Research Plan for New Scientific Whale Research Programin the western North Pacific(NEWREP-NP)
Government of Japan

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EXECUTIVE SUMMARYa.

Primary, Secondary (and, if appropriate Ancillary) objectives and their importanceNEWREP-NP has the following Primary and Secondary objectives (see details in section 2.1 and 2.2 ofthe research plan):Primary Objective I: Contribution to optimizing the establishment of a sustainable catch limit for common minke
whales in the coastal waters of Japan.
Secondary Objectives I (i): Investigate the spatial and temporal occurrence of J stock common minke whales
around Japan, by sex, age and reproductive status; I (ii): Estimate the abundance of the J and O stocks in coastal
waters of Japan; I (iii): Verify that there is no structure in the O stock common minke whale in the Pacific side ofJapan; and I (iv): Improve RMP trials by incorporating age data in their conditioning.
Primary Objective II: Contribution to the RMP/IST for North Pacific sei whale 1.
Secondary Objectives II (i): Abundance estimates for North Pacific sei whale taking account additional variance;
II (ii): Estimation of biological and ecological parameters in North Pacific sei whales for RMP Implementation;
II (iii): Study of the pattern of movement of whales of the ‘pelagic stock’ within the feeding grounds and between
feeding and breeding grounds; and II (iv): Specification of RMP ISTs for North Pacific sei whale.
Ancillary Objective I: Investigation of the influence of environmental changes on whale stocks.
Ancillary Objective II: Examination of the effects of pollutants on whales.
Ancillary Objective III: Study of distribution, movement and stock structure of large whales with particularemphasis on blue and North Pacific right whales.
Primary, Secondary and Ancillary Objectives above are important for the improvement in theconservation and management of whale stocks for the following reasons (see details in section 2.5 of theresearch plan):- Collection and analyses of relevant data and samples (abundance, stock structure, and biological parameters)
will optimize the application of the RMP on the western North Pacific common minke and North Pacific sei
whales.
- The JARPNII final review workshop, endorsed by the IWC SC, noted that ‘if the ISTs for the western North
Pacific common minke whales are to be revised in the future, the age data should be included in the conditioning
process’. NEWREP-NP makes use of age data of common minke and sei whales to optimize their management
under the RMP (both current and as this will develop in the future).
- Those data and samples will contribute to the next Implementation Review in the case of the western North
Pacific common minke whales, and the completion of CA and the carrying out of an Implementation in the caseof sei whale.
- Information on stock structure (biopsy) and abundance trends (sighting surveys) in large baleen whales including
the North Pacific right and blue whales, will contribute to understand the pattern of recovery of those whales after
past commercial whaling. These studies have been encouraged and recommended by the IWC SC.
- Research on the health of the whales is directly related to whale conservation purposes, and studies in this field
have been recommended by the IWC SC.

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It is appreciated that the carrying out of an Implementation of the RMP for sei whales in the North Pacific has
yet to be agreed by the Commission. However this is typically a routine step in extending RMP Implementations
to further resources, so for simplicity of expression this form of words will be used in this document, but that
does not imply that this authorisation will still not have to be given.

2Primary, Secondary and Ancillary Objectives above are important for the conservation and managementof other living marine resources or the ecosystem of which the whale stocks are an integral part for thefollowing reasons (see details in section 2.5 of the research plan):- Under the Ancillary Objective I on environmental changes, several kinds of information will be collected
including prey species in the whale’s stomach, prey species in the research area and environmental data. This willcontribute to the understanding of the interaction between whales and several other components of the ecosystem,
which in turn would contribute to the ecosystem approach of whale resource management.
Primary, Secondary and Ancillary Objectives above are important for testing of hypotheses not directly
related to the management of living resources for the following reasons (see details in section 2.5 of theresearch plan):- Information will be provided to characterize the oceanographic structure of the research area.
- Oceanographic information will provide insight on whether or not environmental changes are occurring in the
research area, particularly in the context of global warming.
- There is a great interest in the IWC SC to investigate the effects of marine debris on cetaceans and a workshop
focused on this subject has taken place.
b.

Evaluation of the use of lethal sampling instead of non-lethal methods (by objective) if it requires
lethal sampling

Lethal sampling is required mainly for Secondary Objectives I (i), I (iv) and II (ii) (sample/data for age
determination, body length and sexual maturity); Ancillary Objective I (sample/data on preycomposition/consumption and on nutritional condition indices such as blubber thickness, girth and bodyweight), and Ancillary Objective II (sample/data on blubber, liver, muscle and plasma) (see details in
section 3.1.1 of the research plan).



A detailed evaluation of the available information on feasibility of lethal and non-lethal techniques led
the proponents to the conclusion that the sample/data listed above can be obtained only through lethal
methods at this stage (see details in section 3.1.1 of the research plan).



During the implementation of the NEWREP-NP research, the proponents will conduct feasibility studies
to evaluate several new non-lethal techniques which potentially could be used to address the objectives
above: DNA-Methylation for age determination, examination of hormone in blubber for determinationof sexual maturity, stable isotope and fatty acids for studies on feeding ecology. Potentially all thesetechniques could be used based on tissues collected by biopsy sampling. Examination of some technicalaspects of the biopsy sampling equipment for common minke whale is itself another of the feasibility
studies on non-lethal techniques (see Figure 2 in section 3.1.1 of the research plan).

c.

Species to be taken and sample size by study area and year (and targeted component of population
if applicable)



The species to be taken for Primary Objective I is the western North Pacific common minke whale of the
O and J stocks (see details in section 3.1.1 of the research plan). The species to be taken for Primary
Objective II is the sei whale of the North Pacific pelagic stock (see details in section 3.2.1 of the researchplan). NEWREP-NP is planned for a total period of 12 years with a mid-term review after the first six
years.

The annual sample size of common minke whale in sub-area 11 (Secondary Objective I (i)) for the first
6 years is 47 animals with the sampling starting in 2017 (more detailed estimates of sample size for theobjective of studying the temporal trend of the J stock mixing proportion will be made once data havebeen accumulated in the first six surveys); the annual sample size of common minke whale in sub-areas
7-9 (Secondary Objective I (iv)) is 123 animals with the sampling starting in 2017 (see details of thesample size estimates in common minke whale in Annex 11 of the research plan).

3The annual sample size of sei whale is 134 animals (Secondary Objective II (ii)) with the sampling
starting in 2017 (see details of the sample size estimates in sei whale in Annex 16 of the research plan).

d.

Summary of effect of catches on targeted stock (s)There is no negative effect on the stocks of common minke whale of the proposed NEWREP-NP catches
in sub-areas 11 and 7-9 (see details of the analyses in section 4.1 of the research plan). (Scenarios wherethat might have been the case are shown to be no longer plausible.)

There is no negative effect on the pelagic stock of sei whale of the proposed NEWREP-NP catches (seedetails of the analyses in section 4.2 of the research plan).

e.

Summary of co-operative research provisions

Scientists from the Institute of Cetacean Research will play the leading role in order to pursue the research
activities and achieve the research objectives of NEWREP-NP, in collaboration (particularly regarding
environmental change investigations) with scientists from other domestic and/or foreign organization.
Annex 20 of the research plan shows a list of collaborating research institutions as well a list of
institutions and research programs from which NEWREP-NP will obtain data relevant to its objectives,
by research objective of NEWREP-NP.



Participation of foreign scientists in the field, laboratory and analytical works is welcomed. To facilitate
collaboration, the proponents have developed specific protocols for foreign scientists to apply forparticipation in field and analytical work (see details in Annex 22 of the research plan).



Data obtained by this research program will be shared with members of the IWC SC in accordance with
the IWC SC Data Availability Agreement.



To facilitate the research collaboration and analyses, databases will be created after each survey under
this program, which will specify the kind of samples and data collected during its research activities.

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CONTENTS
1.

INTRODUCTION (p9)2.

HYPOTHESES AND STUDY OBJECTIVES (p10)
2.1 Primary objectives (p10)2.1.1
Primary Objective I (p10)2.1.1.1 Background on the research needs (p10)2.1.1.2 Detailed basis for data/sample needs (p12)2.1.1.3 Secondary Objectives (p13)2.1.2
Primary Objective II (p14)2.1.2.1 Contribution to the RMP/IST for North Pacific sei whale (p14)2.1.2.2 Estimation of biological and ecological parameters for the application of the RMP to
the North Pacific sei whale (p14)2.1.2.3 Specification of models (p15)2.1.2.4 Detailed basis for data/sample needs (p15)2.1.2.5 Secondary Objectives (p16)
2.2 Ancillary Objectives (p17)2.2.1
Ancillary Objective I (p17)2.2.2
Ancillary Objective II (p17)2.2.3
Ancillary Objective III (p18)
2.3 Relationships amongst Primary Objectives (p18)
2.4 Requirements of lethal sampling, non-lethal methods or a combination of both for each Primary
Objective (p18)2.4.1
Primary Objective I (p18)2.4.2
Primary Objective II (p19)
2.5 Value of each Primary and Ancillary Objective (p19)
2.6 JARPN/JARPNII scientific outputs and relationship with NEWREP-NP (p20)

3.

METHODS TO ADDRESS OBJECTIVES (p21)
3.1 Primary Objective I (p21)
3.1.1
Field methods (p21)
3.1.2
Laboratory methods (p26)
3.1.3
Analytical methods (p27)3.1.4Time frame with intermediate targets (p29)
3.1.5
Explanation that this objective can be achieved by the method proposed (p31)
3.1.6
Data to be obtained (p32)
3.1.7
Description of use of data from other projects or programs (p33)
3.2 Primary Objective II (p33)
3.2.1
Field methods (p33)
3.2.2
Laboratory methods (p34)3.2.3
Analytical methods (p34)3.2.4Time frame with intermediate targets (p35)3.2.5
Explanation that this objective can be achieved by the method proposed (p35)
3.2.6
Data to be obtained (p36)3.2.7
Description of use of data from other projects or programs (p36)
3.3 Summary of the overall justification for final study area, sampling design and sample size (p36)
3.4 Possible modification of lethal sample size (p37)
3.5 Ancillary Objective I (p37)
3.6 Ancillary Objective II (p37)
3.7 Ancillary Objective III (p37)

4.

ASSESSMENT OF POTENTIAL EFFECT OF CATCHES (p37)
4.1 Primary Objective I (p37)
4.2 Primary Objective II (p44)5.

LOGISTICS AND PROJECT MANAGEMENT (p46)
5.1 Description of intermediate targets to allow for adequate review of progress relative to objectives(p46)
5.2 Description of overall project management including personnel and logistic resources (p47)55.3 Backup plan for contingencies (p48)
6.

CO-OPERATIVE RESEARCH (p49)
6.1 Assessment of the degree to which the program will coordinate its activities with related research
projects (p49)
6.2 A note on the provisions for co-operative research (field studies; analytical studies) (p50)

7.

CONCLUSIONS (p50)
References (p50)

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LIST OF ANNEXES
Annex 1: NEWREP-NP and consideration of the reasoning and conclusions in the Judgment of the International
Court of Justice (ICJ) on 31 March 2014 (p56)Annex 2: CPUE data and trend for O stock of western North Pacific common minke whales (p61)
Annex 3: Summary of the results of the 2013 RMP/Implementation Review for western North Pacific common
minke whales (p70)
Annex 4: A summary of the new information on stock structure in the western North Pacific common minke
whales presented to the JARPNII final review workshop (p79)
Annex 5: Overview of JARPN/JARPNII outcomes (p82)
Annex 6: Whale sampling survey design under Primary Objective I (common minke whale) (p85)
Annex 7: Secondary Objective I (i) Investigate the spatial and temporal occurrence of J stock common minke
whales around Japan, by sex, age and reproductive status. Field and laboratory work, and analytical procedure(p92)
Annex 8: Secondary Objective I (ii) Estimate the abundance of the J and O stocks in coastal waters of Japan.
Field and laboratory work, and analytical procedure (p104)
Annex 9: Secondary Objective I (iii) Verify that there is no structure in the O stock common minke whale in the
Pacific side of Japan. Field and laboratory work, and analytical procedure (p108)
Annex 10: Secondary Objective I (iv) Improve RMP trials by incorporating age data in their conditioning. Field
and laboratory work, and analytical procedure (p110)
Annex 11: Estimates of sample size for Primary Objective I (common minke whale) (p111)
Annex 12: Whale sampling survey design under Primary Objective II (sei whale) (p148)
Annex 13: Secondary Objective II (i) Abundance estimates for North Pacific sei whales taking account of theadditional variance. Field and laboratory work, and analytical procedure (p153)
Annex 14: Secondary Objective II (ii) Estimation of biological and ecological parameters in North Pacific sei
whale for RMP Implementation. Field and laboratory work, and analytical procedure (p157)
Annex 15: Secondary Objective II (iii) Study of the pattern of movement of whales of the ‘pelagic stock’ within
the feeding grounds and between feeding and breeding grounds. Field and laboratory work, and analyticalprocedure (p162)
Annex 16: Estimates of sample size for Primary Objective II (sei whale) (p165)
Annex 17: Ancillary Objective I Investigation of the influence of environmental changes on whale stocks. Field
and laboratory work, and analytical procedure (p169)
Annex 18: Ancillary Objective II Examination of the effects of pollutants on whales. Field and laboratory work,and analytical procedure (p176)
Annex 19: Ancillary Objective III Study on distribution and stock structure of large whales with particularemphasis on blue and North Pacific right whales. Protocol for biopsy sampling and photo identification (p179)
Annex 20: List of collaborating and data providing research institutions (p181)
Annex 21: Research vessels (p184)

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Annex 22: Protocol for participation of foreign scientists in field and analytical research under the NEWREP-NP(p188)

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1.

INTRODUCTION

This document presents the research plan for the New Scientific Whale Research Program in the western North
Pacific (NEWREP-NP), which takes into consideration the comments made by the Expert Panel Workshop heldfrom 30 January to 3 February 2017 and by the International Whaling Commission’s Scientific Committee (IWC
SC) 2017 annual meeting, in conformity with paragraph 30 of the Schedule to the International Convention for
the Regulation of Whaling (ICRW) and Annex P (IWC, 2013a; 2016a). This research plan forms the basis for theGovernment of Japan to issue a special permit, in accordance with Article VIII, paragraph 1 of the ICRW. In theprocess of drafting and developing this research plan, Japan also take account of the reasoning and conclusions of
the Judgment of the International Court of Justice (ICJ) in the case concerning Whaling in the Antarctic (Australia
v. Japan: New Zealand intervening) (for further details, see Annex 1).
Research needs in the western North Pacific
NEWREP-NP has two primary objectives: ‘Contribution to optimizing the establishment of a sustainable catch
limit for common minke whales in the coastal waters of Japan’ and, ‘Contribution to the RMP/IST for North
Pacific sei whale’.
The western North Pacific common minke whale (Balaenoptera acutorostrata) and the sei whale (B. borealis),
were the target species of commercial whaling by Japan, until 1975 in the case of sei whales, and until 1987 in
the case of common minke whales. Both are considered target species for future commercial whaling by Japan
under IWC-endorsed catch limits, in accordance with paragraph 10 (e) of the Schedule of the ICRW, calculatedusing the Revised Management Procedure (RMP).
The latest RMP Implementation for western North Pacific common minke whale, which includes the
Implementation Simulation Trials (ISTs) was completed in 2013 (IWC, 2014a). Three stock structure hypotheses
were considered during the 2013 Implementation (see sections 2.1.1.1 and 4.1). However it was not possible for
the IWC SC to agree on the plausibility of these stock structure hypotheses. As a consequence, all three stock
structure hypotheses were classified as ‘no agreement’ and were therefore treated as if they had been assigned‘Medium’ plausibility in the trials. Consequently, the results of the Implementation produced very small catch
limits for common minke whales in coastal waters of the Pacific side of Japan (sub-areas 7CS off Sanriku and7CN off Kushiro); this is difficult to reconcile with the empirical evidence from the last years of commercial
whaling in coastal areas of Japan prior to the commercial whaling moratorium. Japan’s Small Type Coastal
Whaling (STCW) had been catching common minke whales since 1930. For waters around Sanriku, Kushiro andnorth Hokkaido (sub-area 11) the average catch for the last ten years before the commercial whaling moratorium(1978-1987) was 340 animals, with no signs of decreasing Catch Per Unit Effort (CPUE) (Annex 2), so that the
population of the common minke whale was considered a Sustained Management Stock under the New
Management Procedure (NMP) with annual take of 340 animals (IWC, 1986; 1992). Although past CPUE data
might not be completely reliable as an index of abundance (see Annex 2) the results of the 2013 RMP
Implementation are hardly consistent with the reality observed in coastal waters of Japan before the commercial
whaling moratorium. Even considering the uncertainties of the environmental changes and the possibilities ofother interpretations, the wide discrepancy between the empirical evidence from the field and the results of the2013 Implementation indicates that there might be problems in interpretation of the data and key assumptions
used in the population assessment under the RMP Implementation.
Some of the perhaps problematic issues and assumptions used during the 2013 RMP Implementation include,
among others, i) distribution and temporal migratory patterns used to define stocks/sub-areas, ii) that the J stock
common minke whale is estimated to be heavily depleted and; iii) the possible existence of a coastal O stock (theso called Ow stock) as well as two J stocks (Jw and Je).
These problematic issues drive the proponents to the first Primary Research Objective of NEWREP-NP:‘Contribution to optimizing the establishment of a sustainable catch limit for common minke whales in the coastal
waters of Japan’. The idea under this Primary Objective is first to identify the causes for the wide discrepancy
between the empirical evidence from the field and the results of the 2013 Implementation (some are mentioned
above), and second to identify the data and samples required to check, verify and/or reject some of the issues andassumptions used in the 2013 RMP Implementation. Research activities related to the second point above arelisted as several Secondary Objectives (see details in section 2).
The North Pacific sei whale has not been the subject of a previous RMP Implementation. As Japan considers thesei whale to be one of the target species for commercial whaling in the future, Japan intends to bridge the gap
between the scientific work achieved so far at the IWC SC and that necessary for Japan to achieve its ultimate

9

goal (i.e. recommence commercial whaling on sei whale). This gap drives to the second Primary Objective of
NEWREP-NP: ‘Contribution to the RMP/IST for North Pacific sei whale’.
In particular this second Primary Objective will attempt to assess the contribution that biological data (e.g. age
distribution, age at sexual maturity) of sei whales can make to the RMP Implementation. As the RMP is a feedback
management tool, it is expected that new biological data to be used in the Implementation will optimize theperformance of the RMP Implementation for sei whales in terms of catch limits and conservation statistics. In
other words larger catch limits can be calculated without compromising the status of the stock(s) involved using
RMP. To test such hypothesis, additional scientific information is required, which will be addressed under several
Secondary Objectives (see details in section 2).
The program under this research plan therefore will attempt to optimize the application of the RMP to the western
North Pacific common minke and North Pacific sei whales, by collecting and using a variety of relevant data fromwhales and their environment in the western North Pacific.
These two Primary Objectives come within the research categories identified by the IWC SC in its Annex P, i.e.
‘improve the conservation and management of whale stocks’ (IWC, 2013a; 2016a). Achieving a sustainablebalance between the maintenance of the unique marine ecosystem and the utilization of its abundant resources is,
as is common for all seas and oceans, an important challenge for the western North Pacific. This is also fully
consistent with the objectives of the ICRW stipulated in its preamble; “to provide for the proper conservation ofwhale stocks and thus make possible the orderly development of the whaling industry”.

2.

HYPOTHESES AND STUDY OBJECTIVESNEWREP-NP has two Primary Objectives each derived from the elaboration of specific hypotheses to be tested.
For North Pacific common minke whales some of these hypotheses are: i) that J stock is not heavily depleted and,ii) that there is only one O stock in the Pacific side of Japan. For sei whales, the hypothesis is that past and futureseries of biological data such as age, sexual maturity and other biological parameters could make an important
contribution to the application of the RMP for the North Pacific sei whale. In other words the hypothesis is thatby the use of biological data in ISTs larger catch limits can be calculated without compromising the status of thestock(s) involved.
2.1 Primary Objectives
2.1.1

Primary Objective I

Contribution to optimizing the establishment of sustainable catch limit for common minke whales in the coastal
waters of Japan
2.1.1.1 Background on the research needs
The latest Implementation of western North Pacific common minke whale was completed in 2013 (IWC, 2014a).
Annex 3 summarizes the main results of the Implementation Review.
A total of 22 sub-areas were set for the Implementation (Figure 1), and three stock structure hypotheses were used:
Hypothesis A proposes two stocks, J and O stocks, which mix to each other spatially and temporally around Japan;
Hypothesis B is similar to Hypothesis A but it proposes a different stock in the Yellow Sea (Y stock); Hypothesis
C proposes five stocks: Y stock in the Yellow Sea, J stock in the Sea of Japan (Jw), J stock in the Pacific side ofJapan (Je), a coastal O stock (Ow) and a pelagic O stock (Oe) in the Pacific side of Japan.

10Figure 1. The 22 sub-areas used for the RMP Implementation for western North Pacific common minke whale(IWC, 2014b).
The plausibility of the three stock structure hypotheses was discussed at the 2012 IWC SC Annual meeting.
However no agreement on plausibility was reached by the IWC SC.
The relevant information in Annex 3 is as follows:







A total of 11 management variants were used.
Variants 9, 10 and 11 were the most appropriate from the point of view of utilization of the resource.
However, the average median annual commercial catches (years 1-100) for Variants 9, 10 and 11 were17, 15 and 9 animals, respectively, for sub-areas 7CS and 7CN.
Variant 9 was ‘potentially acceptable with research’; Variant 10 was ‘unacceptable’; and Variant 11 was‘potentially acceptable with research’.
All unacceptable trials under Variants 9, 10 and 11 were related to stock structure hypothesis C, which
proposed a coastal O stock in the Pacific side of Japan (Ow).
In addition, unacceptable trials under Variant 10 were related to unacceptable performance of J stock
under stock structure hypotheses A, B and C.

As noted earlier the results of the 2013 RMP Implementation are hardly consistent with the reality observed incoastal waters of Japan before the commercial whaling moratorium. The wide discrepancy between the empiricalevidence from the field and the results of the 2013 Implementation suggests problems in the interpretation of thedata and key assumptions used in the population assessment under the RMP Implementation. Some of the
problematic assumptions/results and research designs identified by the proponents are the following:i)

The J stock common minke whale is heavily depleted. This assessment output led to the results thatsome management variants (5 and 10), for which the average catch was different from zero in subarea 11, were not acceptable because of bad performance of the J stock under stock structure
hypotheses A and B. Furthermore the performance of the Jw stock under hypothesis C wasborderline or unacceptable depending on the trial.

ii)

The occurrence of a coastal O stock (Ow) in the Pacific side of Japan as assumed under stock
structure hypothesis C. This assumption led to the results that Variants 7, 9 and 11 were justpotentially acceptable with research and Variant 10 was unacceptable. Performance for the Ow stock
was unacceptable for Variants 7, 9 and 10 and borderline for Variant 11 under two trials.
Performance under some trials under stock structure C was unacceptable for Variants 7, 9, 10 and
11.

iii)

Large additional variance in abundance estimate. This was because sighting surveys for abundance
estimates were scattered i.e. sighting survey conducted in different sub-areas were conducted indifferent times.

11

Therefore, Primary Objective I attempts to collect data that can improve the situation and that may be used torefine the results of future RMP Implementation on the western North Pacific common minke whales.
2.1.1.2 Detailed basis for data/sample needsi)Further data to inform on the status of the J stock

It is necessary to collect new information on distribution and abundance of the J stock in waters around Japan andin the Okhotsk Sea in order to evaluate the plausibility of the assumption i) of 2.1.1.1. The current estimate fromthe Implementation trials of heavy depletion of this stock is difficult to reconcile with several lines of evidence
which indicate the possibility of an increasing stock that is expanding its distribution. First the sustained orincreasing level of by-catches for a recent period of more than 10 years in the absence of any increase in theamount of stationary gear in which this by-catch occurs (section 3). Second the occurrence of J stock in different
sub-areas and periods in proportions larger than those estimated during the commercial whaling period in subarea 7 (see details in section 3).
New information on abundance based on sighting surveys, as well as investigation of distribution and temporal
trends in the mixing proportion of J stock in sub-areas around Japan, especially sub-area 11 for which available
data are limited, are necessary in order to better understand the status of the J stock. Abundance can also potentiallybe addressed through genetic mark-recapture methods. Individual identification of J and O stock animals is
possible through the combined use of genetics (microsatellite and mtDNA) and non-genetic (flipper color pattern)
data.
ii)

Further data to verify the existence of a single O stock

The plausibility of an Ow stock under the assumption ii) of 2.1.1.1 was evaluated through several studies on stock
structure presented to the JARPNII final review workshop. All of those studies followed specificrecommendations from the 2009 mid-term JARPNII review workshop (see details in Annex 4).
A substantial amount of new information on stock structure of common minke whale has been accumulated since
the last Implementation Review, which was based on data collected until 2007. In particular it is noted the larger
number of new samples (around 1,700), new analytical procedure (DAPC, kinship, statistical power of theheterogeneity test) and the availability of age data.
As noted above, most of the analyses in the documents presented to the 2016 JARPNII final review workshop(summarized in Annex 4) responded to recommendations made during the 2009 JARPNII mid-term review.
Results of all different analyses indicate a single O stock distributed from the Japanese coast to approximately
170°E, and that the data do not support the occurrence of a coastal stock as proposed by Hypothesis C (Ow).
However in the 2016 IWC SC meeting there was not unanimous support for this view. Subsequent kinshipanalyses seem virtually impossible to reconcile with the existence of an Ow stock, but there has not yet been time
for the IWC SC to review these; nevertheless future work should clearly include a component that will lead to anincrease in the size of samples available for kinship analyses to seek even stronger confirmation/verification ofthis result. Kinship analyses therefore will be conducted to investigate the relationship between coastal andoffshore animals as recommended by the IWC SC in 2016 (IWC, 2016b), based on existing and new samples.
Under the proponents’ view of a single O stock scenario, we would expect parent/offspring linkages between
coastal and offshore common minke whales.
iii)

Use of biological data, particularly age data, in the RMP trials conditioning

The IWC SC broadly agrees on the value of age data in ISTs (e.g. conditioning operating models). In the case ofcommon minke whale, ageing techniques have been improved and as a consequence age information is available
for a larger number of animals. Additional age data is very important for the aim of improving RMP trials towards
more reliable representations of possible true stock dynamics.
Additional age data is also important to further verify the existence of a single O stock. Although (as describedabove) the genetic data are continuing to strengthen the case against any O stock, it is important to also to follow
other non-genetic lines of investigation, specifically by means of age data analyses similar to those conducted by
Kitakado and Maeda (2016). Preliminary analyses by these authors suggested that the single stock scenario seems
consistent with the age data.

12

In discussing the paper by Kitakado and Maeda (2016), the JARPNII final review workshop noted that ‘if the
Implementation Simulation Trials for the western North Pacific common minke whales are to be revised in the
future, the age data should be included in the conditioning process’ (IWC, 2016c). To achieve this aim theattainment of new age data from animals in coastal and offshore waters in the Pacific side of Japan will be required.
The need to include age data as agreed by the IWC SC in adopting the JARPNII final review workshop reportstrengthens the justification for continued sampling. Annex 11 provides further and more detailed reasons for thejustification for acquisition of further age data.
iv)

Sighting data for improved abundance estimates for the O stock common minke whale

A series of abundance estimate for O stock common minke whales are available from JARPN and JARPNII.
However, as pointed out in the research design under the assumption iii) of 2.1.1.1, sighting surveys designed todecrease the additional variance are required i.e. different sub-areas covered in the same time period. Systematicsighting survey under the Line Transect Method as well as genetic mark-recapture methods are proposed toaddress this research topic.
2.1.1.3 Secondary Objectives
The research elements identified in section 2.1.1.2 are reflected in the Secondary Objectives of Primary Objective
I below:Secondary Objective I (i): Investigate the spatial and temporal occurrence of J stock common minke
whales around Japan, by sex, age and reproductive status

Secondary Objective I (ii): Estimate the abundance of the J and O stocks in coastal waters of JapanSecondary Objective I (iii): Verify that there is no structure in the O stock common minke whale in the
Pacific side of JapanSecondary Objective I (iv): Improve RMP trials by incorporating age data in their conditioning

With regard to Secondary Objective I (iii), the proponents consider that all the recommendations from the
JARPNII mid-term review workshop were addressed, and that results of the refined analyses following thoserecommendations were presented to the JARPNII final review workshop (IWC, 2016c). None of these refined
analyses support the existence of a coastal Ow stock. Therefore the proponents consider Stock Hypothesis C to
be implausible. The further genetics work proposed under this Secondary Objective (e.g. kinship analyses) is
simply routine monitoring to check for no change in a current position that is already clear, and is proposed only
because genetics information also becomes available, incidental to the necessary collection of future age data
under the program (see below).
As detailed later in this proposal, a feasibility study on satellite tracking will be conducted on baleen whale species.
In the case of the common minke whale, trials will be conducted to address the question of movement across theboundaries separating sub-areas 7CS and 7CN from offshore sub areas. Under the single O stock structure
hypothesis, movement is to be expected across those boundaries. Also if tracking trials are conducted late in thefeeding season, it could be possible to investigate the migration routes of common minke whales to lower latitudes
areas.
With regard to Secondary Objective I (iv), the proponents wish to emphasize here the recommendation from the
JARPNII final review workshop endorsed by the IWC SC:‘Thus, if the Implementation Simulation Trials for thewestern North Pacific minke whales are to be revised in the future, the age data should be included in theconditioning process’, and they understand the IWC SC to have confirmed the fundamental importance of the useof age data in conditioning trials.
The main justification for lethal sampling is to obtain earplugs for age determination and biological samples fordetermination of reproductive status (Secondary Objectives I (i) and I (iv)), and the sampling survey for common
minke whale in sub-areas 11 and 7-9 is designed with this aim in mind.
Details of survey design, area and field and analytical methods are provided in section 3 and annexes.

132.1.2

Primary Objective II

2.1.2.1 Contribution to the RMP/IST for North Pacific sei whale
The North Pacific sei whale has not been the subject of previous RMP Implementation, however the IWC SC
started an in-depth assessment of this species in 2015. While a substantial amount of scientific information on sei
whales has been accumulated in recent years through research programs such as the JARPNII in the western North
Pacific and the IWC-POWER (Pacific Ocean Whale and Ecosystem Research) in the central and eastern North
Pacific, these data have not been yet used in population assessment models in the context of the RMP
Implementation.
Data required for a RMP Implementation
A RMP Implementation including the Implementation Simulation Trials (ISTs) requires several types of
information for the management of whales, including:






Time series of past catches by area
Time series of abundance estimates (and their CVs) by area
Hypotheses of stock structure (for trial structure, definition of target areas, variants of the Catch Limit
Algorithm, CLA)
Biological information on natural mortality, production rate, maturity and recruitment relationship, etc.
(for trail structure)
Stochastic variation of recruitment in particular, amongst other factors (for trial structure)

The RMP was designed to be robust to the uncertainty in biological information reflecting the failure of its
predecessor (NMP). In this regard, the CLA requires only historical catch data and abundance estimates (withtheir CV) when it calculates catch limits. However, the overall RMP exercise has changed into a data-demanding
process so that it cannot be implemented without a wide range of biological/ecological information during its
RMP Implementation including the ISTs process in order to narrow down the scenarios to be considered. Hence,in order to conduct an RMP Implementation, a variety of biological/ecological data is actually required. It should
be noted here that the most conservative whaling scenarios are selected as a precautionary approach, when there
is uncertainty in the biological and ecological information required in the RMP ISTs such as stock structure andreproductive parameters (uncertainty is related to a limited amount of data, which in turn implies less precision in
the parameters). In other words, further biological and ecological information will contribute to reduction of
uncertainty, and therefore less conservative whaling scenarios can be used, which usually provide larger catch
limits. Additional data will improve conservation as well as increase catch limit. This will be in line with one of
the IWC’s management objectives for commercial whaling under the RMP, which is ‘making possible the highest
yield from the stock’ (IWC, 1990).
2.1.2.2 Estimation of biological and ecological parameters for the application of the RMP to the North Pacificsei whale
As mentioned above, the IWC SC agrees that future ISTs should use age-structured models (IWC, 2016c). Under
Primary Objective II, not only abundance estimates and hypotheses of the stock structure but also certain
biological and ecological parameters are key for the specification of trials, and therefore narrowing the reasonable
range of their values and hypotheses is an important issue for calculating reasonable catch limits and thus ensuring
the sound management of whaling once paragraph 10 (e) of the Schedule is amended. Using this basic idea, the
IWC SC could optimize the selection amongst RMP variants.
Abundance data
Some international and national surveys have been conducted in the North Pacific for estimating whale population
sizes and monitoring their population trends. Particularly, the POWER surveys under the auspices of the IWC
have provided valuable information on the distribution and abundance of sei whales in the central and eastern
North Pacific in summer. Also, the Japanese dedicated sighting surveys in the western North Pacific under
JARPNII contributed information on abundance estimates in particular areas of the western North Pacific. A
summary of the sighting datasets to be used in the North Pacific sei whale in-depth assessment by the IWC SC
was summarized in IWC (2016d).

14Biological and ecological parameters
For the North Pacific sei whales, in addition to the abundance estimates mentioned above, several types of
biological data have become available since the commercial whaling era and from the JARPNII surveys. In
particular, the technical procedures for determination of age and maturity status were developed over years. Theseadvances could then give key information for inferring population dynamics of the sei whales as in the case of
Antarctic minke whale, where both the abundance estimates and catch-at-age data were utilised (Punt et al., 2014).
Age-structured dynamics models can be applied to North Pacific sei whales and the biological parameters
including those that will be estimated from data collected by NEWREP-NP will contribute to the trials structurein the RMP ISTs.
Stock structure
A summary of the studies and hypothesis on stock structure in the North Pacific sei whale is presented under
section 4.2 below. For the in-depth assessment the IWC SC agreed to proceed with two alternative stock structure
hypotheses:i)ii)

A single stock in the entire North Pacific as proposed in (Kanda et al., 2015a)
A five-stock hypothesis proposed in (Mizroch et al., 2015):-

Japan coastal;
North Pacific pelagic;
Aleutian Islands and Gulf of Alaska;
Eastern North Pacific migratory; andSouthern North American coastal stock (coastal California)

At the 2016 IWC SC meeting the Committee agreed that the genetic and mark-recapture data currently available
are consistent with a single stock of sei whales in the pelagic region of the North Pacific (IWC, 2016b). Therefore
NEWREP-NP will focus on the single North Pacific pelagic stock.
Under the NEWREP-NP priority will be given to refine the single pelagic stock hypothesis through satellite
tracking experiments to further study the movement of whales within the feeding ground as well possible
migratory routes from feeding areas to breeding areas in low latitudes. Genetic analyses will be also conducted.
2.1.2.3

Specification of models

Conditioning and development of trial structures are a part of the objectives of the NEWREP-NP. For conditioning
and development of trial structures for the RMP/IST, age/sex-structured models will be used, as in previous
RMP/ISTs. In order to help this, estimation of biological and ecological parameters such as a natural mortality andcarrying capacity in the age/sex-structured model will be conducted based on statistical catch-at-age analyses(SCAA) using existing data and newly obtained data under the NEWREP-NP program.
2.1.2.4

Detailed basis for data/sample needs

As described above, the RMP is a management procedure which guarantees sustainability with safe levels of catch
limits over a period of 100 years and more (IWC, 2012a). While considerable data and information are alreadyavailable through past research, more refined information over a longer period is necessary for optimizing the
RMP Implementation (see Table 1).
Therefore, the Primary Objective II aims at providing required data for application of the ISTs and contribute to
the assessment process under the RMP Implementation. Furthermore, the actual catch limits which may be used
for the resumption of commercial whaling will be derived from the achievement of this research objective. The
specific data and samples required in this proposed program for the Primary Objective II are amplified insubsequent sections.

15

Table 1. Current data and future research needs for North Pacific sei whale in the context of Primary Objective II.

1)

Abundance

Existing values andknowledge

Problems/pending issues

IWC-POWER

IWC-POWER estimates become
subject to the “phase-out rule”

JARPN/JARPNII

 Usable for conditioning purpose Usable for CLA in trials
 No estimates agreed for use in
the actual CLA as yet

 Need recent information on thenatural mortality
 Need to monitor any possible
changes in recruitment rate

2)

Biological andecologicalparameters

MSYR(1+)：1～4％(revised range given bymeta-analysis)3)

Stock structure

Single pelagic stock
assumed

4)

Specification of
RMP/IST

Possible use of an SCAA
model

Aspects to potentially be clarified
with past data and new data under
the proposed research plan Obtain new series of abundance
estimates from surveys with IWC
oversight. Repeated calculation ofabundance estimates for study areas
will be helpful to draw information
on inter-annual variation of
distribution (better estimate ofadditional variance andidentification of factors affecting
the variation).These further
abundance estimates are required
for application of the CLA.
(Secondary Objective II (i))
Improvement of precision of
biological/ecological information
 On natural mortality
 Further monitoring of the changes
in the recruitment rate
(Secondary Objective II (ii))

Further investigation on movement
within feeding grounds and between
feeding grounds and breeding grounds(Secondary Objective II (iii))



Need to set a plausible rangeof biological parameters
Need to specify futurechanges in recruitment rate Conditioning of age-/sex-structured
model for base case trials
 The trials structure can also be
considered with linkage between
recruitment and environmental
changes

2.1.2.5 Secondary Objectives
As shown in Table 1, there are several research items necessary to achieve the Primary Objective II. For thisreason, this proposed plan also identifies four Secondary Objectives for sei whales as follows:Secondary Objective II (i): Abundance estimates for North Pacific sei whale taking account of theadditional varianceSecondary Objective II (ii): Estimation of biological and ecological parameters in North Pacific sei
whales for RMP Implementation

Secondary Objective II (iii): Study of the pattern of movement of whales of the ‘pelagic stock’ within
the feeding grounds and between feeding and breeding groundsSecondary Objective II (iv): Specification of RMP ISTs for North Pacific sei whale

With regard to Secondary Objective II (iii) and as detailed later in this proposal, a feasibility study for satellite
tracking will be conducted on baleen whale species. In the case of the sei whale, trials will be conducted to address
the question of movement to the north of the tentative limit of the ‘pelagic stock’ distribution under one of thestock structure hypotheses (see item 4.2) and to the south of the tentative limit. The former will be conducted earlyin the feeding season and the experiment will be useful to understand the northern distribution of the stock and at
the same time the plausibility of some proposed stocks under one of the stock structure hypotheses can be assessed.

16

The latter will be conducted late in the feeding season and the experiment will be useful to investigate migratoryroutes of whales to lower latitude areas.
The main justification for lethal sampling is the attainment of earplugs for age determination, and biologicalsamples for determination of reproductive status (Secondary Objective II (ii)), and the sampling survey for sei
whale in offshore areas is designed with such an aim in mind.
Details on sampling design, sampling areas and field and analytical methodologies are provided in section 3 andannexes.
2.2 Ancillary Objectives
2.2.1 Ancillary Objective I
Investigation of the influence of environmental changes on whale stocks
There have been many studies on regime shift of marine ecosystem in the western North Pacific around 1925,
1947, 1977 and 1998 (King, 2005; Overland et al., 2008). Possible changes in the geographical and temporal
distribution of baleen whale stocks, as a response to environmental changes, will affect the interpretation ofabundance estimates and trends based on systematic sighting surveys. Abundance estimates and trends areimportant pieces of information for management under the RMP. Ecological changes related to minke and sei
whales and possible effects on management under the RMP should be further investigated through theexamination of data on distribution and abundance, whale stomach contents and nutritional conditions, andenvironmental variables. Ecological changes are occurring in recent years as indicated by changes in prey species
compositions of common minke and sei whales in JARPNII (Konishi, 2016). It should be noted that similarchanges in prey species compositions of common minke whales were observed in previous regime shift(Kasamatsu and Tanaka, 1992). There is a need for continuous monitoring to understand the effect ofenvironmental changes on whale stocks.
The proponents stress that the original aim of this Ancillary Objective is to contribute to the understanding of theimplications of environmental change in terms of whale stock management, rather than detection of a major
environment change itself. The proponents do recognize that, based on current scientific knowledge, it is difficult
to predict whether a major environmental change (categorized as a ‘regime shift’) would occur within the proposed
research period of NEWREP-NP.
The proponents will monitor spatial distribution, prey species compositions and body conditions of target whales
and they will investigate potential influential factors (e.g. available prey), if temporal changes (which could
ultimately be related to major change) in whales are observed. Such monitoring and investigation will contributeto future in-depth assessment (IA) of whales as in the case of Antarctic minke whales.
This Ancillary Objective will be investigated using data obtained through surveys designed for other Primary andSecondary Objectives (related to age and reproductive data).
Details on field and analytical methodologies are provided in section 3 and annexes.
2.2.2 Ancillary Objective II
Examination of the effects of pollutants on whales
In 1980, the Special Scientific Committee Working Group on Management Procedures identified that
“Management measures should take into account the effect on whale stocks of environmental changes due either
to natural causes or to human activities” (IWC, 1981) as one of the principles for whale management.
In response to this suggestion, the JARPNII conducted environmental studies under one of its objectives(‘Monitoring environmental pollutants in cetaceans and the marine ecosystem’). It was observed that PCB levels
in common minke whales (Yasunaga and Fujise, 2016a) and total mercury (Hg) levels in common minke, Bryde’s
and sei whales (Yasunaga and Fujise, 2016b), did not change during the research period, and were sufficiently
under their thresholds in other whale species. It was suggested that the adverse effects of pollutants such as PCB
and total Hg to the whale health could be low in the area. On the other hand, some areas for further research wereidentified: i) examination of possible adverse effects of pollutants with adjustment for confounding factors such17

as nutritional condition and ages; ii) species differences of sensitivity and response to pollutants; and iii)
investigate of adverse effects of novel compounds.
These three research items will be addressed under this Ancillary Objective. This Ancillary Objective will be
investigated using data obtained through surveys designed for other Primary and Secondary Objectives (related
to age and reproductive data).
Details on field and analytical methodologies are provided in section 3 and annexes.
2.2.3 Ancillary Objective III
Study of distribution, movement and stock structure of large whales with particular emphasis on blue and North
Pacific right whales
JARPN and JARPNII were useful platforms for the collection of biopsy and photo-id data from large whales,
included the depleted North Pacific right whale. NEWREP-NP will be also a platform for further collection of
those kinds of data, particularly on blue and right whales. On blue whales the IWC SC recommended the analysisof biopsy samples from the central and western North Pacific for comparison with genetic data from the eastern
North Pacific population (IWC, 2016e). NEWREP-NP will contribute with additional biopsy and photo-id data
for such purpose.
The IWC SC has welcomed the research on distribution, movement and stock structure of North Pacific rightwhales (IWC, 2016e). The only genetic study on stock structure was based on samples collected in the eastern
North Pacific (LeDuc et al., 2012). The available biopsy samples from JARPNII and those to be obtained by
NEWREP-NP will allow the genetic comparison between eastern and western North Pacific right whales.
As detailed later in this proposal, a feasibility study on satellite tracking will be conducted on large whale species.
Trials will be conducted on large whale species, included the North Pacific right and blue whales, on an
opportunistic basis.
Details on field and analytical methodologies are provided in section 3 and annexes.
2.3 Relationships amongst Primary Objectives
In both Primary Objectives the research topic is the optimization in the application of the RMP on two different
species in the western North Pacific. However, the approaches to achieve such objectives differ among the species
concerned. In the case of the common minke whale, RMP Implementation has been applied previously so thefocus here is to identify the causes for the unreasonable results from the 2013 RMP Implementation and to identify
data and samples required for a more efficient and realistic application of the RMP on this whale resource. In thecase of the sei whales there is no previous RMP Implementation and the focus here is, by considering theexperience with the common minke whale, make use of available as well new collected data and samples as input
for the RMP Implementation. Of particular importance is the use of biological data during the conditioning, which
again has the potential to optimize the use of the RMP on this whale resource by calculating a larger catch limits
without increasing the depletion risk of the stock.
2.4 Requirements of lethal sampling, non-lethal methods or a combination of both for each Primary Objective(see also section 3.1.1)
2.4.1 Primary Objective ISecondary Objective I (i): Investigate the spatial and temporal occurrence of J stock common minke
whales around Japan, by sex, age and reproductive status

Non-lethal (sighting data for distribution analysis); and lethal (tissues for genetic and morphological analyses,
earplug and eye lens for age determination, ovaries and testis for sexual maturity determination; bodymeasurements).
‘Tissues for genetic analyses’ is listed here and below under the category ‘lethal’. As explained in section 3,
genetic analyses are possible based on tissues obtained by biopsy samples (non-lethal) although the feasibility ofbiopsy sampling varies among whale species (see details in section 3). Since age data are definitively required18

(see section 3), and can be obtained only by lethal methods, genetic data become co-incidentally available fromsuch samples. Therefore, the question of whether biopsy sampling in practical does not require further
consideration.
Secondary Objective I (ii): Estimate the abundance of the J and O stocks in coastal waters of Japan

Non-lethal (sighting data for abundance estimates); and lethal (tissues from fetus and mother for genetic analyseson ‘mark-recapture’).
Secondary Objective I (iii): Verify that there is no structure in the O stock common minke whale in the
Pacific side of Japan

Non-lethal (satellite tracking for studies on movement and distribution of whales); and lethal (tissues for genetic
analyses on kinship).
Secondary Objective I (iv): Improve RMP trials by incorporating age data in their conditioning

Non-lethal (sighting data for abundance estimates); and lethal (earplug and eye lens for age determination; ovaries
and testis for sexual maturity determination; body measurements).

See details of field and analytical methods related to the four Secondary Objectives under section 3 and annexes.
2.4.2 Primary Objective IISecondary Objective II (i): Abundance estimates for North Pacific sei whales taking account additionalvariance

Non-lethal (sighting data for abundance estimates; environmental data as covariates in spatial modeling).
Secondary Objective II (ii): Estimation of biological and ecological parameters in North Pacific sei
whales for RMP Implementation

Non-lethal (sighting data for abundance estimates); and lethal (earplug and eye lens for age determination; ovaries
and testis for sexual maturity determination; body measurements).
Secondary Objective II (iii): Study of the pattern of movement of whales of the ‘pelagic stock’ within thefeeding grounds and between feeding and breeding grounds

Non-lethal (satellite tracking for studies on movement and distribution); and lethal (tissues for genetic analyses).


Secondary Objective II (iv): Specification of RMP ISTs for North Pacific sei whales

Non-lethal and lethal information of the three items above is required.
See details of field and analytical methods related to the five Secondary Objectives under section 3 and annexes.
2.5 Value of each Primary and Ancillary ObjectiveImprovement in the conservation and management of whale stocks--

Collection and analyses of relevant data and samples (abundance, stock structure, biologicalparameters) will optimize the application of the RMP on the western North Pacific common minke
and North Pacific sei whales.
The JARPNII final review workshop, endorsed by the IWC SC, noted that ‘if the ISTs for the western
North Pacific common minke whales are to be revised in the future, the age data should be include
in the conditioning process’ (IWC, 2016c).

