THIS PAPER CAN BE CITED ONLY IN THE CONTEXT OF THE IWC SC MEETINGS
SC/63/SH9

Preliminary mitochondrial DNA analysis of low and highlatitude humpback whales of Stocks D, E and F
Luis A. Pastene1, Mutsuo Goto1, Naohisa Kanda1, Toshihide Kitakado2 and Per J. Palsboll3
1

The Institute of Cetacean Research, 4-5 Toyomi-cho, Chuo-ku, Tokyo 104-0055, JapanTokyo University of Marine Science and Technology, Konan 4-5-7, Minato-ku, Tokyo 108-0075, Japan3
Department of Genetics, Microbiology and Toxicology, Stockholm University, 10691, Stockholm,
Sweden2

ABSTRACT
Genetic samples from 575 humpback whales obtained in the Antarctic during surveys of the
JARPA/JARPA II and IDCR/SOWER, and from 768 whales from low latitude localities of the South
Pacific and eastern Indian Ocean were analyzed to describe the genetic population structure, distribution
and mixing of breeding stocks in the Antarctic feeding grounds. Genetic samples from breeding grounds
were obtained mainly by biopsy sampling but also from sloughed skin and beachcast whales: Western
Australia (n= 167), New Caledonia (n= 243), Tonga (n= 240), Cook Islands (n= 56) and French Polynesia(n= 62). In the Antarctic feeding grounds, samples were obtained only by biopsy sampling: Areas IIIE
(n= 106), IV (n= 231), V (n= 171) and VI (n= 67). Genetic samples of both data sets were examined forapproximately the first half of the mtDNA control region. Duplicated samples were excluded from theanalysis. In the case of mother/calf pairs only one sequence was used. Sequences from both data sets werealigned to produce a single data set comprising 126 haplotypes. Three kinds of analyses were conducted
to examine the distribution and mixing of breeding stocks in the Antarctic under hypotheses on stock
structure agreed by the IWC SC previously for Stock D, E and F: analysis of Fst, mixing proportion andmaximum likelihood comparison. In general results from the three approaches were consistent, althoughsome disagreements were found. The most parsimonious interpretation of results is that the Western
Australia whales (D) distributes mainly in Area IV, in the Antarctic sector comprised between
approximately 80ºE and 125ºE and its occurrence decrease to the west and east of that sector. The
French Polynesia whales (F2) do not occur in the Antarctic research area examined (e.g. fromapproximately 35ºE to 120ºW). The New Caledonia whales (E2) distribute in Areas VE (fromapproximately 150ºE) and VI. Results for Tonga (E3) and Cook Island (F1) whales were similar. They
distribute mainly in Area VI. The pattern is similar when Tonga and Cook Islands whales are treated
together. Signals are clearer when Cook Islands, New Caledonia and Tonga are treated together. In thiscase whales distribute in Area VI and V. Results for Western Australia and French Polynesia are clear inthat whales from those localities belong to different stocks with particular patterns of distribution. Results
for the other three localities are consistent with the scenario Tonga and Cook Islands whales belonging toa same stock (Hypothesis 3) as well with the scenario New Caledonia, Tonga and Cook Islands whales
belonging to a same stock (Hypothesis 4). Results of these analyses are preliminary and several future
works were identified.
KEYWORDS: ANTARCTIC, FEEDING GROUNDS, BREEDING GROUNDS, GENETICS,HUMPBACK WHALE
INTRODUCTION
Humpback whales, Megaptera novaeangliae, are found worldwide in all major oceans. Like other
Balaenopterid species, humpback whales migrate between summer feeding grounds in mid- and highlatitudinal waters and winter breeding grounds in tropical or subtropical waters. Animals occur primarily
in coastal and continental shelf waters.
Regarding the Southern Hemisphere, Mackintosh (1965) showed that humpback whales tend to gather
into five or six distinct feeding concentrations in the Antarctic during the austral summer season. These1

