Technical Reports of the Institute of Cetacean Research (2017)

pp. 15–21

Technical Report (not peer reviewed)

What do we know about the stock structure of Antarctic minke whalesin the Indo-Paciﬁc region of the Antarctic? A brief review ofmethodologies and research outputs
Mioko Taguchi*, Mutsuo Goto and Luis A. Pastene
Institute of Cetacean Research, Toyomi-cho 4–5, Chuo-ku, Tokyo 104–0055, Japan*Contact e-mail: taguchi@cetacean.jp

ABSTRACTThis paper presents a brief review of the studies on stock structure of the Antarctic minke whale conductedunder the Japanese Whale Research Program under Special Permit in the Antarctic (JARPA, austral summer
seasons 1987/88–2004/05) and the Second Phase of JARPA (JARPAII, 2005/06–2013/14), and summarizes themain research ﬁndings. The stock structure of the Antarctic minke whale was examined using genetic and nongenetic approaches. Both research programs were conducted in the International Whaling Commission (IWC)Management Areas IIIE (35°–70°E), IV (70°–130°E), V (130°E–170°W) and VIW (170°–145°W). Both genetics,
i.e., RFLP of the whole mitochondrial DNA (mtDNA), sequencing of mtDNA control region, microsatellite DNA,and non-genetic, i.e., morphometric and mean body length at physical maturity analyses were used. Thesestudies provided evidence for the occurrence of at least two stocks in the research area, which were calledʻeastern Indian Ocean stockʼ (I-stock) and ʻwestern South Paciﬁc stockʼ (P-stock), which overlap geographicallyin the central part of the research area. The results of a modelling approach incorporating genetic and morphometric data suggested that the two stocks have a soft boundary (or area of mixing) mainly in the westernpart of Area V (130°–165°E), which changes by year and sex.

INTRODUCTION
The Antarctic minke whale Balaenoptera bonaerensis(Figure 1), like all the other Southern Hemisphere baleen
whales species apart from the Brydeʼs whale (B. edeni),
was managed by the International Whaling Commission(IWC) on the basis of six geographical ʻAreasʼ (Figure 2).
The IWC established these Areas from the 1974/75 austral summer season, based mainly upon informationfrom Mackintosh (1942; 1966) on distribution of catchesof blue, ﬁn and humpback whales (see review by Donovan, 1991). These Areas were used by the IWC for the
implementation of the New Management Procedure(NMP) on baleen whale species.
However, biological evidence for the particular bound-Figure 1.

aries are weak, especially for those species such as the
Antarctic minke whale, whose data were not consideredwhen the original management Areas were established.
In this regard, important questions were formulated
originally by Hoelzel and Dover (1989): ʻAre the Antarctic
minke whales found in two geographically distinct management Areas from two diﬀerent genetic stocks?ʼ orʻAre individuals from more than one genetic stock present in a particular management Area? If so, what levelof interchange may have occurred between diﬀerent
genetic stocks?ʼ Several approaches were used in the past
to identify genetic stocks of this species in the Antarctic
feeding grounds and to determine to what extent genetic
stocks and IWC management Areas coincide.
Studies on stock structure of the Antarctic minke whale

Antarctic minke whale (Balaenoptera bonaerensis).
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Technical Reports of the Institute of Cetacean Research (2017)

started at the end of the decade of the 1970ʼs, and resultsof genetic and non-genetic analyses were revised by the
IWC Scientiﬁc Committee (IWC SC) during the comprehensive assessment (CA) of the species in 1990. All theanalyses presented at the CA were based on samples anddata from commercial pelagic whaling in the Antarctic.
The genetic studies were based mainly on allozyme atthat time, although studies based on mitochondrial andnuclear DNA were also conducted, most of the analyses
involved small sample sizes from only Areas IV and V.
Non-genetic studies revised in the 1990ʼs CA involved
morphology, catch and sighting distribution pattern, analysis of Discovery marks and ecological markers. Resultsfrom the diﬀerent approaches failed to unambiguously
identify any isolated stock in the Antarctic (IWC, 1991).
Studies on stock structure under the Japanese Whale
Research Program under Special Permit in the Antarctic(JARPA) started after the CA. It was considered that JARPA
samples were more useful for studies on stock structure
than the commercial samples, given the wider geographi-

Figure 2.

