Biological Journal of the Linnean Society, 2010, 99, 424–444. With 5 figures
Multilocus phylogeography of the flightless darkling
beetle Nyctoporis carinata (Coleoptera: Tenebrionidae)
in the California Floristic Province: deciphering an
evolutionary mosaic
MAXI POLIHRONAKIS* and MICHAEL S. CATERINO
Department of Invertebrate Zoology, Santa Barbara Museum of Natural History, 2559 Puesta del Sol
Road, Santa Barbara, CA 93105, USA
Received 16 July 2009; accepted for publication 9 September 2009
bij_1360
424..444
The California Floristic Province (CFP) is considered a global biodiversity hotspot because of its confluence of high
species diversity across a wide range of threatened habitats. To understand how biodiversity hotspots such as the
CFP maintain and generate diversity, we conducted a phylogeographic analysis of the flightless darkling beetle,
Nyctoporis carinata, using multiple genetic markers. Analyses of both nuclear and mitochondrial loci revealed an
east–west genetic break through the Transverse Ranges and high genetic diversity and isolation of the southern
Sierra Nevada Mountains. Overall, the results obtained suggest that this species has a deep evolutionary history
whose current distribution resulted from migration out of a glacial refugium in the southern Sierra Nevada via the
Transverse Ranges. This finding is discussed in light of similar genetic patterns found in other taxa to develop a
foundation for understanding the biodiversity patterns of this dynamic area. © 2010 The Linnean Society of
London, Biological Journal of the Linnean Society, 2010, 99, 424–444.
ADDITIONAL KEYWORDS: cytochrome oxidase I (COI/CoxI) – guftagu – southern Sierra Nevada.
INTRODUCTION
The California Floristic Province (CFP) is simultaneously a region of high biodiversity and one in which
development and other land uses severely threaten
parts of the native biota. As such, it has been recognized as a globally significant biodiversity hotspot
by Conservation International in an effort to raise
awareness and establish its needs as a top conservation priority (Conservation International, 2009). The
CFP comprises approximately 70% of the state of
California and extends north across the state boundary into Oregon and south into the Baja California
peninsula. Understanding the range of diversity
patterns of species in this region is essential for
preservation of its delicate ecological systems. By
reconstructing the evolutionary history of species and
integrating this information with geographic data, we
*Corresponding author. E-mail: [email protected]
424
will develop a better understanding of how these
regions accumulate and maintain diversity (Avise,
2000). The dynamic geographic history and high
habitat diversity of the CFP are frequently invoked as
causes of increased species diversification and have
been used to explain phylogenetic patterns across
many plant and vertebrate taxa (Calsbeek, Thompson
& Richardson, 2003). Recent comparative phylogeographic analyses of the CFP have revealed relatively
concordant spatial barriers and high genetic diversity
related to the orogeny of the Transverse Ranges,
Tehachapi Mountains, and the Sierra Nevada (Calsbeek et al., 2003; Feldman & Spicer, 2006; Rissler
et al., 2006; Chatzimanolis & Caterino, 2007a), and
have used this information to identify diversification
‘hotspots’ within the larger CFP ‘hotspot’ (Davis et al.,
2008). Although these generalized patterns provide a
useful comparative framework for phylogeographic
investigation of the CFP, fine-scale analyses of
patterns within species continue to provide the
© 2010 The Linnean Society of London, Biological Journal of the Linnean Society, 2010, 99, 424–444
PHYLOGEOGRAPHY OF N. CARINATA
foundation for our understanding of how biodiversity
patterns arise in this region because concordance of
genetic barriers across broad spatial scales among
taxa does not necessarily imply parallel patterns of
local adaptation and diversification (Feldman &
Spicer, 2006).
In the past decade, the Transverse Ranges have
received much of the attention of phylogeographers in
the CFP (Calsbeek et al., 2003; Lapointe & Rissler,
2005; Chatzimanolis & Caterino, 2007a). Their
unusual orientation, extending from the California
coastline inland across southern California, and the
diversity of habitats that they encompass have been
suggested as primary contributors to phylogeographic
complexity in this region. Although this intriguing
area deserves further attention, empirical studies
yielding interesting results from populations in the
southern Sierra Nevada and Tehachapi Mountains
have also been accumulating (Macey et al., 2001;
Segraves & Pellmyr, 2001; Jockusch & Wake, 2002;
Matocq, 2002; Feldman & Spicer, 2006; Kuchta &
Tan, 2006; Chatzimanolis & Caterino, 2007a, b; Davis
et al., 2008; Caterino & Chatzimanolis, 2009). Many
of these studies provide evidence for deep divergence
between southern Sierra clades and coastal and more
southerly populations, leading some studies to recognize the southern Sierras as a glacial refugium (Rich,
Thompson & Fernandez, 2008), although evidence for
this is equivocal (Kuchta & Tan, 2006). Divergence
times estimated for a Sierra Nevada break range
from approximately 2 Mya (Feldman & Spicer, 2006)
to 9.9 Mya (Segraves & Pellmyr, 2001), further
emphasizing that concordant spatial genetic patterns
may not imply concurrent chronology (Feldman &
Spicer, 2006), especially when long persisting geographical features are subject to climactic fluctuations over an extended period of time. This long and
dynamic history coupled with increased habitat complexity resulting from the extremely varied topography of the Sierra Nevada highlight the importance of
this area as a centre of genetic diversity and lineage
diversification in the CFP.
