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Further microsatellite analysis of common minke whales in
the western North PacificNaohisa Kanda1, Mutsuo Goto1, Toshiya Kishiro2, Hideyoshi Yoshida2, Hidehiro Kato3, and Luis A.
Pastene1
1

The Institute of Cetacean Research, 4-5, Toyomi-cho, Chuo-ku, Tokyo 104-0055, Japan
National Research Institute of Far Seas Fisheries, 2-12-4, Fukuura, Kanazawa-ku, Yokohama,
Kanagawa, 236-8648, Japan
3
Tokyo University of Marine Science and Technology, 1-5-7, Konan, Minato-ku, Tokyo 108-0075, Japan
2

Contact email:kanda@cetacean.jp

ABSTRACTThis paper is a revised version of the microsatellite analysis presented in SC/J09/JR30 to cover therecommendations from the Expert Workshop to review the JARPNII Programme. The IWC ScientificCommittee (SC) completed the RMP Implementation for the western North Pacific common minke
whales during the 2003 Annual Meeting. At the final stage of the Implementation process, the SC adopted
four stock scenarios (baselines A, B, C, and D) in the western North Pacific (IWC, 2004). The SC did not
examine the plausibility of each scenario at all, however, because it was afraid that any conclusions would
not have been accepted by all. Consequently, the SC rated all of the scenarios the same ‘high’ plausibility
irrespective of available information for each hypothesis. This study examined the plausibility of thesefour stock baseline scenarios by analyzing samples of minke whales collected during JARPNII as well as
JARPN conducted from 1994 to 2007 using 16 sets of hypervariable microsatellite DNA markers. The
samples from 2003 to 2007 were not used during the previous Implementation process. In addition to theircollection years, we further divided the samples by their sighting sites into 7W (140.01°E -147.00°E), 7E(147.01°E -150.00°E), 8W (150.01°E -153.00°E), 8E (153.01°E -157.00°E), 9W (157.01°E -162.00°E),
and 9E (162.01°E -170.00°E). All of the samples were polymorphic for the 16 microsatellites analyzed,
and the genetic diversity was high. We examined if there was any evidence of genetic differences between
the coastal and offshore samples collected in the same year from the 7W, among the samples collected in
the different years from the same sub-area, and among the samples divided and compared on the basis of
proposed stock divisions from each of the four baseline scenarios with the suspected J stock individuals(all individuals included) and without the suspected J stock individuals (individuals of unknown origin
and O stock included) as well as with only the suspected O stock individuals (individuals of unknown
origin and the J stock excluded). We found 1) whales from the J stock existed in the 7W with low butlarge enough number to cause genetic heterogeneity observed in the 7W samples as well as between the
7W and other samples, 2) except the J stock whales, the survey area was mainly occupied by O stock, and3) the baselines C and D were not supported because no other genetically distinct stock was observed in
the survey area. Our simulation study indicated that from genetics standpoint the statistical power for
testing the baseline scenarios with our data set was quite high. Results of this revised paper confirmed themain conclusion in SC/J09/JR30.
KEY WORDS: MINKE WHALE, MICROSATELLITE, STOCK STRUCTURE, JARPN, JARPNII,NORTH PACIFICINTRODUCTION
Common minke whales, Balaenoptera acutorostrata, are the smallest and the most abundant baleen
whale species inhabiting major open oceans world-wide with spatial and temporal separations among
populations (Wada and Numachi, 1991; Bakke et al., 1996; Martinez and Pastene, 1999; Pastene et al.,2007). They live up to 50 years in age and the adult size is, on average, 6-7m. They feed on various preyspecies, such as copepods, Euphausiids, and fish. Their age at first reproduction is five, and they arethought to reproduce every year. As typical baleen whales, common minke whales undergo seasonal1

