Marine Pollution Bulletin 165 (2021) 112171

Available online 20 February 20210025-326X/© 2021 Elsevier Ltd. All rights reserved.

Prediction of marine mammal auditory-impact risk from Acoustic Deterrent Devices used in Scottish aquaculture

Victoria L.G. Todd a, Laura D. Williamson a, Jian Jiang a, Sophie E. Cox a, Ian B. Todd a, Maximilian Ruffert b,*

a Ocean Science Consulting Limited, Spott Road, Dunbar, East Lothian, Scotland, EH42 1RR, UK b School of Mathematics & Maxwell Institute, University of Edinburgh, Edinburgh EH9 3FD, Scotland, UK

A R T I C L E I N F O

Keywords: Acoustic deterrent device (ADD) Acoustic harassment device (AHD) Aquaculture Marine mammal

A B S T R A C T

Acoustic Deterrent Devices (ADDs) are used worldwide to deter pinnipeds from predating fish-aquaculture fa-cilities. Desk-based noise-propagation modelling of six commercial ADD models, and a ‘fictional’ ADD was performed, the latter involving alternating source level, frequency, duty cycle, noise-exposure duration, and number of ADDs active simultaneously. Potential auditory impacts on marine mammals were explored using the Southall et al. (2019) criteria. Depending on operational characteristics, real ADDs were predicted to cause Temporary Threshold Shift (TTS) to Very High Frequency (VHF) cetaceans at ranges of 4–31 km, and a single fictional device operating at the highest outputs tested was predicted to cause TTS to VHF cetaceans at up to 32 km. Cumulative effects of 23 real fish-farm ADDs produced noise across large swathes of the Inner-Hebrides. The single variable causing greatest reduction in potential impact to marine mammals from fictional ADDs was SL.

1. Introduction

Common (Phoca vitulina) and grey (Halichoerus grypus) seals cause significant biological and economic damage to the United Kingdom (UK) finfish aquaculture industry (Gordon and Northridge, 2002; Northridge et al., 2013; Coram et al., 2014; Gordon et al., 2019). Effects include, inter alia, fish predation, injury/reduced growth rates, escapes, wild stock disease transmission and genetic contamination (Würsig and Gailey, 2002). Consequently, fish farm operators place substantial effort on mitigating interactions, including installation of underwater acoustic transmitters called Acoustic Deterrent Devices (ADDs) or ‘seal scarers’ to discourage animals from approaching aquaculture pens, often with mixed success (Nelson et al., 2006; Northridge et al., 2010; Coram et al., 2014; Harris et al., 2014). In addition to their use on finfish farms, ADDs are also deployed during offshore construction activities, e.g. piling, explosives, etc. to mitigate marine mammals approaching loud- impulsive noises that may cause injury or mortality (Brandt et al., 2013). Use of ADDs in these contexts is generally short term (15–30 min), and not considered to cause significant impact and is therefore not discussed further here.

Since ADDs are used on at least half of Scottish finfish farms (Quick

et al., 2004; Northridge et al., 2010), there is considerable overlap in the areas where ADDs are located and marine mammal presence. In Scottish waters, the focus of this study, the key species of concern are harbour porpoise (Phocoena phocoena), minke whale (Balaenoptera acutorostrata), bottlenose dolphin (Tursiops truncatus), and common and grey seal. There is concern that noise pollution results in potentially harmful im-pacts for non-target species (Findlay et al., 2018), especially harbour porpoises (e.g. Schaffeld et al., 2019), which are considered to be particularly sensitive to noise, and therefore the main focus in this study. (Brandt et al., 2013).

Harbour porpoise represents one of the species sighted most frequently off the Scottish west coast (Dolman et al., 2014; Hammond et al., 2017; Ryan et al., 2018; Evans and Waggitt, 2020), perennially occupying inshore waters between 50 and 150 m depth (Marubini et al., 2009). Fig. 1 presents locations of active finfish aquaculture sites within the northern portion of the Inner Hebrides & the Minches Special Area of Conservation (SAC), which was designated for harbour porpoise. The area also hosts high numbers of basking shark (Cetorhinus maximus) and minke whale, resulting in designation of the Sea of the Hebrides Marine Protected Area (MPA), as well as Risso’s dolphin (Grampus griseus), for which the North-east Lewis MPA was designated.

* Corresponding author. E-mail addresses: vt@osc.co.uk (V.L.G. Todd), lw@osc.co.uk (L.D. Williamson), jj@osc.co.uk (J. Jiang), sc@osc.co.uk (S.E. Cox), it@osc.co.uk (I.B. Todd), m.

ruffert@ed.ac.uk (M. Ruffert).

Contents lists available at ScienceDirect

Marine Pollution Bulletin

journal homepage: www.elsevier.com/locate/marpolbul

https://doi.org/10.1016/j.marpolbul.2021.112171 Received 19 November 2020; Received in revised form 8 February 2021; Accepted 10 February 2021

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Use of ADDs on Scottish fish farms is not well documented, primarily because ADDs have not been subject to any specific licencing process. Instead, they have been indirectly consented as part of the fish farm equipment through planning permission by local councils. Of increasing concern is the unquantified level of noise emitted by the aquaculture industry into the marine environment, especially since ‘noise’ can be defined as any sound that has potential to interfere with normal func-tioning of auditory processes or cause harmful behavioural or physio-logical responses (Simonis et al., 2020).

