Technical Reports of the Institute of Cetacean Research (2017)

pp. 37–43

Technical Report (not peer reviewed)

Distribution and movement of ʻOʼ and ʻJʼ stock common minke whales
in waters around Japan based on genetic assignment methods
Mutsuo Goto*, Mioko Taguchi and Luis A. Pastene
Institute of Cetacean Research, 4–5 Toyomi-cho, Chuo-ku, Tokyo 104–0055, Japan*Contact e-mail: goto@cetacean.jp

ABSTRACT
A total of 4,275 western North Paciﬁc common minke whales were examined with a set of 16 microsatellite
DNA loci and the program STRUCTURE to assign individuals to either O or J stocks. Samples were available
from JARPN/JARPNII (1994–2014; n=2,637), and by-catches (2001–2014; n=1,638), from waters around
Japan. Results of the Bayesian clustering analysis conﬁrmed that the whales came from two genetically differentiated stocks, O and J stocks. By using 16 loci, more than 90% of the individual whales were assigned toeither stock. Almost all of the individuals collected from the Sea of Japan side belonged to the J stock, whereas
almost all of the individuals from the oﬀshore North Paciﬁc belonged to the O stock. Intermediate areas contained individuals from both stocks. The southern part of the Paciﬁc side of Japan was mainly occupied by the
J stock, which predominated (around 80% in proportion) throughout the year. In the north part of the Paciﬁcside of Japan the proportion of the J stock animals increased in autumn/winter and decreased in spring/summer, and the O stock showed a reverse pattern.

INTRODUCTION
In the western North Paciﬁc at least two biological stocksof common minke whales Balaenoptera acutorostrata
are known to exist: the Okhotsk Sea-West Paciﬁc (Ostock) and the Sea of Japan-Yellow Sea-East China Sea (Jstock) (Omura and Sakiura, 1956; Ohsumi, 1977; 1983).
The two stocks are diﬀerentiated in morphological andreproductive characters (Omura and Sakiura, 1956;
Ohsumi, 1977; Kato, 1992), as well in genetics (Wada andNumachi, 1991 for allozymes; Goto and Pastene, 1997 for
mtDNA; and Kanda et al., 2009a; b for microsatellites),suggesting their reproductive isolation. The International
Whaling Commission (IWC) had proposed some boundaries for these stocks (Donovan, 1991, Figure 1).
Previous genetic studies showed that both stocks mix
with each other spatially and temporally in the southernpart of the Okhotsk Sea (northern Hokkaido) (Wada,
1991; Pastene et al., 1998). Since then, a substantial number of genetic samples of western North Paciﬁc common
minke whale became available, and modern and more
powerful genetic markers became available in recent
years. The application of such markers to the new samples made ﬁner studies of stock structure of this species
possible for this ocean basin (Pastene et al., 2016a; b).
There are several analytical approaches for estimating

Figure 1.

Historical IWC stock boundaries of western North
Paciﬁc common minke whale (Donovan, 1991).

the mixing proportion in areas where two or more stocks
overlap, based on genetic data. One of those is the frequency-based approach (e.g. Pastene et al., 1998). Under
this method the allele or haplotype frequency distribution for regions where only a single stock is considered to
be present is determined ﬁrst (ʻpure stockʼ frequencies).
Then the proportion of each stock is estimated in overlap
37Technical Reports of the Institute of Cetacean Research (2017)

areas by Maximum Likelihood Methods. The other is theindividual assignment-based approach, which does notneed ʻpure stockʼ assumptions and is based on minimizing departures from Hardy-Weinberg equilibrium (e.g.
Pritchard et al., 2000).
The objective of this study was to gain further understanding of the spatial and temporal distribution of the O
and J stocks around Japan by using an individual assignment-based approach on the large number of genetic
samples of this species collected in waters around Japan.

MATERIALS AND METHODS
Sample collections
To describe the distribution and movement of stocks atotal of six Areas were deﬁned for waters around Japan:
Areas A=southern part of the Okhotsk Sea; Ba=coastal in
the Paciﬁc side oﬀ Hokkaido; Bb=coastal in the northernpart of the Paciﬁc side of Japan; C=oﬀshore Area in the
Paciﬁc side; D=coastal in the southern part of the Paciﬁcside of Japan; and E=coastal Area in the Sea of Japan side
(Figure 2). Sample sizes used in this study are shown in
Table 1, by Area.
Oﬀshore samples were from the Japanese Whale
Research Program under Special Permit in the western
North Paciﬁc (JARPN/JARPNII) surveys from 1994 to 2013
in Areas A, Ba, Bb and C. Common minke whale samples
obtained from the coastal JARPNII survey between 2002
and 2014 were also used in this study, Kushiro in Area Ba
and Sanriku in Area Bb. Samples from bycaught whales in
set net ﬁsheries along the Japanese coast from 2001 to2014 were also used. The bycatches were from Areas A,
Ba, Bb, D and E year-round.

