Hzologzcal journal
of the Lznnean Society (1989), 38: 239-255.
With 9 figures
Morphological variation of species through
time
B. MICHAUX
Euolulionary Genelics Labornlory, ~ o o l o g yDepartment, UniuerszQ
Bag, A ~ c k l u n d ,New zealand
OJ' Auckland,
Private
Recezurd 16 A u ~ p s 11988, a t c e p d f i r publztnlzon 10 1,ebiuar)I I989
Ten measurements, taken from each oi' 7UO shells or h u r biologically distinct shallow marine
gastropod species, were uscd to define thr appr(ipriatc phcnotypcs in multidirncnsiorial space.
Canonical discriminant analysis was perl'ormcd on thr da ta arid a set of allocatory rules was drrivrd.
These allocatory rules, derived from extant specimens, werr than applird t o 644 fossil specimens ol
thrcc of these biological species. Fossil individuals occupy the appropriate phenotypic space as
defiiied by their modern descendants. 'I'he variation of fossil sample- nieaiib about the modern nieans
is illustrated. This variation is in the form of oscillations around the modern mean values arid i s
corrclatcd witti climate. 'I'he distinrtion bctwwn taxonomic and biological spccies is discussed. 'l'hr
rcsults 01' a number of previous studies are rr-examined in the light of this discussion. I t is argucd
that bioloSica1 groupings can only be reliably dotcrminrd when the appropriate da ta are available
for extant organisms. Extant organisms, which have good fossil records, should thercfbrc fi)mm the
basis of paleontological cvolutionary studies.
KEY WORDS:
species
-
Morphological s t
taxonomic species.
~
multivariate morphological analysis
~
/lrna/da
~
biological
CONTENTS
Introduction .
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
. . . . . . . . . . . . . . . . . . .
Materials .
. . . . . . . . . . . . . . . .
Modern specimens
. . . . . . . . . . . . . . . .
Fossil specimens .
Methods .
. . . . . . . . . . . . . . . . . . .
Derivation ol' canonical discriminant functions for the modern data .
. . . .
Allocation of fossil shells to species groups by modern canonical discriminant furictions
. . . . . . . . . . . . . . . . . . . .
Results
Conclusions .
. . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . .
Discussion.
Acknowledgements
. . . . . . . . . . . . . . . . .
References
. . . . . . . . . . . . . . . . . . .
239
241
241
242
243
243
244
244
246
252
254
254
IN 1 KODU C1 I O N
T h e theory of punctuated equilibria (Eldredge & Gould, 1972; Gould &
Eldredge, 1977) represents a taxic rather than a transformational approach to
evolution. Eldredge (1979) used the term taxic to describe a theoretical
approach which stresses that evolution is not simply change in form (the
transformational approach), but rather that change in form is associated with
0024-4066/89/ 1 10239
+ 1 7 $03 00j0
239
0 1989 7 he Llnrlran So(ic ty of 1.01idt~1i
240
B. MlCHAUX
speciation events. Species are not viewed as arbitrary divisions of a genealogical
continuum but as discrete evolutionary units. In rather stark terms speciation is
seen as the cause of form change, not as a consequence of form change.
Biological concepts of species (Mayr, 1942; Paterson, 1980, 1985) stress that
species have a biological reality which may or may not be reflected by
morphology. The taxonomic concept of species relies solely on morphological
criteria. Paterson (1981) has drawn attention to the dangers o f confusing these
two views of species which are embedded in distinct conceptual frameworks. In
terms of the taxic and transformational approaches discussed above, the former
uses a biological species concept whilst the latter employs the taxonomic concept.
Eldredge & Gould (1972) maintaincd that some proportion of (biological)
species show little changc in form through time and those changes that do occur
are oscillations about a ‘mean’ phenotype. T h e research programme of
punctuationists has thus becn to demonstrate stasis in (biological) species
through time. A number of detailed studies have been reported which confirm
that this phenomenon does exist (e.g. Gould, 1969; Eldredge & Gould, 1972;
Coope, 1979; Williamson, 1981; Cronin, 1985; Stanley & Yang, 1987).
