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Separating spatial search and efficiency rates as components of predation risk
1Department of Ecosystem and Conservation Sciences, College of Forestry and Conservation, Wildlife Biology Program, University of Montana, Missoula, MT 59812, USA. ndecesare@mt.gov
Proceedings. Biological Sciences
|September 15, 2012
Summary
Predation risk varies with landscape features, impacting wolf hunting success. Understanding these spatial patterns helps predict predator-prey dynamics and ecosystem health.
Area of Science:
- Ecology
- Wildlife Biology
- Conservation Science
Background:
- Predation risk is a key ecological factor influencing ecosystem dynamics.
- Spatial variation in predation risk can lead to population-level consequences for both predators and prey.
- Understanding the components of risk, such as predator search rates and kill efficiency, is crucial for ecosystem management.
Purpose of the Study:
- To assess the spatial drivers of wolf (Canis lupus) search rate (aggregative response) and predation efficiency rate (functional response).
- To model the cumulative risk of a kill and its relationship to broad-scale kill rates.
- To integrate spatial predation risk components into a comprehensive model.
Main Methods:
- Resource selection modeling
- Proportional hazard time-to-event modeling
- Spatial hazard modeling to predict cumulative risk
Main Results:
- Both search and efficiency rates increased with topographic variation.
- Anthropogenic features influenced only the wolf search rate.
- Spatial hazard models accurately predicted broad-scale kill rates, validating their utility.
Conclusions:
- Spatial heterogeneity in predation risk significantly impacts predator-prey systems.
- Hazard models effectively scale local risk variations to population-level dynamics.
- An integrated model combining search and efficiency rates provides a robust measure of spatial predation risk.
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