SC/66b/SD

Additional genetic analyses on stock structure in North
Pacific Bryde’s and sei whales
Luis A. Pastene1, Mutsuo Goto1 and Mioko Taguchi2
1
2

Institute of Cetacean Research, 4-5 Toyomi-cho, Chuo-ku, Tokyo 104-0055, Japan
Okitsunaka-cho 1347-3-302, Shimizu-ku, Shizuoka-shi, Shizuoka 424-0204, Japan

ABSTRACTDuring the IWC SC JARPNII review workshop conducted in February 2016, information and analyses on
stock structure-related issues were presented in 25 scientific papers. The review workshop noted thesubstantial amount of field, laboratory and analytical work undertaken under the JARPNII program, andthe contribution of the work for the assessment and management of sei, Bryde’s and common minke
whales in the North Pacific. At the same time the workshop provided four medium-long term
recommendations, and three short-term recommendations. The latter should be responded by JARPNII
scientists ‘ideally by the 2016 Annual Meeting but certainly by the 2017 Annual Meeting’ of the IWC
SC. This paper responds to one of the three short-term recommendations from the JARPNII review
workshop that the presence of multiple stocks within sample partitions should be assessed employing
STRUCTURE and DAPC for Bryde’s and sei whales. Results of additional STRUCTURE analyses
supported the hypothesis of a single stock of Bryde’s whale in sub-areas 1 and 2, which contradicts theresults of the hypothesis testing of significant mtDNA and microsatellite differences between sub-areas 1
and 2. This reflects the well-documented difficulty that STRUCTURE has in detecting weakly
differentiated populations. In the case of sei whales, results of the STRUCTURE and hypothesis testing
were similar, and they support the existence of a single stock in the pelagic region of the North Pacific.
INTRODUCTION
The International Whaling Commission Scientific Committee (IWC SC) carried out a specialist workshop
under the guidelines of Annex P (IWC, 2016) to review final data and results of the Second Phase of theJapanese Whale Research Program under Special Permits in the North Pacific (JARPNII) (JARPNII
review workshop). Many of the analyses conducted under the three main objectives of JARPNII,
including those on stock structure, were based on a combined data set of JARPNII and the previous
JARPN program.
On the research objective on stock structure of large whales in the North Pacific, a total of 25 scientificpapers were available for the review workshop. The workshop noted the substantial amount of field,
laboratory and analytical work undertaken under the JARPNII program, and the important contribution of
the studies for the management of common minke and Bryde’s whales under the RMP, and for the indepth assessment of sei whales (SC/66b/Rep 6).
At the same time the review workshop provided four medium-long term recommendations, and three
short-term analytical recommendations. The latter should be responded by JARPNII scientists ‘ideally by
the 2016 Annual Meeting but certainly by the 2017 Annual Meeting’ of the IWC SC (SC/66b/Rep 6).
The three short-term recommendations were the following (from SC/66b/Rep 6 p.18):
i)
ii)
iii)