Unfortunately, these studies have a methodological weakness in their attempts to
demonstrate the biological reality of the species concerned.
It is usually regarded as sufficient to base fossil identification on the taxonomic
criteria by which the study species or their descendants are recognized. If this is
how modern species are recognized, so the argument goes, then it is legitimate to
apply these criteria to the identification of fossil species. ‘This approach, in which
morphological characters that enable taxa to be identified are the basis of the
study, has been criticized as biasing results towards stasis because other variable
characters (that are taxonomically utiinformativc) are ignored (e.g. Levinton &
Simon, 1980). Levinton & Simon (1980) are also critical of the circularity
inherent in delimiting fossil species on the basis of morphological and
palaeontological evidence, and then using this evidence to describe patterns of
change a t thc species level in the fossil record.
Criticism can also be made of the assumption that taxonomic criteria are
necessarily adcquate to identify (biological) species (Lambert, Michaux &
White, 1987). In some cases taxonomic criteria may identify biological
groupings, but this is not always the case. Indeed, when detailed species
identification is required, as in biological control programmes, taxonomic
criteria have been found to be inadequate (e.g. Patcrson, 1964; Richardson,
Ellison & Averhoff, 1982).
The relationship between morphology and biological discreteness is not clear
cut particularly for groups that are morphologically rather simple. Problems can
arise when a single biological species exhibits considerable morphological
variation, particularly when morphs are distributed allopatrically. There are no
reliable criteria to distinguish between this case and that of two allopatric
biological species with Overlapping morphologies. Perhaps more important is the
case where cryptic groupings exist within a single taxonomically defined species.
In this case a number of biological species remain unrecognized. For these
ary to demonstrate that taxonomically defirled fossil species are
biologically discrete, rather than to assume they are, or to ignore the issue
altogether. ‘This issue seems to me to have considerable thcoretical importance
for any hypothesis regarding the evolutionary history of biological species. Before
MORPHOLOGICAL VAKIA’I ION OF SPECIES THROUGH I IME
24 1
any process is invoked to account for a pattern, that pattern must be established,
and the pattern can only be established when the units by which the pattern is
recognized have been justified both theoretically and empirically.
Vrba (1984) has made use of morphological elements of a species’ male-female
communication system to confirm biological discreteness, but this method is
obviously limited to species which have visible morphological characters
associated with this communication system. A more general method is suggested
in this paper, namely that studies of form change be concentrated on species that
not only have extensive fossil records but that are also extant. Using extant
species does not, of course, remove all doubts about the biological status of fossil
taxa-palaeontological data are unlikely ever to prove so definitive. What the
method outlined below does do is to allow species to be defined independently of
both morphology and palaeontological evidence, and to demonstrate the
biological discreteness of the extant taxa.
MATERIALS
Modern specimens
The four species used in this study belong to the marine gastropod genus
Amalda (Olividae: Ancillinae) . These species, A. auslralis, A. depressa, A . mucronata
and A. novaezelandiae, live around the coasts of the North Island and northern
part of the South Island of New Zealand. The genus has been present in this
region since the upper Eocene, and the four extant species since the MiocenePliocene boundary.
These four species have been shown to be biologically discrete because of the
absence of genetic hybrids when combinations of species occur in sympatry. This
lack of intcrbreeding is seen as a consequence of members of a species recognizing
only those individuals which share the same specific-mate recognition system
(SMRS) as mates (Paterson, 1985 and references therein). Despite considerable
morphological variation in both size and shape, each of the three species used in
this study are single species with no dctectable cryptic groupings. Full details or
the electrophoretic study of these species are provided in Michaux ( 1 987).
T,ive specimens (671) of these four species were collected for alloaymic analysis
from a number of sites throughout the known geographic range by the author
( A .australis = 327, A. depressa = 58, A. mucronala = 134, A. novaezelandiae = 152).
There are no external morphological characters that can be used to distinguish
juveniles from adults, therefore all size classes were included in proportion to
their occurrence in each geographic sample. The shclls of these individuals,
which were supplemented with 29 museum specimens of A. mucronala, were
photographed in ventral aspect (plane of aperture parallel to the camara lens).
