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Setup of the range test. Seven acoustic receivers with a built-in transmitter were used. Distances range between 0 and 700 m, with 50 m increments. Tidal influence on depth is not taken into account
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Acoustic telemetry is a commonly applied method to investigate the ecology of marine animals and provides a scientific basis for management and conservation. Crucial insight in animal behaviour and ecosystem functioning and dynamics is gained through acoustic receiver networks that are established in many different environments around the globe. Th...
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Background
Acoustic telemetry is an increasingly common method used to address ecological questions about the movement, behaviour, and survival of freshwater and marine organisms. The variable performance of acoustic telemetry equipment and ability of receivers to detect signals from transmitters have been well studied in marine and coral reef envi...
Background
Passive acoustic telemetry using coded transmitter tags and stationary receivers is a popular method for tracking movements of aquatic animals. Understanding the performance of these systems is important in array design and in analysis. Close proximity detection interference (CPDI) is a condition where receivers fail to reliably detect t...
Citations
... Given the overlap between the detection radii of neighboring receivers, often achieved using grid or gate designs, continuous detection records can be compared among receiver pairs. These datasets can then be analyzed alongside concurrent environmental records and receiver diagnostic data to identify potential correlations with variation in detection efficiency [10,15,18]. These functionalities ultimately streamline range testing, reducing the need for additional equipment and manual labor, and facilitating their implementation at larger spatial and temporal scales. ...
... These results highlight the importance of local and long-term range test studies to capture variation in environmental conditions occurring over both space (e.g., bottom depth) and time (e.g., meteorological events) [35]. In terms of low-power tags, range tests conducted in the Belgian Part of the North Sea (BPNS) reported a midpoint range of 230 m (148 dB) [18], while results from a nearby estuarine environment in Belgium reported a lower range of 106 m (142 dB) [15]. Although the highpower tags used in the current study (147 dB) had a similar power output to those used in the offshore study, the midpoint range observed in the estuarine environment was more closely comparable to our findings (123 m). ...
... Although the highpower tags used in the current study (147 dB) had a similar power output to those used in the offshore study, the midpoint range observed in the estuarine environment was more closely comparable to our findings (123 m). Between the two Belgian studies, the discrepancy in midpoint range was thought to result from differences in tag power output (148 vs. 142 dB), depth (23 vs. 2 m), and ambient noise levels (316 vs. 378 mV) [15,18]. However, Variables displayed are those with significant predictive power (p < 0.05), with the addition of the sine of wind direction, which was only significant when interacting with wind speed given the similarity in both observed detection ranges and in environmental conditions (e.g., average bottom depth, tidal variation, and ambient noise levels) between the Belgian estuarine study [15] and our study area (Tables 2 and 3), we suggest that the local environment may play a pivotal role in determining detection range. ...
Range tests play a critical role in designing acoustic telemetry studies, guiding equipment configuration, deployment techniques, and the analysis of animal movement data. These studies often strive to capture the effects of environmental variation on detection efficiency over time but are frequently limited in spatial and temporal scale. This could lead to disparities between test results and the circumstances encountered during animal tracking studies. In this study, we evaluated detection range and efficiency at two distinct spatial and temporal scales in a dynamic intertidal ecosystem. Two range tests were conducted, the first being a small-scale study using 6 receivers deployed over 1 month. Using modern acoustic receivers with built-in transmitters and environmental sensors, we then conducted a large-scale range test with 22 receiver stations over a full year to approximate the area and duration of a typical animal movement study. Differences in detection range between the two studies occurred as a result of environmental variation and tag power output, with midpoint ranges estimated as 123 m (small scale, low power), 149 m (small scale, high power) and 311 m (large scale, very high power). At both scales, wind speed emerged as the most influential factor explaining temporal variation in predicted detection efficiency. However, this effect was modulated by wind direction which varied as a result of land sheltering and fetch between the two study scales. At the small scale, detection efficiency decreased with winds from the south and east, while at the large scale, northern and westerly winds were most detrimental. Water temperature had a positive effect on predicted detection efficiency at both scales, while relative water level was positive at the small scale and negative at the large scale. Additional factors, including precipitation and Topographic Position Index, were found to influence detection efficiency at a large scale. Moreover, sensors associated with receivers in the larger array revealed the significant influences of receiver tilt and ambient noise. These discrepancies in the outcomes of the two studies underscore the critical role of scale in range test design and emphasize the need for long-term, in situ range testing at relevant spatial scales.
