Appendix 1
Composition of baleen whale species in the JARPA researcharea
KOJI MATSUOKA, TAKASHI HAKAMADA AND SHIGETOSHI NISHIWAKIThe Institute of Cetacean Research, 4-5, Toyomi-cho, Chuo-ku, Tokyo 104-0055, Japan
Contact e-mail: matsuoka@cetacean.jp

ABSTRACTThe Japanese Whale Research Program under Special Permit in the Antarctic (JARPA) was designed
as a large-scaled and long-term monitoring program using line transect surveys. These have been
carried out in a consistent way during the Austral summer every other year in Areas IV and V sincethe 1987/88 season . The established sighting procedures have matched those of the IWC/ SOWER(Southern Ocean Whale and Ecosystem Research) cruises to the extent possible. The current
research area was set in the Antarctic Areas IIIE (35 oE-70oE), IV(70oE-130oE), V (130oE-170oW)
and VIW (170oW -145oW) in the waters south of 60 oS. Major cetacean species sighted in the
research areas were Antarctic minke (Balaenoptera bonaerensis), humpback (Megaptera
novaeangliae), fin (Balaenoptera physalus) and blue (Balaenoptera musculus intermedia) whales.
Current abundances were estimated using the most recent stock boundaries of these species. A“shift in baleen whale dominance” from Antarctic minke to humpback whales, was observed in Area
IV since 1997/98 season. In 1989/90 season, biomass of Antarctic minke was higher (382,000 tons)
than humpback whales (128,000 tons), and after 15 years, the biomass of humpback (841,000 tons)
increased twice than that of Antarctic minke (335,000 tons). Habitat expansion of humpback and fin
whales were also observed in Area IV from the first half (1989/90-1996/97) to the later half ofsurveys (1997/98 -2002/04). At this morment, abundance of Antarctic minke whales is stable in Area
IV, however, increases of abundance and habitat expansion of humpback and fin whales, may cause
competition with Antarctic minke whales. Yearly change in some biological fetures also suggest this“Event”. Further monitoring survey will be required for the baleen whale management in the
Antarctic Ocean.
1. DISTRIBUTION AND ABUNDANCE OF MAJOR BALEEN WHALES IN THE JARPARESEARCH AREA
The Japanese Whale Research Program under Special Permit in the Antarctic (JARPA) was designed as alarge-scaled and long-term monitoring program using line transect surveys. It has been carried out in aconsistent way during the Austral summer seasons every other year in IWC Areas IV and V since the
1987/88 season. The sighting procedures have been established to match the IWC/IDCR (International
Decade for Cetacean Research) and SOWER (Southern Ocean Whale and Ecosystem Research) cruises tothe extent possible. The trackline was designed in order to cover the strata uniformly and all the schoolssighted were recorded (Figure 1). Sighting surveys were conducted only conditions when wind speed was 20
knot or less for the northern strata and 25 knot or less in the southern strata. The current research area was set
in the Antarctic Areas IIIE (35 oE-70oE), IV(70oE-130oE), V (130oE-170oW) and VIW (170oW -145oW) in
the waters south of 60 oS. Major cetacean species sighted in the research Areas were Antarctic minke(Balaenoptera bonaerensis), humpback (Megaptera novaeangliae), fin (Balaenoptera physalus) and blue
(Balaenoptera musculus intermedia) whales (Nishiwaki et al,, 2003, Ishikawa et al,, 2004).
Abundance of Antarctic minke whale was estimated by Hakamada et al, (2005). Abundance of other baleen
whales were estimated by Matsuoka et al, (2005). Table 1 summarize current abundance estimates ofAntarctic minke (Eastern Indian Ocean Stock (I-stock) & Western South Pacific Stock (P-stock)), humpback,(Western Australian Stock (D-stock) & Eastern Australian Stock (E-stock), fin (Indian Ocean Stock (IO–
stock) & Western South Pacific Stock (WP-stock)) and blue whales based on the most recent stockboundaries of these species (Pastene et al,, 2005a and 2005b) using JARPA sighting survey data.

25

1.1. Antarctic minke whale
Antarctic minke whales were widely distributed in the northern and southern strata. They also tended to
distribute in the southern strata rather than northern strata. High density areas were observed in the southern
strata, specially the Ross Sea and Prydz Bay (Figure 2). Abundance of this species between 1989/90 and
2003/04 were estimated by Hakamada et al, (2005).
I-stock: 35oE-165oE
For the Indian Ocean stock (I-stock), because abundance estimates in Area IIIE are available only from the
JARPA survey in the 1995/96 season, abundance of this stock were estimated from the 1995/96 to the
2003/04 seasons. Table 2 and Figure 3 show abundance estimates of this stock in the research area (south of
60oS, 35oE-165oE). Abundance of this stock was stable between the 1995/96 and 2003/04 seasons.
P-stock: 165oE-145oW
For the Western South Pacific Stock (P-stock), because abundance estimates in Area VIW are available only
from the JARPA survey in the 1996/97 season, abundance of this stock were estimated from the 1996/97 to
the 2002/03 seasons. Table 2 and Figure 3 show abundance estimates of this stock in the research area (southof 60oS, 165oE-145oW).
1.2. Humpback whales
D-stock: 70oE-130oE
Humpback whales were concentrated between 90oand 120oE in northern and southern strata, and were
widely dispersed in the other parts of Area IV (Figure 4). Comparison of the distribution pattern between thefirst half of JARPA (1989/90-1996/97) and the later half (1997/98-2003/04) shows an increase in the numberof sightings in Area IV between 90oand 120oE (Figure 5), and that the concentration area of this species was
expanded to the southern and eastern strata year by year. Average latitude of the concentration area was
60o30’S in the first half, and 62o30’S in the later half of the JARPA (Figure 6).
The catch of humpback whales in the Antarctic was banned in 1963. Bannister (1994) reported that a total
population size of some 3,000 whales off Shark Bay, Western Australia, based on the results fromcomparison of the 1991 sighting rate with those from a 1963 commercial aerial spotter. In the late 1990’s,
analyses from coastal aerial surveys, 8,000-14,000 whales was estimated (rate of increase was 10.2±4.6%)
off Western Australia (Bannister and Hedley, 2001). Abundance estimate using IWC/SOWER data for thepart of Area IV (80 o -130 o E) in 1998/99 was estimated as 17,300 (CV=0.17) whales (Matsuoka et al,.,2003). At the start of JARPA, abundance of this stock was only 5,200 (1989/90 season), but current
abundance estimates of this stock was estimated as 31,800 (CV=0.11) in 2003/04 season (Table3 and Figure7). Recent abundance (average of 2001/02 and 2003/04) was 32,380 (CV=0.08). Increasing rate of this stockin the feeding ground (south of 60 o S) was estimated as 16.2±6.4%,because recent habitat extension of thisstock may cause this high estimate (Matsuoka et al,., 2005). As a results of stock assessment, near complete
recoveries to pristine levels are suggested in some 10 years for this stock (Johnston and Butterworth, 2005).
E-stock: 130oE-170oW
For the E-stock in Area V, they tended to distributed in the eastern part of Area V except the Ross sea. They
were distributed clearly along the Pacific Antarctic ridge where the southern boundary of the Antarctic
Circumpolar Current was observed. Table3 shows abundance estimates for this stock. Yearly fluctuations ofabundance estimation were observed for this stock.
There are several reports on abundance estimates of humpback whales in the late 1990’s off Eastern
Australia and Antarctic Area V. Estimate of East Australian humpback whales using land-based survey was
3,185 (s.e.=208) whales in the 1996 (Brown et al,., 1997). The estimate in the Antarctic Area V in 1991/92
season using IWC/IDCR data was 2,104 whales (CV=0.52) (Brown and Butterworth, 1999). Recent JARPA
estimates (average of 2000/01 and 2002/03) are 3,728 (CV=0.15) whales which are consistent as a rate ofincreasing has been assumed to be some 10 %. As a results of stock assessment, near complete recoveries topristine levels are suggested in some 15-20 years for the currently more depleted E-stock (Johnston andButterworth, 2005).

26

1.3. Fin whales
Estimate of abundance of this species in the whole Antarctic waters based on IWC/IDCR and Japanese
Scouting Vessels (JSV) was 18,000 (CV=0.47) in the south of 30oS (Butterworth et al,., 1994). Recent
estimates of this species in the whole area south of 60oS based on the IWC/IDCR and SOWER data were
2,100 (1978/79-1983/84, CV=0.36), 2,100 (1985/86-1990/91, CV=0.45) and 5,500 (1991/92-1997/98: notcompleted, CV=0.53) in the first, second and third circumpolar series, respectively (Branch and Butterworth,2001). In half of Antarctic area (south of 60oS, 35oE -145oW), 15,000 (CV=0.20) whales was estimated using
JARPA 1989/90- 2003/04 data, and the first estimates in this area shows significant increase (Matsuoka et al,,2005). Figure 8 shows the distribution pattern of this species by the JSV data.
IO-stock: 35oE-130oE
Indian Ocean Stock (IO-stock) of this species were widely distributed in the Areas IIIE and IV, and theytended to be distributed in Area IIIE rather than Area IV. They were widely dispersed and also rarely foundwithin the Prydz Bay (Figure 9). Comparison of the distribution pattern during the first half of JARPA(1989/90-1995/96) and the later half (1996/97-2003/04), shows that fin whales appeared more frequently inthe western part of Area IV in recent years (Figure 10).
No abundance estimation of this stock from sightings data was reported. Recent abundance (average of
2001/02 and 2003/04) was estimated as 8,621 (CV=0.19) for south of 60oS (Table 4 and Figure 11). Because
they are mainly distributed in the area north of 60oS (Kasamatsu, 1993), large yearly fluctuation in the area
south of 60oS in Areas IIIE and IV might be attributable to such distribution. For abundance estimation of thewhole IO-stock, it is possible to extrapolate current abundance to the north of 60oS using Japanese scouting
vessel (JSV) data. The abundance in January and February with consideration of seasonal distributionchanges of this species were estimated to be 31,000 whales (CV=0.26) for this stock (south of 40oS, 35oE130oE), from the results of the JARPA-2003/04 data.
WP-stock : 130oE-145oW
For the WP-stock of this species in the area south of 60oS, recent abundance (average of 2000/01 and2002/03) was estimated 4,691 (CV=0.17) (Table 4 and Figure 11).
For the whole Western Pacific Stock abundance estimation, it is possible to extrapolate current abundance tothe north of 60°S using Japanese scouting vessel (JSV) data (Miyashita et al,, 1995), because this species
also distributed in areas more north of 60°S. The abundance in January and February with consideration ofseasonal distribution changes of this species were estimated to be 16,000 whales (CV=0.29) for this stock(south of 40°S, 130°E-145°W), from the results of the JARPA-2002/03 data.
1.4. Blue whales (35oE-145oW)
There is no stock information of blue whales in the JARPA research area. Initially, there were as many as
200,000 blue whales in the whole Antarctic as calculated by a logistic model, but their number was greatly
reduced by over-hunting, and their take was banned in 1964. After forty years, however, they still small
number less than 2,000 (Branch et al,, 2004).
In the JARPA research area, blue whales were rarely encountered by the surveys though they were widelydistributed in the research area. They were usually found in Area IIIE and Area VE (Figure 13). In Area IV,
the number of sightings of this species increased in the later half JARPA (Figure 14). Abundance of thisspecies (south of 60oS, 35oE-145oW) was 900 (CI: 500-1,600) in 1999/2000 + 2000/01 seasons and 500
whales (CI: 300-1,000) in 2001/02 + 2002/03 seasons (Table 5). They still number less than 1,000 (biomass:less than 8,000 tons) in the JARPA research area. Also, the number of survey years is still too short to detect
any precise yearly trend. Further surveys are necessary for improving the precision of estimates of the annual
rate of increase in the feeding ground.
A “SHIFT IN BALEEN WHALE DOMINANCE” FROM ANTARCTIC MINKE TO HUMPBACKWHALES IN AREA IV
Biomass of Antarctic minke, humpback, fin and blue whales in Area IV are shown in Figure 15. A “Shift inbaleen whale dominance” from Antarctic minke to humpback whales was observed in this Area since
1997/98 season. In 1989/90 season, biomass of Antarctic minke was higher (382,000 tons) than humpback
whales (128,000 ton), and after 15 years in 2003/04 season, biomass of humpback (841,000 tons) was twice
than Antarctic minke (335,000 tons). Increase of fin whale was observed in Areas IIIE and IV. In 1989/90
season, biomass of fin was 5,000 tons, and after 15 years in 2003/04 season, biomass of fin was 67,000 tons27

as over 10 times (20 % of Antarctic minke biomass). Abundance of Antarctic minke whales is stable in
Areas IV and V, however, the decrease in blubber thickness in Area IV was observed (Konishi and Tamura,2005), and the decreasing pattern in stomach content weights of matured minke whales was also observed in
Area IV since 1987/88 season using JARPA biological data (Tamura and Konishi, 2005). It is also
reasonable to support a view that increase and habitat expansion of humpback and fin whales in Area IV,
may cause competition with Antarctic minke. Further monitoring survey was required in order tounderstanding Antarctic ecosystem and for the baleen whale management in the Antarctic Ocean.
3. MONITORING WHALE POPULATIONIn the Antarctic Ocean, catch of southern right, humpback, blue, fin and sei whales was prohibited in 1932,
1963, 1964, 1976 and 1978, respectively. Seventy years passed already since southern right whale has beenprotected, and more than 40 years have passed since humpback whale and blue whale have been protected.
In coastal waters of south America, South Africa and east and west coast of Australia, significant recovery ofsouthern right whale and humpback whales are reported recently in these breeding areas. On the other hand,
the information on the present status of pelagic species, such as blue, fin and sei whales were limited. The
IWC/IDCR-SOWER cruises, however not sufficient enough for the monitoring of ecosystem, as survey
covers the same area once in every over 6 years. In this situation, JARPA have been monitoring for baleen
whale species population by the large-scaled and long-term line transect survey for over 15 years in Areas IV
and V. The number of survey years is still too short to detect precise yearly trend for whales population.
Further monitoring survey was required for the baleen whale management in the Antarctic Ocean.
REFERENCES
Bannister, J. L., 1994. Continued increase in humpback whales off western Australia. Rep. Int. Whal.
Commn 44: 309- 310.
Bannister, J. L. and Hedley, S. L. 2001. Southern hemisphere Group IV humpback whales: their status fromrecent aerial survey. Mem. Qld. Mus. 47(2):587-598.
Branch, T. A., and Butterworth, D., S., 2001. Estimates of abundance south of 60oS for cetacean species
sighted frequently on the 1978/79 to 1997/98 IWC/IDCR-SOWER sighting surveys. J. Cetacean. Res.
Manage. 3(3):251-270.
Branch, T.A., Matsuoka, K. and Miyashita, T. , 2004. Evidence for increases in Antarctic blue whales basedon bayesian modelling. MARINE MAMMAL SCIENCE 20 (4): 726-754.
Brown, R. M. Field, M., S., Clarke, E., D., Butterworth, D. S. and Bryden, M., M., 1997. Estimates ofabundance and rate of increase for east Australian humpback whales from the 1996 land-bases survey at
Point Lookout, North Stradbroke Island, Queensland. Paper SC/49/SH35 submitted to the IWC ScientificCommittee, May 1997 (unpublished). 15pp.
Brown, R. M. and Butterworth, D. S., 1999. Estimates of abundance for Southern Hemisphere humpback andblue whales from the IWC/IDCR-SOWER sighting survey cruises. Paper SC/51/CAWS35 submitted to the
IWC Scientific Committee, May 1999 (unpublished).
Butterworth, D., S. Borchers, S., Chalis, J. B., Decker, De. and Kasamatsu, F., 1994. Estimates of abundance
for southern hemisphere blue, fin, sei, humpback, sperm, killer and pilot whales from the 1978/79 to
1990/91 IWC/IDCR sighting survey cruise, with extrapolation to the area south of 30 S for the first fivespecies based on Japanese scouting vessel data. Paper SC/46/SH24 submitted to the IWC ScientificCommittee, 1994 (unpublished).129pp.
Hakamada, T., Matsuoka, K. and Nishiwaki, S., 2005. An update of Antarctic minke whales abundance
estimate based on JARPA data including a comparison to IDCR/SOWER estimates. Paper JA/J05/JR 4
presented to the JARPA Review meeting, January 2005.
Ishikawa, H., Otani, S., Kiwada, H., Isoda, T. Tohyama, D., Honjo, K., Hasegawa, A., Terao, T., Kushimoto,T., Ohshima, T., Sugiyama, K., Sasaki, T., Itoh, S., Takamatsu, T. and Yoshida, T., 2004. Cruise Report of
the Japanese Whale Research Program under Special Permit in the Antarctic (JARPA) Area IV and EasternPart of Area III in 2003/2004. Paper SC/56/O12 presented to the IWC Scientific Committee, (unpublished).
18pp.

28

Johnston, S.J. and Butterworth, D., 2005. Assessment of the west and east Australian breeding populations ofsouthern Hemisphere humpback whales using a model that allows for mixing on the feeding grounds andtaking account of the most recent abundance estimates from JARPA. Paper JA/J05/JR19 presented to the
JARPA Review meeting, January 2005.
Kasamatsu, F. 1993. Studies on distribution, migration and abundance of cetacean populations occurring in
the Antarctic waters. PhD thesis, University of Tokyo (in Japanese).
Konishi, K. and Tamura, T., 2005. Yearly trend of blubber thickness in the Antarctic minke whale in Areas
IV and V. Paper JA/J05/JR 9 presented to the JARPA Review meeting, January 2005.
Matsuoka, K., Hakamada, T., Murase, H. and Nishiwaki, S., 2003. Current distribution, abundance anddensity trend of humpback whales in the Antarctic Areas IV and V. Paper SC/55/SH10 submitted to the
IWC Scientific Committee, 2003 (unpublished). 15pp.
Matsuoka, K., Hakamada, T. and Nishiwaki, S., 2005. Distribution and abundance of humpback, fin and blue
whales in the Antarctic Areas IIIE, IV, V and VIW. Paper JA/J05/JR 10 presented to the JARPA Review
meeting, January 2005.
Miyashita, T., Kato, H. and Kasuya, T., 1995. Worldwide Map of Cetacean Distribution based on Japanese
Sighting Data (Volume 1).pp43-56.
Nishiwaki, S., Tohyama, D., Mogoe, T., Murase, H., Yasunaga, G., Mori, M., Yoshida, T., Fukutome, K.,
Machida, S., Ogawa, R., Oka, R., Ito, S., Konagai, T., Isoda, T., Mori, Y, Iwayama, H. and Horii, N., 2003.
Cruise report of the Japanese Whale Research Program under Special Permit in the Antarctic (JARPA)
Area V and Western Part of Area VI in 2002/2003. Paper SC/55/O6 presented to the IWC ScientificCommittee, (unpublished). 20pp.
Nishiwaki, S., Ishikawa, H. and Fujise, Y., 2005. Review of general methodology and survey procedure
under the JARPA. Paper JA/J05/PJR1 presented to the JARPA Review meeting, January 2005.
Pastene, L., A., 2005a. A new interpretation of the stock identity in the Antarctic minke whale based on
analyses of genetics and non-genetics markers. Paper JA/J05/PJR3 presented to the JARPA Review
meeting, January 2005.
Pastene, L., A., 2005b. Genetic analyses on stock identification in the Antarctic humpback and fin whales
based on samples collected under the JARPA. Paper JA/J05/JR16 presented to the JARPA Review meeting,January 2005.
Tamura, T. and Konishi, K., 2005. Feeding habits and prey consumption of Antarctic minke whales, in
JARPA research area. Paper JA/J05/JR8 presented to the JARPA Review meeting, January 2005.