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IWC Antarctic Areas for the management ofbaleen whale species (except Brydeʼs whale)(Donovan, 1991).

cal coverage of the surveys and that samples were taken
along track-lines in a random mode design. Studies on
stock structure of Antarctic minke whale continued under
the second phase of JARPA (JARPAII).
This paper reviews the studies on stock structure conducted under the JARPA and JARPAII, emphasizing thetechnical aspects and main research outputs.

SAMPLING AND ANALYTICAL APPROACHESJARPAJARPA was conducted during the austral summer seasons
1987/88–2004/05 and the research area was composedof Areas IIIE (35°–70°E), IV (70°–130°E), V (130°E–170°W)
and VIW (170°–145°W) (Figure 2). The main analyticalprocedure used in the genetics and non-genetic studies was hypothesis testing under the null hypothesis of
panmixia.
Genetic approaches
Mitochondrial DNA (mtDNA)
In JARPA, restriction fragment length polymorphisms(RFLP; Box 1.1) was applied for the whole mtDNA (Pastene et al., 1993; 1996). The mtDNA is an extra-chromosomal genome in the cell mitochondria and is inherited
only from the mother. This marker is widely used in constructing intra- and related species phylogenies and inferring evolutionary history.
The mtDNA extracted from a total of 6,256 Antarctic
minke whales was digested with six-base sequence recognition endonucleases (AccI, BanI, EcoRV, HincII, HpaI and
SspI). Restriction fragments were separated by submarine
electrophoresis in 1% agarose gels. After electrophoresis,
the gels were stained with ethidium bromide and wereWhat do we know about the stock structure of Antarctic minke whales in the Indo-Pacific region of the Antarctic?

photographed using Polaroid ﬁlm under an UV irradiation. Distinctive restriction fragment patterns producedby each enzyme were assigned letters. Individuals wereassigned haplotypes consisting of a list of the letters designating the fragment proﬁles produced by each of the six
restriction enzymes. Then, the composite haplotype foreach individual comprises a string of six letters.
Haplotype frequencies were employed to determine
genetic relationships between the samples of the designed strata. Genetic relationships were ﬁrst quantiﬁed using the chi-square statistics for heterogeneity of
mtDNA haplotype frequencies (Roﬀ and Bentzen, 1989).
The level of signiﬁcance obtained by this method is referred to in this paper as the P-value. A P-value smaller
than 0.05 was used as a criterion to reject the null hypothesis of panmixia. Additionally, the quantiﬁcation of
the geographical diﬀerentiation of mtDNA was carriedout using the analysis of molecular variance (AMOVA) of
Excoﬃer et al. (1992).
More detailed descriptions of laboratory and analyticalprocedures were provided in Pastene et al. (1993; 1996).
Microsatellite DNA
In addition to the mitochondrial RFLP analysis, microsatellite analyses (Box 1.2) was also applied on JARPA
samples. Microsatellites are codominant and become apopular marker for many aspects of molecular ecology,
in particular for intraspeciﬁc studies, because of its highmutation rate and polymorphisms compared to othermarkers.
Microsatellite polymorphisms were examined at
six loci in samples from a total of 6,260 minke whales:
EV1, EV104 (Valsecchi and Amos, 1996), GT023, GT211,
GT4195 (Bérubé et al., 2000), and DlrFCB14 (Buchanan
et al., 1996). Polymerase chain reaction (PCR) ampliﬁcations at these loci were performed, which were run withan internal size standard (GENESCAN400HD, Applied Biosystems Japan) using BaseStation100 DNA fragment analyzer. Allelic sizes were determined manually in relation to
the internal size standard and Antarctic minke whale DNAof known size that were re-run on each gel.
The allele frequencies at the six microsatellite lociwere calculated and the departure from expected HardyWeinberg genotypic proportions was tested at each locus
as well as overall loci. The number of alleles per locus,
allelic richness and heterozygosity were also computed.
A conventional hypothesis testing procedure was performed using a heterogeneity test in allele frequencies.
The probability test or Fisherʼs exact test with the Markov chain method was used for the heterogeneity tests
among minke whales in the designed strata. Statisticalsigniﬁcance of the heterogeneity tests was determinedusing the chi-square value obtained from summing thenegative logarithm of P-values over the six microsatellite
loci (Sokal and Rohlf, 1995).
More detailed descriptions of laboratory and analyticalprocedures were provided in Pastene et al. (2006).
Non-genetic approaches
Morphometric analyses
The relationship between body length and longitudinal
strata for ten body measurements of Antarctic minke
whale was investigated using ANCOVA. A cluster analysis was also applied for an estimated average length ofmeasurements to examine the degree of relationships
among whales in six longitudinal strata. A more detailed
description of the analytical procedure was provided in
Hakamada (2006).
Mean body length at physical maturity
Mean body length at physical maturity was comparedamong whales in Areas IIIE, IV, V and VIW for males andfemales. Physically matured individuals were deﬁned as
those with epiphysis fusion occurring in the 6th thoracic
vertebrae. The t-test and ANOVA were used for testing
diﬀerences in mean body length among strata of the
JARPA survey. A more detailed description of the analytical procedure was provided in Bando et al. (2006).
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Technical Reports of the Institute of Cetacean Research (2017)

