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Paleobiology, 32(1), 2006, pp. 100–108
Estimating multivariate selection gradients in the fossil record:
a naticid gastropod case study
Melissa Grey, Elizabeth G. Boulding, and Michael E. Brookfield
Abstract.—The purpose of this paper is to explore the possibility and utility of estimating multivariate selection in fossil assemblages, using naticid gastropods as a case study. We used the presence or the absence of a naticid borehole as an index of survival with respect to drilling attacks,
enabling us to estimate the multivariate selection gradient exerted by this predator on the shell
length and shell thickness of two bivalve genera, Astarte and Spisula. We hypothesized that naticid
selection pressure would favor the survival of large, thick-shelled bivalve prey throughout the Cenozoic.
Differential survival of prey was recorded over geologic time using processed bulk assemblages
from the Miocene, Pliocene, and Pleistocene Epochs. Multivariate logistic regressions were performed by time period to determine if length and thickness were important factors affecting survival. The direction and magnitude of selection on length and thickness for the two genera ranged
from zero (no selection) to large positive or negative values. Only two selection coefficients were
significant after sequential Bonferroni corrections: thin-shelled Astarte survived substantially better than thick-shelled Astarte during the Pleistocene (bavggrad 5 21.23) and large Spisula survived
slightly better than small Spisula during the Miocene Epoch ( bavggrad 5 0.05).
This is the first study using fossils to calculate multivariate selection gradients. It suggests that
naticids were not necessarily strong agents of selection on two traits previously thought to be important to survival of drilling attacks for two of their common prey species. We also show that
multivariate selection gradient estimates differ from traditional predation intensity estimates but
are superior for estimating the magnitude and direction of natural selection because they use differential mortality of different prey phenotypes rather than just absolute mortality from predation.
This work is especially significant for research that involves estimating the relative importance of
predation (naticid or otherwise) as an evolutionary force and will be useful for fossil studies where
differential survival can be recorded.
Melissa Grey.* Department of Integrative Biology, University of Guelph, Guelph, Ontario N1G 2W1,
Canada
Elizabeth G. Boulding. Department of Integrative Biology, University of Guelph, Guelph, Ontario
N1G 2W1, Canada. E-mail: [email protected]
Michael E. Brookfield. Department of Land Resource Science, University of Guelph, Guelph, Ontario
N1G 2W1, Canada
* Present address: Department of Earth and Ocean Sciences, University of British Columbia, Vancouver,
British Columbia V6T 1Z4, Canada. E-mail: [email protected]
Accepted:
4 June 2005
Introduction
Understanding how natural selection affects phenotypes is a major goal of evolutionary biology, and a common theme among evolutionary neontologists is the quantification of
natural selection (see Endler 1986, Kingsolver
et al. 2001, and Hereford et al. 2004 for reviews). Predation is recognized as an important agent of selection and source of diversification in prey species (Vermeij 1987; Endler
1995; Reimchen and Nosil 2002). The prospect
of quantifying selection due to predation for
fossil assemblages is exciting because it can
help elucidate how predation has shaped phenotypes throughout evolutionary history. Beq 2006 The Paleontological Society. All rights reserved.
cause evidence of predation is preserved in the
shells of the prey species, the naticid gastropod predator-prey system is particularly useful for exploring whether it is possible to calculate the selection intensity placed on prey
by their predators over evolutionary time.
Predator-driven evolution has been hypothesized for many prey taxa of naticid gastropods
(e.g., Kelley 1989, 1991a; Dietl and Alexander
2000). Indeed, the increase in prey shell length
and thickness for some taxa over geological
time has been attributed to an evolutionary response to naticid predation (Kelley 1984,
1989).
The naticid predator-prey system is an ideal
0094-8373/06/3201-0006/$1.00
101
ESTIMATING SELECTION IN FOSSILS
candidate for the study of selection in the fossil record and for Recent evolutionary studies
for a variety of reasons: (1) naticid predation
is often stereotyped and predictable (Berg and
Nishenko 1975; Kitchell et al. 1981; Kelley
1987, 1991b; Kabat 1990); (2) naticid boreholes
are characteristic, preservable, and usually
identifiable in prey shells (Kitchell et al. 1981;
Kabat 1990); (3) boreholes in prey shells can
provide a wealth of information, including
predator size and predator behavior (Kitchell
1986); (4) drilling is one method of predation
for which fossils can be used to estimate mortality and antipredatory effectiveness (Vermeij
1983); and (5) naticids are often assumed to be
strong selective agents in prey evolution
(Harper 2003).