feeding concentrations were denominated as Groups I-V (with a Group IIa and IIb) corresponding
roughly to IWC Management Areas I-VI. The Groups most documented are Groups IV and V. Omura(1953) examined the distribution of humpback whale in the feeding grounds of Areas IV and V based oncatch data. He suggested that two populations occur in these Areas with a boundary around 130°-142°E.
He did not discard the possibility of intermingling between these two populations in the feeding ground.
He also examined the pattern of distribution by month and suggested that for the month where more data
were available (November-March) the boundary between these two populations changed from 120°130°E in November to eastside of 140°E in December and to 120°-140°E in January. Dawbin (1966)
summarize the distribution and seasonal migratory movement of humpback whales from Groups IV andV, as demonstrated by mark-recapture data (Discovery-type marks). Whales from Group IV move mainly
between Antarctic Area IV and Western Australia while whales from Group V move between Antarctic
Area V and Eastern Australia and along the coast of New Zealand and southwest Pacific islands.
Interchange of a few individuals between Groups IV and V was reported. Dawbin (1966) also reported
that the boundary of Groups IV and V in the Antarctic do not correspond to the actual boundary between
Areas IV and V and that some whales marked in Area VI were recovered in eastern Australia.
More recently the IWC SC described the hypothetical stock structure and migratory corridors forSouthern Hemisphere humpback whales based mainly on information such as Discovery tags, photo-id,
genetics and satellite track (IWC, 2005). There are seven breeding stocks named from A to G. Some ofwhich (B, C, E and F) are further subdivided into sub-stocks.
The IWC SC has recommended genetic analyses that include samples from both low and high latitude
areas. Samples from low latitude breeding grounds represent signal of the ‘pure’ stock, which can be‘monitored’ in the Antarctic feeding grounds where a degree of spatial and temporal mixing is expected.
The focus of the present genetic analyses is on Stocks D, E and F. We made use of a substantive numberof genetic samples available from low and Antarctic latitudes to understand the structure, distribution andmixing of those breeding stocks in the Antarctic.
For this aim we used mtDNA control region sequences from one locality of Stock D, two of Stock E andtwo of Stock F. These data were already used in a study on stock structure in the breeding grounds(Olavarria et al., 2007), which showed significant differences among those localities. Details of those data
were provided to us through the IWC Secretariat under data access Protocol B (courtesy of Dr. C.S. Baker,
acting Data Administrator, on behalf of the South Pacific Whale Research Consortium).
In the Antarctic mtDNA control region sequences were available from Area IIIE (related to Stock C), IV(related to Stock D), V (related to Stock E) and VI (related to Stock F). Part of these data were alreadyused in a study on stock structure in the feeding grounds (Pastene et al., 2006), which showed significant
differences among those Areas.
During the Workshop on the Comprehensive Assessment of Southern Hemisphere humpback whales(IWC, 2006), animals from Western Australia were considered as part of a single stock (D). Regarding to
Stocks E and F the Workshop listed a total of six stock structure hypotheses and assigned them different
ranks of plausibility (Figure 1). In the present study we did not attempt to carry out additional analyses on
stock structure on breeding grounds samples (see section Discussion). Rather ‘baseline’ breeding groundsamples in our analyses were defined according those hypotheses considered high and medium ranks by
the Workshop (Figure 1).
Previous studies on baleen whales have used ‘baseline’ stock samples to estimate the mixing proportionof stocks in the feeding grounds or migratory corridors (Pastene et al., 1998; Albertson-Gibb, et al., 2008).
The latter study was focused on the southern humpback whales and used a similar mtDNA data set fromlow latitude waters. However their sample size and sampling coverage in the Antarctic was limited.
In the present study we used a comprehensive mtDNA data set from low and Antarctic latitude toinvestigate the structure, distribution and mixing of Stocks D, E and F in the feeding grounds of Areas
IIIE, IV, V and VI using a variety of methods.