Comparative phylogeography demands a broad
perspective, based on many taxa and genetic
markers. To date, our understanding of regional
patterns in the CFP is based heavily on both vertebrates and mitochondrial DNA. In the present
study, we expand both perspectives in a multilocus
analysis of the flightless darkling beetle Nyctoporis
carinata LeConte (Tenebrionidae) throughout its
range in central and southern California. Previous
comparative analysis of N. carinata using mitochondrial DNA (mtDNA) (Caterino & Chatzimanolis,
2009) revealed several interesting patterns within
recognized evolutionary hotspots of the CFP (Davis
et al., 2008). First, althlough many flightless organ-
425
isms exhibit a north–south genetic break attributed
to the Transverse Ranges (Maldonado, Vila &
Wayne, 2001; Calsbeek et al., 2003; Sgariglia &
Burns, 2003; Forister, Fordyce & Shapiro, 2004;
Feldman & Spicer, 2006; Chatzimanolis & Caterino,
2007b), the mtDNA gene tree of N. carinata
revealed a prominent east–west break in the middle
of the Transverse Ranges (as also observed in California mountain king snakes: Rodríguez-Robles et al.
1999; pond turtles: Spinks & Shaffer, 2005; and
Sepedophilus rove beetles: Chatzimanolis &
Caterino, 2007a). Second, the deepest split in the N.
carinata mtDNA gene tree separated the southern
Sierra Nevada and Tehachapi populations from the
central and southern California populations, corresponding to the Sierran break discussed above. In
addition, one of two sampling localities in the Tehachapi Mountains had two highly divergent mtDNA
haplotypes (0.11 uncorrected, 0.25 corrected) with
one haplotype sharing a more recent common ancestor with populations to the south, and the other
being more closely related to populations in the
north. These results suggest that high diversity in
this region may result from mtDNA contact zone
between formerly isolated populations. A detailed
multilocus analysis investigating these patterns will
add to a growing body of research aiming to understand and document the biodiversity of these important ecological regions.
The present study uses two independently evolving
sequence markers to evaluate phylogeographic
hypotheses using N. carinata. It has become apparent
that the validity of phylogeographic hypotheses is
increased when biparentally inherited markers from
the nuclear genome are used in conjunction with
uniparentally inherited mitochondrial markers. Theoretical and empirical studies have documented both
stochastic and deterministic factors that limit the
ability of mtDNA to accurately represent the history
of a species (Irwin, 2002; Zhang & Hewitt, 2003;
Godinho, Crespo & Ferrand, 2008). Most significantly,
these include asymmetrical migration rates of males
and females (Jockusch & Wake, 2002; Miller, Haig &
Wagner, 2005; Berghoff et al., 2008; Kerth et al., 2008;
Ngamprasertwong et al., 2008), genetic drift, and/or
lineage sorting (Maddison, 1997), with all of them
potentially resulting in discordance among markers.
Multilocus analysis of N. carinata phylogeography
provides a robust basis to test several hypotheses and
to examine the generality of patterns documented
to date. Specifically, we investigate whether both
marker types support: (1) the east–west geographic
break through the middle of the Transverse Ranges
(sensu Chatzimanolis & Caterino, 2007a); (2) the isolated southern Sierra Nevada clade with putative
contact to the Transverse Ranges through the
© 2010 The Linnean Society of London, Biological Journal of the Linnean Society, 2010, 99, 424–444
426
M. POLIHRONAKIS and M. S. CATERINO
as a potential outgroup. The differences between N.
vandykei and N. carinata, on the other hand, are very
minor, and preliminary mitochondrial analyses did
not clearly separate these two species; thus, we considered them as probable synonyms in the present
study. All specimens were collected directly into 100%
ethanol and stored at -70 °C prior to extraction.
Collection localities are grouped into regional ‘populations’ in accordance with previous studies (Fig. 1)
(Chatzimanolis & Caterino, 2007a; Caterino & Chatzimanolis, 2009). These areas correspond to geologically discrete subunits of the mountainous areas
surrounding the Transverse Ranges, although boundaries between a few, particularly in the western
Transverse Ranges, are less pronounced. Most of
these, excluding the Santa Lucia Mountains to the
north-west, and the Tehachapi, Breckenridge and
Sierra Nevada Mountains to the north-east, collectively constitute the Transverse Ranges (Fig. 1).
Tehachapi Mountains; (3) designated evolutionary
hotspots within the CFP (Davis et al., 2008); and (4)
lineages of cryptic species within N. carinata
(Caterino & Chatzimanolis, 2009).
MATERIAL AND METHODS
FIELD COLLECTION
Nyctoporis carinata is abundant and widely distributed throughout much of central and southern California, and can be found in detritus material and
under rocks and loose debris. Both sexes of N. carinata lack wings and are thus flightless. Specimens
were collected throughout the Transverse Ranges,
central and southern Sierra Nevada, and the Santa
Lucia mountains of the outer coast ranges. Most
specimens clearly represent the nominal species N.
carinata LeConte. We sampled a small number of
specimens from the central and southern Sierra
Nevada which correspond to Nyctoporis vandykei
Blaisdell, and one specimen from Lake County (north
of the San Francisco Bay) representing Nyctoporis
aequicollis Eschscholtz. Based on morphology, the
latter appears quite distinct, and was initially treated
FOCAL
GENES
Genes from both the mitochondrial and nuclear
genome were targeted in this study to compare infor-
3.1
3.2
3
1.1
1
4
2.2
2.1
2
7.1
6.1
5.1
7.2
7.4 7.3
6.2
6.3
6
13.1
13
4.1
5
8.1
7.5
6.4
6.5
9.1
789
10.1
10.2
10.3
10
11.1
11.2 11.3
11
12
12.1
Figure 1. Map of southern California with population designations and specific collecting localities as coded in the
Appendix (i.e. 1.1 = locality one from population one; 1.2 = locality two from population one, etc.) (1, northern Santa Lucia
Mountains; 2, southern Santa Lucia Mountains; 3, south-western Sierra Nevada; 4, Breckenridge Mountains; 5,
Tehachapi Mountains; 6, Santa Ynez Mountains; 7, north-west Transverse Ranges; 8, central Transverse Ranges; 9, Sierra
Pelona; 10, San Gabriel Mountains; 11, San Bernardino Mountains; 12, San Jacinto Mountains; 13, Santa Cruz Island).
