Internship Report. Chloe Malinka, M. Res., B. Sc.

Transcription

1 Internship Report Evaluation of a Drifting Porpoise Localising Array Buoy: A novel configuration for tracking porpoises in tidal rapids using passive acoustics Chloe Malinka, M. Res., B. Sc.

2 Internship Report: Evaluation of a Drifting Porpoise Localising Array Buoy: A novel configuration for tracking porpoises in tidal rapids using passive acoustics Chloe Malinka 1*, Jamie Macaulay 1, Jonathan Gordon 1, Simon Northridge 1 1 Sea Mammal Research Unit, Scottish Oceans Institute, University of St Andrews, St Andrews, Fife, KY16 8LB, UK * chloe.e.malinka@gmail.com March 23, 2015

3 Contents List of Abbreviations... 2 Introduction... 3 Passive Acoustic Monitoring of Harbour Porpoises... 4 How likely is it that a PAM System will Detect a Porpoise Click? D beam profile of Harbour Porpoise Click... 6 Probability of Localising a Harbour Porpoise Click... 9 Field Methods Study Site Acoustic surveying using a drifting buoy Analysis Results Survey Effort of the PLA-Buoy Comparing the PLA-Buoy with the Boat-based Vertical Array Buzzes Acoustic Localisations and Tracking Porpoises Underwater Internship Deliverables and Follow-up Activity Conclusions of Internship Acknowledgements References Data References

4 List of Abbreviations db GIS ICI KE khz MREKE NERC PAM PLA-Buoy p-p RL SL SMRU TOADs Decibel Geographic Information Systems Inter-click interval; the duration between consecutive echolocation clicks. Knowledge Exchange programme Kilohertz Marine Renewable Energy Knowledge Exchange Natural Environment Research Council Passive Acoustic Monitoring Porpoise Localising Array Buoy Peak to peak; a way of measuring sound, specifically the difference between the maximum positive and the maximum negative amplitudes of a waveform. Received level Source level Sea Mammal Research Unit, St Andrews, Scotland Time of arrival differences KEY WORDS: Harbour porpoise Phocoena phocoena marine renewable energy passive acoustics Porpoise Localising Array Buoy acoustic localisation acoustic behaviour fine-scale movement 2

5 Introduction In the UK and worldwide, there is a growing interest in harvesting renewable and predictable energy from tidal currents via in-stream tidal turbines. This has raised environmental concerns of marine mammal physical injury or death via direct contact with rotating turbine blades (e.g. Wilson et al. 2007; Inger et al. 2009; Gordon et al. 2014a; Hastie et al. 2014; Sparling et al. 2014). There are also concerns of disturbance and habitat exclusion to marine mammals, should these tidal sites be of ecological significance (Gordon et al. 2014a). To predict how marine mammals will respond and behave around underwater turbines, and to understand how their behaviour may affect their collision risk, fine-scale site-specific habitat-use information is needed (Gordon et al. 2011). This information on their underwater movements and dive behaviour will also allow for researchers to get a handle on how and why marine mammals are using such sites, and can be used to inform collision-risk models. Such research is especially relevant considering the scale of developments envisioned by the marine renewable energy industry (Hastie et al. 2014). Environmental monitoring in tidal rapids is a challenging task (Gordon et al. 2014b). Impact assessments, requiring the assessment of marine mammal baseline distributions and abundances, are often done using visual methods, but such observations are limited in the inherently energetic regions that are interest to tidal energy developers (Gordon et al. 2014b; Macaulay et al. 2015; Wilson et al. 2013). Acoustic surveys can be preferred to visual surveys since their performance is less unaffected by weather, sea state, daylight, or differences between observers (Sveegaard et al. 2011). Indeed, passive acoustic monitoring (PAM) serves an important role in both cost-effective monitoring and research pertaining to marine renewables. However, neither towed acoustic surveys nor moored acoustic devices can provide information on fine-scale habitat use (Macaulay et al. 2015). Additionally, data on underwater movements cannot be collected using telemetry. The research group at the Sea Mammal Research Unit (SMRU) in which this internship took place has extensive experience with acoustic surveys, and has been working with Marine Scotland and the Natural Environmental Research Council (NERC) for the past five years to develop the hardware and software necessary for fine-scale tracking animals underwater, specifically harbour porpoises (see: Gordon et al. 2014a,b; Macaulay et al. 2014; Macaulay et al. 2015). They (Dr. Jonathan Gordon, Dr. Simon Northridge, Jamie Macaulay, and Dr. Doug Gillespie) constructed a boat-based wide-aperture acoustic vertical array system, and surveyed across six proposed tidal energy sites around Scotland (see Macaulay et al. 2014, Macaulay et al. 2015). The research group then partnered with NERC s Knowledge Exchange (KE) Programme to build a platform which would allow for this system to be more cost-effective and accessible to both more users and users outside of academia. And thus, the autonomous NERC Porpoise Localising Array Buoy (PLA-Buoy) was born. The intern s role in this Marine Renewable Energy Knowledge Exchange (MREKE) placement was to analyse data collected by this PLA-Buoy and compare its performance to that of the established boat-based vertical array. The fellowship gave the intern the opportunity to learn how to collect, detect, and localise high frequency marine mammal sounds, and to infer behaviours skills which can undoubtedly be applied in the future as the marine renewable industry, and associated required environmental monitoring, grow. The analyses and results presented below demonstrate that there are no obvious reasons to reject the PLA-Buoy in favour of the established boat-based vertical array system. 3

