Deep–Sea Research II 181-182 (2020) 104818

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Deep-Sea Research Part IIjournal homepage: http://www.elsevier.com/locate/dsr2

Abundance, horizontal and vertical distribution of epipelagic ctenophores
and scyphomedusae in the northern Bering Sea in summer 2017 and 2018:
Quantification by underwater video imaging analysis
Marie Maekakuchi a, 1, Kohei Matsuno a, b, Jun Yamamoto c, Yoshiyuki Abe d,Atsushi Yamaguchi a, b, *a

Faculty/Graduate School of Fisheries Sciences, Hokkaido University, 3-1-1 Minato-cho, Hakodate, Hokkaido, 041-8611, Japan
Arctic Research Centre, Hokkaido University, Kita-21 Nishi-11 Kita-ku, Sapporo, Hokkaido, 001-0021, Japanc
Field Science Centre for Northern Biosphere, Hokkaido University, 3-1-1 Minato-cho, Hakodate, Hokkaido, 041-8611, Japand
Research Development Section, Office for Enhancing Institutional Capacity, Hokkaido University, Kita-21, Nishi-10, Kita-ku, Sapporo, Hokkaido, 001-0021, Japanb

A R T I C L E I N F O

A B S T R A C T

Keywords:
Ctenophores
Scyphomedusae
Northern Bering Sea
Vertical distribution
Horizontal distribution
Imaging analysis

We examined the abundance and horizontal and vertical distributions of epipelagic ctenophores and scypho­
medusae in the northern Bering Sea using an underwater video camera during July of 2017 and 2018. The effects
of environmental and biological parameters on the distribution of these species were evaluated by generalized
additive modelling (GAM). In 2017, the dominant ctenophore, Bolinopsis infundibulum, was mainly distributed in
the north and west of St. Lawrence Island (SLI), and their vertical distribution varied with the region but not by
the time of day. We found that B. infundibulum was distributed in the upper pycnocline north of SLI, but below
the pycnocline west of SLI. Biological interactions with other gelatinous zooplankton may explain these regional
differences in vertical distribution; GAM analysis revealed a negative interaction between B. infundibulum and thelarge scyphomedusa, Chrysaora melanaster, which occurred in the upper layer in the west of SLI. B. infundibulum
may avoid that layer to reduce feeding competition. For the ctenophore, Beroe sp., vertical and horizontal dis­tributions were similar to those of B. infundibulum, and GAM analysis also revealed a positive interaction for both
species. As B. infundibulum is an important prey of Beroe sp., a prey-predator interaction may result from theirsimilar horizontal and vertical distributions. Standing stocks of epipelagic ctenophores and scyphomedusae in2018 were low compared to those in 2017, by a factor of 1/20 (C. melanaster) and1/90 (Beroe sp.). This might bedue to annual differences in water mass in this region, in that the thermal conditions characterized by a highabundance of the dominant B. infundibulum in 2017 (<2 and >8 � C) were absent in 2018. As this drastic decreasein standing stock in 2018 was apparent for both ctenophores and scyphomedusae, food availability was hy­
pothesized to be poor that year.

1. Introduction
Recently, increases in the abundance of large ctenophores and scy­phomedusae have been reported in various oceans worldwide, likely due
to human alternation of marine environments and climate change(Purcell et al., 2007; Condon et al., 2013; Duarte et al., 2013). The mainfood sources of ctenophores and scyphomedusae in higher latitudes are
mesozooplankton, especially copepods (Brodeur et al., 2002; Purcell
et al., 2010). Ctenophores and scyphomedusae are thus competitors of
the planktivorous fishes, and also act as predators upon larval fishes;

thus, the abundance of large gelatinous zooplankton can have a great
effect on fish stocks (Brodeur et al., 2002; Purcell et al., 2007; Robinson
et al., 2014). As large gelatinous zooplankton are composed mainly ofwater and require less organic material for their body composition, they
can respond to environmental changes more rapidly than crustacean
zooplankton, and their biomass can vary dramatically between years(Falkenhaug, 1996; Brodeur et al., 2008).
The northern Bering Sea, the target area of the present study, is atransit region for the warmer waters of southern origin (Alaskan Coastal
Water, Bering Shelf Water, Anadyr Water), which intrude into the* Corresponding author. Faculty of Fisheries Sciences, Hokkaido University, 3-1-1 Minato-cho, Hakodate, Hokkaido, 041-8611, Japan.
E-mail address: a-yama@fish.hokudai.ac.jp (A. Yamaguchi).
1
Present address; APA Hotel and Resorts Co. Ltd., Akasaka 3-2-3, Minato, Tokyo, 107-0052, Japan.
https://doi.org/10.1016/j.dsr2.2020.104818
Received 4 January 2020; Received in revised form 18 June 2020; Accepted 21 June 2020
Available online 7 July 20200967-0645/© 2020 Elsevier Ltd. All rights reserved.

