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Analysing detection gaps in acoustic telemetry data to infer differential movement patterns in fish

Research output: Contribution to journalArticlepeer-review

Michael J. Williamson, Emma Jayne Tebbs, Terence Peter Dawson, David J. Curnick, Francesco Ferretti, Aaron Carlisle, Taylor Chapple, Robert Schallert, David Tickler, Xavier A. Harrison, Barbara Block, David M. P. Jacoby

Original languageEnglish
Pages (from-to)2717-2730
Number of pages14
JournalEcology and Evolution
Issue number6
Accepted/In press7 Jan 2021
Published10 Feb 2021

Bibliographical note

Funding Information: Funding for this project was provided by the Bertarelli Foundation and contributed to the Bertarelli Programme in Marine Science. This work was also supported by the Natural Environment Research Council (Grant No. NE/L002485/1) to MJW, as part of the London NERC Doctoral Training Partnership at the Department of Geography, King's College London and the Institute of Zoology, London. All procedures were approved by the Stanford University Administrative Panel on Laboratory Animal Care (APLAC) under permit APLAC‐10765. We thank the BIOT Administration for granting us permission to undertake the research. Publisher Copyright: © 2021 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.


King's Authors


A wide array of technologies are available for gaining insight into the movement of wild aquatic animals. Although acoustic telemetry can lack the fine-scale spatial resolution of some satellite tracking technologies, the substantially longer battery life can yield important long-term data on individual behavior and movement for low per-unit cost. Typically, however, receiver arrays are designed to maximize spatial coverage at the cost of positional accuracy leading to potentially longer detection gaps as individuals move out of range between monitored locations. This is particularly true when these technologies are deployed to monitor species in hard-to-access locations. Here, we develop a novel approach to analyzing acoustic telemetry data, using the timing and duration of gaps between animal detections to infer different behaviors. Using the durations between detections at the same and different receiver locations (i.e., detection gaps), we classify behaviors into “restricted” or potential wider “out-of-range” movements synonymous with longer distance dispersal. We apply this method to investigate spatial and temporal segregation of inferred movement patterns in two sympatric species of reef shark within a large, remote, marine protected area (MPA). Response variables were generated using network analysis, and drivers of these movements were identified using generalized linear mixed models and multimodel inference. Species, diel period, and season were significant predictors of “out-of-range” movements. Silvertip sharks were overall more likely to undertake “out-of-range” movements, compared with gray reef sharks, indicating spatial segregation, and corroborating previous stable isotope work between these two species. High individual variability in “out-of-range” movements in both species was also identified. We present a novel gap analysis of telemetry data to help infer differential movement and space use patterns where acoustic coverage is imperfect and other tracking methods are impractical at scale. In remote locations, inference may be the best available tool and this approach shows that acoustic telemetry gap analysis can be used for comparative studies in fish ecology, or combined with other research techniques to better understand functional mechanisms driving behavior.

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