Sexual Dimorphism in the Adult South African (Cape) Fur Seal 'Arctocephalus pusillus pusillus' (Pinnipedia: Otariidae): Standard Body Length and Skull Morphology

2010·9.7 MB·English

by  C L Stewardson

Sexual Dimorphism in the Adult South African (Cape) Fur
Se^\ Arctocephaluspusilluspusillus (Pinnipedia: Otariidae):
Standard Body Length and Skull Morphology
C. L. Stewardson', T. Prvan^, M. A. Meyer^ and R. J. Ritchie''*
'Botany and Zoology, Australian National University, Canberra, ACT 2601, Australia.
(PresentAddress, Fisheries and Marine Sciences Program Bureau ofRural Sciences, The Department of
Agriculture, Fisheries and Forestry, Canberra, ACT 2601, Australia).
NSW
^Department ofStatistics, Macquarie University, 2109, Australia.
^Marine and Coastal Management (MCM), Rogge Bay, Cape Town, South Africa.
NSW
'School ofBiological Sciences, The University ofSydney, 2006, Australia.
*CorrespondingAuthor: Raymond J. Ritchie, School ofBiological Sciences, The University ofSydney, NSW
2006, Australia, email [email protected].
Stewardson, C.L Prvan, T., Meyer, M.A. and Ritchie, R.J. (2010). Sexual dimorphism inthe adult
SouthAfrican (Cape) farsealArctocephaluspusilluspusillus (Pinnipedia: Otariidae): standard body
length and skull morphology. Proceedings oftheLinnean Society ofNew South Wales 131, 119-140.
We examine differences in standardbody length and skull morphology ofmale (n= 65) andfemale (n=
18) SouthAfrican (Cape) fur seals, Arctocephahispiisilhispiisilliis, from the coast of southern Africa
with the aim to develop an objective method for determining the sex offur seal skulls. Males were
found to be significantly larger than females in standard body length, with K-means cluster analysis
successfully identifying 2 relatively homogeneous groups. Principal component analysis (covariance
matrix) showed that the underlying data structure for male and female skull variables was different, and
that most ofthis variation was expressed in overall skull size rather than shape. Males were signiticantly
larger than females in 30 ofthe 31 skull variables. Breadth ofbrain case was significantly different for the
genders. Relativetocondylobasal length,males were significantly largerthan females in 13 ofthe 31 skull
variables used in the present study. These were gnathion to posterior end ofnasals, breadth at preorbital
processes, least interorbital constriction, breadth at supraorbital processes, greatest bicanine breadth,
breadth of palate at postcanine 1 and 3, calvarial breadth, mastoid breadth, gnathion to anterior of
foramen infraorbital, gnathion to posterior border of preorbital process, height of skull at base of
mastoid and height ofmandible atmeatus. In males, these variableswere associatedwith the acquisition
anddefenseofterritory(e.g., largeheadsize andmass; increasedstructuralstrengthoftheskull; increased
bite capacity). Two skull ratio parameters, breadth ofbraincase/condylobasal length and length ofupper
postcanine row/condylobasal length were significantly higher in females compared to males. Based solely
on the skull data, mature males can be reliably distinguished from immature males and females using
both (a) Classification and Regression Tree (CART) and (b) Hierarchical ClusterAnalysis. Both
approaches had difficulty in reliably distinguishing immature males from females. The Classification
and Regression Tree methodwas the more successhil in correctly distinguishing immature males from
females.
Manuscript received October 2009, accepted for publication 21 April 2010.
1
KEYWORDS: Arctocephahis pusilhis pusilhis, identification of sex, muldvariate analysis, Otariidae,
polygyny,Pinnipeds,principlecomponentandcladisticanalysis,sexualdimorphism,skullmorphometries,
SouthAfrica fur seal, standard body length.