6 Passive Acoustic Monitoring of Harbour Porpoises Animals must obtain and interpret information about their surroundings in order to successfully fulfil basic and necessary activities such as foraging, spatial orientation, and predator avoidance. While many animals rely on passive sensory systems to obtain information on their surroundings, some have evolved to use an active exploration system. Echolocation is unique in that it is an active mode of perception whereby echoes of acoustic pulses (clicks) are used to create and understand an auditory scene. Toothed whales (odontocetes), including the harbour porpoise, use echolocation. The harbour porpoise (Phocoena phocoena, Fig. 1) is the most commonly encountered small cetacean in coastal temperate waters of the northern hemisphere, and is found in all UK waters. (Hastie et al. 2014; Gordon et al. 2014a). They are predicted to be the cetacean most likely to encounter a tidal turbine, given their widespread distribution and abundance (Hastie et al. 2014). They are a European protected species under both the Habitats Directive (in both Annex II and IV) and the UK Biodiversity Action Plan (SCANS II 2008). Figure 1. Harbour porpoises in Kyle Rhea, Scotland. Photo courtesy of Doug Gillespie (taken August ). Harbour porpoises are among the cetaceans which make the highest frequency sounds. Their vocal repertoire is entirely stereotyped by narrowband high frequency (NBHF) echolocation clicks (Fig. 2). They frequently emit series (trains) of these highly directional (3 db beamwidth of 16 ), short-duration clicks (~100 µs), with silent gaps between clicks rarely exceeding one minute in a captive environment (Villadsgaard et al. 2007; Akamatsu et al. 2007). The centre frequency of these ultrasonic clicks is around 130 khz (Au et al. 1999, Teilmann et al. 2002, Hansen et al. 2008, Madsen et al. 2010), with measurements ranging from khz (Richardson et al. 1995, SCANS-II 2008, Madsen et al. 2010). These characteristics make them a good candidate for PAM. Echolocation clicks can provide a means of locating and tracking individual porpoises. The research group in which this internship was undertaken is home to the developers of PAMGUARD (Gillespie et al. 2008; This freely available, open-source PAM software used in industry and academia alike to detect, classify, and localise marine mammal sounds. A sample visualisation of a harbour porpoise click, as viewed in PAMGUARD, is shown (Fig. 2). 4

7 Amplitude Amplitude Frequency Figure 2. A single detected harbour porpoise click, as viewed in PAMGUARD. The waveform (~70 ms duration), click spectrum (peak at ~140 khz), and Wigner plot are displayed. Patterns in clicks can be identified in acoustic recordings, and can tell researchers something about what porpoises are doing in different places. Harbour porpoises exhibit range-locking behaviour; this describes the relationship of the duration between consecutive clicks and the range to echoic targets, whereby inter-click intervals (ICIs) decrease with decreasing distance to a target (Au 2002). Clicks which are closely spaced together can indicate that an echolocator is homing in on a target. For example, harbour porpoise clicks spaced at ~ milliseconds apart are considered to be in the search-phase part of an echolocation click train (Wisniewska et al. 2012; Linnenschmidt et al. 2013). The ICIs of harbour porpoises can reduce to 1.5 ms or less when at close range (within 1-2 porpoise body lengths away; DeRuiter et al. 2009) to a target item (i.e. prey), during the terminal phase of a click train (Verfuß et al. 2009); a series of such closely-spaced clicks is known as buzz. While the intervals between regular, search-phase clicks can tell us about porpoise spatial distribution and lead to density estimates, they are not the best indicator of fine-scale porpoise behaviour because porpoises are clicking so frequently. Buzzes are typically associated with prey capture attempts, and have recently been proposed to serve a social function as well (Clausen et al. 2011). As such, capturing buzzes on acoustic recordings and linking these with where they were produced is especially interesting because it can reveal information about how an animal is using its environment (e.g. where it is attempting to capture prey and/or where social encounters are occurring) in ways that regular clicks cannot. Buzzes are quieter than regular clicks (which have on-axis source levels of db re 1 1 m peakto-peak (p-p) in the wild; Villadsgaard et al. 2007, Linnenschmidt et al. 2013), as porpoises adjust the volume of their clicks as they approach a target to compensate for the strength of the returning echoes. Since porpoise buzzes are ~10 db quieter than these regular clicks (in captive animals, DeRuiter et al. 2009), this greatly impacts the probability of acoustically detecting a click by reducing the range at which they can be detected. This reduction in detection range is amplified when the high directionality of harbour porpoise clicks are considered. 5