The naticid predator-prey system has been
used for studies of coevolution (Kelley 1992),
prey selection (Kitchell et al. 1981; Kelley 1988,
1991b), and escalation (Kelley and Hansen
1996) but no previous studies have attempted
to quantify multivariate selection for this system, or for any other fossil predator-prey system. Drilling frequencies are typically used as
a proxy for selection pressure due to predation (e.g., Kelley 1988, 1989; Kelley and Hansen 1993); Leighton (2002) comments that this
proxy can be valid but with important caveats
that he discusses. Conversely, multivariate
techniques (as described below) can be used
to estimate selection intensity directly. This
method may be particularly important as Van
Valen’s ‘‘Red Queen Hypothesis’’ (Van Valen
1973) indicates that despite evolutionary
changes by the prey, predation intensities may
remain nearly constant because of evolution
by the predator. Predation intensity, therefore,
may not always be a suitable indicator of selection pressure and more direct tests of selection pressure are required.
The strength of selection is frequently calculated by using the multivariate selection
gradient, which is a vector of partial regression coefficients, from a multiple regression
with the various traits as the independent variables and relative fitness as the dependent
variable (Lande and Arnold 1983). It is important to use multivariate methods for determining which traits in a correlated group are
the focus of direct selection, as phenotypic
correlations among traits are very common
and natural selection acts on many characters
simultaneously (Lande and Arnold 1983).
Multiple regression has been widely used by
researchers but logistic regression is a more
suitable method for estimating the selection
gradient when outcomes are dichotomous
(e.g., absolute fitness recorded as survival or
death) and sample sizes are relatively small
(e.g., n 5 50–100) (Janzen and Stern 1998). The
model for logistic regression relates the survival probability for an individual to that individual’s trait values:
W(z) 5 ea01az /1 1 ea01az
T
T
where W is the selection outcome for an individual (1 5 survival; 0 5 death); W(z) is the
survival probability for a set of traits (z1 . . .
zn); a 5 (a1, a2, . . . , ak)T are the logistic regression coefficients for traits (z1 . . . zn); T signifies matrix transposition; and a0 is an intercept (Janzen and Stern 1998). Although the
strength of selection on quantitative traits has
been estimated for numerous neontological
studies, it has not hitherto been estimated for
any fossil system.
The purpose of this paper is to explore the
possibility and utility of estimating multivariate selection gradients for fossil assemblages.
We compare this method to the predation intensity statistic, which is the traditional proxy
of selection for drilling predation in the fossil
record. If both methods accurately estimate
selection, then selection gradient estimates
should be positively correlated with predation
intensity (e.g., if naticids are strong selective
agents on prey shell length and thickness,
then selection gradients will be significant and
predation intensities will be high). Our initial
hypothesis was that the length and thickness
of prey shells would be the most important
traits affecting survival and that larger and
thicker shells (Kitchell et al. 1981) will have a
higher probability of surviving in the presence of naticid predators.
Materials and Methods
Description of Assemblages
Recent. A Recent assemblage of the surf
clam, Spisula (Hemimactra) solidissima, was col-
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MELISSA GREY ET AL.
TABLE 1.
Information on stratigraphic unit, age, taxa, and location collected for all assemblages studied.
Assemblage
name
Chesapeake
Group (Kelley
1983)
Chesapeake
Group (Kelley
1983)
Chesapeake
Group (Kelley
1983)
—
—
—
Stratigraphic unit
and members/zones
Calvert Fm. (Plum
Point Marl
Member; zones
10 and 14)
Choptank Fm.
(Gernant’s Calvert Beach and
Drumcliff Members; zones 16
and 17)
St. Mary’s Fm.
(Little Cove
Point and
Windmill Point
Members; zones
22 and 24)
Yorktown Fm.
(Moore House
Member)
James City Fm.
—
Age
Taxa
Location collected
E. Miocene
Astarte cuneiformis
Chesapeake Bay,
Md.
M. Miocene
Astarte thisphila
Chesapeake Bay,
Md.
L. Miocene
Spisula (Hemimactra) subponderosa
Chesapeake Bay,
Md.
