SC/F14/J04

Estimates of abundance and abundance trend of the
humpback whale in Areas IIIE-VIW, south of 60ºS, basedon JARPA and JARPAII sighting data (1989/90-2008/09)
TAKASHI HAKAMADA and KOJI MATSUOKA
Institute of Cetacean Research, 4-5 Toyomi-cho, Chuo-ku, Tokyo 104-0055, Japan
Contact e-mail:hakamada@cetacean.jp

ABSTRACT
Sighting surveys data from the Japanese Whale Research Program under Special Permit in the Antarctic(JARPA) and its second phase (JARPA II) are analyzed to obtain abundance estimates for humpback whales(Megaptera novaeangliae) in Areas IIIE-VIW, south of 60°S. The surveys were conducted during the
1989/90–2008/09 austral summer seasons (mainly in January and February), alternating between western andeastern sectors of the research area each year. Abundance estimates are obtained from standard line transect
analysis methods using the program DISTANCE assuming g(0)=1.

Area
IIIE
IV
V
VIW

First year
Year
Estimate
1995/96
1,378
1989/90
5,325
1990/91602
1996/97
1,493

CV
0.190
0.302
0.343
0.185

Last year
Year
Estimate CV
2007/08 11,904 0.261
2007/08 29,067 0.255
2008/09 13,894 0.338
2008/09
3,609
0.322

These JARPA/JARPAII estimates are similar to estimates obtained from the IDCR-SOWER surveys, whichwere conducted independently for Area IV in 1978/79, 1988/89 and 1998/99 and for Area V in 1980/81,
1991/92 and 2001/02-2003/04. Abundance increased by an estimated 20.8% (95%CI = 4.1 – 37.6%), 13.6%(95% CI = 8.4- 18.7%), 14.5% (95%CI = 7.6 – 21.5%) and 6.2% (95%CI = -0.9 – 13.4%) per year for Areas
IIIE, IV, V and VIW, respectively. These rates in Areas IV and V are also similar to those obtained from the
IDCR-SOWER surveys. Estimated additional variance with CV’s was 0.635 (Area IIIE) 0.328 (Area IV), 0.416(Area V) and 0.036 (Area VIW). Results of several sensitivity tests suggest that estimates of abundance andabundance trends are not appreciably affected by factors such as different approaches to deal with survey
coverage which in some cases was poor or included gaps. The effects of changes in the order in which survey
strata were covered are investigated using a nested GLM approach. A QAIC model selection criterion suggests a
preference for not attempting to adjust for such changes; under various approaches in which an adjustment was
made, point estimates of increase rates were not greatly affected in Areas IV and V. The JARPA+JARPA II
results thus indicate that humpback whales in Area IV and Area V are definitely increasing rapidly.
KEYWORDS: ABUNDANCE ESTIMATE, ANTARCTIC, HUMPBACK WHALE, SURVEY-VESSEL,TRENDSINTRODUCTION
There are several genetic stocks (genetically differentiated populations within a species) of humpback whales in
the Southern Hemisphere. The IWC SC (International Whaling Commission Scientific Committee) has
hypothesized a total of seven breeding stocks, which it has called Stock ‘A’, ‘B’, …’G’. (IWC, 2005). Currently
the IWC SC is working to refine this stock structure hypothesis. A population named Breeding Stock D has its
breeding grounds in the waters off western Australia and in summer is distributed mainly in Area IV, south of 60ºS. Another population named Breeding Stock E has its breeding grounds in the waters off eastern Australia andsome of the south Pacific islands, and in summer is distributed mainly in Area V south of 60ºS.

Humpback whales were heavily exploited during the past century and most of the stocks in the Southern
Hemisphere were substantially depleted. Allen (1980) estimated that at the end of commercial whaling, thestocks of this species had been reduced to 2% of its original population of 130,000 animals. More recent

1SC/F14/J4
evaluations as part of the Comprehensive Assessment of this species have not been finalized, but results
reported up until recently, when summed over the seven breeding stocks, suggest an original abundance of about
125,000 whales reduced to a minimum of about 4% of that number by the mid-1960s (IWC, 2009; Jackson et al.,2008; Johnston and Butterworth, 2005a, 2005b, 2007; Johnston et al., 2008; Zerbini et al, 2008). Fortunately
signs of recovery are now evident for many of these stocks. In particular the population sizes of Stocks D and E
are estimated from the results of low latitude surveys off Australia to be increasing at annual rates of 9.7 %(CV=0.25) (Hedley et al., 2011) and 10.9% (95%CI 10.5%-11.3%) (Noad et al., 2011), respectively. There is
the need for continued monitoring of the abundance and abundance trends of these whale stocks, especiallybecause they provide an excellent opportunity to improve understanding of the dynamics of baleen whale
populations recovering from low levels.

Another source of sighting data for assessing the population status of this species in the Antarctic is the JARPA(Japanese Whale Research Program under Special Permit in the Antarctic) and its second phase (JARPA II).
This Program has been conducted in every one of the 1987/88 to 2008/09 austral summer seasons. After two
seasons of feasibility studies, full-scale research began in 1989/90. The JARPA Program was designed toalternate surveys in Antarctic Areas IV and V in each of the sixteen years of the full-scale research period. The
objectives of the JARPA were: a) elucidation of the stock structure of the Antarctic minke whale Balaenoptera
bonaerensis to improve stock management; b) estimation of biological parameters of the Antarctic minke whale
to improve the stock management; c) elucidation of the role of whales in the Antarctic marine ecosystemthrough whale feeding ecology; and d) elucidation of the effect of environmental change on cetaceans;(Government of Japan, 1987, 1996). In order to address these four objectives, JARPA was comprised of a
combination of sighting and sampling surveys. The objectives of the JARPA II were: 1) Monitoring of the
Antarctic ecosystem, 2) Modelling competition among whale species and future management objectives, 3)
Elucidation of temporal and spatial changes in stock structure and 4) Improving the management procedure for
Antarctic minke whale stocks (Government of Japan, 2005).

Sighting data collected by the SVs (dedicated sighting vessels) and SSVs (sighting and sampling vessels) during
JARPA have been used to estimate abundance and abundance trends of blue whales (Branch et al., 2004) andother large whale species (Kasamatsu et al., 2000; Matsuoka et al., 2005a, b). Abundance estimates for Antarctic
minke and humpback whales were made taking recommendations made at JARPA review meeting (IWC, 2008)
into account (Hakamada et al., in press; Matsuoka et al., 2011) listed in Table 1. Matsuoka et al. (2011)
suggested that the estimated abundance of humpback whales in Area IV has increased rapidly, although there isalso an increase indicated for Area V, it is neither as rapid nor as precisely estimated. Abundance estimates andabundance trends in Areas IV and V are similar to those for IDCR-SOWER surveys (Branch, 2011).

The main objective of this paper is to update humpback whale abundance estimates in Antarctic Areas IIIE, IV,
V and VIW based on JARPA and JARPA II sighting data, taking into account the relevant recommendations
offered by the IWC SC. Approaches in Matsuoka et al. (2011) are applied to JARPA and JARPA II data in order
to examine if the abundance estimates and their trends for humpback whales were changed from previous
analysis by adding the data obtained during JARPA II surveys (2005/06- 2008/09). To facilitate understanding of
the estimation procedures and the interpretation of results, some details of the JARPA and JARPA II survey
procedures are provided below, with further details set out in Appendix 2 of Hakamada et al. (in press).

Sighting surveys to obtain abundance estimates have been carried out in the waters off both western Australia(Bannister and Hedley, 2001; Paxton et al., 2006; Hedley et al., 2011)) and eastern Australia (Noad et al., 2006;2011). A secondary objective of this study is to compare JARPA and JARPA II abundance estimates in thefeeding grounds of Areas IV and V with those in the breeding grounds and migratory corridors in the waters off
both sides of Australia.
Another secondary objective is to compare abundance estimates in Areas IV and V obtained by JARPA withthose obtained by the IDCR (International Decade for Cetacean Research)-SOWER (Southern Ocean Whale andEcosystem Research) research programmes. Under these programmes, dedicated sighting surveys forassessment purposes had been conducted by the IWC in the Antarctic annually from 1978/79 to 1995/96 (IDCR)
and then from 1996/97 to 2009/10 (SOWER) (see overview of IDCR-SOWER surveys in Matsuoka et al., 2003).
One of the features of JARPA is that, unlike the IDCR-SOWER programmes, surveys have been repeated in thesame area and in the same months every second season over a long period. Therefore the JARPA and JARPA II
surveys facilitate both estimation of trends and the extent of inter-year variability in local abundance.

