An empirical movement model for sixgill sharks in Puget Sound: Combining observed and unobserved behavior

Abstract

Abstract Understanding the movement of animals is fundamental to population and community ecology. Historically, it has been difficult to quantify movement patterns of most fishes, but technological advances in acoustic telemetry have increased our abilities to monitor their movement. In this study, we combined small-scale active acoustic tracking with large-scale passive acoustic monitoring to develop an empirical movement model for sixgill sharks in Puget Sound, WA, USA. We began by testing whether a correlated random walk model described the daily movement of sixgills; however, the model failed to capture home-ranging behavior. We added this behavior and used the resultant model (a biased random walk model) to determine whether daily movement patterns are able to explain large-scale seasonal movement. The daily model did not explain the larger-scale patterns of movement observed in the passive monitoring data. In order to create the large-scale patterns, sixgills must have performed behaviors (large, fast directed movements) that were unobserved during small-scale active tracking. In addition, seasonal shifts in location were not captured by the daily model. We added these ‘unobserved’ behaviors to the model and were able to capture large-scale seasonal movement of sixgill sharks over 150 days. The development of empirical models of movement allows researchers to develop hypotheses and test mechanisms responsible for a species movement behavior and spatial distribution. This knowledge will increase our ability to successfully manage species of concern.