19

-

-

-



Improvement in the conservation and management of other living marine resources or the ecosystem ofwhich the whale stocks are an integral part-

Those data and samples will contribute to the next Implementation Review in the case of the western
North Pacific common minke whales, and the completion of CA and the carrying out of
Implementation in the case of sei whale.
Information on stock structure (biopsy) and abundance trends (sighting surveys) in large baleen
whales including the North Pacific right and blue whales, will contribute to understand the patternof recovery of those whales after past commercial whaling. These works have been welcomed andrecommended by the IWC SC (IWC, 2016c).
Research on the health of whales is directly related to whale conservation purposes, and studies inthis field have been recommended by the IWC SC (IWC, 1995).

Under the Ancillary Objective I on environmental change, several kinds of information will becollected including prey species in the whale stomach, prey species in the research area andenvironmental data. This will contribute to the understanding of the interaction between whales andseveral other components of the ecosystem, which in turn would contribute to the ecosystemapproach of whale resource management.

Testing of hypotheses not directly related to the management of living resources-

Information will be provided to characterize the oceanographic structure of the research area.
Oceanographic information will provide insight on whether or not environmental changes are
occurring in the research area, particularly in the context of global warming.
There is a great interest in the IWC SC to investigate the effects of marine debris on cetaceans anda workshop focused on this subject has taken place (e.g. IWC, 2014c).

2.6 JARPN/JARPNII scientific outputs and relationship with NEWREP-NP
JARPN was started in 1994 and was completed in 1999. The IWC SC conducted a review workshop of JARPN
in 2000 (IWC, 2001). The JARPNII started in 2000 and 2001 as a two-year feasibility survey. The full program
started in 2002 and the first six-year period was completed in 2007. The second six-year period was completed in
2013. Data and results from the JARPNII were reviewed in two workshops, a mid-term review workshop basedon the samples and data collected in the first period (IWC, 2010) and a final review based on samples and datacollected by JARPN and JARPNII until 2013 (some data were available until 2014) (IWC, 2016c). Results of thethree last surveys of JARPNII (2014-2016) that became available after the final review will be reviewed during
the review workshop for NEWREP-NP in January/February 2017.
The main scientific outputs of JARPN/JARPNII are summarized in Annex 5, by research objective of JARPNII.
The JARPNII final review workshop welcomed the scientific contribution of JARPN/JARPNII. At the same time
it identified areas where further work was required, and provided useful suggestions and recommendations torefine the analyses.
Some of the main outputs of JARPN/JARPNII, including the catch at age data to refine RMP/ISTs, will be used
for the future RMP Implementation, together with the new data to be collected by NEWREP-NP, thereby the
future RMP Implementation will be benefited from long-term high quality data.
It should be clarified here that NEWREP-NP is not an extension of JARPN/JARPNII as NEWREP-NP has
different research objectives and a different focus on the issue of environmental change. However the proponents
will continue refining their JARPNII results following the recommendations from the JARPNII final review
workshop and the SC (see Table 24 in IWC, 2016f), and results will be presented to the annual meeting of the
IWC SC. It should also be noted that the NEWREP-NP has been developed using relevant data and results ofscientific work by scientists from all over the world, including but not limited to JARPN and JARPNII.
The main focus of NEWREP-NP is on the optimization of the application of the RMP on common minke and sei
whales. The proponents considered that the priority to include Bryde’s whale is low at least at this stage because
the RMP Implementation the IWC SC conducted on this species in the North Pacific has produced resultscompatible with other information, unlike the case of the common minke whale (see IWC, 2008). As distinct from20the situation for JARPNII where its main scope reflected long-term research need, the proponents see a shorterterm need to narrow the scope of the research especially focusing on common minke whale and sei whale. As
regards the ecosystem the proponent’s primary short-term goal is to contribute to the understanding of theimplication of the environmental changes in terms of whale stock management, and thereby also assist in thedevelopment of ecosystem models by other researchers and research institutions.

3.

METHODS TO ADDRESS OBJECTIVES

3.1 Primary Objective I
3.1.1 Field methods
Species, number, time frame, area

For Primary Objective I, the western North Pacific common minke whale will be the target species and the study
areas will be i) the Sea of Japan side of Japan; ii) north of Hokkaido (sub-area 11) and Pacific side of Japan (subareas 7-9). The Sea of Japan will be the main target area for dedicated sighting surveys for abundance estimate
purposes. North of Hokkaido (sub-area 11) and Pacific side of Japan (sub-area 7-9) will be the main target areafor lethal sampling. Sub-area 11 will be one of the target areas for the research on distribution and temporal trend
in mixing proportion of J stock animals. Sub-areas 7, 8 and 9 will be the main target area for verifying the single
structure of the O stock and for improving the RMP through the use of age data. The research area will be surveyed
between April and October, which is the migratory season of common minke whale around Japan.
The annual sample size for common minke whales in sub-area 11 for the first 6 years is 47 animals, which wasestimated based on Secondary Objective I (i) (see analytical details in section 3.1.3). The annual sample size forcommon minke whales in sub-areas 7-9 in the Pacific side of Japan is 123 animals, which was estimated based on
Secondary Objective I (iv) (see analytical details in section 3.1.3).
The research period under NEWREP-NP is planned to be 12 years with a midterm review after the first six years
in order to evaluate progress in achieving research objectives, and revise the research program if necessary. As
this Primary Objective is associated with the application of the RMP, the six-year period is in line with theannotations to the RMP, which states that ‘An Implementation Review for a species and Region should normallybe scheduled no later than six years since the completion of the previous Implementation (Review)’ (IWC, 2012a).
The detailed timeline of research activities in NEWREP-NP is presented in section 3.1.4.


Sampling protocol for lethal aspects of the proposal

Annex 6 shows the whale sampling design for Primary Objective I (common minke whale). Basically four small
catcher boats will be involved in the survey (see Annex 21), and they will depart the port in the morning andreturn the port every night. A land-based operation system will be incorporated for whale sampling in the coastal
areas. In order to increase the geographical coverage in sub-areas 7CS, 7CN and 11, whales will be sampled indifferent ports regardless of whether or not those ports have a land station to conduct the biological surveys. The
whales sampled will be transported by tracks from the port to the nearest land station for biological survey. Nisshin
Maru may be used as a research oceanic station when necessary.
Land stations with a research head office will be established in Kushiro (sub-area 7CN), Ayukawa (sub-area
7CSW) and Abashiri (sub-area 11). Ayukawa and Kushiro land stations will be switched depending on the
migration of the common minke whale: e.g. Ayukawa from spring to summer and Kushiro from summer to autumn.
Abashiri will be surveyed in different seasons so that data on seasonal changes in distribution and mixing rate of
the J stock can be obtained.
The sampling procedure will be designed taking into account operational capacity, ability, and arrangements ofthe small boats, and will be different from the random sampling procedures adopted by the offshore component
lead by Nisshin Maru. All whales sampled will be transported to a land station and biologically examined by ateam of scientists.
Details of the sampling procedure are given in Annex 6. In particular Tables 1 and 2 of this annex shows thenumber of samples of common minke whale by month, year and sub-area collected by JARPN/JARPNII in the21period 1994-2016, and the expected samples by NEWREP-NP in the period 2017-2022 (including offshore subareas), respectively.
Sampling in sub-areas 7WR, 7E, 8 and 9 will be carried out by the sampling and sighting vessels attached to theresearch base Nisshin Maru, which will be also engaged in sampling of sei whales under Primary Objective II.
Sampling protocol for minke and sei whales in sub-areas 7WR, 7E, 8 and 9 is described in Annex 12.
Assessment of why non-lethal methods, methods associated with any ongoing commercial whaling, or
analyses of past data have been considered to be insufficient

Biological data, including age data and sexual maturity, will contribute the conditioning in the RMP
Implementation, which includes the ISTs. In this regard, obtaining the latest biological data is important for the
RMP Implementation as more refined information over a longer period is necessary for optimizing the RMP
Implementation. Secondary Objectives most relevant to this point are the following:
Secondary Objective I (i): Investigate the spatial and temporal occurrence of J stock common minke
whales around Japan, by sex, age and reproductive status
Secondary Objective I (iv): Improve RMP trials by incorporating age data in their conditioning
The data to be obtained by lethal sampling of common minke whales under these objectives are the age (by reading
earplugs and racemization method), sexual maturity (by examining ovaries and testis samples), body length (bymeasurements of body on board of the vessels) and tissues for genetic analyses (regarding to genetics see also
section 2.4.1).
Age data
Age data are key information for the work under these two objectives. There is currently no satisfactory non-lethal
method to obtain age data. In the context of developing a new whale research plan for the Antarctic waters, theproponents critically reviewed whether the age is indeed unobtainable by methods other than lethal sampling.
After giving serious consideration to the information summarized below, the conclusion was reached that age dataat the annual scale can be obtained only through lethal sampling methods (see details in GOJ, 2015). Thisconclusion would apply to other baleen whales including those in the western North Pacific, and not only to
Antarctic minke whales.
DNA methylation approach (DNA-M) was recently developed and applied to humpback whales for the aim ofage determination in this species (Polanowski et al., 2014). In discussing and evaluating the DNA-M technique
the NEWREP-A review workshop noted that ‘the technique does not provide the chronological age of theindividual but rather a physiological age that can be used as a proxy for chronological age’ and that ‘physiologicaland metabolic differences between species, means that the method will need to be calibrated for each species’.
Furthermore the workshop noted that ‘because the conditions in which individual grow may also affect their
physiological age and metabolism, it is possible that the calibration slopes and variances of the DNA-M technique
may not be interchangeable between populations found in different areas or even between different periods within
the same population, i.e. the technique may require calibration by species, population and period’. Finally theworkshop stated that ‘given the novelty of the technique and the fact that it has only been applied to a single
population of a single species of cetacean, there is as yet no experience on this regard’ (IWC, 2015c).
In addition, several research initiatives were proposed during the 2016 IWC SC meting to evaluate further theutility of the DNA-M technique, among others that, in addition to skin, connective tissue and the lipid filled fat
cells (usually obtained by biopsy sampling) should be investigated. This, in light of the results of Horvath (2013)that the correlation between chronological age and methylation profiles varies a great deal among different tissues(IWC, 2016f).
Recent investigations have indicated that the precision of DNA-M-based recruitment estimates from SCAA are
much worse that those obtained from earplug-based readings, with DNA-M-based results hardly better than thosein the absence of any age data at all (Kitakado, 2016). Hence at this juncture, indications are that the non-lethal
DNA-M approach cannot provide ageing information as precise as earplug-based age readings and that the former
method, unlike the latter, cannot therefore meaningfully improve results from analyses related to assessment andmanagement recommendations.

22This has led the proponents to the conclusion that the DNA-based methods would not provide usefully informative
results at this stage, and that lethal sampling is required for the work under these two objectives of NEWREP-NP.
Furthermore, Yasunaga et al. (2017b) reports on the difficulty of obtaining biopsy samples from common minke
whales as a result of the biopsy sampling experiments conducted between 2014 and 2016 under the JARPN II.
The proponents have started a feasibility study on DNA-M in the Antarctic minke whale as part of the NEWREPA program (plan presented to the IWC SC in 2015) to see whether the information content of the results might be
improved, and they will carry out similar studies on the common minke and sei whales in the North Pacific as partof the NEWREP-NP program based on the results of the studies on Antarctic minke whale and additional
recommendations from the NEWREP-NP review workshop (see Figure 2). Progress of the feasibility study on
Antarctic minke whale will be presented to the 2017 IWC SC meeting while a final report is planned for the 2018
IWC SC meeting. A final assessment of the feasibility of non-lethal techniques will be carried out during the midterm review after the first six years, including an evaluation of possible modification of sample size of the lethal
component of the program, on a whole-program basis. The results of the feasibility study on age determination
based on DNA-M will be relevant here.
Sexual maturity
Determination of sexual maturity, which requires lethal sampling, is also important for the work under these two
objectives because age at sexual maturity affects the reproductivity of the stock that is a key parameter for stock
dynamics. The proponents reviewed the literature to investigate whether or not sexual maturity of common minke
whales can be determined with the use of non-lethal techniques. An attempt was made to assess the reproductive
status of North Atlantic right whales using fecal hormone metabolites (Rolland et al., 2005). The authors
concluded that ‘the analysis of fecal hormone metabolite levels in combination with life history data fromphotographically identified whales shows that the technique can be used to determine gender, determine
pregnancy and lactation, and to assess age at sexual maturity in right whales’. It should be noted that although
adult resting female right whales had higher levels of fecal oestrogens and progestins than juvenile females, thedifferences were not significant. Apart from this, there are two main reasons of why this technique cannot be used
to determine reproductive status in the western North Pacific common minke whale. The first is that theconclusions of the study on right whale were based on a combination of chemical analyses of feces and biologicalinformation of photo-identified whales. It is known that photo-identification is not an appropriate technique forcommon minke whale because of its large abundance. Also, unlike the right and humpback whales, there is no
typical external morphological character useful for individual identification in the common minke whale. The
second reason is that the probability of locating fecal samples from common minke in the field is very low (seeYasunaga et al., 2017a).
There are another two studies that determined the pregnancy status of cetaceans based on measurement ofprogesterone concentration in blubber by radioimmuno-assay (blubber can be obtained by biopsy sampling). The
first study concluded that blubber progesterone concentrations might be used to determine pregnancy status in
free-ranging North Atlantic common minke whales (Mansour et al., 2002). The second study concluded that the
blubber progesterone concentrations can distinguish pregnant from non-pregnant mature and immature ones inthree species of dolphins. However the technique cannot differentiate pregnancy stage (Kellar et al., 2006). The
technique appears to provide consistent results through several cetacean species examined, however it can provide
information on pregnancy only. It cannot distinguish among non-pregnant mature female, immature females,mature males and immature males.
This has led the proponents to a conclusion that the determination of sexual maturity requires lethal sampling for
the work under these two objectives of NEWREP-NP. However to further analyze the feasibility of non-lethal
technique to determine sexual maturity in whales, the proponents will conduct feasibility studies on hormones inblubber and plasma, similar to the studies being conducted on Antarctic minke whale (see Figure 2), following
the experience of the studies under the Icelandic whale research program under special permit (IWC, 2014d).
Progress of the feasibility study on Antarctic minke whale will be presented to the 2017 IWC SC meeting whilea final report is planned for the 2018 IWC SC meeting. A final assessment of the feasibility of non-lethal
techniques will be carried out during the mid-term review after the first six years.
Body length
Body length is important because it has a potential to be used as an indicator of age. Accurate measurement of thewhale body length can be taken only through lethal sampling. After the review of relevant literature (Best, 1984;
Dawson et al., 1995; Jaquet, 2006) it is concluded that the precision of measurements obtained from shipboard
techniques are insufficiently accurate.

23

Tissues for genetic analysis
Genetic analyses are possible based on tissues obtained by biopsy sampling. Tissue samples have a potential to
give indicators of biological data lethally obtained as tissue samples provide basis for other potential non-lethal
methods to determine age such as DNA methylation approach (DNA-M). It should be noted, however, the utilityof such indicators needs to be examined in relation to research objectives. The feasibility of biopsy sampling
varies among whale species. Yasunaga et al. (2017a) summarized the results of the biopsy sampling experiments
conducted between 2014 and 2016 under the JARPNII. There was more success in obtaining biopsy samples in
the case of Bryde’s and sei whales than in the case of common minke whales.
Mogoe et al. (2016) proposed a four-step criterion for evaluating the utility of a new non-lethal technique on
whales, and the success of obtaining biopsy samples from a whale species is just one of those steps (see details in
Mogoe et al., 2016).
In any case the genetic analyses under the Secondary Objective I (i) would be conducted jointly with analyses of
biological data such as age and sexual maturity, which require lethal sampling, so the question of whether biopsy
sampling in practical does not require further consideration (see also section 2.4.1).
Under NEWREP-NP additional feasibility studies on technical aspects of biopsy sampling in common minke
whales will be conducted (Figure 2), and results will be presented to future IWC SC meetings.
Utility of historical data and samples
There are some data on sexual maturity and body length of common minke whale from the past commercial
whaling. Although there are also biological and genetic data on common minke whale from previous JARPN and
JARPNII, the analyses of those data alone are not sufficient for the two objectives above because the future stock
dynamics, which is a key in RMP, can be best projected by incorporating latest biological data such as catch atage in conditioning and development of trial structures for RMP Implementation. The new biological samples tobe collected by NEWREP-NP will be examined together with the available historical data to investigate temporal
trends in the parameters involved. Ongoing changes occurring in common minke whale need to be detected
through collection of relevant data on a yearly basis in order that the two objectives are achieved. This inevitably
needs new samples under this program.

24

Earplug, racemization of eye lensI(i), I(iv), II(ii)

Age determination?

DNA methylation analysis (biopsy samples)1

Analysis of testis and ovaries
Sexual maturity

Field experimental
surveysI(i), I(iv), II(ii)?

Examination of hormone in blubber and plasma (biopsy)
samples)?

Biopsy sampling (minke whale)2?

Satellite tagging

I(i), I(iv), II(ii), II(iii), Ancillary I

Stomach contents/ stable isotope (baleen plate)
Estimation of preycomposition andconsumption

Ancillary I?

Stable isotopes (biopsy samples)?

Fatty acids (biopsy samples)

Blubber thickness, girth
Nutritional
conditions

Ancillary I
Lipid content % of blubber?

Lipid content % of blubber (biopsy sampling)1

Currently a feasibility study of DNA methylation is being conducted on Antarctic minke whale. Depending on
the results (expected by 2018), new feasibility studies could start for western North Pacific common minke and North
Pacific sei whales, if so they will take into consideration the additional recommendations from the NEWREP-NP review
workshop.
2
Statistical analyses based on data collected in 2014-16 suggested that biopsy sampling of common minke whale is not
feasible in practice (Yasunaga et al., 2017a; b). However some additional studies on technical aspects of the biopsy sampling
equipment will be conducted under NEWREP-NP, under the advice of foreign experts.
whales.
Figure 2. Useand evaluation of new non-lethal techniques (field and analytical) on common minke and sei
whales in NEWREP-NP, and relation to primary and ancillary objectives (white: lethal methods; blue: nonlethal methods that will be evaluated in this research). Experiments on new non-lethal techniques are designedby taking technical recommendations from the NEWREP-NP review workshop into consideration.

Sampling protocol for established non-lethal techniques

Sighting survey method
Sighting surveys are to be conducted by the Line Transect Method and the survey protocols will follow theRequirements and Guidelines for Conducting Surveys and Analyzing Data within the Revised Management
Scheme (IWC, 2012b) so that they will be conducted under the oversight of the IWC SC. Sighting protocols are
the same as those used in IWC-POWER surveys. Considering the recommendations from the NEWREP-A review
workshop on sighting surveys (IWC, 2016h), the proponents will consider the following: i) survey design andmethods will be reviewed taking into account previous sighting surveys and spatial model developments; ii) they
will work closely with the IWC SC before finalizing surveys approaches; and iii) they will also ensure that future
survey plans submitted to the IWC SC fully follow the guidelines for such surveys, including the incorporation ofplanned track-lines. The specific sighting plans for each year will be presented to the annual meetings of the IWC
SC to ensure that future survey plans fully follow the IWC SC guidelines. Details of the analytical procedures
focused on common minke whales are provided in section 3.1.3.
Issues on sighting survey’s design, data collection protocols and priorities, data analyses and coordination will be
included in research plans to be submitted to the annual meeting of the IWC SC for approval before the start ofthe survey. Also the following additional issues will be addressed in the research plan: evaluation of past survey’s
analytical difficulties, appropriate temporal stratification, appropriate direction of travel, use of independent
observer (IO) mode, use of passive independent observer, development of protocols/priorities for biopsy-related
activities, evaluation of additional variance analysis and spatial model methods and ‘regime shift’-related aspects.
Photo-identification and biopsy sampling
Photo-ID and biopsy experiments will continue to be conducted for blue, fin, humpback, North Pacific right andkiller whales. These methods will provide useful data for stock structure, mixing and movements. Particular25

emphasis will be given to blue and right whales (see Ancillary Objective III). The IWC SC has welcomed photoID photographs and biopsy samples from those species in the North Pacific (IWC, 2015a; 2016e). Details of the
field procedures are given in section 3.7.
There will be coordination with IWC POWER with respect to sighting surveys, biopsy sampling and photo-ID
for large whales to ensure consistent data collection and processing, as appropriate. Information on the large whale
species will be included in the cruise reports to be submitted to the IWC SC to encourage collaboration with
scientists involved with research on these species.
Oceanographic observations
Oceanographic conditions in this research program will be investigated using data collected by ocean circulation
models such as FRA-ROMS (Okazaki et al., 2016) (see details below).
3.1.2

Laboratory methods

Annexes 7-10 shows the laboratory and analytical procedures for each Secondary Objective. Below is a briefsummary of the laboratory work for the most relevant research items. Secondary Objectives are referred to inparenthesis.
Age determination (I (i) (iv))

Age determination will be conducted by two different methods counting growth layer groups (GLGs) accumulated
in the earplugs and racemization ratio of aspartic acid in eye lens. The former will be the primary ageing method.
The left and right earplugs with glove-finger will be collected carefully onboard the research vessel and fixed in
10% formalin solution until age determination. Because young whales have soft and easily-broken earplugs, they
will be collected using the method of gelatinized extractions, following Maeda et al. (2013). In the laboratory, theflat along the central axis of the earplug will be cut using a sharp blade, ground on a wet stone to expose theneonatal line and growth layers. Growth layers will be counted using a stereoscopy microscope. Details of thelaboratory procedure are given in Annex 7 and they will follow standard procedure (Best, 1982; Lockyer, 1984b).
Analysis of ratio of D- and L-aspartic acids (Asp D/L) will follow the method for whales described by Nerini(1983) and modified by Yasunaga et al. (2014) for Antarctic minke whale. In the field, eye lens samples will be
stored in polyethylene bags at -80°C until analysis at the laboratory. The core sample will be carefully taken fromthe lens to avoid contamination and then it will be homogenized. Details of the laboratory procedure are given in
Annexes 7 and 10.
Determination of sexual maturity (I (i) (iv))

Methods for determination of sexual maturity will follow Lockyer (1984a). Sexual maturity in females will be
preliminary determined at the research base vessel by the presence or absence of corpora lutea/albicantia in theovaries. Ovaries will be preserved at -20°C and counting the number of corpora lutea/albicantia in both ovaries
will be done at the laboratory after cutting the surface of the ovary using a scalpel. Sexual maturity in males will
be determined preliminarily on the research base vessel, based on testis weight criterion. Testis weight (heavierside) of more than 290g will be determined as sexually mature (Bando, unpublished data). At the laboratory, HE
stained testis sections will be prepared and observed using standard microscope. Males with seminiferous tubules
over 100µm diameter will be determined as sexually mature (Kato, 1986; Kato, et al., 1991). Details of laboratory
procedures are provided in Annexes 7 and 10.
Genetics (I (i) (iii))

Standard laboratory protocols will be used for mtDNA control region sequencing and microsatellite DNA profiles.
Laboratory work and data analyses will follow the IWC SC’s guidelines for DNA data quality (IWC, 2009) as
much as possible. Sampling and laboratory procedures of the genetics laboratory of the Institute of Cetacean
Research were summarized by Kanda et al. (2014), and the IWC SC agreed that the paper had responded
appropriately to some relevant recommendations on DNA data quality from the JARPAII review workshop (IWC,
2015a;b). In 2016 additional information was provided by the proponents on estimates of microsatellite
genotyping error rates and again, the IWC SC agreed that the work presented had addressed a recommendation
on DNA data quality from the JARPNII final review workshop (IWC, 2016c).

26

Total genomic DNA will be extracted from tissues preserved in 99% ethanol. For mtDNA, approximately 500bp
of the control region will be amplified by the PCR. All samples will be sequenced for both strands with the sameprimers used for the PCR amplification. For microsatellite DNA a set of at least 15 primers (depending of thewhale species) will be used. Details of the laboratory procedures are provided in Annex 7.
3.1.3

Analytical methods

Annexes 7-10 show the laboratory and analytical procedures for each Secondary Objective. Below is a briefsummary of the analytical procedures for the most relevant research items. Secondary Objectives are referred toin parenthesis.
Sample size estimation

Common minke whale in sub-areas 7-9
Annex 11 and Adjuncts 1-3 provide the rationale and the analyses for the selection of sample size for the North
Pacific common minke whale. The analyses considered some of the recommendations from the NEWREP-NP
review workshop, and were discussed further during the 2017 IWC SC annual meeting.
Lethal sampling is required to obtain age information. This allows for improved conditioning of RMP trials by
providing estimates of population trajectories and their changing trends that are more closely representative of the
population's behavior than can be obtained using abundance estimates alone. The extent of improvement increases
with increasing sample size, which provides part of the basis to make the sample size choice, though clearly thisdecision also requires consideration of other factors including the possible effect of the catches on the stock as
well as of aspects of practicality.
Annex 11 Adjunct 3 provides results labelled in terms of annual numbers n of 0 (i.e. no whales aged, only
abundance estimates available), 40, 80 and 120. These numbers n do, however, refer to an ‘effective’ sample size
which justifies analysis under the assumption of no over-dispersion in the ageing data. The actual sample sizes
have to take that over-dispersion into account, which increase them to 0, 53, 107 and 160 respectively.
The computations focus on changes in recruitment rates (births per adult female) – possibly the result ofenvironmental factors such as oceanographic regime shift and climate change - and how well these and theassociated changes in population trends can be detected in relation to the amount of ageing information available.
As mentioned earlier, the western North Pacific has been experiencing decadal-scale regime shifts of marine
ecosystem that would likely affect population dynamics of whale populations. It is thus very important for resource
managers that possible changes in population trends be detected in a timely manner. The broad pattern of theresults is clear: in the absence of ageing information, survey indices of abundance alone are unable to detect thesechanges; however, given ageing information, they are detected to at least some extent, and also fairly soon after
they have occurred. This remains true for a number of cases of different MSYR values, whether the changes areup or down, and when the changes occur.
Detectability of some change to the true population trajectory, and the associated extent, is clearly best for thelargest annual sample size examined of 120 whales. However, an annual sample size of 80 whales was also foundto be capable of detecting important changes to the true population trajectory and the associated changes, albeit
to a lesser degree than an annual sample size of 120 whales. An annual sample size of 40 whales was found to beincapable of adequately detecting crucial changes in the recruitment rates. An annual sample size of 80 whales(or the actual sample size of 107 after taking into account of over-dispersion) was also found to be a feasible
sample size in terms of the capacity of the research vessels. Taking account of these factors, it was concluded thatthe sample size of 107 O stock common minke whales per annum is the optimal sample size for this research plan.
60% of the sample size will be taken in coastal sub-areas (7CS and 7CN) and 40% in offshore sub-areas (7WR,
7E, 8 and 9) (Annex 11). Therefore 64 animals will be sampled in coastal sub-areas and 43 in offshore sub-areas.
Because around 20% of the animals in sub-areas 7CS and 7CN are from the J stock (Annex 7) the sample size ofO stock in coastal sub-areas needs to be adjusted to 80 animals. Then the total sample size in the Pacific side ofJapan hence becomes 123 animals.
Common minke whale in sub-area 11 (I (i))
Annex 11 Adjunct 4 provides the rational and analyses for the selection of sample size North of Hokkaido (subarea 11). As shown in Annex 7, unlike the case of sub-areas 7CS and 7CN, there are only limited and dated data27

on mixing proportions of the J stock in sub-area 11. Therefore the priority sub-area for addressing Secondary
Objective I (i) will be sub-area 11.
It is known that segregation by sex, age and reproductive status occurs during migration of common minke whales
along the Japanese coast (Hatanaka and Miyashita, 1997). For that reason, information on genetics alone is not
sufficient and simultaneous collection of both genetics and biological information including age data is essential
in order to evaluate the spatial and temporal migration pattern of common minke whales, and to estimate patternsof stock mixing by age and sexual maturity classes. This will ultimately provide important information for
conditioning of future RMP/ISTs trials
It should be noted here that there are not enough data in sub-area 11 for making an exact estimate of sample sizefor the objective of studying the yearly trend in the proportion of the J stock in this sub-area. Therefore the estimateof sample size in Annex 11 Adjunct 4 is preliminary. Basically the proponents conducted an examination of therequired sample size to estimate the mixing proportion itself, rather than the yearly trend thereof, of the J stock inthis sub-area with sufficient precision (e.g. SE (p) less than 0.1), which, combined with the biological datacollected simultaneously, will be important for achieving the objective here. The resulting annual sample size was
47 animals.
This estimate applies only for the first six years of NEWREP-NP. More detailed estimates of samples size for theobjective of studying the temporal trend of the J stock mixing proportion will be made once data have been
accumulated in the first six surveys. At that time, also an evaluation on the level of improvement in the RMP
conditioning of incorporating new information on J stock proportion in sub-area 11 may be considered.
Assignment of common minke whale individuals to stock (I (i))

The newly obtained samples will be assigned to either O or J-stocks, applying microsatellite data to a Bayesianclustering analysis in the program STRUCTURE version 2.0 (Pritchard et al., 2000). The program
implements a model-based clustering method for inferring stock structure (K, the number of stocks in the model)using multilocus genotype data with and without information on sampling locations, which allows for the analysesof the samples without choosing sample units. The posterior probability for K = 2 is estimated from ten
independent runs without information on sampling locations. All runs are performed with 100,000 Markov
chain Monte Carlo repetitions and 10,000 burn -in length using the admixture model which assumes
individuals may have mixed ancestry, with correlated allele frequencies which assumes frequencies in the
different stocks are likely to be similar due to migration or shared ancestry. Individual assignment is conductedusing estimated individual proportion of membership probability (>90%).
The phylogenetic analysis based on the Neighbor-Joining method (Saitou and Nei, 1987) will be performed using
mitochondrial sequences, in the program PHYLIP (Felsenstein, 1993) to complement the individual assignmentby the STRUCTURE analysis. Assignment will be further complemented by the examination of morphologicalcharacters separating O and J stocks (see details in Annex 7).
Abundance estimates (I (ii))

Abundance of whales will be estimated by two approaches: design-based estimator and model-based estimator.
For preliminary analysis under the former approach, mark-recapture distance sampling (Borchers et al., 1988,
2006; Laake, 1999), which is one of the packages in the DISTANCE program (Thomas et al., 2010), will beapplied to estimate abundance considering preliminary g(0) estimates. Regarding the latter approach, Density
Surface Modeling (DSM) (Miller et al., 2013) will be used, which is one of the packages in the DISTANCE
program (Thomas et al., 2010) but other options will be tried as well. For example the approach presented by
Murase et al. (2016a) will be used as a template of this type of analysis bearing in mind the comments from the
JARPNII final review workshop. Sea Surface Temperature (SST), Sea Surface Height anomaly (SSHa) and sea
surface chlorophyll-a concentration (Chl-a) recorded by satellites, and digital seafloor depth data will be used asenvironmental covariates in the models. Data from ocean circulation models such as FRA-ROMS will also be
used as covariates.
Details of each approach for abundance estimation of common minke whales are shown in Annex 8.

28



SCAA (I (iv))

The recent availability of age data from North Pacific common minke whale (Maeda et al., 2016) provides a basis
to improve the accuracy of the RMP ISTs of IWC (2014a) for these common minke whales through taking thesedata into account when conditioning these trials. In this research the new age data will be used by the StatisticalCatch-At-Age (SCAA) assessment approach. The SCAA was applied to Antarctic minke whales (Punt et al.,2014), and this model was recognized by the IWC SC as the ‘best currently available model for examining stock
dynamics for Antarctic minke whales’ (IWC, 2014e). Details of the model are presented in Annexes 10 and 11.
Kinship analysis (I (iii))

Tiedemann et al. (2014) reported a method for finding relatives among North Atlantic common minke whales
based on microsatellite data. The method was welcomed by the IWC SC (IWC, 2015b). The method wasrecommended by the IWC SC to investigate relatives among North Pacific common minke whales (IWC, 2016b).
The method by Tiedemann et al. (2014) will be used to examine previous samples from JARPN/JARPNII and
bycatches, together with new samples collected by NEWREP-NP. Details of the method are provided in Annex
9.
3.1.4

Time frame with intermediate targets

Figure 3 shows the kind of research activities and associated timelines under the NEWREP-NP’s Primary
Objectives I and II, and Ancillary Objectives I-III. For each primary and ancillary objective, the upper part of the
figures shows the timeline for the research activities in the entire 12-years research period. The lower part of the
figures shows the timelines for the first six-year period, specifying the outputs and evaluation to be obtained after
the first six-year period. Details are explained under section 5.1.

Primary Objective I(i) Mixing proportion Genetics
Morphology
J stock(ii) Abundance(iii) Verify single O
stock structure(iv) Age data inconditioning

First 6 years

Review

Second 6 yearsa) DNA Assignment

Sample/Data collection/Analysis

Sample/Data collection/Analysisb) Flippers pattern

Sample/Data collection/Analysis

Sample/Data collection/Analysisc) J stock proportion trend

Statistical analysis

Statistical analysisa) Sighting survey

Data collection

Data collectionb) Abundance estimate

AnalysisAnalysisc) Genetic mark-recapture

Feasibility

Continue?

Geneticsa) Kinship analysis

Othersb) Sattellite tagging

Feasibility

Continue?

c) Biopsy sampling

Feasibility

Continue?

Biologicalinformation

Review

Sample/Data collection/Analysisa) Earplugb) Racemization

Sample collection/reading
Feasibility

Sample/Data collection/Analysis

Sample collection/reading
Continue?

c) DNA Methylation

Feasibilityd) Reproductive status

Sample/Data collection

Sample/Data collection

Initial application

Improvemente) SCAA

29

Continue?

Primary Objective I(i) Mixing proportion Genetics
Morphology
J stock(ii) Abundance(iii) Verify no O
stock structure(iv) Age data inconditioning

First 6 yearsa) DNA Assignment

Sample/Data collection/Analysisb) Flippers pattern

Sample/Data collection/Analysisc) J stock proportion trend

Statistical Analysisa) Sighting survey

Data collectionb) Abundance estimate

Analysisc) Genetic mark-recapture

Feasibility

Geneticsa) Kinship analysis

Othersb) Sattellite tagging

Feasibility

Continue?

c) Biopsy sampling

Feasibility

Continue?

Biologicalinformationa) Earplugb) Racemization

Sample collection/Reading
Feasibility

Feasibilityd) Reproductive status

Sample/Data collection/Analysis

Continue?

Initial application

First 6 yearsa) Sighting surveyb) Abundance estimate

Review

Data collection
Analysis

Sample collection/Reading
Feasibilityd) SCAA(iii) Distribution and Movement
Genetics
movementa) Sattellite tagging

Feasibility

Continue?
Analysisc) DAPC

AnalysisAnalysisPrimary Objective II

Final specification

First 6 yearsa) Sighting survey

Data collectionb) Abundance estimate

Analysisc) Additional variancea) Earplugb) Racemization

Analysis
Sample collection/Reading
Feasibilityd) SCAAa) Sattellite tagging

Preliminary
assessment by
SCAA

Continue?
Feasibilityc) DNA Methylation(iii) Distribution and Movement
Genetics
movement

Improvement

Analysis

Initial specification with SC

Estimationof ageContinue?

b) STRUCTURE

Flowchart of survey & analyses(ii) Biologicalparameters

Sample collection/Reading

Initial application(iv) RMP/IST(i) Abundance

Analysis

Continue?
Feasibilityc) DNA Methylation

Review

AnalysisAnalysisa) Earplugb) Racemization

Second 6 years

Data collectionc) Additional variance
Estimationof ageEvaluation of nonlethal methods on awhole-program basis

Continue?

c) DNA Methylation

Primary Objective II(ii) Biologicalparameters

Preliminary
assessment by
SCAA

Sample/Data collection/Analysise) SCAA(i) AbundancePreliminary
evaluation of J stock
proportion andabundanceContinue?

Initial application
Feasibility

Continue?

b) STRUCTURE

Analysisc) DAPC

Analysis(iv) RMP/IST

Initial specification with SC

30

Evaluation of nonlethal methods on awhole-programbasis

Ancillary Objectives
Distribution/abundance

I Environmental
changes

First 6 years

Review

Second 6 years

Reviewa) Sighting survey

Data collectionb) Spatial modelling

AnalysisAnalysis

Sample/Data collection/Analysis

Sample/Data collection/Analysisc) Prey species

Data collection/fisheries information

Prey consumption/composition

Nutritional
condition

II Effects ofpollutantsd) Stomach contents

Sample/Data collection/Analysis

Sample/Data collection/Analysise) Stable isotope

Feasibility

Continue?

f) Fatty acid

Feasibility

Continue?

g) Sattellite tagging

Feasibility

Continue?

h) Nutritional condition

Sample/Data collection/Analysis

Sample/Data collection/Analysis
Data collection/Analysis

Environmental
variablesi) Oceanographic

Data collection/Analysis

Relationships ofPOPs andbiomarkersa) Legacy POPs

Data collection/Analysis

Data collection/Analysis
Revising research itemsb) Biomarkers

Data collection/Analysis

Data collection/Analysis
Revising research items

Different species ofc) OMICS analysis
sensitivity of POPs

III Stock structure
large whales

Data collection/Analysis

Continue?

Novel compoundsd) Retardants

Data collection/Analysis

Continue?

Distributiona) Sighting survey

Data collection/Analysis

Data collection/Analysis

Movementb) Biopsy sampling

Data collection/Analysis

Data collection/Analysis

Stock structurec) mtDNA & msDNA

AnalysisAnalysis

Ancillary Objectives
Distribution/abundance

I Environmental
changes

First 6 yearsa) Sighting survey

Data collectionb) Spatial modellingc) Prey species

Sample/Data collection/Analysis/fisheries information

Prey consumption/composition

Nutritional
condition

II Effects ofpollutantsd) Stomach contents

Sample/Data collection/Analysise) Stable isotope

Feasibility

Continue?

f) Fatty acid

Feasibility

Continue?

g) Sattellite tagging

Feasibility

Continue?

h) Nutritional condition

Sample/Data collection/Analysisi) Oceanograhphic

Data collection/Analysisa) Legacy POPs
Relationships ofPOPs andb) Biomarkers
biomarkers
Different species ofc) OMICS analysis

Data collection/Analysis

sensitivity of POPs

III Stock structure
large whales

Analysis

Data collection/Analysis
Data collection/Analysis

Novel compoundsd) Retardants

Data collection/Analysis

Distributiona) Sighting survey

Data collection/Analysis

Movementb) Biopsy sampling

Data collection/Analysis

Stock structurec) mtDNA & msDNA

Evaluation of nonlethal methods on
a whole-program
basis

Preliminary examination of
the influence ofenvironmental changes on
whale stocks

Evaluation of theeffects ofpollutants on whale

Evaluation ofstock structure anddistribution

Analysis

Figure 3. Research items associated to Primary and Ancillary Objectives and timeframe for six and 12-year period.
3.1.5

Explanation that this objective can be achieved by the method proposed

Secondary Objective I (i): Investigate the spatial and temporal occurrence of J stock common minke
whales around Japan, by sex, age and reproductive status
Individual assignment to the J and O stocks common minke whales based on a set of microsatellite loci and theBayesian program STRUCTURE has worked well in previous studies for separating O and J stock individuals(e.g. Pastene et al., 2016) as recognized by the IWC SC (IWC, 2010). Following recommendations from the IWC
SC (IWC, 2016b), an extra number of loci will be used in the microsatellite analysis to decrease the number of‘unassigned’ animals. To complement the microsatellite analyses, other genetics (mtDNA sequencing) and nongenetic methods (e.g. morphology) will be used to assign individuals to stocks.

31

It is known that segregation by sex, age and reproductive status occurs during migration of common minke whale
along the Japanese coast (Hatanaka and Miyashita, 1997). For that reason, simultaneous collection of both genetics
and biological information including age data is essential in order to evaluate the spatial and temporal migration
pattern of common minke whales, and to estimate the pattern of stock mixing by age and sexual maturity classes.
Accepted techniques for determination of age (Maeda et al., 2013) and determination of reproductive status(Lockyer, 1984a) will be used. Both genetic and biological information gained from the samples will be used in
conditioning of RMP/ISTs trials.
Secondary Objective I (ii): Estimate the abundance of the J and O stocks in coastal waters of Japan
Systematic sighting surveys under the Line Transect Method is an accepted technique for abundance estimates ofwhales, and the IWC SC Requirements and Guidelines for Conducting Surveys and Analyzing Data within the
Revised Management Scheme (RMS) (IWC, 2012b) will be followed. The Sea of Japan is believed to contain
only J stock common minke whales so interpretation of sighting survey data is straightforward. Sub-areas 7 and11 contains a mix of J and O stocks so in this case, the interpretation of sighting data should take into consideration
the available information on mixing proportion in those sub-areas. It should be noted that such mixing data will
be gathered under the Secondary Objective I (i) above.
Secondary Objective I (iii): Verify that there is no structure in the O stock common minke whale in the
Pacific side of JapanThe IWC SC in 2016 considered that kinship analyses similar to those carried out by Tiedemann et al. (2014)
would be useful to investigate further the two O stock hypothesis (IWC, 2016b). Such analyses will be conductedunder NEWREP-NP based on past and new samples.
Secondary Objective I (iv): Improve RMP trials by incorporating age data in their conditioning
The catch-at-age analyses presented to the JARPNII review workshop (Kitakado and Maeda, 2016) wereconsidered useful by the workshop, which recommended that ‘if the ISTs for the western North Pacific common
minke whales are to be revised in the future, the age data should be included in the conditioning process’ (IWC,
2016c). The proposed SCAA model is recognized as the ‘best currently available model for examining stock
dynamics for Antarctic minke whale’ (IWC, 2014e). See also discussion in Annex 11.
3.1.6

Data to be obtained

Table 2 below shows the data and samples to be collected by NEWREP-NP, by Primary and Ancillary research
objectives.

32

Table 2. Data and samples to be collected under NEWREP-NP, by research objective.
Data
Abundance estimate
1,2,3 Weather data
1,2,3 Effort data
1,2,3 Sighting record of whales
1,2,3 Angle and distance experiments
Common minke whale/sei whale
1,2,3,4 Catching date and location
1 Photographic record of external character
1,2,3,4 Sex and body length
1,2,3 Satellite tracking
3,4 Body weight
3,4 Blubber thickness and nutrition condition
3,4 Stomach content: freshness and weight
1,2,3,4 Testis weight
1,2 Fetal number, sex, length and weight
4 Marine debris (in stomach)
Other large whales
5 Photo-ID

Sample1,2,3,4 Testis
1,2,3,4 Ovary
1,2,4 Earplug
1,2,4 Ocular lens
1,2,3,4 Baleen plates
1,2,4 Tissue samples for genetic study (including fetus)
1,2,3,4 Tissue and organ samples for chemical study
4 Tissue and plasma samples for physiological study
3,4 Prey species in stomach

3,5 Skin sample (biopsy)

1: Data or samples to be used for Primary Objective I: Data or samples to be used for Primary Objective II
3: Data or samples to be used for Ancillary Objective I
4: Data or samples to be used for Ancillary Objective II
5: Data or samples to be used for Ancillary Objective III
2

3.1.7
-

Description of use of data from other projects or programs (Objectives in parenthesis)

Morphological data of common minke whale (Tokyo University of Marine Science and Technology,
Japan) (I (i))
Earplug-based age data (National Research Institute of Far Seas Fisheries, Japan) (I (i); I (iv))

3.2 Primary Objective II
3.2.1 Field methods
Species, number, time frame, area

For this Primary Objective the North Pacific sei whale will be the target species. While lethal sampling of sei
whale will be conducted mainly in the western North Pacific, the study area for non-lethal research such as sighting
survey will be the pelagic region of the North Pacific delimited approximately by the Japanese DNA survey(30°N-50°N; 145°E-140°W), which is occupied by a single stock of sei whale. This research area will be surveyed
between April and October.
The annual sample size for lethal research of sei whale is 134 animals, which was estimated based on Secondary
Objective II (ii) (see analytical details in section 3.2.3).
The research period under NEWREP-NP is planned to be 12 years with a midterm review after the first six years
in order to evaluate progress in achieving research objectives, and revise the research program if necessary. As
this Primary Objective is associated with the application of the RMP, the six-year period is in line with theannotations to the RMP, which states that ‘An Implementation Review for a species and Region should normallybe scheduled no later than six years since the completion of the previous Implementation (Review)’ (IWC, 2012a).
The detailed timeline of research activities in NEWREP-NP is presented in section 3.1.4.


Sampling protocol for lethal aspects of the proposal

Annex 12 shows the details of the whale sampling design for sei whales. A research base vessel (Nisshin Maru)and two sampling and sighting vessels (Yushin Maru No. 1 and 3) will participate in the survey (see Annex 21 fordetails of the vessels). The track lines and the allocation of vessels will be set in a similar manner as in previous
JARPNII surveys. A zig-zag-shaped track line will be set in the research area. The track line consists of one main
and two parallel courses, established seven n. miles from the main course. In order to secure the sampling of theestimated number of samples, an Adaptive Type Survey (ATS) (e.g. Pollard et al., 2002) and a Special Survey

33

(SS) (Bando et al., 2016) may be conducted, when the whale density are expected to be high. ATS will be designedby adding tracks lines over the predetermined track lines. On the other hand, the SS will establish new track lines
independently from the original track lines. The track lines of ATS and SS consist of one main and two parallelcourses that will be established several n. miles apart from main course.
The sampling sighting vessels will survey the research area at a speed of 10.5 knots from one hour after sunrise
to one hour before sunset, with three top men assigned to the barrel. All sei whales sighted as primary andsecondary sightings, excluding cow and calf pairs, will be targeted for sampling. When a sighting consists of morethan one animal, the first targeted animal will be selected using tables of random sampling numbers (TRS).
Each whale sampled will be transported to the research base and examined biologically by a team of scientists.
See Annex 12 for details of the sei whale sampling procedures. In particular Tables 1 and 2 of this annex shows
the number of samples of sei whales by month, year and sub-area collected by JARPNII in the period 2002-2016
and the expected samples by NEWREP-NP in the period 2017-2022, respectively.
Assessment of why non-lethal methods, methods associated with any ongoing commercial whaling, or
analyses of past data have been considered to be insufficient

As in the case of the common minke whale under Primary Objective I, the research items requiring lethal sampling
are age and sexual maturity determination associated with Secondary Objective II (ii).. Therefore the assessmentof why non-lethal methods or analyses of past data have been considered to be insufficient is the same as in thecase of the common minke whale above. As in the case of the common minke whale, several feasibility studies
on new non-lethal techniques will be conducted for sei whale (Figure 2).


Sampling protocol for established non-lethal techniques

Sighting surveys for abundance estimates, photo-id and biopsy of large whale species for studies on stock structure,
distribution and movement, and oceanographic surveys will be also conducted under the Primary Objective II.
Procedures are the same as in the case of the common minke whale described above.
3.2.2

Laboratory methods

Annexes 13-15 shows the laboratory and analytical procedures for Secondary Objectives II (i), (ii) and (iii),
respectively. Below is a brief summary of the laboratory work for the most relevant research items. Secondary
Objectives are referred to in parentheses.