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SURVEY DESIGN AND DATA COLLECTION
As noted above, JARPA and JARPA II were comprised of a combination of sighting and sampling surveys. In
order to obtain biological samples representative of the Antarctic minke whale population, a random sampling
method was adopted within a line transect sighting survey design. The sighting and sampling surveys wereconducted by two or three SSVs proceeding along predetermined tracklines. A dedicated SV was introduced
from the 1991/92 season. The JARPA surveys have been conducted in a generally consistent way every otherseason in both Areas IV and V since the 1989/90 season. There have been eight full-scale surveys in Area IV: inthe 1989/90, 1991/92, 1993/94, 1995/96, 1997/98, 1999/00, 2001/02 and 2003/04 seasons, and eight in Area V:
in the 1990/91, 1992/93, 1994/95, 1996/97, 1998/99, 2000/01, 2002/03 and 2004/05 seasons. Details of thesurveys’ designs and some modifications over time are given in Nishiwaki et al. (2006) and in Appendix 2 ofHakamada et al. (in press). Implications of some of these modifications to the results for abundance andabundance trends are discussed later.
Research area and geographical stratification
In the JARPA II surveys, the main region for full scale research was Antarctic Areas IIIE, IV and V (35oE 175oE) and Area V and VIW (130oE - 145oW) south of 60ºS; each of these Areas was divided into smaller strata(Figure 1). Specifications of the stratification are given in Figure 1. Distributions of primary sightings of
humpback whales and of efforts in Areas IIIE, IV, V and VIW for each year are shown in Figure 2a-2d.
Furthermore, each sector was divided into northern (60ºS to 45 n. miles from the ice edge) and southern (fromthe ice edge to 45 n. miles away) strata. The western sector of Area IV includes a separate Prydz Bay stratum.
For this sector, north and south strata were divided at 66oS. The eastern sector of Area V includes the Ross Sea;for this sector, the north and south strata were divided at 69oS.
Monthly coverage
Although the JARPA research period ranged from the end of November to March in each season, regularresearch in Areas IV and V was concentrated in January and February, which coincide with the peak migration
period of humpback whales to Antarctic feeding grounds (Kasamatsu et al. 1996). JARPA II research period
ranged from December to March in each season (Figure 3). The end date was earlier than usual in 2006/07 due
to a fire accident on the research base Nisshin-Maru (Nishiwaki et al., 2007). Abundance estimates are based on
single coverage of the blocks shown in Figure 1 for the year concerned.
Research vessels
Relevant information on research vessels is given in Table 2. Kyo-maru No.1 (K01), Toshi-maru No.25 (T25),
Toshi-maru No.18 (T18) operated as SSVs for the surveys from 1989/90 to 1997/1998. Kyoshin-maru No.2
(KS2) engaged exclusively in sighting surveys (SV) from 1995/96. Yushin-maru (YS1) was used from the
1998/1999 cruise replacing the T18, Yushin-maru No.2 (YS2) was used from the 2001/2002 cruise replacing theT25, Kaiko-Maru (KK1) engaged exclusively in sighting surveys (SV) from 2005/06 to 2008/09 andYushin-maru No3 (YS3) was used from the 2007/2008 cruise replacing the K01.
Order of the surveys
The order in which strata were surveyed is shown in Figure 4. Abundance estimates are based on single
coverage of the blocks shown in the Figure for the season concerned. In the JARPA II period, northern andsouthern strata were surveyed in the same period (Nishiwaki et al., 2014).
Trackline design
The trackline was designed to cover the whole research area and was followed consistently throughout the
JARPA surveys (Figure 2a-2d). The starting points of the trackline were selected at random from 1 n.mile
intervals on lines of longitude. Trackline way points (where the trackline changes direction) were systematicallyallocated on the ice edge and on the locus of points 45 n.miles from that edge in southern strata, and on thislocus and the 60ºS latitude line in the northern strata. There were two modifications in trackline design in
JARPA II surveys considering the recommendations at the JRM to improve abundance estimation. One is thatthe saw-tooth type trackline for the southern strata was chosen to allow for wide area coverage in JARPA but
was not chosen in JARPA II. Another is that northern and southern strata were surveyed in the same period(Nishiwaki et al., 2014) to avoid temporal gaps occurring in the survey period of southern and northern strata
during JARPA II period.
Sighting survey procedure
There were two or three SSVs traveling in parallel on each predetermined trackline. The distance between theirtracklines was 7 n. miles. The SSVs conducted sighting and sampling survey at a standard speed of 11.5 knots.
The survey was conducted under optimal research conditions only (i.e. when the wind speed was below 25
knots in the southern strata and below 20 knots in the northern strata, and visibility was over 2 n. miles). During

3SC/F14/J4
JARPAII period, SSVs covered south of 62 S whereas SVs covered south of 60 S. Therefore, sighting dataobtained by SSVs was not used for abundance estimation in this period.
oo

One of the three SSVs behaved as a SV from the 1991/92 to 1994/95 cruises. From 1995/96, three SSVs and an
additional SV (KS2) with closing mode (i.e. NSC as above but without sampling of whales) were allocated tothe survey. From 1998/99, the SV (KS2) introduced the passing mode (i.e. NSP in IDCR-SOWER notation i.e.
the vessel did not approach whales after the sighting was made and search from the barrel continued
uninterrupted, except for some special cases such as sightings of blue whales in which closure was effected oncethe vessel came abeam of the whale). The sighting surveys (12 hours during the day) were conducted alternating
between normal closing mode (4 hours) and passing mode (8 hours) during the day. For the SV, these modes aredenoted as SVC and SVP hereafter. The SSVs followed the SV at a distance of over 12 n. miles to avoid any
influence of sampling activities on the SV’s sighting survey. In the JARPA II period, SSVs and SVs weresurveyed independently from each other.
A researcher onboard recorded all the information on the whales sighted. The sighting record included the dates
and times of the sightings, the positions of the vessel, a classification of survey mode and sighting (primary or
secondary), the angles and distances from the vessel of the initial sighting, the species and school size, theestimated body lengths and other information as for the IDCR-SOWER cruises. More details of theseprocedures are given in Nishiwaki et al. (2006).

ANALYTICAL PROCEDURE
The procedure applied to analyze the sighting data is very similar to that used for the IWC/IDCR-SOWER
surveys by Branch and Butterworth (2001a, b). To provide “base case” estimates of abundance: 1) distances andangles are corrected for possible bias by using the results of the distance and angle estimation experiments, 2)
the sighting rate is obtained each day, 3) smearing parameters are obtained by Buckland and Anganuzzi’s (1988)
method II, 4) g (0) is assumed to be 1, and 5) sighting data is pooled each season and across strata to the extent
necessary for reliable estimation of the effective search half-width (ws , using either a hazard rate or half- normal
model) and the mean school size (E(s)), based on standard line transect analysis methods using the program
DISTANCE (Thomas et al., 2010).
The material hereunder sets out further assumptions made to obtain base case estimates, followed bydescriptions of sensitivity tests in which one or more of the base case specifications and assumptions are varied.
Data selected for the analysis
Size of the research area
The surveys covered the region between the ice edge and 60oS. The open water area for each stratum for eachsurvey was calculated using the Marine Explore Geographical Information System version 4 (Environment
Simulation Laboratory Co, Ltd, Japan). The ice edges and hence boundaries between the northern and southern
strata differed for SVs and SSVs because their surveys were not completely synchronous, so the ice edges theyencountered differed. This in turn resulted in slightly different stratum areas for the two. For abundance
estimates developed combining data over the SSV and SV modes, the averages of the two area sizes of eachstratum are used.
Unsurveyed area
Some small parts of Area IV were unsurveyed on four of the cruises, with the proportions not surveyed. These“gaps” arose because of retreat of the ice edge after survey of the more northerly of the two strata concerned had
been completed, necessitating re-location of the trackline for the more southerly stratum. For base caseabundance estimates, these gaps are treated as having the same density as the more northerly stratum. This isbecause densities tend to be higher close to the ice edge, and these gap regions are more typical of areas moredistant from the ice. Note that such “gaps” differ from instances where coverage of a survey was poor orincomplete because of shortage of time and/or bad weather. The consequences for abundance estimates caused
by each of these effects are addressed further below under Sensitivity Tests.
Due to violent action by an anti-whaling non governmental organisation in the research area, the SVs and SSVs
could not carry out the research in the planed track line in Area III East (35°E - 70°E), a part of Area IV (90°E 130°E) and a part of Area V West (130°E - 132°E) in 2009/10 (Nishiwaki et al., 2010). Due to violent action by
an anti-whaling non governmental organisation in the research area, a sighting survey by SV was not conducted
in 2010/11 (IWC, 2012). Therefore, abundance estimates for these years could not be made.

4

SC/F14/J4
Survey modes
Sighting data collected under SSV, SVC and SVP modes was combined for the estimation of the mean school
size and effective search half-width for schools. Although separate estimates are obtained for each of thesemodes in the case of Antarctic minke whales (Hakamada et al. in press), data was pooled here as the limited
number of sightings of humpback whales dictated the need to include as many as possible, as in the case of the
IDCR-SOWER based abundance estimates for species other than minke whales (Branch and Butterworth,
2001b; Branch, 2011).
Abundance estimation
The methodology used here for abundance estimation is described in Branch and Butterworth (2001a, b), andhas been adopted by the IWC SC in the past. The program DISTANCE (Thomas et al., 2010) was used to
implement this. The basic formula is:P=

AE ( s )n
2 wsL

(1)

where,
P is the estimated abundance in numbers in the stratum,
A is the open ocean area of the stratum,
E(s) is the estimated mean school size,n is the number of primary sightings of schools,
ws is the effective strip half-width for schools, and
L is the primary search effort.
The CV of P is calculated using the approximate formula:n
CV( P) = {CV( )}2 + {CV( E ( s))}2 + {CV( ws )}2
L(2)

Under the assumption of distribution log-normality, 95% confidence intervals for the abundance estimates arecalculated as (P/C, CP) where C is given by:

C = exp(Z 0.025 log e [1 + {CV( P)}2 ] )

