Global Ecology and Biogeography, (Global Ecol. Biogeogr.) (2007) 16, 117–128
Blackwell Publishing Ltd
RESEARCH
PAPER
Does versatility as measured by
geographic range, bathymetric range and
morphological variability contribute to
taxon longevity?
Lee Hsiang Liow
Committee on Evolutionary Biology, University
of Chicago, 5743 S. Ellis Ave, Chicago, IL 60637,
USA
ABSTRACT
Aim This paper aims to examine the relationship between versatility as measured
by geographic range, bathymetric range and morphological variability (species and
subspecies richness and the occurrence of morphologically highly variable populations), and the geologic longevities of trachyleberidid ostracode species and genera,
while accounting for sampling biases and other confounding factors.
Location Global.
Methods A large database of occurrence records of species of the family Trachyleberididae s.l. was analysed. The relationships between genus and species longevity
and the above mentioned variables were examined singly and in concert. Re-analyses
of subsets of data and rarefaction techniques were employed to account for sampling
biases, while randomization was used to account for autocorrelation of variables.
Results The mean number of occurrence records, and latitudinal and longitudinal
ranges, were strongly and positively correlated with genus and species longevities. The
number of bathymetric zones occupied by genera had no consistent bearing on their
longevities, but species data subsets tended to indicate significant positive relationships between bathymetric range and longevities. Species richness was significantly
and positively correlated with genus longevities. Species and genera with subspecies and
species with high morphological variability all had significantly greater longevities.
Genus-level characteristics can be explained largely by species-level characteristics,
including longevity, latitudinal ranges and bathymetric ranges to a lesser degree. However, genus longevity was best explained by species richness and genus age, even for
extinct genera, while species longevity was best explained by species latitudinal range.
Correspondence: Lee Hsiang Liow,
Centre for Ecological and Evolutionary
Synthesis, Department of Biology, University
of Oslo, P.O. Box 1066, Blindern, N-0316,
Oslo, Norway
E-mail: [email protected]
Main conclusions In spite of the incompleteness of the fossil record, we can control
for biasing factors and still confidently draw the conclusion that both ecological and
evolutionary versatility contribute to lineage longevity, beyond the shorter temporal
observation windows available to most ecological studies.
Keywords
Fossil record, genus, geologic longevity, sampling, species, trachyleberidid
ostracodes.
Extinction risk and extinction selectivity are foci of today’s
ecological research (McKinney, 1997; O’Grady et al., 2004; Sodhi
et al., 2004; Reynolds et al., 2005). Body size, life history variables,
range size, endemicity and genetic variability, among other factors,
have been examined as contributors to the probability of survival
of extant populations (Spielman et al., 2004; Cardillo et al., 2005;
Saether et al., 2005). However, for a more complete understanding
of the general factors contributing to realized lineage longevities
we need to turn to the fossil record.
Some fossil taxa survived for longer periods of geologic time
than their relatives (Stanley, 1979; Jablonski, 1994). Their observed
persistence cannot simply be explained by preservation or other
© 2006 The Author
Journal compilation © 2006 Blackwell Publishing Ltd
DOI: 10.1111/j.1466-8238.2006.00269.x
www.blackwellpublishing.com/geb
INTRODUCTION
117
L. H. Liow
sampling biases (Foote & Raup, 1996). Having greater lineage
longevity involves (1) not becoming extinct during intervals of
background extinction, at mass extinctions or somewhere along
this continuum, and (2) not evolving into another taxon without
leaving populations of the ancestral taxon (pseudo-extinction).
What could promote increased longevity?
Ecological versatility, here defined as the number of physical
locations (e.g. width of geographic range) and ecological conditions (e.g. different temperature regimes) in which a lineage
can survive, could aid lineage survival (Jackson, 1974; Boucot,
1975; Jablonski, 1980; Martinell & Hoffman, 1983; Jablonski,
1986; Kammer et al., 1997; Bean et al., 2002; Harley et al., 2003;
Viranta, 2003; Kiessling & Baron-Szábo, 2004; Bown, 2005).
However, contrary or non-significant results have also been found,
especially across severe extinction events (Stanley, 1986; Norris,
1992; Jablonski & Raup, 1995; McClure & Bohonak, 1995), presumably because the magnitude of environmental change during these
times is greater than can be tolerated even by ecologically versatile
lineages. Similarly, evolutionary versatility, here approximated as
the propensity to give rise to daughter taxa or morphological
variability, could also be positively correlated with lineage longevity
(Flessa & Jablonski, 1985; King & Hanner, 1998; Liow, 2004).
Having more progeny to increase chance survival is analogous to
increasing reproductive output in individuals.
Here, I use extensive data on the Trachyleberididae (Podocopida:
Ostracoda) to pose questions involving lineage longevity.
Ostracodes are particularly suited to ask macroecological
questions in the fossil record because of their very abundant and
continuous fossil record that has long been studied intensively
due to their utility in applied geology (Maddocks, 1983; Colin &
Lethiers, 1988; Reyment, 1988; Keen, 1993; Athersuch, 1994;
Boomer et al., 2003; Ruiz et al., 2003). Results from this study
will help us to re-evaluate conclusions drawn from other clades,
both extant and extinct, which may have different ecologies,
preservation potentials and states of taxonomic knowledge.
