Novel methods for quantifying movement behavior of free-ranging fish from telemetry data

In recent decades, technological progress in the field of biotelemetry has allowed the collection of vast amounts of data on the movement of free-ranging marine animals and recently there have been great advances in analysing data from tags that allow the observation of complete animal tracks. One of the most common and low-cost tools for tracking marine animals, however, are automated acoustic arrays, which often do not record complete tracks but provide presence/absence data for tagged animals at fixed locations. The development of quantitative methods for analysing these data has lagged behind the technological advances in the field. This thesis applies novel methods for quantifying the movement behaviour of highly mobile free-ranging teleosts and elamsobranchs using automated acoustic tracking data and answers ecological questions of management relevance for tropical tuna (Yellowfin tuna Thunnus albacares) and a temperate shark species (Broadnose sevengill shark Notorynchus cepedianus). Additionally, pop-up satellite archival tag (PSAT) data are analysed for the temperate shark species, to put the findings of the acoustic tracking data analysis into the context of the animals' large-scale movement behaviour. The two acoustic datasets represent two different types of common receiver array designs: For the tuna study, individual receivers were deployed at ecologically significant locations (fish aggregating devices, FADs) to determine the residency at and movement between these locations. For the shark study, receivers were deployed as multiple curtains between opposite shorelines to detect passes of animals through the curtains and determine general movement patterns within a coastal area. Network analysis methods were applied to both datasets to quantify the co-occurrence of individuals at a given location and to determine the relative importance of each location to the animals. For the former, we adapted association indices from social network analysis to quantify temporally explicit joint occurrences of individuals. For the latter we treated the number of transitions between locations as a measure of the connectivity between them. The network analysis approach to the acoustic tracking data was well suited to the type of array used in the tuna study and was a considerable improvement over traditional measures of cooccurrence which often only include either the spatial or the temporal dimension, not both. It provided new insight into the temporal dynamics of tuna aggregations at FADs and how they may be linked to between-FAD movement. We observed large interannual variation in movement rates of tuna between FADs, and corresponding interannual variability in the mean number of spatio-temporal associates for each individual as well as the temporal stability of associations. When movement rates were high, associations within FAD aggregations decayed to randomness three times faster than when movement rates were lower. This raises the possibility that if FADs are sufficiently close for fish to perform frequent between-FAD movements, school mixing may be increased and cohesion reduced. For the shark data, we compared results from the network analysis to a Markovian movement model estimated from counts of observed transitions. Specifically, we tested the suitability of the two methods for determining whether the differences in large-scale movement behaviour between males and females we established from the PSAT data are mirrored in their space-use during their coastal summer residency. Both spatial network analysis and Markov chain analysis showed differences in space-use between male and female broadnose sevengill sharks, however, rankings of the relative importance of geographic areas differed between the two approaches. This indicated that not only transitions but also residency periods, which are not accounted for by spatial network analysis, were important for identifying priority areas for the sharks. Determining how animals interact and move within their environment has been a relatively understudied area, lacking in quantitative analytical methods. This thesis has applied various novel approaches which quantify both how individuals interact and use space, deepening our understanding of the two and the link between them.