SEXUAL DIMORPHISM IN ARCTOCEPHALUS PUSILLUS PUSILLUS
INTRODUCTION Adult male fur seals are about 3 to 5 times
heavier and about 1/4 longer than adult females
Sexual dimorphism isa form oFnon-gcographic (Stirling, 1983; David, 1989; Boncss, 1991; Guinet et
variation tliat can be generated in a species by al., 1998; Arnould and Warneke, 2002; Stewardson et
the process of sexual selection (Bartholomew, al., 2009). Large body size is in itselfan intimidating
1970; Alexander et al., 1979; Stirling, 1983). form of display to discourage rival males from
Highly polygynous species such as fur seals, sea attempting an actual physical challenge and in the
lions and elephant seals, generally exhibit a high event of a physical challenge is advantageous in
degree of sexual dimorphism (Laws, 1953; competitive interactions and enables breeding bulls
Ralls, 1977; Alexander et al., 1979; Stirling, to remain resident on territories for longer periods
1983; Sirianni and Swindler, 1985; McLaren, of time without feeding (Rand, 1967; Miller, 1975;
1993; Arnould and Warneke, 2002). Differences Payne, 1978, 1979; Stirling, 1970, 1983). Strong fore-
in reproductive success among males ofthese species quarters, enlarged jaw and neck muscles, robust
are large, and competition for access to females canines, increased structural strength of the skull,
is intense. Selection pressure appears to favour and long, thick neck hair (protective mane or wig),
the development of traits that enhance male also appear to be potentially advantageous in the
fighting ability, including intimidating body acquisition and maintenance of territory; quan-
size, weaponry and skin thickness (Laws, 1953; titative information on these features, however, are
Bartholomew, 1970; Le Boeuf, 1974;Alexander et al., lacking (Miller, 1991).
1979;McCann, 1981; Stirling, 1983). Here we examine morphological differences
Breeding Southern fur seals (Arctocephaliis between skulls (n = 31 variables) of male (n =
spp.) are among the most territorial of animals, 65) and female (n = 18) South African (Cape) fur
are strongly sexually dimorphic in body size, sealsArctocephaluspusilluspusillus, from the coast
polygynous and gregarious (Peterson, 1968; Harrison of southern Africa. Body length information was
etal., 1968; Stirling, 1970; Bryden, 1972; Alexander also included in analyses where available. Where
et al, 1979; Bonner, 1981; McKenzie et al., 2007). possible, comparisons aremadetothe closelyrelated
In the southern hemisphere, breeding status male Australian fur seal Arctocephaluspusillus doriferus
fur seals (beachmasters) generally arrive at the (King, 1969; Brunner, 1998ab, 2000; Brunner et
rookeries around November to establish ter- al., 2002; Arnould and Warneke, 2002; Brunner et
ritories. Pregnant females arrive soon after. Once al., 2004; Stewardson et al, 2008, 2009) and other
females are present in the male's territory, males otarid species for which morphological data are
guard females until they come into oestrus post- available such as the Steller sea lion {Eumetopias
partum. Females give birth within one week of jubatus) (Winship et al., 2001).
coming ashore and then mate with the nearest For many life history, conservation and
male during the short breeding (pupping/ mating) ecological studies it is important to be able to
season (Guinet et al., 1998). Males seldom leave determine the sex of skull material in museum
the territory until the breeding season is over (Rand, collections, skulls of animals found dead or
1967; Stirling, 1970; Miller 1974; Peterson, 1968; accidentally killed in fishing operations or killed in
Harrison et al, 1968; Bonner, 1981). After mating, other ways. Often only the skull is available. We
the territorial system gradually breaks down and show that two types of multivariate analysis [(a)
males return to sea to replenish their physiological Classification and Regression Tree (CART)
reserves. Males do not care for their young. and (b) Hierarchical Cluster Analysis] can be used
When establishing territories, male fur seals to objectively distinguish mature male, immature
threaten each other with vocal and visual displays, male and female skulls ofthe South African fur seal
emphasising their size, to intimidate competitors {A. pusillus pusillus). By extension the approach
(Bonner, 1968; Stirling, 1970; Stirling and Warneke, could be applied to other fur seals, particularly the
1971; Miller, 1974; Shaughnessy and Ross, 1980). Australian fur seal {A. pusillus doriferus) and the
Much time is spent in making visual and vocal threats New Zealand fiir seal {A. australisforsteri).