29

Table 1. Recent abundance estimates (P) of Antarctic minke whale, humpback, fin and blue whales for each stock using
JARPA 2002/03 and 2003/04 data (south of 60oS). For humpback and fin whales, average of latest two seaosns
abundance were used. The g (0) is assumed to be 1. Avarage weights used for the biomass, were 7, 26.5, 48 and,83 tons for Antarctic minke, humpback, fin and blue whales, respectively.

Species
Antarctic minke (I-stock)
Antarctic minke (P-stock)
Humpback (D-stock)
Humpback (E-stock)
Fin (IO-stock)
Fin (WP-stock)Bluelongitude
35E-165E
165E-145W
70E-130E
130E-170W
35E-130E
130E-145W
35E-145WP
CV Biomass(ton) Ref.
129,000
903,0001(0.25)
95,000665,0001(0.17)
32,400858,600
2(0.08)
3,700
98,0502(0.15)
8,600
412,8002(0.19)
4,700
225,6002(0.17)
500
41,5002(0.29)
Ref. 1: Hakamada et al., 2005.
2: Matsuoka et al., 2005.

Table 2. Abundance estimates (P) of Antarctic minke whale (I-stock and P-stock) between 1995/96 and 2003/04
seasons (south of 60oS). The g (0) is assumed to be 1 (Hakamada et al,, 2005). Avarage weight of this species
was 7 tons for the biomass.
I-stock
Season1995/96
1997/98
1999/2000
2001/02
2003/04

P-stock
P
82,975
124,301
128,110228,349
128,695

CV
0.165
0.187
0.227
0.142
0.248

Season1996/97
1998/99
2000/01
2002/03
2004/05

Biomass
580,825
870,107896,770
1,598,444
900,864

P
156,323
82,489179,417
95,116
-

CV
0.267
0.219
0.197
0.168
-

Biomass
1,094,261
577,423
1,255,919
665,812-

Table 3. Abundance estimates (P) of humpback whale for the D-stock and E-stock (both south of 60oS), between
1989/90 and 2003/04 (Matsuoka et al,, 2005). Avarage weight of this species was 26.5 tons for the biomass.
D-stock

Season1989/90
1991/92
1993/94
1995/96
1997/98
1999/2000
2001/02
2003/04

E-stock

P
5,230
5,350
2,740
8,850
10,874
16,21133,01031,750

CV
0.301
0.190
0.154
0.142
0.166
0.146
0.112
0.114

Season1990/91
1992/93
1994/95
1996/97
1998/99
2000/01
2002/03
2004/05

Biomass
138,605
141,775
72,615234,529
288,168
429,588874,758
841,382

30

P
1,354
3,837
3,567
1,543
8,301
4,720
2,735
-

CV
0.196
0.633
0.306
0.281
0.308
0.217
0.159
-

Biomass
35,891
101,675
94,53840,897219,973
125,068
72,481-

Table 4. Abundance estimates (P) of fin whale (south of 60oS) for the Indian Ocean stock (IO-stock)and Western South
Pacific stock (WP-stock), between 1989/90 and 2003/04 (Matsuoka et al,, 2005). Avarage weight of thisspecies was 48 tons for the biomass.
IO-stock

Season1995/96
1997/98
1999/2000
2001/02
2003/04

WP-stock

P
4,305
715
4,478
10,668
6,573

CV
0.197
0.307
0.221
0.255
0.256

Season1996/97
1998/99
2000/01
2002/03
2004/05

Biomass
206,629
34,326214,929
512,052
315,512

P
1,714
4,850
5,876
3,505
-

CV
0.252
0.354
0.211
0.287
-

Biomass
82,258
232,779
282,051
168,250-

Table 5. Abundance estimates (P) of blue whale (south of 60oS) between 1989/90 and 2003/04. Average weight of thisspecies was 83 tons for the biomass.
Blue
Seasons
1989/90 + 1990/91
1991/92+ 1992/93
1993/94+ 1994/95
1995/96+ 1996/97
1997/98+ 1998/99
1999/00+ 2000/01
2001/02+ 2002/03
2003/04+ 2004/05

Area
IIIE
P
293
248
352
80
540

CV
0.43
0.49
0.59
0.62
0.34

Area
IV
P
65
17
64
6
153
218
295
92

CV
0.48
1.08
0.62
0.94
0.61
0.40
0.44
0.72

Area
V
P
205
231
275
7
221
294
142
-

CV
1.01
0.67
0.64
0.75
2.07
0.49
0.53
-

Area
VIW
P
58
0
0
28
-

Total
CV
0.45
0.94
-

P
270
248
339
364
622
864
545
-

CV Biomass(ton)
0.78
22,4100.63
20,5840.53
28,1370.35
30,2120.78
51,6260.31
71,7120.29
45,235-

Fig. 1. Distribution of the searching efforts in JARPA1987/88-2003/04 seasons. Including middle latitudetransit sighting survey.

31

Fig. 2. Map of the Density Index (number of primary sightings of whales / 100 n.miles) of Antarctic
minke whales during JARPA -1987/88-2003/04 seasons by 1°×1°square.

Fig. 3. Abundance estimates (south of 60oS) of Antarctic minke whales (Left side: I-stock: 35oE-165oE, Right side: Pstock 165oE-145oW) in the research area.

Fig. 4. Map of the Density Index (number of primary sightings of whales / 100 n.miles) of humpback whales during
JARPA -1987/88-2003/04 seasons by 1°×1°square.

32

Fig. 5. Comparison of the distribution plot (Primary sightings) pattern between the first half of surveys (Left: 1989/90 1996/97) and late of surveys (Right: 1997/98-2003/04) by three vessels. Number of sightings were increased in the Area
IV between 90oand 120oE.

Fig. 6. Comparison of the latitudinal density Index (number of primary sightings of whales / 100 n.miles) between thefirst half of JARPA (Left: 1989/90-1996/97) and the later half of JARPA (Right: 1997/98-2003/04). Average ofthe latitude was 6030’S in the half of surveys, and was 6230’S in the second half of the surveys.

14,00045,000

Humpback whale
Areas IV
Stock D

40,000

Humpback whale
Areas V
Stock E

12,000Abundance estimation

Abundance estimation

35,00030,00025,00020,00015,00010,000
8,000
6,000
4,000

10,000
2,000

5,000
0

2004/05

2002/03

2000/01

1998/99

1996/97

1994/95

1992/93

1990/91

2003/04

2001/02

1999/2000

1997/98

1995/96

1993/94

1991/92

1989/900

Seasons

SeasonsFig. 7. Abundance estimates of humpback whales (south of 60oS) between 1989/90 and 2003/2004 seasons (over 15
years) in relation to Table 3. Vertical lines show standard errors. Left side; D-stock, Right side; E-stock.

33

Fig. 8. The Japanese Scouting Vessel (JSV) data (sighting rate of 5°×5°square) for fin whales sighted in January during
1965/66 to1987/88 (Miyashita et al,, 1995).

Fig. 9. Map of the Density Index (number of primary sightings of whales / 100 n.miles ) of fin whales during JARPA 1987/88-2003/04 seasons by 1°×1°square.

Fig. 10. Comparison of the distribution plot (Primary sightings) pattern between the first half of surveys (Left: 1989/90-1996/97) and late of surveys (Right: 1997/98-2003/04) by three vessels. Number of sightings were increased in the
Area IV between 70oand 100oE.

34

Abundance estimation

15,000

Fin whale
Pacific ocean stock(South of 60S, 130E-145W)
10,0005,000

02004/05

2002/03

2000/01

1998/99

1996/97

SeasonsFig. 11. Abundance estimates of fin whales (Indian Ocean stock: south of 60oS, 35oE-130oE) between 1989/90 and
2003/2004 seasons (over 15 years) in relation to Table 4. Vertical lines show standard errors.

Fig. 12. The Japanese Scouting Vessel (JSV) data (sighting rate of 5°×5°square) for blue whales sighted in February
during 1965/66 to1987/88 (Miyashita et al,, 1995).

Fig. 13. Map of the Density Index (number of primary sightings of whales / 100 n.miles) of fin whales during JARPA 1987/88-2003/04 seasons by 1°×1°square.

35

Fig. 14. Comparison of the distribution plot (Primary sightings) pattern for blue whales between the first half of surveys(Left: 1989/90 -1996/97) and late of surveys (Right: 1997/98-2003/04) by three vessels. Number of sightings wereincreased in the Area IV.

Area IV

Biomass [ton]2,000,000
1,800,000

Blue

1,600,000

Fin

1,400,000

Humpback

1,200,000

Minke

1,000,000
800,000
600,000
400,000
200,0000
1989/90

1991/92

1993/94

1995/96

1997/98

1999/00

2001/02

2003/04

SeasonsFig. 15. Biomass of Antarctic minke, humpback, fin and blue whales in Area IV (south of 60oS) surveyed during
January to February, between 1989/90 and 2003/2004 seasons (over 15 years). Abundance of Antarctic minke were
estimated by Hakamada et al,, (2005). A “shift in baleen whale dominance” from Antarctic minke to humpback whales
was observed since 1997/98 season (arrows).

36

Appendix 2
What has happened to the Antarctic minke whale stocks?
A interprepation of results from JARPA --YOSHIHIRO FUJISE, HIROSHI HATANAKA AND SEIJI OHSUMIThe Institute of Cetacean Research,4-5, Toyomi-cho, Chuo-ku, Tokyo 104-0055, JAPAN.
Contact e-mail: fujise@cetacean.jp

ABSTRACT
Historical changes in the Antarctic minke whale stocks were examined based on various results from
JARPA including age at sexual maturity, growth curve, blubber thickness, prey consumption, and
ADPT-VPA analysis of the stocks as well as results from research on mercury accumulation etc. It
has been assumed that feeding conditions of the minke whale improved with the removal of large
baleen whales such as the blue whale by commercial whaling, which promoted rapid growth andyounger age at sexual maturity; however, around 1970, conditions gradually shifted unfavourably,
resulting in slower rates of change in the foregoing parameters. These changes were then arrested by
the 1980s to the 1990s. Reflecting these unfavourable changes, it was observed that blubber
thickness and stomach content weight were reduced, which indicated less prey consumption. There
was also a decrease in the accumulation of mercury resulting from less prey consumption. Also, thedistribution area of humpback and fin whales in the feeding season expanded southward in the
Antarctic from around 1990, suggesting further deterioration of feeding conditions for the Antarctic
minke whales.
KEYWORDS: ANTARCTIC MINKE WHALE; BLUE WHALE; FIN WHALE; HUMPBACK WHALE,
COMPETITION; LONG-TERM CHANGE; HEAVY METALS; AGE AT SEXUAL MATURITY;
PREGNANCY RATEINTRODUCTION
Abundance and biological parameters of Antarctic minke whales have greatly changed over the years, andsince the late 1970s the IWC/SC has spent considerable time discussing possible reasons and trying tounderstand this phenomenon (see IWC, 19xx).
Due to uncertainties related to the estimation of biological parameters, there was no agreement at that time
concerning the data necessary for stock management, including natural mortality rate. This resulted indifficulties in calculating the catch quota and was the primary reason for the moratorium on commercial
whaling. The Government of Japan, therefore, launched a whale research program under the Article VIII of
the International Convention for the Regulation of Whaling (ICRR), in the Antarctic in 1987/88, with theestimation of biological parameters necessary for the management of Antarctic minke whales as the firstobjective. The elucidation of the role of cetaceans in the Antarctic ecosystem was the secondary objective.
The program was called JARPA, and in 1994 and 1995, the elucidation of the effects of environmental
changes on cetaceans and, the Antarctic minke whale stock structure were added to the research objectives.
The JARPA program spanning over eighteen years will end in 2004/05. Research in various fields has been
conducted together with surveys and analyses related to the program objectives. Phenomena suggesting
qualitative and quantitative changes on the Antarctic minke whale stocks have been observed, some of whichhave been reported at the IWC/SC ( e.g. IWC, 1988).
This paper rearranges the results reflecting changes in the Antarctic minke whale stocks, examines what has
happened in these stocks, and predicts possible future changes.
MATERIALS AND METHOD
Examination of the changes in the Antarctic minke whale stocks since whaling began, is based on analysesof sexual maturity age and growth curve (Kato, 1987; Zenitani et al., 2005), blubber thickness (Ohsumi et al.,37

1997; Konishi and Tamura, 2005), and estimated prey consumption (Tamura and Konishi, 2005) using
samples from commercial whaling and JARPA, ADPT-VPA analysis of the stocks (Butterworth et al.,1999),and study of mercury accumulation in the whale body (Honda, 1985; Honda et al., 1987; Fujise et al., 1997;
Yasunaga and Fujise, 2005) and other reports.
Age at sexual maturity estimated by the transition phase of the growth layer in cetacean earplugs has beenused here.
Data for age at sexual maturity for fin and Antarctic minke whales used in this study are from Lockyer(1972) and Kato (1987), respectively. Apparent pregnancy rates for blue and fin whales are from Gambell(1972). Apparent pregnancy rate for humpback whales are from Bando et al. (2005) which were calculated
from the International Whaling Statistics.
RESULTS AND DISCUSSIONSCatch History and Biomass of Large Cetaceans in the Antarctic Ocean
Commercial whaling began in the Antarctic in 1904. Initially, whaling mainly targeted the blue whales that
had high commercial value and humpback whales that are slow swimmers. Later, the object of commercial
whaling gradually shifted to the fin, sei and Antarctic minke whales with reduction of the former target
whale stocks (Fig. 1).
Blue whales
In the 1911/12 season, more than 1,000 blue whales were taken. In 1928/29, the yearly catch exceeded
10,000, and in the 1930/31 season, 29,410 whales were taken as the largest catch on record. Annual catches
continued in the tens of thousands until the 1939/40 season. It temporarily decreased during World War II,
but recorded 9,192 in the 1946/47 hunting season, then declined rapidly (Fig. 1). The take of blue whales
was banned in 1964. Total catch amounted to 331,644 whales. In terms of biomass, this means that amaximum of 2,941,000 tons in a year, and an average of 526,408 tons per year were removed from thestocks, calculated with an average body weight of 100 tons (Fig. 2).
Fin whales
Fin whales were also hunted from the initial period. More than 10,000 were taken in the 1929/30 season,and in 1937/38, more than 20,000, exceeding the catch of blue whales, when the fin became the major targetof commercial whaling. As with blue whales, catches temporarily decreased during World War II, but
recovered when whaling was resumed after the end of the War, and in the 1951/52 season it again exceeded
20,000. Annual catches continued in the tens of thousands until the 1963/64 season (Fig. 1). The largest
catch on record was made in the 1960/61 season, when 28,761 whales were taken. Total catches came to691,890 until the take of fin whales was banned in 1976. In terms of biomass, this means that a maximum of
1,581,855 tons in a year, and an average of 528,527 tons per year were removed from the stocks, calculatedwith an average body weight of 55 tons (Fig. 2).
Sei whales
There is a record of the take of sei whales in 1905/06, but full-scale hunting began in the 1957/58 season.
Since then annual catches increased to a peak of 20, 380 in the 1964/65 season and decreased rapidly afterthat (Fig. 1). Total catch till 1977/78 was 149,594 or, an average of 2,301 whales taken annually. In termsof biomass, this means that a total of 2,917,083 tons, a maximum of 397,410 tons in a year, and an averageof 44,878 tons per year were removed from the stocks, calculated with an average body weight of 19.5 tons
(Fig. 2).
Antarctic minke whales
The take of Antarctic minke whales has been recorded in 1951/52, but it was in the 1971/72 season that fullscale whaling for them began. About 6,000 whales were taken annually from the 1972/73 to the 1986/87
season, when commercial whaling was suspended. Since then, 330 or less have been taken under the special
permit of the Japanese Government up till 1994/95, and 440 or less till 2003/04 (Fig. 1). The largest catchon record was made in the 1976/77 season, when 7,900 were taken. Total catch came to 97,810 whales until
the 1986/87 season, when commercial whaling was suspended or, an average of 2,877 whales taken annually(for reference, total catch is 104,165 and yearly average 2,042 whales if those taken under special permit areincluded). In terms of biomass, this means that a total of 723,794 tons, a maximum of 58,460 tons in a year,38and an average of 21,288 tons per year were removed from the stocks, calculated with an average bodyweight of 7.4 tons (for reference, total biomass is 770,821 tons, and annual average 15,114 if those taken
under special permit are included) (Fig. 2).
Humpback whales
Humpback whales were taken as the major target species from the 1904/05 season, when commercial
whaling began in the Antarctic Ocean, since they were easy to hunt. Their status as the major target
continued until the 1913/14 season. In the 1910/11 season, more than 8,000 whales were taken, but after the1913/14 season, the target shifted to blue and fin whales, and catch gradually decreased until the 1916/17
season, after which it declined to 1,000 or less. From the 1934/35 to 1940/41, and from the 1949/50 to
1959/60 seasons, 1,000 to 2,000 whales were taken, but the take of humpback whales was banned in 1963
(Fig. 1). The largest catch on record was made in the 1936/37 season, when 4,477 whales were taken. Total
catch came to 68,294 or, an annual average of 1,102. In terms of biomass, this means that a total of
2,117,114 tons and an average of 33,605 tons per year were removed from the stock, calculated with anaverage body weight of 31 tons (Fig. 2).
Until around 1970 while fin whales were being hunted, about 2 million tons of whales had been removed
from the stocks. Krill consumed by the whales would have amounted to 60,000 tons per day, assuming that
consumption is 3% of body weight of whales. This all became a surplus since whales were removed by thehunts. If we assume that the blue, fin, humpback and other large whales stayed in the Antarctic Ocean for
one hundred days, as much as 3 million tons of krill would have been left over as surplus every year.
Age at sexual maturity
Age at sexual maturity of the fin and Antarctic minke whales is discussed here since biological data for these
species are comparatively abundant.
Fin whales
Fig. 3 shows the changes in the age at sexual maturity of fin whales in the Antarctic (Lockyer, 1972). Theircatch continued from 1904, when whaling began in the Antarctic, to 1976. Age at sexual maturity declined
markedly from year classes in 1920 to 1930 and this trend is observed until the 1957 year class for which
there are data.
Antarctic minke whales
Fig. 4 shows the changes in age at sexual maturity deduced from the transition phase in earplugs of female
Antarctic minke whales (Kato, 1987). Full-scale whaling for the Antarctic minke whales began in the
1971/72 season, but the age at sexual maturity already began to decline before the season which full-scale
whaling was started. It seems the decline began from around the 1932 year class. Significant decline wasobserved from the 1950 to 1977 year classes (Kato, 1987).
After the moratorium on commercial whaling was implemented in 1987, samples were collected by the
JARPA, which are shown in Fig. 5 (Zenitani and Kato, 2005). The decline tendency in the age at sexual
maturity gradually slowed down around the 1960s, and almost stopped around 1965 to 1980. In case of
females, increasing trends was observed after the 1990 year class.
Pregnancy Rate
Fig. 6 shows the changes in the pregnancy rates of the blue, fin, and humpback whales over the years. The
rates of the three whale species show the tendency to increase from the 1930s, although there are yearlyfluctuations. Pregnancy rates of blue whales increased from about 1930 to 1960, fin whales from around1930 to 1970, and humpback whales from about 1930 to 1960, although the yearly fluctuation is great.
It is considered that Antarctic minke whales are capable of reproducing every year, and the apparent
pregnancy rate estimated from those migrating to the Antarctic is high and constantly in the ninetiethpercentile since 1970s. However, they are segregated by sex and reproductive status, and the 78% (Best,1982) estimated in their breeding ground is considered to be appropriate. No detailed reports are available
on the changes over the years.