The Policy landscape in Scotland is currently undergoing revision. On 21st July 2020, the Animals and Wildlife (Penalties Protections and Powers) (Scotland) Bill became an Act in Scotland (Scottish Govern-ment, 2020), as an amendment to the Marine (Scotland) Act 2010 (Scottish Government, 2010), revoking the provision to grant licences for seal shooting on grounds of protecting fish farms and fisheries. This will undoubtedly increase the industry’s reliance on non-lethal means of preventing depredation, including use of ADDs. The Scottish Govern-ment has also introduced a requirement to apply for a European Pro-tected Species (EPS) licence for cetaceans if ADDs are to be used. In addition, there is potential that further restrictions on certain types of ADD devices may arise as a result of the requirements of the Marine Mammal Protection Act (MMPA) in the USA, a primary export market for farmed salmon from Scotland. Consequently, studies on all aspects of ADD use in UK waters have rapidly become of paramount importance.

This study has employed noise modelling to consider the potential for auditory impacts from ADD systems used in Aquaculture. Underwater-noise propagation varies between locations due to complexity of environments affected by, inter alia, geographical, bathymetrical, oceanographical, and climactic conditions. Numerical

modelling is a relatively inexpensive method to provide prediction of underwater acoustic fields, which can then be used to assess theoretical impacts on marine life; however, the most effective method to quantify potential effects of anthropogenic noise sources on marine mammals is to groundtruth modelled data with empirical environmental data and in- field noise measurements. Due to the large spatial scale investigated in this study and diversity of devices tested, in situ measurements were not feasible, emphasising the importance of a numerical-modelling approach.

In general, to estimate Received Level (RL) at a receptor’s location for a given Source Level (SL) and frequency, it is necessary to model Transmission Loss (TL) through the path from source to receiver. Then, using knowledge gained from propagation modelling, RLs are predicted in three-dimensional space for each spectral band to provide an assess-ment of the frequency band levels surrounding the source, in this case the ADD system.

Effectively, the noise-exposure process may be divided into several parts:

1. ADD noise emission, in terms of parameters specific to the source; 2. ADD noise-transmission process (which depends on boundary and

environmental conditions); and, 3. Sensitivity of the marine-mammal receiver at the location where

ADD noise is detected.

The research objectives of this modelling effort include: (1) under-standing, predicting, and exploiting spatial variability of underwater sound propagation of six types of commercially used ADD in Scottish waters; (2) assessing impacts on marine mammals using the Southall

Fig. 1. Locations of active finfish aquaculture sites within the northern portion of the Inner Hebrides & the Minches Special Area of Conservation (SAC), sourced from http://aquaculture.scotland.gov.uk/map/map.aspx, cross referenced and confirmed with Google Maps satellite view in August 2020. Coordinates in WGS 84 decimal degrees.

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et al. (2019) noise exposure criteria to estimate potential for auditory impact to marine mammal hearing groups; (3) establishing how altering individual ADD ‘transmission variables’ (SL, frequency, duty cycle, duration of exposure, and number of ADDs active simultaneously), may vary predictions of impact; and, (4) presenting underwater-soundscape modelling to aid noise impact assessment at existing, and future fish farm sites.

2. Materials & methods

For the purposes of this study, the modelled ADD sources were placed in geographical locations known to not contain finfish farms or actively transmitting ADDs to ensure impartiality, but with environ-mental conditions consistent with finfish farm locations. Cumulative modelling of existing fish farms equipped with ‘fictional’ ADDs, with realistic noise-transmission parameters was also performed to investi-gate how altering one transmission variable at a time influenced impacts on marine mammals.

2.1. Modelling locations

Fig. 2 shows two real Scottish west coast locations where ‘notional’ fish farms and ADD sources were placed for modelling simulations.

The ‘open water site’ was located at the entrance to Loch Ewe, near Rubha Beag at WGS 84 57.88◦ N, 5.72◦ W, and the ‘semi-enclosed site’ was located in Loch Carron close to Plockton at 57.35◦ N, 5.66◦ W. Water depth at both sites was ca. 30 m. Both sites were deemed repre-sentative of typical fish farm locations, and there were active fish farms located in the vicinity to both sites. Open location line-of-sight water depth ranged from 0 m to the abyssal plane, but for modelling purposes, depth was curtailed at 450 m, just off the continental shelf edge. Semi- enclosed location water depth ranged from 0 to 240 m.

For cumulative modelling, a selection of 23 real, active fish farm locations were chosen from the northern portion of the harbour porpoise SAC. Sites were selected to give approximately even spatial coverage (Fig. 2). If multiple fish farms were adjacent to each other, only one was

used for modelling, resulting in roughly half (23) of the existing 44 fish farms in the area being included in the model. All fish farms were placed in a water depth of ca. 30 m with ADD source at 15 m depth (typical of finfish farm & ADD deployment depths); however, to align with the bathymetry map, some locations required slight adjustment and may therefore not appear exactly as displayed in Fig. 1. It is acknowledged that this arrangement of ADDs may not reflect actual active sites at any one time, but serves to give an indication of potential cumulative effects at a larger scale.

2.2. Commercial ADDs

The current most frequently used commercially available ADDs for Scottish aquaculture were selected for modelling (Table 1).

While empirically-derived field measurements of SL and frequency spectra exist for some devices (e.g. Jacobs and Terhune, 2002; Lepper

Fig. 2. Locations of notional ‘open’ (northern) and ‘semi-enclosed’ (southern) fish farms, and cumulative effects of multiple devices (circles) existing fish farms used for Acoustic Deterrent Device (ADD) modelling on the west coast of Scotland. Most of the region falls into a Special Area of Conservaton (SAC) designated for harbour porpoise. Coordinates in WGS 84 degrees.

Table 1 Developer-reported ADD tonal-transmission variables in order of highest-to- lowest SL used in modelling, including signal classification as per the Southall et al. (2019) assessment criteria. RMS = Root Mean Square.