8 How likely is it that a PAM System will Detect a Porpoise Click? Prior to investigating what our acoustic data contained, it was important to consider what we expected to see. To do this, some simulations exploring how likely it is for PAM system to detect and localise a given porpoise click were conducted. Should we expect our acoustic dataset to be full of buzzes, or have none at all? 3D beam profile of Harbour Porpoise Click The highly directional echolocation click of the harbour porpoise, analogous to the beam of a flashlight, can allow for the possibility of a given porpoise being near an underwater receiver and vocalising but perhaps facing away from the hydrophone (an underwater microphone), and therefore possibly not detected. In order to estimate the odds of click detection, it is important to understand how click intensity varies with the angle of the receiver. Additionally, the beam pattern of a harbour porpoise click is not symmetrical (Koblitz et al. 2012). Estimates for signal detection are typically given in ranges, but this is not appropriate for a species whose clicks have an asymmetric energy distribution and do not have omnidirectional propagation. It is therefore more useful here to get a handle on the volume over which a click can be detected, rather than the range. To do this, scripts were written in Matlab (version 8.4; The Mathworks) to construct the 3D beam profile of a harbour porpoise echolocation click. This builds upon the 2D beam profiles (see Macaulay et al. 2015), constructed from data on the echolocation beam patterns of harbour porpoise clicks (Koblitz et al. 2012) and estimated from dolphin echolocation data (Finneran et al. 2014) for angles outside that investigated by Koblitz et al. (2012). These representations were based on the assumption that it is difficult for an individual receiver to detect a signal with a received level (RL; essentially the amplitude of a signal as detected at the hydrophone) of < 110 db re 1 µpa (Macaulay et al. 2015). Three dimensional representations of volumes in which a click could be detected were modelled for a range of source levels (SL; essentially how loud a click is), encompassing SLs of search-phase clicks and buzzes, as reported for captive and wild porpoises (Fig. 3). The maximum recorded SL of clicks is 205 db re 1 1 m p-p in the wild, and 172 db re 1 1 m p-p in captivity (Villadsgaard et al. 2007). The SL of buzz-phase clicks of captive porpoise is ~10 db re 1 1 m p-p lower than the average level approach-phase clicks (DeRuiter et al. 2009). Since it cannot be assumed that buzzes produced by wild porpoises are equal in SL to those produced by captive porpoises, a range of SLs were simulated (Fig. 4). The volume over which a click can be detected diminishes dramatically with SL (Figs. 3, 4). 6

9 Figure 3. 3D beam profile of harbour porpoise clicks at two different source levels. The black triangle shows the location of the echolocating porpoise (at 0, 0, 0). Contours (at 10 m intervals) outline boundaries that separate where a click is (>110 db) and is not (<110 db) detectable by a receiver, whereby a receiver within the shape can detect it and a receiver outside the shape cannot. The left shows a wild harbour porpoise search-phase click, and the right shows the maximum SL of a captive harbour porpoise. The volumes over which the click here can be detected are ~0.17 km 3 and ~0.001 km 3 respectively. The scanning behaviour of the porpoise, observed concurrent to click production and thought to increase a call s active space (Clausen et al. 2010), was ignored in these simulations. As such, the estimations of volumes over which a given click can be detected by the receiver are likely conservative. An absorption of 0.04 was used to determine transmission loss, according to the peak frequency of harbour porpoise clicks frequency of 130 khz (Madsen et al. 2010), temperature of 5 C, depth of 10 m, salinity of 35 ppt, and ph of 8 (Fisher and Simmons 1977). Acoustic propagation conditions were ignored. 7

10 Figure 4. Volume (km 3 ) over which a harbour porpoise click is detectable (where received level is > 110 db re 1 m), according to source level of the click, which varies depending on environment (wild vs. captive) and click type (search-phase vs. buzz). From left to right, annotation information come from 1) Koblitz et al. 2012, 2) Au et al. 1999, and, 3,4) Villadsgaard et al There are, to my knowledge, no publications describing buzz SL, let alone buzz detection, from wild harbour porpoises. While Linnenschmidt et al. (2013) recorded clicks on A-tags mounted on the dorsal side of several wild porpoises, no buzzes were recorded. Buzzes highly directional and forward-projecting were thought to fall below the trigger level (142 db re 1 µpa) of the dorsally-mounted tag. Additionally, while Villadsgaard et al. (2007) recorded echolocation signals of wild harbour porpoises, their smallest ICIs were within the search-phase range of 30 ms; this is well above the short ICIs of buzzes. The spatial volume over which a single wild click can be detected likely falls within the ranges presented above (Fig. 4). Therefore, until SLs are described for wild buzzes, we can only really say that we expect to find many fewer buzzes in our acoustic dataset than regular clicks, on the scale of at least an order of magnitude s difference. 8