JARPAII
JARPAII was conducted during the austral summer
seasons 2005/06–2013/14 in the same research area
covered by JARPA. The analyses on stock structure werereﬁned in two ways: by using additional genetic markers
and by applying new analytical approaches.
Genetic approaches
Mitochondrial DNA control region sequencing
In JARPAII, sequencing analysis (Box 1.3) was performed
instead of the mitochondrial RFLP used in JARPA, which
provides higher resolution.
A 338 bp-segment of the mtDNA control region was
sequenced for a total of 2,278 samples using the primers MT4 (Arnason et al., 1993) and Dlp 5R or P2 developed by the ICR. PCR and subsequent cycle sequencing
reaction for each sample were performed following the
manufactureʼs protocol. The nucleotide sequence of eachcycle sequencing product was determined using Applied
Biosystems 3500 Genetic Analyzer (Life Technology)
under standard conditions. Both strand samples weresequenced in their entirety for all samples.
The statistical approaches used for the RFLP analyses
in JARPA (hypothesis testing) were also adopted for the
mitochondrial control region sequence data analyses.
In addition to this, constructing haplotype network andmismatch distribution analysis were conducted.
More detailed descriptions of laboratory and analyticalprocedures were provided in Pastene and Goto (2016).
Microsatellite DNA
Genetic variation was analyzed at 12 microsatellite loci18

(instead of the six used in JARPA) in a total of 2,551
samples: AC045, AC082, AC087, AC137, CA234, GT129(Bérubé et al., 2005), DlrFCB14 (Buchanan et al., 1996),
EV1, EV104 (Valsecchi and Amos, 1996), GT023, GT195,
and GT211 (Bérubé et al., 2000). Laboratory protocols
were the same as in JARPA.
The statistical approaches used for microsatellite
analyses in JARPA were adopted for the JARPAII microsatellite analyses. In addition to this, the Bayesian clustering
approach using STRUCTURE (Pritchard et al., 2000) wasused to determine the number of genetically distinct
populations present in the samples based on informationon the individual genotypes.
More detailed descriptions of laboratory and analyticalprocedures were provided in Pastene and Goto (2016).
Modelling approach
Schweder et al. (2011) developed an integrated approachfor estimating longitudinal segregation of two stocks
using diﬀerent sources of data: morphometric, microsatellite and mtDNA data. Under this approach, areas ofoverlap between stocks were allowed to vary by year andsex. A joint likelihood function was deﬁned for the estimation of mixing proportions and statistical tests without assuming any baseline populations. The approach
was originally applied to the JARPA data (Schweder
et al., 2011) and subsequently to JARPA and JARPAII data.
More detailed analytical procedure was described in Kitakado et al. (2014).

What do we know about the stock structure of Antarctic minke whales in the Indo-Pacific region of the Antarctic?

