Interspecific interactions among major carnivores in Panna Tiger Reserve: A multispecies occupancy approach
Bibliographic record
Abstract
Abstract Large carnivores play a crucial role in trophic cascades, affecting the population dynamics of both co‐predators and prey within an ecosystem. Understanding the significance of these carnivores in trophic interactions is essential for developing effective conservation and management strategies. We examined the effects of occupancy dynamics and patterns of species interactions and coexistence within the carnivore guild in the Panna Tiger Reserve in India. We collected camera trap data (two seasons, 2019) in a presence–absence framework and applied multispecies occupancy models to assess the occupancy, co‐occurrence, and interactions among species. We also examined activity overlap to understand the temporal segregation in the carnivore guild. The mean marginal occupancy was highest for leopards in winter (Ψ winter 0.92 ± 0.02, Ψ summer 0.63 ± 0.05) and hyenas in summer (Ψ summer 0.93 ± 0.03, Ψ winter 0.78 ± 0.03) and was lowest for tigers in both seasons (Ψ winter 0.62 ± 0.05, Ψ summer 0.15 ± 0.05). Co‐occurrence probability among carnivores was higher in winter than in summer, and conditional occupancy was consistently higher when other species were present. Different environmental factors influenced marginal occupancy and co‐occurrence patterns across seasons. Strong temporal overlaps were recorded between tiger–leopard (0.87–0.91) and tiger–hyena (0.78–0.79). We detected a significant spatial segregation between tigers and leopards, as they prefer different habitat types in different seasons, along with high temporal overlap. Resource availability strongly governs the association of carnivores with their habitat selection. Hyenas demonstrated higher dependency on tigers than on leopards for resources. These findings indicate that coexistence with apex‐predator species is feasible through strategic adaptation to fulfill resource requisition.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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; both teacher heads agree on what is shown here.
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".