Plankton Benthos Res 17(4): 369–382, 2022

Plankton & Benthos
Research© The Plankton Society of Japan

Seasonal changes in taxonomic, size composition,
and Normalised Biomass Size Spectra (NBSS) of
mesozooplankton communities in the Funka Bay,
southwestern Hokkaido: Insights from ZooScan analysis
Takumi Teraoka1,*, Kanako Amei1,2, Yutaka Fukai1,3, Kohei Matsuno4,5, Hiroji Onishi4,
Atsushi Ooki4,5, Tetsuya Takatsu4 & Atsushi Yamaguchi4,5,*
1

Graduate School of Fisheries Sciences, Hokkaido University, 3–1–1 Minato-cho, Hakodate, Hokkaido 041–8611, Japan
Present Address: Atmosphere and Ocean Research Institute, The University of Tokyo, 5–1–5, Kashiwa, Chiba 277–8564, Japan
3
Present Address: Kushiro Fisheries Research Institute, Hokkaido Research Organization, 2–6 Hamacho, Kushiro, Hokkaido
085–0024, Japan
4
Faculty of Fisheries Sciences, Hokkaido University, 3–1–1 Minato-cho, Hakodate, Hokkaido 041–8611, Japan
5
Arctic Research Centre, Hokkaido University, Kita-21 Nishi-11 Kita-ku, Sapporo, Hokkaido 001–0021, Japan
2

Received 27 September 2021; Accepted 19 September 2022 Responsible Editor: Jun Nishikawa
doi: 10.3800/pbr.17.369
Abstract: Knowledge about the taxonomic and size composition of mesozooplankton is of critical importance forboth ﬁsheries and oceanography. In this study, we collected an annual time series of mesozooplankton samples inFunka Bay and analysed them using ZooScan to reveal the seasonal changes in taxonomic and size structure. Bothzooplankton abundance and biovolume peaked in April and were dominated by an appendicularian Oikopleura labradoriensis which has been reported as being are being important food source for ﬂatﬁsh larvae. Furthermore, Noctiluca
scintillans was abundant from September to December. The occurrence of this species may be related to the recent increase in the transport of Tsugaru Warm Current water into the bay. The Normalized Biomass Size Spectra (NBSS) was
signiﬁcant for 16 of 21 sampling dates. Insigniﬁcant NBSS, with an extremely ﬂat slope, was observed for January–
March. Signiﬁcant NBSS with a ﬂat slope was observed in April. Then, the relatively steep slopes of the NBSS werethe case from mid-May to December. These seasonal changes in the slope of NBSS suggest that the energy transfer efﬁciency for higher trophic levels varied seasonally. The observed slopes of the NBSS in Funka Bay ranged from −1.09
to −0.30, which was ﬂatter than the theoretical value (−1) and the previously reported values for the oceanic region of
the western North Paciﬁc. This suggests that the energy transfer eﬃciency to organisms at higher trophic levels in the
Funka Bay is higher than in the adjacent oceanic region.
Key words: appendicularians, NBSS, Noctiluca scintillans, spring phytoplankton bloom, transfer eﬃciency

Introduction
Mesozooplankton serves as a food source for various
commercially important organisms, and the size distribution of mesozooplankton is an important factor in determining the food selection of ﬁsh (Sheldon et al. 1977).
The size composition of mesozooplankton also aﬀects thegrowth and mortality rates of the ﬁsh (Meeren & Næss* Corresponding author: Takumi Teraoka; E-mail, takumi.terabyte74@
gmail.com, Atsushi Yamaguchi; E-mail, a-yama@ﬁsh.hokudai.ac.jp

1993). Consequently, information on mesozooplankton isimportant for ﬁsheries science. From an oceanographicalviewpoint, the size distribution of the mesozooplankton
community aﬀects the amount of material transported
from the ocean surface to the deep layer via egested faecal pellets, a process called the biological pump (Michaels& Silver 1988, Ducklow et al. 2001). Thus, information on
the size composition of mesozooplankton communities isof critical importance both in ﬁsheries science (as a foodsource for ﬁshes) and oceanography (with respect to material transfer cycles).

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Traditionally, mesozooplankton size has been measured under a microscope, requiring much eﬀort and time.
Consequently, studies on size composition were scarce,
especially considering their importance. Recently a new
instrument, ZooScan, has been developed to quantify mesozooplankton and provide data on size and taxon, by using image analysis (Gorsky et al. 2010). Since ZooScan canobtain taxonomic data as well as information on size, it issuperior to the Optical Plankton Counter (OPC) (Herman1988), which can only obtain data on size. With the widespread availability of these imaging analysis instruments,
information on mesozooplankton in the ﬁeld has accumulated rapidly (Vandromme et al. 2012, 2014, Marcolin et al.
2015a, 2015b, Romagnan et al. 2015, 2016).
The Normalized Biomass Size Spectra (NBSS) is commonly used to evaluate the size spectrum of mesozooplankton (Sprules & Munawar 1986, Zhou 2006, Zhou etal. 2009, Vandromme et al. 2014, Marcolin et al. 2015a).
The NBSS is a regression-generated by plotting the mesozooplankton size on the X-axis and the standardized
plankton biomass on the Y-axis and is used to assess the
structure and trophic state of marine ecosystems (Platt &Denman 1977, 1978). The slope of the NBSS is aﬀectedby both bottom-up and top-down controls (Platt & Denman 1977, 1978, Zhou 2006, Zhou et al. 2009). When thebottom-up controls dominate conditions due to nutrient increase and high productivity, the biomass of the small sizeclasses of mesozooplankton increases. Consequently, theintercept of the NBSS increases, and the slope becomessteeper. However, under top-down conditions, since thelarge-body-sized mesozooplankton dominate, the interceptof the NBSS remains the same, but the slope becomes ﬂattened (Moore & Suthers 2006). From ﬁeld observations in
the neighbouring waters of Japan, the slopes of the NBSS
of the zooplankton samples collected by 335-µm meshquantiﬁed by OPC have been reported to vary geographically (Fukuda et al. 2012, Sato et al. 2015) and seasonally(Hikichi et al. 2018). However, because of the scarcity of
information on mesozooplankton NBSS, it is diﬃcult toinfer general changing patterns of mesozooplankton NBSS
along with geographical and seasonal changes.
Funka Bay is located in the southwestern part of Hokkaido, Japan. It is a shallow (<100 m depth) bay and an
important nursery area for various ﬁsh species such as
walleye pollock (Gadus chalcogrammus Pallas, 1814) andﬂatﬁshes that spawn and feed there during larval and juvenile stages (Kamba 1977, Nakatani 1988, 2016, 2017,
Nakatani & Maeda 1993, Hashimoto et al. 2011). The hydrographic characteristics of Funka Bay result from two
diﬀerent water masses (the Oyashio Cold Current andthe Tsugaru Warm Current) that intrude into the bay,
and which water mass dominates varies with the season(Ohtani 1971, Ooki et al. 2019). In response to seasonalchanges in the physical oceanography, zooplankton communities also show great seasonal ﬂuctuations (Hirakawa
1976, 1979, 1983). In addition to changes in community

