Technical Reports of the Institute of Cetacean Research (2017)

pp. 22–27

Technical Report (not peer reviewed)

Laboratory and analytical approaches to estimate biologicalparameters in the Antarctic minke whale and summary of results
Takeharu Bando*
Institute of Cetacean Research, Toyomi-cho 4–5, Chuo-ku, Tokyo 104–0055, Japan*Contact e-mail: bando@cetacean.jp

ABSTRACTLife history-related biological parameters in marine mammals such as age at sexual maturity and pregnancy
rate are known to change in response to changes in abundance, food availability or competition among species. Therefore, monitoring of biological parameters and investigations of how these parameters change withtime are important information for whale stock assessment and management. This paper presents an outlineof the laboratory and analytical approaches used to estimate biological parameters in large whales and a summary of biological parameters estimated for the Antarctic minke whales based on JARPA and JARPAII biologicalsamples.

INTRODUCTION
Biological parameters such as age at sexual maturity
and pregnancy rate are directly correlated to reproduction of whale stocks. Information on sex ratio and age
at sexual maturity is necessary to assess the proportionof whales which contribute to reproduction; fetus sex
ratio and litter size is information necessary to estimate
the composition of young whales which recruit into thestock. Some of these parameters are known to change
in response to changes in abundance, food availability orcompetition among whale species (Gambell, 1973; Kato,
1986a, 1986b, 1987; Kato and Sakuramoto, 1991; Masaki,
1979; Lockyer, 1972, 1979, 1984a). Therefore, monitoringof biological parameters is indispensable for assessment
and sustainable management of whale stocks (Ohsumi
et al. 1997).
The Antarctic minke whale Balaenoptera bonaerensis
is one of the smallest Balaenopterid species with bodylength generally less than 10 m. Antarctic minke whales
are widely distributed in the Southern Hemisphere, migrating seasonally between feeding grounds in the Antarctic in summer (south of 60°S) and breeding grounds
in the tropical or temperate regions in winter (Perrin
and Brownell, 2009). The Antarctic minke whale was
exploited by commercial whaling in the decades of the1970ʼs and 1980ʼs, until the moratorium on commercial
whaling was implemented in the 1987/88 austral summer season. Given their large abundance, this species is atarget of possible future commercial whaling operations
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in the Antarctic.
Previous estimates of biological parameters of Antarctic minke whale were based on samples collected during
the commercial whaling period (Ohsumi et al., 1970;
Ohsumi and Masaki, 1975; Best, 1982; Kato, 1982, 1983,
1987; Masaki, 1979). However samples from commercial
whaling are not representative of the stock as whaling operations targeted large individuals concentrated aroundthe ice edge. Therefore biological parameters such as
the age at sexual maturity estimated from those samples
were thought to be biased (Kato, 1982, 1987).
The Japanese Whale Research Program under Special
Permit in the Antarctic (JARPA) was conducted between
the seasons 1987/88 and 2004/05. The main objectiveof JARPA was the estimation of biological parameters
to improve the management of Antarctic minke whales.
Relevant samples and data to estimate several biological parameters were collected systematically throughout
the 18-year research period. Under the JARPA, tracklines were designed in each stratum established in the
research area independently and random sampling was
conducted to ensure representativeness of samples toaccurately estimate biological parameters. Similar procedures were used in the second phase of JARPA (JARPAII).
The International Whaling Commissionʼs Scientiﬁc
Committee (IWC SC) had recommended previously arecalculation of biological parameters of Antarctic minke
whale by biological stock (IWC, 1998). Since then, stock
structure analyses of Antarctic minke whale were reﬁned, and a new stock structure hypothesis proposing an

Laboratory and analytical approaches to estimate biological parameters in the Antarctic minke whale and summary of results

ʻEastern Indian Ocean Stock (I-stock)ʼ (distributed mainly
between 35°–130°E) and a ʻWestern South Paciﬁc Stock(P-stock)ʼ (distributed mainly between 165°E–145°W) in
the Antarctic Ocean, was proposed. Pastene and Goto
(2016) presented the latest genetic analyses in support ofthis hypothesis.
This paper presents an outline of the laboratory andanalytical approaches to estimate biological parametersof large whales and a summary of biological parameters
estimated for the Antarctic minke whales.