11 Probability of Localising a Harbour Porpoise Click If one is to describe harbour porpoise behaviours at different depths, the clicks must be of sufficient intensity to be received on multiple hydrophones, as this is necessary for acoustic localisation. The time of arrival differences (TOADs) between the same click on different hydrophones on the PLA-Buoy, together with precise hydrophone position information, allow for the porpoise clicks to be localised and for tracks of their underwater fine-scale movements to be constructed. Localisation accuracy depends on the study animal, physical environment, and array design (Hastie et al. 2014). Therefore, the likelihood of obtaining clicks that can be localised from a harbour porpoise clicking at a range of depths must be understood. A Matlab script, building upon 3D beam profiles shown above, was written to simulate a rough likelihood of localising a depth-varying, clicking harbour porpoise on a vertical array, given any vertical orientation of a porpoise, assuming all orientations are equally likely. Here, the likelihood was defined as: Number of times a RL exceeded a detection threshold (110 db) (Number of porpoise orientations simulated) * (Number of hydrophones on the array) The simulations below show scenarios for both the established boat-based vertical array system (12-channels here, max depth 43 m) and the PLA-buoy array used in the 2014 season (8 channels; see Field Methods section). On the buoy, hydrophones were suspended in a shallow or deep-water configuration, with its deepest hydrophones being at 10 and 30 m respectively. The maximum depth where the PLA-Buoy surveyed in the 2014 field season was ~150 m. Although this is less than the maximum recorded dive depth of a harbour porpoise (226 m; Westgate et al. 1995), the maximum depth of the porpoise in this simulation was set to 150 m. The average SL of search-phase clicks in wild harbour porpoises, 190 db re 1 1 m p-p, was used here (Villadsgaard et al. 2007; Linnenschmidt et al. 2013). It was also assumed that porpoise behaviour was uniform with depth, so that all porpoise orientations were equally likely with depth, that the porpoise did not roll, and that the vertical hydrophone array hung completely straight. The assumptions of porpoise behaviour being uniform with depth and all porpoise vertical orientation being equally probable are both unlikely to be true. For example, if a porpoise were to be exploiting a prey patch at a given depth and wearing a tag that monitors its orientation, we may expect much of the orientation data to reflect, and perhaps be concentrated at, the ascent and descent phases of a dive. This simulation shows that array depth slightly impacts the likelihood of click localisation (Fig. 5). There is a non-linear relationship between the increase in the depth of the position of the lowest element in the array and the increase in detectability. The boat-based vertical array configuration has a greater chance of detecting a deeper click than does the deep buoy, and the deep buoy has a greater chance of detecting a deeper click than does the shallow buoy, but all have an approximately equal chance of detecting a click produced on either side of the array. Localisations are highly likely when the porpoise is within 150 m of either the boat-based vertical array or buoy array (Fig. 5). 9

12 Figure 5. Estimated likelihood of the localisation of a single harbour porpoise click, based on a moving porpoise, at any given location, with varying vertical orientation. The hydrophone array is shown in black, showing A) the 8-channel buoy with its deepest hydrophone at 10 m, B) the 8-channel buoy with its deepest hydrophone at a depth of 30 m, and C) the boat-based 12-channel vertical array configuration with its deepest hydrophone at 43 m. Colour shows the cumulative scaled RL, when RLs were large enough to be detectable, and give a crude estimate of the likelihood of localisation of a click. 10

13 Field Methods Study Site This study took place in the narrow tidal channel of Kyle Rhea and the Sound of Sleat, which both separate the Isle of Skye from the northwest coast of mainland Scotland (~57.2 N, 5.65 W; Fig. 6), from August 20-29, This area is a proposed location for a tidal energy development. Kyle Rhea s deepest areas are ~30 m, and this drops abruptly into the Sound of Sleat, where depths reach ~150 m (Digimap bathymetry, 2014). The flood tide runs from south to north, and the ebb tide runs north to south in Kyle Rhea. Figure 6. Survey site of the PLA-Buoy, in Kyle Rhea and the Sound of Sleat, Scotland, UK, in August Acoustic surveying using a drifting buoy The PLA-Buoy (Porpoise Localising Array Buoy) is a self-contained buoy-based system which replicates the abilities of the established boat-based vertical hydrophone array, but in a platform that is less expensive to build, easier to deploy, and one that can be deployed and recovered from a small, low-cost vessel (Fig. 7). During periods when the PLA-Buoy was surveying, there were simultaneous acoustic surveys from a larger vessel (the Silurian), using the vertical array system with elements (see Macaulay et al. 2015). The PLA-Buoy consists of 8 hydrophones, all sampling at high frequency (500 khz) in order to record the high pitch vocalisations of the harbour porpoise at ~140 khz. All channels were digitised into wave files using a selfcontained embedded computer and data acquisition system. While a minimum four dispersed hydrophones are required to localise individual clicks, additional hydrophones improve localisation reliability. Four of the hydrophones, approximately evenly spaced, were distributed along a non-stretch rope in a non-rigid vertical 11