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movement from winter breeding grounds in low latitude to summer feeding grounds in high latitude.
Around the ocean off the Japanese coast, at least two different stocks of common minke whales are
known to exist: one stock distributes in the western North Pacific and the other in the Sea of Japan(Omura and Sakiura, 1956; Ohsumi, 1977; Kato, 1992; Wada and Numachi, 1991; Goto and Pastene,
1997; Pastene et al., 2007). Contrary to the clear genetic differences detected between these two stocks,
previous analyses of allozymes and mtDNA restriction fragment length polymorphism (RFLP) failed topresent evidence of genetic heterogeneity among samples within the western North Pacific east of Japaneven though these samples were collected from a very wide geographic area from 142°E to 170°E andfrom 35°N to 45°N (Wada and Numachi, 1991; Goto and Pastene, 1997). This could simply indicate asingle stock of minke whales in the area. Alternate explanation is that previously used genetic markers
were not sensitive enough to detect genetic differentiation among stocks of highly migratory species likeminke whales because they represent very small portion of genetic differences on genome. In addition
to that, large stock size and the ability to long distance migration of minke whales suggests low degree ofgenetic differences. Their breeding grounds have not yet been found partially because no aggregation ofminke whale females has been found during the breeding season (Kasamatsu, 2000).
The IWC Scientific Committee (SC) completed the RMP Implementation for the western North Pacificcommon minke whales during the 2003 Annual Meeting. At the final stage of the Implementation process,the SC adopted the following stock scenarios in the western North Pacific (IWC, 2004).
(1) Baseline A: three-stock scenario (J, O, W) with the W stock found only in part of
sub-area 9 and only sporadically.
(2) Baseline B: two stock scenario (J and O) with no W stock as a limiting case of
Baseline A.
(3) Baseline C：four-stock scenario overall, with OW, OE and W to the east of Japan.
Boundaries are fixed at 147°E and 157°E and there is no mixing between the stocks.
(4) Baseline D：three-stock scenario (J, O, W), with O and W mixing over 147°E and162°E, O being dominant to the west and W to the east.
The SC did not examine the plausibility of each baseline scenario at all because it was afraid that any
conclusions would not have been accepted by all. Consequently, the SC rated all of the scenarios the same‘high’ plausibility.
The primary objective of this study was to examine the plausibility of these four baseline stock scenariosby analyzing samples of minke whales collected from JARPN and JARPNII conducted from 1994 to2007 using hypervariable microsatellite DNA markers. The samples of 2003 to 2007 were not used during
the previous Implementation process.
This paper is the revised version of SC/J09/JR30 to cover the recommendations of the expert panel of theExpert Workshop to review the JARPNII Programme held at Tokyo from 26-30 of January. The panel
recommends that the revised paper should include estimates of genetic divergence in addition toprobabilities of homogeneity, report P values from the tests of homogeneity for all loci combined rather
than each locus separately, and assess statistical power for the tests of homogeneity using simulated data.
MATERIALS AND METHODS
SamplesCommon minke whales samples of the JARPNII offshore component were taken from 2000 to 2007. The
JARPN samples from 1994 to 1999 were also used in this study. Eighteen sub-areas were set for
management purpose of the western North Pacific common minke whale during the Implementation
Specification conducted in 2003 (Figure 1). Although the JARPN survey was conducted at the SA11 in
1995 and 1997, we used the samples collected only from the sub-areas 7, 8, and 9. Each of the three
sub-areas was further divided into western and eastern strata for analyses: 7W (140.01°E -147.00°E), 7E(147.01°E -150.00°E), 8W (150.01°E -153.00°E), 8E (153.01°E -157.00°E), 9W (157.01°E -162.00°E),
and 9E (162.01°E -170.00°E). Because of other scientific purposes of the survey (e.g., feeding ecology ofminke whales), the sampling locations differed from year by year. Details of offshore component of
JARPNII survey can be found in Tamura et al. (2009). Another source of the minke whale samples was2