Figure 2.
38

DNA extraction
The IWC guidelines for DNA data quality (IWC, 2009) were
followed as much as possible (see Kanda et al., 2014).
Genomic DNA was extracted from 0.05 g of skin or muscle
tissues using standard proteinase K, phenol-chloroform
procedure described by Sambrook et al. (1989) or using
Gentra Puregene kits (QIAGEN). Extracted DNA was stored
in the TE buﬀer (10 mM Tris-HCl, 1 mM EDTA, pH 8.0).
Microsatellites
Microsatellite polymorphisms were analyzed using
16 loci: EV1, EV14, EV21, EV37, EV94, (Valsecchi andAmos, 1996), GT23, GT195, GT211, GT310, GT509, GT575(Bérubé et al., 2000), GATA28, GATA98, GATA417, TAA31(Palsbøll et al., 1997), DlrFCB14 (Buchanan et al., 1996).
EV1, EV14, EV21 were developed from sperm whale,
EV37, EV94, GT23, GT310, GT575, GATA28, GATA98,
GATA417, TAA31 from humpback whale, and DlrFCB14
from beluga whale. All GT, EV and DlrFCB primers are
Table 1
Sample size used in this study, by Area.
Area

Number of samples

A
Ba
Bb
C
D
E

128
1066
921
942
535
683

Total

4275

Geographical location of each Area deﬁned for this study.

Distribution and movement of ʻOʼ and ʻJʼ stock common minke whales in waters around Japan based on genetic assignment methods

dinucleotide repeats, TAA31 trinucleotide repeats, and all
GATA primers tetranucleotide repeats. Primer sequences
and PCR proﬁles follows those of the original authors
with slight modiﬁcations.
PCR ampliﬁcations were performed in 15 µl reaction
mixtures containing 10–100 ng of DNA, 5 pmole of eachprimer, 0.625 units of Ex Taq DNA polymerase (Takara
Shuzo), and 2 mM of each dNTP, and 10x reaction buﬀer
containing 20 mM MgCl2 (Takara Shuzo). PCR ampliﬁcations followed the manufacturerʼs instructions for theuse of Ex Taq DNA polymerase (Takara Shuzo). Ampliﬁed
products with internal size standard (GENESCAN400HD,
Applied Biosystems Japan) were run on a 6% polyacrylamide denaturating gel (Long Ranger™) using a
BaseStation TM100 DNA fragment analyzer (Bio-Rad) or
were electrophoresed on an Applied Biosystems 3500
Genetic Analyzer. Allele sizes were determined using a
600 LIZ size standard and GeneMapper v. 5.0 (ABI).
Data analysis
The Bayesian clustering approach was implemented withthe microsatellite data in the program STRUCTURE version
2.0 (Pritchard et al., 2000) to determine the most likely
number of genetically distinct stocks present in our samples. The program is a model-based clustering method for
inferring stock structure (K, the number of stocks in themodel) using multilocus genotype data with and without
information on sampling locations. STRUCTURE allowed
for the analyses of the samples without choosing sample
units that did not necessarily correspond to real biologicalstock boundaries. A conceptual diagram of individual assignment under STRUCTURE is shown in Figure 3.
Posterior probabilities for K were estimated from ten
independent runs for each value of K from one to ﬁvewith only genetic information. These data were calculated based on burn-in period of 10,000 iterations and runsof 100,000 iterations. Individual assignment was thenconducted for the most plausible K using the estimatedindividual proportion of membership probability (90%).
The ancestry model used for the simulation was the
admixture model, which assumes individuals may havemixed ancestry. The allele frequency model used was
the correlated allele frequencies model, which assumes
frequencies in the diﬀerent stocks are likely to be similar
due to migration or shared ancestry.

RESULTS
Genetic assignment
Bayesian clustering analyses conducted on the total
samples (4,275 individuals) without information on their

Figure 3.

