Draft - University of Toronto T-Space · Draft 1 Characterizing snow crab (Chionoecetes opilio)...

Draft

Characterizing snow crab (Chionoecetes opilio) movements

in the Sydney Bight (Nova Scotia, Canada): a collaborative

approach using multi-scale acoustic telemetry

Journal: Canadian Journal of Fisheries and Aquatic Sciences

Manuscript ID cjfas-2017-0472.R1

Manuscript Type: Article

Date Submitted by the Author: 24-Apr-2018

Complete List of Authors: Cote, David; Fisheries and Oceans Canada Newfoundland and Labrador

Region, Ecological Sciences Nicolas, Jean-Marc; Emera Newfoundland and Labrador Whoriskey, Frederick G.; Ocean Tracking Network, Dalhousie University Cook, Adam; Bedford Institute of Oceanography, Fisheries and Oceans Canada Broome, Jeremy; Bedford Institute of Oceanography, Fisheries and Oceans Canada Regular, Paul; Fisheries and Oceans Canada Newfoundland and Labrador Region, Ecological Sciences Baker, Darrin; Baker Blue Ocean

Keyword: Snow crab, Ocean Tracking Network, state-space modelling, MIGRATION < General, movement behaviour

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Issue? : Oceans Tracking Network

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Canadian Journal of Fisheries and Aquatic Sciences

Draft

Characterizing snow crab (Chionoecetes opilio) movements in the Sydney Bight (Nova Scotia, Canada): 1

a collaborative approach using multi-scale acoustic telemetry 2

David Cote1,2

, Jean-Marc Nicolas3, Frederick Whoriskey

4, Adam. M. Cook

5, Jeremy Broome

5, Paul M. 3

Regular1 and Darrin Baker

6 4

1 Fisheries and Oceans Canada, Northwest Atlantic Fisheries Centre, P.O. Box 5667, 80 East White Hills 5

Rd, St. John’s, NL, A1C 5X1 6

2Department of Ocean Sciences, Ocean Sciences Centre, Memorial University of Newfoundland, St. 7

John’s, NL A1C 5S7, Canada 8

3Emera Newfoundland and Labrador, 9 Austin St, St. John's, NL, A1B 4C1 9

4Ocean Tracking Network, Dalhousie University, 1355 Oxford St., Halifax, NS B3V 1E7 10

5 Fisheries and Oceans Canada, Bedford Institute of Oceanography, P.O. Box 1009, 1 Challenger Dr, 11

Halifax, Nova Scotia, B2Y 4A2 12

6Baker Blue Ocean, 5349 Highway 329 Blandford, Nova Scotia, B0J 1T0 13

Abstract 14

Like many deeper ocean species, the fine-scale movement ecology of snow crab is not well understood. 15

We integrated fine-scale positioning telemetry with larger-scale position estimates from autonomous 16

mobile surveys and harvester returns to evaluate movements of male and female snow crab. Effects of 17

lifestage-sex, temperature and diel and tidal cycles on movement velocity were observed, with a 18

tendency for increased velocities during the night, slack tide, and at increasing water temperatures. 19

Males also moved faster than females and juveniles. The strength of these statistical relationships, 20

however, was weak (R2=7.2%). The movement direction also did not vary over the tidal cycle. The 21

maximum distance moved for adult males was an order of magnitude higher (37.1 km) than for females 22

(3.6 km) and juvenile males (3.9 km) but median distances were more similar across groups. Individuals, 23

once released, tended to disperse and move toward slope habitats. Little evidence of site fidelity was 24

apparent. The absence of strong environmental influences on movements likely reflected the 25

behavioural plasticity of snow crab and the relative environmental stability of offshore environments. 26

Keywords 27

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Snow crab, movement behaviour, telemetry, migration, state-space modelling, Ocean Tracking Network 28

Introduction 29

Ecological and behavioural traits of most marine species are not well understood, including for many 30

heavily managed commercially important fisheries stocks. Often, fundamental research to understand a 31

species’ full life history only arises after crises such as when a stock collapses for uncertain reasons, e.g. 32

Atlantic cod, tuna, eels and sharks (Myers et al. 1997; Baum et al. 2003; MacKenzie et al. 2009; Béguer-33

Pon et al. 2015). While historically this lack of knowledge resulted from technological, logistic and 34

financial challenges associated with studying a species’ ecology in open ocean environments, the 35

potential costs of not understanding a species’ response to perturbations are also significant in terms of 36

stock health and/or lost opportunities in harvesting and other resource sectors (e.g. Mullowney et al. 37

2012). 38

Snow crab is among the most valuable commercial fishery species in Canada (Weston 2011; Nguyen et 39

al. 2014; DFA 2017). The range of the species extends from Labrador to south-western Nova Scotia, in 40

temporally and spatially variable aggregations. In the past decade, a significant amount of research has 41

been directed at understanding the factors that influence the snow crab population (Choi et al. 2014; 42

Zisserson and Cook 2017). This work remains ongoing, and is primarily aimed at optimizing the 43

management of this resource. However, little information exists about the behaviour of snow crabs due 44

to their offshore and deep-water habitat preferences. What is known regarding behaviour has been 45

largely inferred from coarse-resolution mark-recapture studies and surveys directed toward estimating 46

abundance (Maynard and Robichaud 1986; Moriyasu et al. 2001; Cook et al. 2015; Mullowney et al. 47

2017) or was derived from studies in contained coastal fjords (Maynard and Robichaud 1986; Conan et 48

al. 1996; but see Lefebvre and Brethes 1994) that do not reflect conditions experienced by the vast 49

majority of the populations. These studies provide limited but interesting snapshots of the animals’ 50

behaviour but leave large gaps in our knowledge of the species’ ecology, behaviour or habitat use. This 51

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lack of knowledge limits our ability to predict the impacts on the crabs from perturbations ranging from 52

broad environmental changes to ocean industrial activities other than fisheries (e.g. offshore oil and gas 53

exploration and developments, power generation and transmission; Moriyasu et al. 2001). The lack of 54

knowledge has affected environmental assessments for some proposed offshore developments, with 55

the uncertainty in the prediction of project impacts on crabs generating calls from fish harvesters and 56

conservationists that projects should not be considered until impact predictions are more certain. This 57

is particularly true in areas where snow crab stocks are either currently declining or are projected to 58

decline in the near future (Mullowney et al. 2014; Choi et al. 2014). 59

One new industrial development occurring within the snow crab distribution around Cape Breton, Nova 60

