Optimizing the use of biologgers for movement ecology research

Hannah Williams, Lucy Taylor, Simon Benhamou, Allert Bijleveld, Thomas Clay, Sophie de Grissac, Urska Demsar, Holly English, Novella Franconi, Agustina Gómez-Laich, Rachael Griffiths, William Kay, Juan Manuel Morales, Jonathan Potts, Katharine Rogerson, Christian Rutz, Anouk Spelt, Alice Trevail, Rory Wilson, Luca Börger

Research output: Contribution to journalArticlepeer-review

44 Citations (Scopus)
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Abstract

1.The paradigm-changing opportunities of biologging sensors for ecological research, especially movement ecology, are vast, but the crucial questions of how best to match the most appropriate sensors and sensor combinations to specific biological questions, and how to analyse complex biologging data, are mostly ignored.
2.Here, we fill this gap by reviewing how to optimise the use of biologging techniques to answer questions in movement ecology and synthesise this into an Integrated Biologging Framework (IBF).
3.We highlight that multi-sensor approaches are a new frontier in biologging, whilst identifying current limitations and avenues for future development in sensor technology.
4.We focus on the importance of efficient data exploration, and more advanced multi-dimensional visualisation methods, combined with appropriate archiving and sharing approaches, to tackle the big data issues presented by bio-logging. We also discuss the challenges and opportunities in matching the peculiarities of specific sensor data to the statistical models used, highlighting at the same time the large advances which will be required in the latter to properly analyse biologging data.
5.Taking advantage of the bio-logging revolution will require a large improvement in the theoretical and mathematical foundations of movement ecology, to include the rich set of high-frequency multivariate data, which greatly expand the fundamentally limited and coarse data that could be collected using location-only technology such as GPS. Equally important will be the establishment of multi-disciplinary collaborations to catalyse the opportunities offered by current and future bio-logging technology. If this is achieved, clear potential exists for developing a vastly improved mechanistic understanding of animal movements and their roles in ecological processes, and for building realistic predictive models.
Original languageEnglish
JournalJournal of Animal Ecology
VolumeEarly View
Early online date1 Oct 2019
DOIs
Publication statusE-pub ahead of print - 1 Oct 2019

Keywords

  • Biologging
  • Multidisciplinary collaboration
  • Movement ecology
  • Multisensor approach
  • Big data
  • Data visualization
  • Integrated Biologging Framework
  • Accelerometer
  • GPS

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