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the coastal component of the JARPNII survey conducted from 2002 to 2007. A total of nine surveys had
been conducted as the coastal component of the JARPNII: spring surveys at Sanriku in 2003, 2005, 2006,
and 2007, and fall surveys at Kushiro in 2002, 2004, 2005, 2006, and 2007. Sample size was maximum
60 minke whales per survey. Details of coastal component of the JARPNII can be found in Kishiro et al.
(2009). Table 1 shows the number of individuals used in the present microsatellite analysis by year,
sub-area and the offshore/coastal components, and Figure 2 shows sighting positions of the collectedindividuals.
Microsatellite analysis
We followed the IWC guidelines for DNA data quality (IWC, 2009) as much as possible at the moment.
Skin tissues of minke whales taken during the JARPNII were stored in 95% ethanol until DNA extraction.
Genomic DNA was then extracted from 0.05g each of the skin tissues using standard proteinase K,
phenol-chloroform procedure described by Sambrook et al. (1989). Extracted DNA was stored in the TE
buffer (10 mM Tris-HCl, 1 mM EDTA, pH 8.0).
Microsatellite polymorphisms were analyzed using 16 sets of primers: EV1, EV14, EV21, EV37, EV94,(Valsecchi & Amos 1996), GT23, GT195, GT211, GT310, GT509, GT575 (Bérubé et al., 2000), GATA28,
GATA98, GATA417, TAA31 (Palsbøll et al., 1997), and DlrFCB14 (Buchanan et al., 1996). EV1, EV14,
EV21 were developed from sperm whale (Physeter macrocephalus), EV37, EV94, GT23, GT310, GT575,
GATA28, GATA98, GATA417, TAA31 were from humpback whale (Megaptera novaeanglia), and
DlrFCB14 from beluga whale (Delphinapterus leucas). All GT, EV, and DlrFCB primers were
dinucleotide repeat, TAA31 trinucleotide repeat, and all GATA primers tetranucleotide repeat. Most of theprimers used here were already tested for amplification on minke whales by these authors. Primer
sequences and PCR profiles follows those of the original authors with slight modifications.
PCR amplifications were performed in 15μl reaction mixtures containing 10-100ng of DNA, 5 pmole ofeach primer, 0.625 units of Ex Taq DNA polymerase (Takara Shuzo), and 2mM of each dNTP, and 10x
reaction buffer containing 20mM MgCl2 (Takara Shuzo). PCR amplifications followed the
manufacture’s instructions for the use of Ex Taq DNA polymerase (Takara Shuzo). Amplified productswith internal size standard (GENESCAN400HD, Applied Biosystems Japan) were run on a 6%
polyacrylamide denaturating gel (Long RangerTM) using an BaseStationTM 100 DNA fragment analyzer(Bio-Rad). Although alleles were visualized using CartographerTM software specifically designed for the
BaseStation, allelic sizes were determined manually in relation to the internal size standard and minke
whale DNA of known size that were rerun on each gel.
Data analysis
The number of alleles and expected heterozygosity per locus was calculated using the software FSTAT
2.9.3 (Goudet, 1995). Statistical tests for deviations from the expected Hardy-Weinberg genotypic
proportions were conducted using the software GENEPOP 4.0 (Rousset, 2008).
In order to detect genetic differences in the samples of minke whales, we performed conventional
hypothesis testing procedure using heterogeneity test in frequencies of the microsatellite alleles among
samples. Null hypothesis to be tested is if the samples came from a genetically same group of minke
whales. If genetic differences exist, then it could indicate these samples came from genetically different
stocks of minke whales. Markov chain method implemented in the GENEPOP was used to conduct theheterogeneity tests. Statistical significance was determined using the chi-square value obtained fromsumming the negative logarithm of p-values over the 17 microsatellite loci (Sokal & Rohlf 1995). FST
was calculated using ARLEQUIN 2.0 (Schneider et al. 2000). The samples with less than 5 individuals
were excluded from the genetic divergence analyses.
Assessment of statistical power for the tests of homogeneity
In order to assess statistical power for tests of homogeneity (e.g., Waples and Gaggiotti, 2006), we
generated genotypic data using computer software EASYPOP (Balloux, 2001) and conducted
heterogeneity tests with these generated data. We assumed two or three populations depending on thestock structure scenario we tested (baseline A and D = 2 populations, baseline C = 3 populations), each ofwhich consists of diploid individuals with a constant size and equal sex ratio with random mating. We
assumed ratio of effective population size to census population size to be 1/3 to 1/4 (Roman and Palumbi,2003). The effective population size of the populations was thus set as it becomes 1/3 or1/4 of the census