39

Growth Curve
The growth curve of Antarctic minke whales using samples from commercial whaling is shown in Fig. 6(Kato, 1987). Kato (1987) reported that growth rate increased from year classes in 1940 to 1949 and for
those in 1970 to 1979, and that they matured at a younger age and became larger in size.
We compared the growth curve after the above period, using JARPA samples, and found that the growth rate
has slowed down for year classes in the 1990s, compared with those in the 1980s. The growth curve showsthat the 1990s year group tend to be below those for 1980s (Fig. 8).
VPA Analysis of Antarctic Minke Whale Stocks
Catch-at-age analysis using VPA and others have shown that recruitment of Antarctic minke whales
increased from 1944 to 1968 (Sakuramoto and Tanaka, 1985; 1986; Butterworth et al., 1999). It thendecreased until about 1980, after which the declining trend has halted. The causes for these changes havelong been the subject of discussion at the IWC (see IWC, 1989; 1990; 1991; 1992a; 1992b; 1995;
Sakuramoto and Tanaka, 1986; Butterworth et al., 1999; Butterworth and Punt, 1999).
Accumulation of Pollutants
Honda et al. (1987) analyzed heavy metals in the livers of Antarctic minke whales commercially taken in the
1980/81 season. He found that Hg concentration did not increase with age; rather it decreased after age ten.
It is well known that Hg concentration in the liver increases with age in marine mammals including
cetaceans. However, he reported that such age-related accumulation was not detected in the minke whale
samples. Changes in Hg concentration in the prey was not a plausible explanation, since Hg in theenvironment has not greatly changed, and he considered that it was a result of an increase in prey
consumption, hence the increase of Hg intake. As a factor, he pointed out that feeding conditions had
improved for the Antarctic minke, with the decrease in the abundance of larger whales (Honda et al., 1987).
Further, in order to understand the apparent decreasing pattern of Hg concentration, Honda (1985) estimatedthe total mercury loads (burdens) accumulated in the whale, and examined conditions that would best fit the
mercury accumulation age curve using an accumulation model. In this simulation, he assumed that Hgconcentration in the environment (prey) has not greatly changed and used 4.6 years for the biological halflife of mercury as determined in the striped dolphin. The assumed feeding conditions that fit the curve wasthat in 1980/81, whales up to ten years old consumed prey amounting to 15% of body weight, while
consumption decreased from 15% to 5% for those from ten to thirty; and for those over thirty, it was 5% (Fig.
11). The trend was observed by analyzing samples taken during the 1980/81 to 1981/82 whaling seasons,from which can be deduced that feeding conditions became favourable around 1950, which is thirty years
prior to these sampling dates.
Fujise et al. (1997) continued to monitor Hg accumulation in Antarctic minke whales using JARPA samples.
They clarified the process that reflects an increase in mercury intake for all ages. Examination of theaccumulation changes up to recent years, shows a rise in mercury intake due to increased consumption of
prey. This was found in all age groups. It was confirmed that Hg concentration also increased in Antarctic
minke whales with age as with other cetaceans (Fig. 12).
Furthermore, Hg concentration tends to be lower in the younger age group (one to five year olds), when thedetails of these accumulation curves for the most recent (2003/04) JARPA samples are examined (Fig. 13).
Blubber Thickness
Ohsumi et al. (1997) examined blubber thickness using data from commercial whaling which began in
1971/72 and the JARPA data from 1987/88 to 1995/96. They reported that a reduction in blubber thickness
was observed after 1978 (Fig. 14).
Konishi and Tamura (2005) analyzed blubber thickness using the JARPA data from 1987/88 to 2003/04, andreported that the decrease in thickness found by Ohsumi et al. (1997) was still in evidence (Fig. 15).
Changes in Stomach Content Weight of Antarctic Minke Whales
Tamura and Konishi (2005) examined the stomach contents of Antarctic minke whales using data from the
JARPA 1987/88 to 2003/04 seasons. They reported that the decreasing pattern in stomach content weights ofmature minke whales was observed since the 1987/88 season in which JARPA was started (Fig. 16).
40

Competition with Larger Baleen Whales (Humpback and Fin Whales)
In recent years, it has become known that larger baleen whale stocks, including humpback whales, arerecovering. Matsuoka et al., (2005) estimated abundance of humpback and fin whales in the Antarctic Areas
III (East), IV, V and VI (West), using the whale sighting data from JARPA. They reported that the number of
humpback and fin whales migrating to Antarctic Areas IV and V have been increasing (Fig. 17) and that thebiomass of these species has become larger than that of Antarctic minke whale in recent years (Fig. 18;
Matsuoka et al., 2005). In Area IV, especially, the humpback whale has been seen to be encroaching on the
distribution range of Antarctic minke whales. Many minke whales were sighted in the research area south oflat. 60°S in recent years, but it was observed in the 2003/04 surveys that they tended to be pushed back into
the pack ice (Ishikawa et al., 2004).
Humpback and fin whales used to be only sighted offshore until the 1990s, but in recent years, theirdistribution range has become overlapped with that of the Antarctic minke whale. The overlapping of two or
more whale species in the feeding grounds of the Antarctic suggests competition among these whale species
occurs over krill, which is the key species, especially in a simple marine ecosystem structure as the Antarctic
Ocean. The reduced range of Antarctic minke whales in their feeding ground suggests that those niches havebecome sub-optimal.
What Has Happened to the Antarctic Minke Whale Stocks?
The above considerations can be summarized as follows:
Changes found from 1940 to 1970:* Increase in recruitment (VPA)* Acceleration in growth rate (growth curve)* Decrease in the age at sexual maturity (earplug transition phase)* Increase in mercury intake
Changes found from 1970 to 1980:* Decrease in recruitment (VPA)* Halt in the decreasing trend in the age at sexual maturity (earplug transition phase)* Mercury intake stabilizes at fixed level
Changes from 1980 onwards:* Decreasing growth rate (growth curve)* Decrease in blubber thickness (from 1980 to present)* Decrease in stomach contents weight (from latter half of 1980 to present)* Decrease in mercury intake
Examining the above phenomenon comprehensively, the following possible changes are considered to haveoccurred in the Antarctic minke whale stocks.
Feeding conditions became favourable for the Antarctic minke whales around 1940, at the latest, with thedepletion in large baleen whales such as blue and other whales due to overhunting, and the nutritional statusof each minke whale individual improved. Thus, growth rate increased for the minke, and they grew tomature body length earlier, reaching sexual maturity younger. The increased breeding capability resulted inincreased abundance. Declining age at sexual maturity and increasing pregnancy rates were also observed infin, humpback and other large baleen whales, suggesting improved feeding conditions for them as well.
Overall improvement in feeding conditions is indicated, arising from lower population density due to thedecrease in the number of large baleen whales which consumed huge amounts of krill in the Antarctic Ocean(Kato, 1987).
41

The amount of available prey (krill) per minke whale as a consumer became restricted about 1970. Aroundthat time, growth rate and the declining the age at sexual maturity slowed down. By 1980 a halt in the latter
trend was observed. It seems that the growth rate of whales in year classes of the 1990s was lower than thatof those in year classes of the 1980s. The change in feeding conditions was reflected in blubber thickness.
Blubber thickness of Antarctic minke whale has shown a constant decline since 1978/88. Also, the numberof humpback and fin whales which are higher in their niches than the number of Antarctic minke whales,
migrating to the Antarctic increased from 1990. This suggests the recovery of these stocks, while indicating
a further deterioration in feeding conditions for Antarctic minke whales.
Other factors that may have contributed to the changes in feeding conditions include environmental changes
such as global warming. Melting of fast ice in the seas around the Antarctic Peninsula has been reported,and a decrease in the number of penguins which incubate on ice has been observed (Croxall et al., 2002).
However, Areas IV and V of the Antarctic Ocean, which are the concern of this paper,, are on the opposite
side of the Antarctic Peninsula and no major melting of fast ice has been reported to date.. Analysis ofsatellite data and oceanographic observations carried out in the JARPA programs have not shown any
constant change in the marine environment, although annual fluctuations due to El Nino and La Nina havebeen observed (Watanabe et al., 2005).
It is highly possible that nutritional conditions for the Antarctic minke whales have changed due tocompetition with other whale species such as the humpback whale, and possibly the change in carrying
capacity, in the Antarctic marine ecosystem.
For the appropriate management and sustainable use of Antarctic minke whale stocks, we would need tocollect not only data on abundance and biological parameters of major whale species, but also data on theirhabitat environment and their responses to environmental changes.
ACKNOWLEDGMENTS
We thank Dr. Hidehiro Kato, National Research Institute of Far Seas Fisheries (NRIFSF), Ms. Ryoko
Zenitani, the Institute of Cetacean Research (ICR), for preparing the information on sexual maturity of whale
samples. We also thank Mr. Koji Matsuoka, ICR, Dr. Tsutomu Tamura, ICR, Mr. Takeharu Bando, ICR,
and Dr. Kenji Konishi, ICR, for providing the information in the referenced research documents. Our sincere
thanks are also due to all researchers and crews who were participated in the JARPA surveys from 1987/88
to 2003/04 seasons.
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JARPA Review meeting, January 2005.
Best, P.B. 1982. Seasonal abundance, feeding, reproduction, age and growth in minke whales off Durban(with incidental observations from the Antarctic). Rep. int Whal. Commn 32: 759-786.
Butterworth, D.S., Punt, A.E., Geromont, H.F., Kato, H. and Fujise, Y. 1999. Inferences on the dynamics ofSouthern Hemisphere minke whales from ADAPT analyses of catch-at-age information. J. Cetacean Res.
Manage., 1(1): 11-32
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whales in the Antarctic, May 1997 (unpublished). 16pp.
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bioaccumulations of heavy met al.s in marine mammals). Ph. D. thesis, Univ. Tokyo, 101p.
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Ishikawa, H., Otani, S., Kiwada, H., Isoda, T., Tohyama, D., Honjo, K., Hasegawa, A., Terao, T., Kushimoto,T., Ohshima, K., Sugiyama, K., Sasaki, T., Itoh, S., Takamatsu, T. and Yoshida, T. 2004. Cruise Report of
the Japanese Whale Research Program under Special Permit in the Antarctic (JARPA) Area IV and EasternPart of Area III in 2003/2004. Paper SC/56/O12 presented to the IWC Scientific Committee, June 2004
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Balaenoptera bonaerensis in Areas IV and V. Paper JA/J05/PJR9 presented to the JARPA Review meeting,January 2005.
Lockyer, C. 1982. Investigation of the ear plug of the southern sei whale, Balaenoptera borealis, as a validmeans of determining age. J. Cons. Int. Explor. Mer., 36(1): 71-81.
Matsuoka, K., Hakamada, T. and Nishiwaki, S. 2005. Distribution and abundance of humpback, fin and blue
whales occurring in the Antarctic Areas IIIE, IV, V and VIW (35°E-145°W). Paper JA/J05/PJR10
presented to the JARPA Review meeting, January 2005.
Ohsumi, S., Fujise, Y., Ishikawa, H., Hakamada, T, Zenitani, R. and Matsuoka, K. 1997. The fattyness of the
Antarctic minke whale and its yearly change. Paper SC/M97/18 presented to the IWC Intersessional
Working Group to Review Data and Results from Special Permit Research on Minke whales in the
Antarctic, May 1997 (unpublished). 21pp.
Sakuramoto, K. and Tanaka, S. 1986. A simulation study on management of whale stocks considering feedback systems. Paper SC/38/O10 presented to the IWC Scientific Committee, May 1986.
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Balaenoptera bonaerensis in Areas IV and V of the Antarctic Paper JA/J05/PJR8 presented to the JARPA
Review meeting, January 2005.
Watanabe, I., Yamamoto, Y., Honda, K., Fujise, Y., Kato, H., Tanabe, S. & Tatsukawa, R. 1998.
Comparison of mercury accumulation in Antarctic minke whale collected in 1980-82 and 1984-86. Nippon
Suisan Gakkaishi, 64:105-109.
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to the JARPA Review meeting, January 2005.
43

Zenitani, R. and Kato, H., 2005. Long- term trend of age at sexual maturity of Antarctic minke whales bycounting transition phase in earplugs. Paper JA/J05/PJR7 presented to the JARPA Review meeting, January
2005.

44

35000

Blue
Fin
Sei
Humpback
Minke

30000

Catches (whales)

25000

20000

15000

10000

5000

0
1900

1910

1920

1930

1940

1950

1960

1970

1980

1990

2001

Calender year
Fig. 1. Catch history of large sized baleen whales in the Antarctic since 1904.
4,000,000

Minke

3,500,000

Right
Sperm

Catch (tons)

3,000,000

Sei

2,500,000

HumpbackFin

2,000,000

Blue
1,500,000
1,000,000
500,000

1904
1 9 /05
06
1 9 /0708
1 9 /0910
1 9 /1112
1 9 /1314
1 9 /1516
1 9 /1718
1 9 /1920
1 9 /2122
1 9 /2324
1 9 /25
26
1 9 /2728
1 9 /2930
1 9 /3132
1 9 /33
34
1 9 /3536
1 9 /3738
1 9 /3940
1 9 /4142
1 9 /43
44
1 9 /4546
1 9 /47
48
1 9 /4950
1 9 /51
52
1 9 /5354
1 9 /55
56
1 9 /57
58
1 9 /5960
1 9 /6162
1 9 /63
64
1 9 /65
66
1 9 /67
68
1 9 /6970
1 9 /71
72
1 9 /7374
1 9 /75
76
1 9 /7778
1 9 /7980
1 9 /8182
1 9 /83
84
1 9 /85
86
1 9 /87
88
1 9 /8990
1 9 /91
92
1 9 /93
94
1 9 /95
96
1 9 /9798
2 0 /9900
2 0 /01
02
2 0 /03
04
/05

0

Year

Fig. 2. Total biomass of harvested large sized baleen whales in the Antarctic since 1904.

Age at sexual maturity(year)

15

10

5

0
1900

1905

1910

1915

1920

1925

1930

1935

1940

1945

1950

1955

1960

1965

1970

1975

Year

Fig. 3. Trend of age at sexual maturity of southern fin whales by cohort (Lockyer, 1982)

45

1980

1985

1990

1995

2000

Age at sexual maturity(year)

25
20
15
10
5
0
1900

1905

1910

1915

1920

1925

1930

1935

1940

1945

1950

1955

1960

1965

1970

1975

1980

1985

1990

1995

2000

Year

Fig. 4. Trend of age at sexual maturity of Antarctic minke whales by cohort (Kato, 1987)
26
24

Male

Mean age at sexual maturity

22
20
18

Mean±S.D.

16
14
12
10
8
6
4
2
0
1930

1935

1940

1945

1950

1955

1960
1965
Cohort

1970

1975

1980

1985

1990

1995

26
24

FemaleMean age at sexual maturity

22
20
18

Mean±S.D.

16
14
12
10
8
6
4
2
0
1930

1935

1940

1945

1950

1955

1960
1965
Cohort

1970

1975

1980

1985

1990

1995

Fig. 5. Trend of age at sexual maturity of Antarctic minke whales by cohort (Zenitani and Kato, 2005)

Pregnancy rate (%)

100
90

Blue

80

Fin
Humpback

70
60
50
40
30
20
10
2000

1995

1990

1985

1980

1975

1970

1965

1960

1955

1950

1945

1940

1935

1930

1925

1920

1915

1910

1905

1900

0

Year

Fig. 6. Yearly changes of apparent pregnancy rate of blue, fin and humpback whales in the Antarctic (data fromLockyer (1982) and BIWS).

46

Fig. 7. Yearly changes of growth curve of Antarctic minke whales using samples from commercial whaling (Kato,
1987).

1980’s1980’s1990’sArea IV

1990’sArea IV

1980’s1980’s1990’sArea V

1990’sArea V

Fig. 8. Comparison of growth curve of body length in each cohort for Antarctic minke whales. Left column indicate
male, and right female. Upper and lower figures indicate Area IV and Area V, respectively. Age data in this figure wereused from Ms. Zenitani (unpublished data).

47

Hg ( μ g / g , dr y wt . )Fig. 9. Boot strap estimates of median (solid line), and 5%- and 95%-iles (dotted lines), for recruitment Ny,2 (relative to
its estimated 1968 level for the corresponding bootstrap replicate) for Area IV for the base-case estimator when M isfixed at its corresponding best estimate of o.o57yr-1. (Butterworth et al., 1999)

Ag e ( ye ar )Fig. 10. Age trend of hepatic mercury concentrations (μg/g) in Antarctic minke whales using samples fromcommercial whaling in 1980/81 season . (Honda et al., 1987)

Fig. 11. Age trend of mercury load (mg) in the body of Antarctic minke whales, and accumulation curve obtained fromthe simulation of accumulation model (Honda, 1984).

48

100
80
60
40
01/0202/03 97/9898/99 94/9595/96 88/8989/90

20

84/8585/86

Survey year group

1-5

80/81- 0
81/82

6-15

16-25

Hg concentration (ng/g wet wt)

120

0
26-

Age group

Fig. 12. Comparison of age trends of hepatic Hg concentrations (ng/g) of Antarctic minke whales during five survey
year groups (1980/81+1981/82, 1984/85+1985/86, 1988/89+1989/90, 1994/95+1995/96, 1997/98+1998/99,
2001/02+2002/03).
120

1-5
6-15
16-25
26-

H g c o n c e n tratio n s ( n g/ g)

100

80

60

40

20

0
80/8181/82

84/8585/86

88/8989/90

94/9595/96

97/9898/99

01/0202/03

Su rve y ye ar gro u p

Fig. 13. Yearly changes of hepatic Hg concentrations (ng/g) in minke whales from four age groups (1-5, 6-15, 16-25, 26
or more).

