Social-ecological determinants of contemporary megafauna distributions in Indian tropical dry woodlands
Bibliographic record
Abstract
Megafauna are among the most challenging conservation targets, particularly in the world’s tropical dry woodlands, which are under high and rising pressures. Identifying factors that maintain megafauna in increasingly human-dominated woodlands is therefore important. India’s dry woodlands are critical for megafauna, supporting substantial tiger and Asian elephant populations, yet have suffered greatly from habitat loss and degradation. We examine which social-ecological factors are associated with the contemporary distributions of six megafauna species of conservation concern in Indian tropical dry woodlands (Asian elephant, leopard, sloth bear, dhole, tiger, and gaur). Using generalized linear mixed models, we link current megafauna distributions to a range of social-ecological variables, including variables describing present-day and historical woodland extent. Our study yielded three major findings. First, contemporary tropical dry woodland cover and protected area coverage were positively associated with all six megafauna species, underscoring the importance of protecting contiguous dry woodland patches in otherwise human-dominated landscapes. Second, while the extent of woody cover was positively associated with the presence of all species, for leopards, sloth bears, gaurs, and dholes, human activities or presence were more important predictors of their distributions, potentially because they are fairly generalized and can adapt to human presence in shared landscapes. Third, legacy effects of historical dry woodland change were evident, with greater past loss associated with higher contemporary megafauna presence. Collectively, our results highlight that Indian megafauna can coexist with people across a wide range of social-ecological conditions provided that there are sufficient refuge habitats (e.g., protected areas, contiguous forests). This finding provides hope for many regions that are currently seeing their tropical dry woodlands and megafauna dwindle, provided that conservation planning is carried out to both maintain and restore woodlands to provide refuges in increasingly human-dominated tropical dry woodland landscapes.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".