Scotia is a subsea power transmission cable installation across the Cabot Strait. This development is 61

designed to bring 500 MW of electricity from Cape Ray, Newfoundland to Point Aconi, Cape Breton, 62

Nova Scotia (Figure 1) through two cables buried one meter in the sediment at depths and habitats that 63

snow crab are known to occupy. The operation of the cables creates a magnetic field and will create 64

localized alterations to the natural field. Several migratory marine species have shown sensitivity to 65

altered electromagnetic fields (e.g. spiny lobster, turtles, Pacific salmon, elasmobranchs), with 66

perturbations influencing these animals’ ability to navigate (Lohmann et al. 1995; Boles and Lohmann 67

2003; Wiltschko and Wiltschko 2005; Lohmann and Lohmann 2006; Lohman et al. 2007). Such results 68

indicate that the potential exists for other species to be affected but to date there are no studies 69

investigating the magnetic senses or use of magnetic fields for migration in the snow crab (lab or 70

otherwise). As part of the approved Environmental Assessment for the Cabot Strait cable installation, an 71

environmental monitoring program is being conducted before and after the cables’ installation to 72

evaluate potential effects of the project on snow crab behaviour. 73

A challenge to characterizing snow crab behaviour is the the need to measure the species' movement 74

at multiple relevant spatial scales. Emerging electronic tagging technology makes it possible to monitor 75

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snow crab behaviour in open-ocean environments at a variety of scales but resource limitations usually 76

require trade-offs between the spatial scale of monitoring and the resolution of the data obtained. For 77

example, high-resolution acoustic positioning telemetry can document movement patterns at fine 78

spatial (metres) and temporal (minutes) scales but requires spatially dense allocations of expensive 79

acoustic receivers to determine an individual’s position. This tends to restrict the spatial extent of 80

studies employing fine scale hyperbolic positioning arrays. In contrast, presence-absence arrays can be 81

used to capture movements across broader areas and at longer time scales, or capture habitat 82

occupancy at specific points along movement corridors. However, these systems provide coarse-scale 83

information of limited use in characterizing fine-scale behavioural responses to perturbations. 84

In this study we integrated fine-scale hyperbolic positioning telemetry with larger scale presence-85

absence telemetry and harvester returns of tagged animals to document fine and coarse scale 86

movements of male and female snow crab over a two year period prior to the installation of two subsea 87

cables. Our objectives were to document the migratory pathways of snow crabs in the Sydney Bight 88

area, describe the response of snow crab to oceanographic / physical cycles (diel period and tide) and 89

water temperature, and to determine if these patterns varied across commercial-sized adult males, as 90

well as smaller juvenile males and females. To achieve this, we leveraged the installation of new 91

telemetry infrastructure with the existing system of the Ocean Tracking Network (OTN) to provide 92

unprecedented detail of snow crab movements. 93

Methods 94

Telemetry Array Design and Deployment 95

The telemetry array was deployed in an area of the subsea cable corridor known by harvesters to have 96

relatively high densities of adult male snow crab. Array design was informed by in-situ range tests 97

conducted in September 2014 to define the optimal distances between receivers. A 0.25 km2

high-98

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resolution Vemco Positioning System (VPS) array, consisting of 9 receiver moorings, tethered in strings 99

of 3, and spaced at 250 m, was deployed in 2014. Following the first year of data collection, the 100

manufacturer advised that detection range was better than determined from range testing trials and 101

suggested that the range could be extended without significantly compromising data integrity. In 2015 102

the VPS array was expanded to 1.5 km2 with a total of 16 receivers at 400 m spacing (Figure 1). The VPS 103

array was complemented by four linear (presence-absence) arrays which extended north and south 104

along each side of the proposed subsea cable route (Figure 1). The receiver moorings located north of 105

the VPS were tethered at 500 m spacing along two ropes. Receiver moorings located to the south of the 106

VPS were independently fixed with acoustic releases and were also deployed at 500 m spacing in 2014. 107

In 2015, the independent moorings within the southern linear arrays were extended from 500 m to 108

800 m spacing (Figure 1). The combined use of the VPS array and the linear arrays enabled the coverage 109

of approximately 10 km of the proposed subsea cable corridor, spanning a depth range of 104-116 m. 110

Acoustic receiver mooring design followed a standard Ocean Tracking Network (OTN) configuration, 111

consisting of a 69kHz VR2w acoustic receiver (VEMCO, Halifax, NS) tethered off the bottom using a 112

hardball float. The receiver was positioned at the terminal end of the individual mooring, with the 113

receiver oriented vertically to enable clean lines of sight. Fixed delay, time-synchronizing transmitters 114

(sync tags) were co-located on each receiver mooring assembly within the VPS array. Sync tags, used to 115

calculate precise receiver positions on the ocean bottom, were attached to the rope risers of the VPS 116

receiver moorings at approximately 1 m above the substrate. 117

Arrays were deployed prior to the release of tagged animals and remained in the water through May, 118

2016 to monitor movements except when they were temporarily and briefly retrieved to download data 119

(Table 1). 120

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Animal Capture, Holding, and Tagging 121

Methods for capture, holding, and acoustic tagging of snow crab followed Zisserson and Cameron 122

(2016). Chartered commercial harvesters used baited, 1.8 m diameter, top entrance traps to capture 123

terminally moulted male crab. Female and juvenile male crab were collected using baited, rectangular, 124

top entrance shrimp traps, which were modified for collection of small crab. Soak time of traps ranged 125

between 12 and 36 hours. Upon capture, crabs were removed manually from the trap and inspected for 126

physical damage or signs of decreased health and viability. Animals to be tagged were held temporarily 127

in a 750 L insulated fish box. Thermal conditions of deep water crab habitat were reproduced on deck by 128

filling the fish box with approximately 300 L of ice which was then covered with a non-permeable 129

membrane. Surface sea water was used to fill the remaining portion of the tank, and was aerated and 130

chilled to 1.5oC. The holding box was covered to reduce light exposure and to maintain water 131

temperatures. 132

Crabs were tagged with either Vemco (Halifax, NS) V13 (diameter: 13 mm; length: 36 mm, weight in 133

water: 6.0 g, 69 KHz, estimated tag life: 653 d, transmission frequency: 60-180s), or V9 acoustic 134

transmitters (69kHz, diameter: 9 mm; length: 29 mm, weight in water: 2.9 g, estimated tag life: 347 d, 135

transmission frequency: 60-180 s; Table 2). Crabs were individually selected for tagging and placed 136

upright on a flat surface. To improve tag adhesion, the area of attachment on the dorsal surface of the 137

carapace was dried with paper towel then lightly abraded using a rotary tool. A vinyl tubing, spaghetti-138

style tag (Floy Tag, Seattle, Wash., USA) was attached through a cap built into the transmitter, and 139

positioned around the animal’s carapace between the second and third walking legs. A small volume of 140