From each negative, which included a scale (in mm), a x 2.5 photograph was
reproduced. ‘len measurements, shown in Fig. 1, wcre taken from each
photograph with dividers or parallel ruler, and the results recorded to the
nearest 0.5 mm. Measurements were recorded once with a true-scale precision of
0.2 mm. This is equivalent to 0.6y0 and 1 .8s/0 of mean shell length for the largest
and smallest species respectively. All samples are lodged in the paleontological
collection, Geology Department, IJniversity of Auckland.
Gastropod shell measurerncnt is a task fraught with problems. For Amalda the
242
B. MTCHALX
Figurr 1. Dctails of morphometric incasurcmrnts rinpluyed
ill
this study.
major difficulties are few identifiablc homologous points and thc presence of
extensive spire and parietal callus which obscures all sutures. The measurements
were chosen because they could he measured between identifiable homologous
points, they varied or had been reported to vary between the spccies, and finally
that taken in sum they gave the best possible description orshape. H1 and W1
give overall dimension, H2 and H3 are shape descriptors. H4 approximates spire
height which cannot be measured because callus obscures the body whorl suture.
W2 and H5 measure aperture size and give an estimation of aperture shape
(=shape of the generating curve sensu Raup (1964)). W3 and H6 measure
columella size and shape. W4 is a linear approximation of the angle at which the
generating curve is inclined away from the coiling axis.
Fossil specimen5
Fossil
specimens
(662;
A . auslralis = 243,
A. mucronata = 253
and
A. nouaezelandiae = 166) were measured as dccribed above. Fossil A. depremt
specimens were not common enough and were excluded from this part of the
study. Five hundred and twelve specimcris came from the Plio-Pleistocene
sequence at Waiiganui on the west coast of the North Island of New Zealand.
Full details of the stratigraphy of this sequence are provided by Fleming (1953)
and a summary is given in Table 1. A further 150 specimens of similar age from
MOKPHOLOGICAL VARIA’I’ION OF SPECIES THROUGH
nm
243
A ABLE 1. A synopsis of the stratigraphy of the Plio-Pleistocene sequence at
Wanganui. Based on Flemming ( 1953). Formation 1 = Brunswirk formation,
subsequent formations listed in Flcmming ( 1953) arc numbered sequentially
Currelation
Plristocrnr
Pliocenr
Stagr
Symbol
Hawera
Castlrcliffian
We
Nukumaruan
Wn
Waitotaran
Ww
Group
Pouaki
Shakespeare
Kai-iwi
Okehu
Maxwell
Nukumaru
Okiwa
Papararigi
Formation
1-2
%I4
15-2 I
22-26
27-32
33-38
39-45
46-49
the east coast of the North Island were also measured. All specimens are lodged
with the Geological Survey of New Zealand, Lower Hutt, Wellington.
M E’I’HODS
Canonical discriminant analysis is a multivariate ordination (dimensionreducing) technique which can be used to ‘describe’ shape. A specimen’s shape
(i.e. phenotype) is defined by the numeric values for the variables measured. In
this example, where ten such variables were used, the phenotype is described by
the specimen’s position in ten-dimensional space. The species identity of each
specimen was recorded. This identification was based on the morphological and
genetic data that were obtained from the living specimens described above. The
positions of members of each species in this ten-dimensional space reflect the
phenotypic relationship between species, the degree of overlap between species’
phenotypes, and within-species variability. These important characteristics
remain abstract unless the information is reduced in dimensionality. Canonical
discriminant analysis, like all dimension-reducing techniques, is designed to
reduce the spatial information of the data to fewer dimensions with the
minimum amount of distortion. It does this by creating new axes, called
canonical variates axes, which are combinations of the original variables. The
first axis is constructed so that it accounts for the maximum amount of variance
in the original data. The second axis, which is orthogonal to the first, is
constructed such that it explains the maximum of the remaining variance, and so
on. With n groups there are n - 1 canonical axes. Depending on the cumulative
proportion of variance explained, the first two canonical axes arc usually
sufficent to separate the groups and graphically show their phcnotypic
relationship to each other. A more detailed and rigorous account of canonical
discriminant analysis may be found in Owen & Chmielewski (1985) and
references therin.