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populations size. We used census population size of approximately 20000 for the baselines A and D, andapproximately 10000 for the baseline C. These numbers were used on the basis of the IWC’s accepted
population abundance of this species in the North Pacific. Each generation, simulation produces genotype
data set for 16 independent nuclear gene loci (microsatellites) for each individual. The number of the locisimulated and maximum number of the allelic states (29) was set based on the observed data in this study.
For the two population model, bidirectional migration was assumed with an equal migration rate (m),while for the three population model, stepping stone migration model was assumed. Migration rates
ranged from 0.01 to 0.5, some of which (0.1-0.5) were quite high for genetic method to detect. We
specified a range of genetic divergence using FST values estimated assuming island model between thetwo populations by changing migration rate. Mutation rate of 5x10-4 was chosen to represent
microsatellite loci. For each simulation parameter set, we made 100 replicates. We ran 5000 generations
for each replicate before collecting data. In the final generation of each replicate, sample of 100
individuals for the baseline A, 270 for the baseline C, and 170 for the baseline D were taken from each
population for genetic analysis. The sample size of 100 for the baseline A was selected to reflect sporadic
distribution of the W stock in the SA9 in some years (e.g., Goto et al., 2000). The sample size for thebaseline C approximately equals to the sum of the samples size from SA7E to SA8E where the Oe stock
was assumed. The sample size for the baseline D approximately equals to the samples size from the SA9
where the W stock was assumed. We conducted homogeneity tests for the generated data set using
pairwise tests of differentiation option in the FSTAT. In this option, for each pair of samples, multi-locigenotypes are randomized between the two samples. The overall loci G-statistic is given and statisticalsignificance was decided with a table wide level of significance at 5%.
RESULTS
Kanda et al. (2009) showed that there were the suspected J stock individuals in the samples of minke
whales from the Pacific side of Japan. On the basis of the individual identifications to the stocks
according to the criteria in Kanda et al. (2009), we conducted the tests with three different kinds ofsample groups: 1) one that included all the analyzed individuals, 2) one that excluded the suspected J
stock individuals (samples contained individuals of unknown origin and the O stock) and 3) one that used
only the suspected O stock individuals (samples excluded individuals of unknown origin and the J stock).
The number of the suspected J stock individuals in the offshore component samples was 24 in the 7W and
two in the 9W, while that in the coastal component samples was 79. The number of the suspected O stockindividuals in the samples was 1,365.
Genetic diversity within samples
All of the 16 microsatellites were polymorphic in the overall samples (Table 2). The number of alleles at
each of the loci ranged from two at EV21 to 29 at EV1 with an average of 12.6. Expected heterozygosity
at the loci ranged from 0.328 at EV21 to 0.881 at GT23 with an average of 0.698. These results indicatedsubstantial genetic diversity in the minke whales used in this study. Evidence of deviation from theexpected Hardy-Weinberg genotypic proportions was detected at two loci (GT195 and GT509) in thesample group with the suspected J stock individuals, but disappeared in the sample groups without thesuspected J stock individuals as well as with only the suspected O stock individuals.
Genetic divergence between samples
Genetic differences between offshore and coastal samples in the west of SA7
We looked for evidence of genetic differences between the coastal and offshore samples collected in thesame year from the 7W. None of the comparisons from 2002 to 2007 showed statistically significant
differences in the sample groups with only the suspected O stock individuals (Table 3). Significant
difference was detected at the 2004 sample in the sample group with and without the suspected J stockindividuals. In 2004, only 12 individuals were available for the test in the offshore sample compared to 54
in the coastal one, and the heterogeneity appeared to be due to lack of some minor alleles in the former.
This suggested the difference had little biological meanings. We thus combined the coastal and offshore
samples collected from the same year into one, respectively, for subsequent analyses in all the sample
groups.
Temporal genetic differences within sub-areas
We looked for evidence of genetic differences among the samples collected in the different years within
the same sub-area. No statistically significant genetic differences were detected within the 7E, 8W, 8E,