A few numbers cover multiple proximate populations, indistinguishable at this scale. Populations 6–12 comprise the
entire Transverse Range region.
© 2010 The Linnean Society of London, Biological Journal of the Linnean Society, 2010, 99, 424–444
PHYLOGEOGRAPHY OF N. CARINATA
mation from two independently evolving loci. The
well-studied mitochondrial protein coding cytochrome
oxidase I (COI) gene has been used in a large number
of phylogeographic and phylogenetic analyses, especially among insect and arthropod groups (Caterino,
Cho & Sperling, 2000). The nuclear marker used was
from an intron in the Guftagu (GFT) gene, identified
during a screening of Tribolium introns (M. S.
Caterino, M. Polihronakis, I. Ouzounov, unpubl. data)
provided by V. Krauss (Krauss et al., 2008). In Drosophila, the GFT gene is important during the development of adult morphological structures and is
primarily associated with the external sensory
organs. The targeted intron is located after the first
region of coding sequence relative to both Drosophila
and Tribolium annotated genomes.
GENERATING DNA
SEQUENCE DATA
Genomic DNA was extracted from forebodies (head
and prothorax) of field collected specimens using
DNeasy Tissue extraction kits (Qiagen). Apart from
dissection, extractions were minimally destructive,
and chitinous parts were mounted as vouchers after
extraction. Full collection data, including voucher
numbers and corresponding DNA extractions, can be
accessed through the California Beetle Project database (http://www.sbnature.org/calbeetles). Amplification of the latter half of COI was performed using
previously described polymerase chain reaction (PCR)
protocols and reagents (Caterino & Chatzimanolis,
2009) with the primers C-J-2183 and C1-N-3014
(Simon et al., 1994). Amplification of the GFT intron
required a nested PCR reaction with an initial amplification using degenerate primers GFT37F (5′-AAA
ATG MGN ATH CGN GCN TTT CC-3′) and GFT86R
(5′-TCN ACA TAC TTY TCR TCC AT-3′). The nested
amplification was done using an internal species
specific forward primer located approximately 35 bp
downstream of the degenerate forward primer
(NycaGFT) with the initial reverse primer. PCR products were purified using Qiaquick PCR Purification
kits (Qiagen) or ExoSAP-IT® (USB Corp.). Forward
and reverse sequencing reactions and sequence visualization were performed by Macrogen, Inc. (Korea).
All DNA sequences were edited in GENEIOUS Pro,
version 4.5.4 (Biomatters Ltd) and aligned in SE-AL,
version 2.0a11 (http://tree.bio.ed.ac.uk/software/seal/).
Both genes were easy to align manually; the COI gene
did not have any indels, and the GFT intron had
several small indels that were accommodated by
inserting gaps. Sequence identity was checked by
performing BLAST searches in GenBank (Altschul
et al., 1997).
To test for patterns of selection at either locus,
Tajima’s D (Tajima, 1989) was estimated in ARLE-
427
QUIN, version 3.1 (Excoffier, Laval & Schneider,
2005). Significance was evaluated by comparing the
observed test statistic to a distribution generated
from 1000 permutations of the original data such that
P-values represent the proportion of the distribution
that is less than or equal to the observed value.
Recombination in the nuclear gene was assessed
using the PHI (pairwise homoplasy index) statistic
(Bruen, Phillipe & Bryant, 2006) implemented using
the software SPLITSTREE, version 4.10 (Huson,
1998; Huson & Bryant, 2006).
ANALYSES
OF POPULATION STRUCTURE AND
SPATIAL AUTOCORRELATION
To test for significant genetic breaks across certain
geographic barriers, we performed analysis of
molecular variance (AMOVA) and spatial autocorrelation analyses. The degree of population divergence
and haplotype exclusivity was determined using FST
values (which differ from traditional FST values
because they incorporate both overall similarity and
haplotype frequencies; Excoffier, Smouse & Quattro,
1992), as calculated in ARLEQUIN. Spatial autocorrelation analyses were performed to examine the
relationship between genetic and geographic distance at the individual level, and to compare
markers for possible differences related to sex-biased
dispersal. These analyses provide a finer-scale evaluation of isolation-by-distance (IBD) than matrix correlation tests because it is possible to assess the
behavior of the slope of autocorrelation values as
the size of distance classes increase. These were
performed in GENEALEX, version 6.1 (Peakall &
Smouse, 2006), with each marker treated individually as a single population using the even sample
size option with 20 distance classes. Significance of
the autocorrelation coefficient was assessed using
999 permutations of the data in addition to 1000
bootstrap replicates.
Of the seven evolutionary hotspots designated by
Davis et al. (2008), our samples cover three of them
(Santa Lucia Mountains; north-eastern Transverse
Ranges, Tehachapi and Piute Mountains; and San
Bernardino and San Jacinto Mountains). To determine whether genetic diversity within N. carinata
was consistently higher or more divergent in these
areas, we generated a genetic landscape shape for
each of the markers using the software ALLELES IN
SPACE (AIS) (Miller, 2005). The genetic landscape
interpolation method implemented in AIS uses a
Delaunay triangulation-based connectivity network
from X and Y geographic coordinates and assigns real
and interpolated genetic distances to the Z-axis to
produce a three dimensional landscape (Miller et al.,
2006), which provides a visual representation of
© 2010 The Linnean Society of London, Biological Journal of the Linnean Society, 2010, 99, 424–444
428
M. POLIHRONAKIS and M. S. CATERINO
genetic diversity patterns across a sample area.