(3)

and
Z0.025 represents 2.5-percentage point of a standard normal distribution. More details of the analysis methods
may be found in Buckland et al. (2001) and Branch and Butterworth (2001a, b).
Correction of the estimated angle and distance
To be able to correct for biases in angle and distance observations, experiments using a radar reflecting buoy
were conducted by each vessel during each cruise (the experimental methodology is described in Nishiwaki etal., 2006). Based on the data obtained, biases were estimated for each platform for each cruise. Linear
regression models were used to examine possible differences between observed and true (obtained from radar)
distances. In order to correct for such biases, the estimated distance was divided by the estimated slope of aregression through the origin if this slope differed significantly from 1 at the 5% level. The estimated factors in
2005/06 -2008/09 seasons are shown in Table 3a. A similar approach was used for angles. More details of themethodology may be found in Branch and Butterworth (2001a).
Truncation distanceThe conventional truncation distance for perpendicular distances of sightings that is used for Antarctic minke
whales is 1.5 n.miles (Branch and Butterworth, 2001a; Hakamada et al., in press). However, because of theirlarger bodies and blow sizes, humpback whales can be seen much further from vessels than Antarctic minke
whales. The rule of thumb advocated in Buckland et al. (2001), of truncating to exclude about 5% of the data, istherefore applied as in Branch and Butterworth (2001b), with results rounded to the nearest 0.3 n. miles.
Accordingly the perpendicular distance distributions were truncated at 2.7 n. miles.
Smearing parameters
Smearing parameters were calculated for each cruise to make allowance for errors in estimates of distances andangles. The method used is the same in Branch and Butterworth (2001b). The sightings data is smeared before
their truncation to give n, and then used in the estimation of the effective search half-width (ws) and the meanschool size (E(s)) for input to equation (1). Radial distance and angle data were smeared in the conventionalmanner by using Method II of Buckland and Anganuzzi (1988) and then grouped into intervals of 0.3 n. miles

5SC/F14/J4
for estimating ws values. For Antarctic minke whales, smearing parameters are conventionally estimatedseparately for each stratum from the data. However, due to the lower number of sightings of humpback whales,
some pooling was necessary here to obtain robust estimates from the Buckland and Anganuzzi method. The
smearing parameter values reported in Table 3b were thus obtained from pooled sightings (including sightings
with both confirmed and unconfirmed school size) separately for each JARPA II cruise.
Effective search half-width
The smeared and truncated sightings data for schools was grouped into intervals of 0.3 n. miles to estimate thedetection function A hazard rate model with no adjustment terms and a half-normal model were considered as
detection functions. The better model was selected by AIC in each case. g(0) was assumed to be 1 (i.e. noschools present on the trackline were missed).
Mean school size
A method regressing the logarithm of school size against the detection f(y), as described by Buckland et al.
(2001) was used to estimate mean school size (E(s)). If the regression coefficient was not significant at the 15%
level, the mean of the observed school size was input to equation (1). Note that pooling across survey modes
means use school size estimates for SVP mode which may bias the estimate of E(s) downwards. Only sightingsfor confirmed school size were used to obtain these estimates.
Population rate of increase
To estimate rate of increase in an Area, an exponential trend was assumed with the following error structure:

Py = β exp(αy ) + v y ,Pˆy = Py + u y ,

(4)

where
Py and P̂y are the true and survey estimated abundances in an Area in season y,α is the instantaneous increase rate,
β is abundance for season y=0,
u y reflects survey sampling error, andv y is the error associated with additional variance, which arises from an inter-annual variation in the proportionof whales in the surveyed area at the time of the survey.
In order to take the additional variance of abundance estimates (CVadd) as well as the survey sampling CV into
account, the negative log-likelihood function minimized to estimate α is:() . (5)2log( Pˆy ) − log( β ) − α y122ˆl (α , β , CV add ) = ∑ log CV ( Py ) + CV add + ∑
2
2 
2 y
y
2  CV ( Pˆy ) + CV add



[

]

{

}

Estimates of standard errors for α and CVadd were obtained from the associated Hessian (Information matrix),with CI estimates assuming a t-distribution with 8 degrees of freedom for Areas IV and V and 5degrees of
freedom for Areas IIIE and VIW .
Muller and Butterworth (2012) suggested that breeding stock D is near its pristine abundance using the initial
population dynamics model. It also examined the annual increase rate being estimated by the Logistic model for
Area IV.

Py =K
K − P0 − ry
1+
e
P0

(6)

where K is carrying capacity of this population. Py is abundance estimate in year y. r is instantaneous increasingrate of humpback whales.
Sensitivity tests
Alternative estimates of effective search half-width
The base case selects between the hazard rate and half-normal models of the detection function for
cruise-stratum/set-of-strata combination. For sensitivity tests, either all forms are set to half-normal or all tohazard rate.

6SC/F14/J4
Inclusion of tracklines that followed the contours of the ice edge
Some of the tracklines were nearly parallel to the ice edge in strata where the saw-tooth type trackline design
approach was used (e.g. SW and SE strata in Area IV) during the JARPA survey period. This could lead tooverestimation of abundance because of possible higher density close to the ice edge. As sensitivity tests to
examine the effect of tracklines that followed the contours of the ice edge, two data sets were developed: onethat excluded portions of tracklines that followed the contours of the ice edge (Option B), and the other one that
excluded all tracklines not parallel to lines of longitude (Option C). Because of the small number of sightings in
the SW and SE strata in Area IV on earlier cruises, only seasons from 1997/98 onwards were considered. No
saw-tooth trackline was used in the JARPA II period.
Unsurveyed areas and incomplete coverage
Two approaches are pursued to attempt to bound the uncertainty associated with the treatment of “gaps” incoverage as defined above for the base case estimates. On the conservative side, the abundance contributions
from these gaps are set to zero (i.e. whales in such gaps at the time of surveying the more southerly strata areconsidered as ones already effectively counted in the earlier surveying of the more northerly strata, as thesewhales would subsequently likely have moved further south). On the liberal side, the density in a gap is assumed
to be the same as the higher density in the stratum immediately to the south, rather than that immediately to thenorth as in the base case. Because northern and southern strata were surveyed in the same period, such “gaps”
did not occur in the JARPA II period.
For cases of incomplete coverage, the approach followed to check sensitivity was as follows. For the base caseestimates of abundance, the extrapolated density for the (nearly) unsurveyed portion of a stratum is taken to be
the same as that in the surveyed portion of the stratum. As an alternative to this, the average of the ratio of thedensities in these two portions of the stratum on other cruises was evaluated (in the case of the humpback
analysis, this amounts to considering the ratio of sighting rates, as values of other inputs to the calculation ofdensity as common), and this was used instead to extrapolate the density in the surveyed area to that for the(nearly) unsurveyed portion for the season in question. The development of such averages did not include datafrom every other cruise, as consideration was also given to similarities of ice-edge configurations between thecruises. The strata for which such alternative computations were conducted, together with the other cruises used
to develop the average ratio required shown in parenthesis, were as follows:
Area IIIE: 2005/06 IIIEN over 35o – 55oE
(2007/08)
Area IIIE: 2005/06 IIIES over 35o – 55oE
(2007/08)
Area V: 2006/07 NW over 130o – 159oS(2005/06; 2007/08; 2008/09)(2005/06; 2007/08; 2008/09)
Area V: 2006/07 SW over 130o – 159oS(2006/07; 2007/08)
Area V: 2008/09 NW over 161o – 165oE
Area V: 2008/09 SW over 140o – 150oE(2005/06; 2007/08)
The effect of survey modes and survey timing
To investigate the extent of the effects of the survey modes (i.e. SSV, SVC and SVP) and timing of the survey
conducted in each stratum (which differed in some years because of differences in the order in which the strata
were surveyed) on estimates of population increase rates, GLM analyses were undertaken. In the Prydz Bay
stratum in Area IV and the SE stratum of Area V, no sightings of humpback whales were made for some of thecruises. Hence, a Poisson error structure was assumed for the GLMs. A hierarchy of such models was evaluatedfor each Area. As discussed in Hakamada et al. (in press), since stratum areas vary from season to season as aresult of different ice edge locations, it is not immediately obvious whether such approaches should be based on
the density or on the abundance in a stratum, and arguments can be offered to support either approach. However,density is perhaps the more obvious choice and furthermore Hakamada et al (in press) found little difference inresults for the two approaches for minke whales. Accordingly, the analyses here are based only on density.