Trachyleberidids are marine benthic ostracodes that were
already diverse by the late Cretaceous and form a substantial part of
marine benthic communities today. They are abundant all along
the marine depth gradient, from brackish waters to the abyssal
plains. Shallow water species are commonly epiphytic on plants
and those in deep waters may be detritus feeders (Swain, 1974).
Ostracodes lack pelagic phases, although they can gain extremely
widespread distributions (Whatley & Ayress, 1988), achieved
literally by walking (Benson, 1973), although they must occasionally disperse via currents, rafting or other accidental means.
Ostracode species often have sufficiently short geologic ranges
to be useful in defining biozones that can be correlated across
different locations (van Morkhoven, 1963). There are many
endemic species, as well as very widespread and long-ranging
ones (Whatley & Ayress, 1988). Ostracode geologic ranges
(together with their geographic locations and (palaeo)depths)
are often reported in the taxonomic and biostratigraphic literature, but analyses of ostracode ranges as focal points have been
rare and highly descriptive in nature (Swain, 1992).
Here, I test the hypothesis that both genus and species longevity
are positively correlated with ecological versatility (here measured
118
using the number of bathymetric zones traversed and geographic
spread). Concurrently, I factor out sampling biases that may be
the primary cause of an observed correlation by subdividing my
dataset into broad geographical areas and time periods and by
removing singleton and extant taxa. I also correct geographic
ranges and the number of occurrences by the number of times
a species was mentioned in the literature and attempt to reduce
sampling biases by using rarefaction techniques. In addition, I
test whether genus and species longevity are positively correlated
with evolutionary versatility (the number of species, the number
of subspecies and extreme species morphological variability). I
then compare geographic spread and bathymetric range together
with sampling and other confounding factors (such as taxon age,
which is expected to correlate positively with longevity, at least for
extant taxa) to investigate which factors contribute more strongly to
observed longevity. I discuss whether species patterns are sufficient
to explain genus patterns and conclude by comparing the longevity
patterns of trachyleberidid ostracodes with those of other clades.
METHODS AND MATERIALS
Taxonomic and morphological data
My database of species and genera of Trachyleberididae s.l.
(including Trachyleberididae s.s., Hemicytheridae and Cytherettidae) is updated from a previous database involving the
morphology of trachyleberidid genera (Liow, 2006). The family
s.l., is evidently monophyletic as found by molecular techniques
(T. Oakley, pers. comm.). I systematically traced trachyleberidid
taxa using online databases (Georef, Geobase, Zoological Records,
Biological Abstracts and the Web of Science or ISI), the Kempf
(1986 –2005) database on Ostracoda and the primary literature.
Many obscure references seen in the Kempf database were not
available within the period of this study and they encompass
about 800 species names. Some of these species names are possibly
synonyms. The c. 800 excluded species are taxa from less wellstudied regions of the world, which do not contribute as much
reliable data in terms of depth of occurrence, geographic or geologic ranges (see Discussion). My database contains 398 genera
and 4216 species, ranging from the late Jurassic (trachyleberididlike taxa) to the Recent and with a global coverage.
Ambiguous taxonomic assignments (e.g. cf., aff. and ?),
nomina nuda and unnamed species were recorded but discarded
for the purposes of these analyses. Most of these taxa are very rare
in the studies that report them and are not likely to be sampled
again (Koch, 1987) or there is substantial uncertainty about their
identity, possibly due to poor preservation. Preliminary analyses
involving these ambiguous entries did not change the results
qualitatively. I use the most current genus assignment determined
from the literature unless there is evidence that the current revision
may be less informed than an older one.
While collecting data from the literature, it was apparent that
species reported more frequently might not only be more
abundant in sediments but also better known taxonomically and
more recognizable morphologically. Some of these may also be
garbage-can or cryptic species. To keep track of the variation in
© 2006 The Author
Global Ecology and Biogeography, 16, 117–128, Journal compilation © 2006 Blackwell Publishing Ltd
Versatility and longevity
Table 1 Bathymetric zones. The depth zones coded for species for which data are available are listed, together with the approximate depth range
associated with them. Approximate synonyms as commonly used in the ostracode literature are listed in the last column. These catogories are
loosely based on Keen et al., 1994. Zones 1–7 are used in Fig. 4 while the more inclusive zones 8–9 are used in constructing Figs 2 and 3
Zone
Category
Approximate Depth (m)
“Synonyms”
1
2
3
4
5
6
7
brackish
inner neritic
middle neritic
outer neritic
upper bathyal
lower bathyal
abyssal
NA
0–20
20–100
100–200
200–500
500–4000
>4000
mangrove; or some freshwater influence
lagoonal; beach; tidepool; littoral; intertidal; subtidal; inner shelf
midshelf; nearshore; circalittoral; inner sublittoral
sublittoral; continental slope; midshelf; offshore
8
9
neritic
bathyal
0–200
200–4000
shallow waters; carbonate platform (= Zones 1, 2, 3 and/or 4)
deep sea; deep waters (= Zones 5, 6 and/or 7)
sampling intensity, each new report (even in the same county or
state) of a species that I encountered in the literature is noted as
an additional literature report for that species.
