Report of the Workshop
to Review the Japanese
Whale Research Programme
under Special Permit for
North Pacific Minke Whales

REPORT OF THE WORKSHOP: CONTENTS

1. Welcoming remarks ...........................................................................................................................................................377
2. Terms of Reference ............................................................................................................................................................377
3. Election of Chair and appointment of rapporteurs ............................................................................................................377
4. Meeting arrangements ........................................................................................................................................................377
5. Adoption of agenda ............................................................................................................................................................377
6. Review of documents.........................................................................................................................................................377
7. Review of available data....................................................................................................................................................377
8. Outline of JARPN and past discussions of it in the Committee .......................................................................................377
9. Overview of sampling methodology and results ...............................................................................................................379
10. Stock structure....................................................................................................................................................................379
10.1 Review of past discussions of stock structure of the North Pacific minke whale...................................................379
10.2 Methods of analysis including statistical power.......................................................................................................380
10.3 Synthesis and conclusions ........................................................................................................................................385
11. Feeding ecology .................................................................................................................................................................387
11.1 Background................................................................................................................................................................387
11.2 Methods and results...................................................................................................................................................387
11.3 Synthesis and conclusions.........................................................................................................................................388
12. Other studies.......................................................................................................................................................................389
13. Commission Resolution 1999-2.........................................................................................................................................389
14. Recommendations ..............................................................................................................................................................389
15. Adoption of report..............................................................................................................................................................389

J. CETACEAN RES. MANAGE. 3 (SUPPL.), 2001

377

Report of the Workshop to Review the Japanese Whale
Research Programme under Special Permit for North PacificMinke Whales (JARPN)
The Workshop was held at the Mariner’s Court Hotel,
Tokyo, from 7-10 February 2000. A list of participants isgiven as Annex A.

3. ELECTION OF CHAIR AND APPOINTMENT OFRAPPORTEURS
Bannister was elected Chairman. Punt, Butterworth, Haugand Taylor acted as rapporteurs.

1. WELCOMING REMARKS
Bannister welcomed the participants, informing them that he
was acting as Convenor as Smith had been unable to attend
the Workshop at the last minute for reasons beyond his
control. He read the Workshop a message from the ScientificCommittee Chair, Zeh, in which she conveyed her warmest
greetings to all participants, and expressed her confidence
that those assembled would conduct a rigorous and fairreview of the JARPN results. Hatanaka welcomed Bannisterand the other nine participants from outside Japan. He
expressed his thanks to Bannister as well as to Smith. He
reminded the participants that the JARPN surveys had
occurred over a six-year period, had sampled 498 minke
whales, and that the resulting data had been analysed.
Further, he believed that the research had been successful,and looked forward to constructive discussion andevaluation during the Workshop.

4. MEETING ARRANGEMENTS
Bannister reviewed the arrangements for the meeting, notingwith appreciation the arrangements by the hosts thatsimultaneous translation would be available between
Japanese and English and vice versa.
5. ADOPTION OF AGENDA
The adopted Agenda is given as Annex B. It takes into
account the Terms of Reference of the Workshop and thedraft agenda (IWC, 2000b) developed by the Steering Groupestablished by the Scientific Committee (IWC, 2000d).
6. REVIEW OF DOCUMENTS
The list of documents is given as Annex C.

2. TERMS OF REFERENCE

7. REVIEW OF AVAILABLE DATA

The terms of reference agreed by the Scientific Committee
last year (IWC, 2000b) were to:Annex D lists the data types produced during JARPN thatwere made available for use during the Workshop. Annex E
lists the full set of documents based on the data and material
obtained during JARPN.

(1) Review the methods and results of the research
programme, 1994-1999.
(2) Assess the further potential of existing data for:(a) meeting JARPN objectives;(b) other objectives.
(3) Evaluate whether the main objectives have beenachieved.
The main objectives of JARPN (e.g. see SC/F2K/J29) were
to determine:(1) whether or not the ‘W’ stock exists and if so to estimate
mixing rates between the ‘O’ and ‘W’ stocks; and(2) the feeding ecology of minke whales in the North
Pacific.
The Committee expected that the report of the present
Workshop would provide it with information on theplausibility of options being considered in the RMP
Implementation Simulation Trials for North Pacific minke
whales (IWC, 2000c) when those results are consideredduring the next Annual Meeting.

8. OUTLINE OF JARPN AND PAST DISCUSSIONSOF IT IN THE COMMITTEE
SC/F2K/J29 reviewed the history and objectives of JARPN.
The JARPN surveys started in 1994 with the primaryobjective of elucidating the stock structure of minke whalesin the northwestern North Pacific to assess the plausibility ofworking hypotheses developed by the Working Group on
North Pacific Minke Whale Management Trials (IWC, 1994,
pp.120-44). Originally there were three sub-objectives:(1) to assess whether the ‘W’ stock exists;(2) to provide data to estimate the mixing rate of the ‘W’ and‘O’ stocks; and(3) to assess the validity of the ‘O’ sub-stock scenario.
In 1996, the Committee agreed that the ‘O’ sub-stock
structure scenario should be dropped from the
Implementation Simulation Trials for North Pacific minke
whales, and since then this third sub-objective has not been
considered. A second objective, ‘the feasibility study on the

378

REPORT OF THE WORKSHOP

feeding ecology of minke whales in the research ground’,
was added in 1996. In 1999, a sub-objective was added to theprimary objective, viz. to estimate the mixing rate between
the ‘J’ and O stocks.
SC/F2K/J8 outlined the JARPN research activities from1994-1999. Surveys in 1994 and 1995 were considered to befeasibility surveys, which were followed by full-scale
surveys beginning in 1996. The original research plan wasfor a research period lasting three to five years. The planned
research area comprised sub-areas 7, 8, 9, 11 and 12 of theNorth Pacific (Fig. 1), which covered the area where
improved stock definition information was needed. Initially,
the sighting and sampling techniques were similar to thoseused in JARPA. However, methods were modified in 1995;
this included sampling from the secondary sightings andrestricting the area surveyed to waters < 15°C. The new
survey mode continued to search and sample, with the threesighting/sampling vessels acting cooperatively, even whensea conditions were unsuitable for sighting. A special
monitoring survey (SMS) was also conducted for the limitedarea of high minke whale abundance.
Normally three sighting/sampling vessels searched along
set tracklines. When minke whales or possible minke whale
schools were sighted, the vessel immediately closed on theschool. Sampling was attempted after school size andspecies were confirmed, providing the individual was
identified as a minke whale. If the school consisted of two or
more individuals, the animal to be sampled was selectedusing random table digits as in JARPA.
The 1994 and 1995 surveys were conducted in sub-area 9.
The 1996 survey was conducted in sub-areas 7, 8 and 11. All
these surveys were conducted in mid-summer. The 1997 and1998 surveys were conducted early in the migration season(May and June) following discussions by the Working
Group for the North Pacific Minke Whale Trials in 1996

(IWC, 1997, pp.203-26). The 1999 survey was conducted in
the west of sub-area 7 in June and in sub-area 11 in July toprovide better coverage in those areas at those times.
The Workshop noted that substantial discussions of the
programme had occurred in the Committee at the
programme’s inception, in 1994, when there was a detailed
review (IWC, 1995, pp.82-5), and last year (IWC, 2000a).
Discussions in the intervening years largely referred tocomments in the 1994 review.
At the 1994 Committee meeting the proposal was
reviewed in accordance with the Committee’s agreed fivesets of guidelines (A-E). For three, A (The Proposal), B(Objectives) and E (Research cooperation), the Committee
agreed that the relevant guidelines had been met. For C(Methodology) there was detailed discussion, particularly ofgenetic analyses. In addition, the importance of abundance
estimates in the context of the RMP led to confirmation of
the importance of sightings estimates as well as sampling.
For D (The effect of catches on the stock), after somediscussion the Committee noted the difficulties it had
experienced in the past in adequately providing advice on thematter, referring however to its previous advice that theeffect of a small take for a short period would be negligible.
It had agreed to consider the general question of how toprovide such advice at its next meeting, but there was little
subsequent progress in addressing the problem, despite, forexample, extensive discussions at its 1997 meeting (IWC,
1998).
Last year, the Committee reviewed two options for the1999 survey, one requiring permission from the RussianFederation for sampling in its waters. Concerns expressed
then included the fact that the focus of the research whalingplans is in areas where minke whales from the ‘J’ stock mix
with those from the ‘O’ stock, to estimate, inter alia, mixing
rates of ‘J’ with ‘O’ stock animals there, while the principal

Fig. 1. Whaling grounds and the 13 sub-areas used for the Implementation Simulation Trials for North Pacific minke whales.

J. CETACEAN RES. MANAGE. 3 (SUPPL.), 2001

JARPN objective is to determine the mixing rate between the‘O’ stock and the hypothetical ‘W’ stock further east. In
response, it was argued that clarification of ‘J’/’O’ stock
mixing was now an objective of the research in response toconcerns raised over market sampling results. Anotherconcern related to the take of even a small number of animals
from the ‘ J’ stock, although that was countered by the viewthat the present mixing rate was likely to be small and the
expected catch of ‘J’ stock whales would be negligible
compared with the annual Korean and Japanese bycatch. In
the event, a majority of the Committee was unable to respondpositively to a request for the Russian Federation to be urged
to allow access to its waters for the proposed sampling.
In addition to those discussions in the Committee, initial
results from the programme were discussed in some depth
during the 1996 meeting of the Working Group on North
Pacific Minke Whale Trials (IWC, 1997, pp.203-26).
Information from the research was used in the process ofrevising the trials.
The reasons for the selection of the boundaries for the
sub-areas specified for North Pacific minke whales aredetailed in (IWC, 1994, p.122). The boundaries were chosen,in part, to be able to reflect possible stock and sub-stock
structures under consideration at that time. They accordingly
took account of the positions of historical whaling grounds,
which were then argued to be perhaps indicative ofsite-specific sub-stocks. The southernmost boundaries of
sub-areas 5-9 were chosen in the light of the absence ofcatches and sightings on winter surveys in lower latitudes.
Other boundaries for sub-areas bordering Japan wereselected to reflect the limits of the distribution of historicalcatches, and postulated limits to the movement of ‘J’ stock
whales to the east of Japan and also (possibly) ‘O’ stock
whales into the Sea of Japan. Choices of longitudinalboundaries of 150° and 157°E between sub-areas 7/8 and 8/9
respectively were largely arbitrary. The former was
motivated by a (contested) view that constituted the farthesteastward that minke whales might be found when thesemight also be subject to exploitation by Japanese coastal
whalers (IWC, 1992, p.160). The latter corresponded
roughly to the southern tip of the Kamchatka peninsula toallow for possible site specificity of animals migrating
northward moving to the west (i.e. into the Okhotsk Sea) andeast of the peninsula.
9. OVERVIEW OF SAMPLING METHODOLOGYAND RESULTS
SC/F2K/J8 indicated that sampling methods during the first
two JARPN surveys were similar to those in the JARPA
surveys. However, the sampling method was then changed tothat mentioned under Item 8. A total of 498 animals werecollected in sub-areas 7, 8, 9 and 11. Samples were not taken
in sub-area 12 since this sub-area is in the RussianFederation EEZ and permission to sample there was not
given. Sampling efficiency (animals sampled per animal
sighted) in 1994 was 0.49, but, after the modification to thesampling methods, sampling efficiency improved to 0.6-0.7.
SC/F2K/J8 concluded that the distributions of minke whalesightings roughly matched the distribution of minke whale
samples, thus indicating that the samples were collected
randomly from the areas sampled.
SC/F2K/J9 presented the results of the 1999 JARPN
cruise including sampling results for that year. The survey
was conducted from 6 June to 26 July in sub-areas 7 west and
11 using one research mother ship, three sighting/sampling
vessels (SSVs) and one dedicated sighting vessel (SV). The

379

reason for the choice of these sub-areas is detailed under
Item 8. The search covered a total of 4,459 n.miles with 293
minke whales (271 schools) sighted. As planned, 100
individuals were collected in these sub-areas (50 in sub-area
7 and 50 in sub-area 11). Biological observations and tissue
sampling were conducted as in previous surveys.
By-products were also produced following Article VII of theInternational Convention for the Regulation of Whaling.
Preliminary analysis of the samples from sub-area 7 foundthat the composition by sex and maturity in these sub-areas
was similar to those for the 1996 JARPN survey, which was
conducted one month later than the 1999 survey. In sub-area
11, segregation by sex and maturity of minke whales wasobserved. In the western half of sub-area 11 (west of theKitami Yamato Tai Bank), females were dominant and many
were pregnant. In contrast, mature males were foundpredominantly in the eastern half of sub-area 11 (east of theKitami Yamato Tai Bank). Furthermore, foetal growth curve
data indicated that the females found in the western half of
sub-area 11 do not all belong to the same breeding stock.

10. STOCK STRUCTURE
The Workshop had been specifically requested to commenton both the methods applied to the JARPN data and theresults obtained from the analyses. It agreed to discuss andreport on the methods and results simultaneously. Specificrecommendations regarding methods and results are listed
under Item 14.
10.1 Review of past discussions of stock structure of theNorth Pacific minke whale
SC/F2K/J1 reviewed studies on stock identity from
1956-1999 for minke whales in the North Pacific. Almost all
studies were carried out on the western side of the North
Pacific. The main approaches used were genetics,
morphology/morphometry, examination of conception dates
and analysis of catch distributions. Pollutant burdens andecological markers were also used to a lesser extent. Genetic
studies during the 1980s were based exclusively on
allozymes; however, during the 1990s, techniques based on
mtDNA and nuclear DNA were also used. Until 1994,
samples were restricted to past commercial coastal whaling
operations off Korea and Japan, and the analyses all related
to the coastal areas of those two countries. Since 1994,
samples from the offshore areas east of Japan (sub-areas 7, 8,
and 9) have been collected during JARPN. The results
obtained using several approaches are consistent with theview that there are different stocks (‘O’ and ‘J’) to the east
and west of Japan. Analyses of genetic and conception date
data suggest a temporal mixing of these two stocks in
sub-area 11. ‘O’ stock animals move from low to higher
latitude areas in spring, and the migration is characterised bya marked segregation by sex and reproductive status.
Data are available from the coast of Japan to 170°E.
Several approaches have been used to investigate possible
additional stock structure to the east of Japan. Genetics,
morphometry and examination of conception dates, among
others, it was argued, provide no evidence for additional
stock structure to the east of Japan, there being nostatistically significant differences found among sub-areas 7,
8 and 9.
The Committee (IWC, 1977, p.62) noted the possibility ofstocks to the east and west of Japan in 1976 based on resultsby Omura and Sakiura (1956) and Ohsumi (1977), and, in
1977, it recognised the Okhotsk Sea/West Pacific stock and380

REPORT OF THE WORKSHOP

the Sea of Japan stock (IWC, 1978, p.43). That stock
structure was refined further in 1982 when two stocks (theOkhotsk Sea/West Pacific stock and the Yellow Sea/East
China Sea/Sea of Japan stock) were recognised (IWC, 1983,p.98). An eastern boundary for the Okhotsk Sea/West Pacificstock was placed at 180°E at that time.
The issue of stock identity of minke whales was addressedin detail at the 1993 meeting of the Committee when a
Working Group was established to develop Implementation
Simulation Trials for North Pacific minke whales (IWC,
1994, pp.120-44). In addition to the ‘O’ and ‘J’ stocks, thetrials hypothesised a western (‘W’) stock as well as
sub-stocks within the ‘O’ and stocks. The Implementation
Simulation Trials were refined during the 1996 meeting(IWC, 1997, pp.203-26) when new information obtained
mainly from JARPN was considered. That led to thesub-stock structure hypothesis being abandoned although noconsensus could be reached regarding the plausibility of the‘W’ stock. In reviewing the matter, the Workshop noted
concerns regarding the meaning of ‘stock’ (see Item
10.3.4).
10.2 Methods of analysis (including statistical power)
SC/F2K/J3 discussed the limitations of hypothesis testing asa means of delineating stock structure. It examined theefficacy of hypothesis-testing in determining thedemographic spatial structure within a region and, inparticular, how well a hypothesis-testing approach actuallysets population boundaries. The performance of
hypothesis-testing was evaluated using simulations where
the actual population structure and dispersal rates are known
and can be sampled. The average p-value, average degree ofdifferentiation and the power to detect differentiation aredetermined as a function of the number of putative
populations defined by the researcher and the accuracy ofboundary placement. Statistical power and average
differentiation are much higher and the average p-value ismuch lower when a region is divided too coarsely into only
two putative populations than when it is divided in a way thatreflects the underlying population structure accurately.
There are two reasons for the inverse relationship between
power and the number of putative populations defined. First,
as with any real case, the number of samples per groupincreases as the number of groups decreases, resulting in an
increase in power. Second, defining fewer groups results inmore distantly related samples being placed in adjacentgroups, thus increasing the degree of differentiation between
adjacent groups and thereby the statistical power to detectthat differentiation. The primary lesson from SC/F2K/J3 that
relates to North Pacific minke whales is that initial boundary
placement is important and does influence the analysis of thedata. Improper initial boundary placement can compromise
the power of the analysis. Even if population structure is
detected, that detection does not provide support for the
biological reality of the chosen boundary. The level ofgenetic differentiation (in statistical terms, the effect size)
decreases to low levels with even a small amount of dispersal
and the drop in effect size is even greater for large population
sizes. This agrees completely with genetic theory on therelationship between effect size, dispersal rates andabundance.
SC/F2K/J4 described a new technique to estimate
statistical power for detecting population subdivision using
mtDNA data in hypothesis-testing. Case-specificsimulations are used to capture the spatial relationship andabundances of the putative populations. The actual level ofgenetic differentiation (the effect size) between
neighbouring populations varies through time because ofgenetic drift. This uncertainty about the level of populationdifferentiation is captured by sampling the populations
through time. For each time period a p-value is calculated fora series of statistics used to detect population subdivision.
Statistical power is the proportion of time that the null
hypothesis of panmixia is correctly rejected for a given
a-level (i.e. a given probability of incorrectly rejecting thenull hypothesis). Results are presented as Type I versus TypeII error tradeoff curves, which do not necessitate theresearcher choosing an a-level.
SC/F2K/J5 used a stepping-stone model to calculate
statistical power to compare the performance of fivestatistics commonly used to detect population subdivision:
the haplotypic statistics c2, HST, FST, and the sequence
statistics K*ST and fST. The p-values for all statistics were
estimated using randomisation procedures. These statistics
were evaluated at a high dispersal rate (1% per year) that isof interest in conservation applications. At this dispersal rate,
c2 always performed best and haplotypic statistics always
outperformed sequence statistics, which differs fromprevious investigations that did not examine such high rates
of dispersal. The reason for the poor performance of thesequence statistics is that when dispersal is high relative togenetic drift, the phylogeographic signal is either low or
non-existent. SC/F2K/J5 suggested the use of simple
diagnostics, such as regressing genetic differences against
geographic distance, to choose the appropriate statistic. It
advises that c2 should be used whenever possible, but that if
the situation occurs where most individuals have unique
haplotypes, K*ST is preferred to fST because its performanceis improved by down-weighting the phylogeographic signal
relative to the frequency differences.
In discussion, the Workshop welcomed these papers as
they provided the first attempt at developing an approach forquantifying the effect size for use in tests of panmixia.
Palsbøll suggested that the reduced power of the sequence
statistic relative to the haplotype statistic observed in
SC/F2K/J5 might be due to the high mutation rate (0.0001)
and the few variable sites (40) employed in the simulations.
For instance, in a population of 1,000 mtDNA haplotypes, asingle mutation is expected in each mtDNA sequence after
only 40 generations. Thus, over thousands of generations,multiple mutations are expected at many positions,degrading the phylogenetic signal captured by the sequence
statistic. Genetic drift is probably so rapid in smaller
populations that the effect of the mutation rate is negligible.
The tests for panmixia in SC/F2K/J3, SC/F2K/J4 andSC/F2K/J5 are based only on nearest neighbour comparisons
to mimic common practice. The Workshop agreed that, forapplication to North Pacific minke whales, potential
analyses using geographic distance are not immediately
pertinent because the comparisons presented to theWorkshop were based on data for two rather than for many
areas.
The quantitative results of SC/F2K/J3, SC/F2K/J4 andSC/F2K/J5 are dependent on the specific model and thevalues for its parameters. The model used was notparameterised for minke whales in the North Pacific nor was
the scenario of five sub-populations arranged linearlyconsidered directly relevant to an evaluation of JARPN.
Okamura pointed out that the null hypothesis of panmixia
was not strictly fulfilled in SC/F2K/J3 because only thedifferences between adjacent groups had been examined
there. He therefore called into question the reliability of theresults of SC/F2K/J3. He also drew members’ attention to381

J. CETACEAN RES. MANAGE. 3 (SUPPL.), 2001

the fact that hypothesis testing for North Pacific minke
whales was based strictly on the null hypothesis of
panmixia.
Taylor highlighted that the distributions for the effect sizevary over time and reflect a balance between the rates of
haplotype mutation, dispersal and genetic drift which dependon the overall sizes of the populations. In response to a query
regarding the size of the assumed mutation rate, shecommented that mutation rates for cetaceans were very
poorly known but that the value chosen led to haplotype
frequency distributions that were not too dissimilar from
actual observations.
Some members questioned the inferences made in
SC/F2K/J3, SC/F2K/J4 and SC/F2K/J5 regarding themanagement implications of dispersal rates of the order of
0.5% per year, noting that previous examinations of theperformance of the RMP suggested that unintended stock
depletion becomes less likely with dispersal rates of thismagnitude (IWC, 1993, p.189). This is discussed further
under Item 10.3.2.

animals occurs in sub-area 11 in July-August with the malemixing rate exceeding that of females, SC/F2K/J12 did not
find any evidence for additional stock structure in sub-areas
7, 8 and 9.
SC/F2K/J32 presented the results of an additional analysis
of mtDNA sequences based on JARPN samples. The
purpose of the study was to understand the reasons for the
low p-values found in the comparisons involving sub-area 9
in SC/51/RMP8, SC/F2K/J11 and SC/F2K/J6. The statisticalanalyses based on FST and fST, indicated that a possible
source of mtDNA heterogeneity can be attributed to minke
whales sampled in the western sector of sub-area 9 in 1995
(west of 162°E). Sub-area 9 was divided at this longitude to
maximise the difference between the east and west of
sub-area 9 (Table 1). This is post-stratification. No
significant genetic heterogeneity was found between westernand eastern samples in sub-area 9 in 1995 using a
microsatellite analysis.