 2w y , a L y , a  + log(Dtrue (0, a)) + αy
Model i): log E[nobs ( y, a)] = log
 E y ,a ( s) 



(7-1)

[

]

 2 w y ,a L y , a  + log( Dtrue (0, a )) + αy + M , E (s)  y ,a[]

 2 w y , a L y ,a 
 + log( Dtrue (0, a )) + αy + M + T , E (s)  y ,a

Model ii): log E nobs ( y , a ) = logModel iii): log E nobs ( y , a ) = log

7

(7-2)

(7-3)

SC/F14/J4[]

 2 w y ,a L y ,a 
 + log( Dtrue (0, a )) + αy + M + a * T , (7-4)
 E (s) 
y
,
a



Model iv): log E nobs ( y , a ) = logwhere
y is the season
a is the stratum,E[nobs(y,a)] is the expected number of sightings in stratum a in season y,wy,a,is the effective search half-width for season y and stratum a,
Ly,a and is the primary search distance for season y and stratum a,
E(s)y,a is the estimated mean school size for season y and stratum a,
Dtrue(y,a) is the unbiased (i.e. free from the survey mode effect) density for season y and stratum a,
α is the population’s exponential rate of increase,
M is the mode factor for SSV and SVC surveys standardized to SVP,
T is a categorical variable related to survey timing that is defined below, anda*T is an interaction between the stratum a and timing T factors.
The first term on the right-hand-side is known as the offset. It uses values of ws and E(s) pooled over modes, sothat all inputs required are listed in Tables 4b and 4c. The approach used here makes the assumption that thevariances of ws and E(s) are relatively small compared to the variance associated with the observed number ofsightings. Additional variance has not been considered in these analyses.
The day halfway through the survey period in each stratum was calculated and categorized into groups as a basis
to specify T for models iii) and iv) above. The groups in bold letters below are included in the intercept of thealternative models considered (i.e. the effect of those groups is set to zero in the calculations). Because theestimate of α seemed to be sensitive to the definition of T for Area IV in particular, five groupings wereconsidered:
1) T=1: Dec 15-Jan 15; T=2: Jan 16-31; T=3: Feb 1-15; and T=4 Feb 16-Mar15 (Grouping T1)
2) T=1: Dec 15-Jan 15; T=2: Jan 16-Feb 15 and T=3: Feb 16-Mar 15 (Grouping T2)
3) T=1: Dec; T=2: Jan; T=3: Feb and T=4: Mar (Grouping T3)
4) T=1: Dec and Jan and T=2: Feb and Mar (Grouping T4)
QAIC (Burnham and Anderson, 1998) rather than AIC was used to select amongst these models and alternatives
for specifying T because it can be applied to GLMs with over-dispersed Poisson errors. QAIC is defined here as

QAIC = −2 log( L)
+ 2p
cˆ

(8)

where L is the likelihood of the model without over-dispersion, ĉ is the estimated over-dispersion parameterand p is the number of estimable parameters including the over-dispersion parameter.
RESULTS
Abundance estimates
Tables 4a – 4d show abundance estimates (P) of humpback whales in Areas IIIE, IV, V and VIW, respectively,by season and stratum. The tables also show the total number of the primary sightings after truncation (n), open
ocean area (A), primary search effort (L), n/L, effective search half width (ws), estimated mean school size (E(s)),
estimated whale density (D: whales / 100 n. miles2) and the CVs for each estimate. The primary effort andassociated primary sightings of schools of humpback whales used for these estimates are plotted in Figure 2.
Abundance estimates in Area IIIE change from 1,378 (CV=0.190) for the 1995/96 season to 11,904 (CV=0.261)
for the 2007/08 season (Table 5a). Abundance estimates in Area IV change from 5,325 (CV=0.302) for the
1989/90 season to 29,067 (CV=0.255) for the 2007/08 season (Table 5b). Abundance estimates in Area Vchange from 602 (CV=0.343) for the 1990/91 season to 13,894 (CV=0.338) for the 2008/09 season (Table 5c).
Abundance estimates in Area VIW change from 1,493 (CV=0.185) for the 1996/97 season to 3,609 (CV=0.322)
for the 2008/09 season (Table 5d).Figure 5a and 5b shows the detection probability functions in relation toperpendicular distance from the trackline in nautical miles that were used for the analyses by cruise and stratum(or combination of strata); there are no obvious indications of model mis-specification, nor of any trend towards
distributions with sharper peaks near the trackline in the earlier years.

8SC/F14/J4
Abundance trends
Figure 6 shows the abundance estimates in Areas IV and V plotted against the survey seasons. For comparative
purposes estimates obtained using IDCR-SOWER data (Branch, 2011) have been added to this Figure. An
increasing trend in abundance is evident for both Areas IV and V. Annual rate of increase estimates from the
JARPA surveys using equation (5) are 20.8% (95%CI = 4.1 – 37.6%), 13.6% (95% CI = 8.4- 18.7%), 14.5%(95%CI = 7.6 – 21.5%) and 6.2% (95%CI = -0.9 – 13.4%) per year for Areas IIIE, IV, V and VIW, respectively
in the JARPA and JARPA II period. The estimates for Areas IV and V are clearly significantly positive; theresult for Area IIIE is also significantly higher than zero, but not as clearly so as that for Areas IV and V. The
additional CVs are estimated as 0.635, 0.328, 0.416 and 0.036 for Areas IIIIE, IV, V and VIW respectively(Table 6).
Logistic regression model
Table 7 shows estimated coefficients of the regression model (6) for Area IV. Carrying capacity was estimated as
29,950 (SE=3,250). Abundance estimates in Area IV and predicted abundance by the model are shown in Figure
7. The estimated model seemed to fit abundance estimates in Area IV except for the first two years. The four
latest abundance estimates are close to the carrying capacity estimated by the model (6). These results may
suggest that humpback whales in Area IV are close to the carrying capacity, although mixing between breeding
stock D and other breeding stocks was not taken into account in this analysis.
Sensitivity tests
Alternative estimates of effective search half-width
The effects on abundance estimates at the Area level, and also on annual rates of increase, compared to the basecase for these and the following two sets of sensitivity tests are shown in Tables 5a, 5b, 5c and 5d, withdifferences in estimates of precision and the associated additional variance shown in Table 6.
There are occasional instances of a large difference, but viewed overall, the average change in the abundance
estimates from the base case never exceeds 10% in most of the cases, and any alteration to the rate of increase
estimate is below 1% except Area IIIE. For Area IIIE, Change in ROI estimates is some -2% in three sensitivity
scenarios. Given the high ROI estimates of 20.8% for the base case in Area IIIE, there is no basis to question therobustness of the abundance trend in Area IIIE.
Inclusion of tracklines that followed the contours of the ice edge
These tests apply only to Area IV, and are somewhat restricted because of insufficient data to allow them to be
conducted for the first four seasons of surveys there. For the subsequent years, these alternative treatments makelittle difference on average to abundance estimates (Table 5b), and also have little impact on the estimatedabundance trend (Table 6). Thus there is no definitive indication that including tracklines that followed thecontours of the ice edge in estimating humpback whale abundance and trends introduces substantial bias.
Unsurveyed areas and incomplete coverage
Results for these sensitivity tests mirror those that use alternative functional forms to estimate effective searchhalf-width: the average change in the abundance estimates from the base case, except poor coverage corrections
in Area IIIE and Area VIW, and any alteration in the rate of increase estimate are small (Table 5a-5d and 6).
The effect of survey modes and survey timing
Table 8a shows the observed number of sightings SSV, SVC and SVP surveys, as used for input to the GLM
models of equation (7), by season and stratum. Table 8b shows the QAIC for each model and estimatedinstantaneous annual rates of increase for Areas IV and V with their 95% confidence intervals. Comparison of
the abundance trend estimates in Table 5b, shows broad agreement for Area IV – all point estimates are high andin the 14.1-16.4% range. However, this is not the case for Area V, for which most point estimates in Table 8b areless than that for the base case by 3%-7%. Nevertheless, all the Table 8b estimates fall within the CIs or close to
the lower limit for the corresponding base case estimates in Table 6. QAIC selects the more parsimonious
models, choosing only survey mode amongst the co-variates considered, and then only for Area IV. This does
not necessarily mean that survey timing or the order in which the strata were surveyed has no effect on estimates,
but rather that there is insufficient information content in the data to reveal such an effect. Nevertheless for Area
IV, even if the (changing) order of surveying strata is taken into account, although the best estimate of the rate ofincrease drops, the lower 95% confidence limit remains at or above 10% as for the base case. For Area V theresults in Table 8b show significant increase, although estimates of the rate of increase is lower than the basecase taking survey ordering into account.
Under QAIC, inclusion of survey mode as a factor is selected only for Area IV, but the change to the estimatedrate of increase is negligible, and the mode factor estimates themselves suggest SVC and SSV density estimates
only slightly (and not significantly) greater than those for SVP. For Area V, a likely reason for non-selection of

9SC/F14/J4
these factors, which suggest somewhat lower densities in SVC and SSV modes compared to SVP, is theirassociated high estimated standard errors.
DISCUSSION
Abundance estimates and abundance trend based on JARPA data
As noted earlier the IWC SC has made several suggestions to improve abundance estimation of Antarctic minke
and humpback whales from JARPA surveys during previous meetings. Recent discussions on this topic took
place during the JARPA review meeting (IWC, 2008). Table 1 shows the recommended work by the workshop
and how these suggestions have been addressed in the analyses of this paper, and indicates that all but a few
issues (all accorded only medium priority) have been considered, though these few seem unlikely to greatly
effect the estimates of abundance and trends presented here as suggested in previous analysis (Matsuoka et al,2011).

The results of sensitivity analyses provide no basis to question the pooling of the data across survey modes (SSV,
SVC and SVP) for the base case abundance estimation, though the information content of this data to determineinter-mode differences is poor. The same conclusion follows for the effect of including data from tracklines that
followed the contours of the ice edge in the analyses. The impact on the overall estimates of abundance andtrends of the choice of functional form for the detection function, and of some instances of survey gaps and poor
coverage, are small.
The point estimates of the annual increase rate are high given the estimate of Clapham et al. (2006) of a
maximum demographically plausible annual increase rate for humpback whales of 10.6%. However the lower
95% CIs for this rate for the base case and sensitivities in Table 6 are all below this figure, though only barely sofor some cases.
A high annual increasing rate was estimated for Area IIIE. Given that the abundance estimate in Area IV issuggested to be near its carrying capacity, a possible shift from breeding stock D to breeding stock C could be
the cause of the high estimate in Area IIIE.