Age and sexual maturity determination (II (ii))

Laboratory procedures are the same as in the case of common minke whale (see Annex 14 for the application in
the case of sei whale).


Satellite tracking and genetics (II (iii))

Field and laboratory procedures are the same as in the case of common minke whale (see Annex 15 for theapplication in the case of the sei whale).
3.2.3

Analytical methods

Annexes 13-15 shows the laboratory and analytical procedures for Secondary Objectives II (i), (ii) and (iii),
respectively. Below is a brief summary of the analytical procedures for the most relevant research items.
Secondary Objectives are referred to in parentheses.
Sample size estimation

Annex 16 provides the rationale and analyses for the selection of the sample size for sei whales. The analyses
considered some of the recommendations from the NEWREP-NP review workshop as appropriate, and were also
discussed at the 2017 IWC SC annual meeting.

34

Lethal samples are required to obtain age information. This allows for improved conditioning of RMP trials by
providing estimates of population trajectories and their changing trends that are more closely representative of the
population's behaviour than can be obtained using abundance estimates alone. The approach followed to estimate
the sample size is based on the age-and sex-structured model applied to the single pelagic stock of sei whales forconditioning and generating future data in simulations. The target is to estimate the natural mortality rate, M, byusing SCAA methodology.
In the population dynamics model the natural mortality is assumed to be age-independent at M=0.04 and 0.05(/year), and the MSYR (1+) is set at 1 and 2.5%. These values are used not only for conditioning but also forgenerating future data in the simulation context to assess the estimation performance for the natural mortality rate.
Robust results across four scenarios considered are that for an annual sample size of 100 animals or above, bias
reduces to close to zero, and RMSE stabilizes at about 0.005 (see details in Annex 16). The variance of the
distribution of M estimates narrows considerably as the sample size is increased from 40 to 100. This value makes
no allowance for possible over-dispersion in the age data. Consequently the assumption was made that this is thesame as for common minke whale, corresponding to a need to increase the sample size by a multiplicative factorof 1.34 (Appendix D of Adjunct 3 of Annex 11).
Consequently the annual sample size for sei whale is 134.
Abundance estimates (II (i))

As in the case of the common minke whale abundance estimates will be based on both design-based estimator andmodel-based estimator. Assuming that g(0)=1, design based abundance estimator (Thomas et al., 2010), which
are the standard methodology of line transect surveys, will be applied. Covariates related to detectability of thewhales are used to estimate detection function (e.g. Hakamada and Matsuoka, 2015; 2016). Estimation procedure
will be conducted using DISTANCE program (Thomas et al., 2010). Model selection of the detection functions
will be made using AIC. The estimated abundance for each year and each sub-area can be used as input for models
to estimate additional variance. The approach in Kitakado et al (2012) will be used to estimate yearly variation inabundance levels due to inter-annual change in distribution of the sei whale population and abundance trend of
the sei whales. By considering the inter-annual variance, underestimating the variance of the abundance estimate
can be avoided. This work would respond to the recommendation made at the JARPNII review workshop (IWC,
2016c).
Regarding model-based estimator the DSM (Miller et al., 2013) will be used, which is one of the packages in the
DISTANCE grogram (Thomas et al., 2010). But other options will be tried (e.g. smoother, modeling framework,
variance estimation method etc.) to improve abundance estimates. For example, the approach presented by
Murase et al. (2016a) will be used as a template of this type of analysis bearing in mind the comments from the
JARPNII final review workshop (IWC, 2016c). SST, SSHa and Chl-a recorded by satellites, and a digital seafloor
depth data were used as environmental covariates in the models. Data from ocean circulation models such as FRAROMS will also be used as covariates. It is also planned to compare abundance from model-based estimates withthose from the design-based estimates. This work would respond to the recommendation made at the JARPNII
review workshop (IWC, 2016c).
See details in Annex 13.


SCAA (II (ii))

The analysis is similar to that described for common minke whale under Primary Objective I above (see Annex
14 for the application of SCAA to sei whale).
3.2.4

Time frame with intermediate targets

Figure 3 shows the time frame for the specific research under Primary Objective I and II, for both six-year andtwelve-year periods. See section 5.1 for details.
3.2.5

Explanation that this objective can be achieved by the method proposed

Secondary Objective II (i): Abundance estimates for North Pacific sei whales taking account ofadditional variance35

Systematic sighting surveys under the Line Transect Method is an accepted technique for abundance estimates ofwhales, and the IWC SC Requirements and guidelines for conducting surveys and analyzing data within the
Revised Management Scheme (RMS) (IWC, 2012b) will be followed. The IWC SC has agreed that the pelagic
region of the North Pacific contains a single stock (IWC, 2016b) so that the interpretation of sighting data in thecontext of abundance estimate should be straightforward.
Secondary Objective II (ii): Estimation of biological and ecological parameters in North Pacific sei
whales for RMP Implementation
The proposed Statistical Catch-At-Age (SCAA) model is recognized as the ‘best currently available model for
examining stock dynamics for Antarctic minke whale’ (IWC, 2015c). It can be used for sei whales in the North
Pacific as well.
Secondary Objective II (iii): Study of the pattern of movement of whales of the ‘pelagic stock’ within thefeeding grounds and between feeding and breeding grounds
The IWC SC agreed that a single stock occupies the pelagic region of the North Pacific. The proponents aim toaddress this objective using the satellite tracking approach. As whales will be sampled to obtain age information,
genetic samples will be also examined to update some analyses following recommendations from the IWC SC.
See Murase et al., (2016b) for an application of satellite tracking approach to North Pacific Bryde’s whale.
Secondary Objective II (iv): Specification of RMP ISTs for North Pacific sei whales
This objective will be achieved once the three objectives above are achieved.
3.2.6

Data to be obtained

Table 2 shows the data to be obtained by NEWREP-NP relevant to both Primary Objectives.
3.2.7-

Description of use of data from other projects or programs (Objectives in parenthesis)

Sighting data (IWC-POWER program) (II (i))
Earplug-based age data (National Research Institute of Far Seas Fisheries, Japan) (II (ii))
Biopsy samples (IWC-POWER program) (II (iii))

3.3 Summary of the overall justification for final study area, sampling design and sample size
For the Primary Objective I the study area comprised by sub-area 11 is important for addressing the Secondary
Objective I (i). Clearly there is a need to acquire new information on the distribution of the J stock and genetic
and biological data allowing the estimates of J stock proportion trend in the future in this sub-area. Suchinformation is potentially relevant for the RMP conditioning. This sub-area is also important for Secondary
Objectives I (ii) and Ancillary Objective I. The sample size of 47 animals is considered preliminary and additional
estimates of sample size will be carried out when data have been accumulated in this sub-area. Sampling design
is considered appropriate as a strictly random design is not required to fulfill the research objectives. The use of
several small catcher boats and ports, and the use of transport vessels and oceanic research base vessel, will
increase the geographical coverage and ensure that the sample size is obtained.
The study area comprised by sub-areas 7-9 is important particularly for addressing Secondary Objectives I (iv).
This area is an area for future coastal commercial operations and therefore the optimization of the RMP throughthe use of age data become very important. The number of samples (123) is considered moderate and is well
supported by the quantitative analyses. The sampling design was established to obtain annual samples in bothcoastal and offshore areas.
The study area comprised by the pelagic region of the North Pacific is important for addressing all Secondary
Objectives under Primary Objective II. This region is occupied by a single stock of sei whale and therefore theinterpretation of abundance, biological parameters and stock structure should be straightforward. Sample size(134) is moderate and well supported by the statistical analyses. In this case random sampling will be carried out
along a zig-zag-shaped track line, which is considered appropriate mainly for addressing Secondary Objective II
(ii).

36

3.4 Possible modification of lethal sample size̶The proponents will conduct non-lethal researches such as biopsy sampling and satellite tagging in order toexamine their feasibility during the first six years of NEWREP-NP. The reconsideration of lethal sample size
would be made at the time of the mid-term review based on the results of those non-lethal researches, if they areturned out feasible. While it is premature at this stage to elaborate a concrete and specific protocol of suchreconsideration of lethal sample size, below are some of basic concepts that seem relevant at the mid-term review,
when necessary.

̶̶The criteria developed by Mogoe et al (2016) will be applied to evaluate the feasibility of the employed nonlethal techniques and verify whether the non-lethal method(s) could compliment lethal method so that lethal
sample size could be reduced.
Age data are the key information to judge whether a particular non-lethal techniques (for example, biopsy
sampling for conducting DNA methylation analysis) can replace/reduce the sample sizes of lethal technique
Sufficient analyses have been conducted regarding Q1 and Q2 of the Mogoe’s criteria (efficiency of biopsy
sampling). Further investigation on Q3 (quality of data) and Q4 (cost) may be conducted, if necessary.
3.5 Ancillary Objective I
The methodology associated with this objective is shown in Annex 17.
This Ancillary Objective requires information on stomach contents, blubber thickness, girth and body weight,
oceanographic conditions, fisheries information. A feasibility study to investigate the lipid content % of blubber(blubber can be obtained by biopsy), will be carried out (Figure 2).
3.6 Ancillary Objective II
The methodology associated with the three research items identified under this ancillary objective is shown inAnnex 18. Marine debris in the stomach of the whale samples, particularly plastic debris, will be investigated in
the context of research item (iii).
This Ancillary Objective requires internal tissue (liver) samples, plasma, and age from earplug and racemization
methods.
3.7 Ancillary Objective III
Studies on stock structure, distribution and movement of large baleen whales, with particular emphasis on blue
and right whales, will be conducted through biopsy sampling and photo-identification. Annex 19 describes thebiopsy sampling and photo-identification procedures. Laboratory and analytical procedure for the genetic work issimilar to those used for minke and sei whales (see Annex 7).

4.

ASSESSMENT OF POTENTIAL EFFECT OF CATCHES

4.1 Primary Objective I (common minke whale)


Information on stock structure

Discussions on stock structure of western North Pacific common minke whale have taken place at the IWC SC
since 1993, with the latest comprehensive discussions occurring during the RMP Implementation Review in 2013
(IWC, 2014a).
Three stock structure hypotheses were used in the Implementation Review (IWC, 2013b) (see Introduction for
details of these hypotheses). The plausibility of the three stock structure hypotheses was discussed at the 2012
IWC SC Annual Meeting. A group of five geneticists summarized their interpretation of the relative support for
and against the five hypothesized stocks involved in the different hypotheses (JE, JW, OE, OW and Y) (IWC,
2013b). Despite this effort by geneticists it was not possible for the IWC SC to agree on the plausibility of thethree stock structure hypotheses. This was in part because the IWC SC has not been able to design a clear method
to evaluate plausibility of stock structure hypotheses. As a consequence, the three stock structure hypotheses were37‘no agreement’ and the three hypotheses were therefore treated as if they had been assigned ‘Medium’ plausibility
in the trials (IWC, 2013b).
The relevant questions for the aim of an evaluation on the effects on the stocks of the NEWREP-NP catches iswhether or not there is additional structure within the J and O stocks around Japan. Regarding the J stock, the fivegeneticists concluded that the genetic evidences for a Je stock in the Pacific side of Japan was low and the evidence
against were moderate or high. Regarding the O stock, they concluded that the evidence for an Ow stock in coastal
areas in the Pacific side of Japan were moderate while the evidences against were low or moderate. As noted
above, the IWC SC could not reach an agreement on plausibility of different hypotheses.
As explained in section 2.1, several new analyses on stock structure were presented to the JARPNII final review
workshop (conducted after the 2013 Implementation Review), which were specifically focused to examine theplausibility of additional structure in the O stock. The summary of those studies is provided in Annex 4.
Most of the analyses presented to the JARPNII final review workshop responded to recommendations madeduring the 2009 JARPNII mid-term review. Results of all recent analyses indicate a single O stock distributed
from the Japanese coast to approximately 170°E, and that the data do not support the occurrence of a coastal stockas proposed by hypothesis C (Ow).
Therefore the analyses conducted to evaluate the effect on the common minke whale stocks of future NEWREPNP catches are based primarily on stock structure hypothesis A, which proposes two stocks around Japan, J andO, which mix to each other temporally and spatially, but hypothesis C is also consideredThe estimated abundance of the species/stocks, including methods used and an assessment of uncertainty,
with a note as to whether the estimates have previously been considered by the SC

The relevant information to be considered includes primary effort, primary sighting position, survey blocks, subareas, and area definitions for surveys, and was provided in Appendices 3 and 4 of IWC (2014a). Abundance
estimates based on this information was listed up in (IWC, 2014a), and was based on g(0)=1. Additional
abundance estimates based on JARPNII surveys were added to the list (IWC, 2016g Annex D p12).
Okamura et al. (2009) estimated abundance considering g(0) estimate and they estimate g(0) for each platform
and their combinations. The results were presented to the IWC SC in 2009. In the discussion, it was noted that
although there had been no IO data collection in surveys in previous years, in the absence of direct estimates ofg(0) , the estimates of g(0) presented in Okamura et al. (2009) could be used for the top barrel and the upper
bridge for these earlier surveys.
Corrected abundance estimates based on g(0) estimated by Okamura et al. (2009) are used for an evaluation of
the effects of the catches on the stock (s).
Provision of the results of a simulation study on the effects of the permit takes on the stock that takes
uncertainty into account

The analyses considered some of the recommendations from the NEWREP-NP review workshop, and were also
discussed at the 2017 IWC SC annual meeting.
Three stock structure hypotheses were used in that Implementation Review (IWC, 2013b) (see the Introduction
section of the proposal for more details of these hypotheses). In essence:
Hypothesis A
Hypothesis B
Hypothesis C

J and O stocks
Y, J and O stocks
Y, Jw, Je, Ow and Oe stocks

The baseline trials for those hypotheses developed in that Implementation Review have been used here to assess
the effect of catches, except that:a)Hypothesis B has not been considered, as the hypothesized Y stock to the west of Korea is not impacted
by the catches under consideration.

38b) Those trials (ISTs) considered the lowest plausible MSYR value to be MSYR(mat) = 1%. The ScientificCommittee has subsequently agreed that this minimum be increased to MSYR(1+) = 1% [IWC, 2014b],
so that the deterministic versions of the trials in question have been reconditioned with MSYR(1+) valuesof 1%, 2%, 3% and 4% (only the value of MSYR was changed in these reconditionings).
The constant future annual research catches considered when projecting under the proposed annual take of 170
minke whales is divided amongst sub areas as set out in Table 3, which corresponds to the temporal and spatial
allocation proposed.
Table 3: Distribution of future J and O whale research catches amongst sub areas. Catches take place in the monthsof April-October
Sub area
Annual catch

7CS
40

7CN
40

7WR
5

7E
5

8
10

9
23

11
47

Projections under these catches for MSYR(1+) values of 1% and 2% are shown in Figure 4 for Hypothesis A for
the J and O stocks, and in Figure 5 for Hypothesis C for the Jw, Je, Ow and Oe stocks. Note that these projections
assume that current levels of bycatch continue unchanged. To ease understanding, projections are also shown forthe case of these bycatches only, with no research catch2.

Figure 4. Projections under the proposed catches for MSYR(1+) values of 1% and 2% for Hypothesis A for the J
and O stocks. Depletion refers to the mature female component. Note that the zero catch results refer to thesituation of no commercial or research catch, but bycatch continuing as in the immediate past.

2 The projections here have used the IWC code which allows only for a fixed catch each year following the last year of theassessment, i.e. projections here start in 2013. Thus the proposed scientific catches have been taken to apply starting in 2013,
rather than in 2017. Strictly the actual catches made over 2013-2016 should be input, but the resultant differences to theprojections will be very small and of no consequence to the key conclusions.

39

Figure 5. Projections under the proposed catches for MSYR(1+) values of 1% and 2% for Hypothesis C for the
Jw, Je, Ow and Oe stocks. Depletion refers to the mature female component.
Note that the zero catch results refer to the situation of no commercial or research catch, but bycatch continuing
as in the immediate past.
For MSYR(1+) = 2%, all stocks show increases and/or are well above 54% of their pre-exploitation levels under
the research catches proposed, so there are no population conservation concerns.
For MSYR(1+) = 1%, under Hypothesis A the J stock is currently less than 54% of its pre-exploitation level andis projected to continue to decline, while under Hypothesis C the same applies for the Jw stock (though this is aconsequence of the bycatches only, as no research take from sub areas where this stock is present is planned), and40

the Ow stock, currently at 70.2% of its pre-exploitation level, decreases slowly to reach 66.3% by 2066. However,while these instances might be considered by some to be population conservation concerns, the proponents
consider that issue to be of no real concern, as recent information/analyses have shown the associated stock
structure/MSYR combinations to be clearly implausible, for the reasons set out below.
In summary, the results provided therefore show that the research catches proposed will not adversely impact thestocks, so that no population conservation concern arises.
The assumption of an MSYR(1+) value for 1% for the J stock in Hypothesis A
The conditioning of the North Pacific common minke whale ISTs includes a component in the objective function
which secures trends in whale abundance that are consistent with by-catch per unit effort in fixed set nets,
including those off Japan (see equation F.6 in IWC 2014a).
However this conditioning does not take account of further information that is available on the J:O split of thesebycatches which indicates an increasing proportion of J whales, contrary to what might be expected if the J stock
was heavily depleted and continuing to decline under the current bycatches as indicated for MSYR(1+) = 1% in
Figure 4 above. Figure 6 compares this historical observed trend with the annual values for the proportion of J
whales in the J+O total for different values of MSYR(1+) as predicted, and is suggestive that this further J:O
bycatch ratio information may be able to discriminate amongst different MSYR(1+) values. Note that the
explanation for the recent increase in the J stock proportion in the overall population as MSYR increases is that
the O stock is hardly depleted so that its numbers hardly change, whereas the J stock has been more substantiallyreduced in the past, and has recently been changing at a fairly large rate that increases with MSYR.
Figure 7 compares the estimate of annual trend provided by log-linear regression of the J proportion of the bycatch(with the associated 95% CI) with the point estimates of the trends from the Hypothesis A model abundances fordifferent MSYR(1+) values. This suggests an MSYR(1+) value of 2.8% with a lower 95% confidence limit of
1.6%.
Deterministically such a log-linear relationship is the more justified for the J:O bycatch ratio compared to the J
proportion, but precision decreases because of the greater variance in ratio data. Such an analysis does, however,suggest a larger value for the lower 95% confidence limit for MSYR(1+) of 2.8%.
These bycatch data are thus strongly suggestive of a MSYR(1+) value of 2% or more, for which the results
discussed above indicate no conservation concern for the J stock under the research catches proposed.

41

Figure 6. Comparison of historical observed trend in the proportion of bycatch of J whales in the J+O total withthe trend in the proportion of J whales in the J+O total for different values of MSYR(1+) as predicted under
Hypothesis A.

Figure 7. Comparison of the estimate of annual trend provided by log-linear regression of the observed bycatch(with the associated 95% CI) with the point estimates of the trends from the Hypothesis A model abundances fordifferent MSYR(1+) values.
A more formal investigation is possible through noting that the bycatch model used for the ISTs (IWC 2014c)
indicates that the expected value of the J stock bycatch proportion in each (pertinent) sub area for each year isequal to the corresponding proportion (appropriately averaged over months) of the number of whales in that subarea each year, specifically:

E[CBk ,,ts,m ]  Ak Ptk,m,s Et ,(1)

where E[CBk ,,ts,m ] and Ptk,m,s are the expected bycatch and the number of whales in year t and month m for subareakk and stock s (J or O), respectively (these two quantities depends on the value of MSYR 1+); A

is a sub-area

effect; and Et is an effort in year t.
Assuming catches are Poisson distributed, so that these J stock proportions are binomially distributed, leads to thefollowing negative log likelihood as a function of the value of MSYR(1+):

NLL( MSYR1 )   C log 
k ,J
B ,t

k ,J
 CBk ,,Ot log  tk ,O )  ,
t


t ,k

where

42

(2)

 E[C ]  A P E
P E[C ]  A P E  P
k ,s
B ,t ,mtk ,s

k

m

k ,s
t ,m

t

m

m

k ,s
B ,t ,m

s

k ,s
t ,m

m

k

s

k ,s
t ,m

m


k ,s

t ,m

s

Ptk ,s

P

k ,s

(3)

( s  J/O)

t

m

s

and
Ptk ,s 

P

k ,s
t ,m

( s  J/O) .

m

Since Ptk,m,s depends on the value of MSYR(1+), the loglikelihood is a function of that value as specifically shownin (2).
The associated computations indicate strong support for an MSYR(1+) value of 4% or more. However there aresystematic deviations from model predicted proportions for some sub areas, which are such as preclude theseresults from being used to provide reliable confidence bounds. This indicates a need to refine the current bycatchmodel in the next Implementation Review for these minke whales. In the meantime, however, this result does
provide qualitative support for the conclusion above based on a simpler approach regarding the value ofMSYR(1+).
While in general terms there might be reservations about the assumption of CPUE being proportional to abundance,these concerns are greatly reduced here because the effort in question relates to set nets in fixed locations overtime, and the analysis assumes only that the ratio of the stocks present in the bycatches is given by the ratio of the
populations of those stocks present in the sub area concerned.
The assumption of separate Ow/Oe and Jw/Je stocks for Hypothesis C
Tables 4 and 5 (duplicated from Taguchi et al., 2017) show the number of close-kin pairs observed by sub area
pairings for O and J whales. They also show which sub area pairings should and should not evidence pairings interms of the Hypothesis C mixing matrices for the assumed Ow/Oe and Jw/Je stocks.

Table 4. The number of Parent-Offspring pairs of O stock whales within and between sub-areas (copied from
Taguchi et al., 2017). The blue color indicates those sub-area pairings that are not consistent with the Hypothesis
C mixing matrices for the assumed Ow/Oe stocks; the orange color indicates those sub-areas that are notinconsistent with this hypothesis.
O stock
1E

2C

6E

7CN

1E

1

2C

1

7CS

7WR

7
5

7E

8

9

11

1

3

7

1

1

1

6

6E
7CN
7CS

1

7WR
7E

2

8

2

9

1

11

43

Table 5. The number of Parent-Offspring pairs of J stock whales within and between sub-areas (copied from
Taguchi et al., 2017). The blue color indicates those sub-area pairings that are not consistent with the Hypothesis
C mixing matrices for the assumed Jw/Je stocks; the orange color indicates those sub-areas that are not inconsistent
with this hypothesis.
J stock
2

6

7CN

7CS

2
6
7CN
7CS

4

2
1
2

Table 4 indicates 18 examples of close-kin pairs that are inconsistent with the Hypothesis C split of O whales into
Ow and Oe stocks. This constitutes compelling evidence that this split is NOT supported by the data.
Table 5 indicates 2 examples of close-kin pairs that are inconsistent with the Hypothesis C split of J whales into
Jw and Je stocks. This is not quite as strong evidence as in the Ow-Oe case above, given the lesser number ofclose-kin pairs observed which are inconsistent with the Hypothesis C assumptions. Nevertheless this result, taken
together with the view of geneticists that the genetic evidence for a Jw-Je differentiation is in any case very weak
(IWC 2013b), is sufficient to conclude that this differentiation within J whales in Hypothesis C is not plausible.
In summary, taking account of the close-kin evidence now available, Hypothesis C may no longer be consideredplausible.
4.2 Primary Objective II (sei whale)


Information on stock structure

The most comprehensive studies conducted so far with regard to the stock structure of the North Pacific sei whales
were those presented at the mid-term JARPNII Review workshop in 2009 (Kanda et al. 2009) as well as thosepresented at more recent IWC SC meetings (Kanda et al. 2013). These studies used microsatellite DNA loci and
mtDNA markers to examine sei whales samples collected from almost the entire range of North Pacific.
Kanda et al. (2009) analyzed genetic variation at 17 microsatellite DNA loci and 487bp of mitochondrial DNA(mtDNA) control region sequences in the JARPNII samples (n=489) from 2002 to 2007 in the area between 143°E
and 170°E as well as in the commercial whaling samples (n=301) from 1972 and 1973 conducted in the area
between 165°E and 139°W. The results indicated no evidence of significant genetic differences within as well as
between the JARPNII and commercial whaling samples. Both females and males showed the same pattern of thestock structure. Sequencing and phylogenetic analysis of the mtDNA control region also showed no evidence ofthe genetic heterogeneity in the JARPNII samples as well as no spatially or temporally unique phylogenetic
clusters.
Kanda et al. (2013) examined genetic variations at 14 microsatellite DNA loci in the North Pacific sei whale using
biopsy samples obtained from the IWC-POWER surveys that covered the 173°E - 172°W area of the central North
Pacific in 2010 (n=13), 170°W - 150°W area of the central North Pacific in 2011 (n=29), and 150°W - 135°W
area of the eastern North Pacific in 2012 (n=35), and these obtained data were analyzed with those in Kanda et al.
(2009). This study allowed the authors to examine temporal (40 years apart between the POWER and commercial
whaling data) and spatial (143°E to 135°W area divided into western, central and eastern) genetic differences of
the North Pacific sei whales. Similar to Kanda et al. (2009), the results showed no evidence of the temporal genetic
differences between the recent POWER and past commercial whaling samples collected from the same area andno evidence of the spatial genetic differences among the western, central and eastern samples.
One drawback to these two studies was that there was no direct comparison among samples collected at the sametime of the year from the different areas over the North Pacific. Considering that sei whales conduct seasonal
migration from their breeding ground to feeding ground every year, development of stock structure hypothesis
should test the genetic differentiation in the samples collected in the same year that eliminate temporal negative
biases. If no genetic difference is found, this would hardly suggest a strong possibility of multiple stocks in the44

area. Kanda et al. (2015a) looked at genetic variation at the microsatellite DNA loci to analyze the JARPNII and
POWER samples collected from the same time of years in 2010, 2011 and 2012, respectively. Again the study
failed to demonstrate evidence of multiple stocks of sei whales in the North Pacific.
The in-depth assessment of North Pacific sei whale started at the 2015 IWC SC meeting. The IWC SC agreed toproceed with two initial alternative stock structure hypotheses: i) a single stock in the entire North Pacific asproposed by Kanda et al. (2015a;b), based on several pieces of evidence including genetics; and ii) a five-stock
hypothesis proposed in Mizroch et al. (2015), based mainly on the interpretation of mark-recapture data: Japan
coastal; North Pacific pelagic; Aleutian Islands and Gulf of Alaska; eastern North Pacific migratory; and Southern
North American coastal stock (coastal California) (IWC, 2015a). The IWC SC agreed that discriminating between
these two hypotheses is difficult in the absence of genetic data from the potentially extirpated stocks, and thus
both hypotheses are plausible (IWC, 2015a). The IWC SC agreed that the oceanic regions of the North Pacific arecomposed of a single stock (IWC, 2015a).
At the 2016 IWC SC meeting the Committee agreed that the genetic and mark-recapture data currently available
are consistent with a single stock in the pelagic region of the North Pacific (IWC, 2016b). Therefore the analyses
conducted to evaluate the effect on the sei whale stocks of future NEWREP-NP catches are based on the
hypothesis of a single stock in the pelagic regions of the North Pacific to which the catches to be made will be
restricted.
The estimated abundance of the species/stocks, including methods used and an assessment of uncertainty,
with a note as to whether the estimates have previously been considered by the SC

Hakamada and Matsuoka (2015) estimated abundance estimate based on IWC-POWER data from the 2010-2012
surveys using the design based estimator and detection function with covariates following the previous IWC SC
recommendations. Considering the discussion at the IWC SC in 2015, Akaike-weighted average of the estimateof 29,632 (CV=0.242) was endorsed for use in the in-depth assessment of the sei whales (IWC, 2016d).
Hakamada and Matsuoka (2016) estimated abundance of 5,086 (CV=0.378) in sub-areas 7, 8 and 9 in late season
based on the 2008 JARPNII sighting data using the design based estimator and detection functions consideringsome covariates of detectability. The estimates were presented at the final JARPNII review workshop and thereview workshop recommended that exploration of methods to account for sampling differences between areas
and years to obtain measures of short and long-term variation and trends and estimates the extent of additionalvariance due to changes over time in spatial distribution (IWC 2016c). The additional variance has not been
estimated yet and this would cause some underestimation of variances of abundance estimates.
Since the areas covered by these two surveys do not overlap, the abundance estimates from each have been added.
Hence computations have been conducted for a population estimate of 34,718 in 2010 and its lower 5%-ile of
24,530.
Provision of the results of a simulation study on the effects of the permit takes on the stock that takes
into account uncertainty

The analyses considered some of the recommendations from the NEWREP-NP review workshop, which werediscussed at the 2017 IWC SC annual meeting.
Figures 8 and 9 shows projections of the cases considered for the NP sei whales. The calculation was conductedbased on conditioned age-/sex-structured models (see Annexes 14 and 16). Regardless of parameters assumed,
there is no serious difference in the median trajectory between the two catch scenarios (0 and 134 per year) overthe 12 year research period, and therefore it is evident that the impact of an annual catch of 134 whales is negligible.

45

Figure 8. Population trajectory for the sei whales for 50 years under MSYR(1+)=1%. The black line shows themedian trajectory with the proposed catch of 100 replicates (gray lines). The green line is the median for no catch.
The horizontal dashed line shows the carrying capacity for the 1+ population.

Figure 9. Precautionary evaluation of population trajectory for the sei whales by hitting the lower 5%-tile ofabundance estimate in 2010.

5.

LOGISTICS AND PROJECT MANAGEMENT

5.1 Description of intermediate targets to allow for adequate review of progress relative to objectives
Figure 3 shows the kind of research activities and associated timelines under the NEWREP-NP’s Primary
Objectives I and II. As a general rule, progress in the works of NEWREP-NP under each Secondary and Ancillary
Objective will be presented to annual meetings of the IWC SC. This applies to both the collection of samples andanalysis of data using routine techniques (related to the research objectives of the program) as well the works on
feasibility studies related to new non-lethal techniques.
The proponents will provide additional information on sample and data archiving, and construct relational
database. As explained below they will construct a list of sample/data after each field survey, by research topic or
objective. By the mid-term review they will construct relational databases for specific research topics related toobjectives.

46

In general the work to assess the feasibility of new non-lethal techniques will be conducted during the first two
years (2017-18). The exception is the assessment of DNA-M for North Pacific baleen whales, which will be madeonce the feasibility study on Antarctic minke whale is completed (after 2018). A final assessment of the feasibilityof non-lethal techniques will be carried out during the mid-term review after the first six years, including anevaluation of possible modification of sample size of the lethal component of the program, on a whole-programbasis. The results of the feasibility study on age determination based on DNA-M will be relevant here.
The collection of routine data will be conducted during the first six years, and analyses will be carried out in somecases integrating the new data with those obtained in JARPN and JARPNII. Results for each Secondary Objective
will be presented and evaluated during the mid-term review, and the scientific review will assist the direction of
the analyses in the second period of the NEWREP-NP. Some of the research items requires the attainment of data
during the very first years and analyses will start subsequently (e.g. additional variance).
Details of the analyses to be conducted under each objective are provide in the annexes.
5.2 Description of overall project management including personnel and logistic resources
As for the whole program management, the Fisheries Agency of Japan (FAJ) will assume responsibility, including
provision of the necessary funding. Regarding personnel resources to be engaged in the program, scientists fromthe ICR will play the leading role in order to pursue the research activities and achieve the research objectives of
NEWREP-NP in collaboration with scientists from other domestic and/or foreign organizations (see Annex 20).
The proponents recognize the need for the recruitment of sufficient highly trained and qualified analyst/modellers
to improve study design, data analysis and review. The proponents will continue to look for suitable
analyst/modellers during the research period.
Below is a brief summary of ICR’s laboratories and personnel engaged in the implementation of the NEWREPNP (objectives are indicated in parenthesis):
Reproductive data and biological parameters (I (i), I (iv), II (ii)): Whale Biology Laboratory of ICR, Tokyo. Twoexperienced scientists.
Whale abundance estimates (I (ii), II (i)): two experienced scientists and one doctoral student.
Feeding ecology of whales (Ancillary Objective I): Feeding Ecology Laboratory of ICR, Tokyo. Threeexperienced scientists.
Genetics (I (i), I (iii), II (iii)): Genetic Laboratory of ICR. Three experienced scientists and two technicians.
Pollutant monitoring and whale health (Ancillary Objective II): Environmental Chemical Laboratory of ICR,Tokyo. One experienced scientist and one just-graduated scientist.
A number of researchers from ICR will be dedicated exclusively to field activities under the NEWREP-NP (4),supported by a number of part-time university students (2-3).
Research collaboration
Some of the data will be obtained by external laboratories and some of the analyses will be carried out incollaboration with external scientists (see details in Annex 20). A number of research topics under NEWREP-NP
will be treated in undergraduate and post-graduate university theses.
Research vessels
A number of research vessels will be available to ICR for carrying out the field work (lethal and non-lethal
components of the NEWREP-NP). Pictures and details of the vessels are available in Annex 21.
Report to the IWC SC
The proponents intends to provide relevant information concerning program management to the IWC SC every
year in an annual progress report for the SC’s comments and suggestions to facilitate steady progress of the
program in an open and transparent manner. This information will include progress achieved for each Secondary
Objective as noted in section 2.1 above, the involvement of external scientists/organizations and their roles, aswell as updates on financial and logistic resources. This annual update and comment process through the IWC SC

47

is expected to improve the management of the program throughout its duration.
5.3 Backup plan for contingencies
As research activities could be disrupted by natural factors such as an unusual distribution of whales and badweather, this proposed research plan establishes a contingency backup plan in order to respond to the contingency
and secure the scientific value of data to be collected by this research for the purpose of achieving the statedscientific objectives.
The backup plan would address three aspects; (i) adjustments of research protocols at the scene of disruption, (ii)adjustment of research plans including research period, sample size, and research areas after the year of disruption,and (iii) consideration of analysis methods to compensate the effects of disruptions. Possible issues arising froma disrupted research plan could include reduced sample size, unsurveyed research areas, sampling bias and missed
research periods. They might cause reduced accuracies, reduced randomness, and increased biases.
(i) Adjustments of research protocols at the scene and in the year of disruption
With regard to the variation in whale distribution, from the results of the dedicated sighting surveys under previous
sighting surveys, it was revealed that distribution of baleen whales in the survey area is narrower in the north andsouth due to the influence of the distribution of prey species which was affected by the water temperature. It isdifficult to predict those distributions in advance because they change every year and season with the temporalchanges in oceanographic structures.
At the planning stage, the tracklines for the whale sampling surveys are designed to cover wide range of survey
area. However, when actual surveys are conducted, some tracklines could be cancelled and/or new tracklines
would be designated in order to respond to the actual distribution of the whales that might be predicted by theoceanographic structures at that time.
In addition, some parts of the survey area could be affected by the path of typhoons and other bad weather. Fog
is often dominant in the northern cold waters. Therefore, tracklines would be sometimes forced to be amended to
avoid these bad areas affected by such temporal weather conditions.
It should be noted that reaction to those disruptions, such as the suspension of field research due to bad weather,
inevitably requires a case-by-case decision making. For example, in the North Pacific Ocean, typhoons frequently
pass through the survey area, but how to adjust field surveys depends on, inter alia, the predicted route andmagnitude of respective typhoon.
In case of a disruption, the head of the research (e.g. the cruise leader) will decide whether the research activities
should be continued or relocated to other research areas. These adjustments including resumption of the researchin other areas and periods than originally planned will be fully recorded and made available for the analysis
required in establishing adjusted research plans and in conducting scientific considerations for compensating theeffects of the disruption.
(ii) Adjustment of research plans including research period, sample size, and research areas after the year of
disruption
When the number of samples does not reach a target sample size, the reduced number could be carried over tothe latter years of the research plan and/or the whole research period could be extended when scientificjustification based on the careful analyses of the data collected is established in consultation with the IWC SC.
When this happens, effects on the sampled stock(s) will be reassessed.
Missed research periods and unsurveyed areas might also require adjustment proposed research plans. Scientificjustification for the need of adjustment research plans regarding period and areas will be provided along withpertinent data and its analysis to the IWC SC. Such an adjustment research plan will be established immediately
after the completion of the research of the year of disruption.
A summary information on the progress of the research, on an annual basis, in terms of samples obtained andareas and periods covered will be made public. This summary provides transparency in the implementation of
the proposed research and background for adjustment research plans if they become necessary.

48

(iii) Consideration of analysis methods to compensate the effects of disruptions
Effects of disruptions will be analyzed in terms of reliability of scientific data obtained. This would allow theconsideration of analysis methods to compensate the effects of disruptions. One of the potential problems likely
caused by the disruptions is spatially and temporally imbalanced sampling outcome. Like in the case of discussion
in the abundance estimation, lack of design-unbiasedness may be overcome by introducing the model-based
estimation approaches, where finding better spatial and environmental covariates is a crucial part for its success.
It is also important for the analysis that the adjustments described above in (i) and (ii) are well-planned andexecuted. However, as the effects of the disruptions could vary substantially, a case-by-case approach might beunavoidable. A high level of transparency will be necessary for the analytical methods employed to address theeffects of the disruptions.

6.

CO-OPERATIVE RESEARCH

6.1 Assessment of the degree to which the programme will coordinate its activities with related research
projects
This proposed research program is primarily intended to contribute to the improvement of conservation andmanagement of whale resources in the western North Pacific in accordance with the ICRW as shown in its research
objectives. It follows that its scientific output will be produced first and primarily for the review and discussion
in the IWC SC. At the same time, in line with an observation by the ICJ, there will be increased efforts to publish
its scientific achievements in peer-reviewed journals outside the IWC.
Participation of foreign scientists in the field surveys will be welcomed, so long as they meet the following
qualifications established by the Government of Japan: i) costs for participation, travel expenses to and from thehome ports, subsistence on board the research vessels and any other ancillary cost, will be covered by theparticipant; ii) indemnification and insurance for any casualty or personal injury while on board the research
vessels, will be covered by the participant; iii) participation of those who are found to have intentionally sabotaged
the implementation of the research in the field shall be terminated.
Research collaboration will be sought with relevant scientists and research institutions (national andinternational), in consideration of the objectives of the proposed research. In the case of Primary Objectives I
and II, and its Secondary Objectives, collaboration will be made, among others, with scientists of the IWC SC,
which have been heavily involved with RMP research in the past, and with scientists from national research
institutions such as the Tokyo University of Marine Science and Technology, National Research Institute of Far
Seas Fisheries, National Research Institute of Fisheries Science among others. The ICR will coordinate theresearch activities with other institutions. Annex 20 provides a list of collaborating research institutions, and ofresearch institutions/projects from where relevant data will be obtained, by NEWREP-NP objectives.
As in the case of JARPN and JARPNII, data obtained by this new proposed research program will be shared withmembers of the IWC SC in accordance with the IWC SC Data Availability Agreement (DAA) (IWC, 2004). Dataand samples from the research will be available for other accredited scientists and research organizations inaccordancewiththeprotocolforaccesstosamples/data
from
the
ICR
(http://www.icrwhale.org/pdf/appendix2.pdf) (see also Annex 22).
To facilitate the collaboration and analyses, databases will be created after each survey under this program
conducted by the ICR, which will specify the kind of samples and data collected during its research activities.
Databases which include data from laboratory work will be created in time for the mid-term review of the research
program in line with the Annex P (IWC, 2013a). According to the Annex P the proponent of the research program
should submit a preliminary data description document that explains the data two months before the Annual IWC
SC meeting prior to the specialist workshop that will review the proposed program. It also specifies that the final
data description document and the data themselves will be made available in electronic format one month after
the close of the Annual IWC SC Meeting. The mid-term review is expected after the completion of the first sixyear period of the proposed research plan.
In addition, efforts will be made to respond the NEWREP-A Review Panel’s specific recommendations regarding
research collaboration, which are also relevant here: (1) ad hoc collaborations on specific issues; (2) the
development of a formal protocol for outside scientists to express interest; and (3) the development of a strategy

49

to promote incorporation of external Japanese and/or foreign scientists into the research (IWC, 2016h). Regarding
the recommendation (1), NEWREP-NP will continue contacting potential partners, and co-operative research willbe identified and arranged for specific items in due course, preferably before research activities on such items
start. As for the recommendation (2), NEWREP-NP will develop and post such a protocol on the website of theICR (both in Japanese and English) well in advance of the first research cruise under NEWREP-NP (the same as
was the case for NEWREP-A) (and see section 6.2). With respect to recommendation (3), NEWREP-NP will: i)continue contacting specific potential collaborators directly; and ii) invite co-operative research widely throughthe internet (e.g. ICR’s website) and at related meetings (including those of the IWC SC) indicating specificresearch items for collaboration. An ‘annual progress report’ to the IWC SC, will also help to promote researchcollaboration with external scientists/organizations by including descriptions of the involvement of externalscientists/organizations and specification of their roles in the research (the same as in the case of NEWREP-A).
6.2 A note on the provisions for co-operative research (field studies; analytical studies)
Protocols for collaboration in field and analytical studies are shown in Annex 22, and are also available at the ICR
Home Page (both in English and Japanese).

7.

CONCLUSIONS

Primary, Secondary and Ancillary research objectives are clearly defined in this research plan for NEWREP-NP.
These objectives address topics important for conservation and management of sei and common minke whales in
the western North Pacific. The research under NEWREP-NP involves the use of both lethal and non-lethal
techniques. At this stage, lethal techniques are the only available techniques to obtain information on the age,
reproductive status, prey composition and consumption, and indices of nutritional conditions of the animals, which
are important information for addressing the objectives of NEWREP-NP. Some potential new non-lethal
techniques will be evaluated in NEWREP-NP through feasibility studies. Sample sizes are based on soundstatistical analyses, the levels are moderated and the statistical evaluation by the proponents indicates no negative
effect of the NEWREP-NP catches on the stock (s). This research proposal for NEWREP-NP established a time
period for the research, and timelines for addressing each Primary, Secondary and Ancillary objectives. Finally
this research plan for NEWREP-NP establishes provisions and protocols to facilitate research collaboration.
In summary all the items in the guidelines of Annex P were considered in the development of this research planfor NEWREP-NP.

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JARPNII data for the period 1994-2014. Paper SC/F16/JR30 presented to the JARPNII special permit expert
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(unpublished). 9pp.

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Annex 1
NEWREP-NP and consideration of the reasoning and conclusions in the Judgment of the International
Court of Justice (ICJ) on 31 March 2014
1 The procedure for drafting and development of NEWREP-NP and consideration of the reasoning andconclusions in the Judgment of the ICJ
Annex P provides the detailed procedure under which the review of the special permit program at the ScientificCommittee pursuant to Paragraph 30 of the Schedule is to be conducted and the items for review which should be
included in the proposal for new permit. NEWREP-NP is developed to address these items for review provided
in Annex P.
At the same time, Japan developed this plan for NEWREP-NP with full consideration of the guidance on theissuance of future special permits, provided by the ICJ Judgment on 31 March 2014 in the case Whaling in the
Antarctic (Australia v. Japan: New Zealand intervening) (for the Judgment, dissenting opinions, separate opinions
and declarations, see http://www.icj-cij.org/docket/files/148/18136.pdf). Although the subject-matter of the saidcase did not concern Japan’s scientific whale research program in the western North Pacific, the Judgment in its
reasoning part, stated that “[i]t is to be expected that Japan will take account of the reasoning and conclusions
contained in this Judgment as it evaluates the possibility of granting any future permits under Article VIII,
paragraph 1, of the Convention” (paragraph 246). The Court also stated that it will look to the authorizing State
to explain the objective basis of its determination to grant special permits (paragraph 68). Hence, in this researchplan, Japan explains the objective basis for its determination to grant special permits.
The details of Japan’s analysis of the salient parts of what was stated in the Judgment were provided in the“Research Plan for New Scientific Whale Research Program in the Antarctic Ocean (NEWREP-A)”3 which wasreviewed by the Scientific Committee in 2015 and hence will not be repeated in this proposed plan.
Japan has in particular taken seriously the Court’s finding that the decision to grant special permits under Article
VIII, paragraph 1, of the ICRW, “cannot depend simply on that State’s perception” (paragraph 61). Japan always
welcomes comments from outside that are based upon scientific consideration to which it will give due regard
even after the research plan is finalized. The process for development of the original proposal of the research planis outlined in Appendix.
The question “whether the programme under which these activities occur involves scientific research” (the firstlimb of the standard of review set forth by the Court, paragraph 67) is examined in more detail in relevant partsin Sections 2, 3, 5 and 6 of this proposed plan respectively.
The following part explains “whether, in the use of lethal methods, the programme’s design and implementation
are reasonable in relation to achieving its stated objectives” (the second limb of the standard of review, paragraph67), through the examination of each of the seven elements identified by the Court.
2 Reasonableness of the program’s design and implementation in relation to achieving its stated objectives
Element 1: “decisions regarding the use of lethal methods”
3Japan continues to uphold its scientific policy with regard to whales that it does not use lethal means
more than it considers necessary to achieve the research objectives. In this respect, the proponents are of
the view that the feasibility and practicability of non-lethal methods need to be evaluated in a systematicmanner. In assessing the feasibility and practicability of any non-lethal method, the proponents willconsider the following four questions: (1) whether a tissue and other samples can be obtained by a nonlethal method; (2) whether enough samples for statistical analysis can be obtained by the non-lethal
method; (3) whether the sample obtained by the non-lethal method can produce scientific informationcompared to that produced by a lethal sampling method; and (4) whether the cost for obtaining thesample/producing scientific information is reasonable. Questions 1 and 2 above are technical, Question
3 is analytical, and Question 4 is a logistical evaluation. It should be noted that, in order to conclude thata particular non-lethal method is feasible and practicable to the extent that it can practically replace alethal sampling method, all of the four tests need to be satisfied. In developing this research plan, theAvailable at http://www.jfa.maff.go.jp/j/whale/pdf/151127newrep-a.pdf.

