LAUSR

Passive acoustic telemetry provides the opportunity to monitor and contextualize the movements of diverse aquatic animals. Despite depth being an essential dimension along which many processes are organized, the Eulerian structure of the acoustic telemetry data (movements perceived from fixed locations) and the consequences of sound propagation in water hinders the incorporation of the vertical dimension into animal’s space use analyses. Here, we propose a new data‐driven quantitative method to estimate 3D space use from telemetry networks. The methodology is based on simulating large numbers of stochastic synthetic paths, accommodating the detection probability around receivers and the depth information from transmitters and integrating the local topography. The methodological protocol is explained in detail and tested with acoustic telemetry data from the common dentex Dentex dentex in a Mediterranean marine protected area. We present 3D space use estimations for the tagged individuals and compare them with other 3D and 2D estimations derived with existing probabilistic methods. 3D space use estimations that incorporate topography provided a more comprehensive view of the movement ecology of tracked individuals, with relevant pieces being missed by 2D representations. Our method generated realistic representations of the actual spatial co‐occurrence of individuals, including the spatio‐temporal identification of relevant aggregation areas.