Understanding animal movement is essential to elucidate how animals interact, survive, and thrive in a changing world. Recent technological advances in data collection and management have transformed our understanding of animal “movement ecology” (the integrated study of organismal movement), creating a big-data discipline that benefits from rapid, cost-effective generation of large amounts of data on movements of animals in the wild. These high-throughput wildlife tracking systems now allow more thorough investigation of variation among individuals and species across space and time, the nature of biological interactions, and behavioral responses to the environment. Movement ecology is rapidly expanding scientific frontiers through large interdisciplinary and collaborative frameworks, providing improved opportunities for conservation and insights into the movements of wild animals, and their causes and consequences.

Fish passing downstream through hydraulic structures and turbines may be exposed to an elevated risk of injury and mortality. The majority of live fish studies are single-species laboratory investigations and field studies of Kaplan turbines, with a limited number of studies in Francis and screw turbines. In addition to these studies, the physical conditions during turbine passage can be directly measured using passive sensors. In this study, we investigate the multispecies risk of injury and mortality during downstream passage through a large Archimedes hydrodynamic screw for bream (Abramis brama), eel (Anguilla anguilla), and roach (Rutilus rutilus) in conjunction with passive sensors that record the pressure, acceleration, and rate of rotation. This work proposes several new metrics to assess downstream passage including the times and durations of impact events, the kinetic energies of translation and rotation, and the pressure gradient. The major findings of this work are three-fold: (1) Significant differences in injury and mortality were observed between the three investigated species with 37% mortality for bream, 19% for roach, and 3% for eel on average. (2) The operational scenario was found to be significant only for a limited number of species-specific injuries and mortality rates. (3) In contrast to studies in Kaplan turbines, the sensor data revealed highly chaotic physical conditions in the Archimedes hydrodynamic screw, showing little difference in the physical metrics between operational scenarios.

Aquatic biotelemetry techniques have proven to be valuable tools to generate knowledge on species behaviour, gather oceanographic data and help in assessing effects from anthropogenic disturbances. These data types support international policies and directives, needed for species and habitat conservation. As aquatic systems are highly interconnected and cross administrative borders, optimal data gathering should be organized on a large scale. This need triggered the development of regional, national and international aquatic animal tracking network initiatives around the globe. In Belgium, a national acoustic receiver network for fish tracking, called the Permanent Belgian Acoustic Receiver Network, was set up in 2014 with different research institutes collaborating. It is a permanent network with 160 acoustic receivers and since the start, over 800 animals from 16 different fish species have been tagged and generated more than 17 million detections so far. To handle all the (meta)data generated, a data management platform was built. The central database stores all the data and has an interactive web interface that allows the users to upload, manage and explore (meta)data. In addition, the database is linked to an R-shiny application to allow the user to visualize and download the detection data. The permanent tracking network is not only a collaborative platform for exchange of data, analysis tools, devices and knowledge. It also creates opportunities to perform feasibility studies and Ph.D. studies in a cost-efficient way. The Belgian tracking network is a first step towards a Pan-European aquatic tracking network.

Background: Acoustic positioning telemetry is nowadays widely used in behavioural ecology of aquatic animals. Data on the animal’s geographical location and its changes through time are used to study for instance movement patterns, habitat use and migration. The acoustic signals are detected by stand-alone receivers, allowing to collect huge amounts of data over long periods of time. However, large volumes of data might contain large errors. The traditional Time Difference of Arrival (TDOA) method used to calculate underwater positions, is a point-by-point approach: every position is calculated independently of all other positions. This method assumes that the acoustic transmissions follow a linear path. In many environments, this assumption is violated, for instance by reflections of the acoustic signal against hard surfaces, such as rock formations and concrete walls, or by diffractions around obstacles. Hence, acoustic positioning datasets usually require additional filtering. Unfortunately, the performance of the available filtering techniques is often unclear or ambiguous, especially when reflections occur. An alternative to the point-by-point approach, is a track-oriented approach, as used by YAPS (Yet Another Positioning System). This novel algorithm uses the information that is present in previous and subsequent positions, by combining a model of fish behaviour with Time of Arrival (TOA) of the signals on the receivers. In this study, we investigated the performance of two filtering techniques applied to positions provided by the Vemco Positioning System (VPS) in a highly reflective environment. We compared the unfiltered VPS positions with a standard filtering technique, making use of the Horizontal Positioning Error (HPE), and developed a new filter based on receiver cluster classification. Finally, we recalculated the positions with YAPS and compared the performance of this system to the two filtering techniques. Results: The performance of the VPS system was strongly impeded by the multiple reflections occurring in this study area, but lowering the power output of transmitters can slightly attenuate this issue. None of the filtering techniques was able to compensate for reflections and to improve the positioning accuracy significantly. Only the YAPS algorithm could cope with the high level of reflectivity in this study site. Conclusions: Point-by-point algorithms might fail to provide accurate fine-scale tracks in a highly reflective acoustic environment. As this study has shown, the YAPS algorithm can provide a successful alternative, even in these difficult conditions.