Deep-Sea Research II 107 (2014) 22–28

Contents lists available at ScienceDirect

Deep-Sea Research II
journal homepage: www.elsevier.com/locate/dsr2

Distribution of sei whales (Balaenoptera borealis)in the subarctic–subtropical transition areaof the western North Paciﬁc in relation to oceanic fronts
Hiroto Murase a,n, Takashi Hakamada b, Koji Matsuoka b, Shigetoshi Nishiwaki b,
Denzo Inagake c, Makoto Okazaki c, Naoki Tojo d, Toshihide Kitakado eaNational Research Institute of Far Seas Fisheries, 2-12-4 Fukuura, Kanazawa, Yokohama, Kanagawa 236-8648, JapanThe Institute of Cetacean Research, 4-5 Toyomi-cho, Chuo-ku, Tokyo 104-0055, Japan
National Research Institute of Fisheries Science, 2-12-4 Fukuura, Kanazawa, Yokohama, Kanagawa 236-8648, Japand
JICA expert of ecosystem monitoring and project, c/o Institut National de Recherche Halieutique, 2, Rue Tiznit, Casablanca 20030, MoroccoeTokyo University of Marine Science and Technology, 4-5-7 Konan, Minato-ku, Tokyo 108-8477, Japanbcar t ic l e i nf o

a b s t r a c t

Available online 22 May 2014

The subarctic–subtropical transition area of the western North Paciﬁc is an important summer feeding
grounds of sei whales. The oceanographic structure and circulation of this area are largely determined bystrong oceanic fronts and associated geostrophic currents, namely the Polar Front (PF), Subarctic Front(SAF) and Kuroshio Extension Front (KEF). The relationship between the distribution of sei whales andoceanographic fronts was investigated using a generalized additive model (GAM), and the cetaceansighting survey data and oceanographic observations in July from 2000 to 2007 were used in theanalysis. The number of individual sei whales was used as the response variable while the distances fromthe PF, SAF, and KEF to the whales were used as explanatory variables along with the longitude values.
Sei whales were concentrated north and south of the SAF and the areas from 250 to 300 km north andfrom 100 to 200 km south of the SAF were estimated as high-density areas of sei whales. The entire
inter-frontal zone between the PF and SAF featured an elevated concentration of sei whales, and the area
south of the PF and along the SAF was identiﬁed as an important feeding ground of sei whales in Julyfrom 2000 to 2007.
& 2014 Elsevier Ltd. All rights reserved.

Keywords:
Baleen whale
Cetacean
HabitatOcean front
Oceanography
Kuroshio Extension Front
Kuroshio Bifurcation Front
Subarctic Front
Polar Front

1. Introduction
An ocean front can be deﬁned as a relatively narrow zone ofenhanced horizontal gradients of physical, chemical and biologicalproperties that separates broader areas of different vertical structures occurring at a variety of dimensional (hundreds of meters tothousands of kilometers) and time (short lived to year round)scales (Belkin et al., 2002). Many studies have quantitatively
investigated the relationship between the spatial distribution ofbaleen whales and ocean fronts with the expectation that cetaceans were attracted to ocean fronts with high biological productivity to search for prey. Simultaneous recordings of the spatial
distributions of baleen whales and their prey have been attempted(Murase et al., 2002; Tynan et al., 2005; Friedlaender et al., 2006;
Laidre et al., 2010; Santora et al., 2010; Friedlaender et al., 2011;
Skern-Mauritzen et al., 2011; Murase et al., 2013). However,nCorresponding author. Tel.: þ 81 45 788 7514; fax: þ 81 45 788 5004.
E-mail address: muraseh@affrc.go.jp (H. Murase).

http://dx.doi.org/10.1016/j.dsr2.2014.05.002
0967-0645/& 2014 Elsevier Ltd. All rights reserved.