All references regarding randomness of observations (e.g. unassigned common minke whales)
should be substantiated by a statistical assessment of the presumed randomness.
The presence of multiple stocks within sample partitions should be assessed (employing, e.g.
STRUCTURE and DAPC) for Bryde’s and sei whales.
More explicit information on quality checks be provided in each study as well as study-1specific estimates of genotyping and DNA sequencing error rates.
Respond to the third recommendation above can be found in Goto et al. (2016). This paper provides the
background and the response to the second recommendation above by conducting additional STRUCURE
running in the case of Bryde’s and sei whales. Because results from STRUCTURE and DAPC were very
similar in the case of the North Pacific common minke whale (Pastene et al., 2016a), the authors
considered that the running of only one of those two computer programs is fair enough to respond therecommendation from the JARPNII review workshop.
Response to the first recommendation above will be provided to the next meeting of the IWC SC.
BACKGROUND
Bryde’s whale
During the final JARPNII review workshop, results of the analyses of hypothesis testing for both mtDNA
and microsatellites, were presented. Table 1 shows the number and sources of the genetic samples ofBryde’s whales used in the analyses while Figure 1 shows the geographical distribution of the genetic
samples. In summary both markers showed no significant genetic heterogeneity between whales in subareas 1W and 1E, and the statistical power of the analysis was considered high (see details in Pastene etal., 2016b). This result suggested no stock structure within sub-area 1, and it was consistent with theinformation on movement from mark-recapture and satellite tracking analyses.
In contrast significant differences were found between whales in sub-areas 1 and 2 for both mtDNA andmicrosatellites (Pastene et al., 2016b), suggesting the possibility that different stocks occur in these subareas.
After examining these results, the JARPNII review workshop recommended that ‘the presence of multiple
stocks within sample partitions should be assessed employing, e.g. STRUCTURE and DAPC)’(SC/66b/Rep 6).
Sei whale
During the final JARPNII review workshop, results of the analyses of hypothesis testing for both mtDNA
and microsatellites, were presented. Table 2 shows the number and sources of the genetic samples of sei
whales used in the analyses while Figure 2 shows the geographical distribution of the genetic samples. In
summary both markers showed no significant genetic heterogeneity between whales in the western andeastern sectors of the North Pacific (see details in Pastene et al., 2016c). This result suggested no stock
structure in the pelagic region of the North Pacific which is consistent with other lines of evidences (e.g.
Kanda et al., 2015a).
After examining these results, the JARPNII review workshop recommended that ‘the presence of multiple
stocks within sample partitions should be assessed employing, e.g. STRUCTURE and DAPC’(SC/66b/Rep 6).
MATERIALS AND METHODS
Samples
The number of samples, sub-area or sector and sources are shown in Tables 1 and 2 for Bryde’s and sei
whales, respectively. These are the same used in the hypothesis testing presented to the JARPNII review
workshop. The geographical distribution of the samples of the two species is shown in Figures 1 and 2,
respectively.
Microsatellite analysis
In the case of the two species, genetic variation at microsatellite DNA was analyzed using 17 loci, noneof which was designed specifically from Bryde’s whales: EV1, EV14, EV21, EV94, EV104 (Valsecchi
and Amos, 1996), GT011 (Bérubé et al., 1998), GT23, GT211, GT271, GT310, GT575 (Bérubé et al.,2000), GATA28, GATA53, GATA98, GATA417, GGAA520 (Palsbøll et al., 1997), and DlrFCB17(Buchanan et al., 1996).

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Details of the laboratory procedures were given in Pastene et al. (2016b;c).
Analytical procedure
The Bayesian clustering approach was implemented with the microsatellite data in the STRUCTURE
version 2.0 (Pritchard et al., 2000) to determine the most likely number of genetically distinct stocks
present in the samples. The program is a model-based clustering method for inferring stock structure (K,the number of stocks in the model) 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 biological stock boundaries. Posterior probabilities for K were
estimated from ten independent runs for each value of K=1-5 for Bryde’s whale and K=1-3 for sei whalewith only genetic information. All runs were performed with a burn-in period of 10,000 iterations and100,000 MCMC iterations. The ancestry model used for the simulation was the admixture model, whichassumes individuals may have mixed 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 tomigration or shared ancestry.
Following the recommendation from the JARPNII review workshop, in the case of Bryde’s whale
STRUCTURE was running for each sampling partition (sub-area 1E, sub-area 1W, sub-area 2 and entire
sub-area). In the case of sei whales STRUCTURE was running for the entire research area.
RESULTS AND DISCUSSION
Bryde’s whale
Bayesian clustering analyses conducted for different sampling partitions without information on theirgeographic origins presented the highest likelihood probability at K=1 (Tables 3-6). Figures 3-6 shows
estimated stock structure at K=2-5. As evident from the figures, additional stocks were indistinguishable.
These results indicated that the samples came from a single stock of Bryde’s whale in all sampling
partitions examined.
However these results are different from those from the hypothesis testing presented at the JARPNII
review workshop (Pastene et al. 2016b). This reflects the well-documented difficulty that STRUCTURE
has in detecting weakly differentiated populations.
Based on the results of the hypothesis testing, it is suggested that the plausibility of the stock structure
hypotheses for western North Pacific Bryde’s whale used in the 2007 Implementation whale should be reexamined. The results of this study suggest that the two-stock hypotheses (Hypotheses 2 and 3) could be
more plausible than the one-stock hypothesis (Hypothesis 1) and the three-stock hypothesis (Hypothesis
4).
Sei whale
Bayesian clustering analyses conducted for all samples in the entire research area without information on
their geographic origins presented the highest likelihood probability at K=1 (Tables 7). Figure 7 shows
estimated stock structure at K=2-3. As evident from the figures, additional stocks were indistinguishable.
These results indicated that the samples came from a single stock of sei whale.
In this case, results of the STRUCTURE and those from hypothesis testing (Pastene et al., 2016c), weresimilar, and they support the existence of a single stock in the pelagic region of the North Pacific.
The in-depth assessment of North Pacific sei whale started at the 2015 IWC SC with two initialalternative stock structure hypotheses: i) a single stock in the entire North Pacific as proposed by Kanda
et al. (2015a;b), based on several pieces of evidences included the genetics; and ii) a five-stock
hypothesis proposed in Mizroch (2015), based mainly on the interpretation of mark-recapture data: Japan
coastal; North Pacific pelagic; Aleutian Islands and Gulf of Alaska; eastern North Pacific migratory; andSouthern North American coastal stock (coastal California) (IWC, 2015). As noted earlier the IWC SC
agreed that discriminating between these two hypotheses is difficult in the absence of genetic data fromthe potentially extirpated stocks, and thus both hypotheses are plausible (IWC, 2015).

