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SC/D06/J9

Genetic analysis on stock structure in the Antarctic minke
whales from the JARPA research area based on
mitochondrial DNA and microsatellites
LUIS A. PASTENE, MUTSUO GOTO, NAOHISA KANDA
The Institute of Cetacean Research, Toyomi-cho 4-5, Chuo-ku, Tokyo 104-0055, Japan

ABSTRACT
Stock structure in the Antarctic minke whales was investigated using mitochondrial DNA (mtDNA)
restriction fragment length polymorphism (RFLP, six restriction enzymes) and microsatellites (six loci),and samples obtained during JARPA surveys from 1987/88 to 2004/05 austral summer seasons in
Areas IIIE, IV, V and VIW. Samples were grouped into the six longitudinal strata used by JARPA
surveys: IIIE (35°-70°E); IVW (70°-100°E) (north and south); IVE (100°-130°E); VW (130°-165°E);
VE (165°E-170°W) (north and south) and VIW (170°W-145°W). The total sample sizes used in the
mtDNA and microsatellite analyses were 6,256 and 6,260 animals, respectively. The level of genetic
diversity was high for both genomes: the nucleon diversity at the mtDNA ranged from 0.856 and 0.891
and the mean expected heterozygosity at the nuclear loci at 0.807 for the total samples. In general
results based on both markers were similar, showing substantial spatial genetic heterogeneity among
the strata. For both genetic markers whales in the most distant geographic strata (IIIE, IV and VE, VIW,
respectively) were differentiated genetically. Mitochondrial DNA was more sensitive to detect structurein the middle longitudinal strata. Our results are consistent with the hypothesis of at least two stocks
distributed in the JARPA research area, possibly related to the proposed breeding areas in the Indian
and western South Pacific Oceans, respectively. The pattern of spatial differentiation found provides
little support for IWC stock boundaries among III, IV, V and VI. The pattern of genetic differentiationof males and females in the feeding grounds was similar according to the mtDNA analysis, which isconsistent with the previous view on whale longitudinal movement based on mark-recapture analysis.
The microsatellite heterogeneity tests suggested more structure in females than males. However nosignificant differences were found when the allele frequencies of males and females were compared ineach of the strata. The results of a fine-scale mtDNA analysis suggested a stock division in the sector
comprised between 150º-160ºE. An area of mixing of stocks around that longitudinal sector can not be
discarded. Site fidelity to particular areas of krill concentrations could explain the spatial segregation ofstocks of Antarctic minke whales in the feeding grounds.
KEY WORDS: ANTARCTIC, FEEDING GROUNDS, GENETICS, ANTARCTIC MINKE WHALE,
EUPHAUSIIDS.
INTRODUCTION
The study on stock structure in the Antarctic minke whale is conducted under the JARPA research
objective titled ‘elucidation of the stock structure of the Southern Hemisphere minke whales to improvestock management’. Information on stock structure is important for a) the estimation of biologicalparameters, which should ideally be carried out on the basis of biologically identified stocks and b) the
future application of the multi-stock rules of the Revised Management Procedure (RMP) (IWC, 1994).
Hoelzel and Dover (1989) defined three categories of stocks: ‘dynamic stock’ is thefundamental unit described by a population model or assessment procedure, ‘management stock’ is thegroup of whales occurring within a specific geographical boundary which is actively or potentiallyexploited and ‘genetic stock’ is a genetically differentiated population within a species. The aim of
JARPA is the identification of geographical and temporal boundaries of genetic stocks.
The Antarctic minke whale like all the other balaenopterids (except the Bryde’s and pygmy
blue whales) are believed to undertake seasonal migrations between feeding grounds south of 60ºS insummer and breeding grounds in the tropical or temperate regions in winter. For this species, however,1there is only a single evidence of such linkage, based on mark-recapture data. Two whales that had
been marked in the Antarctic were recovered off Brazil (Buckland and Duff, 1989). There are also a
few indirect evidences on this linkage based on ecological markers (Nemoto et al., 1980; Ohsumi,1973).
Only one of the breeding grounds has been identified in Brazil based on Discovery markrecovery analysis (Buckland and Duff, 1989). Of interest for the stock structure studies of JARPA in
Antarctic Areas IV and V, however, is the information on location of possible breeding grounds in low
latitudes of the Indian and western South Pacific Oceans. Kasamatsu et al. (1995) examined Japanesesighting data obtained during 1976 to 1987. Based on spatial distribution in tropical and sub-tropicalwaters during the latter half of the conception period of the species, they suggested that there were twobreeding grounds in the eastern and western South Pacific and two others in the eastern and western
Indian Ocean. The breeding grounds that could be related to JARPA research areas in the Antarctic
feeding grounds are those in the Indian Ocean and the western South Pacific. Very little is known about
the pattern of movement of this species between low latitude breeding grounds and high latitude
feeding grounds and we do not know the level of genetic connectivity of whales between these
proposed breeding grounds.
In the austral summer 1987/88, JARPA surveys started in IWC Antarctic Areas IV and V,
under the assumption that these two Areas are occupied by different genetic stocks. At that time there
was little scientific evidence supporting such assumption. Several genetic studies were conducted basedon samples obtained during past commercial whaling operations in the Antarctic, mainly in Areas IV
and V. Most of these studies failed to detect any substantial genetic heterogeneity (Wada and Numachi,
1991; Hoelzel and Dover, 1991; vanPijlen et al., 1991), or just detected weak differences (Amos andDover, 1991), between those Areas.
JARPA samples were subsequently used in genetic studies based on mtDNA, which suggested
substantial genetic heterogeneity in Areas IV and V and some stock structure hypotheses were
proposed, which were not consistent with the current boundaries of Areas IV and V (Pastene et al.,
1993; 1996) (see details of previous genetic studies and hypotheses on stock structure in Document
SC/D06/J12).
In general the interpretation of genetic results in the Antarctic minke whale has been difficult
due to several factors. First and perhaps the most important, is that all the analyses were based
exclusively on samples obtained from the feeding grounds, where possible spatial/temporal mixing ofstocks could complicate the interpretation of results. Ideally genetic analyses should be based on
samples from the breeding grounds where stocks are probably more isolated from each other. Second,
past commercial whaling operations were concentrated around the ice-edge therefore samples based insuch operations could not be representative enough of the genetic diversity of minke whales (Pastene
and Goto, 1999). Third most of the studies that used commercial samples were based on limited sample
sizes. Previous genetic studies suggested that the effect size (expected degree of genetic differentiation
among stocks) is very small in the Antarctic minke whale (Pastene et. al., 1996; Bakke et al., 1996).
This factor and the high genetic diversity of this species means that analysis based on small sample
sizes are misleading and not very informative.
JARPA surveys were conducted systematically in the feeding grounds of Areas IIIE, IV, V
and VIW south of 60°S. Surveys were designed to cover both offshore and ice-edge regions. Therefore
JARPA samples are seen as more representative of the genetic diversity than those from pastcommercial operations. Here a comprehensive genetic study based on all samples collected by JARPA
between 1987/88 and 2004/05 is conducted with the aim to test the hypothesis that minke whales in thefeeding grounds of Areas IIIE, IV, V and VIW are structured into different genetic stocks.
The analysis is based on the maternal inherited mtDNA and bi-parental inherited
microsatellites. Further the analysis is conducted for total samples as well for each sex separately. Suchanalysis allows for the investigation of possible sex-differentiated pattern of dispersal in the feeding
ground. The specific questions to be addressed by our genetic analysis are: Are the Antarctic minke
whales distributed in the feeding grounds of Areas IIIE, IV, V and VIW structured into different
genetic stocks? If so, what is the geographical and temporal pattern of stock structure? Is such pattern
the same for both females and males?