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9W, 9E and in each of the sample groups (Table 4). For the subsequent analyses, we combined thesamples of the different survey years from the same sub-area into one, respectively. Contrary, significant
genetic differences were detected within the 7W in the sample group with the suspected J stockindividuals (Table 4). The heterogeneity found in the 7W samples, however, disappeared in the sample
group without the suspected J stock individuals. We combined the samples of the different survey years
into the single 7W sample, at all the sample groups for the subsequent analyses
Baseline A. Baseline A is a three-stock scenario (J, O, W stocks) with the W stock found only in part ofSA9 and only sporadically. In order to test the heterogeneity within the SA9, we conducted theheterogeneity test between the 9W and 9E samples. Statistically significant difference was detected at allof the sample groups (Table 5). Considering the result from the previous test above, we decided to treat
the 9W and 9E samples separately for the following tests. FST value between the samples was 0.00091 forwith the suspected J stock individuals and 0.00082 with only the suspected O stock individuals, and bothwere significantly different from zero.
Baseline B. Baseline B is a two stock scenario (J and O) with no W stock. Statistically tests for the
scenario B are same as those for the baseline A shown above.
Baseline C. Baseline C is a four-stock scenario with OW, OE, and W to the east of Japan in addition to the
J stock in the Sea of Japan. Boundaries are fixed at 147°E and 157°E and there is no mixing between thestocks. We first conducted the heterogeneity tests among the 7E, 8W, and 8E samples that wereassumed to belong to the OE stock in the scenario. No statistically significant difference was detected (7E
x 8W x 8E; Table 6), so that these samples were combined into one as 7E-8E for the following analyses inall the sample groups. We then tested for genetic differences among the 7W, 7E-8E, 9W, and 9E samples(7W x 7E-8E x 9W x 9E, 7W x 7E-8E x SA9; Table 6). In the sample groups with and without thesuspected J stock individuals, statistically significant difference was detected (Table 6). Pair-wisecomparisons for the sample group with the suspected J stock individuals showed statistically significant
differences between the 7W and other three samples (7E-8E, 9W, and 9E; Table 7). These differences,
however, disappeared in the sample group without the suspected J individuals (Table 7). Contrary, in thesample group with only the suspected O stock individuals, no evidence of genetic difference was detectedamong the 7W, 7E-8E, and SA9 samples. In addition to the 9W and 9E pair, statistically significant FST
value was detected between the samples from 7W and 7E-8E, and 7W and 9E both for with the suspected
J stock individuals (Table 8).
Baseline D. Baseline D is another three-stock scenario (J, O, W stocks), with the O and W stocks mixing
over 147°E and 162°E, the O being dominant to the west and W to the east. If this scenario is true, weshould detect genetic differences not only between the 7W and 9E but also among the 7E, 8W, 8E and 9W
samples. No statistically significant difference was detected among the 7E, 8W, 8E and 9W samples (7E x
8W x 8E x 9W; Table 9) in all the sample groups. These samples were combined into one as 7E-9W for
the following analyses. We then conducted the heterogeneity tests among 7W, 7E-9W, and 9E (7W x
7E-9W x 9E; Table 9). Statistically significant difference was detected at the sample groups with as wellas without the suspected J stock, but not with only the O stock individuals (Table 9). Pair-wisecomparisons for the sample group with the suspected J individuals showed statistically significant
differences in the two pairs between the 7W and other two samples (7E- 9W, and 9E; Table 10). FST was
statistically significant at the pairs between the 7W and 7E-9W, and 7W and 9E both for with thesuspected J stock individuals, but not with only the O stock individuals (Table 11).
Assessment of statistical power for the tests of homogeneity
Table 12 shows the input parameters used and the results of simulation analysis to assess the statisticalpower for the tests homogeneity conducted in each of the baselines. From genetics perspective, oursimulation attempted to test the statistical power for very small genetic divergence between two samples.
For instance, estimated FST values were all smaller than 0.01 for the two stocks baseline scenario.
Because both the baselines A and D assumed existence of the two stocks, O and W, the input parameters
for simulating them were all same except the sample size for the homogeneity tests. The sample size
differed between the baselines because we looked for the power to detect the W stock sporadicallyappeared in the SA9W for the baseline A while we looked for the power to detect the W stock always
existing in the SA9 for the baseline D. The difference between the results for the two baselines thus5

