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Applied Ichthyology J. Appl. Ichthyol. 32 (2016), 18–31 © 2015 The Authors. Journal of Applied Ichthyology Published by Blackwell Verlag GmbH. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. ISSN 0175–8659

Received: March 5, 2015 Accepted: June 24, 2015 doi: 10.1111/jai.12940

Limited influence of a wind power project submarine cable on a Laurentian Great Lakes fish community By E. S. Dunlop, S. M. Reid and M. Murrant Aquatic Research and Monitoring Section, Ontario Ministry of Natural Resources and Forestry, Trent University, Peterborough, ON, Canada

Summary Previous research has identified the generation of electromagnetic fields (EMFs) emanating from renewable energy project transmission cables to be a potential stressor to aquatic communities. In this study, we investigated whether the presence of a high voltage submarine transmission cable affected the spatial pattern and composition of nearshore and offshore fishes at a Laurentian Great Lakes site. The transmission cable investigated in this study runs 7.8 km along the lakebed of Lake Ontario, carrying electricity from the Wolfe Island wind power project to the city of Kingston, Ontario. In autumn of 2011, both nearshore electrofishing and deeperwater fisheries acoustic surveys were conducted along transects at varying distances to the cable. For both habitat types, no detectable effects of the cable on the fish community were found. Local habitat variables, including substrate or depth, were more important in explaining variation in fish density than proximity to the cable. Common species encountered during the surveys were round goby (Neogobius melanostomus) in the nearshore and alewife (Alosa pseudoharengus) in the deeper channel. American eel (Anguilla rostrata), thought to be an electromagnetically sensitive species, was also encountered during the surveys including in close proximity to the cable. More robust impact assessments require sampling fishes before a cable installation, over greater time frames (additional seasons or years), and habitats that support more diverse native assemblages.

Introduction Submarine transmission cables are present in aquatic systems around the world and are used to carry electricity generated from offshore areas or carry electricity between land masses. These transmission cables are increasingly being employed as part of renewable energy projects, including offshore wind power installations and in-stream hydrokinetic projects. When electricity created from wind power or other sources moves through underwater transmission cables, electric and magnetic fields are created (Worzyk, 2009; Gill et al., 2012). Modern cables are often armoured, which prevents penetration of the directly produced electric field beyond the cable armouring. The magnetic field, however, penetrates the shielding and is emitted into the surrounding environment. U.S. Copyright Clearance Centre Code Statement:

Induced electric fields are then created when objects, including organisms such as fish or even water currents, pass through the magnetic field (Gill et al., 2012). Collectively the electric and magnetic fields created as a result of a transmission cable are referred to as electromagnetic fields (EMFs). The geomagnetic field can also be disturbed in the immediate vicinity of a power cable (Worzyk, 2009). Cable burial does not shield magnetic fields, but increases the distance between the cable and objects moving through the water (Gill et al., 2012). Certain fishes have been identified as being able to detect and respond to electric and/or magnetic fields. There is evidence that magnetic field perception aids navigation in migrating fish, such as Pacific salmon (Putman et al., 2014a,b) and eels (Durif et al., 2014). The presence of magnetic materials have been detected in the bodies of these migratory fishes (Moore and Riley, 2009). Other species, most notably elasmobranchs, have electro-receptors that might enable them to navigate through Earth’s magnetic field or even detect other fish (Kempster et al., 2012). Some of the most thoroughly studied electro-magnetic sensitive species reside in marine systems. However, species known to be sensitive to EMFs are also present in freshwater systems, including lampreys, catfishes, sturgeon, eels, and several salmonids (Nienhuis and Dunlop, 2011a). In addition to orientation and behavioural responses, EMFs could have physiological effects (e.g. impaired embryonic development) (Formicki and Winnicki, 1998; Lerchl et al., 1998; Ohman et al., 2007; Lewczuk et al., 2014). However, these potential effects have received much less investigation, are expected to be localized to the immediate vicinity of the cable, and are of greatest concern for sensitive life stages. With the expansion of offshore wind power projects in marine systems, there is a burgeoning field of work examining potential environmental effects. These wind power projects can be large, and contain an expansive network of submarine transmission cables that connect turbines and carry electricity to shore. There is considerable uncertainty, however, as to whether these cables and their EMFs have negative effects on fishes. The migratory behaviour and habitat use by some fishes could be affected by the presence of artificially generated EMFs (Ohman et al., 2007; Gill et al., 2012). However, the number of field and laboratory experiments is low and the variety of species tested for sensitivity