2

MATERIALS AND METHOD
Samples
Antarctic minke whales sampled by JARPA surveys in Areas IIIE (35°-70°E), IV (70°-130°E), V(130°E-170°W) and VIW (170°-145°W) between 1987/88 and 2004/05, were used in the analysis(Figure 1). All samples were taken randomly along pre-defined track-lines (see Document SC/D06/J2).
Grouping of samples
The same geographical sectors used by the JARPA surveys were used in the analysis: IIIE (35°-70°E),
IVW (70°-100°E), IVE (100°-130°E), VW (130°-165°E), VE (165°E-170°W) and VIW (170°-145°W)(Figure 1). Because IVW and VE involve a considerable wider latitudinal range, only in these twocases the JARPA’s north/south division was considered (Figures 1 and 2).
In each stratum samples were further divided on a monthly basis. This temporal analysis
enabled us to check for the possibility of a temporal component in the distribution of stocks. In the
1998/99 survey, the Ross Sea was not accessible and samples in VE were taken only in the northern
part. Therefore samples of stratum ‘VES’ in 1998/99 were included into stratum VEN.
A total of 6,256 minke whale samples (JARPA 1987/88-2004/05) were used for the mtDNA
analysis (2,892 females and 3,364 males) and a total of 6,260 (JARPA 1989/90-2003/04) were used forthe microsatellite analysis (2,875 females and 3,385 males) (Table 1).
Laboratory procedures
Mitochondrial DNA
Routinely about 300mg of liver were used to extract mtDNA using a mini-prep procedure (Pastene etal., 1993). Crude mtDNA (15ul) was digested with 2 or 3 units of six six-base sequence recognition
endonucleases (AccI, BanI, EcoRV, HincII, HpaI and SspI). These enzymes were chosen because they
were known to be polymorphic in the Antarctic minke whale. Digestions were carried out underconditions recommended by the manufacturer (Toyobo) and were completed within three hours at 37°C.
Digestion was stopped by adding 5ul of dye mixture containing 0.1% bromophenol blue, 50% sucrose,
7M urea and 10mM EDTA. Three-hundred milligrams of frozen liver generated enough mtDNA for
about 20 digestions.
Restriction fragments were separated by submarine electrophoresis in 1% agarose gels
(SeaKem LE), using a TPE buffer system (Sambrook et al., 1989). After electrophoresis, the gels were
stained with ethidium bromide (1mg/500ml) for 15min and were photographed using Polaroid 667 film
under 312nm UV irradiation. Sizes of the fragments were obtained in relation to those of the lambda
EcoT14I marker (Takara Shuzo Co.). Distinctive restriction fragment patterns produced by eachenzyme were assigned letters. Individuals were assigned haplotypes consisting of a list of the lettersdesignating the fragment profiles produced by each of the six restriction enzymes. Then, the composite
haplotype for each individual comprises a string of six letters.
Microsatellites
Genomic DNA was extracted from 0.05g of each skin tissue sample using the protocol described bySambrook et al. (1989). Extracted DNAs were then stored in TE buffer (10mM Tris-HCl, 1mM EDTA,
pH 8.0). Microsatellite polymorphisms were analyzed using six sets of primers: EV1, EV104(Valsecchi & Amos 1996), GT023, GT211, GT4195 (Bérubé et al., 2000), and DlrFCB14, (Buchanan
et al., 1996). None of the primers was designed specifically from Antarctic minke whales. All primers
were dinucleotide repeats. Although primer sequences follow those of the original authors, anannealing temperature of each of the loci was optimized for Antarctic minke whales used in this study.
Polymerase chain reaction (PCR) amplifications were performed in 15ul reaction mixturescontaining 10 to 100ng of DNA, 5pmol of each primer, 0.625 U of Ex Taq DNA polymerase (Takara
Shuzo), 2mM of each dNTP, and 10 X reaction buffer containing 20mM MgCl2 (Takara Shuzo).
Amplified products with internal size standard (GENESCAN400HD, Applied Biosystems Japan) wererun on a 6% polyacrylamide denaturing gel (Long Ranger) using BaseStation100 DNA fragment
analyzer (BIO-RAD). Although alleles were visualized using Cartographer software specificallydesigned for the BaseStation, allelic sizes were determined manually in relation to the internal size
standard and Antarctic minke whale DNA of known size that were rerun on each gel.

3

Statistical analysis
Mitochondrial DNA
The degree of sequence divergence between two mtDNA haplotypes was calculated based on the
proportion of DNA fragment shared (formula 5.55 in Nei, 1987). The degree of mtDNA diversity ofminke whales in the strata examined was estimated using the nucleon diversity (Nei and Tajima, 1981).
Haplotype frequencies were employed to determine genetic relationships between the samplesof the designed strata. Genetic relationships were first quantified using the chi-square statistics forheterogeneity of mtDNA haplotype frequencies (Roff and Bentzen, 1989). This Monte Carlo approach
estimates the significance of the chi-square test computed from the raw data. In each trial, 10,000
randomizations of the original data sets were made. The level of significance obtained by this method isreferred in this paper as the p-value. A p-value smaller than 0.05 was used as a criterion to reject thenull hypothesis of panmixia.
In general analyses followed a stepwise fashion. First, each stratum was tested for monthly
variation. Next, north and south strata were tested in IVW and VE. Finally pairwise comparisons wereconducted among the longitudinal strata. Analyses were conducted for male and female separately aswell for both sample combined. Sequential Bonferroni corrections were made in case of multiple tests.
Samples from several years were pooled in each stratum. This required the assumptions thatthe pattern of seasonal movement are the same for a given breeding stock in different years and thatlateral movement on feeding ground and pattern of mixing are similar between years. In someparticular situations analyses by year was conducted to investigate source of genetic heterogeneity.
Additionally, the quantification of the geographical differentiation of mtDNA was carried out
using the analysis of molecular variance (AMOVA) of Excoffier et al. (1992). The AMOVA program(version 1.55) calculates variance components from a distance matrix and the PHI statistic (PHIst)
reflecting the correlation of haplotype diversity at different levels of hierarchical subdivision. The
significance of the variance components and PHIst were tested using a random permutation procedure
available in the program. For the trials, 10,000 randomizations of the original data sets were made. The
level of significance obtained by this procedure is referred in this paper as the p-value. A hierarchicalanalysis was carried out to estimate differentiation among longitudinal strata, between latitudinal
sectors in strata and within strata.
Microsatellite
The GENEPOP program (Raymond and Rousset, 1995) was used for calculation of allele frequencies
at the six microsatellite loci analyzed and tests for the deviations from expected Hardy-Weinberg
genotypic proportions at each of the loci. The number of alleles per locus, allelic richness andheterozygosity were computed using FSTAT 2.9.3 (Goudet, 1995). A conventional hypothesis testingprocedure was performed using a heterogeneity test in allele frequencies. The probability test (orFisher’s exact test) with Markov chain method implemented in the GENEPOP was used for theheterogeneity tests among minke whales in the designed strata. Statistical significance of theheterogeneity tests was determined using the chi-square value obtained from summing the negative
logarithm of p-values over the six microsatellite loci (Sokal and Rohlf, 1995). Sequential Bonferroni
corrections were made in case of multiple tests. For the analysis the same stepwise fashion used in the
mtDNA, was followed.
RESULTS
Mitochondrial DNA
Mitochondrial DNA fragment patterns
The total number of fragment patterns produced by restriction enzymes AccI, BanI, EcoRV, HincII,
HpaI and SspI in the total sample of 6,256 whales were 28, 7, 6, 13, 7 and 31, respectively.
Mitochondrial DNA genome size
The mean mtDNA genome size in the Antarctic minke whale, obtained by averaging the sums of thefragment sizes for all the enzymes was 16,597bp (SD: 668bp).