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western Arctic Ocean (Shimada et al., 2006; Sasaki et al., 2016; Dan­ielson et al., 2017). A polynya forms south of St. Lawrence Island (SLI),
the largest island in this region, and is characterized as being ice-free,even in winter (Grebmeier and Cooper, 1995). Recently, a drastic
decrease in the ice-covered area and an early ice retreat in the northern
Bering Sea has been reported (Comiso et al., 2008; Parkinson andComiso, 2013; Stabeno and Bell, 2019). Additionally, changes inzooplankton biomass, a northern shift of the fish community, and a massmortality of seabirds occurred during the winter of 2017/2018 andspring/summer of 2018 (Cornwall, 2019; Duffy-Anderson et al., 2019;
Huntington et al., 2020). Under conditions of greater variability in theenvironment and marine ecosystem, the amount and distribution of
ctenophores and scyphomedusae were also expected to change. How­ever, ecological information on these species is presently scarce for thisregion.
The methods used to quantify ctenophores and scyphomedusae haveseveral limitations (Graham et al., 2003; Uye et al., 2017). Traditional
sampling using a plankton net tow is hampered by patchy
spatio-temporal distributions, relatively large body size, low abundance,and net avoidance, leading to inevitable underestimation of theirbiomass and species diversity (Youngbluth and Båmstedt, 2001; Graham
et al., 2003; Raskoff et al., 2005; Uye et al., 2017). The fragile bodies ofctenophores and scyphomedusae are also heavily damaged by net tow­
ing (Graham et al., 2003; Raskoff et al., 2005: Uye et al., 2017).
Large-volume trawl nets have been used; however, using these nets re­quires large effort and cost compared to plankton sampling. Moreover,changes in the mouth area and collection efficiency varies with meshsize and towing speed. These nets cause serious damage to the fragile
bodies of gelatinous zooplankton, making quantitative collection diffi­
cult for ctenophores and scyphomedusae (Graham et al., 2003; Uyeet al., 2017). To overcome these problems in the quantification of
ctenophores and scyphomedusae, alternative non-capture methods suchas sonar cameras (Han and Uye, 2009), video cameras using a Remotely
Operated Vehicle (Båmstedt and Martinussen, 2015), and visual moni­
toring using ships and airplanes (Purcell et al., 2000) have been used.
In the Bering Sea, Brodeur et al. (2017) reported horizontal distri­butions, and seasonal and annual changes in ctenophores and scypho­
medusae based on data collected by trawl nets, although there was thepaucity of data for the northern Bering Sea. The vertical distributions ofctenophores and scyphomedusae in the southeastern Bering Sea havebeen observed using a video camera mounted on an ROV (Brodeur,
1998; Brodeur et al., 2002). Annual variations in the biomass of the large
scyphomedusa, Chrysaora melanaster, over the southeastern Bering Sea
shelf has previously been analysed using Generalized Additive Models(GAM) to explore which environmental variables might explain thevariability (Brodeur et al., 2008). Although the northern Bering Sea ischaracterized by large interannual changes in the ice-covered area andtiming of the ice retreat, few studies have investigated interannualchanges in ctenophores and scyphomedusae in this region.
In the present study, we quantified the horizontal and vertical dis­tributions, and annual changes in the abundances of ctenophores andscyphomedusae using an underwater video camera in the northern
Bering Sea during the summers of 2017 and 2018. Interactions among
vertical, horizontal, and annual changes in the abundance of cteno­phores and scyphomedusae were assessed with environmental param­
eters (depth, temperature, salinity, diel period, year, and location
relative to the pycnocline) and biological parameters (mesozooplankton
biomass, other species of ctenophores and scyphomedusae) by GAM
analysis.

located between 63� 000 –66� 440 N and 166� 300 –174� 500 W in the north­ern Bering Sea. These sampling stations were occupied by the T/SOshoro-Maru during 9–22 July 2017 and 2–12 July 2018 (Fig. 1). Im­
aging data down to 50 m were collected by dead-slow (0.1 m s-1) vertical
deployment of an underwater video camera (Marine Arkas, Kowa Co.
Ltd.) mounted within a stainless frame of 1.0 � 1.0 m bottom and 1.5 m
depth (Fig. 2B). A charge-coupled device (CCD) camera (NTSC PA-290)
was equipped with a f2.9 lens that had 0.035 lux light sensitivity. The
final resolution of each digital frame was 768 (horizontal) by 494(vertical) pixels. The in situ images were monitored from the ship. To
evaluate diel changes in vertical distribution, observations were made at
1 h intervals at one station (St. 10) during 19:40–7:10, 13–14 July 2017
(total number of samples ¼ 11) (Appendix A). Observations were madeboth day and night at three additional stations (St. 14, 20, and 23) in2017. At each station, temperature and salinity were measured using a
Conductivity Temperature Depth (CTD) sensor (SBE911, Sea-Bird Elec­tronics, Inc.). To evaluate mesozooplankton biomass, a verticallystratified tow of a 60 cm opening-closing net (mesh size: 100 μm)(Kawamura, 1989) was conducted from the sea-surface to the thermo­cline, and from the thermocline to near-bottom. Mesozooplankton
samples were preserved in 5% (v/v) borax-buffered formalin seawater.
The underwater camera (Marine Arkas, Kowa Co. Ltd.) was equippedwith two halogen lights (JCD100V-150 W) with 150 W and 3300 lumen
luminous flux and a pressure-depth sensor (model P193-010-45, SEN­
SIT., Co. Ltd., Hampshire, UK) with a precision of �0.25%FS. A pictureof the frame camera is presented in Fig. 2B. Using the bottom observa­
tion frame as a guide, the camera was able to image an observational
area of 1.2 � 0.8 m (Fig. 2B and C). On the side of the frame, a current fin(0.8 � 0.3 m) was attached so that the horizontal current was flowing in
one direction along the diagonal of the bottom observation frame.
Sinkers (20 kg each) were set at the four corners of the frame. We
measured the wire angle, and, because of the heavy weight of thecamera and frame, the angles were less than 5� at each cast. Underwater
videos were transferred on-board through a tether cable and recorded
using an HDD and DVD recorder (Toshiba RD-X4). The recording
method was MPEG2. The depth data were displayed on a captured image
and were recorded using video imaging data. For examples of the video
images, see video supplemental materials captured for Cast 14 at St. 10
on 14 July 2014 (Video 1) and for Cast 27 at St. 19 on 19 July 2017.
Supplementary video related to this article can be found at htt
ps://doi.org/10.1016/j.dsr2.2020.104818
2.2. Quantification of ctenophores and scyphomedusae
In the laboratory on land, all ctenophores and scyphomedusae within
the observation frame (0.8 m � 1.2 m) were identified and counted in 2
m vertical intervals from the recorded video. As the frame camera was
towed at a speed of 0.1 m s-1, video images obtained at 2 m depth in­tervals corresponded to 20 s (¼ 2.0/0.1). Depth data were expressedwith 0.1 m accuracy, and the error for estimated depths obtained by thesonar- equipped ship was less than 0.5 m. To evaluate the flow rates ofhorizontal currents, the diagonal passage time (Pt, s) of ctenophores,
scyphomedusae and marine snow within the observation field wasmeasured at 10 m intervals. The Pt was not varied with the targets. For
real images of the video, see video supplemental materials. Note that wemeasured current speed every 10 m constantly and applied these current
data for jellyfishes quantified with 2 m interval.
To calculate individual density, observation volume over 2 m in­tervals (V, m3) was calculated from the following equation (Fig. 2C):

2. Material and methods

V ¼ 2 � 1.2 � 0.8 � 20 � 1/Pt,

2.1. Field observation

where, 2 � 1.2 � 0.8 is the volume of the observation field (height �width � depth, m3). Thus, 1/Pt represents the changes in viewing within
1 s. As a 2 m vertical movement of the video camera required 20 s, “20 �
1/Pt” represents the change in view caused by horizontal advection

Imaging data for ctenophores and scyphomedusae were collected byvertical casts of a frame camera at 21 (2017) and 14 (2018) stations2

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Fig. 1. Location of the stations used to observe ctenophores and scyphomedusae by frame camera in the northern Bering Sea in 9–22 July 2017 (left) and 2–12 July
2018 (right). Numbers in italics denote the depth strata in meters.