14 array, and were suspended from the buoy at maximum depth of either ~30 m or ~10 m, depending on the depth of survey area. A weight at the bottom aimed to hold the array approximately vertical in the moving water column, as this previously proved successful at maintaining vertical configuration, even in strong tidal currents (Gordon et al. 2011). TOADs of sounds collected on these dangling hydrophones allow for the position of a vocalising porpoise to be determined along the intersection of several 2D hyperbolic surfaces. The other four hydrophones were in a rigid cluster configuration provided a 3D bearing to the vocalising animal, allowing for 3D acoustic localisations (see Macaulay et al and Gordon et al. 2014a). Validation tests of the boatbased vertical array system showed sub-metre accuracy in 3D localisations (Macaulay et al. 2014). GPS systems monitored the movement of the buoy and the speed at which it was drifting. Three orientation sensors (OpenTags, Loggerhead Instruments), located between the suspended hydrophones, monitored hydrophone position. The buoy had a surface float and contained a computer in a waterproof case to manage this autonomous system. A high-visibility flag atop the surface float aided with retrieval. The buoy was deployed and retrieved with a rigid hull inflatable boat (RHIB), and was visually monitoring while drifting. Figure 7. Porpoise localising array buoy. Photo courtesy of Jonathan Gordon (taken August 2014). An advantage of using a drifting system in tidal rapids is that the elements on the array do not experience as much resistance against the surrounding high-flow environment; if the hydrophones were rigid, they would collect self-noise as the fast-moving water rushes past it. A drifting system also allows for the collection of data with high spatial and temporal resolution and allows for the mapping of ambient sounds. This is of particular interest in tidal environments where ambient noise levels both are elevated (Basset et al. 2010) and spatially variable within small tidal channels (Malinka 2013; Willis et al. 2013). Even with this partial mitigation, hydrophone position can still be altered by currents. Note that both the boat-based vertical array and the PLA- Buoy were both drifting systems. 12

15 Analysis All acoustic data were analysed in PAMGUARD (Gillespie et al. 2008). It was important to create an optimal porpoise click detector one which maximised true detections and minimised false detections. This can be tricky in a tidal environment where signal detection can be hampered by high background noise levels inherent to high-energy sites, by either masking clicks of interest, or triggering the detector. Indeed, high-frequency noise has been observed in tidal rapids (Gordon et al. 2011; Malinka 2013; Macaulay et al. 2015). An automated porpoise click detector was run, and click classification was specialised for harbour porpoise clicks. Several classification schemes were tested and noise band analyses were run. The click detection settings settled on for the PLA-Buoy were then applied to the acoustic data from the boat-based vertical array to allow for comparison. The porpoise click detections from the initial automated porpoise click detector were scrutinised by looking at their waveforms, and it was found that many of these did not seem to be characteristic of porpoise clicks. Additionally, there seemed to be many porpoise clicks detected in the southern end of Kyle Rhea, where none were spotted during concurrent visual surveys. This suspicious initial result prompted a noise band analysis, as it was suspected that perhaps spurious ambient noises were setting off the click detector. The noise band analysis revealed high levels of high frequency (70-91 khz) noise to be present and spatially correlated with specific regions of the survey area, notably the southern end of Kyle Rhea. This frequency band (70-91 khz) was chosen as it was high-frequency, but below the frequency of porpoise clicks. For this reason, clicks were reclassified and this appeared to reduce the false detection rate in such regions (Table 1). Regions where high frequency noise exceeded a threshold (75 db) were noted and taken into consideration when mapping click densities. Since noise set off the click detector here, the inclusion of data from these regions in maps of click density would give a false representation of porpoise click density. This emphasizes the importance of adjusting a click detector for the given survey environment. It also highlights concerns of using an instrument which only collects information about click detections (and not raw sound files, e.g. the CPOD), especially in the noisy tidal rapid environment. Table 1. Comparison of the number of clicks detected by the PLA-Buoy, per hydrophone, using old and new porpoise click detectors, in noisy and not-noisy conditions, (where noisy means when noise levels in the khz frequency band exceeded a 75 db threshold). Number of porpoise clicks detected Old click detector Updated click detector When not noisy 420,374 (94%) 172,309 (97%) When noisy 26,973 (6%) 4,963 (3%) TOTAL 447, ,257 The GIS software Quantum Geographic Information Systems (qgis version 2.6.1; Open Source Geospatial Foundation) was used to map both survey effort and effort-adjusted click densities. The same methods (in Matlab and qgis) were applied to the data collected by the boat-based vertical array system. This allowed for the comparison of results for largely concurrent drifts of the PLA-Buoy and the boat-based vertical array. The acoustic data collected by the PLA-Buoy was also examined for acoustic behavioural events, including buzzes. Results The buoy collected over 1.3 terabytes of acoustic data, and surveyed over a total of 42 hours and 23 minutes from August 20-29, Survey effort and effort-adjusted click densities are shown (Figs. 8, 9). 13