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reflected the difference in the samples size. High power was detected with m=0.01 for the baseline A andwith m=0.01 and 0.02 for the baseline D.
Stepping stone model was assumed for the baseline C because three populations, OW, OE, and W fromwest to east were assumed to distribute with fixed boundaries between them, suggesting lower migration
rate between the OW and W than between OW and OE, and between OE, and W. Census population size
was also assumed to be 10000 compared to 20000 in the baselines A and D. Estimated FST values in thetable 12 represented for between the neighbor populations (i.e., between OW and OE, and between OE andW). High statistical power was observed at the migration rate of 0.1 for the comparisons between theneighbor populations (i.e., between OW and OE, and between OE and W) and even at 0.2 for between thefirst and third populations (i.e., OW and W).
DISCUSSION
We believe that the results of this study substantially improve our knowledge of the stock structure ofcommon minke whales in the western North Pacific and are quite informative for effective managementof this species. Additional 923 minke whales were collected after 2003 Implementation process and used
for the current study. Approximately 90% of these additional minke whales were collected from the 7W
and SA9. As shown in the Figure 2, now our samples spatially covered the survey areas quite well.
These facts allowed us to look for evidence of distribution of the individuals from the J and W stocks, if
they exist, in our survey area. In addition to that, in this study we conducted simulation analysis to assess
statistical power to see if the number of minke whales we sampled and the number of the microsatellite
loci we analyzed was sufficient to test adequately the alternate stock structure hypothesis.
We conducted the heterogeneity tests with three different kinds of sample groups: 1) one that included all
the analyzed individuals, 2) one that excluded the suspected J stock individuals (samples contained
individuals of unknown origin and the O stock) and 3) one that used only the suspected O stockindividuals (samples excluded individuals of unknown origin and the J stock). Identification of the stock
origins for the individual whales was according to Kanda et al., (2009). The SC has recommended thatthe suspected J stock individuals should be excluded from the analyses of the North Pacific common
minke whales because they could have large effects on the analyses. In fact, evidence of deviations fromthe expected Hardy-Weinberg genotypic proportions was detected in the sample group with the suspected
J stock individuals, but disappeared in the sample group without them. Similarly, the temporal genetic
heterogeneity detected in the 7W samples should have reflected the difference in the number of the J
stock individuals between the earlier and later samples. The J stock individuals were fewer in the offshore
than in the coastal 7W samples (Kanda et al. 2009) and the earlier samples from 1994 to 2001 consistedof only the offshore ones. Since no diagnostic marker has been found between the O and J stockindividuals, we think the genetic identification used is the best available so far.
The baseline C suggests the existence of the three genetically distinct stocks, OW (7W), OE (7E-8W), andW (9W-9E) with no mixing between the stocks. The baseline D suggests two stocks, O (7W) and W (9E),in the JARPNII survey area with the two mixing over 147°E and 162°E (7E-9W) with a cline. Bothbaselines are similar in terms of assuming a distinct coastal North Pacific stock in the 7W. Our study,
however, did not support that possibility. The results of the heterogeneity tests for the coastal stock of thebaselines C and D differed among the sample groups. The statistical significance in the heterogeneity tests
between the 7W and other offshore (east of 7E) samples was disappeared when the suspected J stockindividuals were excluded from the samples, that is, with only the O stock individuals, no statisticalsignificance was detected under the baselines C and D. The number of the suspected J stock individuals
excluded was 103, and there were still 789 individuals in the 7W samples for the test without the J stockindividuals. The disappearance of the statistical significance is highly likely due to exclusion of the J
stock individuals from the samples but not due to the reduced sample size for the tests. The genetic
heterogeneity we have seen in the samples from the 7W thus indicated the existence of some individuals
from the J stock, but not from the other genetically distinct coastal stock. We did not also detect any
heterogeneity among the samples from the middle sub-areas (7E to 8E or 9W) after exclusion of the J
stock from the analysis, which did not support the OE and W stocks under the baselines C and the W
under the baseline D. Unless the population sizes of the stocks are much larger than we have anticipated,
our simulation study indicated that from genetics standpoint the statistical power for testing the baselines
C and D with our data set was quite high. We believe from these results that the JARPNII survey area of6

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the western North Pacific is primarily occupied by the whales from the O stock. The baselines C and D
are highly unlikely.
It was a little difficult to evaluate the baseline A, however. The baseline A assume sporadic migration of
the W stock into the SA9 because past mtDNA studies (e.g., Goto et al., 1997) found the genetic
heterogeneity in the area in some years. We did not find such temporal genetic differences within thesamples from the SA9, but the genetic heterogeneity between the 9W and 9E samples. The simulation
study indicated that from genetics viewpoint the statistical power for testing the baseline A with our data
set was reasonably high. The heterogeneity we observed could be due to sporadic migration of the W
stock or a group of genetically related individuals from the O stock. We should await results from moredetailed genetic analysis (e.g., look for the pair of individuals that are related), from other independentstudies conducted on the same samples (e.g., morphometric study) as well as from continued monitoringof minke whales migrating to the SA9 in order to better understand migration pattern of the W stock
under the baseline A.
ACKNOWLEDGEMENTS
We thank researchers and crewmembers participating in the JARPN and JARPNII for their effort incollecting the samples used in this study. Our sincere gratitude also goes to H. Oikawa and S. Azumi for
their assistance in DNA extraction, and H. Hatanaka and the expert panel of the Expert Workshop to
review the JARPNII Programme for valuable comments on the paper.
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Table 1. Samples used for the microsatellite analyses.
Survey area
Coastal
Year
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
Total