... For marine species, these studies emphasize the value of releasing fish with acoustic tags within established receiver arrays to understand localized movement within a predefined area. This is particularly important in offshore regions where oceanographic conditions may be more dynamic (increased current and wind speeds), resulting in lower detection probability (Reubens et al., 2019) and where receivers are generally scarce and typically located nearshore or at intersections between bodies of water like the mouth of the Chesapeake Bay (Secor et al., 2020). ...
Black sea bass (Centropristis striata; BSB) are a commercially managed species with an increasing population in the Northwest Atlantic Ocean. Understanding their movement ecology can be difficult due to their wide distribution and ability to inhabit both inshore and offshore reef habitats. BSB have been studied using a range of tagging techniques, and here we present the results of the first deployments of pop‐up satellite archival tags (PSAT) on this species. During 2019 and 2021, we conducted four fishing trips within the southern Mid‐Atlantic Bight region of the NW Atlantic and tagged a total of 30 fish with T‐bar tags and external data loggers, of which 4 received a PSAT and the rest received a Star‐Oddi conductivity–temperature–depth (CTD) archival tag. All PSATs transmitted some data, with short attachment durations (8–32 days) relative to the programmed release of 250 days, and we did not recover a Star‐Oddi tag. External tag attachment techniques need to be examined and improved before continued deployment of larger data loggers on BSB.
... Failure to detect a tagged animal may have multiple causes. It could indicate the animal is absent from an area, had died or was not moving into range of a receiver, or was present in the area but had lost its tag elsewhere, among other possibilities [23,35,46]. Indigenous knowledge helped fill some of the knowledge gaps resulting from limitations in study design and animal capture. ...
American lobster inhabit the unique, brackish Bras d’Or Lake system, although densities are low compared to areas with similar habitats in the Atlantic Ocean. Nevertheless, lobsters are an important part of local First Nation (Mi’kmaq) food and culture. We used acoustic telemetry and habitat mapping, combined with local Mi’kmaw knowledge, to document the movements and habitat use of adult lobsters within a section of the Lake. Movement patterns of acoustically tagged individual lobsters were analyzed with both resource selection functions and integrated step selection functions using data obtained from a high-resolution VEMCO Positioning System within a restricted bay in the Bras d’Or Lake. The resource selection function suggested stronger selections of substrates that contained a combination of soft and hard sediments. While the integrated step selection functions found substantial individual variability in habitat selections, there was a trend for lobsters to exhibit more resident behaviour on the combined soft/hard substrates despite the fact these sediments provided little in the way of obvious shelters for the animals. Adult lobsters at this site have very little risk of predation, which presumably allows them to freely exhibit exploratory behaviours and reduce their association with substrates that provide shelters.
... The double instrumentation will allow for more direct measurements of how these methods perform when reconstructing real animal paths and thus allow for a more realistic assessment of how these methods perform in ecological applications.Similar tests have simulated tracks in the field using a motorboat trailing a transmitter through an array (towed test), which is only feasible over a relatively small spatial rangeBaktoft et al., 2017). Unlike towed tests, the current method for simulating tracks and deriving acoustic telemetry data can be performed over a broad spatial scale as it does not require costly field techniques and subsequent motorboat engine sound, which can impede the detection capabilities of acoustic receivers(Reubens et al., 2019). However, there exists a trade-off between feasibility and estimation accuracy of detection range.Range is dynamic as it is affected by the surrounding environment(Huveneers et al., 2016;Kessel et al., 2013;Mathies et al., 2014;Reubens et al., 2019;Selby et al., 2016) and since our study encompassed such a broad spatial scale and all receivers in the cooperative networks have not been range tested, it would be effectively impossible to obtain accurate detection probability metadata for the current study. ...
... Unlike towed tests, the current method for simulating tracks and deriving acoustic telemetry data can be performed over a broad spatial scale as it does not require costly field techniques and subsequent motorboat engine sound, which can impede the detection capabilities of acoustic receivers(Reubens et al., 2019). However, there exists a trade-off between feasibility and estimation accuracy of detection range.Range is dynamic as it is affected by the surrounding environment(Huveneers et al., 2016;Kessel et al., 2013;Mathies et al., 2014;Reubens et al., 2019;Selby et al., 2016) and since our study encompassed such a broad spatial scale and all receivers in the cooperative networks have not been range tested, it would be effectively impossible to obtain accurate detection probability metadata for the current study. As the network detection databases become more sophisticated, and acoustic telemetry technology makes determining detection probabilities more feasible (e.g., sentinel tags,Innovasea, Nova Scotia, Canada), these kinds of metadata could and should be incorporated into methods analyses such as the current one. ...
