Testing the VEMCO Positioning System: spatial distribution of the probability of location and the positioning error in a reservoir

Abstract

Background: Recent improvements in fixed acoustic monitoring receivers allow the tracking of individual aquatic animals over long periods of time with regular fine-scale positions. The VEMCO Positioning System (VPS) is now widely used, but various methodological issues remain to be clarified. The aim of this study was to analyze the spatial distribution of the probability of location and the positioning error over the entire surface of a hydropower reservoir, prior to analyzing fish behavior. Findings: Filtering the data set by the horizontal position error (HPE) significantly reduced the positioning error. Retaining only the positions with an HPE less than 15 retained 79% of VPS positions and decreased the positioning error by 33% (mean = 3.3 m, SD = 3.3 m). A higher probability of location was observed inside than outside the receiver array (44% and 36%, respectively). Moreover, the positioning error significantly differed inside (n = 243, mean = 2.4 m, SD = 2.1 m) and outside (n = 253, mean = 4.2 m, SD = 4.0 m) the receiver array (P < 0.001). Finally, the lowest positioning errors were detected in the area with the highest receiver density. Conclusions: The VPS measures fish positioning in a reservoir, under suitable conditions, with satisfactory accuracy. We showed that the probability of location and the positioning error differed spatially in accordance with previous results in other conditions. Consequently, these analyses are recommended as a prerequisite to further spatial analyses using VPS-derived data.

Habitat use and preference of adult perch (Perca fluviatilis L.) in a deep reservoir: variations with seasons, water levels and individuals

“…The spatial variability of the performance was assessed in a prior study (Roy et al, 2014): the performance (positioning error and probability to get a position) was lower in the littoral zone than in the pelagic one. At least two reasons can explain this: firstly, the littoral zone is a structurally complex zone what has been shown to affect the system performance in terms of detection and error ; secondly, by construction of the receiver network, the littoral zone is mainly outside this network whereas the pelagic one is inside and the VPS theory tells that the performance of the system is lower outside the network (Smith, 2013).…”

“…We also paid great attention to the crucial step of telemetry experiment design (Kessel et al, 2014;Steel et al, 2014) and evaluated its performance (Roy et al, 2014) as recommended by Biesinger et al (2013). The spatial variability of the performance was assessed in a prior study (Roy et al, 2014): the performance (positioning error and probability to get a position) was lower in the littoral zone than in the pelagic one.…”

“…In this study, we followed the recommendations of Roy et al (2014) for the same system and only positions with horizontal position error not exceeding 15 were retained; this limit represented a good compromise between the mean position error (3.3 m throughout the reservoir) and the percentage of positions kept (79%) (see Roy et al, 2014 for detailed calculations of these error and percentage). Moreover, the probability of location map, estimated by Roy et al (2014), showed that some parts of the lake were not well sampled, all located at the ends of the lake or on the shore. In parallel, in some of these areas very few locations were recorded.…”

“…An array of 40 underwater VR2W 69kHz omnidirectional acoustic receivers (Vemco) with their associated synchronization tag (V13-1L) was anchored at the bottom throughout the reservoir from January 2012 until (Roy et al, 2014). Roughly every 6 months, receivers were removed from the lake to download fish detections.…”

“…The number of positions in a grid square was corrected with the probability of location in this grid square, estimated by Roy et al (2014), to minimize the spatial variability of the sampling inherent to a telemetry system. The proportion of each type was calculated for each habitat variable.…”