Statistical Methods for Identifying Wolf Kill Sites Using Global Positioning System Locations
| Autor: | Mark Hebblewhite, Evelyn H. Merrill, Nathan F. Webb |
|---|---|
| Rok vydání: | 2008 |
| Předmět: |
Ecology
biology business.industry Decision rule biology.organism_classification Predation Canis Geography Global Positioning System General Earth and Planetary Sciences Cluster analysis business Cartography Ecology Evolution Behavior and Systematics Space-Time Clustering Nature and Landscape Conservation General Environmental Science Multinomial logistic regression |
| Zdroj: | Journal of Wildlife Management. 72:798-807 |
| ISSN: | 1937-2817 0022-541X |
| DOI: | 10.2193/2006-566 |
| Popis: | Accurate estimates of kill rates remain a key limitation to addressing many predator–prey questions. Past approaches for identifying kill sites of large predators, such as wolves (Canis lupus), have been limited primarily to areas with abundant winter snowfall and have required intensive ground-tracking or aerial monitoring. More recently, attempts have been made to identify clusters of locations obtained using Global Positioning System (GPS) collars on predators to identify kill sites. However, because decision rules used in determining clusters have not been consistent across studies, results are not necessarily comparable. We illustrate a space–time clustering approach to statistically define clusters of wolf GPS locations that might be wolf kill sites, and we then use binary and multinomial logistic regression to model the probability of a cluster being a non–kill site, kill site of small-bodied prey species, or kill site of a large-bodied prey species. We evaluated our approach using field v... |
| Databáze: | OpenAIRE |
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