Abstract Acoustic telemetry has helped overcome many of the challenges faced when studying the movement ecology of aquatic species, allowing to obtain unprecedented amounts of data. This has made it into one of the most widely used methods nowadays. Many ways to analyse acoustic telemetry data have been made available and deciding on how to analyse the data requires considering the type of research objectives, relevant properties of the data (e.g., resolution, study design, equipment), habits of the study species, researcher experience, among others. To ease this decision process, here we showcase (1) some of the methods used to estimate pseudo-positions and positions from raw acoustic telemetry data, (2) methods to estimate residency and (3) methods to estimate two-dimensional home and occurrence range using geometric or hull-based methods and density-distribution methods, a network-based approach, and three-dimensional methods. We provide examples of some of these were tested using a sample of real data. With this we intend to provide the necessary background for the selection of the method(s) that better fit specific research objectives when using acoustic telemetry.
Authors
S. Kraft, M. Gandra, R. Lennox, J. Mourier, A. Winkler, D. Abecasis
- Bibliographic Reference
- S. Kraft, M. Gandra, R. Lennox, J. Mourier, A. Winkler, et al.. Residency and space use estimation methods based on passive acoustic telemetry data. Movement Ecology, 2023, 11 (1), pp.12. ⟨10.1186/s40462-022-00364-z⟩. ⟨hal-04034195⟩
- DOI
- https://doi.org/10.1186/s40462-022-00364-z
- HAL Collection
- ['IRD - Institut de recherche pour le développement', "Sciences De l'Environnement", 'CNRS - Centre national de la recherche scientifique', "IFREMER : Institut français de recherche pour l'exploitation de la mer", 'GIP Bretagne Environnement', 'Université de Montpellier', 'MARine Biodiversity, Exploitation and Conservation', 'Université de Montpellier (2015-2021)', 'Université de Montpellier - EPE', 'TEST3-HALCNRS', 'collection test', 'collection test 5', 'Institut écologie et environnement du CNRS']
- HAL Identifier
- 4264231
- Institution
- ['University of Algarve [Portugal]', 'NORCE Norwegian Research Center', 'Institut de Recherche pour le Développement', "Institut Français de Recherche pour l'Exploitation de la Mer"]
- Laboratory
- ['Centre of Marine Sciences [Faro]', 'MARine Biodiversity Exploitation and Conservation [Sète]']
- Published in
- France
Table of Contents
- Residency and space use estimation methods based on passive acoustic telemetry data 2
- Abstract 2
- Introduction 2
- Methods 3
- Abacus plots 4
- Residency estimation 5
- Residency index 5
- Weighted residency index 5
- Continuous time residence 5
- Pseudo-position estimation from passive acoustic telemetry data 6
- Center of activity 6
- Triangulation or trilateralization 8
- Proprietary positioning systems 8
- Vemco (now Innovasea) positioning system 8
- Thelma pinpoint positioning system 8
- Open-source positioning systems 9
- Lotek code division multiple access 9
- Yet another positioning solver 9
- Accuracy 12
- Geometric, hull-based estimators 12
- Minimum convex polygon 12
- Characteristic hull polygons 12
- Local convex hull (LoCoH) methods 13
- Density distribution probabilistic estimators 14
- Kernel utilization distribution 14
- Utilization distribution 14
- Smoothing factor or bandwidth 14
- Kernel utilization distribution 14
- Autocorrelated kernel density estimation 15
- State-space models 15
- Brownian bridge movement model 16
- Biased random bridge kernel method 17
- Dynamic Brownian bridge movement model 17
- Time-geographic density estimation 18
- Network analysis-based home range estimation 18
- Three-dimensional KUD 20
- Discussion 23
- Active telemetry 25
- Summary 25
- Acknowledgements 26
- References 26