because such a practice faces logistical challenges, ocean fronts
are used in other studies as indicators of the presence of prey. The
relationship between the spatial distribution of baleen whales andsea surface thermal fronts detected by satellite remote sensing
data (generally up to 10 km grid cell resolution) were widely
investigated and included ﬁn (Balaenoptera physalus), minke(Balaenoptera acutorostrata) and humpback whales (Megaptera
novaeangliae) in the mid-western North Atlantic Ocean (Hamazaki,2002), blue (Balaenoptera musculus), ﬁn, humpback and minke
whales in the Gulf of St. Lawrence (Doniol-Valcroze et al., 2007),
blue whales off the Baja California Peninsula (Etnoyer et al., 2006),
ﬁn whales in the Mediterranean Sea (Cotté et al., 2011; Druon et al.,2012) and humpback whales in the coastal waters of British
Columbia and adjacent areas (Dalla Rosa et al., 2012). The relationship with coastal upwelling fronts was also investigated andincluded humpback whales in the northern California Current
System (Tynan et al., 2005) and bowhead whales (Balaena mysticetus)
off Alaska (Okkonen et al., 2011). The relationship between the spatial
distribution of grey whales (Eschrichtius robustus) and in-situ
measured fronts was investigated in the south-central Chukchi Sea

H. Murase et al. / Deep-Sea Research II 107 (2014) 22–28

23

Fig. 1. The survey area (thin black line), surveyed tracklines (gray line) and sighting positions of sei whales (orange circle) from 2000 to 2007 (A). The mean sea surface
chlorophyll a (Chl-a) concentrations in July from 2000 to 2007 (B). The locations of three major oceanic fronts – the Polar Front (PF), Subarctic Front (SAF) and Kuroshio
Extension Front (KEF) – and the subarctic–subtropical transition zone are shown in (A) and (B). The Level 3 monthly mean Chl-a data (4 km resolution) obtained by SeaWiFS(Feldman and McClain, 2008) were used in (B).

(Bluhm et al., 2007). However, quantitative investigations of therelationship between the spatial distribution of baleen whales andbasin scale oceanic fronts have rarely been conducted except in theSouthern Ocean (Bost et al., 2009; Ainley et al., 2012; Santora and Veit,
2013).
In the Northwest Paciﬁc Ocean east of Japan, three major
oceanic fronts have been known for a long time: the Polar Front(PF), Subarctic Front (SAF), and Kuroshio Extension Front (KEF)(Science Council of Japan, 1960). This pattern has been conﬁrmed
by numerous studies (Kitano, 1972; Roden et al., 1982; Belkin and
Mikhailichenko, 1986; Miyake, 1989; Belkin et al., 1992; Yoshida,
1993; Onishi, 2001; Belkin et al., 2002; Shotwell et al., 2014)(Fig. 1). The KEF tends to bifurcate in the vicinity of the Shatsky
Rise, which is located at approximately 351N and 1601E; its
northern branch (sometimes called the Secondary Kuroshio Front,
SKF) extends to approximately 401N, where it joins the SAF. The
SKF was noted in earlier studies as being related to the SAF (Kawai,
1972; Roden et al., 1982; Mizuno and White, 1983; Yoshida, 1993).
Therefore, at least two bifurcations of the Kuroshio front havebeen reported: one at a short distance east of Japan (west of 1501E)
and another upstream of the Shatsky Rise (at approximately
1551E) and the term “Kuroshio Bifurcation front (KBF)” is ambivalent and not used in this paper.
The area between the PF and KEF is called the subarctic–
subtropical transition (interfrontal) area of the western North
Paciﬁc and is also called the Kuroshio–Oyashio transition area.
The nutrients supplied by cyclonic eddies in the transition area
support high primary production and high secondary production(Olson, 2001; Yatsu et al., 2013; also see Fig. 1). Small pelagic ﬁsh
species such as the Japanese sardine (Sardinops melanostictus) andanchovy (Engraulis japonicas) in the transition area (Murase et al.,2012) are transported from the spawning ground on the coastalside of the Kuroshio by the Kuroshio extension (Itoh et al., 2009).
Piscivore species such as skipjack tuna (Katsuwonus pelamis)(Nihira, 1996) and baleen whales (Murase et al., 2007) feed on
the small pelagic ﬁsh in the area and a wide variety of species are
distributed in the area (Pearcy et al., 1996).
Sei whales (Balaenoptera borealis) are the third largest baleen
whales and typically reach 15 m of body length, weigh 20 t and are
distributed in temperate and high-latitude oceanic waters of bothhemispheres (Horwood, 1987; Horwood et al., 2009). In thewestern North Paciﬁc, previous feeding ecology studies using
stomach contents obtained by commercial whaling indicated thatsei whales utilized the subarctic–subtropical transition area as
their feeding grounds in the summer (Mizue, 1951; Nemoto, 1957;
Kawamura, 1982). The distribution of commercial catch positionsof sei whales in relation to the sea surface temperature (SST) fronts
off the coast of Japan were also studied qualitatively (Uda, 1954;
Uda and Dairokuno, 1957; Uda and Suzuki, 1958; Nasu, 1966). The

