SC/61/IA17

Preliminary examination of the effect of timing of ice
melting on the density of Antarctic minke whales - a newenvironmental indexHIROTO MURASE1 AND PAUL ENSOR2
1
2

The Institute of Cetacean Research, 4-5 Toyomi-cho, Chuo-ku, Tokyo, 104-0055, Japan
Governors Bay, Lyttelton RD1, New Zealand
ABSTRACT
Effect of days after sea ice melting on densities of Antarctic minke whales was
examined in the Weddell Sea (0°-60°W; Area II as defined by the IWC) of Antarctic.
Area II was surveyed in 1986/87 as second circumpolar survey (CPII) and, in 1996/97
and 1997/98 as third circumpolar survey (CPIII). This paper corresponds to therecommendation raised in 60th IWC/SC. CPII and CPIII were surveyed in same
season (austral summer from late December to early February). However, allocationsof survey effort in IO mode in reference to timing of sea ice melting were different
between CPII and CPIII. Peak of survey effort was after 20 days of sea ice melting in
CPII while it was after 50 days in CPIII. Densities of minke whales were high rightafter the sea ice meting and they declined subsequently. Consideration of effect ofdays after sea ice melting on abundance estimation of minke whales is criticallyimportant to understand reasons of the difference of abundances between CPII and
CPIII. Direct comparison of abundance between CPII and CPIII is not valid at thisstage because the timing of survey in terms of timing of sea ice melting is different.
We only focus on Area II in the present study as preliminary attempt. It is necessary toinvestigate the relationship in other areas to determine whether it is regional or
circumpolar phenomena.