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





feasibility of non-lethal methods as an alternative to or a means of reducing the planned scale of lethal
sampling was carefully reviewed (see Section 3).
With regard to Primary Objective I (common minke whale), it has been concluded in this plan that there
are no non-lethal methods available for obtaining age-data, sexual maturity, and body length, all of which
are required for achieving Objective I (i) and Objective I (iv) (see Section 3.1.1). These mean that theanswer to the question (3) above “whether the sample obtained by the non-lethal method can produce
scientific information compared to that produced by a lethal sampling method” is “No”. Furthermore,
Yasunaga et al. (2017) reports the difficulty of obtaining biopsy samples from common minke whales.
In other words, the answer to the question (2) “whether enough samples for statistical analysis can beobtained by the non-lethal method” “No”. Since it means that not all four criteria mentioned above canbe satisfied at once, the proponents concluded that no non-lethal method is feasible and practicable interms of achieving Primary Objective I.
Likewise, with regard to Primary Objective II (sei whale), it has been concluded in this plan that there
are no non-lethal methods available for obtaining age-data, sexual maturity, and body length, all of which
are required for achieving Objective II (ii) (see Section 3.2.1). These mean that the answer to the question(3) above “whether the sample obtained by the non-lethal method can produce scientific informationcompared to that produced by a lethal sampling method” is “No”. Since it means that not all four criteria
mentioned above can be satisfied at once, the proponents concluded that no non-lethal method is feasible
and practicable in terms of achieving Primary Objective II.
Furthermore, the proponents will also conduct further study on the feasibility and practicability of avariety of non-lethal methods including satellite tagging, biopsy sampling and their associated analyticalmethodologies (see Figure 2 in section 3.1.1). A final assessment of the feasibility of non-lethal
techniques will be carried out during the mid-term review after the first six years, including an evaluationof possible modification of sample size of the lethal component of the program, on a whole-programbasis. Specifically, this proposed plan includes the following feasibility study of the non-lethal methods:


Investigating the feasibility of age-determining methods other than earplug reading (i.e.
DNA methylation analysis);Conducting satellite tagging on common minke whales and sei whales to elucidate
movement within the feeding grounds and the location of their breeding grounds, in
preparation for the collection of genetic samples from the breeding grounds;

Elements 2 and 3: “the scale of the programme’s use of lethal sampling” and “the methodology used to selectsample sizes”Element 2, namely, “the scale of the programme’s use of lethal sampling” and Element 3, namely, “themethodology used to select sample sizes” are both related to the selection of sample sizes.
As noted above, there are several data that are indispensable for this research plan to achieve its statedobjectives, such as age data and sexual maturity that require lethal sampling.
With regard to common minke whales, Secondary Objectives I (i) and I (iv) are the most relevant as thescientific grounds for the sample size calculation are the requirement for age data, which can be obtainedwith the necessary accuracy only through lethal sampling methods, as key information (see Section 3.1.3)
o Sample size of common minke whale in sub-area 11 (Secondary Objective I (i)): it is known
that segregation by sex, age and reproductive status occur during migration of common minke
whale along the Japanese coast (Hatanaka and Miyashita, 1997). For that reason, information
on genetics alone is not sufficient and simultaneous collection of both genetics and biologicalinformation including age data is essential in order to evaluate the spatial and temporalmigration pattern of common minke whales, and to estimate pattern of stocks mixing by age
and sexual classes in sub-area 11. It was calculated that 47 animals are required to estimate themixing proportion of the J stock in this sub-area with sufficient precision (e.g. SE (p) less than0.1, see Annex 11 for details), which, combined with the biological data collected
simultaneously, will be essential for achieving the objective here, and both genetic andbiological information gained from these animals will be used in the conditioning of RMPISTs.
It should be noted that this estimate only applies for the first six years of NEWREP-NP. Moredetailed estimates of samples size for the objective of studying the temporal trend of the J stock
mixing proportion will be made once data have been accumulated in the first six surveys.
o Sample size of common minke whale in sub-areas 7-9 (Secondary Objective I (iv)): lethal
samples are required to obtain age information. This allows for improved conditioning of RMP
trials by providing estimates of population trajectories and their changing trends that are more57closely representative of the population's behavior than can be obtained using abundance
estimates alone. The extent of improvement increases with increasing sample size, which
provides part of the basis to make the sample size choice. On the other hand, there should beother considerations such as the need to restrain the lethal sample size to not more thannecessary to achieve the proposed research objective, the sufficient quantity of data to be able
to detect important changes to recruitment rates under different scenarios, the possible effect of
the catches on the stock, and the feasibility of research implementation. Taking account of thesefactors, the proponents concluded that the sample size of 123 per annum is the optimal size forthis research plan.
With regard to sei whales, Secondary Objectives II (ii) is the most relevant as the scientific grounds forthe sample size calculation are the requirement for age data, which can be obtained only through lethal
sampling methods; these data constitute the key information for this objective (see Section 3.2.3).
o Age data allows for improved conditioning of RMP trials by providing estimates of population
trajectories and their changing trends that are more closely representative of the population's
behavior than can be obtained using abundance estimates alone. The target is to estimate thenatural mortality rate by using SCAA methodology. In the population dynamics model thenatural mortality is assumed to be age-independent at M=0.04 and 0.05 (/year), and the MSYR
(1+) is set at 1 and 2.5%. These values are used not only for conditioning but also for generating
future data in the simulation context to assess the estimation performance for the natural
mortality rate. Robust results across four scenarios considered are that for an annual sample sizeof 100 animals or above, bias reduces to close to zero, and RMSE stabilizes at about 0.005(Annex 16). Allowing for possible over-dispersion in the age data, the annual sample size forsei whale is 134.

Element 4: “a comparison of the target sample sizes and the actual take”

As research activities could be disrupted by natural factor such as bad weather and other obstructions,this research plan establishes a contingency backup plan in order to secure the scientific value of data forthe purpose of achieving the established scientific objectives (see Section 5.3).

Element 5: “the time frame associated with a programme”
This research plan has set its research period as 12 years. It has also established “intermediary targets”,
as suggested by the Judgment, specifying concrete target outputs of the first 6 years, together with asystem of mid-term review. These time frames are determined in view of the prospects for scientificachievements and practical factors including the natural environment in the western North Pacific,
required time for verifications and analyses of collected data and information, the capacity of the research
and financial constraints (See Sections 3.1.1, 3.2.1 and 5.1).

Element 6: “the programme’s scientific output”
This research plan is primarily intended to contribute to the improvement of conservation andmanagement of whale resources in the western North Pacific in accordance with the ICRW as shown in
its research objectives. It follows that its scientific output will be produced first and primarily for thereview and discussion in the IWC SC. At the same time, in line with an observation by the Court, there
will be increased efforts to publish its scientific achievements in peer-reviewed journals outside the IWC.
It should also be noted that scientific data generated from this research will be made available to otherscientists both inside and outside the IWC SC in accordance with the IWC Data Availability Agreement(IWC, 2004) and the Institute of Cetacean Research (ICR)’s protocol for access to samples/data. Dataavailability arrangements are also specified in this plan (see Sections 6.1 and 6.2) in order to ensure thatthe research results will be utilized broadly by scientists worldwide.

Element 7: “the degree to which a programme co-ordinates its activities with related research projects”
Scientists of the ICR, which is expected to conduct the research program under this plan, have alreadystarted to strengthen existing collaboration with relevant research institutions that have direct interest in
the western North Pacific marine ecosystem such as the Tokyo University of Marine Science andTechnology, Japan’s National Research Institute of Far Seas Fisheries, National Research Institute ofFisheries Science among others. Scientific outputs of this research plan will be shared with those research

58

institutions and joint research will be proposed to relevant research institutions. Section 6 will deal withspecific discussions on this element (see also Annexes 20 and 22).
As the ICJ found that “Japan has complied with its obligations under paragraph 30 of the Schedule” to the ICRW
(paragraph 247(6)), it will continue to abide by this provision. This plan specifies, as required, (a) objectives of
the research (see Section 2), (b) number of the whales to be taken (see Section 3), (c) opportunities for participationin the research by scientists of other nations (see Section 6) and (d) possible effect on conservation of stock (seeSection 4). The plan was completed after the process of “review and comment” by the Scientific Committee, andcomments were given due regard.
References
International Whaling Commission. 2004. Report of the Scientific Committee. Annex T. Report of the Data
Availability Working Group. J. Cetacean Res. Manage. (Suppl.) 6: 1-76.
Hatanaka, H. and Miyashita, T. 1997. On the feeding migration of the Okhotsk Sea-west pacific stock of minke
whales, estimated based on length composition data. Rep. Int. Whal. Commn 47: 557-564.
Yasunaga, G., Mogoe, T., Tamura, T., Yoshida, H., Bando, T. and Kato, H. 2017. Results of the feasibility study
on non-lethal techniques to address the key research objective of JARPNII, based on data and samples obtainedin the period 2014-2016. Paper SC/J17/JR03 presented to the Expert Panel Workshop on the Proposed Research
Plan for New Scientific Whale Research Programme in the western North Pacific (NEWREP-NP). February 2017
(unpublished). 38pp.

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Appendix

1. The Transparency of the whole process
As in the case of NEWREP-A, Japan decided to have the draft of NEWREP-NP reviewed by external scientists
with a wide range of expertise to get comments and suggestions before it is submitted to the IWC ScientificCommittee (i.e. in addition to the official review process in accordance with the “Annex P”). This is a “voluntary”
review process open to external experts to obtain valuable inputs, including constructive criticisms, for improving
the draft research plan through e-mail correspondence from middle September to early October.

2. Chronology of the actual process for development of this proposed research plan
On September 16, 2016, approximately 150 external experts in the following categories were invited to participate
in Japan’s “voluntary” review process of the new research plan, by an e-mail sent from Japanese scientists
participating in the IWC Scientific Committee:
 Members of the IWC Scientific Committee (Participants in the 2016 meeting of the Committee and otherregular participants in the past); External expert panel members for the past special permit research reviews held by the IWC ScientificCommittee;
 Experts who provided witness testimony to the ICJ in the case concerning Whaling in the Antarctic;
 Chairs of scientific subsidiary bodies (and panel members) of RFMOs which covers the waters adjacent to
the western North Pacific (i.e. WCPFC, IATTC, NPFC and NPAFC ); Director and ex-Directors of Fisheries Resources Management and Research Division, Food and Agriculture
Organization of the United Nations (FAO); and Other experts who have good insights into the biology of marine mammals, the Pacific marine ecosystemand the conservation or sustainable use of marine living resources.
Seven (7) external experts from four (4) countries other than Japan had confirmed their interests in reviewing thedraft of the proposed research plan.
On September 23, 2016, the draft of the new research plan was sent by e-mail to the seven (7) external experts
who had confirmed his/her interests in the new research plan by that time. The draft was also sent to the otherexpert. By October 7, two (2) experts sent their comments on the draft. The received comments were consideredby the proponents and taken into account as much as possible in developing the final draft of the research planthat was submitted to the IWC SC on November 8, 2016. Japan had this proposed research plan circulated by the
IWC Secretariat to all Contracting Governments to the ICRW, for their review and comments in order to improve
the substance of the proposed plan.
More open opportunities for discussing the plan were secured during the official review process at the IWC
Scientific Committee after the proposed research plan was submitted in accordance with the “Annex P.” The
Expert Panel workshop to review the proposed plan was held in Tokyo from January 30 to February 3 2017. The
report of the Expert Panel was published on April 3, 2017 together with the proponents’ preliminary response to
the report. The findings and recommendations made by the Panel were duly considered and the proponents
submitted the revised proposed plan and results of the additional analyses for further discussions and comments
at the IWC SC annual meeting in May 9-21, 2017.
The final research plan for NEWREP-NP was prepared giving due regard to comments from the IWC SC annual
meeting in 2017.

60

Annex 2
CPUE data and trend for O stock of western North Pacific common minke whales

This annex provides some information on the analyses on stock assessment based on CPUE, conducted for coastal
minke whaling before the moratorium on commercial whaling.
CPUE series
There were two CPUE series used for the assessment of O stock of western North Pacific common minke whales
conducted in 1985 (IWC, 1986). CPUE1 and CPUE2 were used in CPUE analyses conducted by Japanese scientists(Ohsumi 1977; 1980; 1981; 1982; 1983; Wada 1985; 1986). Each CPUE is defined as follows (Wada, 1985);
CPUE1: Catch divided by total tonnage of the operating catcher boat and a corrected factor caused by introductionof the motor boat to small-type whaling (Ohsumi, 1980). Data are available from 1952.
CPUE2: Catch divided by total searching times for all the catcher boats. Data are available from 1977.
Time series of CPUE1 (1952-1983) and CPUE2 (1977-1983) are shown in Table 1. Figure 1 shows catch positionsof the common minke whale by small type coastal whaling 1977-1984 by whaling grounds. This figure showsthat catch distribution was not substantially change during the period.
Main results in Wada (1985; 1986) and discussions at IWC SC in 1984 and 1985
Wada (1985) estimated yearly trend of CPUE 1 (1952-1983) and CPUE2 (1977-1983). Yearly change in CPUE1
and CPUE2 were shown in Figures 2 and 3, respectively. Neither significant increasing nor decreasing trends wereobserved. This results was submitted to the IWC/SC in 1984.
At the IWC/SC, it was noted that since CPUE1 is the total seasonal catch divided by pooled tonnage, possible
shifts in the length of season and availability through the season and possible shifts between whaling grounds may
bias the trend in CPUE1 (IWC, 1985). Two opinions about reliability of the available CPUE data for a stock
assessment were expressed in the sub-committee. Some members argued that the CPUE series could be used forstock assessment. Other members felt that the CPUE1 was too crude for that use and that the CPUE 2 series was
too short to be used for calculation of replacement yield. It was agreed that a more refined analysis of the CPUE
series was needed to get a more reliable index of stock abundance for the time prior to 1977 (IWC, 1985).
Given the agreement at the IWC/SC, Wada (1986) estimated CPUE trend. First, regression analysis between
CPUE1 and CPUE2 for the period of 1977-1984 was conducted to predict CPUE2 in 1975 and 1976 using CPUE1
data. CPUE2 data for the period of 1977-1984 and predicted CPUE2 for 1975 and 1976 are shown in Table 2.
Using the CPUE2 data in Table 2, annual CPUE2 trends were estimated for 1977-1984 and 1975-1984. The
estimated trends are -1.39% and -1.41% for 1977-1984 and 1975-1984, respectively. Both of the estimated trends
were not statistically significant declines (Table 3).
Although the sub-committee recognized that a regression estimate might level off possible variations in the data,and consequently also influence the slope of the extended CPUE 2 series, it was plausible that this effect might besmall in this case. The sub-committee agreed to analyse the CPUE data from Wada (1986) using a model andprocedures analogous to that used in the assessment for the West Greenland stock. Population estimates in 1981
were assumed to be 10,015 (e.h. = 1.00) and 13,520 (e.h. =1.35) (IWC, 1985). Population trajectories using theassessment model are shown in Table 4. Some members of the sub-committee felt that the probabilities estimatedin Table 3 were sufficient as a basis for classifying this stock as SMS (provisional) since the apparent trend in
CPUE is not statistically significant under a regime of approximately constant catches. Other member considered
this stock should be classified as SMS (provisional), although the estimates indicated that the stock may be in therange from 51 to 65% of its initial size, so there may be a possibility that the stock is in the protection category.
The sub-committee therefore recommended that the Okhotsk Sea-West Pacific of the common minke whales
should be classified provisionally as a Sustainable Management Stock (IWC, 1986).
Discussions on CPUE at previous Implementation Reviews
Discussions on the utility of CPUE data for assessment purpose were conducted by the IWC SC during previous
Implementation Reviews in 2003 and 2013. This was done in the context of evaluation of plausibility of stock
structure scenarios (Kawahara, 2003).
In 2003 the IWC SC reminded its discussions held in 1991 that it was not possible to use the CPUE 2 series (the1977-87 data) as an indicator of trend in stock abundance because of i) changes in the focus of operations from61

year to year; ii) variability arising from other weather or oceanographic factors; and iii) changes in vessel
efficiency, for which correction factors were not available (IWC, 1992; 2004).
With regard the analyses conducted by Kawahara (2003) some IWC SC members noted that CPUE may not be areliable index of abundance especially in coastal operations where there may be changes in the focus of operations
from year to year and changes in vessel efficiency for which correction factors are not available. In addition, theyasserted that in the absence of a quantitative analysis to estimate the power of these data to detect trends, noconclusion could be drawn as to whether or not the data in Kawahara (2003) are consistent with some stock
structure scenarios. Other IWC SC members acknowledged that direct use of these data in a population model
fitting exercise, such as an assessment or conditioning, was inappropriate, indeed because of some of thereservations raised. Nevertheless they considered that CPUE data had utility to check/discriminate hypotheses
about population trends at a broad level (e.g. IWC, 2001, p178 for southern humpback whale). There was thus noconsensus among IWC SC members as to whether or not these CPUE data provided information on the relativeplausibility of the different stock structure hypotheses and trials (IWC, 2004).
Miyashita et al (2012) summarized information pertaining to catch, sightings and effort data from Japanese smalltype whaling during 1977-1987 in relation to the common minke whales and presented results to the IWC/SC in
2012. They concluded that catch or sighting per unit effort data can be useful as an index of population trend if
standardised. This analysis covered most of the factors identified during the First intersessional workshop for the
Implementation Review of western North Pacific common minke whales (IWC, 2013a). In discussion ofMiyashita et al. (2012) at the IWC SC in 2012 it was noted that there was considerable variation in whereindividual vessels operated during the year, and that if vessel movement reflects availability of whales, CPUE orsighting per unit effort data (SPUE) may be biased as an index of relative abundance (IWC, 2013b). It wassuggested that focusing on April-May only may provide more consistency, and consequently further GLM-based
analyses were conducted.
At the 2013 IWC SC meeting it was discussed whether analyses of CPUE data could be used qualitatively to
inform assignment of plausibility weights to the hypotheses (stock structure and MSYR) on which the ISTs werebased (IWC, 2013b). It was considered that further analysis and model diagnostics would need to be provided
before the resultant SPUE trends could be used to assist the assignment of plausibility to hypotheses related tostock structure and MSYR. The proponents are in the process of addressing these issues.
In conclusion some problems on the use of CPUE data were identified by the IWC SC, and some of them werealready addressed as explained above. Notwithstanding the proponents consider that the CPUE data can be used
as an index of stock trend at a broad level.
References
International Whaling Commission. 1985. Report of the Sub-Committee on Northern Hemisphere minke whales(Annex F). Rep. int. Whal. Commn. 35: 90-9.
International Whaling Commission. 1986. Report of the Sub-Committee on Northern Hemisphere minke whales(Annex F). Rep. int. Whal. Commn. 36: 79-88.
International Whaling Commission. 1992. Report of the Scientific Committee, Annex F. Report of the SubCommittee on North Pacific Minke Whales. Rep. int. Whal. Commn 42:156-77.
International Whaling Commission. 2001. Report of the Scientific Committee. Annex G. Report of the SubCommittee on the Comprehensive Assessment of Whale Stocks In-depth Assessments. J. Cetacean Res.
Manage. (Suppl.) 3:177-208.
International whaling Commission. 2004. Annex D Report of the sub-committee on the Revised Management
Procedure. J. Cetacean Res. Manage. (Suppl.) 6: 75-184.
International whaling Commission. 2013a. Report of the second ‘First intersessional workshop’ for the
Implementation Review of western North Pacific common minke whales. J. Cetacean Res. Manage. (Suppl.) 14:
357-70.
International whaling Commission. 2013b. Annex D1 Report of working group on the Implementation Review
for western North Pacific common minke whales. J. Cetacean Res. Manage. (Suppl.) 14: 118-36.

62

Kawahara, S. 2003. A review of Japan’s small-type whaling and CPUE analyses to address the relative plausibilityof trials on western North Pacific minke whale. Paper SC/55/IST16 presented to IWC Scientific Committee(unpublished). 9pp.
Miyashita, T., Kishiro, T. and Kanaji, Y. 2012. Operation information on the Japanese small-type minke whaling
1977-87. Paper SC/64/NPM4 presented to the IWC Scientific Committee (unpublished). 26pp.
Ohsumi, S. 1977. Catch of the minke whales in the coastal waters of Japan. Rep. int. Whal. Commn. 27: 164-6.
Ohsumi, S. 1980. Minke whales in the coastal waters of Japan, 1978. Rep. int. Whal. Commn. 30: 307-11.
Ohsumi, S. 1981. Minke whales in the coastal waters of Japan, 1979. Rep. int. Whal. Commn. 31: 333-5.
Ohsumi, S. 1982. Minke whales in the coastal waters of Japan, 1980 and a population assessment of the Okhotsk
Sea-West Pacific stock. Rep. int. Whal. Commn. 32: 283-6.
Ohsumi, S. 1983. Minke whales in the coastal waters of Japan, 1981, with special reference to their stock boundary.
Rep. int. Whal. Commn. 33: 365-71.
Wada, S. 1985. Further analysis of CPUE data for the Okhotsk Sea-West Pacific stock of minke whales.
Rep. int. Whal. Commn. 35: 295-8
Wada, S. 1986. CPUE trend for the Okhotsk Sea-West Pacific stock of minke whales, 1977-1984. Rep. int. Whal.
Commn. 36: 221-3.

63

Table 1. Yearly change in CPUE1 and CPUE2 (Wada, 1985).

64

Table 2. Yearly change in CPUE1 and extended CPUE2 for 1975-1984 of the Okhotsk Sea-West Pacific stock of
the minke whales.

1. Corrected for error in Wada (1985)
2. Predicted by regression model in Figure 3.
Table 3. Trend of the CPUE2 series for the Okhotsk Sea-West Pacific of the common minke whales in Wada
(1986).

65

Table 4. Population trajectories for various estimates of exploitable stock size in 1981 (IWC, 1985) and trend(1975-1984) for the O stock of the common minke whales.

66Figure 1. Whaling regions and catch positions of common minke whales, 1977-1984 (Wada, 1985; 1986). Region
A: Okhotsk Sea coast of Hokkaido, Region B: Pacific coast of Hokkaido, Region C: Pacific coast of Sanriku,
between 37oN and 41oN. Region G: Sea of Japan coast of Hokkaido. Bottom figure shows the catch positions in
1984.

67

Figure 2. Yearly change in CPUE1 series during 1952-1983 for Japanese coastal common minke whales (Wada,
1985).

Figure 3. Yearly change in CPUE2 series during 1977-1983 for Japanese coastal common minke whales (Wada,
1985). Region A: Okhotsk Sea coast of Hokkaido, Region B: Pacific coast of Hokkaido, Region C: Pacific coastof Sanriku, between 37oN and 41oN.

68

Figure 4. Regression between CPUE1 and CPUE2, for 1977-1984 and predicted CPUE2 for 1975 and 1976 (Wada,
1986).

Figure 5. Annual trend of CPUE2 for seasons 1975 to 1984 in Wada (1986). Vertical bars show the 95%
confidence intervals of the estimates for 1975 and 1976.

69

Annex 3
Summary of the results of the 2013 RMP/Implementation Review for
western North Pacific common minke whales
The main results of the RMP Implementation Review completed in 2013 are summarized based on the IWC/SC
report (IWC, 2014). Average catch limits over 100 years under 6 base case trials among the variants examined
are compared.
Definition of Variant
Figure 1 shows 22 sub-areas used for the Implementation Review for the western North Pacific common minke
whales. Table 1 summarized the definition of 11 variants examined. Variants 1-4, 6 and 7 didn’t include sub-areas
12 SW and 12 NE as a (part of) Small Areas whereas Variant 5 and 8-11 included sub-areas 12 SW and 12 NE.
Because abundance estimates for Small Areas or Combination Areas are used as input for application of the CLA,
abundance estimates for sub-areas 12 SW and 12 NE were used for Variant 5 and 8-11 and were not used under
Variants 1-4, 6 and 7. As mentioned in the Remarks in Table 1, catch limits for sub-areas 12 SW and 12 NE were
not taken into account under Variant 5. In summary, abundance estimates in sub-areas 12 SW and 12 NE wereused for applying the CLA under Variants 8-11 and were not used under Variants 1-7.
Average catch limit among the Variants
Table 2 lists the average catches by sub-area for each variant for the six base-case trials. Average catches arereported in Table 5 for years 1-10 and for the entire 100-year projection period. The average catch for Variants 17 are smaller than those for Variant 8-11. Sum of average catch (1-100 years) in sub-areas 7CS and 7CN for
Variants 9-11 are 17, 15 and 9, respectively.
Acceptability for each Variant
Table 3 shows acceptability of each Variant. Variants 9-11, which were the most appropriate Variants from theviewpoint of utilization of the resource, were not acceptable because performance was not acceptable for stock
OW in some trials under stock hypothesis C (Table 3). Figures 2-6 shows performance plot for trials B04, A04,
B03, C03 and C04 for two statistics (final depletion, upper panel, and minimum population ratio, lower panel)and for the stocks examined. Variants are ‘acceptable’ for a stock if their performance exceeds that for the 0.72
tuning of the CLA on one of the two statistics (solid dots above the upper horizontal line) and are ‘unacceptable’
for a stock if their performance is in the hashed area for both statistics. Variants are ‘borderline’ for a stock if they
are neither ‘acceptable’ nor ‘unacceptable’.
These figures show the following:
1.

2.

Variants 5 and 10, under which the average catch for 1-100 years was not 0 in sub-area 11, were not acceptablebecause performance of J stock under stock hypotheses A and B and that of JW stock under stock hypothesis
C is borderline (trials A04, B03, C03 and C04) or unacceptable (trial B04).
Variance 7, 9 and 11 are potentially acceptable with research and Variant 10 is unacceptable. Performance of
OW stock was unacceptable for Variants 7, 9, 10 and borderline for Variant 11 under trials C03 and C04.
Performance under some trials with stock hypothesis C were unacceptable for Variants 7, 9, 10 and 11.

Given these results of trials of the RMP/IR for the common minke whales, it is necessary to investigate thefollowing:With respect to input data that could be used for future RMP/IR trialsAbundance estimate for sub-areas where J stock animals are distributed including sub-area 11 and stock
structure in sub-area 11 (related to item 1 above).
Verify that the O stock is not sub-structured into Ow and Oe using non-genetic markers such as age data,
body length data and maturity data, in combination with genetic data,.
(related item 2 above).
Planning sighting surveys at to avoid increased additional variance in abundance estimate.

With respect to the framework of RMP or RMP/IR

Setting of sub-areas in according the results of the stock structure research i.e. if hypothesis C became notplausible, then there is no need to set up many of the current sub-areas.

70

Catch Cascading was conducted using abundance estimate in summer season regardless of the timing of thecatch. Explore methods for allocating the catch limit for Combination Area to Small Areas provided that thecommon minke whales usually migrates during catch season and that catch will be conducted in migration
corridor.

References
International whaling Commission. 2014. Annex D1 Report of working group on the Implementation Review for
western North Pacific common minke whales. J. Cetacean Res. Manage. (Suppl.) 15: 112-88.

71

Table 1. Summary of definition of variants 1-11 in IWC (2014). Description about sub-areas 5, 6 and 10 are
omitted for simplicity.
Variant12
3
4

Small Area
7CS, 7CN, 7WR, 7E, 8, 9*, 11
7+8, 9*, 11
7+8, 9*, 11
7CS, 7CN, 7WR+7E,+8, 9*, 11Sub-areas where catches are taken
7CS, 7CN, 7WR, 7E, 8, 9, 11
7CN, 9, 11
7CS, 9, 11
7CS, 7CN, 7WR, 9, 115

7+8+9*+11+12

7CS, 7CN, 7WR, 7E, 8, 9, 11

6
7

7+8, 9*, 11
7+8+9*+11

7CS, 7CN, 9, 11
7CN

8

7+8+9*+11+12

8,9

9

7+8+9*+11+12

7CS, 7CN, 7WR, 7E, 8, 9

10

7+8+9*+11+12

7CS, 7CN, 7WR, 7E, 8, 9, 11

11

7+8+9*+11+12

7CS, 7CN, 7WR, 7E, 8, 9

Remarks
Catch limit in Small Area 7+8 taken from 7CN
Catch limit in Small Area 7+8 taken from 7CS
Catch limit in Small Area 7WR+7E+8 taken from 7WR
The catches are cascaded to the sub-areas within the
Combination Area . The catch limits for sub-areas
12SW and 12NE are not taken.
Catch limit in Small Area 7+8 in 7 CS and 7CN
Cacth limit in the Small Area is taken from 7CN
Cacth limit in the Small Area is taken from 8 and 9
using catch cascading
Cacth limit in the Small Area is taken from 7CS, 7CN,
7WR, 7E, 8 and 9 using catch cascading
Cacth limit in the Small Area is taken from 7CS, 7CN,
7WR, 7E, 8, 9 and 11 using catch cascading. Catches
sub-area 11 occur in May and June.
Cacth limit in the Small Area is taken from 7CS, 7CN,
7WR, 7E, 8 and 9 using catch cascading. Catches from
7CS, 7CN, 7WR and 7E are reduced by 50%.

9*: Sub-area 9 excluding sub-area 9N.
A+B: Combination area of sub-areas A and B
Table 2. Average (over the six base-case trials) median annual commercial catches (years 1-100 and 1-10) by
sub-area and RMP variant.

72

Table 3. Summary of the ‘medium’ plausibility trials on which each of the variants failed to achieve

Figure 1. Sub-areas used during the 2013 RMP Implementation

Figure 2. Performance plot for trial B04

73

Figure 3. Performance plot for trial A04

Figure 4. Performance plot for trial B03

74

Figure 5. Performance plot for trial C03

Figure 6. Performance plot for trial C04

75

Addendum 1. The list of trials. Details of the trials are given in Appendix 2 of IWC (2014). Trial 24 is assigned
low plausibility and so is crossed through.

76Addendum 2. The factors in the Implementation Simulation Trials and their plausibility. The plausibility
assigned to the new Trial 31 occurred during 2013 IWC/SC meeting (IWC, 2014).

77

78

Annex 4
A summary of the new information on stock structure in the western North Pacific common minke whales
presented to the JARPNII final review workshop

The relevant documents on common minke whale stock structure presented to the JARPNII final review meetingwere the following: Pastene et al. (2016a; b), Bando and Hakamada (2016) and Kitakado and Maeda (2016). Asummary of each of these studies is presented below.
Pastene et al. (2016a) examined a total of 4,275 western North Pacific common minke whales with a set of 16
microsatellite DNA loci and the program STRUCTURE to assign individuals to either J or O stocks. The relevant
information in this paper for the discussion in the SDWG (stock definition working group) was on the unassigned
individuals in the STRUCTURE analyses. A simple simulation exercise showed that the number of unassigned
individuals decreased with the increase in the number of microsatellite loci used, and they were widely distributed
geographically (Figure 1). It was concluded that the unassigned individuals are not related to the occurrence ofadditional stock structure. Based on these results, the authors considered that only the animals assigned to the Ostock with assignment probability greater than 90% could be used to investigate additional structure with the Ostock using alternatively analytical approaches.
Pastene et al. (2016b) examined the genetic population structure of ‘O’ stock common minke whale in the western
North Pacific based on mitochondrial DNA control region sequencing (487bp) and microsatellite DNA (16 loci).
Samples used in the tests of homogeneity were obtained during the surveys of the JARPN and JARPNII in subareas of the Pacific side of Japan between 1994 and 2014 (n= 2,071 for microsatellite; n=2,070 for mtDNA).
Whales were assigned to the ‘O’ stock by the analysis of STRUCTURE presented in Pastene et al. (2016a). Tests
based on both genetic markers and different grouping of the samples showed no evidence of sub-structuring inthe ‘O’ stock common minke whale in the Pacific side of Japan. A simulation exercise showed that the statisticalpower of the homogeneity test was high. In addition, a Discriminant Analysis of Principal Components (DAPC)
based on the total samples used in Pastene et al. (2016a) showed clear differentiation between J and O stock
whales but no evidence of sub-structuring within the O stock samples. Consequently the results of this study
suggested a low plausibility for the hypothesis of sub-division of the O stock common minke whale into OW and
OE.
Bando and Hakamada (2016) conducted a morphometric analyses to examine stock structure of western North
Pacific common minke whales by using external measurement data collected during 1994 and 2014 JARPN and
JARPNII surveys. External measurements of mature males were first compared between O and J stock animals
assigned by the microsatellite DNA analysis. Then only O stock animals were compared among sub-areas. The
analytical procedures used were the Analysis of Covariance (ANCOVA) and Discriminant Analysis (DA).
Significant differences were detected between O and J stock whales. J stock animals had longer head region
compared to O stock animals. No significant differences were detected in O stock animals among sub-areas. The
results of the present morphometric analyses provided no evidence for sub-structuring of the O stock into Ow andOe as proposed in one of the hypotheses used in the RMP Implementation, as common minke whales from coastaland offshore sub-areas did not differ in morphometric characters.
Kitakado and Maeda (2016) used catch-at-age data for common minke whales in the western North Pacificprovided by the JARPN/JARPNII program to refine existing RMP Implementation Simulation Trials (ISTs) in a
simple way, so as to investigate the relative plausibility of the single- and two (Ow and Oe) stock hypotheses for
the O whales in the Pacific side of Japan. While the single stock scenario seems consistent with these age data, it
is difficult to reconcile the two stock hypothesis with these data particularly because of the relative absence ofyounger whales in a supposedly separate discrete Oe stock. In other words, the analysis based on age data supports
the single O stock scenario. The analysis demonstrates the importance for management purposes of obtaining age
data for the common minke whales in the western North Pacific, which in turn necessitates lethal sampling. Suchage data need to be incorporated in the conditioning of revised RMP ISTs for common minke whales in this region.
During the JARPN II final review meeting the proponents provided preliminary results on kinship analyses.
Preliminary results of the analysis of the total samples of over 4,000 animals, found a total of 22 parent-offspring
pairs for the O-stock. Half of the pairs showed one in the coastal and the other in the offshore area. This work isin progress and a paper will be prepared for a future meeting.

79

It is considered that a substantial amount of new information on stock structure of common minke whale has been
accumulated since the last Implementation Review, which was based on data collected till 2007. Of particularimportance was the larger number of new samples (around 1,700), a new analytical procedure (DAPC, kinship,
statistical power of the heterogeneity test), and the availability of age data.
Most of the analyses in the documents summarized above responded to recommendations made during the 2009JARPNII mid-term review. According to these, results of all different analyses indicate a single O stock distributed
from the Japanese coast till approximately 170°E. In the last IWC SC meeting in 2016, however, there was notunanimous support for this view, and the IWC SC suggested some additional genetic analyses on kinship. On theother hand the IWC SC broadly agrees on the value of age data in ISTs. In the case of western North Pacificcommon minke whale, additional age data are very important to verify the existence of a single O stock. Bothlines of research (kinship and SCAA) will be implemented in NEWREP-NP.
References
Pastene, L.A., Goto, M., Taguchi, M. and Kitakado, T. 2016a. Temporal and spatial distribution of the ‘J’ and‘O’ stocks of common minke whale in waters around Japan based on microsatellite DNA. Paper SC/F16/JR38
presented to the Expert Panel Workshop of the final review on the western North Pacific Japanese Special
Permit programme (JARPN II), Tokyo, February 2016 (unpublished). 14pp.
Pastene, L.A., Goto, M., Taguchi, M. and Kitakado, T. 2016b. Updated genetic analyses based on mitochondrialand microsatellite DNA indicated no sub-structure of the ‘O’ stock common minke whale in the western North
Pacific. Paper SC/F16/JR40 presented to the Expert Panel Workshop of the final review on the western North
Pacific Japanese Special Permit programme (JARPN II), Tokyo, February 2016 (unpublished). 19pp.
Bando, T. and Hakamada, T. 2016. Morphometric analysis on stock structure of the O stock common minke
whale in the western North Pacific. Paper SC/F16/JR41 presented to the Expert Panel Workshop of the final
review on the western North Pacific Japanese Special Permit programme (JARPN II), Tokyo, February 2016
(unpublished).10pp.
Kitakado, T. and Maeda, H. 2016. Fitting to catch-at-age data for North Pacific common minke whales in the
Pacific side of Japan. Paper SC/F16/JR43 presented to the Expert Panel Workshop of the final review on thewestern North Pacific Japanese Special Permit programme (JARPN II), Tokyo, February 2016 (unpublished).
15pp.

A)

80

B)

Figure 1. Location of the common minke whales that were assigned to O stock (green), J stock (blue), andunassigned (red), based on STRUCTURE. A) total areas; B) zoom of A) for coastal areas.

81Annex 5
Overview of JARPN/JARPNII outcomes
Below are some key scientific outcomes of JARPN and JARPNII combined (see details in Tamura et al., 2016
and IWC, 2016):
Feeding ecology and ecosystem studies


Analyses of seasonal spatial distributions of common minke, sei and Bryde’s whales in the JARPNII
research area using Generalized Additive Models (GAM) indicated that spatial segregation occurredamong the three baleen whale species although some overlaps occurred. Given this, the extent of directinteraction among whale species could be minimal although indirect interaction could occur as they sharethe same prey species.

The prey consumption by whales in both offshore and coastal waters were estimated based on energetic
equations, and accounted for some uncertainties such as the number of whales distributed in the researcharea, body weight of whales, consumption models, energy content of prey species, assimilation efficiency
and the ratio of low/high feeding intake of whales. As a consequence, estimates of prey consumption ofwhales in coastal and offshore waters were made with an improved level of precision.



In offshore waters, the prey preferences of baleen whales were estimated based on data from concurrent
surveys of cetacean and prey species. Common minke whale showed preference toward pelagic fishes
such as Japanese anchovy and Pacific saury. Bryde’s whales showed preference for Japanese anchovy
while sei whales showed preference for copepods.



In offshore waters the yearly trend of prey compositions in Bryde’s and sei whales was different. The
Bryde’s whale showed no trend, feeding every year on krill and Japanese anchovy. On the other handdrastic yearly changes were observed in the prey of sei whales, shifting from Japanese anchovy in the
period 2002-2010 to mackerels and Japanese sardine after 2010.



In coastal waters off Kushiro yearly changes in the prey species of common minke whale, were observed.
It shifted from Japanese anchovy and Pacific saury in the period 2002-2011 to Japanese sardine andmackerels after 2011.

In Kushiro waters immature animals of common minke whale tend to feed on walleye Pollock on thecontinental shelf and slope regions. Mature animals feed on Japanese common squids and Pacific sauryin the area outside of the continental shelf. These results suggested that migration and prey preference ofcommon minke whales in the coastal waters off Kushiro in autumn possibly differ with their maturity
stage. It is suggested that the feeding strategy of common minke whales might change to adapt to the
local environments.



The marine ecosystem of the western North Pacific from 1994 to 2013 (20 years) was modeled using awhole ecosystem model, Ecopath with Ecosim (EwE). Although the results are still preliminary, theconstructed model will serve as a basis for further investigation on ecosystem level changes (e.g. regime
shift) observed in the region.

A statistical analysis was conducted to assess predation impacts of the common minke whales on thesand lance population off Sanriku region. Results showed that the predation by the common minke
whales accounts for a certain proportion of the current adult biomass for the sand lance population
although the level of the proportion is sensitive to the model assumption.

Monitoring environmental pollutants in cetaceans and the marine ecosystemYearly changes of Hg (1994-2014) and PCB (2002-2014) levels in tissues of common minke, sei and
Bryde’s whales from the western North Pacific were examined considering several explanatory variables,such as sampling location, biological data and main prey item. Results suggested that the backgroundlevels of Hg and PCB were stable during the JARPN/JARPNII research period.

82



Results of organochlorines isomer analyses in whale tissues showed that almost no recent inputs of DDT,
HCH and CHLs have been released into the JARPNII research area.

No significant differences were found in the total levels of Hg between J and O stocks common minke
whales off Sanriku.

The analysis of the relationship between total Hg levels in whale tissue and main prey species in whale’s
stomachs revealed an effect of prey species on whales. Such effect was not observed for PCB. Based onthese results, it is suggested that the influence of prey species on pollutant accumulations in whales, isdifferent depending of the kind of pollutant.



Monitoring of I131, Cs134 and Cs137 levels in large whales from the western North Pacific after the
Fukushima nuclear accident in 2011, was carried out. Based on a comparison with radiation safety
threshold in humans, it was suggested that the levels detected do not represent a health risk for whales.



Information on the utility of new biomarkers for future studies on adverse effects of organochlorines inbaleen whales, and for future studies on potential vulnerability to viral infection in whales, was provided.

Stock structure of large whales
Monitoring of the O and J stock common minke whales in Japanese waters, was attained. Almost all
animals from the Sea of Japan belonged to the J stock while all animals in the Pacific side east of SA7WR
belonged to the O stock. Intermediate sub-areas (7CN, 7CS, and 11) contained animals from both stocks.

In SA2 the J stock common minke whale animals were predominant through the year. In SA7CS andSA7CN the proportion of J stock animals increased in autumn/winter and decreased in spring/summer.
The O stock had a reverse trend.

Results of genetics and morphometric analyses showed no evidence of O stock common minke whale
sub-structuring into OW and OE in the Pacific side of Japan.

Preliminary catch-at-age data for common minke whales provided by JARPN/JARPNII were useful torefine existing RMP ISTs. Catch-at-age analyses showed that it was difficult to reconcile the two O stock
hypothesis (OW and OE) with age data.



Results of genetic analyses showed no significant heterogeneity between Bryde’s whales in sub-areas
1W and 1E. Results suggested genetic differentiation between whales in sub-area 1 and sub-area 2.

Results of the genetic analysis confirmed the view of a single stock of sei whale in the pelagic regionsof the North Pacific.

Others

Advances were made in ageing western North Pacific common minke whales based on earplugs. Agereadability was 45.2% (males) and 41.2% (female) of common minke whales sampled by JARPN and
JARPNII.



Advance were made in ageing western North Pacific sei whales based on earplugs. Readability of all
samples was 63%.

References
International Whaling Commission. 2016. Report of the Expert Panel of the final review on the western
North Pacific Japanese Special Permit programme (JARPN II). Paper SC/66b/Rep06 presented to IWC
Scientific Committee (unpublished). 96pp.
Tamura, T., Kishiro, T., Bando, T., Yasunaga, G., Murase, H., Kitakado, T. and Pastene, L. A. 2016. The Japanese
Whale Research Program under Special Permit in the western North Pacific Phase-II (JARPNII): results and83conclusions in the context of the three main objectives, and scientific considerations for future research. Paper
SC/F16/JR1 presented to The Expert Panel Workshop of the final review on the western North Pacific JapaneseSpecial Permit programme (JARPN II), Tokyo, February 2016 (unpublished). 68pp.

84

Annex 6
Whale sampling survey design under Primary Objective I (common minke whale)
Research area
Sub-areas 7 (7CN, 7CS, 7WR, 7E), 8, 9 and 11 are proposed as the research areas for Primary Objective I. Subareas 7, 8 and 9 are particularly important for the research under Secondary Objective I (iii; iv) while sub-area
11 is particularly important for the research under Secondary Objective I (i).
Research period
Annual surveys in the sub-areas above will be conducted between April and October, which is the migratory
season of common minke whale around Japan. The research period under the NEWREP-NP is planned to be 12
years with a mid-term review after the first six years (see rational in section 3.1.1 of the main text).
Target species and sample sizes under Primary Objective I
The target species is the common minke whale. The annual sample size in sub-areas 7-9 will be 123 animals
while that in sub-area 11 for the first 6 years will be 47 animals. In the Pacific side of Japan, 80 will be sampled
in coastal subareas (7CS and 7CN) and 43 will be sampled in offshore waters (sub-areas 7WR, 7E, 8 and 9) (seedetails on sample size estimates in Annex 11).
The number of samples by month, year and sub-area collected by JARPN/JARPNII in the period 1994-2016 andthe expected number of samples by NEWREP-NP in the period 2017-2022, are shown in Tables 1 and 2,
respectively.
Research vessels
Five small type whaling catcher vessels (Sumitomo Maru No. 51; Taisho Maru No. 3; Koei Maru No. 8, Katsu
Maru No. 7 and Seiwa Maru) will be employed for sampling of common minke whales in sub-area 11 and subareas 7CS and 7CN. The pelagic research vessels (Nisshin Maru research base and two sampling and sighting
vessels, Yushin Maru No. 1 and 3) will be employed for sampling common minke whales in offshore waters(sub-areas 7-9). See details of the research vessels in Annex 21.
Survey procedures
Sampling in sub areas 7CN, 7CS and 11
A land-based operation system will be incorporated for whale sampling in the coastal sub-areas. Basically thevessels depart the port every morning, and return to the port every night. In order to cover a larger area within sub
areas 7CS, 7CN and 11 (excluding the EEZ zones of foreign countries), whales will be sampled in different ports
regardless of whether or not those ports have a land station to conduct the biological survey. All whales sampled
will be transported by tracks from the port to the nearest land station. Nisshin Maru may be used as a researchstation when necessary.
Land stations with a research head office will be established in the respective season for biological sampling,
flensing, and commanding the operation of the sampling vessels. Land stations will be established in Kushiro(sub-area 7CN), Ayukawa (sub-area 7CS) and Abashiri (sub-area 11).
The sampling procedure is designed taking account operational capacity, ability, and arrangements of the smallboats, and is different from the random sampling procedures adopted by the NEWREP-NP offshore component
using large vessels (Nisshin Maru research fleet). The general procedure is as follows:(1) A predetermined course (direction from the port) at an angle of regular intervals (usually 10-15 degreeintervals) are set up by the head office, and allocated to the respective boat (Figure 1-A). The boats departthe port with respective course, and start searching at a survey speed of 10-11 knots.
(2) The boats search along the course until common minke whales are sighted, or continue the search until
they arrive at 30 n. miles from the port (Figure 1-B). Each boat tries to take her first encountered whale.
If the boats miss the targeted whale, they resume searching along the course.
(3) If the boat captures a whale, the boat returns to the port transporting the animal to the research station.
During the return, searching is resumed, and other common minke whales sighted are targeted forsampling, when the situation allows it. After the whale is transported to the station, the boat departs again

85

from the port. Carrying vessel (s) might be deployed to transfer caught whales from the small boats tothe port so that the boats could focus on sampling.
(4) After arriving at 30 n. miles from the port, the boats change the course freely, and continue the searching(Figures C, D).
(5) When the weather or sea state are expected to worsen before arriving at 30 n. miles from the port, thenthe boats change the course freely at that point. When the weather changed to more bad conditions (waves
of around 2m height or Beaufort 4 or more), the boats return to the port.
(6) Searching is continued until 30 minutes before sunset, and then all boats return to the port.
(7) The predetermined course is changed every day to cover broader areas.
(8) If the vessels could not reach the number of common minke whales targeted, Nisshin Maru research fleet
will conduct sampling activity in sub areas 7CN, 7CS as a backup survey to increase the sampling effort.

Searching will be carried out from the top barrel (6 to 7m above the surface) by all crew members (4 to 5 persons),
except those persons handling the boat. Searching will be also conducted occasionally from the upper bridge by
one or two crew members and a researcher. At least one researcher will be on board in each boat, and will record
information on sighting, sampling and searching effort, e.g., time and location of sighting and sampling, species
and school size sighted, and activity and cruise tracks of the boat. Weather information (weather, visibility, windforce, and sea surface water temperature) will be also recorded at every hour.
Sightings of whales will be classified into primary and secondary sightings. The primary sightings are those seen
during normal searching mode (sighting effort from the top barrel). The secondary sightings are those made inmode other than normal searching mode, e.g., during closing or chasing target whales, when there is no observerin the top barrel, or outside of the research time.
All primary and secondary sighting, excluding cow and calf pairs, will be targeted for sampling. Observers on the
top barrel will count the number of whales in the school and will estimate the body length of each animal. If asighting is a solitary whale, the whale will be sampled immediately after the body length estimation. If a school
consists of two or more animals, the researcher will assign a serial number to each individual and the first targeted
whale will be chose for sampling using tables of random sampling numbers (TRS). When two whales are sampledfrom a school, the second target whale will be selected by the same manner after the first animal is sampled. In
this case, the remaining individuals are renumbered according to the latest position in the school.
Sampling is made by 50mm whaling cannon. In order to maintain the human safety during the operations, chasing
will be usually limited to a maximum of 120min.
The whale sampled will be pulled onto the rear deck of the vessel and will be transported to the port. At the port,
the whale will be lifted up from the vessel by a crane, using a wire net, and transported to the land station by an
11-tons freight trailer. All the whales sampled will be biologically examined by researchers on the land station inalmost the same manner as that for the JARPNII.
Details of the field, laboratory and analytical procedures are given in section 3.1 of the main text.
Ayukawa and Kushiro land stations will be switched depending on the migration of the common minke whale;e.g. Ayukawa from spring to summer: Kushiro from summer to autumn.
Abashiri (sub-area 11) will be surveyed in different seasons as follows (just for indication):
2017: Summer
2018: Autumn
2019: Spring
2020: Autumn
2021: Spring
2022: Autumn

86

(ii) Sampling in sub-areas 7WR, 7E, 8 and 9
As indicated above sampling of common minke whales in offshore waters will be carried out by the sampling andsighting vessels attached to the research base Nisshin Maru, which will be also engaged in sampling of sei whales
under Primary Objective II. Sampling procedure for minke and sei whales in offshore waters is described in Annex
12.