MATERIALS AND METHODSThis section summarizes the sampling and analytical procedures used by diﬀerent authors for estimating several
biological parameters in the Antarctic minke whale.
Age determination based on earplugs
One of the most important information obtained by
JARPA and JARPAII was the age of the whales, which was
obtained by examining the internal earplugs of whales.
Sampling at the ﬁeld
The left and right earplugs were collected carefully byresearchers at the ﬁeld, which were immediately ﬁxed in
10% formalin.
Laboratory work
At the laboratory, individual age was determined bycounting growth layers appearing on the bisected surfaceof the earplug using a stereoscopic microscope, assuming
an annual deposition of growth layers (i.e. one pair ofdark and pale laminae accumulated per year) (Figure 1)(Lockyer, 1984b).
Calibration work
The inter-reader variability has been evaluated undersuggestions and guidance from the IWC SC. After such
evaluation, the estimated ages with this variability was in-

Figure 2.

corporated into the Statistical Catch-At-Age (SCAA) analysis (IWC, 2012; Kitakado et al., 2013; Punt et al., 2014),
which was conducted to estimate the historical andcurrent population trajectories of the stocks as well thenatural mortality rates by age classes in the Antarctic
minke whale (see below).
The ages of whales with unreadable earplugs havebeen estimated by applying an age-length-key for the
purposes of the SCAA. In more recent years the racemization technique was developed for the Antarctic
minke whale (Yasunaga et al., 2017) and therefore thistechnique can provide age estimation for unreadable earplugs, which in turn will improve the SCAA performance.
Sexual maturity determination
Sampling at the ﬁeld
Testes samples of about 1.5 cm square were collectedfrom testes from the right side and immediately ﬁxed in
10% formalin. Ovaries from both sides were collected andpreserved at −20°C for later analyses.
Laboratory work
Sexual maturity of males was determined by examinationof histological samples of testes stained by hematoxylineosin. Males with seminiferous tubules over 100 µm
diameter, spermatid or open lumen in the tubules were
determined as sexually mature (Figure 2) (Kato, 1986a;
Kato et al., 1990, 1991). Sexual maturity for females was

Figure 1.

Earplug of Antarctic minke whale.

Histological testis sample of immature (left) and mature (right) Antarctic minke whales.
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Technical Reports of the Institute of Cetacean Research (2017)

determined by the presence of corpora luteum (CL) or
albicans (CA) in both ovaries (Lockyer, 1984a) (Figure 3).
Physical maturity
Sampling at the ﬁeld
Physical maturity status was identiﬁed by examinationof vertebrae. The fusion of the vertebral epiphysis to thecentrum was known to start at the anterior cervical, thenat the posterior caudal vertebrae, and is completed on
the middle or posterior dorsal vertebrae (Kato, 1988). A
part of the 6th dorsal vertebra which contains cartilage
between centrum and anterior epiphysis was collected
and ﬁxed in the 10% formalin solution.
Laboratory work
Physical maturity was determined by examination of thevertebrae stained by 0.25% toluidine blue-O solution.
Cartilage between epiphyses and centrum was observed
by naked eye or stereoscopic microscope. Whales withthe epiphyses fused to the centrum were deﬁned asphysically mature (Figure 4) (Kato, 1988).

Figure 3.

Y = 1+ e (aX +b ) −1

where Y is the proportion mature at age/body length X,
and a and b are empirical parameters. Age/body length at
50% maturity was calculated as −ba−1.
Age at physical maturity
Age at 50% physical maturity was estimated by logistic
regression analysis based on maximum likelihood. This is
the same as the method for estimation of the age at 50%

Ovary of Antarctic minke whales with corpora lutea (left) and corpora albicantia (right).

Figure 4.
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Age/length at sexual maturity
Body length and age at sexual maturity was estimated by
two methods. The ﬁrst is the body length and age at ﬁrst
ovulation (Lmov, tmov) (Kato, 1987). Under this method
the mean body length and age were calculated for thewhales with one corpus luteum and no corpus albicans
in both ovaries.
The second method is the body length and age at 50%
sexual maturity (Lm50%, tm50%) (Kato, 1987). Under
this method the body length and age at 50% maturity
was estimated by logistic regression analysis based on
maximum likelihood. The logistic model was ﬁtted to age/body length and sexual maturity rate as:

Vertebra of physically immature (left) and mature (right) Antarctic minke whale.

Laboratory and analytical approaches to estimate biological parameters in the Antarctic minke whale and summary of results

sexual maturity (tm50%).
Growth curve
The von Bertalanﬀy growth model was ﬁtted to the bodylength and age as:(

Lt = L∞ 1 − e− K (t −t0 ))where Lt is the body length at age t, L ∞ is asymptotic
length, K is the growth rate coeﬃcient and t0 is the theoretical time at zero length.
Proportion of pregnant whales in matured females (PPF)
PPF is deﬁned as the proportion of pregnant females
within the sexually matured females.
Annual ovulation rate
Annual ovulation rate was estimated by applying linear
regression analysis between age and total number ofcorpora (CL and CA). Only individuals after the 1970 cohort were used because of the reported decline of age
at sexual maturity (determined from transition phase in
ear plug) from the 1940s to the 1960s cohorts (Kato and
Sakuramoto, 1991; Thompson et al., 1999). The regression line was ﬁtted to age 10 and 30 because almost all
animals are mature at the age of 10 and sample size was
not large enough for ages over 30.
Fetal sex ratio and litter size
Presence or absence of fetus was identiﬁed by cutting
both sides of the uterus horn. Fetus sex was identiﬁedby the appearance of the genital organ. Small fetuses ofwhich sex could not be identiﬁed were excluded from theanalysis.
Natural mortality via SCAA
Natural mortality was estimated by the Statistical Catchat-Age (SCAA) model (Punt et al., 2014). Individual age,abundance and catch history information were incorporated in the SCAA model and age dependent natural
mortality was estimated (Punt et al., 2014).

