Inferring activity patterns of aquatic animals from single‐receiver acoustic telemetry setups

Abstract Acoustic telemetry has become an essential tool for studying activity patterns of animals in aquatic environments. Activity is typically recorded using transmitters with integrated sensors or dense receiver arrays for positional tracking. While effective, these approaches are financially and logistically expensive due to the need for advanced transmitters or a large number of acoustic receivers. This study presents a novel methodology to quantify activity patterns from single‐receiver acoustic telemetry setups. Our method extracts the time of arrival (TOA) of acoustic signals and estimates the relative distance between the individual and the receiver. By examining variations in TOA‐based distances, movement parameters such as step lengths can be calculated, which can then be used to classify behavioural states through hidden Markov models or other statistical approaches. We validated our approach through a positioning test and demonstrated its effectiveness in inferring behavioural states across multiple species by analysing six acoustic telemetry datasets. The validation also included a comparison between TOA‐based distances in multiple receivers and a positioned telemetry dataset. Our method proved to be effective in estimating the distance between transmitters and single receivers, as well as characterising the activity patterns of the analysed species. It is particularly effective for species with certain site fidelity, where movement relative to a fixed receiver can provide significant insights into activity patterns. The method can also be applied in analysis workflows to check post‐tagging or natural mortality by identifying stationary transmitters. By providing a cost‐efficient method, this approach will enable detailed behavioural studies in a wide range of species and contexts, leveraging minimum equipment availability.