Derivation of canonical discriminant function.! f o r the modern data
As discussed by Owen & Chmielewski, the twin goals of canonical
discriminant analysis are allocation and separation (sensu Geisser ( 1977)).
Allocation, which was the major goal of this study, refers to the classification of a
datum into one of the groups recognized a priori. In this study the a priori groups
B. hlICHAUX
244
recognized were the biological species already described. T h e groups were also
confirmed by principal component analysis which is an ordination technique
that does not assume group structure in the data (PROC PRINCOMP, SAS
User’s Guide: Statistics, 1982). l‘hc canonical discriminant €unctions, which
were used to allocate probablility estimates for a given datum belonging to each
of the groups, were generated by PROC CANDISC (SAS User’s Guide:
Statistics, 1982). ‘The data sets of the four modern species were combined and
divided into two sets (odd and even observations). One set was used to generate
the allocation rules and the other to test the calibration of these rules. As both
sets gave similar allocation results, the combined data set was used to generate
the final rules.
l h e probability of a datum belonging to a group depends on its position
relative to the mean values of the groups. T h e datum’s position is in turn
dependent on the contribution of the original variables to the new canonical
axis. This contribution is a product of a variable’s coefficient of a canonical axis’
eigenvector and the datum’s numerical value for that variable minus the grand
mean for that variable. The contribution of all variables is summed and defines a
point for a given datum on that canonical axis.
l‘he interpretation of the canonical axes (CAs) follows from the magnitudes
and signs of each variable’s canonical coefficient. Individuals that score highly
on CAl are large slim shells with relatively large apertures. Individuals that
have low scores on this axis tend to be smaller and wider. However, as the values
for the variables in this region of the graph are close to the grand mean values,
separation of A. australis, A. depressa and A. novaezelandine is poor, despite
A. auslralis and A . nouaeselandiae generally being easy to separate in the field on
the basis of length and width. ‘lhe second canonical axis is dominated by the
coefients of‘ shell width ( W l ) , aperture width (W2) and columella length (Hfi).
Wide shells with relatively wider apertures and longer columellas score highly on
this axis. The summary statistics of these canonical axes are provided in ‘Table 2.
Allocation
of‘,fossil shells to species groups
by modern canonical discriminant functions
Canonical scores for the fossil data were generated using the eigcrivalue
coefficients derived from the modern data. These scores have been plotted in
Figs 3, 4 & 5. The circles represent 9504 and 99% confidence surfaces based on
the modern data. The radii of these circles were calculated by (x2)’r2,where
has 2 degrees of freedom and the appropriate confidence value. Owen &
Chmielewski ( 1985) have recently discussed the sub.ject of constructing
confidence ellipses around canonical means. ‘lhey suggest a n alternative method
based on the output from a principal component analysis on the canonical
scores. Readers should refer to this paper for details. Such confidence ellipses
were constructed around the species’ means, b u t as these ellipses were quite
circular and of similar dimensions to the confidence circles, these latter
representations were employed in Figs 3 , 4 & 5.