10.2.1 DNA and allozyme data
In preparation for the discussion of methods and results
related to DNA and allozyme data, Palsbøll (Annex F)
outlined the basic concepts and statistics.
SC/F2K/J10 examined genetic population structure inwestern North Pacific minke whales based on eightmicrosatellite loci. The 496 samples collected during
JARPN between 1994 and 1999 were used (sub-area 7,
n = 137; sub-area 8, n = 91; sub-area 9, n = 188; and sub-area
11, n = 8). Samples from the former coastal whaling
operation in Korea and from recent bycatches in the Sea ofJapan (sub-area 6, n = 39), were used as an out-group.
Significant deviations from Hardy-Weinberg equilibrium
were detected in the JARPN datasets for 1996 and 1999.
These were attributable to the inclusion in the analysis ofsamples from sub-area 11. However, no deviation was
detected in sub-areas 7, 8 and 9 nor was hierarchicalstructure observed among sub-areas 7, 8 and 9. Homogeneity
tests also revealed genetic heterogeneity in sub-area 11.
SC/F2K/J10 supported previous allozyme and mtDNA
analyses that mixing of ‘J’ and ‘O’ stock animals occurs inthe southern part of the Sea of Okhotsk, but did not support
the existence of additional stock structure to the east ofJapan.
SC/F2K/J11
used
restriction
fragment
lengthpolymorphism (RFLP) and sequencing analyses of themitochondrial DNA (mtDNA) control region to examine
genetic stock structure of minke whales in the western North
Pacific. The 418 samples (sub-area 7, n = 139; sub-area 8,
n = 91; sub-area 9, n = 188) collected between 1994 and 1999
were used in the analysis. Samples from past coastal
commercial whaling in Korea were used as an outgroup(sub-area 6, n = 29). Homogeneity tests were based on
haplotype (FST) and sequence statistics (fST) using Analysisof Molecular Variance (AMOVA). Significantly lower
nucleotide diversity was estimated for sub-area 6 comparedto the sub-areas of the east of Japan. The results of thehomogeneity test showed that whales from sub-area 6 were
genetically different from those to the east of Japan. No
statistically significant differences at a = 0.05 were found in
the data for sub-areas 7, 8 and 9.
SC/F2K/J12 used data on allozymes at loci Adh-1, Gpi
and 6Pgd from 497 minke whales taken in the JARPN
surveys to examine whether or not more than one stock ofminke whales is found to the east of Japan. Although theresults confirmed that substantial mixing of ‘J’ and ‘O’ stock&RPSDULVRQEHWZHHQVXEDUHD -$531 DQGVXEDUHD -$531 XVLQJDUDQGRPLVHG  . WHVW  VLPXODWLRQV  9DOXHV JLYHQ DUH SUREDELOLWLHV
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Hatanaka highlighted two possible interpretations of thelow p-values in SC/F2K/J32. The result could be a statisticalartefact; such a conclusion is consistent with the lack of an
indication of stock structure in sub-area 9 from, for example,
nuclear DNA and allozymes. Alternatively, it may be theresult of a group of animals that is genetically distinct fromthe ‘O’ stock entering the west of sub-area 9 once every few
years. Such a group would probably constitute only arelatively small fraction of the total abundance in sub-area 9.
Taylor expressed the view that the result in SC/F2K/J32 was
not different from the recent discovery that geneticallydistinct stocks of Southern Hemisphere minke whales appear
to be found in some areas during some years. Walløe warnedof not over-interpreting the results given that the data were
post-stratified to achieve the largest possible difference
within sub-area 9. Punt cautioned that, although a significant
result had only been found for 1995, the sample size for 1995
was larger than for 1997 and (particularly) 1994.
SC/F2K/J30 examined genetic structure between
sub-areas of the western North Pacific minke whale using
allozyme allele frequency data from Adh-1 locus. The
statistical power of tests for determining whether there is asignificant difference between samples from sub-areas 7 and
9 was estimated using a model for the hypothesised ‘W’stock that assumed that the allele frequency for such a stocklay between those for the ‘J’ and ‘O’ stocks. SC/F2K/J30
argued that conversion of the allele frequency for the ‘W’382

REPORT OF THE WORKSHOP

stock compared to that for ‘O’ stock to a dispersal rate led toa better understanding of the results and gave a reliable guidefor the relationship between gene flow and statistical power.
SC/F2K/J30 concluded that it was unlikely that a stock thatis genetically different from the ‘O’ stock is found in
sub-area 9.
SC/F2K/J30 estimated the dispersal rate between
sub-areas 7 and 9 from the value for FST by inverting
Wright’s Island formula and assuming a value for theeffective population size. The Workshop agreed it would behighly desirable if distributions of dispersal rate could bederived from values of FST. Taylor outlined a modelling
framework based on the simulation models similar to thosethat underlie SC/F2K/J3, SC/F2K/J4 and SC/F2K/J5, which
can be used to determine the likelihood of different rates ofdispersal given a value for FST. The approach can only utilise
values of FST from analyses of mtDNA data because of thecomplications associated with developing a model ofmicrosatellites as that would involve explicitly modelling
breeding strategies.
The Workshop agreed with the conclusion of a small
group (Butterworth, Okamura, Kawahara, Palsbøll, Punt,
Taylor and Walløe) chaired by Walløe that the approach
used in SC/F2K/J30 was probably inadequate. Reasons forthis include the fact that the actual value of FST can vary
substantially over time due to the impact of mutation anddispersal (Taylor et al., 2000). The size of this effect can be
reduced by considering multiple loci (although that is notpossible for analysis of mtDNA data). Furthermore, thedispersal rate is a function of the reciprocal of FST, so thatapplication of Equation 4 of SC/F2K/J30 will lead to abiased result. Finally, there is considerable uncertainty
regarding the estimation of the effective population size forcetacean stocks (for example, the CVs for the abundance
estimates for sub-area 9 range from 0.32-0.40) and theimpact of the assumption that the effective population size ofthe two populations is the same (Taylor et al., 2000). Table
3 of SC/F2K/J32 highlighted some of the uncertainty
associated with this approach; the estimates FST based ondata for 1994, 1995 and 1997 differ by more than an order ofmagnitude, as therefore would any estimate of dispersal
rate.
SC/F2K/J28 examined the possibility of assigningindividuals to the ‘J’ stock. A total of 863 mtDNA control
region sequences from past commercial whaling in Japanand Korea (sub-areas 6, 7 and 11), from bycatches in the Sea
of Japan (sub-area 6), and from JARPN surveys in sub-areas
7, 8, 9 and 11 were examined. Phylogenetic reconstruction ofunique sequences was based on the neighbour-joining
method. The tree showed a cluster containing haplotypes
that occur predominantly in the Sea of Japan or share
haplotypes ‘3’ and ‘5’ of a previous mtDNA control region
RFLP analysis (Goto and Pastene, 1997). There is currently
no certainty, however, that the haplotypes contained in thecluster are diagnostic markers for the ‘J’ stock. Nevertheless,several biological studies (SC/F2K/J13, SC/F2K/J15,
SC/F2K/J17, SC/F2K/J20, SC/F2K/J25) that used thismethod to identify possible ‘J’ stock animals foundsignificant differences between the animals identified as ‘J’
stock animals and other animals (assumed to be from the ‘O’stock).
Using the methods of SC/F2K/J28, 2-11% of the animals
in sub-areas 7, 8 and 9 were identified as being from the ‘J’stock (table 2 of SC/F2K/J28). However, the percentages
probably overestimate the actual number of ‘J’ stock animals
in those sub-areas, as some ‘O’ stock animals may share thehaplotypes used to identify ‘J’ stock animals. The Workshop

agreed that the probability of correctly assigning animals tothe ‘J’ stock was probably similar to that of 0.95 obtained by
Congdon et al. (1999). However, SC/F2K/J28 is based on alarger sample of known location than SC/51/RMP20,
including additional animals from sub-area 6.
SC/F2K/J6 used the randomisation version of c2 toreanalyse the mtDNA data gathered during JARPN. The
reanalysis concentrated on the question of whether there ispopulation structure among minke whales to the east andnorth of Japan. Comparisons of sub-areas 7 and 8 to sub-area
9 resulted in a p-value of ≈ 0.06-0.07 depending on whether
the data for sub-areas 7 and 8 are compared separately orpooled. Given that statistical power is likely to be low for
dispersal rates of interest, SC/F2K/J6 concluded that a
p-value of 0.06 probably indicates that population
subdivision is present. The power to detect population
subdivision is also likely to be compromised by initialboundary placement because the boundaries between these
sub-areas clearly cut through high densities of samples.
SC/F2K/J6 concluded that there is no justification for
asserting that these data are consistent with no population
subdivision within sub-areas 7, 8 and 9, and that it is likelythat the analyses of population structure have been
compromised by poor initial boundary placement. The
differences between stocks are not fixed differences, butrather small differences in haplotype frequencies. These
small frequency differences will make it impossible toidentify most individuals to their stock-origin.
SC/F2K/J7 estimated the statistical power when detecting
population subdivision for a plausible stock structure forNorth Pacific minke whales. The analysis was limited to thequestion of whether two stocks exist to the east and north ofJapan (i.e. within sub-areas 7, 8, 9, 11 and 12). Historicalnumbers were based on one of the base-case Implementation
Simulation Trials (N1-j1g0, IWC, 1999b, pp.86-97). This
trial assumes that 30% of the animals in the Sea of Okhotsk(sub-area 12) come from the ‘O’ stock. Power was estimatedusing simulations and the effect size of a dispersal rate of
0.5% between the stocks. The simulation technique wasmodified to use minke whale-like birth and death rates,
which resulted in an average birth and death rate of 0.04 anda generation time of 19.6 years. Even for the most powerfulstatistic of population differentiation (c2), the power todetect population subdivision was only 0.49 when a = 0.05.
Using a = 0.05 as the criterion for significance would resultin making Type II errors (under-protecting minke whales)
over ten times more frequently than making Type I errors(over-protecting minke whales). When Type I and Type IIerrors were equalised, the critical a-level was 0.23, i.e. any
p-value less than 0.23 would result in rejecting the null
hypothesis of no population structure. Even with thisincreased a-level, the statistical power would be only 0.77.
The paper concluded by suggesting future directions for
estimating statistical power for North Pacific minke
whales.
Taylor indicated that one approach to handling
uncertainty about boundaries was to use the data to indicate
possible boundaries and then to determine the dispersal rate
across each such boundary. Butterworth questioned theassertion that the current boundary at 150°E passed throughan area of high density and argued that using the genetic data
to identify possible boundaries was inappropriate as it
involved using the data twice (once to identify the boundary
and then to test hypotheses related to that boundary). This isdiscussed further under Item 10.2.4. SC/F2K/J7 highlighted
the strategy of choosing a-levels so that the a-level equals
the b-level. Butterworth considered that account also needed

J. CETACEAN RES. MANAGE. 3 (SUPPL.), 2001

to be taken of the number of tests conducted and the likely
utility of the techniques on which those tests are based wheninterpreting results and selecting a-levels. Taylor
commented that standard Bonferroni factors to correct for
multiple comparisons were often inappropriate for biologicalquestions and should not be applied blindly.
Okamura commented that the assumption of two
populations and (more than) three arbitrary boundaries in thewestern North Pacific was appropriate when estimating
statistical power. However, SC/F2K/J7 assumed two
populations and two correct boundaries. Therefore, hebelieved that the statistical power calculated in SC/F2K/J7
was unreliable for the situation of minke whales in thewestern North Pacific. Finally, he commented that both theresults of pooling and non-pooling of data in the western
North Pacific should not be assumed to have the same
statistical power.
SC/F2K/J2 described a Bayesian modelling frameworkthat can use genotype frequency information for one or moreloci to assign relative probabilities to alternative
stock-structure hypotheses by means of the Bayes factor.
The authors argued that this framework has advantages overmaximum-likelihood estimation as it provides a basis toassign weights to alternative hypotheses. A set of priordistributions for the allele frequency probabilities for
two-stock hypotheses were put forward. These range fromassuming that the relative frequencies for the two stocks are
independent, to assuming that they are almost perfectly
correlated. When applied to the data for the Adh-1 and Gpi
loci for sub-areas 6, 7 and 11 for the North Pacific minke
whales, the results confirm those of previous studies that
there are (at least) two stocks in those sub-areas. In contrast,
applications to data for sub-areas 7, 8 and 9 support the
hypothesis of a single stock there, unless, a priori, the allele
frequencies for two stocks that are adjacent spatially arelikely to be very similar. The technique was not applied to
mtDNA data due to the computational demands of themethods and because of the difficulties of developing
appropriate priors.
It was suggested that values for the parameters of thepriors needed for the approach of SC/F2K/J2 could be
developed from inferences from other stocks or frommechanistic models (such as in SC/F2K/J3). However,comments were made that although high correlation in theallele frequencies among populations should be expected
given the low mutation rates associated with isozyme data, it
is not straightforward to use that information to provide
specifications for priors for use in a Bayesian analysis. The
differences in allele frequencies between stocks in someareas are high (e.g. the ‘O’ and ‘J’ minke whale stocks in the
North Pacific, and the Central and NE minke whale stocks in
the North Atlantic). However, they can also be negligible(e.g. for minke whales in the Southern Hemisphere) evenwhen based on other techniques there is clear evidence forstock structure.
10.2.2 Biological (e.g. reproductive) data
SC/F2K/J13 examined some biological parameters (bodylength distribution, mean body length of mature animals,
growth curve, maximum body length and incidence of
anomalous testis) for minke whales in the western North
Pacific, estimated using data collected by JARPN. The data
were divided into ‘O’ and ‘J’ stock animals on the basis of
the method in SC/F2K/J28 (459 and 39 individuals
respectively). There are clear differences for mature females
in the body length distribution, the mean body length, the383

maximum body length (mean body length of animals older
than 14 years) and the growth curve, between ‘J’ and ‘O’stock animals. No clear differences were found in biologicalparameters among ‘O’ stock animals collected fromsub-areas 7, 8, 9 and 11. SC/F2K/J13 provided additional
information about the temporal and spatial aspects of sexualand reproductive segregation. There is no case that allcomponents (immature males, mature males, immature
females and mature females) of the population are found in
the same sub-area. Consequently, it was argued that it isunlikely that an independent ‘W’ stock exists.
In discussion, it was noted that there is a preponderance ofmales in sub-areas 7, 8 and 9 (SC/F2K/J13). Recent JARPN
data in sub-areas 8 and 9 have increased the temporal
coverage in those sub-areas. Although the proportions offemales there are also low, they are similar to that in sub-area
7. Possibly, mature females in sub-areas 8 and 9 are further
to the north (in the unsampled Russian EEZ) as is the case in
the west, closer to Japan. It is not clear whether or not thedata on juvenile proportions continue to support theargument that low proportions of juveniles in offshore areas
are inconsistent with the hypothesis of more than one stock.
There are confounding effects of differing sample sizes permonth and sub-area. The Workshop recommends a
multivariate statistical analysis of the data to clarify theissue.
SC/F2K/J14 examined stock structure hypotheses for thearea to the east of Japan using data on conception dates fromJARPN. Kato (1992) found two foetus cohorts that differ interms of their peak conception dates. ‘O’ stock animals
conceive in winter while ‘J’ stock animals conceive inautumn. Three hypotheses were developed regarding stock
structure in sub-area 9: ‘O’ stock only, ‘W’ stock only and amodel that allowed for mixing of ‘O’ and ‘W’ stock animals
in sub-area 9. The ‘O’-stock-only model gained support
among the three on the basis of Akaike Information Criteria(AIC). SC/F2K/J14 also examined the statistical power to
identify a ‘W’ stock using conception date information basedon the assumption of a difference in peak conception dates of
one month between the ‘O’ and a hypothesised ‘W’ stock.
The results of the simulations combined with the AIC result
led SC/F2K/J14 to argue that there is no ‘W’ stock.
Taylor believed that little could be concluded about theexistence or otherwise of a ‘W’ stock from the results of
SC/F2K/J14. This is because species in other areas (e.g.
North Pacific humpback whales) that can be clearlydelineated into several stocks exhibit no differences inmorphology or conception dates. She commented that while
differences in conception dates and morphology wererelevant when defining evolutionary significant units, thiswas not the case when attempting to identify management
units. Other members commented that differences inconception dates and morphology have been found in otherspecies and stocks, including minke whales.
10.2.3 Morphometric and morphological data
SC/F2K/J15 examined data for thirteen characteristics to
examine the morphological heterogeneity of ‘O’ /’W’ minke
whales, and morphological differences between ‘O’ and ‘J’stock minke whales. Data for 132 individuals (22 fromsub-area 7, 15 from sub-area 8, 81 from sub-area 9 and 14 for
sub-area 11) from JARPN were analysed. Except for one
characteristic, no morphological differences were observed
between sub-areas 7, 8 and 9 (i.e. the hypothesised ‘W’ stock
was argued to be absent) based on an analysis of covariancetaking body length as a covariate, an analysis of variance, a384

REPORT OF THE WORKSHOP

principal component analysis and a discriminant analysis.
The analyses also suggested that there are morphologicaldifferences between ‘J’ and ‘O’ stock animals for fivecharacteristics, although the sample size for the ‘J’ stock was
small.
Hakamada noted that work had started on re-analysing themorphological data using the strata for sub-area 9 identified
in SC/F2K/J32. The Workshop recommended that the work
be continued and the results presented to the next meeting of
the Committee.
10.2.4 Geographical distribution
SC/F2K/J16 summarised the information on distribution
from JARPN. The authors believed that this information canbe used to assess stock identity and to select stockboundaries. Based on the data for 1994-1999, thedistribution pattern of minke whale sightings from
April-September was mapped. Minke whales were widelydistributed north of 40°N between the Japanese coast and theeastern boundary of sub-area 9 (170°E) from May-August(where surface temperature ranged from 3°C to 26°C). The
main distribution area moved northward from 38°N to 45°N
from May-July in the sub-areas to the east of Japan, whichcoincides with the known northward seasonal migration of
the species. Blue, fin, sei, humpback and northern rightwhales were generally seen north of 38°N in sub-areas 8 and9. Bryde’s whales were sighted mainly in the eastern part of
sub-area 7. Sperm whales were widely distributed to the eastof Japan. The minke whale distribution pattern was therefore
not observed for the other large whales. From the viewpointof stock identity, SC/F2K/J16 found no clear evidence forareas of low density that might imply two stocks to the eastof Japan.
Fig. 2, tabled at the meeting, shows the relative density(sightings per unit effort) by degree of longitude throughout
the JARPN sub-areas. It indicates a drop in density at 147°E
related to the boundary of the EEZ of the Russian Federation.
The Workshop was unable to agree whether the current
boundaries of sub-areas 7, 8 and 9 passed through areas ofhigh density. It therefore recommends that, to further
investigate this issue, the sightings data be analysed using a
Generalised Linear Model that includes the covariates ofyear, month, Beaufort Sea state and temperature (see also
Item 12).

