Can rare positive interactions become common when large carnivores consume livestock?
Bibliographic record
Abstract
Livestock populations in protected areas are viewed negatively because of their interaction with native ungulates through direct competition for food resources. However, livestock and native prey can also interact indirectly through their shared predator. Indirect interactions between two prey species occur when one prey modifies either the functional or numerical responses of a shared predator. This interaction is often manifested as negative effects (apparent competition) on one or both prey species through increased predation risk. But indirect interactions can also yield positive effects on a focal prey if the shared predator modifies its functional response toward increased consumption of an abundant and higher-quality alternative prey. Such a phenomenon between two prey species is underappreciated and overlooked in nature. Positive indirect effects can be expected to occur in livestock-dominated wildlife reserves containing large carnivores. We searched for such positive effects in Acacia-Zizhypus forests of India's Gir sanctuary where livestock (Bubalus bubalis and Bos indicus) and a coexisting native prey (chital deer, Axis axis) are consumed by Asiatic lions (Panthera leo persica). Chital vigilance was higher in areas with low livestock density than in areas with high livestock density. This positive indirect effect occurred because lion predation rates on livestock were twice as great where livestock were abundant than where livestock density was low. Positive indirect interactions mediated by shared predators may be more common than generally thought with rather major consequences for ecological understanding and conservation. We encourage further studies to understand outcomes of indirect interactions on long-term predator-prey dynamics in livestock-dominated protected areas.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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; 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".