4Mitochondrial DNA haplotypes
Restriction enzyme digestion of mtDNA from the total sample revealed a total of 157 unique mtDNA
haplotypes.
Mitochondrial DNA diversity
Sequence divergence among haplotypes ranged from 0.00149 to 0.02759. Table 2 shows the estimateof nucleon diversity for minke whales in the primary geographical strata used in this study. The
nucleon diversity ranged from 0.8757 to 0.8911.
Geographical distribution of mtDNA haplotypes
A total of 33 haplotypes (21.0% of the total) were represented by a single specimen. Haplotypes ‘1’ to‘5’ and ‘10’ were the predominant haplotypes (60.1%) found in all strata examined in similar
proportions. The number of ‘private’ haplotypes in strata IIIE, IVW, IVE, VW, VE and VIW were 3, 9,
4, 10, 8 and 1, respectively. Regardless of their frequencies, 39 haplotypes were common to all strata.
Examination of genetic heterogeneity based on chi-square tests
No significant heterogeneity was detected among months in each of the strata for females, males andboth sexes combined, respectively (Table 3). Therefore samples obtained in different months werepooled in each stratum. No significant heterogeneity was found in the comparison between north andsouth samples in IVW so that both samples were combined for further analyses. In stratum VE somedegree of heterogeneity was detected for females (p=0.0126) and total samples (p=0.0111). An
examination of the source of heterogeneity revealed two particular years, 1988/89 and 1992/93. Afterthese samples were excluded, no substantial heterogeneity was detected between north and south
samples in this stratum (p= 0.1182 and p=0.0825 for females and total, respectively). The next analysis
was conducted by excluding these two years in stratum VE for female and total samples.
Tables 4a and 4b show the results of pairwise statistical comparisons among six longitudinal
strata for females and males, respectively. In the case of females the total p-value was 0.0190 while inthe case of males was 0.2164. In both cases several p-values below 0.05 were found with some of them
being significant after Bonferroni correction. Most of these low p-values occurred in the comparisons
between strata in IIIE, IV and stratum VE. Although some differences occur, the general pattern ofvariation between females and males are similar.
Table 4c shows the results of the pairwise statistical comparisons among six longitudinal strata
for female and male samples combined. The total p-value was significant and several pairwise
comparisons resulted in p-values below 0.05. Four of them remained significant after Bonferroni
correction (IIIE-VE, IVW-VE, IVE-VE and IVW-VW). Comparisons between IIIE, IVW, IVE andVIW resulted in p-values below 0.05 but these were not significant after Bonferroni corrections. This
result is probably due to the sample size of VIW, which is the smallest of all strata.
Results of pair-wise comparisons suggest a) no significant differences among IIIE, IVW and
IVE, b) no significant differences between VIW and VE, c) significant differences between IIIE, IVW,
IVE and VE. Stratum VW resulted in significant differences with IVW but not with IVE. A low but notsignificant p-value (0.0188) was obtained in the comparison between VW and VE. As shown in Table
4c whales in stratum VW seems to be differentiated from both IVW and VE.
To investigate further the pattern of longitudinal variation, two additional fine-scale analyses
were conducted. These analyses were conducted for female and male samples combined. Also these
two analyses were conducted for all year samples as well total samples minus the two ‘variable’ years
mentioned above. Because the results were similar only the results for the total samples are shown here.
The first analysis considered a ‘baseline’ sample composed of whales from Areas IIIE+IVW (the mostwestern strata). The haplotype frequencies in this sample were compared with the frequencies in whales
distributed to the east, grouped by 10° longitude. Table 5 shows the results of the statisticalcomparisons. All the comparisons with whales between sector 100°-110°E and 140°-150°E resulted inno significant p-values. Comparisons with whales to the east (from sector 150°-160°E) resulted insignificant p-values. The second analysis used two ‘baseline’ samples: IVW and IVE. The haplotype
frequencies of whales in IVW were compared with those of whales to the east grouped by 10°
longitude. The haplotype frequencies of whales in IVE were compared with those of whales to the west
grouped by 10° longitude. As shown in Table 6a in the comparison based on IVW large p-values were5

obtained until sector 140°-150°E. From sector 150°-160°E most of the p-values resulted significant.
None comparison made to the west (based on IVE) showed a p-value smaller than 0.05 (Table 6b).
Examination of genetic heterogeneity based on AMOVA
Table 7 shows the results of the nested analysis by AMOVA applied to the eight groups. The analysis
was conducted for female and male sampled combined. Only 0.05% of the total molecular variance was
accounted for the longitudinal division; a negative value (-0.01%) was accounted for by latitudinal
division and >99% by diversity within the groups. None of the p-values were significant although the
p-value for PHIst was near-to significant (0.0693). Table 8 shows the results of pairwise comparisonsfor six longitudinal strata (north and south samples were combined in IVW and VE). In this case thetotal p-value was significant (0.0383) and several comparisons resulted in p-values below 0.05 again
involving comparisons among the most distant strata.
Microsatellites
Genetic diversity
The six microsatellite loci were successfully amplified in Antarctic minke whales and werepolymorphic in the samples examined (Table 9). The total number of alleles at the loci in all samples
combined ranged from 10 (DlrFCB14) to 24 (GT195) with an average of 19.5. Samples from all thestrata had the same levels of genetic diversity, as the average number of alleles per locus ranged from
15.8 and 17.7. In addition the average expected heterozygosity per locus was similar among strata
ranging from 0.805 and 0.810.
No statistically significant level of deviation from the Hardy-Weinberg genotypic proportion
was detected through the strata at each of the six loci (Table 9). The same was true for overall loci in all
samples combined (chi-square=16.948, d.f.=12, p=0.152).
Examination of genetic heterogeneity
No significant statistical heterogeneity was detected due to monthly division at the strata (Table 10).
Samples taken in different months were pooled in each stratum. Regarding latitudinal division in strata
IVW and VE, only the female samples in IVW showed a significant degree of heterogeneity (p= 0.000).
An analysis conducted by year at that stratum showed that such heterogeneity was due mainly tosamples from 1989/90 and 1991/92. However significant north/south heterogeneity remained even in
the case these samples were excluded from the analysis. Therefore the subsequent analysis for females
was conducted for strata IVW separated into north and south.
Results of the heterogeneity test for longitudinal variation are shown in Tables 11a, 11b and11c, for females, males and both samples combined, respectively. In the case of females the total pvalue was significant (0.0020) suggesting structure. Pairwise comparisons showed some degree ofheterogeneity between IIIE and IVWS. Most of the other significant heterogeneity detected was due tocomparisons among the most distant strata. Five comparisons remained significant after Bonferroni
correction (IVWN-IVWS, IVWN-VE, IVWN-VIW, IVWS-VE and IVWS-VIW) (Table 11a). In thecase of males the total p-value was not significant (0.317) (Table 11b).
In the case of combined samples the total p-value was significant (0.0390) suggesting
structure. In pairwise comparisons, p-values smaller than 0.05 were observed among the most distantstrata, IIIE, IV and VW, VE, VIW, respectively. Only one comparison remained significant after
Bonferroni correction (IVW-VE) (Table 11c).
DISCUSSION
Consistent with the results of previous genetic studies, values of nucleon diversity (mtDNA) and
expected heterozygosity (microsatellites) suggested a high degree of genetic diversity in the Antarctic
minke whale. The high genetic diversity reflects in part the abundance of this species in the Southern
Hemisphere. In fact, some previous studies estimated high N (or Ne) for this species (IWC, 1991).
Our genetic study was conducted in order to respond some research questions outlined earlier,which are addressed below.