10.2.5 Pollutant burdens
From the viewpoint of identifying stock structure,
SC/F2K/J17 examined the levels of persistent organic
pollutants such as PCBs and organochlorine pesticides in 76
minke whales collected during 1996 and 1999. A principal
component analysis (PCA) suggested two groups. One
consists of four individuals collected from sub-area 11 in
1996 which show higher concentrations of DDTs andhexachloro-cyclohexanes (HCHs). As the background levelsof these contaminants are greater in the Sea of Japan than in
the western North Pacific, SC/F2K/J17 suggested that thesefour individuals originated in the Sea of Japan and mixed
with the ‘O’ stock. The study also suggested the use of
persistent environmental pollutants as chemical tracers to
examine the ecology of the North Pacific minke whales.
SC/F2K/J18 presented an attempt to identify
stock-structure using ecological tracers based on
accumulation levels of iron (Fe), mercury (Hg) and cadmium(Cd) in liver, and of polychlorinated biphenyls (PCBs),
DDTs, chlordane compounds (CHLs), HCHs andhexachlorobenzene (HCB) in blubber, collected by the
JARPN surveys in 1994-1999. Some minke whales in
sub-area 11 had higher concentration levels of DDTs,
especially of p,p’-DDT and PCBs. These whales also
showed a relatively lower concentration of Hg. SC/F2K/J18
suggested that they might belong to the ‘J’ stock. The
opposite pattern was found in the rest of the whales in
sub-area 11, which suggests that they could be ‘O’ stock
animals. Genetic results (SC/F2K/J28) and occurrence ofscars on the skin surface also supported these conclusions.
Principal component and discriminant analyses of thesechemical accumulations revealed that the ‘J’ and ‘O’ groups
can be clearly discriminated. SC/F2K/J18 did not find any
statistically significant differences among sub-areas 7, 8 and
9 and hence save no support for the hypothetical ‘W’stock.
Hester commented on the differences in degree of scarring
noted on ‘J’ and ‘O’ stock animals in tables 2 and 3 of
SC/F2K/J18. The scars are likely the result of bites by small
mesopelagic sharks of the genus Isistius, which are found intropical oceanic waters. The fact that these marks are much
more prevalent on ‘O’ stock animals suggests that the ‘J’ and‘O’ stocks are isolated not only by a difference in thebreeding season as noted in SC/F2K/J14, but also by spatial
separation of the breeding areas; ‘O’ stock animals using

Fig. 2. Relative density by longitude across the JARPN sub-areas.

J. CETACEAN RES. MANAGE. 3 (SUPPL.), 2001

tropical oceanic waters where they are attacked by Isistius,whereas ‘J’ stock animals might breed in more coastal waters
where these sharks are less likely to be encountered. He
further commented that information on pollutants incetaceans was of general interest to the Commission and thisis discussed further under Item 12.
10.2.6 Parasite loads
SC/F2K/J19 summarised parasite and epizoite studies during
JARPN to identify ‘J’ stock whales in sub-area 11 and ‘W’stock animals in sub-areas 7, 8 and 9. Three species ofparasites: Lecithodesmus goliath (Digenea), Anisakis
simplex (Nematoda) and Penella balaenoptera (Copepoda)
were used for the analyses because they showed roughregional differences in prevalence. Host-age related changes
in prevalence were ruled out by using mature males for the
analyses. The method described in SC/F2K/J28 was used todivide the animals in sub-area 11 into ‘O’ and ‘J’ stock
animals. Putative ‘J’ stock whales were characterised by alow prevalence of P. balaenoptera. Although several
regional differences were found in the prevalence of L.
goliath and P. balaenoptera in sub-areas 7, 8 and 9, no
statistically significant difference was found among these
sub-areas when the frequency distributions of the intensities
of both parasites were compared. Therefore, SC/F2K/J19
concluded that the ‘W’ stock could not be differentiated fromthe ‘O’ stock because no area-specific parasite was found,and because regional differences in prevalence and intensity
were insufficiently large to identify a ‘W’ stock.
The Workshop discussed the possible causes for thestatistically significant differences among sub-areas 7, 8 and
9 in the prevalence of L. goliath and P. balaenoptera. These
included that there was some stock structure, that there is anage-effect in the parasite load with age being correlated withincreasing longitude, and that the parasite load is primarily
determined by feeding and migration behaviour. The
Workshop agreed that interpretation of the results of any
analyses based on parasite loads required information on thelikely residence time of the parasite (noting that P.
balaenoptera is an external rather than an internal parasite).
It was noted that the likelihood of invasion by parasites
depended on body condition as well as on feeding behaviour
and age. For external parasites, the residence time may beparticularly short if, as seems likely for P. balaenoptera, theparasite is lost once the animal enters cold water.
10.2.7 Other data
SC/F2K/J20 examined carbon and nitrogen stable isotope
ratios in baleen, muscle and liver (21, 44 and 44 individuals
respectively) of mature male minke whales to estimate
recent diet and to examine stock structure. One or two
d15N-depletion peaks were formed in the baleen of thewhales caught in sub-areas 7 and 8 and they were considered
to be formed in early summer. The growth rate of baleen was
estimated to be about 130mm/year. It was therefore assumed
that approximately 1.5 years of diet record would remain in
the baleen plates of mature minke whales. The isotopic
values in d13C-d15N maps differed between sub-areas 7+8
and 11 in the three tissues although there were no differences
between sub-areas 7 and 8. Some of the whales, identified as
being from the ‘O’ stock from genetic analyses(SC/F2K/J28), showed isotopic values characteristic of
sub-areas 7 and 8 in spite of its being sampled in the sub-area
11, and some whales sampled in sub-areas 7 and 8 showedisotopic values characteristic of sub-area 11. This suggeststhat some of the ‘O’ stock animals migrate among sub-areas
7, 8 and 11.

385

Punt commented that basing stock structure for North
Pacific minke whales on stable isotope ratios could lead tolarge Type I errors as these ratios may represent recent
feeding behaviour rather than stock structure.
Tamura indicated that the information on condition factor(‘fatness’) in SC/F2K/J25 provided some data that may be
relevant to assessing stock structure for minke whales in the
North Pacific. Punt commented that care should be taken
when interpreting differences in condition factor among
sub-areas as this may be a result of differences in foodavailability for different areas rather than in stock
structure.
10.3 Synthesis and Conclusions
10.3.1 The existence of the ‘W’ stock (objective 1)
Discussion of this issue was based on preliminary viewssummarised by Hatanaka (Annex G) and Taylor (Annex H)prior to discussion of the agenda item by the Workshop. The
report as set out below does not repeat material in thosesummaries, but lists only points raised in discussion andconclusions reached, using the same sub-headings as in the
Annexes.
10.3.1.1 DNA ANALYSIS

In the light of points raised during the Workshop, the
mtDNA analyses were repeated using the c2 statistic, andwith data from the commercial fishery in sub-area 7 both
excluded and included. A significant effect (at the 5% level)
between sub-areas 7 and 8 on the one hand, and 9 on theother was noted in the former case; when commercial data
are included, the p-values, although above 5%, remain
sufficiently small to be suggestive of some effect (see Table1). The effect seems to arise from samples taken in thewestern part of sub-area 9 in 1995 (SC/F2K/J32).
The Workshop agreed that further analyses of these andother data collected during JARPN should be carried out toexplore this finding further, using stratifications differingfrom those adopted for the sub-areas for the RMP trials,
although taking care not to use identical data for bothhypothesis generation and testing. Specific suggestions forthese further analyses are detailed in Annex I.
The Workshop agreed that in the light of these results, thepossibility of the existence of some group of minke whales tothe east of Japan that differed from the ‘O’ stock could not be
ruled out, but that the data nevertheless provided a basis torestrict the number of ‘W’ stock hypotheses that need to beconsidered in the RMP trials, as discussed further below.
10.3.1.2 ALLOZYME ANALYSISThe Workshop noted that in theory allozymes should
provide less resolution of stock structure than mtDNA andmicrosatellites. However, although this was often born out inpractice, there is at least one case where the reverse holds,
e.g. in the North Atlantic. The Workshop emphasised theneed to consider results of various genetic analyses incombination.
10.3.1.3 BIOLOGICAL PARAMETERS

Discussion of sex and length data collected during JARPN isreported under Item 10.2.2 above. The Workshop agreed
that while differences in mean conception dates comprised
strong evidence for more than one stock, it is much lesscertain what inferences can be drawn in the reverse situation.
While it agreed that the reverse situation could increase

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probabilities assigned to a one stock hypothesis prior to suchinformation being available, it would be difficult to quantify
the extent of the change.

10.3.1.4 MORPHOLOGICAL AND MORPHOMETRIC ANALYSESThe Workshop agreed that discussions of the implications ofthese analyses were complicated by the fact that thoughsome differences significant at the 5% level had been found,many tests for differences had been conducted.

10.3.1.5 POLLUTANTS, PARASITES, STABLE ISOTOPES AND OTHERANALYSES

The Workshop agreed that the pertinence or otherwise of
information under these headings to stock structure
determination depended particularly on residence time andaccumulation effects. More information was needed on thesefactors before any significant differences detected underthese headings can be interpreted in the context of stock
differentiation.

10.3.1.6 IN SUMMARY

The Workshop agreed that some of the difficulties
experienced in discussing stock structure arose from lack ofclarity in the Committee as to what constituted a ‘stock’.
This needed to be expressed in terms of likely dispersal rates
between ‘stocks’, where ‘dispersal’ refers to geneflow. In thecontext of trials, the Workshop recognised that ‘dispersal’ ismodelled as permanent transfer from one breeding
population to another. For example, established differences
between the ‘J’ and ‘O’ stocks were sufficiently large thatany such dispersal rate must be negligible on the time scale
relevant to demographics and management. Hester, Ohsumi
and Kawahara believed that there is no evidence for the
existence of a ‘W’ stock in the sense used by the Committee
in 1993 and 1996. It was clear from analyses presented thatany differences between the ‘O’ and hypothesised ‘W’ stock
would have to be much smaller than those between the ‘O’and ‘J’ stocks. In these circumstances, the associated ‘O’ and‘W’ stock dispersal rate might be sufficiently large tonotably affect demographics. The present assumption in the
Implementation Simulation Trials of setting this dispersal
rate to zero would then be inappropriate.
In particular, what has been unclear in the Committee’s
use of the word ‘stock’ is whether it is referring to‘evolutionarily significant units’ or to ‘management units’(e.g. see Donovan, 1991; IWC, 1999a). It was certainly notclear that the level of difference evident between the ‘J’ and‘O’ stocks (which are clearly evolutionarily significant
units) should necessarily serve as the norm for defining
separate management units. On the one hand, for example,
humpback stocks with no differences in biological measures(e.g. conception dates), but known from photo-identificationand mtDNA studies to be demographically isolated, werecited. On the other hand, North Atlantic minke whale stocks
had been differentiated by allozyme data, and in the absenceof geographical features, which in the case of the J-’O’ stock(the re-opening of the Sea of Japan some 10,000 years ago)
rendered the development of differences easier tounderstand.
The Workshop noted that the Committee has established a
Working Group to examine general issues of stock identity
in a management context.
Given difficulties that had arisen in interpreting resultsfrom multiple applications of significance tests, theWorkshop recommends that further methods of analysis,
such as multivariate analysis, be pursued to attempt to avoid
this problem.
10.3.2 Estimation of mixing rates between ‘O’ and ‘W’stocks (objective 1)
In the RMP trials ‘mixing’ has been taken to refer to theextent of overlap of whales from different stocks,
particularly in feeding areas. Such information is needed tointerpret catches and estimates from sightings surveys ofabundance on a per-stock basis. It is quite distinct frompermanent transfer of animals between breeding stocks,
referred to above as ‘dispersal’ (or ‘leakage’ in RMP trial
terminology). Estimates of mixing determined from genetic
studies (e.g. SC/F2K/J2) will be less precise the smaller the
genetic difference between the overlapping stocks.
In the context of the hypothesised ‘W’ stock, ‘mixing’
relates to the sub-areas (and times) where animals from thisstock might be present. The Workshop agreed that it would
be premature to draw conclusions on the extent of thepossible presence of ‘W’ stock animals west of sub-area 9,prior to completion of the further analyses detailed in Annex
I. However, it also agreed that if such analyses provided noevidence to change the existing sub-area stratification froma stock structure identification perspective, then sub-areas 7
and 8 need not be distinguished for that purpose.
Furthermore, current hypotheses placing ‘W’ stock animals
in sub-area 7 and/or 8 could then be rejected. The Workshop
recommends that the results of these further analyses arereported to the next Committee meeting for consideration.
Existing genetic analyses suggested that possible ‘W’stock animals might be present in only part of sub-area 9, andthen only in some years (SC/F2K/J32). Such information
might be used to estimate maximal abundance for the ‘W’stock, but the Workshop noted that the precision of any such
estimate would be low given that sub-area 9 has beensampled only twice at most in any one month.
Regarding dispersal, the Workshop agreed that if there
was a ‘W’ stock, there had also to be a non-negligible levelof dispersal between this and the ‘O’ stock, for the reasons
discussed above. This in turn likely meant that such dispersal
effects needed to be included in the RMP trials. A sub-groupof Butterworth, Kawahara, Okamura, Punt, Taylor andWalløe was appointed to advise what further computations
were required to assist in determining ranges of dispersal
rates appropriate for consideration in the trials. Following
their advice, the Workshop recommends that Taylor’s
program (Taylor et al., 2000) should be used for this purpose
and that the sub-group should monitor the progress of theassociated computations and present a report to the next
Committee meeting. Initially, dispersal rates of 0.005 and
0.0005 per annum would be examined, with sampling rates
equal to and double those assumed by Taylor in SC/F2K/J7,
and with distributions of the actual and sampled values of thestandard genetic statistics reported. If necessary the
sub-group can specify possible further calculations in thelight of the results of the initial computations, if there issufficient time to undertake the computationally extensive
exercises.
10.3.3 Estimation of mixing rates between ‘J’ and ‘O’stocksSC/F2K/J27 presented estimates of the proportion of ‘J’stock animals in sub-area 11, by month and sex. Threemolecular markers were used: mtDNA control region RFLP
haplotype frequencies, mtDNA control region sequencing

J. CETACEAN RES. MANAGE. 3 (SUPPL.), 2001

haplotype frequencies and microsatellite allele frequencies.
The data on which the analyses were based (720 samples)
were obtained from JARPN surveys and from past coastal
whaling operations off Korea and Japan. Samples fromsub-area 6 were used as the baseline for the ‘J’ stock andsamples from sub-area 7 were used as the baseline for the ‘O’stock. Estimates obtained using mtDNA RFLP andsequencing data were similar. These analyses werecross-checked by assuming sub-area 9 samples to reflect the‘O’ stock. The mtDNA and microsatellite data suggested
that a substantial fraction of the females found in sub-area 11
in April are from the ‘J’ stock. The estimate of the mixing
proportion obtained using the mtDNA data was, however,higher though not significantly so. Furthermore, a relatively
high mixing proportion of ‘J’ stock males in sub-area 11 was
obtained using the mtDNA analyses for August. The
microsatellite analysis resulted in a high but imprecise
estimate for that proportion.
Noting that some of the mixing rate estimates reported in
SC/F2K/J27 were based on the assumption that all samples
taken from sub-area 9 were from the ‘O’ stock, theWorkshop recommends that the sensitivity of these results
to omission of the samples for the west of sub-area 9 (i.e.
west of 162°E) in 1995 be checked as this area may containsome ‘W’ stock animals (SC/F2K/J32). The results should
be reported to the Committee to take into account further
refinement of the Implementation Simulation Trials.
10.3.4 Implications for Implementation Simulation Trials
The Workshop noted that the discussion and decisions
reflected under Items 10.3.2 and 10.3.3 are also relevant tothis agenda item.
One key aspect of the trials to which those discussions do
not refer, is the variety of assumptions about the proportionof animals in sub-area 12 (the Okhotsk Sea) that may
originate from the hypothesised ‘W’ stock. There are no data
available from JARPN for this sub-area (or portions of
sub-areas 7, 8 and 9 in the Russian EEZ) to perhaps shedlight on this aspect. However, it may be possible to draw
further inferences about the relative likelihood of alternative
hypotheses about the ‘W’ stock in sub-area 12 on the basis of
the results of the further ‘W’ stock-related computations
recommended (see Item 10.3.1 and Annex I). The Workshop
recommends that further genetic samples from particularly
sub-areas 12, 9 and possibly 8, be obtained to facilitateclearer discrimination among alternative ‘W’ stock
hypotheses.

11. FEEDING ECOLOGY
11.1 Background
When the JARPN feasibility studies started in 1994, themain objective was to elucidate the stock structure ofwestern North Pacific minke whales. When those activities
were upgraded from feasibility studies to full-scale studies in
1996, it was considered necessary also to assess theecological role of the minke whales in the highly variable
ecosystem of the western North Pacific. Therefore, anadditional objective ‘the feasibility study on the feeding
ecology of minke whales in the research ground’ was added
to the research plan. Although some stomach contents had
been collected in 1994 and 1995, dedicated feasibility
studies to meet the new objective of ecological studies were
not initiated until 1996, whereafter they were continued in all
subsequent years.

387

SC/F2K/J31 gave a brief review of studies of minke whale
feeding ecology conducted in the western North Pacific prior
to the JARPN surveys. Those studies, which included
stomach analyses of whales taken in commercial catches,
had suggested geographical, seasonal and annual changes ofminke whale prey species in the area. The whales wereassessed as being opportunistic feeders with a broad diet andflexible feeding habits. They fed on swarming zooplankton
and a number of schooling fish species, and exhibited theability to pursue single prey species aggregations. Observed
annual variation in minke whale prey species probably
reflect changes in prey availability in the areas investigated.
For example, in the west of sub-area 7, the change of minke
whale prey species from chub mackerel (Scomber japonicus)
to Japanese pilchard (Sardinops melanosticus) in 1977
corresponded with a shift in dominance of species taken bycommercial fisheries in the same area in 1976. Despiteprevious attempts to obtain information from commercial
catches, knowledge of the feeding activity and foodconsumption of minke whales in the western North Pacificremained fragmentary and insufficient until thecommencement of the JARPN surveys.
11.2 Methods and results
SC/F2K/J22 described the geographical and seasonalchanges of minke whale prey species as observed in thewestern North Pacific during the 1994-1999 JARPN
surveys. The study used contents from 498 whale stomachs,
sampled from May-September. Sixteen prey species (10fish, 1 squid, 4 euphausiid and 1 copepod) were identified.
‘Swallowing’ feeding behaviour was confirmed, and it was
shown that the whales had fed on swarming zooplankton andschooling fishes. Clearly, most of the whales had pursued
single prey species aggregations. The results revealed both
geographical and temporal changes in feeding behaviour. To
the east of Japan, Japanese anchovy (Engraulis japonicus)
was the most important prey species in May and June, while
Pacific saury (Cololabis saira) was most important in Julyand August. Krill species (Euphausia pacifica, Thysanoessa
inermis, T. inspinata and T. longipes) constituted the mostimportant prey group in September. In coastal waters overthe continental shelf, walleye pollock (Theragra
chalcogramma) was also an important prey species during
June and September. In sub-area 11, krill dominated among
the prey species in July and August. These observed changes
in minke whale prey species throughout the research area
most probably reflect changes in the availability of the preyspecies.
The Workshop welcomed the data presented. Given its
nature (a feasibility study) and less than optimal sampling
regime (actually designed for the purpose of stock identity
elucidation), it agreed that the work was a useful addition to
the knowledge of the feeding habits of minke whales in thearea. Haug raised the question why the observed temporaland geographical shifts in diets might occur. The Workshop
agreed that present limited information about the biology,
distribution and abundance of the prey species in the
research area prevented any firm conclusions being drawn.
Concurrent mapping of prey abundance, undertaken alongwith the whaling activities for the first time in 1999, might bea first step to resolving the question.
Diurnal changes in the feeding activity of minke whales in
the western North Pacific were described in SC/F2K/J23.
The study examined the 498 stomach samples obtained in the
1994-1999 JARPN surveys, and classified each whale
according to one of four dominant prey species: Japanese

388

REPORT OF THE WORKSHOP

anchovy, Pacific saury, walleye pollock and krill in the
sub-areas to the east of Japan, and krill in sub-area 11. The
results suggested little diurnal change in feeding activity.
The lack of diurnal patterns in krill consumption differedfrom observations of minke whales feeding near the ice-edge
in the Antarctic where there was usually a morning peak infeeding activity (Ohsumi, 1979). Kato suggested that thefeeding areas surveyed might be sub-optimal with respect tokrill availability, and that more Antarctic-like behaviour
might take place closer to the ice-edge, for example in
sub-area 12. Observations similar to those in the western
North Pacific had been made in the Norwegian ecologicalstudies of minke whales in the North Atlantic (Haug et al.,1995).
SC/F2K/J24 estimated the daily and seasonal foodconsumption based on contents from the 498 stomachs,
sampled from May-September in the 1994-1999 JARPN
surveys and estimates of abundance by sub-area from thesightings surveys. Daily food consumption was estimatedusing two independent methods: (1) diurnal change in theforestomach and fundus content weight; and (2) energetic
requirements. Estimates obtained by method (1) were
3.9-5.7 and 2.6-3.9% of body weight if the proportion offood remaining in the stomachs after eight hours of digestion
was assumed to be 5 and 20%, respectively. Estimatesobtained by method (2) ranged from 1.8-5.2% of bodyweight. The values were comparable with estimates madefor northeast Atlantic minke whales and Antarctic minke
whales. The estimated total consumption of prey species byminke whales occurring to the east of Japan (sub-areas 7, 8
and 9) during August and September was 2.1-4.0 3 104 tonsof krill, 0.4-0.6 3 104 tons of Japanese anchovy, 2.8-6.2 3104 tons of Pacific saury and 0.3-0.4 3 104 tons of walleye
pollock. Total consumption of krill by minke whales
occurring in sub-area 11 during August and September was
calculated as 1.4-2.2 3 104 tons by the two methods.
The Workshop recognised the attempts to estimate dailyand seasonal food consumption using two different andindependent methods, but considered that both neededrefinement. In method (1), the assumption of an average
passage time of eight hours for all food items was made.
Since no information is yet available on food passage time
for minke whale stomachs, the assumption is subject toconsiderable uncertainty. The Workshop agreed that if thismethod, originally designed to calculate consumption rates
in fish, is to be used in future minke whale studies, some of
the assumptions should be refined using empirical data. It
noted that, with the logistics applied in the JARPN surveys(including the use of a large mother vessel), experiments
addressing some of these questions might well be carried out
in the field. With respect to method (2), it noted that theenergetic costs of blubber deposition and visceral fat
deposition had not been taken into consideration in thecalculations. Haug suggested that this be done, and that
future calculations of food consumption using method (2)follow the approach described by Folkow et al. (2000) in
their calculations of minke whale food consumption in thenortheast Atlantic.
The Workshop noted that the consumption calculations
were performed only for August and September. With thesampling design used in JARPN so far, a quantitative
measure of temporal and geographical changes in minke
whale diets could not be obtained. Thus, extrapolations to
calculate the annual consumption of the entire population
found in the research areas could not be performed. It agreed
that if surveys are to be performed in the future, the sampling
design should permit such calculations.

