Accelerometer-derived activity correlates with volitional swimming speed in lake sturgeon (Acipenser fulvescens)

Canadian Journal of Zoology
By: , and 

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Abstract

Quantifying fine-scale locomotor behaviours associated with different activities is challenging for free-swimming fish.
Biologging and biotelemetry tools can help address this problem. An open channel flume was used to generate volitional
swimming speed (Us) estimates of cultured lake sturgeon (Acipenser fulvescens Rafinesque, 1817) and these were paired with
simultaneously recorded accelerometer-derived metrics of activity obtained from three types of data-storage tags. This study
examined whether a predictive relationship could be established between four different activity metrics (tail-beat frequency
(TBF), tail-beat acceleration amplitude (TBAA), overall dynamic body acceleration (ODBA), and vectorial dynamic body acceleration
(VeDBA)) and the swimming speed of A. fulvescens. Volitional Us of sturgeon ranged from 0.48 to 2.70 m·s−1 (0.51–3.18 body
lengths (BL) · s−1). Swimming speed increased linearly with all accelerometer-derived metrics, and when all tag types were
combined, Us increased 0.46 BL·s−1 for every 1 Hz increase in TBF, and 0.94, 0.61, and 0.94 BL·s−1 for every 1g increase in TBAA,
ODBA, and VeDBA, respectively. Predictive relationships varied among tag types and tag-specific parameter estimates of Us are
presented for all metrics. This use of acceleration data-storage tags demonstrated their applicability for the field quantification
of sturgeon swimming speed.

Additional publication details

Publication type Article
Publication Subtype Journal Article
Title Accelerometer-derived activity correlates with volitional swimming speed in lake sturgeon (Acipenser fulvescens)
Series title Canadian Journal of Zoology
DOI 10.1139/cjz-2014-0271
Volume 93
Year Published 2015
Language English
Publisher NRC Research Press
Contributing office(s) Leetown Science Center
Description 10 p.
First page 645
Last page 654
Online Only (Y/N) N
Additional Online Files (Y/N) N