Unlike AMOVA, this method requires no a priori
group designations. Genetic landscapes were interpolated using raw genetic distances and a 50 ¥ 50 grid
with a distance weight value of one. Sensitivity of the
analysis to changes in grid size, weighting parameter
values, and genetic distance measure were evaluated,
but resulted in minimal changes to the resulting
landscape plot. We also calculated genetic diversity
within populations using uncorrected and corrected
distances, as calculated in PAUP* (Swofford, 2002).
in GFT, where both haplotypes from this individual
were minimally different from those in many populations of N. carinata. Therefore, we consider the
species status and relationship of this entity uncertain and do not treat it as an outgroup. For this
reason, our trees should be interpreted as unrooted,
although ‘midpoint rooting’ (as implemented in
PAUP*) is used for presentation.
RESULTS
SEQUENCE
PHYLOGENETIC
ANALYSIS AND
NETWORK CONSTRUCTION
Relationships among individuals or haplotypes were
inferred using phylogenetic and network methods to
obtain both bifurcating and nonbifurcating perspectives of the gene lineages. Models of molecular evolution for each individual marker were evaluated
in MRMODELTEST, version 2.3 (Nylander, 2004).
According to the Akaike information criterion, the COI
data best fit the HKY + I + G model, and the GFT data
best fit the GTR + G model. Gene trees were inferred
in MRBAYES, imposing the model specified by AIC,
using default priors for all parameters. Branch length
priors for each marker were determined through comparison of branch lengths of maximum likelihood trees
generated in GARLI, version 0.96 (Zwickl, 2006) to
those obtained in the Bayesian analyses. Haplotype
networks were built using COMBINE TREES
(Cassens, Mardulyn & Milinkovitch, 2005), which
implements the union of maximum parsimonious
trees approach (UMP), using parsimony trees as
input. For the nuclear data set, parsimony trees were
generated with gaps coded as a fifth state, using a
heuristic search in PAUP* (Swofford, 2002) with tree
bisection–reconnection branch swapping and 500 replicates of random sequence addition, saving 200 trees
per replicate. Heuristic search options for the mitochondrial data set were modified to accommodate the
large number of trees generated (500 replicates of
random sequence addition saving a maximum of 20
trees per replicate). Because of the computational
demands of the COMBINE TREES software, the first
1000 trees from the parsimony search were analysed
in two sets of 500 trees each. Ten networks were
constructed for each data set which were then used to
generate a ‘best network’ with the fewest number of
cycles (Cassens et al., 2005). The best networks for
each set of 500 trees were compared to ensure concordance when only subsets of trees from the parsimony
search were used.
Although mitochondrial DNA showed N. aequicollis
to be rather divergent from other samples, tentatively
supporting its outgroup status, this was not the case
DATA
A total of 130 and 109 individuals were sequenced for
the COI (826 bp) (Genbank accessions EU37099EU37190 and GU049332-GU049339) and GFT
(497 bp) (Genbank accessions GU049270-GU049331)
genes, respectively. Of the 109 samples with GFT
sequence, 34 had polymorphic sites (Appendix S1).
Individuals with one polymorphic site were phased
manually and both haplotypes were included in the
analysis. Specimens with two or more polymorphic
sites were phased using the software PHASE, version
2.1 (Stephens, Smith & Donnely, 2001; Stephens &
Scheet, 2005). There were three cases that resulted in
ambiguous phase calls and so autapomorphic polymorphic sites for these individuals were coded as
missing data. For all three cases, this resulted in just
one parsimony informative polymorphic site that
was phased manually. Thus, further discussion of
sequences from both genes will refer to haplotypes.
The mean Tajima’s D-values for COI and GFT
estimated across all populations were not significant
(P = 0.55 and 0.52, respectively). At the population
level, the northern Santa Lucia population had a
significant Tajima’s D-value (P = 0.01) for the COI
gene, and the north-west Transverse Range population had a significant Tajima’s D-value (P = 0.05) for
the GFT gene, potentially indicating past selection or
population bottlenecks for these two populations.
There was no evidence for recombination in the GFT
intron according the PHI test (P = 0.80).
The latter half of the COI gene targeted for amplification had 224 variable sites, with 207 of those
being parsimony informative. The COI data set had a
total of 100 unique haplotypes with no one haplotype
dominating more than 10% of the entire sample. Of
the 497 bp sequenced of GFT, 53 were variable, with
27 of those being parsimony informative. The GFT
data set had a total of 62 unique haplotypes, although
the three most common haplotypes dominated 49% of
the data set. Interestingly, approximately 20% of the
haplotype diversity in the GFT data came from within
the south-western Sierra population, whereas this
population only accounted for 9% of the haplotype
diversity of the COI gene.
© 2010 The Linnean Society of London, Biological Journal of the Linnean Society, 2010, 99, 424–444
PHYLOGEOGRAPHY OF N. CARINATA
POPULATION
STRUCTURE AND
AUTOCORRELATION ANALYSIS
High differentiation among populations was supported by both markers. All FST values based on the
COI data were significant, except for some of the
comparisons with the Breckenridge Mountains population where only two individuals were sampled
(Table 1, lower diagonal). Pairwise FST values based
on the GFT locus were also almost all significant
(Table 1, upper diagonal), with exceptions between
the Sierra Pelona and central Transverse Range
populations, as well as between the southern Santa
Lucia and north-west Transverse Range populations.
Both of these insignificant values are between
geographically adjacent areas, suggesting gene flow
between them, although insufficient sampling cannot
be ruled out as an explanation.