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Limited effects of power cable on fish

to EMFs is limited. Although there are currently no offshore wind power projects in the Laurentian Great Lakes or in any other North American freshwater systems, there is the potential for future offshore renewable energy development in these environments as global demand for renewable energy increases. Furthermore, the development of wind power projects on islands or close to lake and river shorelines can require submarine power cables to traverse freshwater environments. A review of the potential impacts of offshore wind power projects to Great Lakes fishes identified that effects related to EMFs represent one of the most significant knowledge gaps (Nienhuis and Dunlop, 2011b). Studies in freshwater ecosystems are needed. The purpose of this project was to investigate the effects of the Wolfe Island wind power project submarine transmission cable on the fish community. The cable is a 7.8 km high-voltage transmission cable that runs across the lakebed of eastern Lake Ontario, connecting a wind power project on Wolfe Island to the mainland power grid near Kingston, Ontario (Canada) (Figs 1 and 2). The Wolfe Island wind power project is an 86 turbine, 197.8 MW project operational since 2009. The cable was laid in 2008 and has a diameter of 235 mm. The cable is buried under rubble and sediment in proximity to shore, but otherwise sits on top of the lakebed, relying on its own weight to hold it in place. The Wolfe Island submarine cable is a high voltage alternating current (HVAC) 3-core XLPE cable. At the time of construction, the transmission cable had the highest voltage (245 kV) of any submarine power cable (Worzyk, 2009), including that of the 91 turbine (209.3 MW project) Horns Rev 2 offshore wind power project in Denmark, which has a

Fig. 1. Map of nearshore boatelectrofishing transect locations along Kingston and Wolfe Island shorelines. Asterisks = cable landings. Right frame = schematic diagram of the point sampling strategy

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maximum cable voltage of 170 kV (Offshore wind farm database: www.4coffshore.com). The high voltage for the Wolfe Island project was possible because of the relatively short cable length (7.8 km), whereas most offshore wind power projects have longer cables running to shore (Worzyk, 2009). We tested whether the spatial pattern and composition of nearshore and offshore fishes were influenced by proximity to the Wolfe Island cable and associated EMFs. As the cable is located in an area of American eel (Anguilla rostrata Lesueur, 1817) stocking, it provided a rare opportunity to characterize the response of an endangered species expected to be sensitive to EMFs. The project had two main components: (i) an electrofishing survey of nearshore fishes; and (ii) a fisheries acoustics survey of fishes inhabiting the deeper areas of the channel. For both surveys, sampling was done at various distances from the cable in order to determine if any detectable effects of the cable’s presence were noted. The overarching goal of the study was to examine whether cable effects are observable at a spatial scale relevant to Great Lakes fisheries management (i.e. at distances greater than just a few meters beyond the cable). Materials and methods Nearshore electrofishing surveys

A spatially intensive daytime boat-electrofishing survey was completed along the shorelines to assess the potential influence of EMFs on nearshore fish distribution. Six transects of point samples were completed, with transects located perpen-

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E. S. Dunlop, S. M. Reid and M. Murrant

Fig. 2. Map of study area and offshore acoustic survey transects within Lake Ontario. Coordinates of study area: 44o120 08.13″N and 76o320 54.15″W

dicular to the cable and at two reference locations (Fig. 1). Points along each transect were separated by 10 m. The survey extended 900 m to the east and 1650 m to the west on either side of the Kingston cable landing, and 900 m on either side of the Wolfe Island cable landing. The reference transects (50 points each) were located on either shore, beginning 6 km (Kingston) and 2 km (Wolfe Island) to the east of the cable landing. Each point sample consisted of two successive 1-min boat-electrofishing samples (two netters, settings: 3 Amps, 60 pulses per second, range: 0–10%) (Lapointe et al., 2006). Collected fish were identified to species, enumerated and released. Electrofishing was between 23 September and 3 October 2011. At each sample point, the water quality and habitat characteristics were measured, or visually assessed: water depth, water temperature, dissolved oxygen, conductivity, turbidity, percent coverage of six bed material classes (silt/clay, sand, gravel, cobble, boulder and bedrock), percent coverage of two aquatic vegetation classes (simple and complex architecture), and percent coverage of woody debris.