INTROIDUCTION
The International Whaling Commission (IWC) has conducted the Antarctic minke whale(Balaenoptera bonaerensis) abundance assessment cruises since 1978/79 in the Antarctic in
austral summer. The names of the cruises were firstly the International Decade of Cetacean
Research programme (IDCR, from 1978/79 to 1995/96) and then the Southern Ocean Whaleand Ecosystem Research programme (SOWER, from 1996/97 to present). Matsuoka et al.
(2003) presented an extensive review of these cruises. To the present time, these cruises
covered three circumpolar surveys for the purpose of comprehensive assessments. Abundance
estimates were calculated using each circumpolar data set; 1978/79-1983/84 (first circumpolar,
CPI), 1984/85-1990/91 (second circumpolar, CPII) and 1991/92-2003/2004 (third
circumpolar, CPIII) (Branch, 2006). A noticeable abundance decline from CPII to the CPIII
using the IWC standard abundance estimation method (Branch, 2006) has raised questions
whether the decline is true or apparent. Discussion on reasons for differences between minke
whale abundance estimates between CPII and CPIII is ongoing in the Scientific Committee of
IWC (IWC/SC).
It is well documented that minke whales are aggregated along sea ice edge while they
spend their time in Antarctic waters in austral summer (Kasamatsu et al., 2000) where their1prey, krill, is abundant (Murase et al., 2002). However, high densities of minke whales havebeen observed in offshore of sea ice edge in some occasion. It was reported that high densities
of minke whales were observed offshore region of the Weddell Sea (0°-60°W; Area II as
defined by the IWC) in CPII (Kasamatsu et al. 1998). Kasamatsu et al. (1998) investigatedrelationship between the density of minke whales and two environmental factors (sea surface
temperature and distance from the ice edge) but they found no clear relationships. Suchoffshore aggregation of minke whales was not observed in Area II in CPIII.
Position of sea ice edge rapidly changes in austral summer because of process ofmelting (Calvalieri and Parkinson, 2008). Phytoplankton bloom is associated with sea ice
retreat (Lancelot et al., 1993). Density of Antarctic krill (Euphausia superba) is generallyhigh around the sea ice edge in the Weddell Sea (e.g. Brierley et al., 2002; Daly andMacaulay, 1988; Donnelly et al., 2006; Godlewska, 1993). Some of these results suggested
that density of krill was high just outside of the ice edge (Daly and Macaulay, 1988; Donnelly
et al., 2006; Godlewska, 1993). Receding speed of sea ice edge may exceed swimming speedof krill (Brierley and Thomas, 2002). Brierley and Thomas (2002) postulated that distributionof krill in offshore side of sea ice edge could be the results of receding of sea ice above krill tosouth. If the postulate is true, such dynamic interaction between sea ice melting and krill
could affect distribution pattern of minke whales.
The effect of sea ice dynamics on distribution pattern of minke whales was discussed
in the Sub-Committee on In-Depth Assessment (IA) in the 60th IWC/SC (IWC, 2009). Suchinteraction was observed, for example, in the northeastern region of Area II during CPII. Theinteraction could account for reasons of differences between minke whale abundance
estimates from CPII and CPIII. The IA Sub-Committee recommended to the sea-ice
intercessional group to investigate the interaction. This paper corresponds to therecommendation. This paper examined the effect of timing of ice melting on the density ofminke whales in Area II. Specifically, following points were examined: 1) difference ofsighting survey effort allocation between CPII and CPIII in relation to days after sea ice
melting, 2) relationship between days after sea ice melting and school density of minke
whales.
MATERIALS AND METHODS
Data sets
Sea ice
To calculate timing of days after sea ice melting, satellite derived sea ice data were used.
Bootstrap Sea Ice Concentrations from Nimbus-7 SMMR and DMSP SSM/I (Comiso, 1999)
was used in the analysis. The data were recorded daily basis. The original data was in thepolar stereographic projection and it was converted to the Zenithal equal area projection. The
sea ice data (sea ice concentration) was recorded at 25 km by 25 km grid resolution.
Whale sighting data
IWC divided southern ocean into six areas for the management of baleen whales(Donovan, 1992). Area II is set between 0° and 60°W (Fig. 1). Sighting survey for theabundance estimation of Antarctic minke whale was conducted in austral summer. CPII
survey was conducted from December 28, 1986 to February 4, 1987. Full longitudinalcoverage was made in 1986/87 cruise. In CPIII, Area II was divided into two at 30°W.
Eastern half (0°-30°W) was surveyed in 1996/97 cruise (January 16-February 14, 1997)
whereas western half (30°W-60°W) was surveyed in 1997/98 cruise (January 18-February 14,1998). Latitudinal coverage was south of 60°S to ice edge except 0-°20°W of CPII where the2northern limit was set at 61°S-63°S. Sighting survey effort (surveyed distance), positions ofsighted Antarctic minke whale and survey area boundary stored in the IWC DatabaseEstimation Software System (DESS) version 3.0 (Strindberg and Burt, 2000) were used.
There were two survey modes: the closing mode and the passing mode withindependent observer mode (IO mode). In closing mode, two observers were stationed in top
barrel while no observer was stationed in independent observation platform (IOP). Once asighting was made, the ship approaches to the sighting to confirm species and school size. In
the IO mode, two observers were stationed in top barrel while an observer was stationed in
IOP. No approach is made to sightings in the IO mode.
Analysis methods
Surveyed distance was divided into 5 km segments. For each 5 km segment, days aftersea ice melting were calculated. A program search sea ice data until it found the day withmore than 15 % sea ice concentrations which corresponded to segmented survey effort data.
Sea ice concentrations more than 15% was commonly used as definition of sea ice edge in thesea ice analyses (e.g. Bjøgo et al., 1997; Hanna 2001; Zwally et al., 2002). After the days
after sea ice melting were calculated, the data were aggregated into 30 km by 30 km grids byusing ArcGIS 9.3. The data were aggregated by survey vessels, survey stratum and survey
mode. Total effort, total number of schools of minke whales and mean days of days after sea
ice melting were calculated for each 30 km by 30 km grids. Density of school of minke
whales was calculated by using effective search half width (esw) reported in Branch (2006).
RESULTS AND DISCUSSION
Geographic distribution patterns of the sighting survey effort in Area II in relation with days
after sea ice melting are shown in Fig. 1. As indicated in the figure, timing of the survey in
CPIII was later than CPII in terms of timing of sea ice melting. Peak of the survey effort in
CPIII was around 50 days after sea ice melting while it was around 20 days in CPII (Fig. 2).
Mean of density of school of minke whales in each 10 days bin indicated that the density
declined as days after sea melting increased (Fig. 3).
In response to last year’s recommendation by the IA sub-committee specifically, effectof timing of sea ice melting on density of school of minke whales in the northeastern regionof Area II (Fig. 4) was examined. The general patterns were same as in the case of entire areaof Area II. Peak of the survey effort in CPIII was around 50 days after sea ice melting while it
was around 20 days in CPII (Fig. 5). In CPIII, no survey was conducted in the area with lessthan 30 days after sea ice melting where density was high in CPII (Fig. 6).
This qualitative study suggested the negative relationship between the timing of sea
ice melting and school density of minke whales. Further consideration of effect of days aftersea ice melting on abundance estimation of minke whales is required to understand the reasonof the difference of abundances between CPII and CPIII. Direct comparison of abundance
between CPII and CPIII is not valid because the timing of survey in terms of timing of sea ice
melting is different.
In this study, we only focused on school density in Area II. Same analysis in other
Areas must be conducted to detect whether the relationship is global phenomena at thecircumpolar scale. In addition, the effect of the timing of sea ice melting on school size must
be examined in the future. The esw reported in Branch (2006) was used in this study but thetiming of sea ice melting could affect the estimation of esw itself. Ultimately, the effect oftiming of sea ice melting should be considered in newly developed abundance estimation
models, if the further qualitative analysis provides promising results.
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Fig. 1. Spatial distribution patterns of the sighting survey efforts in terms of days after sea ice melting: CPII (a) and CPIII (b). Sighting efforts
and sighting positions of minke whales: CPII (c) and CPIII (d). IO and closing mode survey data are shown in the maps simultaneously in thesefigures.
640Effort in IO mode (%)