Acoustic deterrent device

Source level (dB re 1μPa RMS @ 1 m)

Frequency (kHz)

Duty cycle (%)

Signal type

Airmar dB Plus II 198 10 50 Non- impulsive

Ace Aquatec US3 196 10–20 0.7–8 Non- impulsive

Ace Aquatec RT1 195 1–5 0.7–8 Non- impulsive

OTAQ SealFENCE standard mode

189 9–11 31.5 Non- impulsive

GenusWave Targeted Acoustic Startle Technology (TAST)

182 0.5–1.5 0.8–4 Impulsive

OTAQ SealFence patrol mode

165 9–11 9 Non- impulsive

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et al., 2004; Shapiro et al., 2009; Brandt et al., 2012; McGarry et al., 2020; Todd et al., 2021), these introduce, inter alia, variations in geog-raphy, oceanography, source-operating status, source number online, input-power levels, directionality, and calibration status into results; consequently, for consistency, only developer-provided, SL, frequency range, and highest reported duty cycle were used for modelling (Table 1), obtained either from developers’ websites or from values reported in McGarry et al. (2020). Duty cycle is usually based on the total duration of ‘on’ and ‘off’ periods. This does not take into account pulsed signals when the ‘on’ period may be comprised of multiple short (10s of ms) pulses. Nor does it account for the effective duty cycle of the system where multiple units are deployed.

Noise from ADDs was considered tonal, non-impulsive (continuous) for each commercially available and ‘fictional’ device, except the GenusWave TAST. The short (<5 ms) rise time of the GenusWave TAST, which is intended to elicit a startle response in seals (Gotz and Janik, 2015), was considered to produce impulsive noise, and as such, signals were treated differently when estimating potential impact to marine mammals (see Section 2.6). Each model was run using input parameters specified in Table 1 for a duration of 24 h.

2.3. Fictional ADDs

Simulations were run to investigate how SL, frequency, duty cycle, hours of exposure, and number of ADDs operating simultaneously (all termed collectively here as ‘transmission variables’) affect impact pre-dictions. The simulations were run using VHF cetacean (harbour por-poise) for all scenarios, and LF cetacean (minke whale) for the frequency range comparison. These ‘fictional’ (i.e. artificial) ADDs were modelled as non-impulsive sources (Table 2).

For comparability (and to prevent nearby land influencing results), simulations were run at the open-water location only, under the same source depth and propagation conditions as detailed previously. More-over, to reproduce typical, real-world fish farm ADD deployment con-figurations, models with multiple ADD sources were arranged on a grid with devices spaced 50 m apart in two rows.

2.4. Noise metrics

Further explanations of noise metrics are given in Todd et al. (2021). A variety of noise-level indicators were chosen appropriate to analysis of the tonal, non-impulsive nature of all ADD model sources, except the impulsive GenusWave TAST, where PTS/TTS threshold data of which were treated differently (see Section 2.6). Root-Mean Square Source Level (RMS SL) was selected as the input for modelling, as it was the metric most consistently provided by developers.

Sound Exposure Level (SEL) is a measure of the pulse energy content and is calculated from a pulse pressure squared integral of the pulse in units of Pa2s, with the value units in dB (Madsen, 2005). This metric was selected for impact assessment to both be in line with other underwater acoustics researchers (e.g. Blackwell et al., 2004; Madsen, 2005; Schaf-feld et al., 2020), and for comparison with the Southall et al. (2019) noise exposure criteria. SEL is also useful when considering the dose level of a receptor over time, such as 24 h, as modelled in this study.

2.5. Model selection

As per the groundtruthed ADD noise measurement & modelling study of Todd et al. (2019), a two-dimensional ray-tracing based un-derwater acoustic model (Porter and Bucker, 1987; Yang et al., 2009; Jensen et al., 2011; Porter, 2011; Dong and Dong, 2014; Gul et al., 2017) was used to predict, and explore temporal (hourly, daily), and spatial (on-site, local, and regional) propagation of underwater ADD noise across the open and semi-enclosed water locations. This is a traditional beam-tracing model for predicting acoustic pressure fields in ocean environments and is most suited to shorter range, mid-to-high frequency

scenarios. The ray-tracing model was developed originally by Mike Porter at HSL Research. Alec Duncan from the Centre for Marine Science and Technology at Curtin University wrote the Acoustic Toolbox User- interface (AcTUP) for the program.

In most cases, prevailing geography (headlands, islands) and elevated-subsea bathymetry were expected to restrict ADD noise prop-agation to a few kilometres. Consequently, the model was constructed using European Marine Observation and Data network, bathymetry data (EMODnet Bathymetry Consortium, 2018) for the entire region. Fish farms were located in 30 m water depths with an ADD source depth of 15 m. Calculations were set to the gridded-spatial resolution of the ba-thymetry data (ca. 115 m × 115 m), with results exported for visual-isation in 2D plots along 100 radial slices (3.6◦) at 200 distance bands (1.08 km) for the open site, and 100 radial slices at 100 (368 m) distance bands for the semi-enclosed site. Analysis was performed at 150 depth bands, resulting in vertical resolution of 5.3 m for the open site and 1.7 m for the semi-enclosed site. Results were displayed as the highest value

Table 2 Fictional, non-impulsive ADD model simulations of various noise- transmission variables run at the open water location. Grey cells repre-sent the single variable altered between each iteration.