E. Pliocene
Astarte undulata and A. conheni; Spisula (Hemimactra)
sp.
Astarte concentrica; Spisula
(Hemimactra) sp.
Spisula solidissima
East coast of U.S.A.
E. Pleistocene
Recent
lected from Wrightsville Beach, North Carolina, by G. Dietl (Yale University). Wrightsville
Beach is a wave-exposed sandy beach on the
Atlantic Ocean. This assemblage was primarily used to compare Recent selection gradients
with those of fossil assemblages, where the effects of time-averaging will have a greater effect on the magnitude of selection estimates.
Fossil. Fossils used in our analyses were
collected by P. H. Kelley (University of North
Carolina at Wilmington) and included processed material from the Miocene, Pliocene,
and Pleistocene (Table 1). Miocene assemblages were from the Chesapeake Group in Maryland and all were from an unconsolidated offshore environment (Kelley 1983, 1984). The exposures of the Chesapeake Group include
sediments assigned to the Calvert, Choptank,
and St. Mary’s Formations. Refer to Kelley
(1983) for specific sampling techniques and a
complete description of the Chesapeake
Group assemblages. Plio-Pleistocene collections were from the Yorktown and James City
Formations, respectively.
Bivalve genera studied were Astarte and
Spisula; these were the most common genera
present from the Miocene and traceable
through to the Plio-Pleistocene. Following Kel-
East coast of U.S.A.
Wrightsville Beach,
N.C.
ley (1983), we assume that, at least for Astarte,
the lineages studied represent true ancestordescendant relationships in the Chesapeake
Group. The naticid species found in these assemblages include Neverita duplicata (Say) and
Euspira heros (Say). Table 1 contains information on the biostratigraphy, taxa, and age for
all assemblages studied.
Measurements
We measured two traits, length and thickness, that are expected to have adaptive value,
as indicated by previous studies of naticid gastropod predation on bivalves (Kitchell et al.
1981; Roopnarine and Beussink 1999). All
shells were measured for maximum length
with digital calipers. Thickness measurements on the shells, made with a digital depth
gauge, were taken in the regions of the umbo
(corresponding to sector 2 in Kelley [1988]),
middle (corresponding to sector 5 in Kelley
1988), and edge (corresponding to sector 8 in
Kelley 1988). Overall thickness of a shell was
calculated as an average of the thickness at the
umbo, middle, and edge regions. All measurements were taken to the nearest 0.01 mm
and were entered into a customized database
103
ESTIMATING SELECTION IN FOSSILS
TABLE 2. Overall multivariate logistic regression results for Astarte from the Miocene to the Pleistocene. n is the
number of bivalves measured in the assemblage; bavggrad is the transformed logistic regression coefficient; p is the
original value before correction for multiple tests within each epoch; and SE is the standard error. Analyses used
fitness (drilled versus undrilled) as the dependent variable and length and thickness as the independent variables.
bavggrad
p
SE
Epoch
n
Predation
intensity (%)
Length
Thickness
Length
Thickness
Length
Thickness
Miocene
Pliocene
Pleistocene
58
51
50
76
71
48
0.007
0.06
0.1
20.09
20.46
21.23
0.64
0.07
0.03
0.60
0.09
0.03†
0.06
0.35
0.25
0.7
3.5
3.6
† Remained significant after the sequential Bonferroni correction within each epoch (Rice 1989).
using an automatic data acquisition program,
written in FoxPro.
Predation Intensity and Selection Gradients
for Fossil Assemblages
Overall predation intensity for each time
period was calculated by 2(D/N) where D is
the number of drilled valves and N is the total
number of valves (Thomas 1976).
Multivariate logistic regressions were performed in SPSS for both Astarte and Spisula by
time period. Absolute fitness (survival 5 1;
death by drilling 5 0) was the dependent variable (Janzen and Stern 1998) and prey shell
length and thickness were independent variables. Each selection episode, or time period in
this case, has been treated as a separate experiment, after Fairbairn and Reeve (2001). We
present results for significant levels corrected
for multiple comparisons using the sequential
Bonferroni method (Rice 1989) within each
epoch, thus maintaining an experimentwise
error of alpha 5 0.05. Unlike the standard
Bonferroni test, the sequential Bonferroni
method retains statistical power while correcting for experimentwise Type I error (Rice
1989).