Results from examination of body fat condition of western
North Pacific minke whales were presented in SC/F2K/J25.
Data were obtained from the 498 whales collected in the
1994-1999 JARPN surveys from May to September. The
properties of three different body fat condition indices were
tested, and it was observed that the patterns of body fat
condition differed by sex and maturity stage. The preferredindex (f(3) = W/Lb) was applied with b, as determined byregression, being 2.0 and 2.5 for sexually mature males andfemales, respectively. W is total weight in kg and L the total
length in metres. Relative blubber thickness and girth werealso used as indicators of body fat condition. It was
concluded that girth was the better measure of body fatness.
Sexually mature females were slightly fatter than males.
Furthermore, the body fat condition of pregnant whales
increased throughout the gestation period until the foetus had
attained a length of approximately 120cm. After this, either
body fat condition increase ceased, or the even fatter
pregnant females may have left the surveyed feeding
grounds. The results indicate that there are wintering whales
occurring in the research area and that most individuals of
the assumed ‘O’ stock move gradually into the surveyed
feeding grounds from breeding grounds elsewhere. After
July, fat whales may either leave the surveyed feeding
grounds, or may remain there for further deposit of fat
reserves. The maximum figure of f(3) was about 1.8 times
the minimum figure. The average rate of increase in f(3)from May to July was about 7% in the research area. Annual
variation in body fat condition was not observed in the
research area during the years 1994-1999, and the observed
results may indicate that the migration pattern of animals
belonging to the ‘J’ stock differs from that of the ‘O’stock.
The Workshop was informed that the condition factor
calculations use the total weight of the animals less theweight of stomach contents and the weight of any foetus. The
weight was, however, not adjusted for blood lost between
killing and weighing. Hester commended the usefulness ofdata of this type, and pointed out their importance withrespect to potential future environmental change studies.
11.3 Synthesis and conclusions
The Workshop noted that the feeding ecology investigations
under JARPN were only a feasibility study. The primaryobjective of JARPN was to obtain data necessary to addressquestions related to stock identity, and this implied asampling design that was less than optimal for the ecologicalstudies. The latter were conducted using well-establishedand appropriate methods, and the Workshop considered thestudy to be successful within those limitations.
The Workshop agreed that if ecological studies of minke
whales are to be conducted in the area, the sampling regime
must be designed to allow for a more quantitative estimationof temporal and geographical variation in diet. That would
eventually permit estimation of the total annual consumptionof fish and crustaceans by minke whales. Given the
migration patterns of minke whales in the area, it is also of
the utmost importance for future ecological studies thataccess be obtained to the unsurveyed feeding grounds in the
Russian EEZ. They include the northern parts of sub-areas 8
and 9 and all of sub-area 12. The Workshop agreed thatsurveys in those areas would give a more complete picture ofboth the ecology and more general biology of the whole
population, including, particularly, mature females.
The Workshop also agreed that it is necessary to obtain an
improved understanding of the distribution and abundanceof relevant prey species to better understand the dynamics of

J. CETACEAN RES. MANAGE. 3 (SUPPL.), 2001

minke whale food choice and consumption. It therefore
recommends that acoustic and trawl surveys, designed toaddress such questions, should be conducted concurrently
with future whale surveys, if possible.

12. OTHER STUDIES
SC/F2K/J26 overviewed the oceanographic conditions in thewestern North Pacific using information collected during
JARPN. Two major frontal systems (the Sub-Arctic Front
and the Sub-Arctic Boundary) were observed to the east ofJapan. The location of the Sub-Arctic Boundary exhibits
strong inter-annual variability, which leads to large
anomalies in temperature. The peak-to-peak value of theyear-to-year variations of Sea Surface Temperature (SST) in
the front region reached about 3°C. In the Sea of Okhotsk, astrong ‘temperature minimum layer’ was found below 1°C.
South of Hokkaido, there are three major components: theTsugaru Warm Current, the Oyashio, and the Warm Core
Ring. A preliminary analysis of the relationship between
oceanographic conditions and the distribution of minke
whale sightings to the east of Japan indicated a strong
correlation between SST and the northward migration ofminke whales.
Taylor highlighted the importance of collecting
information on habitat and prey species for use in analyses ofsightings data. She warned at over-interpreting the result thata correlation between the temperature and minke whale
abundance had been found because the tracklines were notplaced randomly to obtain an even coverage of the region.
Butterworth and Fujise noted that, at the start of JARPN, thetracklines had been placed randomly. However, after it was
found that no sightings were made in water with SST> 15°C, it was decided not to conduct surveys in water
warmer than 15°C. Fujise noted that an echo sounder had
been installed on one vessel in 1999 and that it could be used
in a study of prey species of minke whales.
Hester noted that SC/F2K/J17, SC/F2K/J18 and
SC/F2K/J25, whilst directly addressing questions of stock
identity, also address other priority issues identified by theCommission on the effects of pollution and environmental
change on whales. These, and a number of other reports
JARPN has produced (Annex E), constitute a valuable
source of comparative information for baleen whales of theNorth and South Pacific (JARPA).

13. COMMISSION RESOLUTION 1999-2
The Workshop noted that under this Resolution the
Scientific Committee was asked to advise the Commission
on whether the information sought in research programmes
under Special Permit was: (a) required for management; and(b) could be obtained by non-lethal means.
Bannister conveyed the views of the Scientific Committee
Chair, Zeh, to the Workshop. She believed that while theitem should be on the Workshop agenda, there should not bea long discussion of it. Rather, any results relating to this
topic that emerged during the Workshop should be noted
under this agenda item for presentation to the full Committee
at its forthcoming Annual Meeting in Adelaide. Fulldiscussions should occur during the Annual Meeting, when
all Committee members can participate.
In that context, the Workshop noted that it had not
discussed matters relevant to item (b) above, but that inrelation to item (a), information obtained during JARPN had
been and will continue to be used in the refinement of
Implementation Simulation Trials for North Pacific minke
whales, and consequently was relevant to their
management.
14. RECOMMENDATIONS
Following discussion of Items 1-13, two additional
recommendations were identified:(1) Research potentially employing new technology should
be undertaken to find the breeding grounds, recognisingthat the most definitive stock structure data will likely
come from such grounds.
(2) The age-composition data collected during JARPN
should be analysed further to provide information foruse in conditioning of Implementation Simulation
Trials.
Table 2 outlines all the Workshops recommendations.
In response to the suggestion that research be conducted in
sub-area 13, the Workshop recommends that a full proposal
be presented for consideration at the next meeting of theCommittee.
15. ADOPTION OF REPORTThe report was adopted at 16:50 on 10 February 2000.
The Workshop expressed its appreciation to the Japanesescientists for the clear presentation of their analyses, which
greatly facilitated evaluation of the data collected during
JARPN. Hatanaka expressed appreciation to Bannister forhis guidance during the meeting. Bannister thanked all

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REPORT OF THE WORKSHOP

participants for undertaking a vigorous and fair review; heexpressed the appreciation of all present to the Governmentof Japan and the Institute of Cetacean Research for their
hospitality, meeting arrangements and provision of facilities,
and in particular, to the hard working Secretariat personnel.
He thanked the rapporteurs for their unstinting contributions.
He also thanked the interpreters for their cheerful hard workthroughout the Workshop, noting how much thesimultaneous translation had assisted the Workshop’s
discussions.
REFERENCES
Congdon, B.C., Lento, G.M. and Baker, C.S. 1999. High-resolution
mtDNA identification of minke whale stocks in the North Pacific.
Paper SC/51/RMP20 presented to the IWC Scientific Committee,
May 1999, Grenada, WI (unpublished). 6pp. [Paper available fromthe Office of this Journal].
Donovan, G.P. 1991. A review of IWC stock boundaries. Rep. int.
Whal. Commn (special issue) 13:39-68.
Folkow, L.P., Haug, T., Nilssen, K.T. and Nordøy, E.S. 2000.
Estimated food consumption of minke whales Balaenoptera
acutorostrata in Northeast Atlantic waters in 1992-1995. NAAMCO
Sci. Publ. 2.
Goto, M. and Pastene, L.A. 1997. Population structure of the western
North Pacific minke whale based on an RFLP analysis of themitochondrial DNA region. Rep. int. Whal. Commn 47:531-7.
Haug, T., Gjosaeter, H., Lindstrom, U., Nilssen, K.T. and Rottingen, I.
1995. Spatial and temporal variations in northeast Atlantic minke
whale Balaenoptera acutorostrata feeding habits. pp. 225-39. In:
A.S. Blix, L. Walloe and O. Ulltang (eds.) Whales, Seals, Fish andMan. Proceedings of the International Symposium on the Biology ofMarine Mammals in the Northeast Atlantic. Elsevier, Amsterdam.
720pp.
International Whaling Commission. 1977. Report of the ScientificCommittee. Rep. int. Whal. Commn 27:36-70.
International Whaling Commission. 1978. Report of the ScientificCommittee. Rep. int. Whal. Commn 28:38-74.
International Whaling Commission. 1983. Report of the sub-committeeon minke whales. Rep. int. Whal. Commn 33:91-122.
International Whaling Commission. 1992. Report of the sub-committee
on North Pacific minke whales. Rep. int. Whal. Commn
42:156-77.
International Whaling Commission. 1993. Report of the ScientificCommittee, Annex I. Report of the Working Group on

Implementation Trials, Appendix 4. Specifications of the North
Atlantic minke whaling trials. Rep. int. Whal. Commn 43:189-95.
International Whaling Commission. 1994. Report of the ScientificCommittee, Annex G. Report of the Working Group on North PacificMinke Whale Management Trials. Rep. int. Whal. Commn
44:120-44.
International Whaling Commission. 1995. Report of the ScientificCommittee. Rep. int. Whal. Commn 45:53-103.
International Whaling Commission. 1997. Report of the ScientificCommittee, Annex J. Report of the Working Group on North PacificMinke Whale Trials. Rep. int. Whal. Commn 47:203-26.
International Whaling Commission. 1998. Report of the ScientificCommittee. Rep. int. Whal. Commn 48:53-127.
International Whaling Commission. 1999a. Report of the ScientificCommittee, Annex D. Appendix 4. A recommendation by the RMP
Working Group on Stock Identification to establish a working groupof the Scientific Committee on stock definition. J. Cetacean Res.
Manage. (Suppl.) 1:82-3.
International Whaling Commission. 1999b. Report of the ScientificCommittee, Annex D. Appendix 6. Specifications of the North
Pacific minke whaling trials. J. Cetacean Res. Manage. (Suppl.)
1:86-97.
International Whaling Commission. 2000a. Report of the ScientificCommittee. J. Cetacean Res. Manage. (Suppl.) 2: 1-67.
International Whaling Commission. 2000b. Report of the ScientificCommittee. Annex Q. Terms of Reference for Review of theJapanese Whale Research Programme under Special Permit for
North Pacific minke whales: JARPN. J. Cetacean Res. Manage.
(Suppl.) 2: 309-10.
International Whaling Commission. 2000c. Report of the ScientificCommittee. Annex D. Report of the sub-committee on the Revised
Management Procedure. J. Cetacean Res. Manage. (Suppl.) 2:
79-124.
International Whaling Commission. 2000d. Report of the ScientificCommittee. Annex U. E-mail Correspondence Groups (with Current
Membership). J. Cetacean Res. Manage. (Suppl.) 2: 318.
Kato, H. 1992. Body length, reproduction and stock separation ofminke whales off northern Japan. Rep. int. Whal. Commn
42:443-53.
Ohsumi, S. 1977. Catch of minke whales in the coastal waters of Japan.
Rep. int. Whal. Commn 27:164-6.
Ohsumi, S. 1979. Feeding habits of the minke whale in the Antarctic.
Rep. int. Whal. Commn 29:473-6.
Omura, H. and Sakiura, H. 1956. Studies on the little piked whale fromthe coast of Japan. Sci. Rep. Whales Res. Inst., Tokyo 11:1-37.
Taylor, B.L., Chivers, S.J., Sexton, S. and Dizon, A.E. 2000. Using
simulation models that incorporate uncertainty to estimate dispersal
rates from mitochondrial DNA data. Conserv. Biol.

Annex A
List of Participants
JAPAN
H. AbeT. Bando
Y. Fujise
M. GotoT. Hakamada
H. Hatanaka
H. KatoS. Kawahara
M. Komatsu
T. Kuramochi
K. Matsuoka

K. Mihara (I)T. Miyashita
J. Morishita
S. Nishiwaki
S. Ohsumi
M. Ohta (I)H. Okamura
T. Tamura
A. Tomita (I)K. Yamamura
R. Zenitani

NORWAY
L. Walløe

ST VINCENT AND
THE GRENADINES
F. Hester

INVITED PARTICIPANTS
J. Bannister
D. Butterworth
T. Haug
P. Palsbøll
L. Pastene
A. Punt
B. Taylor

USA
R.L. Brownell Jr.

(I) = Interpreter

RUSSIAN FEDERATION
R. BorodinJ. CETACEAN RES. MANAGE. 3 (SUPPL.), 2001

391

Annex B
Agenda
1. Welcoming remarks
2. Terms of Reference
3. Election of Chair and appointment of rapporteurs
4. Meeting arrangements
5. Adoption of Agenda
6. Review of documents
7. Review of available data
8. Outline of JARPN and past discussions of it in theCommittee
9. Overview of sampling methodology and results
10. Stock structure
10.1 Review of past discussions of stock structure of
the North Pacific minke whale
10.2 Methods of analysis including statistical power
10.2.1 DNA and allozyme data
10.2.2 Biological data (e.g. reproductive)
10.2.3 Morphometric and morphological data
10.2.4 Geographic distribution
10.2.5 Pollutant burdens
10.2.6 Parasite loads
10.2.7 Other data

10.3 Synthesis and conclusions
10.3.1 The existence of the ‘W’ stock(objective 1)
10.3.2 Estimation of mixing rates between ‘O’and ‘W’ stocks (objective 1)
10.3.3 Estimation of mixing rates between ‘J’and ‘O’ stocks
10.3.4 Implications
for
Implementation
Simulation Trials
11. Feeding ecology
11.1 Background11.2 Methodology of data collection
11.3 Methods of analysis
11.4 Results
11.5 Synthesis and conclusions
11.5.1 Determination of feeding(objective 2)
12. Other studies (e.g. oceanography)
13. Commission Resolution 1999-2
14. Recommendations
15. Adoption of report

ecology

392

REPORT OF THE WORKSHOP, ANNEX C

Annex C
List of Scientific Documents
SC/F2K/J1. PASTENE, L.A., GOTO, M. and FUJISE, Y.
Review of the studies on stock identity in the minke whale
Balaenoptera acutorostrata from the North Pacific.
SC/F2K/J2. PUNT, A.E., BUTTERWORTH, D.S. and
WADA, S. On the use of allele frequency data within a
Bayesian framework to evaluate the relative probabilities ofalternative stock structure hypotheses for the North Pacificminke whales.
SC/F2K/J3. MARTIEN, K.K. and TAYLOR, B.L. The
limitations of hypothesis testing as a means ofdemographically delineating independent units.
SC/F2K/J4. TAYLOR, B.L., CHIVERS, S.J. and DIZON,
A.E. Estimating the statistical power to detect population
subdivision using mitochondrial DNA.
SC/F2K/J5. TAYLOR, B.L. and CHIVERS, S.J. Evaluating
the performance of different statistics to detect population
subdivision.
SC/F2K/J6. TAYLOR, B.L. Genetic population structure in
the western North Pacific minke whale: an analysis of
mtDNA data.
SC/F2K/J7. TAYLOR, B.L. and CHIVERS, S.J. An
example of the calculation of the statistical power to detect
population sub-division in North Pacific minke whales.
SC/F2K/J8. FUJISE, Y. Outline of the research activities of
the Japanese Whale Research Program under Special Permit
in the North Pacific (JARPN) from 1994 to 1999.
SC/F2K/J9. FUJISE, Y., ZENITANI, R., TAMURA, T.,
BANDO, T., OHTANI, S., TAKEDA, S., KITAJIMA, A.,
KIMURA, T., MASAKI, T. and TOHYAMA, D. Cruise
Report of the Japanese Whale Research Program underSpecial Permit in the North Pacific (JARPN) in 1999.
SC/F2K/J10. ABE, H., GOTO, M. and PASTENE, L.A.
Population structure in the western North Pacific minke
whale inferred from microsatellite analysis.
SC/F2K/J11. GOTO, M. and PASTENE, L. A. Population
structure in the western North Pacific minke whale based on
RFLP and sequencing analyses of mtDNA control region,
using data from the 1994-1999 JARPN surveys.
SC/F2K/J12. WADA, S. Stock structure of the western
North Pacific minke whales based on the allozyme
analyses.
SC/F2K/J13. ZENITANI, R., KATO, H and FUJISE, Y.
Some analyses on biological parameters of western North
Pacific minke whales, from a view point of stock
identification.
SC/F2K/J14.
OKAMURA,H.,ZENITANI,R.,
HIRAMATSU, K. and KATO, H. Some analyses on thepossibility of the existence of W-stock minke whale in
sub-area 9 using the information on conception dates.
SC/F2K/J15. HAKAMADA, T. and FUJISE, Y. Preliminary
examination of the heterogeneity of external measurementsof minke whales in the western part of the North Pacific,
using data collected during 1994-1999 JARPN surveys.
SC/F2K/J16. MATSUOKA, K., HAKAMADA, T., FUJISE,
Y. and MIYASHITA, T. Distribution pattern of minke
whales based on sighting data during the JARPN
1994-1999.