2

MATERIALS AND METHODS
Samples
Skin biopsy samples were obtained from free-ranging whales along the sighting surveys of the JARPA
and JARPA II and IDCR/SOWER surveys in Areas IIIE, IV, V and VI, on an opportunistic basis. Biopsy
samples in JARPA were collected using an air gun described in Kasamatsu et al. (1991) and more
recently using a Paxarm system. Biopsy samples in IDCR/SOWER were collected using several methods
including Paxarm system and crossbows. At the laboratory all biopsy samples were checked for the
possibility of re-sampling (two or more samples taken from a same individual) by comparing the
genotype profiles produced by a set of six microsatellites. When mother/calf pairs were sampled, only thegenetic information of the mother was used for the analysis (nine cases in Area V).
Genetic samples from breeding grounds were obtained mainly by biopsy sampling but also from sloughedskin and beachcast whales (see details in Olavarria et al., 2007). At the laboratory the biopsy samples
were checked for the possibility of re-sampling.
Table 1 shows the number of samples used in the present analysis by sampling locality. A total of 768
samples were used from the breeding grounds and 575 from the feeding grounds. Figure 2 shows thebreeding ground localities and the geographical distribution of samples in the feeding grounds of Areas
IIIE, IV, V and VI.
Molecular genetic analysis
Extraction of DNA and mtDNA control region sequencing
Details of the genomic DNA extraction and sequencing of samples from breeding and feeding grounds
are given in Olavarria et al. (2007) and Pastene et al. (2006), respectively.
All sequences were aligned by eye. The aligned sequences involved a common segment of 335bp of the
mtDNA control region. A total of 126 unique sequences (haplotypes) were determined in the common
data set of 1,343 whales.
Data analysis
Samples from Western Australia were considered a baseline sample for Stock D. Baseline samples for
Stocks E and F were defined according to the specifications of the high and medium rank plausibility
hypotheses in Figure 1, (IWC, 2006), adapted to the availability of samples:
Hypothesis 1 (medium): New Caledonia (E2), Tonga (E3), Cook Islands (F1) and French Polynesia (F2)
are separate stocks.
Hypothesis 3 (high): New Caledonia (representative sample for New Caledonia+Chesterfield Reaf),
Tonga+Cook Island and French Polynesia are separated stocks
Hypothesis 4 (medium): New Caledonia+Tonga+Cook Islands, French Polynesia are separated stocks.
Three kinds of analyses were conducted.
Fst analysis
The first analysis involved the estimation of Fst between the baseline stocks and samples of humpback
whales in Areas IIIE, IV, V and VI. Fst values were estimated using the AMOVA (Excoffier et al., 1992).
The significance of the Fst values was estimated using 10,000 random permutations of the data matrix.
Mixing proportion analysis
The second analysis involved the estimation of mixing proportion of the baseline stocks in the Antarctic
Areas. For this aim we used a maximum likelihood procedure (e.g. Fournier et al., 1984), implemented in
a computer program developed by one of us (TK). Variance of these estimates consisted of the variancefrom the sampling from the mixed population but do not consider the variance from the baseline stocks.

