Evaluating goodness-of-fit of animal movement models using lineups

Models of animal movement are frequently fit to animal location data to understand how animals respond to and interact with local environmental features. Several open-source software packages are available for analyzing animal movements and can facilitate parameter estimation, yet there are relatively few methods available for evaluating model goodness-of-fit. We describe how a simple graphical technique, the lineup protocol, can be used to evaluate goodness-of-fit of integrated step-selection analyses and hidden Markov models, but the method can be applied much more broadly. We leverage the ability to simulate data from fitted models, and demonstrate the approach using both methods applied to fisher (Pekania pennanti) data. A variety of responses and movement metrics can be used to evaluate models, and the lineup protocol can be tailored to focus on specific model assumptions or movement features that are of primary interest. Although it is possible to evaluate goodness-of-fit using a formal hypothesis test, the method can also be used in a more exploratory fashion (e.g., to visualize variability in model behavior across stochastic simulations or identify areas where the model could be improved). We provide coded examples and two vignettes to demonstrate the flexibility of the approach and encourage movement ecologists to consider how their models will be applied when choosing appropriate graphical responses for evaluating goodness-of-fit.