Spatial autocorrelation analyses showed a strong
decline in relatedness with increasing distance
A)
429
(Fig. 2). A decreasing slope of the spatial autocorrelation graphs is indicative of an IBD trend (i.e.
autocorrelation values decrease as distance class
size increases), whereas significant r-values indicate
higher or lower genetic relatedness than predicted if
individuals were randomly distributed (Smouse &
Peakall, 1999; Peakall, Ruibal & Lindenmayer,
2003). COI haplotypes showed significant IBD with
decreasing r-values from 0–165 km. The increase
in r-values at approximately 200 km likely reflects
the close relationship of some individuals from
the central Transverse range population with individuals from the San Bernardino and San Jacinto
populations. Beyond 218 km, autocorrelation values
were relatively unchanging and significantly negative. The GFT locus exhibited a very similar
pattern, showing a general IBD trend up to approximately 150 km, at which point r-values remained negative with some fluctuation. The similar
relationships between genetic and geographic
0.8
0.7
0.6
0.5
0.4
r
0.3
0.2
0.1
0.0
-0.1
-0.2
-0.3
29
49
67
86
98
117 140 150 165 178 205 218 235 255 270 295 317 368 477
Distance (km)
B)
0.7
0.6
0.5
0.4
0.3
r
0.2
0.1
0.0
-0.1
-0.2
-0.3
29
51
69
90
107 121 145 159 178 204 217 235 252 270 293 313 346 453
Distance (km)
Figure 2. Spatial autocorrelation graphs of COI haplotypes (A) and GFT haplotypes (B). Dotted lines represent the 95%
confidence interval with respect to the null hypothesis that individuals are randomly distributed.
© 2010 The Linnean Society of London, Biological Journal of the Linnean Society, 2010, 99, 424–444
0.29
–
0.65
0.83
0.71
0.27
0.31
0.75
0.56
0.61
0.63
0.62
0.58
–
0.80
0.75
0.95
0.79
0.56
0.73
0.90
0.75
0.72
0.75
0.63
0.90
Southern
Santa
Lucias
0.68
0.68
0.69
0.64
0.71
0.72
0.70
0.60
0.39
0.36
–
0.81
0.81
Southwestern
Sierra
Nevada
Bold values are significantly different from zero (P < 0.01).
Northern Santa
Lucias
Southern Santa
Lucias
Southwestern
Sierra Nevada
Breckenridge
Mountains
Tehachapi
Mountains
Santa Ynez
Mountains
Northwest
Transverse
Ranges
Central
Transverse
Ranges
Sierra Pelona
San Gabriel
Mountains
San Bernardino
Mountains
San Jacinto
Mountains
Northern
Channel
Islands
Northern
Santa
Lucias
0.94
0.80
0.83
0.80
0.82
0.96
0.81
0.66
0.41
–
–
–
–
Breckenridge
Mountains
0.75
0.69
0.73
0.69
0.73
0.77
0.73
0.62
–
–
0.79
0.53
0.58
Tehachapi
Mountains
0.37
0.43
0.39
0.19
0.25
0.44
0.32
–
0.46
–
0.77
0.22
0.32
Santa
Ynez
Mountains
0.48
0.64
0.63
0.59
0.63
0.71
–
0.27
0.57
–
0.85
0.05
0.30
Northwest
Transverse
Ranges
0.88
0.72
0.65
0.62
0.60
–
0.68
0.49
0.12
–
0.82
0.80
0.73
Central
Transverse
Ranges
Table 1. Pairwise population FST comparisons for COI (lower diagonal) and GFT (upper diagonal)
0.70
0.56
0.47
–
0.23
0.04
0.66
0.48
0.12
–
0.81
0.75
0.70
Sierra
Pelona
0.68
0.57
0.48
0.25
–
0.25
0.53
0.43
0.26
–
0.76
0.46
0.52
San
Gabriel
Mountains
0.70
0.57
–
0.83
0.63
0.85
0.64
0.16
0.70
–
0.86
0.66
0.66
San
Bernardino
Mountains
0.71
–
0.11
0.87
0.66
0.89
0.66
0.18
0.74
–
0.87
0.70
0.70
San
Jacinto
Mountains
–
0.75
0.70
0.78
0.51
0.83
0.30
0.31
0.59
–
0.82
0.32
0.43
Northern
Channel
Islands
430
M. POLIHRONAKIS and M. S. CATERINO
© 2010 The Linnean Society of London, Biological Journal of the Linnean Society, 2010, 99, 424–444
PHYLOGEOGRAPHY OF N. CARINATA
B)
Y (Eas tern
edge)
A)
431
X (Southern
edge)
Y (Eas te
rn edge)
C)
X (Souther
n edge)
Figure 3. Landscape shapes from ALLELES IN SPACE analyses. A, connectivity network based on Delaunay triangulation overlayed onto map of southern California (the vertex of each triangle represents a collecting locality). B, landscape
interpolation of COI sequence data. C, landscape interpolation of GFT sequence data. The Z-axis in (B, C) represents the
degree of genetic discontinuity between two localities.
distance between the two genes suggest that dispersal is not sex-biased.
Comparison of the genetic landscape shapes for the
two genes provided a visual representation of the
genetic diversity patterns observed over the sampling
area (Fig. 3). Peaks on each landscape shape represent the degree of genetic discontinuity between two
localities as determined by the Delaunay triangulation method (Miller et al., 2006). Thus, when collecting localities are geographically close in proximity
(short distances between vertices), high peaks repre-
sent areas of high genetic diversity. On the other
hand, when localities are further apart (long lines
between vertices), high peaks are more appropriately
interpreted as genetic barriers. Both markers demonstrated high diversity among the south-western
Sierra populations as a result of high genetic divergence among several geographically proximate localities, as well as a barrier across the Central Valley.