Basic concept of individual assignment: (a) with allele frequency at single loci (bar plot in this ﬁgure)in each source population. In this case, it is highly
possible that individual A originates from population 1 since it has two alleles that are major in
population 1. In contrast, individual B is likely tocome from population 2 since it has two alleles
that are minor in population 1; (b) with no allele
frequency in each source population. In this case,genotypes at multiple loci in each individual enable estimation of allele frequency for the source
population and an assignment probability for eachindividual by repeating the following steps: (I) estimation of allele frequency from tentative clusteringin Hardy-Weinberg equilibrium, and (II) individualassignment based on the tentative allele frequency
according to the concept of Figure 3a.

geographic origins presented the highest likelihood probability at K=2 (Table 2). These results conﬁrmed that the
samples came from two genetically distinct stocks ofcommon minke whales (O and J stocks). In this study, theindividuals with the membership probability of over 90%
for either of the two stocks at each of the runs were assigned as pure individuals. All other individuals with themembership probability of less than 90% to the eithergroups were ʻunassignedʼ.
Spatial distribution of O and J stocks along the Japanese
coast
Both the stock-assigned and unassigned individuals were39Technical Reports of the Institute of Cetacean Research (2017)

Figure 4.

Spatial occurrence of O and J stocks common minke whale in waters around Japan.

Table 2
Results of the Bayesian clustering method analyzed for overall
samples.
K

Log P (k/x)

Variance

Pr (k/x)

1
2
3
4
5

−210753.0−202085.7−203026.1−202960.7−204283.6

85.2
873.1
3693.04761.08075.9

~0.0
~1.0
~0.0
~0.0
~0.0

grouped based on the deﬁned Areas (Figure 4). Almost
all of the individuals collected from the Sea of Japan side
(Area E) belong to the J stock, whereas almost all of theindividuals from the oﬀshore North Paciﬁc (Area C) belong to the O stock. Area D (southern part of the Paciﬁcside of Japan) was mainly occupied by the J stock. Areas A(northern Hokkaido) and Ba and Bb (northern part of the
Paciﬁc side of Japan) represent areas where both stocks
overlap geographically.
Temporal distribution of O and J stocks along the Paciﬁccoast of Japan
Figure 5 shows the temporal distribution of the O and J
stocks in Areas Ba, Bb and D in the Paciﬁc side of Japan,
expressed as three months moving average. In Area D, the J
stock was predominant (around 80% in proportion) throughout the year. In Areas Ba and Bb the proportion of the J
stock increased in autumn/winter and decreased in spring/summer. Conversely the proportion of O stock decreased inautumn/winter and increased in spring/summer.
40

Figure 5.

Monthly occurrence of O and J stocks in Areas Ba,
Bb and D in the Paciﬁc side of Japan. Each bar isexpressed as three months moving average. Sample
size is on the top of each bar. The sampling years in
Areas Ba and Bb were 1994–2014. In Area D sampling years were 2001–2014.

Distribution and movement of ʻOʼ and ʻJʼ stock common minke whales in waters around Japan based on genetic assignment methods

DISCUSSION
Assignment methods based on genetic data
There are several methods for assigning individuals tosource populations. Dawson and Belkhir (2001) developed a maximum likelihood method for assigning theindividuals in a sample to source populations, on thebasis of their genotypes at co-dominant marker loci.
Cornuet et al. (1999) used a partially Bayesian exclusion
test that uses an exclusion simulation method in the
Geneclass software. Mantel et al. (2002) showed that the
fully Bayesian assessment test of Prichard et al. (2000)
performed better than the partially Bayesian exclusion
test of Cornuet et al. (1999). However they recognizedthat the fully Bayesian method required the assumptionthat the true population origin was sampled. Given thisbackground the fully Bayesian clustering approach of
Pritchard et al. (2000), implemented in the STRUCTURE
program, was used in this study to assign individuals toeither O and J stocks, which are highly diﬀerentiatedgenetically.
Temporal and spatial distribution of O and J stocks
Results of the Bayesian clustering analysis conﬁrmedthat the whales came from two genetically diﬀerentiatedstocks, O and J stocks. By using 16 loci, more than 90% of
the individual whales were assigned to either stock. Almost all of the individuals collected from the Sea of Japanside (Area E) belonged to the J stock, whereas almost allof the individuals from the oﬀshore North Paciﬁc (Area C)
belonged to the O stock. Intermediate areas (Areas A, Ba
and Bb) contained individuals from both stocks. In Area D
the J stock was predominant (around 80% in proportion)
throughout the year. In Areas Ba and Bb the proportion of
the J stock increased in autumn/winter and decreased inspring/summer.
The fact that the J stock is distributed in Area D
throughout the year suggests that the Kuroshio Current,
which is one of the strongest west-boundary currents ofthe subtropical gyre, is working as the stock boundary
between O and J stocks.
It is important to note that the individuals from the
JARPN/JARPNII and those from the bycatch samples
diﬀer in their body length. Average body length of the
JARPN/JARPNII samples including both the oﬀshore andcoastal components was 6.67 m (SD=1.13) and that of
the all bycatch sample was 4.94 m (SD=0.99). Kato (1992)
estimated mean body length at sexual maturity of North
Paciﬁc minke whales to be 6.3 m for males and 7.1 m forfemales, so that the bycatch sample in the present study