Fig. 2. Captured images (A): Bolinopsis infundibulum (a), Chrysaora melanaster (b), Beroe sp. (c). Frame camera (B): video camera (a), current fin (b), weight (20 kg x4) (c), observation frame (d), halogen light (x 2) (e), electronic data cable (f). Schema shows the calculation of the observed volume (C). For details, see the text.

within a 2 m observation distance. Swimming speeds of ctenophores andscyphomedusae may also affect their quantification. The swimming
speed (V: cm s-1) of ctenophores is known to be a function of diameter(Dia: cm): V ¼ 0.12 þ 0.04 Dia (Cowan and Houde, 1992). If we assume
15–20 cm diameter, the swimming speed of the ctenophore would havebeen 0.72–0.92 cm s-1. From Pt, the horizontal current speed was
calculated to be ca. 0.5–2.0 m s-1. Thus, since horizontal current speed
was generally faster than the swimming speed of ctenophores and scy­phomedusae, the effect of their swimming speeds on the quantificationof their numbers was ignored.
Ctenophores and scyphomedusae were quantified for both thedescent (D) and ascent( A) of the tows, and the data from both directions
corresponded well (D ¼ 0.857 � A, r2 ¼ 0.742, ρ < 0.0001, n ¼ 561)
(Appendix B). Thus, we calculated the mean descent and ascent abun­dance for each depth. The settling volume for mesozooplankton samples
collected by the closing net was measured with 0.1 mL accuracy andexpressed as their biovolume biomass (mL m-3).

2.3. Statistical analysis
To examine diel changes in vertical distribution, the abundances at
depths of 10, 25, 50, 75, and 90% (D10%, D25%, D50%, D75%, and D90%,
respectively, Pennak, 1943) were calculated for all stations at which
day-night observations were made (St. 10, 14, 20, 23, in 2017). To
evaluate diel vertical migration, D50% was compared between the day (n¼ 7) and night (n ¼ 4) using a Mann Whitney U-test at St. 10. For theremaining stations (St. 14, 20, 23) where day and night sampling was
conducted, the Kolmogorov-Smirnov test was used to evaluate dielchanges in vertical distribution (Sokal and Rohlf, 1995).
The effects of environmental and biological parameters on the dis­tribution of ctenophores and scyphomedusae were analysed by GAM.
The densities of ctenophores and scyphomedusae were applied as
response variables, and environmental and biological parameters, suchas hydrography (temperature, salinity), depth, day-night, year, upper/
lower pycnocline, mesozooplankton biomass, and the densities of otherctenophores and scyphomedusae were applied as explanatory variables.
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The pycnocline was defined as the depth at which the seawater density
was higher than that at the 5 m depth by 0.1 kg m-3 (Danielson et al.,2011). For the GAM analysis, R software with “mgcv” package was used
(Wood, 2017).

observed: the ctenophores, Bolinopsis infundibulum and Beroe sp., and thescyphomedusae, Chrysaora melanaster (Fig. 2A). Among these,
B. infundibulum was the most numerous species in both 2017 and 2018.
In 2017, the standing stock of B. infundibulum was 0–35.6 ind. m-2 andwas the greatest north and west of SLI. The maximum abundance of
C. melanaster and Beroe sp. occurred at 0.689 and 0.567 ind. m-2,
respectively, and they were abundant west and south of SLI, and north of
SLI to the Bering Strait, respectively. In 2018, standing stocks of all
species were much lower than those in 2017, and their mean abundancein 2018 was 1/90 (C. melanaster)–1/20 (Beroe sp.) of those in 2017
(Fig. 5).

3. Results
3.1. Hydrography
Cross-sectional distributions of temperature and salinity along eachline transect in the northern Bering Sea during 2017 and 2018 are shownin Figs. 3 and 4, respectively. In 2017, water temperatures ranged from-1.26 to 11.6 � C and salinities from 30.2 to 32.9 psμ, respectively(Fig. 3). In most locations, the upper layer was characterized by warm
temperatures and low salinity. No pycnocline developed north of 66� N,
near the Bering Strait, whereas a pycnocline was observed around 6–32
m in the western and southern regions of SLI, with substantial differ­ences in temperature between the upper and lower layers. Conversely, in
2018, temperature and salinity ranged from -0.21 to 12.8 � C and from
28.3 to 32.9 psμ, respectively (Fig. 4). Pycnocline development wasmuch weaker in 2018 than in 2017. The differences in temperature
between the upper and lower layers of the pycnocline were smaller in2018 compared with 2017.