I recorded all the subspecies that were recognized. I also noted
species that authors described as highly morphologically variable
or having many morphotypes in the same sample, outcrop or
local region, beyond the variation recorded among instars and
between the sexes. Only if these purported morphotypes were
examined by the same author in each species, were they coded
as such. This is to have some confidence that these taxa have a
greater chance of being truly variable lower taxa than simply
being mis-identified. It is acknowledged that these are possibly
different but closely related species that have maintained
geographical coexistence to some extent and that some truly
morphologically variable species may not be coded as such. For
instance, Hazel (1967) reported that ‘the variability of R. tuberculata
is great’, confirming earlier observations, and Brouwers (1993)
further described the variation and included morphological plots
of Robertsonites tuberculata (Sars, 1865). Hence R. tuberculata is
coded in my database as being highly morphologically variable.
Geographic range data
Genus geologic ranges (= genus longevity) in my database are
informed by species ranges (= species longevity), which are in
turn tracked by occurrences of species. Each occurrence record in
my database (n = 10,466) is defined by a unique combination of
the time and location at which the species in question occurs.
I converted each published occurrence of a species within a time
interval to a numerical value using the International Stratigraphic
Chart (International Commission on Stratigraphy, 2004). I
coarsened the location resolution of the reported data where
appropriate, so that less precise but nevertheless useful data can
be accommodated. These locations are semi-arbitrary divisions of
space that tend to be present-day political units (countries, states
and natural geographical divisions, e.g. islands). Each of these
locations is identified by their current mid-point latitudinal and
longitudinal positions using the online databases at the National
Geophysical Data Center for DSDP and ODP sites and the online
including continental rise
abyssal plains, deep ocean basins
Getty Thesaurus of Geographic Names or, in a few cases, approximated centrally on a hard copy of a current map.
Because of plate tectonic motions, reconstructed palaeogeographical coordinates are needed to provide a consistent
basis for calculating geographic ranges. Thus, I rotated all the
occurrences one million years (1 Myr) and older from their current coordinates to their palaeocoordinates using the program
locrot, written by David Rowley (pers. comm.). For example, if
a record for a given species is ‘the Moodys Branch Formation in a
particular road cut in Clarke County, Mississippi’, regardless of
whether actual present day coordinates were given, that record
will be taken as Upper Eocene, Mississippi, with current coordinates
32.3, −90.2 and rotated coordinates 27.6, −77.4. This approach
was taken because ostracode biogeographical provinces are not
known for some regions of the world. Available data are also not
detailed enough for a quadrant approach (e.g. Viranta, 2003).
Moreover, ostracodes are described not only from coastal outcrops but also from terrestrial outcrops that are far inland, and
from deep-sea cores, rendering impossible the latitudinal linear
range approach used by Jablonski and colleagues (e.g. Jablonski
& Valentine, 1990) for taxa occurring on continental shelves. It
has been shown empirically that method and resolution should
not be critical impediments to the recognition of large-scale biogeographic patterns (Blackburn et al., 2004).
Bathymetric data
The water depths in which extant species were collected are
sometimes reported in the literature quite precisely (within a
metre) and these were used to put species in broadly defined
depth zones of occurrence (Table 1). The palaeodepth or palaeoecology of a species is often inferred with a good amount of confidence from prior geological knowledge of the area from which
the ostracodes in question were collected, or from the community
composition of the ostracodes found (van Morkhoven, 1963;
Benson, 1973). Although the palaeodepth data inferred from the latter
studies may appear circular, only a few key taxa were used to determine depths of occurrences and these include non-trachyleberidid
taxa. Authors may either report a depth range for the fossil
© 2006 The Author
Global Ecology and Biogeography, 16, 117–128, Journal compilation © 2006 Blackwell Publishing Ltd
119
L. H. Liow
Table 2 Data subsets. The mean, median, maximum and minimum longevity (millions of years) of genera and species are reported for data
subsets (where ALL = all taxa, EX = extinct taxa, NOS = singleton species removed, CRET = taxa extant during the Cretaceous, PALE = taxa
extant during the Palaeogene, NAM = North American taxa, EU = European taxa), with N being their respective sample sizes. The zero values
reflect taxa that are found only in a single time interval. The last two columns (ks.test(dataset)) report P-values for Kolmogorov-Smirnov tests
between pairs of datasets, and grey boxes indicate a significant difference (P < 0.05)
Genus
ALL
EX
N
338
165
Mean
Median
Max
Min
ks.test ALL
27.5
26.8
18.6
20.9
140.5
95.0
0.0
0.0
0.56
NOS
287
26.7
16.6
134.5
0.0
0.12
CRET
PALE
129
161
23.4
30.6
20.9
28.9
122.0
87.7
0.0
0.0
0.07
0.02
ks.test Pale
0.01
NAM
EU
109
78
24.4
29.9
14.6
19.3
116.5
122.0
0.0
0.0
0.24
0.30
ks.test NAM
0.06
Species
ALL
EX
3749
2723
4.7
4.9
0.0
0.0
68.2
59.2
0.0
0.0
0.00
NOS
2130
8.4
5.0
68.2
0.0
0.00
CRET
PALE
923
1234
5.8
8.2
3.0
3.3
68.2
68.2
0.0
0.0
0.00
0.00
ks.test Pale
0.00
NAM
EU
681
1220
4.8
4.5
0.0
1.5
56.4
51.3
0.0
0.0
0.57
0.06
ks.test NAM
0.02
community or use descriptive terms such as ‘continental shelf ’ or
‘littoral’ or ‘deep waters’, or state both descriptive terms and
approximate quantitative measures. Some terms have variable
usage, but I tried to take into consideration the authors’ practices
to give the species reasonable depth assignments. Where the literature is ambiguous, I used the broadest categories in Table 1
(Zones 8 and 9) or left the depth unassigned.