to rival males and chasing them away, but fights may
develop, occasionally resulting in severe injury
or death (Rand, 1967; Stirling, 1970; Shaughnessy MATERIALSAND METHODS
and Ross, 1980; Trillmich, 1984; Campagna and Le
Boeuf, 1988). Collection ofspecimens
South African (Cape) fur seals {Arctocephalus
120 Proc. Linn. Soc. N.S.W., 131, 2010
C.L. STEWARDSON, T. PRVAN, M.A. MEYERAND R.J. RITCHIE
pusilhis pusilhis) were collected along the Eastern Museum records
Cape coast of South Africa between Plettenberg The data setonthe males used inthepresent study
Bay (34° 03'S, 23° 24'E) and East London (33° has alreadybeenpublished in (Stewardson et al., 2008)
03'S 27 54'E), fromAugust 1978 to December 1995 and fiarther details can be found in Stewardson (2001).
(Stewardson et al., 2008, 2009), and accessioned The list ofmale specimens used in the present study is
at the Port Elizabeth Museum (PEM). Specimens shown in Appendix 1. There were 39 adult males, 24
were collected dead or dying from the coastline and immature sub adult males and twojuvenile males only
some from accidental drowning in fishnets; none 2 years old. No standard body length measurements
were deliberately killed (cf. Guinet et al., 1998). were available on four (4) of the adult males (PEM
Routine necropsies were performed and biological 2004, PEM 2007, PEM 2013, PEM 2036) but it is
parameters recorded, based on recommendations unlikely that any adult male skulls wouldbe assigned
of the Committee on Marine Mammals (1967). tothewrongsexbecausematuremale skulls aremuch
Animals were aged from incremental lines observed largerthan females and more heavily built. However,
in the dentine of upper canines (Stewardson et al., there were no SBL measurements available on four
2008, 2009). The sample was supplemented with (4) of the immature males (PEM 2006, PEM 2009,
measurements from 1 1 known-aged adult males PEM 2010 and PEM 2014). This raises some doubts
(animals tagged as pups) from Marine and Coastal aboutthecertaintythatthesespecimenswerecorrectly
Management (MCM), Cape Town. The specimens identified as males. Generally if the SBL had been
MCM
from the collection have accession numbers determined, the genitalia would have been available
MCM MCM MCM
beginningwith (e.g. 1809). The for examination. The raw data set for the females
collection also housed 5 tag-aged adult females (18 adults, 4 juveniles and sub adults) is shown in
and 3 tag-aged sub adult/juvenile females. Appendix 2 and the means and standard deviations
All animals considered adults had reached full inAppendix 3.All the female carcasses were complete
reproductive capacity, i.e., males > 8 y (Stewardson enough forreliable determination oftheir sex.
et al., 1998; Stewardson et al., 2008, 2009) and
females > 3 y (J.H.M. David, pers. comm.). When Skull variables
age was not known, males > 170 cm (Stewardson et A total of 32 skull measurements were recorded
al., 2008, 2009) and females > 135 cm (Guinet et al., (Table 1). However, one ofthese variables, height of
1998; J.H.M. David, pers. comm.) were considered sagittal crest, was not examined statistically because
fully adult males and females and included in the there were few measurements for females and also
analysis as adults even iftheir dentition age was less becausewehavefoundthatsagittalcrestmeasurements
than 8 y for males. South African fur seals > 12 y seemtoprovidelittleusefialinformationinmaleskulls
cannot be aged from counts of growth layer groups (Stewardson et al., 2008). Thus, statistical analysis
(GLG) in the dentine of upper canines because of was conducted on 31 of the 32 variables. Skull
closure of the pulp cavity. Estimated longevity for preparation and measurement procedures follow
male SouthAfrican Furseals is c. 20y(Wickens, 1993; Stewardson et al. (2008).