Source level (dB re 1μPa RMS @ 1 m)

Frequency (kHz)

Duty cycle (%)

Exposure (h) Number of ac�ve ADDs

165 8–12.5 10 1 1

170 8–12.5 10 1 1

175 8–12.5 10 1 1

180 8–12.5 10 1 1

185 8–12.5 10 1 1

190 8–12.5 10 1 1

195 8–12.5 10 1 1

195 1–5 10 1 1

195 8–12.5 20 1 1

195 8–12.5 30 1 1

195 8–12.5 50 1 1

195 8–12.5 100 1 1

195 8–12.5 10 6 1

195 8–12.5 10 12 1

195 8–12.5 10 18 1

195 8–12.5 10 24 1

195 8–12.5 10 1 2

195 8–12.5 10 1 4

195 8–12.5 10 1 6

195 8–12.5 10 1 8

195 8–12.5 10 1 12

195 8–12.5 10 1 16

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from all depth bands, e.g. the highest value from each x,y location. For the seabed, only surficial sediment data are necessary at all six-

commercial ADD frequencies of operation, because signal penetration at these wavelengths is limited and unlikely to contribute to down range re-emergence back into the water column. Consequently, bottom- sediment type was used to define a simple loss vs. grazing angle meth-odology which is used commonly in ray/beam models. Geoacoustic parameters of the bottom boundary were assumed to be those of mud (typical of the area), with an estimated speed of sound of 1700 ms− 1, a density of 1500 kg m− 3, and an attenuation of 1 dB/wavelength (Jensen et al., 2011). While absorption is frequency dependent and negligible for low frequencies and short distances, under normal circumstances for a 10 kHz signal (e.g. the prime operating frequency of the OTAQ and Airmar ADDs), a typical absorption of 0.8–1 dB per km can be assumed. To reduce computer processing time, modelling was restricted to fre-quencies between 125 Hz and 32 kHz, as the devices investigated are stated to only produce noise from 0.5–20 kHz. Results were exported as Sound Exposure Level (SEL) for all devices.

To use the ray-tracing model, sound profiles of the considered area must be known or predicted. Consequently, all simulations assumed a harmonic median sound speed, chm, of 1500 ms− 1, Beaufort sea state 0, a temperature of 8 ◦C, a salinity of 35 PSU, and no influence of currents or ambient noise floor, i.e. worst-case scenario signal-propagation condi-tions. These conditions can, and do occur on the west coast of Scotland, and so were reasonable assumptions for the area. Use of these parame-ters also facilitated comparison of the operational elements of ADD signals as opposed to differences due to environmental factors.

Potential cumulative impacts of multiple aquaculture facilities operating ADDs simultaneously were investigated by modelling noise propagation from a selection of 23 fish farms in and around the Minch (Fig. 2). All locations were based on real fish-farm positions, and were assumed to operate one fictional ADD unit on a 10% duty cycle for 24 h at a frequency range of between 8 and 12 kHz, with a SL of either 165 or 195 dB re 1μPa RMS @ 1 m. All other parameters were the same as described above for the open-water site.

2.6. Marine mammal assessment criteria

The range over which marine mammals hear ADD signals depends on distance from the source that either falls below the perceived ambient- noise level or the individual’s auditory threshold. It is important to note that noise perception does not necessarily constitute auditory or behavioural impact. There are considerable differences in factors that influence observed response, such as an animal’s behaviour at the time of exposure, previous exposure history, sex and age of individual, background noise and the environmental conditions that affect local propagation (McGarry et al., 2020). Currently there are no agreed behavioural thresholds and so this study focused on PTS and TTS thresholds.

Weighted thresholds (Southall et al., 2019) for PTS and TTS for the tonal, non-impulsive, continuous nature of the majority of ADD signals were used to investigate potential impacts on marine mammals

(Table 3). The GenusWave TAST was the only model of ADD considered to generate impulsive signals; consequently, impulsive PTS/TTS thresholds were used for this device only (Table 3).

Hearing groups investigated included Low Frequency (LF), High Frequency (HF), and Very High Frequency (VHF) cetaceans and Phocid Carnivores in Water (PCW) (Southall et al., 2019). Analysis assumed animals did not flee from the noise source and, in combination with the assumed calm weather and optimal oceanographic conditions for propagation, was thus considered to be a worst-case scenario in pre-senting PTS/TTS ranges, and is likely to be an overestimate of impact, as animals are assumed to remain within the impact range. Considering ADDs are used on ca. half of Scottish salmon farms, a fleeing model was not used, as animals may flee a single source only to encounter another ADD on another fish-farm shortly afterwards. Moreover, ADD use in the area has been ongoing for decades, and it is entirely possible that habituated animals may not demonstrate fleeing behaviour, but continue to exploit suitable foraging opportunities within ensonified areas. Moreover, since knowledge of marine mammal behaviour in the presence of ADDs (especially these models) is extremely scarce/absent, a worst-case scenario was considered to be the optimal, initial approach.

3. Results

Desk-based noise-propagation modelling of six commercially avail-able and ‘fictional’ ADDs, and their cumulative potential impacts on Scottish west coast marine mammals, are presented.

3.1. Commercial ADDs

Table 4 presents Southall et al. (2019) calculated PTS and TTS weighted hearing thresholds for all six commercial models of ADD at the notional open location, which is represented visually in Fig. 3. Fig. 4 presents the same information at the semi-enclosed water site. Table 4, Figs. 3 and 4 and , highlight that commercial ADDs with the loudest reported SLs (as presented in Table 1) exhibited highest SELs and TTS and PTS ranges.

ADD noise propagates much further in the open water site Fig. 3 (open water) in comparison to the semi-enclosed site Fig. 4 (semi- enclosed water). Radiated ADD noise was obscured by land in all di-rections at the semi-enclosed site, preventing signals from propagating at the long ranges observed in the open-water location.

There was wide variation in propagation range between the different ADD models depending on reported operating parameters listed in Table 1. For the VHF cetaceans, the OTAQ SealFence patrol mode ADD, with its comparably low SL of 165 dB re 1μPa RMS @ 1 m, potentially caused the smallest (4.34 km) range of TTS. Accordingly, the Airmar dB Plus II, with a comparable centre frequency of 10 kHz, but with a much higher SL of 198 dB re 1μPa RMS @ 1 m, caused the largest range (30.93 km) of TTS. Conversely, TTS for the LF cetaceans was highest for ADDs that emitted lower-frequency noise, with highest impact from the 1–5 kHz AceAquatec RT1 at a TTS range of 17.39 km, and lowest TTS range (0.76 km) from the OTAQ SealFence patrol mode ADD.