structure, seasonal changes in the various dominant mesozooplankton taxa have also been reported (Dohi 1982,
Shiga 1985, Yokouchi 1985, Yamaoka et al. 2019). Suchinformation is important, which makes it unfortunate thatno data are available on the size structure and NBSS of themesozooplankton and their seasonal changes.
It should also be noted that water temperatures in Funka Bay have been warmer recently, which may be related
to climate change (Ooki et al. 2019). The volume of the
Tsugaru Warm Current transported from the Japan Sea
through the Tsugaru Strait is reported to be increased during 1996–2012 (Kida et al. 2021). In Funka Bay, due to thewarming, the water mass classiﬁcations dating from the
1960s and 70s (Ohtani 1971) are outdated, and new watermass classiﬁcations have been established recently (Ookiet al. 2019). Such warming is expected to aﬀect marine
ecosystems, but as yet, little information is available on
the changes observed in the mesozooplankton community
resulting from the warming.
In this study, we analysed a time series of mesozooplankton samples collected at one station in the central
section of Funka Bay from December 2018 to December
2019. We collected the mesozooplankton using a plankton
net with a ﬁne mesh (100 µm) in order to collect the wholemesozooplankton community. The mesozooplankton samples were preserved in formalin and subsequently analysedby ZooScan for taxonomic and size information along with
abundance and biovolume. The taxonomic information obtained was then compared with the taxa recorded in themesozooplankton communities in the 1980s (Hirakawa
1983, Shiga 1985). We compared the NBSS data of thezooplankton samples collected by 335-µm mesh net andquantiﬁed by OPC from around Hokkaido with those fromthe oceanic region of the western North Paciﬁc (Fukuda etal. 2012, Shiota et al. 2013, Sato et al. 2015, Hikichi et al.
2018, Mishima et al. 2019). It should be noted that we useda zooplankton net with 100-µm mesh size and quantiﬁedsamples by ZooScan in this study. To make quantitative/
qualitative comparison possible with the previous studies,
we calculated NBSS based on the size ranges of 350-µm
to 5-mm which is the same as in the previous studies.
Through this comparison, we evaluated general changing
patterns in terms of the geographical (coastal vs. oceanic)or seasonal changes in the NBSS.
Materials and Methods
Field sampling and hydrography
We sampled mesozooplankton at a quasi-monthly interval from 12 December 2018 to 16 December 2019 using a
North Paciﬁc Standard (NORPAC) net (mouth diameter
45 cm, 100 µm mesh) deployed to near the bottom (87±
2 m [mean±sd]) and towed vertically 21 times at Sampling Station 30 (St. 30), located at the centre of Funka
Bay (depth: 95 m) (Fig. 1). The ﬁltration volume of the net

371

Seasonal zooplankton size and taxonomic community in Funka Bay

Kofoid & Swezy, 1921 (hereafter we termed Noctiluca),
benthos larvae, and detritus. Within them, detritus was excluded from subsequent analyses because it is a non-living
fraction.
ZooScan provides estimates of body length (major axisof the best ﬁtting ellipse) and width (minor axis) (Gorsky
et al. 2010). The volume of the ellipse (Volume, mm3) was
calculated using the major axis length (Lmajor, mm) and theminor axis width (Lminor, mm) (Vandromme et al. 2012):

Volume = 4/3×π × ( Lmajor /2) × ( Lminor /2)2
Fig. 1. Location of the sampling station (St. 30) at the centerof Funka Bay, southwestern Hokkaido, Japan. Directions of thecurrents are shown by the arrows in the upper-right panel. Depth
contours are superimposed on the main panel.

was 11.9±2.4 m3, and the mean ﬁltration eﬃciency was
86%. The collected mesozooplankton samples were preserved with 5% v/v borax-buﬀered formalin seawater. At
each sampling, water temperature and salinity were measured using a conductivity-temperature-depth (CTD) probe(SBE 19plus, Sea-Bird Scientiﬁc Inc.). To identify the water masses, T-S diagrams were made. For the classiﬁcationof water masses, we referred to Ooki et al. (2019). Using
the seawater samples from 0, 5, 10, 20, 30, 40, 50, 60, 70,
75, 80, and 85 m that were collected by a bucket (0-m) or
the rosette-mounted Niskin bottles on the CTD, nutrient
concentrations (NO−3 and NO−2 ) were measured by the colorimetric method using a QuAAtro system (BL-Tec, Osaka,
Japan). Chlorophyll a concentrations in the seawater samples (100 mL) were measured by the Welschmeyer method(Welschmeyer 1994) using a ﬂuorometer model 10-AU-005(Turner Designs, San Jose, CA, USA).
ZooScan analysis
In the laboratory, zooplankton images were scannedwith a ZooScan system (Hydrooptic Inc.) based on themethod of Gorsky et al. (2010). Before each measurement,
background measurements were made with deionised water. Zooplankton subsamples of 1/3 to 1/90 (depending on
the amount of the sample) were made by a wide-bore pipette and scanned. The obtained images were separated
into individual images using the ZooProcess software. The
zooplankton images were digitised at 2400 dpi resolution,
at which one pixel corresponded to 10.6 µm. The obtained
images were uploaded to the website Ecotaxa (http://ecotaxa.obs-vlfr.fr/prj/). The identiﬁcation of each taxon wasmade semi-automatically through the web (Picheral et al.
2017). The taxonomic groups and species identiﬁcationsin this study included the large copepod Eucalanus bungii
Giesbrecht, 1893, Metridia paciﬁca Brodsky, 1950, Neocalanus spp., other members of Copepoda, Euphausiacea,
Appendicularia, Chaetognatha, Polychaeta, Amphipoda,
Cnidaria, Thaliacea, Noctiluca scintillans (Macartney)