16 Survey Effort of the PLA-Buoy Figure 8. Acoustic survey effort of the Porpoise Localising Array Buoy in Kyle Rhea and the Sound of Sleat, Scotland, August 20-29, Areas outlined in black show where high noise levels contaminated data and where false detections were high. Figure 9. Harbour porpoise clicks per effort, as detected by the Porpoise Localising Array Buoy in Kyle Rhea and the Sound of Sleat, Scotland, August 20-29,

17 Comparing the PLA-Buoy with the Boat-based Vertical Array Survey results from the PLA-Buoy and the boat-based vertical array system can be compared since their efforts were largely overlapping in Kyle Rhea and the Sound of Sleat, from August The survey effort of the boat-based vertical array is shown (Fig. 10). The effort-adjusted click densities from the vertical-array are also shown, but divided into day and night-time drifts (Figs. 11, 12). Note that the PLA-Buoy only surveying during the day time; as such, Figure 9 and 11 can be compared. Both survey set-ups how the highest click density in the same region, between and W, and between and N (Figs. 9, 11). These similarities lend support to the performance of the PLA-Buoy. The sometimes non-overlapping survey effort can likely partially explain discrepancies in effort-adjusted click counts between the two survey set-ups. Effortadjusted click densities were lower at night than in daylight hours (Fig. 11, 12). Figure 10. Acoustic survey effort of the boat-based vertical array in Kyle Rhea and the Sound of Sleat, Scotland, during daytime and night-time, August 20-29, Note that daytime drifts often were concurrent with concurrent with PLA- Buoy surveys. 15

18 Figure 11. Harbour porpoise clicks per effort, as detected by the boat-based vertical array in Kyle Rhea and the Sound of Sleat, Scotland, during daytime only, concurrent with PLA-Buoy surveys, August 20-29, Figure 12. Porpoise clicks per effort, as detected by the boat-based vertical array in Kyle Rhea and the Sound of Sleat, Scotland, during night-time only, August 20-29, Night-time drifts were not concurrent with PLA-Buoy surveys. 16

19 Buzzes Several example buzz sequences found in the acoustic dataset from the PLA-Buoy were scrutinized to confirm the click detector used in PAMGUARD could indeed detect buzzes and discriminate between very closelyspaced clicks (Fig. 13). Clicks spaced by only 1 ms gaps were successfully identified as individual clicks in PAMGUARD. A sample of a buzz sequence, as viewed in PAMGUARD s click detector, is shown (Fig. 14). Notice how the ICIs and SL decrease with time (Fig. 14). Figure 13. Demonstration that the click detector used in PAMGUARD can detect a buzz. (Top) Amplitude of the clicks detected by the detector; (Bottom) Channel of the raw wav file on which the buzz had the highest RL. Both graphs have aligned x-axes. Here, it looks like clicks trains from 2 different porpoises are interleaved. Individual inter-click intervals are as little as 3 ms above, with PAMGUARD above demonstrating it can discriminate clicks with ICIs of 1 ms. 17

20 Occurence Click Amplitude Time Figure 14. Visualisation of a buzz sequence, as viewed in PAMGUARD, collected by the PLA-Buoy. Here, ICIs reach down to 2 ms. Clicks are coloured by the hydrophone they were received on. The entire duration along the x-axis is 0.3 s. Sequences of buzzes that were identified in the PLA-Buoy acoustic dataset were investigated. Specifically, the number of hydrophones on which a buzz sequence was detected was counted for 102 identified buzzes. A sequence was considered to be a buzz if ICIs were < 5 ms. Since there were instances when an individual hydrophone may have detected some clicks within a buzz sequence, a hydrophone was only considered to have detected a buzz if it picked up ICIs < 5 ms. Most buzz sequences were detected on four elements of the array, and this hold for when the array was in either the shallow or deep water configuration (Fig. 15). Such information can feed into likelihood estimations of buzz detection. Buzzes seemed to be detected on more hydrophones when the array was in the deep water configuration (max depth of ~30 m) Shallow configuration Deep configuration Number of Hydrophones on which a buzz was detected Figure 15. Histogram of how many hydrophones on the PLA-Buoy (8 total) a buzz sequence was detected on (n = 102 buzzes), for both deep (max depth ~30 m) and shallow (max depth ~10 m) water configurations. 18