6. 0

BT/BL( *100)

5. 5

5. 0

4. 5

4. 0
1970

1975

1980

1985
Year

1990

1995

2000

Fig. 14. Yearly changes in average fattyness index of blubber thickness in February (closed circle indicates males,
open circle females. (Ohsumi et al., 1997)

49

6.0

Mean blubber thicknes

5.5

5.0

y = -0.1117x + 4.5923
2
R = 0.6016
4.5

4.0

3.5

3.0
0

1
1987/88

2
3
4
5
6
7
8
9
1999/00
2003/04
1989/90
1993/94
1995/96
1997/98
2001/02
1991/92

10

Survey year

Fig. 15. Yearly changes in average blubber thickness of pregnant females in February (Konishi and Tamura, 2005).

Area VI

Area V
140.0

140.0

Male

120.0

120.0
y = -1.5017x + 3077.6
2
R = 0.2133

100.0

kg

kg

100.0

Male

y = -1.0507x + 2172.8
2
R = 0.0606

80.0

80.0

60.0

60.0

40.0
1988

1990

1992

1994

1996

1998

2000

2002

40.0
1988

2004

1990

1992

1994

1996

1998

2000

2002

2004

140.0

140.0

FemaleFemale

120.0

120.0
y = -3.3534x + 6782.2
2
R = 0.3655

100.0

kg

kg

100.0

y = -3.6764x + 7424.1
2
R = 0.6431

80.0

80.0

60.0

60.0

40.0
1988

1990

1992

1994

1996

1998

2000

2002

40.0
1988

2004

Year

1990

1992

1994

1996

1998

2000

2002

2004

Year

Fig. 16. Yearly changes of stomach contents (kg) of mature Antarctic minke whales in Area IV and V (Tamura andKonishi, 2005). Data used was from individuals collected from an area south of 63 degree S in January andFebruary. The content weight was combined the first and second stomachs.

50

Fig. 17. Yearly changes of abundance estimates for humpback and fin whales in Antarctic Area IV (70E-130E). Upper
figure shows humpback whales, lower figure fin whale (Matsuoka et al., 2005)

Fig. 18. Biomass of Humpback and Antarctic minke whales in Antarctic Area IV (70E-130E) using data from 1989/90
to 2003/04 JARPA (Matsuoka et al., 2005).

51

Appendix 3
Temporal and spatial changes in stock structure of baleen
whale species in the Antarctic feeding grounds
LUIS A. PASTENE AND NAOHISA KANDA
The Institute of Cetacean Research, 4-5, Toyomi-cho, Chuo-ku, Tokyo 104-0055, Japan
Contact e-mail: pastene@cetacean.jp

Information on stock structure of the main whale species comprising the Antarctic ecosystem is important fora better interpretation of the estimation of abundance and trends, estimation of biological parameters and forthe implementation of management procedures.
The levels of available information on stock structure are different among the several baleen whale species
inhabiting the Antarctic. Furthermore in absence of geographical barriers, temporal and spatial changes instock structure could occur, particularly in the Antarctic feeding ground, which is subjected to changes inoceanographic and other environmental conditions. Here we provide a background on stock structure foreach of the main species and identify additional research needs on stock structure.
1- TRUE BLUE WHALE
Little information is currently available on the stock structure of this species in the Antarctic. Past Markrecapture analysis conducted showed that a large proportion of whales tended to return year after year to thesame part of the Antarctic (Brown, 1954). Mark-recapture analysis based on a larger number of data (Brown,1962) and analysis of catch distribution suggested that the six IWC whaling areas were probably valid forthis species (Brown, 1962; Mackintosh, 1965).
No analysis based on genetics has been conducted to investigate stock structure of true blue whale in the
Antarctic. During the Japanese Whale Research Program under Special Permit in the Antarctic (JARPA),
biopsy samples have been collected but low sample size prevented us from studying their stock structure.
Effort will be made during JARPA II to collect more biopsy samples from traditional IWC areas III, IV and
V and to evaluate whether the Area division is still valid for this species. Genetic analyses will be based on
the standard mtDNA control region sequencing and microsatellites. As an initial step, it is desirable thecollection of 20-50 samples from each of the management areas (IWC, 1991).
In addition tagging methods will be developed for data loggers (TDR) and satellite tagging transmitters.
2- FIN WHALE
Little information is currently available on the stock structure of this species in the Antarctic. As in the caseof the blue whale, earlier mark-recapture analysis showed that most whales returned to the same part of the
Antarctic year after year (Brown, 1954). Historical non-genetic studies showed that the six whaling areas
were probably better valid for blue and humpback whales than for fin whales (Mackintosh, 1965). There wascertain segregation in the feeding ground between certain longitudes in four sectors which lie: South of theAtlantic Ocean, South of the Indian Ocean, South of Western South Pacific Ocean and South of EasternSouth Pacific Ocean (Mackintosh, 1965). South of the Indian Ocean corresponds approximately to JARPA
Areas IIIE and IV and South of Western South Pacific to JARPA Areas V and VIW.
Only a single study based on mtDNA and biopsy samples collected by JARPA has been conducted to
examine genetic difference between the whales from IIIE+IV and VW (Pastene et al., 2005b). However,sample size was too small (8 and 15, respectively) to make a firm conclusion on stock structure of thisspecies in the Antarctic.
Acquiring additional genetic data should be important for testing the hypothesis of segregation in the feeding
ground by oceanic areas. The number of fin whales to be sampled in JARPA II for the objective ofmonitoring of biological parameters will be 50 in each year. These samples will be used to examine stock53

structure of the species in conjunction with biopsy samples that also will be obtained during JARPAII. In thisway comparison between Indian Ocean and Western South Pacific populations can be achieved. Genetic (e.g.
mtDNA, microsatellites) and non-genetic techniques (e.g. mean body length of physically matured whales,morphometric, ecological markers) will be used for this purpose. For genetic analysis the IWC has
recommended sample size of 20-50 from each population (IWC, 1991). However this should be interpreted
as a general recommendation as the sample size depends on the effect size of each species.
In addition tagging methods will be developed for data loggers (TDR) and satellite tagging transmitters.
Both blue and fin whales have experimented substantial changes in abundance in the Antarctic and it can be
expected that stock structure changed from that postulated in the past. Identification of such changes isimportant for the adequate interpretation of abundance estimation and biological parameters.
3- MINKE WHALE
One of the research objectives of the JARPA was the elucidation of stock structure of the Antarctic minke
whale to improve stock management of this species. Based on the available JARPA samples, several
analytical approaches, involving both genetics and non-genetics methods, were used to investigate stock
structure of this species (Pastene et al., 2005a).
The JARPA review meeting called by the Government of Japan agreed that the most reasonable explanation
for the results of the analyses on stock structure was the two stocks present in the research area: an eastern
Indian (I) and a western South Pacific (P). These stocks appeared to mix across a soft boundary, which
would probably be best placed near 165°E. The meeting also suggested that further analyses could usefully
estimate the proportion of the I and P animals in an overlap area such as Area VW (130°-165°E), using amethod similar to that used in the case of North Pacific minke whale (IWC, 2003).
JARPA II will attempt to investigate the pattern of mixing between the I and P-Stocks in the suggested
overlap sector, in particular it will test whether or not there is significant yearly differences in this pattern.
The required sample size for such analyses was investigated based on the samples obtained by JARPA.
3-1 Method
Mixing proportion of the I-Stock in the mixed assemblage was estimated using a simple Bayesian method(IWC, 2003) and mtDNA haplotype frequency data. In this method, the baseline stocks (I and P in this case)are assumed to be pure (and known) and there is a prior on the mixing proportion of I and P-Stocks in theoverlap sector (VW in this case). The analysis assumes no uncertainty about the proportion of different
haplotypes in the I and P-Stocks.
3-2 Annual changes in I-stock proportion (MP) in VW
For this analysis the following baseline stocks were used:
I-Stock Baseline: Area IV, all JARPA surveys (n=2,655)
P-Stock Baseline: Area VE+VIW, all JARPA surveys (n=1,637)

MP
0.62460.49070.6046
0.2446
0.65120.48470.42670.532090/91 (n=180) 173
92/93 (n=193) 192
94/95 (n=130) 129
96/97 (n=121) 119
98/99 (n=171) 170
00/01 (n=133) 131
02/03 (n=89) 89
All years (n=1,017) 1003

From this table, MP in 1996/97 appears to be smaller than in other years.
54

SD
0.12530.15130.17080.15760.13630.17130.21930.0652

3-3 Estimating the required sample size to find significant differences in mixing proportion between
1996/97 and AYC (All Years Combined)
In the next analysis the samples from all but 1996/97 years were combined, which is named as ‘AYC’, and
the AYC was considered as the sample representative of the mixing rate of I and P-Stocks in VW. The
sample from 1996/97 is considered as a ‘variable’ sample. The required sample size was calculated to detectthe difference observed between the AYC and the variable sample.
For this analysis the following baseline stocks were then used:
I-Stock baseline: Area IV (n=2,655)
P-Stock baseline: Area VE+VIW–(96/97) (n= 1,335)
The Bayesian method used can inform precision implications of the sample size in the overlap sector (VW).
The number of samples by haplotype was therefore scaled upwards in sector VW of the 1996/97 season. The
Bayesian program was run repeatedly with increasing sample size from initial n=121 until the Credibility
Intervals (CI) of MP in 1996/97 season did not overlap with the CI of MP in AYC.

1996/97nMP

Credibility
Intervals

VW(130165°E)

1210.24790.01300.5990

AYC

n1(scaledupward)MP300

0.1975CredibilitynMPIntervals
0.01500.4430

Credibility
Intervals

896

0.59750.46300.7290

Results obtained showed that for non-overlapping 95% credibility intervals between the estimates of themixing proportions over 130-165°E, a sample size in that region of about 300 will be required. This sample
size will provide the power to detect an annual change as big as the one that appears to have occurred in
1996/97 season.
3-4 Remarks
Samples in VW should be taken equally over the sector VW (about 100 samples in each 10° sector). This
will allow similar analysis conducted at smaller longitudinal sectors. The analysis at smaller longitudinal
sector was not possible using JARPA data because the annual average number of samples by 10° sector in
VW was only 48.
Monitoring of changes in stock structure is important for management purpose. For example catch quotas
based on stock will have to be adjusted for a shifting in stock boundaries (or equivalently changes of therelative proportions of stocks in mixing areas). Otherwise there is the risk of a negative impact on the stock.
The ecological factor(s) is important to be investigated for the possible causes deriving such shifting.
It should be noted that the distributions of minke and humpback whale overlap in Area IV. One of thepossibilities for the changes in stock structure of minke whale stock could be a response to the stable rate ofincrease in abundance of Stock D humpback whales in Area IV.
4- Humpback whale
As a result of the comprehensive assessment of this species by the IWC/SC, breeding areas, feeding areas
and migratory corridors of the southern humpback whale were defined (see Fig. 1 in IWC, 2001). Using
biopsy samples taken by JARPA, we tested the validity of stock structure in these feeding areas in the
Antarctic: Stock C (35-55°E, n=34), Stock D (80-110°E, n=79), Stock E (130°E-170°W, n=64) and Stock F(170-145°W, n=36). All the pairwise comparisons of mtDNA haplotype frequencies (by randomized chisquare test) resulted in significant statistical differences. Therefore genetic analysis of JARPA samples
showed a segregation of humpback whales Stocks C, D, E and F in the feeding ground (Pastene et al.,2005b).
55

It is also known that Stock D of southern humpback whale has shown a stable rate of increase in abundance(Bannister and Hedley, 2001). This is likely reflected in changes in proportion of Stock D in the mixing
sector 110-130°E suggested by past mark-recapture analysis (Chittleborough, 1959; Dawbin, 1966).

Sector/Survey

Proportion of Stock D (SD)110-130°E (n=10, 93/94, 95/96)

0.6015 (0.1865)

110-130°E (n=11, 97/98, 99/00)

0.6640 (0.2166)

110-130°E (n=13, 01/02, 03/04)

0.7591 (0.1172)

110-130°E (n=34, total)

0.7422 (0.0999)

Although the standard deviations of the estimates are large due to small sample size, proportion of this stockin the mixed area seems to have increased with time. These results are consistent with the results of sighting
surveys that indicate that this stock is increasing its abundance.
The number of humpback whales to be sampled in JARPA II in Area IV for the objectives of monitoring of
biological parameters is 50 in each year. This sample, in conjunction with new biopsy samples obtained in
the research area, will be used to examine yearly variation in the pattern of stock structure. Of particularimportance is the examination of the contribution of stock D in the sector 110-130°E and east in order toinvestigate possible expansion of the D stock. Genetic (e.g. mtDNA, STR) and non-genetic techniques (e.g.
mean body length of physically matured whales, morphometric, ecological markers) will be used for thispurpose.
REFERENCES
Bannister, J.L. and Hedley, S.L. 2001. Southern Hemisphere Group IV humpback whales: their status fromrecent aerial survey. Mem. Qld. Mus. 47 (2): 587-598.
Brown, S.G. 1954. Dispersal in blue and fin whales. Discovery Reports. Vol. XXVI: 355-384.
Brown, S.G. 1962. The movement of fin and blue whales within the Antarctic zone. Discovery Reports. Vol
XXXIII: 1-54.
Chittleborough, R.G. 1959. Australian marking of humpback whales. Norsk Hvalfangsttid 48: 47-55.
Dawbin, W.H. 1966. The seasonal migratory cycle of humpback whales. In Norris, K.S. (ed.). Whales,
dolphins and porpoises. University of California Press, Berkerley. pp. 145-171.
International Whaling Commission. 1991. Report of the workshop on the genetic analysis of cetacean
populations. Rep. int. Whal. Commn (special issue 13): 3-21.
International Whaling Commission. 2001. Report of the Scientific Committee. J. Cetacean Res. Manage., 3(Suppl.): 1-82.
International Whaling Commission. 2003. Report of the workshop on North Pacific common minke whale(Balaenoptera acutorostrata) Implementation Simulation Trials. J. Cetacean Res. Manage. 5 (Suppl.): 455488.
Mackintosh, N.A. 1965. The stocks of whales. Fishing News (Books) Ltd.., London. 232pp.
Pastene, L.A., Goto M., Kanda, N., Bando, T., Zenitani, R., Hakamada, T., Otani, S. and Fujise, Y. 2005a. A
new interpretation of the stock identity in the Antarctic minke whale based on analyses of genetics and nongenetics markers. Document JA/J05/JR3 presented to the JARPA Review Meeting, Tokyo 18-20 January(unpublished), 31pp.
Pastene, L.A., Goto, M., Kanda, N. and Nishiwaki, S. 2005b. Genetic analyses on stock identification in the
Antarctic humpback and fin whales based on samples collected under JARPA. Document JA/J05/JR16
presented to the JARPA Review Meeting, Tokyo 18-20 January (unpublished), 12pp.

56

NOT TO BE CITED WITHOUT PRIOR REFERENCE TO THE AUTHORS

Appendix 4
Monitoring of environmental pollutants in cetaceans and themarine ecosystem in the Antarctic Ocean and the western
North Pacific Ocean
GENTA YASUNAGA AND YOSHIHIRO FUJISEThe Institute of Cetacean Research, 4-18, Toyomi-cho, Chuo-ku, Tokyo 104-0055, Japan.
Contact e-mail:yasunaga@cetacean.jp

INTRODUCTION
It is known that the distribution of anthropogenic pollutants, such as organochlorines and heavy metals, inthe open ocean air and water is global in extent. The spatial and temporal distribution of these pollutants
must be revealed in order to predict changes in the future. Environmental monitoring of the pollutants
generally uses environmental samples, such as air and seawater, however, the pollutant levels are extremely
low in the open ocean. Whales are high in the food chain in the ocean, thus they may be particularly suitable
as monitors of pollutant levels and their adverse effects.
The Antarctic is an important area for environmental monitoring of the pollutants, since it is at the end of
their global transport as are the middle and low latitude areas, such as western North Pacific, which is where
the primary anthropogenic pollutant sources are located. Thus, the pollutants levels of the baleen whales in
the Antarctic are lower than those in middle and low latitudes of the northern hemisphere (Fig. 1).
Comparison of polluted and control areas is useful for monitoring of global distribution and behaviour of thepollutants.
Pollutants, especially organochlorines, mainly affect the immune system of vertebrates. Control animals arenecessary for laboratory study of toxicology. Therefore, Antarctic baleen whales are well suited as control
animals for toxicology studies of free-ranging whales.
From these points of view, pollutant dynamics in whales will be examined by monitoring pollution in baleen
whales in the JARPA II combined with JARPN II in the western North Pacific. Furthermore, the fate of thepollutants from a more global perspective will be examined by analyses of pollutant levels in air, seawaterand prey species. The relationship between the pollutant levels and some adverse effects in whales will also
be examined in this research.
OBJECTIVES
The following three objectives for the comprehensive monitoring of environmental pollutants in whales,
their food items and environmental samples is conducted as a part of the ecosystem monitoring which is oneof the main objectives of the JARPA II plan.
1.

Elucidation of future accumulation and biological processes of pollutants in whales from the Antarctic
and the western North Pacific2.

Elucidation of transport and fate of pollutants in the Antarctic and the western North Pacific ecosystem

3.

Elucidation of adverse effects of the pollutants for whales in the Antarctic and the western North Pacific
Ocean.

