Differentiating the L\'evy walk from a composite correlated random walk

1. Understanding how to find targets with incomplete information is a topic of interest in many disciplines. In ecology, the development of the Lévy and area-restricted search (ARS) strategies are emerging as important areas of research. Although the processes underlying these strategies differ, they can produce similar movement patterns. Current methods cannot reliably differentiate between them, partly because the models used to describe these strategies are not directly comparable. 2. Here, we present a method that differentiates between the two strategies. It consists of likelihood functions, including a hidden Markov model, and associated statistical measures that assess the support for each strategy. 3. Using a simulation study, we show that our method can differentiate between the two search strategies over a range of parameter values. Using the movement data of two polar bears (Ursus maritimus), we show that the method can be applied to complex, real-world movement paths.