Logistic regression coefficients were con-
verted into least-squares selection gradients
(as in Lande and Arnold 1983) using the methods described by Janzen and Stern (1998).
Conversion of the coefficients results in the average gradient vector (bavggrad) and requires
calculating W(z) for each individual (Janzen
and Stern 1998). These calculations were performed using a program created by P. Lelièvre
in MatLab.
Results
Predation intensities decreased from 76% to
48% from the Miocene to Pleistocene (Table 2)
for Astarte and decreased from 80% to 40% for
Spisula from the Miocene to Recent (Table 3).
Logistic regression results by time period
revealed that length and thickness did not
usually affect the probability of being drilled
for Astarte (p . 0.25 for two out of six tests;
Table 2) or for Spisula (p . 0.25 for five out of
eight tests; Table 3). However, the test for
thickness for Astarte concentrica during the
Pleistocene was significant after the sequential
Bonferroni correction (p 5 0.03) and this result corresponded to a highly negative selection gradient value (bavggrad 5 21.23) (Table 2,
Fig. 1), indicating selection for thinner shells.
Also, one test for length for Spisula during the
TABLE 3. Overall multivariate logistic regression results for Spisula from the Miocene to the Pleistocene. n is the
number of bivalves measured in the assemblage; bavggrad is the transformed logistic regression coefficient; p is the
original value before correction for multiple tests within each epoch; and SE is the standard error. Analyses used
fitness (drilled or undrilled) as the dependent variable and length and thickness as the independent variables.
Epoch
n
Predation
intensity (%)
Miocene
Pliocene
Pleistocene
Recent
147
147
80
111
80
53
30
40
bavggrad
p
SE
Length
Thickness
Length
Thickness
Length
Thickness
0.05
0.002
0.005
0.005
0.17
0.24
0.11
0.31
0.01†
0.89
0.54
0.10
0.82
0.31
0.77
0.10
0.09
0.06
0.11
0.05
5.2
1.2
3.3
2.9
† Remained significant after the sequential Bonferroni correction (Rice 1989).
104
MELISSA GREY ET AL.
FIGURE 1. Length-thickness graph for Astarte shells unbored and bored by naticids in the Pleistocene Epoch.
Late Miocene was significant (p 5 0.01) after
the sequential Bonferroni correction but this
result corresponded to a very small selection
gradient value (bavggrad 5 0.05) (Table 3, Fig. 2),
indicating weak selection for larger shells. Refer to the Appendix for number of bored shells
sampled and trait means and standard deviations.
Selection intensity and predation intensity
were inversely correlated for Astarte and were
positively correlated for Spisula (Tables 2 and
3, respectively, Fig. 3).
Discussion
Logistic regression analyses indicated that
length and thickness, two traits often assumed
to be important to survival, did not usually
significantly affect the probability of finding
naticid drill holes in Astarte and Spisula. We
have also shown that high predation intensities do not always correlate with strong selection. As we discuss below, these results indicate that
1. predation intensity may not always be an
appropriate proxy for selection; or
2. the traits measured (length and thickness)
were not experiencing selection pressure
from naticids and were not important factors to survival. Therefore, attributing temporal increases in thickness and/or length
in prey shells to naticid predation is not valid unless there is direct evidence; or
3. selection has not been measured in an appropriate manner.
Predation intensity may not always be an
appropriate proxy for selection because it es-
FIGURE 2. Length-thickness graph for Spisula shells unbored and bored by naticids from the St. Mary’s Formation in the Miocene Epoch.
timates absolute mortality from predation
rather than differential mortality of different
prey phenotypes. Predation intensity, as defined here, measures the percentage of bivalve
valves of a particular species that were drilled
by naticid predators without any reference to
shell traits. In contrast, a selection gradient estimates the covariance between the values of
shell length and shell thickness and whether
or not a naticid predator drilled the shell. This
differential survival with respect to particular
values of prey traits is important as only it can
result in natural selection and ultimately evolution of heritable traits (reviewed in Endler
1986).
It is possible that neither length nor thickness was experiencing strong selection during
these time periods but our values are comparable to those for Recent populations. Absolute values of linear selection zbavggradz for this
study averaged 0.20 (range 5 0.002–1.23, for
length and thickness results combined). This
is comparable to the mean value of 0.22 for
other studies of natural selection for a variety
FIGURE 3. Relationship between selection coefficients
and predation intensities for Astarte and Spisula.