7W

50
50
58
120
95
107
480

Offshore
7W

31
2
25
50
24
43
60
17
15
32
36
79
414

7E

31

8W

1
1
44

7
7

2
47

8E

15
30

21

21
8
17

7
10
2
86

7
28
13
139

9W

9E

Total

7
78

14
22

19

48

16
29
32
24
42
19
23
2
291

14
41
30
1
4
174

21
100
47
100
100
50
40
100
150
150
156
215
195
207
1631

Table 2. The number of alleles (A), expected heterozygosity (He),and test results for deviation from the expected Hardy-Weinberg genotypic
proportions (HW) at 16 microsatellite loci analyzed in the samples of minke
whales used in this study. n.s. = not significant
Microsatellites

A

He

HW

HW*

HW**

DlrFCB14
EV1
EV14
EV21
EV37
EV94
GATA28GATA98GATA417
GT23
GT195
GT211
GT310
GT509
GT575
TAA31

5
29
6
2
12
8
22
6
13
16
13
16
14
23
12
4

0.379
0.814
0.565
0.328
0.726
0.655
0.841
0.621
0.751
0.881
0.835
0.879
0.825
0.861
0.820
0.381

n.s.
n.s.
n.s.
n.s.
n.s.
n.s.
n.s.
n.s.
n.s.
n.s.
<0.01
n.s.
n.s.
<0.001
n.s.
n.s.

n.s.
n.s.
n.s.
n.s.
n.s.
n.s.
n.s.
n.s.
n.s.
n.s.
n.s.
n.s.
n.s.
n.s.
n.s.
n.s.

n.s.
n.s.
n.s.
n.s.
n.s.
n.s.
n.s.
n.s.
n.s.
n.s.
n.s.
n.s.
n.s.
n.s.
n.s.
n.s.

all loci

12.6

0.698

0.000

0.217

0.157

*Tested without the suspected J stock individuals.
** Tested with only the suspected O stock individuals.

9

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Table 3. Results (p-values) of the heterogeneity tests between the offshore and coastal samples collected from the survey years in the 7W．Tests were conducted
respectively for the sample groupings with and without the suspected J stock individuals as well as with only the suspected O stock individuals.
With the suspected J stock individuals

Without the suspected J stock individuals

Only the suspected O stock individuals

2002 2003 2004 2005 2006 2007

2002 2003 2004 2005 2006 2007

2002 2003 2004 2005 2006 2007

0.380 0.653 0.033 0.288 0.063 0.614

0.531 0.748 0.005 0.252 0.150 0.711

0.363 0.700 0.056 0.117 0.335 0.551

Table 4. Results (p-values) of the heterogeneity tests among the samples collected in the different survey years from the same sub-area. Tests were conducted
respectively for the sample groupings with and without the suspected J stock individuals as well as with only the suspected O stock individuals.
With J

Without J*

Only O

7W

7E

8W

8E

9W

9E

7W

9W

7W

7E

8W

8E

9W

9E

0.014

0.422

0.190

0.785

0.949

0.061

0.162

0.926

0.073

0.356

0.225

0.795

0.924

0.157

* The suspected J stock individuals were detected only at the 7W and 9W.

Table 5. Results (p-values) of the heterogeneity tests and FST valuses between the 9E
and 9W samples. Tests were conducted respectively for the sample groupings withand without the suspected J stock individuals as well as with only the suspected O stock ones.
9W x 9E
With J

Without J

Only O

Heterogeneity test

0.007

0.005

0.027

FST

with J: 0.00091*

only O: 0.00082**P<0.05

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Table 6. Results (p-values) of the heterogenety tests for the baseline C.
Tests were conducted respectively for the sample groupings with and without thesuspected J stock individuals as well as with only the suspected O stock individuals.
7E x 8W x 8E

7W x 7E-8E x 9W x 9E

With / without J

Only OWith J

Without J

Only O

0.815

0.885

h.s.

0.030

0.207

h.s.: highly significant.

Table 7. Results (p-values) of the pair-wise heterogenety
tests between the samples of minke whales from different
areas for the baseline C. Tests were conducted respectively
for the sample groups with and without the suspected J stockindividuals.
With J

Without J

7W x 7E-8E
7W x 9W
7W x 9E

0.001
h.s
0.000

0.448
0.363
0.060

7E-8E x 9W
7E-8E x 9E

0.758
0.667

0.740
0.647

9E x 9W

0.007

0.006

h.s.: highly significant.

Table 8. FST values between the samples of minke whales from different areas for the baseline C.
The values were estimated respectively for the sample groupings all individuals (below diagonal)
and of only O (above diagonal).