Stewardson et al., 2008, 2009). There is much less
information on the longevity offemale South African Statistical analyses
fiar seals (despite the large numbers ofanimals that are Six methods ofanalyses were employed. Firstly,
shot in culling and hunting operations) but Wickens two sample t-tests (assuming equal variance) were
(1993) based on zoo records concluded that females used to test the hypothesis that the mean value of a
could liveto c. 30 y. skull variable was significantly different for males
Australian male fur seals {A. pusilhis dorifems) and females against an appropriate alternative
alsohaveasimilarlifespanofabout20yearsbutfemale y^
^ 0' HTiales f'^females' "I'r^males f'^femafes' 1" ^females
Australian fiar seals based on age tags are currently > 111^3,^3). Since more than 1 skull variable was being
knownto live towell over20y (Amould andWameke, considered, the Bonferroni correction was used - the
2002). Seal life spans in arange ofseal species average experiment-wise error rate was divided by the total
about 15 to 20 y for males and in excess of20 y for number oftests performed (Cochran, 1977).
females (New Zealand fur seal {A. australlsforsteri), Secondly, K-means clustering, a non-
McKenzie et al., 2007; Antarctic fur seal {A. gazelld), hierarchical cluster analysis was used to classify
Payne, 1978, 1979); Steller sea hon {Eumetopias observations into 1 of2 groups based on some ofthe
jubatus), Winship et al., 2001). skull variables. Observations on some of the skull
variables fromboth sexeswerepooled sothat initially
there is a single cluster with its centre as the
Proc. Linn. Soc. N.S.W., 131, 2010 121
SEXUAL DIMORPHISM IN ARCTOCEPHALUS PUSILLUS PUSILLUS
moan vector of the variables considered. These PLUS (MathSoft, Inc., Seattle, 1999, 5.1).
observations were then assigned at random to two Fifthly, the data mining approach. Classification
sets. Step entails calculating the mean vector of and Regression Trees (CART), a technique that
1
the variables considered (ccntroid) for each set. generates a binary decision tree, was used to classify
Step 2 entails allocating each observation to the the observations. In this approach, the set of data is
clusterwhosecentroid is closest to that observation. progressivelysub-dividedbasedonvaluesofpredictor
These two steps are repeated until a stopping variables into groups that contain higher proportions
criterion is met (there is no further change in the of "successes" and higher proportions of "failures".
assignment of the data points). Before doing this The relative importance of the predictor variables
all variables were standardised. Closest neighbour is assessed in terms of how much they contribute to
(similarity) was measured using Euclidean distance successful splits into more homogeneous sub-groups.
(Johnson and Wichem, 1992). The groupings ofskull The classification is most commonly earned out using
variables we considered were dorsal, palatal, lateral the Gini criterion, which always selects the split that
and mandibular. We also used k-means clustering to maximises the proportion of "successes" in one of
classify observations into 1 of2 groups using standard the groups (Petocz, 2003). Data mining techniques
body length. are attractive because no distributional assumptions
Thirdly, plots oflog,ofeachskullvariableagainst are needed, data sets can have missing data and
log^ofstandard body length (SBL) for the genders analyses are less time consuming. The training data
were examined. 'Robust' regression (Huber M- usedto createthe binary decision setwas the setofall
Regression) was usedto fit straight lines (log y = log a animals that have already been determined to be adult
+ b log x) to the transfoiTned data (Weisberg, 1985; males, immature males and mature females. SPSS
Myers, 1990). Clementine 12.0 was used for the analysis.