Statistical analyses of nearshore data

Boat-electrofishing data from within the immediate vicinity (within 100 m and 250 m) of the cable landing was compared to reference transect data. Comparisons were based on number of fish captured (Kruskal–Wallis test), species richness (Kruskal–Wallis test and rarefaction methods), and fish community structure (Canonical Analysis of Principal Coordinates, CAP: Anderson and Willis, 2003). CAP was implemented using log-transformed fish abundance data and the Bray-Curtis dissimilarity measure. For multivariate analysis, species found at 0.05). At the 250 m scale, significant differences among transects were only between reference transects (Kruskal–Wallis test, P < 0.025). Rarefaction curves were developed to compare species richness along sampled transects (Fig. 4). Species richness was greatest along the more complex Kingston shoreline. There was little difference between cable and reference transects. The multivariate-based test for differences in fish community structure (CAP) indicated no significant differences among the four transects at either the 100 m (P = 0.07) or 250 m (P = 0.08) scale. Small discontinuities (or weak boundaries) in the fish community structure were detected near the cable landing (within 100–200 m) on the Kingston side (Sand Bay) (Fig. 5). However, strong shifts in composition were located 600–1200 m east of the cable. Fish and habitat data indicate that these

Table 1 Summary of transect catch data from nearshore boat-electrofishing point sampling along Lake Ontario shoreline Transect Species Round Goby White Sucker Rock Bass Pumpkinseed Smallmouth Bass Largemouth Bass Bluegill American Eel Logperch Brook Silverside Silver Redhorse Yellow Perch Spotfin Shiner Banded Killifish Longnose Gar Tubenose Goby Number of Fish Number of Species Number of Points

Kingston East

Kingston West

Kingston Reference

Cable (Sand Bay)

Wolfe Island West

Wolfe Island East

Wolfe Island Reference

191 4 8 2 2

27 0 0 2 0

75 0 4 4 2

4 2 1 0 8

44 0 3 0 4

98 0 33 0 45

85 0 3 1 15

1

0

1

2

11

4

3

0 7 3 0

0 3 2 0

1 6 1 1

0 8 9 0

0 0 0 0

0 3 0 0

0 0 1 0

0 1 0 0 0 1 220 10

0 0 0 0 0 0 34 4

0 0 0 0 0 0 95 9

1 0 0 0 0 0 35 8

0 0 0 0 0 0 62 4

0 0 0 0 0 0 183 5

0 1 1 3 1 0 114 10

165

88

55

17

88

88

55

24

E. S. Dunlop, S. M. Reid and M. Murrant 8

Species richness

100 m 6

4

2

0 0

10

20

30

40

50

Number of individuals 6

250 m

Species richness

5 4 3 2 1 0 0

10

20

30

40

Number of individuals

50

60

Fig. 4. Comparison of species richness (rarefaction method) within 100 m (upper panel) and 250 m (lower panel) of submarine cable along Kingston (solid blue line) and Wolfe Island (solid red line) shorelines to reference transects (Kingston – blue hatched line; Wolfe Island – red hatched line). To improve readability, overlapping 95% confidence intervals are not plotted

Fig. 5. Moving split window analysis of nearshore fish community data along Kingston sampling transects. Peaks with highest values indicate strongest and most consistent discontinuities. Values at the start of the x-axis = most eastern sampling point, increasing in a westerly direction. Cable landing is at position 165

discontinuities reflect: (i) the large numbers of round goby captured from sampling points 600–900 m east of the cable; and, (ii) the large expanse of beach (sand) habitat located 270–600 m east of the cable where only a single round goby was collected from all point samples. Similar to the Kingston shoreline, a small discontinuity in fish community structure was detected in the vicinity of the transmission cable on the Wolfe Island side (Fig. 6). Stronger discontinuities were

detected 400 m to the east of the cable, and 100 m west of the cable. Both locations correspond to large increases in the number of round goby captured. Canonical Correspondance Analysis (CCA) extracted three axes that explained 25% of the variation in the fish community structure along the Kingston shoreline (CCA model significance: P = 0.003), and 18% for the Wolfe Island shoreline (P = 0.001). For both datasets, correlations


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Fig. 6. Moving split window analysis of nearshore fish community data along Wolfe Island sampling transects. Peaks with highest values indicate strongest and most consistent discontinuities. Values at start of x-axis = most eastern sampling point, increasing in a westerly direction. Cable landing represented between positions 88 and 89

between site scores and individual environmental variables were highest for water depth (Kingston Axis 1 = 0.77; Wolfe Island Axis 1 = 0.95), percent coverage of boulder (Kingston Axis 2 = 0.61; Wolfe Island Axis 3 = 0.75), and percent coverage of aquatic vegetation (Kingston Axis 3, complex vegetation = 0.80; Wolfe Island Axis 2, complex vegetation = 0.59; simple vegetation = 0.79). These results indicate that the nearshore fish community structure reflects spatial variation in local habitat characteristics, rather than proximity to the transmission cable.

