# Effects of anthropogenic magnetic fields on the behavior of a major predator of the intertidal and subtidal zones, the velvet crab Necora puber

Luana Albert, Frédéric Olivier, Aurélie Jolivet, Laurent Chauvaud, Sylvain Chauvaud

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## To cite this version:

Luana Albert, Frédéric Olivier, Aurélie Jolivet, Laurent Chauvaud, Sylvain Chauvaud. Effects of anthropogenic magnetic fields on the behavior of a major predator of the intertidal and subtidal zones, the velvet crab Necora puber. Marine Environmental Research, 2023, 190, pp.106106. 10.1016/j.marenvres.2023.106106. hal-04196756

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Submitted on 24 Nov 2024

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# Effects of anthropogenic magnetic fields on the behavior of a major predator of the intertidal and subtidal zones, the *velvet crab* *Necora puber*

Albert Luana <fnref n="1" />, <fnref n="3" />, *, Olivier Frédéric <fnref n="2" />, Jolivet Aurélie <fnref n="1" />, Chauvaud Laurent <fnref n="3" />, Chauvaud Sylvain <fnref n="1" />

## Abstract :

With the progress of the offshore renewable energy sector and electrical interconnection projects, a substantial rise in the number of submarine power cables is expected soon. Such cables emit either alternating or direct current magnetic fields whose impact on marine invertebrates is currently unknown and hardly studied. In this context, this study aimed to assess potential short-term exposure (30 min) effects of both alternating and direct magnetic fields of increasing intensity (72–304 µT) on the behavior of the high-ecological value *velvet crab* (*Necora puber*). Three experiments were designed to evaluate whether the strongest magnetic field intensities induce crabs' attraction or repulsion responses, and whether foraging and sheltering behaviors may be modified. We extracted from video analyses several variables as the time budgets crabs spent immobile, moving, feeding, or sheltering as well as total and maximal distance reached in the magnetic field (MF) gradient. The crabs exposed to artificial MF did not exhibit significant behavioral changes compared with those exposed to the “natural” MF. Overall, our results suggest that, at such intensities, artificial magnetic fields do not significantly alter behaviors of N. puber. Nevertheless, future studies should be conducted to examine the effects of longer exposure periods and to detect potential habituation or resilience processes.

## Highlights

* Submarine power cables emit high-strength magnetic fields in their vicinity. * Their protective rock

cover can cause a reef effect and attract crustacean species. * Necora puber crabs were exposed to AC

and DC magnetic field gradients (max. 304 µT). * Exploratory, feeding and sheltering behaviors were

studied across three scenarios. * *Necora puber* behavior was not altered by short-term magnetic field exposures.

<footnote n="1">¹ TBM Environnement, Auray, France</footnote>

<footnote n="2">² Muséum National d'Histoire Naturelle, Biologie des Organismes et Écosystèmes Aquatiques (BOREA), UMR 7208 MNHN/SU/UNICAEN/UA/CNRS/IRD, Paris, France</footnote>

<footnote n="3">³ Université de Brest, Laboratoire des Sciences de l'Environnement Marin (LEMAR - UMR 6539 CNRS, UBO, IRD, IFREMER), LIA BeBEST, Institut Universitaire Européen de la Mer, Plouzané, France</footnote>

<footnote>* Corresponding author : Luana Albert, email address : l.albert@tbm-environnement.com</footnote>
**Keywords** : magnetic fields, magneto-sensitivity, crustaceans, submarine power cables, marine
renewable energy devices, behavior
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# 1. INTRODUCTION

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One of the most urgent challenges of the 21st century is to provide energy security for countries facing climate change combined with demographic and industrial growth (Amorim et al., 2018). The development of the offshore renewable energy sector (e.g., wind, wave, and tidal energy) is one of the suggested ways to achieve carbon neutrality and sustainable energy systems. Wind farms, which are the most advanced offshore technology, are thus expanding over coastal areas (Ellaban et al., 2014; IRENA, 2019; Rinaldi, 2020; Soares-Ramos et al., 2020). As a result, numerous submarine power cables (SPCs) have been installed to transfer electrical power to the shore and to establish electrical connections between countries. When operational, SPCs generate magnetic fields (MFs, expressed in teslas, T), whose values vary linearly with current intensity, and decrease with distance from the cable (Meißner et al., 2006; Worzyk, 2009; Normandeau Associates Inc. et al., 2011).

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The potential effects of cable emissions on marine ecosystems are of major societal concern (Taormina et al., 2018). Many marine species from diverse taxonomic groups (e.g., teleost fish, mammals, crustaceans, mollusks, and elasmobranchs; reviewed in Fischer and Slater, 2010), orient their migratory movements using the latitudinal variations of the geomagnetic field, from 20 µT at the equator to 70 µT at the poles (e.g., Wiltschko, 1995; Lohmann and Ernst, 2014; Klimley et al., 2016). These natural cues are exclusively direct current (DC) fields, whereas SPC fields are either direct current (DC) or alternating current (AC) and depend on the number, twisting and distance between the electric wires embedded in the main cable. Dedicated to long-distance power transfers (>50 km), DC cables produce static MFs that are superimposed on the ambient geomagnetic field (Wei et al., 2017; Otremba et al., 2019), while AC cables are usually shorter and induce both a 50-60-Hz MF and an induced electric field (Meißner et al., 2006; Gill et al., 2012; Kavet et al., 2016). Currently, the values of cables' MF emissions are mostly estimated from modeling and theoretical calculations (Albert et al., 2020). For example, it is estimated that a single-phase DC cable (15-cm diameter, 1000 A) buried 0.5 m deep would emit the following MF intensities: 2700 µT at contact, 400 µT at seabed, 200 µT at 1 m, 100 µT at 2 m, and 20 µT at 10 meters distance. Due to a compensation effect between their three electrical phases, AC cables (27-cm diameter, 12 cm between the cores) produce lower MFs with faster decline: 2479 µT at contact, 80 µT at seabed, 24 µT at 1 m, 7 µT at 2 m, and 0 µT at 10 meters distance (formulas from Salinas et al., 2009). In either case, at cable contact, artificial MFs can be 50 times higher than the geomagnetic field naturally experienced by marine species. SPCs are generally buried between 0.3 and 3 m deep in soft sediment or covered by thick and heavy structures on hard bottoms (Meißner et al., 2006). The exposure probability of a
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species is thus highly dependent on its vertical distribution and motility. Accordingly, species living close to the bottom, belonging to the demersal and benthic epi- and endofauna, should experience the strongest MFs on a chronic basis (Albert et al., 2020). For example, large decapod crustaceans can be prone to a reef effect and be observed on the foundations of offshore devices and SPC protective structures (e.g., concrete mattresses, rocks) (Langhamer, 2009; Krone et al., 2013; Taormina et al., 2020).

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Decapods are an important part of global coastal fisheries and play significant ecological roles in benthic ecosystems (Boudreau and Worm, 2012). Some adult species strongly affect benthic community structure through top-down control of other decapod and mollusk species (Quijon and Snelgrove 2005a, b). Occasionally, decapods may also act as keystone predators by regulating grazing communities, thus preserving the structural complexity and productivity associated with benthic vegetation (Elner and Vadas 1990; Silliman and Bertness 2002). Decapods, particularly early life stages, are subjected to high predation pressure (Eggleston et al. 1997; Palma et al. 1998). As a result, many decapods forage at night and seek protective shelter during the day (Stevens et al., 2003; Hunter and Sayer, 2009).