3M® 5200 marine adhesive was then placed on the carapace area prepared with the rotary tool and the 141

cap pressed into the adhesive. Once the acoustic tag was mounted in the adhesive, the spaghetti tag 142

was tightened and the aluminum sleeve was crimped to secure it in place and excess tubing trimmed. 143

Thin wire pipe cleaners were then used to secure the posterior portion of the acoustic tag to further 144

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ensure tag position and adhesive contact throughout curing. This curing process takes ~24 hours but can 145

occur while submerged in sea water. 146

Animals were released as close as possible to their capture location to minimize the potential for 147

alteration of natural behaviour patterns. Since no females or juvenile males were found within the 148

habitats of the telemetry array, they were captured and relocated within our telemetry system from 149

slope habitats (70-100 m depth) ~5 km to the southwest of the VPS array (Figure 1). 150

Animals were released within six hours of tagging in four equal sized groups at separate locations within 151

the arrays (two release locations on each side of the proposed subsea cable area). Locations were 152

selected to maximize the likelihood of animals interacting with the proposed subsea cable area and to 153

avoid signal collisions which are typically associated with having too many tagged animals in one 154

location. Each tagging group was released to the bottom at the prescribed location by ferrying them to 155

the substrate in a custom-designed release cage that was opened by an acoustic release triggered from 156

the surface. This method of release minimized potential pelagic drift away from the study area during 157

releases and protected them from potential predation during transit through the water column. 158

OTN Wave Glider Surveys and Supplementary Position Information 159

In partnership with the Ocean Tracking Network (OTN), mobile telemetry surveys were conducted using 160

a Wave Glider™ (Liquid Robotics, Sunnyvale, California, USA). Wave Glider surveys were used to search 161

for snow crab that had moved outside of the detection range of the fixed telemetry arrays. The Wave 162

Glider is a remotely piloted autonomous vehicle that can be programmed to follow pre-defined routes 163

to search for acoustic transmissions from tagged animals. Pilots are in constant contact with the vehicle, 164

permitting rapid change of its programming. When the Wave Glider’s towed acoustic receiver 165

(approximately 9 m in depth) detects an acoustic transmitter, the detected location and time is 166

transmitted in real time via satellite link to the Ocean Tracking Network offices. Five Wave Glider 167

deployments were conducted in our study area (Figure 2; Table 3); four of which were specifically 168

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targeted toward sampling snow crabs in our study. The last of these targeted surveys (May 30 – June 7, 169

2017) had to be aborted after 9 days due to potential conflicts with the vessel laying the subsea cable. It 170

was reinitiated approximately 4 weeks later (July 2-14, 2017) after installation was complete but prior to 171

the operation of the subsea cables (Table 3). Survey coverage during the missions varied from 266 to 172

447 km2 and was influenced by ocean conditions (tide and sea state) and light conditions; the latter of 173

which was important for recharging the Wave Glider’s solar-powered battery systems. 174

Commercial harvesters provided the location and tag number from seven marked snow crab that were 175

intercepted during commercial fishing operations. These data were integrated into the final presence-176

absence analysis. 177

Presence-absence detections on telemetry receivers as well as harvester returns provided, by our 178

definition, coarse scale information on snow crab occurrences and movements. Unlike VPS approaches 179

(see below), which used hyperbolic positioning to achieve fine-scale positions, single receiver detections 180

could only determine that the animal was in detection range (estimated at 500 m) of a particular 181

receiver at the time the animal was detected. When an animal was concurrently detected by more than 182

one receiver, additional inference on its estimated location could be acquired. To achieve this, we 183

calculated a daily weighted average of the detecting receivers’ locations for each animal. The weighting 184

was based on the number of detections for a given receiver, following the assumption that animals in 185

closer proximity to a given receiver would be detected more frequently than on more distant receivers. 186

In cases where an animal was detected on a single receiver, the position estimate we used was simply 187

the location of that receiver. Positions from all detection sources (fixed arrays, Wave Glider surveys and 188

harvester returns) were compiled for each animal to form movement paths. 189

190

Analysis of Hyperbolic Positioning Data 191

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Data from acoustic positioning systems can be subject to large measurement errors, particularly in 192

acoustically challenging environments such as our study area. Removing measurement errors generally 193

involves either: 1) filtering aberrant locations using a series of rules or 2) accounting for these errors 194

using hierarchical models. The latter option has become more tractable in recent years with the 195

development of analytical software platforms such as Template Model Builder (Kristensen et al. 2016; 196

Auger-Méthé et al. 2017). We applied a version of 1-behaviour first-difference correlated random walk 197

(DCRW) state-space model presented in Auger-Méthé et al. (2017), which accounts for measurement 198

error and accommodated irregular sampling intervals. We estimated the parameters using a joint model 199

as recommended by Jonsen (2016). See Supplement 1 for further details on the analysis of 200

measurement error and Supplement 2 for a more detailed description of the DCRW model. The resulting 201

processed tracks were then used in modeling snow crab behaviour. 202

Environmental variables (depth, tide, temperature and diel period) were linked by time-stamp and/or 203

location to the animal positions obtained from the state-space model. Depth was estimated by 204

intersecting animal positions with a bathymetry layer (GEBCO 2014), whereas tide state and diel period 205

were obtained from Environment Canada databases for the North Sydney area (Figure 1). Tide trend was 206

included in models as it was assumed to more directly influence water current velocity and direction. It 207

was calculated as the hourly change in tide height and applied to all animal positions within that time 208

interval. Temperatures within the fine-scale positioning were measured by the VR2-AR telemetry 209

receivers and averaged to provide a single estimate that was applied across all animals within the 210

detection range. 211

Metrics of snow crab movement behaviour (i.e. velocity and changes to movement direction) were 212

calculated for each segment within a snow crab’s state-space modelled track using the BCPA package in 213

R (Gurarie et al. 2009). Velocity was analyzed within a Generalized Additive Mixed Model (GAMM; mgcv 214

package in R using Generalized Cross Validation) to evaluate its relationship with environmental 215