x2
KESULI‘S
I he positions of the four species’ modern means and 95(% confidence surfaces
are given in Fig. 2. T h e allocation results are given in Table 3 . The allocation
7
7
M O R P H O L O G I C A L VAR IAT ION OF SPECIES THROCGH T I M E
245
TABLE
2. Summary statistics of the canonical axes
~
~
~~
~~~
A. Distarice matrix for pairwise combinations of the species. T h e upper figure is Mahalonobis’
D, the distance bctwern species’ means in full dimensional spare. T h e lower figure is the
distance in rcduced space
il. australis
A . australit
A . m ucronata
A . nouaezelandtae
A . depres.ra
x
A . muscronata
A. nouaezelandiae
A . depressa
x
4.64
4.64
2.67
2.60
2.17
2.25
5.26
5.25
5.72
5.58
3.95
3.79
x
Variance ratio
OjVariance
explained
F statistic
h o b > !I
3.66
1.35
0.23
69.8
25.8
4.4
91.6
51.1
18.6
0
0
0
X
B. Variancc ratios
CA 1
CA2
CA3
results for the modern specimens (where identification of species is based on
characters in addition to gross phenotype) confirms observations. It is not always
easy to separate some A. auslralis and A. depressa specimens, and large A. austra1i.r
shells would be difficult to identify with certainty if shell colour was absent. The
allocation of fossil specimens shows a comparable pattern. Two differences are
CAI
A. mucronafa
0 A. ausfra/is
o 4, novaeze/andiae
v A. depressa
-6
1
Figitrr 2. Positions of the mean canonical variare axcs scorcs I c r rnodrrn Antaldn aurlralic,
A . rnucrunata, I!. deprnsa and A. nouaezrlandiae. Circlcs rcprcsent 95”<1confidcncr sut-lacc.~.
246
U. MICHAUX
TABLE
3. Allocation results from canonical discriminant functions. Rcsults arc perccntagcs of
correct classification. ’Thc rows are classified into thr columns, thus 85yz;, ol‘ modern A . azistmlis are
classifird 21s A. azistm-alis, 4(?i1as A. r n ~ ~ r ~ and
~ a l a11li,as A. deflresJa. Area 1 =Wanganui, Arca
2=east coast North Island
c1asaifird
.: . a s
j
N
Sprcies
~~~~
11. azistrali.c
A . rnucronaia
A . noanezvlandifle
A . dekre.i.sa
A. auJlralis
8. mucronata
A. norueerlandiae
A. australis
A. rnucrimata
A. nouarzelandiue
Agc
.
~
327
163
152
58
143
135
117
50
50
50
.I. au.ctrahc A . niucronala A . noi~aezrliinclinr A. drl,rrs.\a
Asra
Modern
Modcsn
Modern
Modern
l’lio-Holo
Plio-Plcist
Plrist
Plrist
PI&
l’lrisc
~~~~~
85
2
1
~
98
1
911
95
5
1
1
1
2
2
2
ni
3
I6
84
6
12
.
II
4
16
95
6
14
94
I .5
2
1.5
78
2
88
apparent. ‘lhe first of these is the higher percentage of A . (iu.rLrdii.s shells
misclassifed a s A. rnucronata, which is a consequence of the highcr proportion of
larger A. auslralis shells in the fossil collections. The s( lnd difference is the
higher percentage of misclassification of A . novneselandine individuals from 110th
fossil collections as A. auslralis. Inspection of Fig. 5 reveals that the mean value
ne
for these fossil collections lies to thc right of the modern A . n o u u e ~ e l ~ n ~mean,
and hence closer to the A . nusLrali.r. mean. This results in a highcr proportion of
fossil A. nouaeselandiae specimens being misclassified.
The positions of individual fossil specimens on the two canonical axes are
shown in Figs 3, 4 & 5. These plots have been included l o visually dernonstratc
that individual fossil specimens plot within the phenotypc space defined by thc
appropriate modern biological species. Although the allocatory rules
demonstrate this algebraically the programme used will allocate any datum, no
matter how distant, to one of the n priori classes. ‘I’hus all points ha^ heen
visualized. The majority of all points lie within the confidence surfaces of the
respective means. Those that lie outside show distibutions and ranges similar to
modern specimens. For fossil A . mucronata samples (Fig. 4) the proportion of
larger shells is greater than in the modern samples, and it is these shell which
tend to lie outside the confidence surfaces. Within individual stratigraphic
groups the number o f these points do not appear to be correlated with time. ‘lhis
also applies to fossil A. auslrnlis samples (Fig. 3 )) although for this species the
confidence surfaces seem to more accurately account for variability. For
A. novaezelandiae the Confidence surface is clearly overestimated for both modern
and fossil samples (Fig. 5 ) .
The individual stratigraphic group means arc plottccl against tinic in Fig, 6 .