Fisheries acoustic surveys

Overall, fish density did not vary significantly as a function of distance to the cable. This was true for both pelagic and benthic zones and for both survey nights (Table 2; Figs 7 and 8). When examining fish density along the acoustic transects as the cable is approached from either side, a high degree of variability in fish density is apparent and with no discernable effect of the cable (Fig. 7). A large proportion of this variability in fish density can be attributed to bottom depth. The bottom depth was a significant factor in all statistical models, showing a positive effect on fish density in all zones and for both survey nights (Table 2; Fig. 8). In other words, fish density was higher in deeper areas of the channel, but there was no overall effect from the cable. We also visually assessed patterns between distance to the cable and fish density for an EDSU of 5 m (instead of 50 m), to confirm that any obvious effects at much smaller scales were not being overlooked. As expected, estimates of fish density were highly variable at this spatial scale and no trends were observed. For most fish school parameters, there was no detectable effect from the cable. A significant negative relationship was found between density of fish in benthic schools and distance to the cable for the first survey day (Table 2). There was also a significant relationship between pelagic school volume and distance to the cable for the second survey day (Table 2). In other words, benthic fish schools became denser and pelagic fish schools became larger in volume as distance from the

cable increased. A significant effect of bottom depth was found in only one case, where pelagic school density decreased with bottom depth for the second survey day (Table 2). Relationships in all other cases were not significant. A total of 155 fish were caught during the companion netting surveys, including 116 alewife (Alosa pseudoharengus Wilson, 1811), eight emerald shiner (Notropis atherinoides), five rainbow smelt (Osmerus mordax Mitchell, 1814), 25 yellow perch (Perca flavescens Mitchell, 1814), and one lake trout (Salvelinus namaycush Walbaum, 1792). Therefore, based on the netting data, the main pelagic species present in the channel area is alewife, which represented 75% of the catch. Discussion Our study is the first field study to examine the effects of a wind power project submarine cable on Great Lakes fishes. Based on nearshore and offshore fisheries surveys, we detected little to no effect of the Wolfe Island submarine cable on local fish communities. Habitat features, described either by depth or substrate, were the overriding factors explaining variation in fish distribution. Furthermore, the use of fisheries acoustics was well suited for this study because it permitted examining continuous changes in fish density and school characteristics relative to distance from the cable; fish could also be readily separated into those inhabiting benthic and pelagic zones. The majority of previous EMF-related research has focused on laboratory experiments. Recent laboratory research examining the effects of EMFs on behaviour has identified some freshwater fishes that respond to the presence of EMFs (Bevelhimer et al., 2013). One Great Lakes species that exhibited a strong response was the lake sturgeon (Acipenser fulvescens Rafinesque, 1917), however, the threshold of no impact occurred at only 10–20 cm from the magnet in the experiment (Bevelhimer et al., 2013). Our study would not have detected effects at such a small spatial scale. We purposely chose a broader spatial distribution over which to consider effects for

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Table 2 Results of the Generalized Linear Models explaining variation in fish density or school parameters measured during the fisheries acoustics surveys Dependent variable

Survey day or night

Predictor

Estimate

Standard error

t-value

P-value

Benthic fish density Benthic fish density Pelagic fish density Pelagic fish density Benthic fish density Benthic fish density Pelagic fish density Pelagic fish density Benthic school area Benthic school area Benthic school volume Benthic school volume Benthic school density Benthic school density Pelagic school area Pelagic school area Pelagic school volume Pelagic school volume Pelagic school density Pelagic school density Benthic school area Benthic school area Benthic school volume Benthic school volume Benthic school density Benthic school density Pelagic school area Pelagic school area Pelagic school volume Pelagic school volume Pelagic school density Pelagic school density

Night 1 Night 1 Night 1 Night 1 Night 2 Night 2 Night 2 Night 2 Day 1 Day 1 Day 1 Day 1 Day 1 Day 1 Day 1 Day 1 Day 1 Day 1 Day 1 Day 1 Day 2 Day 2 Day 2 Day 2 Day 2 Day 2 Day 2 Day 2 Day 2 Day 2 Day 2 Day 2

Distance to cable Bottom depth Distance to cable Bottom depth Distance to cable Bottom depth Distance to cable Bottom depth Distance to cable Bottom depth Distance to cable Bottom depth Distance to cable Bottom depth Distance to cable Bottom depth Distance to cable Bottom depth Distance to cable Bottom depth Distance to cable Bottom depth Distance to cable Bottom depth Distance to cable Bottom depth Distance to cable Bottom depth Distance to cable Bottom depth Distance to cable Bottom depth