Data subsets
I divided the database (ALL) into subsets (Table 2). EX comprises only extinct genera or extinct species, respectively, for
genus and species subsets. The subset with no singletons (NOS)
is the subset with removal of species recorded only at one place at
one time interval (i.e. one occurrence record). Genus variables
were recalculated with the remaining non-singleton species. The
North American (NAM) subset contains all the occurrences of
taxa in North America and Central America, including Mexico,
Panama and the Caribbean islands, as studied thoroughly by van
den Bold, Howe and Hazel and their co-workers (e.g. Hazel, 1967;
van den Bold, 1970; Howe & Howe, 1973). The European (EURO)
subset contains all the occurrences of taxa in Western Europe, a
geographic region for which ostracodes have also been well
studied for a long time (Benson, 1966). The Cretaceous (CRET)
subset contains all taxa that were extant during the Cretaceous
(including those with first and last appearances outside of the
Cretaceous) and the Palaeogene (PALE) subset contains all the
taxa that were extant during the Palaeogene (including those with
first and last appearances outside of the Palaeogene). Jurassic
taxa are very few and their identities as trachyleberidids are
120
uncertain, while Neogene taxa tend to exhibit range truncation
toward the Recent if they are extant. Hence these two obvious
temporal divisions of data are left out. The data and bibliographic sources are available upon request.
Analyses
To test for significant differences in (1) longevity distributions
among data subsets and (2) proportions of species occurring in
various depth zones and during different time intervals, I used
the Kolmogorov–Smirnov test, henceforth the K–S test (Sokal &
Rohlf, 1995).
To test for significant correlations between latitudinal ranges,
longitudinal ranges, the number of records and longevity, I used
non-parametric correlation tests. This is because assumptions of
parametric tests are violated by my data (Sokal & Rohlf, 1995).
Spearman’s rank test gave the same qualitative results as Kendall’s
test in all cases. Therefore I report and discuss only Kendall’s tau
and the associated Bonferroni corrected probability values (Sokal
& Rohlf, 1995). I corrected for sampling intensity by dividing the
geographic ranges and occurrence records with the number of
literature reports, and then recalculating correlation coefficients.
Similarly, I report Kendall’s tau and Bonferroni corrected probability values for the correlations between depth range, morphological
variability and species richness, vs. species and/or genus longevity.
A second method I used to account for unequal sampling
intensity is rarefaction analysis. I singled out species with two or
more records, then only species with three or more records,
through to only those with eight records or more (‘Qualifying’ in
Appendix S1 in Supplementary Material). I then randomly chose
© 2006 The Author
Global Ecology and Biogeography, 16, 117–128, Journal compilation © 2006 Blackwell Publishing Ltd
Versatility and longevity
a fixed number of records (‘Rarifying’ in Appendix S1) associated
with qualifying species to control for their ‘commonness’ in the
literature. I then calculated rarified longevities and latitudinal
and longitudinal ranges and reanalysed the correlation between
them. Each rarefaction exercise was repeated 100 times. Rarefaction
was not used to equalize depth records because relatively fewer
primary literature sources reported individual depth occurrences,
as compared with geographic occurrences. Most depth data were
reported from composite sources, as composite depths and are
hence not adequately structured for a rarefaction exercise.
Genus-level characters (genus geographic range and depth
range and longevity) are not independent from species-level
characters because they are calculated directly from those at the
lower taxonomic level. To test for significant relationships beyond
an expected autocorrelation, I used a randomization approach. For
example, I randomly drew values from the list of original species
median longevities, with replacement, and assigned those to
genera. When a randomly drawn species longevity value was larger
than the associated genus longevity, I discarded that value and
randomly drew another one until the drawn value was logically
possible. The probability of the correlation for these randomized
values was then compared with that of the original data.
I used multiple regression to investigate which variables
contribute more strongly to genus and species longevities. For
genus longevity, latitudinal range, longitudinal range, depth range,
the number of records, the number of literature reports, age (first
appearance in the fossil record) and species richness were included
as variables. For species longevity the same variables were
included except the last. As none of the variables are normally
distributed, I ranked the variables and used the resulting ranks as
inputs for multiple regression analysis (Conover & Iman, 1981).
All the analyses were performed using R (R Development Core
Team, 2005).
RESULTS
Longevity and ecological versatility I: geographic
spread
The mean number of occurrence records (of species constituting
genera), and latitudinal and longitudinal ranges of genera, were
strongly positively correlated with genus longevities for all subsets
of data (Fig. 1, Table 3). Similarly, the number of records, and
latitudinal and longitudinal ranges of species, were also strongly
positively correlated with species longevities (Table 3).
Correcting for sampling intensity, by dividing geographic
ranges and the number of occurrence records by the number of
literature reports, generally did not change the strong positive
relationships between genus longevity and latitudinal and longitudinal ranges or the number of records. For the subsets EX,
NOS, NAM and EURO, the number of records was unrelated to
genus longevity after this correction. This was not the case for
species, where a significant positive relationship between longevity and the number of records, latitudinal and longitudinal
ranges remained after this correction, except for the last comparison for NOS (Table 3).