7W
7E-8E
9W
9E

7W

7E-8E

9W

9E

----0.00067**
0.000190.00097**0.00027-----0.00013-0.00021-0.00001-0.00014----0.00091*

0.00016-0.00021
0.00082*-----*: P<0.05, **: P<0.01

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Table 9. Results (p-values) of the heterogenety tests for the baseline D.
Tests were conducted respectively for the sample groupings with and without
the suspected J stock individuals as well as with only the suspected O stock ones.
7E x 8W x 8E x 9W

7W x 7E-9W x 9E

With J

Without J

Only OWith J

Without J

Only O

0.819

0.799

0.922

h.s

0.044

0.101

h.s.: highly significant.

Table 10. Results (p-values) of the pair-wise heterogenety
tests between the samples of minke whales from different
areas for the baseline D. Tests were conducted respectively
for the sample groupings with and without the suspected J
stock individuals.

7W x 7E-9W
7W x 9E
7E-9W x9E

With J

Without J

h.s
0.000
0.094

0.255
0.056
0.095

h.s.: highly significant.

Table 11. FST values between the samples of minke whales from different
areas for the baseline D. The values were estimated respectively for the sample
groupings with all individuals (below diagonal) and with only O (above diagonal).

7W
7E-9W
9E

7W

7E-9W

9E

----0.00039***0.00097**0.00016----0.00040

0.000160.00035-----**: P<0.01, ***: P<0.001

12

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Table 12. Input parameter sets used for generating simulated data set using EASYPOP to asessstatistical power in our samples and results of the homogenetiy tests with the simulated data. The
following were fixed in all sets other than shown in the table: diploid, random mating, equal sex ratio, allsubpopulations of constant Ne, mutation rate of 0.005, 16 nuclear gene loci, 29 maximum allelic states,and 100 replicates each with 5000 generations.
Input parameters
n

N

Ne

19980
19980
19980
19980
19980
19980

6660
6660
6660
6660
6660
6660

2
2
2
2
2
2

20000
20000
20000
20000
20000
20000

Baseline C
N=3Ne
3
3
3
3
3
N=4Ne

Baselin D
N=3Ne

N=4Ne

Nem

FST

S

% rejecting panmixia

0.01
67 0.0037
0.02 133 0.0019
0.05 333 0.0008
0.1
666 0.0004
0.2 1332 0.0002
0.5 3330 0.0001

100
100
100
100
100
100

OxW
97
57
25
11
7
6

5000
5000
5000
5000
5000
5000

0.01
50 0.0050
0.02 100 0.0025
0.05 250 0.0010
0.1
500 0.0005
0.2 1000 0.0002
0.5 2500 0.0001

100
100
100
100
100
100

100
80
27
11
10
6

10050
10050
10050
10050
10050

3350
3350
3350
3350
3350

0.01
34
0.05 168
0.1
335
0.2
670
0.67 2245

0.00740.00150.00070.00040.0001

270
270
270
270
270

OW x OE or OE x W
100, 100
100, 100
97, 9729, 31
1, 2

OW x W
100
100
100
93
13

3
3
3
3
3

10000
10000
10000
10000
10000

2500
2500
2500
2500
2500

0.01
25
0.05 125
0.1
250
0.2
500
0.67 1675

0.00990.00200.00100.00050.0001

270
270
270
270
270

100, 100
100, 100
100, 98
67, 52
2, 2

100
100
100
99
12

2
2
2
2
2
2

19980
19980
19980
19980
19980
19980

6660
6660
6660
6660
6660
6660

0.01
67 0.0037
0.02 133 0.0019
0.05 333 0.0008
0.1
666 0.0004
0.2 1332 0.0002
0.5 3330 0.0001

170
170
170
170
170
170

OxW
100
94
44
11
7
6

2
2
2
2
2
2

20000
20000
20000
20000
20000
20000

5000
5000
5000
5000
5000
5000

0.01
50 0.0050
0.02 100 0.0025
0.05 250 0.0010
0.1
500 0.0005
0.2 1000 0.0002
0.5 2500 0.0001

170
170
170
170
170
170

100
99
44
18
9
2

Baseline A
N=3Ne
2
2
2
2
2
2
N=4Ne

m

13

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Figure 1. Eighteen sub-areas used for the Implementation Simulation Trials for the North Pacific minke
whales.

Figure 2. Sighting positions of the collected minke whales during the JARPN and JARPNII surveys.
Both the offshore and coastal component samples are included.

14