87Table 1. Distribution of available samples of common minke whale, by year, month and sub-area.

88

Table 1 (Cont.)

89

Table 2. Tentative distribution of common minke whale samples under the NEWREP-NP, by year, month andsub-area
YearMonthTot

Sub-areas
11

7CS

7CN

7WR

7E

8

9

2017-42017-52017-62017-72017-8

47
43

170
80

2017-92017-10
2017-112018-42018-5
2018-62018-7
2018-8

170

80

43

80

43

80

43

80

43

80

43

47

2018-92018-10
2018-112019-42019-547

2019-6
2019-7
2019-8170

2019-92019-10
2019-112020-42020-52020-62020-72020-8170
47

2020-92020-102020-112021-42021-5472021-62021-72021-81702021-92021-102021-112022-42022-52022-62022-72022-82022-9170472022-102022-1190

Figure 1. Schematic diagram showing the searching mode for sampling in the coastal component of the NEWREPNP. Arrows with letters ‘a’ to‘d’ indicate examples of the movements of respective small-type whaling
catcher boat.

91

Annex 7
Secondary Objective I (i)Investigate the spatial and temporal occurrence of J stock common minke whales around Japan, by sex, age andreproductive status
Field and laboratory work, and analytical procedure
Background
Information on stock structure, including the information on distribution, movement and mixing of the O and J
stocks is important for the RMP Implementation of western North Pacific common minke whale. With theimplementation of JARPN and JARPNII and the development of analytical techniques for examining genetic data,a substantial amount of information has been obtained on the distribution and mixing of O and J stocks around
Japanese waters.
The last genetic study on distribution and mixing proportion of O and J stocks around Japanese waters was basedon JARPN/JARPNII and bycatch samples obtained till 2014 (Pastene et al., 2016). The study showed that thecomposition of O and J stocks, estimated by microsatellite DNA and the STRUCTURE program, differs amongareas and survey component (Figures 1 and 2).
It was concluded during the RMP Implementation that the J stock is heavily depleted. However this perception isdifficult to reconcile with several lines of evidence. For example J stock animals showed a sustained or increasing
trend of bycatches for a recent period of more than 10 years, while decreasing in the amount of set nets in which
this bycatch occur (Table 1).
Another line of evidence is the proportion of J-stock animals in sub-area 7, which increased from 1.8% in thecommercial whaling in 1983-1987 (Goto, unpublished data) to 21.7% for the coastal JARPNII surveys in 20022014 (Pastene et al., 2016). Commercial whaling in 1983-1987 in sub-area 7CS (Sanriku) was conducted mainlyin the months April-June, which is similar to the period of coastal whaling by JARPNII in the same sub-area. The
distribution range of J stock animals on the Pacific side of Japan is limited to the coastal zone, mainly within 30
miles from the coastline. When commercial whaling-Sanriku is compared with JARPNII whaling-Sanriku, alarger percentage of J stock animals was estimated for the later, for distances <10n miles and 10-20n miles fromthe coastline. Sample size for distances >20n miles is very small for JARPNII (see details in Appendix 1).
The information summarized above could indicate the possibility of an increasing J stock that is expanding its
distribution.
Information on distribution and mixing proportion of J and O stocks in sub-area 11 is limited (see details in Table2), but a similar trend for the J stock proportion as that observed in sub-area 7 is expected. Clearly additional
sampling in different months is required for sub-area 11, and NEWREP-NP will carry out such sampling andanalyses on J and O stocks mix proportion trend in that sub-area.
Hatanaka and Miyashita (1997) showed that O stock animals segregate by sex and reproductive status in thewestern North Pacific. A similar pattern of segregation can be expected for J stock animals. The study suggested
that in order to evaluate the spatial and temporal migration pattern of whales, both genetic and non-genetic datasuch as age, sex, body length and sexual maturity, is required.
This annex explains the field, laboratory and analytical procedures associated with this Secondary Objective.
Methods
Field work
Genetic samples
Skin tissues of common minke whales will be taken during NEWREP-NP and stored in 99% ethanol until DNA
extraction. In the case of biopsy sampling, the details of equipment and sampling procedure are described in
Annex 19.
Morphology (flipper coloration pattern)
Morphological differences in the size and pattern of the white patch on the flipper of each whale (Nakamura etal., 2016) will be examined to assist the genetic assignment into J and O stock animals (see below). The
proportional size and boundary area pattern of the white patch on the flipper of each whale will be the focus for92this study. The following three flipper characteristics are measured after the flipper is dissected from the whale’s
body: flipper length, distance from the tip of the flipper to the distal end of the white patch and the tip to mesial
end of the white patch. These points will be measured to millimeter scale accuracy using measuring tape or astainless steel caliper.
Biological samples(1) Age
There are two potential methods to collect age-data for common minke whales: counting of growth layer groups(GLGs) accumulated in the earplug of whales and the use of racemization ratio of aspartic acid in eye lens.
Earplug
The left and right earplugs with glove-finger are collected carefully, and immediately fixed in 10% formalinsolution until age estimation. Because young whales have soft and easily broken earplugs, earplugs of small
individuals are collected using the method of gelatinized extraction, following Maeda et al. (2013).
Racemization
Eye lens from both sides will be collected from each whale and stored in polyethylene bags at -80°C until analysis.
(2) Body length
Body length is measured in a straight line from the tip of the snout to the notch of the flukes for all animals.
(3) Maturity status
Maturity of females will be preliminary determined in the field by the presence or absence of corpora
lutea/albicantia in both ovaries. Both ovaries are preserved at -20℃.
Maturity of males will be preliminary determined in the field by testis weight, and confirmed later by examinationof histological testis samples. Testis weight (heavier side) of more than 290g is defined as sexually mature (Bando
unpublished data). Testis tissue samples will be collected from all males and fixed in 10% formalin solution.
Presence of fetus will be examined by cutting both sides of the uterine horn. Photographic records, body length
and weight measurements and sex identification will be conducted for each fetus.
Laboratory work
Genetics
Laboratory work and data analyses described in this Annex will follow the IWC SC’s guidelines for DNA data
quality (IWC, 2009) as much as possible. Sampling and laboratory procedures of the genetic laboratory of theInstitute of Cetacean Research were summarized by Kanda et al. (2014), and the IWC SC agreed that the paper
had responded appropriately to some relevant recommendations on DNA data quality from the JARPA II review
workshop (IWC, 2015a, b). In 2016 additional information was provided by the proponents on estimates of
microsatellite genotyping error rates and again, the IWC SC agreed that the work presented had addressed arecommendation on DNA data quality from the JARPNII final review workshop (IWC, 2016).
Total genomic DNA is extracted from tissue pieces preserved in 99% ethanol at room temperature,using Gentra Puregene kits (QIAGEN). Extracted DNA is stored in the TE buffer (10 mM Tris-HCl, 1 mM
EDTA, pH 8.0).
For microsatellite DNA (msDNA), a set of 16 loci are used: EV1, EV14, EV21, EV37, EV94, (Valsecchi andAmos, 1996), GT23, GT195, GT211, GT310, GT509, GT575, (Bérubé et al., 2000), GATA28, GATA98,
GATA417, TAA31, (Palsbøll et al., 1997), and DlrFCB14 (Buchanan et al., 1996). Ten additional microsatellite
loci will be considered in an effort to decrease the number of unassigned animals by the STRUCTURE analysis(see below). PCR amplifications will be performed following the manufacturer’s instructions for the use of Ex
Taq DNA polymerase (Takara Shuzo). All PCR products will be electrophoresed on an ABI 3500
Automated DNA Sequencer. Allele sizes will be determined using a 600 LIZ size standard andGeneMapper v. 4.0 (Applied Biosystems, Inc).
For mitochondrial DNA (mtDNA), approximately 500 base pairs of the hypervariable portion from the 5’
end of the control region and flanking genes will be amplified by the polymerase chain reaction (PCR)
with a set of primers, light-strand MT4 (5'-CCTCCCTAAGACTCAAGGAAG-3'; Árnason et al., 1993) andheavy-strand Dlp5R (5'-CCATCGAGATGTCTTATTTAAGGGGAAC-3'). PCR is carried out in a 25 µL
reaction mixture containing PCR buffer (10 mM KCl, 2 mM Tris -HCl [pH 8.0], 2 mM MgCl 2 ), 0.5

93mM dNTPs, 1.25 µM primers, 0.65 units Taq DNA polymerase (Takara, Otsu, Japan), and 10 –100 ng
DNA template. PCR products will be purified by MicroSpin S-400HR columns (Pharmacia Biotech), and cycle
sequenced using BigDye terminator v3.1 cycle sequence Kit (Applied Biosystems, Inc). All samples will besequenced for both strands with the primers used in PCR amplification, which will be purified using AutoSeq G50 spin Columns (Pharmacia Biotech). The labeled sequencing fragments will be resolved by electrophoresis on
ABI 3500 Automated DNA Sequencer (Applied Biosystems, Inc).
Biological samples(1) Age
Earplug
In the laboratory, the flat along the central axis of the earplug will be cut using a sharp blade, then it will be groundon a wet stone to expose the neonatal line and growth layers. Growth layers will be counted under water using
stereoscopic microscope. A year of age is defined as one pair of the light and dark laminae in the core inaccordance with Best (1982) and Lockyer (1984). Age reading will be conducted in the following manner: i)earplug of the left side will be read. If the growth layers in the earplug are ambiguous, the earplug from the rightside will also be read. Reading from the less ambiguous side will be adopted; ii) age reading will be conducted
only once without any knowledge of biological information such as body length or sex; iii) when reading of all
sample is completed, age data will be compared with biological data such as body length or sexual maturity, andsome samples will be re-read to check for outliers, incomplete samples or invalid readings. An inter-reader
calibration experiment, following the method of Kitakado et al. (2013), will be conducted if necessary.
Racemization
Analysis of the ratio of D- and L-aspartic acids (Asp D/L) will follow the method previously described (Yasunaga
et al., 2014). The core samples will be carefully taken from the lens samples to avoid contamination andhomogenized with Tris-buffer (200mM Tris, 150mM NaCl, pH 8.0) using ultrasonic disruptors. The homogenate
will be centrifuged at 15,000 × g for 15 min. at 4°C, and it will then be desalted with acetone and air-dried. The
purified samples will be lyophilized in tubes and hydrolyzed in the gas-phase 6N-HCl for 7 hr at 108°C. The
hydrolysates will be dissolved and incubated in 0.1N-HCl and Borate buffer (0.1M, pH10.4), and incubated witho-phthalaldehyde (OPA) and n-tert-butyloxycarbonyl-L-cysteine (Boc-L-Cys) to form diastereoisomers. The D/Lratio of aspartic acid will be determined using RP-HPCL (Alliance ® HPLC systems e2696, Waters) with a NovaPak ODS column (3.9mm ×300mm, Waters) using fluorescence detection (344 nm excitation wavelength and 433
emission wave length). Elution will be carried out with a simple isocratic adsorption of 3% acetonitril+3%
tetrahydrofuran /0.1M acetate buffer pH6.0 in 45 min at a flow rate of 0.8 ml/min, at 23°C. To estimate ages by
ratio of enantiomers of aspartic acid, the formula of Bada et al. (1980): 2Kasp・t =Ln ((1 + D/L) / (1 - D/L)) - Ln((1 + D/L) / (1 - D/L))t=0, where Kasp is the rate constant of conversion between L and D enantiomers, t is the ageof the whale, D/L is the ratio of the enantiomers in the lens, and “t=0” is the ratio at birth, will be used. The
specific coefficients in each whale species will be determined by comparing with their earplug ages.
(2) Maturity status
Counting the number of corpora lutea/albicantia in both ovary will be conducted by cutting the surface of ovary
with a scalpel.
HE stained testis section will be created and observed under a standard microscope for identification of sexual
maturity status. Males with seminiferous tubules over 100μm diameter, spermatid or open lumen in the tubules
have been determined to be sexually mature (Kato, 1986; Kato et al., 1990, 1991).
Analytical procedure
Genetics
The newly obtained samples will be assigned to either O or J-stocks, applying all available microsatellite data toa Bayesian clustering analysis in the program STRUCTURE version2.0 (Pritchard et al., 2000). The
program implements a model-based clustering method for inferring stock structure (K, the number of stocks inthe model) using multilocus genotype data with and without information on sampling locations, which allows forthe analyses of the samples without choosing sample units. The posterior probability for K = 2 will be estimatedfrom ten independent runs without information on sampling locations. All runs will be performed with
100,000 Markov chain Monte Carlo repetitions and 10,000 burn-in length using the admixture model
which assumes individuals may have mixed ancestry, with correlated allele frequencies which assumes
frequencies in the different stocks are likely to be similar due to migration or shared ancestry. Individualassignment will be conducted using estimated individual proportion of membership probability (>90%). In
addition, the number of alleles, expected heterozygosity and inbreeding coefficient, per locus and across loci will
be calculated in sub-area 11 using the FSTAT 2.9.3 (Goudet, 1995) to understand the genetic variations of the94

present msDNA data. The deviations from expected Hardy-Weinberg equilibrium will be assessed using the
GENEPOP 4.0 (Rousset, 2008). The False Discovery Rate approach (Benjamini and Yekutieli, 2001) will be used
to adjust p-value for all multiple comparisons.
The phylogenetic analysis based on the Neighbor-Joining method (Saitou and Nei, 1987) will be performed using
mitochondrial sequences, in the program PHYLIP (Felsenstein, 1993) to complement the individual assignmentby the STRUCTURE analysis. The program DNADIST of PHYLIP will be used to estimate the genetic distancesamong haplotypes based on Kimura’s two-parameter model (Kimura, 1980) and the transition-transversion ratioof five to one. The genealogy will be rooted using the homologous sequence from North Atlantic common andAntarctic minke whales. To estimate reliability for each node, a total of 1,000 bootstrap simulations will be
conducted and the majority-rule consensus genealogy estimated. In addition, the number of haplotypes, haplotype(Nei, 1987) and nucleotide diversities (Nei, 1987: equation 10.5) based on the Kimura’s two-parameter (Kimura,1980) with its standard errors will be calculated in sub-area 11 as one of ancillary data.
Flipper coloration pattern
The boundary area pattern of the white patch named as “Grayish Accessary Layer (GAL)” will be classified into
four groups. In the process of the statistical analysis, the Mann–Whitney U-test will be adopted to compare theproportional size of the white patch on the flipper and Pearson’s chi-square test will be adopted to compare thefrequency of GAL types between two stocks. Each analysis will use the statistic software R 2.13.0.
Spatial and temporal occurrence of J stock by sex, age and reproductive status
The pattern of spatial and temporal occurrence of J stock animals in sub-area 11 by sex, age and reproductive
status will be examined after the first year period of NEWREP-NP. Yearly trend in the J stock proportion will be
estimated by Linear Regression Models.
Table 3 shows the number of historical samples in sub-area 11 by month, year and the tentative sampling under
NEWREP-NP during the first six years of the program.
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whales using the method of gelatinized extraction of earplug. NAMMCO Scientific Publications 10:17pp.
Nakamura, G., Kadowaki, I., Nagatsuka, S., Hayashi, Kanda, N., Goto, M., Pastene, L.A. and Kato, H. 2016.
White patch on the fore-flipper of common minke whale, as a potential morphological index to identify stocks.
Open Journal of Animal Sciences 6(2):116-122.
Nei, M. 1987. Molecular Evolutionary Genetics. Columbia University Press, New York.
Palsbøll, P.J., Bérubé, M., Larsen, A.H., and Jørgensen, H. 1997. Primers for the amplification of tri-and tetramer
microsatellite loci in baleen whales. Mol. Ecol. 6:893-895.
Pastene, L.A., Goto, M., Taguchi, M. and Kitakado, T. 2016. Temporal and spatial distribution of the ‘J’ and ‘O’stocks of common minke whale in waters around Japan based on microsatellite DNA. Paper SC/F16/JR38
presented to the JARPNII special permit expert panel review workshop, Tokyo, February 2016 (unpublished).
14pp.
Pritchard, J.K., Stephens, M., and Donnelly, P. 2000. Inference of population structure using multilocus genotype
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96

Yasunaga, G., Bando, T. and Fujise, Y. 2014. Preliminary estimation of the age of Antarctic minke whales basedon aspartic acid racemization. Paper SC/F14/J12 presented to the IWC SC JARPAII Special Permit Review
Workshop, February 2014, Tokyo, Japan (unpublished). 10pp.

97

Table 1. Number of bycaught common minke whales around Japanese waters, and the number of large set nets,
by year and stock.
No. of large
Year
J stockO stock
Unassigned
set nets
2001
37
3
5
774
2002
74
9
10
781
2003
81
18
9
781
2004
86
6
12
757
2005
90
14
9
729
2006
103
18
10
703
2007
108
20
12
654
2008
97
11
13
651
2009
95
6
10
648
2010
96
6
9
644
2011
75
6
4
617
2012
83
9
8
617
2013
77
9
8
598
2014
107
13
11
594

Table 2. Number of available samples from Pacific and Okhotsk coastal area of Japan by month, sub-areas andsources. CW: commercial whaling from 1983 to 1987, JARPN: 1994-1999, JARPNII: 1994-2014, BC: Bycatch
2001-2014
2
Month
1
2
3
4
5
6
7
8
9
10
11
12

CW

0

BC
69
58
51
68
54
29
18
10
1
11
38
81
488

CW

7CN
JARPN(II)

1
7
15
5
23

48
112
54
22
521
219

51

976

BC

CW

8
13
21
19
5
5
2
7
10
90

25
14
13
6

58

7CS
JARPN(II)

185
369
57
23
4
1

639

98

BC
31
7
19
44
52
44
12
7
4
5
26
31
282

CW

1

1

7WR
JARPN(II)

58
37
4
1

100

CW

54
39
19
1
4
5

122

11
JARPN

50
30

BC

9
11
2
3
10
13

80

48

Table 3. Number of historical and future sample/data of common minke whales in sub-area 11 (allocation tomonth is tentative)
Year
1984
1985
1986
1987
1996
1999
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2014
2017
2018
2019
2020
2021
2022

SourceCommercial
Commercial
Commercial
Commercial
JARPN
JARPN
Bycatch
Bycatch
Bycatch
Bycatch
Bycatch
Bycatch
Bycatch
Bycatch
Bycatch
Bycatch
Bycatch
Bycatch
BycatchNEWREP-NP
NEWREP-NP
NEWREP-NP
NEWREP-NP
NEWREP-NP
NEWREP-NP

April
13
13
13
13

May
24

June

July

August

10
4

6
6

1

2
2
30

September
2

OctoberNovember

1
1
3

2
4

3

50
2
1

1
1
1
2
1
1

2
1
1
1
1

3
2
2
1

2
1
2

1
1

2
1
1

1
1
1
47
47

47
47
47
47

*DNA and other biological data from whales sampled in a given year will be available in the next year

Figure 1. Sub-areas used for the management of common minke whale under the RMP.

99

Total
46
13
31
31
30
50
3
5
8
3
6
3
6
3
1
4
1
4
2
47
47
47
47
47
47

Figure 2. Spatial occurrence of O and J stocks in waters around Japan. BC2, BC6, BC7CS, BC7CN, BC10, BC11=
bycatches from sub-areas 2, 6, 7CS, 7CN, 10 and 11. K7CN= coastal survey at Kushiro. S7CS= coastal survey at
Sanriku. 7CS, 7CN, 7WR, 7E, 8, 9 and 11= offshore survey of JARPN and JARPNII. Sample size is on the topof each bar. Each whale was assigned to the ‘O’, ‘J’ and ‘Unassigned’ stock based on the microsatellite analysis(Pastene et al., 2016).

100

Appendix 1
Mixing of J and O stock common minke whales in the coastal area of Japan
Common minke whales have been caught by past commercial whaling, JARPN/JARPNII and bycaught by set net
fisheries along the Japanese coast. Composition of J and O stock common minke whales estimated by
microsatellite assignment differs among sub-areas and survey components. Although some of the J stock animals
migrate into the Pacific side of Japan, their distribution range is limited to the coastal zone, mainly within 30 miles
from the coastline (Figures 1 and 2).
The mixing proportion of J stock animals in sub-area 7 during the 1983-1987 commercial whaling period was
1.8% (Goto, unpublished data). On the other hand, the mixing proportion of J stock animals during the 2002-2014
JARPNII coastal surveys conducted in sub-area 7 was 21.7% which was much larger than the commercial whaling
period (Figure 1).
Sampling of commercial whaling and JARPNII coastal survey was conducted at approximately the same season
at the Sanriku region (sub-area 7CS): April to June. However, mixing proportion of J stock animals differs
between commercial and JARPNII coastal survey in each distance from the coastline in Sanriku, being larger in
the JARPNII coastal survey (Table 1, Figure 1).
The information above suggests a possible recovery of J stock common minke whales and an ensuing increased‘spill over’ from the Sea of Japan to the Pacific side of Japan. Further investigation is necessary to confirm this.
There is no much data to speculate on the J stock proportion yearly trend in sub-area 11. Monthly composition of
J and O stock animals in sub-area 11 collected by commercial whaling, JARPN and bycatches are shown in Figure
3. In the commercial whaling samples, the proportion of J stock animals was over 60% in the April, however, thefew samples from other months had a low proportion of J stock animals. On the other hand, available samples
from JARPN were limited to two months (July and August) and the proportion of J stock in both months wasaround 30%. Clearly the number of samples are very limited in sub-area 11.

Table 1. Mixing proportion of J stock common minke whales in sub-area 7CS by distance from coastline. Samples
were collected by commercial whaling (1983-1987) and JARPNII coastal Sanriku survey (2003-2014) in spring
season (April to June).

Distance
fromcoastline(n.miles)Commercial

JARPNII (coastal Sanriku)

J
stock

O
stock

Unassigned

J stock
ratio (%)

J
stock

O
stock

Unassigned

J stock
ratio (%)

<10

0

6

0

0.0

39

120

20

21.8

10-20

1

25

2

3.6

81

218

32

24.5

20-30

1

18

2

4.8

0

5

1

0.0

101

Figure 1. Differences in composition of J and O stock common minke whales in relation to the distance from thecoastline. Data of sub-area 7 were summarized for JARPNII coastal component off Sanriku and Kushiro, offshore
component and commercial whaling. Data of sub-area 11 were summarized for commercial whaling and JARPN
survey. Sample size is shown in the graph. The figures for bycatch samples (BC) in each sub-area was added toeach plot.

102

Figure 2. Sighting/catch position of common minke whales collected during 1983-1987 commercial whaling (left)
and 1994-2014 JARPN/JARPNII surveys (right) in sub-areas 7 and 11 assigned as O stock (blue), J stock (red)and unassigned (green), based on microsatellite DNA and STRUCTURE analysis.

Figure 3. Monthly composition of J and O stock common minke whales collected in sub-area 11 by commercial
whaling, JARPN and bycatches.

103Annex 8

Secondary Objective I (ii)
Estimate the abundance of the J and O stocks in coastal waters of Japan
Field and laboratory work, and analytical procedure
Background
Most of the common minke whales are considered J stock animals in sub-areas 5, 6W, 6E, 10W and 10E. Mostof the common minke whales are considered O stock animals in sub-areas 7WR, 7E, 8, 9 and 12NE. In sub-areas
7CS, 7CN, 11 and 12SW, it is necessary to estimate the mixing proportion of the J and O stocks because the twostocks are mixing in these areas. In order to fully estimate abundance for the J and O stock, information on mixing
estimates in these sub-areas are necessary.
Dedicated sighting surveys in sub-areas 6E, 10E and 10W were conducted in May-June by the National ResearchInstitute of Far Seas Fisheries (NRIFSF) for 2002-2007 (Miyashita et al., 2009; IWC, 2014). Sub-area 11 wassurveyed in August-September for 1990, 1999, 2003 and 2007 (IWC, 2014). Sub-areas 12SW and 12NE weresurveyed in August-September for 1990, 1999, 2003 and 2007 (IWC, 2014). In 2010, sighting surveys and biopsy
sampling of the common minke whales was conducted for genetic analysis in these sub-areas (Yoshida et al.,2011). Restricted areas in the Sea of Okhotsk were surveyed in 2015 and 2016 under the cooperation between the
Russian Federation and Japan (Myasnikov et al., 2016; Tiupeleev et al., 2016). Some parts of sub-areas 5 and
6W were surveyed in April-June by Korean sighting survey for 2000-2011 (IWC, 2014). In the JARPN II,
dedicated sighting surveys were conducted sub-areas 7, 8 and 9 excluding foreign EEZ in early and late seasons(Kiwada et al, 2009; Matsuoka et al., 2016).
From these surveys, abundance estimates assuming g(0)=1, which were used in the RMP/IST of the common
minke whales, were summarized including information on primary effort, primary sighting position, survey blocks,
sub-areas, and area definitions for surveys for western North Pacific common minke whales in Appendices 3 and
4 of IWC (2014). Based on these appendices, IWC (2014) listed the accepted abundance estimates used in the
RMP context for the common minke whales (JCRM (suppl) 15: 128-9). This table also summarized the extent of
the acceptability and the extent of the evaluation. Additional abundance estimates based on JARPNII were added
to the list (see p12 of Annex D of IWC, 2016b).
Okamura et al. (2009) estimated abundance considering g(0) estimates for each platform and their combinations.
The results were presented to IWC/SC in 2009. In the discussion, it was noted that although there had been no IO
data collection in surveys in previous years, in the absence of direct estimates of g(0) , the estimates of g(0)presented in Okamura et al. (2009) could be used for the top barrel and the upper bridge for these earlier surveys.
Field work
Sighting surveys are planned to be conducted by line transect method following the survey protocols set out in
the Requirements and Guidelines for Conducting Surveys and analyzing data within the Revised Management
Scheme (IWC, 2012) so that sighting surveys will be conducted under oversight by the IWC SC. Considering therecommendation from the NEWREP-A expert panel (IWC, 2015), the proponents will consider the following; (a)survey design and methods will be reviewed taken into account previous IWC sighting surveys and spatial model
developments; (b) they will work closely with the IWC SC before finalizing survey approaches; (c) they will also
ensure that future survey plans submitted to IWC SC follow fully the guidelines for such surveys, including theincorporation of planned track-lines.
Survey area and period
To conduct sighting surveys in sub-areas 5, 6W and 10W, it is necessary to collaborate with foreign countries,
such as Korea, Russia. If the proponents cannot collaborate with the foreign countries in sighting surveys,
abundance estimate based on the sighting surveys would not be available and it would be necessary to conductindirect methods to estimate abundance such as spatial modelling framework and mark-recapture using genetic
data.
Sighting surveys in sub-areas 6E and 10E in May-June will be conducted as in 2002-2007. Sighting surveys in
sub-area 11 in summer will be conducted. Sighting surveys in the Sea of Okhotsk conducted in summer arenecessary to estimate abundance for J and O stocks. Sighting data obtained during the sighting surveys in the
restricted area in the Sea of Okhotsk for 2015 and 2016 can be used for abundance estimation. If the framework104

of dedicated sighting surveys in the Sea of Okhotsk under the cooperation between the Russian Federation andJapan will be continue, it would not be necessary to conduct sighting surveys in the Sea of Okhotsk under the
NEWREP-NP.
Sighting survey in sub-areas 7CS, 7CN, 7WR, 7E, 8 and 9 are planned for summer (See also Annex 13).
Survey months are selected according to previous sighting surveys mentioned above. In order to estimate
abundance for use in the assessment of the J and O stocks and to obtain inter-annual variance from the NEWREPNP data, it would be better to obtain abundance estimates every three years. However, considering the availabilityof the dedicated sighting vessels, it is more realistic to estimate abundance every six years.
Survey mode
The sighting surveys will be conducted using Passing with Independent Observer (IO) mode, as in the past, in
sub-areas 6E, 10E and 11, which are in marginal seas. Weather conditions and sea state are generally not good
and there are high swells in sub-areas 7, 8 and 9, as these sub-areas are in open sea. For this reason passing modewith abeam closing mode will be conducted in these sub-areas as in the past instead of the Passing with IO mode.
Passing with IO mode is to be conducted as follows. Two topmen in the top barrel and two topmen on the
independent observer platform (IOP) observe at all times. Communications are essentially one-directional, withthe topmen reporting information to the upper bridge observers, but no information being exchanged between the
top barrel and IOP. The observers on the upper bridge should communicate with the topmen only to clarify
information on the sightings (Miyashita and Okamura, 2011). The sighting method followed the Guideline forsighting survey under RMS (IWC, 2012). In order to conduct the survey, it is necessary to collaborate and to
consult with NRIFSF staff, who have much experience and know-how of sighting surveys for the common minke
whales using IO mode.
Biopsy sampling
In order to complement the estimate of mixing rate of J and O stocks (Annex 7), feasibility study of biopsy
sampling for genetic analysis are planned. When biopsy sampling is conducted using the Larsen gun system,
restricted closing mode will be conducted (Yoshida et al., 2011).
Analytical procedure
Design-based estimator
For preliminary analysis, mark-recapture distance sampling (Borchers et al., 1988, 2006; Laake 1999), which isone of the packages in the DISTANCE grogram (Thomas et al., 2010), will be applied to estimate abundanceconsidering preliminary g(0) estimate. In order to estimate parameters in the detection function from each observer,
likelihood of the mark-recapture component and the distance sampling component are maximized, followed byuse of Horvitz-Thompson-like estimator to estimate the number of objects in the covered region (i.e. the strips
searched on the survey) (Borchers et al., 2006) and therefore abundance estimate in the survey areas can beobtained. If sufficient sightings during IO mode will become available, a more sophisticated model such as the
OK model (Okamura and Kitakado, 2012) will be applied to estimate abundance taking g(0) estimate into accountusing sighting data obtained in closing and IO mode so that the effects of covariates such as school size estimate
and weather condition can be estimated on the g(0) estimation
Model-based estimator
Density Surface Modeling (DSM) (Miller et al., 2013) will be used, which is one of the packages in the
DISTANCE grogram (Thomas et al., 2010). But there is room for trying other options (e.g. smoother, modelingframework, variance estimation method etc.) to improve abundance estimates. For example, an approachpresented by Murase et al. (2016) would be used as a template of this type of analysis bearing in mind thecomments from the JARPNII final review workshop (IWC, 2016a). Sea Surface Temperature (SST), Sea Surface
Height anomaly (SSHa) and sea surface chlorophyll-a concentration (Chl-a) recorded by satellites and digital
seafloor depth data would be used as environmental covariates in the models. Data from ocean circulation models
such as FRA-ROMS would also be used as covariates. It is also planned to compare abundance from model-based
estimates with those from the design-based estimates. This work would be response to recommendation at the
JARPNII final review workshop (IWC, 2016a).
Inter-annual variance (Additional variance)
The approach in Kitakado et al (2012) can be used to estimate yearly variation in abundance levels due to interannual change in distribution of the common minke whale population and abundance trend of the common minke
whales. By considering the inter-annual variance, underestimating the variance of the abundance estimate can be
avoided. This work would be response to recommendation at the JARPNII review workshop (IWC, 2016a).

105

Genetic mark-recapture analysis
The common minke whales will be taken in sub-areas 7CS, 7CN and 11. In these sub-areas, pregnant animals canbe taken. Kanda et al. (2014) conducted the paternity analysis using genetic data of mother-fetus pairs andpotential fathers of the fetus. This method estimated the number of the mature male in the stock. By applying themethod to the samples in sub-areas 7CS, 7CN and 11, mature male numbers of the O and J stocks can be obtained
if sufficient samples are available. In addition to samples from NEWREP-NP, samples from JARPN/JARPNII
surveys can be used for this analysis.
References
Borchers, D.L., Zucchini, W. and Fewster, R.M. 1988. Mark-recapture models for line transect surveys.
Biometrics 54: 1207-1220.
Borchers, D.L., Laake, J.L., Southwell, C. and Paxton, C.L.G. 2006. Accommodating unmodelledheterogeneity in double-observer distance sampling surveys. Biometrics 62:372-378.
International Whaling Commission. 2012. Requirements and Guidelines for conducting surveys andanalysing data within the Revised Management Scheme. J. Cetacean Res. Manage. (Suppl.) 13:509-17.
International Whaling Commission. 2014. Annex D1. Report of the Working Group on the
Implementation Review for Western North Pacific Common Minke Whales. J. Cetacean Res. Manage.
(Suppl.) 15: 112-88.
International Whaling Commission. 2015. Report of the Expert Panel to review the proposal by Japan for
NEWREP-A. Paper SC/66a/Rep6 presented to IWC Scientific Committee (unpublished). 62pp.
International Whaling Commission. 2016a. Report of the Expert Panel of the final review on the western
North Pacific Japanese Special Permit programme (JARPN II). Paper SC/66b/Rep06 presented to IWC
Scientific Committee (unpublished). 96pp.
International Whaling Commission. 2016b. Report of the Scientific Committee. Paper IWC/66/Rep1(unpublished). 136pp.
Kanda, N., Goto, M. and Pastene, L.A. 2014. Paternity analysis on Antarctic minke whales using
JARPA and JARPAII samples. Paper SC/F14/J7 presented to the IWC SC JARPAII Special Permit
Review Workshop, February 2014, Tokyo, Japan (unpublished). 4pp.
Kitakado, T., Hakamada, T. and Miyashita, T. 2012. Extrapolation of abundance to unsurveyed areas in
sub-areas 8, 11 and 12NE for the western North Pacific common minke whales by using prediction with alinear model. Paper SC/64/NPM5 presented to IWC Scientific Committee (unpublished). 6pp.
Kiwada, H., Kumagai, S. and Matsuoka, K. 2009. Methodology and procedure of the dedicated sighting
surveys in JARPN II –Offshore and coastal component of Sanriku and Kushiro-. Paper SC/J09/JR2
presented to JARPNII review workshop. Yokohama, January 2009 (unpublished). 16pp.
Laake, J.L. 1999. Distance sampling with independent observers: Reducing bias from heterogeneity by
weakening the conditional independence assumption. In Amstrup, G.W., Garner, S.C., Laake, J.L., Manly, B.F.J.,
McDonald, L.L. and Robertson, D.G. (eds) Marine mammal survey and assessment methods, Balkema,
Rotterdam: 137-148.
Matsuoka, K., Hakamada, T. And Miyashita, T. 2016. Methodology and procedure of the dedicatedsighting surveys in JARPN II (2008-2013) - Offshore component -. Paper SC/F16/JR2 presented to the
JARPN II review workshop, Tokyo, February 2016.
Miller, D.L., Burt, M.L., Rexstad, E.A. and Thomas, L. 2013. Spatial models for distance sampling
data: recent developments and future directions. Methods in Ecology and Evolution 4: 1001-10.
Miyashita, T. and Okamura, H. 2011. Abundance estimates of common minke whales using the Japanese
dedicated sighting survey data for RMP Implementation and CLA - Sea of Japan and Sea of Okhotsk.

106

Paper SC/63/RMP11 presented to the IWC Scientific Committee, June 2011, Tromsø, Norway(unpublished). 34pp.
Miyashita, T., Okamura, H and Kitakado, T. 2009. Abundance of J-stock common minke whales in the
Sea of Japan using the Japanese sighting data with g(0)=1. Paper SC/61/NPM7 presented to IWC
Scientific Committee (unpublished). 10pp.
Murase, H., Hakamada, T., Sasaki, H., Matsuoka, K. and Kitakado, T. 2016. Seasonal spatial distributionsof common minke, sei and Bryde’s whales in the JARPNII survey area from 2002 to 2013. Paper
SC/F16/JR7 presented to the Expert Panel of the final review on the western North Pacific JapaneseSpecial Permit programme (JARPN II) (unpublished). 17pp.
Myasnikov, V.G., Vinnikov, A.V., Ryabov, A.A., Tyupeleev, P.A., Gushcherov, P.S., Samanov, V.I. andMiyashita, T. 2016. Cruise report of the cetacean sighting survey in the northern part of the Sea of Okhotsk in
2015. Paper SC/66b/IA17 presented to IWC Scientific Committee (unpublished). 25pp.
Okamura, H., Miyashita, T. and Kitakado, T. 2009. Revised estimate of g(0) for the North Pacific common minke
whale. Paper SC/61/NPM5 presented to IWC Scietific Committee (unpublished). 7pp.
Okamura, H and Kitakado, T. 2012. Abundance estimates of Antarctic minke whales using the OK
method. IWC Doc. SC/64/IA2 submitted to IWC Scientific Committee, June 2012 (unpublished). 24pp.
Thomas, L., Buckland, S.T., Rexstad, E.A., Laake, J.L., Strindberg, S., Hedley, S.L., Bishop, J.R.B.
Marques, T.A. and Burnham, K.P. 2010. Distance software: design and analysis of distance sampling
surveys for estimating population size. Journal of Applied Ecology 47: 5-14.
Tiupeleev, P.A., Gushcherov, P.S., Samonov, V.I. and Miyashita, T. 2016. Plan of the cetacean sighting survey
in the northern part of the Sea of Okhotsk in 2016. Paper SC/66b/IA11rev presented to IWC Scientific Committee(unpublished). 6pp.
Yoshida, H., Kishiro, T., Kanda, N. and Miyashita, T. 2011. Cruise report of the sighting and biopsy sampling
survey in the Okhotsk Sea, summer 2010, including individual stock identification of common minke whales.
Paper SC/63/RMP9 presented to IWC Scientific Committee (unpublished). 10pp.

107

Annex 9
Secondary Objective I (iii)
Verify that there is no structure in the O stock common minke whale in the Pacific side of Japan
Field and laboratory work, and analytical procedure

Background
Despite considerable investment in the analyses of genetic and non-genetic data, different views remain in the
IWC Scientific Committee (IWC SC) on the plausibility of sub-structure within the O stock of common minke
whales in the Pacific side of Japan. In terms of the 2013 RMP trials for common minke whales in the western
North Pacific, there could be only one stock (hypotheses A and B), or there could be two: a coastal (Ow) and an
offshore (Oe) stock (hypothesis C) (IWC, 2014).
After the 2013 Implementation Review, several new genetic and non-genetic analyses were conducted to evaluate
the plausibility of an Ow stock. The studies followed specific recommendations from the 2009 JARPNII review
workshop. All these studies provided support for a single O stock in the Pacific side of Japan (see a summary of
the studies in Annex 4). Therefore the proponents believe that the plausibility of hypothesis C is very low.
Research under this Secondary Objective involves new genetic analyses, particularly kinship analyses, to verify
that there is no structure in the O stock common minke whale.
Methods
Field work
Genetic samples
Skin tissue samples of common minke whales will be taken during NEWREP-NP and stored in 99% ethanol until
DNA extraction. In the case of biopsy sampling, the details of equipment and sampling procedures are describedin Annex 19.
Satellite tagging
Feasibility trials on satellite tracking will be conducted to address the question of movement across the boundaries
separating sub-areas 7CS and 7CN from offshore sub-areas. Under the single O stock structure, movement will
be expected across those boundaries. Also if trials are conducted late in the feeding season, it could be possible toinvestigate migration routes of common minke whales to lower latitudes areas. Tracking trials will be conductedwhen dedicated sighting surveys are carried out in coastal areas. On such occasions, a total of five trials will be
attempted in the research period.

The study will be based on a pneumatic tool (e. g. the whale tag launcher: Aerial Rocket Tag System (ARTS),
Lars Kleivane and Restech Norway A/S, Norway and satellite tag: SPOT6, Wildlife computers, WA, USA) (Isoda
et al., 2016). Satellite tags with a blubber penetration-type mount system will be shot by this tool from the bow
deck. The tagged whales will be also target of biopsy sampling using the Larsen-gun system.
As the first step, satellite tagging will be carried out close to Japanese coastal waters. If a biopsy sample is obtained
from the same animal which the satellite tags were attached to, genetic information with migrating route topotential breeding grounds will contribute to clarify the exact stock structure.
In planning this feasibility trial, effort is spent in developing an attachment system in consultation with staff of
the National Research Institute of Far Seas Fisheries (NRIFSF, Yokohama, Japan) and Lars Kleivane from
Norway, all of whom are experienced in telemetry studies on common minke whale (see Kishiro and Miyashita,2011).
In addition a member of the proponents will attend the IWC-ONR Joint Workshop on Tag Development, FollowUp Studies and best Practices to be held in September 2017 in Silver Spring, MD (USA) to become acquainted
with the most current tagging technologies and deployment methods.
Laboratory work
Genetics
Details of laboratory work for genetics on common minke whale are described in Annex 7.

108

Analytical procedure
Kinship analysis
At the 2014 IWC SC meeting, Tiedemann et al. (2014) reported a method for finding relatives among North
Atlantic common minke whales based on microsatellite data. The method involves the investigation of therelationship between false discovery rate and detection power.
The application of the method involves the following steps (see details in Tiedemann et al., 2014):
1) Calculation of the locus-wise relative allele frequencies for mother-fetus pairs.
2) Calculation of the pairwise logarithm of the odds (LOD) scores among all pairs of individuals.
3) Estimation of the p-values for each LOD score of the original data set by comparing them to LOD scoresobtained in a random data set of unrelated specimens.
4) Significance is established controlling for the false discovery rate (FDR).
5) Simulation of a data set of 10,000 specimens with the relatedness of interest, taking into account the applicable
probabilities of locus-specific numbers of alleles identical-by-descent. The detection power of a given FDR
and relatedness category will be calculated as the relative proportion of the simulated related specimens witha LOD score equal to or exceeding the FDR-specific LODq score threshold.
This method will be used for investigating relatives among western North Pacific common minke whales, and thisinformation will be very valuable for verifying the single O stock scenario. Under this scenario we will expect
kinship relationship between offshore and coastal animals. For this purpose, both JARPN/JARPNII and newly
collected samples will be used.
References
Isoda, T., Kawabe, S., Ohkoshi, C., Mogoe, T. and Matsuoka, K. 2016. Results of the NEWREP-A dedicatedsighting survey in Area IV during the 2015/16 austral summer season. Paper SC/66b/IA05 presented to the IWC
Scientific Committee, May 2015 (unpublished). 25pp.
International Whaling Commission. 2014. Report of the Scientific Committee. Annex D1. Report of theWorking Group on the Implementation Review for Western North Pacific Common Minke Whales. J. Cetacean
Res. Manage. (Suppl.) 15:112-88.
Kishiro, T., Miyashita, T. 2011. Satellite tracking of a common minke whale in the coastal waters off Hokkaido,
northern Japan in 2010. Paper SC/63/RMP10 presented to the IWC Scientific Committee, May 2011
(unpublished). 10pp.
Tiedemann, R., Tiedemann, M.R., Gunnlaugsson, G., Pampoulie, C. and Víkingsson, G.A. 2014. Finding
relatives among North Atlantic common minke whales (Balaenoptera acutorostrata) based on microsatellite
data: the relationship between false discovery rate (FDR) and detection power. Paper SC/65b/RMP05 presented
to the IWC Scientific Committee, May 2014 (unpublished). 8pp.

109

Annex 10
Secondary Objective I (iv)
Improve RMP trials by incorporating age data in their conditioning
Field and laboratory work, and analytical procedure
Background
The IWC SC broadly agreed on the value of age data in ISTs (e.g. conditioning operating models). In the case ofcommon minke whale, ageing techniques have been improved and as a consequence age information is available
for a larger number of animals. Additional age data is very important for the aim of improving RMP trials, andthis is the main aim under this Secondary Objective.
Methods
Field work
Biological samples for SCAA
Procedures for sampling to obtain information required for SCAA such as age, body length and reproductive
status are described in Annex 7.
Laboratory work
Biological information
Details of laboratory work for biological information on common minke whale are described in Annex 7.
Analytical procedure
SCAA
The recent availability of age data from western North Pacific common minke whale (Maeda et al., 2016) provides
a basis to improve the accuracy of the RMP ISTs of IWC (2014a) for these common minke whales through taking
these data into account when conditioning these trials. In this research the new age data will be used by theStatistical-Catch-At-Age (SCAA) assessment approach. The SCAA was applied to Antarctic minke whale (Puntet al., 2014) and the SCAA model was recognized by the IWC SC as the ‘best currently available model for
examining stock dynamics for Antarctic minke whales’ (IWC, 2014b). Details of the model are presented in
Annex 12.

References
International Whaling Commission. 2014a. Report of the Scientific Committee. Annex D1. Report of theWorking Group on the Implementation Review for Western North Pacific Common Minke Whales. J. Cetacean
Res. Manage. (Suppl.) 15:112-88.
International Whaling Commission. 2014b. Report of the Scientific Committee. Annex G. Report of the SubCommittee on In-depth Assessments. J. Cetacean Res. Manage. (Suppl.) 15: 233-249.
Maeda, H., Bando, T., Kishiro, T., Kitakado, T. and Kato, H. 2016. Basic information of earplug as age characterof common minke whales in western North Pacific. Paper SC/F16/JR53 presented to the JARPNII special permit
expert panel review workshop, Tokyo, February 2016 (unpublished). 10pp.
Punt, A.E., Hakamada, T., Bando, T. and Kitakado, T. 2014. Assessment of Antarctic minke whales using
statistical catch-at-age analysis. J. Cetacean Res. Manage. 14:93-116.

110

Annex 11
Estimates of sample size for Primary Objective I (common minke whale)

General background and rationale for the sample size on the Pacific side of Japan (sub-areas 7-9)
The SCAA assessment of Antarctic minke whale populations by Punt et al. (2014) was a watershed advance for
the IWC SC because, through its ability to take account of age in addition to survey abundance data, it pointed tothe extent of recruitment changes4 that could occur, and its results did not conform particularly closely to the
behaviour predicted by the standard population models used to assess and hence to provide baseline ISTs forbaleen whale populations. Figure 1 contrasts the results from an application by GOJ (2016) of the Punt et al.
SCAA methodology to those that would follow from a FITTER approach necessitated if only catch and survey
abundance information were available (as required for the RMP).

4 Recruitment refers to the numbers of young whales added to the population each year (also called a ‘cohort’). This cannot

be determined well if only a series of abundance estimates of the whole population are available. The availability of age
data, however, allows estimates of total population numbers to be split into the numbers of each cohort present that year.
From one survey only, such estimates would not be precise, but the accumulation of age data over successive years allows
for multiple estimates of the size of each cohort, and it is effectively the combination of these which ultimately allows forreasonable estimates of annual recruitment to be obtained.