6

Stock structure
Are the Antarctic minke whales distributed in the feeding grounds of Areas IIIE, IV, V and VIWstructured into different genetic stocks?
Significant levels of genetic heterogeneity detected for both mtDNA and microsatellites suggest that
Antarctic minke whales do not distribute randomly in the research area of Areas IIIE, IV, V and VIW,
rather these levels indicate a degree of stock segregation in the feeding grounds. Our genetic analyses
therefore, based on two different genetic markers, suggest stock structure of this species in the feeding
grounds. The mtDNA heterogeneity found is consistent with previous studies based on the same marker(Pastene et al., 1993; 1996). The present microsatellite analysis was thought more informative than the
allozyme analysis conducted in the past (Wada and Numachi, 1991).
What is the geographical and temporal pattern of stock structure?
Our statistical analysis of haplotype and allele frequencies data failed to detect any substantial temporal(monthly) heterogeneity in the research area. It should be noted, however, that when samples are
divided by month in each stratum the sample sizes become small. Then the power of this specificanalysis is probably low.
The geographic pattern of structure is consistent with at least two-stocks involved in these
Areas, which appear to be structured longitudinally. Probably these stocks are related to the breedingareas in the eastern Indian Ocean and western South Pacific suggested by Kasamatsu et al. (1995).
These authors examined sighting data collected by dedicated Japanese sighting surveys in low latitudes.
After consideration of the sighting effort these authors found high encounter rates of Antarctic minke
whales in the eastern Indian Ocean (10º-20ºS; 100º-110ºE) and in the western South Pacific (10º-20º
S; 150º-170ºW), which were attributed to breeding areas of the Antarctic minke whale (Figure 3).
These results are consistent with the significant differences in alleles and haplotype frequencies foundbetween the most distant strata (Areas III, IVW and VE, VIW, respectively); whales in Areas IIIE andIV could be related to breeding grounds in the Indian Ocean and whales in Areas VIW and VE tobreeding grounds in the western South Pacific. Assuming this two-stock scenario, the fine-scale
analysis using mtDNA demonstrated that it is possible to identify a longitudinal sector where bothstocks segregate, 150º-160ºE, near the boundary between sectors VW and VE. Therefore the generalstock structure archetype for the Antarctic minke whale in the feeding grounds is multiple stocks withspatial (longitudinal) segregation. However given the absence of geographical barriers the possibility ofa sector where the two stocks mix can not be discarded. It should be noted that the pattern of stock
structure found by our analysis is not consistent with the actual longitudinal boundaries of the IWC
Antarctic management Areas.
It is concluded that Antarctic minke whales are genetically structured in the feeding grounds
however the genetic divergence between stocks in the Antarctic is very small as revealed by a mtDNA
analysis that compared whales from two broad sectors: 70º-165ºE and 165ºE-145ºW. The PHIst fromthis comparison was 0.001, which was significant (p=0.0069).
Some degree of mtDNA latitudinal heterogeneity was observed for females in stratum VE,
which were not observed by the microsatellite analysis. On the other hand some degree of
microsatellite latitudinal heterogeneity was observed for females in stratum IVW, which were notobserved by the mtDNA analysis. The interpretation of such apparent heterogeneity is difficult as
results derived from both markers were inconsistent. Further heterogeneity in IVW was due to a single
locus (Ev1) only. Although the possibility of additional structure to the west of the research area (e.g.
intrusion and mixing with a third stock around Area IIIE) can not be discarded at this stage, suchpossibility is considered weak (see also Pastene et al., 1996). As mentioned earlier the very highgenetic diversity in this species sometimes produces misleading results when the analyses are based on
smaller sample sizes. With regard the apparent mtDNA heterogeneity in VE, the alternative explanationis that the pattern of distribution (and mix) of stocks around longitude 165ºE change by year.
Our primary analysis was conducted by pooling the samples from several austral summer
seasons under several assumptions. Analysis by austral summer seasons have been attempted in thepast, however, these have necessarily been based on smaller number of samples. It has been difficult tointerpret results of statistical analysis of samples grouped by year. Again given the very high genetic
diversity, annual sample size may not be large enough to represent the stock diversity. Notwithstanding
when the haplotype frequencies were compared among years in each of the six longitudinal strata
examined, no significant differences were found.

7

Is the pattern of structure the same for females and males?
According to the mtDNA analysis similar pattern of genetic heterogeneity was observed between
females and males. This result suggests that the pattern of lateral movement in the feeding grounds issimilar between sexes. This is further corroborated by statistical analysis that compared the haplotype
frequencies between males and females in each of the strata examined, which showed no significant
heterogeneity (data not shown). This is consistent with the results of studies of mark-recapture
conducted in the past based on commercial samples, which found no significant differences between
sexes in the average longitudinal distance moved (Kato et al., 1993). The results of the heterogeneity
test based on microsatellite found more structure in females suggesting more lateral movement ofmales in the feeding ground. However the statistical analysis comparing allele frequencies between
males and females in each of the strata showed no significant heterogeneity, except in the case of
stratum IVWN (data not shown). In conclusion our genetic results are more consistent with the view ofa similar pattern of lateral movement between sexes in the feeding ground.
Mechanism of segregation of stocks in the feeding groundAs mentioned above the genetic results are consistent with the occurrence of at least two stocks of the
Antarctic minke whale in the JARPA research area, which are segregated around the longitudinal sector
150º-160ºE. What kind of mechanism is responsible to keep segregated different stocks in the feeding
grounds in absence of geographical barriers? The main prey species of the minke whale in the Antarctic
is the krill (Euphausia superba). Whales migrating south from their respective breeding grounds will
not need to conduct extensive longitudinal movements in the feeding grounds if food enough isavailable in their ‘home’ longitudinal sector. If the availability of krill is not large enough in their‘home’ sector, minke whales will need to move longitudinally in search of other areas of krill
concentration. Results of our genetic analysis showed a longitudinal segregation of stocks in the
Antarctic suggesting a degree of fidelity of stocks to specific feeding grounds.
Following the above logic, distribution and pattern of movement of different stocks of minke
whales in the feeding ground will depend on the distribution of their key prey species, the krill, which
in turn depends on bottom topography, sea-ice and hydrographic features (Ichii, 1990). Krill is acircumpolar species, with their main centers of concentration around island groups and along thecontinental shelf break and slope (Nicol, 2006). Around the Antarctic continent, a series of gyres link
the westward-flowing Coastal Current (CC) and the Antarctic Circumpolar Current (ACC) andprevious studies have suggested that variation in abundance of krill are linked to the gyral circulation
pattern (Nicol, 2006). Figure 4 reproduced from Nicol (2006), shows that historical krill distribution
overlaid on maps of known current features suggesting that krill concentrations may be related tosurface circulation.
Our genetic results suggest a segregation of stocks around the longitudinal sector 150º-160ºE.
These longitudes coincide with the aperture of the Ross Sea and from the oceanographic point of view
this sector is influenced by the Ross Sea Gyre (Figure 4). Based on these antecedents and the results ofour genetic study, it is postulated that Antarctic minke whales originating from breeding grounds in thewestern South Pacific have some degree of fidelity to the krill concentration associated to the Ross Sea
Gyre (‘home’ sector). On the other hand whales originating in the Indian Ocean have some fidelity to
the krill concentration related to the gyre located between 90º-120ºE (‘home’ sector) (Figure 4). Bothstocks could expand longitudinally interacting in the area of concentration located between 150º-180ºE(Figure 4). Therefore any boundary (or proportion of stocks in areas of mixing) in the Antarctic should
be considered as ‘soft’.
Consistency with results of independent approaches
In reviewing the results on stock structure derived from JARPA, the Scientific Committee noted that only
preliminary conclusions can be drawn at this stage and that more concrete conclusions will be able to bemade following the completion of different analyses. It further supported the suggestion that additional
analyses using alternative groupings and analytical methods should be conducted (IWC, 2004).
The most effective way to address questions on stock identity is to consider results fromseveral techniques, genetics and non-genetics (Donovan, 1991; Pastene et al., 2000; Perrin, 2001; Rughet al., 2003). In the case of the Antarctic minke whale the application of multi-approaches to investigate
stock identity is particularly desirable because previous genetic analysis suggested that the effect size inthis species is low. Therefore it is desirable that results obtained using genetics are checked using8