SUMMARY OF RESULTS
Biological parameters of Antarctic minke whales on stockbasis (Pastene and Goto, 2016) are presented in Table 1.
Both stocks presented similar values for age at sexual andphysical maturity. In both stocks the values were smaller
in males than females.
Remarkable diﬀerences between stocks were found inbody length at sexual maturity (Lmov, Lm50%) and in theasymptotic length calculated from growth curves, which
was about 20 cm larger in I-stock than P-stock for both
sexes. The PPF of both stocks was as high as about 0.9 andannual ovulation rate supported the high pregnancy rate
in both stocks. The fetus sex ratio is almost parity for bothstocks and multiplets are rare in this species.
Age dependent natural mortality was estimated from
SCAA. The pattern was similar between the two stocks
with natural mortality being higher in young and old animals. It was calculated as 0.048 (for age=15) to 0.107 (forage=35) for the I-stock and 0.046 (for age=15) to 0.103

Table 1
Summary of biological parameters of Antarctic minke whales estimated from 1987/88 to 2004/05 JARPA samples.
I-stock (35°E–130°E)

P-stock (165°E–145°W)

Male

FemaleMale

FemaleLt =8.60(1−e−0.272(t+1.97))

Lt =9.16(1−e−0.228(t+2.19))

Lt =8.44(1−e−0.269(t+2.08))

Lt =8.97(1−e−0.203(t+2.90))

16.9

20.8

16.9

20.6

GrowthGrowth curve
Age at physical maturity

50%mature

Sexual maturity
Age at sexual maturity

tmov
tm50%

Body length at sexual
maturity (m)

7.6
5.3

Lmov
Lm50%

7.6

8.5
5.4

8.39 m7.28 m8.20 m8.1
8.32 m

7.14 m

7.99 mReproductive characteristics
Proportion of pregnant inmatured female (%)

92.1%

Annual ovulation rate
Foetal sex ratio
Litter size

87.7%

0.989/year
52.1%

47.9%
1.002

1.005/year
46.8%

53.2%
1.013

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Technical Reports of the Institute of Cetacean Research (2017)

Figure 5.

Time-trajectories of total (1+) population size
(upper panels), age-speciﬁc natural mortality(center panels), and total (1+) population size relative to carrying capacity (lower panels) for three
ways to model natural mortality (the Siler model,
autoregressive and piecewise linear) of two stocksof Antarctic minke whale (from Punt et al., 2014).
Biological data obtained from both JARPA and
JARPAII were used in the SCAA.

(for age=35) for P-stock (Figure 5) (Punt et al., 2014).
Time-trajectories derived from SCAA showed that total
population size of Antarctic minke whale increased until
1970ʼs and then declined until 2000ʼs for both stocks (Figure 5) (Punt et al., 2014).

DISCUSSION
At present examination of earplugs is the only practicablemeans to obtain age data at the annual scale. The earplug
has proved to be a valid and useful tool for age determination (Lockyer, 1984b), and is the only method providing
age data accurate enough for population-level analyses
such as the SCAA of Antarctic minke whales. Because
there are a number of whales sampled with unreadable
earplugs, the feasibility of other ageing techniques isbeing investigated by ICR scientists such as that based on
enantiomers of aspartic acid in eye lens, which are measured using high performance liquid chromatography (Yasunaga et al., 2017) and the DNA methylation approach
which was applied to humpback whale (Polanowski
et al., 2014). Potentially these techniques could complement the age information obtained from earplugs.
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Age and other reproductive data obtained by JARPA
and JARPAII enabled the estimation of important biological parameters in the Antarctic minke whale, which
are signiﬁcant for assessment and management of thisspecies in the Antarctic. Of particular importance was
the estimate of age-speciﬁc natural mortality rate (Puntet al., 2014) in this species, which was one of the main
research objectives of JARPA.
Another important aspect was that the estimation of
biological parameters was made on the basis of biologicalstocks and not on the basis of politically-based geographical boundaries. It was found that some biological parameters diﬀered between stocks.
Some of the biological parameters are known tochange in response to changes in abundance, food availability or competition with other species (Gambell, 1973;
Lockyer, 1979; Kato, 1986b, 1987). Monitoring of biological parameters is useful for understanding of the present
status of stocks and to predict future trends, which areessential for sustainable management of whale stocks.
Moreover, information on biological parameters is useful
to improve the performance of the Revised Management
Procedure (RMP).

ACKNOWLEDGEMENTS
Sincere thanks are due to all researchers and crews who
participated in the JARPA/JARPAII surveys.

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