111

Figure 1: Two approaches to conditioning potential ISTs for the I stock of Antarctic minke whales are compared. The first uses
the conventional approach for baseline trials in RMP Implementations, with only past catch and survey abundance estimates(in this instance from the IDCR-SOWER cruises) available, and is calculated here using the FITTER-with-fixed-MSYR
methodology. The second uses the SCAA approach of Punt et al. (2014), as implemented by GOJ (2016), which can in addition
take age data into account. Results are shown for the 1+ population trajectory for two different values of MSYR(1+). The very
different perception of the dynamics of the population that follows once age data are available for use in the conditioning, andshow that catches have not been the primary determinant of the population’s behaviour, is readily evident.

The considerable difference is obvious; self-evidently optimal management based the scenario (and associatedsensitivities) provided by the SCAA, which can estimate recruitment directly through the availability of age data,
would be very different to that from the deterministic stock-recruitment relationship scenarios (as, e.g., the
FITTER methodology has to assume), which at best would need to consider a very wide range of robust tests,
resulting in an inefficient approach (less allowable catch for the same perceived risk).
The Punt et al. (2014) analysis constitutes an important step in contributing to the evolution of the RMP towards
a more efficient version which is based on better conditioned operating models, and is stock specific (as are thevarious current AWMPs) rather than generic as at present. Age data contribute to this better conditioning throughallowing much improved estimation of recruitment and its changes and may also be able to improve theperformance of a refined version of the RMP, as has been demonstrated in the case of Antarctic minke whales(GOJ, 2016). The NEWREP-NP proposal, with its analyses, has the intent that the age data to be collected willcontribute to this evolutionary process.
The JARPN II Final review workshop report, endorsed by the IWC SC, noted that ‘if the Implementation
Simulation Trials (ISTs) for the western North Pacific minke whales are to be revised in future, the age data should
be included in the conditioning process’ (SC/66b/Rep06, Report of the Expert Panel of the final review on thewestern North Pacific Japanese Special Permit program (JARPN II), 4.4.1). The example above shows that age
data, whenever potentially available, are needed for conditioning such trials so that recruitment and its changes
may be reflected far better. This is the primary reason why the proponents support the use of age data for theconditioning of the next set of ISTs for the North Pacific common minke whale, which they understand to beendorsed also by the IWC SC. Naturally recruitment is hardly estimable for other than past years spanned by thecollection of age data, so for future sets of ISTs also to best reflect underlying dynamics, age data must continue
to be collected, notwithstanding the fact that the impact of data from the first few years of NEWREP-NP to thenext NP common minke whale Implementation Review may not be that large.

112

The proponents’ approach is entirely in line with fisheries management approaches elsewhere, including in thedevelopment of MPs in other Regional Fisheries Management Organizations (RFMO). There a high premium isplaced on obtaining and improving age data and/or on equivalent information to provide information on
recruitment changes. Further comments on this and other aspects of the use of age data in fisheries management
may be found in Adjunct 1. Furthermore Adjunct 2 provides an example of how the availability of age data aids
the estimation of the extent of the impact of environmental factors on recruitment trends – a matter of importanceat this time given concerns about the possible impacts of Climate Change.
Note that while age data could be used in a future RMP in a similar way to that in the proposal in Government ofJapan (2016), the primary contribution of such data remains to the conditioning of ISTs, and (as has proven to be
the preferred approach for other MPs internationally) their contribution to feedback adjustments to management
measures might be through the regular re-conditioning of the ISTs rather than by changes to the MP itself.
Moving to the matter of sample size, it is perhaps helpful to first summarise the proponents’ rationale for thenumber advanced, before elaborating upon it in more detail. This rationale is that:

Age data are needed for improved conditioning of ISTs for testing management procedures, to informbetter on recruitment changes and hence improves the trials’ realism

Simulation results (see Adjunct 2) indicate that larger age samples would allow better estimation ofrecruitment changes for this NP minke situationOn the other hand, operational considerations regarding the practically maximum sample size and theeffect on the population must also be taken into account in determining the optimal sample sizeTherefore, the optimal sample size should meet both of these criteria: that it is operationally maximal
and is also sufficient to provide meaningful improvement in the estimation of recruitment changes;
simulation results (see Adjunct 3) indicate that is the case for this NP minke situation. (The matter ofeffect on the population is dealt with in Section 4.1 of the main text of Revised Research Plan.)To elaborate then, given the clear and widely accepted benefits in principle of the inclusion of ageing data to the
IST conditioning process, the only question that then remains is how much age data is needed to make ameaningful improvement to that NP minke whale conditioning. A detailed calculation for this would need to be
based on the planned updated conditioned (including with the age data available at that time) set of NP minke
ISTs, and consequently would need to await completion of that exercise which is the responsibility of the IWC
SC.
However, in the interim, much simpler computations are adequate to bound the problem, and are conducted in
Adjunct 3. These are based on a simpler model broadly accepted when presented to the JARPN II review, which
was intended to be illustrative and to assist this bounding.
Note first that the model showed performance improved with increases in the sample size aged, and that these
improvements are meaningful over the sample sizes examined which were consistent with what was operationallypractical5. This last consideration then provides the desirable sample size, but always provided that a) the criterionof no adverse effect on the population is met, and b) that sample size is itself sufficient to provide a meaningfulimprovement in performance. The intent of the calculations of Adjunct 3 is to address this last question, and thisis successfully achieved – note that this is an exercise for which primarily only relative measures of performance
when comparing results with to those without ageing data are needed. Once the updated conditioning is complete,that could be used to update these overall results, though any difference would not be expected to be large, andthe priority for such an update would not seem to be very high, and results from this bounding an illustrative
exercise are sufficient to address the immediate question.
Given the relatively slow dynamics of minke whales, coupled to the nature of the information content of age data,
the improvements to ISTs achieved by use of these data take time to reveal their full extent (see the plots in Adjunct3), so that there is a need to show results for projections over a number of decades, extending beyond the timeframe of the current research program. Self-evidently the results for these larger numbers of years must be taken
5

Based on the scientific knowledge on minke whale distribution around Japan, estimated sampling efforts
given the available research vessels (see Annex 21 of the proposed proposal) and the allocation of efforts tothe two target species, annual sample size of 107 for minke whales was found to be optimal and feasible.

113into account; otherwise the injudicious situation would arise that research with longer term benefits would nevercommence because those benefits could never become evident in the short term.
In summary it is considered that the annual sample size of 107 minke whales in sub-areas 7-9, which is the
maximum feasible within the operational constraints of the program, is sufficient to result in meaningfulimprovement in the detection of minke whale recruitment changes.
This intended sample size applies to O stock whales. It is planned that 60% of this sample size be taken in coastal
sub-areas (7CS and 7CN) and 40% in offshore sub-areas (7WR, 7E, 8 and 9). Evaluating an optimalcoastal:offshore ratio for this sample would be an enormous task technically, but it seems reasonable to expectthat a 50:50 split would be near optimal in terms of distinguishing possible differences between the two regions
if any. Taking into account operational reasons as well, the ratio has been decided to be 60:40, noting that typicallysuch “distinguishability” performance behaves quadratically, so does not deteriorate much with relatively small
movement away from the actual optimal split. Hence it is planned that 64 animals will be sampled in coastal subareas and 43 in offshore sub-areas. Because around 20% of the animals in sub-areas 7CS and 7CN are from the J
stock (Annex 7), the sample size in the coastal sub-areas needs to be adjusted upwards to 80 animals in total toachieve sampling of 64 O stock whales. Thus the total sample size planned on the Pacific side of Japan becomes
123 whales.
Rationale for the sample size selected for the area north of Hokkaido (sub-area 11)
For the area north of Hokkaido (sub-area 11), the main objective is to estimate the J-O mixing proportion in thissubarea annually with a standard error of no more than 0.1 irrespective of the true proportion. The sample size
selected is 47. The basis for the selection of this value is explained in Adjunct 4.
Total planned sample size
With 123 whales to be taken on the Pacific side of Japan, and 47 north of Hokkaido, the total sample size plannedfor common minke whales is 170.
References
Government of Japan. 2016. Results of the analytical works on NEWREP-A recommendations. Paper
SC/66b/SP10 presented to the IWC Scientific Committee. June 2016 (unpublished). 23pp.
Punt, A., Hakamada, T., Bando, T. and Kitakado, T. 2014. Assessment of Antarctic minke whales using statisticalcatch-at-age analysis (SCAA). J. Cetacean Res. Manage. 14:93-116.

114

ADJUNCT 1
On the Use and Utility of Catch–at-Age Data in Marine Resource Assessment and Management
The inclusion of age data in fishery assessments is widespread in fishery management agencies worldwide,
including in Regional Fisheries Management Organisations (RFMOs). This use can also extend there to theprocess of developing management procedures (MPs), certainly for conditioning the operating models used fortesting those MPs, and sometimes directly in the MPs themselves. Generally a high premium is placed on
obtaining and improving age data and/or equivalent information to provide information on recruitment changes.
Examples of this in RFMOs are provided, for example, by:
CCAMLR: Further collection of age data for the assessment of toothfish stocks is recommended (e.g.
CCAMLR 2016).
CCSBT: Age data are used in conditioning the operating models used for MP selection for southern
bluefin tuna (SBT), and indirectly (through recruitment indices) in the MP itself (e.g. CCSBT 2016).
ICCAT: Age data are used in assessments of, for example, Atlantic bluefin tuna, and in the developmentof operating models for the MP in development for that resource (e.g. ICCAT 2014).
NAFO: Age data were used in conditioning the operating models for the MP previously adopted forGreenland halibut, and are similarly in use for the revision of this MP that is currently in progress (e.g.
NAFO 2010).
WCPFC: Age data are used in the assessments of various stocks, including bigeye tuna (e.g. Harley etal. 2014).
Many of the species involved above are long-lived, some to four decades which approaches the longevity of many
whale species, so that dynamics, time scales, and management concerns are not dissimilar from those for whales.
One reason that perhaps increases the priority for ageing information for the species above compared to whales is
its contribution towards estimation of abundance in absolute terms – whale sightings surveys provide better
approximations to this than are obtainable from abundance indices for many fish species. Nonetheless the primary
improvement provided by the availability of age data is the ability to assess year-class (recruitment) strength andits variations. The identification of (series of) good and of poor recruitment plays an important role in the
management of these species despite their longevity, both as regards increasing and reducing catch limits. Thus
there is, for example, absolute unanimity in the CCSBT Scientific Committee on the need for recruitment
monitoring inputs in the MP used to recommend catch limits for SBT, following experience in that case of theconsequences of a run of poor recruitments across the turn of the century.
These same considerations apply to whales, where the absence of age data accordingly necessitates moreconservative management than might otherwise be necessary, i.e. lower catches for the same perceived risk.
The current IWC RMP relies (historical catches aside) on the input of survey based indices of abundance (withCVs) only. The assessment of the US Gulf of Maine winter flounder (NEFSC 2011) provides a note of caution inthis regard. If survey indices of abundance only were considered, that stock appeared perfectly healthy; howevera full assessment taking age data into account as well led to a different appreciation, suggesting a resource
appreciably reduced in abundance over recent decades. This points again to the sound management of a marine
resource requiring that age information (in addition to survey-based indices in isolation) be obtained and taken
into account whenever possible.

115References
Commission for the Conservation of Antarctic Marine Living Resources. 2016. Report of the Thirty-fifth meetingof the Scientific Committee (Hobart, Australia, 17 to 21 October 2016) ,SC-CCAMLR-XXXV. 481pp.
Available at https://www.ccamlr.org/en/system/files/e-sc-xxxv.pdf
Commission for the Conservation of Southern Bluefin Tuna. 2016, Report of the Seventh Operating Model andManagement Procedure Technical Meeting, 3-4 September 2016, Kaohsiung, Taiwan. 22 pp. Available
athttps://www.ccsbt.org/sites/ccsbt.org/files/userfiles/file/docs_english/meetings/meeting_reports/ccsbt_
23/report_of_OMMP7.pdf
Harley, S. J., Davies, N., Hampton, J., and McKechnie, S. 2014. Stock assessment of bigeye tuna in the Western
and Central Pacific Ocean. Technical Report WCPFC-SC10-2014/SA-WP-01, WCPFC ScientificCommittee, Majuro. 115pp.
International Commission for the Conservation of Atlantic Tunas. 2014. Report of the 2014 Atlantic Bluefin Tunastockassessment
session.
Madrid,Spain.
178pp.
Availableathttps://www.iccat.int/Documents/Meetings/Docs/2014_BFT_ASSESS-ENG.pdf
North Atlantic Fisheries Organisation. 2010. Report of the Working Group on Greenland Halibut Management
Strategy Evaluation (WGMSE). 16-17 September. Halifax, Nova Scotia, Canada. 64 pp. Available athttps://www.nafo.int/Portals/0/PDFs/fc/2010/fcdoc10-30.pdf
Northeast Fisheries Science Center. 2011. 52nd Northeast Regional Stock Assessment Workshop (52nd SAW)
Assessment Report. US Dept Commer, Northeast Fish Sci Cent Ref Doc. 11-17. 967 pp. Available athttps://www.nefsc.noaa.gov/saw/saw52/crd1117.pdf .

116

ADJUNCT 2
Enhancement of the Detection of the Effects of Environmental Factors on Whale Dynamics given the
Availability of Catch–at-Age Data
Introduction
This Appendix intends to provide an illustration of how the availability of catch-at-age data may lead to improved
estimation of the effect of an environmental factor (or factors in combination) on whale population dynamics.
Specifically the magnitude (G) of the trend in an enhancement of recruitment success is estimated without andwith the availability of catch-at-age data, and estimation performance contrasted in terms of bias, variance androot mean square error.
The situation modelled is loosely based on the O stock of North Pacific common minke whales, and is developed
from the model of Kitakado and Maeda (2016), and as refined further in Adjunct 3. Details of the methods applied
are set out in Appendix A. The data available to the estimator are the results of six-yearly sightings surveys of 1+
abundance, and annual catch-at-age information with an effective (i.e. “independent”) sample size of either 0 or80.
Estimation performance for the environmental effect (G) parameter is compared after 20 and after 50 years forthe two different sample sizes for catch-at-age data.
Results and discussion
Table 1 summarises the results for 20, and 50 year projections given 0 and 80 6 age samples each year, while
Figures 1 plots the results.
The bottom row of Figure 1 in particular makes visually evident that there is an improvement in precision of theestimated trajectory of female births when the age data are also available to the estimator.
The extent of this improvement is best quantified by the statistics in Table 1 which relate to estimation
performance for G. After 20 years there is appreciable negative bias in the absence of age data and variances arelarge, but the RMSE is appreciably less when age data are available. After 50 years bias and variance aresubstantially reduced, and the RMSE (which still remains less if age data are provided) is reduced in that last caseto a level where a result is obtained which is almost statistically significant at the 5% level.
References
Kitakado, T and Maeda H. 2016. Fitting to catch-at-age data for North Pacific common minke whales in the
Pacific side of Japan. Paper SC/F16/JR43 presented to the Expert Panel of the final review on the western
North Pacific Japanese Special Permit programme (JARPN II) (unpublished) 12pp.

6

As in Adjunct 3, the actual annual catch here is 107, but after allowing for over-dispersion, the effective“independent” sample size is 80.

117

Table 1: Mean, standard deviation, CV and root mean square error (RMSE) for the estimated environmental
effect on recruitment parameter G (the true value of G is 0.005) after periods of 20 and 50 years, and given either
an effective n=0 or n=80 age samples each year
20yrs
mean
stdev
CV
RMSE

n=0
0.013930.03106
2.229930.03217n=80
0.00634
0.011271.777440.0112950yrs
n=00.006620.00387
0.583450.00417n=80
0.00598
0.00251
0.41898
0.00268

Figure 1: Top row: Medians for “true” and estimated total numbers and female births for sample sizes of 0 and
80 after 50 years. Second row: Medians for “true” and estimated female births for a sample size of 0 (LHS) and80 (RHS), estimated after 20 and 50 years. Third row: Estimated 95%iles, some individual trajectories estimatedand “true” female births for a sample size of 0 (LHS) and 80 (RHS) after 50 years.

118

Appendix A – Methodology
The text following sets out the equations and other general specifications of the SCAA estimation approach
followed by details of the contributions to the log-likelihood function from the different sources of data available.
Quasi-Newton minimization is then applied to minimize the total negative log-likelihood function to estimateparameter values (the package AD Model BuilderTM (Fournier et al. 2012) is used for this purpose).

A.1. Population dynamics

A.1.1 NUMBERS-AT-AGE
The resource dynamics are modelled by the following set of population dynamics equations:𝑖0.5𝑏𝑦+1

if 𝑎 = 0𝑔𝑔(𝑁𝑦,𝑎−1 − 𝐶𝑦,𝑎−1 )𝑆𝑎−1𝑔𝑔𝑔𝑔(𝑁𝑦,𝑚−1 − 𝐶𝑦,𝑚−1 )𝑆𝑚−1 + (𝑁𝑦,𝑚 − 𝐶𝑚 )𝑆𝑚𝑔
𝑁𝑦+1,𝑎 = {if 1 ≤ 𝑎 < 𝑚 (A1)
if 𝑎 = 𝑚

where
𝑔

𝑁𝑦,𝑎
𝑔

is the number of whales of gender g and age a at the start of year y,𝐶𝑦,𝑎is the catch (in number) of whales of gender g and age a during year y,𝑏𝑦𝑖

is the number of calves born at the start of year y,𝑆𝑎

is the survival rate 𝑒 −𝑀𝑎 where 𝑀𝑎 is the instantaneous rate of natural mortality (assumed to be
independent of gender),𝑚 = 50 is the maximum age (treated as a plus-group).

A.1.2. BIRTHS
Density-dependence is assumed to act on the female component of the mature population.
𝑓

𝑓

𝑓 𝑧

𝑏𝑦 = 𝐵𝑁𝑦 {1 + 𝐴 [1 − (𝑁𝑦 ⁄𝐾 ) ]}

(A2)

where
𝐵

is the average number of births (of both genders) per year for a mature female in the pristine population,

𝐴

is the resilience parameter,𝑧

is the degree of compensation,𝑓
𝑓 𝑓
𝑁𝑦 = ∑𝑎𝑚 𝑓𝑎 𝑁𝑦,𝑎

𝑎𝑚
𝑓

𝑓𝑎

is the number of mature females at the start of year y,is the earliest age-at-first parturition;is the proportion of females of age a which have reached the age at first parturition (ogive with parameters
given in Table A.1), and

119

𝐾

𝑓

is the number of mature females in the pristine population.

A.1.3. TOTAL CATCH AND CATCHES-AT-AGE
The catch-at-age is given by:

𝑔

𝑔 𝑔

𝑔

𝐶𝑦,𝑎 = 𝐹𝑦 𝑣𝑦,𝑎 𝑁𝑦,𝑎

(A3)

where
𝑔

𝐶𝑦,𝑎

is the catch-at-age, i.e. the number of animal of gender g and age a caught during year y,

𝑔

𝑔

𝑣𝑦,𝑎

is the commercial selectivity of an animal of gender g and age a for year y; when 𝑣𝑦,𝑎 = 1, the age-classa is said to be fully selected, and

𝑔

𝑔
𝐶𝑦
𝑔
𝑔
𝑎 𝑣𝑦,𝑎 𝑁𝑦,𝑎𝐹𝑦 = ∑

is the proportion of a fully selected age class that is caught.

A.1.4. INITIAL CONDITIONS
For the first year (y0) considered in the model, the numbers-at-age are taken to be at unexploited equilibrium, i.e.:𝑔
𝑁𝑦0,𝑎 = {𝑔
𝑁𝑦0,𝑎−1 𝑆𝑎−1

0.5𝐵𝐾𝑓

if 𝑎 = 0
if 1 ≤ 𝑎 < 𝑚

𝑁𝑦0,𝑚−1 𝑆𝑚−1 ⁄(1 − 𝑆𝑚 )if 𝑎 = 𝑚𝑔(A4)

Input values for the model parameters and data were selected to give a typical population trajectory, which is at
about 50% of carrying capacity in the year the projections start (see Tables A1 and A2).

A.2. Projections

For each simulation i, the population is projected forward using equation A1 and a constant catch of 107 animals
per year.

Future recruitments include residuals and an environmental effect G = 0.005 which reflects a 0.5% increase perannum in recruitment (density dependent effects aside):
𝑓,𝑖

𝑓,𝑖

𝑓 𝑧

𝑖

𝑏𝑦𝑖 = (1 + 𝐺(𝑦 − 2011))𝐵𝑁𝑦 {1 + 𝐴 [1 − (𝑁𝑦 ⁄𝐾 ) ]} 𝑒 𝜑𝑦

𝜑𝑦𝑖 generated from 𝑁(0, (𝜎𝑅 )2 ) with 𝜎𝑅 = 0.25.

120

(A5)

Future observed abundance indices are computed as:
𝑓,𝑖

𝑖

𝜀𝑦
𝐼𝑦𝑖 = ∑𝑚𝑎=1 𝑁𝑦,𝑎 𝑒(A6)𝜀𝑦𝑖 are generated from 𝑁(0, (𝜎𝐼 )2 ) with 𝜎𝐼 = 0.25

Future catch-at-age data are generated under the assumption of a multinomial error distribution:
𝑔,𝑖

𝑔,𝑖 𝑔

𝑔

𝑔,𝑖

𝑂𝑦,𝑎 = ∑𝑎′ 𝐹𝑦 𝑣𝑦,𝑎′ 𝑟𝑎′ 𝑁𝑦,𝑎′ 𝐸𝑎,𝑎′

(A7)

where
𝑔,𝑖

𝑂𝑦,𝑎

is the observed number of whale of age a and gender g caught in year y for simulation i,𝐸𝑎,𝑎is the ageing error matrix (Table A3), and𝑔𝑟𝑎is the age readability at age a for gender g (Table A4).

The standardised residuals are computed as:𝑔,𝑖𝜔𝑦,𝑎 =

𝑔,𝑖
𝑔,𝑖
𝑔,𝑖
𝑔,𝑖
𝑂𝑦,𝑎 ⁄∑𝑎′ 𝑂𝑦,𝑎′−𝑂̂𝑦,𝑎 ⁄∑𝑎′ 𝑂̂𝑦,𝑎′
𝑔,𝑖

𝜎𝑦,𝑎

(A8)

with
𝑔,𝑖

𝑔,𝑖

𝜎𝑦,𝑎 =

𝑂𝑦,𝑎

̂ 𝑔,𝑖
̂ 𝑔,𝑖
𝑂
𝑂
𝑦,𝑎
𝑦,𝑎
(1−
)
̂𝑔
∑𝑎′ 𝑂
̂ 𝑔,𝑖
∑𝑎′ 𝑂
𝑦,𝑎′
𝑦,𝑎′
𝑔,𝑖

∑𝑎′ 𝑂𝑦,𝑎′(A9)A.3. The likelihood function

The model is fitted to projected estimates of total (1+) numbers (from surveys every six years, starting in the firstyear of the projection) and annual catch-at-age data to estimate model parameters. Contributions by each of theseto the negative of the log-likelihood (−𝑙𝑛𝐿) are as follows.

A.3.1 ESTIMATES OF TOTAL (1+) NUMBERS
2(𝜀 𝑖 )−𝑙𝑛𝐿𝑎𝑏𝑢𝑛𝑑 = ∑𝑦 { 𝑦 2 } (A10)
2𝜎

with
𝑓,𝑖

𝑓,𝑖

𝜀𝑦𝑖 = 𝑙𝑛(𝐼𝑦𝑖 ) − 𝑙𝑛(∑𝑎 𝑓𝑎 𝑁𝑦,𝑎 )

(A11)

121

A.3.2. COMMERCIAL CATCHES-AT-AGE
The contribution of the catch-at-age data to the negative of the log-likelihood function under the assumption of amultinomial error distribution is given by:𝑔,𝑖−𝑙𝑛𝐿𝐶𝐴𝐴 = ∑𝑦,𝑔,𝑎 −𝑂𝑦,𝑎 𝑙𝑛 (

𝑔,𝑖
𝑂̂𝑦,𝑎
𝑔,𝑖

∑𝑎′ 𝑂̂𝑦,𝑎′

)
(A12)

A.3.3. FEMALE BIRTHS
The following penalty added to the negative log-likelihood given the variability about the stock-recruitment
relationship:
2

𝑖)
(𝜑𝑦

𝑝𝑒𝑛𝑏𝑖𝑟𝑡ℎ = ∑𝑦 {

2
2𝜎𝑅

}

(A13)

The model assumes an unexploited equilibrium age structure in the starting year (1930). The estimable parametersof the model are K, the environmental effect G, and the annual recruitment residuals 𝜑𝑦 .
References
Fournier, D.A., Skaug, H.J., Ancheta, J., Ianelli, J., Magnusson, A., Maunder, M.N., Nielsen, A., and Sibert, J.
2012. AD Model Builder: using automatic differentiation for statistical inference of highly parameterized
complex nonlinear models. Optim. Methods Softw. 27:233-249.

122

Table A1: Model parameter values assumed. Note that maturity and selectivity are logistic, with am referring to
the earliest age at which first parturition can occur.

123

Table A2: Historical male and female catches assumed.

124

Table A3: Ageing error matrix.

125Table A4: Age readability proportion for males and females.

126

ADJUNCT 3
Analyses underlying choice of sample size for Primary Objective I (common minke whale) for the Pacificside of Japan (sub-areas 7-9)
Introduction
This Adjunct provides the details of an illustrative example of the extent of improvement achievable for theassessment of the dynamics of the O stock of western North Pacific common minke whales in relation to the sizeof the sample taken to provide age data.
The approach followed is founded on the SCAA methodology applied to this stock by Kitakado and Maeda (2016),
which is used to generate future data in a simulation testing context. The intent is to illustrate how well, using
the SCAA methodology to analyse the future data generated, it is possible to detect changes in recruitment (strictlyin the number of recruits per adult female) – specifically whether the sample sizes proposed do secure ameaningful improvement in this detectability.
Data and Methodology
The data used for these analyses are set out in Appendix A. Appendix B provides details of the SCAA assessment
methodology. Note that this remains as in Kitakado and Maeda (2016), and has not been extended to incorporate
some of the suggestions made by the 2016 JARPNII review panel, such as allowing for dome-shaped selectivity.
The reason is that those extensions are not of particular pertinence to the issue under examination in theillustrative exercise here, and are considered to better await subsequent work when the NP minke RMP trials are
re-conditioned on a basis that includes the use of age data, when they will likely also estimate rather than pre-fix
natural mortality (note that estimates of natural mortality at age for larger ages and the extent of doming in theselectivity function are confounded).
Appendix C details how the population model of Appendix B is used to generate the future data required to test
how well the SCAA approach can estimate future recruitments. These data comprise annual catches at age as wellas six-yearly estimates of population abundance. Note that the effects of ageing error are incorporated in both theassessment (Appendix B) and in the projections (Appendix C). The age data are generated using a multinomial
distribution, but analysis of existing data suggests some over-dispersion. Appendix D explains this and how it istaken into account.
Results
Results are presented to show first the dependence on (aged) sample size of the detectability of a 30% decrease
in recruits per adult female. Changes of such a magnitude over a relatively short period are evident from the SCAA
assessments of Antarctic minke whales (GOJ, 2015). For the scenario examined, this change is assumed to takeplace 10 years into the projection period (corresponding to 2022).
The second scenario considered includes instead a 30% increase in recruits per adult female, taking place 10 years
into the projection period.
The third scenario considered is based on the recruitment variability evident for Antarctic minke (stocks I and P)
as estimated in SCAA results for Antarctic minke whales reported to the 2016 annual meeting of the ScientificCommittee. The 1970-2010 vector 𝑿 of moving averages for recruitment variability (renormalized so that the1970 value is 1, see Table 1 for I and P stocks) is used to project recruitment forward from 2011 (using the 1971
value) onwards, with the 2051 value taken to apply to all years from 2052 onwards. A three-year moving average
is used to eliminate some of the estimation error around the real underlying trend; values prior to 1970 are notused as they reflect more model assumptions than being informed by the actual age data. Equation C8 (seeAppendix C) for future births is modified:𝑓,𝑗𝑏𝑦𝑖 = 𝐵 𝑗 𝑁𝑦 𝑋𝑦(1)Results are shown for estimation of O-stock trajectories in terms of annual female births. They compare acrossdifferent “multinomial” sample sizes (n) for the acquisition of age information (see Appendix D for how these“effective” sizes are related to actual sample sizes when allowance is made for over-dispersion). Figure 1 reports
results for a scenario which considers a 30% drop in recruits per adult female after the 10 th year of the projections

127

for the A01_1 RMP trial (IWC, 2014) which sets MSYR(mature) equal to 1%. The results are shown for
estimation after 20 and after 50 years, and include both medians and worm plots (for ten realisations/individual
trajectories, and also showing the 90% probability envelopes shaded). Figure 2 shows similar results for this same
situation except that recruits per adult female increase instead of decreasing by 30%. Figure 3 shows such results
for the A01_1 trial for P stock MSYR(mature) 1% equivalent recruitment variations.
These illustrative results show clearly that the recruitment change is not detected in the absence of age data.
Furthermore detectability improves with both an increasing age sample size and a longer period of data availability,
and is meaningful for the sample size (n=80) proposed (even after 20 years). Note that after adjustment for overdispersion as indicated in Appendix D, this effective sample size of n=80 is increased to an actual size of 107.
References
Government of Japan, 2015. Proponents additional responses to the Report of the Expert Panel to review the
proposal for NEWREP-A. Paper SC/66a/SP8 presented to the IWC Scientific Committee meeting, May 2015
(unpublished) 37pp.
International Whaling Commission. 2014. Report of the Scientific Committee. Annex D1. Report of the Working
Group on the Implementation Review for Western North Pacific Common Minke Whales. J. Cetacean Res.
Manage. (Suppl.) 15: 112-88.
Kitakado, T and Maeda H. 2016. Fitting to catch-at-age data for North Pacific common minke whales in the
Pacific side of Japan. Paper SC/F16/JR43 presented to the Expert Panel of the final review on the western North
Pacific Japanese Special Permit programme (JARPN II) (unpublished) 12pp.

128

Table 1: Moving averages of recruitment variability (renormalized so that the values for 1970 for Antarctic minke
and for 2011 for the assumed projected values for the North Pacific O stock of minke whales are 1). The Antarctic
values correspond to those reported for the I and P stocks of Antarctic minke whales for an MSYR of 1% in
analyses presented by Kitakado to the 2016 meeting of the IWC Scientific Committee. The 1970-2010 values
from the Antarctic are used in the projections for the 2011-2051 period for the North Pacific, with values being
kept constant after 2051.

129

Figure 1: Estimates of female births for scenario A01_1, with MSYR 1% recruitments, with a 30% drop in(per capita) recruitment after 10 years. The left side plots compare medians of estimates after 20 and after 50
years with the true values. The right side plots show worms (individual realizations) after 50 years together with
90% probability envelopes (shaded). The rows reflect different effective (i.e. “independent”) annual sample sizes
for age, ranging from n=0 to n=120.

130

Figure 2: Estimates of female births for scenario A01_1, with MSYR 1% recruitments, with a 30% increasein (per capita) recruitment after 10 years. The left side plots compare medians of estimates after 20 and after
50 years with the true values. The right side plots show worms (individual realizations) after 50 years together
with 90% probability envelopes (shaded). The rows reflect different effective (i.e. “independent”) annual sample
sizes for age, ranging from n=0 to n=120.

131

Figure 3: Estimates of female births for scenario A01_1, for P stock MSYR 1% equivalent recruitment
variations. The left side plots compare medians of estimates after 20 and after 50 years with the true values. The
right side plots show worms (individual realizations) after 50 years together with 90% probability envelopes(shaded). The rows reflect different effective (i.e. “independent”) annual sample sizes for age, ranging from n=0
to n=120.

132

Appendix A - The data
The catches assumed by regions/stocks for males and females separately are given in Table A1 (Cherry Allison,pers. commn). These catches are median outputs from trials A01_1/4 which are detailed in IWC (2014). For the
one stock hypotheses, the catches for males and females have been split by region corresponding to OW and OE(see details given below), assuming the same OW:OE proportions as those in the corresponding C01_1 and C01_4
trials.
The numbers assumed for mature females in 2000 are provided in Table A2. They correspond to deterministic
values for the associated trials, kindly provided by Cherry Allison.
Table A3 gives the males and females catches-at-age from JARPN surveys for the regions corresponding to OW
and OE. Catches in sub-areas 8, 9 and 7E have been assigned to region/stock OE. Catches in sub-areas 11, 7CN
and 7CS have been assigned to region/stock OW. Catches in sub-area 7WR have been assumed to belong toregion/stock OE if taken east of 145E and OW otherwise.
Table A4 lists the life history parameters used (IWC, 2014).
The ageing error matrix is given in Table A5 and is taken to be the same for males and females, across regions.
The sex-specific age readability vectors are listed in Table A6. The assumed proportion of the total sample ofmales and females in each region, based on averages over the 2000-2010 period for JARPN and JARPNII isshown in Table A7.

133

Table A1: Historical male and female minke catches assumed (see text above for source).

134

Table A2: Number of mature females in 2000 (from NP minke ISTs – see text above - Cherry Allisson, pers.
commn). Only the A01_1 scenario is considered here.

135

Table A3: Catch-at-age data from JARPN and JARPN II surveys for regions corresponding to OW and OE.

136

Table A4: Life history parameter values (as defined for the ISTs detailed in IWC (2014)). The maturity ogive islogistic, with am the earliest age at which first parturition can occur.

137

Table A5: Ageing error matrix.

138

Table A6: Age readability proportion for males and females. These values were obtained by fitting logistic curves
to the data available.

Table A7: Assumed proportion of the total sample of males and females in each region, based on averages overthe 2000-2010 period for JARPN and JARPNII.

139

Appendix B - The Statistical Catch-at-Age Model
The text following sets out the equations and other general specifications of the SCAA followed by details of thecontributions to the log-likelihood function from the different sources of data available. Quasi-Newton
minimization is then applied to minimize the total negative log-likelihood function to estimate parameter values(the package AD Model BuilderTM (Fournier et al., 2012) is used for this purpose).

B.1. Population dynamics
B.1.1 NUMBERS-AT-AGE
The resource dynamics are modelled by the following set of population dynamics equations:0.5𝑏𝑦+1𝑔
𝑁𝑦+1,𝑎 = {𝑔

if 𝑎 = 0𝑔(𝑁𝑦,𝑎−1 − 𝐶𝑦,𝑎−1 )𝑆𝑎−1

if 1 ≤ 𝑎 < 𝑚𝑔𝑔𝑔𝑔(𝑁𝑦,𝑚−1 − 𝐶𝑦,𝑚−1 )𝑆𝑚−1 + (𝑁𝑦,𝑚 − 𝐶𝑚 )𝑆𝑚

if 𝑎 = 𝑚

(B1)

where
𝑔

𝑁𝑦,𝑎

is the number of animal of gender g and age a at the start of year y,𝑔𝐶𝑦,𝑎is the catch (in number) of animal of gender g and age a during year y,𝑏𝑦is the number of calves born to females at the start of year y,𝑆𝑎

is the survival rate 𝑒 −𝑀𝑎 where 𝑀𝑎 is the instantaneous rate of natural mortality (assumed to be
independent of gender),𝑚 = 50 is the maximum age (treated as a plus-group).

B.1.2. BIRTHS
Density-dependence is assumed to act on the female component of the mature population.
𝑓

𝑓

𝑓 𝑧

𝑏𝑦 = 𝐵𝑁𝑦 {1 + 𝐴 [1 − (𝑁𝑦 ⁄𝐾 ) ]} 𝑒 𝜀𝑦

(B2)

where
𝐵

is the average number of births (of both genders) per year for a mature female in the pristine population,

𝐴

is the resilience parameter (see Table A4),𝑧

is the degree of compensation (see Table A4),𝑓
𝑓 𝑓
𝑁𝑦 = ∑𝑎𝑚 𝑓𝑎 𝑁𝑦,𝑎

𝑎𝑚
𝑓

𝑓𝑎
𝐾

𝑓

is the number of mature' females at the start of year y,is the earliest age-at-first parturition (see Table A4);
is the proportion of mature female of age a,is the number of mature females in the pristine population, and𝜀𝑦 from 𝑁(0, (𝜎𝑅 )2 ) with 𝜎𝑅 = 0.25.

140B.1.3. TOTAL CATCH AND CATCHES-AT-AGE
The catch-at-age is given by:𝑘,𝑔𝑘,𝑔 𝑘,𝑔𝑔

𝐶𝑦,𝑎 = 𝐹𝑦 𝑣𝑦,𝑎 𝑁𝑦,𝑎

(B3)

where
𝑘,𝑔

𝐶𝑦,𝑎

is the catch-at-age, i.e. the number of animal of gender g and age a caught during year y in region k(where k refers to inshore/offshore),𝑘,𝑔is the commercial selectivity of an animal of gender g and age a for year y in region k; when 𝑣𝑦,𝑎 = 1,
the age-class a is said to be fully selected, and

𝑔

𝑣𝑦,𝑎

𝑘,𝑔

𝐹𝑦

𝑘,𝑔

=

𝐶𝑦

𝑘,𝑔 𝑔
∑𝑎 𝑣𝑦,𝑎 𝑁𝑦,𝑎is the proportion of a fully selected age class that is caught in region k.

B.1.4. INITIAL CONDITIONS
For the first year (y0) considered in the model (here 1930), the numbers-at-age are taken to be at unexploitedequilibrium, i.e.:
0.5𝐵𝐾𝑓𝑔
𝑁𝑦0,𝑎 = {if 𝑎 = 0
if 1 ≤ 𝑎 < 𝑚𝑔
𝑁𝑦0,𝑎−1 𝑆𝑎−1𝑔
𝑁𝑦0,𝑚−1 𝑆𝑚−1 ⁄(1 − 𝑆𝑚 )(B4)

if 𝑎 = 𝑚

B.2. The likelihood function
The model is fitted to estimates of mature female numbers and catch-at-age data to estimate model parameters.
Contributions by each of these to the negative of the (penalised) log-likelihood (−𝑙𝑛𝐿) are as follows.

Mature female numbers
2

𝑎𝑏𝑢𝑛𝑑

−𝑙𝑛𝐿

(𝜀𝑦 )

= ∑𝑗 {

2𝜎𝑦2

}

(B5)

with
𝑓

𝑓

𝜀𝑦 = 𝑙𝑛(𝐼𝑦 ) − 𝑙𝑛(∑𝑎 𝑓𝑎 𝑁𝑦,𝑎 )

(B6)

where
𝐼𝑦
𝜎𝑦 = {

is the estimate of mature female numbers in year y, and
0.01
0.25

for 𝑦 = 2000 (i.e. sufficiently low to force and exact fit to 𝐼2000 )𝑦 ≥ 2012

Commercial catches-at-age
The contribution of the catch-at-age data to the negative of the log-likelihood function under the assumption of amultinomial error distribution is given by:

141

𝑘,𝑔
𝑂̂𝑦,𝑎

𝑘,𝑔

−𝑙𝑛𝐿𝐶𝐴𝐴 = ∑𝑘,𝑦,𝑔,𝑎 −𝑂𝑦,𝑎 𝑙𝑛 (𝑘,𝑔∑𝑎′ 𝑂̂𝑦,𝑎′

)

(B7)

where
𝑘,𝑔

𝑂𝑦,𝑎

is the observed number of whale of age a and gender g caught in year y in region k,

𝑘,𝑔
𝑂̂𝑦,𝑎

is the model-predicted number of whale of age a and gender g caught in year yin region k,

where
𝑘,𝑔
𝑘,𝑔 𝑘,𝑔 𝑔 𝑔
𝑂̂𝑦,𝑎 = ∑𝑎′ 𝐹𝑦 𝑣𝑦,𝑎′ 𝑟𝑎′ 𝑁𝑦,𝑎′ 𝐸𝑎,𝑎′

(B8)

with
𝐸𝑎,𝑎
𝑔

𝑟𝑎

being the ageing error matrix (Table A5), andbeing the age readability at age a for gender g (Table A6).

The standardised residuals are computed as:𝑘,𝑔𝜀𝑦,𝑎 =

𝑘,𝑔,𝑘

𝑔

𝑔

𝑔

𝑂𝑦,𝑎 ⁄∑𝑎′ 𝑂𝑦,𝑎′−𝑂̂𝑦,𝑎 ⁄∑𝑎′ 𝑂̂𝑦,𝑎′

(B9)

𝑔,𝑗

𝜎𝑦,𝑎

with
𝑘,𝑔

𝑘,𝑔

𝑝𝑂𝑦,𝑎

𝜎𝑦,𝑎 =

̂ 𝑘,𝑔
̂ 𝑘,𝑔
𝑂
𝑂
𝑦,𝑎
𝑦,𝑎
(1−
)
𝑘,𝑔
̂
̂ 𝑘,𝑔
∑𝑎′ 𝑂
∑𝑎′ 𝑂
𝑦,𝑎′
𝑦,𝑎′

(B10)

𝑘,𝑔

∑𝑎′ 𝑂𝑦,𝑎′Female births (recruitment) residuals are defined by:
𝑓

𝑓

𝑓 𝑍

𝑏𝑦 = 𝐵𝑁𝑦 {1 + 𝐴 [1 − (𝑁𝑦 ⁄𝐾 ) ]} 𝑒 𝜑𝑦(B11)where 𝜑𝑦 from 𝑁(0, (𝜎𝑅 )2 ) with 𝜎𝑅 = 0.25

with the following penalty added to the negative log-likelihood:(𝜑𝑦 )𝑝𝑒𝑛𝑏𝑖𝑟𝑡ℎ = ∑𝑦 {

2
2𝜎𝑅

2

}

(B12)

The standard deviations for total numbers are computed as follows, taking account of the estimation bias:
2𝑁̂𝑦𝑡𝑜𝑡 − 𝛽𝑦 − 𝑁𝑦𝑡𝑜𝑡 ) ⁄𝑛𝜎𝑦 𝑡𝑜𝑡 = √∑𝑛(𝑁(B13)with the bias computed as:̂𝑦𝑡𝑜𝑡 − 𝑁𝑦𝑡𝑜𝑡 )⁄𝑛𝛽𝑦 = (𝑁(B14)

and similarly for the female births.
To allow for a better fit, carrying capacity K is allowed to change (by a limited amount) every 10 projected years,
starting in 2012, but staying constant during each of these 10 year periods:
𝐾𝑦 = 𝐾𝐾𝑦 = {𝐾𝑦−1 𝑒 𝜀𝑦
𝐾𝑦−1

for 𝑦 ≤ 2011
for 𝑦 = 2012, 2022, 2032 …
for 𝑦 ≠ 2012, 2022, 2032 …

(B15)

142

with the following penalty added to the negative log-likelihood:(𝜀𝑦 )𝑝𝑒𝑛𝐾 = ∑𝑦 {

2
2𝜎𝐾

2

}

(B16)

with 𝜎𝐾 = 0.1.
Thus, aside from selectivity-related parameters, the estimable parameters of the model are K, and the 10-yearly
𝜀𝑦 together with the annual recruitment residuals 𝜑𝑦 .

B.3. Harvesting selectivity
Fishing selectivities-at-age in each region k are estimated using a logistic form:
𝑘,𝑔

𝑘,𝑔

𝑘,𝑔 −1𝑣𝑦,𝑎 = (1 + 𝑒 (∆𝑦,𝑎−𝑎)⁄𝛿𝑦,𝑎 )(B17)Pre-1988, the selectivities are taken to be the same for males and females, with the parameters fixed:   4 and  1.2 (i.e. as for the trials detailed in IWC (2014)).
Post-1988, the selectivities are estimated separately for males and females. Furthermore, 𝜌 is estimated for thefemale selectivity, so that:𝑓𝑓𝑣𝑦,𝑎 → 𝜌𝑣𝑦,𝑎(B18)

Reference
Fournier, D.A., Skaug, H.J., Ancheta, J., Ianelli, J., Magnusson, A., Maunder, M.N., Nielsen, A., and Sibert, J.
2012. AD Model Builder: using automatic differentiation for statistical inference of highly parameterized complex
nonlinear models. Optim. Methods Softw. 27:233-249.

143

Appendix C – Projection methodology
Projections into the future and their evaluation are developed using the following steps.
Step 1: Begin-year numbers-at-age𝑔

The components of the numbers-at-age vector for each gender g and at the start of 2012 (𝑁2012,𝑎 ) are obtained
from the MLE of an assessment.
𝑔𝑔

Error is included for all ages, i.e.: 𝑁2012,𝑎 → 𝑁2012,𝑎 𝑒 𝜀𝑎𝜀𝑎 from 𝑁(0, (𝜎𝑁 )2 )

(C1)

where
𝜎𝑁 is taken to be 0.2 (independent of age).
Step 2: Catch
These numbers-at-age are projected one year forward at a time given a catch for the year concerned 𝐶𝑦 .
𝑘,𝑔This requires specification of how the catch is disaggregated by gender and age and region to obtain 𝐶𝑦,𝑎 , andhow future births are generated.

Step 3: Catch-at-age by region, gender and age
Catch by region:
A 60:40 ratio is assumed for the future catches in the inshore:offshore regions.

Catch by gender:
The male/female fishing mortality ratio is taken to stay constant at the 2007-2011 average estimated in theassessment:
1

𝑘,𝑓
𝑘,𝑚
𝜌 = ∑2011⁄𝐹𝑦
𝑦=2007 𝐹𝑦(C2)

5so that:
𝑘,𝑓

𝐹𝑦

=

𝐶𝑦𝑘
𝑘,𝑓 𝑓
𝑘,𝑚 𝑚
∑𝑎 𝑣𝑦,𝑎 𝑁𝑦,𝑎 +𝑟 ∑𝑎 𝑣𝑦,𝑎
𝑁𝑦,𝑎

(C3)

and
𝑘,𝑓

𝐹𝑦𝑘,𝑚 = 𝜌𝐹𝑦(C4)

The catch by gender is computed by:
𝑘,𝑔

𝐶𝑦

𝑘,𝑓

= 𝐹𝑦

𝑘,𝑔 𝑔 𝑔∑𝑎 𝑣𝑦,𝑎𝑟𝑎 𝑁𝑦,𝑎(C5)Catch by age
𝑘,𝑔

𝑘,𝑔

𝐶𝑦,𝑎 is obtained by assuming that the commercial selectivity of an animal of gender g and age a for year y (𝑣𝑦,𝑎 )stays constant in the future as estimated in the assessment.
𝑘,𝑔𝑘,𝑓 𝑘,𝑔 𝑔𝑔𝐶𝑦,𝑎 = 𝐹𝑦 𝑣𝑦,𝑎 𝑟𝑎 𝑁𝑦,𝑎(C6)

The numbers-at-age can then be computed for the beginning of the following year (y+1):144

0.5𝑏𝑦+1
𝑔𝑘,𝑔(𝑁𝑦,𝑎−1 − ∑𝑘 𝐶𝑦,𝑎−1 )𝑆𝑎−1
𝑔
𝑘,𝑔
𝑔
𝑘,𝑔
(𝑁𝑦,𝑚−1 − ∑𝑘 𝐶𝑦,𝑚−1 )𝑆𝑚−1 + (𝑁𝑦,𝑚 − ∑𝑘 𝐶𝑚 )𝑆𝑚𝑔
𝑁𝑦+1,𝑎 = {if 𝑎 = 0
if 1 ≤ 𝑎 < 𝑚(C7)

if 𝑎 = 𝑚

Step 4: Births
Future births are obtained assuming a density-dependence acting on the female component of the mature
population.
𝑓

𝑓

𝑓 𝑍

𝑏𝑦 = 𝐵𝑁𝑦 {1 + 𝐴 [1 − (𝑁𝑦 ⁄𝐾 ) ]} 𝑒 𝜀𝑦(C8)Step 5: Generate data
The information obtained in Steps 1 to 4 is used to generate NEWREP-NP catch-at-age data. These data are
generated assuming the same multinomial error structure as in the past. The multinomial parameters are theprobabilities for each age and the sample size. The probabilities are the expected proportions-at-age for gender g:𝑘,𝑔𝑂̂𝑦,𝑎 =𝑘,𝑔𝑔𝑔

∑𝑎′ 𝑣𝑦,𝑎′𝑟𝑎′ 𝑁𝑦,𝑎′𝐸𝑎,𝑎′(C9)𝑘,𝑔 𝑔 𝑔∑𝑎∗,𝑎′ 𝑣𝑦,𝑎′𝑟𝑎′ 𝑁𝑦,𝑎′𝐸𝑎∗,𝑎′while the sample size for the corresponding gender is a fixed proportion of the total sample size:𝑛𝑔 = 𝛾 𝑔 𝑛

(C10)

with
𝛾𝑔

given in Table A7.