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Stressful events, including anthropogenic pollution, can disrupt the frequency, duration, and performance of one or more activities associated with feeding and anti-predator behaviors and thus adversely affect crustacean fitness (Rossong et al., 2011; Wale et al., 2013, Roberts and Laidre, 2019). For example, a decrease or cessation of locomotor behavior may lead to a decline in food encounters and/or intake and reduce the chance of escape and shelter from predators (Wale et al., 2013). The ability to access and use natural crevices or other shelters is known to be a limiting factor for population growth and recruitment dynamics in several crustacean species (Lawton and Lavalli, 1995; Vannini and Cannicci, 1995). In turn, prolonged anti-predator responses can result in significant energetic costs (Lima and Dill, 1990). The burgeoning research effort on magnetic pollution has indicated that the edible crab (*Cancer pagurus*), the European lobster (*Homarus gammarus*) (Scott et al., 2018; 2019; 2021), the freshwater crab (*Barytelphusa cunicularis*) (Rosaria and Martin, 2010), and the freshwater spiny cheek crayfish (*Orconectes limosus*) (Tanski et al., 2005) show a clear attraction to MF-exposed shelters. In contrast, potential signs of repulsion were observed in the spiny lobster *P. argus* (Ernst and Lohmann, 2018), while other works have recorded no changes in the shelter-seeking behavior of the European lobster (*Homarus gammarus*) with MF addition. In line with such results, MF induced no changes in the spatial distribution of the brown shrimp (*Crangon crangon*), the estuarine mud crab (*Rhithropanopeus harrisii*), the American lobster (*H. americanus*), the Dungeness crab (*Metacarcinus magister*), the red rock crab (*Cancer productus*), and the yellow
rock crab (*Metacarcinus anthonyi*) (Bochert and Zettler, 2006; Woodruff et al., 2012, 2013; Love et al., 2015, 2017). This conflicting literature emphasizes the lack of understanding of crustacean responses to artificial MF and suggests potential intensity-dependent effects, as most attraction responses only occurred with very high-intensity MF (2.8 mT).

In this study, a series of laboratory tank-based experiments were carried out to explore whether artificial magnetic fields affect foraging and shelter-seeking behaviors of a common crab of the European coasts, the velvet crab (*Necora puber*) (Wilhelm, 1995). Velvet crabs are part of the epibenthic fauna, being attracted to the hard substrate and artificial shelters associated with offshore wind farms (Ter Hofstede et al., 2022). They are commercialized and a major predator and scavenger species of the European intertidal and subtidal zones (at depths up to 80 meters) and are found on rocky and sandy bottoms (Norman, 1989, Freire and González-Gurriaran, 1995). Our experiments were designed under the assumption that artificial MF cues are a stressful signal for crustaceans. Both AC and DC MF gradients were tested with a maximum intensity of 304 µT, to mimic the emission at seabed from an AC/DC three-phase cable powered with 1600 A and buried at 0.3-meter depth. In a first experiment, we documented the exploratory/roaming behavior of velvet crabs and hypothesized that they would be repelled by the highest MF intensities and reduce their locomotor behavior. In a second experiment, we probed crabs' foraging behavior by adding food in the zone of highest MF emissions. We predicted that exposed crabs would reduce both their locomotor behavior and progress along the gradient, resulting in a decrease in food intake. Finally, we evaluated whether MFs interfere with crabs' sheltering behavior by placing an artificial shelter at the end of the gradient. We expected that MFs would stimulate shelter-seeking behavior, reflected by a rise in locomotor behavior. We presumed that MF exposure could interfere with the use of the shelter.

## 2. MATERIALS & METHODS

### 2.1 Crustacean collection and maintenance

Velvet crabs (*Necora puber*, 250 individuals) were collected in November 2020 by scuba diving in the bay of Brest, France. The individuals were kept in two 600 L flow-through tanks (length × width × height of 1 × 1 × 0.6 m) supplied with 13 °C seawater (natural seasonal temperature), for 23 days. They were fed daily with a variety of frozen food (e.g., squids, mussels, shrimps, and fish) and provided with artificial shelters (grey pipe pieces). To ensure the detection of the crabs during video tracking analysis, a test pattern (a 2 × 1 cm rectangular white piece of oil cloth) with a central black cross design was glued to the center of reach crab's carapace. Behavioral trials were carried out
in a thermally regulated (19–22 °C) and blind experimental room with a 10:14 h light: dark cycle that matched the winter photoperiod. Before the trials, 220 crabs were distributed among five 100-L glass tanks (44 crabs per 0.3 m²; water depth: 30 cm) for a 2-week acclimation period to the experimental facilities, with two feedings a day. The tank surface was complexified using artificial shelters (PVC pipes 63 mm in length, 125- and 200-mm diameter) both to reduce agonistic behaviors and cannibalism and to accustom crabs to their use. All the room tanks were supplied by continuous seawater flow (84 L h⁻¹) in a closed circuit (with freshwater supply of 151 L h⁻¹). The successive filtering systems included mechanical polyethylene filtration followed by Biogrog biological filtration and UV treatment. Throughout the study period, the temperature was maintained at 13.4 ± 0.42 °C by a cooling unit. Each acclimation tank was provided with an air pump to maintain >95% oxygen saturation. The water was kept at a pH of 7.8 and other parameters were maintained below the following threshold values: NH₄⁺ <0.1 mg/L, NH₃ <0.01 mg/L, NO₂ <0.05 mg/L, NO₃<10 mg/L.

## 2.2 Experimental device

The artificial MFs were created using the Magnotron, a Helmholtz copper coil system (1.5 m × 1.5 m, 2.5-mm² wire diameter) detailed in Albert et al. (2022). Briefly, two coils were deployed in a vertical position and parallel to each other at 1 meter distance. With this configuration, the MF strength was homogeneous between the coils (304 µT) and decreased to 72 µT in their periphery (Fig. 1). The coils produced both direct (DC) and alternating (AC) current magnetic field: in DC treatment, they were connected in a branch circuit to a DC power supply (14.5 V; 4.6 A) and in AC treatment, they were powered by the electrical current (60 V; 5 A) generated by an isolating transformer (model CM3300/200/PT), with rheostat control. All the electrical parameters (voltage, electric intensity, on/off switching, and coil temperature) were recorded in real time by purpose-built software developed by MAPPEM Geophysics (http://www.mappem-geophysics.com/). The MF intensity gradients were monitored using a magnetometer (Mag690 Three-axis, Bartington Instruments, and 0.1 Hz) placed within the area of homogeneous intensity. The whole system was isolated by black curtains to avoid visual disturbance of the crabs during the behavioral trials.
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## 2.3 Behavioral trials

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A white opaque Plexiglas tank (1.5 × 0.45 × 0.25 m) was centered in each of the two MF gradients (Fig. 1), with one end under the coil (~ 304 µT). Lengthwise, the experimental tanks were separated hermetically into three identical corridors (15 cm wide, 0.2 m water depth) with independent water inflows/outflows connected to the main water circuit. At the end furthest from the coil, a removable perforated and transparent section delimited an *initial zone* (0.2 × 0.15 × 0.25 m) associated with the lowest MF strengths (72–78 µT). For both tanks, the incoming water flows were directed towards the initial zones. Three distinct experimental scenarios (tests 1 to 3) were set up to study the potential effects of artificial MFs on the exploratory, feeding, and shelter-seeking behavior of crustaceans, respectively. Test 1 evaluated whether MFs induce repulsive responses in crustaceans and reduce their exploratory behavior (N = 69 crabs). Tests 2 and 3 investigated whether MFs modify velvet crab foraging (N = 72 crabs) and shelter-seeking behaviors (N = 69 crabs), respectively. For each test, three MF treatments were used: (1) ambient with the coils being turned off (i.e., 47 µT) for the control treatment, CT; (2) direct current, DC (72–304 µT), and (3) alternating current, AC (72–304 µT). All individuals were tested once, and the magnetic treatments were randomly assigned. Due to technical constraints, the initial zone was exposed to 72 µT during the MF treatments, which was 1.5 times higher than the ambient field of the room. However, the control treatment group was included in the experimental design to monitor the potential effects associated with such exposure in the initial zone.