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The main purpose of this study was to examine genetically all the available genetic samples of the sei
whale in the North Pacific in order to confirm the hypothesis of a single stock in the oceanic regions of
the North Pacific (the ‘North Pacific pelagic’ in the second stock structure hypothesis indicated above).
As noted by the IWC SC it is not possible to check the plausibility of other putative stocks under thesecond hypothesis using genetics analyses because no genetic samples are available from the regions
where these putative stocks are proposed.
Results of the present analysis are in agreement with previous genetic analyses based on smaller sample
sizes (Kanda et al., 2009; 2015a). Kanda et al. (2015b) analyzed all non-genetic evidences that wereconsistent with the single stock in oceanic regions. In fact, the genetic and non-genetic evidencessummarized by Kanda et al. (2015b) were more consistent with the first hypothesis above, a single stockof sei whales in the whole North Pacific.
It is considered that the evidences for proposing the second stock structure hypothesis (five stocks) are
weak and that the IWC SC should evaluate objectively the plausibility of the additional putative stocks
other than the ‘North Pacific pelagic’.
ACKNOWLEDGEMENTS
We thank N. Kanda (NUS Japan) for producing the microsatellite data used in the present analyses.
REFERENCES
Bérubé, M., Aguilar, A., Dendanto, D., Larsen, F., Notarbartolo-di-Sciara, G., Sears, R., Sigurjónsson, J.,
Urban-Ramirez, J., and Palsbøll, P.J. 1998. Population genetic structure of North Atlantic,
Mediterranean Sea and Sea of Cortez fin whales, Balaenoptera physalus (Linnaeus, 1758); analysisof mitochondrial and nuclear loci. Mol. Ecol. 7:585-599.
Bérubé, M., Jørgensen, H., Mcewing, R., and Palsbøll, P.J. 2000. Polymorphic di-nucleotide
microsatellite loci isolated from the humpback whale, Megaptera novaeanglliae. Mol. Ecol. 9:21812183.
Buchanan, F.C., Friesen, M.K., Littlejohn, R.P., and Clayton, J.A. 1996. Microsatellites from beluga
whale Delphinapterus leucas. Mol. Ecol. 5:571-575.
Goto, M., Yoshida, H. and Pastene, L.A. 2106. A note with an estimate of microsatellite genotyping error
rate for common minke whales. Paper SC/66b/DNAx presented to the IWC Scientific Committee,
June 2016 (unpublished). 3pp.
International Whaling Commission. 2015. Report of the Scientific Committee, Annex G. Report of the
Sub-Committee on In-Depth Assessments. J. Cetacean Res. Manage. 16 (suppl.): 176-195.
International Whaling Commission. 2016. Report of the Scientific Committee. Annex P. Process for the
Review of Special Permit Proposals and Research Results from Existing and Completed Permits as
Modified at SC/66a in Light of Resolution 2014-5. J. Cetacean Res. Manage. (Suppl.) 17:409-14.
Kanda, N., Goto, M., Yoshida, H., and Pastene, L.A. 2009. Stock structure of sei whales in the North
Pacific as revealed by microsatellites and mitochondrial DNA analyses. Paper SC/J09/JR32
presented to the JARPN II Review Workshop, Tokyo, January 2009 (unpublished).
Kanda, N., Matsuoka, K., Goto, M. and Pastene, L.A. 2015a. Genetic study on JARPNII and
IWC/POWER samples of sei whales collected widely from the North Pacific at the same time of theyear. Paper SC/66a/IA8 presented to the IWC Scientific Committee, San Diego, May 2015
(unpublished). 8pp.