57

METHODOLOGYTo clarify the distribution and behaviour of pollutants globally, it is necessary to conduct comprehensive
monitoring of pollutants in cetaceans and the marine ecosystem in control areas, such as Antarctic Ocean(JARPA II), as well as polluted areas such as western North Pacific Ocean (JARPN II).
1) Organochlorine compounds
In the JARPN II research, man-made compounds, such as PCBs, DDTs and HCHs, have been analysed inthree baleen whales (minke, Bryde’s and sei whales), one tooth whale (sperm whales), their prey species(fishes, krill etc) and environmental samples (air and seawater) in the western North Pacific. Accordingly, in
the JARPA II research, these compounds will be analysed in three baleen whales (Antarctic minke,
humpback and fin whales), their prey species (Antarctic krill etc) and environmental samples (air andseawater) in the Antarctic Ocean. Both research results will be combined for analysis of the fate anddistribution of pollutants in the ecosystem. The blubber and liver of whales are used for analysis oforganochlorines because of higher levels and sensitivity however, this protocol may be modified as needed.
2) Heavy metals
In the JARPN II research, harmful heavy metals, such as Hg, Cd and Pb have been analysed in three baleen
whales (minke, Bryde’s and sei whales), one tooth whale (sperm whales), their prey species (fishes, krill etc)
and environmental samples (air and seawater) in the western North Pacific. Accordingly, in the JARPA II
research, these compounds will be analysed in three baleen whales (Antarctic minke, humpback and fin
whales), their prey species (Antarctic krill etc) and environmental samples (air and seawater) in the Antarctic
Ocean. Both research results will be combined for analysis of the fate and distribution of the pollutants in theecosystem. The liver and muscle of whales are used for analysis of heavy metals because of higher levels andsensitivity however, as for organochlorines, this protocol may be modifed as needed.
3) Relationship between chemical pollutants and cetacean health
Ecotoxicological and pathological approaches are used to detect dose-effect relationships of pollutants forwhales.
3-1) Ecotoxicological study
It is known that some organochlorines have adverse effects on the immune system of whales, however, there
have been few reports on these effects in free-ranging whales. Therefore, dose-effect relationships ofpollutants for whales are examined by toxicological approaches, follow as: 1) examination of the relationshipbetween biomarkers, such as cytochrome P-450, thyroid hormones, vitamin A and metallothionein, and thepollutant levels in whales; 2) understanding of the contaminant sensitivity of whales; 3) examination of therelationship between pollutant levels and expression of chemical related genes in the whales.
3-2) Pathology examinations
It is known that some organochlorines have adverse effects on the immune system of whales. Therefore,
necropsies are carried out to examine immnological effects, such as exodermis and lymph nodes
inflammation. In the western North Pacific, a considerable number of minke whales are observed withanomalous testis tissues. Similarly, this phenomenon is observed in Antarctic baleen whales. Thisphenomenon suggests that the relationship between the pollutant levels and prevalence rate of pathologicalevents in whales requires examination.
SAMPLE SIZEIn the JARPA II survey, the sample size for pathological monitoring in baleen whales was calculated by theprevalence rate. Table 1 shows the relationship between precisions and prevalence rates for pathologicalmonitoring at the 95% confidence level.
There have been few reports on the statistical pathology in free-ranging whales such as the Antarctic minke
whale. Exodermis and lymph nodes inflammation in the feasibility observations of the JARPA surveys wereequal to or smaller than 10%. The prevalence rate of these effects in free-ranging whales on a global basis
may be expected to be similar to these levels.

58

For Antarctic minke whales (their prevalence rate=10%), a minimum of 864 animals is required in each cellwith 40% precision. This precision value is generally used to estimate of prevalence rate in epidemiology(Nakamura, 2002). Eight handred fifty animals expected in this research would be sufficient for estimation ofprevalence rates in order to elucidate of relationship between pollutants and their effects, while are notcomplete enough to conduct all the pathological research.
REFERENCES
IWC. 1999. Report of the workshop on chemical pollution and cetaceans. J. Cetacean. Res. Mnage. (Special
Issue 1):1-42.
Nakamura, K. 2002. Enjoyable epidemiology. Igakushoin, Co. Ltd., Tokyo, pp236 (in Japanese).

Table 1. Necessary sample size of estimation of the prevalence rate in pathological study at the 95%
confidence level.
Prevalence rate (%)
Precision
5

10

15

20

25

30

40%

1825

864

544

384

288

224

30%

3244

1537

968

683

512

398

20%

7299

3457

2177

1537

1152

896

10%

29196

13830

8708

6147

4610

3585

5

25

25

5

25

5

5

5

5

8.8

5

5

0

PCB DDT

Minke whale 7)0

Hg

PCB DDT

0

Hg

15.3

0

0

0

Minke whale 8)

25

Fin whale 12)50

Hg PCB DDT

cBowhead whale9,10)

PCB DDTFin whale 7)

Minke whale 11)0

PCB DDT

Humpback whale 7)00

PCB DDT PCB DDT

Minke whale 2)0

PCB DDTSei whale 3)

Fin whale 6)0

Hg

Fin whale 12)0

PCB DDT

Humpback whale 5)

5

5

5

25

1.00

Concentrations (ppm wet wt.)

5
4

0.75

3

0.50
2

0.25

1

<0.5
PCB DDT

0

0

0

0

PCB DDT

0.00

Hg

Hg

PCB DDT

Antarctic minke whale 1,2)

Antarctic minke whale 3)

Fig. 1. PCB, DDT Levels in the Blubber and Hg Levels in the Liver of Baleen Whales<0.5
PCB DDT0

Fin whale 3).
1) Honda et al. (1987); 2) Aono et al. (1997); 3) Henry and Best (1983); 4) Tomita and Nishimura （1973）; 5) Taruski et al. (1975) ; 6) Hobbs et al. (2001);
7) Gauthier et al. (1997); 8) Hansen et al. (1990); 9) O'Hara et al. (1999); 10) Krone et al. (1999); 11) Kleivane and Skaare (1998); 12) Sanpera et al. (1993)

59

Appendix 5
Hypotheses on the the abundance changes of krill predators in
the Antarctic ecosystem
HIROSHI HATANAKAThe Institute of Cetacean Research, 4-5, Toyomi-cho, Chuo-ku, Tokyo 104-0055, Japan
Contact e-mail: hatanaka@cetacean.jp

I propose the following hypotheses on the abundance changes of krill predators, such as baleen whales,
crabeater seal and penguins in the Antarctic ecosystem. These hypotheses will be examined and selectedbased on data obtained by JARPA and future JARPA II programs on the course of developing the ecosystemmodel.
1. HYPOTHESIS OF CONSTANT OVERALL CARRYING CAPACITY
The total carrying capacity for the four baleen whale species (blue, fin, humpback, and Antarctic minke
whales) that mainly prey on Antarctic krill is constant depending on krill biomass in the feeding grounds. It
is equivalent to the total biomass of four species before the days of commercial whaling in the Antarctic
Ocean. However, carrying capacity may change depending on fluctuations in krill biomass and composition(relative abundances) of the whale species. Based on abundance estimates in their pristine level and in pastand recent years and their daily krill consumption estimates, some estimates of total krill consumption bylarge whales will be obtained. The plausibility of this hypothesis will be checked through the comparison ofthese estimates.
2. HYPOTHESIS OF KRILL SURPLUS
The decline in large whale stocks due to commercial hunting resulted in a large surplus of krill which had
been consumed by large whales. Other predators of krill, such as Antarctic minke whales, pinnipeds, and sea
birds, fed on the surplus and increased in abundance. This hypothesis is an established theory, and will be
the basic concept of the ecosystem model.
3. HYPOTHESIS OF CHANGING CARRYING CAPACITY BY SPECIES
Carrying capacity may be fixed for the total biomass of all baleen whales, but may change for individual
species. The carrying capacity for Antarctic minke whales has increased greatly with the decline in blue, fin,and humpback whales. The abundance of the minke before 1940 and that in recent years (760,000 animals,
IWC, 1990) probably indicates two levels of carrying capacity for Antarctic minke whales. This hypothesis
will be used in the model as an assumption.
4. HYPOTHESIS OF STOCK INCREASE DUE TO A DECLINING OF AGE AT SEXUAL
MATURITY
The trophic condition of juveniles improves with the surplus in krill, inducing faster growth, which results ina younger age at sexual maturity. The proportion of adults in the stocks increases as a result, which in turnincreases recruitment so that abundance increases at a faster rate. At the same time, growth of fetus andcalves would be enhanced since mature cows are well fed and able to provide ample milk, and which would
most likely lead to a lower infant mortality rate. Such a mechanism will probably be an important process to
express quantitatively in the competition model among whale species. The sexual maturity age of Antarctic
minke and fin whales is observed to have decreased, and the JARPA Phase I data on the former could be
useful. It would probably be possible to determine the recent sexual maturity age of fin and humpback
whales from the samples taken. The number of parents and the resulting number of recruits can be estimatedwith the VPA analysis, and it will be confirmed whether or not the decline of age at sexual maturity can61explain quantitatively the increase of recruitment. Then equations for expressing the process of population
growth will be considered.
5. HYPOTHESIS OF A PREDOMINANT SPECIES IN THE ECOSYSTEM
The humpback whale, which is predominant (highest biomass) in the ecosystem, can increase even if theminke whale is near the upper limit of its carrying capacity and there is no surplus in krill. On the contrary,
the minke, which is in an inferior position, cannot increase by pushing aside other whale species. If weexamine the balance among whale species before any whaling had begun, the blue, fin, and humpback
whales were in a more predominant position in this sense than the Antarctic minke. At that time Antarctic
minke whales occupied only narrow niches when other large whales were dominant. The plausibility andnecessity of this hypothesis (assumption) will be checked on the course of model construction.
6. HYPOTHESIS OF DECLINING PREGNANCY RATES AND/OR JUVENILE SURVIVALRATES DUE TO INADEQUATE TROPHIC CONDITIONS
It has been observed that the blubber thickness of Antarctic minke whales is decreasing. This fact indicatesthat they are becoming unable to store sufficient nutrition during their feeding period. Consequently, theproportion of animals capable of becoming pregnant is decreasing, resulting in lower pregnancy rates. At thesame time, the age at maturity increases. In other words, it is the reverse process of hypothesis No.4, which
results in a decrease in abundance. It is possible to estimate sexual maturity age of year classes going backseveral years or a decade or so from the time samples were taken since it is estimated by observing thetransition phase of the growth layer in their earplugs. However, the blubber thickness and pregnancy rates
are measured only just after the time samples are taken. They are however important indices that enablereal-time tracking of qualitative changes in the stocks. Based on data of blubber thickness, krill consumption
and pregnancy rate, the relationships among them will be analysed. The decreasing process of mink whale
abundance will be considered through these analyses.
7. HYPOTHESIS OF COMPETITION AMONG WHALE SPECIESAs the abundance of humpback and fin whales (and blue whales) recover, Antarctic minke whales will begin
to decrease in abundance. The major mechanisms behind the decline will be increasing sexual maturity age
leading to decreasing recruitment and lower pregnancy rates due to inadequate trophic conditions or
unfavourable feeding conditions. These mechanisms will be formularized based on past JARPA data as wellas those to be collected through monitoring in JARPA II and incorporated into the model.
8. HYPOTHESIS OF SLOW RECOVERYBlue whales have been so severely depleted by over-hunting that mating opportunities are limited; andalthough there is indication of abundance increase they are far from full recovery. Long-term monitoring
will be necessary to determine whether their rate of recovery will remain slow or increase.
9. HYPOTHESIS OF ENVIRONMENTAL CHANGES AFFECTING CETACEANS
Climatic changes such as global warming will bring about changes in the production and biomass of krill.
The change in feeding conditions of baleen whales will affect growth and recruitment rates. The effects may
differ depending on the whale species. These effects will be formularized using information from CCAMLR
and other organizations and data obtained from monitoring krill density in the research area.

62

Appendix 6
Sample sizes of Antarctic minke, humpback and fin whales
required for statistical examination of yearly trend in
biological parameters
TAKEHARU BANDO1), TAKASHI HAKAMADA1), RYOKO ZENITANI1), YOSHIHIRO FUJISE1), EIJI TANAKA2) AND HIDEHIRO
KATO3)
1)The Institute of Cetacean Research, 4-5 Toyomi-cho, Chuo-ku, Tokyo, 104-0055, Japan
2) Tokyo University of Marine Science and Technology, 4-5-7, Konan, Minato-ku, Tokyo, 108-8477, Japan
3) National Research Institute of Far Seas Fisheries 5-7-1 Orido, Shimizu, Shizuoka 424-8633, JapanThe Institute of Cetacean Research, 4-5, Toyomi-cho, Chuo-ku, Tokyo 104-0055, Japan
Contact e-mail:bando@cetacean.jp

Biological parameters such as pregnancy rate and age at sexual maturity in baleen whales are thought tochange in response to changes in abundance, food availability and competition with other species (Gambell,
1973; Kato, 1987; Masaki, 1979; Lockyer, 1979; 1984). Monitoring of biological parameters to detectchange in quality of habitat for baleen whales is one of the objectives of JARPA II.
Sample sizes required for statistical examination of yearly trend in the proportion of pregnant in matured
female (PPF) of Antarctic minke whales, apparent pregnancy rate of humpback and fin whales and age atsexual maturity for minke and fin whales were calculated.
Ideally “true pregnancy rate”, which is the probability that one mature female would become pregnant in one
year, should be used. However since estimation of “true pregnancy rate” is difficult, the “apparent pregnancy
rate”, which is the ratio of pregnant females in the mature female samples caught in a certain area, isconventionally used as an approximation of the “true pregnancy rate”.
It is known that the apparent pregnancy rate could be biased by segregation or date of sampling. However inthe case of fin whale, apparent pregnancy rate estimated from commercial whaling data was considered tochange in response to changes in abundance or density. Therefore apparent pregnancy rate in fin whalereflects “true pregnancy rate” to some degree (Kato, 1991). Therefore apparent pregnancy rate was used inthis study for fin whale as an approximation of the “true pregnancy rate”.
There was no information about the degree of bias of apparent pregnancy rate in humpback whale. However,
the apparent pregnancy rate estimated from commercial whaling data showed the same yearly trend as in thefin whale and was considered to vary in response to changes in abundance or density. Thus, apparent
pregnancy rate was also used for humpback whale as an approximation of the ‘true pregnancy rate’.
In the case of the Antarctic minke whale, a substantial degree of bias appears to occur in the estimation of
apparent pregnancy rate. Timing of migration from assumed equatorial breeding areas to Antarctic feedingareas differs according to reproductive status. Whales that conceive earlier in the breeding season tend to
migrate to Antarctic feeding areas earlier (Kato and Miyashita, 1991; Kato, 1995).
Observed apparent pregnancy rate in the Antarctic commercial whaling data was about 0.9 which wasthought to be biased upward from the “true pregnancy rate” of 0.78 (Best, 1982), which was estimated fromcommercial whaling data in breeding areas (Kato, 1991).
It is concluded that the apparent pregnancy rate in Antarctic minke whales might not reflect “true pregnancy
rate”. Therefore in the case of this species the term ‘proportion of pregnant in matured females’ is usedinstead of ‘apparent pregnancy rate’. This ratio is an important parameter to monitor migration strategy,
distribution pattern and feeding environment of Antarctic minke whale, so, this parameter was included in
calculation.

63

1. BIOLOGICAL PARAMETERS USED IN THIS STUDY.
1) Apparent pregnancy rate (APR) (humpback and fin whales): ratio of pregnant whales in total mature
female samples.
2) Proportion of pregnant in matured female (PPF) (Antarctic minke whale): Same statistic as “apparent
pregnancy rate”.
3) Age at sexual maturity (ASM): Mean TP (Transition Phase) value in each year class.
2. METHOD
Sample sizes required for examining statistically significant trends in the regression lines (applied to thevalue of biological parameters in each year), were calculated. Details of these calculations are shown in the
appendix. Initial value and rate of change in APR and PPF were deduced from JARPA samples andknowledge from past commercial whaling data. Frequency of year-classes samples of females was deduced
from 1999/2000-2003/04 (for 6 years research period) and 1993/94-2003/04 (for 12 years research period)
JARPA samples collected in south of 62S in Area IV. Variance of error was deduced from linear regression
analysis conducted to female of 1971-1990 year classes collected by JARPA survey in 1987/88-2003/04 in
Area IV.
3. SAMPLE SIZE REQUIRED FOR STATISTICAL EXAMINATION OF YEARLY TREND IN
THE PPF AND APR
3.1 Yearly trend of PPF in the Antarctic minke whale.
The PPF calculated from past commercial whaling data in the period of 1971/72-1986/87 and JARPA sample
in the period of 1987/88-1999/2000 in Areas IV and V stabled around 90% and slight increasing anddecreasing trend was observed in Area V in commercial whaling data and JARPA samples, respectively,
although the trends were not significant (Fig. 1) (Zenitani et al. 2001).
3.2 Yearly trend of APR in humpback and fin whale,
The number of mature and pregnant females (classified by reference to body length and presence of fetus) of
humpback and fin whale was extracted from the International Whaling Statistics (IWS). APR was calculated
from these data (Fig. 2).
APR in humpback whale increased from about 30% in the early 1930’s to 70% in the 1960’s with large
yearly variation. Rate of increase was calculated as 3.95%/year in the period 1933/34-1937/38 and1.30%/year in the period 1949/50-1962/63.
APR in fin whale showed the same trend as in humpback whale. In this case APR increased from 30% to
50% in the 1930’s and increased again from the end of WW2 to about 60% in the late 1950’s. From that dateto the 1970’s it remained stable. Rate of increase was calculated as 2.46%/year in the period of 1930/311939/40 and 1.78%/year in the period of 1946/47-1957/58. Gambell (1973) conducted similar analysis for
Antarctic fin whales and reported an increasing trend of APR during pre-war years and post-war years.
From the observed past yearly trend of PPF in Antarctic minke whales and APR for humpback and fin
whales, the initial values and rates of change needed to calculate sample size were set as follows:
Initial rate (PPF)：

80%、90%Initial rate (APR)：

30%, 40%, 50%, 60%, 70%

Rate of change：

1.0%/year、1.5%/year、2.0%/year、2.5％/year、3.0%/year

3.3 Sample size of mature females required for statistical examination of yearly trends.
The calculated sample size of mature females required for statistical examination of yearly trends are shownin Table 1.