3.2. Fictional ADDs

Fig. 5 presents plots of open water iterative model simulations of varying transmission details in terms of Southall et al. (2019) weighted TTS effects on VHF cetaceans, including potential effects of SL, fre-quency, duty cycle, hours of cumulative exposure, and number of de-vices. Potential impacts of changes to operating frequency are also shown for TTS for LF cetaceans (Fig. 5b). Fig. 6 represents these plots in two dimensions.

It is clear from both figures that TTS distances for VHF cetaceans increased with increasing SL, duty cycle, hours of exposure and number of active ADDs. Increasing SL (Figs. 5a and 6a) and duty cycle (Figs. 5c and 6c) did not exhibit a ‘levelling off’ with distance; however, distance

Table 3 Weighted Sound Exposure Level (SEL dB re 1μPa2s) thresholds for non-impulsive and impulsive noise for Temporary and Permanent Threshold Shifts (TTS and PTS respectively) for Low Frequency (LF), High Frequency (HF), and Very-High Frequency (VHF) cetaceans and Phocid Carnivores in Water (PCW) according to the Southall et al. (2019) exposure criteria.

Hearing group Example species Non-impulsive Impulsive

TTS PTS TTS PTS

LF Minke whale 179 199 168 183 HF Dolphin spp. 178 198 170 185 VHF Harbour porpoise 153 173 140 155 PCW Grey and common seal 181 201 170 185

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appeared to plateau at higher hours of exposure and number of devices (Fig. 5e). Frequency also impacted the range at which cetaceans may have experienced TTS, with VHF cetaceans potentially experiencing TTS at larger ranges for higher frequency devices (8–12.5 kHz) than lower frequency devices (1–5 kHz); however, the inverse was true for LF ce-taceans, which displayed higher potential impact for devices operating at lower frequencies (Fig. 5b).

When ADDs were operated on a 10% duty cycle for 1, 6, and 12 h,

increases in distance of TTS were observed; however, operation for 18 or 24 h a day showed a negligible increase (Fig. 6d), and also very little difference when there were six or more ADDs active simultaneously at a site (Fig. 6e). A scenario of a single fictional device operating at 195 dB re 1μPa RMS @ 1 m at a frequency of 8–12.5 kHz on a 100% duty cycle for 24 h (Fig. 6f) was predicted to cause potential TTS to VHF cetaceans at a range of up to 32 km.

Table 4 Southall et al. (2019) calculated hearing group Permanent Threshold Shift (PTS) and Temporary Threshold Shift (TTS) ranges (in m) for the six commercial brands of ADD at the open-water location based on a single device operating for 24 h. Using Weighted Sound Exposure Level (SEL dB re 1μPa2s) thresholds for non-impulsive and impulsive noise.

Hearing group LF HF VHF PCW

Impact criteria PTS TTS PTS TTS PTS TTS PTS TTS

Airmar dB Plus II 3817 13,032 3816 12,772 13,292 30,928 3816 12,773 Ace Aquatec US3 1439 5966 1667 5990 7063 17,922 1443 5967 Ace Aquatec RT1 2736 17,379 760 4874 4629 24,955 1678 11,125 OTAQ SealFENCE standard mode 1439 5991 1439 5989 7062 19,808 1241 5980 GenusWave TAST 2739 10,951 NA 758 762 4914 762 4915 OTAQ SealFENCE patrol mode NA 758 NA 758 760 4336 NA 758

Fig. 3. Weighted Southall et al. (2019) marine mammal hearing thresholds and SEL (dB re 1μPa2s) for all commercially available ADD brands at the open water location. All assume non-impulsive signals, except the impulsive GenusWave TAST. Coordinates in WGS 84 decimal degrees.

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3.3. Cumulative impacts

It is apparent from Fig. 7 that, again, SL was the dominant factor affecting 24-h, cumulative impact of a single, fictional 8–12 kHz ADD operating on a 10% duty cycle transmitting simultaneously on 23 aquaculture facilities. By increasing SL by 30 dB, Fig. 7b highlights that ADD noise could theoretically cover large swathes of the Inner Hebrides and the Minches SAC.

4. Discussion

ADDs with highest reported SLs exhibited greatest TTS and PTS ranges and signals propagated furthest in the notional open-water location; however, before any perceived implications on marine mam-mals can be discussed, it is important to highlight caveats that render desk-based noise propagation modelling of a non-fleeing animal a truly worst-case scenario for assessing impact.

Any simulation is only as accurate as its input parameters, and one of the key factors modelled was SL, which can be derived in several ways. Since the term ‘SL’ originates in sonar engineering, it is conceivable that some ADD manufacturers performed conversions of electrical power

through a transducer to acoustic power (or intensity), instead of more accurate calibrated empirical (tank or field) measurements; therefore, reported ADD SLs could be higher than real-calibrated values, which could result in over estimation of RLs. When measured empirically, acoustic-output SLs can vary with depth of source due to surface in-teractions, or be affected by fish-farm site configuration, fouling on the transducer and/or lower battery voltages (Lepper et al., 2014; Todd et al., 2021). Moreover, as with acoustic power, SL is a characteristic of the source type itself, and can vary with direction. For example, Shapiro et al. (2009) found differences in measured SLs of various Airmar pingers (not seal scarers) of up to 4.7 dB in different directions. In the-ory, a well-specified ADD SL should provide direction of measurement or plot the level (dB re 1 μPa RMS @ 1 m) as a function of angle; however, this is an idealised acoustic far-field parameter of SPL, that would exist at 1 m range from the acoustic centre of the equivalent ‘simple’ source, which radiates the same acoustic power into the me-dium as the source in question. For a simple source like an ADD, pressure is inversely dependent on range; however, for real ADD sources in field conditions, the SL-value is highly unlikely to represent actual SPL at this range. For a large distributed 16-ADD source on a fish farm, a position so close to the source may be in the acoustic nearfield (or even inside the

Fig. 4. Weighted Southall et al. (2019) marine mammal hearing thresholds and SEL (dB re 1μPa2s) for all commercially available ADD brands at the semi-enclosed water location. All assume non-impulsive signals, except the impulsive GenusWave TAST. Coordinates in WGS 84 decimal degrees.