1.59E03 8.28E01 1.50E04 5.33E01 4.72E04 4.48E01 2.42E05 5.70E01 1.20E04 4.55E02 5.50E05 5.92E02 1.32E03 6.53E02 1.06E03 6.39E02 1.09E03 7.48E02 1.64E04 6.99E02 1.85E03 5.17E03 1.49E03 7.65E03 1.86E04 1.11E03 2.85E03 1.44E01 3.10E03 1.37E01 8.55E05 1.06E01

1.30E03 6.77E02 1.14E03 5.95E02 8.37E04 4.44E02 1.28E03 6.77E02 5.36E04 3.64E02 6.17E04 4.19E02 6.50E04 4.41E02 7.38E04 6.66E02 8.76E04 7.90E02 9.29E04 8.38E02 9.58E04 4.09E02 1.24E03 5.29E02 1.84E03 7.87E02 1.42E03 9.79E02 1.50E03 1.03E01 3.58E04 2.47E02

1.23E+00 1.22E+01 1.31E01 8.95E+00 5.63E01 1.01E+01 1.90E02 8.42E+00 2.24E01 1.25E+00 8.90E02 1.41E+00 2.04E+00 1.48E+00 1.43E+00 9.59E01 1.25E+00 9.47E01 1.77E01 8.34E01 1.93E+00 1.26E01 1.20E+00 1.45E01 1.01E01 1.40E02 2.01E+00 1.48E+00 2.07E+00 1.33E+00 2.39E01 4.30E+00

0.22 0.00* 0.90 0.00* 0.57 0.00* 0.98 0.00* 0.82 0.21 0.93 0.16 0.04* 0.14 0.16 0.34 0.22 0.35 0.86 0.41 0.06 0.90 0.24 0.89 0.92 0.99 0.05 0.15 0.05* 0.19 0.81 0.00*

Significant effects (at P < 0.05) are shown with an asterisk (*). All dependent variables were natural log transformed.

several reasons. First, there is almost nothing known about the EMF sensitivities of many freshwater fishes. Second, detecting effects at much smaller spatial scales in the wild would be difficult, especially considering the movement patterns and home ranges of most fish. Third, the cable traverses a channel, and we did not know whether EMFsensitive fish would avoid passing over the cable, thus potentially impacting their distribution at broader spatial scales. Fourth, and most importantly, we were interested in potential effects of the cable from a spatial scale relevant to fisheries management decision-making in the Great Lakes. The number of field studies examining the impacts of offshore wind power projects to aquatic ecosystems is rapidly increasing, particularly in the last five years or so. Despite that, little is known about how EMFs emitted from offshore transmission cables affect fish. Several studies have identified EMFs as one of the potential stressors to aquatic life arising during the operational phase of a wind power project (Gill, 2005; Nienhuis and Dunlop, 2011a; Gill et al., 2012; Bergstrom et al., 2014; Hammar et al., 2014). Based on a literature review, Bergstrom et al. (2014) rated the potential impact of EMFs to fish as low to moderate depending on the species, although noting that little research has been done. In an ecological risk assessment of the potential effects

of an offshore wind farm to Atlantic cod (Gadus morhua Linnaeus, 1758), the effects from EMFs were deemed as undecided, basically due to a lack of knowledge (Hammar et al., 2014). Although research is in its infancy, most recent studies seem to indicate that EMF impacts are likely minimal (both in spatial scope and magnitude). This interpretation is based on our results, laboratory experiments suggesting that effects occur over small spatial scales and only to some species (Bevelhimer et al., 2013), and recent field observations of some fishes aggregating at the base of offshore turbines despite the presence of EMFs (Bergstrom et al., 2013; Reubens et al., 2013, 2014). Eels have been identified as being sensitive to electro-magnetic fields. They possess magnetic material in their bodies (Moore and Riley, 2009), detect and respond to magnetic fields (Souza et al., 1988; Nishi et al., 2004), and are thought to use magnetic information when migrating (Durif et al., 2014). There is preliminary evidence that eels could be influenced by the EMFs generated by submarine transmission cables. In an unpublished study described in Ohman et al. (2007), 60 silver European eels (Anguilla anguilla Linnaeus, 1758) were tagged with ultrasonic tags, released, and monitored as they crossed a channel with a 130 kV AC submarine transmission cable. Eels were found to move significantly