SUMMARY OF RESULTS
JARPA
A summary of the results of the analyses on stock structure under the JARPA is shown in Table 1.
Taking all results together, Pastene (2006) suggested
that whales in the eastern part of Area III and westernpart of Area VI were more diﬀerentiated than they wereto whales in the Areas IV and V. Therefore, the author
concluded that the single stock scenario cannot be applied to Antarctic minke whales in the feeding grounds ofAreas IIIE–VIW, and proposed the occurrence of at least
two genetic stocks in the research area. The author alsosuggested that this observation is probably related to thebreeding areas in the eastern Indian Ocean and westernSouth Paciﬁc proposed by Kasamatsu et al. (1995). The
following names were proposed for these stocks by Pastene (2006): ʻEastern Indian Ocean Stockʼ (I-stock) andʻWestern South Paciﬁc Ocean Stockʼ (P-stock).
While the microsatellite and morphometric analyses

were unable to identify any boundary between them, the
mtDNA RFLP analyses suggested that the western part ofArea V was more related to the I-stock than the P-stock,
and a boundary in the sector 150°–160°E was proposed.
This was consistent with the results of mark-recapturethat showed movement of whales through 130°E (division between Areas IV and V). No western boundary of
the I-stock and eastern boundary of the P-stock were
proposed.
JARPAII
The main objective here was to test the stock structure
hypothesis derived from JARPA analyses by using a set of
new genetic samples obtained by JARPAII, and mitochondrial control region sequencing and microsatellite DNA
genotyping.
Results of the heterogeneity test for both markers
showed signiﬁcant genetic diﬀerences between whales
in two sectors, the western (35°–130°E) and eastern(165°E–145°W) research area, conﬁrming that diﬀerent

Table 1
Summary of the results on stock structure in JARPA.
Analytical approaches

mtDNA

Sex

Period of sampling

Pattern of geographical variation

References

F+M

1987/88–2004/2005

IIIE=IVW=IVE
VIW=VE
IIIE, IVW, IVE≠VE, VIW
Possible boundary in the sector 150°–160°E

Pastene et al. (2006)

F

1989/90–2003/2004

IVWN, IVWS≠VE, VIW
Some degree of diﬀerence in haplotype
frequency between Areas IIIE and IVW

M

1989/90–2004/2005

No signiﬁcant diﬀerence in haplotype frequency

F+M

1989/90–2004/2005

IVW≠ VE

F

1987/88–2004/2005

IIIE=IVW=IVE=VW
VIW=VE
IIIE, IVW, IVE, VW≠VE, VIW

M

1987/88–2004/2005

VEN≠VES
IIIE=IVW=IVE=VW
VIW=VEN, VES
IIIE, IVW, IVE, VW≠VEN, VES, VIW

F

1987/88–2004/2005

IIIE=IVW=IVE=VW
VIW=VE
IIIE, IVW, IVE, VW≠VE, VIW

1987/88–2004/2005

IIIE=IVW=IVE
VIW=VE
IIIE, IVW, IVE≠VW, VE, VIW

Microsatellites

MBLM

Morphometrics
M

Pastene et al. (2006)

Bando et al. (2006)

Hakamada (2006)

MBLM indicates mean body length of physically matured whales. A sign ʻ=ʼ means that the statistical test found no signiﬁcant difference at a=0.05
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Technical Reports of the Institute of Cetacean Research (2017)

Figure 3.

Hypothesis on stock structure of the Antarctic
minke whale. The upper ﬁgure shows the encounter rates of Antarctic minke whales in 10° squaresof latitude and longitude in waters 0–30°S during
October (Kasamatsu et al., 1995). The high sighting
densities in the eastern Indian Ocean and westernSouth Paciﬁc could correspond to breeding groundsof this species. At least two stocks (I- and P-stocks)
occur in the research area of JARPA and JARPAII,
which mix through a transition area. The transitionarea and the mixing rate appears to change by year
and sex (Pastene and Goto, 2016).

