Using lineups to evaluate goodness of fit of animal movement models

Movement models are frequently fit to animal location data to understand how individuals respond to and interact with local environmental features. Several open-source software packages are available for analysing 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 an integrated step-selection analysis and a hidden Markov model 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 statistical significance using a formal hypothesis test, the method can also be used in a more exploratory fashion (e.g. to explore variability in model behaviour across stochastic simulations or to identify areas where the model could be improved). We provide coded examples and vignettes to demonstrate the flexibility of the approach. We encourage movement ecologists to consider how their models will be applied when choosing appropriate graphical responses for evaluating goodness of fit.