3.3. Diel changes in the vertical distribution of Bolinopsis infundibulum
Diel changes in the vertical distribution of B. infundibulum were
examined at four stations in 2017 (Fig. 6). At St. 10, where multiple
observations were made, day and night D50% (mean � 1 sd) was 6.97 �
4.62 and 1.92 � 0.32 m, respectively. Although the night D50% was 5 m
shallower than the day D50%, this difference was not significant (p >0.05, U-test), suggesting that there was no diel vertical migration(DVM). For the three stations with only one day-night observation (St.
14, 20, 23), diel differences were detected at St. 14 and 20 (St. 14: p <0.005, St. 20: p < 0.001, Kolmogorov-Smirnov test); however, the dielpattern varied with the station. A nocturnal ascent occurred at St. 14,
while a nocturnal descent occurred at St. 20. The diel changes in D50%
were 5.3 m (St. 14) and 5.5 m (St. 20). No significant change was
detected between the day and night vertical distributions at St. 23 (p >0.05), likely due to the extremely low abundance at that station (Ap­pendix D). For details of each observation, see Appendix C (St. 10) and3.2. Horizontal distribution of ctenophores and scyphomedusae
Horizontal distributions of ctenophore and scyphomedusa standing
stocks (ind. m-2) at each sampling station in 2017 and 2018 are shown in
Fig. 5. Three taxa of large gelatinous zooplankton were commonly

Fig. 3. Temperature (upper) and salinity (lower) cross-sections at each line set in the northern Bering Sea during 9–22 July 2017. The location of each line is shownin the upper-right map.
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Fig. 4. Temperature (upper) and salinity (lower) cross-sections at each line set in the northern Bering Sea during 2–12 July 2018. The location of each line is shownin the upper-right map.

Appendix D (Sts. 14, 20, 23).

high abundances at >8 and < 2 � C, and low abundance at intermediate
temperatures (2–8 � C). Conversely, the thermal range available in 2018was mostly limited to 2–8 � C and B. infundibulum showed very low
densities within these temperature ranges.

3.4. Vertical distributions of ctenophores and scyphomedusae
In 2017, the vertical distribution of B. infundibulum showed a clear
regional pattern (Fig. 7). This species was distributed throughout thewater column north of the Bering Strait (St. 1, 5), but was distributed
around or below the pycnocline south of the Bering Strait (St. 7, 9).
B. infundibulum was primarily distributed at shallower depths than thepycnocline north of SLI (St. 12, 13), while a bimodal distribution withpeaks in the upper and lower layers of the water column was observed
northwest of SLI (St. 16, 18). West of SLI (St. 19, 20, 24), this species was
distributed below the pycnocline.
In 2017, C. melanaster was distributed in a layer shallower than thepycnocline (Fig. 8). In the region west and south of SLI, C. melanaster was
distributed at shallower depths than the pycnocline with a maximum
density at 0.161 ind. m-3 (St. 22, 6–8 m) for these regions.
Beroe sp. were distributed at depths shallower than the pycnocline
south of the Bering Strait (St. 6, 9), and both above and below thepycnocline north of SLI (St. 13, 14) (Fig. 9). Conversely, they were
distributed entirely below the pycnocline west and south of SLI (St. 18,
20, 22, 24).

3.6. GAM environmental relationships
In 2018, depth, temperature, salinity, and zooplankton all had sig­
nificant effects on B. infundibulum, which were abundant at night andbelow the pycnocline; these factors were negatively related to
C. melanaster abundance, and positively related to Beroe sp. (Table 1).
There was a significant positive relationship between C. melanasterabundance and temperature, salinity, and zooplankton biomass, and anegative relationship with B. infundibulum abundance. There was asignificant relationship between Beroe sp. abundance and depth, tem­
perature, salinity, and zooplankton biomass, and a positive interaction
with B. infundibulum abundance. Smoothing spline regressions between
ctenophore and scyphomedusae abundance and environmental param­
eters with a significant relationship are shown in Fig. 11. The abundanceof B. infundibulum was high at depths <24 m, temperatures of -1–2,
5.5–7.5, and 9–10 � C, salinities of >30.7, 31.8–32.1, and >32.3 psμ, andzooplankton biomasses of 0.1–0.6, 1.4–3.0, and 3.4–4.1 mL m-3. The
abundance of C. melanaster was high at temperatures >5.5 � C, salinities
between 31.0 and 32.4 psμ, and zooplankton biomasses of <1.7, and
3.0–4.4 mL m-3. The abundance of Beroe sp. was high at depths <14 m,
temperatures <6.9 � C, salinities of <30.4, 30.8–31.3, and 31.7–32.8 psμ,and zooplankton biomasses between 0.2–2.1 mL m-3.

3.5. Interannual changes in ctenophores and scyphomedusae densities
Based on data from all sampling stations, the densities of the mostdominant ctenophore (B. infundibulum) in 2017 and 2018 are shownwith the hydrography in Fig. 10. Annual changes were observed be­
tween 2017 and 2018, where 2017 showed a bimodal distribution, with5

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Fig. 5. Horizontal distribution of standing stock (ind. m-2) of Bolinopsis infundibulum (left), Chrysaora melanaster (middle), and Beroe sp. (right) in the northern Bering
Sea during 9–22 July 2017 (upper) and 2–12 July 2018 (lower).

4. Discussion
4.1. Quantification of ctenophores and scyphomedusae
In the present study, we used an underwater video camera to collectquantitative data on ctenophores and scyphomedusae during day andnight, even under dark conditions in the deepest layers using artificial
light (3300-lumen luminous flux). Use of an underwater video camera toquantify ctenophores and scyphomedusae has been somewhat limited inpast studies by reduced visibility and difficulty quantifying their abun­dance in high turbidity waters (Honda and Watanabe, 2007; Honda
et al., 2016), but we did not encounter high turbidity water in our study
region in either year as judged by by using the square frame at thebottom of the frame as a guide.
Several metrics have been presented to quantify data on ctenophores
and scyphomedusae obtained with an underwater video camera. These
include individual number over each observation time within a certain
depth range (ind. min-1 or ind. hour-1) (Toyokawa et al., 2003; Raskoff
et al., 2005, 2010; Honda and Watanabe, 2007), the individual number
observed at each depth (number observed) (Purcell et al., 2010; Båm­stedt and Martinussen, 2015), and species composition within the total
observed number throughout the water column (%) (Brodeur, 1998). In
the present study, we calculated the observed volume by multiplying theobservation area (1.2 � 0.8 m) by depth (2 m) and considered thechange in view caused by horizontal advection within a 2 m observation(Fig. 2C). A similar calculation method has been used in previous
studies. Youngbluth and Båmstedt (2001) calculated volume by multi­
plying the observation area by vertical depth. To account for horizontal
advection, the current flow of the water mass was applied (Nogata et al.,2009), and by measuring the horizontal current using a shipboard
acoustic Doppler current profiler (ADCP), Honda et al. (2016) were able
to calculate volumes considering horizontal advection. On our cruises,

Fig. 6. Diel changes in the vertical distribution of Bolinopsis infundibulum atfour stations (St. 10, 14, 20, 23) in the northern Bering Sea during 9–22 July
2017. Thick bars represent the distribution core (D25%–D75%) split with the
distribution centre (D50%). Thin bars show the ranges of D10% and D90%. Hori­zontal black bars at the top indicate night-time samplings. Shaded zones
represent the sea bottom. Triangles represent pycnocline depths. Details of eachobservation are presented in Appendix C (St. 10) and Appendix D (Sts. 14,
20, 23).