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source). Indeed, real-world field measurements of SL are generally quieter. For example, developer-reported SL of the Airmar dB Plus II is 198 dB re 1μPa @ 1 m RMS, but reported SLs in the literature range from 190 to 192 dB re 1μPa @ 1 m RMS (Lepper et al., 2004; Brandt et al., 2012); however, extreme caution must be applied when contrasting SLs with those reported in the literature, inter alia, because of different units, calculation methods, and environmental conditions at the time.

The next factor to consider is propagation of noise in the ocean, which is complicated especially in shallow water. Empirical-noise transmission that affects levels received by animals three- dimensionally in the field, is difficult to predict in real-word complex and range-dependent environmental settings. For example, a moderate level source transmitting over an efficient (ideal) propagation path may produce the same received SPL, as a higher-level source transmitting through a ‘lossy’ propagation path. Moreover, in deep water (where ADD signals travelled long range at the open-water location), variations in water properties such as temperature, salinity, sea state, etc., affect sound propagation strongly (Marsh and Schulkin, 1962). Conversely, in

shallow waters (e.g. of the semi-enclosed location), surface and bottom have stronger effects. Variation in bathymetry, and thus physical ‘ob-stacles’ can also have significant effects on sound transmission (as evi-denced strongly in this study, especially in the semi-enclosed water location).

There was no background noise in simulations. In real-life scenarios, background noise plays a role on RL. Aside from presence of air bubbles, wind, wave, surf rain, etc. and noise from biological organisms, there are a number of other contributing anthropogenic sources that influence levels detected by animals at range from a source. On a real fish farm, noise floors are likely to be elevated by vessels, wave slap on hard structures, fish-feeding pumps, toilets, aerators, and compressors, personnel walking on pontoons, etc. Specifically, for a fish farm, ma-chinery noise emitted through coupling with pontoon will likely be apparent.

It is also worth mentioning that sound speed in the real world in-creases with increasing temperature, depth (hydrostatic pressure), and salinity, highlighting further, the simplicity of the constant

Fig. 5. Open water iterative model simulations of non-impulsive fictional ADD transmission variables in relation to weighted Southall et al. (2019) Very High Frequency (VHF) and Low Frequency (LF – in b) cetacean Temporary Threshold Shift (TTS) hearing thresholds represented as distance from source.

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oceanographical parameters set the modelling scenario which provide a worst-case estimate of noise propagation. In general, temperature de-creases with depth, and strongest dependence is on temperature. This leads to a complex variation of sound speed with depth. In real field conditions, the sound speed profile may be divided into several layers. Just below the surface is what is sometimes called the ‘surface layer’ where sound speed is susceptible to daily changes due to heating, cooling, and wind action. This is followed by a seasonal thermocline, a region characterised by a negative sound-speed gradient due to the decrease in temperature with depth. Below the main thermocline and extending into the deep ocean is the deep isothermal layer, which is nearly constant in temperature at about 4 ◦C. In this layer, sound speed increases with depth due to increasing hydrostatic pressure. Variation with salinity is less of an influence in deep oceanic waters, but can have a strong influence where water layers of different salinity are mixing, for example at the estuaries of fresh-water rivers, which is highly typical in Scottish sea lochs, where entire upper layers of the water column can be freshwater runoff (Boyd et al., 2010). Moreover, the region of influence of a sound source can vary dramatically depending upon fish farm operating site and depth, and on seasonal changes in water properties. All these factors alter the real RLs of noise received by marine mammals at the various distances (and water depths) from the source in the field.

While duty cycles used here were the highest reported by developers for a single device, in reality, ADDs are deployed in multiple arrays on a single fish farm. Consequently, duty cycles in the field are higher than those used here. In conclusion, with exception of SL (which is considered to be independent of its immediate surroundings), and duty cycle (which serves to potentially increase ADD TTS/PTS ranges), all other

environmental factors (e.g. wind, rain, waves, tides, sediment transport, etc.) serve to lessen ADD PTS/TTS ranges; therefore, any form of desk- based modelling should be treated as an indicative, risk-based approach, rather than a definitive evidence base for assessment as to whether there is potential for any ADD in any situation to cause impact (McGarry et al., 2020).

4.1. Commercial ADDs

Quick et al. (2004) and Northridge et al. (2010) reported that ADDs are used at ca. half of Scottish fish farms, and Findlay et al. (2018) demonstrated an increase in acoustic detections of ADDs between 2006 and 2016, showing that their use continues to rise, with the ratio of ADD detections to number of acoustic recordings more than doubling over those 11 years. The potential effects of ADD noise on non-target species is therefore a problem that needs to be addressed.