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In all three tests, each magnetic treatment was simultaneously applied to three individuals and replicated eight times (n = 24), except for DC in Test 1 and CT in Test 3, which were replicated 7 times (n = 21). Before each trial, the corresponding magnetic field was launched, and one crab was placed in each of the 6 initial zones for a 30-minute acclimation period. Prior the transfer of the crabs, a fixed quantity of frozen shrimps or a shelter (a 63–mm diameter PVC pipe section), for Test 2 and Test 3 respectively, were placed in the zone of highest MF strength of each corridor. Individual behavior was recorded using two GoPro HERO 5 black cameras located 1 m above each experimental tank (2.7-K resolution, linear screen, 30 frames per second). These were remotely launched 5 minutes prior the end of the acclimation phase. The behavioral trial was then started for a 30-minute period when the partition walls were removed. At the end of each trial, the individuals’ carapace width (cm) was measured. Since *N. puber* forages predominantly at night, all trials were nocturnal and performed from 18 h 30 to 23 h 00 pm. Although the vision of the velvet crab has not been thoroughly studied, there is evidence that blue crabs (*Callinectes sapidus*), which belong to the same super family
(Portunoidea), are visual predators (Hines, 2007). Some behavioral experiments have suggested that the blue crab can discern blue, yellow, and red colors (Baldwin and Johnsen, 2009). Accordingly, as vision may assist the nocturnal exploratory behavior of *N. puber*, a weak light source (a dim white LED tape between of 7.7–10.7 µmol. photons.m⁻²s⁻¹) was added one meter above each corridor. In addition, the use of LED rails ensured light homogenization along the MF gradient.

## 2.4 Behavioral analyses

The exploratory, foraging and shelter-seeking behaviors of the velvet crabs were described using a set of seven variables. First, activity budgets were described by three behavioral variables that were common to the three tests: the time spent stationary ($T_{station}$), the time spent walking ($T_{walk}$), and the time spent trying to exit the tank ($T_{escape}$). In Test 2 and Test 3, respectively, the times spent feeding ($T_{food}$) and inside the shelter ($T_{shelter}$) were also measured. Crabs' activity budgets were compiled from 30-min video footages using the focal sampling method on BORIS software (Behavioural Observation Research Interactive Software v. 7.9.7). Then, all videos were analyzed to compile the crabs' x and y coordinates in each frame (29.97 fps) by use of Kinovea video-tracking software. The *trajr* R package was used to draw the trajectory of each crab. As the tank's configuration forced the crabs' movement path to one dimension (x-axis), their trajectories were simply described by the *Total distance traveled* and *Maximal distance reached* in the corridor, in cm. In addition, the crabs were divided into three groups according to their progression in the MF gradient: i) reached the end of the corridor (*complete crossing*); ii) remained in the initial zone (*no crossing*); or iii) moved through the corridor without reaching the opposite end (*incomplete crossing*) (see trajectory examples in **Error! Reference source not found.**).

## 2.5 Statistical analyses

First, the mean carapace width (cm) of the crabs was compared across the MF treatments using the single-factor ANOVA test, with Tukey's post-hoc tests. The effects of the MF treatments on the crab's behavioral variables were investigated using models that account for the excess of sampling zeroes (or one in some cases) that was caused by stationary individuals. Zero- or one-inflation models, GAMLSS (generalized additive models for location, scale, and shape), were used for proportional data (e.g., time fraction spent in the different behavioral categories). GAMLSS allowed the fitting of a zero/one-inflation parameter using a mixed parametric distribution (i.e., both continuous and discrete) on the interval [0, 1]. The magnetic treatment was used as the linear predictor of the response variable (either *Tstation*, *Twalk*, *Tescape*, *Tfood*, *Tshelter*, or *Maximal distance reached*). The
GAMLSS models were performed using the “FactomineR” and the “gamlss.inf” packages (Stanisopoulos et al., 2017) in R version 4.1.0 (R Core Team, 2021). Then, a binomial-gamma hurdle model (a generalized linear model) was used for zero-inflated continuous data (i.e., Total distance traveled). The relevance of the MF treatment predictor was assessed with likelihood ratio tests (“lmtest” package) that compared the fit of the observed data of the null model (without any predictor) and the full model (with the MF treatment as predictor). When the p-value was lower than an alpha level of 0.05, pairwise comparisons between the three modalities of the MF treatment variable (i.e., CT, AC and DC) were performed (“emmeans” package). Model goodness-of-fit was assessed by the graphical analysis of normalized quantile residuals. Finally, the effects of the MF treatments on crabs’ progress through the gradient (i.e., type of trajectory) were assessed using Fisher’s exact test (in the “stats” package).

## 3. RESULTS

The mean carapace width of the crabs tested was equal to 5.26 ± 0.77 cm (mean ± standard deviation SD) and was not significantly different between the three MF treatments (ANOVA: *F* = 2.01, *df* = 2, *p* = 0.14). During the acclimation phase, the crabs sheltered inside the PVC pipes provided. However, due to high agonistic behaviors during the first few days of acclimation, 7 crabs died, and 5 crabs lost a leg. Among the injured crabs, two individuals with unimpaired locomotor ability were used during the experiment.

### 3.1 Activity budgets

In Test 1, designed to characterize the exploratory behavior of crabs, the individuals remained motionless most of the time regardless the MF treatment, (86.8 ± 4.3%, mean ± standard error) (Fig. 3). In particular, 37.7% of the crabs remained stationary inside the initial zone throughout the 30-min trial. Active individuals spent 9.1 ± 2.8% of the time walking and 4.1 ± 1.6% trying to escape the tank. The crabs' activity budgets did not vary significantly in DC and AC treatments in comparison with the control group, demonstrating no alteration of their exploratory behavior (Table 1).

In Test 2, which explored the crabs' foraging behavior, *Tstation*, *Twalk*, *Tescape*, and *Tfeed* occurred 84.5 ± 5.6%, 5.8 ± 2.1%, 1.7 ± 0.7%, and 8.0 ± 4.5% of the time, respectively. In total, 36.1% of the individuals remained motionless in the initial zone. The DC and AC treatments caused no changes in the activity budgets of the crabs tested compared to control group. The locomotor behavior and food intake were not affected by the MF treatments (Table 1).
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Test 3 aimed to evaluate whether MFs interfere with the crabs' shelter-seeking and sheltering behavior. During the behavioral trials, crabs spent 88.9 ± 3.9% of the time stationary, and among them, 42% remained strictly in the initial zone. In active individuals, 6.2 ± 2.1% of the time was spent walking, 0.9 ± 0.5% on escape attempts, and 4.1 ± 2.3% inside the shelter (Table 1).

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## 3.2 Progression through the MF gradient

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Crabs' progress along the MF gradient was classified as either *complete crossing*, *incomplete crossing*, or *no crossing*. In Test 1, 56.5% of the crabs remained in the initial zone (*no crossing*), 15.9% performed *incomplete crossings*, and 27.5% reached the end of the corridor (*complete crossing*) (details in supplementary data). With food addition (Test 2), a higher proportion of crabs (33.3%) initiated an *incomplete crossing*, 20.8% a *complete crossing* and 45.8% did not cross the corridor at all. Finally, in Test 3, 55.1% of the crabs performed *no crossing*, 15.9% an *incomplete crossing*, and 29.0% a *complete crossing*. Across these three experimental scenarios, the MF treatments (CT, AC, and DC) caused no changes in the crabs' trajectory (Test 1: *p* = 0.63, Test 2: *p* = 0.94, Test 3: *p* = 0.28; with χ² test).