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Fig. 7. Vertical distribution of temperature, salinity, and Bolinopsis infundibulum in the northern Bering Sea during 9–22 July 2017. Triangles represent pycno­
cline depths.

horizontal current was also measured by the shipboard ADCP. However,vertical changes in the horizontal current speed were also observed in
the present study. Thus, we measured horizontal current speed at depth
using the time taken for a particle (e.g. marine snow) to pass through theobservation frame at 10 m depth intervals. As we set the current fin for
the frame, the horizontal current was flowing diagonally; thus, it waspossible to quantify the horizontal current measurements in this study.
Båmstedt and Martinussen (2015) reported a maximum density of
B. infundibulum of 2–5 ind. m-3 at 0–50 m depths in a western Norwegian
fjord. This value corresponds well with the maximum density (3.58 ind.
m-3) observed in our study. For C. melanaster, a maximum density of 0.07
ind. m-3 has been reported for the southeastern Bering Sea shelf (Bro­deur, 1998), whereas in the present study, we observed 0.16 ind. m-3.
Thus, our use of underwater video to quantify individual density,
considering horizontal advection, seems appropriate and comparable to
the results of previous studies.

lacking organs that can detect light (Graham et al., 2001). However, it
was recently reported that ctenophores may possess an organ capable ofdetecting light (Haraldsson et al., 2014).
The DVM pattern observed for B. infundibulum varied with the sta­tion, and the magnitude (5.3–5.5 m) was close to the sampling intervalof this study (2 m), and relatively small compared to the entire obser­
vational depth (50 m). Therefore, we conclude that B. infundibulum did
not perform extensive DVM in our study region. The DVM of Beroe spp.
has been reported for the northeast Atlantic and the south Brazilian
Bight (Roe et al., 1984; Júnior et al., 2015), but in the present study,
because of the low abundance, DVM could not be evaluated for Beroe sp.
Several studies have reported the DVM of scyphomedusae (Youngbluthand Båmstedt, 2001; Graham et al., 2001; Gorbatenko et al., 2009;
Brodeur et al., 2017). For C. melanaster, no DVM had been reported in
the southwestern Bering Sea shelf region (Brodeur et al., 2017), and in
the present study, C. melanaster was distributed above the pycnocline
during both day and night.

4.2. Diel vertical migration of ctenophores and scyphomedusae

4.3. Horizontal and vertical distribution of ctenophores andscyphomedusae

For B. infundibulum, no diel changes in vertical distribution wereobserved at two stations (St. 10, 23), nocturnal ascent was observed at
one station (St. 14), and nocturnal descent was found at one station (St.
20). However, where changes were observed, the diel differences were
small (5.3–5.5 m). Little information is available regarding the DVM ofctenophores (Vereshchaka, 2002; Haraldsson et al., 2014; Júnior et al.,2015). The absence of DVM in ctenophores has been attributed to their

4.3.1. Bolinopsis infundibulum
The vertical distribution of B. infundibulum varied with the region
and was distributed above the pycnocline north of SLI, and below thepycnocline west of SLI. The region west of SLI was characterized by anextremely cold water mass (<0 � C) below the pycnocline (Fig. 3), and7

M. Maekakuchi et al.

Deep-Sea Research Part II 181-182 (2020) 104818

Fig. 8. Vertical distribution of temperature, salinity and Chrysaora melanaster in the northern Bering Sea during 9–22 July 2017. Triangles represent pycno­
cline depths.

the occurrence of C. melanaster above the pycnocline (Fig. 8). Therefore,
the deep distribution of B. infundibulum in the west of SLI could havebeen caused by both physical oceanographic factors and biologicalinteraction factors. We were unable assess the relative contributions ofthese variables.
A polynya was present in 2017 (Grebmeier, J.M. pers. comm.), andthe loss of saline and dense brine water during the formation of ice may
have forced B. infundibulum to be distributed below the pycnocline.
Several ctenophores, Mnemiopsis leidyi, Pleurobrachia spp., and Beroespp., do not appear to cross a strong pycnocline, and instead distribute
either above or below the pycnocline (Roe et al., 1984; Vereshchaka,
2002; Haraldsson et al., 2014). When a strong pycnocline developed
west of SLI, B. infundibulum was restricted to below the pycnocline anddid not appear to migrate upward across the pycnocline. B. infundibulum
can live under cold (<0 � C) conditions (Raskoff et al., 2005), and may beable to survive under the cold conditions that occur below the pycno­
cline in this region.
Due to predator-prey interactions, the occurrence of large scypho­
medusae C. melanaster above the pycnocline west of SLI may havecaused B. infundibulum to avoid that layer. GAM analysis revealed anegative interaction between these two species. C. melanaster feeds ongelatinous zooplankton (Purcell, 1991), and a prey-predator interaction
between C. melanaster and Bolinopsis spp. has been noted off Japan(Kinoshita et al., 2006); thus, the distribution of B. infundibulum that we
observed may have been a behavioural avoidance of predation by
C. melanaster. Indeed, in the Nordic fjord, B. infundibulum has beenshown to remain below the pycnocline to avoid predation from a large
predatory scyphomedusae, Cyanea capillata (Båmstedt and Martinussen,2015). However, in the Canada Basin, in the western Arctic Ocean, thecoexistence of C. melanaster and B. infundibulum within the same depth
layer has been reported (Raskoff et al., 2005; Purcell et al., 2010).
Although we identified two possible factors that may explain hori­zontal changes in the vertical distribution of B. infundibulum, physicaloceanographic factors and biological interaction factors, we cannot
conclude which factor is most important in determining the regionalchanges in vertical distribution. B. infundibulum has been reported tooccur at depths up to 1250 m in the Oyashio Current in the western
subarctic Pacific Ocean (Toyokawa et al., 2003) and Canada Basin, in
the western Arctic Ocean (Raskoff et al., 2005; Purcell et al., 2010).
These findings suggest that B. infundibulum exhibits much flexibility interms of their vertical distribution and ability to adapt to various envi­
ronments and regions.
4.3.2. Chrysaora melanaster and Beroe sp.
We found that C. melanaster was distributed above the pycnocline at
most stations, and the GAM analysis revealed a significant positive
interaction between C. melanaster abundance and temperature (p <0.01, Table 1, Fig. 11). Previous studies have reported that C. melanasteris distributed above the pycnocline (Brodeur, 1998; Brodeur et al., 2002,
2017; Raskoff et al., 2005; Gorbatenko et al., 2009; Radchenko, 2013).
Raskoff et al. (2005) reported that the above pycnocline distribution of
C. melanaster may be explained by their feeding on copepods andgelatinous zooplankton, which are more abundant above the pycno­
cline. Radchenko (2013) noted that the standing stock of zooplankton ismore important than the thermal condition above the pycnocline in
explaining the vertical distribution of this species. Previous studies haveshown that C. melanaster feed on crustaceans, gelatinous zooplankton,
larvae of walleye pollock, ostracods, and decapod larvae in the Bering
8M. Maekakuchi et al.