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variables such as tide, temperature and diel period. GAMMs were used because the shape of the 216

relationship between velocity and environmental variables was not known. The model for movement 217

velocity was as follows: 218

Log(Movement Velocity) ~ s(hour of day) + s(tide trend) + s(water temperature) + Lifestage/Sex 219

+ Acclimation Period +1|Animal 220

It incorporated smoothed terms for hour of day (cyclic cubic regression spline), tide trend (cubic 221

regression spline) and water temperature (cubic regression spline), and categorical terms for 222

Lifestage/Sex (Adult Male, Juvenile Male and Female) and acclimation period (During/After). Each 223

animal was treated as a random effect to account for individual variability and potential autocorrelation 224

among positions (Rooney et al. 1998). We also separated our data into acclimation (<24h following 225

release) and post-acclimation periods (>24h following release) to account for potential flight responses 226

(e.g. Maynard and Robichaud 1987; Conan et al. 1996). 227

Analyses of movement direction with respect to tide required a different approach due to the nature of 228

circular bearing data (Pewsey et al. 2013). As mixed effects models using multiple environmental 229

variables were not possible, state-space modelled tracks were collapsed into single averaged bearing 230

estimates for each individual with a categorical variable of tide trend (i.e. rising or falling). Tide trend 231

was selected as the single environmental variable of interest because it had been shown to influence 232

movement direction in snow crab (Kanawa et al. 2014). These individual mean values were collectively 233

assessed for each tide state to determine the population tendency to deviate from a uniform directional 234

distribution (Rao’s Spacing Test of Uniformity; Pewsey et al. 2013; Circular package, R). Distributions of 235

movement bearings (post-acclimation data only) were statistically compared to assess whether bearings 236

from each tide state were likely drawn from the same distribution (Watson’s Two-Sample Test of 237

Homogeneity; Pewsey et al. 2013; Circular package, R). 238

239

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Results 240

Presence – Absence 241

All tagged animals were successfully detected at some point in the array (Figure 3) and collectively snow 242

crab generated 3.2 million detections. Most animals dispersed away from the fixed array relatively 243

quickly. After the 2014 release, 50% of animals left the array within 10 days whereas 50% of the animals 244

released in 2015 departed within 23 days (Figure 3, Figure 4). While no animals remained continuously 245

in the array for the two year duration of the study, seven adult males released in 2014 returned to the 246

array later in the same year and three of those were detected in the array again in the second year (see 247

right panel Figure 3). In contrast, twelve animals released in 2015 remained in the array for all of the 248

2015 observation period. One of the animals was an adult male captured at the array site, whereas the 249

remainder were females (n=4) and sub-commercial males (n=7) that were captured and relocated from 250

the nearby slope habitats outside the array (Figure 1). VPS tracks indicated that all, save two juvenile 251

males, were suspected of shedding their tag or dying shortly after release (>100 d of inactivity with no 252

subsequent movements). These animals were removed from subsequent analyses. Of the animals that 253

initially moved out of detection range of the array in 2015, 14 of 70 adult males returned, compared to 254

only one of 15 females and 3 of 31 sub-commercial males that returned for brief periods after their 255

initial departure. 256

Presence/absence detections with fixed arrays, Wave Glider surveys (1,017 detections) and harvester 257

returns (7 detections) enabled the relocation of animals at larger spatial and temporal scales. Adult 258

male snow crab were detected up to 647 days after release (median 81 days), whereas juvenile males 259

and females were detected up to 224 days after release (median values were 38 days and 60 days 260

respectively). Over these time periods the maximum distances moved for adult male snow crab were an 261

order of magnitude higher (37.1 km) than for females (3.6 km) and juvenile males (3.9 km) and unlike 262

adult males, females (0 of 11) and juvenile males (2 of 26) were rarely relocated outside the fixed 263

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telemetry arrays. Median dispersal distances, however, were more similar across lifestage/sex groups 264

(adult males: 3.6 km; juvenile males: 2.9 km; females: 2.9 km). Depth ranges occupied by individuals 265

spanned 40-157 m for adult males, 95-105 m for juvenile males and 95-109 m for females. 266

Presence-absence-derived movements of the tagged animals indicated a general southerly pattern of 267

movement after release (Figure 4) for males in 2014 and 2015 and for females and juvenile males 268

released in 2015. Detections of the 2014 release group by the first Wave Glider survey (19 animals; June 269

2015) were predominantly to the south of the array, near slope habitats (Figure 4). In 2015, the timing 270

of this movement did not occur immediately after release, as it did in 2014, but appeared to be 271

synchronized with the departure timing of adult males tagged in 2014 (Figure 5). Though the average 272

latitude of detected individuals shifted northward towards the end of November in 2014 and 2015, the 273

numbers of animals remaining within detection range at this time were greatly reduced which in turn 274

reduced our level of confidence that this represented a population shift (Figure 5). A modest increase in 275

March 2016 in number of detected animals suggests that animals were not simply passively dispersing 276

from the array and that they have an increased likelihood of occupying the study area during some 277

periods of the year. Among the adult males detected by the Wave Glider, the average maximum 278

displacement distance from their release point was 10 km while the greatest distance across all animals 279

was approximately 37 km (crab 19854; Figure 4). While this provides evidence that at least some 280

animals travelled considerable distances, there were no reported detections on the Ocean Tracking 281

Network’s Cabot Strait or St. Ann’s Bank arrays, which are situated 57 km to the northwest and 84 km to 282

the east of our study area respectively (Figure 1). 283

Nevertheless, some animals covered significant distances over the study period. For example, an adult 284

male snow crab (# 19879) that was tagged October 31, 2014, left the array to the south on November 4, 285

2014, returned on November 28, 2014 and moved north through the array, disappearing on December 286

11, 2014 (Figure 4). It was later detected 17.6 km away by the Wave Glider on June 19, 2015 and 287

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returned to the array on February 29, 2016 for the remainder of the baseline study. The distance 288

travelled by this animal was at least 92 km, within an area of at least 14 km2 during the one and one-half 289

years the animal was tracked. 290

Hyperbolic Positioning 291

One hundred and sixty-four snow crabs were tagged for the study and 71% had sufficient positions to 292

undergo the state-space model filtering (92 adult males, 12 juvenile males and 8 females) used in the 293

fine-scale positioning analysis. In total, 47,265 positions were used in the 2-D positioning analysis (on 294

average 422 positions per animal). 295

Movement patterns of tagged snow crab often exhibited a period of elevated velocity after release, 296

suggestive of a flight response (see Figure 6-bottom left panel). Movement paths also included periods 297

of directional and meandering movements but these were not linked with obvious differences in 298

movement velocities (Figure 6). 299

The GAMM analysis showed significantly higher movement velocities during the acclimation period 300