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Kanda, N., Bando, T., Matsuoka, K., Murase, H., Kishiro, T., Pastene, L.A. and Ohsumi, S. 2015b. A
review of the genetic and non-genetic information provides support for a hypothesis of a single
testock of sei whales in the North Pacific. Paper SC/66a/IA9 presented to the IWC ScientificCommittee, San Diego, May 2015 (unpublished). 17pp.
Mizroch, S.A., Conn, P.B. and AND Rice, D.W. 2015. The mysterious sei whale: Its distribution,
movements and population decline in the North Pacific revealed by whaling data and recoveries ofDiscovery-type marks. Paper SC/66a/IA14 presented to the IWC Scientific Committee, San Diego,
May 2015 (unpublished). 112pp.
Palsbøll, P.J., Bérubé, M., Larsen, A.H., and Jørgensen, H. 1997. Primers for the amplification of tri-and
tetramer microsatellite loci in baleen whales. Mol. Ecol. 6:893-895.
Pastene, L.A., Goto, M., Taguchi, M. and Kitakado, T. 2016a. Updated genetic analyses based on
mitochondrial and microsatellite DNA indicated no sub-structure of the ‘O’ stock common minke
whale in the western North Pacific. Paper SC/F16/JR40 presented to the JARPNII special permit
expert panel review workshop, Tokyo, February 2016 (unpublished). 19pp.
Pastene, L.A., Goto, M., Taguchi, M. and Kitakado, T. 2016b. Updated genetic analyses based on
mtDNA and microsatellite DNA suggest possible stock differentiation of Bryde’s whales between
management sub-areas 1 and 2 in the North Pacific. Paper SC/F16/JR44 presented to the JARPNII
special permit expert panel review workshop, Tokyo, February 2016 (unpublished). 17pp.
Pastene, L.A., Goto, M., Taguchi, M. and Kitakado, T. 2016c. Genetic analyses based on mtDNA control
region sequencing and microsatellite DNA confirmed the occurrence of a single stock of sei whales
in oceanic regions of the North Pacific. Paper SC/F16/JR46 presented to the JARPNII special permit
expert panel review workshop, Tokyo, February 2016 (unpublished). 10pp.
Pritchard, J.K., Stephens, M., and Donnelly, P. 2000. Inference of population structure using multilocus
genotype data. Genetics. 155:945-959.
Valsecchi, E., and Amos, W. 1996. Microsatellite markers for the study of cetacean populations. Mol.
Ecol. 5:151-156.

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Table 1. Sample sizes of Bryde’s whales used in the present study in the microsatellite analyses, by subarea, sex, and source of samples. Only the samples genotyped for the complete microsatellite loci set were
included in the analysis.
Sub-area

Sex
Male
FemaleMale
FemaleMale
Female

West

1

East

2
Total

JARPNII
274
346
14
45

Commerc.
105
66
16
12

679

1
200

POWER

10
20
29
23
82

Jap. dedic.
20
36
1
1

58

Total
399
448
41
78
29
24
1019

Table 2. Sample sizes of sei whales used in the present study for the microsatellite analyses, bylongitudinal sector, sex, and source of samples. Only the samples genotyped for the complete
microsatellite loci set were included in the analysis. Western and Eastern sectors were divided at 180°.
Data source
JARPNII
POWER
Commercial

Sex

SectorWestern
551
623
1
1
88
92
1356

Male
FemaleMale
FemaleMale
Female

Total

Total
Eastern

36
40
67
55
198

551
623
37
41
155
147
1554

Table 3. Results of Bayesian clustering method for samples of Bryde’s whales in sub-area 1E.
K
Log P(k/x)*
Variance*Pr(k/x)**1-5745.21