This graph shows the distribution of sample mcans in phenotypic space through
time. All the fossil mean values lie close to the respective modern mcans whicli
have been prqjected back i n t o time as lines parallel to the time axis. ‘lhe agc
values on this axis are only approximate.
C:ONCX,USIOhS
This study demonstrates that fossil members of threp biologically distinct
species fall within the range of variation that ir exhibited b y extant mcmhery oL
247
B. MICHAUX
248
A. Shakespeare group
C. Kai-iwi group
8. Shakespeare group
D. Okehu, Okiwa and Paparangi
CAI
10-
E.
CAI
Figure 4. Individual canonical variatr axcs scows Tor Iossil Amnldn nrzicronntn. 'l'lir circlcs reprcscnt
9.?"/;,
and 99'),, confidence surfaccs calcn1;itcd from modern A . mucionnlu caiionical 1 aridlc scorcs. A-D from Wanganui, Formation 1 = Rrnnswick Maritic Sand, following numbcrq arc scqiicntial to the
list givcn in Flcming (1953). 1: from Hawkcs bay.
these species. The phenotypic trajcctory of each species is shown to oscillate
around the modern mean through the time pcriod under consideration. 'lhis
pattern demonstrates oscillatory change in phcnotypc: within prescribed limits,
that is, phenotypic stasis.
The post-Miocene history of the Wanganui subdivision was one of complex
and rapid changes in both climate and paleogcograpliy (Fleming, 1953). 'lhe
major climatic, fluctuations, deduced by Fleming (1953) from floral and fhunal
evidence, have been indicated on Fig. 7. The Hautawari (formations 41-39)
represents a thermal minimum wlieri temperaturcs wcre some 3" 6°C:. lowcr
than today and glaciation extended as far riortli as 43"s. 'lemperatures
subsequently increased (formations 38- 3 3 ) to levels equivalent to those of tlie
southern extremity of the South Island today. Further climatic dctcrioratiori
MORPHOLOGICAL, VAKIAI'ION O F SPECIES T H R O U G H T I M E
A. Shakespeare group
249
B. KO!-Iwi Qroup
CAI
CAI
D.
C. Okehu group
CAI
CAI
notion
Figure 5. Individual canonical variatc axcs scores lor fossil Amnldn nouaezelnndiae. Tlic circles
rcprcscnt 95% and 9Yo,;l confidence surfaccs calculated from modern A. novaezelandiae canonical
variatr scores. A-C from Wanganui, Formation 1 =Brunswick Marinr Sand, following numbrrs are
sequential to the list given in Fleming (1953). D from Hawkes Bay.
during formations 32-22 was followed by a progressive warming during the
Putikian (formations 17-3) reaching a maximum during formations 16-14, when
temperatures were estimated to have been 3" 6"C(?) higher than at present.
Variable conditions existed during the Hawera stage which followed (formations
1 and 2 ) .
Structurally, the basin had a complex history, with downwarping, margin
tilting, variable sediment supply, and regional tectonics interplaying to give
complex shore-line migration patterns. This resulted in the alternation of
auslralisldepresra and mucronatalnouaeZelandiue collections as shallow, coastal
conditions alternated with deeper offshore environments. Tracking of their
preferred habitat by these species, a phenomenon reported by Coope (1979) on a
regional scale for coleopteran communities, has important evolutionary and
biogeographic implications which are discussed in detail in a manuscript in
preparation.
B. MICHAUX
250
e
I,
-444
ACA'
Figurr 6. Individual stratigraphic group inc-ail canonical variate scores for A. austm lk, A. rnucronata
atid A. novap~elandineplottcd against time. Time axis unit is million years before prearnt (M.Y.BP).
Agrs are only approximate.
I t is against this background of environmental change that the variation in
fossil sample means must be interpreted. There are also biases in the statistics
derived from fossil samples which must also be borne in mind when interpreting
these means. 'The major source of bias was undoubtedly introduced during
collection, all samples being individually collected. T h e sample means are almost
certainly, therefore, to be overestimations. The other likely source of bias was
probably post-death sorting, a particular problem within the higher energy
environments h a t A. australis inhabits.
