WORKSHOP REGISTRATION IS LIMITED TO 38 ATTENDEES
LEARNING OUTCOMES INCLUDE:
● Import data, perform visual diagnostics, and detect/remove outliers
● Fit movement models via maximum likelihood
● Perform AIC-based selection of movement models
● Conduct home-range analysis using autocorrelated kernel density estimation
● Quantify home-range overlap with the Bhattacharya coefficient
● Estimate habitat suitability with integrated resource selection functions
● Perform scale-free estimation of speed and distance traveled
● Perform population-level analyses using hierarchical models
● Quantify and model telemetry error
● Estimate trajectories and occurrence areas via time-series Kriging
● Simulate trajectories conditional on tracking data
● Link questions, analyses, and studying design
WORKSHOP REQUIREMENTS:
- Participants will be expected to have a laptop on hand with current versions of R, RStudio, ctmm (available via CRAN), and access to MoveApps
Coffee, tea, and snacks will be provided.