Animal tracking data often come with substantial autocorrelation and location error that render classical analyses invalid and cause differential biases across studies, sites, taxa, and individuals. Continuous-time methods offer a solution to these challenges, but can be conceptually challenging and are often misapplied. This workshop will provide beginners with an introduction to important concepts, as well as hands-on experience using point-and-click software (ctmmweb) and the R command line (ctmm), to apply advanced statistical methods to tracking data. Participants will learn how to fit continuous-time movement models to their tracking data, select the most appropriate movement model for their analysis, interpret model parameters, perform home-range analysis via autocorrelated kernel density estimation (AKDE), perform path reconstruction via occurrence estimation, quantify and distinguish between the different types of utilization distributions, quantify home-range overlap and estimate encounter distributions.
Organizers: Christen H. Fleming, University of Maryland, College Park, MD; Michael J. Noonan, University of British Columbia, Okanagan, BC