Role of anthropogenic drivers in altering the forest community structure in a prime tiger habitat in central India
Bibliographic record
Abstract
Tropical forests are complex systems with heterogeneous community assemblages often threatened under anthropogenic disturbances and grazing. We studied the change in plant community composition and structure under a disturbance gradient in the tropical dry deciduous forest of the corridor area between Nagzira Wildlife Sanctuary and Navegaon National Park of central India. We tested the hypothesis that the plant community will change along the gradient of proximity to human settlements depending on the anthropogenic stress. We sampled 183 nested quadrat plots to collect data on species abundance and various disturbance parameters. Density, diversity, and importance value index were calculated, and multivariate analysis was performed to assess the changes in species assemblage along the disturbance gradients. We found 76% overall dissimilarity between the plant communities in the three distance classes perpetrated by the difference in mean abundance of species like Tectona grandis, Terminalia sp., and Largerstroemia parviflora. The anthropogenic factors influence the density and diversity of tree species and regeneration classes. We found the abundance of regeneration class increased along the distance from the villages. The study intensifies the need for proper management and conservative approach to preserve the diversity of the forest patches for their structural and functional contiguity as a corridor in central India’s highly susceptible and intricate corridor framework.
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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 | 0.001 |
| 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".