The landscape based on the COI data (Fig. 3B) also
exhibited genetic discontinuity in the Transverse
ranges, beginning at the southern tip of the Central
© 2010 The Linnean Society of London, Biological Journal of the Linnean Society, 2010, 99, 424–444
432
M. POLIHRONAKIS and M. S. CATERINO
Valley separating the Tehachapis, Breckenridge
Mountains, and south-western Sierra populations
from the eastern and western Transverse Range
populations. The plot of the GFT data (Fig. 3C) had a
barrier that was not exhibited by the COI data
between the southern Sierra Nevada and northern
Transverse Ranges. Thus, the areas of high genetic
diversity in N. carinata corresponded to the Transverse Ranges and southern Sierra hotspots designated by Davis et al. (2008). However, in contrast to
Davis et al. (2008) our samples from the Santa Lucia,
San Bernardino, and San Jacinto Mountains did not
exhibit increased levels of diversity.
PHYLOGENETIC
ANALYSIS AND
NETWORK RECONSTRUCTION
mtDNA
Analyses of COI revealed very high levels of divergence
among haplotypes, especially among regions. Uncorrected distances were as high as 0.11 uncorrected (0.27
corrected), or 0.07 uncorrected (0.11 corrected) if the
nominally distinct populations of N. aequicollis and N.
vandykei are excluded. The UMP method of network
building resulted in one network but with a large
number of unsampled nodes. Thus, because of the high
haplotype diversity and non-network-like behavior of
the COI gene, these data are presented as a phylogenetic tree only. The COI gene tree showed five main
clades, principally: the western Transverse Ranges
(most) + Channel Islands + southern Santa Lucias;
eastern, central, and small inclusions of western
Transverse Ranges and Tehachapis; San Jacinto
Mountains (most); northern Santa Lucias; and Sierra
Nevada (including the Breckenridge Mountains) +
Tehachapis (most) (Fig. 4). The most strongly supported relationship among the major clades linked
the eastern and western Transverse Range clades
(PP = 1.0). This supported a single lineage covering the
bulk of the Transverse Ranges with two exceptions: (1)
it did not include the San Jacinto Mountains and (2) it
did include the southern part of the Santa Lucia
Mountains, which is not considered part of the Transverse Ranges. The break between these two major
Transverse Range groups corresponds loosely to the
Ventura and Cuyama River drainages in the lower
elevations. However, at higher elevations, no such
obvious geographic barrier is observed.
Most populations were predominantly single lineages. However, almost all had individuals appearing
elsewhere in the tree. The only two monophyletic
populations were those from the northern Santa
Lucia Mountains (the north-western part of our sampling region) and from Santa Cruz Island. Most individuals from the San Jacinto Mountains population
(at the south-eastern extreme) fell out in an isolated
clade, although two San Jacinto individuals (haplotype N21) were more closely related to a clade of
primarily San Bernardino (the neighbouring region
to the north) haplotypes. The large clade containing
the remaining eastern Transverse Range samples
contained San Bernardino, San Gabriel, and Sierra
Pelona haplotypes intermingled with minimal site
fidelity. Although the San Bernardino haplotypes
were the most cohesive of these, two of these individuals were more closely related to haplotypes from
elsewhere in this broad region. The eastern Transverse Range clade included haplotypes from the
central Transverse Ranges (the Tecuya Trail locality
in the San Emigdio Mountains), as well as one
haplotype from the Tehachapis. Another interesting
element of this larger eastern Transverse Range clade
was a subclade of haplotypes from further west in
Ojai and the eastern-most Santa Ynez Mountains (the
Murrietta Trail locality). Although the area covered
by the eastern Transverse Range clade is more or less
contiguous, it is the most wide-ranging, with several
extensions beyond its core area. The mainly western
Transverse Range clade included all individuals from
the north-western Transverse Range and Santa Cruz
Island populations, as well as all individuals from the
southern Santa Lucia Mountains. Most individuals
from the Santa Ynez Mountains were also included,
with the exception of the Murrietta Trail samples
mentioned above.
GFT
Divergence among GFT alleles was much lower than
that seen in mtDNA. Most haplotypes differed by only
one or a few changes. For this reason, the phylogenetic
tree based on these sequences was largely unresolved.
With such low divergence, the likelihood of direct
ancestor–descendant relationships among sequences
was high, and we therefore based our inferences on
the UMP network (Fig. 5). Although genetic variation
was generally low, three of the four main groups in
this network were recognized by a high frequency of
identical haplotypes over broad (mostly) contiguous
geographic regions, along with linked derivative
haplotypes. The most widespread of these was the
western group (orange), including all haplotypes from
the northern and southern Santa Lucias, northwestern Transverse Ranges, Santa Ynez Mountains,
Santa Cruz Island, the central Tranverse Ranges, and
a single individual from the San Gabriel Mountains;
the central group (green) included most haplotypes
from the Sierra Pelona, San Gabriel Mountains, Tehachapi Mountains, and the northern California representative of N. aequicollis (G58 & G59); the eastern
group (blue) included all haplotypes from the San
Jacinto Mountains, all but one from the San Bernardino Mountains, one haplotype from the San Gabriel
© 2010 The Linnean Society of London, Biological Journal of the Linnean Society, 2010, 99, 424–444
PHYLOGEOGRAPHY OF N. CARINATA
433
Figure 4. A, COI gene tree inferred in MRBAYES (*posterior probability ⱖ 0.80). B, corresponding clade designations on
sample map. Arrow from the yellow clade refers to the placement of the Nyctoporis aequicollis specimen from the
northernmost Lake County sampling area (not visible on map).
Mountains, and a disjunct group of haplotypes from
the Ojai Valley and extreme eastern end of the Santa
Ynez Mountains. The fourth main group (yellow) represented a diverse clade of related, mostly unique,
haplotypes from the southern Sierra Nevada region.