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Fig. 7. Fish density in relation to cable for two example acoustic transects that ran perpendicular to and intersected with the cable. Negative distances on southwest side of the cable; positive distances on northeast side of the cable. Fish distribution in relation to the cable is highly variable, with no effect detected

slower while in the vicinity of the cable, their passage delayed by 30 min. In a Swedish study described by Ohman et al. (2007), catches of European eel from pound nets set in the vicinity of a windmill were significantly different when the windmill was on vs off, but whether or not this was a result of EMFs is not known. Given the presence of the American eel in Lake Ontario and the St. Lawrence River, our study provided an opportunity to characterize their distribution in the vicinity of a high voltage cable. Overall, American eel were associated with cobble and boulder-sized material and not negatively affected by the presence of the cable. Interestingly, we found American eel utilizing rocky substrate placed over the cable as it approaches the landing on shore, where habitat was homogenous. Thus, as could be

the case with turbine foundations that provide increased habitat complexity (Lindeboom et al., 2011; Langhamer, 2012) the placement of rocky substrate on top of or around submarine transmission cables could enhance fish habitat. We did not make any measurement of the strength of the EMFs produced by the submarine cable. High voltage AC power cables such as the Wolfe Island cable do produce detectable EMFs above background levels (Normandeau Associates et al., 2011; Bevelhimer et al., 2013). However, field measurements of magnetic fields are unavailable for most submarine cables. The strength of the emitted magnetic field depends on several factors, including composition of the cable armouring and current. Field strength declines rapidly with distance from the cable, decreasing horizontally along

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Fig. 8. Fish density as a function of bottom depth and distance to the cable measured from fisheries acoustics surveys. For any given bottom depth, distance to the cable has no discernable effect on fish density. Fish density tends to increase with bottom depth. Benthic zone extends from lake bottom to 5 m above bottom. Pelagic zone includes those fish suspended in the water column, spanning from 5 m above lake bottom to 5 m below the surface. Values lying along y-axis represent density values of 0 (a value of 1 fish per km3 added to facilitate viewing on a logarithmic scale)

the lakebed and into the water column vertically (Worzyk, 2009). In situ measurement of the induced electric field produced when a fish passes through the magnetic field are even more difficult to measure because the field depends on severable factors, including swimming speed and size of the fish. In any case, field measurements or modeling of the EMFs would not have changed the conclusions drawn from our study. Given the lack of knowledge on fish sensitivities to EMFs, measured or modelled EMF levels would have been difficult to interpret. Had we found an effect of cable presence on fish distribution, then additional modelling and field study of EMF strength would have been informative. It is recognized that our results were based on sampling completed over a limited period of time and undertaken

several years after the cable was laid. More robust conclusions would require sampling designs that included: (i) data collection before and after the cable was installed (e.g. Before/After – Control/Impact design); (ii) multiple sampling events, for example at different times of the year; and (iii) replication (i.e. more than a single transmission cable). One factor that could alter the strength of EMFs (and realized effects) being generated by the submarine cable is the wind speed. Maximum wind speeds during sampling ranged from 11 to 33 km h1 (accessed from: www.climat.meteo.gc.ca). Days or nights when wind speeds are higher are expected to produce stronger EMFs because the electricity generated and moving through the cable is higher. Furthermore, the fish community in the Wolfe Island area was found to be simple