21 Acoustic Localisations and Tracking Porpoises Underwater The PLA-Buoy can reveal fine-scale movement and track fragments of vocalising porpoises. Figure 16 (from Macaulay et al. 2015) reveals the potential of this system. Here, porpoise track fragments (portions of a dive where a porpoise is clicking and those clicks are localised) in Kyle Rhea and the Sound of Sleat, as localised with the boat-based vertical array, are shown (Fig. 16). Here, we see many porpoise track fragments at the northern end of the Sound of Sleat, concentrated at the steep drop-off from the southern end of Kyle Rhea, ~20 m to ~140 m (Fig. 16). This location of porpoise track density is concurrent with effort-adjusted click densities (Figs. 9, 11). Data on the proportion of time porpoises were observed to spend at different depths can inform collision risk assessment (Gordon et al. 2014a). Figure 16. Track fragments of all vocalising harbour porpoises detected and localised with the boat-based vertical array in August The white arrows show the tidal flow direction during ebb tide. Courtesy of Jamie Macaulay (see Macaulay et al. 2015). Internship Deliverables and Follow-up Activity The intern contributed to a report to the Scottish Government on fine-scale tracking of harbour porpoises at tidal energy sites using boat-based vertical hydrophone arrays (see Macaulay et al. 2015), and will soon assist in upcoming fieldwork using the PLA-Buoy in Welsh waters. In the coming months, the intern plans to co-write a manuscript for journal publication, focussing on the acoustic behaviour of wild harbour porpoises. As previously mentioned, there is no literature describing buzzes in wild harbour porpoises. A logical next step would be to combine the localisation and tracking results from recordings collected by the PLA-Buoy to estimate source levels of wild harbour porpoise clicks. It would also be interesting to explore how porpoises move in relation to the tidal currents around them. Additional sound-detection devices, SoundTraps (Ocean Instruments New Zealand), were also deployed on drifters in Kyle Rhea at this time, and the intern is working on defining the detection function for this new instrument. 19

22 Conclusions of Internship With the tools described above, we are closer to understanding and being able to meaningfully interpret data on the responses of NBHF cetaceans to marine renewable energy devices. There were no obvious reasons to reject the PLA-Buoy in favour of the established boat-based vertical array system. In future projects where the PLA-Buoy is used, there will be a need for operators who can both deploy the system and analyse the data it can provide. In addition, the analysis methodology learned by the intern here will be similar to the methods that will be used to analyse data from static arrays around turbines. For example, recommendations here may feed into data interpretation of the Scottish Government Demonstrator Project, which will consist of static arrays of hydrophones placed around operating tidal turbines. Given the growth in interest and development in the tidal energy industry, these learned skills could be widely applied in the future. Acknowledgements Thanks to all of those who collected the data in the field: Jamie Macaulay, Doug Gillespie, Jonathan Gordon, Alex Coram, Arthur from SMRU Marine Asia Pacific, and the captain and mate of the Silurian, Stuart and Ed. Thank-you to Annie Linley for helping to arrange funding with the MREKE programme. References Akamatsu, T., J. Teilmann, L. A. Miller, J. Tougaard, R. Dietz, D. Wang, K. Wang U. Siebert and Y. Naito (2007). "Comparison of echolocation behaviour between coastal and riverine porpoises." Deep Sea Research Part II: Topical Studies in Oceanography 54(3): Au, W. W., and R. A. Kastelein (1999). "Transmission beam pattern and echolocation signals of a harbor porpoise (Phocoena phocoena)." Journal of the Acoustical Society of America 106(6): Au, W. W. (2002). "Echolocation." In Encyclopedia of Marine Mammals. Ed. B. Wursig, W. F. Perrin, and J. G.M. Thewissen, San Diego, California: Academic Press. Bassett, C., J. Thomson, and B. Polagye (2010). "Characteristics of underwater ambient noise at a proposed tidal energy site in Puget Sound," in OCEANS 2010 conference, IEEE. Clausen, K. T., M. Wahlberg, K. Beedholm, S. DeRuiter, and P. T. Madsen (2011). "Click communication in harbour porpoises Phocoena phocoena." Bioacoustics: The International Journal of Animal Sound and its Recording 20(1): DeRuiter, S. L., A. Bahr, M.-A. Blanchet, S. F. Hansen, J. H. Kristensen, P. T. Madsen, P. L. Tyack, and M. Wahlberg (2009). "Acoustic behaviour of echolocating porpoises during prey capture." Journal of Experimental Biology 212(19): Finneran, J. J., B. K. Branstetter, D. S. Houser, P. W. Moore, J. Mulsow, C. Martin, and S. Perisho (2014). High-resolution measurement of a bottlenose dolphin s (Tursiops truncatus) biosonar transmission beam pattern in the horizontal plane. Journal of the Acoustical Society of America, 136(4): Fisher, F. and V. Simmons (1977). "Sound absorption in sea water." Journal of the Acoustical Society of America 62(3): Gillespie, D. M., D. Mellinger, J. C. D. Gordon, D. Mclaren, P. Redmond, R. McHugh, P. Trinder, X. Deng. and A. Thode (2008). "PAMGUARD: Semi-automated, open source software for real-time acoustic detection and localisation of cetaceans." Journal of the Acoustical Society of America 30(5): Gordon, J. C. D., D. Thompson, R. Leaper, D. Gillespie, C. Pierpoint, S. Calderan, J. D. J. Macaulay and T. Gordon. (2011) Assessment of Risk to Marine Mammals from Underwater Marine Renewable Devices in Welsh Waters. Marine Renewable Energy Strategic Framework Phase 2 - Studies of Marine Mammals in Welsh High Tidal Waters. Report to the Welsh Assembly Government. Gordon, J. C. D., J. D. J. Macaulay, and S. Northridge (2014a). Tracking porpoise underwater movements in Tidal Rapids using drifting Hydrophone Arrays. Filling a Key Information Gap for Assessing Collision Risk. 2nd International Conference on Environmental Interactions of Marine Renewable (EIMR) Energy Technologies, Stornoway, Isle of Lewis, Outer Hebrides, Scotland. Gordon, J. C. D., J. D. J. Macaulay, and S. Northridge (2014b). Improved Arrays for Towed Hydrophone Surveys of Small Cetaceans at Offshore Marine Energy Sites. 2nd International Conference on Environmental Interactions of Marine Renewable (EIMR) Energy Technologies, Stornoway, Isle of Lewis, Outer Hebrides, Scotland. 20