Both the COI and GFT gene trees supported an
east–west break in the Transverse Ranges in the
eastern Santa Ynez Mountains/western Ventura
County area. However, the genetic break between the
two clades supported by the COI data was positioned
slightly west of the break supported by the GFT data
set. In addition, the geographic relationships of populations within each clade were somewhat different
between genes in that the COI haplotypes from the
eastern group were almost all closely related to haplotypes found in the Sierra Pelona and San Gabriel
Mountains, whereas GFT haplotypes in these areas
were more closely allied with those further east, in
the San Bernardino Mountains population. Although
the region where these discontinuities are observed
more-or-less coincides with the confluence of several
major drainages (principally the Ventura and Santa
Clara Rivers), it is only approximate, and neither
corresponds precisely to the Santa Clara break found
by Chatzimanolis & Caterino (2007a) in Sepedophilus
beetles, and among other species.
The results from an analysis of the COI and GFT
markers differed in many other respects. Although
both gene trees revealed a few large clades with broad
geographic continuity, the exact regions defined
by these clades showed little congruence. The GFT
network did not reveal a strong relationship between
© 2010 The Linnean Society of London, Biological Journal of the Linnean Society, 2010, 99, 424–444
434
M. POLIHRONAKIS and M. S. CATERINO
Figure 5. A, GFT union of maximum parsimonious trees approach network; sizes of boxes within coloured clades scaled
to haplotype frequency, numbers in parentheses denote the frequency of the haplotype if > 1 (haplotypes in some
haplotype boxes have different numbers as a result of missing data but are otherwise identical). B, corresponding clade
designations on sample map. Arrow from the green clade refers to the placement of the Nyctoporis aequicollis specimen
from the northernmost Lake County sampling area (not visible on map); ‘X’ in population four denotes no nuclear data
are available for this region.
© 2010 The Linnean Society of London, Biological Journal of the Linnean Society, 2010, 99, 424–444
PHYLOGEOGRAPHY OF N. CARINATA
Sierran and Tehachapi populations as seen with COI,
instead grouping the Tehachapis strongly with the
central portion of the Transverse Ranges, the San
Gabriel Mountains, and the Sierra Pelona (haplotype
G01 is the most common in all these areas). Sierran
populations were more closely related to Tehachapi
individuals than to any other group, but were highly
divergent relative to the minimal divergence observed
throughout the remainder of the network. Most individuals from the San Jacinto and San Bernardino
Mountains shared a GFT haplotype, whereas most
San Jacinto COI haplotypes were highly divergent.
Almost all northern Santa Lucia individuals had a
GFT sequence identical to those from the southern
Santa Lucias, as well as to most individuals from the
north-western Transverse Ranges, and Santa Ynez
Mountains, whereas the COI data supported the
northern Santa Lucia population as being exclusive
and highly divergent. Finally, although the Lake
County specimen (corresponding to N. aequicollis)
differed by only a single mutation in GFT from the
eastern Sierra Pelona group, its COI sequence was
highly divergent from all other groups.
DISCUSSION
Detailed comparative phylogeographic analyses
provide a means to study how geography influences
the evolutionary history and biodiversity patterns of
organisms. Within the CFP, there are many geographic barriers that are hypothesized to have a
pervasive effect on species across different taxonomic
groups. Although evidence supporting this hypothesis
is increasing, much of the data are focused on vertebrates, and, until recently, heavily dependent on
single locus analyses of mitochondrial DNA. The
present study aimed to evaluate the phylogeographic
history of a dynamic part of the CFP through analysis
of N. carinata, a flightless darkling beetle with
a widespread distribution in central and southern
California, using mitochondrial and nuclear genes.
THE
PHYLOGEOGRAPHIC HISTORY OF
N.
CARINATA
Phylogeographic expectations of N. carinata are
guided by two main ecological factors. The first is
their flightlessness; we expect populations to be relatively isolated as a result of their inability to traverse
unsuitable habitat, and for lineage breaks to correspond well with major geographic or ecological features (although these may have varied considerably
over time). Second, we expect similar dispersal abilities of males and females and therefore do not expect
population structure to be significantly influenced
by sex-biased dispersal (Jockusch & Wake, 2002;
Matyukhin & Gongalsky, 2007).
435
The COI sequences of N. carinata were characterized by high divergence, high haplotype diversity, low
population connectedness, broad geographic cohesiveness, and a combination of mono- and polyphyletic
populations. This pattern signifies an old, broadlydistributed species with historically-isolated populations, some of which have come into secondary contact
with subsequent gene flow (Jockusch & Wake, 2002).
This was supported by the overall non-monophyly of
populations with otherwise high FST values. Interestingly, geographically peripheral populations from the
southern Sierra Nevada, the northern Santa Lucia
Mountains, and the San Jacinto Mountains were the
most isolated and exclusive (with one individual
exception in the latter case), whereas more centrally
located populations showed higher levels of admixture. This suggests that, if populations had remained
completely isolated, they would have had enough time
to achieve monophyly. Monophyly of the Santa Cruz
Island population can also be cited in this respect
because, although founder effects would be likely to
explain monophyly for this disjunct population, there
was no evidence for a bottleneck based on estimates of
Tajima’s D.
The GFT data supported a somewhat different scenario. The results obtained based on this marker
showed low levels of divergence and low haplotype
diversity within and across most populations (with a
few common haplotypes shared among, and dominating most populations), but were similar to mitochondrial results in low population connectedness, and
showed similar patterns of geographic relationships
among populations. This overall pattern is consistent
with a series of relatively rapid, stepwise colonizations from one or more ancestral pools of diversity
into more peripheral areas, with historical continuity
between populations that now appear to be isolated.
East–west Transverse Range break
The COI gene tree and GFT gene network both supported an east–west genetic break through the Transverse Ranges, although they did not completely
overlap. The location of this break based on the COI
gene followed the eastern boundary of the north-west
Transverse Ranges but turned west to include the
southernmost sampling locality from the Santa Ynez
Mountains (Fig. 4B). The location of the genetic break
based on the GFT network was further east between
the central Transverse Ranges and the Sierra Pelona.