SC/F2K/J17. NAKATA, H., TANABE, S., NIIMI, S.,
MINH, T.B., SAKAKIBARA, A., FUJITA, K. and FUJISE,
Y. Population structure in minke whale from the North
Pacific examined by the persistent organic pollutants as
chemical tracers.
SC/F2K/J18. FUJISE, Y., HAKAMADA, T., AOKI, M.,
NIIMI, S., NAKATA, H., HONDA, K. and TANABE, S. An
attempt to identify stocks in the western North Pacific minke
whale (Balaenoptera acutorostrata) using the accumulationlevels of heavy metals and organochlorines as ecologicaltracers.
SC/F2K/J19. KURAMOCHI, T., ARAKI, J. UCHIDA, A.,
MORIYAMA, N., TAKEDA, Y., HAYASHI, N., WAKAO,
H., MACHIDA, M. and NAGASAWA, K. Summary ofparasite and epizoit investigations during JARPN surveys
1994-1999, with reference to stock structure analysis for thewestern North Pacific minke whales.
SC/F2K/J20. MITANI, Y., BANDO, T., TAKAI, N. andSAKAMOTO, W. Diet records and stock structure of minke
whales Balaenoptera acutorostrata around Japan examinedby d13 C and d15 N analyses.
SC/F2K/J21. HATANAKA, H. Comprehensive summary
on W stock hypothesis of minke whale through JARPN
program.
SC/F2K/J22. TAMURA, T. and FUJISE, Y. Geographicaland seasonal changes of prey species in the western North
Pacific minke whale.
SC/F2K/J23. TAMURA, T. and FUJISE, Y. Diurnal change
in feeding activity in the western North Pacific minke
whale.
SC/F2K/J24. TAMURA, T. and FUJISE, Y. Daily andseasonal food consumption by the western North Pacificminke whale.
SC/F2K/J25. TAMURA, T., OHSUMI, S. and FUJISE Y.
Some examinations on body fatness of the western North
Pacific minke whales.
SC/F2K/J26. WATANABE, T. MATSUOKA, K.
TAMURA, T. and FUJISE Y. Oceanographic conditions of
the western subarctic gyre region based on oceanographic
data during the JARPN 1994-1999.
SC/F2K/J27. GOTO, M., ABE, H. and PASTENE, L.A.
Estimation of the mixing proportion of the ‘J’ and ‘O’ stocks
in sub-area 11 using uni- and bi-parental genetic markers.
SC/F2K/J28. GOTO, M., KIM, Z.G., ABE, H. and
PASTENE, L.A. A note on the possibility of identifying
individual J stock animals from a mixed assemblage basedon mitochondrial DNA analysis.
SC/F2K/J29. OHSUMI, S., HATANAKA, H. and FUJISE,
Y. Review on the objectives of Japanese Whale Research
Program under Special Permit in the north-western North
Pacific (JARPN).
SC/F2K/J30. OKAMURA, H. and GOTO, M. The statisticalpower of the hypothesis testing for the elucidation of genetic
population structure in the North Pacific minke whales using
allele frequency data.

J. CETACEAN RES. MANAGE. 3 (SUPPL.), 2001

SC/F2K/J31. TAMURA, T. and FUJISE, Y. Brief review ofthe studies of feeding ecology in the minke whale
Balaenoptera acutorostrata from the western North Pacificprior to JARPN surveys.

393

SC/F2K/J32. GOTO, M., ABE, H. and PASTENE, L.A.
Additional analyses of mtDNA control region sequences in
the western North Pacific minke whales using JARPN
samples.

Annex D
Datasets Produced by JARPN[Table 1 on following pages]

394

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J. CETACEAN RES. MANAGE. 3 (SUPPL.), 2001

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395

396

REPORT OF THE WORKSHOP, ANNEX E

Annex E
List of Scientific Papers based on Data and Material Obtained
during JARPN
1. Abe, H., Goto, M., Palsbøll, P.J. and Pastene, L.A. 1997.
Preliminary microsatellite analyses of western North
Pacific minke whales, Balaenoptera acutorostrata.
Paper SC/49/NP12 presented to the IWC ScientificCommittee, September 1997. 11pp.
2. Abe, H., Goto, M. and Pastene, L.A. 1998. Further
microsatellite analysis in the western North Pacificminke whale, Balaenoptera acutorostrata. Paper
SC/50/RMP8 presented to the IWC ScientificCommittee, April 1998. 10pp.
3. Abe, H., Goto M., Katsumata, Y., Mizutani, M. andPastene L.A. 1999. Preliminary microsatellite DNA
analysis to investigate stock structure in the Antarctic
minke whales (Balaenoptera acutorostrata). Paper
SC/51/CAWS9 presented to the IWC ScientificCommittee, May 1999. 12pp.
4. Aono, S., Tanabe, S., Fujise, Y. and Tatsukawa, R.
1996.
Specific
accumulationofpersistentorganochlorines in minke whale (Balaenoptera
acutorostrata) and their prey species from the Antarctic
and the North Pacific. Paper SC/48/O22 presented to the
IWC Scientific Committee, June 1996. 10pp.
5. Aono, S., Tanabe, S., Fujise, Y., Kato, H. and
Tatsukawa, R. 1996. Persistent organochlorines inminke whale (Balaenoptera acutorostrata) and theirprey species from the Antarctic and the North Pacific.
Environmental Pollution. 98: 81-89.
6. Araki, J., Kuramochi, T., Machida, M., Nagasawa, K.,
and Uchida, A. 1996. A note on the parasite fauna of thewestern North Pacific minke whale (Balaenoptera
acutorostrata). Rep. int. Whal. Commn 47: 565-567.
7. Butterworth, D.S. and Punt, A.E. 1996. Some analyses
pertinent to the conditioning of RMP Implememtation
Simulation Trials for the North Pacific minke whales.
Paper SC/48/NP20 presented to the IWC ScientificCommittee, June 1996. 4pp.
8. Butterworth, D.S., Geromont H.F. and Wada S. 1996.
Further analysis of allele frequency data to provide
estimates of the extent of mixing between the various
North Pacific minke whale stocks, and theirimplications for the status of the ‘O’stock. Rep. int.
Whal. Commn 46: 443-451.
9. Fujise, Y. 1995. Preliminary analysis of heavy metals
and organochlorines in minke whales taken from thecoastal Japan (sub-area 7) and offshore area (sub-area 9)in the western North Pacific. Paper SC/47/NP5
presented to the IWC Scientific Committee, May 1995.
9pp.

10. Fujise, Y. 1995. On the first-year survey of the Japanese
Whale Research Program under Special Permit in the
North Pacific. Geiken Tsushin 385:1-8 [In Japanese].
11. Fujise, Y. and Kato, H. 1995. Preliminary report ofmorphological differences of minke whales between
coastal Japan (sub-area 7) and offshore area (sub-area 9)of western North Pacific. Paper SC/47/NP6 presented to
the IWC Scientific Committee, May 1995. 9pp.
12. Fujise, Y., Kishiro, T., Zenitani, R., Matsuoka, K.,
Kawasaki, M. and Shimamoto, K. 1995. Cruise report of
the Japanese Whale Research Program under a Special
Permit for North Pacific Minke Whales in 1994. Paper
SC/47/NP3 presented to the IWC Scientific Committee,
May 1995. 29pp.
13. Fujise, Y. and Kato, H. 1996. Some morphorogicalaspects of the western North Pacific minke whales;
preliminary analysis of materials from the JARPN
surveys in 1994-5. Paper SC/48/NP11 presented to the
IWC Scientific Committee, June 1996. 10pp.
14. Fujise, Y. 1996. Heavy metal concentrations in minke
whales from the Pacific coast of Japan and an offshore
area in the western North Pacific. Paper SC/48/NP22
presented to the IWC Scientific Committee, June 1996.
29pp.
15. Fujise, Y. 1996. On the second-year survey of theJapanese Whale Research Program under Special
Permit in the North Pacific in 1995. Geiken Tsushin
390:1-14 [In Japanese].
16. Fujise, Y. 1996. Minke whale. pp.44-45. In: T. Hidaka,
K. Izawa, T. Kasuya, T. Kawamichi (eds.) The
Encyclopaedia of Animals in Japan Vol.2 – Mammals
II. Heibonsha. Tokyo, Japan. 155pp. [In Japanese].
17. Fujise, Y., Iwasaki, T., Zenitani, R., Araki, J., Matsuoka,
K., Tamura, T., Aono, S., Yoshida, T., Hidaka, H., Nibe,T. and Tohyama, D. 1996. Cruise report of the Japanese
Whale Research Program under a Special Permit for
North Pacific minke whales in 1995 with the results ofa preliminary analysis of data collected. Paper
SC/48/NP13 presented to the IWC ScientificCommittee, June 1996. 39pp.
18. Fujise, Y. 1997. On the 1996 survey of the Japanese
Whale Research Program under Special Permit in the
North Pacific and on the recent results of the analyses
used from the JARPN samples. Geiken Tsushin
395:1-20 [In Japanese].
19. Fujise, Y., Tanabe, S., Aono, S. and Tatsukawa, R.
1997. Use of organochlorines and heavy metals as
chemical tracers for elucidating the ecology of western

J. CETACEAN RES. MANAGE. 3 (SUPPL.), 2001

North Pacific minke whale. IBI Report. 7: 109-120 [InJapanese].
20. Fujise, Y., Shimada, H., Zenitani, R., Goto, M., Tamura,T., Lindstrøm, U., Uchida, A., Yoshida, H., Shimamoto,K., Yuzu, S., Kasai, H., Kinoshita, T., Iwata, T. andToyama, D. 1997. Cruise report of the Japanese Whale
Research Program under a Special Permit in the North
Pacific (JARPN) in 1996 with some preliminary
analysis of data collected during the 1994-1996 JARPN
surveys. Paper SC/49/NP8 presented to the IWC
Scientific Committee, September 1997. 38pp.
21. Fujise, Y., Zenitani, R. and Kato, H. 1998. An
examination of the W-stock hypothesis for North Pacificminke whales, with special reference to some biologicalparameters using data collected from JARPN surveys
from 1994 to 1997. Paper SC/50/RMP12 presented to
the IWC Scientific Committee, April 1998. 14pp.
22. Goto, M. and Pastene, L.A. 1995. Populationdifferentiation in the western North Pacific minke whale
as revealed by RFLP analysis of mitochondrial D-loop
DNA. Paper SC/47/NP4 presented to the IWC ScientificCommittee, May 1995. 15pp.
23. Goto, M. and Pastene, L.A. 1997. Population structureof western North Pacific minke whale based on an RFLP
analysis of mtDNA control region. Rep. int. Whal.
Commn 47: 531-537.
24. Goto, M. and Pastene, L.A. 1997. RFLP analysis of themitochondrial DNA control region in minke whales
sampled during the 1996 JARPN. Paper SC/49/NP10
presented to the IWC Scientific Committee, September
1997. 10pp.
25. Goto, M. and Pastene, L.A. 1998. Population structurein the North Pacific minke whale as revealed by RFLP
and sequencing analyses of the mtDNA control region.
Paper SC/50/RMP7 presented to the IWC ScientificCommittee, April 1998. 15pp.
26. Goto, M. and Pastene, L.A. 1999. Genetic population
structure in the western North Pacific minke whale
examined by mtDNA control region sequencing
analysis. Paper SC/51/RMP8 presented to the IWC
Scientific Committee, May 1999. 12pp.
27. Government of Japan. 1994. Research program forclarification of minke whale stock structure in thenorthwestern part of the North Pacific. Paper
SC/46/NP1 presented to the IWC Scientific Committee,
May 1994. 13pp. + 22pp Appendix.
28. Government of Japan. 1994. Reconsideration of the1994 Japanese research program for clarification ofminke whale stock-structure in the northwestern part of
the North Pacific. Circular Communication to Membersof the Scientific Committee (Ref. RG/VJH/25352).
6pp.
29. Government of Japan. 1995. The 1995 research plan for
the Japanese Whale Research Program under Special
Permit in the Northwestern part of the North Pacific continuation of the feasibility study. Paper SC/47/NP1
presented to the IWC Scientific Committee, May 1995.
8pp. + 13pp Appendix.
30. Government of Japan. 1995. Further consideration on
the 1995 Japanese research program for clarification ofminke whale stock-structure in the northwestern part of
the North Pacific. Circular Communication to Membersof the Scientific Committee. 2pp.
31. Government of Japan. 1996. The 1996 and 1997
research plan for the Japanese Whale Research Program
to elucidate the stock structure of the minke whale in thenorthwestern part of the North Pacific. Paper

397

SC/48/NP1 presented to the IWC Scientific Committee,
June 1996. 14pp.
32. Government of Japan. 1997. Implementation of the1996 research and minor modifications for the 1997
plan of the Japanese Whale Research Program underSpecial Permit in the North Pacific (JARPN). Circular
Communication to Members of the ScientificCommittee (Ref. RG/JAC/26700). 4pp.
33. Government of Japan. 1997. The 1998 research plan for
the Japanese Whale Research Program under Special
Permit in the Northwestern part of the North Pacific(JARPN). Paper SC/49/NP1 presented to the IWC
Scientific Committee, September 1997. 5pp.
34. Government of Japan. 1998. The 1999 research plan for
the Japanese Whale Research Program under Special
Permit in the Northwestern part of the North Pacific(JARPN). Paper SC/50/O2 presented to the IWC
Scientific Committee, April 1998. 3pp.
35. Hakamada T. 1999. On the Hitter-Fitter Program.
Geiken Tsushin 401:1-8 [In Japanese].
36. Hatanaka, H. 1997. A short review of hypotheses onminke whale stock structure in the Northwestern part of
the North Pacific. Rep. int. Whal. Commn 47:
553-555.
37. Hatanaka, H. and Miyashita, T. 1997. On the feeding
migration of the Okhotsk Sea-West Pacific stock ofminke whales, estimates based on length composition
data. Rep. int. Whal. Commn 47: 557-564.
38. Institute of Cetacean Research. 1995. Research
activities of the Institute of Cetacean Research May
1994 to April 1995. Paper SC/47/O7 presented to the
IWC Scientific Committee, May 1995. 10pp.
39. Institute of Cetacean Research. 1996. Research
activities of the Institute of Cetacean Research May
1995 to April 1996. Paper SC/48/O16 presented to the
IWC Scientific Committee, June 1996. 11pp.
40. Institute of Cetacean Research. 1997. Research
activities of the Institute of Cetacean Research July
1996 to September 1997. Paper SC/49/O11 presented to
the IWC Scientific Committee, September 1997. 14pp.
41. Institute of Cetacean Research. 1998. Research
activities of the Institute of Cetacean Research October
1997 to April 1998. Paper SC/50/O3 presented to the
IWC Scientific Committee, April 1998. 11pp.
42. Institute of Cetacean Research. 1999. Research
activities of the Institute of Cetacean Research (RAICR)May 1998-April 1999. Paper SC/51/O6 presented to the
IWC Scientific Committee, May 1999. 29pp.
43. Ishikawa, H., Yuzu, S., Shimamoto, K., Bando, T.,
Ohshima, K., Kasai, H., Kinoshita, T., Mizushima, Y.,
Iwakami, H., Nibe, T., Hosoyama, T., Kuramochi, T.,
Numano, K. and Miyamoto, M. 1997. Cruise report of
the Japanese Whale Research Program under a Special
Permit in the North Pacific (JARPN) in 1997. Paper
SC/49/NP9 presented to the IWC Scientific Committee,
September 1997. 28pp.
44. Ishikawa, H. 1998. Cruise report of the JARPN survey
in the 1997 season. Geiken Tsushin 399:6-15 [InJapanese].
45. Iwasaki. T. 1996. Constituents of the urine in the North
Pacific minke whales with some notes on urinary
concentrations of sex steroid hormones. Paper
SC/48/NP14 presented to the IWC ScientificCommittee, June 1996. 9pp.

398

REPORT OF THE WORKSHOP, ANNEX E

46. Kuramochi, T., Machida, M., Araki, J., Uchida, A.,
Kishiro, T. and Nagasawa, K. 1996. Minke whales(Balaenoptera acutorostrata) are one of the major final
hosts of Anisakis simplex (Nematoda: Anisakidae) in the
Northwestern North Pacific Ocean. Rep. int. Whal.
Commn 46: 415-419.
47. Le, T. H. L., Takahashi, S., Saeki, K., Nakatani, N.,
Tanabe, S., Miyazaki, N. and Fujise, Y. 1999. High
percentage of butyltin residues in total tin in the livers ofcetaceans from Japanese coastal waters. Environmental
Science & Technology 33 (11): 1781-1786.
48. Lindstrøm, U., Fujise, Y., Haug, T. and Tamura, T.
1998. Feeding habits of western North Pacific minke
whales, Balaenoptera acutorostrata, as observed in
July-September 1996. Rep. int. Whal. Commn
48:463-469.
49. Martines, I. and Pastene, L.A. 1999. RAPD-typing ofCentral and Eastern North Atlantic and Western North
Pacific minke whales, Balaenoptera acutorostrata.
ICES Journal of Marine Science 56:640-651.
50. Miyashita, T. and Fujise, Y. 1996. Abundance estimateof the western North Pacific minke whale using sighting
data of the Japanese Whale Program under a Special
Permit in sub-area 9 and notes on the results of dedicatedsighting surveys. Paper SC/48/NP7 presented to the
IWC Scientific Committee, June 1996. 10pp.
51. Miyashita, T. and Fujise, Y. 1996. Abundance estimateof the western North Pacific minke whale in sub-area 9
with notes on the results of dedicated surveys. Rep. int.
Whal. Commn 47: 543-551.
52. Pastene, L.A. and Goto, M. 1994. Application of
population genetics for the management andconservation of the minke whale. Geiken Tsushin
384:1-8 [In Japanese].
53. Pastene, L.A. and Goto, M. 1996. Application ofmolecular genetics for the management andconservation of large whale species. Suisan Shigen
Kanri Danwakaihou 16:3-16 [In Japanese].
54. Pastene, L.A., Goto, M. and Kishino, H. 1998. An
estimate of mixing proportion of ‘J’ and ‘O’ stocks
minke whale in sub-area 11 based on mitochondrial
DNA haplotype data. Rep. int. Whal. Commn 48:
471-474.
55. Pastene, L.A., Goto, M. and Fujise Y. 1999. Review ofthe studies on stock identity in the minke whale
Balaenoptera acutorostrata from the North Pacific.

Paper SC/51/RMP15 presented to the IWC ScientificCommittee, May 1999. 28pp.
56. Tamura, T. 1998. Studies on feeding ecology of minke
whales Balaenoptera acutorostrata in the Northwestern
North Pacific and Antarctic. Doctoral Thesis of the
Hokkaido University. 125pp [In Japanese].
57. Tamura, T. 1998. Feeding habitat of minke whales in the
Northwestern North Pacific. Geiken Tsushin 400:5-12[In Japanese].
58. Tamura, T., Fujise, Y. and Shimazaki, K. 1998. Diet ofminke whales Balaenoptera acutorostrata in the
Northwestern part of the North Pacific in Summer 1994
and 1995. Fisheries Science 64(1): 71-76.
59. Uchida, A., Kawakami, Y., Yuzu, S., Kishikawa, S.,
Kuramochi, T., Araki, J., Machida, M. and Nagasawa,K. 1998. Prevalence of parasites and histopathology ofparasitisation in minke whales (Balaenoptera
acutorostrata) from the western North Pacific Ocean
and Southern Sea of Okhotsk. Rep. int. Whal. Commn
48: 475-479.
60. Wada, S. 1995. Comparison of allele frequencies
between minke whale samples from Japanese coastal
waters and pelagic waters (sub-area 9). Paper
SC/47/NP7 presented to the IWC Scientific Committee,
May 1995. 4pp.
61. Wada, S. 1996. Results of allozyme analysis on minke
whale samples from JARPN in 1995. Paper
SC/48/NP21 presented to the IWC ScientificCommittee, June 1996. 4pp.
62. Wada, S. 1997. Results of allozyme analysis on minke
whale samples from JARPN in 1996. Paper
SC/49/NP14 presented to the IWC ScientificCommittee, September 1997. 2pp.
63. Zenitani, R. 1999 Distribution of minke whales in
sub-areas 7E and 8 from spring to early summer season.
(Summary of the 1998 JARPN survey.) Geiken Tsushin
404:1-12 [In Japanese].
64. Zenitani, R., Fujise, Y., Matsuoka, K., Tamura, T.,
Bando, T., Ichihashi, H., Shimokawa, T., Krasnenko,
A.S., Taguchi F., Kinoshita, T., Mori, M., Watanabe,M., Ichinomiya, D., Nakamura, M., Sakai, K.,
Matsuzaka, K., Kamei, H. and Tohyama, D. 1999.
Cruise report of the Japanese Whale Research Program
under a Special Permit in the North Pacific in 1998.
Paper SC/51/RMP7 presented to the IWC ScientificCommittee, May 1999. 20pp.