commercial harvesting of sei whales has been banned since 1976.
The initial population level of sei whales in the North Paciﬁc wasestimated to be between 58,000 and 82,000 individuals (Ohsumi
et al., 1971). These whales have been heavily exploited by commercial harvesting, and the population was depleted to 8,600
individuals in 1974 (Tilman, 1977). An assessment of the population has not been conducted since then. Studies on sei whales haverarely been conducted since the ban of commercial whaling
because of data scarcity (Prieto et al., 2012).
Recently, results of studies on sei whales using data obtainedby the second phase of the Japanese Whale Research Program
under Special Permit in the western North Paciﬁc (JARPNII) from2000 to present have been reported. The survey area of JARPNII islocated in the transition area. Konishi et al. (2009) and Watanabe
et al. (2012) reported that sei whales mainly fed on euphausiids,
copepods, and Japanese anchovy in the survey area. The distribution of sei whales in the survey area in relation to environmental
variables that are derived from satellite remote sensing data suchas the SST, chlorophyll-a concentration (Chl-a) and sea surface
height anomaly (SSHa), and the depth were also investigated bya generalized linear model (GLM). The results suggested that theorder of effective variables for the distribution of sei whales were
SST, SSHa, Chl-a (Sasaki et al., 2013). The study reported that sei
whales were distributed in an interquartile range of 13.1–16.8 1C
with a mean value of 15.5 1C. The results of canonical a correspondence analysis (CCA) analysis indicated that SST was one of
the most signiﬁcant variables for describing the distribution of sei
whales (Konishi et al., 2009).
The relationship between the spatial distribution of sei whales
and oceanographic conditions was also quantitatively investigated inother regions of the world. Long-term surface temperature data
were used as a covariate in a GLM to predict the habitat of sei whalesin the waters of coastal British Columbia (Gregr and Trites, 2001).
Although temperature was selected in the model, the explicit
relationship was not mentioned in the paper. The spatial distributionof sei whales at small scale (1–20 km2) along the Mid-Atlantic Ridge
was related to the ocean ﬂow gradients interacting with the steep
topography (Skov et al., 2008), and a PLS regression and Ecological
Niche Factor Analysis (ENFA) were used in the analysis. To date,however, the relationship between the distribution of sei whales andbasin scale oceanic fronts has not been studied quantitatively.
In this paper, the current distribution of sei whales in thewestern North Paciﬁc in relation to basin scale oceanic fronts isstudied quantitatively. Speciﬁcally, the relationship between thenumber of sei whales and their distance to three subsurface fronts,
the PF, SAF and KEF, is investigated by using a generalized additivemodel (GAM). Because the GAM is a non-parametric, regression
technique not restricted by linear relationships, it is ﬂexible
enough to model relationships between the spatial distribution

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H. Murase et al. / Deep-Sea Research II 107 (2014) 22–28

of biological organisms and variables describing their environments (Murase et al., 2009).
The spatiotemporal scale of the feeding ecology of cetaceans
can be deﬁned as follows: at the macro scale, cetaceans migrateseasonally (months) between feeding and breeding grounds(4 1,000km); at the meso scale, cetaceans move over days andweeks in search of a preferred local (4 100 km) abundance offood; at the micro scale, whales dive and search for food within
localized areas ( 410 km) within hours (IWC, 2003) and at thenano scale, whales attack a prey patch in their proximity withinminutes. The focus of this paper is from the macro to meso scales.