From the volume of the ellipse, the Equivalent Spherical
Diameter (ESD, mm) with the same volume was calculated:
ESD = 3

Volume × 3
4π

The abundance (N: ind. m−3) was calculated from the number of particles (n, where n is the number of particles ineach size class every 0.05 mm between 0.2 and 5.0 mm
ESD) and the volume of ﬁltered water (F: m−3). The biovolume (B: mm3 m−3) was also calculated from the volume(mm3) and F using the following equation:
n
N=
F ×s
VolumeB=
F ×s
where s is the split factor of the ZooScan measurement.
Zooplankton community
To evaluate the trends of the mesozooplankton community structure, cluster analysis based on their abundance
was conducted. Cluster analysis was performed by connecting the Bray-Curtis similarities using the mean linkage method based on the standardised log (X+1) valuesof the abundance data (X: ind. m−3) of each zooplankton
taxon in each sample. Diﬀerences in abundance between
the communities were tested by one–way ANOVA and the
Tukey–Kramer test. These statistical analyses were performed using the Primer 7 software package (Primer-E,
Ltd., Quest Research Limited, Albany, Auckland, New
Zealand) and StatView 5.01 (SAS Institute Inc., Cary, NC,USA).
To evaluate the relationship between environmental
parameters and the zooplankton community, a distancebased linear modelling (DistLM) and a distance-based redundancy analysis (dbRDA) were carried out. All environmental parameters were normalized, and then the DistLM
was run with dbRDA plot by combining the resemblance
matrix (based on Bray-Curtis similarities between theabundances of zooplankton species in the samples) andthe hydrographic variables (including slope and intercept
from NBSS). To run DistLM, we choose “All speciﬁed” asa selection procedure, “R2” as a selection criterion, and the372

T. Teraoka et al.

number of permutations was 999. The analyses were conducted using the Primer 7 software.
NBSS
For NBSS analyses, although we used a plankton net
with a mesh size of 100 µm, to make an adequate comparison with the previous studies that used a 335 µm mesh net,
we used only the data with>0.35 mm ESD for the NBSS
calculation. The biovolume (mm3 m−3) summed at each
0.05 mm between 0.35 and 5.0 mm ESD was used for thedata of the NBSS analysis. These size categories were thesame as the previous studies (Fukuda et al. 2012, Shiota etal. 2013, Sato et al. 2015, Hikichi et al. 2018, Mishima etal. 2019). The X-axis of the NBSS is the biovolume of eachsize class transformed to the normal logarithm (X: log10
zooplankton biovolume [mm3 ind−1]), and the Y-axis isthe biovolume of each size class divided by the diﬀerencein biovolume between adjacent size classes (Δbiovolume[mm3]). (Y: log10 zooplankton biovolume [mm3 m−3]/
Δbiovolume [mm3]). The linear equation of NBSS was obtained using the MS Excel solver function:
Y = aX + b

where a and b are the slope and intercept of the NBSS,
respectively. To clarify the interaction between slope (a)and intercept (b) of the NBSS, we made a scatter plot between them.
Results
Hydrography
Water temperatures ranged from 2.1 to 20.5°C throughout the entire period (12 December 2018 to 16 December2019) at St. 30 in Funka Bay (Fig. 2a). From February to
March, the temperatures were vertically uniform and decreased to 3–4°C in this period. However, after April, water temperature increased in the epipelagic zone, and thedevelopment of the thermocline was observed at a depth ofapproximately 40 to 50 m from August to October.
Salinity ranged from 30.0 to 34.1 but was high (>33.8)
and vertically uniform from December to February (Fig. 2b).
After March, low salinity was observed in the epipelagiczone. A low-salinity water (<32.4) was observed at depths
shallower than 30 m from May to August.
Nutrients (NO−3 +NO−2 ) ranged from 0.05 to 18.88 µM L−1

Fig. 2. Seasonal changes in temperature (a), salinity (b), nutrients (c), chlorophyll a (d), and water mass (e) at St. 30 in Funka Bay, southwestern Hokkaido, Japan, from December 2018 to December 2019. Triangles at the top abscissa indicate sampling dates. Water mass classiﬁcations are derived from Ooki et al. (2019). T: Tsugaru Warm Current, Fw: Funka Bay water formed in winter, O: Oyashio Coastal Branch,
Fs: Funka Bay water formed in summer.