(model estimates indicated approximately 75% faster; P<0.001). Results also indicated that 301

Lifestage/Sex group had a significant effect on movement velocity with adult males moving at 302

significantly higher velocities than juvenile males (P=0.037) or females (P=0.005). Model fits for hour of 303

day (P<0.001), tidal trend (P<0.001) and bottom temperature (P<0.001) were significant, with a 304

tendency for increased velocities during the night, slack tide and at increasing water temperatures 305

(Figure 7). Despite the highly significant results for these factors, the amount of variation accounted for 306

was very low for the model (R2=0.072) indicating that there is considerable variation in movement 307

velocity that remains unexplained (Figure 6). 308

Movement direction of tagged snow crab within the VPS array tended toward the southeast (Figure 8) 309

but was not significantly different than a uniform distribution for either rising (Rao Spacing Test of 310

Uniformity: 138.5; P>0.1; n=80) or falling tides (Rao Spacing Test of Uniformity: 123; P>0.1; n=80). 311

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Direction of movement also did not differ according to tide trend (Watson Two-Sample Test of 312

Homogeneity: 0.083; P>0.1, n=80). 313

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Discussion 314

Habitat requirements of many species are dynamic, shifting in response to the external environment 315

and to changing intrinsic life history priorities. As a consequence, movement and migration are 316

important adaptations to the health and resilience of individuals and populations to which they belong 317

(Dingle 1996; Nathan et al. 2008; Secor 2015). Our familiarity with more accessible fauna (terrestrial or 318

shallow marine) indicates that cyclic or periodic movement behaviour associated with environmental 319

fluctuations (e.g. seasonality, light, tide) is the norm (e.g. diel vertical migrating species (Dingle 1996; 320

Hays 2003). In contrast to terrestrial and shallow marine environments, deep water habitats are more 321

temporally stable for environmental factors such as light (or its absence) and temperature. Accordingly, 322

it might be expected that cyclic behaviour would be less pronounced in animals confined to deeper 323

benthic habitats (e.g. Aguzzi et al. 2009; Bahamon et al. 2009; Aguzzi et al. 2015 – but see Priede et al. 324

1994 for evidence of seasonal changes). Such is the case for snow crab monitored in this study, where 325

short term cyclic environmental fluctuations like light, tide and temperature played a very small role in 326

determining movement velocities. In contrast to shallower-distributed and better-studied species, low 327

levels of light reach the depths occupied by snow crab in our study area (likely <1% of surface levels; 328

Jerlov 1969). It is uncertain whether the snow crab’s slight nocturnal tendencies observed in this study 329

were driven by marginal reductions in predation risk, improved foraging success, or other mechanisms. 330

Most crab species studied to date have shown a tendency toward increased nocturnal activity levels 331

(Scylla serrata Hill 1978; Tachypleus tridentatus Wada et al. 2016; Callinectes sapidus Carr et al. 2004), 332

which has been related to foraging or predator avoidance. The relevance of these studies to snow crab 333

behaviours are uncertain as the majority of previous studies have occurred in shallow estuaries. Snow 334

crabs are generalist feeders, willing to take a variety of benthic invertebrates and fish or scavenge for 335

food (Squires and Dawe 2003). Such a wide spectrum of prey may allow foraging opportunities 336

throughout the diel cycle. Larger snow crab (particularly those above 65 mm) are less vulnerable to 337

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predation relative to younger conspecifics (Chabot et al. 2008) and therefore may also rely less on the 338

cover of darkness to avoid the visual predators that are most active diurnally. 339

Responses to tidal cycles were also weak, with slight increases in activity observed during slack and 340

slightly falling tides and no change in movement direction. Such a subtle response was unexpected 341

based on a brief hyperbolic positioning telemetry study on primarily female snow crab off Japan 342

(Kanawa et al. 2014), where snow crab were qualitatively observed to move into currents of 6-7 cm/s. 343

Modelled tidal current velocities in our area during the first 3 days post-release are comparable to those 344

observed by Kanawa et al. (2014), averaging 5 cm/s across the tidal cycle and reaching up to 13 cm/s 345

(http://navigator.oceansdata.ca portal). Even slow current velocities could provide important scent cues 346

to scavenging crabs but such behaviours, if they exist, did not emerge as an important explanatory 347

variable. 348

Snow crab are stenothermic and their population dynamics are heavily influenced by changes in water 349

temperature (e.g. Zisserson and Cook 2017). Laboratory work (Foyle et al. 1989; Maynard 1991) and 350

limited field observations (Maynard 1991) suggest that temperature is also a key driver of snow crab 351

activity. For example, Foyle et al. (1989) observed in the laboratory that snow crab moved faster in 352

warm environments (0-18°C), but these high temperature movements were restricted to short bursts of 353

activity, whereas snow crab in that study were more continuously active at temperatures between 0 and 354

3°C. Even small shifts in temperature can negatively affect snow crab movement physiology. For 355

example, walking can induce oxygen debts in snow crab when water temperatures are increased from 356

0°C to 3.5°C (Maynard 1991). Such rising metabolic costs with temperature likely constrain snow crab to 357

temperatures less than 7°C (Foyle et al. 1989). Observations in the lab and in the wild suggest snow crab 358

pursue low energy lifestyles with considerable time in sedentary modes (Foyle et al. 1989; Maynard 359

1991; Kanawa et al. 2014). In our study, water temperature explained little of the variation in observed 360

movement velocities but the trends we observed were significant and did support the idea that 361

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movement velocities generally increase with temperature within the typical range of temperatures in 362

our study area (0-3°C). Movements observed under natural conditions will probably rarely reach the 363

maximum capacity of snow crab except during predator avoidance or mating (Maynard 1991). Within 364

this physiological envelope, it appears there is room to achieve the modest velocities that characterize 365

normal snow crab movements. This is supported by the observation that tagged snow crab moved 366

significantly faster in the first 24 h following release. 367

The absence of strong environmental influence on movement appears to be largely driven by the 368

behavioural plasticity of snow crab coupled to the more stable offshore environments they occupy 369

compared to the often studied inshore crab species. In snow crab, movement velocities regularly 370

spanned 1-2 orders of magnitude within short timeframes. Limited observations of movements by snow 371

crab have been conducted in laboratory studies and through camera observations in the wild as well as 372

inferred from other smaller scale telemetry studies (Maynard et al. 1991; Kanawa et al. 2014). The 373

velocity results observed in this study generally correspond to those observed in coastal areas where 374

