FREE-RANGING MARINE MAMMALS: THE NEXT ACOUSTIC SHIPS OF OPPORTUNITY?
Abstract
Understanding the nature of species interactions in the ocean is challenging because direct observation is usually impossible. The deployment of dual transmitting and receiving acoustic transceivers and satellite-linked GPS tags on mobile marine predators provides a unique opportunity to resolve species associations in space and time. However, an approach for how best to analyze and draw biological inferences from these data is lacking. I evaluated the detection efficiency of acoustic transceivers deployed on grey seals (Halichoerus grypus) in 2010 off Sable Island in response to changing field conditions using generalized linear models (GLM) applied to post-processed detection data and summarized raw transceiver data. Distance between seals, wind stress, and depth were the most important predictors of detection efficiency. Access to the raw acoustic transceiver data greatly improved our ability to identify legitimate periods of silence when the receiver recorded no part of an acoustic transmission. I demonstrated how the non-parametric Lagrangian method, T-LoCoH, may be applied to GPS location data to characterize pat- terns in the individual and collective movement of instrumented grey seals and account for uneven sampling effort. Consistent patterns in collective area-use emerged that may relate to seasonal energy requirements and prey distribution. At the individual-level, T-LoCoH can be used to identify behavioural patterns and to calculate the transmission reception per unit sampling effort (TPUE) using time and space-use metrics. This thesis represents a first step towards analyzing acoustic data collected by mobile marine animals. My findings highlight the importance of understanding the factors influencing tag performance and the biological processes driving animal movement in order to draw accurate biological inferences. In addition, these findings demonstrate effective approaches that may be used to quantify and account for changes in detection efficiency and uneven sampling effort.