Acoustic telemetry array evolution: From species- and project-specific designs to large-scale, multispecies, cooperative networks
Ellis, R.D.; Flaherty-Walia, K.E.; Collins, A.B.; Bickford, J.W.; Boucek, R.; Walters Burnsed, S.L.; Lowerre-Barbieri, S.K. (2019). Acoustic telemetry array evolution: From species- and project-specific designs to large-scale, multispecies, cooperative networks. Fish. Res. 209: 186-195. https://dx.doi.org/10.1016/j.fishres.2018.09.015
In: Fisheries Research. Elsevier: Amsterdam. ISSN 0165-7836; e-ISSN 1872-6763, more
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| Keywords |
ASW, Mexico Gulf
Measurement > Telemetry > Acoustic telemetry
Movement
Sciaenops ocellatus (Linnaeus, 1766) [WoRMS]
Gulf of Mexico [Marine Regions]
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| Author keywords |
Artificial reef; Grouper; Red drum |
| Authors | | Top |
- Ellis, R.D.
- Flaherty-Walia, K.E.
- Collins, A.B.
- Bickford, J.W.
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- Boucek, R.
- Walters Burnsed, S.L.
- Lowerre-Barbieri, S.K.
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| Abstract |
Acoustic telemetry is a powerful tool for investigating the movement ecology of aquatic animals. As the number of studies using passive acoustic telemetry technology has grown in recent years, so has membership in regional collaborative networks in which methodologies and detection data are shared among researchers. These networks can significantly augment research projects by increasing the geographic coverage of detection data beyond the initial monitored area, and encourage the development of research collaborations with the goal of improving aquatic research management. As tags expire and projects end, researchers must decide whether to maintain their receiver stations, adjust the configuration to accommodate a new scope of research, or remove the stations. We assessed telemetry data from two projects designed to monitor fishes in nearshore and offshore habitats of the eastern Gulf of Mexico to determine the configuration of receiver stations most informative for network scale monitoring. Modeled on the Index of Relative Importance commonly used to analyze fish diets, the Receiver Efficiency Index (REI) allowed us to reduce the size of the two arrays from 59 to 24 and 33 to 21 stations, reductions of 59% and 27%, while retaining more than 75% of all detections. The application of this method has general relevance to understanding the spatial dynamics of these arrays while providing researchers with a quantitative tool to guide decision making that can maximize spatial coverage at the lowest maintenance cost. |
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