3

ln likelihood analysis
The third analysis involved a finer grouping of the samples in the feeding grounds. Antarctic samples
were arranged from east to west. The baseline stocks were compared using lnML, with samples 1-15, 216, 3-17, etc. until reach the most western sample. A high ln likelihood means that samples are alike. The
95% confidence intervals were obtained by creating samples randomly from all the Antarctic samples
1,000 times and estimated the lnML in each case. This analysis was implemented using a computer
program developed by one of us (PP).
RESULTSFst analysis
Table 2 shows the estimates of Fst. The Western Australia whales differed significantly from all Antarctic
Areas except Area IV. The New Caledonia, Tonga and Cook Islands differed significantly from all Areas
except Area VI. The French Polynesia differed significantly from all Areas.
Tonga+Cook Islands and New Caledonia+Tonga+Cook Islands showed a pattern similar when those
localities were analyzed individually (differed significantly from all Areas except Area VI).
There is a good correlation between Fst and geography. For example for Area IIIE and IV the Fst values
increase with distance (Table 2). For Area IIIE the smallest Fst value was in the comparison with Western
Australia and the largest value in the comparison with the French Polynesia. The higher Fst values were
found in the comparisons between the Antarctic Areas and the French Polynesia whales.
In summary the Fst analysis suggest that Western Australia whales are closely related to Area IV while
New Caledonia, Tonga and Cook Islands whales are closely related to Area VI. The French Polynesia
whales are not related to any of the Antarctic Areas examined.
Mixing proportion analysis
Table 3 shows the results of mixing proportion. The Western Australia whales are highly represented in
Areas IV and IIIE, much less in Area V and absent in Area VI. With the exception of Area IIIE results are
consistent with the results of the Fst.
The New Caledonia whales are mainly represented in Areas V and VI and less represented in Areas IV
and IIIE. From the geographical point of view the figure of 17.4% in Area IIIE is surprisingly high.
The Tonga whales are mainly represented in Area VI and much less in the other Areas, which isconsistent with the results of Fst.
The Cook Island whales are poorly represented in the Areas examined. It is represented in Area VI with a
19.6% and is almost absent in other Areas. This result is consistent with that of Fst.
The French Polynesia is absent in all Areas, which is consistent with the Fst results.
When we treated Tonga+Cook Islands whales together, they are represented in higher percentage in Area
VI, result consistent with that of Fst. When we treated New Caledonia+Tonga+Cook Islands whales
together, they are highly represented in both Areas VI and V.
Ln likelihood analysis
Figure 3 show the results of the ln likelihood for Western Australia whales. The highest ln likelihood arefound in the Antarctic sector comprised between 80ºE and 125ºE approximately, corresponding roughlywith the limit of Area IV. Then there is concordance in these results with the geography. The values
become smaller toward Area IIIE and much smaller toward Areas V and VI, which is consistent with theresults found by the Fst (Table 2) and mixing proportion analyses (Table 3).
There is also some signals in the plotting for New Caledonia whales (Figure 4) where the maximum
values are found in the sector comprised between 122ºW and 150ºE approximately (Area VI and east partof Area V). Values become much smaller to the west of that longitude. Then there is concordance in theseresults with the geography. This result do not agree with the Fst analysis, which was small but significant