independent non-genetic markers. Morphometric and average length of physical maturity analyses wereconducted to examine stock structure using JARPA samples (see Documents SC/D06/J10 and
SC/D06/J11). In general results of these studies are broadly consistent with those of the genetic
analysis that showed the Antarctic minke whales structured into at least two genetic stocks.
Results on mark-recapture analysis conducted during the time of commercial whaling in theareas surveyed by JARPA could assist greatly in the interpretation of results on stock structure found in
this study. Kato et al (1993) used information from marks both released and recovered within the
Antarctic i.e. 110 marks or 101 recaptured individuals. All but one mark were recovered duringcommercial whaling operations. One mark in his analysis was recovered during a JARPA survey (3Feb. 1992). Results relevant to our genetic study were: a) patterns of longitudinal movement are very
similar between sexes, which is consistent with the genetic results and b) although some individuals
moved great distances (over 100° longitude), most whales appear to return to relatively close to thesector in which they were marked (30°-40° longitude apart), which is consistent with a degree offidelity to some specific feeding grounds proposed by the genetic analysis.
Mark-recapture analysis showed marked movement of whales through longitude 130ºE(division between Areas IV and V), which is also consistent with the results of the genetic analysis.
With regard boundaries, Kato et al. (1993) noted that the absence of mark crossing at 80ºE and 160ºE
suggests the possibility of separate feeding stocks. Following an examination of mark distribution andcatching effort they concluded that discontinuity at 80ºE could be more suggestive of a boundary
between stocks than that at 160ºE.
On this regard mark-recapture results are partially consistent with the boundary suggested bygenetic analysis. While the boundary at 160°E is consistent with our proposal around that longitude,boundary at 80°E proposed by mark-recapture analysis is not consistent with the results of our study (atleast in regard the mtDNA analysis), which suggested that Area IIIE is similar to Area IV.
It should be noted that two other marks recovered during JARPA surveys were not available
for the Kato et al. (1993)’s analysis. One of them (elapsed time of 12 years) was marked in the easternpart of Area V and recovered in the western part of this Area (Fujise et al., 1993). The other one(elapsed time of 21 years) was marked in the western part of Area V and recovered in the eastern partof Area IV (Ishikawa et al., 2002).
Further research needs
The following topics are recommended for future studies on stock structure:a)Yearly changes in stocks distribution and boundaries (or changes in the proportion of stocks inareas of mixing) in the region 150ºE-180ºshould be investigated in the future in relation tobottom topography, currents and krill distribution.
b) Western boundary (or areas of mixing) of the stock originating in the eastern Indian Ocean
and the eastern boundary (or areas of mixing) of the stock originating in the western Pacific
Ocean should be investigated in the future.
c) To elucidate the possibility of mixing in the feeding ground at a better resolution, samples andgenetic analysis of whales from the breeding grounds are necessary. Experiments of satellite
tracking would be very useful to examine lateral movement and possible mixing in the feeding
grounds as well movement between feeding grounds and lower latitudes wintering grounds.
ACKNOWLEDGEMENTS
We thank researchers and crew members of the 1987/88-2004/05 JARPA surveys for their effort incollecting the data and samples used in this study. H. Hatanaka, S. Ohsumi and H. Murase (ICR)
contributed with useful discussion and comments that improved this paper.
REFERENCES
Amos, W. and Dover, G.A. 1991. The use of satellite DNA sequences in determining populationdifferentiation in the minke whale. Rep. int. Whal. Commn (special issue 13):235-24.

9

Bakke I, Johansen S, Bakke Ø, El-Gewely MR (1996) Lack of population subdivision among theminke whales (Balaenoptera acutorostrata) from Icelandic and Norwegian waters based on
mitochondrial DNA sequences. Marine Biology 125:1-9.
Bérubé, M., Jørgensen, H., Mcewing, R., Palsbøll, P.J. 2000. Polymorphic di-nucleotide microsatellite
loci isolated from the humpback whale, Megaptera novaeanglliae. Mol. Ecol., 9, 2181-2183.
Buchanan, F.C., Friesen, M.K., Littlejohn, R.P., Clayton, J.A. 1996. Microsatellites from beluga
whale Delphinapterus leucas. Mol. Ecol., 5, 571-575.
Buckland, S.T. and Duff, E.I. 1989. Analysis of the Southern Hemisphere minke whale mark-recovery data.
Rep. int. Whal. Commn (special issue 11): 121-43.
Donovan, G. 1991. A review of IWC stock boundaries. Rep. int. Whal. Commn (special issue 13): 3968.
Excoffier, L., Smouse, P.E. and Quatro, J.M. 1992. Analysis of molecular variance inferred from metricdistances among DNA haplotypes: application to human mitochondrial DNA restriction data.
Genetics 131:479-91.
Fujise, Y., Zenitani, R., Saino, S., Itoh, S., Kawasaki, M., Matsuoka, K. and Tamura, T. 1993. Cruise
report of the 1992/93 Japanese research under the special permit for Southern Hemisphereminke whales. Paper SC/45/SHBa12 presented to the IWC Scientific Committee, April 1993
(unpublished). 39pp.
Goudet, J. 1995. FSTAT, version 1.2: a computer program to calculate F-statistics. J. Hered., 86,
485-486.
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.
Hoelzel, A.R. and Dover, G.A. 1991. Mitochondrial D-loop DNA variation within and between populationsof the minke whale (Balaenoptera acutorostrata). Rep. int. Whal. Commn (special issue 11): 171181.
Ichii, T. 1990. Distribution of Antarctic krill concentrations exploited by Japanese krill trawlers and minke
whales. Proc. NIPR Symp. Polar Biol. 3:36-56.
International Whaling Commission. 1991. Report of the Scientific Committee. Rep. int. Whal. Commn
41:51-89.
International Whaling Commission. 1994. Report of the Scientific Committee, Annex H. The Revised
Management Procedure (RMP) for Baleen Whales. Rep. int. Whal. Commn 44:145-52.
International Whaling Commission. 2004. Report of the Scientific Committee. J. Cetacean Res.
Manage. 6 (suppl.): 1-411.
Ishikawa, H., Otani, S., Mogoe, T., Kiwada, H., Tohyama, D., Yoshida, T., Hayashi, T., Nagamine, M.,
Fukutome, K., Koyanagi, T., Fujihira, T., Sasaki, T., Ishihara, T. and Mori, M. 2002. Cruise
report of the Japanese Whale Research Program under Special Permit in the Antarctic (JARPA)
Area IV and Eastern Part of Area III in 2001/2002. Paper SC/54/O18 presented to the IWC
Scientific Committee, May 2002 (unpublished). 20pp.
Kasamatsu, F., Nishiwaki, S. and Ishikawa, H. 1995. Breeding areas and southbound migrations ofsouthern minke whales Balaenoptera acutorostrata. Mar. Ecol. Prog. Ser. 119:1-10.
Kato, H., Tanaka, E. and Sakuramoto, K. 1993. Movements of southern minke whales in the Antarctic
feeding grounds from mark-recapture analyses. Rep. int. Whal. Commn 43:335-342.
Nei, M. 1987. Molecular Evolutionary Genetics. Columbia University Press, New York. x+512pp.