Seasonal zooplankton size and taxonomic community in Funka Bay

373

curred in September-October. Finally, the Tsugaru Warm
Current dominated the following December again. Thus,
within the annual scale, clockwise changes were observed
for the plotted positions in the T–S diagram (Fig. 3).
Zooplankton abundance and biovolume

Fig. 3. Seasonal changes in Temperature-Salinity diagrams at
St. 30 in Funka Bay, southwestern Hokkaido, Japan, from December 2018 to December 2019. Black lines denote seasonal changes
in properties at the sea surface. Red lines represent water masses.
Water mass classiﬁcations are derived from Ooki et al. (2019). O:
Oyashio Coastal Branch, Fs: Funka Bay water formed in summer,
T: Tsugaru Warm Current, Fw: Funka Bay water formed in winter.

and were vertically uniform from December to February(Fig. 2c). From the end of February to early March, the nutrients above 40 m rapidly decreased from 8 to<2 µM L−1.
The lowest nutrient concentration (<2 µM L−1) was observed for the upper 40 m of the station during the long
period between March and October.
Chlorophyll a concentrations ranged from 0.00 to
29.71 µg L−1 and were high for a temporally restrictedperiod: from the end of February to mid-April (Fig. 2d).
For the other periods, high chlorophyll a concentrations(>4 µg L−1) were not detected.
The plot positions in the T–S diagram varied greatly
within each water mass (Fig. 3). Four water masses wereidentiﬁed in Funka Bay, namely: Funka Bay water formed
in winter (Fw), Oyashio Cold Current water (O), Funka
Bay water formed in summer (Fs), and Tsugaru Warm
Current water (T) (Fig. 2e). In addition, the transitions between them from mixing processes, such as Fw–O and Fs–
T, are also present, as were the transitions resulting fromwarming or cooling processes within the water masses,
such as O–Fs and T–Fw (Ohtani 1971, Ooki et al. 2019).
During the study period, the Tsugaru Warm Current wasobserved in December 2018, and its cooling process (T–Fw) occurred in January 2019. Fw dominated in February
and was subsequently replaced by the Oyashio Cold Current in March–April; its warming process (O–Fs) in turnwas seen in May. During June and August, Fs dominated,
and the mixing process of the two water masses (Fs–T) oc-

The total zooplankton abundance and biovolume ranged
from 255 to 3,467 ind. m−3 and 12 to 2,034 mm3 m−3, respectively (Fig. 4). Seasonal changes in abundance andbiovolume varied with taxa, and four seasonal patterns ofchange were detected. The ﬁrst pattern was forming abrupt
abundance peaks in April, which was observed for the copepods M. paciﬁca and Neocalanus spp., as well as for
Euphausiacea, Appendicularia, Polychaeta, and Amphipoda. The second pattern was abundant between April andJune, which was observed for the copepod E. bungii andthe other Copepoda. The third pattern was abundant during June-December, including Chaetognatha and Cnidaria.
The fourth pattern was abundant from September to December and not detected for the other periods, observed for
Thaliacea and Noctiluca.
Zooplankton communities
The cluster analysis based on zooplankton abundance
separated the zooplankton community into three groups
at 73.1% dissimilarity (Fig. 5a). The remaining four samples were treated as an “out-group”. Each group contained
4 to 9 samples. We termed the three groups A, B, andC. The occurrence period of each group was separated
clearly: Group A was seen from August to January, GroupB occurred from December to February, and Group C appeared from April to June. For taxonomic accounts, theoccurrence pattern of each taxon was classiﬁed into sevengroups at 89.8% dissimilarity. Within them, for the taxonomic groups including several taxa, large copepods suchas Eucalanus bungii, Metridia paciﬁca, Neocalanus spp.,
and polychaetes occurred dominantly in Group C. For
the remaining taxa, it should be noted that Noctiluca occurred in great numbers in Group A. Inter-group diﬀerences in abundance were tested by one–way ANOVA andthe Tukey–Kramer test (Table 1). For the taxa, two species/
taxa exhibited signiﬁcantly diﬀerent abundances between
the groups: E. bungii, a large copepod, was abundant inGroup C, and Noctiluca was present in high numbers inGroup A.
Results of dbRDA indicated that the zooplankton community in the Funka Bay could be classiﬁed from the Xaxis (dbRDA 1) representing changes in temperature andthe Y-axis (dbRDA 2) indicating NBSS intercept (Fig. 5b).
Contributions for the variation of each axis were similar(35.0% and 21.4%), and it should be noted that these twoaxes contributed a relatively high component (>50%) of
the variations. From the result of DistLM, four environmental parameters (temperature, salinity, NBSS intercept
and slope) explained 65.7% of the zooplankton variation.
Within the dbRDA plots, the large changes in the plotted374

T. Teraoka et al.

Fig. 4. Seasonal changes in abundance and biovolume of each zooplankton taxon at St. 30 in Funka Bay, southwestern Hokkaido, Japan,
from December 2018 to December 2019.

area were observed on two occasions: 14 June to 29 August and 15 March and 11 April (Fig. 5b). For the changes
from 14 June to 29 August, the changes in the plotted area
were seen along the X-axis (dbRDA 1). This change represented the community change from Group C to GroupA. While for the other large changes from 15 March to 11
April, their changes were observed along the Y-axis (dbRDA
2). It should be noted that the zooplankton community ofGroup C was plotted at the left end of the dbRDA plots but
has a large plotted area vertically within the same Group C(Fig. 5b).

NBSS
Signiﬁcant NBSS with a negative slope was observedfor 16 of the 21 sampling dates (r2=0.33–0.90, p < 0.05;
Fig. 6). The periods when NBSS was not signiﬁcant wererestricted from 28 January to 15 March, and most of thembelonged to Group B. During that period, the slopes of the
NBSS were extremely ﬂat. For the dates showing a signiﬁcant NBSS, the slope of the NBSS ranged from −1.09
to −0.30. Flat slopes of NBSS (−0.63 to −0.29) were observed for 11–17 April belonging to Group C. These dates
were characterized by the high biovolume of Appendicularia (Fig. 4). On the other hand, the slopes were steeper
for the rest of the season: mid-May to January, ranging