4

in the comparison between New Caledonia and Area V (Table 2), but it is consistent with the results
found by the mixing proportion analysis (Table 3).
The signal for the Tonga whales (Figure 5) is in the sector comprised between 122ºW and 176ºW (Area
VI) and become smaller to the west of that longitude. Again there is concordance with geography andresults are consistent with the Fst (Table 2) and mixing proportion analyses (Table 3).
The signal for the Cook Island whales is less clear. Higher values are found in the sector 122ºW-177ºW(Area VI), which is consistent with geography, and consistent with the results found in the Fst (Table 2)
and mixing proportion (Table 3) analyses. However another peak is observed in Area IVE.
There is no signal for the French Polynesia whales, which is consistent with geography, and also
consistent with the results of the Fst (Table 2) and mixing proportion (Table 3) analyses. Considering theresults of the three analyses whales from the French Polynesia are probably distributed outside of ourresearch area in the Antarctic.
For the combination Cook Islands+Tonga (Figure 8) the results are consistent with geography andconsistent with the results of Fst (Table 2) and mixing proportion (Table 3) (but in this case thecontribution in Area VI is higher, 65.2%, Table 3), as the signal in Figure 8 is from 122ºW to 174ºE
approximately (almost Area VI).
The combination Cook Islands+New Caledonia+Tonga shows a clearer signal (Figure 9). Larger lnlikelihood values are in the sector comprised between 122ºW and approximately 137ºE (Areas VI and V).
Values become lower in Areas IV and IIIE, which is consistent with geography. Results are consistent
with the high mixing proportion of this baseline stock in Areas V and VI (Table 3) but do not agree with
the Fst results regarding Area V which showed a small but significant Fst value in the comparison
between New Caledonia+Tonga+Cook Islands and Area V (Table 2).
DISCUSSION
Following previous recommendations from the IWC SC we conducted a mtDNA analyses on samples
from low and high latitudes of Breeding Stocks D, E and F. The main objective of this analysis was toinvestigate the distribution and mixing of those stocks in the feeding grounds of Areas IIIE, IV, V and VI
under different grouping of the samples from the breeding grounds as defined in stock structure
hypotheses listed previously by the IWC SC.
For this objective we used a variety of approaches, which were in general consistent in results, althoughsome differences were found. Our most parsimonious interpretation of the results is as follow.
1) Results regarding the Western Australia whales (Stock D) were clear and consistent among theapproaches used, and support the previous view that the core of this stock distributes mainly in
Area IV, in the Antarctic sector comprised between 80ºE and 125ºE. This stock distributes andmixes with a different stock in Area IIIE and to a lesser extent with other in Area VW.
2) Results regarding the French Polynesia baseline stock (F2) were clear and consistent among theapproaches used. Whales from this putative stock do not occur in the Antarctic research area
examined (e.g. from 35ºE to 122ºW). This was the stock most strongly differentiated from all
Areas examined.
3) The New Caledonia baseline stock seems to distribute in Area VE and VI. There are somediscrepancy for this pattern in the results found for the Fst that found significant differences
between New Caledonia and Area V. This discrepancy could be elucidated perhaps by
conducting analyses in Area V at smaller longitudinal sectors.
4) Results found for Tonga and Cook Island were similar and consistent among the approaches.
They seem to distribute mainly in Area VI. The pattern is similar when Tonga and Cook Islands
samples are pooled. It should be noted that the sample size in Area VI is still small to allow
definitive conclusions.
5) Signals are clearer when Cook Islands, New Caledonia and Tonga are treated together. Whales
distributes in Areas VI and V.

5

In summary results for Western Australia and French Polynesia are clear in that whales from those
localities belong to different stocks with particular patterns of distribution in the feeding grounds. For theother three localities results are consistent with the scenario Tonga and Cook Islands whales belonging toa same stock (Hypothesis 3) as well with the scenario New Caledonia, Tonga and Cook Islands whales
belonging to a same stock (Hypothesis 4).
Results regarding Western Australia/Area IV were similar to those of Albertson-Gibbs et al. (2008) but
the allocation to Area IV in the present study was much higher. Results were also similar regarding
Tonga/Area VI. Discrepancies between both studies are probably due to different sample sizes used for
the Antarctic Areas, which were much higher in the present study.
Our results should be considered as preliminary pending further analyses. The following future works
were identified.
Stock structure genetic analyses have been carried out for the breeding grounds samples based on
hypothesis testing and results showed significant differences among all localities (Olavarria et al., 2007).
Further analyses should include samples from Eastern Australia (E1). Apart from hypothesis testing,estimates of the migration rates among putative breeding stocks using IM or Mdiv would be useful. It
would also useful to investigate possible yearly variation in the pattern of structure.
Previous genetic analyses in the feeding grounds have shown different pattern of distribution by sex withmales being more mobile than females (Pastene et al., 2006). Future analyses of distribution and mixing
in the feeding grounds similar to those conducted in this study should be conducted separately for males
and females.
Distribution of stocks in the feeding grounds could change yearly according to oceanographic conditions
which in turn determine the distribution of krill. Analyses on a year basis (or groups of years) in the
Antarctic samples would be useful. This could be possible for Areas where sample sizes are larger (e.g.
Area IV).
The analytical tool used for estimating mixing proportion does not consider variance attributed to thehaplotype frequency in the baseline stocks. The program used should be modified to take this into accountand the analyses repeated.
ACKNOWLEDGEMENTS
We thank all the researchers and crew members of JARPA/JARPA II and IDCR/SOWER surveys
involved in the sampling of the Antarctic biopsy samples used in this study. The response to the data
request (for Western Australia, New Caledonia, Tonga, Cook Islands and French Polynesia) andsubsequent data transfer were communicated by C.S. Baker, acting Data Administrator, on behalf of theSouth Pacific Whale Research Consortium. We thank researchers and other personnel involved in biopsy
sampling and analyses of samples from those localities. Data access was possible under the IWC SC data
access Procedure B. K. Konishi (ICR) assisted us by producing Figure 2.
REFERENCES
Albertson-Gibb, R., Olavarria, C., Garrigue, C., Hauser, N., Poole, M., Florez-Gonzalez, L., Antolik, C.,
Steel, D. And Baker, C.S. 2008. Using mitochondrial DNA and mixed-stock analysis to estimate
migratory allocation of humpback whales from Antarctic feeding areas to South Pacific breeding
grounds. Paper SC/60/SH15 presented to the IWC Scientific Committee, June 2008 (unpublished).
6pp.
Dawbin, W.H. 1966. The seasonal migratory cycle of humpback whales. In: Whales, dolphins andporpoises, Norris, K.S. (ed.). University of California Press, Berkerley. pp. 145-171.
Excoffier, L., Smouse, P.E. and Quattro, J.M. 1992. Analysis of molecular variance inferred from metricdistances among DNA haplotypes: application to human mitochondrial DNA restriction data.
Genetics 131:479-491.