399

J. CETACEAN RES. MANAGE. 3 (SUPPL.), 2001

Annex FThe JARPN 2000 Workshop Crash-Course in Cetacean Genetics
Per J. Palsbøll
School of Biological Sciences, University of Wales, Gwynedd LL57 2UW, UK

LOCATION OF GENETIC MATERIAL AND
MODES OF INHERITANCE
Most eukaryote cells have their genetic material (the DNA,
deoxyribonucleic acid) located in at least two cellularcompartments: the cell nucleus and the mitochondrion. Plant
cells have an additional cellular compartment, thechloroplast, which also has its own genome. This paper
focuses exclusively on mammals.

haplotypes. Identical haplotypes may be identical by descent(autozygote) or by state, but not descent (allozygote). The
term allele and copy are often used interchangeably and theactual meaning has to be deduced from the context. In thispaper, however, allele has the same meaning as haplotype,i.e. each unique variant at a locus. The genotype refers to the
combination of the two copies at a locus. The homozygosity
is the probability of sampling two copies of the same

Inheritance of nuclear DNA
The cell nucleus is diploid, i.e. it contains two fullcomplements of chromosomes, one inherited from eachparent. Each such haploid set of chromosomes consists of asex chromosome (the Y- or the X-chromosome) as well as afull set of autosomal chromosomes. This kind of inheritanceis termed bi-parental or Mendelian transmission.
During the formation (meiosis) of the germ cells (thesperm in males and oocyte in females) each identical pair ofchromosomes will align and exchange segments of DNA, aprocess termed recombination. After recombination, thetwo ‘new’ haploid sets of chromosomes are separated andallocated to each germ cell, which then contains a haploid setof chromosomes. In this manner the genetic material isreshuffled between sister chromosomes every generation.
The more distant the two different DNA sequences (loci) arelocated on a chromosome the higher the likelihood they will
segregate to different sister chromosomes (the twohomologous chromosomes in a diploid organism) duringrecombination. Such loci are thus not linked and segregate
independently. Loci in close proximity to each other, on theother hand, may be linked to some variable degree and may
thus segregate as a single unit, rather than independent
units.
The importance of linkage is often ignored in population
genetic analyses. Population genetic analysis is in essence
based upon estimation of genetic relatedness, from which
inferences are drawn. The data collected from each locus
constitutes an independent estimate of, for example, thedegree of divergence among sub-populations. However, if
two loci are linked they do not represent two independent
estimates of divergence, which, if linkage is ignored and few
loci analysed, may bias the outcome.

haplotype, i.e. HO =Basic terms
A specific segment of DNA (e.g. a large section or just asingle nucleotide position) is termed a locus. Due tocombined action of mutation and recombination, the actual
DNA sequence at the same locus will accumulate differencesamong sister chromosomes over time. Each such uniquevariant at a specific locus is termed a haplotype or an allele.
For loci located on autosomal chromosomes in a diploid
nucleus, there are two copies of each locus, which may haveidentical (homozyogote) or different (heterozygote)jÂ p , where p is the population
2
i

i

i =1

frequency of the ith haplotype. The heterozygosity is theprobability of sampling two copies of different haplotypes,
i.e. 1-HO. In many instances the observed and the expected
hetero/homozygosity is estimated, the former simply being
the proportion of homo/heterozygote individuals in thesample, and the latter the expected number estimated fromthe observed haplotype frequencies (assuming panmixis, see
below).
Inheritance of mitochondrial DNA
The mitochondrion is the organelle responsible for cellularrespiration. The mitochondrion resembles a prokaryote inmany ways and probably represents an ancient symbiosis
between an eukaryote and prokaryote cell. Over time, mostof the genes in the mitochondrial genome have beentransferred and incorporated into the nuclear genome, andtoday the mitochondrion in eukaryote cells is not an
independent unit. In cetaceans the mitochondrion contains asingle circular chromosome, approximately 16,500
nucleotides long (Arnason and Gullberg, 1993). Although
there is only one ‘chromosome’ this may exist in several
thousand copies in each mitochondrion. In most instances all
the mitochondrial DNA molecules in a single organism
appear to have identical nucleotide sequences, although anincreasing number of cases are being reported where morethan one mitochondrial haplotype has been detected(heteroplasmy, e.g. Baker et al., 1990). Contrary to nuclear
chromosomes (usually denoted nuclear DNA 2 ncDNA) the
mitochondrial DNA (mtDNA) is inherited in an
uni-parental fashion, more precisely from the mother, i.e.
maternally transmitted (e.g. Gyllensten et al., 1985). The
sperm cell does not appear to contribute any mitocondria at
the fusion with the oocyte during fertilisation. Paternal
leakage of mtDNA has been detected (e.g. mice, Gyllensten
et al., 1985) and some non-mammalian species, such asmussels, have been shown to have bi-parental inheritance of
mtDNA (Zouros et al., 1992). The general rule for mammals,
howevef, is a strict maternal inheritance of mtDNA. Since all
chromosomes contained in a mitochondrion have an
identical nucleotide sequence, recombination would nothave any effect even if it occurred (recent reports suggeststhat mtDNA may recombine). Thus, mtDNA is inherited not

400

REPORT OF THE WORKSHOP, ANNEX F

only in a maternal but also a clonal fashion, and all loci in the
mtDNA linked. This implies that mutations are notexchanged between different evolutionary lineages contrary
to ncDNA.
STRUCTURE AND CHANGES IN DNA
SEQUENCES
Basic structure of DNA
A chromosome consists of two opposite directed andcomplementary strands. Each strand is composed of four
different deoxyribonucleic acids: the pyrimidines, thymine(T) and cytosine (C), as well as the purines, adenine (A) andguanine (G). The complementary nature of the two-strand
configuration has the advantage that each strand acts as atemplate for the other. During DNA synthesis (i.e. atreplication or repair), the DNA polymerase simply uses thecomplementary strand as the template and adds a G if thecomplementary strand has an A in that position and viceversa, or a T if the complementary strand has a C (and viceversa).
Changes in the DNA sequences
The sequence of nucleotides changes over time due tomutations. Mutations are introduced by extrinsic factors
such as radiation and oxidation, as well as intrinsic factors,
such as errors during replication. Mutations can be divided
into two kinds, substitutions and insertions/deletions (alsonicknamed indels) which either might involve single
nucleotides only or larger sections of DNA. Substitutions areusually limited to a single or few nucleotides and generally
occur at relatively low rates (in the order of 1029). Indels, on
the others hand often involve larger segments of DNA and insome instances at high rates (e.g. 1025-1024 at microsatellite
loci, Edwards et al., 1992).

The mode of mutation depends to a large extent upon the
nucleotide sequence itself, i.e. whether it is a repetitive
sequence or not. A commonly analysed class of loci issimple tandem repeats (STRs) also called microsatellite
loci (Tautz, 1989; Edwards et al., 1991). A microsatellite
locus consists of a short DNA sequence of less than six
nucleotides in tandem repeat (see Fig. 1).
Microsatellite loci predominantly mutate by insertion ordeletion of repeats presumably caused by single-strand
slippage facilitated by the repetitive nature of the nucleotide
sequence (Levinson and Gutman, 1987; Schlötterer andTautz, 1992). During DNA replication the twocomplementary strands may slip and subsequently mis-align(due to the repetitive nature of the sequence), which implies
that one or more repeats are added or lost depending on the
direction of the slippage (see Fig. 2).
In contrast, nucleotide substitutions usually involve only asingle nucleotide as illustrated in Fig. 3. Such mutations areoften referred to as SNPs (Single Nucleotide
Polymorphism’s, pronounced ‘snips’). These kinds ofmutations are typically observed in non-repetitive DNA
sequences (see Fig. 3).
Apart from the actual mode of mutation, theregion/nucleotide position also in part determines the rate of
mutation. Put simply, parts of the genome are likely to be
subjected to various degrees of selection pressure (i.e.
affecting the fitness of the individual), whereas other regions
are not. Our current knowledge of which nucleotide
sequences are under selection pressure and which are not isvery limited. In addition, it is likely that selection pressures
vary with context (e.g. abiotic factors, stage of development,amino acid composition etc.) making predictions difficult.
Nc- and mtDNA nucleotide sequences at which mutations
supposedly do not affect the phenotype are thus assumed to
be selectively neutral (or neutral) (Kimura, 1985). The rate¶WDFFWJDFJWJJ$*$*$*$*$*$*$*$*$*$*$*WDFFJJFDJF¶ $* ¶FJWWFDJWDFDD*$*$*$*$*$*$*$*$*$*$*$FJWWDDWJDW¶ *$ 
Fig. 1. Tandem repeated array or microsatellite.

¶WDFFWJDFJWJJ$*$*$*$*$*$*$*$*$*$*$*WDFFJJFDJF¶¶FJWWFDJWDFDD*$*$*$*$*$*$¶>'1$3RO\PHUDVH!@__$*>6LQJOHVWUDQGHGORRSGXHWRVOLSSDJH@
Fig. 2a. Slippage creates a loop.

¶WDFFWJDFJWJJ$*$*$*$*$*$*$*$*$*$*$*WDFFJJFDJF¶*$ ¶FJWWFDJWDFDD*$*$*$*$*$*$*$*$*$*$*$FJWWDDWJDW¶ *$ __$*
Fig. 2b. DNA polymerase continues strand synthesis in effect adding an extra GA-repeat.

¶WDFFWJDFJWJJ$*$*$*$*$*$*$*$*$*$*$*$*WDFFJJFDJF¶ *$ ¶FJWWFDJWDFDD*$*$*$*$*$*$*$*$*$*$*$*$FJWWDDWJDW¶ *$ 
Fig. 2c. In subsequent replications one daughter strand will give rise to a sequence with an additional GA-repeat.
Fig. 2. Single-strand slippage at microsatellite locus during replication.

J. CETACEAN RES. MANAGE. 3 (SUPPL.), 2001

401

2ULJLQDOQXFOHRWLGHVHTXHQFH

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0XWDWLRQLQRQHVWUDQGHJJHQHUDWHGGXULQJUHSOLFDWLRQ¶WDFJDFJDWWJFDJDDJFWFWJFDFDWDDJDJWWFJF¶¶FJWDJWDJFFDWJDJ$DWFWFDWJWJFJJDJDFFWDW¶
$OOVXEVHTXHQWGDXJKWHUVWUDQGVZLOOFRQWDLQWKHµQHZ¶EDVH¶WDFJDFJDWWJFDJD*JFWFWJFDFDWDDJDJWWFJF¶¶FJWDJWDJFFDWJDJ$DWFWFDWJWJFJJDJDFFWDW¶
Fig. 3. Single nucleotide substitutions.

of mutation at such nucleotide sequences is presumably
equal to the ‘base line’ mutation rate. DNA sequences underselection may, for instance, be sequences that encode forenzymes. A mutation in the DNA sequence at such a locus
may result in a change of the amino acid encoded at that
position (a non-synonymous mutation) which in turn may
change the function/efficiency of the enzyme (or render it
non-functional). Nucleotide sequences that are subject toselection introduce additional variables that subsequently
have to be considered in the data analysis, i.e. only certain
mutations are viable and thus selection might introduce anincreased possibility of multiple identical mutations at thesame nucleotide position (convergence or homoplasy). Not
every amino acid substitution alters the functionality of the
enzyme and not all nucleotide substitutions in an encoding
DNA sequence yield an amino acid change(synonymous/silent mutations) and therefore might beselectively neutral.

between four to six nucleotides in length). A mutation (be ita substitution or an indel) in the recognition sequence of aparticular RE will alter the nucleotide sequence and the RE
will subsequently fail to recognise the site and not cut thestrand. The result is detected as a single long DNA fragment
rather than two (see Fig. 4). The advantage of RFLP analyses
is its simplicity, speed and the fact (in relation to isozyme
analyses) that any portion of the genome in principle can beanalysed. Its main disadvantage is that the nature of themutation is unknown, i.e. if it is a substitution, an indel oreven multiple mutations.

Detecting genetic variation
Isozyme electrophoresis
There are many different biochemical techniques by which
genetic variation can be detected. From the mid-1960s to thelate-1970s, isozyme or allozyme electrophoresis was the
predominant method. Isozyme electrophoresis detects
differences in overall electrical charge of enzymes and is afast and low-cost technique.
The genetic variation uncovered by isozyme
electrophoresis are those mutations that generate a change in
the amino acid sequence, i.e. limited to DNA positions that
encode for enzymes and likely to be subject to selection.
Despite this latter aspect, isozyme analyses have yieldedmuch insight into the evolution and population structure of ahost of organisms. The real possibility of selection is often
dealt with by discarding loci that deviate from expectations,which harbours a risk of introducing biased results (i.e.
primarily due to circular data partition). Although still usedin many studies and organisms, the vast majority of genetic
analyses aimed at cetaceans today employ DNA-based
techniques (see below).
RFLP analysis
In the late 1970s technical advances meant that mutations
could be detected directly at the level of the DNA itself and
not indirectly through isozyme electrophoresis. The initial
population studies involved RFLP analyses (Restriction
Fragment Length Polymorphisms, pronounced ‘reflips’
according to Dr. Andy Dizon). The method employs
restriction endonucleases (REs), enzymes that in vitro ‘cut’
the DNA strand at a specific nucleotide sequence (typicallyFig. 4. Autoradiogram of mitochondrial RFLPs.

Nucleotide sequencing
The most precise characterisation of any locus is obtained bydetermining the actual sequence of nucleotides. Initially,
nucleotide sequencing of a specific DNA segment wastechnically challenging, time consuming and expensive.

402

REPORT OF THE WORKSHOP, ANNEX F

However, thanks to the development of the PCR technique(Polymerase Chain Reaction 2 in vitro amplification of a
specific segment of DNA thereby generating billions ofidentical copies, a pre-requisite for nucleotide sequencing;Mullis and Falooma, 1987), fluorescent labelling andautomated detection of DNA fragments, nucleotide
sequencing is today a trivial, off-the-shelf exercise. For adetailed record of the data, see Fig. 5 [this figure is not
reproduced here – colour copies are available from the
Office of this Journal, the legend reads: Fig. 5. Output(chromatogram) of nucleotide sequence obtained by from an‘automated’ ABI Prism 377Ö DNA sequencer]. The maindrawback of nucleotide sequencing directly by PCR is whenit comes to diploid loci (i.e. ncDNA in mammals). The
difficulty arises because both copies of the locus areamplified and sequenced at the same time. Any SNP along
the nucleotide sequence is evident as two peaks/bands at thesame position indicating the presence of two different
nucleotides. Hence, while it is possible to detect all SNPs
and the kind of nucleotides at polymorphic site it is notpossible to assign nucleotides to haplotype (i.e. which of thetwo copies each nucleotide ‘belong’ to). This aspectcurrently constitutes the single main obstacle of using
ncDNA SNPs for population genetic analyses. The situation
can be partially or fully resolved by various methods, such as
cloning of single haplotypes with subsequent isolation andsequencing of individual clones. However, thesemanipulations are time consuming and other errors are
introduced during the process greatly increasing theexperimental effort.
Due to the haploid nature of mtDNA, each individual only
contains a single haplotype and thus any mtDNA locus iseasily sequenced directly.
Micro- and minisatellite analyses
As explained above, repetitive nucleotide sequences, such as
microsatellite and minisatellite (longer repeats, Jeffreys etal., 1985) loci, generally evolve by changes in the number of
repeats, i.e. in the length of the repetitive region.
Microsatellite alleles can thus be distinguished bydifferences in length of the repetitive region. The DNA
sequence amplified is the repeat array plus part of eachflanking sequence, to which the PCR olgi-nucleotide primers
anneal. The amplified fragments will therefore differ inlength if they differ in the number of repeats (see Fig. 6).
Contrary to ncDNA SNPs, the haplotype (i.e. the length) of
each copy at a diploid locus is readily discernable, whichmake microsatellite loci ideal markers for diploid genomes(although their mode and rate of mutation add otheruncertainties, see below).
RAPDs, AFLPs and multi-locus fingerprinting
Each of these methods detects variation at multiple loci in asingle experiment. The data looks much like a bar code withmultiple bands each representing a haplotype of an unknown
locus. The advantage of these methods is that multiple
variable loci are detected in a single analysis. There are sometechnical issues with some of the methods, such as RAPDs(randomly amplified polymorphic DNA), which arehighly sensitive to the experimental conditions andreproducibility is thus a major issue. Common for RAPDs
and multi-locus fingerprinting is that the bands are resolved
by electrophoresis through an agarose rather than ahigh-density polyacrylamide matrix. This implies that it isdifficult to ascertain the size of each fragment (band) withconfidence, which subsequently makes it difficult tocompare data across different experiments and laboratories(this is not the case with microsatellite or sequence data). In
terms of data analysis, the multi-locus approach has the
disadvantage that alleles cannot be assigned to specific loci,which implies that some standard population genetic
parameters (i.e. panmixis, linkage etc.) are difficult or
impossible to estimate. In brief, data are scored as
pre/absence of bands, i.e. equivalent to a dominant genetic
marker (however, some fragments might represent the same
locus).
The amount of genetic variation within populations
The amount of genetic variation within a population
basically depends upon the mutation rate and the effective
population size (the number of individuals that are
breeding). The amount of genetic variation is captured in thecomposite parameter q. For a diploid Mendelian inherited
genome:q = 4Ne m

where Ne denotes the effective population size and m themutation rate. Intuitively, it makes sense that these twoparameters determine the level of variation in a population.
The more copies of a locus a population contains (theeffective population size, Ne), the more haplotypes possible,
which in turn is positively correlated with the rate by which
new haplotypes are generated (the mutation rate, m).
The degree of variation in a sample (and thus q) can be
estimated from a number of variables, such as the number of
haplotypes, the heterozygosity (defined above), the numberof polymorphic positions, the nucleotide diversity (defined
below) as well as the variance in number of repeats (formicrosatellite loci). The expected value and variance of q
when estimated from the above variables has been derived
for several different evolutionary models. Some of thestandard demographic assumptions in such models are:panmixis, discrete generations, negligible migration andconstant population size (Ne). The mode of mutation
constitutes a central aspect in such models. The three mostcommonly employed mutation models are: the infinite allele
model (every mutation generates a new haplotype), theinfinite site model (every mutation happens at a new
nucleotide position) and the stepwise mutation model(basically the manner in which microsatellite loci are
believed to evolve, i.e. mutations move alleles back and forth
between different allelic states, Fig. 7).
An estimate of q can be obtained from the heterozygosity,
assuming an infinite allele model, by numerically solving theequation below:qˆ 3 +(7 - t )qˆ 2 +(8 - 5t )qˆ - 6t = 0iwhere t = H/(1 2 H), and H = 1 −∑ x , where x is the2iifrequency of the ith haplotype (Chakraborty and Wiess,1991).
q may also be estimated from the variance in repeat
number at microsatellite loci assuming a stepwise mutation
model (Di Rienzo et al., 1994):qˆ =2(n - 1)-2

Â( j - j )iiwhere n is the number of chromosomes sampled, ji thenumber of repeats detected at the ith copy and the mean
number of repeats for all sampled chromosomes.

403

J. CETACEAN RES. MANAGE. 3 (SUPPL.), 2001
*$&$&$*$*$7*7$*$$**$*JFDDJJFDJFDDDJFDJJDDDJJDJDJJDFFDDJDJJWJDJWJDJWJDW!
)RUZDUGSULPHU
JFDJDJJJDWJDWDJWJDJDWDJDWDFDFDJDWDFDFDJDWJDWDJDWDFDWDJDWDJDWJDWDDDWJJDWJDWDDDWJJJWDDWDJDW*$7$*$7$*$7$*$7$*$7$*$7$*$7$*$7$*$7$JDFDJDFDJDFDJDF
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
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Fig. 6a. The nucleotide sequence at microsatellite locus GATA053 in humpback whale (Megaptera novaeangliae) and the position of theoligo-nucleotide primers employed in the PCR amplification of the locus.

Fig. 6b. Autoradiogram of the genotypes obtained at the tetra-nucleotide microsatellite locus GATA053 in humpback whale.
Fig. 6. Microsatellite data.

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Fig. 7. The step-wise mode of mutation at microsatellite loci by loss and gain of repeats.

404

REPORT OF THE WORKSHOP, ANNEX F

Estimates of q can be utilised for many purposes, e.g.
estimates of q from different populations but at the same loci(i.e. the same mutation rate across all populations) provide
relative estimates of Ne. Comparing estimates of q at
different loci from the same set of individuals in a single
population yields an estimate of the relative difference inmutation rates (m) between loci. It should be noted, however,that the variance of estimates of q is often considerable.
Perhaps a more interesting use of q lies in detecting
deviations from the model expectations. In principle,
estimates of q from different variables should yield similar
results, e.g. number of haplotypes, heterozygosity etc. Since
the variables might be sensitive to different aspects of theunderlying model, any large discrepancies in estimates of q
obtained from different variables is indicative of violationsof the underlying model. This approach has been used todetect fluctuations in population size from microsatellite
genotype data.
The distribution of variation among individuals
A single population (or sometimes sub-population) is
generally defined as a panmictic (i.e. random mating)population in a genetic sense. Random mating in this context
does not imply that individuals choose mating partners
indiscriminately, but simply that the loci that are analysed
are not traits that are involved in the selection of mate (which
is likely to be true for most loci). The equilibrium genotype
frequencies for Mendelian inherited loci under panmixis are
known as the Hardy-Weinberg (and Castle, in someinstances, Hardy, 1908) equilibrium. Under panmixis thefrequency of each genotype is simply the probability ofsampling those two copies, i.e. the haplotype frequencies inthe sample. For instance, in the case of a locus with two
different haplotypes, the probability of sampling a genotype
with two identical and two different haplotypes is and 2pAqB,
respectively, where pA is the sample frequency of haplotype
A and qB of haplotype B.
Comparing observed genotype with the expected
Hardy-Weinberg frequencies is a common way to test for
deviations from panmixis, i.e. possible population structure
within a sample. Traditionally this is done by a G- or c2-test,
which is somewhat less powerful than randomisation tests. A
relatively powerful statistic for multiple loci is the average
heterozygosity per individual. The observed value isobtained from the data and the expected distribution byrandomising the data within each locus among individuals.
Probability of identity
Genetic data are also used to identify individuals. The
probability of identity (I) (Paetkau and Strobeck, 1994), i.e.
the probability that two unrelated individuals from the same
panmictic population have identical genotypes, is theprobability of collecting the same genotype twice,ji.e.