Seasonal zooplankton size and taxonomic community in Funka Bay

375

in Fig. 8. For the zooplankton in Group A, both abundanceand biovolume were stable and similar within the community. For the zooplankton in Group B, the slope andintercept of the NBSS in December greatly varied from theother dates, but for the other dates, slopes were extremely
ﬂat, resulting in insigniﬁcance of NBSS. The greatest differences in NBSS within the same zooplankton community were seen for the zooplankton in Group C observed
from April to June. For April, the slopes of NBSS were
ﬂat, then having insigniﬁcant NBSS on 8 May, after that,the slopes of NBSS showed steep slopes (−0.99 to −0.75)
for other dates.
Discussion
Seasonal changes in zooplankton communities

Fig. 5. Result of cluster analysis based on the mesozooplankton
abundance at St. 30 in Funka Bay, southwestern Hokkaido, Japan,
from December 2018 to December 2019 (a). Dashed lines represent
signiﬁcant divisions for the taxon (horizontal axis) and sampling
dates (vertical axis). dbRDA plots of the three groups (A–C) withenvironmental parameters (b). The arrowhead direction and lengthof the arrow lines in the middle of the panel indicate the relationship between groups and the strength of the parameters. The slope
and intercept of the NBSS were referred from Fig. 6.

from −1.09 to −0.63. The intercept of NBSS ranged from
0.273 to 2.101.
Based on the data from the whole study period, there
was a signiﬁcant positive relationship between the slope
and intercept of the NBSS (r2=0.28, p < 0.05; Fig. 7). Thissigniﬁcant relationship was also the case by eliminating
the ﬁve dates of insigniﬁcant NBSS (r2=0.55, p < 0.05).
Within the scatter plots between slope and intercept of
NBSS, the plotted area varied with the zooplankton community. Thus, zooplankton in Group A were settled in the
middle of the scatter plot. Insigniﬁcant NBSS (underlined
dates in Fig. 7) was mostly observed for the zooplankton inGroup B. The largest variabilities of the plotted area wereseen for the zooplankton in Group C.
Seasonal changes in the zooplankton community
Seasonal changes in water mass, zooplankton community, zooplankton abundance, biovolume, and slope and intercept of NBSS during the study period are summarized

Both zooplankton abundance and biovolume peaked in
April (Fig. 8), which is consistent with previous reports regarding zooplankton abundance and biomass around Hokkaido peaking in spring (Ban et al. 1998, Yamaguchi etal. 2003, 2014, Shimada et al. 2012, Arima et al. 2014a,
Hirakawa et al. 2019). This is a result of the abundant
spring bloom of phytoplankton occurring approximately
one month earlier than that time (Fig. 2d). Consequently,
the numerically dominant small copepods reproduce, andgrowth takes place simultaneously in the biomass-dominant large copepods such as Neocalanus spp. (Yamaguchi& Shiga 1997, Shimada et al. 2012, Arima et al. 2014a,
2014b, Kitamura et al. 2016). In this study, the numericallydominant taxa were “other Copepoda”. The species belonging to this category are Pseudocalanus spp. and Paracalanus spp., and both are known to be abundant throughout
the year (Yamaguchi & Shiga 1997, Ban et al. 1998, Yamaguchi et al. 2003).
The dominant appendicularian during April, when
whole zooplankton abundance and biovolume are high,has been reported to be the cold-water species Oikopleura
labradoriensis Lohmann, 1892 (Shiga 1985, Yamaoka et
al. 2019). In Funka Bay, the cold-water species Fritillaria
borealis Lohmann, 1896 is also abundant, especially in the
Fw and O water masses (Shiga 1985). Of these, the larger O. labradoriensis is abundant by biovolume in spring(Teraoka unpublished). In various subarctic regions of thenorthern hemisphere, appendicularians are known to havehigh ﬁltering rates and productivity, and their discarded
houses play an important role in vertical material transport (Alldredge 1976, Flood 1991, Choe & Deibel 2008,
Doubleday & Hopcroft 2015). In Funka Bay, the dominant
appendicularian, O. labradoriensis, is reported to be an
important food source for the larvae of the ﬂathead ﬂounder (Hippoglossoides dubius Schmidt, 1904) and the stone
ﬂounder (Platichthys bicoloratus [Basilewsky, 1855]) fromJanuary to May (Miyamoto et al. 1993, Hashimoto et al.
2011). It also should be noted that appendicularians havethe ability to feed on small particles by ﬁltering ambient376

T. Teraoka et al.

Table 1. Inter-group diﬀerences in the abundance of each taxon or species of the three groups of mesozooplankton separated by Bray–Curtis similarity (cf. Fig. 5a) in Funka Bay from December 2018 to December 2019.
Taxa/species
Eucalanus bungii
Metridia paciﬁca
Neocalanus spp.
Other copepods
Euphausiacea
Appendicularia
Chaetognatha
Benthos larvae
Polychaeta
Amphipoda
Cnidaria
Thaliacea
Noctiluca scintillans
Others
Total

Mean abundance (ind. m−3)

one-way

A (4)

B (4)

C (9)

ANOVA

1.07a
5.80
7.69
632.3a,b
2.49
87.64
18.49
20.07
5.72
0
8.72
5.20
122.77b122.771039.62

2.14a
3.82
8.99
286.59a
2.44
24.37
6.34
40.18
2.62
0
0.13
0
0a
26.08
403.7234.47b
5.94
14.06
1277.45b2.57
111.47
23.58
70.39
49.41
0.73
5.25
0
0a
43.80
1639.11

***
NS
NS
*
NS
NS
NS
NS
NS
NS
NS
NS
**
NS
NS

Values in parentheses indicate the number of samples included in each group. Diﬀerences were tested by one-way ANOVA and Tukey–
Kramer tests. Results of the Tukey–Kramer test are shown by diﬀerences in superscript alphabets (p < 0.05). NS: not signiﬁcant *: p < 0.05;**: p < 0.01; ***: p < 0.001.