In this study, the commercially available ADDs with least potential impact to VHF cetaceans were the OTAQ SealFENCE patrol mode and GenusWave TAST. Both devices’ manufacturers reported lower SLs of 165 and 182 dB re 1μPa RMS @ 1 m respectively, which corresponded to only a 190 m difference in VHF TTS between the two ADDs at just under 5 km for both; however, one potential disadvantage of the lower fre-quency GenusWave TAST compared to the higher frequency OTAQ SealFENCE patrol mode, is that the former had a larger predicted impact than OTAQ SealFENCE patrol mode on LF cetaceans, such as the minke whale, which is also a species of concern in Scottish waters. The OTAQ patrol mode had the lowest potential impact on the LF group at only 0.76 km, and no PTS. To date, the only controlled exposure study to test

Fig. 6. Open water influence of alternating permutations of ADD transmission variables on weighted Southall et al. (2019) Very High Frequency (VHF) cetacean (e.g. harbour porpoise) Temporary Threshold Shift (TTS) hearing thresholds. F) depicts a scenario for a single device using the highest output levels investigated. Co-ordinates in WGS ’84 decimal degrees.

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effects of an ADD on LF cetaceans was performed by McGarry et al. (2017). These workers tested a Lofitech ADD in Faxafloi Bay, Iceland and found that minke whales both increased speed and directness of their path in relation to exposure to ADD playback. The unit deployed in that study was found to have a SL of 198 dB re 1 μPa RMS @ 1 m for a fundamental frequency of 14.6 kHz. Developers on the GenusWave attempted investigation into effects on minke whales; however, sighting rates were low, and while they reported no evidence of impacts at dis-tances greater than 1 km, they were unable to determine effects conclusively (Gotz and Janik, 2015). While there are no direct measures for auditory thresholds in the LF group, the 0.2–19 kHz range of minke whale audibility given in Southall et al. (2019), has been derived from minke whale vocalisation data (e.g. Schevill and Watkins, 1972; Gedamke et al., 1997; Edds-Walton, 2000), reactions to sound playbacks (e.g. Sivle et al., 2015) and auditory system anatomical measurements (e. g. Tubelli et al., 2012). This reinforces the notion that when it comes to potential effects of ADDs on non-target species, the phrase ‘once size fits all’ does not apply.

The device with the largest impact on VHF cetaceans was the Airmar dB Plus II, which was reported by Findlay et al. (2018) to be the device used most commonly on Scottish fish farms, representing ca. 80–95% of acoustic ADD detections within the area between 2011 and 2015. This ADD had the highest SL and duty cycle of all ADDs tested. Previous studies have predicted that common seal may be able to hear an Airmar (specific model not known) at ranges of 20 km in ideal conditions, and harbour porpoise up to 42 km (Jacobs and Terhune, 2002; Olesiuk et al., 2002).

4.2. Fictional ADDs

The single factor which had greatest influence on potential impact ranges to harbour porpoise from fictional devices investigated was reducing SL, which resulted in ranges of TTS of ca. 1 km at a SL of 165 dB re 1μPa RMS @ 1 m, compared to 12 km at SL of 195 dB re 1μPa RMS @ 1 m (Fig. 6a). Altering ADDs to use lower frequencies (e.g. 1–5 kHz as opposed to 8–12.5 kHz) reduced the potential impact on VHF cetaceans, but nearly doubled predicted impact on LF cetaceans; therefore, consideration of species most likely to be present in an area is required before recommending this as a mitigation measure. Increases to duty cycle exhibited a nearly linear trend between 10% and 100% duty cycle resulting in potential VHF TTS at 12 to 18 km respectively.

Operating the ADD for 24 h, as opposed to 1 h, caused the range of potential TTS to nearly double (12 km to 22 km). A reduction in hours of ADD operation could be proposed as a means of minimising potential impact, but it would need to only be active a few hours a day, since range of TTS was nearly 20 km even at 12 h of operation. Operators could also take advantage of intermittent cycling of devices, so they are active for e. g., 30 min every 3–4 h. Investigation of time of day when most predation events occur could be used to target times when ADDs should be active. For example, Sepúlveda and Oliva (2005) reported that predation events of South American sea lions (Otaria flavescens) on Chilean aquaculture facilities occurred generally at night.

An increasing number of active devices operating simultaneously from the same location caused predictions to rise; however, this appeared to plateau at six or more devices operating simultaneously, with limited additional impact (Fig. 5e). Many current facilities use arrays of devices with up to 24+ devices. Most operate on a random

Fig. 7. Predicted combined, cumulative (24-h) impact of a single ‘fictional’ 8–12 kHz ADD operating at a 10% duty cycle, with a SL dB re 1μPa RMS @ 1 m of either a) 165 or b) 195 transmitting simultaneously on 23 aquaculture facilities in and around the Minch. Coordinates in WGS 84 degrees.

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operation cycle in which case multiple devices may, by chance, activate at the same time. This could be averted by using systems in which multiple transducers are all choreographed from a central control unit to prevent activation of multiple devices simultaneously, which is appar-ently the case with the OTAQ patrol mode ADD (Todd et al., 2021). Nevertheless, after a certain point, increasing number of devices oper-ating simultaneously does not appear to cause increasing impact.

4.3. Cumulative impacts

The predicted combined, cumulative (24-h) impact of a single ‘fictional’ 8–12 kHz ADD operating at a 10% duty cycle, with 195 dB re 1μPa RMS @ 1 m SL transmitting simultaneously on 23 aquaculture facilities in and around the Minch produced disturbing visual results, that included potential ‘barriers of noise’ across the Minch. Aside from the aforementioned caveats applied to desk-based modelling, the 23 fish farms were selected to have ADDs that provided roughly even spatial coverage over the entire area, which is likely not the case in reality. Moreover, if multiple farms were located very near each other, only one was assumed to have active ADDs. In reality, adjacent fish farms often operate ADDs simultaneously, so clusters of fish farms may present comparably higher cumulative impact than predicted in this scenario. Additionally, there are areas that are particularly affected by seal depredation attempts, rendering ADD use ‘patchier’ than modelled here.