Plots of the canonical variate scores for the fossil samples of A . australiJ against
formation number are shown in Fig. 7. The pattern of variation of CA1 and CA2
through time is similar and both thcsc patterns show changes that appear to
track climatic change. During cold periods shells are larger, wider and have
bigger apertures, with the converse during warmer conditions. This appears to
be an example of a molluscan equivalent of Bergman's Rule. Interestingly the
reverse appears true for A. mucronata (Fig. 8), cold climate being associated with
MORPHOLOGICAL VARIA'IION 01: SPECIES ' I H R O U G H 'I I M E
25 1
Temperature
W
n
g
._0
L
z
V
a
-2
4
-3
0
I
I
10
20
I
I
30
Formation number
Figurc 7. Plot ol' CAI atid CA2 scorcs f i r fbssil samplcs o f ' i l .n u i t i a h
that age incrrasrs to tlw right.
DJ.
formation numbrr. S o t r
smaller shells and warmer climate with larger shells. T h e phenotypic trajectories
through time are thus climatically modulated for these species, a result also
reported by Cronin ( 1 985) for marine ostracods.
One hypothesis that could account for this modulation is that it results from
the dynamic interplay between an organism's developmental system and
mucronafa and ausfro/is CAN I scores
0-
-5
-
a
V
-4
-
2
s
Q
h
-3
m
Formation number
Figure 8 . Plot of' CAI scorcs for fossil camplrs of A . nuctrnli, and d. ~ I L U ( J W ~ L 7)s. hrmation r i u r r l l m
Noic t h a t agc incrrasrs to tlic right.
252
R. MICHAUX
external context (Michaux, 1988). Changes in temperature can alter the kinetics
and hence the catalytic rates of biological reactions that are components of the
organism’s developmental system. For this particular example it seems to me
that two aspects of ontogeny are relevant, namely somatic growth rates and
timing of sexual maturation. For A. nutralis the results of this study are consistent
with prolonging the onset of sexual maturity during periods of lower
temperatures. Somatic growth rates were either unaffected or slowed relatively
less. The result is that the animal grows for a longer period, producing a larger
shell with a bigger aperture. For A. mucronutu the rate of somatic growth was
slowed relative to the onset of sexual maturity during periods of lower
temperature. In this case the animal grows slower and produces smaller shells by
the time it becomes sexually mature. Because these species are extant, this
hypothesis is open to experimental investigation and hence to refutation.
UlSCUSStON
I have argued for the importance of using extant taxa for detailed
evolutionary studies using paleontological data. This is certainly not new (see,
for example, Williamson, 1981; Vrba, 1984; Cronin, 1985; Stanley & Yang,
1987), and is simply a n extension of the principle of uniformitarianism, but what
is new is the use to which data obtained from extant organisms are used. Any
historical study of species must have an accurate knowledge of what biological
groupings exist within the taxon being studied, and this cannot be achieved,
without varying degrees of uncertainty, using morphology alone. Morphological
criteria are used for identification once the biological groupings have been
established by critera independent of morphology. This conclusion, I believe,
applies equally to both paleontological and biological research.
When biological groupings are defined by morphological criteria the results of
the study are inconclusive, both because of the circularity of the argument arid
the doubt about the validity of such groupings. It is a weak argument to suggest
that because modern taxa are identified so it is .justifiable to use these same
criteria, because there are a large and increasing number of examples,
particularly stemming from medical and pest control research where accurate
(and hence costly) knowledge of groupings is essential, that provide
coun ter-examples.
The refinements in methodology outlined above overcome, I believe, some of
the weaknesses that are inherent in palaeontological data. The most important of
these is the ability to base species definitions on data independent of both
morphology and fossil evidence. This appears to me to be an important
requirement if one is to describe patterns of speciation in the fossil record- a
conclusion that applies equally to both taxic and transformational approaches.
Having established the biological discreteness of the t a m involved, their overall
morphology can then be quantified-in
this particular study by multivariate
techniques-and fossil morphologies compared using the same methods.