Deep-Sea Research Part II 181-182 (2020) 104818

Fig. 9. Vertical distribution of temperature, salinity and Beroe sp. in the northern Bering Sea during 9–22 July 2017. Triangles represent pycnocline depths.

Sea (Brodeur et al., 2002; Zavolokin et al., 2008; Ruzicka et al., 2020).
Video images from the present study showed that hydromedusae
Aglantha digitale was abundant above the pycnocline (Maekakuchi un­
published data). Since A. digitale is also an important food item for
C. melanaster (Radchenko, 2013), we suggest that the observed distri­bution of C. melanaster may be related to the abundance of their fooditems, such as copepods and gelatinous zooplankton, above thepycnocline.
Standing stocks of C. melanaster were highest in the southern region
in this study (south of SLI). C. melanaster is very abundant in thesoutheastern Bering Sea shelf where it can exert a substantial effect onother pelagic animals and marine food web structure in that region(Brodeur et al., 2002, 2008), and C. melanaster has been reported inlower abundances farther north, in the Canada Basin of the western
Arctic Ocean (Raskoff et al., 2005; Purcell et al., 2010). These obser­
vations suggest that the high standing stocks of C. melanaster in thesouthern region of this study may reflect the regional differences instanding stocks.
The GAM analysis revealed a positive relationship between Beroe sp.
and the abundance of B. infundibulum. Beroe sp. were mainly distributed
above the pycnocline, but they were distributed below the pycnocline in
the west of SLI, which parallels the regional pattern of vertical distri­bution for B. infundibulum (Fig. 9). We suggest that predator-prey re­lationships may be the cause of this parallel regional vertical
distribution pattern of Beroe sp. with those of B. infundibulum. Beroe spp.
has been shown to feed on B. infundibulum (Greve, 1970; Purcell, 1991),
and the vertical distribution of Beroe cucumis has been documented to be
similar to that of their prey (Falkenhaug, 1996; Bandara et al., 2016).

Fig. 10. T-S diagrams of all stations in 2017 (left) and 2018 (right) (A).
Abundance (ind. m-3) of Bolinopsis infundibulum at 2 m intervals is shown by
bubble plots on T-S diagrams (B).
9

M. Maekakuchi et al.

Deep-Sea Research Part II 181-182 (2020) 104818

Table 1Results of generalized additive models (GAM) based on the abundance of ctenophores and scyphomedusae (Bolinopsis infundibulum, Chrysaora melanaster, Beroe sp.),and environmental parameters: depth, temperature, salinity, the effect of pycnocline (U: upper), day/night, and species interactions of other jellyfishes. þ: positive, -:negative, *: p < 0.05, **: p < 0.01, ***: p < 0.001. Detailed patterns between each parameter are presented in Fig. 1.
Bolinopsis infundibulum
Chrysaora melanaster
Beroe sp.

Year

Depth

Temperature

Salinity

Day/Night

Pycnocline

Zooplankton biomass

B. infundibulum— (2018)

***

***
**
*

***
**
***

þþþ (N)þþ (U)

***
**
*

–
þþ

***

C. melanaster

Beroe sp.

–þþþFig. 11. Result of the generalized additive model (GAM) based on abundance anomalies of three large gelatinous zooplankton with environmental parameters.

However, as noted for B. infundibulum, Beroe sp. may be restricted intheir distribution to below the pycnocline due to highly saline water, so
there could also be a physical oceanographic mechanism affecting theirdistribution.

copepods such as Pseudocalanus and Acartia dominate the zooplankton
biomass (Hunt et al., 2011), which may result in poor food conditions forC. melanaster (Brodeur et al., 2008). Conversely, in cold years, thephytoplankton bloom initiates earlier, and large copepods, such as
Calanus, dominate the zooplankton biomass and these provide sufficient
food conditions for the survival and growth of ephyrae of C. melanaster,thus leading to an increase in scyphomedusae biomass (Brodeur et al.,2008). Large changes in biomass over a short period have been observedin other regions. For example, the biomass of ctenophores and scypho­
medusae along the Kurile Islands in the Western Pacific Ocean increased
10-fold from 2011 to 2012; intrusions from the Bering Sea and Okhotsk
Sea was invoked to explain this high biomass (Radchenko, 2013). Thus,
there are large annual fluctuations in the biomass of ctenophores andscyphomedusae, which are related to climate change and oceanographic
conditions.
Observations of water masses with high (>8 � C) and low (<2 � C)
temperature conditions that were characterized by a high abundance of
B. infundibulum in 2017 were much more limited in 2018, and a decrease