2. Materials and methods
2.1. Cetacean sighting survey data
The cetacean sighting surveys were conducted in the western
North Paciﬁc in July from 2000 to 2007 as part of JARPNII (Fig. 1).
The southern, northern, eastern and western boundaries of thesurvey area were 351N, the boundary of the economic exclusive
zone (EEZ) claimed by countries other than Japan, 1701E and theeastern coast line of Japan, respectively. Six survey vessels were
engaged in the cetacean sighting surveys from 2000 to 2007 andtheir speciﬁcations were similar. Their gross tonnages wereapproximately 1,000 GT with two main observation platforms:
top barrels were set at 20 m above the sea surface and upper
bridges were set at 10 m above the sea surface. Three observers at
each observation platform using 7  50 binoculars were engaged
in the sighting surveys. Sightings within 5.6 km ( E3 nautical
miles, nm) from the survey tracklines were counted. The survey
vessels steamed at 19.5 km/h (E10.5 knots) along the survey
tracklines during the survey hours and the survey was conductedduring the daytime from 1 h after sunrise to 1 h before sunset.
Surveying was stopped when the visibility was o 3.7 km (E2 nm)
and/or sea state 44 on the Beaufort wind force scale.
Activities aboard the ship were classiﬁed into two categories:
on-effort and off-effort. On-effort activities were times when a fullsearch effort was executed within acceptable conditions to conduct research. Off-effort activities were all times that were not oneffort and were not used in the analysis. All sightings recorded
during on-effort activities were classiﬁed as primary-sightings. Allother sightings were considered secondary sightings. On-effort
surveys were conducted in the closing and passing mode; thesurvey vessels approached all sightings during the closing-mode
to conﬁrm the species and number of individuals in a school, andall sightings during the passing-mode were not approachedalthough the species and estimated number of individuals in aschool were recorded. As single year survey could not cover theentire survey area, so the data collected during on-effort activities
in July from 2000 to 2007 were pooled in the analysis.
2.2. Oceanographic data
The subsurface water temperature and salinity data wereobtained by conductivity-temperature-depth (CTD) proﬁlers(CTD), expendable CTD (XCTD) and the Argo proﬁling ﬂoats. The
CTD (SBE-19, Sea-Bird Electronics, USA) and XCTD (Tsurumi Seiki
Co., Japan) data were obtained at 158 and 10 stations, respectively,in the JARPNII survey area from 2001 to 2007. The data from theArgo proﬁling ﬂoats that were prepared by Oka et al. (2007) andobtained at 3,913 locations north of 301N from 2001 and 2007
were used. The data from 2001 to 2007 were pooled in theanalysis because the oceanographic observations in a single year
could not cover the entire survey area. The PF is deﬁned as a 4 1C
isotherm at 100 m depth (Favorite et al., 1976), the SAF is deﬁned

as a 6 1C isotherm at 300 m depth (Mizuno and White, 1983), andthe KEF is deﬁned as a 14 1C isotherm at 200 m depth (Kawai,1969). To locate the positions of the PF, SAF and KEF, watertemperature maps at 100, 200 and 300 m depths were estimatedby ordinary kriging with the aid of the geographic information
system (GIS), ArcGIS 10.1 (ESRI, USA).
2.3. Modeling the relationships between whales and oceanic fronts
The relationship between the density of sei whales anddistance from the oceanic fronts was investigated on a
30  30 km grid cell. The nearest distance from the oceanic fronts
to the center of each grid cell within the survey area wascalculated by using the “Near” tool of ArcGIS. The distance wasa positive value if the grid cells were located north of the fronts
and negative if the cells were located to south. Distances from theoceanic fronts to each grid cell were used as explanatory variablesin the model. Longitude was also used as an explanatory variable
under the premise that the oceanic fronts might not capture thelongitudinal heterogeneity of the distribution of whales because
they were located in a direction parallel with the lines of latitude.
The number of individual sei whales in each 30  30 km gridcell was used as a response variable, and the following procedures
were conducted to estimate the number of individuals. Sighting
effort data were divided ﬁrst into 1 km segments, and then thesesegments were pooled in each grid cell (d). Schools of sei whales
were also pooled in each grid cell (n). To estimate the number ofsei whales in each grid cell, the effective search width (esw) andmean school size (E(s)) were estimated based on the multiplecovariate distance sampling method (Thomas et al., 2010). The esw
and E(s) were estimated for the entire area (not just in each cell)using all sighting data because a sufﬁcient number of sightings(e.g., more than 15 sightings) were generally required to obtainreliable estimates (Branch and Butterworth, 2001). A hazard rate
model with no adjustment terms was used as a detection function
model in the method. The surveyed years and the vessels wereused as the covariates. It was assumed that the probability ofdetection of whales on the track line was 1 (g(0)¼ 1). Doubleplatform line transect data are widely used to estimate g(0) of
whales (Okamura et al., 2003). However, because no such data
were collected during the survey, the estimation of g(0) could not
be carried out. It was reported that g(0) of Bryde’s (Balaenoptera
edeni) and sei whales in the California Current ecosystem was
0.921 (Barlow and Forney, 2007). Therefore, the g(0) in this study
could also be less than 1, but the effect on the estimated number ofsei whales was not substantial. The number of individuals in a gridcell was ﬁrst calculated by the density (n  E(s))/(d  2  esw), andthen it was multiplied by area of a grid cell.
The relationship between the spatial distribution of sei whales
and, the studied oceanographic fronts and longitude was modeledusing GAM having a Tweedie error distribution with a logarithmic
link function, which was similar to the method used by Williams
et al. (2011). A Tweedie random variable with 1 op o2 is a sum of
N gamma random variables in which N has a Poisson distribution(Wood, 2013). If p equals 1, then it is a generalization of a Poisson
distribution and a discrete distribution supported on integer
multiples of the scale parameter. If p is larger than 1 and smaller
than 2 (1 op o2), then the distribution is supported on thepositive reals with a point mass at zero. If p equals 2, then it isa gamma distribution. In this analysis, p is set as 1.1. The smoothness parameters were estimated with the generalized crossvalidation (GCV). For this analysis, the mgcv package (Wood,2006) version 1.7–26 of the R software version 3.0.2 (RDevelopment Core Team, 2013) was used. The shapes of thefunctional forms for the all covariates were also plotted by using
the package. When the slopes of the functional forms wereH. Murase et al. / Deep-Sea Research II 107 (2014) 22–28