water (Alldredge 1976, Flood 1991, Choe & Deibel 2008,
Doubleday & Hopcroft 2015). These facts suggest that the
appendicularian O. labradoriensis probably plays an important role in material transfer connecting the productivity of the spring phytoplankton bloom to the higher trophic
levels in the spring marine ecosystem of Funka Bay. The
other abundant taxa in this period included Polychaeta, Amphipoda, Euphausiacea, and the copepods M. paciﬁca and
Neocalanus spp. (Fig. 4). All of these are cold-water taxa,
having large body sizes, and are expected to be highly nutritional food for higher trophic level organisms.
For the dominant taxa of summer to autumn, Noctiluca
stood out. While Noctiluca has not previously been reported to be dominant in Funka Bay (cf. Hirakawa 1983),
they are reported to dominate in warm water masses suchas the Kuroshio and the Tsushima Warm Current (Miyaguchi et al. 2006, Ara et al. 2013, Suzuki et al. 2013). In thepresent study, Noctiluca were limited to Fs–T and T water
masses, which indicates that this genus was transported by
the Tsugaru Warm Current. It is interesting to note that,while Fw is the cooled Tsugaru Warm Current (Ohtani
1971, Ooki et al. 2019), no Noctiluca were observed in Fw
after December, suggesting that Noctiluca died oﬀ undersuch cold conditions (Fig. 4). In recent years, warming
trends have been reported for Funka Bay (Ooki et al. 2019).
A yearly increasing trend of the amount of the Tsugaru
Warm Current transported has been reported for 1995–
2012 (Kida et al. 2021). The dominance of warm-waterNoctiluca, which has never been reported previously, during the warm season in Funka Bay is noteworthy as aneﬀect of climate change on the zooplankton community in

Funka Bay.
In this study, the zooplankton community in Funka
Bay was classiﬁed into three major groups, of which threegroups (A, B, and C) occurred clearly separated by season(Fig. 8). Concerning Group C, temporal variability of theplotted area in dbRDA plot was prominent for Group C(Fig. 5b). In the dbRDA plot, the plotted area of Group C
lay on the left side (low dbRDA1) but had high variability
along the Y-axis (dbRDA2). In fact, for the three dates plotted in the lower-left corner of the dbRDA plot (11 April, 5June, and 12 June), the abundances of the other Copepoda,
Appendicularia, Chaetognatha, and benthos larvae were
the highest (Fig. 5a). On the other hand, within Group C,
for the four dates characterized with a positive dbRDA2(17 April, 8, 12, 14 May), the abundances of the above taxa
were relatively low (Fig. 5a). Based on the ﬁve-years of observations in Funka Bay, the spring phytoplankton bloom
has been reported to occur in March-April (Kudo & Matsunaga 1999) which corresponds with that also observed inthis study (the end of February to mid-April) (Fig. 2d). Asa mechanism for the initiation of the spring phytoplankton bloom in Funka Bay, intrusion of the Coastal Oyashio
Water is important (Shinada et al. 1999a). During spring,the magnitude of the phytoplankton bloom exhibited great
spatiotemporal changes (Sasaoka et al. 1998, Shinada etal. 1999b). Under such conditions, such large spatiotemporal variability is also expected to be present in the zooplankton community. Thus, large variabilities in dbRDA2
observed for the zooplankton in Group C would be a reﬂection of the spatiotemporal changes in the zooplankton
community. These phenomena would be related to the bot-Seasonal zooplankton size and taxonomic community in Funka Bay

377

Fig. 7. Relationship between slope and intercept of normalised
biomass size spectra (NBSS) derived from mesozooplankton in
Funka Bay, southwestern Hokkaido, Japan, from December 2018
to December 2019. Diﬀerences in symbols (A, B, C, and Out)represent diﬀerences in the zooplankton community (cf. Fig. 5a).
Five dates with underlines indicate the insigniﬁcance of NBSS (cf.
Fig. 6). Dashed and solid lines represent signiﬁcant relationships
between slope (Y) and intercept (X) of NBSS based on the whole
data set (dashed line) and only for the signiﬁcant NBSS data (solidline), respectively.
Fig. 6. Seasonal changes in normalised biomass size spectra(NBSS) at St. 30 in Funka Bay, southwestern Hokkaido, Japan,
from December 2018 to December 2019. Note that, except for ﬁve
sampling dates (28 January, 10 and 23 February, 15 March and 8
May 2019), NBSS regressions are highly signiﬁcant (r2=0.40–
0.87, p < 0.05). The alphabets in the parentheses indicate zooplankton community groups identiﬁed from the cluster analysis (cf.
Fig. 5a). Out: out-group.

tom-up eﬀect of the primary productivity, which exhibitedlarge spatiotemporal changes (Sasaoka et al. 1998, Shinada
et al. 1999b).
For the zooplankton community in Group A, the largechanges along the X-axis in dbRDA1 between 14 June and
29 August were induced by the changes in the zooplankton
community from Group C to Group A (Fig. 5b). The diﬀerences in the dominant zooplankton taxa between the twogroups were E. bungii, Polychaeta, M. paciﬁca, and Neocalanus spp. for Group C, while Thaliacea and Noctiluca
dominated Group A (Fig. 5a). Note that the dominanceof Thaliacea was observed only from August to October.
The dominant water masses in the period where Group A
dominated were S, S-T, and T. Under such warm conditions, development of the thermocline occurred (Fig. 2a),and primary productivity was expected to be low, considering the chlorophyll a data (Fig. 2d). With such low
primary production and stable conditions, zooplankton is
also expected to be in a stable state. These facts suggest
the dominance of a complex planktonic food-web during
this season. Combining such a complex food-web struc-Fig. 8. Summary panels on seasonal changes in water mass, mesozooplankton community classiﬁcation based on abundance (cf.
Fig. 5a) (upper panels), abundance and biovolume (middle panel),and slope and intercept of normalised biomass size spectra (NBSS)(cf. Fig. 6) (lower panel) in Funka Bay, southwestern Hokkaido,
Japan, from December 2018 to December 2019. Crosses for the
NBSS slope indicate the insigniﬁcance of the NBSS. The box at thebottom represents the period of the spring phytoplankton bloom in
Funka Bay (cf. Fig. 2d).