Â p +Â p q . For multiple loci the overall probability
4
i

i -1

i j

iπ j

of identity is obtained as the product of I for each locus. The
probability of identity varies with the degree of genetic
variation in the population as well as the degree ofrelatedness, i.e. the more closely related the higher the
probability of having identical genotypes. One fact to keep inmind in this regard is that the number of pairs of related
individuals is inversely correlated to the degree ofrelatedness for most relevant population models, e.g. eventhough half-siblings have a higher probability than unrelated
individuals of having identical multi-locus genotypes any
random population sample will contain much fewer pairs ofhalf-siblings than pairs of unrelated individuals. Thus, theabsolute contribution of ‘false’ matches will be similar or
lower than that from unrelated individuals despite the higher
probability of identity.
Genetic drift
An important evolutionary process is random genetic driftor just genetic drift. Genetic drift simply denotes the
sampling error in haplotype frequencies across generations.
In essence, the offspring generation is a random sample of
haplotype copies collected from the parent generation. As
with any other finite sample this process is subject tostochastic variance, which in turn yields variation in the
population haplotype frequencies. In the absence of theintroduction of ‘new’ copies/haplotypes either by mutationor gene flow from other sub-populations and assuming
constant population size, any neutral locus would eventually
become monomorphic, i.e. all individuals possess the same
haplotype. The rate by which the population becomesmonomorphic (in the absence of mutation and gene flow) or
the rate of fixation is inversely correlated with the size of theeffective population. The effect of genetic drift upon genetic
diversity implies that a severe reduction in effective
population size holds the potential of reducing the degree ofgenetic variation. However, there are two points to keep inmind in this regard; the effective population size (in apopulation genetic sense) is a harmonic mean, which implies
Ne has to be reduced for many generations in order to havean effect upon the level of genetic diversity. Each individual
contains two copies of each locus, which implies that asample, for instance, of 50 individuals will contain 100
copies at any given autosomal locus and thus contain most of
the variation contained in the population. These two facts
imply that in theory a bottleneck will have to be severe andprolonged in order to result in any measurable reduction in
genetic diversity.
In the presence of mutation/migration, a point ofequilibrium is reached when the rate of loss of haplotypes(by genetic drift) equals the introduction of new haplotypes(by mutation/migration). Because genetic drift is a random
process, two isolated populations, initially part of the same
population, will diverge increasingly over time with regard
to haplotype frequencies or reach a state of equilibrium
depending upon the rate of gene flow and mutation.
If loci are under selection, the sampling across generations
is not random and the effects of genetic drift are either
accelerated or decelerated.

GENETIC DIVERGENCE AMONG POPULATIONSPopulation genetic structure evolves under assortive
mating, i.e. when mating is non-random. Many different
variables can cause population genetic structure, e.g., spatialor temporal segregation. Assortive mating implies
individuals are more closely related within sub-populations
than between sub-populations, or, in other words, theancestors of an individual are likely to originate from thesame sub-population. The likelihood that descendants andancestors are part of the same sub-population decreases withthe amount of dispersal (gene flow) among sub-populations.
Thus, if gene flow is high relative to the rate of genetic drift
and mutation then population genetic structure is unlikely.
How high a level of gene flow will prevent population
genetic structure depends upon the mutation rate andeffective population size. It is commonly assumed that morethan ten migrants per generation are sufficient to prevent

405

J. CETACEAN RES. MANAGE. 3 (SUPPL.), 2001

significant levels of divergence in haplotype frequencies
among sub-populations.
The statistics developed to measure the degree of
population structure are, in principle, based upon the effectof assortive mating, i.e. if population genetic structure exists,
individuals within sub-populations will be more closely
related to each other than to individuals from othersub-populations. The majority of measures of population
genetic divergence estimate the reduction in genetic
variation due to population structure. In essence,q
divergence = 1 - SUB , where q- SUB is the average genetic
q TOT
variation within a sub-population and qTOT is the genetic
variation in the total sample. It follows that the degree of
population structure can thus be estimated from the same
variables that q (see above) is estimated from, e.g. theexpected heterozygosity, number of alleles, nucleotide
diversity, number of polymorphic positions as well as
variance in repeat number.
Haplotype data are basically of two kinds: haplotype onlyor haplotype as well as the relative degree of relatedness
among haplotypes (i.e. a measure of the number of mutations
between haplotypes). The statistics used for these kinds ofdata are often referred to as haplotype and sequence
statistics, respectively. Personally, I prefer the terms
frequency (only) and distance (as well) statistics.
Haplotype/frequency data
The relative degree of relatedness within and among
sub-populations is estimated by the decrease inheterozygosity ( = increased homozygosity) or variance due
to population structure. This approach was originallyformulated by Sewall Wright (1969) who proposed a numberof inbreeding coefficients, called F statistics. If two samples
of individuals are collected from two different populations,the difference in haplotype frequencies due to genetic drift
implies that the heterozygosity will be lower within each
population than in the overall sample. The more divergent
haplotype frequencies, the greater the decrease inheterozygosity. An example of such a statistic is Wright’s
FST, which is defined as:
H - HS
FST = T
HT

where HS is the average HS among all sub-populations;jHS = 1 -

Â

pi2,s

i =1

i.e. the expected heterozygosity in sub-populations; andj

HT = 1 -

Âp

2
i

i =1

i.e. the expected heterozygosity of the entire sample. The
term pi denotes the frequency of the ith haplotype of j
haplotypes in total.
There are other statistics, which are similar in principle,
such as Hudson’s HST (Hudson et al., 1992). The maindifference between FST and HST is that the latter weigh thecontribution of HS from each sub-population by the sample
size (reflecting the uncertainty in the estimation) in the samemanner as KST (see below). FST and HST take values between

0 and 1.0. Weir’s q is a FST statistic as well, but estimates thepartition of variance (Weir and Cockerham, 1984). There areother measures of genetic divergence, such as Nei’s D (Nei,
1987), which can take any value from 0 to infinity. Nei’s D
is defined as:
D = –1n(I)J XY, where JXX and JYY denote the estimate
J XX JYY
of homozygosity (defined above) in population X and Y,
respectively. The term JXY denotes the probability ofchoosing one copy from population X and one copy from
population Y of identical haplotype.

where I =Sequence/distance statistics
Genetic analyses may often not only determine what
haplotype a given sampled copy is, but also the relative
degree of genetic divergence among different haplotypes. In
the case of nucleotide sequence data, the degree ofdivergence (at the intra-specific level, i.e. among closely
related haplotypes) is commonly expressed as the number ofnucleotide substitutions per nucleotide position. This extra
level of information provides extra power when there aremany different haplotypes, i.e. when haplotype frequencies
are low. There are several statistics which estimate thedegree of divergence among copies within and between
populations. An example is KST suggested by Hudson et al.
(1992). KST estimates the reduction in nucleotide diversity
due to population structure. The definition of KST by Hudson
et al. (1992) is:
KST = 1 – (KS / KT), when
KS = wK1 + (1 – w)K2, where w = n1/(n1 + n2)
and
ni -1

ni

ÂÂd
Ki =

ij ,ikj =1 k = j +1

Ê ni ˆ
Ë 2¯, i = 1, 2

and
2

ni -1

ni

ÂÂ Â
KT =

i =1 j =1 k = j +1

n1

dij,ik +n2

ÂÂd

1 j ,2 k

j =1 k =1

Ê n1 + n2 ˆ
Ë 2 ¯

The term ni denotes the number of sequence copies collectedfrom locality i, and dij,lk the number of single nucleotide
substitutions between the jth sequence from locality i and thekth sequence from locality l.
Microsatellite statistics
As explained above, microsatellite loci evolve in a stepwisemanner, i.e. a mutation results in the addition or deletion ofotherwise identical repeats. Thus, the mode of mutation does
not fit an infinite allele model, in that a new mutation event
has a high probability of generating a haplotype alreadypresent in the population (Fig. 7). This implies that for locicomposed of repetitive sequences there is likely to be aconsiderable degree of homoplasy, especially whenmutation rates are high, as is the case for many microsatellite
loci. To accommodate these aspects microsatellite-specific

406

REPORT OF THE WORKSHOP, ANNEX F

estimators of genetic divergence among populations havebeen developed. The variable used to estimate the degree ofdivergence is either: the variance in repeat number (Slatkin,1995), or the mean number of repeats per copy (Goldstein etal., 1995). Taking the mutation mode (basically a linear
random walk) into account introduces additional andconsiderable amounts of variance in the estimation ofdivergence and thus a large number of loci will need to beanalysed in order to obtain a reasonable precise estimate ofthe degree of genetic divergence. This is true for any class ofloci, but even more so for loci that evolve rapidly in a
stepwise manner. If the taxa under study are likely to havediverged recently the level of homoplasy might be at a level
when a stepwise mutation model can be ignored and infinite
allele model-based statistics used instead (which has a lower
variance). It has been found, however, that the desirable
linear relationship between the degree of genetic divergenceand time since divergence becomes eroded quite quickly at
microsatellite loci. For instance, Paetkau et al. (1998) foundthat the linearity between divergence time and genetic
divergence ceased at less than 20,000 years.
Assessing the significance of an estimate of divergence
Even if samples were collected from the same panmictic
population, the sampling variance is likely to yield an
estimate of divergence between the samples that is larger
than zero. Hence, before estimating the level of genetic
divergence, a homogeneity test is usually performed. Any
appropriate estimator of genetic divergence can be used as atest statistic in addition to more conventional statistics, suchas c2 or G. The most powerful manner by which to obtain theprobability of the observed value under the null-hypothesis(that samples were collected from the same population)
appears to be Monte Carlo permutations from which thenull-distribution of the test statistic is estimated (e.g. Roffand Bentzen, 1992).
Likelihood methods
The above presented estimators are all relatively simple,
moment estimators. Genetic divergence can also be
estimated in a traditional or Baysian likelihood framework,
although these approaches are often computationallyintensive, which is likely to become less of a problem ascomputers become more powerful (Nielsen et al., 1998).
Model assumptions
It is important to keep in mind that the above estimators are
based upon a number of assumptions, e.g. the mode ofmutation. The change in haplotype frequencies due togenetic drift is negatively correlated with the effective
population size, and thus the rate of genetic divergence
depends upon population size. This in turn implies that if
populations differ radically in terms of effective population
sizes, the degree of genetic divergence cannot necessarily becompared directly from one inter-population comparison toanother. There are distance estimators that are less sensitive
to differences in population sizes, e.g. Cavelli-Sforza’s
Chord distance (Cavalli-Sforza and Edwards, 1967), butthese are rarely used. Fluctuations in the effective population
size, e.g. population bottlenecks or expansions, will thus alsochange the rate of divergence.
The validity of the standard assumptions can often be
tested, although if significant deviations are detected there
might be no obvious solutions in terms of how to scale thedegree of divergence. Often such tests are based uponestimation of q from different aspects of the data, such asheterozygosity and number of haplotypes, or variance inrepeat number (microsatellite loci). An estimate of the same
parameter (in this case q) but from different aspects of thedata should generate similar observed values. If not, thismight indicate a violation of the model assumptions. Thisapproach (the ratio of estimates q from different aspects ofthe data) has proven useful for detecting exponential
decrease or increase in the effective population size, e.g. at
microsatellite loci estimating q from the heterozygosity andvariance in repeat number (e.g. Kimmel et al., 1998).
Other, more advanced likelihood methods have beendeveloped to obtain an estimate of q for the most likely rateof population growth/decrease (Kuhner et al., 1998).
INDIVIDUAL-BASED APPROACHES
Detection of individuals and/or parent-offspring pairs
The ease and speed by which microsatellite loci are analysed
implies that it is relatively straightforward to obtaingenotypes from multiple loci from the sampled individuals.
If a sufficient number of loci have been analysed individuals
can reliably be identified, and with additional loci,parent-offspring relations as well. The distribution ofindividuals or parent-offspring relations in time and spacecan be utilised to obtain estimates of current rates ofdispersal and (i.e. population structure) as opposed to theevolutionary measures mentioned above. The temporal scaleof such dispersal estimates may be more relevant tomanagement issues. However, in order for a sample tocontain a useful number of parent-offspring relations or
re-sampled individuals, the sampled proportion of each
population must be relatively large. While this approachholds a lot of promise it is still in its initial stages.
Assignment tests
FST statistics do not effectively combine the additional
information that is contained in multiple genotypes, e.g. if
the genotype has been determined at several microsatellite
loci for each individual. With basis in the expected
Hardy-Weinberg genotype frequencies the likelihood ofeach single-locus and thus also the combined multi-locus
genotype observed in each individual is readily estimated(Paetkau et al., 1995). This aspect has long been used toestimate the population origin of individual samples inmixed-stock fisheries. However, the same approach can inprinciple be utilised to detect population differentiation. The
typical procedure is to estimate the likelihood of eachindividual multi-locus genotype in each sub-population(after removing the individual from the sample) and assign
the individual to the sub-population its multi-locus genotype
is most likely to originate from. The higher proportion ofindividuals assigned to the sub-population they were
sampled from, the higher the degree of differentiation. In
some procedures individuals will only be assigned to a
sub-population if the likelihood of the multi-locus genotype
is significantly higher for one sub-population than theremaining sub-populations. No formalised statistics have yet
been developed using this approach to estimate the degree ofgenetic differentiation. There are several problems, e.g. how
to deal with uneven sample sizes and what is a ‘significant’proportion of assignment.
POSTSCRIPT
Inferring population/stock structure and dispersal rates from
population genetic data is basically an estimation process.
Although a wealth of genetic markers and techniques haveJ. CETACEAN RES. MANAGE. 3 (SUPPL.), 2001

become available, the resolution and reliability of any suchstudy hinges critically upon sample sizes (both in terms ofsamples and genetic markers), as is true for any estimation.
Hence, drawing affirmative conclusions from small sample
sizes, few loci, or based upon a poorly understood
population/evolutionary/mutation model harbours a real riskof misinterpretation. Population genetic analyses contain an
additional level of variance due to the sampling of genes
across time (i.e. generations) apart from the sampling
variance due individuals and loci, which is why results fromsingle loci should be viewed with utmost caution.

REFERENCES
Arnason, A. and Gullberg, A. 1993. Comparison between the complete
mtDNA sequences of the blue and the fin whale, two species that canhybridize in nature. J. Mol. Evol. 37:312-22.
Baker, C.S., Palumbi, S.R., Lambertsen, R.H., Weinrich, M.T.,
Calambokidis, J. and O’Brien, S.J. 1990. Influence of seasonal
migration on geographic distribution of mitochondrial DNA
haplotypes in humpback whales. Nature, Lond. 344(6263):238-40.
Cavalli-Sforza, L.L. and Edwards, A.W.F. 1967. Phylogenetic
analysis: models and estimation procedures. Evolution 21:550-70.
Chakraborty, R. and Wiess, K.M. 1991. Genetic variation of themitochondrial DNA genome in American Indians is at mutation-drift
equalibrium. Am. J. Phys. Anthropol. 86:497-506.
Di Rienzo, A., Peterson, A.C., Garza, J.C., Valdes, A.M., Slatkin, M.
and Freimer, N.B. 1994. Mutational processes of simple-sequence
repeat loci in human populations. Proc. Natl Acad. Sci. USA
91:3166-170.
Edwards, A., Civitello, A., Hammond, H.A. and Caskey, C.T. 1991.
DNA typing and genetic mapping with trimeric and tetramerictandem repeats. Am. J. Hum. Genet. 49:746-56.
Edwards, A., Hammond, H.A., Jin, L., Caskey, C.T. and Chakraborty,
R. 1992. Genetic variation at five trimetric and tetrameric tandem
repeat loci in four human population groups. Genomics 12:241-53.
Goldstein, D.B., Ruiz Linares, A., Cavalli-Sforza, L.L. and Feldman,
M.W. 1995. Genetic absolure dating based upon micorsatellites andthe origin of modern humans. Proc. Natl Acad. Sci. USA
92:6723-7.
Gyllensten, U., Wharton, D. and Wilson, A.C. 1985. Maternal
inheritance of mitochondrial DNA during backcrossing of two
species of mice. J. Hered. 76:321-4.
Hardy, G.H. 1908. Mendelian proportions in a mixed population.
Science 28:49-50.

407

Hudson, R.R., Boos, D.D. and Kaplan, N.L. 1992. A statistical test for
detecting geographic subdivision. Mol. Biol. Evol. 9:138-51.
Jeffreys, A.J., Wilson, V. and Thein, S.L. 1985. Hypervariable‘minisatellite’ regions in human DNA. Nature, Lond. 314:67-73.
Kimmel, M., Chakraborty, R., King, J.P., Bamshad, M., Watkins, W.S.
and Jorde, L.B. 1998. Signatures of population expansion in
microsatellite repeat data. Genetics 148:1921-30.
Kimura, M. 1985. The neutral mutation-random drift hypothesis as anevolutionary paradigm. In: The Neutral Theory of Molecular
Evolution. Cambridge University Press, Cambridge.
Kuhner, M.K., Yamato, J. and Felsenstein, J. 1998. Maximum
likelihood estimation of population growth rates based on the
coalescent. Genetics 149:429-34.
Levinson, G. and Gutman, G.A. 1987. Slipped-strand mispairing: amajor mechanism for DNA sequence evolution. Mol. Biol. Evol.
4:203-21.
Mullis, K.B. and Falooma, F.A. 1987. Specific synthesis of DNA in
vitro via a polymerase-catalysed chain reaction. Methods Enzymol.
155:335-50.
Nei, M. 1987. Molecular Evolutionary Genetics. Columbia University
Press, New York. x+512pp.
Nielsen, R., Mountain, J.L., Hulsenbeck, J.P. and Slatkin, M. 1998.
Maximum-likelihood estimation of population divergence times andpopulation phylogeny in models without mutation. Evolution
52:669-77.
Paetkau, D. and Strobeck, C. 1994. Microsatellite analysis of genetic
variation in black bear populations. Mol. Ecol. 3(489-95)
Paetkau, D., Calvert, W., Stirling, I. and Strobeck, C. 1995.
Microsatellite analysis of population structure in Canadian polar
bears. Mol. Ecol. 4:347-54.
Paetkau, D., Shields, G.F. and Strobeck, C. 1998. Gene flow between
insular, coastal and interior populations of brown bears in Alaska.
Mol. Ecol. 7:1283-92.
Roff, D.E. and Bentzen, P. 1992. Detecting geographic subdivision: Acomment on a paper by Hudson et al. Mol. Biol. Evol. 9:968.
Schlötterer, C. and Tautz, D. 1992. Slippage synthesis of simple
sequence DNA. Nucleic Acids Res. 20:211-5.
Slatkin, M. 1995. A measure of population subdivision based on
microsatellite allele frequencies. Genetics 139:457-62.
Tautz, D. 1989. Hypervariability of simple sequences as a generalsource of polymorphic DNA markers. Nucleic Acids Res.
17:6462-71.
Weir, B.S. and Cockerham, C.C. 1984. Estimating F-statistics for the
analysis of population structure. Evolution 38:1358-70.
Wright, S. 1969. Evolution and the Genetics of Populations. The
Theory of Gene Frequencies. University of Chicago Press, Chicago.
511pp.
Zouros, E., Freeman, K.R., Oberhauser Ball, A. and Pogson, G.H.
1992. Direct evidence for extensive paternal mitochondrial DNA
inheritence in the marine mussel Mytilus. Nature, Lond. 359:412.