Figure 6.

Assumed feeding migration route of O stock andJ stock animals (modiﬁed after Hatanaka andMiyashita, 1997 and Goto et al., 2010). Dark blue:
female of O stock animals, light blue: male of O
stock animals, red: J stock animals. Solid line: mature, dotted line: immature.

consisted mostly, if not all, of immature whales. The
observed diﬀerence in the maturity status between theindividuals from the bycatch and JARPN/JARPNII samples,
however, could indicate that the patterns of the temporaland spatial distributions illustrated with the bycatches
for the Areas Ba, Bb and D in this study may be diﬀerent
to some extent from those of adults. In regard to Area D,
common minke whales from the oﬀshore Area are notavailable. A related concern can be also seen in Area A.
The number of J stock individuals in Area A diﬀered between the bycatch and JARPN samples. This diﬀerence
could be due to the immature/mature, temporal, or bothfactors, but we were not able to distinguish among these
possibilities. Although we substantially increased our understanding of common minke whale distribution in thewaters around Japan from this study, our sample set isstill missing samples from some areas to depict the whole
picture of distribution and movement of the two stocks.
Genetic samples from the central and northern Okhotsk
Sea are therefore highly desirable.
The pattern described above conﬁrms the migration
pattern proposed by Hatanaka and Miyashita (1997) for
the O stock and that proposed by Goto et al. (2010) for
the J stock (see a summary of movements in Figure 6).
Possibility of additional structure with the O and J stocks
STRUCTURE has generated considerable discussion in the
IWC Scientiﬁc Committee (SC) (e.g. IWC, 2007; 2010).
One major concern is the well-documented diﬃcultythat STRUCTURE had in detecting weakly diﬀerentiated41Technical Reports of the Institute of Cetacean Research (2017)

populations/stocks, e.g. the approach could not detect
additional structure within the O and J stocks.
In this regard one of the issues discussed at the IWC
SC was the signiﬁcance of the unassigned individuals
that could not reliably be assigned to either O or J stocks(IWC, 2010). Some IWC SC members have argued thatsome if not all of the unassigned individuals, might belong to a diﬀerent stock. Alternatively, these unassigned
individuals could be the product of low statistical powerof the analysis. Taguchi et al. (2017) showed that the
proportion of unassigned individuals decreased with anincrease of the number of loci used. Therefore the most
likely explanation for the unassigned individuals is thelow power of the analysis due to a small number of lociused.
On the other hand, Pastene et al. (2016b) conductedhypothesis testing to examine the genetic population
structure of O stock common minke whales assigned by
STRUCTURE, and found no signiﬁcant heterogeneity inthe sample providing support for a single O stock in thewestern North Paciﬁc. A simulation exercise showed thatthe statistical power of the test was high.
More recently Tiedemann et al. (2017) investigated
the spatial distribution of parent/oﬀspring pairs based on
microsatellite genotype proﬁles. Several pairs were foundin which the parents were distributed in oﬀshore waters
and the oﬀspring in the coastal waters in the Paciﬁc sideof Japan, a pattern diﬃcult to reconcile with a multiple O
stocks scenario in the western North Paciﬁc.

ACKNOWLEDGEMENTS
We gratefully acknowledge the researchers and crew
members that participated in JARPN/JARPNII surveys forthe collection of genetic samples. We thank H. Oikawa(ICR) who collaborated in the process of DNA extraction.
We also thank N. Kanda (JANUS-Japan) for preparing the
microsatellite data set used in this study.

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