Figure 1 Geographic range vs. genus longevity. Genus longevity
(Myr) plotted against genus latitudinal range (degrees) for the whole
data set (ALL). Solid circles represent uncorrected latitudinal ranges
and empty ones represent those divided by the number of literature
reports. Rank correlation coefficients and probabilities are reported
for each case (tau for the uncorrected and cor-tau for the corrected).
After rarifying the records, neither longitudinal nor latitudinal
ranges of genera correlated with genus longevity, with only one
exception (see Supplementary Appendix S1). It should be noted
that this culling exercise was very severe because it left out,
together with truly rare or little-known species, locally common
and well-known species whose occurrences were combined in
very few records or even just one. The rarified species data
showed a different result. After rarifying the records, latitudinal
ranges of species were still significantly correlated with species
longevity in 5 out of 21 cases, in particular, if the number of
qualifying species was equal to the number of sampled species.
Longitudinal ranges of genera were not significantly correlated
with species longevity after rarefaction, except in a few cases (see
Supplementary Appendix S1).
Longevity and ecological versatility II: bathymetric
spread
The number of depth zones occupied by genera had no consistent
bearing on their longevities, although both the subset excluding
singletons (NOS) and the subset of Palaeogene genera (PALE)
indicated a significant positive one (Table 4). Species data subsets
showed more cases of significant positive relationship between
depth range and longevities (Table 4), although again, the significance was not universal across the subsets of data and correlation
coefficients were small.
Genera consisting of only shallowly distributed or only deeply
distributed species were significantly different from genera that
© 2006 The Author
Global Ecology and Biogeography, 16, 117–128, Journal compilation © 2006 Blackwell Publishing Ltd
121
L. H. Liow
Table 3 Geographic spread and longevity. Correlation cofficients (Kendall’s tau) calculated from comparing the listed variables and taxon
longevity are reported for various data subsets (where ALL = all taxa, EX = extinct taxa, NOS = singleton species removed, CRET = taxa extant
during the Cretaceous, PALE = taxa extant during the Palaeogene, NAM = North American taxa, EU = European taxa). The asterisks *, ** and
*** represent significance at the P = 0.05, 0.01 and 0.001 levels, respectively (after Bonferonni correction for 3 × 7 = 21 overlapping datasets).
NS = not significant. Square brackets indicate a change in significance if values divided by the number of literature reports were used to calculate
correlation coefficients
Genus
ALL
EX
NOS
NAM
EURO
CRET
PALE
Species
Mean Species
Occurrence Records
Latitudinal
Range
Longitudinal
Range
No. Occurrence
Records
Latitudinal
Range
Longitudinal
Range
0.29***
0.39*** [NS]
0.31*** [NS]
0.21 NS [NS]
0.20* [NS]
0.30*** [NS]
0.39***
0.54***
0.63***
0.45***
0.51***
0.51***
0.61***
0.66***
0.47***
0.61***
0.39***
0.51***
0.45***
0.54***
0.59***
0.69***
0.73***
0.29***
0.57***
0.72***
0.72***
0.73***
0.63***
0.71***
0.19***
0.51***
0.67***
0.67***
0.70***
0.61***
0.68***
0.16*** [NS]
0.50***
0.64***
0.67***
0.66***
Table 4 Bathymetric range versus longevity. Correlation values
(Kendall’s tau) between bathymetric range and longevity. The
asterisks * , ** and *** represent significance at the P = 0.05, 0.01
and 0.001 levels, respectively (after Bonferonni correction for seven
overlapping datasets). NS = not significant. Sample sizes (N ) are
shown because depth data are available only for some taxa. As before,
ALL = all taxa, EX = extinct taxa, NOS = singleton species removed,
CRET = taxa extant during the Cretaceous, PALE = taxa extant
during the Paleogene, NAM = North American taxa,
EU = European taxa
ALL
EX
NOS
NAM
EURO
CRET
PALE
N
Genus
N
Species
228
98
194
64
78
68
76
−0.11 NS
−0.15 NS
0.33***
0.09 NS
0.02 NS
0.12 NS
0.23*
976
442
917
194
202
179
255
0.09***
0.12**
−0.01 NS
0.11 NS
0.13**
0.09 NS
0.27***
span both shallower and deep waters, which had greater mean
and median longevities (K–S test, P << 0.05). Even when extant
taxa were removed, the longevities of these three subdivisions of
depth occupation were still very different, although the difference was significant only between deeply distributed genera and
those with mixed distributions (Fig. 2).
Longevity distributions of shallowly distributed species,
deeply distributed species and those with mixed-depth zone
occupation of either the global or extinct datasets were not
significantly different from one another (K–S test, P >> 0.05 in
all cases, Fig. 3). However, both mean and median longevities of
species with mixed-depth occupation were greater than those of
exclusively shallow and deep species, even though the longevity
distributions were not significantly different.
122
Figure 2 Genus longevity and depth zones. Histograms of genus
longevities as subdivided by whether they occupy only shallower
waters (Zone 8 in Table1), only deep waters (Zone 9) or both.
All = all genera, Ex = extinct genera, N = sample size, mean = mean
genus longevity (Myr), median = median genus longevity (Myr),
max = maximum genus longevity (Myr).