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REPORT OF THE WORKSHOP, ANNEX G

Annex G
Comprehensive Summary of the ‘W’ Stock Hypothesis1
Hiroshi Hatanaka
National Research Institute of Fisheries Science, Fukuura, Yokohama, 236-0051 JapanINTRODUCTION
The hypothesis of two stocks of minke whale, the Sea ofJapan-Yellow Sea-East China Sea stock (‘J’ stock) and the
Okhotsk Sea-West Pacific stock (‘O’ stock), was commonlyused for minke whales in the western North Pacific. The
IWC Scientific Committee conducted a Comprehensive
Assessment of North Pacific minke whales in 1991, andagreed that there were at least two stocks (IWC, 1992). The
eastern boundary of the ‘O’ stock for the run of
HITTER/FITTER models was set at 157°or 150°E, because
there were no available data east of 157°E (IWC, 1992). New
stock structure hypotheses were introduced by the Working
Group on North Pacific Minke Whale Management Trials in
1993, i.e. three sub-stocks in the ‘J’ stock, four sub-stocks inthe ‘O’ stock and an additional stock (the ‘W’ stock) in thecentral region (157-170°E or 150-170°E) (IWC, 1994b).
These new hypotheses were developed because there wasno direct evidence to rule them out, although there was noevidence to support them either (Hatanaka et al., 1994).
Recognising this, the Scientific Committee has pointed out
the desirability of improving information on the stock
structure in the area (IWC, 1994a). Accordingly, theJapanese Government started a research programme under
special permit (JARPN) in 1994. These hypotheses werere-examined in the Working Group on North Pacific Minke
Whale Trials in 1996, based on the information obtained
from JARPN and re-analyses of old data (IWC, 1997b). The
group agreed that the available data and information weregenerally inconsistent with there being sub-stocks and thesub-stock structure was dropped in the trials (IWC, 1997a).
However, while the group agreed that no evidence waspresented to support the hypothesis for the ‘W’ stock, thegroup could not conclude on the plausibility of the ‘W’stock. The Scientific Committee agreed that acomprehensive review of JARPN should be held in 2000 to
evaluate whether the objectives have been achieved. This
paper summarises the results of the ‘W’ stock hypothesis
obtained through the JARPN programme until 1999.
DIRECT INFORMATION TO SUPPORT THE ‘W’
STOCK HYPOTHESIS OBTAINED THROUGH
JARPN
DNA analyses
SC/F2K/J11 described RFLP analysis of a whole mtDNA
control region and sequencing of a 487 base-pair segment of
the control region using 418 samples obtained through1

Originally presented as SC/F2K/J21.

JARPN and 29 samples taken in Korea and the Sea of Japan.
Results showed that whales from sub-area 6 could bediscriminated from whales from the Pacific side of Japan.
However, no significant statistical differences were foundamong sub-areas 7, 8 and 9, thus the ‘W’ stock hypothesis
was not actively supported.
SC/F2K/J10 described microsatellite analysis for the
samples obtained by JARPN. They investigated eightmicrosatellite loci, and showed that samples from sub-areas
7, 8 and 9 followed the Hardy-Weinberg equilibrium. The
authors concluded that their results did not support theexistence of the ‘W’ stock in the offshore waters of the North
Pacific but supported the mixing of ‘J’ and ‘O’ stocks in
sub-area 11.
Allozyme analysis
SC/F2K/J12 described an allozyme analysis, using 497
specimens obtained through JARPN from 1994-1999. The
results showed that the existence of stocks other than ‘O’stock was not supported in sub-areas 7, 8 and 9 and that the
mixing of ‘J’ and ‘O’ stocks occurred in sub-area 11.
Biological parameters
SC/F2K/J13 described analyses on biological parameters.
After identification to either the ‘J’ or ‘O’ stock or anindividual basis based upon mtDNA analysis (SC/F2K/J11),
the authors found significant differences in the mean bodylength of physically mature animals, conception date,
growth and maximum body length between ‘J’ and ‘O’stocks. No differences were found in these biologicalmarkers between sub-areas 7, 8 and 9. However, the sex ratio
and size composition were different to various degrees
between these sub-areas, suggesting segregation by sex andmaturation within one stock.
SC/F2K/J14 examined the possibility of the existence of‘W’ stock minke whales in sub-area 9 by means ofhypothesised models based on conception date in thesamples obtained by JARPN. A model for which only the‘O’ stock existed in sub-area 9 received most support on thebasis of AIC, and the statistical power of the result was
discussed.
Morphological and morphometric analyses
SC/F2K/J15 examined the data of external measurements
collected during JARPN in order to detect the existence of ahypothesised ‘W’ stock. From the analysis of covarianceusing 12 measurements of body proportion, no significant
difference was observed among sub-areas 7, 8 and 9. The

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J. CETACEAN RES. MANAGE. 3 (SUPPL.), 2001

results did not support the ‘W’ stock hypothesis. However,significant differences were found between ‘J’ and ‘O’stocks by means of analysis of variance (AMOVA) anddiscriminant analysis.
Pollutant burden
SC/F2K/J17 investigated persistent organic pollutants suchas PCBs and organochlorine pesticides in the blubber of 76
animals collected by JARPN. Two groups were identified;
one of them (including four individuals) collected from the
Sea of Okhotsk was estimated to be derived from the Sea ofJapan. Little evidence for the ‘W’ stock hypothesis wasfound.
SC/F2K/J18 described a study of heavy metals andorganochlorines accumulated in minke whale tissues. The
discriminant analysis revealed no significant differencesamong the Pacific sub-areas (sub-areas 7, 8 and 9) and theyalso found no evidence to support the ‘W’ stock
hypothesis.
Parasites
SC/F2K/J19 analysed nine species of parasites and two
species of epizoites. No theoretical ‘W’ stock could be
differentiated from ‘O’ stock animals because no
area-specific parasite was found and regional differences inprevalence and intensity of parasite were large enough to
identify ‘W’ stock. However, ‘J’ stock whales werecharacterised by a low prevalence of Pennella balaenoptera
compared with ‘O’ stock animals.
Stable isotopes
SC/F2K/J20 investigated the stable isotope ratio of carbon
and nitrogen on 44 samples taken from sub-areas 7, 8 and 11.
The values of stable isotopes showed different patterns
between the Pacific (sub-areas 7 and 8) and Okhotsk Sea(sub-area 11), but not within the Pacific (between sub-areas
7 and 8). This result coincided with the population structure
revealed by genetic analyses, and did not support the ‘W’stock hypothesis.
OthersSC/F2K/J16 described seasonal variations in the
distributions of minke whales based on sightings madeduring the JARPN surveys. Although not all areas andseasons were covered, the authors estimated that minke
whales are distributed continuously from coastal waters to
offshore waters in the western North Pacific.
SC/F2K/J25 investigated body fatness of minke whales
sampled by the JARPN programme. No difference wasobserved between the ‘O’ stock (sub-area 7) and the
hypothesised ‘W’ stock (sub-area 9), while it was observed
between ‘J’ and ‘O’ stocks.
CONSISTENCY BETWEEN RESULTS OBTAINEDBY JARPN AND PAST KNOWLEDGE
Results obtained from the JARPN Programme revealed clear
differences between the ‘J’ and ‘O’ stocks but no difference
between the ‘O’ and ‘W’ stocks. Differences between ‘J’ and‘O’ stocks were found in mtDNA (SC/F2K/J11), nuclear
DNA (SC/F2K/J10), allozyme (SC/F2K/J12), maximum
body length, growth curve and conception date
(SC/F2K/J13), pollutants (SC/F2K/J18 and SC/F2K/J17),
parasites (SC/F2K/J19) and stable isotopes (SC/F2K/J20).
These results are consistent with the established theory that

there are two stocks of minke whale in the western North
Pacific (Omura and Sakiura, 1956; IWC, 1983; Ohsumi,
1983; Hatanaka, 1997; SC/F2K/J1).
The JARPN Programme provided data on sex ratio andmaturity rate by sub-areas. These data were tested to see
whether they are consistent with hypotheses on segregationand migration. The length compositions by sex and by
sub-areas were examined in SC/F2K/J13. They found thatfemales were relatively abundant in the Okhotsk Sea(sub-area 11), the maturity rate (rate of mature animals) was
relatively lower in coastal waters (sub-area 7) and mature
males were dominant in offshore waters (sub-area 9).
SC/F2K/J20 estimated that some animals caught in the
Okhotsk Sea (sub-area 11) migrated from the West Pacific(sub-areas 7 and 8), based on stable isotope analysis. This
information is consistent with the hypothesis on migrationand segregation of the ‘O’ stock given by Hatanaka andMiyashita (1997). At the same time, segregation by sex andmaturity, especially in sub-area 9, indicates that animals inthis sub-area can not comprise a complete stock, but rather
that they are a part of a stock.
DISCUSSION
The Working Group on North Pacific Minke Whale Trials
held in 1996 agreed that no evidence was presented tosupport the hypothesis for the ‘W’ stock, although somemembers considered that the information did not exclude thepossibility of its existence. The reasons were: (1) insufficient
data to detect genetic differences; (2) insufficient seasonal
coverage of sub-area 9 (not included April to May, and sizeand sex compositions of animals in April-June areimportant); (3) insufficient spatial coverage of sub-area 9(especially not the northern coastal area); and (4) large
portions of sub-areas 8 and 12 had not been sampled.
Through the six years of the JARPN Programme, most ofthese points have been addressed. The number of samples
used in mtDNA analyses, for example, increased from 121 to
502 including four biopsy samples. Eighty-one samples(including size and sex data) were obtained in May-June in
sub-area 9, and 91 samples were from sub-area 8.
SC/F2K/J11 pointed out that genetic analyses based on
JARPN samples used large sample sizes, at least larger thanthose used in most genetic studies on marine mammals.
However, samples were not obtained from the northerncoastal area of sub-area 9 and from sub-area 12, because thepermission to sample in Russian waters could not be
obtained. Data from sub-area 12, such as sex ratio and size
composition, would be useful for examination of thesegregation and migration of the ‘O’ stock, and samples
from this sub-area are essential for detecting the mixing rateof ‘J’ and ‘O’ stocks. However, information from sub-area
12 would not provide direct evidence with respect to the ‘W’stock hypothesis, because animals in sub-area 9 (pure ‘W’stock) show no difference from ‘O’ stock. As for thenorthern coastal area of sub-area 9, length and sex data from
Russian catches are available (Ivashin, 1992). If abnormallylarge animals are ignored, the sex ratio and male length
distribution are similar to those in sub-area 12, and lengthcomposition of females is similar to those in sub-area 11(Hatanaka and Miyashita, 1997). This means that small
animals (smaller than 6m or so) are relatively few in thisarea, and small animals of ‘W’ stock are still unknown in thiscase.
The necessity of showing statistical power whenpresenting the results of analyses has been pointed out.
However, it is difficult to set the appropriate alternative

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hypothesis in the case of the ‘O’/’W’ stock situation, because
no significant differences were observed between them.
However, SC/F2K/J30 tried to estimate statistical power in
the analysis of conception date, assuming that meandifference of conception date was one month between the‘O’ and ‘W’ stocks. In this case, the 13 available samples
from sub-area 9 had a power of about 70%. SC/F2K/J14
conducted a simulation for estimating statistical power using
allele frequency data from the Adh-1 locus. It was estimatedthat the present sample size in sub-area 9 (178 individuals)
had a good statistical power in the case of two stocks, one
was ‘O’ stock in sub-area 9 and the other was an assumed
stock in which 80% of ‘O’ stock and 20% of ‘J’ stock weremixed. The authors also estimated a dispersal rate of 0.33
between sub-areas 7 and 9 and pointed out that there was no
meaning in distinguishing such a slight difference formanagement objectives. In addition, SC/F2K/J11 estimatedthat the dispersal among sub-areas 7, 8 and 9 was 131.2
females per generation. These high dispersion rates
suggested that those animals were effectively the same
population.
Some may say that the JARPN Programme cannot provide
any definitive evidence to prove that ‘O’ and ‘W’ were thesame stock, even though it provided results that suggested no
substantial differences between them. However, the ‘W’stock hypothesis was not based on supportive information,
but rather because there were no available data in offshore
waters in 1993. However, at this time a large amount of dataand samples are available through the JARPN Programme,
none of which support a ‘W’ stock hypothesis. I believe,
therefore, that we have no more reason to maintain it. In
other words, if the present information was available at themeeting of the Working Group on North Pacific Minke
Whale Management Trials in 1993, the ‘W’ stock hypothesis
would not have been established.
In summary, a fairly large amount of data has beencollected through the JARPN Programme and a wide varietyof analyses have been conducted. Despite this, no supportive
information on the existence of a ‘W’ stock has emerged.

The JARPN Programme has revealed various differences
between the ‘J’ and ‘O’ stocks. This indicates that thevarious methods applied to detect the existence of different
stocks could give positive results when more than one stockis present.

REFERENCES
Hatanaka, H. 1997. A short review of hypotheses on minke whale stock
structure in the northwestern part of the North Pacific. Rep. int. Whal.
Commn 47:553-5.
Hatanaka, H. and Miyashita, T. 1997. On the feeding migration of
Okhotsk Sea-West Pacific stock minke whales, estimates based on
length composition data. Rep. int. Whal. Commn 47:557-64.
Hatanaka, H., Kato, H. and Ohsumi, S. 1994. Is the sub-stock scenario
for minke whale stock structure in the waters surrounding Japanplausible? Paper SC/46/NP3 presented to the IWC ScientificCommittee, May 1994 (unpublished). 15pp. [Paper available fromthe Office of this Journal].
International Whaling Commission. 1983. Report of the ScientificCommittee, Annex E. Report of the sub-committee on minke whales.
Rep. int. Whal. Commn 33:91-122.
International Whaling Commission. 1992. Report of the sub-committee
on North Pacific minke whales. Rep. int. Whal. Commn
42:156-77.
International Whaling Commission. 1994a. Report of the ScientificCommittee. Rep. int. Whal. Commn 44:41-201.
International Whaling Commission. 1994b. Report of the ScientificCommittee, Annex G. Report of the Working Group on North PacificMinke Whale Management Trials. Rep. int. Whal. Commn
44:120-44.
International Whaling Commission. 1997a. Report of the ScientificCommittee. Rep. int. Whal. Commn 47:59-258.
International Whaling Commission. 1997b. Report of the ScientificCommittee, Annex J. Report of the Working Group on North PacificMinke Whale Trials. Rep. int. Whal. Commn 47:203-26.
Ivashin, M.V. 1992. Report of the sub-committee on North Pacificminke whales, Appendix 7. USSR catch and sightings of minke
whales. Rep. int. Whal. Commn 42:168-9.
Ohsumi, S. 1983. Minke whales in the coastal waters of Japan in 1981,
with special reference to their stock boundary. Rep. int. Whal.
Commn 33:365-71.
Omura, H. and Sakiura, H. 1956. Studies on the little piked whale fromthe coast of Japan. Sci. Rep. Whales Res. Inst., Tokyo 11:1-37.

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J. CETACEAN RES. MANAGE. 3 (SUPPL.), 2001

Annex H
An Alternative Summary of the Results Relating to the ‘W’
Stock Hypothesis
Barbara L. Taylor
Southwest Fisheries Science Center, La Jolla, CA 92038-0271, USA
Annex G presents a summary of JARPN results on thequestion of whether data collected provides evidence formore than one stock within the JARPN study area. This
working paper presents an alternate interpretation of thesame data under the same headings.
DNA analysis
Mitochondrial DNA data are analysed in SC/F2K/J6,
SC/F2K/J7, SC/F2KJ11, SC/F2K/J32 and Goto and Pastene(1999). All these analyses reveal low p-values comparing
either 7 to 9, 8 to 9, or 7 and 8 together to 9. SC/F2K/J32
shows clearly significant differences when the data are
re-stratified between sub-area 9W and other areas. These
results are consistent with more than one stock utilising thearea and are similar to results for Southern Hemisphereminke whales where additional stock structure was accepted(summarised in Pastene and Goto, 1997). Although similar
evidence for multiple stocks was not found whenmicrosatellites were used, this is not an uncommon result incetacean research. There are two possible explanations: (1)power is lower because the effective population size isapproximately four times as large for nuclear DNA as for
mtDNA, which effectively halves the effect size; or (2) there
is more dispersal among males.
Allozyme analysis
Allozymes generally provide less resolution on stock
structure because of their lower mutation rate. For example,
no differences were found using allozymes for minke whalesin the Antarctic and yet differences were found using
mtDNA. Allozymes are commonly used when differenceson an evolutionary scale are expected. This is consistent withfinding differences between the ‘J’ and ‘O’ stock which
probably diverged hundreds of generations ago.
Biological parameters
Although it is good to look for potential differences in bodylength and conception dates because they can be expected
between populations that differ on an evolutionary timescale, not finding differences does not constitute evidence
against there being stock structure. The timing of breeding
and body size are related to the environment that animals
encounter. It is likely that female minke whales across theopen North Pacific time reproductive events to match withmaximum productivity along the ice edges, which may not
differ markedly across the northern part of the ocean basin.

The reproductive timing of other stocks in the open North
Pacific basin is the same within a species for other whales,such as gray, white and humpback whales, and yet multiple
stocks are known to exist. Because JARPN was only able toexamine minke whales in the southern part of theirsummering grounds, and minke whales are known tosegregate latitudinally by sex and age, it is clear that
sub-areas 7, 8 and 9 do not completely contain any stock.
Adult females are known to be in more northern waters.
Therefore, while one can state that sub-area 7 does notcontain an entire stock, one cannot state that the lack of
certain sex and age groups in sub-area 9 constitutes evidence
against an offshore stock because essentially the same
condition exists across this latitudinal range.
Morphological and morphometric analyses
Although p-values were not presented when > 0.05 in
SC/F2K/J15, the following differences were found: Table 2:
V11 p > 0.01, v5% p < 0.05, v10%, p < 0.01, v11%
p < 0.01.
Pollutant burden
Differences (p < 0.05) were found between years but thesewere attributed to ‘J’ and ‘O’ stock differences.
Parasites
Differences were found in parasite prevalence but not for
intensity within sub-areas 7, 8 and 9.
Stable isotopes
Stable isotopes did not show differences within sub-areas 7,
8 and 9 but participants agreed that such studies are used to
see what animals have consumed on the time-scale of weeks
and that therefore this technique was not appropriate forstudies of stock structure.
OthersSC/F2K/J25 compared body fatness between sub-areas 7
and 9 and obtained the following p-values by month:
May = 0.07, June = 0.12, August = 0.12.
SUMMARY
SC/F2K/J21 summarised the JARPN results as presenting noevidence for stock structure within sub-areas 7, 8 and 9. The
above summary shows that there are many indications that
more than one stock may utilise these waters. Differences

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REPORT OF THE WORKSHOP, ANNEX H

between management units or stocks can be expected to bemuch smaller than differences between populations thatdiffer at a level sufficient for evolution to take place. A
commonly used rule of thumb is that populations’evolutionary differences can accumulate if there are fewer
than one disperser per generation. The Sea of Japan stock
differs from other North Pacific minke whales at thisevolutionary level and is inappropriate as a standard against
which to measure the ‘W’ stock hypothesis. It is also
inappropriate to only consider data of management
significance when p < 0.05. Such a standard could result in avery unsatisfactory type 1 to type 2 error ratio.

REFERENCES
Goto, M. and Pastene, L.A. 1999. Genetic population structure in thewestern North Pacific minke whale examined by mtDNA control
region sequencing analysis. Paper SC/51/RMP8 presented to the
IWC Scientific Committee, May 1999, Grenada, (unpublished).
12pp. [Paper available from the Office of this Journal].
Pastene, L.A. and Goto, M. 1997. A review of the studies on
stock/species identity in the minke and other baleen whale species,
conducted under the Japanese Whale Research Program under
special permit in the Antarctic (JARPA). Paper SC/M97/2 presented
to the Intersessional Working Group to Review Data and Resultsfrom Special Permit Research on minke whales in the Antarctic,
Tokyo, Japan, 12-16 May 1997 (unpublished). 34pp. [Paper
available from the Office of this Journal].

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Annex I
Suggestions for Alternate Stratification and Analyses of Genetic
Data
P. Palsbøll, L. Pastene and B. Taylor
In addition to homogeneity tests between sample partitions
under different stratification schemes, estimating possible
correlations across space and/or time with genetic distances
between partitions could be performed (e.g. Mantel test).
Such tests may be more appropriate in situations where geneflow is high. To avoid putting potentially heterogeneous
samples within the same partition, partitions should be kept
relatively narrow in terms of space and time.
Regarding stratification (for the above kind andhomogeneity tests) we suggest that sample partition be basedon additional parameters. Oceanographic features such as
water temperature and currents, topography, etc. could beconsidered. In addition, new stratification analyses should
include the recommendation (Item 10.2.4) to analysesightings data using a Generalised Linear Model that
includes (among other variables) the covariates of year,
month, Beaufort Sea state and temperature.
The above factors could be considered in addition to or in
combination with biological parameters, fat content, putative
migration routes and prey preference.