10

Nei, M. and Tajima, F. 1981. DNA polymorphism detectable by restriction endonucleases. Genetics 97:
145-63
Nemoto, T., Best, P.B., Ishimaru, K. and Takano, H. 1980. Diatom films on whales in south African waters.
Sci. Rep. Whales Res. Inst., Tokyo 32:97-103.
Nicol, S. 2006. Krill, Currents, and Sea Ice: Euphausia superba and its changing environment. Bioscience
56 (2): 111-120.
Ohsumi, S. 1973. Find of marlin spear from the Antarctic minke whales. Sci. Rep. Whales Res. Inst., Tokyo
25:237-239.
Pastene, L.A., Kobayashi, T. and Numachi, K. 1993. Mitochondrial DNA differentiation in Antarctic minke
whales. Rep. int. Whal. Commn 43:349-355.
Pastene, L.A., Goto, M., Itoh, S. and Numachi, K. 1996. Spatial and temporal patterns of mitochondrial
DNA variation in minke whale from Antarctic Areas IV and V. Rep. int. Whal. Commn 46: 305-314.
Pastene, L.A. and Goto, M. 1999. Further spatial and temporal analysis of mitochondrial DNA
variation in minke whales from Areas III and IV considerations on the pack-ice distribution.
Paper SC/51/CAWS11 presented to the IWC Scientific Committee, May 1999 (unpublished).
11pp.
Pastene, L. A., Goto, M. and Fujise, Y. 2000. Review of the studies on stock identity in the minke
whale Balaenoptera acutorostrata from the North Pacific. Paper SC/F2K/J1 presented to IWC
Scientific Committee Workshop to review JARPN, February 2000 (unpublished).
Perrin, W. 2001. Draft review of the utility of non-genetic data for differentiating stocks of whales.
Paper SC/53/SD2 presented to the IWC Scientific Committee, July 2001 (unpublished).
Raymond, M. and Rousset, F. 1995. GENEPOP (version 1.2): population genetics software for exact
tests and ecumenicism . J. Heredity 86:248-249.
Roff, D.A. and Bentzen, P. 1989. The statistical analysis of mtDNA polymorphisms: chi-square and the
problem of small samples. Mol. Biol. Evol. 6:539-45.
Rugh, D., DeMaster, D., Rooney, A., Breiwick, J., Shelden, K. and Moore, S. 2003. A review of
bowhead whale (Balaena mysticetus) stock identity. J. Cetacean Res. Manage 5(3):267-279.
Sambrook, J., Fritsch, E.F., and Maniatis, T. (1989). Molecular cloning: A laboratory manual. 2nd Ed.
Cold Spring Harbor Laboratory, New York.
Sokal, R.R., and Rohlf, F.J. (1995). Biometry: the Principles of Statistics in Biological Research.
Freeman and Company, New York.
Valsecchi, E. and Amos, W. 1996. Microsatellite markers for the study of cetacean populations. Mol.
Ecol., 5, 151-156.
van Pijlen, I.A., Amos, B. and Dover, G.A. 1991. Multilocus DNA fingerprinting applied to population
studies of the minke whale Balaenoptera acutorostrata. Rep. int. Whal. Commn (special issue13):245-254.
Wada, S. and Numachi, K. 1991. Allozyme analyses of genetic differentiation among the populations
and species of the Balaenoptera. Rep. int. Whal. Commn (special issue 13): 125-54.

11

Table 1: Number of samples examined by geographical strata, genetic marker and sex.
Areas IIIE and IV
IIIE
F
218
227

mtDNA
Microsatellites*

IVWN
M
311
322

F
160
164

M
640
676

F
205
184

M
302
320

IVWS
F
M
462
497
488
534

M
507
491

F
622
619

IVW
F
622
652

IVE
M
799
854

F
601
526

M
633
558

M
675
656

VIW
F
M
170
306
179
319

Areas V and VIW
VW
F
454
488

mtDNA
Microsatellites*

VEN

VES

VE
M
168
165

F
826
803

* Sample size changes among loci. Figures shown are the maximal sample size used among the loci.

Table 2: Nucleon diversity in the Antarctic minke whale, by longitudinal strata. Sample sizes inparenthesis.
Strata (sample size)
IIIE (529)
IVW (1,421)
IVE (1,234)
VW (1,094)
VE (1,502)
VIW (476)

Number of haplotypes (private)65 (3)
110 (9)102 (4)
97 (10)104 (8)71 (1)

Nucleon diversity
0.8898+/- 0.0103
0.8911+/- 0.0062
0.8757+/- 0.0075
0.8795+/- 0.0079
0.8775 +/- 0.0068
0.8822 +/- 0.0114

Table 3: Results of the heterogeneity test for monthly mtDNA variation in each geographic stratum, bysex.
Strata
IIIE

IVWN

IVWS

IVE

VW

VEN

VES

VIW

Sex
F
M
Total
F
M
Total
F
M
Total
F
M
Total
F
M
Total
F
M
Total
F
M
Total
F
M
Total

Chi-square p-value
0.42710.5026
0.27400.35210.57910.07200.61420.20230.05280.15140.30430.1926
0.98590.50600.59290.55990.77150.56470.12480.95630.36840.60620.28800.429812

Table 4a: Results of the heterogeneity test for longitudinal mtDNA variation in female samples. The
total P-value was 0.0190 suggesting structure. P-values smaller than 0.05 are underlined. Bold show
those P-values that remain significant after Bonferroni corrections.

IIIE

IIIE
(218)

IVW
(622)

IVE
(601)

VW
(454)

VE
(659)

VIW
(170)

-

0.47990.11490.00320.00090.3639-0.35740.05660.00460.3529-0.32270.12720.6655-0.02040.0604-0.3176

IVW
IVE
VW
5E
6W

-

Table 4b: Results of the heterogeneity test for longitudinal mtDNA variation in male samples. The total
P-value was 0.2164. P-vales smaller than 0.05 are underlined. Bold show those P-values that remain
significant after Bonferroni corrections.

IIIE

IIIE
(311)

IVW
(799)

IVE
(633)

VW
(640)

VE
(675)

VIW
(306)

-

0.58430.75540.34370.16190.1176-0.88520.21040.00040.0857-

0.66610.00520.1119-0.33990.7267-0.6785

IVW
IVE
VW
5E
6W

-

Table 4c: Results of the heterogeneity test for longitudinal mtDNA variation in total samples (F+M).
The total P-value was 0.0024 suggesting structure. P-values smaller than 0.05 are underlined. Boldshow those P-values that remain significant after Bonferroni corrections.