The question of whether fossil individuals are members of the same modern
biologically defined species is unanswerable. However, if fossil specimens have
identical diagnostic taxonomic characters, overall phenotypic parameters,
habitat and environrncntal preferences, and faunal associations as these modern
species, it is difficult to imagine by what criteria they could he judged dilrerent.
M O R P H O L O G I C A L VAR IAT ION 0 1 ‘ SPECIES T H R O U G H ‘ [ M E
E
CA2
253
/
/
2
I
N
I
X
2
X
3
X
(i)
Figure 9. Hypothetical case rrsulting in ‘pliylctic gradualism’ in the fossil rccord. S c r text f i r details.
They could be regarded as cryptic species, which indeed thay may be. I n this
particular study I have demonstrated the lack of cryptic groupings within the
modern species, but cannot of course demonstrate that the fossil specimens are
not. I have little doubt in my own mind that these fossil individuals represent
samples from a genealogical continuum that stretches back from the present into
the Pliocene, but leave the reader to reach his own conclusions.
‘The importance of using independent species definitions is demonstrated by
the example reported in Raup & Crick (1981). In this study the authors looked
at the evolution of single characters in the Jurassic ammonite genus Kosmoceras
and concluded that some characters changed gradually whilst others changed
abruptly. By identifying species morphologically, transformationists would
conclude that species changed phyletically and taxists would conclude that they
changed abruptly. This example illustrates that characters can change either
gradually or abruptly, but sheds little light on the evolution of (biological)
species. Consider the example presented in this paper. Figure 2 shows that there
is considerable overlap in the morphologies of three biological species,
254
R. WICHAUX
A. nouaezelnndiue, A. australis and A. deflressn. For the sake of‘ argument, presume
that rather than being molluscs, these represent three biological specics of
planktonic foraminifera (Fig. 9A), Further, let us presume that these biological
species are distributed latitudinally within the Southern ocean, each preferring a
particular climatic zone. Apart from thc rather abrupt transformation of
molluscs into forams this scenario is reasonable, and is diagramatically illustrated
in Fig. 9.
Consider now the effects of climate deterioration which results from thc onset
and intensification of glaciation in Antarctica. The oceanic zones will migrate
north, and the foram specics, because of their habitat preferences, will follow
(Fig. 9B i iii). At locality X the stratigraphic sequence will be specics 1, 2 arid 3,
which could quite conceively show a scqucntial, gradual change in morphology
(Fig. 9C). I t is possible that there are n o characters which show any abrupt
changes because biological groupings may he ‘cryptic’. I t could be concluded
from this hypothetical case that these species show progressive and gradual
change through time (e.g. Gingerich, 1976; Malmgren & Kennett, 198 I ) . ‘I’his
interpretation is quite erroneous arid serves to underline the importance of
knowing what biological groupings otic is dealing with, arid then describing thc
morphological variability of each biological species as fully as possible. This
includes atialysing samples from as much of the geographic rarigc as possible, a
point already stressed by a number of authors (e.g. Gould & Eldredge, 1977).
In summary, I have tried to show that extant taxa with good fossil records
should be used for detailed paleontological evolutionary studies. ‘I’lie advantage
of using such groups is simply to provide the maximum possi tile infornia tiori.
T h e results of such studies would then give us increased confidence in describing
the pattern of evolutionary change with respect to speciation in the fossil record.
This is certainly not to imply that extinct groups are of little value in
evolutionary studies, but simply to argue that patterns in speciation change arc
lcast unequivocal when the maximum amount of data arc available. T h c task of
documenting speciation patterns in the fossil record is, in my estimation, of some
importance and rightly raised to prominence by Eldredge & Gould in 1972.
ACKNO\1’LED(:F,MI,,~’l S
An earlier draft of this paper benefited from the comments of an anonymous
reviewer. I would like to thank D r Brian McArdle (University of Auckland) for
discussion and encouragement on all matters statistical. The work was supported
by U.G.C. grant number 449.202 and A.U.R.C. grant number 449.194. This
publication represents No. 33 from the Evolutionary Genetics Laboratory.
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