One concern with palaeobathymetric information is that
some time intervals are better known than others. However, the
proportions of species occupying different depth zones were not
different for Cretaceous, Palaeogene and Neogene time intervals
© 2006 The Author
Global Ecology and Biogeography, 16, 117–128, Journal compilation © 2006 Blackwell Publishing Ltd
Versatility and longevity
Figure 3 Species longevity and depth zones. Histograms of
longevities of species as subdivided by whether they occupy only
shallower waters (Category 8 in Table1), only deep waters (Category
9) or both. All = all species, Ex = extinct species, N = sample size,
mean = mean species longevity (Myr), median = median species
longevity (Myr), max = maximum species longevity (Myr).
(Fig. 4; K–S tests, P >> 0.05 after Bonferroni correction for three
overlapping datasets), despite more available information on the
depth distribution of the largely extant Neogene species. It is
acknowledged, however, that even though there is no global difference in the distribution of depth zones for the three broad time
intervals, regional and local differences could still bias the data.
Longevity and evolutionary versatility I:
species richness
Species richness was significantly and positively correlated
(P < 0.001) with genus longevities in both the global data and all
the subsets (Kendall’s tau ranging from about 0.50–0.60, detailed
results not shown), even when possible garbage-can genera
(Cythereis, Trachyleberis, Cytheretta) were removed.
Longevity evolutionary versatility II: subspecies
richness
Of the 4216 species in my database, 279 had two to nine subspecies described. The longevity distributions of these species
and the genera that contained them were significantly different
from the dataset as a whole (K–S test, P < 0.001 in all compari-
Figure 4 Distribution of species occupying various depth zones.
Number (top values) and percentage (bottom values) of species
occurring at bathymetric zones listed in Table1 during the
Cretaceous, Palaeogene and the Neogene.
sons, median longevity for these species = 8.1 Myr and median
longevity for these genera = 53.2 Myr, see Table 2 to compare
these values with other data subsets).
Longevity evolutionary versatility III: extreme species
morphological variability
Twenty-seven species (of 4216 species) have been described
as being highly variable in morphology. Of these 27 highly
variable species, seven also have subspecies assigned to them.
Similarly, longevity distributions of these species and the genera
that contained them were significantly different from the dataset
as a whole (K–S test, P < 0.001 in all comparisons.) In fact, the
median genus and species longevities were about doubled for
morphologically variable genera (respectively 54.5 and 10.3 Myr),
compared with the dataset as a whole.
Which factors are stronger?
Genus longevity has been shown in the previous sections to be
positively correlated with geographic spread, species richness and
only weakly related to bathymetric spread. However, genus age
and sampling can also contribute to the observed genus longevity.
The older a genus is or the earlier it first appears in the fossil
record, the greater its chance of having an increased longevity
compared with younger genera whose longevity is necessarily
capped by the frame of observation that includes the Recent time
interval. Additionally, the more frequently a species is sampled in
© 2006 The Author
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123
L. H. Liow
Table 5 Results of multiple-regression analyses where longevities of genera and species were regressed on the factors listed in the first column.
Results from whole data set (ALL) and the extinct dataset (EX) for genera and species are shown. The asterisks *, ** and *** represent significance
at the P = 0.05, 0.01 and 0.001 levels, respectively
Estimate
Std Error
t value
P-value
Genus/ALL
Intercept
latitudinal range
depth range
literature reports
genus age
species richness
−23.835
0.057
0.018
0.112
0.455
0.497
9.271
0.052
0.037
0.035
0.030
0.047
−2.571
1.104
0.492
3.243
15.291
10.503
0.011*
0.270
0.623
0.001**
0.000***
0.000***
Genus/EX
Intercept
latitudinal range
depth range
literature reports
genus age
species richness
−7.695
−0.027
0.064
0.187
0.209
0.660
7.109
0.088
0.061
0.060
0.049
0.076
−1.082
−0.302
1.056
3.092
4.255
8.663
Species/ALL
Intercept
latitudinal range
depth range
literature reports
species age
121.193
0.697
−0.016
0.040
0.214
39.487
0.011
0.010
0.011
0.010
Species/EX
Intercept
latitudinal range
depth range
literature reports
species age
12.292
0.548
0.060
0.252
0.081
12.239
0.041
0.042
0.042
0.032
P-value
R-squared
Adjusted R
193
0.000
0.744
0.740
0.281
0.763
0.292
0.002**
0.000***
0.000***
70
0.000
0.687
0.677
3.069
64.989
−1.576
3.655
22.075
0.002**
0.000***
0.115
0.000***
0.000***
1528
0.000
0.620
0.620
1.004
13.468
1.426
6.013
2.523
0.316
0.000***
0.155
0.000***
0.012*
142
0.000
0.580
0.576
the fossil record the more likely its known longevity would be
lengthened, simply by chance. Multiple regression shows that the
two most important factors contributing to genus longevity are
genus age and species richness, regardless of whether the entire
(ALL) or the extinct (EX) data set is used (Table 5).
Similarly, species longevity is related to geographic spread
and bathymetric range but species age and sampling also
contribute to the observed species longevities. Simple multiple
regression shows that latitudinal spread is the strongest factor
contributing to species longevity. Even though age and sampling
do play a part, their contributions are not as strong (Table 5).
Again, both the whole data set and the extinct data set show the
same qualitative result.
Are species patterns sufficient to explain genus
patterns?