IIIE
IVW
IVE

IIIE
(529)

IVW
(1,421)IVE(1,234)VW(1,094)VE(1,283)

VIW
(476)

-

0.78120.04750.01250.00020.0055-0.93750.00240.00020.0283-0.45370.00030.0261-0.01880.3969-0.4397

VW
VE
VIW

-

13

Table 5: Results of the comparison of mtDNA haplotype frequencies between Areas IIIE+IVW(n=1,950) and 10°-sectors in IVE, VW and VE for total samples (female+male). Significant p-values
are in bold.
Sectors(IVE) 100-110E (394)(IVE) 110-120E (443)(IVE) 120-130E (397)(VW) 130-140E (278)(VW) 140-150E (309)(VW) 150-160E (418)(VW-E) 160-170E (243)(VE) 170E-180 (599)(VE) 180-170W (605)(VIW) 170W-145W (620)

Chi-square-pvalue
0.91140.28590.23440.26870.12280.00010.00440.02530.00010.0024

Table 6a: Results of the comparison of mtDNA haplotype frequencies between Area IVW (n=1,421)
and 10°-sectors in IVE, VW and VE for total samples (female+male). Significant p-values are in bold.
Sectors(IVE) 100-110E (394)(IVE) 110-120E (443)(IVE) 120-130E (397)(VW) 130-140E (278)(VW) 140-150E (309)(VW) 150-160E (418)(VW-E) 160-170E (243)(VE) 170E-180 (599)(VE) 180-170W (605)(VIW) 170W-145W (620)

Chi-square p-value
0.99030.76160.60050.50400.21150.00090.0366
0.09200.00070.0167

Table 6b: Results of the comparison of mtDNA haplotype frequencies between Area IVE (n=1,234)
and 10°-sectors in IVW and IIIE, for total samples (female+male).
Sectors(IVW) 90-100E (440)(IVW) 80-90E (401)(IVW) 70-80E (580)(IIIE) 60-70E (224)(IIIE) 50-60E (150)(IIIE) 35-50E (155)

Chi-square p-value
0.43550.8874
0.66820.05290.41660.2036

Table 7: Results of the nested analysis of molecular variance of Antarctic minke whale mtDNA
haplotypes in Areas IIIE, IV, V and VIW. The p-value is the probability of a more extreme variancecomponent or PHIst than that observed, in comparison to a null distribution of these values on 10,000
random permutations of the data matrix. PHIct and the among longitudinal sectors variance component
involves the permutation of whole longitudinal/latitudinal groups among longitudinal sectors; thePHIsc and the among latitudinal groups within longitudinal sectors involves the random permutation ofindividuals among longitudinal/latitudinal groups within longitudinal sectors; the PHIst and the withinlongitudinal/latitudinal groups components involves the random permutation of individuals among theeight longitudinal/latitudinal groups.
Among long. Sectors
Among latitudinal
Within groups

df
5
2
6,248

% total variance
0.05
-0.01
99.96

14

PHI
CT: 0.000
SC: -0.000
ST: 0.000

P
0.27500.47770.0693

Table 8: Haplotypic correlation (PHIst, below diagonal) and their probabilities (P, above diagonal)
among six (north/south combined in IVW and VE) longitudinal groups of Antarctic minke whales from
Areas IIIE, IV, V and VIW. In parenthesis is the sample size. Underline indicates those haplotypiccorrelations presenting a p-value below 0.05. The total p-value was 0.0383 suggesting structure.
IIIE
(529)

IVW
(1,421)IVE(1,234)VW(1,094)VE(1,502)

VIW
(476)

IIIE

-

0.37910.19930.05230.03230.0500IVW

0.0001-0.92410.07230.00650.0328IVE

0.0005-0.0004-

0.41120.07270.1243VW

0.00130.0006-0.0000-

0.82780.7884VE

0.00140.00130.0006-0.0003-

0.9895VIW

0.00200.00160.0008-0.0006-0.0009-15

Table 9: Number of alleles (#A), allelic richness (AR), expected heterozygosity (He) and test result for
expected Hardy-Weinberg genotypic proportion (HW) at six microsatellite loci analyzed in the
Antarctic minke whale.
IIIE

IVWN

IVWS

IVE

VW

VEN

VES

VIW

Total

15

16

14

17

18

17

16

18

22

EV1
#A
AR

14.7

16.0

12.4

14.3

15.3

15.8

14.5

17.8

14.8

He

0.817

0.821

0.820

0.817

0.821

0.829

0.821

0.821

0.821

HW

0.749

0.390

0.199

0.774

0.269

0.396

0.047

0.330

#A

17

16

17

17

16

17

16

16

EV104
17

AR

17.0

16.0

16.5

16.7

16.0

16.7

16.0

16.0

16.4

He

0.907

0.905

0.903

0.908

0.906

0.907

0.908

0.908

0.906

HW

0.284

0.782

0.258

0.810

0.919

0.061

0.867

0.973

GT211
#A

19

18

22

21

22

20

21

19

23

AR

18.9

18.0

19.7

19.1

19.4

19.3

20.3

19.0

19.4

He

0.891

0.891

0.896

0.888

0.893

0.893

0.892

0.894

0.892

HW

0.069

0.046

0.294

0.533

0.833

0.602

0.482

0.470

DlrFCB14
#A

9

8

8

8

9

8

8

8

10

AR

8.6

8.0

7.4

7.5

8.0

7.4

7.1

7.9

7.6

He

0.480

0.476

0.446

0.461

0.456

0.478

0.453

0.450

0.463

HW

0.921

0.090

0.591

0.989

0.220

0.362

0.154

0.037

#A

19

19

21

23

20

17

20

19

GT195
24

AR

18.9

19.0

19.7

20.7

18.3

16.8

18.8

18.9

19.2

He

0.870

0.860

0.872

0.864

0.867

0.864

0.866

0.862

0.866

HW

0.185

0.665

0.643

0.302

0.721

0.551

0.569

0.830

#A

19

18

21

19

21

19

18

19

GT23
22

AR

18.8

18.0

19.3

18.6

19.5

18.8

17.8

18.9

19.0

He

0.895

0.888

0.892

0.892

0.896

0.888

0.896

0.892

0.892

HW

0.110

0.389

0.458

0.741

0.114

0.881

0.103

0.547

All loci
#A

16.3

15.8

17.2

17.5

17.7

16.3

16.5

16.5

19.7

AR

16.2

15.8

15.8

16.1

16.1

15.8

15.7

16.4

16.1

He

0.810

0.807

0.805

0.805

0.807

0.810

0.806

0.805

0.807

HW

0.173

0.188

0.455

0.950

0.512

0.451

0.139

0.447

16

Table 10a: Results of the heterogeneity test for monthly female microsatellite variation in eachgeographic stratum.
SectorMicrosatellite locus
EV1

EV104

GT211

DlrFCB14

GT195

GT23

All loci

IIIE

0.227

0.549

0.434

0.207

0.485

0.670

0.509

IVWN

0.281

0.255

0.854

0.589

0.873

0.960

0.858

IVWS

0.596

0.199

0.707

0.139

0.954

0.500

0.582

IVE

0.383

0.924

0.651

0.155

0.255

0.680

0.601

VW

0.924

0.619

0.328

0.054

0.291

0.583

0.387

VEN

0.005

0.906

0.228

0.569

0.931

0.406

0.151

VES

0.841

0.113

0.596

0.615

0.554

0.438

0.656

VIW

0.057

0.441

0.899

0.501

0.520

0.706

0.533

Table 10b: Results of the heterogeneity test for monthly male microsatellite variation in eachgeographic stratum.
SectorMicrosatellite locus
EV1