ESTIMATING SELECTION IN FOSSILS
of Recent populations (Kingsolver et al. 2001).
In addition, we found that 21% of estimates
were significant (14% after the sequential Bonferroni correction), similar to the Kingsolver
et al. (2001) review of 63 published studies
that found significance in 25% of all estimates
of selection (where corrections for multiple
tests were not normally calculated). Selection
strength was very small (bavggrad 5 0.05) for Spisula during the Miocene Epoch for increased
length. Even very small selection coefficients,
however, can have large evolutionary effects
over geologic time (Lande 1979). It is intriguing that selection has sometimes been weak or
nonsignificant on these two common prey
genera because naticids and other drilling gastropods are often assumed to have placed significant selection pressure on their prey
(Harper 2003).
Future research will need to discern between two, ultimately testable, hypotheses:
that selection pressure by naticids is weak and
is not the primary factor for observed bivalve
morphological evolution or that the methods
used here are not suitable for evaluating selection. A common reason for not detecting selection is that sample sizes are too small (Endler 1986). Although logistic regression works
well with relatively small sample sizes, the
power of the analysis may increase with larger
sample sizes (Kingsolver et al. 2001) and we
recommend that sample sizes be maximized
for work involving the calculation of selection
gradients.
This study is based on four assumptions
that may have substantially affected our interpretations and will be described below.
Note that the importance of non-facultative
predation is not discussed here because it
does not affect questions relating to the importance of naticids as drilling predators.
Taphonomic bias in assemblages can hinder
analyses as some predation events can be lost.
For example, differential fragmentation (Roy
et al. 1994) and valve sorting (Boucot et al.
1958; Lever and Thijssen 1968) may eliminate
a portion of drilled shells from assemblages.
Although the presence of boreholes in shells
significantly reduces shell strength, shell-toshell contact has a greater effect on valve
breakage (Zuschin and Stanton 2001). Even
105
though quantifying selection does not rely on
estimating frequencies, differential fragmentation may have affected our results. For instance, the observed strong negative selection
(bavggrad 5 21.23) for Astarte during the Pleistocene suggests that thinner-shelled prey survived better than thick-shelled prey and may
be a result of differential fragmentation; thinner shells may have been removed from assemblages, representing a severe taphonomic
bias. This may have been a real trend, however, as all the selection coefficients for shell
thickness were negative for Astarte for all geological epochs whereas all were positive for
Spisula. Roy et al. (1994) presented a method
for assessing the amount of taphonomic loss
in fossil assemblages, but because we used
previously processed and published material
(see Kelley 1983) we were not able to assess the
extent of the bias. The development of probabilistic models to account for taphonomic loss
and multiple hypotheses testing as advocated
by Kaplan and Baumiller (2000) should also be
considered when estimating selection intensities.
The destruction of bivalve shells by crabs
and other shell-breaking predators (Vermeij et
al. 1989) may have also affected our results.
Valve destruction will be of major concern for
this study if large removals of bivalves with
specific characteristics (e.g., thin and/or
small) took place. Removals could account for
the observed negative selection gradient for
Astarte only if crabs differentially removed
thicker shells from the record, but crabs prefer
thinner and flatter shells (Boulding 1984). As
mentioned earlier, the assemblages we
worked with had already been processed and
the magnitude of fragmentation could not be
judged. Future studies, however, can assess
crab predation by using the relative abundance of shell fragments with angular (Oij et
al. 2003) or chipped ventral margins (Boulding 1984). Valve destruction is of much greater
concern for drilling intensity statistics because
it will overestimate the importance of drillers.
Taphonomic alteration, among other factors, can affect the geometry of a drill hole
(Kowalewski 1993), causing the source of
predatory holes to be misidentified. We do not
believe that there were many misidentified
106
MELISSA GREY ET AL.
holes in this study because preservation was
satisfactory. For assemblages where concerns
about this assumption are high, Kowalewski
(1993) has presented a method for a morphometric analysis of drillholes.
Time-averaging is another important issue
that must be addressed as it can mask intense
bouts of selection over time. Our results for the
Recent assemblage of Spisula closely match
those for fossil assemblages, and our overall
results are similar to published material on
Recent populations (Kingsolver et al. 2001).
We are therefore confident that our results are
reasonably accurate; however, time-averaging
remains an important issue that will require
further attention as research in this area continues.