positive, the covariates were related positively to the response
variable, and vice versa. Collinearity among explanatory variablesin the model could lead to the wrong identiﬁcation of relevant
predictors (Dormann et al., 2012). The collinearity was investigated by the variance inﬂated factor (VIF) using AED package (Zuuret al., 2009) working under R software version 2.15.0.

3. Results
A total of 483 schools of sei whales during 56,450 km ofsighting efforts recorded from 2000 to 2007 were used in theanalysis. The number of grid cells used in the GAM was 1,441. The
esw and E(s) were estimated as 3.39 km (≈1.83 nm) and 1.83
individuals, respectively. The values of VIF and results of the GAM
modeling are shown in Table 1. The collinearly among explanatory
variables was considered minimal because the values of VIF wereless than 10, although no speciﬁc rule to determine an acceptablelevel of collinearity based on the VIF has been reported. The
approximate signiﬁcance levels suggested that all covariates in themodel were signiﬁcant and had p-values lower than 0.01.

25

The shape of the functional response forms for the longitude
indicated that the number of sei whales was low in the westernpart of the survey area (Fig. 2). The shape was relatively ﬂat east of1501E, except in a small depression at approximately 1601E. The
shape of the functional response form for the distance from the PF
indicated that the number of sei whales decreased from the south
to north of the PF. The shape of the functional response form forthe distance from the SAF indicated that the number of sei whales
increased from the south to north of the SAF, with a small peak tothe south at approximately 200 km from the SAF. The shape of thefunctional response form for the distance from the KEF indicatedthat the number of sei whales increased to north of the KEF. These
results suggested that the number of sei whales was high in thearea south of the PF and along the SAF west of 1501E. The results
clearly depicted in the map of estimated spatial distributions of
the sei whales using the model (Fig. 3). Speciﬁcally, the estimatednumber of sei whales was high in the areas from 250 to 300 km

Table 1Results of a generalized additive model (GAM) to detect the relationship between
the spatial distribution of sei whales and distance from oceanic fronts (PF ¼Polar
Front, SAF¼ Subarctic Front and KEF ¼ Kuroshio Extension Front) and longitude. The
approximate signiﬁcance levels (p-value), F statistics (F) and estimated degrees of
freedom (edf) are shown for each of the explanatory variables. The values of thevariance inﬂated factor (VIF) for each explanatory variable are also shown.
FamilyTweedie

Link function
Adjusted R2
Deviance explained (%)
GCV score

Log
0.09
44.9%
12.85
edf

F

p-Value

VIF

7.18
8.61
6.84
7.62

17.20
21.76
4.82
10.06

o 0.01o 0.01o 0.01o 0.01

3.16
4.34
4.54
7.82

Explanatory variables
Longitude
Distance from PF
Distance from SAF
Distance from KEF

Fig. 3. The estimated distribution patterns of the number of individual sei whales
obtained by using a generalized additive model (GAM). The locations of the Polar Front(PF), Subarctic Front (SAF) and Kuroshio Extension Front (KEF) are also shown.