Fourthly, principal component analysis (PCA) Finally, Minitab was also used to perform
was used. Oneuseful application ofPCAisidentifying hierarchical clustering and produce dendrograms
the most important sources ofvariation in anatomical showing the degree ofsimilarity ofthe skull data for
measurements for various species (Jackson, 1991; males, females and immature males. In general, the
Jolliffe, 2002). When the covariance matrix is used and conclusions reached were similar to those from the
the data has not been standardized the first principle CART analysis: it was possible to distinguish mature
component (PC)usuallyhas all positive coefficients males from immature males and mature females but
and according to Jolliffe (2002) this reflects the it was not possible to clearly distinguish immature
overall 'size' of the individuals. The other PCs males from females.
usually contrast some measurements with others Unless otherwise statedvalues are means quoted
and according to Jolliffe (2002) this can often be ± standard errors with the number of data points in
interpreted as reflecting certain aspects of 'shape', brackets.
which are important to the species.
Skull measurements were recorded in the same
units; therefore a covariance matrix was used to RESULTS
calculate PCs (however this gives greater weight to
larger,andhencepossiblymorevariablemeasurements Standard body length (SBL)
because the variables are not all treated on an equal SBL ranged from 157-201 cm in males (n =
footing). Genders were examined separately 33, SBL was not recorded for 4 of the adult males)
because the grouped PCA was quite different, and 135-179 cm in females (n = 18). Mean lengths
in most cases, to either the separate male PCA or were 182.9 ± 2.3 (n = 33) and 149.1 ± 2.5 (n = 18),
female PCA. respectively. The two sample t-tests on our data
PCA and two sample t-tests were calculated in indicated that adult males were significantly larger
Minitab (Minitab Inc., Slate College, 1999, 12.23). than adultfemales (Table 1). Theratioofmean female
K-means cluster analyses for skull variables and SBL to mean male SBL was 1:1.23.
SBL were calculated in Minitab (Minitab Inc., K-means clusteranalysis successfully identified2
Slate College, 1999, 12.23) and in SPSS (SPSS Inc., relatively homogeneous groups from the pooled
Chicago, Illinois, 1989-1999, 9.0.1), respectively. data, i.e., cluster 1,predominantlymales andcluster2,
This was necessary because Minitab could only predominantly females (Table 2). Ofthe 18 females,
perform K-means cluster analysis for 2 or more 17 (94%) were correctlyclassified. Ofthe 33 males, 28
variables, therefore SBL (a single variable) was (85%) were correctly classified.
analysed in SPSS. The regressions were fitted in S-
122 Proc. Linn. Soc. N.S.W., 131, 2010
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Proc. Linn. Soc. N.S.W., 131, 2010 125
SEXUAL DIMORPHISM IN ARCTOCEPHALUS PUSILLUS PUSILLUS
Table 2: Classification ofskull measurements ofSouth African fur seals using K-means clusters analy-
sis, n is the number ofanimals. All variables except standard body length (SBL) were standardised
(dorsal, palatal and mandibular).
Skullvariables Sex Cluster1 Cluster2 n
Male 22 (96%) (4%) 23
1
Dorsal
Female 11 (100%) 11
Male 24 (92%) 2 (8%) 26
Palatal
Female 17(100%) 17
Male 28 (80%) 7 (20%) 35
Lateral
Female 10(100%) 17
Male 25 (93%) 2 (7%) 27
Mandibular
Female (6%) 16(94%) 17
1
Male 28 (85%) 5(15%) 33
Standardbodylength
Female (6%) 17(94%) 18
1
Skull variables of mandibular tooth row (M29) (Table 1). Height
Absolute skull size: two sample t-tests ofsagittal crest (L27) was not examined statistically
The two sample t-tests indicated that 30 of because there were too many skulls with missing or
the 31 mean skull variables were significantly damaged sagittal crests.