35
30

CPII
CPIII

25
20
15
10
5

0
10 days

20 days

30 days

40 days

50 days

60 days

70 days

80 days

90 days

90 days <Days after sea ice melting
Fig. 2. Frequency of IO mode survey effort distances in the entire area of Area II in relation todays after sea ice melting. Frequency is calculated in each 10 days bin.

School density in IO mode (Sch./km2)

0.16
0.14

CPII
0.12

CPIII
0.1
0.08
0.06
0.04
0.02

0
≤10 days≤20 days≤30 days≤40 days≤50 days

50 days <Days after sea ice melting
Fig. 3. School density of Antarcitic minke whales in the entire area of Area II in relation todays after sea ice melting. Mean of the density in each 10 days bin is caluculated. School
density in IO mode is shown.

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Fig. 4. EN stratum in CPIII (hatched area) is overlaid on EN (purple area) and ES1 (greenarea) in CPII. These area are defined as the northeastern region of Area II in this study.

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80

CPII
CPIII

Effort in IO mode (%)

70
60
50
40
30
20
10

0
10 days

20 days

30 days

40 days

50 days

60 days

Days after sea ice melting
Fig. 5. Frequency of IO mode survey effort distances in the northeastern region of Area II in
relation to days after sea ice melting. Frequency is calculated in each 10 days bin.

School density in IO mode (Sch./km2)

0.14

CPII
0.12

CPIII
0.1

0.08

0.06

0.04

0.02

0
≤10 days≤20 days≤30 days≤40 days≤50 days

Days after sea ice melting
Fig. 6. School density of Antarcitic minke whales in the northeastern region of Area II in
relation to days after sea ice melting. Mean of the density in each 10 days bin is caluculated.
School density in IO mode is shown.

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