52.09

~1.00

2

-5876.05

357.89~0.00

3-6004.32

629.35~0.00

4-6061.36

751.07~0.00

5-6000.82

609.39~0.00* log likelihood of the data for different values of K and the variance.
** Probability for each K.
Table 4. Results of Bayesian clustering method for samples of Bryde’s whales in sub-area 1W.
K
Log P(k/x)*
Variance*Pr(k/x)**1-40201

62.23

~1.00

2

-406551218.9~0.00

3-40975

2019

~0.00

4

-41786

3726

~0.00

5

-429446130.4~0.00* log likelihood of the data for different values of K and the variance.
** Probability for each K.

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Table 5. Results of Bayesian clustering method for samples of Bryde’s whales in sub-area 2.
K
Log P(k/x)*
Variance*Pr(k/x)**1-2534.9

44.24

0.91

2

-2537.2

51.82

0.09

3

-2544.8

71

~0.00

4

-2548

79.19

~0.00

5

-2555.5

96.37

~0.00

* log likelihood of the data for different values of K and the variance.
** Probability for each K.
Table 6. Results of Bayesian clustering method for samples of Bryde’s whales in the entire research area.
K
Log P(k/x)*
Variance* Pr(k/x)**
1-48510

62.71

~1.00

2

-490121353.1~0.00

3-493682223.9~0.00

4-501343867.4~0.00

5-517757225.4~0.00* log likelihood of the data for different values of K and the variance.
** Probability for each K.

Table 7. Results of Bayesian clustering method for samples of sei whales in the entire research area.
K
Log P(k/x)
VariancePr(k/x)1-68842.9

69.75

~1.00

2

-69340.5

1653.6~0.00

3-71366.9

5968.8~0.00* log likelihood of the data for different values of K and the variance.
** Probability for each K.

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125E

135E

145E

155E

165E

175E

175W

165W

155W

145W

45N

45N

35N

35N

25N

25N

15N

15N

5N
125E

135E

145E

155E

165E

175E

175W

165W

155W

145W

5N

Figure 1. Sub-areas used during the RMP Implementation of Bryde’s whale (left) and geographicaldistribution of genetic samples from different sources (right): Green: JARPNII samples; Blue: Japanese
dedicated sighting survey samples; Orange: past commercial whaling samples; Red: IWC/POWER survey
samples (from Pastene et al., 2016b).

130E

140E

150E

160E

170E

180E

170W

160W

150W

140W

130W

55N

55N

45N

45N

35N

35N

25N
130E

140E

150E

160E

170E

180E

170W

160W

150W

140W

25N
130W

Figure 2. Sampling locations of sei whales used in the present genetic study. Blue: JARPNII samples;
Red: past commercial whaling samples; Green: IWC/POWER samples. For the statistical analyses
samples were arbitrarily divided into two sectors: Western and Eastern at 180° (from Pastene et al.,2016c).

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Figure 3. Plot of membership probabilities at K=2-5 for Bryde’s whales in sub-area 1E. Each individuals
is characterized by a thin vertical line, which is divided into K colored segments on the basis of theindividual’s membership fractions in K clusters.

Figure 4. Plot of membership probabilities at K=2-5 for Bryde’s whales in sub-area 1W. Eachindividuals is characterized by a thin vertical line, which is divided into K colored segments on the basisof the individual’s membership fractions in K clusters.

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Figure 5. Plot of membership probabilities at K=2-5 for Bryde’s whales in sub-area 2. Each individuals
is characterized by a thin vertical line, which is divided into K colored segments on the basis of theindividual’s membership fractions in K clusters.

Figure 6. Plot of membership probabilities at K=2-5 for Bryde’s whales for the entire research area.
Each individuals is characterized by a thin vertical line, which is divided into K colored segments on thebasis of the individual’s membership fractions in K clusters.

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Figure 7. Plot of membership probabilities at K=2-3 for sei whales in the entire research area. Eachindividuals is characterized by a thin vertical line, which is divided into K colored segments on the basisof the individual’s membership fractions in K clusters.

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