6

Fournier, D., Beacham, T.D., Riddell, B.E. and Busack, C.A. 1984. Estimating stock composition in
mixed-stock fisheris using morphometric, meristic, and electrophoretic characteristics. Can. J. Fish.
Aquat. Sci. 41:400-408.
International Whaling Commision. 2005. Report of the Sub-Committee on Other Southern Hemisphere
Whale Stocks. J. Cetacean Res. Manage. (Suppl) 7:235-244.
International Whaling Commission 2006. Report of the Workshop on the Comprehensive Assessment ofSouthern Humpback Whales. Paper SC/58/Rep 5 presented to the IWC Scientific Committee, June
2006 (unpublished). 77pp.
Kasamatsu, F., Iwata, S. and Nishiwaki, S. 1991. Development of biopsy skin sampling system for fastswimming whales in pelagic waters. Rep int Whal Commn 41:555-557.
Mackintosh, N.A. (1965). The stocks of whales. Fishing News (Books) Ltd., London. 232pp.
Olavarria, C., Baker, C.S., Garrigue, C., Poole, M., Hauser, N., Caballero, S., Flores-Gonzalez, L.,
Brasseur, M., Bannister, J., Capella, J., Clapham, P., Dodemont, R., Donoghue, M., Jenner C.,
Jenner, M.N., Moro, D., Oremus, M., Paton, D, Rosenbaum, H. and Russell, K. 2007. Population
structure of South Pacific humpback whales and the origin of the eastern Polynesian breeding
grounds. Mar Ecol Prog Ser 330:257-268.
Omura, H. 1953. Biological study on humpback whales in the Antarctic whaling areas IV and V. Sci Rep
Whales Res Inst Tokyo 8:81-102.
Pastene, L.A., Goto, M., Kishino, H. 1998. An estimate of the mixing proportion of ‘J’ and ‘O’ stocks
minke whales in sub-area 11 based on mitochondrial DNA haplotype data. Rep. Int. Whal. Commn
48:471-474.
Pastene, L.A., Goto, M., Nishiwaki, S., Yoshida, H. and Kanda, N. 2006. Genetic characteristics andpopulation structure of humpback whales in the Antarctic feeding ground as revealed by
mitochondrial DNA control region seqwuencing and microsatellite analyses. Paper SC/D06/J31
presented to the JARPA Review Workshop, December 2006 (unpublished). 14pp.

