopoli, 1786), Egyptian vulture (Neophron percnopterus, Linnaeus, 1758), White-rumped vulture (Gyps bengalensis, Gmelin, 1788), Eurasian Griffon vulture (Gyps fulvus, Hablizl, 1783), Red-headed vulture (Sarcogyps calvus, Scopoli, 1786), Cinereous vulture (Aegypius monachus, Linnaeus, 1766) and Himalayan Griffon vulture (Gyps himalayensis, Hume, 1869). Their average total abundance was of 7,028 individuals, maximum being Long-billed vulture (3,351) and minimum being Cinereous vulture (39). Thematic maps documented distributions in different agroclimatic regions and ecozones. Orography and forest structure influenced vulture presence, but human disturbance did not. Vulture protection, food monitoring and human-induced disturbances are manageable with critical, informed and flexible policies. These findings contribute to monitoring and management planning for vulture conservation in Central India and elsewhere.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".