Simple search strategies fail to explain the movement data of grizzly bears, polar bears, and caribou

Background/Question/Methods

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-concentrated search strategies has been an important area of research. Although their underlying processes differ, these strategies can produce similar movement patterns and current methods cannot reliably differentiate between them. We developed a new method to differentiate between these two simple search strategies. It consists of likelihood functions, including a hidden Markov model, and associated statistical measures that assess the support for each strategy. We apply our method to the movement of grizzly bears (Ursus arctos), polar bears (Ursus maritimus), and woodland caribou (Rangifer tarandus caribou), using data collected during periods when these animals are searching for food.

Results/Conclusions

We found greater support for the area-concentrated search strategy than for the Lévy strategy. However, we show that both strategies are insufficient to explain the movement of most animals. Our results emphasize the usefulness of our method when evaluating the evidence for these two search strategies and indicate a need for additional mechanistic search strategy models.