Musiani, MarcoKermish-Wells, Joseph2017-07-142017-07-1420172017Kermish-Wells, J. (2017). Spatiotemporal Clusters of GPS Locations and Prediction of Grizzly Bear Behaviour (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/27847http://hdl.handle.net/11023/3954Changes to grizzly bears foraging patterns caused by natural or anthropogenic alterations in their environment could have substantial consequences for both ungulate populations of prey and for bears in Alberta, where the species is considered as “Threatened”. I developed a method for identifying foraging sites of bears fitted with Geographic Positioning System collars, which allowed downloads of locations through satellites. Using spatiotemporal collar data and landscape data I created logistic regression models to predict occurrence of bedding, predation, and other foraging behaviours. I was therefore able to precisely identify sites where grizzly bears concentrated their activity and also increased the predictability of predation event locations by 2.75 times, compared to visits of random GPS-collar locations. My study also determined the natural and human factors influencing bear behavioural patterns, prominently forestry operations and human infrastructure; i.e. factors to be considered in conservation planning for grizzly bears.engUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.Forestry and WildlifeEcologyGrizzly bearUrsus arctosGPSSpace-time clustersWest-central AlbertaBehaviour predictionForagingPredationBeddingmaster thesis10.11575/PRISM/27847