Fig. 2. Smoothed ﬁts of selected covariates modeling the number of individuals of sei whales Tick marks on the x-axis are the observed data points. The y-axis represents thecontribution of the smoother to the ﬁtted values, and shaded areas indicate the 95% conﬁdence bounds. PF¼ Polar Front, SAF¼Subarctic Front and KEF¼Kuroshio Extension Front.

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H. Murase et al. / Deep-Sea Research II 107 (2014) 22–28

Fig. 4. The estimated number of individual sei whales in relation to the distancefrom the Subarctic Front (SAF).

north and 100 to 200 km south of the SAF (Fig. 4). Few sei whales
were sighted north of the PF and west of the SAF.

4. Discussion
This study revealed that the area south of the PF and along the
SAF were important distribution areas of sei whales in the western
North Paciﬁc in July from 2000 to 2007. It was qualitatively
reported that the distribution of sei whales and the sub-polar
front (SPF) were related along the Mid-Atlantic Ridge (Skov et al.,2008). Similar relationships between baleen whales and oceanic
fronts were reported in the Southern Ocean (Bost et al., 2009;
Ainley et al., 2012; Santora and Veit, 2013). However, this is theﬁrst study that reports quantitative relationship between baleen
whales and the basin scale oceanic fronts of the North Paciﬁc.
Interestingly, the abundance of sei whales was low near the SAF(i.e., within 100 km from the SAF), and a high abundance wasobserved in the areas from 250 to 300 km north and 100 to
200 km south of the SAF. We conducted the same analysis at thescale of a 10  10 km grid cell and observed almost the same
bimodal distribution pattern (not shown). The distribution pattern
did not appear to be sensitive to the scale of the grid cells. It can be
hypothesized that the bimodal distribution of sei whales along the
SAF was linked to the distribution of their prey species. A study on
the feeding ecology of sei whales that was conducted in the same
area and time period (2000–2007) as this paper suggested that
their main prey were copepods (Neocalanus spp.), euphausiids andJapanese anchovy and suggested that sei whales fed on Japanese
anchovy in the western part of the survey area where the SST was
higher and on copepods in the eastern part where the SST waslower (Konishi et al., 2009). Japanese anchovy spawn along thecoastal side of the Kuroshio in spring and summer and the eggs
and larvae are transported to the transition area by the Kuroshio
extension (Aoki and Miyashita, 2000; Itoh et al., 2009), although it
has been reported that Japanese anchovy also spawn offshore(Funamoto and Aoki, 2002). In contrast, high densities of krill(Euphausia paciﬁca) (Tojo et al., 2010) and Neocalanus spp. (Kobari,1999) were observed south of the PF. Two high density areas of sei
whales north and south of the SAF could reﬂect the distribution of
their prey species. Although a high abundance of sei whales wasobserved bimodally across the SAF, their distribution was continuous. The result of the satellite tracking of a sei whale in the North
Atlantic showed that the mean travelled distance per day was
90 km (Olsen et al., 2009) indicating that sei whales could move
between the bimodal distribution areas within a few days.
Furthermore, a study of the genetic characteristics of sei whales