Randomly assigned median species longevity values are barely
correlated with genus longevities (tau = 0.1, P = 0.06) but the
correlation in the original data set is strong (tau = 0.24, P =
3.0 × 10−11; Fig. 5). Randomly assigned median species latitudinal
range values are correlated with genus latitudinal ranges (tau = 0.34,
P = 0.05) but the correlation in the original data set is much
124
F-statistic
more probable (tau = 0.16, P = 1.1 × 10−5). Randomly assigned
species mean and median bathymetric ranges values are, respectively, correlated and not correlated with the respective genus
bathymetric ranges (tau = 0.22, P = 0.005; tau = 0.11, P = 0.09).
But again, the correlation in the original data set is much
stronger (tau = 0.55, P = 2.2 × 10−16; tau = 0.33, P = 12.4 × 10−13,
respectively). Thus species variables do scale up to genus variables
(e.g. genera with greater longevities have member species with
greater longevities).
DISCUSSION
Ecological versatility, as measured by geographic and bathymetric spread, does to some extent contribute to genus and species
longevities. Evolutionary versatility as measured by species or
subspecies richness and morphological variability is also associated
with genus and species longevity.
It has been often verified empirically that taxa with greater
longevities should be geographically widespread (Jackson, 1974;
Martinell & Hoffman, 1983; Jablonski, 1986, 1987; Jablonski &
Raup, 1995; this work). Unfortunately for the purpose of analyses,
widespread taxa are also encountered or sampled with a greater
probability (McKinney, 1986; this work), thus possibly producing
© 2006 The Author
Global Ecology and Biogeography, 16, 117–128, Journal compilation © 2006 Blackwell Publishing Ltd
Versatility and longevity
Figure 5 Genus vs. species longevity. The area on the left delimited
by the line y=x is the logically impossible area (IMPOSSIBLE) for
the plot of median species longevity vs. genus longevity. The original
simple correlation (Kendall) of the plotted data shows a significant
P-value as expected, but when compared with a randomized data set
the original P-value is shown to be highly significant.
a positive correlation between longevity and geographic range
when there is none (Russell & Lindberg, 1988). Although many
palaeontological studies have explicitly accounted for sampling
effects (Pease, 1985; Koch & Morgan, 1988; Miller & Foote, 1996;
Kammer et al., 1997; Marshall, 1997; and references therein), this
approach has not been universally applied. After correcting ranges
and occurrence records by the number of literature reports, the
strong relationship between trachyleberidid geographic ranges
and longevity encouragingly remained in general for species and
genus datasets (Fig. 1). However, using a rather severe rarefaction
regime (Supplementary Appendix S1), latitudinal and longitudinal
ranges of species are only on occasion significantly correlated
with species longevity. Although singleton species can be true
sampling artefacts, this result signifies that many singleton
species discarded in the rarefaction exercise were true narrowly
distributed species that do contribute to the clade pattern. The
rarified genus data show no correlation between longitudinal or
latitudinal ranges with longevities in almost all rarified cases.
However, when multiple factors were examined in concert, latitudinal range turned out to be the most important contributor to
species longevities (Table 5). This study serves to confirm that
even for benthic organisms that may not disperse as easily as
organisms with a planktonic dispersal phase in their life cycles,
geographic range is an important factor in promoting longevity,
as has been shown in molluscs (Jablonski, 1980, 1986, 2005) and
foraminiferans (Buzas & Culver, 1984), at least during background extinction time intervals.
Depth is not a simple variable because it co-varies with other
physical parameters (e.g. light penetration, oxygen levels, temper-
ature) that could affect the vertical range of a taxon (Pineda, 1993).
Taxa with wider depth ranges are presumably more ecologically
tolerant (Harley et al., 2003) and hence we expect depth ranges to
be positively correlated with lineage longevities. I note that greater
depth ranges may not aid survivorship across mass extinctions
(Jablonski & Raup, 1995). It is also possible that vertically spread
species have less of a tendency to speciate (Pineda, 1993) and thus
do not have the propensity to result in the extinction or pseudoextinction of their potential ancestral species. Depth may also
affect pelagic and benthic taxa differentially. Here I have shown
that bathymetric range only has a weak relationship to genus and
species longevities, although genera and species that live in both
deep and shallow waters (i.e. those taxa that are extremely broadly
vertically distributed) do have greater longevities (Figs 2 and 3).
However, when bathymetric range is examined in concert with
other factors, it does not contribute significantly to genus or species
longevity. It is possible that bathymetric distribution is not a good
proxy for ecological versatility for these benthic ostracodes. Temperature, grain size or nutrient level tolerance may serve as better
approximators of ecological versatility but are not available at the
scale of this study. Alternatively, the subdivisions of depth zones made
in my data may not be fine enough to capture ecological versatility, or perhaps ecological versatility as measured by the width of
depth distribution actually does not aid in trachyleberidid longevity.
Species richness, subspecies richness and morphological
variability are recognized here as evolutionary versatility. Having
more species or subspecies may promote longevity (Flessa &
Jablonski, 1985; McKinney, 1995; but see Fortey, 1980) via greater
abundance and geographic spread such that chance events have a
smaller probability of wiping out the entire lineage. Alternatively,
the different species or subspecies or various morphological
forms may respond to environmental changes differently such
that one species or subspecies or form may continue surviving
when changes detrimentally affect congenerics or conspecifics. A
test of the two alternative pathways will require abundance data and
more detailed morphological data, neither of which are available
at the moment. Another untested possibility is that benthic
ostracodes, not being able to disperse easily as individuals, may
rely more on variability for survival, in contrast with taxa that are
able to disperse widely as larvae or adults.