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"Marine renewable energy: potential benefits to biodiversity? An urgent call for research." Journal of Applied Ecology 46(6): Koblitz, J. C., M. Wahlberg, P. Stilz, P. T. Madsen, K. Beedholm, and H.-U. Schnitzler (2012). "Asymmetry and dynamics of a narrow sonar beam in an echolocating harbor porpoise." Journal of the Acoustical Society of America 131(3): Linnenschmidt, M., J. Teilmann, T. Akamatsu, R. Dietz, and L. A. Miller (2013). "Biosonar, dive, and foraging activity of satellite tracked harbor porpoises (Phocoena phocoena)." Marine Mammal Science 29(2): E77-E97. Macaulay, J. D. J., C. E. Malinka, A. Coram, J. C. D. Gordon, and S. Northridge (2015). Progress report on fine-scale tracking of harbour porpoises. Submitted to the Scottish government under the Marine Mammal Scientific Support Research Programme. Macaulay, J. D. J., D. M. Gillespie, S. Northridge, J. C. D. Gordon (2014). "Tracking porpoise underwater movements in tidal rapids using drifting hydrophone arrays." 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D. J. MacAulay (2014). Marine mammals and tidal turbines: Understanding true collision risk, 2nd International Conference on Environmental Interactions of Marine Renewable (EIMR) Energy Technologies, Stornoway, Isle of Lewis, Outer Hebrides, Scotland. Sveegaard, S., J. Teilmann, P. Berggren, K. N. Mouritsen, D. M. Gillespie and J. Tougaard (2011). "Acoustic surveys confirm the high-density areas of harbour porpoises found by satellite tracking." ICES Journal of Marine Science: Journal du Conseil 68(5): Teilmann, J., L. A. Miller T. Kirketerp, R. A. Kastelein, P. T. Madsen, B. K. Nielsen, and W. W. Au (2002). "Characteristics of echolocation signals used by a harbour porpoise (Phocoena phocoena) in a target detection experiment." Aquatic Mammals 28(3): Verfuß, U. K., L. A. Miller, P. K. D. Pilz, H.-U. Schnitzler (2009). "Echolocation by two foraging harbour porpoises (Phocoena phocoena)." Journal of Experimental Biology 212(6): Villadsgaard, A., M. Wahlberg, and J. Tougaard (2007). 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24 Data References Digimap Bathymetry. Hydrospatial gridded bathymetry [ASCII geospatial data, 1 arcsecond]. Tile nw , Updated 2008, SeaZone Solution Ltd., Using: EDINA Marine Digimap Service, < downloaded October GEBCO Bathymetry. GEBCO_08 grid version < GSHHG coastline data. A Global Self-consistant, Hierarchical, High-resolution Geography Database. Grid version < Distributed under the GNU Lesser General Public license. Original version of dataset available from < Downloaded July