Comparison with IDCR-SOWER estimates
As is readily evident from the list of JARPA and IDCR-SOWER estimates of abundance in Table 9a, and thecorresponding plot in Figure 6, results from the two sets of surveys are entirely consistent.
Rates of increase in Areas IV and V as estimated from JARPA and IDCR-SOWER results are also similar (Table
9b). Rates of increase estimated from JARPA data are 13.6% (95% CI = 8.4- 18.7%) in Area IV and 14.5%(95%CI = 7.6 – 21.5%) in Area V, which compare with rates estimated from IDCR-SOWER data of 14.9%(95% CI 10.0-19.7%) and 12.8% (95% CI 6.7–17.4%) for those two Areas respectively (Branch, 2011).
However Branch’s estimates of precision are based on estimates of additional variance of zero; if instead theestimates determined in this paper are used, though the IDCR-SOWER estimates change only slightly, their CIs
do expand (Table 9b). They nevertheless still reflect somewhat greater precision than do the JARPA estimates.
The reason for this is that the IDCR-SOWER surveys extend over a longer period of time. Importantly though,the greater frequency of the JARPA surveys makes realistic (and reasonably precise – Table 6) estimates ofadditional variance achievable – something that is scarcely possible for the lesser numbers of IDCR-SOWER
surveys, and this has important implications for reliable estimation of precision.

Comparison with Western and Eastern Australia estimates
The abundance estimate of humpback whales off western Australia based on an aerial survey conducted in 2005
is 13,145 (95% CI 4,984–38,726) (Paxton et al., 2006). The annual rate of increase for this population has been
estimated at 9.7% (CV=0.25) (Hedley et al., 2011). Off eastern Australia the abundance estimate based on datacollected in 2004 is 7,090 (SE=660) and the rate of increase is estimated at 10.9% (95%CI =10.5 -11.3%) (Nordet al., 2011). These quite high estimates of rates of increase are consistent among surveys conducted in breedingareas and migratory corridors, and those carried out in Antarctic feeding areas (IDCR-SOWER and
JARPA/JARPA II).
Estimates of abundance in absolute terms off western and eastern Australia of 28,830 in 2008 (Hedley et al.,2011) and 14,522 in 2010 (Nord et al., 2011) are similar to the latest abundance estimates for Antarctic Areas
IV and V, respectively.

10SC/F14/J4
In summary, humpback whales in Area IV and Area V are definitely increasing rapidly.
ACKNOWLEDGEMENTS
Our gratitude goes out to Luis A. Pastene and Toshihide Kitakado for their help in the preparation of this paperand Doug Butterworth for useful technical suggestions. We would like to thank all of the researchers, captains,
officers and crew members participating in the JARPA and JARPA II surveys. We also would like to thank Seiji
Ohsumi, Hiroshi Hatanaka, Yoshihiro Fujise and Shigetoshi Nishiwaki for their useful comments on theanalyses; Tatsuya Isoda, Nobuyuki Suzuki and Satoshi Suzuki for their help in preparing this paper.
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Table 1. List of recommendations for improvements to estimates of abundance of humpback whales from the
JARPA surveys from the IWC Scientific Committee (IWC, 2008) and priority assigned by the Advisory
Group.
Tasks

Priority

Remarks

1. Estimation of detection function（re-estimate in the cases
where the number of detection is small ）H

2. Investigation of sensitivities to pooling all vessels to estimate
effective strip width and mean school size.

M

3. Variance estimation from the SSV data

M

4. Sensitivity analysis with appropriate weighting and/or
bootstrapping
5. Abundance estimates treating as if abundance in gaps between
two strata were 0.
6. Extrapolation of density into unsurveyed areasM

7. Abundance estimates accounting for change in order that thestrata were surveyed
8. Estimation of additional variance

H

Addressed
Table 5a-5d (Abundance)
Table 6 (Trend)
For humpback whales, data
had already been pooled forall vessels.
To be addressed in future
work
Addressed
Tables 5a, 5b and 6
Addressed
Table 5b and 6
Addressed
Table 5a-5d and 6
Addressed
Table 8bPartially addressed
Table 6 and 9b, Future
analyses will utilize GLM
Addressed
Table 6 and 9b.

LH

M

9. Revised estimates of annual increase rate and its CV
following suggestions 1-8

M

Table 2. Specifications of the research vessels used for the JARPA and JARPA II surveys.
Kyo-maru
No.1

Toshi-maru
No.25

Toshi-maru
No.18

Yushin-maru

Yushin-maru
No.2

Kyoshin-maru
No.2

JKNG

8JCG

JPMQ

JLZS

JPPV

JFHR

Register length (m)

69.15

68.37

63.20

69.61

69.60

68.18

Molded breadth (m)

10.30

9.90

9.90

10.40

10.80

10.80

Gross register tonnage

812.08739.92758.33720.00747.00372.00

Barrel height (m)

18.00

18.00

18.00

18.00

18.00

17.00

IOP height (m)

-

-

-

13.50

13.50

10.50

10.00

10.00

10.00

10.00

10.00

8.00

Call sign

Upper bridge height (m)Bow height (m)

6.40

6.00

6.20

6.50

6.50

-

Maximum continuous output (hp)

5,000

3,600

3,500

5,280

5,280

2,100

14

SC/F14/J4
Table 3a. Estimated observer bias (expressed as multiplicative correction factors) in distance and angle
estimation for JARPA surveys from 2005/06 to 2008/09.

Year
2005/06
2006/07
2007/08
2008/09

Platform
BarrelUpper bridge
Distance
Angle
Distance
Angle
KS2
1.043
0.914
n.s.
n.s.
KK1
1.049
n.s.
n.s.
n.s.
KS2
n.s.
n.s.
n.s.
n.s.
KK1
n.s.
n.s.
n.s.
n.s.
KS2
n.s.
0.961
n.s.
0.950
KK1
n.s.
n.s.
0.839
n.s.
KS2
n.s.
0.918
n.s.
n.s.
KK1
1.055
0.963
n.s.
0.949
*n.s. indicates not significant at 5% level.
VesselTable 3b. Smearing parameters for each year used in abundance estimation. Units for angles are degrees, while
for distances the values given are proportions.
Year
2005/06
2006/07
2007/08
2008/09

angle
5.244
9.278
7.826
5.379

15

distance
0.154
0.154
0.333
0.14

SC/F14/J4
Table 4a. Abundance estimates for humpback whales in Area IIIE (south of 60 S) from the 1995/96 to 2007/08
JARPA and JARPA II cruises. A: size of research area, n: number of schools sighted on primary effort(truncated at a perpendicular distance of 2.7 n. miles after smearing), L: primary searching distance, ws:
the effective search half width (hazard rate model estimate, or half normal if shown in italics), E(s): meanschool size, D: estimated density (individuals / 100 n. miles 2), P: estimated abundance.
oYearStratum

1995/96
1997/98
1999/2000
2001/02
2003/04
2005/06

IIIE
IIIE
IIIE
IIIE
IIIE
IIIEN
IIIES
Total
IIIEN
IIIES
Total

2007/08A(n.mile 2 )250,272
267,522354,053355,694
330,467
332,409
51,635384,043
228,382
50,431
278,813

n
54.0
26.0
141.0
102.0
194.0
55.5
2.0
57.5
80.3
77.0
157.3

L
(n.mile)5,646.8
6,704.0
3,679.7
4,822.9
4,844.9
674.2
675.0
1,349.2
931.4
1,126.2
2,057.6

n /L
* 102
0.956
0.388
3.832
2.115
4.004
8.228
0.294
4.259
8.620
6.839
7.645

CV

CV

E (s)

CV

0.174
0.211
0.122
0.198
0.096
0.362
0.587

ws
(n.mile)
1.291
1.480
0.946
1.320
1.437
1.999
1.999

0.108
0.172
0.065
0.078
0.059
0.127
0.127

1.480
1.923
1.681
1.681
1.747
2.017
2.017

0.063
0.493
0.030
0.042
0.030
0.064
0.064

0.270
0.327

1.660
1.615

0.098
0.098

1.678
1.833

0.096
0.168

D
(ind.)
0.546
0.251
3.412
1.347
2.435
0.042
0.001
0.036
0.044
0.039
0.043

P
(ind.)
1,378
671
12,081
4,791
8,045
13,79776
13,874
9,946
1,958
11,904

CV
0.190
0.360
0.130
0.200
0.100
0.389
0.604
0.387
0.303
0.380
0.261

Table 4b. Abundance estimates for humpback whales in Area IV (south of 60oS) in the 2005/06 and 2007/08
JARPA II cruises. The notation is as for Table 4a.
Year

Stratum

2005/06

NW
NE
SW
SE
PB
Total
NW
NE
SW
SE
PB
Total

2007/08A(n.mile 2)
228,919
213,660
47,11737,22831,689577,386
213,311216,236
39,78736,277577,386

n

149.9
59.8
131.3
230.1
0.0
1359.6
141.6
63.7
205.9
73.7
1359.6

L(n.mile)1,131.4
1,450.3
859.4
865.5
381.1
13,392.0
958.9
1,332.4
847.5
819.8
13,392.0

n/L* 102
13.245
4.124
15.27526.5890.000
10.15214.7684.782
24.2998.987
10.152

CV

0.431
0.279
0.424
0.253
0.851
0.077
0.314
0.425
0.282
0.415
0.077

ws
(n.mile)
2.218
2.169
1.665
1.736
2.700
1.376
1.891
2.021
2.027
-

CV

E (s)