Passive acoustic telemetry can be used within cooperative networks to track migratory species over great distances at a relatively low cost. However, the non‐uniform distribution of fixed receivers within networks often results in sporadic detection data.
Here, we propose a novel combination of methods to measure the reliability of hot spot analysis results derived from track reconstructions of passive telemetry data. We use an iterative process to simulate tracks of animals, derive detection data from these tracks, and reconstruct tracks from these derived data using a movement model. We then compare quadrat count residuals from the simulated and reconstructed tracks for different grid resolutions. The methodological framework is outlined in detail and tested on the acoustic telemetry cooperative arrays off the US East Coast. Our methods are applied to a subset of blacktip shark, Carcharhinus limbatus, acoustic telemetry detection data collected off the US East Coast. We then apply the resultant quadrat count to a hot spot analysis to determine the distribution of animals derived from these track reconstruction methods. We integrate the results of our methods process with the hot spot analysis results to determine the reliability of this distribution information.
The track reconstruction methods performed well in coastal regions, from Palm Beach County, FL to Long Island, NY, minimized the clustering effect of high densities of receivers, and closed the gaps in some regions that were lacking receiver coverage. This performance was primarily affected by the presence/absence of receivers, and to a lesser extent by receiver density and water depth, depending on the grid resolution.
Our method combination demonstrates a means by which passive telemetry data can be regularized to determine the spatial distribution of animals across regions with non‐uniform sampling coverage. These methods also allow the user to determine the reliability of animal distribution products in a telemetry array and the factors that contribute to high accuracy and precision. Our iterative process enables managers to infer the reliability of ecological results in decision‐making processes and could be leveraged for use as a gap analysis to develop a national strategy for telemetry assets.
... In the majority of cases, monitoring lines extended the full width of a channel; however, some monitoring lines (A, M, and L, Figure 1b) only partially covered the channel. The detectability of acoustic tags varies depending on the type of water (i.e., fresh water vs. saltwater) and local environment (e.g., noise reduces the detection range of tags; Reubens et al., 2019). Previous studies conducted in coastal marine waters, similar to those in this study, demonstrated detection ranges for V7 tags of 190-400 m (Main, 2021;Newton et al., 2021). ...
The migratory behavior of Atlantic salmon (Salmo salar) post‐smolts in coastal waters is poorly understood. In this collaborative study, 1914 smolts, from 25 rivers, in four countries were tagged with acoustic transmitters during a single seasonal migration. In total, 1105 post‐smolts entered the marine study areas and 438 (39.6%) were detected on a network of 414 marine acoustic receivers and an autonomous underwater vehicle. Migration pathways (defined as the shortest distance between two detections) of up to 575 km and over 100 days at sea were described for all 25 populations. Post‐smolts from different rivers, as well as individuals from the same river, used different pathways in coastal waters. Although difficult to generalize to all rivers, at least during the year of this study, no tagged post‐smolts from rivers draining into the Irish Sea were detected entering the areas of sea between the Hebrides and mainland Scotland, which is associated with a high density of finfish aquaculture. An important outcome of this study is that a high proportion of post‐smolts crossed through multiple legislative jurisdictions and boundaries during their migration. This study provides the basis for spatially explicit assessment of the impact risk of coastal pressures on salmon during their first migration to sea.
... The behaviour of migratory fish is known to be largely influenced by prevailing environmental conditions. In general, it is hypothesised that fish prefer to migrate during specific environmental conditions to save energy, maximize survival and avoid predation [53]. In the case of the critically endangered European Eel (Anguilla anguilla), high current velocities [65] and river discharge are linked with increased migration activity [13,16,39,52,70], and migration speed [1,57,70]. ...
... Therefore, these factors can limit the detection of emitted acoustic telemetry signals drastically, inducing uncertainties and possibly even erroneous conclusions of the main biological research subject [32]. Past studies determined current velocity and turbidity as main influencing factors in coastal systems [40,53]. Additionally, waves and wind cause underwater noise, possibly impairing successful signal transmission. ...
... Additionally, waves and wind cause underwater noise, possibly impairing successful signal transmission. In general, the presence of air bubbles (e.g., entrapped by precipitation, waves and currents) and sediment particles can cause an undirected scattering or absorption of the sound waves resulting in a higher signal loss [53,58]. Moreover, ambient noise, originating from anthropogenic sources, e.g., nautical traffic, rattling of buoy chains, is known to potentially conceal transmitter pings [32,40,53]. ...