64

3.4 Correction coefficientTo calculate required total sample size, sample size of mature female should be divided according to
expected ratio of mature female in total samples. Sexual and maturity composition of Antarctic minke
whales collected in south of 62S in Areas IV and V in the 1989/90-2003/04 JARPA survey and of humpbackand fin whales taken in past commercial whaling in Antarctic is shown in Figs. 3-1, 3-2 and 3-3, respectively.
Correction coefficient was calculated as 3.00 for Antarctic minke whale, 2.91 for humpback whale and 2.72
for fin whale.
3.5 Calculation of total sample size
3.5.1 Total sample size required for statistical examination of yearly trend of PPF in Antarctic minke whale
Calculated total sample size is shown in Table 2. As explained above, PPF of Antarctic minke whale isabout 90% at this stage and it is important to detect the start of decreasing. Sample size required forstatistical examination of yearly trend at the rate of 1.0-1.5%/year in 6-years research period was calculated
as follows.
Rate of change = -1.0%/year→

Sample size = 1617

Rate of change = -1.5%/year→

Sample size = 663

3.5.2 Total sample size required for statistical examination of yearly trend of APR in humpback and fin
whales
3.5.2.1 CALCULATED SAMPLE SIZE OF HUMPBACK WHALE

Sample size required for statistical examination of yearly trend in 12-years research period was calculated asfollows, considering APR as 30-70% and yearly rate of change as 1.5-3.0%/year (Table 3).
APR = 30%→

Sample size = 41-160

APR = 50%→

Sample size = 56-181

APR= 70%→

Sample size = 41-160

3.5.2.2 CALCULATED SAMPLE SIZE OF FIN WHALE

Sample size required for statistical examination of yearly trend in 12-year research period was calculated asfollows, considering APR as 30-60% and yearly rate of change as 2.0-2.5%/year (Table 4).
APR = 30%→

Sample size = 55-107

APR = 50%→

Sample size = 69-99

APR = 60%→

Sample size = 63-99

4. SAMPLE SIZE REQUIRED FOR STATISTICAL EXAMINATION OF YEARLY TREND OF ASM

4.1 Yearly trend of ASM in Antarctic minke and fin whales
Yearly trend of ASM (estimated from TP) was studied in Antarctic minke whale using past commercial
whaling data and JARPA samples. ASM in females decreased from the 1945 year class to the 1970 year
class and the rate of change was calculated as 0.2/year (Fig. 4) (Kato, 1987). Stable or slightly increasing
trend was found from the 1970’s using JARPA samples (Zenitani and Kato, 2005).
A decreasing trend in ASM in females was also found in fin whales from commercial whaling data. Age atsexual maturity decreased from 10-14 years old in the 1930’s year classes to 6-10 years old in the 1960’s
year classes (Lockyer, 1979) and rate of change was calculated as about 0.1/year (Fig.5).
Yearly trend of ASM was not available for humpback whales because when the ear plug was demonstrated
to be useful for age determination in this species in the mid 1950’s, the level of catches of humpback whale
had already decreased substantially.
From the observed yearly trend of ASM, the rate of change needed to calculate sample size was set as
follows.
Rate of change: 0.05/year, 0.10/year, 0.15/year, 0.20/year65

4.2 Calculation of sample size of target year class required for statistical examination of yearly trendof ASM.
ASM was calculated till the 1990 year class based on JARPA samples. Frequency of recent 6 year classes
was deduced from frequency of 1985-1990 year classes in samples collected in south of 62S in Area IV in
the 1999/2000-2003/04 JARPA survey. Frequency of recent 12 year classes was also deduced by the samemanner, from frequency of 1979-1990 year classes in samples collected in south of 62S in Area IV in the
1993/94-2003/04 JARPA survey. Variance of error from regression line was deduced from regression
analysis conducted to 1971-1990 year classes of females collected in Area IV by 1987/88-2003/04 JARPA
surveys.
Calculated sample sizes for 6-years research period and 12-years research period is shown in Table 5.
4.3 Correction coefficientTo calculate the required total sample size, sample size of target year classes should be divided according to
expected ratio of target year classes in the total samples.
Collection coefficient for 6-years research period was deduced from ratio of 1985-1990 year classes offemales in the samples collected in south of 62S in Area IV during 1999/2000-2003/04 JARPA surveys(Fig.6-1; 25.7). Collection coefficient for 12-years research period was also deduced by the same manner,from ratio of 1979-1990 year classes of females in the samples collected in south of 62S in Area IV during
1993/94-2003/04 JARPA surveys (Fig. 6-2; 16.2).
As for fin whale, no data was available about year class composition in the total samples. Correction
coefficient calculated for Antarctic minke whale was used for fin whale as an approximation.
4.4 Total sample size required for statistical examination of yearly trend of ASM
The calculated total sample size is shown in Table 6.
4.4.1 Calculated sample size of Antarctic minke whale
As explained above, rate of change in ASM observed in Antarctic minke whale from commercial data and
JARPA sample was about 0.20/year and stable around zero or slightly increasing in recent year class. It is
not plausible that the change starts in the rate of 0.2/year, rather it seems to start more slowly. Then therequired total sample size for statistical examination of yearly trend of ASM in 6-years research period,
assuming initial rate of change as 0.10/year, was calculated as 1288 in each research year.
4.4.2 Calculated sample size of fin whale
As explained above, rate of change in ASM observed in fin whale from commercial whaling data was about
0.1/year. The required total sample size for statistical examination of yearly trend of ASM in 12-years
research period was calculated as 131 samples in each research year for that rate of change.
5. REFERENCES
Best, P. B. 1982. Seasonal abundance, feeding, reproduction, age and growth in minke whale off Durban(with incidental observations from the Antarctic). Rep. Int. Whal. Commn 32: 759-786.
Gambell, R. 1973. Some effects of exploitation on reproduction in whales. J. Reproduct. Fert., Suppl. 19:
533-553.
Kato, H. 1987. Density dependent changes in growth parameters of the southern minke whale. Sci. Rep.
Whales Res. Inst. 38: 47-73.
Kato, H. 1995. Migration strategy of southern minke whales to maintain high reproductive rate. In Blix, A.
S., Walloe, L. and Ultang O. (Ed.) Whales, seals, fish and man. Elsevier Science: 465-480.
Kato, H. and Miyashita, T. 1991. Migration strategy of southern minke whales in relation to reproductive
cycle estimated from foetal length. Rep. Int. Whal. Commn 41: 363-369.
Masaki, Y. 1979. Yearly change of the biological parameters for the Antarctic minke whale. Rep. Int. Whal.
Commn 29: 375-395

66

Lockyer, C. 1972. The age at sexual maturity of the southern fin whale (Balaenoptera physalus) using annual
layer counts in the ear plug. J. Cons. Int. Explor. Mer. 34(2): 276-294.
Lockyer, C. 1979. Changes in a growth parameter associated with exploitation of southern fin and sei whales.
Rep. Int. Whal. Commn 29: 191-196.
Lockyer, C. 1984. Review of baleen whale (Mysticeti) reproduction and implications for management. Rep.
Int. Whal. Commn (Special Issue 6): 27-50.
Zenitani, R., Kato, H. and Fujise, Y. 2001. Year to year trends of some biological parameters of Antarctic
minke whales from the viewpoint of population monitoring. Paper SC/53/IA13 presented to the IWC
Scientific Committee, July 2001 (unpublished). 16pp.
Zenitani, R. and Kato, H. 2005. Long-term trend of age at sexual maturity of Antarctic minke whales bycounting transition phase in earplugs. Paper JA/J05/PJR7 presented to the JARPA Review meeting, Tokyo,
Jan. 2005 (unpublished). 12pp.

67

Table 1. Sample size of mature females required for statistical examination of yearly trend.
Rate of change
Research
InitialperiodRate(%)+1% -1% +1.5% -1.5% +2% -2% +2.5% -2.5% +3%30%1060 944462
438
256 259
162
175
111
40%
1175 1118
519
507
291 292
186
192
130
50%
1195 1195
534
534
303 303
197
197
139
60%
1118 1175
507
519
292 291
192
186
138
6 years70%
944 1060
438
462
259 256
175
162
131
80%
674
848
328
363
206 197
154
123
134
90%
304
539
203
221
116
70
30%
126
99
55
50
31
35
20
39
14
40%
136
122
61
58
35
36
23
26
17
50%
135
135
62
62
36
36
25
25
19
60%
122
136
58
61
36
35
26
23
23
12 years
70%
99
126
50
55
35
31
39
20
80%
63
104
43
44
24
15
90%
71
29
15
9
-

-3%
131
138
139
130
111
83
46
23
19
17
14
10
6

Table 2. Total sample size of Antarctic minke whales required for statistical examination of yearly trend.
Rate of change
Research
InitialperiodRate(%)+1% -1% +1.5% -1.5% +2% -2% +2.5% -2.5% +3% -3%80%2022 2544
984
1089 618 591
462
369
402 249
6 years90%
912 1617 609
663
348
210
138
80%
189
312
129
132
72
45
30
12 years
90%
213
87
45
27
18

Table 3. Total sample size of humpback whales required for statistical examination of yearly trend .
Rate of change
Research
InitialperiodRate(%)+1% -1% +1.5% -1.5% +2% -2% +2.5% -2.5% +3% -3%30%3083 2746 1344 1274 745 754
472
509
323 38140%3417 3252 1510 1475 847 850
541
559
379 402
6 years
50%3475 3475 1553 1553 882 882
573
573
405 40560%
3252 3417 1475 1510 850 847
559
541
402 37970%2746 3083 1274 1344 754 745
509
472
381 32330%
367
288
91 102
59
114
160
146
41
40%
396
355
102 105
67
76
178
169
50
67
12 years
50%
393
393
105 105
73
73
181
181
56
56
60%
355
396
105 102
76
67
169
178
67
50
70%
288
367
102 91
114
59
146
160
41
Table 4. Total sample size of fin whales required for statistical examination of yearly trend.
Rate of change
Research
InitialperiodRate(%)+1% -1% +1.5% -1.5% +2% -2% +2.5% -2.5% +3%30%2887 2571 1259 1193 698 706
442
477
303
40%
3200 3045 1414 1381 793 796
507
523
355
6 years50%
3255 3255 1455 1455 826 826
537
537
379
60%
3045 3200 1381 1414 796 793
523
507
376
30%
344
270
150
137
39
85
96
55
107
40%
371
333
167
158
47
96
99
63
71
12 years
50%
368
368
169
169
52
99
99
69
69
60%
333
371
158
167
63
99
96
71
63

68

-3%
357
376
379
355
63
52
47

Table 5. Sample size of female whales of recent 6(12) year classes
required for statistical examination of yearly trend of ASM.
Rate of change

Research
period

0.05/year

0.10/year

0.15/year

0.20/year

6 years

199

50

23

13

12 years

30

8

4

2

Table 6. Total sample size required for statistical examination of
yearly trend of ASM.
Rate of change

Research
period

0.05/year

0.10/year

0.15/year

0.20/year

6 years

5125

1288

594

336

12 years

488

131

66

35

69

Fig. 1. PPF of Antarctic minke whales, caught during 1971/72-1986/87 by commercial whaling and 1987/88-2001/02
by JARPA surveys conducted in Areas IV and V (From Zenitani et al. (2001)).

5000

y = 3.954x +6.018

80.0

R2 = 0.799

4000

60.0
3000

1949/50-1962/63

2000

y = 1.303x +29.82

40.0

2

R = 0.240

20.0

1000

12000

1974/75

1971/72

1968/69

1965/66

1962/63

1959/60

1956/57

1953/54

1950/51

1947/48

1944/45

1941/42

100.0

Fin

10000

1938/39

1935/36

1932/33

0.0
1929/30

0Number of mature female

100.0

Apparent pregnancy rate

1930/31-1939/40

1946/47-1957/58

y = 2.459x +20.12

y = 1.782x +5.238

R2 = 0.757

R2 = 0.877

8000

80.0
60.0

6000
40.0
4000
20.0

2000

1974/75

1971/72

1968/69

1965/66

1962/63

1959/60

1956/57

1953/54

1950/51

1947/48

1944/45

1941/42

1938/39

1935/36

1932/33

0.0
1929/30

0Apparent pregnancy rate (%)

Number of mature female

Humpback

1933/34-1937/38

Apparent pregnancy rate (%)

Number of mature female

6000

Fig. 2. APR of humpback and fin whales caught in Antarctic Ocean (Data extracted from International Whaling
Statistics).

70♂:Imm♂:M at♀:Imm♀:M at

8.4

33.3

19.3

34.4

Fig. 3-1. Sexual and maturity
composition of Antarctic minke whales
taken by JARPA surveys in 1989/902003/04 in south of 62゜S

12.2

36.7

♂:Imm
♂:M at♀:Imm♀:M at

38.2

24.9

43.7
14.6

♂:Imm
♂:M at♀:Imm♀:M at12.9

21.4

Fig. 3-2. Sexual and maturity compositionof humpback whales taken by commercial
whaling in 1930/31-1965/66 in Antarctic.

Fig. 3-3. Sexual and maturity composition of
fin whales taken by commercial whaling in
1929/30-1975/76 in Antarctic.

in Antarctic Areas IV and V.

(Data extracted from International Whaling
Statistics)(Data extracted from International Whaling
Statistics)

Correction coefficient

Correction coefficient

Correction coefficient=100/33.3 =3.00=100/34.4=2.91= 100/36.7=2.72

Regression line fitted to 1945-1970 year classes(Weight by sample size)
Male: Age at sexual maturity = 22.15-0.219t
Female: Age at sexual maturity = 21.64-0.206t(From Kato (1987))

Fig. 4. Yearly trend of ASM in Antarctic minke whale (From Kato (1987)).

71

Area IV
0.10/year

0.075/year

Yearly rate of change from 1920’s to1960’s year classArea V
0.085/year

Fig. 5. Yearly trend of ASM in female fin whales (From Lockyer (1979)).

M ale
Female: Immature & TP unreadable
Female: Other year class
Female: Recent 6 year class

3.9

17.6

M ale
Female: Immature & TP unreadable
Female: Other year class
Female: Recent 12 year class

6.2
9.2

44.5
32.6

52.0

34.0

Fig. 6-1. Ratio of recent 6 year classes in the total
whales sampled in south of 62゜S in Area IV during
1999/2000-2003/04 JARPA surveys.

Fig. 6-2. Ratio of recent 12 year classes in the total
whales sampled in south of 62゜S in Area IV during
1993/94-2003/04 JARPA surveys.

Correction coefficient

Correction coefficient=100/3.9=25.7=100/6.2=16.2

72

Appendix:

Estimation of sample size
This appendix explains the method of estimation of required sample size to test whether a significant increase or
decrease of biological parameters is observed at the 5% level (i.e. to test if the slope of the regression is significantly
different from 0 at the 5% level). For some biological parameters, not all samples are used for the analysis. Therefore
estimated minimum simple size should be divided by the ratio of the sample size used for the analysis to overall
samples.

In order to estimate increasing/decreasing rate per year of variable y per year during a years (In case of age at sexual
maturity (Transition Phase (TP)), a year-classes) using samples collected bienniary, we consider a regression model
following;y i = β 0 + β 1 xi

（i=1,･･･,m）(1)where, m is the number of data to fit to the regression model. Then, upper and lower bound of the confidence interval
are expressed byβˆ1 ± t (0.025, m − 2) Vˆ ( βˆ1 )(2)where, β̂ 1 is estimator of β1（i.e. level of the change per year we intend to detect）, Vˆ ( βˆ1 ) is estimated variance ofβ̂ 1 and t (0.025, m − 2) is upper 2.5%-ile of t-distribution of m –2 degrees of freedom. For simplicity, in thiscalculation, it is assumed t (0.025, m − 2) ≒1.96 because t-distribution is asymptotically normal distribution. Vˆ ( βˆ1 )can be expressed by the formulaσˆ 2Vˆ ( βˆ1 ) =(3)∑i =1 ( xi − X ) 2mwhere, σ̂ is residual mean square and X is estimated mean of x among the samples. From here, the formulation isdifferent for the case of TP and that of APR and PPF. Therefore we separate the description into each case.
2< PPF/ APR >In this case, m=a/2, xi = 2i − 1 and variance-covariance matrix for estimated value of APR/PPF ( p xi ) is as follows.

 p1 (1 − p1 )01
1
V= Ω= 
n
n L

0


0
p3 (1 − p3 )
L
0

L
L
L
L

0


0


L

p 2 m −1 (1 − p 2 m −1 )

(4)

In the case that generalized least-squares estimate β̂ 1 >0, if βˆ1 − 1.96 V ( βˆ1 ) > 0 , would be significantly different
from 0. Therefore, required sample size n can be estimated by solving inequality with respect to n following, which isderived from formulas (4).
2

 1.96  cn > 
ˆ  22
β
 1 

[

t

−1

In this case, ｃ２２ means element of matrix X Ω X

].
−1

73

(5)

 1 x1 
X = L L  1 x m 
In the case that β̂ 1 <0, the inequality (5) would be derived, similarly.
Substituting the values to the formula (5), required sample size can be estimated.

＜Age at sexual maturity estimated by transition phase (TP)＞As for TP, because compositions of year-classes are different by year, samples should be appropriately weighted toestimate value of the denominator of formula (3)∑ ( x − X ) . For a=6, we calculated a weighted
m

i =1

2

i

∑ ( x − X ) for 1985-1990 year-classes from samples collected in south of 62S in Area IV during 1999/20002003/04 JARPA surveys. For a=12, we calculated a weighted ∑ ( x − X ) for 1979-1990 year-classes from
m

i =1

2

i

m

2

i =1

i

samples collected in south of 62S in Area IV during 1993/94-2003/04 JARPA surveys. The following paragraph shows
how samples are weighted by sample size.

Setting njk as the number of samples of year-class k caught in year j and nj as the total sample size of a year-classes
caught in year j, the denominator of formula (3) is∑ (x − X ) = ∑ ∑ n (x − X )
m

2

i =1

i

b

a

j =1

k =1

j ,k

2

k

b
a  n j ,k ( x − X ) 2= ∑ j =1 n j ∑k =1  n  k j where b is the number of years when survey is conducted. For simplicity, assuming that the number of samples of yearclass a (nj) and composition of the numbers of samples by year-class (njk/nj) is constant every year, this formula became nk 

∑ ( x − X ) = bn∑  n ( x − X )
m

2

i =1

a

k =1

i

2

(6).

k

Substituting the right hand side of formula (6) to denominator of formula (3),V ( βˆ1 ) =σˆ 2a  n bn ∑ k =1  k  ( x k − X ) 2
 n 

(3)’’

Similar to the derivation of the formula (5), from this formula,2

 1 .96 σˆ 2n > ˆ 
 β 1  b ∑ a  n k  ( x − X ) 2
k
k =1
 n 
is derived ( b nk 

(7)∑  n ( x − X ) =7.7 for a=6 and 51.1 for a=12).
a

2

k =1

k

Residual mean square ( σˆ ) was deduced from regression analysis conducted to 1971-1990 year classes class (theperiod of which distinct yearly change in TP had not occurred) of females collected in Area IV by 1987/88-2003/04
JARPA surveys. By substituting this figure toσ2 in formula (7), the required sample size can be calculated.
2

Similarly, required sample size can be estimated in the case of other parameters.

74

Appendix 7
Sample size of Antarctic minke whale for the purpose ofmonitoring yearly trend of blubber thickness
KENJI KONISHI, TAKASHI HAKAMADA AND TSUTOMU TAMURAThe Institute of Cetacean Research, 4-5, Toyomi-cho, Chuo-ku, Tokyo 104-0055, Japan
Contact e-mail: konishi@cetacean.jp

We calculated the required sample size of the Antarctic minke whale to examine the yearly trend of blubber
thickness in the Antarctic. This calculation is explained in detail by Bando et al. (in Appendix 6) which tests
whether there is significant trend of blubber thickness at the 5 % level for 6 years periods. For thiscalculation, we used mature males and pregnant females (not lactating) sampled at southward of 62°S by
JARPA. Because the blubber thickness is highly affected by the feeding period, samples taken at the end of
the feeding season (February) were used.
The change of blubber thicknesses per year were estimated as approximately 0.05 cm for both mature males
and pregnant females, using JARPA data in Area IV (Figs. 1 and 2). The calculated sample sizes for eachmature male and pregnant female in February were 123 and 145, respectively. The correction coefficients(inverse numbers of each sexual stage proportion in total samples collected at southward of 62°S in Area IV
from 1999/2000 to 2003/04) used to estimate entire sample sizes from the sample sizes of each sexual
maturity group in February were 7.90 and 5.64, respectively (Bando and Zenitani, unpublished). Using these
correction coefficients, total sample sizes for mature male and pregnant female in entire survey season werecm

calculated as 972 and 818, respectively.

5.0
4.8
4.6
4.4
4.2
4.0
3.8
3.6
3.4
3.2
3.0

y = -0.04747x + 4.135288

87/88

91/92

95/96

99/00

03/04

year

Fig. 1. Trend of blubber thickness of mature male in Area IV (southward of 62S) in February.

75

cm

5.0
4.8
4.6

y = -0.04771x + 4.541568

4.4
4.2
4.0
3.8
3.6
3.4
3.2
3.0
87/88

91/92

95/96

99/00

03/04

year

Fig. 2. Trend of blubber thickness of pregnant female in Area IV (southward of 62S) in February.

