Fine-scale movement patterns and behavioral states of gray triggerfish Balistes capriscus determined from acoustic telemetry and hidden Markov models

Abstract

Abstract Movement is a central feature of the ecology of fish, yet the study of fish movement has been inhibited due to its multidimensional nature and technological and analytical limitations. We used a relatively new fine-scale acoustic tracking system to quantify movements of an economically valuable, demersal marine fish species (gray triggerfish Balistes capriscus) on a natural hardbottom reef on the continental shelf of North Carolina, USA. Overall, 30 fish were tagged and released, and 104,170 highly precise (˜1–3\u2009m) spatial positions were estimated during the 43-d study. To quantify gray triggerfish movements, we used a combination of exploratory data analyses and hidden Markov models (HMM), the latter of which can identify and elucidate normally hidden behavioral states. Both methods suggested gray triggerfish movements varied by diel period and among individuals, and that some of the variation among individuals could be explained by fish size. Depending on model specification, HMMs identified two or three behavioral states, one of which was likely resting that occurred mostly at night and another was likely foraging or transit that occurred mostly during the day. Moreover, resting at night occurred in small, discrete patches within the study area, whereas foraging or transit behaviors occurred broadly throughout the study area. We encourage a wider use of acoustic telemetry and HMMs to shed light on the normally hidden behaviors of demersal fishes.