stocks inhabit the Indian and Paciﬁc sectors of the Antarctic (I- and P-stocks) (Pastene and Goto, 2016). On theother hand, the STRUCTURE analysis for the microsatellites did not show genetic structuring of this species. Thisobservation is probably due to a very low level of genetic
diﬀerentiation. Microsatellite DNA analyses also showed
more dispersal in males than females, and also some degree of annual variation.
The results of the modelling approach conﬁrmed theoccurrence of at least two stocks (I- and P-stocks) in the
JARPA/JARPAII research area, which could be related tothe suggested breeding areas in the eastern Indian Ocean
and western South Paciﬁc Ocean (Figure 3). Furthermore,
the results indicated that the spatial distribution of thetwo stocks has a soft boundary (or area of mixing) mainly
in Area VW (130°–165°E) (Figure 3), which changes by
year. Results also suggested possible sex diﬀerences in
the pattern of distribution of the two stocks (Kitakado
et al., 2014).

CONCLUSION
In conclusion, stock structure analyses for the Antarctic
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minke whale conducted under the JARPA and JARPAII
program indicated that the structure of Antarctic minke
whale in Areas IIIE–VIW is more complex than originally
thought: there are at least two stocks (I- and P-stocks),
which overlap geographically in a wide area locatedmainly at 130°–165°E, which changes with year and sex.
Pastene and Goto (2016) postulated that Antarctic
minke whales originating from breeding grounds in thewestern South Paciﬁc (P-stock) have some degree of ﬁdelity to the krill concentration associated with the Ross Sea
Gyre (120°W–180°) (ʻhomeʼ sector). On the other hand,whales originating in the Indian Ocean (I-stock) havesome ﬁdelity to the krill concentration associated withthe gyre located between 90°E and 120°E (ʻhomeʼ sector).
They also postulated that both stocks could expand longitudinally (depending on the particular oceanographic
conditions in a given year) and interact in the middle
sectors and that therefore any boundary (or proportionof the populations in areas with mixing) in the Antarctic
should be considered ʻsoftʼ probably changing annuallyaccording to changes in the oceanographic conditions.

ACKNOWLEDGEMENTS
We gratefully acknowledge the researchers and crew
members that participated in JARPA/JARPAII 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.

REFERENCES
Arnason, U., Gullberg, A. and Widegren, B. 1993. Cetacean
mitochondrial DNA control region: sequences of all extant
baleen whales and two sperm whale species. J. Mol. Biol.
Evol. 70: 960–970.
Bando, T., Zenitani, R. and Fujise, Y. 2006. A study on stock structure in the Antarctic minke whale from the JARPA researcharea based on analysis of body length of physically matured
whales. Paper SC/D06/J11 presented to the IWC Scientiﬁc
Committee JARPA review meeting, December 2006 (unpublished). 7 pp.
Beebee, T.J.C. and Rowe, G. 2008. An Introduction to Molecular
Ecology 2nd edition. Oxford University Press, New York. 400 pp.
Bérubé, M., Jørgensen, H., McEwing, R. and Palsbøll, P.J. 2000.
Polymorphic di-nucleotide microsatellite loci isolated fromthe humpback whale, Megaptera novaeangliae. Mol. Ecol.
9: 2181–2183.
Bérubé, M., Rew, M.B., Skaug, H., Jørgensen, H., Robbins, J.,Best, P., Sears, R. and Palsbøll, P.J. 2005. Polymorphic microsatellite loci isolated from humpback whale, Megaptera
novaeangliae and ﬁn whale, Balaenoptera physalus. Conserv.

What do we know about the stock structure of Antarctic minke whales in the Indo-Pacific region of the Antarctic?