Finally, the conservative models in this study assumed that animals remained in ADD-ensonified areas permanently, which was likely to be only partially realistic. It has been demonstrated that large swaths of the west coast were probably ensonified with ADD noise {Findlay 2018 #13887}. This could mean that animals may habituate to noise, or be exposed to ADDs from different fish farms for extended durations, as they move around the coastline. In the case of harbour porpoise, which have a high metabolic/feeding rate (Lockyer, 2007; Wisniewska et al., 2016; Hoekendijk et al., 2018), if ADDs are located in areas of high prey availability, it is possible that animals remain exposed to ADD noise for longer, potentially increasing their risk of TTS (Schaffeld et al., 2020), although, porpoise may be able to self-mitigate and reduce their hearing sensitivity when potentially predicting noisy events (Kastelein et al., 2020); however, while marine-mammal-fleeing behaviour/habituation studies (especially for these models of ADD) are lacking in the literature, it is feasible that animals would move out of the region, as some studies have demonstrated fleeing from a disturbing or startling sound source (Gotz and Janik, 2011). Since the extent of fleeing/habituation behav-iour in marine mammals around West coast fish farms is unknown, and studies are needed urgently, in reality there would likely be a mixture of avoidance of ‘hotspot ADD-noise areas’ and habituation. Certainly for porpoises, other anthropogenic noise behaviour studies (such as play-backs of loud and impulsive pile-driving noise), have elicited avoidance reactions, such as increased swimming speed and moving tens of kilo-metres away from the source (Kastelein et al., 2013); however, such extreme ranges of disturbance/avoidance are not expected for ADDs. This is because field trials using an Airmar dB Plus II (the loudest commercially available device tested here) have reported harbour- porpoise approach distances as close as 200–650 m from the source, and a significant decrease in detection up to 3.5 km away (Johnston, 2002; Olesiuk et al., 2002). The behaviour of minke whales, however, is likely to differ from that of porpoises, inter alia, because they have lower- frequency hearing and may be more sensitive to these devices. Indeed McGarry et al. (2017) demonstrated that minke whales all moved away from a Lofitech ADD (not used in aquaculture), increasing their swim-ming speed by 7.4 km h− 1. Any marine mammal species’ ability to flee from an ADD depends on its ability to locate the source correctly. Localisation abilities of ‘LF specialist’ common seals have been tested between 0.2 and 16 kHz, with better localisation capacity at lower fre-quencies (Bodson et al., 2007). Harbour porpoise’ ability to locate sources has not been tested below 16 kHz (Kastelein et al., 2007), and it is not known how well they can localise lower frequencies (Schaffeld

et al., 2020), which may impact their ability to flee. Nevertheless, model results highlight that noise from these devices can be widespread in the environment, potentially causing far-ranging impacts at scales that had not been considered previously.

4.4. Conclusions

The single ADD variable that has potential to cause greatest miti-gation in potential impact to non-target marine mammals was a reduc-tion in SL. Unexpectedly, reducing number of ADDs operational simultaneously, had minimal impact on TTS beyond a number of six units, and increasing duration of operation plateaued at ca. 18 h. Lowering ADD frequency lessened impacts on VHF cetaceans (harbour porpoise), but at the cost of the LF group (minke whale), reinforcing the conclusion that when it comes to producing the ‘ideal’ ADD, ‘one size does not fit all’.

This desk-based study has proven a useful, yet inexpensive exercise in demonstrating how interplay between simulations of various ADD- transmission variables may serve to lessen impact on marine mammals in Scottish waters (all of which are protected by UK & EU law). It should be noted that, in addition to potential impacts on non-target species, selection of devices for use on fish farms is also influenced by their in-dustry preference and presumed efficacy in preventing seal predation – an aspect which has not been investigated here. Assessing efficacy of devices in deterring seals, and even noise produced by ADDs in real field conditions, is still largely an open area of research. It is hoped that re-sults of this work will provide useful insights for managers when con-senting devices for use on finfish farms and encourage ADD manufacturers to continue efforts to develop the most effective device at deterring seals, while minimising potential impact to non-target species in a bid to achieve compliance with current and future underwater-noise regulations.

CRediT authorship contribution statement

Victoria L.G. Todd: Funding acquisition, Conceptualization, Inves-tigation, Writing – original draft, Writing – review & editing. Laura D. Williamson: Funding acquisition, Conceptualization, Formal analysis, Writing – original draft, Writing – review & editing. Jian Jiang: Conceptualization. Sophie E. Cox: Project administration. Ian B. Todd: Project administration. Maximilian Ruffert: Writing – review & editing.

Declaration of competing interest

The authors declare the following financial interests/personal re-lationships which may be considered as potential competing interests: The lead author at OSC (Victoria Todd) has worked together with most of the ADD manufacturers since 2003, originally as a post doc at the Scottish Association of Marine Science (SAMS), and latterly as managing Director of Ocean Science Consulting (OSC), an independently-funded private research company; however, OSC won the competitive Scottish National Heritage (SNH) tender process for the investigation presented here, with full knowledge by SNH of the historical and current working relationships between OSC and the various ADD manufacturers. There is no conflict of interest, as OSC is not a manufacturer of ADDs, and was not funded by any manufacturers to produce this work. It is worth noting that another marine mammal academic research institute both publishes papers on, and own a shareholding, in a firm that both manufactures and leases ADDs commercially; consequently, we do not feel that this paper can be seen as any conflict of interest, especially as no single ADD manufacturer participated in any aspect of this research.

Acknowledgements

This study was funded by NatureScot, formerly Scottish Natural

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Heritage (SNH). We gratefully acknowledge guidance and assistance during this project from Caroline Carter, Liam Wright, George Lees (NatureScot), Ross Culloch and Hannah Millar (Marine Scotland Science).

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