Methods for finding wolf (Canis lupus) kill sites using location clusters: a study in Grand Portage Indian Reservation, Minnesota
Abstract
Wolves have profound effects on the ecosystems around them. As large carnivores, they can significantly manipulate ecosystems by controlling potentially overabundant ungulate populations. This study attempts to find predation sites to help understand wolf prey selection, seasonal preference, and frequency of kill within the Grand Portage Reservation. We developed and tested three methods to identify wolf kill sites using GPS location clusters from collared wolves in Grand Portage Indian Reservation. During October 2019 to January 2020, we identified location clusters using the program R to analyze GPS locations gathered from Vectronic Vertex Plus Iridium collars attached to seven local wolves. Search teams then visited the location clusters to determine why the cluster occurred and if there was a predation event. We tested three methods, including Method One: Stratified Random Sampling, in which a subsets of location clusters were chosen randomly in a stratified approach; Method Two: Census of Clusters Produced by One Wolf or Pack, in which clusters were chosen from a singular wolf pack and all sites from that pack were visited when possible; and Method Three: Hand Picking Clusters, in which clusters were handpicked by search teams based on criteria and trends from past experience. After visiting 30 sites from 240 (11 %) clusters produced by the algorithm, the search team concluded that each of the three methods had pros and cons. Method Three was the most effective method tested, as it produced the highest likelihood of finding a predation event, given the resources allocated to the study.
Collections
- Undergraduate theses [325]