378

T. Teraoka et al.

ture within the zooplankters, high temperatures and low
primary productivity, energy transfer to the higher trophiclevels (e.g. ﬁshes) is expected to be small from summer toautumn.
For zooplankton in Group B, which were observed during the cold season (December to February), the abundances of the seasonal supplemental zooplankton taxa (e.g.
Thaliacea and Noctiluca for Group A or E. bungii, Polychaeta, M. paciﬁca, and Neocalanus spp. for Group C)
were diminished, and only core zooplankton taxa (other
Copepoda, Appendicularia, Chaetognatha, and benthic larvae) were present, albeit to a limited extent (Fig. 5a). These
facts suggest that the zooplankton in Group B is a transitional zooplankton community between the warm zooplankton in Group A to the high productivity-correlated
zooplankton in Group C. Since the primary productivity in
the Funka Bay is low during the winter before the onset ofthe phytoplankton bloom (Kudo & Matsunaga 1999), andthere is a die-oﬀ of expatriated warm-water zooplankton(Thaliacea and Noctiluca in Group A), the zooplankton
taxa comprising transitional zooplankton Group B are expected to be limited.
NBSS
This study is the ﬁrst attempt to evaluate the seasonalvariation of the NBSS based on zooplankton biovolume
in Funka Bay (Fig. 6). The NBSS is used as an index of
productivity, transfer eﬃciency to the higher trophic levels,and predator-prey interactions in marine ecosystems (Herman & Harvey 2006, Marcolin et al. 2015a). The slope of
the NBSS varies depending on the productivity, energy
transfer eﬃciency, and predator-prey interactions (Zhou
2006, Zhou et al. 2009). Theoretically, a slope of −1 for
the NBSS indicates a steady zooplankton community, aslope steeper than −1 indicates a low transfer eﬃciency,
and a ﬂat slope indicates a high transfer eﬃciency (Sprules& Munawar 1986). It should also be noted that a ﬂat slope
is attributable to a high abundance of large zooplankters(García-Comas et al. 2014, Soviadan et al. 2022). The
NBSS intercept becomes large when either the overall biomass or the number of small organisms increases (Moore& Suthers 2006).
In Funka Bay, NBSS was signiﬁcant for 16 occasions of
21 sampling dates (Fig. 6). The insigniﬁcant NBSS values
were observed for a restricted zooplankton group (GroupB) and season (January to March) (Fig. 6). The NBSS
slopes in Funka Bay showed clear seasonality separated
into three groups. Signiﬁcantly ﬂat slopes (−0.63 to −0.29)
were observed for 11–17 April, then relatively steep slopes(−1.09 to −0.63) were observed for May to January, andthen extremely ﬂat slopes and insigniﬁcant NBSS fromJanuary to March (Fig. 8). This clear seasonality in the
NBSS slope is informative from the viewpoint of energy
transfer from primary production to higher trophic levels.
Primary productivity in Funka Bay is initiated by the
spring phytoplankton bloom that occurred from the endof February to mid-April (Fig. 2d), and nearly half of theannual primary production is concentrated over this shortperiod (Kudo & Matsunaga 1999). After the spring bloom,
the NBSS slopes were signiﬁcant but ﬂat observed for 11–
17 April (Fig. 6). The dominant zooplankton taxon at thesedates was the large-sized appendicularian, O. labradoriensis (Fig. 4, Shiga 1985). Appendicularia have the ability
to feed on small-sized particles by ﬁltering feeding (Alldredge 1976, Flood 1991, Choe & Deibel 2008, Doubleday& Hopcroft 2015). O. labradoriensis has been reported to
be an important food item for ﬂatﬁsh larvae in the Funka
Bay during spring (Miyamoto et al. 1993, Hashimoto etal. 2011, Yamaoka et al. 2019). The high biovolumes, ﬂat
slopes of NBSS, and dominance of large-sized appendicularians suggest that energy transfer from primary production to higher trophic levels functions well during that period (mid-April).
On the other hand, the slopes of NBSS were relatively
steep for the long remaining season: May-January. During
these seasons, because of the steep slopes of NBSS, energy
transfer to higher trophic levels is expected to be small. The
dominance of carnivorous taxa: Chaetognatha and Cnidaria
during these periods (Fig. 4) also suggests that the energy isconsumed within the zooplankton community.
The slopes of the NBSS were extremely ﬂat from late
January to March (Fig. 6). These seasonal sequences in
the NBSS slope may be interpreted that high energy transfer occurs during the high productivity season (mid-April).
Then the energy is consumed within the zooplankton
community and only minimal energy reaches the higher
trophic levels from May to January. After that, the zooplankton community was pause in both size and taxa fromJanuary to March (Fig. 6). Because of the low productivity
during this period (Kudo & Matsunaga 1999), low energy
transport to the higher trophic levels must occur duringthat period.
A special ﬁnding of this study is a signiﬁcant relationship was apparent between the slope and intercept of the
NBSS (Fig. 7). The spread of points across the graph especially for each of the three zooplankton groups varied fromeach other (Fig. 7). For group C, the spread was especiallybroad. This may partly be an artifact due to the numberof sample points (i.e. dates) being greatest for this group(9 of 21 dates). Slope-intercept combinations for Group C
appeared to be clustered into two temporal periods-earlydates with high primary productivity (11 April to 8 May)and the later period (12 May to 14 June). The Appendicularia-dominant early period is characterized by a highenergy transfer to higher trophic levels (e.g. mid-April).
After that, low energy transfer to higher trophic levels was
the norm for Group C. The NBSS values of Group A suggested low energy transfer throughout all periods they occurred. For zooplankton Group B, strong vertical mixing
in shallow Funka Bay in winter may prevent the initiationof a high primary productivity regime (Fig. 2). Under suchconditions, the dominant taxa were few in number and bio-