CV

0.060
0.130
0.076
0.059
0.000
0.193
0.117
0.068
0.113
-

1.973
1.713
2.040
1.609
1.706
1.600
1.857
1.833
1.600
-

0.172
0.086
0.143
0.066
0.038
0.082
0.077
0.078
0.153
-

D
(ind.)
5.890
1.628
9.356
12.323
0.000
4.496
0.086
0.023
0.110
0.035
5.034

P
(ind.)
13,483
3,479
4,408
4,588
0
25,95818,318
5,078
4,384
1,287
29,067

CV

0.468
0.320
0.454
0.268
0.852
0.263
0.378
0.448
0.301
0.457
0.255

Table. 4c. Abundance estimates for humpback whales in Area V (south of 60oS) in the 2006/07 and 2008/09
JARPA II cruises. The notation is as for Table 4a.
Year

StratumA(n.mile 2)nL(n.mile)2005/06

NW
SW
NW
NE
SW
SE
Total
NW
SW
NW
NE
SW
SE
Total

238,068
49,999351,072
340,889
38,198
139,575
869,734
275,376
43,609224,275
324,889
64,901
277,209891,274

15.3
49.5
5.5
44.9
8.0
0.0
58.4
35.3
14.0
23.0
56.6
48.0
6.0
133.6

613.8
652.6
97.2
2,107.7
136.2
2,272.9
4,614.1
1148.1864.9
1,144.7
1,369.5
638.1
2,757.8
5,910.1

2006/07

2007/08

2008/09

n/L
* 102
2.489
7.584
5.683
2.130
5.872
0.000
3.072
1.619
2.009
4.132
7.522
0.218
-

CV

ws
(n.mile)

CV

E (s)

CV

D
(ind.)

P(ind.)

CV

0.45
0.39
0.339
0.196
0.305

1.661
1.661
1.670
1.670
1.670

0.11
0.11
0.115
0.115
0.115

1.629
1.629
1.864
1.864
1.864

0.06
0.06
0.046
0.046
0.046

0.27
0.32
1.068
0.405
0.330
0.328
-

1.201
1.201
1.255
1.775
1.255
1.775
-

0.21
0.21
0.092
0.115
0.092
0.115
-

1.473
1.473
1.718
1.889
1.718
1.889
-

0.06
0.06
0.046
0.059
0.046
0.059
-

0.012
0.037
0.032
0.012
0.033
0.000
1.890
0.019
0.010
0.014
0.022
0.052
0.001
1.559

2,905
1,859
11,135
4,052
1,252
0
16,438
5,189
433
3,085
7,145
3,343
321
13,894

0.47
0.41
0.361
0.232
0.329
0.266
0.34
0.39
1.073
0.425
0.345
0.353
0.338

16

SC/F14/J4
Table 4d. Abundance estimates for humpback whales in Area VIW (south of 60 S) from the 1996/97 to 2008/09
JARPA and JARPA II cruises. The notation is as for Table 4a.
oYearStratum

1996/97
1998/99
2000/01
2002/03
2004/05
2006/07

VIW
VIW
VIW
VIW
VIW
VIWN
VIWS
Total
IIIEN
IIIES
Total

2008/09

A(n.mile 2 )215,064
29,908289,954
318,055
278,538
220,818
31,008251,826
166,610
76,255
242,865

n

62.5
5.0
48.7
48.1
35.8
18.3
7.0
25.3
25.6
20.0
45.6

L
(n.mile)6,464.2
1,114.5
4,383.6
5,950.2
3,954.7
756.4
721.2
1,477.6
721.6
990.1
1,711.7

n /L
* 102
0.967
0.449
1.111
0.808
0.905
2.426
0.970
1.715
3.549
2.020
2.664

CV

CV

E (s)

CV

0.164
0.672
0.163
0.216
0.233
0.375
0.638

ws
(n.mile)
1.229
0.664
1.012
1.132
0.823
2.700
2.700

0.154
0.233
0.203
0.174
0.460
0.224
0.224

1.768
1.707
1.533
1.402
1.460
2.039
2.039

0.045
0.046
0.056
0.058
0.078
0.117
0.117

0.358
0.249

1.538
1.538

0.125
0.125

1.490
1.490

0.070
0.070

17

D
(ind.)
0.697
0.543
0.842
0.493
0.803
0.009
0.004
0.008
0.017
0.010
0.015

P
(ind.)
1,493
171
2,440
1,614
2,237
2,022
114
2,136
2,863
746
3,609

CV

0.185
0.721
0.196
0.235
0.353
0.452
0.686
0.437
0.386
0.287
0.322

SC/F14/J4
Table 5a.Abundance and annual rate of increase (ROI) estimates for Area IIIE for the base case and sensitivities.

Year

1995/96

1997/98

1999/00

2001/02

2003/04

2005/06

2007/08

Average %of change

ROI(%)

Changefrom basecase (%)

1,378

671

12,081

4,791

8,045

13,874

11,904

-

20.8

-

-

-

-

-

-

-

-

-

-

-

1,163

620

10,703

4,299

7,527

13,296

11,311

-

19.8

-1.0

-16%

-8%

-11%

-10%

-6%

-4%

-5%

-9%

-

-

1,378

671

12,081

4,791

8,045

13,874

11,904

-

20.8

0.0

0%

0%

0%

0%

0%

0%

0%

0%

-

-

1,378

671

11,252

4,791

8,045

13,874

11,904

-

18.9

-1.9

-

-

-7%

-

-

-

-

-7%

-

-

1,378

671

12,542

4,791

8,045

13,874

11,904

-

18.9

-1.9

-

-

4%

-

-

-

-

4%

-

-

1,378

671

5,108

4,791

8,045

8,861

11,904

-

18.6

-2.2

-

-

-58%

-

-

-36%

-

-47%

-

-

Base caseHazard rate model

Half-normal model

Trackline Option B *Trackline Option C *Poor coveragecorrections ***: Saw-tooth design was used in 1999/00 season.
**: 1999/00 and 2005/06 seasons.

Table 5b. Abundance and annual rate of increase (ROI) estimates for Area IV for the base case and sensitivities.

Year

1989/90

1991/92

1993/94

1995/96

1997/98

1999/00

2001/02

2003/04

2005/06

2007/08

Average %of change

ROI(%)

Changefrom basecase (%)

5,325

5,408

2,747

8,066

10,657

16,751

31,13427,78325,95829,067-

13.6-

Base case
-

-

-

-

-

-

-

-

-

-

-

-

-

5,325

5,666

2,331

8,051

10,537

17,233

31,10825,81825,59130,162

-

13.6

0.0

Hazard rate model
0%

5%

-15%

0%

-1%

3%

0%

-7%

-1%

4%

-1%

-

-

4,041

5,183

2,747

8,066

11,205

12,632

32,84427,70827,32725,626

-

14.0

0.5

Half-normal model
-24%

-4%

0%

0%

5%

-25%

5%

0%

5%

-12%

-5%

-

-

5,325

5,408

2,747

8,066

10,705

14,68530,71329,37625,95829,067

-

13.7

0.1

Trackline Option B *
-

-

-

-

0%

-12%

-1%

6%

-

-

-2%

-

-

5,325

5,408

2,747

8,066

11,03414,14630,48434,22425,95829,067

-

13.9

0.3

Trackline Option C *
-

-

-

-

4%

-16%

-2%

23%

-

-

2%

-

-

5,325

5,408

2,747

7,467

10,657

16,47930,35924,92425,95829,067

-

13.5

-0.1

Gap abundance =0 **Gap abundance = stratum
below **
Poor coveragecorrections ***

-

-

-

-7%

-

-2%

-2%

-10%

-

-

-5%

-

-

5,325

5,408

2,747

8,578

10,657

18,14531,73031,90525,95829,067

-

13.8

0.2

-

-

-

6%

-

8%

2%

15%

-

-

8%

-

-

5,325

5,408

2,747

8,279

10,657

16,751

31,13427,78325,95829,067

-

13.6

0.0

-

-

-

3%

-

-

-

-

-

-

3%

-

-

*: Due to the small number of sightings, there were insufficient data to evaluate options B and C for the 1989/90 to 1995/96 seasons; theaverages quoted for these sensitivities refer to the 1997/98 to 2003/04 seasons.
**: 1995/96, 1999/00, 2001/02 and 2003/04 seasons.
*** Line under the table to read: SE stratum in 1995/96 season

18

SC/F14/J4
Table 5c. Abundance estimates and annual rates of increase for Area V for the base case and sensitivities.

Year

1990/91

1992/93

1994/95

1996/97

1998/99

2000/01

2002/03

2004/05

2006/07

2008/09

Average %of change

ROI(%)

Changefrom basecase (%)

602

4,388

3,678

1,474

3,831

5,127

2,873

9,342

16,43813,894

-

14.5

-

-

-

-

-

-

-

-

-

-

-

-

-

-

Base case

523

5,396

3,592

1,460

3,994

4,734

2,873

9,067

14,401

14,838

-

14.5

0.0

-13%

23%

-2%

-1%

4%

-8%

0%

-3%

-12%

7%

-1%

-

-

602

4,388

3,785

1,474

2,302

4,824

3,415

9,342

16,43813,894

-

14.9

0.4

0%

0%

3%

0%

-40%

-6%

19%

0%

0%

0%

-2%

-

-

770

4,386

3,678

1,474

3,831

5,518

2,873

11,466

15,837

12,498

-

13.7

-0.8

28%

0%

-

-

-

8%

-

23%

-4%

-10%

7%

-

-

Hazard rate model

Half-normal model

Poor coveragecorrections **: SE stratum in 1990/91, NE stratum in 1992/93, SE stratum in 2000/01, NW and SW strata in 2004/05 seasons.