Historically, in palaeobiology and macroevolution, the genus
has always been a convenient focal taxonomic level because it is
sampled more completely than the species. Although higher taxa
like the genus have been shown to be suitable for macroevolutionary studies (Sepkoski & Kendrick, 1993; Robeck et al., 2000),
the nature of biological hierarchies can complicate longevity
patterns (Valentine & May, 1996). Here, I have shown that species
characters do reflect genus characters (longevity, geographic
and bathymetric range) such that when these characters are
examined at the genus level, they can potentially reflect patterns at
the species level. However, details of patterns may differ at the two
taxonomic levels. At least in these data, genus longevity is most
strongly influenced by genus age (see Miller, 1997) and species
richness, while species longevity is most strongly affected by
latitudinal range. This suggests that it is important to study
macroevolutionary patterns at different levels of the taxonomic
© 2006 The Author
Global Ecology and Biogeography, 16, 117–128, Journal compilation © 2006 Blackwell Publishing Ltd
125
L. H. Liow
hierarchy (Robeck et al., 2000) as details can change and affect
our understanding of the underlying processes.
Caveats
The taxonomy of trachyleberidid ostracodes is in flux, as it is for
other groups of organisms that enjoy continued study. Inevitably,
some published identifications may be erroneous despite best
efforts. For instance, some previously good species may actually
be multiple species and vice versa (e.g. Jellinek & Swanson, 2003;
Schornikov, 2005), such that there are both range over- and
underestimates. However, most named species are relatively
undisputed (Benson, 1966; L.H.L. pers. obs.), although their
membership in genera can be volatile in the literature. Moreover,
no comprehensive phylogenetic framework is available for
trachyleberidids. Some recorded extinctions of some species in
my database will inevitably contain pseudo-extinctions and some
of the named taxa may also be paraphyletic, but these have not
caused problems in macroevolutionary studies (Sepkoski &
Kendrick, 1993; Jablonski, 1994; Robeck et al., 2000). Taxonomic
errors should tend to dampen significant results rather than
promote them. It has been demonstrated that results from such
large-scale compilations of data can remain robust despite new
taxonomic information (Sepkoski, 1993). To be really sure that
taxonomic problems are not giving falsely positively results, we
need the concerted efforts of taxonomic revisions followed by reanalyses of data. On a positive note, however, the taxonomically
better studied subsets of data in this study, namely North American
and European subsets, largely show the same patterns as the data
set as a whole even though they each represent only about
one-third of the globally known species data in my database.
This result gives some reassurance that even though taxonomic
misidentifications do exist, they do not drive the results. The
Palaeogene and Cretaceous datasets were also based on very
different sets of taxonomic workers, and only about 15% of the
known Cretaceous species extend to the Palaeogene after the
Cretaceous–Tertiary extinction, but despite their differences,
results from the two data subsets were again not dissimilar. In
addition, the c. 800 species names that were excluded from the
study (largely from outside of North America and Europe) may
clarify patterns if included, but since the North American and
European data subsets show largely the same patterns compared
with the full data set, we can infer that the missing species will not
change the general patterns qualitatively. Even without detailed
phylogenetic information, large-scale issues in macroevolution
and macroecology, such as those discussed in this paper, can and
should be tackled (Brown et al., 1996).
In addition to taxonomic uncertainties, longevity patterns
may be due largely to changes in sampling probabilities due
to the rise and fall of global sea-levels. However, the number
of originations and extinctions over geological time for both
trachyleberidid genera and species do not vary in synchrony with
eustatic sea-level changes (data not shown). However, as noted
before, this does not at all imply that local or even regional species
sampling is not affected by regional or basinal sedimentation
patterns or sea-level changes.
126
Conclusions
Being versatile promotes longevity and reflects the idea that
generalists are better equipped to survive for longer periods of
time (Simpson, 1944; Liow, 2004). However, many details of exactly
how versatility operates still elude us, for example whether species
richness promotes genus longevity via greater abundance or
increased ecological tolerances. Versatility does play a real part
in long-term survivorship as observed in the fossil record, on
temporal scales beyond that of most ecological studies.
ACKNOWLEDGEMENTS
Comments from two anonymous referees greatly improved the
flow and accessibility of this manuscript. I thank Scott Lidgard,
Leigh van Valen, Gene Hunt, Arnold Miller, Paul Harnik, Peter
Wagner, David Jablonski and Carl Simpson for discussions and
the entire marine ostracode research community, especially Todd
Oakley, Tom Cronin and Joe Hazel for their guidance. Joe Hazel who
recently left this world will be greatly missed for his kindness, generosity and immense knowledge on ostracodes. David Rowley and
David Sunderlin kindly helped with palaeogeographical rotations.
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BIOSKETCH
Lee Hsiang Liow was a PhD candidate in the Committee
on Evolutionary Biology at the University of Chicago. She is
broadly interested in the patterns and causes of persistence,
be they morphological, taxonomic or genetic. She has
done research on the morphological distribution of longranging crinoid and ostracode taxa in the fossil record.
Conservation biology is her persistent side-interest.
Editor: Matt McGlone
SUPPLEMENTARY MATERIAL
The following material is available online at
www.blackwell-synergy.com/loi/geb
Appendix S1 Resampled correlations
© 2006 The Author
Global Ecology and Biogeography, 16, 117–128, Journal compilation © 2006 Blackwell Publishing Ltd