Note that because the purpose of the exercise is to compare estimation performance for different sample sizes forage data, it is desirable that the true numbers-at-age trajectories are the same though these sample sizes differ.
This has been done by computing the dynamics using the largest sample size considered (160 in this case), andthen scaling down the age-readability vectors to reflect the actual sample size.
In addition, survey estimates of abundance are generated every six years, commencing in year 2012, as follows:𝑓𝑓

𝐼𝑦 = ∑𝑎 𝑓𝑎 𝑁𝑦,𝑎 𝑒 𝜀𝑦(C11)𝜀𝑦 from 𝑁(0, (𝜎)2 ) with = 0.25 .

Step 6: Conduct updated assessment using generated data
The updated assessments follow the procedures set out in Appendix B, incorporating all those historical data in−𝑙𝑛𝐿. For the generated data, the catch-at-age data is included as for the historical data. The generated survey
estimates of abundance are included using equation B5, with 𝜎𝑦 = 0.25, i.e. the assessment assumes the samevalue as used in generating these data.

145

Appendix D – Over-dispersion in catch-at-age data
Over-dispersion in the catch-at-age data has been estimated from the fit of the baseline population model to the
A01_1 scenario, using the following equation:
2

𝐷=∑𝑦,𝐴(∑𝑎∈𝐴(𝑛𝑦,𝑎 𝑝𝑦,𝑎 )−∑𝑎∈𝐴(𝑛𝑦,𝑎 𝑝̂𝑦,𝑎 ))(D1)∑𝑦,𝐴[∑𝑎∈𝐴(𝑛𝑦,𝑎 𝑝̂𝑦,𝑎 )(1−∑𝑎∈𝐴 𝑝̂𝑦,𝑎 )]where the ratio of summations over years rather than the average of yearly ratios was used in the interests of morerobust estimation in the face of differing annual sample sizes.
The result of the calculation yielded D = 1.34, i.e. an increase of about one third.
The original intention was to generate future catch-at-age data from an over-dispersed multinomial distribution
with this value of 1.34 for the over-dispersion parameter. However for the small samples sizes typical for most of
the ages considered here, standard Dirichlet–multinomial generation procedures exhibit large small sample bias,
precluding their use.
In these circumstances the assumption has been made that effective sample size scales inversely with variance.
Hence, given that the value D = 1.34 reflects an increase of about one third, for an actual intended sample size ofN, the sample size used when generating catch-at-age data from a multinomial has been set at n =0.75N.

146

ADJUNCT 4
The selection of sample size North of Hokkaido (sub area 11)
There is limited information on mixing proportion of J stock in sub area 11 (see Annex 7). An examination of therequired sample size to estimate the annual mixing proportion in this sub area with sufficient precision (e.g. SE(p) is less than 0.1).
In the formula below p is the proportion of J stock in the sub-area and n is the number of the samples in the subarea. Standard error of p, SE( p̂ ) is:

SE ( pˆ ) pˆ 1  pˆ n(1)Considering overdispersionφ(>1), equation (1) becomes:

SE ( pˆ ) pˆ 1  pˆ n(1)’

SE( p̂ ) is a maximum when p=0.5 for fixed n. Therefore for this calculation p=0.5 is assumed, without loss ofgenerality. It is desirable to obtain the proportion of the J stock in sub-area 11 with sufficient precision (e.g.
SE( p̂ ) is less than 0.1). To fulfil this condition:

0.5 

 0.1
n
n  25

(2)

Considering that the ratio of unassigned samples is 9% in sub-areas 7CS and 7CN (data from the JARPNII coastal
component), the required sample size should satisfy the following condition:n25
(1  0.09)(3)

The overdispersion parameter was estimated by using the samples in sub-area 7CN, assuming a quasi-binomial
error in conducting Generalized Linear Model GLM):p

exp  a1  a 2 y 
1  exp  a1  a 2 y 

(4)where a1 and a2 are coefficients to be estimated and y indicates year. The overdispersion parameterφ wasestimated as 1.689. Substituting the formula (3) for the estimated parameter the resulting sample size is 47.
It should be noted that this estimate is preliminary, and only applies for the first six years of NEWREP-NP. Moredetailed estimates of sample sizes for the objective of studying yearly trend in the J stock proportion will be madeonce new data are accumulated after the first six surveys.

147

Annex 12
Whale sampling survey design under Primary Objective II (sei whale)
Research area
The main study area for lethal sampling of sei whale will be the western North Pacific while non-lethal researchsuch as sighting survey will be conducted in the pelagic region of the North Pacific delimited by 30°N-50°N;
145°E-140°W, which correspond approximately to the area covered by the Japanese DNA survey.
Research period
Annual surveys in this region will be conducted between April and October, which coincide with the migrationof the species to the summer feeding grounds.
Target species and sample sizes under Primary Objective II
The target species is the sei whale. The annual sample size in the survey area will be XXX animals (see detailsof the sample size estimates in Annex 16. The number of samples by month, year and sub-area collected by
JARPNII in the period 2002-2016 and the expected samples by NEWREP-NP in the period 2017-2022 areshown in Tables 1 and 2, respectively.
Research vessels
The research base Nisshin Maru and two sampling and sampling vessels (Yushin Maru No. 1 and 3) will be
employed for sampling sei whales. See details of the research vessels in Annex 21.
Survey procedure
The track lines and the allocation of vessels will be set in a similar manner as in previous JARPNII surveys. A
zigzag-shaped track line will be set in the research area (see example in Figure 1). The track line consists of one
main and two parallel courses, which will be established seven n.miles apart from the main course. Furthermore,in order to secure the sampling of the estimated number of samples, an Adaptive Type Survey (ATS) (e.g. Pollard
et al., 2002) and a Special Survey (SS) (Bando et al., 2016) may be conducted, when the whale density are
expected to be high. ATS will be designed by adding tracks lines over the predetermined track lines. On the other
hand, the SS will establish new track lines independently from the original track lines. The track lines of ATS andSS consist of one main and two parallel courses that will be established several n. miles apart from main course.
Survey will be conducted under two main modes, NSC and NSS, depending on weather and sea conditions. The
condition to conduct surveys under NSC mode is similar to those established in Japanese dedicated sighting
surveys (i.e. visibility of 2 n.miles or more and Beaufort wind scale of 4 or below). The NSS mode will be used
under unfavorable weather and sea conditions, though the sampling of whales is still possible. These two survey
modes will be recorded separately for future analysis.
Each of the sampling/sighting vessels will change the track line every day to avoid possible sighting bias by afixed position. The starting position of the day will be set at a point where one of the vessels ended the survey inthe previous day in the most advanced position. Other vessels will move to the starting position of the next day
after the end of the daily survey. These daily arrangements of vessels will be determined by the cruise leader. The
survey is conducted at a speed of 10.5 knots from 1 hour after sunrise to 1 hour before sunset (or maximum from06:00 to 18:00), with three top men assigned to the barrel.
Sightings of whales will be classified into primary and secondary sightings. The primary sightings are those madein normal searching mode (three observers searched from the top barrel of the vessel on the predeterminedtrackline). The secondary sightings are those made in modes other than normal searching mode (e.g. duringconfirming or chasing whales, no observer in the top barrel or the vessel engaging in other work).
A researcher on board will record sighting effort and all of the large whale sightings. The sighting record includes
date, time, position of the vessel, survey mode (primary or secondary), angle and distance from the vessel at thesighting, species and school size, estimated body length, etc. Weather information (weather, visibility, winddirection and speed, sea surface water temperature) will be recorded every hour.
All sei whales sighted as primary and secondary sightings, excluding cow and calf pairs, will be targeted forsampling. When a sighting consists of more than one animal, the first targeted animal will be selected using tablesof random sampling numbers (TRS).

148

Sampling will be made by a 75mm whaling cannon. Observers on the top barrel will count the number of whalesin the school and will estimate the body length of each animal. If a sighting is a solitary whale, it will be sampled
immediately after the body length estimation. If a school consists of two or more animals, the researcher willassign a serial number to each individual and the first target whale will be selected using the TRS. When two
whales are sampled from a school, the second target will be selected by the same manner after the first animal issampled. In this case, the remaining individuals will be renumbered according to the latest position in the school.
In order to maintain the human safety during the operations, chasing will be usually limited to a maximum of 120
minutes.
When the sampling vessel take a whale, the whale sampled will be pulled onto the upper deck of the research basevessel where it will be biologically examined by a team of scientists.
Details of the field, laboratory and analytical procedures are given in section 3.2 of the main text.
References
Bando, T., Yasunaga, G., Tamura, T., Matsuoka, K., Murase, H., Kishiro, T. and Miyashita, T. 2016.
Methodology and survey procedures under the JARPNII -offshore component- during 2008 and 2014 withspecial emphasis on whale sampling procedures. Paper SC/F16/J14 presented to the workshop of the Expert
Panel of the final review on the western North Pacific Japanese Special Permit programme (JARPNII),
February 2016 (unpublished). 14pp.
Pollard, J.H., Palka, D. and Buckland, S.T. 2002. Adaptive Line Transect Sampling. Biometrics 58:862-870.

149

Table 1. Distribution of available sei whale samples, by year, month and sub-area.

150

Table 2. Tentative distribution of sei whale samples under the NEWRE-NP, by year, month and sub-area.
Sub-areas
Year-Month

Tot
7

8

9

2017-52017-62017-72017-8

134

134

134

134

134

134

134

134

134

134

134

134

2017-92018-5
2018-62018-7
2018-8
2018-92019-52019-6
2019-7
2019-82019-92020-52020-62020-72020-82020-92021-52021-62021-72021-82021-92022-52022-62022-72022-82022-9

151

50N

45N

40N

35N
130E

135E

140E

145E

150E

155E

160E

165E

170E

Figure 1. Schematic track line design for whale sampling in the offshore component of the NEWREP-NP.

152

Annex 13
Secondary Objective II (i)Abundance estimates for North Pacific sei whales taking account of the additional variance
Field and laboratory work, and analytical procedure
Background
The previous assessment in the IWC/SC performed by Tillman (1977) revealed that the North Pacific sei whales
had undergone substantial decline (approximately 20%) from 42,000 in 1963 to 8,600 in 1974 due to intensive
pelagic whaling. Forty years has passed since whaling of the sei whales was stopped in the North Pacific.
In JARPN II surveys, dedicated sighting surveys were conducted in sub-areas 7, 8 and 9 excluding foreign EEZ
in early and late seasons (Kiwada et al, 2009; Matsuoka et al., 2016). Since 2010, IWC-POWER surveys havecovered the central and eastern North Pacific in longitudinal range between 170 oE and 135oW, in the south of
20oN during 2010-2016 (IWC, 2016a). Given that the sei whales are distributed in the north of 40 oN in summer(Horwood, 1987), most of main distribution area of the sei whales were covered except in the east of 135 oW
longitudinal line.
Hakamada et al. (2009) estimated abundance for the sei whale in sub-areas 7, 8 and 9 in late season as 5,406(CV=0.300) using design based estimator (i.e. IWC standard methodology) based on JARPNII 2006 and 2007
sighting data. Hakamada and Matsuoka (2016) estimated abundance of 5,086 (CV=0.378) in sub-areas 7, 8 and 9
in late season based on 2008 JARPNII sighting data using the design based estimator and detection functions
considering some covariates of detectability. The estimates were presented at the JARPN II review workshop in2016 and the review Panel recommended that (1) exploration of methods to account for sampling differences
between areas and years to obtain measures of short and long-term variation and trends and estimates of the extent
of additional variance due to changes over time in spatial distribution and (2) comparison of results from thedesign-based estimates of abundance with those of model-based estimates, which can be directly obtained fromspatial models of distribution and using additional data (IWC, 2016b). Hakamada and Matsuoka (2015) estimatedabundance based on IWC-POWER data 2010-2012 using the design based estimator and detection function withcovariates. Considering the discussion at the IWC/SC in 2015, Akaike-weighted average of the estimate of 29,632(CV=0.242) was endorsed for use in the in-depth assessment of the sei whales (IWC, 2016c).
Recommendations (1) and (2) raised by the JARPNII review panel should be addressed to investigate the extent
of recovery and the abundance trend of the sei whale stock in the North Pacific.
Field work
Sighting surveys will be conducted by line transect method following the survey protocols set out in theRequirements and Guidelines for Conducting Surveys and analyzing data within the Revised Management
Scheme (IWC, 2012) so that sighting surveys are conducted under oversight of IWC/SC. The research plan will
be submitted to the IWC/SC before the surveys start. Sighting protocols are the same as those used in the IDCRSOWER surveys (IWC, 2008). Considering the recommendation from the NEWREP-A expert panel (IWC, 2015),
the proponents will consider the following: (a) the survey design and methods will be reviewed to take accountprevious IWC sighting surveys and spatial model developments; (b) the proponents will work closely with the
IWC Scientific Committee before finalizing survey approaches; (c) the proponents will also ensure that future
survey plans submitted to IWC SC follow fully the guidelines for such surveys, including the incorporation ofplanned tracklines.
Survey area and period
Provided that two dedicated sighting vessels will be available for the surveys, survey areas are planned to cover
sub-areas 7, 8 and 9 in summer once in three years. For example, sub-areas 7CS, 7CN, 7WR and 7E will besurveyed in the first year, sub-area 8 is planned to be surveyed in the second year and sub-area 9 will be surveyed
in the third year. In this case, abundance estimate for sei whales in sub-areas 7, 8 and 9 would be obtained every
3 years. In case dedicated sighting surveys in the Pacific side and other sub-areas will not be conductedsimultaneously, sub-areas 6E, 10E and 11 would be surveyed once in other three years. In this case, abundance
estimate for sei whales in sub-areas 7, 8 and 9 would be obtained every 6 years.
Areas in the east of 170oE longitude line, are not planned to be covered in the NEWREP-NP dedicated sighting
survey because this area were surveyed in previous IWC-POWER surveys and could be surveyed in future IWC-

153

POWER surveys. Given that IWC-POWER have been conducted in summer (July and August), the sighting
surveys are planned to be conducted in the summer.
Survey mode
Because the use of passing mode in the IWC-POWER would result in very high proportions of unidentified
cetaceans, the POWER technical advisory group (TAG) recommended that Passing with abeam closing mode is
the most appropriate survey mode, both with respect to confirming species identity and school size (IWC, 2013).
This situation would likely occur in sub-areas 7, 8 and 9 because the weather conditions and sea state are notgenerally good in these sub-areas.
The sighting survey will be conducted using Passing with abeam closing. This survey mode follows the protocol
endorsed for the IWC-POWER surveys. Passing with abeam closing mode is in effect passing mode. Two topmen
observe from the barrel at all times. There is open communication between the upper bridge and the barrel. The
observers on the upper bridge should communicate with the topmen only to clarify information and should not
direct the topmen to disrupt their normal search procedure unless directed to do so by the Cruise Leader (Matsuoka
et al., 2012). Immediately after a sighting is made from the barrel, the topmen inform the upper bridge of theirestimate of the distance and angle to the sighting (and also, if possible, the species and number of animals present),
but does not change the normal searching pattern in order to keep contact with the sighting. The observers on theupper bridge must attempt to locate the sighting made by the topmen and decide whether it is possible for themto confirm the species and number before the sighting passes abeam of the vessel. The topmen give no further
information to the upper bridge unless the whale group happens to surface again within the normal searchingpattern of the topmen. A designated researcher on the upper bridge records the species and estimated number ofwhales in the school when the sighting passes abeam of the vessel, in consultation with other researchers. Whenthe sighting passes abeam of the vessel, the ship then changes course to the appropriate heading to approach thewhale, and vessel speed is increased to 15 knots to hasten the closure.
Analytical procedure
Design-based estimator
Assuming that g(0)=1, design based abundance estimator (Thomas et al., 2010), which are the standard
methodology of line transect surveys, were applied. Covariates related to detectability of the whales are used toestimate detection function (e.g. Hakamada and Matsuoka, 2015; 2016). Estimation procedure will be conductedusing DISTANCE program (Thomas et al., 2010). Model selection of the detection functions is made using AIC.
The estimated abundance for each year and each sub-area can be used as input for models to estimate additionalvariance.
Inter-annual variance (additional variance)
The approach in Kitakado et al (2012) can be used to estimate yearly variation in abundance levels due to interannual change in distribution of the sei whale population and abundance trend of the sei whales. By considering
the inter-annual variance, underestimating the variance of the abundance estimate can be avoided. This work
would respond to the recommendation made at the JARPNII review workshop (IWC, 2016b).
Model-based estimator
Density Surface Modeling (DSM) (Miller et al., 2013) will be used, which is one of the packages in the
DISTANCE grogram (Thomas et al., 2010). But there is a room for trying other options (e.g. smoother, modelingframework, variance estimation method etc.) to improve abundance estimates. For example, an approachpresented by Murase et al. (2016) would be used as a template of this type of analysis bearing in mind thecomments from the JARPNII final review workshop (IWC, 2016b). Sea Surface Temperature (SST), Sea Surface
Height anomaly (SSHa) and sea surface chlorophyll-a concentration (Chl-a) recorded by satellites and a digital
seafloor depth data would be used as environmental covariates in the models. Data from ocean circulation models
such as FRA-ROMS would be used as covariates. It is also planned to compare abundance from model-based
estimates with those from the design-based estimates. This work would respond to the recommendation made at
the JARPNII final review workshop (IWC, 2016b).
References
Hakamada, T., Matsuoka, K. and Miyashita, T. 2009. Distribution and the number of western North
Pacific common minke, Bryde’s, sei and sperm whales distributed in JARPN II Offshore component
survey area. Paper SC/J09/JR15 presented to the IWC Scientific Committee Expert Workshop to review
the JARPN II Programme, Yokohama, January 2009 (unpublished). 18pp

154

Hakamada, T. and Matsuoka, K. 2015. Abundance estimate for sei whales in the North Pacific based onsighting data obtained during IWC-POWER surveys in 2010-2012. Paper SC/66a/IA12 presented to IWC
Scientific Committee (unpublished) 11pp.
Hakamada, T. and Matsuoka, K. 2016. The number of western North Pacific common minke, Bryde’s andsei whales distributed in JARPNII Offshore survey area. Paepr SC/F16/JR12. Submitted to the Expert
Panel of the final review on the western North Pacific Japanese Special Permit programme (JARPN II).
(unpublished) 13pp.
Horwood, J. 1987. The sei whale: population biology, ecology and management. London: Croom Helm.
375pp.
International Whaling Commission. 2008. IWC-SOWER cruise 2008/09 Information for researchers.
https://iwc.int/private/downloads/m4RVc06JhBVw3ymd3oPcw/Guide%20%20for%20Researchers%20200809.pdf
International Whaling Commission. 2012. Requirements and Guidelines for conducting surveys andanalysing data within the Revised Management Scheme. J. Cetacean Res. Manage. (Suppl.) 13:509-17.
International Whaling Commission. 2013. Report of the Technical Advisory Group (TAG) meeting on the shortand medium term objectives and plans for the IWC-POWER cruises. Tokyo 26-28 September 2011. J. Cetacean
Res. Manage. (Suppl.) 14: 341-355.
International Whaling Commission. 2015. Report of the Expert Panel to review the proposal by Japan for
NEWREP-A. Paper SC/66a/Rep6 presented to IWC Scientific Committee (unpublished) 62pp.
International Whaling Commission. 2016a. Report of the meeting of the IWC-POWER TechnicalAdvisory Group (TAG). Paper SC/66b/Rep01 presented to IWC Scientific Committee (unpublished)
24pp.
International Whaling Commission. 2016b. Report of the Expert Panel of the final review on the western
North Pacific Japanese Special Permit programme (JARPN II). Paper SC/66b/Rep06 presented to IWC
Scientific Committee (unpublished). 96pp.
International Whaling Commission. 2016c. Report of the IWC Scientific Committee. J.Cetacean Res.
Manage. (Suppl.) 17: 1-92.
Kitakado, T., Hakamada, T. and Miyashita, T. 2012. Extrapolation of abundance to unsurveyed areas in
sub-areas 8, 11 and 12NE for the western North Pacific common minke whales by using prediction with alinear model. Paper SC/64/NPM5 presented to IWC Scientific Committee (unpublished). 6pp.
Kiwada, H., Kumagai, S. and Matsuoka, K. 2009. Methodology and procedure of the dedicated sighting surveys
in JARPN II –Offshore and coastal component of Sanriku and Kushiro-. Paper SC/J09/JR2 presented to JARPNII
review workshop. Yokohama, January 2009 (unpublished) 16pp.
Matsuoka, K., Mizroch, S. and Komiya, H. 2012. Cruise report of the 2011 IWC-Pacific Ocean Whale andEcosystem Research (IWC-POWER). Paper SC/64/IA5 presented to IWC Scientific Committee (unpublished)
27pp.
Matsuoka, K., Hakamada, T. And Miyashita, T. 2016. Methodology and procedure of the dedicatedsighting surveys in JARPN II (2008-2013) - Offshore component -. Paper SC/F16/JR2 presented to the
JARPN II review workshop, Tokyo, February 2016.
Miller, D.L., Burt, M.L., Rexstad, E.A. and Thomas, L. 2013. Spatial models for distance sampling
data: recent developments and future directions. Methods in Ecology and Evolution 4: 1001-10.
Murase, H., Hakamada, T., Sasaki, H., Matsuoka, K. and Kitakado, T. 2016. Seasonal spatial distributionsof common minke, sei and Bryde’s whales in the JARPNII survey area from 2002 to 2013. Paper
SC/F16/JR7 presented to the Expert Panel of the final review on the western North Pacific JapaneseSpecial Permit programme (JARPN II) (unpublished) 17pp.

155

Thomas, L., Buckland, S.T., Rexstad, E.A., Laake, J.L., Strindberg, S., Hedley, S.L., Bishop, J.R.B.
Marques, T.A. and Burnham, K.P. 2010. Distance software: design and analysis of distance sampling
surveys for estimating population size. Journal of Applied Ecology 47: 5-14.
Tillman, M.F. 1977. Estimates of population size for the North Pacific sei whale. Rep. int. Whal. Commn(Special issue 1):98-106.

156

Annex 14
Secondary Objective II (ii)
Estimation of biological and ecological parameters in North Pacific sei whale for RMP Implementation
Field and laboratory work, and analytical procedure
Background
Under the RMP/ISTs, information on biological and ecological parameters is one of key issues for the specificationof trials. Although some parameters like the age at sexual maturity are directly obtainable from observations, there
are several parameters which can only be derived from the results of stock assessments. The IWC has spent a
decade for its discussion and now the SCAA model is recognized as the ‘best currently available model for
examining stock dynamics for Antarctic minke whales’ (IWC, 2014). The SCAA is also applicable to other whale
stocks, such as North Pacific sei whales.
In the age-structured population dynamics model, parameters such as the ‘natural mortality rate (M)’, the ‘MSYR’,recruitment relationship and time-varying carrying capacity are influential to the results. The estimated changes
in the recruitment rate (the number of recruited whales divided by that of mature females) and carrying capacity
over years were clear so far, but estimating and monitoring such likely changes in the future has scientificimportance given consideration of various changes in the ecosystem and environment in the North Pacific.
Therefore, the biological parameters including these which will be estimated from data collected by this program,
will contribute to the trials structure in the RMP ISTs. Biological information required for SCAA analysis will becollected during this program (see Adjunct 1).
Methods
Field and laboratory work
Biological information required for SCAA analysis will be collected from all of the sampled animals. Age data
will be collected by ear plug reading and aspartic acid racemization technique in eye lens. As in the case ofcommon minke whales, earplugs of small individuals will be collected using the method of gelatinized extraction.
Ages of whales with unreadable earplugs are estimated applying age-length-key from body length data to betentatively incorporated into the SCAA (Punt et al., 2014). Body length will be measured straight line from tip ofsnout to notch of flukes for all animals. Maturity of females is determined by presence or absence of corpora
lutea/albicantia in both ovaries. Presence of fetus is examined by cutting both side of uterine horn. Maturity ofmales is preliminary determined by testis weight at the field, and confirmed by examination of histological testis
sample. Testis weight (heavier side) of more than 1,090g is defined as sexually mature (Bando unpublished data)(see Annex 7 for details of field and laboratory works for biological information).
Analytical procedure
Models used in this Secondary Objective are mostly similar with the current SCAA models developed in Punt(2014). The basic assumption is same as that in Punt (2014). The following basic population dynamic is assumed.
1) Basic structure of underlying population dynamics)

Pt ,ga : the number of animals of age a and sex g at the beginning of year t

Rt : the number of birth in year t
0.5Rtfor a  0
 g
gg
P  ( Pt 1,a 1  Ct 1,a 1 ) Sa 1
for 1  a  m  1
 g
g
g
g
g
g
for a  m
( Pt 1,m 1  Ct 1,m 1 ) Sm 1  ( Pt 1,m  Ct 1,m ) Sm
Sa  exp(M a ) : annual survival probability of animals age agt ,aM a : natural mortality rate of animals age a1572) Recruitment function

Rt 

exp logit(ft )   t 
1  exp logit(f t )   t 

Pt F   P  z 
f t  f exp  A 1   t ,1     K    t ~ N (0,  R2 )f

: pregnancy rate at the carrying capacity

A : resilience
K : carrying capacity for 1+ populationm

Pt F    a Pt ,Fa : the number of mature female animals at the beginning of year ta 1mPt ,1   ( Pt ,Ma  Pt ,Fa ) : 1+ population sizea 1

 a : maturity rate for animals of age a3) Catch and selectivity

Ct : catch in year t
 g Pt ,ga

Ctg, a  amax a

 P
a 0

g
a

Ctg

: expected catch of animals of age a and sex g

g
t ,a

1

  a /  : selectivity specific to age, sex and period (Commercial/Scientific)
 tg,a  1  e



g
y

g
y

4) Likelihood function
Log-normal distributions are assumed for abundance estimates. Also, multinomial distributions are used fordescribing stochastic nature of sex-specific catch-at-age data. Also, likelihood for recruitment deviations
contributes to the total likelihood as a penalty function given  R or as an integrand for an integrated likelihood.
Codes written in ADMB or TMB will be employed for optimization.
5) Expected outcomes
The results of SCAA analyses will provide improvement in the precision of key biological and ecologicalparameters. Also, the outcomes will contribute to the specification of the ISTs.
References
International Whaling Commission 2014. Report of the Scientific Committee. Annex G. Report of the SubCommittee on In-depth Assessments. J. Cetacean Res. Manage. (Suppl.) 15: 233-249.
Punt, A.E., Hakamada, T., Bando, T. and Kitakado, T. 2014. Assessment of Antarctic minke whales using
statistical catch-at-age analysis. J Cetacean Res. Manage 14:93-116
Punt, A.E. 2014. A summary history of the application of statistical catch-age analysis (SCAA) to Antarctic minke
whales. J. Cetacean Res. Manage 14: 81-92.

158

Table 1. Key assumption in the model specification
Parameter/Structure in the model
Stock structure
MSYR1+MSYL1+
Mortality rate (M)Initial year and initial depletion
Carrying capacity K1+
Recruitment
Selectivity
Additional variance in abundance estimates(inter-annual distributional change)

Assumption
Single stock
0.01 and 00.25 (given)
0.6 (given)
To be estimatedD (=1) at 1906
To be estimatedDensitity dependence with a fixed MSYR
Deviation in the recruitment
Estimated (commercial, scientific, by sex)
To be estimated and incorporated into the model

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ADJUNCT 1
Further reasons for improving the estimates of M
The views was expressed by the Review Panel for NEWREP-NP about the likely poor precision of attempts tosimultaneously estimate the values of M and MSYR for North Pacific sei whales given the information currently
available and planned to be obtained under NEWREP-NP.
It has already been pointed out by the Proponents in their responses during the Review that such joint estimation
was not the purpose of the proposal (see their morning papers of 1 and 2 February, 2017) submitted to the Panel.
Note also that the Panel seems not to have taken certain important comments in these morning papers into accountin its report (SC/67a/SCSP01).
It is also certainly true that in the case on North Pacific sei whales, the limited data available (either now or in the
short term future) would be insufficient to allow reliable direct estimation of MSYR, either on its own or in
combination with M. However this last point has little immediate pertinence, as at present the standard practicefor ISTs is to consider trials for fixed values of MSYR, and as explained in those morning papers, the NEWREPNP proposal related to estimation of M conditional on a value for MSYR to secure ISTs that more realisticallyreflected stock dynamics, as always needs to be the aim for such trials.
Those morning papers explained that the utility of having such an estimate of M related to transient effects in thestock dynamics. The higher the value of M, the more rapidly population abundance will respond to changes (forexample in recruitment). Annex 16, Figure 5 reports that present data do not exclude values of M for North Pacificsei whale within the range of about [0.02; 0.10]. This corresponds to a multiplicative range of a factor of five,
about the same as typical for a cod compared to a sardine, for which fisheries management approaches certainly
differ in consequence.
One example of the differential consequences of the value of M as a result of such transients emerges fromprojections based on the set of assessments for North Pacific sei whales presented in Annex 16. The conditioning
is simple given that this example is intended to purely as a simple illustration: commercial and research
selectivities are taken to be fixed at their values for the M=0.04 and MSYR(1+)=1% case of the four scenarios
considered in that Annex 16 (in any case those selectivities do not differ greatly across those scenarios), and theresilience parameter A is adjusted for compatibility with MSYR(1+)=1% and a range on M values from 0.02 to
0.10. For each value of M, a value of K for the mature female component of the population is found to secure thepopulation trajectory passes through the abundance estimate for the stock as a whole for 2010. Finally projections
are used to establish what constant future annual catch would result in the population reaching a depletion of 0.72
(the CLA equilibrium) of that component of K after 50 years.
Table 1 lists the values of this catch for each of the values of M considered. What is evident is that despite allthese calculations being conducted for the same value of MSYR, the value of the annual catch changes byrelatively substantial amounts as the value of M is changed. Such differences would certainly be of interest to
managers. Thus even if the value of MSYR is known/assumed, knowledge of the value of M remains important.

160

Table 1: Values of a fixed annual catch that secures a depletion of 0.72 in terms of the mature female populationof North Pacific sei whales after 50 years in relation to the value of natural mortality M.

M

Catch

0.02
0.04
0.06
0.08
0.10

153
93
57
30
6

Moving beyond the current typical ISTs, there is of course the general relationship evident for marine species thatvalues for productivity and M across resources tend to be positively correlated (e.g. Andersen et al. 2009), so that
information on the value of M adds qualitatively at least to an evaluation of the plausibility of different values for
MSYR.
But as SC/67a/SCSP01 states, the NEWREP-NP proposal considers the RMP not only in its current form, but as
it will need to be modified for future improvement, particularly given the availability of age data. This allows formuch improved estimation of annual recruitments and their changes over time, and moves the situation for thewhale stock concerned much closer to that typical for the management (including under MPs) of fish populations.
The calculation basis underlying SC/67a/SCSP08 is a class of assessment models (sometimes called agestructured production models) used in a “data-limited” situation (as has applied in the past for most whale
populations), and in particular relies heavily of an assumed stock-recruitment function and the assumption of a
resource at equilibrium prior to the onset of exploitation. In contrast, the greater data set (particularly including
age data) that is available for many fish stock assessments sees much less reliance on such assumptions to obtain
more reliable results. The associated projections (including for MP testing purposes) are typically much moreheavily based on estimates over a recent period of annual recruitments in relation to the reproductive componentof the population. In these circumstances, the value of M has a much greater influence on assessment outputs andon the estimation of target levels for abundance. For whales there are already cases such as the Eastern North
Pacific gray whale and the Indo-Pacific Antarctic minke whale which provide examples of violations of thoseassumptions regarding pre-exploitation equilibrium and standard stock-recruitment relationships. This adds
weight to the desirability of moving whale stocks closer to the typical fish stock assessment situation, given
especially the availability of age data; this process is likely to see the value of M start to play a more importantrole in the manner in which ISTs are developed in the future.

Reference
Andersen, K. H., Farnsworth, K. D., Pedersen, M., Gislason, H., and Beyer, J. E. 2009. How community ecology
links natural mortality, growth, and production of fish populations. – ICES Journal of Marine Science, 66: 1978–
1984.

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Annex 15
Secondary Objective II (iii)
Study of the pattern of movement of whales of the ‘pelagic stock’ within the feeding grounds and between
feeding and breeding grounds
Field and laboratory work, and analytical procedure

Background
The in-depth assessment of North Pacific sei whale started at the 2015 IWC SC meeting. The IWC SC agreed toproceed with two initial alternative stock structure hypotheses: i) a single stock in the entire North Pacific asproposed by Kanda et al. (2015a;b), based on several pieces of evidences included the genetics; and ii) a fivestock hypothesis proposed in Mizroch (2015), based mainly on the interpretation of mark-recapture data: Japan
coastal; North Pacific pelagic; Aleutian Islands and Gulf of Alaska; eastern North Pacific migratory; and Southern
North American coastal stock (coastal California) (IWC, 2015a). The IWC SC agreed that discriminating between
these two hypotheses is difficult in the absence of genetic data from the potentially extirpated stocks, and thus
both hypotheses are plausible (IWC, 2015a). The IWC SC agreed that the oceanic regions of the North Pacific arecomposed by a single stock (IWC, 2015a).
Under this new research program both satellite tracking and routine genetic analyses will be used to address thisSecondary Objective. Under the single pelagic stock hypothesis it is expected random movement of whales in thefeeding grounds. Satellite tracking experiments have also the potential to provide information on movement of
whales from the feeding grounds to breeding grounds. The method of satellite tracking is widely used by IWC SC
and was also useful to track the movement of two Bryde’s whales in the North Pacific (Murase et al., 2016).
All samples obtained from the surveys of JARPNII, IWC-POWER, past commercial whaling and additional new
samples from the new research will be analyzed to further examine the spatial population genetic structure of sei
whale in the North Pacific, in particular to examine the plausibility of the ‘North Pacific pelagic’ stock.
Methods
Field works
Satellite tagging
Feasibility trials for satellite tracking will be conducted to address the question of movement to the north of thetentative limit of the ‘pelagic stock’ under one of the stock structure hypothesis (see item 4.2 in the main text),
and to the south of the tentative limit. The former will be conducted early in the feeding season and the experimentwill be useful to understand the northern distribution of the stock and at the same time the plausibility of some
proposed stocks under one of the stock structure hypotheses (see section 4.2). The latter will be conducted late in
the feeding season and the experiment will be useful to investigate migratory routes of whales to lower latitude
areas. Trials will be conducted during the dedicated sighting surveys or by the sighting and sampling vessels. On
such occasions a total of five trials will be attempted during the research period.
With regard to field methods as well as tag types, ICR scientists will collaborate and consult with experienced
foreign and Japanese colleagues.
The study will be based on a pneumatic tool (e. g. the whale tag launcher: Aerial Rocket Tag System (ARTS),
Lars Kleivane and Restech Norway A/S, Norway and satellite tag: SPOT6, Wildlife computers, WA, USA) (Isoda
et al., 2016). Satellite tags are shot by this tool from the bow deck with a blubber penetration-type mount system.
The tagged whales will be also target of biopsy sampling using the Larsen-gun system.
In addition a member of the proponents will attend the IWC-ONR Joint Workshop on Tag Development, FollowUp Studies and best Practices to be held in September 2017 in Silver Spring, MD (USA) to become acquainted
with the most current tagging technologies and deployment methods.
Genetic samples
Skin tissues of sei whales will be taken during NEWREP-NP and stored in 99% ethanol until DNA extraction. In
the case of biopsy sampling, the details of equipment and sampling procedure are described in Annex 19.
Laboratory works
Genetics
Laboratory work and data analyses described in this Annex will follow the IWC SC’s guidelines for DNA data

162

quality (IWC, 2009) as much as possible. Sampling and laboratory procedures of the genetic laboratory of theInstitute of Cetacean Research were summarized by Kanda et al. (2014), and the IWC SC agreed that the paper
had responded appropriately to some relevant recommendations on DNA data quality from the JARPAII review
workshop (IWC, 2015a, b). In 2016 additional information was provided by the proponents on estimates of
microsatellite genotyping error rates and again, the IWC SC agreed that the work presented had addressed arecommendation on DNA data quality from the JARPNII final review workshop (IWC, 2016a).
Details of the laboratory procedure for microsatellite marker can be found in Annex 7. However, a different setof microsatellite loci are used in the present analyses: EV1, EV14, EV21, EV94, EV104 (Valsecchi and Amos,
1996), GT011 (Bérubé et al., 1998), GT23, GT211, GT271, GT310, GT575 (Bérubé et al., 2000), GATA28,
GATA53, GATA98, GATA417, GGAA520 (Palsbøll et al., 1997), and DlrFCB17 (Buchanan et al., 1996).
Analytical procedure
Genetics
Following recommendations from the IWC SC further analyses based on STRUCTURE and DAPC will be
conducted (IWC, 2016b).
The Bayesian clustering approach is conducted in the program STRUCTURE version 2.0 (Pritchard et al., 2000)
to determine the most likely number of genetically distinct stocks using all available genotype data. The program
implements a model-based clustering method for inferring stock structure (K, the number of stocks in the model)using multilocus genotype data with and without information on sampling locations. The program STRUCTURE
allows for the analyses of the samples without choosing sample units. In the present analysis, posterior
probabilities for each K are estimated from ten independent runs for K = 1-3 without information on sampling
locations. All runs are performed with 100,000 Markov chain Monte Carlo repetitions and 10,000 burn in length using the admixture model which assumes individuals may have mixed ancestry, with correlated
allele frequencies which assumes that frequencies in the different stocks are likely to be similar due to migrationor shared ancestry.
The Discriminant Analysis of Principal Components (DAPC) is performed to identify and describe clusters ofgenetically related individuals (Jombart et al., 2010). DAPC relies on data transformation using PCA as a priorstep to DA which ensures that variables submitted to DA are perfectly uncorrelated, and that their number is lessthan that of individuals analyzed. Along with the assignment of individuals to clusters, DAPC provides a visualassessment of between-population genetic structures, permitting to infer complex patterns such as hierarchicalclustering or clines (Jombart et al., 2010). Following these authors, the K-means clustering of principal
components is used to identify groups of individuals. K-means relies on the same model as DA to partition genetic
variation into a between-group and a within-group component, and attempts to find groups that minimize the latter(Jombart et al., 2010). K-means is run with different numbers of clusters, each of which gives rise to a statisticalmodel and an associated likelihood.
References
Bérubé, M., Aguilar, A., Dendanto, D., Larsen, F., Notarbartolo-di-Sciara, G., Sears, R., Sigurjónsson, J., UrbanRamirez, J., and Palsbøll, P.J. 1998. Population genetic structure of North Atlantic, Mediterranean Sea and Sea ofCortez fin whales, Balaenoptera physalus (Linnaeus, 1758); analysis of mitochondrial and nuclear loci. Mol. Ecol.
7:585-599.
Bérubé, M., Jørgensen, H., Mcewing, R., and Palsbøll, P.J. 2000. Polymorphic di-nucleotide microsatellite lociisolated from the humpback whale, Megaptera novaeanglliae. Mol. Ecol. 9:2181-2183.
Buchanan, F.C., Friesen, M.K., Littlejohn, R.P., and Clayton, J.A. 1996. Microsatellites from beluga whale
Delphinapterus leucas. Mol. Ecol. 5:571-575.
Buchanan, F.C., Friesen, M.K., Littlejohn, R.P., and Clayton, J.A. 1996. Microsatellites from beluga whale
Delphinapterus leucas. Mol. Ecol. 5:571-575.
International Whaling Commission. 2009. Report of the Scientific Committee. Annex I. Report of the working
group on stock definition. Appendix 2. Guidelines for DNA data quality control for genetic studies relevant to
IWC management advice. J. Cetacean Res. Manage. (Suppl.) 11:252-256.
International Whaling Commission. 2015a. Report of the Scientific Committee, Annex G. Report of the SubCommittee on In-Depth Assessments. J. Cetacean Res. Manage. (Suppl.) 16:176-195.

163

International Whaling Commission. 2015b. Report of the Expert Workshop to Review the Japanese JARPAII
Special Permit Research Programme. J. Cetacean Res. Manage. (Suppl.) 16: 369-409.
International Whaling Commission. 2016a. Report of the Expert Panel of the Final Review on the Western North
Pacific Japanese Special Permit Programme (JARPN II). J. Cetacean Res. Manage. (Suppl.) 18: xxx-xxx.
International Whaling Commission. 2016b. Report of the Scientific Committee. Annex I. Report of the Working
Group on Stock Definition. J. Cetacean Res. Manage. (Suppl.) 18: xxx-xxx.
Isoda, T., Kawabe, S., Ohkoshi, C., Mogoe, T. and Matsuoka, K. 2016. Results of the NEWREP-A dedicatedsighting survey in Area IV during the 2015/16 austral summer season. Paper SC/66b/IA05 presented to the IWC
Scientific Committee, May 2015 (unpublished). 25pp.
Jombart, T., Devillard, S. and Balloux, F. 2010. Discriminant analysis of principal components: a new method forthe analysis of genetically structured populations. BMC Genetics 11:94.
Kanda, N., Goto, M., Oikawa, H. and Pastene, L.A. 2014. Update of note on sampling and laboratory procedure
protocols of the genetic work at the Institute of Cetacean Research (SC/F14/J27rev). Paper SC/65b/DNA1
presented to the IWC Scientific Committee, May 2014 (unpublished). 6pp.
Kanda, N., Matsuoka, K., Goto, M. and Pastene, L.A. 2015a. Genetic study on JARPNII and IWC-POWER
samples of sei whales collected widely from the North Pacific at the same time of the year. Paper SC/66a/IA8
presented to the IWC Scientific Committee, San Diego, May 2015 (unpublished). 8pp.
Kanda, N., Bando, T., Matsuoka, K., Murase, H., Kishiro, T., Pastene, L.A. and Ohsumi, S. 2015b. A review ofthe genetic and non-genetic information provides support for a hypothesis of a single stock of sei whales in the
North Pacific. Paper SC/66a/IA9 presented to the IWC Scientific Committee, San Diego, May 2015 (unpublished).
17pp.
Mizroch, S.A., Conn, P.B. and Rice, D.W. 2015. The mysterious sei whale: Its distribution, movements andpopulation decline in the North Pacific revealed by whaling data and recoveries of Discovery-type marks. Paper
SC/66a/IA14 presented to the IWC Scientific Committee, San Diego, May 2015 (unpublished). 112pp.
Murase, H., Tamura, T., Otani, S. and Nishiwaki, S. 2016. Satellite tracking of Bryde’s whales Balaenoptera
edeni in the offshore western North Pacific in summer 2006 and 2008. Fish. Sci. 82: 35-45.
Palsbøll, P.J., Bérubé, M., Larsen, A.H., and Jørgensen, H. 1997. Primers for the amplification of tri-and tetramer
microsatellite loci in baleen whales. Mol. Ecol. 6:893-895.
Pritchard, J.K., Stephens, M., and Donnelly, P. 2000. Inference of population structure using multilocus
genotype data. Genetics 155:945-959.
Valsecchi, E., and Amos, W. 1996. Microsatellite markers for the study of cetacean populations. Mol. Ecol. 5:151156.

164

Annex 16
Estimates of sample size for Primary Objective II (sei whale)
Introduction
This annex introduces an approach to estimate the proposed sample size for the North Pacific sei whales to meetthe Primary Objectives II, especially the Secondary Objective II (ii). The approach followed is based on the ageand sex-structured model applied to this stock for conditioning and generating future data in a simulation. The
target is to estimate the natural mortality rate, M, by using the SCAA methodology.
Materials and methods
Data for conditioning
The data used for the conditioning are as follows:
i)
ii)
iii)

Catch series since 1906 (aggregated over ages and sexes) (Figure 1).
Sex-specific catch-at-age data for commercial period (1966-1973) and those from JARPNII (20022013) (Figures 2 and 3).
An abundance estimate of the sei whales, 34,718 (CV=21.4%) in the whole North Pacific area
(Hakamada and Matsuoka, 2015; 2016). Note that this estimate adds the contributions from the IWCPOWER and JARPNII cruises which covered non-overlapping areas

Model assumed for conditioning
The population dynamics assumed for the conditioning is the same as the model shown in Annex 14 except for
the recruitment as   P  z FRt  f Pt exp  A 1   t ,1     K   
The plus group age is set at m=40, and in the maturity ogive, age at 50% maturity is fixed at 7.5 with scaleparameter 1.2. The natural mortality is assumed to be age-independent as M=0.04 and 0.05 (/year) (the reasonsfor these choices are explained below), and the MSYR(1+) is set at 1 and 2.5%. These values are used not only
for conditioning but also for generating future data in the simulation context to assess the estimation performanceof the natural mortality coefficient.
For the estimation process, given the single abundance estimate available, a procedure like ‘Hitter’ was applied,which means the standard deviation of abundance estimate was intentionally set at a tiny value (here at 0.01) while
naive multinomial distributions were assumed for the catch-at-age data. Unknown parameters to be estimated in
the model fitting process) are the carrying capacity, sex- and fleet- (same as period-) specific selectivity parameters
given the values of M and as well as MSYR (equivalently given A). The fecundity is solved internally assumingthat population in the start year 1906 is at equilibrium.
Conditioning gave rise to some problems because the historical catch-at-age data for the commercial period show
substantial variability and are in fact made available only as ages rounded to odd integers. The likelihoods obtained
did, however, indicate a preference for M values close to the 0.04 to 0.05 range.
Model assumed for simulation
Based on the conditioned models, projections were conducted to generate future abundance estimates and catchat-age data. Given the somewhat questionable nature of the historical age data from commercial whaling, it was
decided not to use these when fitting the model given additional data generated in the future; furthermore
commercial and research selectivities (the same for the past and the future) were fixed at their values estimatedfor the MSYR/M scenario concerned. For 12 years research period, it was assumed that an abundance estimate isavailable twice though not for the whole area of the North Pacific but only the survey area covered under
NEWREP-NP. These abundance estimates are subject to the process error due to inter-annual variations in spatial
distribution, and therefore it was assumed that the abundance estimates generated when inflated to the whole areafor use in the simulations have a larger CV (30%) than CV=21.4% for the actual survey to take additional varianceinto consideration.