Genet. 6: 631–636.
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.
Donovan, G.P. 1991. A review of IWC stock boundaries. Rep. int.
Whal. Commn (special issue 13): 39–68.
Excoﬃer, L., Smouse, P.E. and Quattro, J.M. 1992. Analysis ofmolecular variance inferred from metric distances among
DNA haplotypes: application to human mitochondrial DNA
restriction data. Genetics 131: 479–491.
Goldstein, D.B. and Schlotterer, C. (eds.). 1999. Microsatellites:
Evolution and Applications. Oxford University Press, Oxford.
368 pp.
Hakamada, T. 2006. Morphometric analysis on stock structurein the Antarctic minke whale based on JARPA samples. Paper
SC/D06/J10 presented to the IWC Scientiﬁc Committee JARPA
review meeting, December 2006 (unpublished). 8 pp.
Hoelzel, A.R. and Dover, G.A. 1989. Molecular techniques for
examining genetic variation and stock identity in cetacean
species. Rep. int. Whal. Commn (special issue 11): 81–120.
International Whaling Commission. 1991. Report of the
Scientiﬁc Committee. Rep. int. Whal. Commn 41: 51–89.
Kasamatsu, F., Nishiwaki, S. and Ishikawa, H. 1995. Breedingareas and southbound migrations of southern minke whales,
Balaenoptera acutorostrata. Mar. Ecol. Prog. Ser. 119: 1–10.
Kitakado, T., Schweder, T., Kanda, N., Pastene, L.A. and Walloe,
L. 2014. Dynamic population segregation by genetics andmorphometrics in Antarctic minke whales. Paper SC/F14/J29
presented to the IWC Scientiﬁc Committee JARPA review
meeting, February 2014 (unpublished). 20 pp.
Lowe, A., Harris, S. and Ashton, P. 2004. Ecological Genetics:
Design, Analysis, and Application. Blackwell Publishing,
Oxford. 326 pp.
Mackintosh, N.A. 1942. The southern stocks of whalebone
whales. Disc. Rep. 22: 197–300.
Mackintosh, N.A. 1966. The distribution of southern blue andﬁn whales. pp. 125–144. In: K.S. Norris (ed.) Whales, Dolphinsand Porpoises. University of California Press, Berkeley and Los
Angeles. xv+789 pp.

Pastene, L.A. 2006. What do we know about the stock structureof the Antarctic minke whale? A summary of studies and hypotheses. Paper SC/D06/J12 presented to the IWC Scientiﬁc
Committee JARPA review meeting, December 2006 (unpublished). 24 pp.
Pastene, L.A. and Goto, M. 2016. Genetic characterization andpopulation genetic structure of the Antarctic minke whale
Balaenoptera bonaerensis in the Indo-Paciﬁc region of theSouthern Ocean. Fish. Sci. 82: 873–886.
Pastene, L.A., Goto, M., Itoh, S. and Numachi, K. 1996. Spatial
and temporal patterns of mitochondrial DNA variation inminke whale from Antarctic Areas IV and V. Rep. int. Whal.
Commn 46: 305–314.
Pastene, L.A., Goto, M. and Kanda, N. 2006. Genetic analysis
on stock structure in the Antarctic minke whales from the
JARPA research area based on mitochondrial DNA and microsatellites. Paper SC/D06/J9 presented to the IWC Scientiﬁc
Committee JARPA review meeting, December 2006 (unpublished). 22 pp.
Pastene, L.A., Kobayashi, T., Fujise, Y. and Numachi, K. 1993.
Mitochondrial DNA diﬀerentiation in Antarctic minke whales.
Rep. int. Whal. Commn 43: 349–355.
Pritchard, J.K., Stephens, M. and Donnelly, P. 2000. Inferenceof population structure using multilocus genotype data.
Genetics 155: 945–959.
Roﬀ, D.A. and Bentzen, P. 1989. The statistical analysis of mtDNA
polymorphisms: chi-square and the problem of small samples. Mol. Biol. Evol. 6(5): 539–545.
Schweder, T., Kitakado, T., Kanda, N., Pastene, L. and Walloe,
L. 2011. Dynamic population segregation by genetics andmorphometrics in Antarctic minke whales. Paper SC/63/IA7
presented to the IWC Scientiﬁc Committee, May 2011 (unpublished). 20 pp.
Sokal, R.R. and Rohlf, F.J. 1995. Biometry: the Principles of
Statistics in Biological Research 3rd edition. Freeman andCompany, New York. 887 pp.
Valsecchi, E. and Amos, W. 1996. Microsatellite markers for the
study of cetacean populations. Mol. Ecol. 5: 151–156.

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