EV104

GT211

DlrFCB14

GT195

GT23

All loci

IIIE

0.085

0.411

0.566

0.840

0.772

0.287

0.512

IVWN

0.011

0.638

0.558

0.832

0.285

0.520

0.223

IVWS

0.739

0.202

0.984

0.112

0.610

0.964

0.678

IVE

0.613

0.540

0.276

0.874

0.442

0.687

0.827

VW

0.859

0.530

0.257

0.412

0.879

0.946

0.893

VEN

0.560

0.621

0.961

0.703

0.512

0.485

0.931

VES

0.845

0.906

0.801

0.400

0.633

0.111

0.776

VIW

0.415

0.507

0.236

0.092

0.381

0.792

0.356

Table 10c: Results of the heterogeneity test for monthly microsatellite variation in each geographic
stratum (total samples)
SectorMicrosatellite locus
EV1

EV104

GT211

DlrFCB14

GT195

GT23

All loci

IIIE

0.102

0.457

0.384

0.489

0.770

0.333

0.430

IVWN

0.359

0.513

0.675

0.535

0.562

0.719

0.842

IVWS

0.627

0.202

0.955

0.011

0.625

0.515

0.212

IVE

0.518

0.985

0.237

0.893

0.376

0.871

0.878

VW

0.954

0.568

0.116

0.176

0.824

0.961

0.662

VEN

0.334

0.486

0.507

0.853

0.732

0.220

0.706

VES

0.740

0.433

0.343

0.692

0.732

0.405

0.817

VIW

0.192

0.423

0.388

0.217

0.538

0.935

0.500

17

Table 11a: Results of the heterogeneity test for microsatellite variation in females Antarctic minke
whales from different longitudinal sectors. The total p-value was 0.002 suggesting structure. In bold arethose p-values that remained significant after Bonferroni correction.
Microsatellite locus
Sector
EV1
EV104 GT211 DlrFCB14 GT195
GT23
All loci
All sectors

0.013

0.060

0.841

0.004

0.654

0.162

0.002

IIIE x IVW-N

0.867

0.038

0.385

0.636

0.412

0.404

0.352

IIIE x IVW-S

0.001

0.343

0.234

0.535

0.066

0.955

0.011

IIIE X IVE

0.045

0.404

0.210

0.659

0.534

0.964

0.349

IIIE x VW

0.290

0.692

0.048

0.702

0.364

0.982

0.440

IIIE x VE

0.283

0.928

0.412

0.171

0.483

0.960

0.658

IIIE x VIW

0.049

0.225

0.574

0.013

0.186

0.814

0.032

IVW-N x IVW-S
IVW-N x IVE

0.001

0.082

0.521

0.022

0.454

0.119

0.001

0.069

0.019

0.728

0.281

0.908

0.040

0.027

IVW-N x VW

0.299

0.078

0.432

0.184

0.445

0.140

0.112

IVW-N x VE

0.083

0.000

0.887

0.028

0.494

0.084

0.000

IVW-N x VIW
IVW-S x IVE

0.055

0.000

0.850

0.005

0.872

0.284

0.000

0.095

0.993

0.774

0.151

0.572

0.149

0.305

IVW-S x VW

0.234

0.634

0.798

0.333

0.019

0.358

0.171

IVW-S x VE

0.244

0.484

0.662

0.019

0.012

0.002

0.001

IVW-S x VIW
IVE x VW

0.137

0.073

0.967

0.000

0.601

0.136

0.002

0.872

0.217

0.089

0.612

0.927

0.112

0.322

IVE x VE

0.618

0.460

0.882

0.567

0.865

0.209

0.836

IVE x VIW

0.293

0.220

0.985

0.027

0.994

0.521

0.299

VW x VE

0.639

0.334

0.293

0.214

0.996

0.370

0.562

VW x VIW

0.263

0.063

0.797

0.030

0.883

0.670

0.159

VE x VIW

0.190

0.143

0.982

0.002

0.956

0.737

0.061

18

Table 11b: Results of the heterogeneity test for microsatellite variation in male Antarctic minke whales
from different longitudinal sectors. The total p-value was 0.317.
Microsatellite locus
Sector
EV1
EV104 GT211 DlrFCB14 GT195
GT23
All loci
All sectors

0.522

0.514

0.731

0.285

0.025

0.744

0.317

Table 11c: Results of the heterogeneity test for microsatellite variation in Antarctic minke whales fromdifferent longitudinal sectors (female and male samples combined). The total p-value was 0.039
suggesting structure. In bold are those p-values that remained significant after Bonferroni correction.
SectorMicrosatellite locus
EV1

EV104

GT211

DlrFCB14

GT195

GT23

All loci

All sectors

0.081

0.192

0.430

0.224

0.067

0.179

0.039

IIIE x IVW

0.048

0.334

0.309

0.406

0.323

0.507

0.190

IIIE X IVE

0.300

0.386

0.309

0.224

0.522

0.535

0.429

IIIE x VW

0.097

0.370

0.145

0.488

0.034

0.664

0.076

IIIE x VE

0.298

0.698

0.396

0.093

0.103

0.432

0.193

IIIE x VIW

0.017

0.137

0.491

0.213

0.096

0.489

0.030

IVW x IVE

0.834

0.652

0.773

0.742

0.944

0.203

0.933

IVW x VW

0.551

0.704

0.550

0.379

0.000

0.308

0.017

IVW x VE
IVW x VIW

0.169

0.063

0.772

0.008

0.256

0.009

0.080

0.008

0.604

0.253

0.772

0.676

0.002
0.072

IVE x VW

0.717

0.696

0.167

0.621

0.008

0.268

0.106

IVE x VE

0.770

0.462

0.288

0.383

0.706

0.433

0.716

IVE x VIW

0.414

0.196

0.691

0.537

0.692

0.472

0.682

VW x VE

0.396

0.386

0.203

0.741

0.179

0.304

0.343

VW x VIW

0.118

0.279

0.620

0.674

0.386

0.950

0.565

VE x VIW

0.273

0.455

0.641

0.254

0.768

0.409

0.606

19

MALESFEMALES

Figure 1: Geographical distribution of Antarctic minke whales sampled by JARPA and examined inthis study (upper figures: males; lower figure: females).

20

Area IV

Area III E
40ﾟE

60ﾟE

55ﾟS

80ﾟE

100ﾟE

Area VI W

Area V
120ﾟE

West

East

IV-WN

IV-E

140ﾟE

160ﾟE

180ﾟ

West

East

V-W

V-EN

160ﾟW

140ﾟE
55ﾟS
60ﾟS

60ﾟS
III-E

65ﾟS

VI-W

65ﾟS

IV-WS

70ﾟS

V-ES
(Ross Sea)

70ﾟS

75ﾟS

75ﾟS

Figure 2: Geographic strata used in the present genetic analyses of stock structure in the Antarctic
minke whale.

Figure 3: Encounter rates of Antarctic minke whales in 10º squares of latitude and longitude in waters
0º-30ºS in October (from Kasamatsu et al., 1995).

21

Figure 4: Distribution of krill in summer, overlaid with surface ocean circulation pattern. Red gyres arewell documented; blue ones are more speculative (Taken from Nicol, 2006).

22