Acoustic telemetry provides valuable insights into behavioural patterns of aquatic animals such as downstream migrating European eels (Anguilla anguilla), so called silver eels. The behaviour of silver eels during the migration is known to be influenced by environmental factors, yet so is the performance of acoustic telemetry networks. This study quantifies the impact of these environmental factors on both, migration behaviour and receiver performance to determine possible limiting conditions for detecting tagged eels in tidal areas. A dominance analysis of the selected models describing migration speed, activity and receiver performance was conducted following 234 silver eels that were tagged with acoustic transmitters and observed by a receiver network in the Ems River during two subsequent migration seasons. The results suggest a passive locomotion of silver eels during their downstream migration by taking advantage of selective tidal stream transport (STST). It is further shown that water temperature, salinity, turbidity, precipitation, and especially current velocity were major parameters influencing migration activity and speed. At the same time, analyses of the detection probability of tagged eels under varying environmental conditions indicated a decreased receiver performance during increased current velocities, meaning that high migration activity and -speed coincides with reduced detection probability. Consequently, there is a risk that particularly during phases of increased activity, migration activity may be underestimated due to reduced acoustic telemetry performance. To avoid bias in telemetry studies, it is, therefore, crucial to conduct range tests and adjust the receiver placement in areas and conditions of high current velocities.
... However, the number of potential explanatory variables in these studies has remained limited and assessments were often restricted to exploratory wavelet analyses [17,18]. Regression-based models with multiple variables and interactions have been developed to understand detection range variability, yet these models did not explicitly account for causality nor distinguish between indirect and direct drivers [19]. Since insight in the actual contributors to detection range variability is crucial to decide on the sampling design, and given the broad range of potentially correlated and important variables (e.g., tilt angle of the receiver, ambient noise and water speed) in an estuarine environment, an alternative approach might provide more insight. ...
... More recently, time-logging built-in tags record the exact moment at which a signal is transmitted, allowing to trace each individual detection back to its original transmission and removing the necessity to aggregate the data. Since in this study receivers with time-logging built-in tags were used, both non-aggregated [22,23] and aggregated data [19,24,25] were available for analysis. To assess the effect of data aggregation, and therefore temporal resolution, models of both datasets were developed and compared. ...
... Two datasets were constructed from the raw data: in a first dataset the detections were combined in hourly bins per receiver-tag combination [19,25], which we will refer to as the aggregated data. Since the transmission of each signal was time-stamped by the built-in tag of each receiver, we knew exactly when transmissions were sent and how many transmissions were sent per tag per specific hourly bin (Additional file 1). ...
Insight into the detection range of acoustic telemetry systems is crucial for both sampling design and data interpretation. The detection range is highly dependent on the environmental conditions and can consequently be substantially different among aquatic systems. Also within systems, temporal variability can be significant. The number of studies to assess the detection range in different systems has been growing, though there remains a knowledge gap in estuarine habitats. In this study, a 2-month experimental set-up was used to assess the detection range variability and affecting environmental factors of an estuary. Given the expected complex interplay of different factors and the difficulties it entails for interpretation, a structural equation modelling (pSEM) approach is proposed. The detection range of this estuarine study was relatively low and variable (average 50% detectability of 106 m and ranging between 72 and 229 m) compared to studies of riverine and marine systems. The structural equation models revealed a clear, yet complex, tidal pattern in detection range variability which was mainly affected by water speed (via ambient noise and tilt of the receivers), water depth and wind speed. The negative effect of ambient noise and positive effect of water depth became more pronounced at larger distances. Ambient noise was not only affected by water speed, but also by water depth, precipitation, tilt angle and wind speed. Although the tilt was affected by water speed, water depth and wind speed, most of the variability in tilt could be traced back to the receiver locations. Similarly, the receiver locations seemed to explain a considerable portion of the detection range variability. Retrospective power analyses indicated that for most factors only a minor gain in explanatory power was achieved after more than two days of data collecting. Redirecting some of the sampling effort towards more spatially extensive measurements seems to be a relevant manner to improve the insights in the performance of telemetry systems in estuarine environments. Since the low and variable detection range in estuaries can seriously hamper ecological inferences, range tests with sound sampling designs and appropriate modelling techniques are paramount.
... This may have contributed to the unexpectedly low detection efficiency of TMR_124 for the surface transmitter, just 120 m above. However, previous range tests using VR2ARs have not demonstrated evidence of CPDI for transmitters with similar power outputs to those used for this study (146 dB; Reubens et al., 2019;Brownscombe et al., 2020). The detection efficiency of TMR_124 for the surface transmitter was, however, the only model response affected by gust speed (Figure 5a), tidal water level (Figure 5b), and ambient ultrasonic noise (Supplementary Figure 1). ...