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One critical ambition of the behavioral trials was to evaluate the effects of an MF gradient on the crabs' locomotor behavior. As stated earlier, a significant proportion of the crabs did not move in the MF gradient, which resulted in a zero-inflated data distribution of the continuous variable *Total distance traveled*. To consider this large number of zeros and fit the data distribution, a binomial-Gamma hurdle model was used to model the zero and non-zero data as two separate processes. First, the binomial model questioned the effects of MF on the probability that crabs would travel a non-null distance. Then, a gamma glm model evaluated whether the average of the non-zero distances covered by the crabs, differed significantly from those of the control group over AC and DC treatments. On average, regardless of the treatment, the crabs traveled 504.03 ± 166.91 cm in Test 1; 313.93 ± 135.31 cm in Test 2, and 304.02 ± 101.79 cm in Test 3. In Test 1 and 2, the AC and DC treatments did not change the ratio of moving and non-moving crabs (Table 2) and had no influence on their mean total distance traveled compared with that of the control group (Fig. 4, Table 2). In Test 3, the null hypothesis that the null and full models were equally effective was rejected at the 5% level. However, pairwise comparisons indicated that the variability explained by the MF treatment was due to a significant difference between the AC and DC treatments, but not between these treatments and the control group.

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Before the trials, we assumed that while moving on the x-axis of the tank, a crab would be exposed to increasing MF intensities that could potentially interfere with its locomotor behavior and
stop its progression. This hypothesis was tested by measuring the maximal distance reached (cm) through the MF gradient. However, this value did not vary significantly between the MF and the control treatments in any test (Fig. 5, Table 1).

<table><caption>Table 1. Summary of the likelihood ratio tests evaluating the effects of the MF treatments on the activity budgets and the Maximal distance reached of the velvet crab (Necora puber).</caption><thead><tr><th>Response variables ~ predictors</th><th>AIC</th><th>LRT(χ<sup>2</sup>(2))</th><th>P-value</th></tr></thead><tbody><tr><td colspan="4"><strong>TEST 1</strong></td></tr><tr><td>Tstation ~ 1</td><td>43.6</td><td></td><td></td></tr><tr><td>Tstation ~ MF treatment</td><td>40.3</td><td>0.73</td><td>0.69</td></tr><tr><td>Twalk ~ 1</td><td>16.0</td><td></td><td></td></tr><tr><td>Twalk ~ MF treatment</td><td>12.9</td><td>0.95</td><td>0.62</td></tr><tr><td>Tescape ~ 1</td><td>0.7</td><td></td><td></td></tr><tr><td>Tescape ~ MF treatment</td><td>-2.1</td><td>1.24</td><td>0.54</td></tr><tr><td>Maximum distance reached ~ 1</td><td>52.1</td><td></td><td></td></tr><tr><td>Maximum distance reached ~ MF treatment</td><td>49.8</td><td>1.68</td><td>0.43</td></tr><tr><td colspan="4"><strong>TEST 2</strong></td></tr><tr><td>Tstation ~ 1</td><td>50.7</td><td></td><td></td></tr><tr><td>Tstation ~ MF treatment</td><td>46.9</td><td>0.25</td><td>0.88</td></tr><tr><td>Twalk ~ 1</td><td>-14.4</td><td></td><td></td></tr><tr><td>Twalk ~ MF treatment</td><td>-17.2</td><td>1.27</td><td>0.53</td></tr><tr><td>Tescape ~ 1</td><td>0.7</td><td></td><td></td></tr><tr><td>Tescape ~ MF treatment</td><td>-20.1</td><td>1.24</td><td>0.54</td></tr><tr><td>Tfeed ~ 1</td><td>77.9</td><td></td><td></td></tr><tr><td>Tfeed ~ MF treatment</td><td>74.5</td><td>0.60</td><td>0.74</td></tr><tr><td>Maximum distance reached ~ 1</td><td>56.4</td><td></td><td></td></tr><tr><td>Maximum distance reached ~ MF treatment</td><td>53.4</td><td>0.98</td><td>0.61</td></tr><tr><td colspan="4"><strong>TEST 3</strong></td></tr><tr><td>Tstation ~ 1</td><td>50.0</td><td></td><td></td></tr><tr><td>Tstation ~ MF treatment</td><td>47.1</td><td>1.09</td><td>0.58</td></tr><tr><td>Twalk ~ 1</td><td>8.4</td><td></td><td></td></tr><tr><td>Twalk ~ MF treatment</td><td>7.8</td><td>3.45</td><td>0.18</td></tr><tr><td>Tescape ~ 1</td><td>0.7</td><td></td><td></td></tr><tr><td>Tescape ~ MF treatment</td><td>-2.1</td><td>1.24</td><td>0.54</td></tr><tr><td>Tshelter ~ 1</td><td>59.3</td><td></td><td></td></tr><tr><td>Tshelter ~ MF treatment</td><td>56.9</td><td>1.66</td><td>0.44</td></tr><tr><td>Maximum distance reached ~ 1</td><td>45.9</td><td></td><td></td></tr><tr><td>Maximum distance reached ~ MF treatment</td><td>42.2</td><td>0.25</td><td>0.88</td></tr></tbody></table>
<table><caption>Table 2. Summary of the likelihood ratio tests evaluating the effects of the MF treatments on the *Total distance traveled* by the velvet crab (*Necora puber*). The asterisks (*) indicate values under the 5% threshold. Pairwise comparisons between the modalities of the MF treatment predictor were performed for the binomial model that fitted the data observed in Test 3.</caption><thead><tr><th>Response variables ~ predictors</th><th>df</th><th>Log Likelihood</th><th>Test statistic<br>(χ<sup>2</sup>(2))</th><th>P-value</th></tr></thead><tbody><tr><td colspan="5"><strong>TEST 1</strong></td></tr><tr><td colspan="5"><strong>Binomial models (0 or 1):</strong></td></tr><tr><td>Non null Total distance traveled ~ 1</td><td>1</td><td>-46.2</td><td>0.10</td><td>0.95</td></tr><tr><td>Non null Total distance traveled ~ MF treatment</td><td>3</td><td>-46.1</td><td></td><td></td></tr><tr><td colspan="5"><strong>Gamma models (only the non-null distances):</strong></td></tr><tr><td>Total distance traveled ~ 1</td><td>2</td><td>-290.1</td><td>0.10</td><td>0.95</td></tr><tr><td>Total distance traveled ~ MF treatment</td><td>4</td><td>-290.0</td><td></td><td></td></tr><tr><td colspan="5"><strong>TEST 2</strong></td></tr><tr><td colspan="5"><strong>Binomial models (0 or 1):</strong></td></tr><tr><td>Non null Total distance traveled ~ 1</td><td>1</td><td>-49.7</td><td>0.34</td><td>0.85</td></tr><tr><td>Non null Total distance traveled ~ MF treatment</td><td>3</td><td>-49.5</td><td></td><td></td></tr><tr><td colspan="5"><strong>Gamma models (only the non-null distances):</strong></td></tr><tr><td>Total distance traveled ~ 1</td><td>2</td><td>-243.9</td><td>2.88</td><td>0.24</td></tr><tr><td>Total distance traveled ~ MF treatment</td><td>4</td><td>-242.4</td><td></td><td></td></tr><tr><td colspan="5"><strong>TEST 3</strong></td></tr><tr><td colspan="5"><strong>Binomial models (0 or 1):</strong></td></tr><tr><td>Non null Total distance traveled ~ 1</td><td>1</td><td>-47.6</td><td>8.68</td><td>0.01*</td></tr><tr><td>Non null Total distance traveled ~ MF treatment</td><td>3</td><td>-43.3</td><td></td><td></td></tr><tr><th>Pairwise comparisons:</th><th>estimate</th><th>standard error</th><th>df</th><th>z.ratio</th><th>p-value</th></tr><tr><td>CT - AC</td><td>0.79</td><td>0.62</td><td>inf</td><td>1.28</td><td>0.41</td></tr><tr><td>CT - DC</td><td>-1.00</td><td>0.64</td><td>inf</td><td>-1.56</td><td>0.26</td></tr><tr><td>AC - DC</td><td>-1.79</td><td>0.64</td><td>inf</td><td>-2.80</td><td>0.01*</td></tr><tr><td colspan="5"><strong>Gamma models (only the non-null distances):</strong></td></tr><tr><td>Total distance traveled ~ 1</td><td>2</td><td>-239.3</td><td>1.41</td><td>0.49</td><td></td></tr><tr><td>Total distance traveled ~ MF treatment</td><td>4</td><td>-238.6</td><td></td><td></td><td></td></tr></tbody></table>

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# 4. DISCUSSION

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As a major colonizer of the artificial reefs associated with offshore wind farms, the velvet crab (*N. puber*) is likely to undergo chronic exposure to cable induced MFs. This study investigated the effects of an artificial magnetic field gradient (maximum intensity of 304 µT) on its exploratory, foraging, and shelter-seeking behaviors.