and numerically dominated by the non-native round goby in the nearshore and alewife in the offshore. A more diverse native fish community might respond differently to EMFs. Finally, the Wolfe Island cable is a single submarine cable crossing a channel. Renewable energy installations, and offshore wind power projects in particular, could have many different types of cable configurations and could be placed in different types of habitats (e.g. Schlappy et al., 2014). Our study therefore represents a first step toward examining the potential effects of submarine power cables on fish communities within the Great Lakes. Acknowledgements Funding for this project was provided by the Renewable Energy Program and Species at Risk Branch of the Ontario Ministry of Natural Resources and Forestry (OMNRF). We thank Sarah Hogg and Mike Parna (Aquatic Research and Monitoring Section ARMS, OMNRF) and Alex Price and Jarrod Stackhouse (Fisheries and Oceans Canada) for field assistance with the nearshore boat electro-fishing surveys. We thank the captain and crew of the Ontario Explorer I (Lake Ontario Management Unit of OMNRF) and Julie Henry and Benjamin Maynard (ARMS, OMNRF) for providing field support during the acoustic surveys. Ted Schaner (Lake Ontario Management Unit, OMNRF) provided assistance with the acoustic survey design and collection of acoustic data. GIS support and maps were provided by Trevor Middel and Justin Trumpickas (ARMS, OMNRF). Valuable discussion of the project design and acoustic data were provided by Scott Milne (Milne Technologies) and Trevor Middel, Brent Metcalfe, and Sarah Nienhuis (ARMS, OMNRF). References Anderson, M. J.; Willis, T. J., 2003: Canonical analysis of principal coordinates: a useful method of constrained ordination for ecology. Ecology 84, 511–525. Bergstrom, L.; Sundqvist, F.; Bergstrom, U., 2013: Effects of an offshore wind farm on temporal and spatial patterns in the demersal fish community. Mar. Ecol.-Prog. Ser. 485, 199–210. Bergstrom, L.; Kautsky, L.; Malm, T.; Rosenberg, R.; Wahlberg, M.; Capetillo, N. A.; Wilhelmsson, D., 2014: Effects of offshore wind farms on marine wildlife-a generalized impact assessment. Environ. Res. Lett. 9, 12. Bevelhimer, M. S.; Cada, G. F.; Fortner, A. M.; Schweizer, P. E.; Riemer, K., 2013: Behavioral responses of representative freshwater fish species to electromagnetic fields. Trans. Am. Fish. Soc. 142, 802–813. Dunlop, E. S.; Milne, S. W.; Ridgway, M. S., 2010: Temporal trends in the numbers and characteristics of Lake Huron fish schools between 2000 and 2004. J. Gt. Lakes Res. 36, 74–85. Durif, C. M. F.; Browman, H. I.; Phillips, J. B.; Skiftesvik, A. B.; Vollestad, L. A.; Stockhausen, H. H., 2014: Magnetic compass orientation in the European Eel. PLoS ONE 8, 7. Formicki, K.; Winnicki, A., 1998: Reactions of fish embryos and larvae to constant magnetic fields. Ital. J. Zool. 65, 479–482. Gill, A. B., 2005: Offshore renewable energy: ecological implications of generating electricity in the coastal zone. J. Appl. Ecol. 42, 605–615. Gill, A. B.; Bartlett, M.; Thomsen, F., 2012: Potential interactions between diadromous fishes of U.K. conservation importance and the electromagnetic fields and subsea noise from marine renewable energy developments. J. Fish Biol. 81, 664–695.

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Reubens, J. T.; Pasotti, F.; Degraer, S.; Vincx, M., 2013: Residency, site fidelity and habitat use of Atlantic cod (Gadus morhua) at an offshore wind farm using acoustic telemetry. Mar. Environ. Res. 90, 128–135. Reubens, J. T.; Degraer, S.; Vincx, M., 2014: The ecology of benthopelagic fishes at offshore wind farms: a synthesis of 4 years of research. Hydrobiologia 727, 121–136. Rudstam, L. G.; Parker-Stetter, S. L.; Sullivan, P. J.; Warner, D. M., 2009: Towards a standard operating procedure for fishery acoustic surveys in the Laurentian Great Lakes, North America. ICES J. Mar. Sci. 66, 1391–1397.

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Appendix 1: Acoustic system details, parameter settings, and calibration Table A1: Fisheries acoustics system and settings for 2011 Wolfe Island surveys Transducer description

DTX 70 kHz

DTX 120 kHz

Nominal frequency (kHz) Transducer type Beam type Serial number Pulse duration (ls) 2-way beam angle (10log(w)dB) Source level (dB Re 1 lPa at 1 m) Receiver sensitivity (dB) y-axis (minor axis, along) 3 dB one-way beamwidth (°) x-axis (major axis, athwart) 3 dB one-way beamwidth (°) Minor-axis (alongship) offset (°) Major-axis (athwartship) offset (°) Transducer face diameter (m) Transducer deployment depth (m)

70 BioSonics Split DT6-46-70-0615-003 400 22.972725 220 56.5 5.4 5.4 0.25 0.15 0.188 1.3

120 BioSonics Split DTX-46-120-0615-010 400 20.004328 220.8 49.6 7.6 7.6 0.4 0.62 0.12 0.52

Table A2: Fisheries acoustic system calibration values used to apply TS and Sv offsets for 2011 Wolfe Island surveys Calibration details

DTX 70 kHz

DTX 120 kHz

Calibration date WC calibration sphere diameter (mm) Theoretical target strength of sphere (dB re 1 m2)

09-Aug-11 36.00 42.00

27-Jul-11 33.00 40.65

Target Strength (TS) Calibration

DTX 70 kHz

DTX 120 kHz

Maximum beam compensation (dB) Number of single targets Observed target strength (dB re 1 m2) Standard deviation (dB re 1 m2) TS difference (dB re 1 m2)