Maynard (1991) found snow crab in 4°C water moved at 11-26 m/h (n=4). However, our measured 375

velocities were much higher than found in individuals tracked at 1°C in other studies (2-9 m/h, Maynard 376

1991; 6 m/h, Foyle et al. 1989). Our results were also higher than those obtained from mark-recapture 377

observations (Brethes and Coulombes 1990 cited by Maynard; 1991), which averaged 5-9 m/h 378

depending on depth strata and presumably temperature. Underestimates of speed would be expected 379

for mark-recapture studies as any deviation from a linear movement path would not be accounted for. 380

Telemetry studies such as ours would likely provide more robust estimates of instantaneous speeds than 381

traditional studies. Nevertheless, our results should still be considered minimum estimates as our 382

underlying movement paths could incorporate brief periods of inactivity. While we were unable to 383

separate sedentary from active behaviour between consecutive locations (i.e. a track segment), the 384

movement tracks indicated that animals in our study remained active for a large portion of time and no 385

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animals were observed to remain within a small area for very long. This is in contrast to some laboratory 386

(Foyle et al. 1989) and telemetry (Kanawa et al. 2014) observations where snow crabs spent 387

considerable time in a sedentary state. For example, Foyle et al. (1989) state that snow crabs spent 388

extensive periods of time inactive and would become sporadically active for 30-45 minute periods. 389

Kanawa et al.’s (2014) accelerometer sensors indicated that even at their most active time of day, only 390

about 30% of snow crabs were mobile. The observed differences might be explained by the confinement 391

and stress of laboratory conditions (Foyle et al. 1989) or the sensitivity of accelerometer sensors 392

(Kanawa et al. 2014), for which little detail was provided. 393

The spatial nature of movements also varied in this study, with clear periods of meandering interspersed 394

with directed linear movements. Phases of movement were often maintained for several days. While it 395

is tempting to assign such patterns to foraging and dispersal behaviours, no obvious differences in 396

velocity were apparent that might distinguish different motivations to move. Patterns of localized 397

movement interspersed with periods of dispersal are characteristics of Levy Flight movement patterns; 398

which are thought to be advantageous in systems with patchy prey fields (Humphries et al. 2010). Due 399

to the generalist nature of snow crab diet and homogenous nature of the substrate in the study area we 400

had little expectation that snow crab movements would be characterized as Levy Flight or other 401

foraging-based descriptor. 402

The homogeneity of habitat may be a factor explaining the lack of site fidelity displayed by our tagged 403

snow crab. Most tagged animals quickly left the telemetry array to roam the Sydney Bight basin and 404

few returned. Most animals that were relocated by mobile surveys were within 10-15 km of the release 405

site; a distance that allowed access to shallower slope habitats where mating occurs (Mullowney et al. 406

2017). Occupation of shallow water was followed by a return to deep water habitats and a small 407

increase in the number of animals detected by our array in mid-March, 2016. However, the majority of 408

tagged animals were detected beyond our fixed telemetry array, or not at all. Other decapods show 409

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strong site fidelity. For example, the American lobsters in coastal habitats adjacent to our study site 410

(Cote unpublished data) and in other study areas (Karnofsky et al. 1989) repeatedly occupied specific 411

den sites. More extreme examples are spiny lobsters, which have remarkable abilities to return to home 412

ranges once displaced from long distances (Boles and Lohmann 2003; Lohmann and Lohmann 2006). 413

Both of these species live in heterogeneous coastal environments where certain habitat features 414

provide important ecological services (e.g. refuge). In contrast, the uniformly muddy bottom in Sydney 415

Bight may provide little reason to remain in or return to a specific location. This may be different in 416

other areas. For example, in Bonne Bay, a Newfoundland fjord, the patchy distribution of snow crab 417

was thought to be driven by local substrate differences (Comeau et al. 2011). 418

The estimated individual crab displacements observed during our work (mean of 10 km and max of 37 419

km) was well within the range of those estimated by mark-recapture studies in our general study area at 420

29.9 km/year (Cook et al. 2015), the adjacent Scotian Shelf at 25.4 km/year (Cook et al. 2015) and other 421

areas such as the northern Gulf of St. Lawrence (20 km/year, Brethes and Coulombes 1990, in Maynard 422

1991), Bonavista Bay (Taylor 1992) and the Grand Banks (Mullowney et al. 2017). Many of our animals 423

were not detected once leaving the telemetry array and could have moved farther afield than our Wave 424

Glider survey area. However, harvester returns were restricted to the Sydney Bight area and no animals 425

were detected moving beyond to the Cabot Strait (by OTN’s Cabot Strait array) or to the Scotian Shelf 426

(by OTN’s St. Ann’s Bank array). Other mark-recapture (Moriyasu et al. 2001) and telemetry studies 427

(Cook et al. 2015) found that snow crabs can move between eastern and western Cape Breton, 428

however, this movement does not appear to occur in all years. Cook et al. (2015) documented 10 of 27 429

acoustically tagged adult male snow crab in 2013 migrating between eastern and Western Cape Breton 430

within eight months of release, whereas none of the tagged snow crab in the current study made this 431

migration. One mechanism that may explain the interannual variability in long distance migration is 432

mate search patterns as has been observed in many other species (Dingle 1996). The sex ratio of mature 433

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animals in the population for 2013-2014 in eastern Cape Breton was 1% females (Cook et al. 2015), 434

whereas western Cape Breton was >55% females (Hébert et al. 2017). This suggests that males had a 435

much greater likelihood of finding a mate in waters off western Cape Breton compared to those of 436

eastern Cape Breton. During the current study, sex ratios of mature snow crab were >20% female in 437

eastern Cape Breton (DFO 2016), while the sex ratio remained similar to that observed in 2013-2014 in 438

western Cape Breton. 439

All life-stages / sexes of tagged snow crab during both autumn releases displayed a general tendency to 440

move in a southerly direction beginning in October. For juveniles and females, which were captured on 441

slope habitats and released into the study area, this shift in distribution may at least in part represent a 442

return to their preferred habitat (but see below). The directional shift of our adult males however, 443

combined with subsequent Wave Glider relocations of many animals in proximity to slope habitats, 444

suggests that these animals were initiating their annual mating migration, but much earlier than would 445

be expected. It is well established that mature or maturing snow crab undertake migrations to 446

shallower water to moult or mate in the spring; returning to deeper water in the fall (reviewed by 447