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## 4.1 Exploratory behavior

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The first experiment investigated the effects of MFs on the exploratory behavior of crabs, assuming they would be repelled by the highest intensities and would reduce their locomotor behavior. The results show that the mean total distance traveled by *N. puber* individuals was unaffected by the MFs, confirming the results obtained in other crustaceans, such as the American lobster (*Homarus americanus*) (Hutchison et al., 2020) and the European lobster (*Homarus gammarus*) (Taormina et al. 2020). Similarly, the time spent in stationary, walking, and escaping behaviors was not modified by AC and DC MFs, as also reported in *H. gammarus* (Taormina et al., 2020). From test 1 to test 3, the proportions of crabs performing *complete*, *incomplete*, and *no crossings* were not related to the magnetic field exposure. Accordingly, though higher than the ambient field (47 µT), the magnetic field recorded in the initial zone (72 µT) during MF treatment did not cause any behavioral alteration in the crabs tested.

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## 4.2 Foraging behavior

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The second set of experiments explored the effects of MFs on the foraging behavior of *N. puber*. We predicted that exposed crabs would reduce their locomotion along the MF gradient, resulting in a decrease in their food intake. However, the addition of AC and DC magnetic fields did not cause any behavioral changes in individual crabs, and both their average distance traveled and maximal distance reached remained similar compared with values in the control conditions. Likewise, the crabs' activity budget did not vary significantly with the addition of MFs. Although knowledge of how MFs interact with crab foraging and feeding behaviors is very limited, the few available works are consistent with the present findings. For example, AC MFs from both buried and unburied AC cables (13.8–116.8 µT and 24.6–42.8 µT, respectively) did not prevent *Cancer productus* and *Metacarcinus Magister*, from entering a baited trap (Love et al., 2017). Similarly, the freshwater crab *B. cunicularis* did not alter its food consumption rate in response to an AC magnetic field (Rosaria and Martin, 2010).
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## 4.3 Shelter-seeking behavior

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The bulk of the literature has exploited the shelter-seeking behavior of crustaceans to study their attraction or repulsion to MFs. Here we evaluated whether MFs interfere with crabs' sheltering behavior by placing an artificial shelter at the end of the gradient. We expected that MFs would stimulate shelter-seeking behavior, reflected by a rise in locomotor behavior. However, we presumed that MF exposure could interfere with the use of the shelter, resulting in a behavioral trade-off. We found that the addition of magnetic fields did not modify the time crabs spent inside the shelter (Maximum distance reached) nor change their locomotion through the MF gradient (Total distance traveled). The current literature about the potential tropism of crustaceans to MF-exposed shelters also provides heterogeneous findings. On the one hand, several studies have reported attraction responses towards magnet-equipped shelters in the edible crab *Cancer pagurus* (2.8 mT DC, Scott et al., 2018; 500 and 1000 µT DC, Scott et al., 2021), the European lobster *H. gammarus* (2.8 mT; Scott, 2019), and the spiny cheek crayfish *Orconectes limosus* (800 µT DC; Tanski et al., 2005). On the other hand, a repulsive size-dependent behavior was observed in larger individuals of spiny lobster (*Panulirus argus*), which selected control versus magnet-equipped dens (320 µT DC; Ernst and Lohmann, 2018). The sole study of Taormina et al. (2020) corroborates our findings since the exposure of juvenile European lobsters (*H. gammarus*) to AC and DC gradients (51–200 µT) did not induce any temporal shifts in shelter-seeking and sheltering behaviors.

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## 4.4 Success of the attractive stimuli

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In this study, regardless of the treatment, only 25% of the tested crabs fed on the food items provided. Since this proportion was lower than expected and unrelated to the MF treatment, we thus questioned the experimental design. In each corridor, the water inflow used for water renewal was located behind the food items and allowed the circulation of the chemical cues to the crab. Since crustacean species use chemical cues to detect and locate food items at low concentrations (Weissburg and Zimmer-Faust, 1993; Rebach et al., 1996), we immediately excluded the hypothesis that food might be undetectable by the crabs from the initial zone. Furthermore, as crabs were starved before the experiments, rejection of the food seemed unlikely. Accordingly, we assumed that a combination of inter-individual behavioral plasticity and stress related to handling and environmental change were causing these response variations (Guerarhdi et al., 2012).

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A similar percentage (26% of crabs) was observed for the sheltering response, demonstrating a rather moderate attractiveness of the refuge. In a natural environment, holding a shelter is generally crucial for the survival of most crustacean species and takes place in predator defense and
reproductive behaviors (Nelson, 2005). In the laboratory experiments conducted so far, crustaceans usually settled in the refuges provided. For example, *C. pagurus* and *H. gammarus* occupied the refuge 48-66% and 32% of the time, over 7-hour and 45-minute experimental periods, respectively (Scott et al., 2018, Taormina et al., 2020). Similarly, 49 out of 51 individuals of the spiny lobster (*P. argus*) occupied a shelter during a 15-minute trial (Ernst and Lohmann, 2018). In the present work, the low number of sheltering responses may have been a consequence of the species tested, the short experimental duration (30 min), and/or the tank design. However, sheltering is known to be part of the ecology of *N. puber*, which is usually found within crevices and under boulders (Norman, 1989). In addition, Hinchliff et al. (2015) observed a very quick sheltering behavior within a 10-min period in 18 velvet crabs. Moreover, as acclimating crabs were provided with artificial shelters like those used in the trials, they were assumed to be accustomed to them. We cannot exclude that the 140-cm distance to the shelter was too far to allow visual detection by stationary individuals. However, other studies confirmed the absence of attraction to the MF gradients (230 µT) despite shorter crustacean-shelter distances (122.5 cm) (Taormina et al., 2020).

## 4.5 Interaction of environmental cues

The marine environment provides many signals that marine organisms can detect (e.g., chemical, physical, biological, and acoustical cues) (Bullock et al., 2008). Since variations in environmental conditions can alter the availability and reliability of such signals, marine crustaceans tend to orient using multiple cues, such as wave surge, sound, or the geomagnetic field (Herrnking and MacLean, 1971). In the field, crustaceans extract redundant signals and combine and hierarchize the information in them (Ugolini, 2002). Within that context, investigating the interaction between such additional signals and magnetic fields should improve our understanding of the response mechanisms occurring in natural conditions. The present work is a contribution to this approach as the first to demonstrate that MFs gradient do not alter the natural behavioral response to chemical cues from food items.

