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Brownscombe JW, Thiem JD, Hatry C, Cull F, Haak CR, Danylchuk AJ, Cooke SJ. Recovery bags reduce post-release impairments in locomotory activity and behavior of bonefish (Albula spp.) following exposure to angling-related stressors. J Exp Mar Bio Ecol. 2013;440:207–15.
In Experiment #1, linear mixed-effects models were used to determine the relationship between EA and swimming speed and TBF (fixed-effects), and between VAR and the latter two parameters (Additional file 1: Table S2). In this analysis, fish was included as a random factor, and the lowest Akaike information criterion was used to determine the best model (i.e., using a linear regression or log transformed data). Linear mixed-effects models were used to analyze the effect of swimming speed (fixed-effect) on fH, HRV and the percentage of QI0 data, with fish as a random factor.
The modified implantation method used in this study was effective for recording fH and acceleration in Atlantic salmon. In order to effectively record fH, the electrodes of fH loggers and transmitters must remain close to the pericardium throughout deployment . Therefore, we chose to suture the centi-HRT ACT tag to the body wall before closing the incision. This resulted in good quality ECG recordings during both the exhaustive exercise (Ucrit) protocol and the 1 and 6 weeks that the salmon were held in the large tanks; the average percentage of good quality ECGs (i.e., QI0) approximately 68, 86 and 88%, respectively (Table 2). It has been reported that increased activity can interfere with ECG recordings due to potentials produced by the aerobic muscles . However, this was very rare in these studies. There were only two instances when fH that could not be calculated due to noisy signals corresponded with feeding activity. The positioning of the tag was also consistent with suggestions for implanting accelerometers, e.g., aligning the tag with the major plane of movement (i.e., the lateral movement of the tail) and placing the tags close to the animal’s center of gravity . Further, suturing the tags to the body wall would have reduced the potential for variation in logger position between individuals, which can impact the interpretation of accelerometry data .
Peake SJ, Farrell AP. Locomotory behaviour and post-exercise physiology in relation to swimming speed, gait transition, and metabolism in free-swimming smallmouth bass (Micropterus dolomieus). J Exp Biol. 2004;207(9):1563–75.
During the Ucrit test, fH increased significantly from 61.1 ± 1.0 bpm at rest to 77.1 ± 0.7 bpm at 1.6 BL s−1 (P < 0.0001), while HRV decreased significantly from 62.4 ± 3.6 to 30.1 ± 4.3 ms (P < 0.0001) (Fig. 3; Additional file 1: Table S3). The percentage of good quality ECGs (i.e., QI0) did not change significantly with swimming speed (P > 0.05), but decreased marginally from 83% at rest to ~ 60% while swimming. An average of 68% of the measurements were QI0 and only 0.1% of the total dataset could not be manually calculated after the experiments were completed (Table 2). The absolute difference in fH between manually calculated values and those calculated by the tag algorithm increased with the reported QI value (i.e., 2.3 ± 8.0 bpm for QI0; 10.8 ± 27.2 bpm for QI1; 31.0 ± 63.0 bpm for QI2; and 39.5 ± 41.2 bpm for QI3; data not presented).
Based on signal-processing theory, it has been suggested that sampling rate should be at least twice the highest frequency of the waveform being measured . In this research, we determined that the maximum TBF of Atlantic salmon of this size was approx. 3.5 Hz. However, we recommend that researchers perform preliminary tests to determine the most effective sampling frequency for their species. Such recordings require significant memory and battery life, and thus, discrete sampling is a valuable option depending on a user’s research objectives.
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