Autonomous underwater vehicles (AUVs) or gliders are increasingly being used with acoustic telemetry to elucidate fish movements while collecting simultaneous environmental data. We assessed the utility of an AUV equipped with an integrated acoustic receiver to detect Pacific herring (Clupea pallasii) in Prince William Sound, AK, USA. A range test evaluated the effect of glider flight characteristics and environmental conditions on the detection efficiency of transmitters at varying depths. While distance from transmitters was the strongest predictor of detections, glider depth had a variable effect on detection efficiency which depended on transmitter depth and dive orientation. The detection efficiency of the glider-mounted acoustic receiver was less affected by wind speed and water level than that of stationary acoustic receivers deployed within the study area. The AUV also performed repeated, adaptive transects in an area of ∼630 km2 area and detected 30 Pacific herring transmitters without a priori knowledge of their locations. Of these herring transmitters, 14 were presumed shed after repeated detections within the same area, and 2 were detected at multiple locations. This study is the first to demonstrate that glider-mounted acoustic receivers have high detection efficiency for transmitters at varying depths and can detect movements of migratory forage fish in large search areas.
... It is increasingly clear that the relationship between the probability of a tag being detected and distance from the receiver (often simplified as the detection radii or the distance at which a tag will be detected for a specific percentage of the time) is dynamic and influenced by a number of variables that researchers need to keep in mind when designing arrays, and also account for when conducting analyses (Brownscombe et al., 2020). Detection efficiency can be affected by vegetation (Thiemer et al., 2022), wind speed (Reubens et al., 2019), thermal stratification (Klinard et al., 2019), and animal behavior, particularly burrowing or burying (Grothues et al., 2012), among other factors. Tag placement on the animal (internal vs. external) can also affect detection range (Dance et al., 2016). ...
... However, one of the main drawbacks of acoustic telemetry is that environmental conditions can hinder or impede the reception of tagged animals by altering acoustic conditions in the water (Reubens et al., 2019). For example, variation in wind speed, water velocity and depth, among other environmental variables, influences sound propagation through water and can limit the potential detection range of a receiver (Gjelland & Hedger, 2013;Kessel et al., 2014;Reubens et al., 2019). ...
... However, one of the main drawbacks of acoustic telemetry is that environmental conditions can hinder or impede the reception of tagged animals by altering acoustic conditions in the water (Reubens et al., 2019). For example, variation in wind speed, water velocity and depth, among other environmental variables, influences sound propagation through water and can limit the potential detection range of a receiver (Gjelland & Hedger, 2013;Kessel et al., 2014;Reubens et al., 2019). Prior research has found that various network properties are altered by the detection ranges inherent to the receivers (Mourier et al., 2017). ...
... In 2012, an array of passive acoustic receivers (N ¼ 73, VR2 and VR2W, Innovasea/VEMCO Ltd, Bedford, NS, Canada) recorded the occurrence of tagged fish within the Delaware Bay and surrounding coastal waters (Fig. 1). Although acoustic detection range is highly variable (Reubens et al., 2019), the maximum detection range of acoustic arrays near the study area is typically 600e1000 m (Haulsee et al., 2015;Kilfoil, 2014;Oliver et al., 2017). ...
Social network analyses are used by ecologists to examine the various drivers of animal social structures. While social behaviours are found throughout the animal kingdom, their roles in structuring marine communities are poorly understood. Comparisons of sociality across marine fishes in the same location and time are rare. A large acoustic telemetry network in Delaware Bay allowed us to analyse the sociality of Atlantic sturgeon, Acipenser oxyrinchus oxyrinchus, and sand tiger sharks, Carcharias taurus. Both species co-occur in the bay, are long-lived, make seasonal migrations and aggregate for unknown reasons. However, these species occupy distinctly different trophic positions and ecological niches. We found little evidence for sociality among Atlantic sturgeon. However, sand tigers exhibited evidence for both preferential co-occurrence and assortment by maturity. In addition, we found that these species preferentially associate with conspecifics. Our findings suggest that sand tigers exhibit a higher degree of sociality than Atlantic sturgeon while in the Delaware Bay. From these findings, we outline the social structures of two evolutionary distinct species while they co-occur in the Delaware Bay. Additionally, we explored the influence that environmental acoustic conditions have on social network metrics and make recommendations for future analyses using acoustic telemetry in estuarine environments.