76

Appendix 8
Sample size required for genetic mark-recapture method tomonitor population trend
NAOHISA KANDA
The Institute of Cetacean Research, 4-5, Toyomi-cho, Chuo-ku, Tokyo 104-0055, Japan
Contact e-mail: kanda@cetacean.jp

INTRODUCTION
Mark-recapture method has been used in whale studies to estimate population abundance and to examine
migration pattern. Such studies in recent years have utilized biopsy sampling and molecular genetic markers.
Use of the biopsy samples, however, is not very practical because the amount of effort involved to obtainlarge number of sample size is excessive. In order to compensate the deficiency, paternity testing in catcheson the basis of DNA profiles of mother-fetus pairs and those of matured males genotyped from a set of
microsatellite markers is more effective. Suspected fathers for the fetus are looked for, and such matchings
combined with the traditional mark-recapture analysis such as the Petersen method can be used to estimate
population abundance and to monitor population trend (e.g., Skaug and Øien, 2004). Attempts with thisapproach may be also used to describe stock structure and migration pattern.
Here we calculated sample size required to conduct the above approach in JARPAII for the Antarctic minke
whales from the Area IV+V west .
METHODS
Biological information: The number of matured males and fetus in future JARPAII samples were projectedfrom the data obtained during the JARPA averaged over the eight seasons (Table 1). The number of fetus
was equaled the number of pregnant females.
Mark-recapture method: In this analysis, the total number of mature males genotyped in a sample formed thefirst capture sample, the total number of fetus genotyped formed the second capture, and the total number offather-fetus matchings formed the recapture. It is then important to note that this method estimate maleabundance in the population. Petersen mark-recapture method modified by Chapman (1951) was used toinfer male abundance (Nm):
Nm = {(M+1)(C+1) / (R+1)}-1,
with variance,
V(Nm) = (M+1)(C+1)(M-R)(C-R) / (R+1)(R+1)(R+2),
where, for the Antarctic minke whales analysis, M is the number of the captured mature males, C is the total
number of genotyped fetus, and R is the number of fetus in C that matched to the fathers in M.
These three parameters were then replaced with the reproductive information given in Table 2 that also
incorporate sample size, S, such as M=0.462S and C=0.243S. R depends on matching percent, so that
R=0.243S (matching percent).
The minke whale abundance in this area was estimated to be on average approximately 100,000 (102,292:
63,971 to 170,047) from the number of sightings between 1990/91 to 2002/03 seasons (Hakamada et al.,2005; T. Hakamada, personal communication). Applying the biological information we used (% mature

77

males in the total sample), this population abundance indicates that the male abundance in this area isslightly below 50,000.
RESULTS AND DISCUSSION
Table 2 shows the samples size from 400 to 1000 with four different matching percent (1.0, 1.5, 2.0, and2.5%) giving different levels of abundance estimates and coefficient of variation (CV). As expected, single
year samplings provide lower abundance and higher CV than when the samples were pooled for threeseasons obtained from six years research. Hereafter, we consider only the latter.
Biological information we used (i.e., M and C in the equation) and the male abundance we have (50,000)
were thought to be the most reliable among the all parameters we used because these values were obtained
from the large amount of data of the JARPA. The calculations showed that in order to have the maleabundance of about 50,000 the combinations of % matching-sample size should be 1%-1200, 1.5%-1800,
2%-2400, and 2.5%-3000. In other word, with male abundance estimate of about 50,000, we expect to see
the % matching from 1% to 2.5% with sample size from 400 to 1000. These % matchings are comparable to
the reported values in the similar studies (e.g., Skaug and Øien, 2004). In Norway, similar approach was
conducted to the Atlantic minke whales in their DNA register. From four matchings with reasonablestatistical power from the DNA profiles of 288 mother-fetus pairs compared to the total of 3301 registeredminke whales yielded five true fathers expected in the Norwegian DNA database.
The key issue that would influence our approach, however, is the number of microsatellite loci in thepaternity analysis part of the method. Currently, up to 10 loci has been used for individual identification in
the Antarctic minke whales in our institution, which is similar to Skaug and Øien (2004). The effort willthen apply to increase the number of the loci for the analysis in order to have better resolution and higher
statistical power. In addition, DNA profiles of the fathers estimated from the mother-fetus pairs is partial, sothat likelihood function of the paternity will be required to evaluate the statistical confidence of the paternity(Marshall et al., 1998). It is also important to note that, even with increased number of maker loci, we might
not have any matchings in our samples if the population abundance is much higher than previously estimated.
CONCLUSION
Considering that we will conduct long-term monitoring of trends in population abundance, values of Nm
estimated in future based on the method we are proposing need to be higher confidence, i.e., Nm with low
CV. This indicates the sample size of 800-1000 per year will be suitable.
REFERENCES
Chapman, D.G. (1951) Some properties of he hypergeometric distribution with applications to zoologicalsample censuses. University of California Publications in Statistics 1: 131-160.
Hakamada, T., Matsuoka, K., and Nishiwaki, S. (2005) An update of Antarctic minke whales abundance
estimate based on JARPA data including comparison to IDCR/SOWER estimates. Paper JA/J05/PJR4
presented to the JARPA Review meeting, January 2005.
Marshall, T.C., Slate, J., Kruuk L.E.B., and Pemberton, J.M. (1998) Statistical confidence for likelihoodbased paternity inference in natural populations. Molecular Ecology 7: 639-655.
Skaug, H. and N. Øien (2004) Genetic tagging of males in North Atlantic minke whales throughcomparison of mother and fetus DNA-profiles. SC/56/SD3

78

Table 1. Biological information of Antarctic minke whales from Area IV+VW obtained from JARPA surveys.

Biological information
JARPA season
89/90-90/91
91/92-92/93
93/94-94/95
95/96-96/97
97/98-98/99
99/00-00/01
01/02-02/03
Average

MT
48.9
56.3
68.4
56.7
58.8
56.4
46.7
56

Males
MMM
89.7
83.9
83.2
81.5
77.4
80.3
80.6
82.4

MMT
43.9
47.2
56.9
46.2
45.5
45.3
37.6
46.2

FT
51.1
43.7
31.6
43.3
41.2
43.6
53.3
44

Females
PFF
64
62.4
44.2
61.1
36.5
57.1
62
55.3

PFT
32.7
27.3
14
26.5
15
24.9
33.1
24.3

Abbreviations: MT = Proportion of males in total sample, MMM = Proportion of matured males in total males, MMT =Proportion of matured males in total sample, FT = Proportion of females in total sample, PFF = Proportion of pregnant
females in total females, PFT = Proportion of pregnant females in total females.

Table 2. Sample sizes (S) and coefficient of variance (CV) for abundance estimates calculated from Petersen markrecapture method modified by Chapman (1951) with different matching %. SD = standard deviation, and see text forother abbreviations (M, C, R, Nm).

S

M

Single year sampling
C
R
Nm

SD

400
600
800
1000

184.8 97.2
277.2 145.8
369.6 194.4
462.0 243.0

1.0
1.5
1.9
2.4

CV
S
M
1.0% matching
9251 5285 0.571
1200 554.4
16614 8821 0.531
1800 831.6
24597 12243 0.498
2400 1108.8
32935 15481 0.470
3000 1386.0

400
600
800
1000

184.8 97.2
277.2 145.8
369.6 194.4
462.0 243.0

1.5
2.2
2.9
3.6

7422 3915
12814 6159
18491 8213
24320 10088

400
600
800
1000

184.8 97.2
277.2 145.8
369.6 194.4
462.0 243.0

1.9
2.9
3.9
4.9

6197
10428
14814
19278

3049
4608
5989
7226

400
600
800
1000

184.8 97.2
277.2 145.8
369.6 194.4
462.0 243.0

2.4
3.6
4.9
6.1

5318
8791
12357
15967

2460
3611
4610
5495

1.5% matching
0.5281200 554.4
0.481
1800 831.6
0.444
2400 1108.8
0.415
3000 1386.0
2.0% matching
0.4921200 554.4
0.442
1800 831.6
0.404
2400 1108.8
0.375
3000 1386.0
2.5% matching
0.463
1200 554.4
0.411
1800 831.6
0.373
2400 1108.8
0.344
3000 1386.0

79

Three seasons pooled
C
R
Nm
291.6
437.4
583.2
729.0

SD

CV

2.9
4.4
5.8
7.3

41498
67921
94897
122135

18526
26651
33607
39724

0.446
0.392
0.354
0.325

291.6 4.4
437.4 6.6
583.2 8.7
729.0 10.9

30239
48275
66510
84834

11810
16282
20029
23294

0.391
0.337
0.301
0.275

291.6 5.8
437.4 8.7
583.2 11.7
729.0 14.6

23786
37444
51195
64987

8348
11228
13621
15700

0.351
0.300
0.266
0.242

291.6 7.3
437.4 10.9
583.2 14.6
729.0 18.2

19602
30582
41613
52665

6292
8327
10012
11475

0.321
0.272
0.241
0.218

Appendix 9
Effect on the stock of the catches during JARPA II
TAKASHI HAKAMADAThe Institute of Cetacean Research, 4-5, Toyomi-cho, Chuo-ku, Tokyo 104-0055, Japan
Contact e-mail: hakamada@cetacean.jp

The possible effects of an annual take of 850 minke whales (425 males and 425 females) during JARPA II
on Eastern Indian Ocean stock (I-stock) and Western South Pacific stock (P-stock), respectively, areexamined by using Hitter Methodology. Further, the possible effects of an annual take of 50 humpback
whales (25 males and 25 females) from Areas IV and V alternatively on Western Australian Stock (D-stock)and Eastern Australian Stock (E-stock), respectively, are also examined by using population dynamics modelin Johnston and Butterworth (2005).
MATERIALS AND METHODSMinke whale
Based on the knowledge on stock structure, it is assumed a scenario that there is one stock in west of 165oE(I-stock) and another in east of 165oE (P-stock), respectively and that I-stock and P-stock are mixing between
130 oE and 175 oE. Table 2 shows previous catches by sex from I-stock and P-stock, respectively. Survey will
be conducted in 35 oE-175 oE in the first year and in 130 oE-145 oW in the second year. Survey will be
conducted in each area every two years alternately. Therefore, animals will be taken in 130 oE-175 oE every
year, where the two stocks are assumed to be mixing. As for sex ratio of minke whales to be harvested in the
future, we have assumed that it will be 1:1. A standard scenario as for future catches is as follows. Assumingthat the number of animals taken and mixing rate in 130 oE-175 oE is almost same in the first year and thesecond year, the number of animals taken from P-stock in the first year and the number of animals from Istock in the second year would be almost same. For example, assuming approximately 284 (=850/3) animals
are taken in 130 oE-175 oE every year and that mixing rate of I-stock is 50% in this sector, from I-stock, 708
animals would be taken in the first year and 142 in the second year and, from P-stock, 142 animals would betaken in the first year and 708 animals in the second year. Therefore, it is assumed that 850 animals are takenfrom I-stock and P-stock every two years, alternately, as a standard catch scenario. As sensitivity test withrespect to future catches, the case that animals in 130 oE-175 oE are from I-stock is also examined. Because aratio of averaged abundance in western part of Area V (130 oE -165oE) estimated from 1996/97–2002/03
JARPA to that in 130 oE –145 oW is about 1/3. It can be assumed that 850 animals (425 males and 425
females) are taken from I-stock in the first year and 284 animals (142 males and 142 females) are taken in
the second year. Future catches assumed in standard scenario and in sensitivity test are shown in Table 3.
As for abundance estimate, two scenarios are assumed. One is assumption that 192,653 (CV=0.192) in Istock and 212,258 (CV=0.152) in P-stock based on estimates from CPII in Branch and Butterworth (2001).
The other is 228,349 (CV=0.092) in I-stock and 95,116 (CV=0.168) based on the latest abundance estimate
from JARPA in 2001/02 and 2002/03 (Hakamada et al., 2005). It is also assumed that g(0)=0.611 (Okamura
et al., in press). The case where the abundances are assumed to be the 90% lower limit for the estimate has
been also investigated as in past examinations for impacts on the stock using the Hitter methodology.
Humpback whale
The population dynamics model described in Johnston and Butterworth (2005) is used to examine the effectof the catches during JARPA II on the D-stock and E-stock. In the first year, 50 animals are planned to betaken from Area IV and 50 animals from Area V in the second year. The survey will be conducted in thisway in each area every two years alternately. The previous catches from Areas IV and V in the south of 40oS
are shown in Table 4. The previous catches from D-stock and E-stock in the breeding ground (North of 40oS)
are shown in Table 5. Future catches assumed in this study are shown in Table 6.

81

Population dynamics model used in this study is following. Population dynamics model in breeding ground
is

N

B,D
y +1

N

B,E
y +1

=N

B,D
y

D

+r N

B,D
y

  N B , D  2.39   y  D
1 −  D   − C y  K  

(1)

=N

B,E
y

+r N

B,E
y

  N B , E  2.39   y  E
1 −  E   − C y  K  

(2)

E

where NyB,D and NyB,E are the number of whales D-stock and E-stock in the breeding area at the start of year
y, respectively, rD and rE are the intrinsic growth rate (the maximum per capita the population can achieve,
when its size is very low) for D-stock and E-stock, respectively, KD and KE are the carrying capacity of Dstock and E-stock, respectively and CyD and CyE are the number of catches from D-stock and E-stock at thestart of year y. Taking possibility of mixing of D-stock and E-stock animals in feeding area into account,population dynamics model in feeding area is

N yF , IV = αN yB , D + (1 − β )N yB , E(3)N yF ,V = (1 − α )N yB , D + βN yB , E(4)where NyF,Ⅳ and NyF,Ⅴ are abundances in Areas IV and V at the start of year y, α is the population of Dstock which feeds in Area IV and βis the population of E-stock which feeds in Area V. Catches in Areas IV
and V are allocated in the proportion of abundance for D-stock and E-stock in these Areas.
Information on abundance used to estimate intrinsic growth rate and initial population size of the stocks in
Johnston and Butterworth (2005) are relative abundance estimates in breeding area (IWC, 1996; Brown et al.,1997), CPUE data in breeding area (Chittleborough, 1965), Abundance estimates in feeding area from
JARPA (Matsuoka et al., 2005), Abundance estimate in breeding area (Bannister and Hedley, 2001;Brown etal., 1997) and Abundance estimates in feeding area from IWC/IDCR-SOWER (Branch and Butterworth,
2002). The abundance estimates from JARPA are treated as a relative index of abundance in this study sameas Johnston and Butterworth (2005). These figures are shown in Table 7 – 11.
By fitting the models described above to abundance data, Johnston and Butterworth (2005) obtained
estimates rD =0.122, rE =0.126, KD =16,879, KE =33,857, α=0.944 and β=0.671. These estimates are usedin this study.
RESULTS AND DISCUSSIONSMinke whale
For each option, depletions in 1987/88 (when commercial whaling ceased), in 2005/06 (present), in 2011/12(after 6 times of surveys) are shown. For reference, depletion after 30 years is also shown.
As shown in Table 12, both for best estimate and for 90% lower limit, even if MSYR(1+)=1%, abundance
would show increasing trend when 850 whales are taken every year from 2005/06. For P-stock, abundance
keeps nearly carrying capacity.
Table 13 shows results of sensitivity test. This table shows similar results in Table 13 and suggests no ill
effect of the catches on the I-stock and P-stock.
Therefore, it can be concluded that there would be no negative effect on the minke whale stocks of thesefuture catches.

82

Humpback whaleFigs. 1 and 2 show that population trajectories relative to initial population size for D-stock and E-stock,
respectively. For comparison, the population trajectories in the case of 0 future catch are also shown. As both
Figs. show, there is little difference among the trajectory for 50 annual caches and that for 0 future catches.
Therefore, it can be concluded that there is no negative effect on the humpback whale stocks.
REFFERENCE

Bannister, J. L. and Hedley, S. L. 2001. Southern hemisphere Group IV humpback whales: their status fromrecent aerial survey. Mem. Qld. Mus. 47(2):587-598.
Branch, T. A. and Butterworth, D. S. 2001. Southern Hemisphere minke whales: standardised abundance
estimates from the 1978/79 to 1997/98 IDCR-SOWER surveys. J. Cetacean Res. Manage. 3:143-174.
Branch, T. A. and Butterworth, D. S. 2002. Estimates of abundance south of 60OS for cetacean species
sighted frequently on the 1978/79 to 1997/98 IWC/IDCR-SOWER sighting surveys. J. Cet. Res. Manage.
3(3):251-270
Brown, M. R., Field, M. S., Clarke, E. D., Butterworth, D. S. and Bryden, M.M. 1997. Estimates ofabundance and rate of increase for East Australian humpback whales from the 1996 Landbased survey at
Point Lookout, North Stradbroke Island, Queensland. Document SC/49/SH35 submitted to the IWC
Scientific Committee, 15pp.
Chittleborough, R. G. 1965. Dynamics of two populations of the humpback whale, Megaptera Novaeanglae(Borowski). Aust. J. Mar. Freshw. Res. 16:33-128.
Hakamada, T., Matsuoka, K. and Nishiwaki, S. 2005. An update of Antarctic minke whales abundance
estimate based on JARPA data including comparison to IDCR/SOWER estimates. Document JA/J05/JR4
submitted to JARPA review meeting January 2005 (unpublished).
International Whaling Commission. 1996. Report of the Sub-Committee on Southern Hemisphere baleen
whales, Annex E. Rep. Int. Whal. Commn. 46:117-138.
Johnston, S. J. and Butterworth, D. S. 2005. Assessment of the west and east Australian breeding populationsof Southern Hemisphere humpback whales using a model that allows for mixing on the feeding grouds andtaking account of the most recent abundance estimates from JARPA. Document JA/J05/JR19 submitted to
JARPA review meeting January 2005 (unpublished).
Matsuoka, K., Hakamada, T. and Nishiwaki, S. 2005. Distribution and abundance of humpback whales in the
Antarctic Areas IIIE, IV, V and VIW (35OE-145OW) Document JA/J05/JR10 submitted to JARPA review
meeting January 2005.
Okamura, H., Kitakado, T. and Mori, M. An improved method on line transect sampling in the Antarctic
minke whales survey. (unpublished).
Pastene, L. A., Goto, M., Kanda, N., Bando, T., Zenitani, R., Hakamada, T., Otani, S. and Fujise, Y. 2005. A
new interpretation of the stock identity in the Antarctic minke whale based on analyses of genetics and nongenetics markers. Document JA/J05/JR3 submitted to JARPA review meeting January 2005 (unpublished).