Mullowney et al. 2017). The up-slope movements are often 10s of kilometres, vary according to local 448

bathymetric conditions (Mullowney et al. 2017) and are thought to be triggered by water temperature 449

(Conan et al. 1996; Biron et al 2007). The entry into shallower water by adult males is timed to avoid 450

seasonally warm surface waters. The much earlier initiation of movement observed in our study might 451

be explained by the fact that much of the existing knowledge of snow crab movement patterns are 452

based on data collected from surveys with low temporal resolution or from small-scale telemetry 453

studies. Furthermore, in our study area, the relatively flat bottom of Sydney Bight means that autumn 454

movements toward the slope habitats does not result in great changes of water depth. In our study 455

area, surface waters temperatures peaked in mid-September and continued to cool to sub or near 0°C 456

temperatures in the spring (March and April). In contrast, the deep water in the area of the array 457

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continued to warm until December. Therefore, it is possible that individuals were staging near slope 458

habitats until thermal conditions were optimal for mating. 459

The extent of southerly movements was consistent with those previously documented in the wild for 460

snow crabs of different lifestages/sexes. This was true even for the animals which we translocated 461

during the study. Juvenile males in our study migrated earlier and moved further than females and, to a 462

lesser extent, adult males. Within a specific area, migrations are typically greatest for juvenile males 463

and primiparous females, which typically occupy deeper, warmer waters before moving to shallower 464

mating and moulting grounds (Mullowney et al. 2017). In contrast, multiparous females showed a 465

reduced seasonal up-slope movement (Lovrich et al. 1995; Mullowney et al. 2017). 466

The lifestage/sex comparisons in this study were somewhat confounded by the fact that juvenile males 467

and females were relocated from hard-bottom slope habitats into the mud-bottomed habitat typically 468

occupied by adult males. The shift of these lifestage/sex classes to habitats that they normally avoid 469

might be expected to trigger compensatory responses such as a quick return to more favorable slope 470

habitats (Biron et al. 2007) or to seek refuge from predators. Few females or juveniles were detected by 471

the Wave Glider surveys and none were found on or near slope habitats. Lifestage/sex-specific 472

behavioral responses (burying in the mud or hiding within structurally complex substrates) and shorter 473

battery life of the tags used for these smaller animals may have limited the detections of juveniles and 474

females by the Wave Glider. Commercial fishery returns are also biased as the fishery targets adult 475

males and therefore would be less likely to document movements of other lifestage/sex classes beyond 476

the array. Nevertheless the movement velocities of females and juveniles were slower than for adult 477

males, suggesting they have a reduced ability and/or willingness to move. Furthermore, observations of 478

restricted movements were also noted in previous telemetry studies for females (Maynard and 479

Robichaud 1986; Conan et al. 1996) as well as translocated individuals of other species (e.g. Cook et al. 480

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2014). Therefore, despite the potential detection differences among lifestages and sexes, it is probable 481

that females and juveniles had reduced movement behaviour relative to adult males. 482

Advances in biologging technologies are allowing marine scientists to reveal previously unobserved 483

movements and behaviour. This is especially true for species that reside in deeper benthic habitats 484

where basic attributes such as speed and migratory patterns are often unknown for such species. Here 485

we demonstrate the utility of acoustic telemetry for filling knowledge gaps in the movements of snow 486

crab. This technology does not come without its challenges, however, as observations received are not 487

perfect. Error prone triangulations of locations can plague standard analyses as aberrant fixes cloud 488

perceptions of true movements. State-space models have long been proposed as a means to account for 489

large observation errors and improve inference of movement behaviour (Jonsen et al. 2005), but 490

widespread use has been hampered by the computational burden of fitting such models (Jonsen 2016). 491

Recent developments in tools for estimation of complex hierarchical models, such as Template Model 492

Builder, may change this trend by making the application of state-space models more efficient and 493

accessible (Auger-Méthé et al. 2017). The coupling of advanced biologging technologies with advanced 494

computational methods therefore creates great potential for revealing previously unobservable traits 495

and behaviours. 496

Ocean engineering technologies are rapidly advancing, now permitting the development of both small 497

and large scale marine industrial projects that were previously not possible. This “Ocean Industrial 498

Revolution” (McCauley et al. 2015) will bring great social and economic benefits to human societies, but 499

it will be critical that we plan and manage these in ways that do not compromise the health and 500

resilience of ocean ecological communities which similarly support the food security and economic well-501

being of human communities. The influence of the subsea cable installation on snow crab in Sydney 502

Bight remains to be evaluated, however, the hybrid telemetry technology combined with a partnership-503

oriented approach among commercial harvesters, the electric utility, the regulator, and the Ocean 504

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Tracking Network enabled the collection of baseline data which will be essential to evaluating the 505

potential effects of the project. Collaboration between industry, academia and government has been 506

demonstrated to increase the effectiveness of environmental science (Morris et al. 2017; Rosenlund 507

2017). The benefits of such collaborations can be far reaching, including improved access to resources 508

and data, broader expertise, increased trust and confidence in the science outcomes, and improved 509

social license for industry. 510

Acknowledgements 511

This work was funded by Emera Newfoundland and Labrador as part of the monitoring program 512

associated with the Environmental Assessment for the Maritime Link Project. Gratitude is extended to 513

local harvesters and Ben Zisserson (DFO) for advice on local snow crab distributions and tagging 514

techniques. Field activities were supported by a large and varied team including the captains and crew 515

of the Island Venture 1 and 3Js 1, Randy Norman, Maureen Cameron and John Gosse from Amec Foster 516

Wheeler (AFW), and Duncan Bates, Joe Pratt, Sue L’Orsa, Richard Davis and the data science team from 517

Ocean Tracking Network. Emera (receivers, moorings and transmitters) and OTN (receivers and Wave 518

Glider) provided field equipment for the project. GIS support was provided by Juanita Abbott (AFW), 519

Christina Pretty (DFO), Peter Horn (Emera) and Heather Snow (Emera). Thanks are also given to Darrell 520

Mullowney (DFO) for access to his team’s draft review of snow crab movements and to Jim McCarthy 521

(AFW) for comments on the manuscript. 522

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Linnaeus University, Kalmar, 145p. 654

Secor, D.H. Migration Ecology of Marine Fishes. John Hopkins University Press. 2015. 304 pp. 655

Squires, H.J. and Dawe, E.G. 2003. Stomach contents of snow crab (Chionoecetes opilio, Decapoda, 656