## 5. CONCLUSION

In conclusion, these results suggest that anthropogenic MFs of comparable intensity to SPC emissions (300 µT) induce neither attraction nor repulsion behavioral responses and do not alter exploratory, feeding, and sheltering behaviors. Nonetheless, as crustaceans' magneto-sensitivity is assumed to be level-dependent, dose response studies should be conducted to assess the effects of cable emissions. In addition, since *in situ* scenarios presume chronic exposure, future studies should
392 also question the temporal component of the MF response mechanism to detect potential habituation

393 or resilience.

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# 6. ACKNOWLEDGEMENTS

We are grateful to the Université de Bretagne Occidentale and the LEMAR and LIA BeBEST laboratories for their scientific support and contribution to this work. We are grateful to the CIFRE grant from the 'Association Nationale de la Recherche et de la Technologie' and the TBM Environnement firm for co-funding the PhD thesis of L. Albert. Many thanks to the Oceanopolis staff and the Lemar diving team for the provision and care of animals as well as technical assistance. Finally, we would like to thank Anne-Hélène Olivier from the Université Rennes II for her valuable advice and training in the use of the tracking software. Finally, we would like to thank the two anonymous reviewers who gave us insightful comments and helped us improve the quality of this work.

# 7. FUNDING

This research was supported by the OASICE project which is a collaboration between the French transmission system operator, Rte, the TBM Environnement firm, and the LEMAR laboratory. A PhD fellowship was provided by the *Association Nationale de la Recherche et de la Technologie*.
410 **8. REFERENCES**

411 Albert, L., Maire, O., Olivier, F., Lambert, C., Romero-Ramirez, A., Jolivet, A., Chauvaud, L., Chauvaud, S., 2022. Can artificial magnetic fields alter the functional role of the blue mussel, *Mytilus edulis*? Mar. Biol. 169, 75 (2022). https://doi.org/10.1007/s00227-022-04065-4

414 Albert, L., Deschamps, F., Jolivet, A., Olivier, F., Chauvaud, L., Chauvaud, S., 2020. A current synthesis on the effects of electric and magnetic fields emitted by submarine power cables on invertebrates. Mar. Environ. Res. 159, 104958. https://doi.org/10.1016/j.marenvres.2020.104958

418 Amorim, C.E.G., Vai, S., Posth, C., Modi, A., Koncz I., Hakenbeck, S., La Rocca, M.C., Mende, B., Bobo, D., Pohl, W., Baricco, L.P., Bedini, E., Francalacci, P., Giostra, C., Vida, T., Winger, D., von Freeden, U., Ghirotto, S., Lari, M., Barbujani, G., Krause, J., Caramelli, D., Geary, P.J. & Veeramah, K.R. 2018. Understanding 6th-century barbarian social organization and migration through paleogenomics. Nat. Commun. 9, 3547. https://doi.org/10.1038/s41467-018-06024-4

424 Bochert, R., Zettler, M.L., 2006. Effect of electromagnetic fields on marine organisms. In Offshore Wind Energy (pp. 223-234). Springer, Berlin, Heidelberg.

426 Boudreau, S. A., Worm, B., 2012. Ecological role of large benthic decapods in marine ecosystems: a review. Mar. Ecol. Prog. Ser., 469, 195-213. https://doi.org/10.3354/meps09862

428 Bullock, T., Atema, J., Fay, R.R., Popper, A.N., Tavolga, W.N., 2008. Sensory processing in aquatic environments. Springer Science & Business Media.

430 Eggleston, D. B., Lipcius, R. N., Grover, J. J., 1997. Predator and shelter-size effects on coral reef fish and spiny lobster prey. Mar. Ecol. Prog. Ser., 149, 43-59. https://doi.org/10.3354/meps149043

433 Ellabban, O., Abu-Rub, H., Blaabjerg, F., 2014. Renewable energy resources: Current status, future prospects and their enabling technology. Renewable and Sustainable Energy Rev. 39, 748-764. https://doi.org/10.1016/j.rser.2014.07.113

436 Elner, R. W., Vadas Sr, R. L., 1990. Inference in ecology: the sea urchin phenomenon in the northwestern Atlantic. Am. Nat., 136(1), 108-125. https://doi.org/10.1086/285084
438 Ernst, D.A., Lohmann, K.J., 2018. Size-dependent avoidance of a strong magnetic anomaly in 439 Caribbean spiny lobsters. J. Exp. Biol. 221 (5), jeb172205. https://doi.org/10.1242/jeb.172205

440 Fischer, C., Slater, M., 2010. Electromagnetic Field Study. Effects of electromagnetic fields on 441 marine species: A literature review. Oregon Wave Energy Trust, Oregon, United States. 442 https://ir.library.oregonstate.edu/concern/technical_reports/sb397891b

443 Freire, J., Gonzalez-Gurriaran, E., 1995. Feeding ecology of the velvet swimming crab *Necora puber* 444 in mussel raft areas of the Ría de Arousa (Galicia, NW Spain). Mar. Ecol. Prog. Ser. 445 Oldendorf. 119 (1), 139-154. https://doi.org/10.3354/MEPS119139

446 Gill, A.B., Bartlett, M., Thomsen, F., 2012. Potential interactions between diadromous fishes of UK 447 conservation importance and the electromagnetic fields and subsea noise from marine 448 renewable energy developments. J. Fish Biol. 81 (2), 664-695. https://doi.org/10.1111/j.1095-449 449 8649.2012.03374.x

450 Gherardi, F., Aquiloni, L., Tricarico, E., 2012. Behavioral plasticity, behavioral syndromes and 451 animal personality in crustacean decapods: An imperfect map is better than no map. Curr. 452 Biol., 58(4), 567-579. https://doi.org/10.1093/czoolo/58.4.567

453 Herrnkind, W.F., McLean, R., 1971. Field studies of homing, mass emigration, and orientation in the 454 spiny lobster, *Panulirus argus*. Annals of the New York Academy of Sciences. 188 (1), 359- 455 376. https://doi.org/10.1111/j.1749-6632.1971.tb13109.x

456 Hinchliff, L., Dick, J., Sigwart, S., Gilmore, L., 2015. The velvet swimming crab (*Necora puber*) 457 fishery in Northern Ireland: a study of populations and welfare to enhance 458 sustainability, Final report SR688. Seafish. 459 https://www.seafish.org/document/?id=3424c022-1f56-4e8e-9df8-b4d922988500

460 Ter Hofstede, R., Driessen, F. M. F., Elzinga, P. J., Van Koningsveld, M., & Schutter, M., 2022. 461 Offshore wind farms contribute to epibenthic biodiversity in the North Sea. J. Sea Res. 462 102229. https://doi.org/10.1016/j.seares.2022.102229

463 Hunter, W.R., Sayer, M.D.J., 2009. The comparative effects of habitat complexity on faunal 464 assemblages of northern temperate artificial and natural reefs. ICES J. Mar. Sci. 66 (4), 691- 465 698. https://doi.org/10.1093/icesjms/fsp058
466 Hutchison, Z.L., Gill, A.B., Sigray, P., He, H., King, J.W., 2020. Anthropogenic electromagnetic
fields (EMF) influence the behaviour of bottom-dwelling marine species. Scientific reports.
467
468 10 (1), 1-15. https://doi.org/10.1038/s41598-020-60793-x

469 IRENA., 2019. Future of Wind: Deployment, investment, technology, grid integration and socio-economic aspects (A Global Energy Transformation paper). Report by International Renewable Energy Agency (IRENA), Abu Dhabi. https://www.irena.org/-/media/files/irena/agency/publication/2019/oct/irena_future_of wind 2019.pdf
470
471
472

473 Kavet, R., Wyman, M.T., Klimley, A.P., 2016. Modeling magnetic fields from a DC power cable
474 buried beneath San Francisco Bay based on empirical measurements. PLoS One. 11 (2),
475 e0148543. https://doi.org/10.1371/journal.pone.0148543