4.4. Interannual changes in ctenophores and scyphomedusae
This study was conducted in the same location and season over two
consecutive years and standing stocks of ctenophores and scyphome­dusae were much lower in 2018 than in 2017, by a factor of 1/20 to 1/
90. The biomass of large scyphomedusae in the southeastern Bering Sea
has been shown to fluctuate annually due to climate variability (Brodeur
et al., 2017). There, the biomass of large scyphomedusae, which isdominated by C. melanaster, increased 20-fold from 1975 to 2000, thendecreased to one-third of the maximum after 2001, possibly due toclimate-induced changes in the lower trophic levels (Brodeur et al.,2008). In warm years, ice melts quickly, leading to late pycnocline
development and phytoplankton bloom initiation; thus, smaller
10

Year

2017

11

Cast

Position

Local time

Day/
night

Lat. (N)Lon. (W)

Date

Hour

Descent
Observed volume (m3)AscentNumber of counted

Observed volume (m3)

B. infundibulum

C. melanaster

Beroe sp.

Number of counted
B. infundibulum

C. melanaster

Beroe sp.

1 (57)
2 (53)
5 (44)
6 (55)
7 (51)
9 (42)
10 (28)10 (28)10 (28)10 (28)10 (28)10 (28)10 (28)10 (28)10 (28)10 (28)10 (28)11 (34)12 (42)13 (40)14 (46)
14 (46)15 (45)16 (47)17 (53)18 (48)19 (65)20 (66)20 (66)21 (54)22 (47)23 (46)23 (46)24 (76)

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34

66� 16ʼ
66� 00ʼ65� 45ʼ
65� 20ʼ65� 03ʼ
65� 03ʼ
64� 30ʼ64� 30ʼ64� 30ʼ64� 30ʼ64� 30ʼ64� 30ʼ64� 30ʼ64� 30ʼ64� 30ʼ64� 30ʼ64� 30ʼ64� 30ʼ64� 30ʼ64� 30ʼ64� 30ʼ64� 30ʼ64� 30ʼ64� 15ʼ
64� 00ʼ
63� 45ʼ
63� 30ʼ
63� 12ʼ
63� 12ʼ
62� 54ʼ
62� 35ʼ
62� 10ʼ62� 10ʼ
63� 00ʼ

168� 54ʼ
168� 54ʼ
168� 09ʼ
168� 54ʼ
169� 38ʼ
168� 12ʼ
167� 10ʼ
167� 10ʼ
167� 10ʼ
167� 10ʼ
167� 10ʼ
167� 10ʼ
167� 10ʼ
167� 10ʼ
167� 10ʼ
167� 10ʼ
167� 10ʼ
167� 50ʼ
168� 40ʼ
169� 31ʼ
170� 21ʼ
170� 21ʼ
170� 53ʼ
171� 26ʼ
171� 57ʼ172� 29ʼ
173� 00ʼ
172� 42ʼ
172� 42ʼ
172� 04ʼ
171� 26ʼ
170� 30ʼ
170� 30ʼ
174� 05ʼ

9 July10 July
11 July
11 July
12 July
13 July
13 July
13 July
13 July
13 July
14 July
14 July
14 July
14 July
14 July
14 July
14 July
16 July
17 July
17 July
17 July
18 July
18 July
18 July
18 July
19 July
19 July
19 July
20 July
20 July
20 July
21 July
21 July
22 July

13:00
03:40
09:00
16:30
08:45
10:00
19:40
21:15
22:15
23:12
00:15
01:12
02:13
03:12
04:13
06:10
07:10
20:12
03:50
11:40
17:50
02:10
10:50
16:40
21:50
03:50
10:55
18:20
02:10
10:35
18:45
01:10
10:55
01:30

Day
Night
Day
Day
Day
Day
Day
Day
Day
Day
Day
Night
Night
Night
Night
Day
Day
Day
Night
Day
Day
Night
Day
Day
Day
Night
Day
Day
Night
Day
Day
Night
Day
Night

677.8
1105.4
701.9
780.5
995.0
697.8
496.0
547.2
428.4
478.2
508.4
459.5
452.6
342.6
430.4
282.9
285.3
615.9
710.2
425.4
609.2
724.2
677.3
680.5
935.0
870.1
661.7
658.7
731.5
548.4
520.7
518.2
330.2
645.3

221
215
59
77
89
262
48
35
16
20
25
30
62
93
18
32
43
400
549
161
227
146
187
206
783
1026
324
79
69
0
12
1
2
295

0
0
1
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
3
0
1
0
0
0
0
1
6
7
3
7
17
1
3
6

1
0
2
10
0
20
2
9
1
9
5
0
5
7
3
5
3
6
2
5
5
4
17
2
0
2
0
0
4
0
1
0
1
1

688.9
1069.1
818.1
946.0
934.6
620.8
492.6
475.4
340.7
274.3
438.0
297.4
272.0
297.1
357.0
250.6
305.9
504.9
475.3
361.3
651.0
815.5
521.8
569.9
889.6
880.8
522.8
561.1
678.7
480.3
427.5
404.7
510.5
527.1

111
177
17
113
100
163
15
15
14
3
58
35
73
44
27
15
18
300
320
271
279
304
116
197
487
861
283
109
130
0
18
0
1
251

0
0
0
1
0
0
0
0
0
0
0
0
0
1
0
0
0
1
2
1
0
1
0
0
0
3
7
9
3
7
3
5
6
2

0
1
5
13
0
8
3
7
5
3
2
5
2
7
6
4
2
4
0
1
10
5
4
5
2
0
0
1
4
0
0
0
0
2

4 (76)
6 (56)
8 (36)
11 (55)
14 (46)
17 (35)19 (28)20 (45)22 (52)23 (49)30 (42)29 (56)

35
36
37
38
39
40
41
42
43
44
45
46

63� 09ʼ62� 53ʼ
62� 28ʼ
63� 53ʼ
64� 30ʼ64� 30ʼ64� 21ʼ
65� 04ʼ
65� 05ʼ
65� 13ʼ
66� 44ʼ
66� 15ʼ

173� 50ʼ
172� 12ʼ
170� 05ʼ
172� 15ʼ
170� 54ʼ
168� 00ʼ
166� 30ʼ
168� 00ʼ
169� 39ʼ
169� 18ʼ
168� 58ʼ
168� 54ʼ