Although violation of these assumptions affects the utility of calculating selection gradients, we feel there is vast potential for this
method to be applied in paleobiological studies involving predation, and natural selection
in general. Future research on this system
should include additional prey taxa and traits,
such as internal volume (see Kelley 1989), that
may have adaptive value and are likely to be
heritable. Our methods will be most valuable
for assemblages for which many of the assumptions above can be met. For many unprocessed fossil assemblages it should be possible to minimize the number of assumptions
and create a powerful test for estimating multivariate selection. For results that are not statistically significant, choosing between the alternative hypotheses—that selection pressure
is not strong or that the specimens/variables/
sampling methods are not suitable—should
pose an interesting challenge to paleobiologists.
Researchers of drilling predation may consider using incomplete boreholes in prey as a
measure of unsuccessful predation. Prey with
unsuccessful boreholes would receive a fitness
value of one, whereas prey with complete
boreholes would receive a value of 0. We were
unable to perform this because the incidence
of incomplete holes in our samples was extremely low (5%) and would not allow for reasonable statistical power. Also, many examples from modern drilling systems indicate
that an incomplete borehole may not result in
failed predation (for naticids, see Vermeij
1980, Ansell and Morton 1987, and Grey 2001;
for muricids, see Kowalewski 2004). It is also
important to recognize that a naticid may
have encountered a prey item but did not attempt to drill it because of its particular traits,
representing a form of prey selection that
would be ignored if only incomplete holes
were used as a measure of survival. Comparing selection coefficients that use only incomplete boreholes as a measure of survival with
results that use all undrilled shells may prove
useful for determining which method is most
appropriate.
Conclusions
The importance and role of natural selection
in evolution has been the subject of numerous
studies by neontologists, but has never before
been estimated for fossils. We have shown it is
possible to measure the strength of selection
for fossil predator-prey systems, noting important caveats for interpretation. This paper
represents a growing body of research that
aims to directly assess predation pressure in
the fossil record (e.g., Harper 2003; Gahn and
Baumiller 2005; Grey et al. 2005). The methods
presented here are useful not only for assessments of drilling predation but also for any
fossil system where differential survival can
be recorded. Our paper highlights four important points:
1. multivariate selection can be quantified for
fossil assemblages;
2. naticids may not be important selective
agents on bivalve evolution, as often assumed, or bivalve thickness and length
traits may not be important to survival, as
often assumed;
3. predation and selection intensities are not
always positively correlated (Fig. 3), indicating either that predation intensities cannot always be a useful measure of selective
pressure or that selection gradients are not
accurately estimated; and
4. the most powerful tests for multivariate selection will include comparisons of drilling
intensities with selection gradients in fossil
assemblages that are well preserved, with
minimal taphonomic biases.
ESTIMATING SELECTION IN FOSSILS
Estimation of selection in the fossil record is
an exciting prospect as it can help us further
understand the role of predation as a selective
force and recognize how natural selection has
affected morphological evolution in the past.
We hope that this work will encourage researchers to use and further develop the methods we describe here to estimate selection in
the fossil record.
Acknowledgments
This research was funded by a Discovery
grant to E. G. Boulding and by a Post-Graduate Scholarship-A to M. Grey from the Natural Sciences and Engineering Research
Council of Canada. We thank J. W. Haggart for
reading early drafts of this manuscript, P. G.
Lelièvre for creating a program in MatLab, T.
K. Hay for writing a custom database program, and especially G. P. Dietl and P. H. Kelley for the extensive use of their collections.
This manuscript has been significantly improved by helpful comments from T. K. Baumiller and reviews by G. P. Dietl, P. H. Kelley,
and M. Kowalewski.
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Appendix
Number of drilled shells, mean and standard deviation for length and thickness for all bivalve shells measured in
study.
Epoch
No. of drilled
shells
Mean
thickness (mm)
SD
Average
length (mm)
SD
Astarte
Miocene
Pliocene
Pleistocene
22
18
12
1.39
1.12
1.06
0.45
0.434
0.455
21.53
14.38
14.6
5.54
4.42
6.08
Spisula
Miocene
Pliocene
Pleistocene
Recent
59
39
12
22
0.21
0.66
0.42
0.78
0.06
0.22
0.19
0.167
9.23
13.82
11.91
36
3.83
4.72
6.09
9.23