larger in males than in females, i.e., we reject H^ in
favour ofH^: \i^^^^^^>\i^^^^^^^(Table 1, Fig. 1). Mean value Relative skull size: two sample t-tests
of breadth of brain case (D9) was not significantly When skull variables were analysed relative to
different for the genders (Table 1). The coefficient condylobasal length (CBL, Dl), males were found
of variation (C.V.) was larger in males, with the to be significantly larger than females for 13 (43%)
following exceptions: least interorbital constriction variables: (1) gnathion to posterior end of nasals
(D7), breadth of brain case (D9), gnathion to (D3), (2) breadth at preorbital processes (D8), (3)
anterior of foramen infraorbital (L24) and length least interorbital constriction (D7), (4) breadth
at supraorbital processes (D8), (5)
250
greatestbicanine breadth (PI2), (6)
.' breadth of palate at postcanine 1
200
Fig. 1: Mean values of31 skullvar-
iables for male and female South
African fur seals. Numbers cor-
150 respond to skull variables listed in
Table 1 (numbers 1-9 correspond
to parameters Dl to D9, 10-23 to
OJ
PIO to P23 and 24-32 to L24 to
100 L32). Numbers above the dashed
line, males > females; numbers on
the line, males = females; numbers
50 below the line, females > males.
Minitab could only perform K-
means cluster analysis if there
was > 2 variables, therefore SBL
(a single variable) was analysed in
o 50 100 150 200 SPSS. SBL was not recorded for 4
Females (cm) ofthe 39 males (i.e., n = 35).
126 Proc. Linn. Soc. N.S.W., 131, 2010
1
ex. STEWARDSON, T. PRVAN, M.A. MEYERAND R.J. RITCHIE
The remaining 15 (50%)
variables were not significantly
different for the genders (Table
1). Since males were larger than
females in 'absolute size', this
suggested that the 15 variables
were proportionate to CBL
regardless of sex, i.e., the
ratio relative to CBL (Dl) was
E
significantly different for the
genders.
CO The coefficient of variation
o
for values 'relative to CBL'
OS
was larger in males for about
1/3 rd of all variables (Table 1).
Exceptions were breadth at pre-
orbital processes (D6), least
interorbital constriction (D7),
palatal notch to incisors (PIO),
breadth of zygomatic root of
maxilla (P14), breadth of palate
at postcanine 5 (P17), gnathion
to foramen infraorbital (L24),
0.4 0.6 0.8
gnathion to hind border of
Females (cm) preorbital process (L25),
length of mandible (M28) and
length of mandibular tooth row
Fig. 2: Mean values of 30 skull variables, relative to condylobasal (M29). The coefficients of 2 of
length, for male and female South African fur seals. Numbers corre- these variables (least interorbital
spond to skull variables listed in Table 1 (numbers 1-9 correspond to constriction (D7) and length of
parameters Dl to D9, DlO-23 to PIO to P23 and P24-32 to L24 to L32). mandibular tooth row (M29))
Numbers above the line, males > females; numbers on the line, males were considerably larger in
= females, numbers below the line, females > males. females in both 'absolute size'
and size 'relative to CBL' (M29/
(P15), (7) breadth ofpalate at postcanine 3 (P16), Dl and D7/D1).
(8) calvarial breadth (P21), (9) mastoid breadth
(P22), (10) gnathion to foramen infraorbital K-means cluster analysis
(L24), (11) gnathion to hind border of preorbital K-meansclusteranalysissuccessfullyidentified
process (L25), (12) height of skull at bottom of 2 relatively homogeneous groups from the pooled
mastoid (L26) and (13) height of mandible at data, i.e., cluster 1, predominantly males and cluster
meatus (M31) (Table 1, Fig. 2). Differences between 2, predominantly females (Table 2). Classification
the genders were highly significant (P < 0.001); apart based on dorsal, palatal and mandibular obser-
from gnathion to foramen infraorbital (L24) and vations was highly successful in recapturing the 2
height of skull at bottom of mastoid (L26), which groups. Classification based on lateral observations
were significant at the 5% level (Table 1). was less successful.