83

Table 1. Abundance estimates used in this study.
surveyI-stock

P-stock

IWC-IDCR

192,653 (CV=0.162) in 1987/88

212,258 (CV=0.152) in 1988/89

JARPA

228,349 (CV=0.142) in 2002/03

95,116 (CV=0.168) in 2002/03

Table 2. Previous catches (1955/56-2004/05) by sex from I-stock and P-stock. We assume all samples aretaken from I-stock and P-stock, respectively, because 2004/05 JARPA haven’t completed yet.

year
1955
1956
1957
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004

I-stock
P-stock
Male Female Male Female
1
1
0
0
0
0
0
0
208
273
0
0
18
24
0
0
76
99
0
0
33
39
31
43
1
0
1
0
9
10
0
0
81
20
3
3
2
3
0
0
1
0
4
3
7
2
1
4
390
211
0
1
108
39
2
2
85
53
7
4
120
82
0
0
1222
1965
0
0
2911
2780
0
0
2161
3855
10
3
1769
2622
0
0
1620
2156
18
13
2272
3669
0
0
1117
2477
357
249
1454
2660
73
52
2228
2636
2
4
1740
2969
336
591
1383
2705
644
183
1619
3357
287
489
1466
2297
148
399
944
2060
294
90
805
1752
302
98
692
1895
129
285
154
119
0
0
0
0
86
155
185
144
0
0
99
90
65
73
165
123
0
0
110
96
57
67
200
130
0
0
85
55
115
75
273
167
0
0
59
68
146
167
279
159
0
0
116
68
131
74
233
206
0
0
86
55
172
127
201
239
0
0
51
49
184
156
200
240
0
0
220
220
220
220

84

Table 3. Assumed future catches from I-stock and P-stock under standard scenario and sensitivity test,
respectively.
standard scenario

year
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
2033
2034

sensitivity test

I-stock
P-stock
Male Female Male Female
425
425
0
0
0
0
425
425
425
425
0
0
0
0
425
425
425
425
0
0
0
0
425
425
425
425
0
0
0
0
425
425
425
425
0
0
0
0
425
425
425
425
0
0
0
0
425
425
425
425
0
0
0
0
425
425
425
425
0
0
0
0
425
425
425
425
0
0
0
0
425
425
425
425
0
0
0
0
425
425
425
425
0
0
0
0
425
425
425
425
0
0
0
0
425
425
425
425
0
0
0
0
425
425
425
425
0
0
0
0
425
425
425
425
0
0
0
0
425
425

year
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
2033
2034

85

I-stock
P-stock
Male Female Male Female
425
425
0
0
142
142
283
283
425
425
0
0
142
142
283
283
425
425
0
0
142
142
283
283
425
425
0
0
142
142
283
283
425
425
0
0
142
142
283
283
425
425
0
0
142
142
283
283
425
425
0
0
142
142
283
283
425
425
0
0
142
142
283
283
425
425
0
0
142
142
283
283
425
425
0
0
142
142
283
283
425
425
0
0
142
142
283
283
425
425
0
0
142
142
283
283
425
425
0
0
142
142
283
283
425
425
0
0
142
142
283
283
425
425
0
0
142
142
283
283

Table 4.

The catches of humpback whales from Areas IV and V in the south of 40oS
Year
1904
1905
1906
1907
1908
1909
1910
1911
1912
1913
1914
1915
1916
1917
1918
1919
1920
1921
1922
1923
1924
1925
1926
1927
1928
1929
1930
1931
1932
1933
1934
1935
1936
1937
1938
1939
1940
1941
1942
1943
1944
1945
1946
1947
1948
1949
1950
1951
1952
1953
1954

Area IV
0
0
0
0
217
118
83
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
11
0
0
159
82
593
1,340
938
1,435
832
835
0
0
0
0
0
0
0
0
1
11
725
1,208
958
224
310
379

Area V
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
4
0
0
24
0
0
0
0
0
0
0
0
0
74
1,308
998
487
723
1,121
2,615

Year
1955
1956
1957
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004

86

Area IV
844
27
545
1,661
66
779
468
2,352
289
92
76
172
98
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0

Area V
157
182
1,159
3,182
13,159
9,847
1,936
291
322
71
266
112
27
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0

Table 5. The previous catches of humpback whales in the breeding ground (in the north of 40oS)
Year
1904
1905
1906
1907
1908
1909
1910
1911
1912
1913
1914
1915
1916
1917
1918
1919
1920
1921
1922
1923
1924
1925
1926
1927
1928
1929
1930
1931
1932
1933
1934
1935
1936
1937
1938
1939
1940
1941
1942
1943
1944
1945
1946
1947
1948
1949
1950
1951
1952
1953
1954

D-stock
0
0
0
0
0
0
0
0
296
670.5
1968
1430
0
0
0
0
0
0
155
166
0
669
735
996
1033
0
0
0
0
0
0
0
3072
3242
917
0
0
0
0
0
0
0
0
2
4
193
388
1224
1187
1300
1320

E-stock
0
0
0
0
0
0
0
0
296
670.5
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
78
110
18
44
52
57
69
55
75
80
107
86
71
90
88
107
110
101
92
141
79
111
721
809
898

Year
1955
1956
1957
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004

87

D-stock
1126
1119
1120
967
737
573
587
548
87
1
5
28
12
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0

E-stock
832
1013
1025
1023
1278
1341
981
209
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0

Table 6. Assumed future catches of humpback whales from Areas IV and V

Year
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
2033
2034

Area IV
0
0
50
0
50
0
50
0
50
0
50
0
50
0
50
0
50
0
50
0
50
0
50
0
50
0
50
0
50
0

88

Area V
0
0
0
50
0
50
0
50
0
50
0
50
0
50
0
50
0
50
0
50
0
50
0
50
0
50
0
50
0
50

Table 7. Relative abundance estimates in D-stock (IWC, 1996) and E-stock (Brown et al, 1997)year

D-stock

1982

10.2

1986

16.7

1988

12.7

1991

23.6

1994

36.0

year

E-stock

1981

381

1982

493

1986

1008

1987

879

1991

1533

1993

1807

1996

2872

Table 8. CPUE data off the west and east coast of Australia (Chittleborough, 1965).
year

west（D-stock）

1950

0.475

1951

0.424

1952

0.347

1953

0.353

0.972

1954

0.351

0.755

1955

0.244

0.779

1956

0.178

0.704

1957

0.146

0.714

1958

0.123

0.750

1959

0.090

0.740

1960

0.062

0.522

1961

0.055

0.230

1962

0.051

0.069

east（E-stock）

89

Table 9. JARPA estimates of abundance of humpback whales in feeding Areas IV and V (Matsuoka et al., 2005).
year

Area IV

1989/903873

1991/92

5203

1993/94

2740

1995/968850

1997/9810874

1999/2000

16211

2001/0233010

2003/04

31750

year

Area V

1990/91

767

1992/933837

1994/953567

1996/971543

1998/99

8301

2000/01

4720

2002/03

2735

Table 10. Estimates of breeding ground abundance of humpback whales used in the modelstock

abundanceyear

sourceD-stock

8000

1999

Bannister and Hedley (2001)

E-stock

3200

1996

Brown et al. (1997)

Table 11. Estimates of abundance of humpback whales south of 60oS from the IWC/IDCR-SOWER sighting surveys.
year

circumpolar surveys

Area IV

Area V

1978/79

I

1039

-

1980/81I-

966

1985/86

II

-

568

1988/89

II

3375

-

1991/92

III

-

2066

90

Table 4. Effects on the Antarctic minke whales of 850 animals (425 males and 425 females) from I-stock and P-stock
every two years alternately using Hitter Methodology.

I-stocka.

Assuming that abundance estimate from IDCR in CPII.

i) Hit 1987/88 total (1+) population of 315,245 (best estimate)

Statistic
K (1+)
Depletion - 1987
Depletion - 2005
Depletion - 2011
Depletion - 2035
RY - 2005
MSY (+1)

1
386,992
81.5%
85.2%
86.4%
90.3%
831
2,322

2
373,212
84.5%
91.6%
93.2%
96.6%
1,125
4,479

MSYR (1+) (%)
3
4
362,490 354,130
87.0%
89.0%
95.2%
97.1%
96.4%
97.9%
98.3%
98.9%
1,112
988
6,525
8,499

5
347,580
90.7%
98.1%
98.6%
99.2%
850
10,427ii) Hit 1987/88 total (1+) population of 228,741(90% lower limit)

Statistic
K (1+)
Depletion - 1987
Depletion - 2005
Depletion - 2011
Depletion - 2035
RY - 2005
MSY (+1)

1
301,953
66.7%
75.8%
77.5%
83.3%
777
1,812

2
288,992
67.0%
82.4%
85.3%
92.5%
1,125
3,468

MSYR (1+) (%)
3
4
278,628 270,336
67.4%
67.8%
87.1%
90.3%
90.2%
93.0%
95.5%
96.6%
1,161
1,055
5,015
6,488

91

5
263,684
68.3%
92.4%
94.6%
97.1%
915
7,911

(Table 4 continued)b.

Assuming that latest abundance estimate from JARPA.

Statistic
K (1+)
Depletion - 1987
Depletion - 2005
Depletion - 2011
Depletion - 2035
RY - 2005
MSY (+1)

1
432,578
76.8%
84.0%
85.3%
89.6%
848
2,595

2
407,798
76.8%
88.6%
90.6%
95.2%
1,123
4,894

MSYR (1+) (%)
3
4
393,825 386,084
77.2%
77.7%
91.8%
93.9%
93.8%
95.6%
97.0%
97.7%
1,099
971
7,089
9,266

5
381,742
78.4%
95.2%
96.6%
98.0%
834
11,452i) Hit 2002/03 total (1+) population of 373,655 (best estimate)

Statistic
K (1+)
Depletion - 1987
Depletion - 2005
Depletion - 2011
Depletion - 2035
RY - 2005
MSY (+1)

1
339,807
70.4%
78.9%
80.5%
85.8%
805
2,039

2
315,157
69.8%
84.3%
87.0%
93.3%
1,127
3,782

MSYR (1+) (%)
3
4
300,402 291,880
69.9%
70.3%
88.4%
91.3%
91.2%
93.7%
95.9%
96.9%
1,146
1,033
5,407
7,005

ii) Hit 1990 total (1+) population of 278,082 (90% lower limit)

925286,997
71.0%
93.2%
95.2%
97.3%
892
8,610

(Table 4 continued)
P-stocka. Assuming that abundance estimate from IDCR in CPII.
a) Hit 1988/89 total (1+) population of 347,324 (best estimate).

Statistic
K (1+)
Depletion - 1987
Depletion - 2005
Depletion - 2011
Depletion - 2035
RY - 2005
MSY (+1)

1
351,999
98.1%
98.2%
97.4%
95.7%
160
2,112

MSYR (1+) (%)
2
3
4
351,079 350,363 349,802
98.1%
98.1%
98.1%
98.6%
98.9%
99.1%
97.9%
98.2%
98.3%
96.7%
97.2%
97.5%
184
188
185
4,213
6,307
8,395

5
349,361
98.2%
99.2%
98.4%
97.7%
180
10,481b) Hit 1988/89 total (1+) population of 255,322 (90% lower limit)

Statistic
K (1+)
Depletion - 1987
Depletion - 2005
Depletion - 2011
Depletion - 2035
RY - 2005
MSY (+1)

1
260,005
97.4%
97.6%
96.5%
94.2%
160
1,560

2
259,089
97.4%
98.2%
97.1%
95.5%
184
3,109

MSYR (1+) (%)
3
4
258,373 257,812
97.5%
97.5%
98.5%
98.7%
97.5%
97.7%
96.2%
96.6%
188
185
4,651
6,187

93

5
257,370
97.5%
98.9%
97.8%
96.9%
180
7,721

(Table 4 continued)b. Assuming that latest abundance estimate from JARPA.
a) Hit 2002/03 total (1+) population of 155,641 (best estimate).

Statistic
K (1+)
Depletion - 1987
Depletion - 2005
Depletion - 2011
Depletion - 2035
RY - 2005
MSY (+1)

1
160,047
95.8%
96.1%
94.3%
90.4%
159
960

2
158,361
95.8%
97.0%
95.3%
92.6%
184
1,900

MSYR (1+) (%)
3
4
157,422 156,875
95.8%
95.9%
97.5%
97.9%
95.9%
96.2%
93.8%
94.4%
188
185
2,834
3,765

5
156,539
95.9%
98.1%
96.4%
94.9%
181
4,696

b) Hit 2002/03 total (1+) population of 112,042 (90% lower limit)

Statistic
K (1+)
Depletion - 1987
Depletion - 2005
Depletion - 2011
Depletion - 2035
RY - 2005
MSY (+1)

1
116,492
94.2%
94.6%
92.1%
86.6%
158
699

2
114,801
94.2%
95.8%
93.5%
89.7%
184
1,378

MSYR (1+) (%)
3
4
113,849 113,293
94.2%
94.3%
96.6%
97.1%
94.3%
94.7%
91.3%
92.2%
189
186
2,049
2,719

94

5
112,952
94.3%
97.4%
95.0%
92.9%
181
3,389

Table 5. Results of sensitivity test with respect to future catches. It is assumed that 284 animals (142 males and 142
females) are taken from I-stock and 566 (283 males and 283 females) from P-stock, instead of 850 animals from Pstock, during surveys in 130oE –145oW.

I-stocka. Assuming that abundance estimate from IDCR in CPII.
i) Hit 1987/88 total (1+) population of 315,245 (best estimate)

Statistic
K (1+)
Depletion - 1987
Depletion - 2005
Depletion - 2011
Depletion - 2035
RY - 2005
MSY (+1)

1
386,992
74.1%
81.9%
82.9%
86.8%
831
2,322

2
373,212
74.6%
87.3%
89.1%
93.6%
1,125
4,479

MSYR (1+) (%)
3
4
362,490 354,130
75.1%
75.7%
90.9%
93.2%
92.7%
94.7%
95.8%
96.7%
1,112
988
6,525
8,499

5
347,580
76.2%
94.7%
95.8%
97.0%
850
10,427ii) Hit 1987/88 total (1+) population of 228,741(90% lower limit)

Statistic
K (1+)
Depletion - 1987
Depletion - 2005
Depletion - 2011
Depletion - 2035
RY - 2005
MSY (+1)

1
301,953
66.7%
75.8%
77.0%
81.7%
777
1,812

2
288,992
67.0%
82.4%
84.9%
91.1%
1,125
3,468

MSYR (1+) (%)
3
4
278,628 270,336
67.4%
67.8%
87.1%
90.3%
89.7%
92.5%
94.4%
95.5%
1,161
1,055
5,015
6,488

95

5
263,684
68.3%
92.4%
94.1%
96.0%
915
7,911

(Table 5 continued)b.

Assuming that latest abundance estimate from JARPA.

Statistic
K (1+)
Depletion - 1987
Depletion - 2005
Depletion - 2011
Depletion - 2035
RY - 2005
MSY (+1)

1
432,578
76.8%
84.0%
85.0%
88.5%
848
2,595

2
407,798
76.8%
88.6%
90.3%
94.3%
1,123
4,894

MSYR (1+) (%)
3
4
393,825 386,084
77.2%
77.7%
91.8%
93.9%
93.4%
95.2%
96.2%
96.9%
1,099
971
7,089
9,266

5
381,742
78.4%
95.2%
96.2%
97.3%
834
11,452i) Hit 2002/03 total (1+) population of 373,655 (best estimate)

Statistic
K (1+)
Depletion - 1987
Depletion - 2005
Depletion - 2011
Depletion - 2035
RY - 2005
MSY (+1)

1
339,807
70.4%
78.9%
80.1%
84.4%
805
2,039

MSYR (1+) (%)
2
3
4
315,157 300,402 291,880
69.8%
69.9%
70.3%
84.3%
88.4%
91.3%
86.5%
90.7%
93.2%
92.1%
94.8%
95.9%
1,127
1,146
1,033
3,782
5,407
7,005

ii) Hit 2002/03 total (1+) population of 278,082 (90% lower limit)

965286,997
71.0%
93.2%
94.7%
96.4%
892
8,610

(Table 5 continued)
P-stocka.

Assuming that abundance estimate from IDCR in CPII.

a) Hit 1988/89 total (1+) population of 347,324 (best estimate).

Statistic
K (1+)
Depletion - 1987
Depletion - 2005
Depletion - 2011
Depletion - 2035
RY - 2005
MSY (+1)

1
160,047
95.8%
96.1%
95.1%
93.1%
159
960

MSYR (1+) (%)
2
3
4
158,361 157,422 156,875
95.8%
95.8%
95.9%
97.0%
97.5%
97.9%
96.2%
96.8%
97.1%
95.0%
95.8%
96.3%
184
188
185
1,900
2,834
3,765

5
156,539
95.9%
98.1%
97.3%
96.6%
181
4,696

b) Hit 1988/89 total (1+) population of 255,322 (90% lower limit)

Statistic
K (1+)
Depletion - 1987
Depletion - 2005
Depletion - 2011
Depletion - 2035
RY - 2005
MSY (+1)

1
116,492
94.2%
94.6%
93.3%
90.4%
158
699

2
114,801
94.2%
95.8%
94.7%
93.0%
184
1,378

MSYR (1+) (%)
3
4
113,849 113,293
94.2%
94.3%
96.6%
97.1%
95.5%
96.0%
94.2%
94.8%
189
186
2,049
2,719

97

5
112,952
94.3%
97.4%
96.2%
95.3%
181
3,389

(Table 5 continued)b.

Assuming that latest abundance estimate from JARPA.

Statistic
K (1+)
Depletion - 1987
Depletion - 2005
Depletion - 2011
Depletion - 2035
RY - 2005
MSY (+1)

1
160,047
95.8%
96.1%
94.7%
91.8%
159
960

2
158,361
95.8%
97.0%
95.8%
93.9%
184
1,900

MSYR (1+) (%)
3
4
157,422 156,875
95.8%
95.9%
97.5%
97.9%
96.3%
96.7%
94.9%
95.4%
188
185
2,834
3,765

5
156,539
95.9%
98.1%
96.9%
95.8%
181
4,696

a) Hit 2002/03 total (1+) population of 155,641 (best estimate).

Statistic
K (1+)
Depletion - 1987
Depletion - 2005
Depletion - 2011
Depletion - 2035
RY - 2005
MSY (+1)

1
116,492
94.2%
95.1%
92.7%
88.7%
158
699

MSYR (1+) (%)
2
3
4
114,801 113,849 113,293
94.2%
94.2%
94.3%
96.2%
97.0%
97.5%
94.1%
94.9%
95.4%
91.4%
92.8%
93.6%
184
189
186
1,378
2,049
2,719

b) Hit 2002/03 total (1+) population of 112,042 (90% lower limit)

98

5112,952
94.3%
97.8%
95.7%
94.1%
181
3,389

Fig. 1. D stock population trajectories relative to initial population size K in the case of 0 future catch and in the caseannual 50 catches from Areas IV and V alternatively.
Fig. 2. E stock population trajectories relative to initial population size K in the case of 0 future catch and in the case of

D stock
1.2
10.8
N/K 0.6
0.4

0
50

0.2
0
1900

1950

2000

2050

year
annual 50 catches from Areas IV and V alternatively.

E stock
1.2
10.8
N/K 0.6
0.4

0
50

0.2
0
1900

1950

2000
year

99

2050