Table 5d. Abundance estimates and annual rates of increase for Area VIW for the base case and sensitivities.

Year

1996/97

1998/99

2000/01

2002/03

2004/05

2006/07

2008/09

Average %of change

ROI(%)

Changefrom basecase (%)

1,493

171

2,440

1,614

2,237

2,136

3,609

-

6.2

-

-

-

-

-

-

-

-

-

-

-

1,505

193

2,440

1,614

2,237

2,139

3,410

-

5.8

-0.4

1%

13%

0%

0%

0%

0%

-6%

1%

-

-

1,493

171

2,086

1,443

1,362

2,136

3,609

-

5.4

-0.8

0%

0%

-15%

-11%

-39%

0%

0%

-9%

-

-

1,493

223

2,440

1,614

2,237

2,136

3,609

-

6.1

-0.1

-

23%

-

-

-

-

-

23%

-

-

Base caseHazard rate model

Half-normal model

Poor coveragecorrections **: VIW in 1998/99.

19

SC/F14/J4
Table 6. Estimated annual instantaneous rates of exponential increase, together with their standard errors and
95% confidence intervals, for base case and other detection function selections for Areas IIE, IV, V and
VIW, respectively. α is the instantaneous rate of increase. CVadd is the CV corresponding to theadditional variance associated with abundance estimates.
Area IIIE

α

se(α)

Base casehazard rate
half-normal

0.208
0.198
0.208

0.065
0.060
0.065

95%CILL
0.041
0.045
0.041

95%CIUL
0.376
0.352
0.376

CVadd
0.635
0.529
0.635

se(CVadd)
0.194
0.188
0.194

opt B

0.189

0.058

0.041

0.337

0.503

0.184

opt C

0.189

0.061

0.031

0.346

0.547

0.194

poor coverage corrections

0.186

0.030

0.108

0.263

0.134

0.150

Area IVαse(α)

95%CILL

95%CIUL

CVadd

se(CVadd)

Base casehazard rate

0.136
0.136

0.022
0.024

0.084
0.080

0.187
0.192

0.328
0.372

0.093
0.100

half-normal
opt B

0.140
0.137

0.022
0.022

0.089
0.086

0.192
0.188

0.328
0.324

0.092
0.093

opt C
Gap abun=0

0.139
0.135

0.023
0.022

0.087
0.084

0.191
0.185

0.335
0.320

0.095
0.092

Gap abun=below
poor coverage corrections

0.138
0.136

0.023
0.022

0.085
0.084

0.191
0.187

0.344
0.328

0.096
0.093

Area Vαse(α)

95%CILL

95%CIUL

CVadd

se(CVadd)

Base casehazard rate

0.145
0.145

0.030
0.031

0.076
0.075

0.215
0.215

0.416
0.424

0.138
0.147

half-normal

0.149

0.028

0.084

0.214

0.369

0.139

poor coverage corrections

0.137

0.030

0.068

0.206

0.411

0.135

Area VIW

αse(α)

95%CILL

95%CIUL

CVadd

se(CVadd)

Base casehazard rate

0.062
0.058

0.028
0.026

-0.009-0.010

0.134
0.125

0.036
0.002

0.582
0.374

half-normal

0.054

0.033

-0.032

0.140

0.086

0.394

poor coverage corrections

0.061

0.026

-0.007

0.129

0.002

0.339

Table 7. Coefficients and their SE for logistic regression model (6). SE of P0 estimate was very high.

K

Estimate
29,950

SE
3,250

P0

674

498.3

r

0.440

0.023

20

SC/F14/J4
Table 8a. Observed number of sightings (truncated at 2.7 n. miles perpendicular distance after smearing) bysurvey mode used as input in the GLMs of equation (7) in Areas IV and V.
Area IV by SSV
Year
Stratum
1989/90

1991/92

1993/94

1995/96

NW

Area IV SVC
Year
Stratumn obs
21

1991/92

SW

Area IV SVP
Year
Stratumn obs
7

1997/98

NW

n obs
9

NE

20

SE

6

NE

1

SW

10

PB

1

SW

21

SE

1

NW

10

SE

1

1993/94

PB

2

NE

11

NW

42

SW

7

NE

16

SE

1

NE

43

SW

13

PB

1

SW

21

SE

10

NW

21

SE

58

1995/96

PB

0

NE

13

NW

34

SW

20

NE

17

SE

SW

17

SE

6

1997/98

PB

0

NW

10

PB

3

NW

41

7

NE

40

2001/02

PB

0

SW

97

NW

29

SE

10

PB

3

NE

25

NW

101

SW

18

NE

33

SE

SW

35

SE

21

1999/00

1999/00

PB

0

NW

33

5

NE

53

2003/04

PB

0

SW

64

NW

4

SE

128

PB

0

NE

23

PB

1

NW
NE
SW
SE
PB

150
80
130
18
2

SW
SE
PB
NW
NE

8
21
0
16
18

2005/06

NW
NE
SW
SE
PB

114
38
106
181
0

NW
NE
SW

41
94
76

SW
SE
PB

30
1
0

2007/08

NW
NE
SW

101
50
158

SE

86

NW

33

SE

61

2001/02

PB
NW

0
195

NE
SW

28
32

2003/04

NE
SW
SE
PB
NW

179
261
52
0
175

SE
PB
NW
NE
SW

39
1
36
23
24

NE
SW
SE

199
294
280

SE
PB
NW

49
0
40

PB

0

NE

14

SW
SE

48
13

1997/98

1999/00

2001/02

2003/04

2005/06

2007/0821

SC/F14/J4
Table 8a (Cont.).
Area V by SSV
Year
Stratum

1990/91

Area V SVC
Year
Stratumn obs

1992/93

NW
NE
SW
SE
NW

1
1
22
1
5

1994/95

NE
SW
SE
NW

3
1
3
6

1996/97

NE
SW
SE
NW

10
27
3
1

NE
SW
SE

13
8
6

NW
NE
SW
SE

3
17
16
30

2000/01

NW
NE
SW
SE

29
24
12
0

2002/03

NW
NE
SW
SE
NW
NE
SW
SE

6
40
15
2
9
46
15
9

2004/05

1998/99

2000/01

2002/03

2004/05

1992/93

Area V SVP
Year
Stratumn obs

1994/95

NW
NE
SW
SE
NW

0
6
4
1
8

1996/97

NE
SW
SE
NW

17
15
2
0

1998/99

NE
SW
SE
NW

1
9
0
5

NE
SW
SE

5
3
0

NW
NE
SW
SE

5
8
4
0

NW
NE
SW
SE

1
3
2
0

NW
NE
SW
SE
NW
SW
NW
NE
SW
SE
NW
SW
NW
NE
SW
SE

6
7
0
0
4
5
1
10
2
0
14
1
4
18
14
5

2005/06
2006/07

2007/08
2008/0922

1998/99

n obs

2000/01

NW
NE
SW
SE
NW

4
0
12
4
9

2002/03

NE
SW
SE
NW

12
15
0
5

2004/05

NE
SW
SE
NW

15
2
1
5

NE
SW
SE

23
2
1

NW
SW
NW
NE

11
44
4
35

SW
SE
NW
SW

6
0
22
13

NW
NE
SW
SE

19
39
35
1

2005/06
2006/07

2007/08
2008/09

SC/F14/J4
Table 8b. QAIC and estimated annual instantaneous rate of exponential increase in Areas IV and V. ĉ is theestimated over-dispersion parameter. The line in bold indicates the model selected by QAIC.

Area IV
Model

ĉ

QAIC

∆ QAICαα 95%UL

18.69
19.00
19.76

135.23131.36131.50135.23131.36131.50

0.141
0.159
0.162

se(α)
0.014
0.017
0.018

α 95%LL

i)

0.114
0.125
0.127

0.168
0.192
0.197

19.54

131.70131.70

0.158

0.017

0.124

0.192

iii) with T3iii) with T4

16.47
19.13

iv) with T1iv) with T2

14.41
14.50

139.21132.17
159.70139.21132.17
159.70

0.164
0.162
0.155

0.017
0.017
0.020

0.131
0.127
0.115

0.197
0.196
0.194

152.88152.88

0.160

0.018

0.125

0.195

iv) with T3iv) with T4

14.12
15.62

156.40144.96156.40144.96

0.148
0.143

0.016
0.017

0.116
0.110

0.180
0.175

ii)
iii) with T1iii) with T2

Area V
Model

ĉ

QAIC

∆ QAICαse(α)α 95%LL

α 95%UL

i)
ii)

12.32
12.21

92.66
93.10

92.66
93.10

0.117
0.085

0.026
0.029

0.066
0.027

0.167
0.144

iii) with T1iii) with T2iii) with T3iii) with T4iv) with T1iv) with T2iv) with T3iv) with T4