2 July3 July3 July4 July5 July5 July5 July6 July6 July7 July11 July
11 July

14:08
01:34
12:50
14:58
01:20
14:54
21:56
06:48
16:40
21:58
00:50
10:18

Day
Night
Day
Day
Night
Day
Day
Day
Day
Day
Day
Day

1144.5
875.9
515.9
794.8
704.3
279.9
294.7
512.0
588.7
711.0
652.9
575.4

3
44
56
1
1
10
0
11
6
39
14
10

2
0
3
0
0
0
0
0
0
0
0
0

0
5
0
0
0
0
0
0
0
0
0
0

928.4
928.1
334.1
750.9
646.8
487.6
247.6
656.3
392.4
706.5
475.6
571.8

3
94
31
2
0
33
0
15
2
91
17
22

3
0
0
0
0
0
0
0
0
0
0
0

0
13
0
0
0
0
0
0
0
0
0
0
(continued on next page)

Deep-Sea Research Part II 181-182 (2020) 104818

2018

Station(depth m)

M. Maekakuchi et al.

Appendix A. Data for ctenophores and scyphomedusae observations in the northern Bering Sea during 9–22 July 2017 and 2–12 July 2018.
One cast required approximately 20 min. To evaluate day-night differences, 11 observations were made at 1 h intervals at St. 10 from 19:40 13
July to 7:10 July 14, 2017. During that period, seven day (19:40, 21:15, 23:12, 0:15, 6:10, 7:10) and four night (1:12, 2:13, 3:12, 4:13) casts
were made. Observed volume (m3) and total counts of each species during descent and ascent of each cast are also shown.

C. melanaster

0
0
0
0
51
36

B. infundibulum

0
0
59
164

0
0

619.5
244.7

Observed volume (m3)
C. melanasterB. infundibulum

Observed volume (m3)

397.1
305.4

We thank the crew members of the T/S Oshoro-Maru and our col­laborators, especially Toru Hirawake, for assistance in collecting thevideo and CTD data. Constructive comments from Richard D. Brodeur
and one anonymous reviewer significantly improved the manuscript andare highly appreciated. This work was conducted by the Arctic Chal­lenge for Sustainability (ArCS) Project (Program Grant Number
JPMXD1300000000) and ArCS II. Part of this study was supported by aGrant-in-Aid for Scientific Research 20H03054 (B), 19H03037(B),18K14506 (Early Career Scientists), and 17H01483 (A) from the Japan
Society for the Promotion of Science (JSPS).

Day
Day
21:37
09:30
11 July
12 July168� 58ʼ
169� 00ʼ
47
48
27r (46)
16r (41)65� 40ʼ64� 30ʼ

Hour
Date
Lon. (W)Cast

Lat. (N)

Local time

Declaration of competing interest

Acknowledgments

Station(depth m)

Positionin optimal thermal conditions for B. infundibulum (>8 and < 2 � C) may
explain their very low abundance that year. Brodeur et al. (2017) re­
ported that the biomass of C. melanaster was high around SLI during bothwarm and cold periods. This suggests that around SLI, conditions are
suitable for the growth of C. melanaster polyps. Regarding annual dif­ferences in the oceanographic conditions of this region between 2017and 2018, the sea ice retreated in April during 2018, which wasapproximately 1 month earlier than in 2017 (see Appendix F which isderived from Arctic Data archive System (ADS) (https://ads.nipr.ac.jp/). As previously noted, early ice retreat may induce late phyto­plankton blooms, the dominance of small-sized copepods, and low
productivity, severely affecting food availability for C. melanaster (Bro­deur et al., 2008). As the sea ice began to retreat faster in 2018 comparedwith 2017, food conditions were likely to have been poor for the survivaland growth of the ephyrae of C. melanaster. The ephyrae of C. melanastergrow in the spring to become medusae in summer and reach their peaklevel of biomass in autumn (Zavolokin et al., 2008). Thus, the lower
numbers of C. melanaster in 2018 may be related to poor food conditions
for their ephyra larvae, which in turn, may be related to the early ice
retreat that year.
The ctenophores, B. infundibulum and Beroe sp., which dominated inthis region, spend their entire life cycle in the plankton. Thus, annual
differences in food conditions are experienced during their early juve­
nile life-history phases. The main food for small ctenophores andephyrae of scyphomedusae is copepods (Purcell, 1991). Thus, the timingof the ice retreat underlies annual differences in food conditions: early
ice retreat leads to low productivity with a dominance of small co­
pepods, whilst late ice retreat leads to high productivity due to thedominance of large copepods (Brodeur et al., 2008). For ctenophores
and scyphomedusae in this region, low standing stocks in 2018 may berelated to low productivity of large copepods, which was caused by theearly ice retreat in that year.

Appendix A. Supplementary data
Supplementary data to this article can be found online at https://doi.
org/10.1016/j.dsr2.2020.104818.
Appendix A

Year(continued )Deep-Sea Research Part II 181-182 (2020) 104818

There is no Conflict of Interest on the manuscript.

Day/
night

Descent

Number of counted

Beroe sp.

AscentNumber of counted

Beroe sp.

M. Maekakuchi et al.

12

M. Maekakuchi et al.

Deep-Sea Research Part II 181-182 (2020) 104818

Appendix B. Scatter plot on the density of Bolinopsis infundibulum quantified during descent and ascent.

Appendix C. Diel changes in the vertical distribution of Bolinopsis infundibulum at St. 10 during 13–14 July 2017. Open and solid markers represent day and night,
respectively.

Appendix D. Day (open) and night (solid) vertical distribution of Bolinopsis infundibulum at St. 14, 20, 23 during 17–21 July 2017.
13

Deep-Sea Research Part II 181-182 (2020) 104818

M. Maekakuchi et al.

Appendix E. Contour plots for abundance anomalies of three large gelatinous zooplankton on a T-S diagram.

Appendix F. Sea ice concentration on April 1st in 2017 (left) and 2018 (right). Images were downloaded from Arctic Data archive System (ADS) (https://ads.nipr.ac.
jp/).

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