6.00 2897 41.79 0.0000003 0.210

6.00 255 41.54 0.0000120 0.890

Volumetric Back-scattering Strength (Sv) Calibration

DTX 70 kHz

DTX 120 kHz

BioSonics calibration offset applied (dB re 1 m2) Maximum beam compensation (dB) Number of single targets Observed target strength (dB re 1 m2) Standard deviation (dB re 1 m2) Observed mean Sv of calibration sphere (dB re 1 m1) Nautical area scattering coefficient (m2 nmi2) Area backscattering coefficient (m2 m2) Calibration region height mean (m) Calibration region depth mean (m) Number of pings Theoretical Sv of calibration sphere (dB re 1 m1) Sv difference after target strength calibration (dB re 1 m1)

0.21 0.05 214 42.24 0.0000010 33.401693 4709.726602 0.000109271 0.239152 10.493169 215 33.121 0.280

0.00 0.50 30 41.10 0.0000160 35.117406 4262.898581 9.89038E-05 0.321332 8.128176 29 32.790 2.328


31

Table A3: Fisheries acoustics system parameters and Echoview settings for 2011 Wolfe Island surveys Logging Global settings 1

Estimated speed of sound (m s ) Temperature (°C) Depth (m) Absorption coefficient from Echoview (dB m1) Wavelength of medium (m) Equivalent 2-way beam angle (dB re 1 Steradian) Major axis 3 dB beam angle (°) Minor axis 3 dB beam angle (°) Nearfield distance (range) calculation (m)

Processing

70 kHz

120 kHz

70 kHz

120 kHz

1465.17 15 1.0 0.0012717 0.020931 22.973 5.4 5.4 1.69

1465.17 15 1.0 0.0037374 0.01221 20.0043 7.6 7.6 1.18

1465.93 15 1.0 0.0012720 0.020942 22.973 5.4 5.4 1.69

1465.93 15 1.0 0.0037370 0.01212 20.0043 7.6 7.6 1.18

Logging Volumetric back-scattering strength (Sv) 2

Target strength calibration offset (dB re 1 m ) Sv calibration offset (dB re 1 m1) Transmitted pulse length (ms) Ping rate (pings per s) Sample depth (m) Minimum 1 R2 Sv threshold (dB re 1 m-1) Minimum target strength threshold (dB re 1 m2) Time varied gain range correction method Minimum target strength threshold calibration offset (dB re 1 m1)

Processing

70 kHz

120 kHz

70 kHz

120 kHz

0.00 0.00 0.40 2 variable 100

0.00 0.00 0.40 2 variable 100

0.210 0.280 0.40 2 100 None 66 BioSonics 0.490

0.890 2.328 0.40 2 100 None 66 BioSonics 1.438

Logging School detection parameters

Processing

70 kHz

120 kHz

Minimum total school length (m) Minimum total school height (m) Minimum candidate length (m) Minimum candidate height (m) Maximum vertical linking distance (m) Maximum horizontal linking distance (m) Distance mode Logging

70 kHz

120 kHz

2 1.1 0.15 0.15 0.25 1.25 GPS

2 1.1 0.15 0.15 0.25 1.25 GPS

Processing

Sv

70 kHz

120 kHz

70 kHz

120 kHz

Units

Sv calibration offset Transmitted pulse length Ping rate Sample depth Minimum 1/R2 Sv threshold applied Minimum target strength threshold TVG range correction method Minimum target strength threshold calibration offset

0.00 0.40 2 Variable 100 – – –

0.00 0.40 2 Variable 100 – – –

0.280 0.40 2 100 None 66 BioSonics 0.490

2.328 0.40 2 100 None 66 BioSonics 1.438

db ms pps m db db

Logging

db

Processing

School detection parameters

70 kHz

120 kHz

70 kHz

120 kHz

Units

Minimum total school length Minimum total school height Minimum candidate length Minimum candidate height Maximum vertical linking distance Maximum horizontal linking distance Distance mode

– – – – – – –

– – – – – – –

2 1.1 0.15 0.15 0.25 1.25 GPS

2 1.1 0.15 0.15 0.25 1.25 GPS

m m m m m m m

Author’s address: Erin S. Dunlop, Aquatic Research and Monitoring Section, Ontario Ministry of Natural Resources and Forestry, Trent University, DNA Building, 2140 East Bank Drive, Peterborough, ON K9J 7B8, Canada. E-mail: [email protected]