476 Klimley, A.P., Wyman, M.T., Kavet, R., 2016. Assessment of Potential Impact of Electromagnetic
477 Fields from Undersea Cable on Migratory Fish Behavior (No. FINAL REPORT, DOE-EPRI-
478 EE0006382). Electric Power Research Inst.(EPRI), Palo Alto, CA (United States).
479
480 https://doi.org/10.2172/1406896

481 Krone, R., Gutow, L., Joschko, T.J., Schröder, A., 2013. Epifauna dynamics at an offshore
482 foundation-implications of future wind power farming in the North Sea. Mar. Env. Res. 85,
483 1-12. https://doi.org/10.1016/j.marenvres.2012.12.004

483 Langhamer, O., 2009. Wave energy conversion and the marine environment: Colonization patterns
484 and habitat dynamics (Doctoral dissertation, Acta Universitatis Upsaliensis). http://uu.diva-
485 portal.org/smash/record.jsf?pid=diva2%3A228184&dswid=-570

486 Lima, S. L., Dill, L. M., 1990. Behavioral decisions made under the risk of predation: a review and
487 prospectus. Can. J. Zool., 68(4), 619-640. https://doi.org/10.1139/z90-092

488 Lohmann, K., Ernst, D.A., 2014. The geomagnetic sense of crustaceans and its use in orientation and
489 navigation. In: Derby, C., Thiel, M. (Eds.), Nervous Systems and Control of Behavior. Oxford
500 University Press.

491 Love, M., Nishimoto, M., Clark, S., McCrea, M., Scarborough, B., 2017. Assessing potential impacts
492 of energized submarine power cables on crab harvests. Continental Shelf Research. 151 (1),
493 23-29. https://doi.org/10.1016/j.csr.2017.10.002
494 Love, M., Nishimoto, M., Clark, S., Scarborough, B., 2015. Identical response of caged rock crabs (Genera *Metacarcinus* and *Cancer*) to energized and unenergized undersea power cables in Southern California, USA. Bulletin, Southern California Academy of Sciences. 114 (1), 33–41. https://doi.org/10.3160/0038-3872-114.1.33

498 Meißner, K., Schabelon, H., Bellebaum, J., Sordyl, H., 2006. Impacts of submarine cables on the marine environment. A literature review. Report by Institute of Applied Ecology (IfAO). Report for German Federal Agency for Nature Conservation (BfN).

501 Nelson, R.J., 2005. Biology of aggression. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780195168761.001.0001

503 Norman, C.P., 1989. Ecology of the velvet swimming crab *Liocarcinus puber* (L.) (*Brachyura: Portunidae*). http://hdl.handle.net/10026.1/2273

505 Normandeau., Exponent., Tricas, T., Gill, A., 2011. Effects of EMFs from Undersea Power Cables on Elasmobranchs and Other Marine Species. U.S. Dept. of the Interior, Bureau of Ocean Energy Management, Pacific OCS Region, Camarillo, California, United States. OCS Study BOEMRE 2011-09. https://espis.boem.gov/final%20reports/5115.pdf

509 Otremba, Z., Jakubowska, M., Urban-Malinga, B., Andrulewicz, E., 2019. Potential effects of electrical energy transmission—the case study from the Polish Marine Areas (southern Baltic Sea). Oceanol. Hydrobiol. Stud. 48 (2), 196-208. https://doi.org/10.1515/ohs-2019-0018

512 Palma, A. T., Wahle, R. A., Steneck, R. S., 1998. Different early post-settlement strategies between American lobsters Homarus americanus and rock crabs Cancer irrora tus in the Gulf of Maine. Mar. Ecol. Prog. Ser., 162, 215-225. https://doi.org/10.3354/meps162215

515 Quijón, P. A., Snelgrove, P. V., 2005a. Differential regulatory roles of crustacean predators in a sub-arctic, soft-sediment system. Mar. Ecol. Prog. Ser., 285, 137-149. https://doi.org/10.3354/MEPS285137

518 Quijon, P. A., Snelgrove, P. V., 2005b. Predation regulation of sedimentary faunal structure: potential effects of a fishery-induced switch in predators in a Newfoundland sub-Arctic fjord. Oecologia, 144, 125-136. https://doi.org/10.1007/s00442-005-0017-4

521 R Core Team (2022). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/
523 Rebach, S., 1996. Role of prey odor in food recognition by rock crabs, *Cancer irroratus* Say. J. Chem. Ecol. 22 (12), 2197-2207. https://doi.org/10.1007/BF02029540

525 Rinaldi, G., 2020. Offshore Renewable Energy. In Qubeissi MA, El-kharouf A, Soyhan HS (Eds), Renewable Energy - Resources, Challenges and Applications. IntechOpen. https://doi.org/10.5772/intechopen.81765

528 Roberts, L., Laidre, M. E., 2019. Finding a home in the noise: cross-modal impact of anthropogenic vibration on animal search behaviour. Biol. Open, 8(7), bio041988. https://doi.org/10.1242/bio.041988

531 Rosaria, J.C., Martin, E.R., 2010. Behavioral changes in freshwater crab, *Barytelphusa cunicularis* after exposure to low frequency electromagnetic fields. World Journal of Fish and Marine Sciences. 2, 487-494.

534 Rossong, M. A., Quijon, P. A., Williams, P. J., Snelgrove, P. V. R., 2011. Foraging and shelter behavior of juvenile American lobster (Homarus americanus) : the influence of a non-indigenous crab. J. Exp. Mar. Biol. Ecol., 403(1-2), 75-80. https://doi.org/10.1016/j.jembe.2011.04.008

538 Salinas, E., Bottauscio, O., Chiampi, M., Conti, R., Cruz Romero, P. L., Dovan, T., Dular, P., Hoeffelman, J., Lindgren, R., Maiolo, P., Melik, M., Tartaglia, M., 2009. Mitigation techniques of power frequency magnetic fields originated from electric power systems. Report by Conseil international des grands réseaux électriques (CIGRE), Paris.

542 Scott, K., Harsanyi, P., Easton, B.A., Piper, A.J., Rochas, C., Lyndon, A.R., 2021. Exposure to Electromagnetic Fields (EMF) from Submarine Power Cables Can Trigger Strength-Dependent Behavioural and Physiological Responses in Edible Crab, *Cancer pagurus* (L.). J. Mar. Sci. Eng. 9 (7), 776. https://doi.org/10.3390/jmse9070776

546 Scott, K., 2019. Understanding the biology of two commercially important crustaceans in relation to fisheries and anthropogenic impacts (Doctoral dissertation, Heriot-Watt University).

548 Scott, K., Harsanyi, P., Lyndon, A.R., 2018. Understanding the effects of electromagnetic field emissions from Marine Renewable Energy Devices (MREDs) on the commercially important edible crab, *Cancer pagurus* (L.). Mar. Pollut. Bull. 131, 580-588. https://doi.org/10.1016/j.marpolbul.2018.04.062
552 Silliman, B. R., Bertness, M. D., 2002. A trophic cascade regulates salt marsh primary
553 production. Proc. Natl. Acad. Sci. U.S.A., 99(16), 10500-10505.
554 https://doi.org/10.1073/pnas.162366599

555 Soares-Ramos, E.P., de Oliveira-Assis, L., Sarrias-Mena, R., Fernández-Ramírez, L.M., 2020. Current status and future trends of offshore wind power in Europe. Energy. 202, 117787.
556
557 https://doi.org/10.1016/j.energy.2020.117787

558 Stasinopoulos, M.D., Rigby, R.A., Heller, G.Z., Voudouris, V., De Bastiani, F., 2017. Flexible regression and smoothing: using GAMLSS in R. CRC Press. https://doi.org/10.1201/b21973