379

Seasonal zooplankton size and taxonomic community in Funka Bay

Table 2. Comparison of the slope (a) of normalised biomass size spectra (Y=aX + b) of the mesozooplankton community reported fromthe neighbouring waters of Japan, as obtained from the present study in Funka Bay, southwestern Hokkaido.
Location/region

Latitude (˚N)

Depth (m)Period (n)Mesh size(µm)

Instrument

Slope

References

Mombetsu (Southern Okhotsk Sea)

44°20′

0–8

Year-round (105)

335

OPC

−1.52 to −0.85

Hikichi et al. (2018)

Neighboring waters of Japan20°20′–45°20′

0–150

May–August (78)

335

OPC

−1.24 to −0.90

Sato et al. (2015)

North Paciﬁc (eight latitudinal transects)

35°00′–60°00′

0–150

May–August (1396)

335

OPC

−1.08 to −0.49

Shiota et al. (2013)

Central North Paciﬁc (180° latitudinal transect)

35°00′–51°00′

0–150

June (444)

335

OPC

−0.81 to −0.55

Fukuda et al. (2012)

NW Paciﬁc (three latitudinal transects)

35°00′–46°00′

0–150

July–August (86)

335

OPC

−0.75 to −0.42

Mishima et al. (2019)

Funka Bay

42°16′

0–87

Year-round (21)100

ZooScan−1.09 to −0.30

This study(n) indicates the number of samples examined. Note that diﬀerences in methodology (net mesh size and instrument) occurred. To make an adequate comparison with previous studies, we treated the same size range (0.35–5.00 mm) and applied the same size interval (every 0.05 mm)
for the calculation of NBSS in this study.

mass for zooplankton Group B. The low zooplankton taxa
and size ranges may have led to the lack of a signiﬁcant
NBSS for zooplankton Group B.
For a regional comparison, previously reported slopesof the NBSS based on the biovolume of zooplankton in
the seas around Japan and the subarctic Paciﬁc are summarised in Table 2. Several studies have compared seasonal changes in NBSS within the regions. The slope of
the NBSS at Mombetsu Harbour in the southern Okhotsk
Sea has been reported to be −0.85 to −1.1 during the period from January to April, while it increases to −1.31 to−1.52 during the period between May and December (Hikichi et al. 2018). The slope of the NBSS at 35–44°N alongthe 155°E line in the western Paciﬁc has been reported as−0.90 in May, steepening to −1.11 to −1.24 in July andAugust (Sato et al. 2015). These results indicate that theslope of the NBSS is ﬂat during the spring phytoplankton
bloom period but becomes steeper after summer. Such seasonally changing patterns in the NBSS slope correspondwith the results of this study in Funka Bay.
Regional patterns of NBSS slopes are ﬂat in the transitional region but steep in the subarctic and subtropicalregions, as has been reported for latitudinal transects in
the North Paciﬁc (Fukuda et al. 2012, Shiota et al. 2013).
Annually changing patterns in NBSS slopes have also
been reported for latitudinal transects in the western North
Paciﬁc (Mishima et al. 2019). Through comparison withthose reported values of NBSS slopes for the seas around
Japan and the subarctic Paciﬁc, the NBSS slopes in Funka
Bay are characterised as ﬂatter than previously reported
slopes. In particular, the ﬂattest slope of the NBSS observed in this study (−0.32) is beyond the range of otherstudies. This ﬂat slope is an indicator of high energy transfer eﬃciency to higher trophic level organisms (Sprules &Munawar 1986). This suggests that Funka Bay, located ina coastal area, has more eﬃcient energy transfer to higher
trophic level organisms than in oceanic regions.
While these ﬁndings are interesting, it should be notedthat the previous reports applied a diﬀerent methodology:
zooplankton samples were collected by a 335-µm meshsize net, and the biovolume data were quantiﬁed by OPC.
Since we collected zooplankton samples using a 100-µm

mesh size net and obtained imaging data by ZooScan, differences in methodology may have aﬀected the results.
However, we applied the same size ranges for analysing NBSS as in the previous studies (350 to 5000 µm).
Since we applied the same size ranges for the estimationof NBSS, the results obtained in this study should make acomparison possible with previous studies.
OPC is an instrument capable of counting and sizing
zooplankton and simultaneously measuring light attenuation (Herman 1988). Contrastingly ZooScan can capture
images of the zooplankton contained in the sample, andboth size and taxonomic information become analysable(Gorsky et al. 2010). Since ZooScan can also obtain taxonomic information from the samples, ZooScan may besuperior to OPC. However, during the mounting of zooplankton on the ZooScan frame, the spreading of fragile zooplankton bodies (e.g., jellyﬁshes) may lead to an
overestimate of their biovolume (Naito et al. 2019). Additionally, the accuracy of OPC data is compromised bycontamination from the non-living fraction (e.g. detritus),and size underestimations may occur for taxa with slenderbodies (e.g. Chaetognatha) or with transparent bodies (e.g.
jellyﬁshes) (Yokoi et al. 2008). In the future, considering
these characteristics of optical and imaging instruments, itwill be necessary to accumulate information on zooplankton size and structure in various locations and obtain general patterns for the geographical and seasonal changes inzooplankton size structure to clarify the factors that aﬀect
zooplankton size and composition.
Acknowledgements
We thank the captains, oﬃcers, crews, and researchers
onboard the T/S Ushio-Maru, Hokkaido University, fortheir great eﬀorts during the ﬁeld sampling. This work
was supported by the Arctic Challenge for Sustainability
II (ArCS II) Program (Grant Number JPMXD1420318865);
the Environment Research and Technology Development
Fund (JPMEERF20214002) of the Environmental Restoration and Conservation Agency of Japan; and Grants-inAid for Challenging Research (Pioneering) (JP20K20573)
and Scientiﬁc Research (JP22H00374 (A), JP21H02263

380

T. Teraoka et al.

(B), JP20H03054 (B), JP19H03037 (B), and JP17H01483(A)) from the Japan Society for the Promotion of Science(JSPS).
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