7

Table 1. Number of samples of the humpback whale used in the present mtDNA analysis.
Breeding grounds
Feeding grounds
WA
NC
TG
CI
FP
Total
A IIIE
A IV
AV
A VI
Total
167
243
240
56
62
768
106
231
171
67
575
WA= Western Australia; NC= New Caledonia; TG= Tonga; CI= Cook Islands; FP= French Polynesia

Table 2. Fst values between breeding ground samples grouped under different stock structure hypotheses(see text for explanation) and feeding grounds sample from Antarctic management Areas (significant pvalues are shown in parenthesis).
WA
NC
TG
CI
FP
TO+CI
NC+TO+CI
A IIIE
0.00890.02130.02450.03790.04520.02450.0211A IV-0.00180.01350.01280.01950.03360.01150.0105
AV
0.01440.00580.01130.02790.04220.01190.0072A VI
0.00030.00100.01070.0001-0.00170.00930.0320
WA= Western Australia; NC= New Caledonia; TG= Tonga; CI= Cook Islands; FP= French Polynesia

Table 3. Mixing proportion of breeding ground samples grouped under different stock structure
hypotheses (see text for explanation) in the Antarctic management Areas (standard errors are shown inparenthesis).
WA
NC
TG
CI
FP
TO+CI
NC+TO+CI
0.791
0.174
0.005
0.000
0.030
0.000
0.187
(0.059)(0.098)(0.096)(0.000)(0.045)(0.000)(0.068)
A IV
0.064
0.065
0.042
0.000
0.107
0.169
0.828
(0.034)(0.029)(0.036)(0.031)(0.000)(0.032)(0.033)
AV
0.142
0.000
0.026
0.000
0.032
0.847
0.832
(0.041)(0.043)(0.000)(0.023)(0.000)(0.030)(0.044)
A VI
0.000
0.371
0.000
0.433
0.196
0.652
1.000
(0.000)(0.129)(0.154)(0.097)(0.000)(0.122)(0.000)
WA= Western Australia; NC= New Caledonia; TG= Tonga; CI= Cook Islands; FP= French Polynesia
A IIIE8

Figure 1. Schematic diagram showing possible models for stock structure in the South Pacific. N=
number of breeding stocks and Rank, l= low, m= medium and h= high (taken from IWC, 2006). Samples
from the New Caledonia, Tonga, Cook Islands and French Polynesia (in addition to Western Australia),
were available for the present mtDNA study.

Figure 2: Geographical distribution of humpback whale samples from breeding and feeding grounds
analyzed in this study.

9ln likelihood

13637W - 16447W

16729W - 16927W

17810W - 17507E

17017E - 16420E

16208E - 15757E

15003E - 14045E

14001E - 13318E

12020E - 11401E

10810E - 10448E

10034E - 09828E

09441E - 09027E

08811E - 08645E

08317E - 07957E

07226E - 06847E

05956E - 05739E

04734E - 04238E

03930E - 03447E

Western Australia

10
0
-10
-20
-30
-40
-50
-60
-70
-80
-90
Longitude

Figure 3. Comparison of samples from Western Australia and samples from the feeding grounds ofmanagement Areas VI-IIIE ordered from east to west, based on maximum likelihood analysis. A high ln
likelihood means that samples are alike (0.975 CI= -3.568; 0.025 CI= -50.619).

10

ln likelihood

1116309W - 16708W

16848W - 17110W

17810W - 17507E

17355E - 16631E

16327E - 16151E

15748E - 15117E

14740E - 14025E

13940E - 12813E

12026E - 11429E

11043E - 10716E

10258E - 10034E

09831E - 09558E

09245E - 08930E

08752E - 08641E

08342E - 08009E

07859E - 07140E

06453E - 06102E

05804E - 04956E

04521E - 04134E

03930E - 03447E

New Caledonia

20

0
-20

-40

-60
-80

-100
Longitude

Figure 4. Comparison of samples from New Caledonia and samples from the feeding grounds ofmanagement Areas VI-IIIE ordered from east to west, based on maximum likelihood analysis. A high ln
likelihood means that samples are alike (0.975 CI= -3.893; 0.025 CI= -48.752).