11.31
11.41
10.55
12.49
7.98
7.81
6.67

104.25102.01
107.54104.25102.01
107.54

0.070
0.073
0.077

0.031
0.032
0.027

0.008
0.010
0.022

0.132
0.136
0.131

93.35
141.80137.49146.5893.35
141.80137.49146.58

0.086
0.094
0.095
0.104

0.031
0.031
0.027
0.024

0.026
0.033
0.040
0.057

0.147
0.155
0.150
0.151

10.49

109.52109.52

0.099

0.028

0.043

0.156

23

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Table 9a. Comparison of JARPA (Matsuoka et al., 2011)/JARPA II and IDCR-SOWER (Branch, 2011, here
those incorporating his comparable areas adjustments) abundance estimates of humpback whales in Areas
IV and V.
Area IV
Year

JARPA

IDCR/SOWER

estimate-CV-estimate
1,102

CV
0.46

1988/89
1989/90
1991/92
1993/94

5,325

0.302

4,167
-

0.53
-

5,408
2,747

0.188
0.153

-

-

1995/96
1997/98
1998/99
1999/00

8,066
10,657

0.142
0.166

-

-

16,7510.143

17,938-0.18-

2001/02
2003/04
2005/06
2007/08

31,13427,783

0.123
0.115

-

-

25,95829,067

0.263
0.255

-

-

1978/79

Area VYear
1980/81JARPA

IDCR/SOWER

estimateCVestimate

CV

-

-

1,876

0.60

1985/86

-

-

622

0.50

1990/91
1991/92

602
4,388
3,678

0.343
0.623
0.307

3,310
-

0.34
-

1992/93
1994/95
1996/97
1998/99

1,474

0.274

-

-

3,831
5,127

0.430
0.215

-

-

2,873
-

0.157
-

13,2460.20

2006/07

9,342
16,438

0.337
0.266

-

-

2008/09

13,894

0.338

-

-

2000/01
2002/03
2003/04
2004/05

Table 9b. Comparison of JARPA+JARPA II and IDCR-SOWER (Branch, 2011) rates of increase estimates inAreas IV and V. The values marked IDCR-SOWER are as estimated by Branch (2011) , whose estimatesof CVadd were zero for both these Areas; those marked IDCR-SOWER* revise Branch’s results byincorporating the base case estimates of CVadd obtained for each of these Areas from the analyses of thispaper (Table 7).
Area IV
Program

Period (Y/M/D)

JARPA
1989/12/31 - 2004/3/1
IDCR-SOWER 1978/12/28 - 1999/2/22

estimate

95%CILL

95%CIUL

0.136
0.148

0.084
0.081

0.187
0.215

Area V
Program

Period (Y/M/D)

estimate

95%CILL

95%CIUL

JARPA

1991/1/11 - 2005/3/8

0.145

0.076

0.215

0.122

0.053

0.191

IDCR-SOWER 1980/12/17 - 2004/2/28

24

SC/F14/J4

Figure 1. Stratification of the JARPA and JARPA II research area. During JARPA II, Areas IIIE and VIW werestratified into Northern and Southern strata.

25

SC/F14/J4

Figure 2a. Primary search effort (thin lines) and associated primary sightings (circle) of humpback whales in Area
IV (70oE-130oE) with the ice edge line (dotted) during the 1989/90 to 2007/08 JARPA surveys..

26

SC/F14/J4

Figure 2b. Primary search effort (thin lines) and associated primary sightings (circle) of humpback whales in Area
VW (130oE-165oE) with the ice edge line (dotted) during the 1990/91 to 2008/09 JARPA surveys..

27

SC/F14/J4

Figure 2b. (Cont.).

28

SC/F14/J4

Figure 2c. Primary search effort (thin lines) and associated primary sightings (circle) of humpback whales in Areas
VE and VIW (165oE-145oW) with the ice edge line (dotted) during the 1990/91 to 2008/09 JARPA surveys..

29

SC/F14/J4

Figure 2c. (Cont.).

30

SC/F14/J4

Figure 2d. Primary search effort (thin lines) and associated primary sightings (circle) of humpback whales in Area
IIIE (35oE-70oE) with the ice edge line (dotted) during the 1995/96 to 2007/08 JARPA surveys..

31

SC/F14/J4

Figure 3. Start and end dates of JARPA II surveys (2005/06-2008/09) for abundance estimation of humpback
whales in the survey area.

32

SC/F14/J4a) Areas IIIE, IV and part of V combined (35oE-175oE).
1989/90
IV-NW IV-NE
5
2
IV-SW IV-SE
3
1
IV-PB
4

1991/92
IV-NW IV-NE
5
1
IV-SW IV-SE
3
2
IV-PB
4

1993/94
IV-NW IV-NE
5
2
IV-SW IV-SE
3
1
IV-PB
4

1995/96
IV-NW IV-NE
III-E
3
5
1
IV-SW IV-SE
2
6
IV-PB
4

1997/98
IV-NW IV-NE
III-E
2
4
1
IV-SW IV-SE
5
3
IV-PB
6

1999/00
IV-NW IV-NE
III-E
2
3
1
IV-SW IV-SE
5
4
IV-PB
6

2001/02
IV-NW IV-NE
III-E
2
3
1
IV-SW IV-SE
5
4
IV-PB
6

2003/04
IV-NW IV-NE
III-E
2
3
1
IV-SW IV-SE
5
4
IV-PB
6

2005/06
III-NE IV-NW IV-NE V-NW V-NE
3
4
6
2
1
III-SE IV-SW IV-SE V-SW V-SE
3
4
6
2
1
IV-PB
5

2007/08
III-NE IV-NW IV-NE V-NW
V-NE
1
2
3
4
unsurveyed
III-SE IV-SW IV-SE V-SW V-SE
1
2
3
4
unsurveyed

IV-PB
unsurveyedb) Areas V and VIW combined (130oE-145oW)
1990/91
V-NW V-NE
2
4
V-SW V-SE
1
3

1992/93
V-NW V-NE
3
1
V-SW V-SE
2
4

1994/95
V-NW V-NE
2
3
V-SW V-SE
1
4

1996/97
V-NW V-NE
VI-W
4
2
1
V-SW V-SE
3
5

1998/99
V-NW V-NE
VI-W
2
1
5
V-SW V-SE
3
4

2000/01
V-NW V-NE
VI-W
4
2
1
V-SW V-SE
5
3

2002/03
V-NW V-NE
VI-W
4
2
1
V-SW V-SE
5
3

2004/05
V-NW V-NE
VI-W
4
2
1
V-SW V-SE
5
3

2006/07
V-NW V-NE VI-NW
42
1
V-SW V-SE VI-SW
4
3
1

2008/09
V-NW V-NE VI-NW
1
42
V-SW V-SE VI-SW
1
3
2

Figure 4. Survey order by strata for the JARPA cruises from 1989/90 to 2008/09. Key: III=Area III, IV=Area IV,
V=Area V, VI=Area VI, E=East, W=West, NW=North-West, NE=North-East, SW=South-West,
SE=South-East, PB= Prydz Bay. A common number in a season indicates that two strata were surveyed in
the same period. V-NE, V-SE and IV-PB strata could not be surveyed at all in 2007/08 season.

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SC/F14/J4

2007/08 IIIES

2005/06 IIIE

2005/06 SW

2007/08 IIIEN

2007/08 SW

2005/06 SE

2007/08 SE

2005/06 NW

2007/08 NW

2005/06 NE

2007/08 NE

Perpendicular distance (n. miles)

Figure 5a. Estimated detection probability functions (AIC-based selection between hazard rate and half-normal
forms) for humpback whales in Areas IIIE and IV during the 2005/06 and 2007/08 JARPA II surveys.
These results are for data combined across the SVC and SVP survey modes.
2005/06 NW+SW

2006/07
Area V

2007/08
NW+SW

2008/09
NW+SW

2008/09
NE+SE

2008/09 VIW

Perpendicular distance (n. miles)

Figure 5b. Estimated detection probability functions (AIC-based selection between hazard rate and half-normal
forms) for humpback whales in Areas V and VIW during 2005/06 - 2008/09 JARPA II surveys. These
results are for data combined across the SVC and SVP survey modes.

34

SC/F14/J4

50000
45000

Humpback whale
Area IV

Abundance estimation

40000
35000
30000
25000
20000
15000
10000
5000
0

1995/96

1997/98

1999/00

2001/02

2003/04

2005/06

2007/08

1996/97

1998/99

2000/01

2002/03

2004/05

2006/07

2008/09

1993/94

1991/92

1989/90

1986/87

1984/85

1982/83

1980/81

1978/79

Year

30000

Humpback whale
Area V

Abundance estimation

25000

20000

15000

10000

5000

0
1994/95

1992/93

1990/91

1988/89

1986/87

1984/85

1982/83

1980/81Year

Figure 6. Abundance estimates for humpback whales in Areas IV and V (south of 60oS), which were surveyed
primarily during January to February, from the JARPA and JARPA II surveys from 1989/90 to 2008/09.
Estimates from the IDCR-SOWER surveys (Branch, 2011) are shown by the filled circles. Vertical lines
show 95％ confidence intervals.

35

SC/F14/J4

50,00045,00040,000Abundance estimate

35,00030,00025,00020,00015,00010,0005,000
01986
1986/871991
199192

1996
1996/97

2001/02
2001

2006/07
2006

Year

Figure 7. Abundance estimates in Area IV and predicted abundance estimate by regression model (6). Verticallines show 95％ confidence intervals of abundance estimates.

36