conducted in the same area and within the same period of
this paper showed that a single population of sei whales inhabited
the western North Paciﬁc (Kanda et al., 2006). These results
precluded that the bimodal distribution of sei whales observedin this study could result from the existence of two distinct
populations.
Both climatic and biological regime shifts have occurred in the
North Paciﬁc Ocean (Hare, 2000; Yatsu et al., 2001; Mantua, 2004;
Overland et al., 2008). The relationship between the distribution ofsei whales and oceanic fronts was investigated in this paper byusing pooled data from 2000 to 2007. A regime shift was notreported as occurring during this period; therefore, the results ofthis paper can be considered fairly representative of the state of
the ocean during this time at the macro to meso scale. However, it
is obvious that the analysis overlooked the spatiotemporal relationship at the micro to nano scale. Furthermore, environmental
factors other than distances from the oceanic fronts were notconsidered in this paper according to the editorial policy of thisspecial issue. The observed bimodal distribution of the highabundance of sei whales across the SAF might reﬂect a year toyear change of their environment at the micro and nano scales.
Energetic jets (streamers) (Isoguchi et al., 2006) and meso scaleeddies (Itoh and Yasuda, 2009) associated with the oceanic fronts
in the transition area were reported. Sasaki et al. (2013) found thatthe spatial distribution of sei whales in the western North Paciﬁc
was related to the SST, Chl-a and SSHa at the 4 km grid cellresolution using monthly mean satellite remote sensing data. It
was also well documented that the distribution of other baleen
whale species were associated with meso to micro scale SST fronts(Hamazaki, 2002; Tynan et al., 2005; Doniol-Valcroze et al., 2007;
Cotté et al., 2011; Dalla Rosa et al., 2012; Druon et al., 2012).
A satellite tagging study of one sei whale indicated that its
movement at the micro scale was associated with surface current
patterns in the North Atlantic (Olsen et al., 2009). It was also
reported that the distribution of sei whales was related to micro
scale (1 to 20 km) frontal processes (Skov et al., 2008). The
distribution of the prey of sei whales might be related to suchmeso to macro scale oceanographic conditions. For instance, therelationship between the vocalization rate of sei whales andvertical migration of coped were reported in the southwestern
Gulf of Maine at a scale of 10 km (Baumgartner and Fratantoni,2008). The inclusion of prey data as an explanatory variable of themodel might produce more insight into the spatial prey-predator
relationship at the meso to micro scale. No nano scale behavior ofsei whales has been reported. The observation of nano scale
behavior of sei whales in relation to their environment using adata logger such as a high-resolution digital tag (Goldbogen et al.,2008) is warranted, and the integration of studies from the macro
to nano scales is required to understand the detailed processes
involved in the spatial distribution of sei whales.
In the past, the main whaling grounds of sei whales werelocated north of the survey area studied in this paper. In particular,
high densities of sei whales were observed south of the AleutianIslands and Gulf of Alaska (Masaki, 1977). The whaling grounds
were in the Alaska and Subarctic Current System. Stomach contents analysis of commercially harvested animals revealed thatsei whales mainly fed on copepods (Neocalanus plumchrus andNeocalanus cristatus) (Nemoto and Kawamura, 1977). It wassuggested that the spatial distribution of copepods around the
Aleutian Islands were linked to the Alaska Coastal Current andAlaska Stream (Coyle, 2005). The spatial distribution of sei whales
south and north of the PF might be different because of thedifferent oceanographic structures and circulations on the opposite sides of this front. The distribution patterns of sei whales
north of the PF should be studied in the future and compared withthe results of this paper.

H. Murase et al. / Deep-Sea Research II 107 (2014) 22–28

5. Conclusion
The spatial distribution of sei whales in the subarctic–subtropical transition area of the western North Paciﬁc was associatedwith three oceanic fronts (PF, SAF and KEF), and the whales wereconcentrated north and south of the SAF. The basin scale oceanic
fronts can be considered indicators of their feeding ground at themacro to meso scale. It was reported that energetic jets (streamers) and meso scale eddies associated with these fronts wereobserved in the feeding ground. It can be assumed that the whales
search for their prey using these oceanographic conditions at themeso to macro scale and then ﬁnally attack the prey at the nanoscale. Further study should be designed to capture the linkage
among these scales. An integration of data of oceanography,
whales and their prey will enhance our understanding of theecology of whales.

Acknowledgements
The authors express their thanks to the crews and researchers
who participated in the surveys to collect these valuable data. We
thank Dr. Igor Belkin for his kind invitation to submit our manuscript to this special issue “Fronts, Fish, and Top Predators.” He also
provided us the deﬁnitions of the oceanic fronts used in the paper.
Drs. Igor Belkin and Rui Prieto as well as four other reviewers
provided thoughtful comments to improve our manuscript. The
study was supported by the Fisheries Agency of Japan, the Fisheries Research Agency of Japan and the Institute of Cetacean
Research. We thank these institutions for their support.
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