Brachyura) from the northeast Newfoundland Shelf. J. Northw. Atl. Fish. Sci. 32: 27-38. 657

Taylor, D.M. 1992. Long-term observations on movements of tagged male snow crabs in Bonavista Bay, 658

Newfoundland. N. Am. J. Fish. Manag. 12: 777-782. 659

Wada, T., Mitsushio, T., Inoue, S., Koike, H. and Kawabe, R. 2016. Movement patterns and residency of 660

the critically endandered horseshoe crab Tachypleus tridentatus in a semi-enclosed bay determined 661

using acoustic telemetry. PLoS ONE11(2).e0147429. https://doi.org/10.1371/journal.pone.0147429 662

Weston, R. (chair). 2011. Report on the snow crab industry in the Atlantic provinces and in Quebec. 663

Report of the Standing Committee on Fisheries and Oceans. 664

Wiltchko, W. and Wiltschko, R. 2005. Magnetic orientation and magnetoreception in birds and other 665

animals. J. Comp. Physiol. 191: 675-693. 666

Zisserson, B.M. and Cameron, B.J. 2016. Application of Acoustic Telemetry Tags on Snow Crab. Can. 667

Tech. Rep. Fish. Aquat. Sci. 3169: v + 17 p. 668

Page 29 of 41



Draft

Zisserson, B. and Cook, A. 2017. Impact of bottom water temperature change on the southernmost 669

snow crab fishery in the Atlantic Ocean. Fish. Res. 195:12-18. 670

Page 30 of 41



Draft

Tables 671

Table 1: Summary of acoustic receiver mooring deployments to monitor movements of snow crab 672

within Sydney Bight in 2014 and 2015. 673

674

Deployment

Period

Number of

Receivers Receiver Type Array Configuration

Deployment

Depth

2014-10-23 41 Tethered VR2

(n=20)

VR2 acoustic

release (n=21)

~500 m x 500 m high-

resolution positioning

system (9 receivers at 250 m

spacing) + detection lines (33

receivers at 500 m spacing)

106-115m

2014-09-13 –

2015-10-06 –

2016-05-15

40 Tethered VR2

(n=27)

VR2 acoustic

release (n=13)

~1200 m x 1200 m high-

resolution positioning

system (16 receivers; 400 m

spacing) + detection lines (n

receivers at 500-800 m

spacing deployed in two

lines)

106-115m

675

Table 2: Tagging deployments of snow crab within Sydney Bight in 2014 and 2015. 676

Date Released N Male Female Tag Type

2014-10-31 48 48 adults 0 V13 (n=24), V9 (n=24)

2015-10-05

38 38 adults 0 V13

2015-10-07

78 32

adults;

31

juveniles

15 V9

677

Table 3. Summary of Wave Glider surveys conducted within Sydney Bight to detect movements of 678

acoustically tagged Snow Crab. 679

Survey Date Survey Distance (km) Spatial Coverage

(km2)

1

Crab Detected

Jun 13-22, 2015 544 447 19

Oct 5-31, 2015 320 272

110

Oct 19-28, 2016 430 339 17

May 30-Jun 7,

20172

306 266 11

Jul 2-14, 2017 554 366 16 1Area estimates assume a transmitter detection range of 500 m 680

2aborted 681

Page 31 of 41



Draft

Figure Captions 682

Figure 1: Telemetry array configuration in 2014 and 2015 relative to local bathymetry in the Cabot Strait 683

and the capture area of females and juveniles (red polygon). Inset: location of the Subsea Cable 684

Corridor (red) and Ocean Tracking Network receiver lines in the Cabot Strait and St. Ann’s Bank. 685

686

Figure 2: Wave Glider survey paths during mission portions when the vehicle was within the Sydney 687

Bight study area in 2015 (June and October), 2016 (October) and 2017 (May-June and July). The subsea 688

corridor is indicated by the shaded polygon. 689

690

Figure 3: Detections of tagged snow crab in the Sydney Bight study area by fixed receivers, Wave Glider 691

surveys and harvester returns. 692

693

Figure 4: Dispersal of all tagged snow crab (left panel) and chronology of movements for three animals 694

(#19854 and #19879: released Oct 31, 2014; #38306: released Oct 5, 2015). 695

696

Figure 5: Latitudinal movements over time of commercial sized male snow crab in 2014 and 2015 (top 697

left panel) and adult males, juvenile males and female snow crab tagged in 2015 (top right panel). 698

Locally Weighted Smoothers (LOESS) and 95% confidence intervals are superimposed. The change in the 699

detected population for each respective group is shown in the bottom panels. Dashed lines indicate the 700

spatial extent of the hyperbolic positioning array. 701

Page 32 of 41



Draft

Figure 6: Fine scale movement patterns (top panels) and corresponding velocities (bottom panels) of 702

two tagged commercial sized adult male snow crab. Release location is indicated by the black 703

crosshairs, whereas color patterns indicate specific days since release for each animal. 704

705

Figure 7: GAMM model predictions for movement velocity according to hour of day (left panel), tide 706

trend (centre panel) and bottom water temperature (right panel). Predictions are based on an adult 707

male crab at 1AM at slack tide with a bottom temperature of 2°C unless otherwise noted. Dotted lines 708

are 95% confidence intervals of the model prediction. 709

710

Figure 8: Average movement direction of tagged snow crab (points) during the post-acclimation period 711

(>1 day following release) during rising (blue) and falling tide (red). Lines external to the circle represent 712

the density distribution of bearings. Arrows represent the population mean direction of movement, 713

with the length of the arrows representing the weight of movement in that direction. 714

Page 33 of 41



Draft!

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Page 34 of 41



Draft

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Page 35 of 41



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Snow Crab Individuals#19854#19879#38306

±Data Sources: General Bathymetric Chart of the Oceans (GEBCO, 2014), GeoGratis

Page 36 of 41



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Oct 2014

Jan 2015

Apr 2015

Jul 2015

Oct 2015

Jan 2016

Apr 2016

Jul 2016

Oct 2016

Jan 2017

Apr 2017

Jul 2017

Tagging group●

●

●

Female

Adult Male

Juvenile Male

Detections of Tagged Snow CrabPage 37 of 41



Draft

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Falling TideRising Tide

Page 41 of 41



Draft - University of Toronto T-Space · Draft 1 Characterizing snow crab (Chionoecetes opilio)...

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Transcript of Draft - University of Toronto T-Space · Draft 1 Characterizing snow crab (Chionoecetes opilio)...