Breadth of brain case (D9) was significantly Apart from 1 mandibular variable, all females
different in 'absolute size' for males and females, were correctly classified. The majority ofmales were
but 'relative to CBL' parameterD9/D1 forfemales correctly classified with the following exceptions -
was larger than males (Table 1). Length of upper dorsal, 2 palatal, 2 mandibular and 7 lateral variables
postcanine row (Pll) was larger in 'absolute size' in were incorrectly classified as females (Table 2).
males, but 'relative to CBL' Pll/Dl in females was Misclassification occurred in small males only.
larger than in males (Table 1).
Proc. Linn. Soc. N.S.W., 131, 2010 127
SEXUAL DIMORPHISM IN ARCTOCEPHALUS PUSILLUS PUSILLUS
Fig. 3 Fig. 4
4.2
#•
4.1
E E
E 5.5 4.0- •.'*.
^ >^
C 5.4 D jvi.
3.9
OJ
• ftT* •
if> 5.3 DQ 3.8- X"'
Q
o <cU J/
>O, 5.2 'c 3.7-
oJ (o0 /•• # .v>-
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CO 3.6- •••
X"
• ><^
>
3.5-
4.4 4.5 4.6 4.7 4.8 4.9 5.0 5.1 5.2 5.3 03 /•y y
Ln Seal Body Length (cm) <1u— / • ^•
CD 3.4-
X
c y
_l • ^
3.3-
Fig. 5
4.4 4.5 4.6 4.7 4.8 4.9 5.0 5.1 5.2 5.3
5.1
Ln Seal Body Length (cm)
5.0
Figs. 3, 4 & 5: Bivariate plot of: (3) log [CBL (Dl)
4.9
(mm)] on log (SBL(cm)); (4) log [greatest bicanine
breadth (P12) (mm)] on log (SBL (cm)); (5) log
4.8-1
[mastoid breadth (P22) (mm)] on log (SBL (cm).
Circles, males. Squares, females.
c 4.7
0)
o 4.6 The first 3 PCs accounted for most of the
"o variation. The first PC (PCI) can be interpreted
w
05 4.5 as a measure of overall skull size while PC2 and
PC3 define certain aspects of shape (Table 3).
4.4
Interpretations for the first 3 PCs for the 2 genders
are given in Table 4, together with the percentage of
4.3-1
total variation given by each PC. The variances of
4.2 corresponding PCs forthe two genders do vary and
I ' "'I 1 ' I ' 1 I I interpretations are dissimilar for mostpairs ofPCs.
4.4 4.5 4.6 4.7 4.8 4.9 5.0 5.1 5.2 5.3
Ln Seal Body Length (cm) Determining the gender ofan isolated skull
It is claimed that it is often possible to make
a visual determination of the gender of an isolated
Linear regression South African fur seal skull, provided the skull is
All transformed variables were regressed on from an adult animal (Brunner, 1998ab). However,
log, (SBL in cm). Three variables that best depicted visual identification based on morphology of the
maximum discrimination between the sexes, using skull alone can be misleading, e.g., young adult
regression, are given in Figs. 3, 4 and 5. These males can be mistaken for larger, older females
were CBL (Dl), greatest bicanine breadth (P12) and sex determination of a pup from examining
and mastoid breadth (P22). These plots (males the skull alone would be very difficult. A more
closed black circles, females grey squares) clearly objective procedure in determining sexes of skulls
show pronounced sexual dimorphism in adult South would be desirable. In most practical situations if
African fur seals, supporting findings of the two- the carcass was available for examination, the sex
sample t-test and K-means cluster analysis. would usually be detenninable, however for many
museum specimens only the skull is available. The
Principal component (PC) analysis
128 Proc. Linn. See. N.S.W., 131, 2010