165

In the projection and generation of future data, log-normal deviations are incorporated into the recruitment
although these recruitment deviations were turned off in the estimation process. The projection starts from 2014
because the model was conditioned data up to 2013. In the 3-year gap, the actual catch was allocated to age
composition using estimated selectivity and numbers-at-age. For future catch-at-age data, multinomial
distributions were used without assuming any overdispersion and age-reading error. Age-readability was assumed
to be 70% across all the ages based on a coarse analysis. The various annual sample sizes for the 12 years of theresearch program generated for the evaluation were 40, 60, 80, 100, 120 and 140. For each sample size, data
generation and estimation were repeated 100 times (i.e. n=100 for the measures defined below). Estimation
assumed the true selectivities, so that only carrying capacity K and natural mortality M were estimated estimated.
The existing JARPNII age data were not included in the likelihood for these fits because of ‘double usage’concerns since they had been used to fix the research selectivity; including them would not have a large effect on
results as they total only 100, which is small compared to the sample numbers to be accumulated over the research
period.
Performance measures
The parameter of interest is the natural mortality (M), and therefore the following three measures are used forevaluation of estimation performance by sample size.
RMSE 

CV 





2
1 n ˆ
Mi  Mn i 1





2
1 n ˆ
 Mi  M / M
n i 11 n
Relative Bias  100   Mˆ i  M  / M
 n i 1Results and conclusion
Figure 4 shows the performance measures for the four scenarios (true M/MSYR combinations) considered. Robust
results across these scenarios are that for an annual sample size n of 100 or above, bias reduces to close to zero,
and RMSE stabilises at about 0.005. Figure 5 illustrates how the variance of the distribution of M estimates
narrows considerably as the sample size is increased from 40 to 100.
This value makes no allowance for possible over-dispersion in the age data, and the sample sizes available are too
small to estimate this reliably. Consequently the assumption has been made that this is the same as for minke
whales, corresponding to a need to increase the sample size by a multiplicative factor of 1.34 (see Appendix D of
Adjunct 3 of Annex 11).
Consequently the proposed annual sample size for sei whales is 134.
References
Hakamada, T. and Matsuoka, K. 2015. Abundance estimate for sei whales in the North Pacific based on sighting
data obtained during IWC-POWER surveys in 2010-2012. Paper SC/66a/IA12 presented to IWC ScientificCommittee, May 2015 (unpublished). 11pp.
Hakamada, T. and Matsuoka, K. 2016. The number of western North Pacific common minke, Bryde’s and sei
whales distributed in JARPNII Offshore survey area. Paper SC/F16/JR12 presented to the Expert Panel of the
final review on the western North Pacific Japanese Special Permit programme (JARPN II),Tokyo, February 2016 (unpublished). 13pp.

166

Figure 1. Catch series for the North Pacific sei whales.

Figure 2. Catch-at-age data for male (left) and female (right) in commercial period (1966-1975)

Figure 3. Catch-at-age data for male (left) and female (right) in JARPN-II period (2002-2013).

167

Figure 4. Summary of estimation performance for the true values of M at 0.04 and 0.05 under MSYR(1+)=1.0
and 2.5%.

Figure 5. Histogram of estimates of M for the sample sizes 40 and 100 under M= 0.04 and MSYR= 2.5%

168

Annex 17
Ancillary Objective I
Investigation of the influence of environmental changes on whale stocks
Field and laboratory work, and analytical procedure
Background and objectives
There have been many studies on regime shift of the marine ecosystem in the western North Pacific around 1925,
1947, 1977 and 1998 (King, 2005, Overland et al., 2008, Takasuka et al., 2008; Tian et al., 2004; Yatsu et al,
2001, 2008). It is well known that the regime shift triggered fish replacement: dominant pelagic fish specieschanged from Japanese sardine (Sardinops melanosticus) in the 1980s and 1990s to mackerels in the 2000s, andrecent data indicates the recovery of Japanese sardine. It is important to elucidate the effect of environmental
change on baleen whales from both ecological and management points of view. On the latter, possible changes in
the geographical and temporal distribution of baleen whale stocks will affect the interpretation of abundance
estimates and trends based on systematic sighting surveys. Abundance estimates and trends are important pieces
of information for management under the RMP.
The results suggested that JARPNII from 2000 to 2013 was conducted in relatively stable oceanographic
conditions on a broader scale while oceanographic conditions on a local scale (i.e. off Kushiro) in the same period
were highly variable. However, it has been pointed out that further monitoring of oceanographic conditions would
be required to determine whether the climatic regime for the period of JARPNII had changed or not (Tamura etal., 2016a).
In recent years, yearly changes in the prey species of common minke whales were not observed in coastal water
off Sanriku (Tamura et al., 2016b). On the other hand, in the Pacific coastal water off Kushiro, the dominant preyspecies shifted from Japanese anchovy (Engraulis japonicus) and Pacific saury (Cololabis saira) to Japanesesardine and mackerels after 2011. Similarly, the yearly changes in the dominant prey species of sei whales shiftedfrom Japanese anchovy to Japanese sardine and mackerels after 2014 (Tamura et al., 2016c). These phenomena
could be associated with pelagic fish regime shift as described in Yatsu et al., (2001) and Takasuka et al. (2008).
As with past studies (e.g. Kasamatsu and Tanaka, 1992), this suggests that the feeding strategy of common minke
and sei whales are adaptive to optimize their feeding strategy in their environments.
This aspect of the NEWREP-NP will be focused on following two issues.
i.
ii.

Contribution to the understanding of the environmental change based on phenomenon such as thechange in distribution of whales and their prey species.
Data collection for elucidation of the cause of the change in distribution of whales and their prey species.

The research will contribute to the scientific understanding of the impact of prey change on common minke andsei whales and their geographical movements in the western North Pacific during the long-term research activityof NEWREP-NP. For example, NEWREP-NP could see changes in migration timing of common minke and sei
whales that may be caused by environmental change. Such ecological changes related to common minke and sei
whales and the possible effects on management under the RMP should be further investigated through theexamination of data on distribution, abundance and feeding habits of common minke and sei whales andenvironmental variables. For a better understanding of this Secondary Objective Figure 1shows a flow chartindicating the data to be collected, analyses and expected outputs.
Field work
Sighting surveys
Dedicated sighting surveys will be conducted in the coastal waters of Japan to understand the distribution patternsof common minke and sei whales. Survey protocols will follow the ‘Requirements and Guidelines for conducting
surveys and analyzing data within the Revised Management Scheme’ (IWC, 2012). Sighting protocols aredescribed in Annexes 8 and 14.
Trawling and acoustic survey for prey species
One of the key elements of this aspect of NEWREP-NP is to monitor the pelagic fish replacement since baleen
whales are highly depend on pelagic fishes.

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In the Sanriku region, the prey survey will be conducted by the Miyagi Prefecture Fisheries Technology Institute.
Survey protocols will be applied as in Wada et al (2016). Acoustic, trawl, and oceanographic surveys will be
conducted using a trawler-type R/V, “MIYASHIO” (Miyagi prefecture, 199 GT). Data on the distribution andabundance of the prey species will be recorded by a quantitative echosounder, EK60 (Simrad, Norway) with
operating frequency at 38, 120 and 200 kHz. The RV will steam at 9-10 knots along the track-lines. Acoustic data
will be stored with the aid of software, Echoview (Sonar Data, Australia). Calibration will be carried out in thesurvey area using the copper sphere technique described in the EK 60 manual. Vertical oceanographic
observations will be conducted with CTD. Subsurface (approximately 5m water depth) temperature, salinity andchlorophyll-a index will be recorded every minute (in time) along the track-lines. Trawl sampling will be
conducted to identify the species and size compositions of targeting echo signs. The trawl net will have a mouth
opening of 7 m (width) by 3.5 m (height) and a 3 mm liner cod end. The depth and the height of the mouth of the
net will be monitored with a net recorder. The towing speed of the trawl net will be 2-4 knots. Catches will beidentified to the species level and weighed aboard the vessel.
The prey survey will not be conducted at this stage in the Kushiro, Okhotsk and offshore regions (sub areas 8 and
9). However, the information on abundance and occurrence of prey species in these regions will be obtained fromthe Japan Fisheries Research and Education Agency (FRA), Kushiro Fisheries Research Institute and Abashiri
Fisheries Research Institute in the Hokkaido Research Organization.
Whale sampling for common minke whales
Sampling procedure for common minke whales is described in Annex 6.
Whale sampling for sei whales
Sampling procedure for sei whales is described in Annex 12.
Measurement of nutritional condition indexes and stomach contents
The measurement of nutritional condition indexes and stomach contents will be applied as described by Tamura
et al. (2016b, c) and Konishi (2016). After capture, the stomach contents will be removed from each compartment
and weighed to the nearest 0.1kg on the ship’s flensing deck. The analysis of prey consumption in this study will
be based on data collected from the first compartment (forestomach) and second compartment (fundus). To
examine the daily feeding rhythms of the whales, the freshness of prey in the forestomach will be categorized into
four digestion levels. An estimate of the daily prey consumption requires the use of some additional biologicaland morphometric data. Body length of the whales will be measured to the nearest 1cm from the tip of the upper
jaw to the deepest part of the fluke notch in a straight line. Body weight will be measured using large weighing
machine to the nearest 50kg. Energy requirements are different for sexual maturity classes; therefore, estimationsof the daily prey consumption in this study will take into consideration information on sexual maturity. Sexual
maturity of each whale will be defined by testis weight and observation of the ovaries. Nutritional condition will
be measured as a part of routine measurements of marine mammals such as blubber thickness, girth, body weightin combination with lipid contents (%) of blubber.
Stomach contents/tissue sampling
The analysis of prey composition and consumption will be based on data collected from the first compartment(forestomach) and second compartment (fundus). First stomach content will be removed from each stomach
component and will be weighed to the nearest 0.1kg. Then all contents will be classified to major prey groups
such as euphausiids, copepods, fish and others. Basically, a sub-sample (1-5kg) of stomach contents will beobtained and frozen and/or fixed with 10% formalin for later analyses. The sub-sample volume will depend on
the whole stomach volume and on the prey’s size. When stomach contents are prey-diverse, more sub-samples ofstomach contents will be obtained and frozen. This methods will ensure that the samples is representative of thewhole stomach contents.
At the laboratory prey species in the sub-samples will be identified to the lowest taxonomic level as possible.
Undigested prey will be identified using morphological characteristics, based on different reference sources. The
stomach will be transferred to a system consisting of three sieves (20mm, 5mm and 1mm), which was applied in
the Norwegian scientific research to filter off liquid from the rest of the material (Haug et al., 1995).
To measure the lipid content %, the blubber, ventral groove and intestinal fat of all whales will be sampled.

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Attachment of satellite tagging and data logger
To understand seasonal migration and reaction to prey environment, satellite tagging and data logger experiments
for the common minke and sei whales will be conducted. As in the past survey, the study will be based on apneumatic tool (the whale tag launcher: ARTS Aerial Rocket Tag System, Lars Kleivane and Restech Norway
A/S, Norway) and satellite tag (SPOT6, Wildlife computers, WA, USA). Satellite and dummy tags will be shotfrom the bow deck by the pneumatic tool carrying a blubber penetration-type mount system for whales. The
harpoon heads function to anchor under the skin.
Oceanographic observation
Oceanographic conditions in the NEWREP-NP will be investigated using data from ocean circulation models
such as FRA-ROMS (Okazaki et al., 2016a, b) and other resources.
Laboratory work
Prey species identification
In the laboratory prey species in the sub-samples will be identified to the lowest taxonomic level as possible.
Undigested prey will be identified using morphological characteristic, based on different sources: copepods(Brodskii, 1950), euphausiids (Baker et al., 1990), squids (Kubodera and Furuhashi, 1987) and fish (Masuda etal., 1988; Chihara and Murano, 1997). The otoliths and jaw plate will be used to identify the fish with advanced
stage of digestion (Morrow, 1979; Ohe, 1984; Kubodera and Furuhashi, 1987; Arai, 1993).
When undigested fish and squid are found, fork length, mantle length and the weights will be measured to thenearest 1mm and 1g, respectively. This data will be used for restoring stomach contents with advanced stage ofdigestion.
The total number of each fish and squid species in the sub-sample will be calculated by adding to the number of
undigested fish or squid, undigested skulls and half the total number of free otoliths. The total weight of each preyspecies in the sub-sample will be estimated by multiplying the average weight of fresh specimens by the numberof individuals. The total number and weight of each prey species in the stomach contents will be estimated byusing the figures obtained from the sub-sample and the total weight of stomach contents.
Feeding period estimation
Stable isotope analyses from the edge of baleen plates will also be conducted under the NEWREP-NP program toestimate the time spent and dive time by common minke and sei whales in feeding grounds. Stable isotopes inbaleen plates (n=10-20) of common minke and sei whales sampled under NEWREP-NP will be analysed early inthe research program, as an initial step. At the same time, in order to obtain further information on time spent bycommon minke and sei whales in the feeding grounds, tagging methods for data loggers (TDR) and satellite
tagging transmitters will be developed.
Nutritional condition
Dermal and hypodermal layers will be removed from blubber samples and their lipid content % of blubber will
be measured with Near-Infrared Spectroscopy using CA-HN (Joy World Pacific Co. Ltd).
Analytical procedure
Abundance estimation of whales
The standard methodology of line transect surveys (e.g. Branch and Butterworth, 2001) will be applied to estimate
abundance of common minke and sei whales in sub areas 7, 8, 9 and 11. Abundance estimation protocols aredescribed in Annexes 8 and 14.
Prey composition (W %) in each individual
In order to simplify the comparison of feeding indices, prey species will be divided as follow: copepods(Neocalanus cristatus, N. plumchrus, Calanus sp.), krill (Euphausia pacifica, E. similes, E. gibboides,
Thysanoessa gregaria, Nematoscelis difficilis), Japanese anchovy, Japanese sardine, Pacific saury, walleye
pollock, oceanic lightfishes (Vinciguerria nimbaria; Maurolicus japonicus), other squids (Japanese common
squid, minimal armhook squid (Berryteuthis anonychus)), and other fishes (Japanese pomfret (Brama japonica),
Atka mackerel (Pleurogrammus monopterygius), Salmonidae).
The relative prey composition (%) by weight of each prey species (RW) in each individual will be calculated asfollows:
RW = (Wi / Wall) × 100
Wi = the weight of contents containing prey group i.

171Wall = the total weight of contents analyzed.
Feeding period estimation
To consider the uncertainties such as feeding period in the calculation of prey consumption, stable isotopes
analyses from the edge of baleen plates will also be conducted under the NEWREP-NP program to estimate timespent by common minke and sei whales in the feeding grounds. The analyses will be conducted based on Mitani
et al (2006). At the same time, the tagging and satellite tracking that records the position of whales for a long
period will be conducted for the common minke and sei whales to examine the migration patterns and duration ofstay in the western North Pacific. The tagging of sensor data logger (depth and acceleration) will be conducted
for the common minke and sei whales to examine daily feeding patters.
Feeding habits, estimation of daily and seasonal prey consumption
The amount of prey consumed by common minke and sei whales in each area and period will be estimated using
theoretical energy requirement calculations. The uncertainties associated with the relevant parameters will betreated by Monte Carlo simulations.
The daily prey consumption (Dkg) in each sexual maturity class will be estimated from the standard metabolic rate
(SMRkJ) and energy deposit according to the following equation:
Dkg =SMRkJ / (EKJ * AE)
Where Dkg is daily prey consumption (kg day-1), SMRkJ is the standard metabolic rate (kJ day-1), EkJ is the caloric
value of prey species (kJ kg-1), and AE is assimilation efficiency (%).The details of these items are described in
Tamura et al. (2016b, c). Nutritional condition will be used when serious depletion of prey environments or drasticchange in amount of prey are observed.
Spatial modelling
A hierarchical structure with two levels of Generalized Additive Models (GAMs) based spatial distribution models
will be considered: (1) daily prey consumption by common minke and sei whales and (2) relative abundance of
these species. The product of two levels of models are prey consumption by these species. For the second level,
Density Surface Modeling (DSM) (Miller et al., 2013) would be one of the options (see also Appendices 10 and
14). Environmental variables such as Sea surface temperature (SST), sea surface height anomaly (SSHa) and sea
surface chlorophyll-a concentration (Chl-a) will be used as covariates of these models. Data from ocean circulation
models such as FRA-ROMS would also be used as covariates. The models presented by Tamura et al. (2016d)
would be used as a template bearing in mind the comments from the panel of the final review of JARPNII (IWC,
2016).
Abundance of prey species and fisheries catch statistics
In the Sanriku region information on abundance and occurrence of prey species will be obtained from the Miyagi
Prefecture Fisheries Technology Institute. In Kushiro, Abashiri regions and offshore areas (sub areas 7, 8 and 9),
the information on abundance and occurrence of prey species will be obtained from Japan Fisheries Research and
Education Agency (FRA), Kushiro Fisheries Research Institute and Abashiri Fisheries Research Institute of the
Hokkaido Research Organization.
3. Distinctive features and expected outcome
The abundance estimates of common minke and sei whales will be used as an important input parameter for theestimation of prey composition and consumption by whales. It should be noted that the proponents will examine
stomach contents with the main aim to investigate the influence of environmental change on the whale stocks.
From this perspective, changes in the proportion of different prey items is important. Information on the amountof prey consumed is important for the spatial modelling approach to be used under this Secondary Objective. The
outcome of the NEWREP-NP could contribute more reality to the management and stock assessment of common
minke and sei whales. The estimated abundance, prey composition, consumption and any observed nutritionalchange of whales will be reported to the IWC/SC and other scientific organization such as PICES. The obtained
data by the NEWREP-NP could contribute to not only management of common minke and sei whales but also to
the management of several commercial fish species such as sandlance, Japanese anchovy, Japanese sardine andPacific saury in the around of Japan.
The proponents will monitor spatial distribution, prey species compositions and body conditions of target whales
and they will investigate potential influential factors (e.g. available prey), if temporal changes (which could
ultimately be related to major changes) in whales are observed. Such monitoring and investigation will contributeto future in-depth assessment (IA) of whales as in the case of Antarctic minke whales

172

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Baker, A. de. C., Boden, B. P. and Brinton, E. 1990. A practical guide to the euphausiids of the world. Natural
History Museum Publications, London, 96 pp.
Branch, T.A. and Butterworth, D.S. 2001. Southern Hemisphere minke whales: standardised abundance estimatesfrom the 1978/79 to 1997/98 IDCR-SOWER surveys. J. Cetacean Res. Manage. 3(2): 143-74.
Brodskii, K. A. 1950. Calanoida of the far eastern seas and polar basin of the USSR. Opred. Faune SSSR, 35: 1442. [In Russian] (Transl: Israel Program for Scientific Translations, Jerusalem 1967).
Chihara, M. and Murano, M. (eds.) 1997. An illustrated guide to marine plankton in Japan. Tokai University
Press, Tokyo, Japan, 1574 pp.
Haug, T., Gjøsæter, H., Lindstrøm, U. and Nilssen, K. T. 1995. Diets and food availability for northeast Atlantic
minke whale Balaenoptera acutorostrata during summer 1992. ICES Journal of Marine Science 52: 77-86.
International Whaling Commission. 2012. Requirements and guidelines for conducting surveys and analyzing
data within the Revised Management Scheme. J. Cetacean Res. Manage. (Suppl.) 13: 507-19.
International Whaling Commission. 2016. Report of the Expert Panel of the final review on the western North
Pacific Japanese Special Permit programme (JARPN II). Paper SC/66b/Rep06 presented to IWC ScientificCommittee (unpublished). 96pp.
Kasamatsu, F. and Tanaka, S. 1992. Annual changes in prey species of minke whales taken off Japan 1948-87.
Nippon Suisan Gakkaishi. 58: 637-51.
King, J.R., 2005. Report of the study group on fisheries and ecosystem responses to recent regime shifts, PICES
Sci. Rep. North Pacific Marine Science Organization (PICES), Sidney. 162pp.
Konishi, K. 2016. Analyses of body condition in sei, Bryde’s and common minke whales in the western North
Pacific with JARPN and JARPN II dataset. Paper SC/F16/JR27 presented to the JARPNII special permit expert
panel review workshop, Tokyo, February 2016 (unpublished). 39pp.
Kubodera, T. and Furuhashi, M. 1987. Guide to the identification of lantern fishes and cephalopods in the stomach
contents. Appendix document of the report on the modeling of ecosystem in northern North Pacific. Fisheries
Agency of Japan, 65 pp. [In Japanese].
Masuda, H., Amaoka, K., Araga, C., Uyeno, T. and Yoshino, T. (eds.) 1988. The fishes of the Japanesearchipelago. Second edition. Tokai Univirsity Press, Tokyo, Japan, 378 pp.
Miller, D.L., Burt, M.L., Rexstad, E.A. and Thomas, L. 2013. Spatial models for distance sampling data: recent
developments and future directions. Methods in Ecology and Evolution 4: 1001-10.
Mitani, Y., Bando, T., Takai, N. and Sakamoto, W. 2006. Patterns of stable carbon and nitrogen isotopes in thebaleen of common minke whale Balaenoptera acutorostrata from the western North Pacific. Fish. Sci. 72: 69-76.
Morrow, J. E. 1979. Preliminary keys to otoliths of some adult fishes of the Gulf of Alaska, Bering Sea, andBeaufort Sea. NOAA Technical Report NMFS circular 420: 32 pp.
Ohe, F. 1984. Otoliths of the coastal fishes along Japanese Islands and of fishes of adjacent seas. Report of Bullten
The senior High School attached to Aichi University of Education 11: 183-220.
Okazaki, M., Masujima, M., Murase, H. and Morinaga, K. 2016a. Oceanographic conditions in the JARPNII
survey area from 2000 to 2013 using FRA-ROMS data. Paper SC/F16/JR5 presented to the JARPNII special
permit expert panel review workshop, Tokyo, February 2016 (unpublished). 25pp.

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Okazaki, M., Masujima, M., Murase, H. and Morinaga, K. 2016b. Oceanographic conditions in the survey areaof JARPNII coastal component off Kushiro in September from 2000 to 2013 using FRA-ROMS data. Paper
SC/F16/JR6 presented to the JARPNII special permit expert panel review workshop, Tokyo, February 2016
(unpublished).
Overland, J., Rodionov, S., Minobe, S. and Bond, N. 2008. North Pacific regime shifts: Definitions, issues andrecent transitions. Prog. Oceanogr. 77: 92-102.
Takasuka, A., Oozeki, Y. and Kubota, H. 2008. Multi-species regime shifts reflected in spawning temperature
optima of small pelagic fish in the western North Pacific. Mar. Ecol. Prog. Ser. 360: 211-7.
Tamura, T., Kishiro, T., Bando, T., Yasunaga, G., Murase, H., Maeda, H., Kitakado, T. and Pastene, L. 2016a.
Response to the ‘Report of the Expert Panel of the final review on the western North Pacific Japanese Special
Permit program (JARPNII)’. Paper SC/66b/SP1 presented to the IWC Scientific Committee, June 2016
(unpublished). 17pp.
Tamura, T., Kishiro, T., Yoshida, H., Konishi, K., Yasunaga, G., Bando, T., Saeki, M., Onodera, K., Mitsuhashi,M., Yamashita, Y., Funamoto, T. and Kato, H. 2016b. Updated prey consumption by common minke whales andinteraction with fisheries in coastal areas. Paper SC/F16/JR17 presented to the JARPNII special permit expert
panel review workshop, Tokyo, February 2016 (unpublished). 47pp.
Tamura, T., Konishi, K. and Isoda, T. 2016c. Updated estimation of prey consumption by common minke, Bryde’s
and sei whales in the western North Pacific. Paper SC/F16/JR15 presented to the JARPNII special permit expert
panel review workshop, Tokyo, February 2016 (unpublished). 28pp.
Tamura, T., Murase, H., Sasaki, H. and Kitakado, T. 2016d. Preliminary attempt of spatial estimation of prey
consumption by sei whales in the JARPNII survey area using data obtained from 2002 to 2013. Paper
SC/F16/JR16 presented to the JARPNII special permit expert panel review workshop, Tokyo, February 2016
(unpublished). 21pp.
Tian, Y., Ueno, Y., Suda, M. and Akamine, T. 2004. Decadal variability in the abundance of Pacific saury and its
response to climatic/oceanic regime shifts in the northwestern subtropical Pacific during the last half century. J.
Mar. Syst. 52: 235-57.
Wada, A., Onodera, K., Saeki, M. and Tamura, T. 2016. Estimation of prey species biomass in the Sanriku region
based on 2008 and 2009 JARPNII acoustic surveys. Paper SC/F16/JR19 presented to the JARPNII special permit
expert panel review workshop, Tokyo, February 2016 (unpublished). 12pp.
Yatsu, A., Nishida, H., Ishida, M., Tomosada, A., Kinoshita, T., and Wada, T. 2001. Trajectories of catch andstock abundance of dominant small pelagic fishes and common squid with some related environmental indicesaround Japan. PICES Sci. Rep., 18: 175-8.
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Figure 1. Flow chart with data, analyses and outputs of the research related to Ancillary Objective I.

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Annex 18
Ancillary Objective II
Examination of the effects of pollutants on whales
Field and laboratory work, and analytical procedure

Background and Objectives
In 1980, the Special Scientific Committee Working Group on Management Procedures identified that
“Management measures should take into account the effect on whale stocks of environmental changes due either
to natural causes or to human activities” (IWC, 1981) as one of principles for whale management.
In response to this suggestion, the JARPNII conducted environmental studies under one of its objectives(‘Monitoring environmental pollutants in cetaceans and the marine ecosystem’). It was observed that PCB levels
in common minke whales (Yasunaga et al., 2016a) and total mercury (Hg) levels in common minke, Bryde’s andsei whales (Yasunaga et al., 2016b) did not change during the research period, and were sufficiently below theirthresholds in other species. It was suggested that adverse effects of pollutants such as PCB and total Hg to thewhale health could be low in the area.
On the other hand, it was recognized that further work was required including, i) Examination of possible adverse
effects of pollutants with adjustment for confounding factors such as nutritional condition and ages, ii) Species
differences of sensitivity and response to pollutants, iii) Investigation of possible adverse effects of novelcompounds. These tasks are set as sub-objectives, in order to clarify the effects of pollutants on the stock levelsof marine mammals.
Research item (i): Examination of possible adverse effects of pollutants with adjustment for confounding factors
such as nutritional condition and ages
A major toxicological effect of PCBs, one of the major persistent organic pollutants (POPs), in marine mammals
is immunosuppression (Loseto and Ross, 2011). Immunosuppression might be induced in whales, even if their
PCBs levels are lower than the threshold of other animals. This is because, immunosuppression in marine
mammals could be induced by not only pollutants but also nutrient depletion, stress and aging (Alam and Pawelec,2012). Accordingly, it is necessary examine confounding factors, such as nutritional condition, stress and age inorder to clarify the possible adverse effects of pollutants to immune functions in marine mammals.
Research item (ii): Species differences of sensitivity and response to pollutants
There are inter species differences of genotype related to the sensitivities and response to organochlorine pollutant
levels (Curran et al., 2011), however, uncertainty factors have to be applied when extrapolating the differences in
response and sensitivity of experimental model animals to individual non-model species. Accordingly, it isnecessary to examine the factors underlying the susceptibility that cause species differences using OMICS
approach.
Research item (iii): Investigation of possible adverse effects of novel compounds
Polybrominated diphenylethers (PBDEs) are one of the flame retardants used in plastic materials for electric
devices and automobile interior articles etc. These are listed in the Stockholm Convention on POPs (UNEP, 2011),
because PBDEs are lipophilic and bioaccumulate in wildlife through the food chain in the marine environment(Burreau et al., 1999). In addition, plastic marine debris ingested by marine mammals are possibly one of thesources of flame retardants such as PBDEs (Derraik, 2002). A major effect of these compounds is neurologicaldysfunction related to thyroid hormone depletion in utero (Chevrier et al., 2010). Accordingly, PBDE levels inwhales and their sources including ingested marine debris will be investigated for understanding of their pathway
and the possible impact on whale stocks.

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Methods
Field work
Research items (i, ii & iii): Blubber, plasma and other tissues from common minke and sei whales will be collected
onboard the research base vessel. Blubber and other samples will be frozen and shipped to the laboratory andstored -20˚C until chemical analysis, and plasma samples for specific analyses such as immunoassay will be stored-80˚C until each analysis is conducted. Prey items and plastic marine debris ingested by whales will be collected
onboard the research base vessel. The tissues and samples will also be frozen and shipped to the laboratory andstored -20˚C until chemical analyses are conducted.
Laboratory and analytical works
Research item (i):Concentrations (expressed as lipid weight) of POPs (PCBs, DDTs, HCHs, HCB and CHLs) will be measured in
10 blubber samples from each of J- and O-stock minke and sei whales every year using gas chromatography-mass
spectrometry (Yasunaga et al., 2015), and biomarkers such as ethoxyresorufin-O-deethylase (EROD) activity(Fossi et al., 2007), total and free thyroxin in plasma (Schwacke et al., 2009), cortisol in plasma (Romano et al.,2004) and retinol in liver (Simms and Ross, 2000).
.
The changes of biomarkers relating immune functions of whales will be assessed by multiple regression in thecontext of other factors (R Development Core Team, 2006).
Research item (ii):
Changes at multi-ome levels through intracellular receptors will be measured to examine the disruption of
intracellular receptor signaling by chemical exposure in whales (Hirakawa et al., 2011).
Research item (iii):
Concentrations (expressed as lipid weight) of flame retardants such as PBDE will be measured in 10 blubbersamples of the same sei whales collected for item i) above, 10 prey items and 10 plastic marine debris samples
every year using the high-resolution mass spectrometry (Kajiwara et al., 2006), and materials contained in theplastic marine debris will be determined using the Fourier transform infrared spectroscopy.
Expected outcome and future plan
These studies could be helpful to predict the potential risk of infectious disease in each stock due to pollutants.
Pollutants and the other items measured, and the next themes of basic research will be re-examined every sixthyear based on progress and results from this study.
The proponents will collaborate with a wildlife immunotoxicologist from Ehime University (research item ii)
above).
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Kajiwara, N., Kamikawa, S., Ramu, K., Ueno, D., Yamada, T.K., Subramanian, A., Lam, P.K.S., Jefferson, T.A.,
Prudente, M., Chung, K.H. and Tanabe, S. 2006. Geographical distribution of polybrominated diphenyl ethers(PBDEs) and organochlorines in small cetaceans from Asian waters. Chemosphere 64:287-295.
Loseto, L.L. and Ross, P.S. 2011. Organic contaminants in marine mammals. In: W.N. Beyer and J.P. Meador(eds.) Environmental Contaminants in Biota. CRC Press, Florida, pp 349-376.
R Development Core Team 2006. R: A language and environment for statistical computing. R Foundation for
Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, URL http://www.R-project.org.
Romano, T.A., Keogh, M.J., Kelly, C., Feng, P., Berk, L., Schlundt, C.E., Carder, D.A. and Finneran, J.J. 2004.
Anthropogenic sound and marine mammal health: measures of the nervous and immune systems before and after
intense sound exposure. Can. J. Fish. Aquat. Sci. 61:1124-1134.
Schwacke, L., Hall, A., Townsend, F., Wells, R., Hansen, L., Hohn, A., Bossart, G., Fair, P. and Rowles, T. 2009.
Hematologic and serum biochemical reference intervals for free-ranging common bottlenose dolphins (Tursiops
truncatus) and variation in the distributions of clinicopathologic values related to geographic sampling site. Am.
J. Vet. Res. 70:973–985.
Simms, W. and Ross, P.S. 2000. Vitamin A physiology and its application as a biomarker of contaminant-related
toxicity in marine mammals: a review. Toxicol. Ind. Health 16:291-302.
UNEP, 2011. Draft revised guidance on the global monitoring plan for persistent organic pollutants,
UNEP/POPS/COP.5/INF/27, United Nation Environment Programme, UNEP Chemicals Geneva, Switzerland.
Wayland, M., Gilchrist, H.G., Marchant, T., Keating, J. and Smits, J.E. 2002. Immune Function, Stress Response,and Body Condition in Arctic-Breeding Common Eiders in Relation to Cadmium, Mercury, and Selenium
Concentrations. Environ. Res. 90(1):47-60.
Yasunaga, G., Fujise, Y., Zenitani, R., Tanabe, S. and Kato, H. 2015. Spatial and temporal variation of PCBs andorganochlorine pesticides in the Antarctic minke whales, Balaenoptera bonaerensis, in the period 1987-2005.
Chemosphere 126:11-17.
Yasunaga, G., Hakamada, T. and Fujise, Y. 2016a. Update of the Analyses on Temporal trend of PCB levels incommon minke whales from the western North Pacific for the period 2002-2014. Paper SC/66b/E/07 presented
to the IWC Scientific Committee, June 2016 (unpublished). 11pp.
Yasunaga, G., Hakamada, T. and Fujise, Y. 2016b. Update of the Analyses on Temporal trend of Total Hg levelsin three baleen whale species based on JARPN and JARPNII data for the period 1994-2014. Paper SC/66b/E/08
presented to the IWC Scientific Committee, June 2016 (unpublished). 18pp.

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Annex 19
Ancillary Objective III
Study on distribution and stock structure of large whales with particular emphasis on blue and North Pacificright whales
Protocol for biopsy sampling and photo identification
Biopsy sampling
Equipment
The Larsen systems will be used for biopsy sampling (Larsen, 1998). Biological samples (skin/blubber) will becollected by projectile dart which will be shot from sighting and sampling vessel, and the procedure below will
be followed.
Sampling procedure1) During any single encounter, no more than five biopsy sampling attempts per individual will be made.
2) The projectile biopsy sample will be collected from animals within approximately 5 to 30m of the bowof the vessel. When the vessel approaches to the whales, she must avoid rapid engine and directionchanges and follows a path convergent with the direction of travel of the whale. While it is possible tocollect samples at ranges of up to 50m - normally do not shoot at distances less than 10m. Care should
be taken to avoid the head region.
3) For large cetaceans, small samples (<1 gram) will be obtained from free-ranging individuals using a
biopsy dart with a stainless steel tip measuring approximately 4 cm in length with an external diameterof 9mm and is fitted with a 2.5 cm stop to ensure recoil and prevent deeper penetration (so that only
1.5cm of the tip is available to penetrate the animal).
4) During sampling, the biopsy tips are thoroughly cleaned and sterilized with bleach. Biological samples
may be collected from adults, juveniles, females with calves and calves. The same size biopsy dart would
be used for calves as for adults. No biological samples will be taken from newborn calves.
5) All collected samples will be frozen at -20°C until use for analyses.
Laboratory analyses of biopsy samples are similar to those described for minke and sei whales in Annex 7.
Photo-identification
Procedures are similar to those used in the IWC-POWER surveys.
Equipment
Digital single-lens reflex (SLR) cameras (e.g. 300mm lens, Canon Co., Ltd., Japan) will be the primary equipment
for this study. It should be shot as raw files (if the camera permits researcher can simultaneously also shoot finejpegs).
Procedure for blue whales







It is preferable to take photographs perpendicular to the whale.
As the identification pattern can be different on both sides of the animal, it is important to try andphotograph both sides, but priority should be given to the left hand side, i.e. that side should be attempted
first whenever possible.
If working with a group, try to concentrate on one whale before starting on another and use ‘marker
frames’ between animals in order to avoid ambiguities in analysing photographs. From the viewpoint of
the development of a visual key, it is particularly important to try to also obtain photographs from behind
the animal.
The aim is to photograph as much of the flanks as possible. It is important to try to avoid both glare
reflecting off the body and backlighting, both of which can result in useless (if artistic) pictures.
If the animal is one that shows its flukes on diving then try to photograph this, but only after you aresatisfied that the flanks have been adequately photographed.

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

In closing to the animals, it is important not to approach too fast nor change direction or speed frequently.
It has been most productive to follow a course almost parallel to the whale but converging slowly with
it.

Procedure for right whales






The key area for identification is the head (callosities and lip patches) and where possible from the top failing that both sides of the head should be photographed. If only one side is possible, it should be theleft hand side.
Head photographs should be taken as vertically as possible, i.e. from the barrel
Other distinguishing or unusual marks or scars should also be photographed, including the flukes offluking animals.
If working with a group, try to concentrate on one whale before starting on another and use ‘marker
frames’ between animals in order to avoid ambiguities in analysing photographs.
A similar approach and methods that are described for blue whales is recommended.

Satellite tracking
Satellite tracking experiments will be conducted as feasibility studies on an opportunistic basis. Technical detailsof the equipment are given in Annexes 9 and 15.
References
Larsen, F. 1998. Development of a biopsy system primarily for use on large cetaceans. Paper SC/50/O15 presented
to the IWC Scientific Committee, May 1998 (unpublished). 8pp

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Annex 20
List of collaborating and data providing research institutions

Research activities under the NEWREP-NP will be carried out by the Institute of Cetacean Research (ICR) in
collaboration and coordination with several research institutions. Furthermore relevant data will be acquired fromother research institutions and research programs. This annex provides a list of collaborating research institutions,and a list of institutions and research programs from where data will be obtained, by NEWREP-NP objectives.
Primary Objective I
Contribution to optimize the establishment of a sustainable catch limit for common minke whales in the coastal
waters of JapanSecondary Objective I (i): Investigate the spatial and temporal occurrence of J stock common minke
whales around Japan, by sex, age and reproductive status (Annex 7)a)Collaborating research institutions/projects-

Tokyo University of Marine Science and Technology (morphological characterization of J stock;
assignment analysis based on genetic data; estimates of J stock mixing proportion trend).
National Research Institute of Far Seas Fisheries (age determination based on earplug, genetic
characterization of J stock).
Azabu University (feasibility study on DNA methylation).
Riken Genesis Co. (feasibility study on DNA methylation).



Secondary Objective I (ii): Estimate the abundance of the J and O stocks in coastal waters of Japan(Annex 8)a)Collaborating research institutions/projects-

Tokyo University of Marine Science and Technology (estimate of whale abundance based on Line
Transect Method and spatial modelling, g(0) estimates; additional variance).
National Research Institute of Far Seas Fisheries (survey in IO mode; spatial modeling).

Secondary Objective I (iii): Verify that there is no structure in the O stock common minke whale in the
Pacific side of Japan (Annex 9)a)Collaborating research institutions/projects-

National Research Institute of Far Seas Fisheries (consultation on satellite tracking techniques).
Lkarts Norway (consultation on satellite tracking technique).



Secondary Objective I (iv): Improve RMP trials by incorporating age data in their conditioning (Annex
10)a)Collaborating research institutions/projects-

Tokyo University of Marine Science and Technology (SCAA).
National Research Institute of Far Seas Fisheries (age determination based on earplug, consultation
on satellite tracking techniques).
Azabu University (feasibility study on DNA methylation).
Riken Genesis Co. (feasibility study on DNA methylation).

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Primary Objective II
Contribution to the RMP/IST for North Pacific sei whaleSecondary Objective II (i): Abundance estimates for North Pacific sei whales taking of the accountadditional variance (Annex 13)a)Collaborating research institutions/projects-

Tokyo University of Marine Science and Technology (estimation of whale abundance based on Line
Transect Method and spatial modelling, additional variance).
National Research Institute of Far Seas Fisheries (survey in IO mode; spatial modeling).

-b) Research institutions/projects providing data and samples


IWC-POWER (sighting survey).

Secondary Objective II (ii): Estimation of biological and ecological parameters in North Pacific sei
whale for RMP Implementation (Annex 14)a)Collaborating research institutions/projects-

Tokyo University of Marine Science and Technology (SCAA).
National Research Institute of Far Seas Fisheries (age determination based on earplug).
Azabu University (feasibility study on DNA methylation).
Riken Genesis Co. (feasibility study on DNA methylation).

Secondary Objective II (iii): Study of the pattern of movement of whales of the ‘pelagic stock’ within thefeeding grounds and between feeding and breeding grounds (Annex 15)a)Collaborating research institutions/projects-

National Research Institute of Far Seas Fisheries (consultation on satellite tracking technique).
Lkarts Norway (consultation on satellite tracking technique).
Tokyo University of Marine Science and Technology (genetic analyses based on DAPC).

b) Research institutions/projects providing data and samples


IWC-POWER (biopsy sampling).

Secondary Objective II (iv): Specification of RMP ISTs for North Pacific sei whalesa)Collaborating research institutions/projects-

Tokyo University of Marine Science and Technology (RMP ISTs specifications).

Ancillary Objective I (Annex 17)a)Collaborating research institutions/projects-

National Research Institute of Far Seas Fisheries (spatial estimation of prey consumption;
consultation on satellite tracking technique).
Lkarts Norway (consultation on satellite tracking technique).
Hokkaido University (stable isotope analyses).
Miyagi Prefecture Fisheries Technology Institute (prey survey).

-b) Research institutions/projects providing data and samples-

National Research Institute of Fisheries Science (oceanographic data and oceanographic data
analyses based on FRA-ROM).

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-

Hokkaido National Fisheries Research Institute (information on fisheries).
Hokkaido Research Organization (information on fisheries).
Japan Chemical Analysis Center (stable isotope analyses).
Japan Food Research Laboratories (fatty acid analyses).

Ancillary Objective II (Annex 18)a)Collaborating research institutions/projects-

Ehime University (immunotoxicology study).

Ancillary Objective III (Annex 19)a)

Research institutions/projects providing data and samples-

IWC POWER (biopsy samples; photo-identification data.

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Annex 21
Research vessels
Research Base vessel
Vessel engaged in the biological and ecological surveys of whales sampled.
Nisshin Maru

Length overall: 129.58m
Molded breadth: 19.40m
Gross tonnage: 8,145GT
Engine power: 7,320PS
Speed: 14.30kt

Sighting/sampling vessels
Vessels engaged in whale sighting and sampling, and experiments.
Yushin Maru No.1

Yushin Maru No.3

Length overall: 69.61m
Molded breadth: 10.40m
Gross tonnage: 724GT
Engine power: 5,280PS
Speed: 12.00kt

Length overall: 69.61m
Molded breadth: 10.80m
Gross tonnage: 742GT
Engine power: 5,280PS
Speed: 12.00kt

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Dedicated sighting vessel
Vessel engaged exclusively in whale sighting and experiments.
Yushin Maru No.2

Length overall: 69.61m
Molded breadth: 10.80m
Gross tonnage: 747GT
Engine power: 5,280PS
Speed: 12.00kt

Sighting/sampling vessels (Coastal component)
Sumitomo Maru No.51 (51S)

Length overall: 21.31m
Molded breadth: 4.45m
Gross tonnage: 30.00GT
Engine power: 987PS
Speed: 10.00kt

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Taisho Maru No. 3 (3T)

Length overall: 20.25m
Molded breadth: 4.24m
Gross tonnage: 19.00GT
Engine power: 1,210PS
Speed: 13.00kt

Koei Maru No.8 (8K)

Length overall: 19.96m
Molded breadth: 4.30m
Gross tonnage: 32.00GT
Engine power: 330PS
Speed: 10.00kt

Katsu Maru No.7 (7K)

Length overall: 19.97m
Molded breadth: 4.30m
Gross tonnage: 32.00GT
Engine power: 400PS
Speed: 11.00kt

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Seiwa Maru

Length overall: 15.10m
Molded breadth: 3.20m
Gross tonnage: 15.20GT
Engine power: 160PS
Speed: 11.00kt

Prey survey vessel (Coastal component)
Miyashio

Length overall: 44.50m
Molded breadth: 7.6m
Gross tonnage: 199GT
Speed: 13.0kt

Equipment* Echo sounder: EK60 (38kHz, 120kHz and 200kHz)* CTD* Water sampling gear (12L)* Trawl net (mouth area 7m2)

Potential dedicated sighting vessel (Offshore component)
Kaiyo Maru No. 7

Length overall: 60.02m
Molded breadth: 10.6m
Gross tonnage: 649GT
Engine power: 1,600PS
Speed: 12.50kt

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Annex 22
Protocol for participation of foreign scientists in field and analytical research under the NEWREP-NP
Field surveys
Participation of foreign scientists in the field surveys of NEWREP-NP will be welcomed, so long as they meetthe following qualifications established by the Government of Japan: i) costs for participation, travel expenses toand from the home ports, subsistence on board the research vessels and any other ancillary cost, will be coveredby the participant; ii) indemnification and insurance for any casualty or personal injury while on board the research
vessels, will be covered by the participant; iii) participation of those who are found to have intentionally sabotaged
the implementation of the research in the field shall be terminated.
PROTOCOL
Scientists interested in participating in field surveys of NEWREP-NP should:
1. Complete the application form below.
2. Send the application form electronically to the director of the Survey and Research Division of the Institute of
Cetacean Research (ICR) (tamura@cetacean.jp) at least five month before the start of the survey.
An ad-hoc team in ICR will examine applications and communicate its resolution to applicants at least threemonths before the start of the survey.
APPLICATION FORM
Family name:First name:Research institution, postal address and E-mail address:

Field expertise:
Explain briefly the reasons of why you want participate in the NEWREP-NP field survey:
Past field experience:

Indicate the field survey of your interest: Whale biological survey: Cetacean dedicated sighting survey: Whale’s prey survey: Oceanographic survey: Other (ex: satellite tracking:)
Medical check to see if you fit for long-period field surveys at sea : Y
Remarks:
Date:

Signature:

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N

If yes, attach certificate

Research collaboration
As in the case of JARPN and JARPNII, data obtained by NEWREP-NP will be shared with members of the IWC
SC in accordance with the IWC SC Data Availability Agreement (DAA) (IWC, 2004). Data and samples fromthe research will be available for other accredited scientists and research organizations in accordance with theprotocol for access to samples/data from the ICR (http://www.icrwhale.org/pdf/appendix2.pdf).
To facilitate the collaboration and analyses, databases will be created after each annual survey, which will specify
the kind of samples and data collected during the research activities, and the list will be posted on the ICR Home
Page.
PROTOCOL
Scientists interested in conducting a particular research based on data and/or samples collected by NEWREP-NP
should follow two steps:
1. Complete the application form below.
2. Send the application form electronically to the director of the Survey and Research Division of the Institute of
Cetacean Research (ICR) (tamura@cetacean.jp).
An ad-hoc team in ICR will examine research proposals and communicate its resolution to applicants within two
weeks after receiving the proposal.

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APPLICATION FORMRESEARCH PROPOSAL TO THE INSTITUTE OF CETACEAN RESEARCH

Title of the research
Principal Investigator
Institution andAddress of Principal
Investigator
Co-Investigators
Institutions andAddresses of CoInvestigators
Objective of theresearch and rationale
Data requested
Methods
Research plan andschedule
Output of the research(oralpresentations,publications)
Other remarks

Reference
International Whaling Commission. 2004. Report of the Data Availability Working Group. Annex T. J. Cetacean
Res. Manage. 6 (Suppl.): 406-408.

190