13637W - 16447W

16728W - 16923W

17612W - 17519E

17355E - 16631E

16302E - 16142E

15338E - 14821E

14026E - 13958E

12540E - 11905E

11229E - 10810E

10440E - 10139E

09831E - 09558E

09124E - 08912E

08658E - 08436E

08037E - 07859E

07138E - 06453E

05936E - 05558E

04651E - 04235E

03930E - 03447E

Tonga

20
ln likelihood

0
-20
-40
-60
-80
-100
Longitude
Figure 5. Comparison of samples from Tonga and samples from the feeding grounds of management
Areas VI-IIIE ordered from east to west, based on maximum likelihood analysis. A high ln likelihoodmeans that samples are alike (0.975 CI= -8.753; 0.025 CI= -59.704).

12

ln likelihood

13637W - 16447W

16728W - 16923W

17612W - 17519E

17355E - 16631E

16302E - 16142E

15338E - 14821E

14026E - 13958E

12540E - 11905E

11229E - 10810E

10440E - 10139E

09831E - 09558E

09124E - 08912E

08658E - 08436E

08037E - 07859E

07138E - 06453E

05936E - 05558E

04651E - 04235E

03930E - 03447E

Cook Islands

0
-10
-20
-30
-40
-50
-60
-70
-80
-90
Longitude

Figure 6. Comparison of samples from Cook Islands and samples from the feeding grounds ofmanagement Areas VI-IIIE ordered from east to west, based on maximum likelihood analysis. A high ln
likelihood means that samples are alike (0.975 CI= -32.114; 0.025 CI= -69.565).

13

ln likelihood

12216W - 13938W

16655W - 16728W

16924W - 17612W

17519E - 17418E

16643E - 16314E

16142E - 15719E

14825E - 14043E

14003E - 13738E

12050E - 11435E

11043E - 10716E

10240E - 09925E

09714E - 09440E

09019E - 08817E

08645E - 08342E

08009E - 07719E

07007E - 06347E

05915E - 05323E

04643E - 04212E

03930E - 03447E

French Polynesia

0
-10
-20
-30
-40
-50
-60
-70
-80
-90
Longitude

Figure 7. Comparison of samples from French Polynesia and samples from the feeding grounds ofmanagement Areas VI-IIIE ordered from east to west, based on maximum likelihood analysis. A high ln
likelihood means that samples are alike (0.975 CI= -42.408; 0.025 CI= -75.414).

14

14949W - 16704W

16729W - 16927W

17612W - 17519E

17418E - 16708E

16327E - 16151E

15743E - 15003E

14732E - 14015E

13833E - 12353E

11541E - 11224E

10752E - 10424E

10050E - 09832E

09558E - 09149E

08925E - 08721E

08623E - 08317E

07956E - 07406E

06949E - 06257E

05858E - 05253E

04617E - 04207E

03930E - 03447E

Cook Islands+Tonga

ln likelihood

40
20
0
-20
-40
-60
-80
-100
Longitude

Figure 8. Comparison of samples from Cook Islands+Tonga and samples from the feeding grounds ofmanagement Areas VI-IIIE ordered from east to west, based on maximum likelihood analysis. A high ln
likelihood means that samples are alike (0.975 CI= -5.628; 0.025 CI= -60.040).

15

13637W - 16447W

16728W - 16923W

17612W - 17519E

17355E - 16631E

16302E - 16142E

15338E - 14821E

14026E - 13958E

12540E - 11905E

11229E - 10810E

10440E - 10139E

09831E - 09558E

09124E - 08912E

08658E - 08436E

08037E - 07859E

07138E - 06453E

05936E - 05558E

04651E - 04235E

03930E - 03447E

Cook Islands+New Caledonia+Tonga

ln likelihood

40
20
0
-20
-40
-60
-80
-100
-120
Longitude
Figure 9. Comparison of samples from Cook Islands+New Caledonia+Tonga and samples from thefeeding grounds of management Areas VI-IIIE ordered from east to west, based on maximum likelihood
analysis. A high ln likelihood means that samples are alike (0.975 CI= 9.873; 0.025 CI= -44.676).

16