560 Stevens, B.G., 2003. Settlement, substratum preference, and survival of red king crab *Paralithodes camtschaticus* (Tilesius, 1815) glaucothoe on natural substrata in the laboratory. J. Exp. Mar. Biol. Ecol. 283 (1-2), 63-78. https://doi.org/10.1016/S0022-0981(02)00471-9

563 Taormina, B., Di Poi, C., Agnalt, A. L., Carlier, A., Desroy, N., Escobar-Lux, R. H., D'Eu, J., Freyet, F., Durif, C.M., 2020. Impact of magnetic fields generated by AC/DC submarine power cables on the behavior of juvenile European lobster (*Homarus gammarus*). Aquat. Toxicol. 220, 105401. https://doi.org/10.1016/j.aquatox.2019.105401

567 Taormina, B., Bald, J., Want, A., Thouzeau, G., Lejart, M., Desroy, N., Carlier, A., 2018. A review of potential impacts of submarine power cables on the marine environment: Knowledge gaps, recommendations and future directions. Renewable and Sustainable Energy Rev. 96, 380-391.
568
569
570 https://doi.org/10.1016/j.rser.2018.07.026

571 Tanski, A., Formicki, K., Sadowski, M., Winnicki, A., 2005. Sheltering behaviour of spinycheek
crayfish (*Orconectes limosus*) in the presence of an artificial magnetic field. Bulletin Français
de la Pêche et de la Pisciculture. 376-377, 787-793.
574 https://doi.org/10.1051/kmae:2005033

575 Ugolini, A., 2002. The orientation of equatorial sandhoppers during the zenithal culmination of
576 the sun. Eth. Ecol. Evol. 14 (3), 269-273. https://doi.org/10.1080/08927014.2002.9522745

577 Vannini, M., Cannicci, S., 1995. Homing behaviour and possible cognitive maps in crustacean
decapods. J. Exp. Mar. Biol. Ecol., 193(1-2), 67-91. https://doi.org/10.1016/0022-0981(95)00111-5
580 Wale, M. A., Simpson, S. D., Radford, A. N., 2013. Noise negatively affects foraging and antipredator behaviour in shore crabs. Anim. Behav., 86(1), 111-118.
581
582 https://doi.org/10.1016/j.anbehav.2013.05.001

583 Wei, Q., Xu, B., Zargari, N.R., 2017. Overview of offshore wind farm configurations. IOP Conf. Ser.: Earth Environ. Sci. 93-012009. https://iopscience.iop.org/article/10.1088/1755-1315/93/1/012009
584
585

586 Weissburg, M.J., Zimmer-Faust, R.K., 1993. Life and death in moving fluids: hydrodynamic effects on chemosensory-mediated predation. Ecology. 74 (5), 1428-1443.
587
588 https://doi.org/10.2307/1940072

589 Wilhelm, G., 1995. Contribution à l'étude de l'étrille Necora puber (Crustacea, Brachyura) dans le Mor-Braz (Bretagne Sud): données halieutiques, biologiques et pathologiques (Doctoral dissertation, Paris 6). https://archimer.ifremer.fr/doc/1995/these-1197.pdf
590
591

592 Wiltschko, R., 1995. Magnetic Orientation in Animals, Springer Science & Business Media. Berlin, Heidelberg 297 p.
593

594 Woodruff, D., Cullinan, V., Copping, A., Marshall, K., 2013. Effects of Electromagnetic Fields on Fish and Invertebrates Task 2.1.3: Effects on Aquatic Organisms Fiscal Year 2012 Progress Report (No. PNNL-22154). Pacific Northwest National Laboratory, Richland, Washington (USA).
595
596
597
598 https://www.pnnl.gov/main/publications/external/technical_reports/PNNL-22154.pdf

599 Woodruff, D.L., Schultz, I.R., Marshall, K.E., Ward, J.A., Cullinan, V.I., 2012. Effects of Electromagnetic Fields on Fish and Invertebrates: Task 2.1.3: Effects on Aquatic Organisms-Fiscal Year 2011 Progress Report-Environmental Effects of Marine and Hydrokinetic Energy (No. PNNL-20813 Final). Pacific Northwest National Lab.(PNNL), Richland, WA (United States).
600
601
602
603
604 https://www.pnnl.gov/main/publications/external/technical_reports/PNNL-20813Final.pdf

605 Worzyk, T., 2009. Submarine power cables: design, installation, repair, environmental aspects. Springer, Berlin, Heidelberg 296 p.
606
607
608
FIGURES CAPTIONS

**Figure 1.** Side view of the experimental facilities

**Figure 2.** Examples of *Necora puber* crabs' trajectories within the MF gradient. The magnetic field strength (μT) is minimal (75.8–96.7 μT) within the initial zone (x axis = 0–20 cm) and maximal (304 μT) at the opposite end of the tank (x axis = 140–150 cm). MF intensities are averaged on the 3 corridors measurements. Crabs were confined to the initial zone for 30min before opening the gate. *Complete crossing* corresponds to the crabs that reached the end of the corridor; *no crossing* is for those that remained in the initial zone and *incomplete crossing* for the crabs that moved through the corridor but did not reach the opposite end.

**Figure 3.** Average time fractions (%) spent by the velvet crabs (*Necora puber*) in the different behavioral categories (*Tstation*, *Twalk*, *Tescape*, *Tfeed* and *Tshelter*), according to the MF treatments. Tests 1, 2 and 3 were designed to study potential alterations of the exploratory, feeding, and sheltering behaviors, respectively. Each barplot is a mean obtained from 24 crabs except for the CT and DC treatments of Test 1 and test 3 respectively, where n = 21. Error bars are standard errors. The black bars group the variables that were statistically compared.

**Figure 4.** Average *Total distance traveled* (cm) by the moving crabs (*N. puber*) as a function of the MF treatments. Tests 1, test 2 and test 3 were designed to study potential alterations of the exploratory, feeding, and sheltering behaviors, respectively. Each barplot is a mean obtained from 24 crabs except for the CT and DC treatments of Test 1 and test 3 respectively, where n = 21. Error bars are standard errors. The asterisks "*" indicate statistical differences at the 5 % level.

**Figure 5.** Average *Maximal distance reached* (cm) by the moving crabs (*N. puber*) in the corridor (150 cm in length), as a function of the MF treatments. Tests 1, test 2 and test 3 were designed to study potential alterations of the exploratory, feeding, and sheltering behaviors, respectively. Each barplot is a mean obtained from 24 crabs except for the CT and DC treatments of Test 1 and test 3 respectively, where n = 21. Error bars are standard errors.
<figure><img src="image_3.png" /><figcaption>Figure 1 (should appear in color)</figcaption></figure>
<figure><img src="image_4.png" /><figcaption>Figure 2 (should appear in color)</figcaption></figure>
<figure><img src="image_5.png" /><figcaption>Figure 3</figcaption></figure>
<figure><img src="image_6.png" /><figcaption>Figure 4</figcaption></figure>
<figure><img src="image_7.png" /><figcaption>Figure 5</figcaption></figure>
HIGHLIGHTS

* Submarine power cables emit high-strength magnetic fields in their vicinity

* Their protective rock cover can cause a reef effect and attract crustacean species

* Necora puber crabs were exposed to AC and DC magnetic field gradients (max. 304 μT)

* Exploratory, feeding and sheltering behaviors were studied across three scenarios

* *Necora puber* behavior was not altered by short -term magnetic field exposures
**LA:** conceptualization, methodology, validation, formal analysis, investigation, original draft writing, review and editing, visualization. **FO:** conceptualization, methodology, review and editing, supervision. **AJ:** conceptualization, methodology, review and editing, supervision. **LC:** conceptualization, project administration, supervision, funding acquisition. **SC:** conceptualization, project administration, supervision, funding acquisition.

<figure><img src="image_8.png" /></figure>
**Declaration of interests**

[x] The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

[ ] The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:

<figure><img src="image_9.png" /></figure>