Although there are no significant geographic barriers
that would explain a genetic break in either of these
regions, there are two other examples of an east–west
break further east in the Transverse Ranges, in Sepedophilus rove beetles (Chatzimanolis & Caterino,
2007a) and California mountain king snakes (Lampropeltis zonata) (Rodríguez-Robles et al. 1999), that
© 2010 The Linnean Society of London, Biological Journal of the Linnean Society, 2010, 99, 424–444
436
M. POLIHRONAKIS and M. S. CATERINO
approximately correspond with N. carinata. Increased
sampling of N. carinata in these regions, in addition
to further comparative work including other taxa,
would help determine whether these genetic breaks
are a result of stochastic processes (Irwin, 2002), or
the result of geography.
Isolation of southern Sierra Nevada population
On the basis of the high diversity of the nuclear gene
in the southern Sierras, we propose that this population was ancestral and potentially served as a glacial
refugium (Hewitt, 2000; Rich et al., 2008). Furthermore, the genetic data from both the mitochondrial
and nuclear markers supported a south and westward
dispersal out of this area with an ancient stepping
stone colonization through the Transverse Ranges.
Potential geographic barriers reducing southward
dispersal for flightless N. carinata beetles are the
Kaweah and Kern River drainages (Segraves &
Pellmyr, 2001; Feldman & Spicer, 2006). These drainages may have served as successive filters to dispersal, resulting in reduced population sizes during
colonization as demonstrated by a single derived
nuclear haplotype in the Tehachapis (G01), which
linked the larger western, central, and eastern groups
throughout the rest of the range. Interestingly, all of
the main groups in the GFT network, with the exception of the southern Sierra population, were dominated by one main haplotype with several derivative
haplotypes that suggest there were subsequent filters
to dispersal east and west out of the Tehachapis
Mountains and Sierra Pelona region.
EVOLUTIONARY
HOTSPOTS
Our finding of both high genetic divergence and diversity of N. carinata populations from the Sierra and
Tehachapi Mountains populations is interesting in
light of similar results from an increasing number of
other studies focusing on a wide variety of taxa distributed throughout the CFP (Macey et al., 2001; Segraves & Pellmyr, 2001; Jockusch & Wake, 2002;
Matocq, 2002; Feldman & Spicer, 2006; Kuchta &
Tan, 2006; Chatzimanolis & Caterino, 2007a, b; Davis
et al., 2008). In addition to evidence of divergent
southern Sierran populations, two of these studies
with sufficient taxon sampling also support higher
genetic diversity in this region (Kuchta & Tan, 2006;
Rich et al., 2008). This contrasts with previous work
revealing higher genetic diversity within southern or
coastal populations (Law & Crespi, 2002; Matocq,
2002), suggesting that refugia and/or genetic diversity
hotspots have existed in multiple areas, although
possibly over different time periods.
The elevated diversity in the southern Sierran
region for both genes clearly supports the contention
that this area represents an evolutionary hotspot.
Can these data shed light on any of the underlying
processes? The maintenance of high diversity in
these populations supports the hypothesis that this
region once served as a glacial refugium that potentially sourced expansion into coastal and southern
populations via the Transverse Ranges. However, this
population was paraphyletic in the mtDNA tree with
respect to haplotypes from the Tehachapi and Breckenridge Mountains, but monophyletic and quite
divergent in the GFT network. Non-monophyly of
mtDNA combined with monophyly of the nDNA is
considered characteristic of differential introgression
patterns between the two genomes (Chan & Levin,
2005; Weisrock et al., 2006; Linnen & Farrell, 2007;
Peters et al., 2007; Spinks & Shaffer, 2007; Zhang &
Sota, 2007; Gompert et al., 2008), and is suggestive of
some interesting evolutionary dynamics in the Tehachapi Mountains.
Conflicting relationships inferred by the nuclear
and mitochondrial markers in the Tehachapi Mountains are consistent with differential introgression
combined with several range fluctuations, which
resulted in unique contact zones for each of the two
markers. The haplotype relationships of the two
markers from the southern Sierra Nevada suggest
that migration out of this region comprised multiple
events that occurred over an extended period of
time. Under this scenario, an initial population
expansion southward was followed by subsequent
isolation (i.e. population contraction or relatively
simple isolation-by-distance) between populations in
the south-western Sierra, and those in the Breckenridge and Tehachapi Mountains. The divergence
patterns of haplotypes in this region suggest that
this isolation lasted long enough for several
population-specific mutations to accumulate in both
the nuclear and mitochondrial genes. To explain the
discrepancy of relationships of the Tehachapi Mountains population between the two markers, we
hypothesize secondary contact between these isolated populations with differential introgression of
mitochondrial genes from the south-western Sierra
populations south into the Breckenridge and Tehachapi Mountains populations. This scenario would
explain why individuals from the Tehachapi
Mountains had a derived nuclear haplotype and an
ancestral mitochondrial haplotype. The data are
suggestive of asymmetrical mitochondrial introgression during secondary contact as a result of a lack
of derived nuclear or mitochondrial haplotypes in
the south-western Sierra population. We also did
not sample any individuals with an ancestral
nuclear haplotype and a derived mitochondrial haplotype. Finer-scale sampling would help resolve historical connections in this area.
© 2010 The Linnean Society of London, Biological Journal of the Linnean Society, 2010, 99, 424–444
PHYLOGEOGRAPHY OF N. CARINATA
High genetic diversity of N. carinata from the
southern Sierras and Transverse Ranges corresponded to evolutionary hotspots designated by Davis
et al. (2008). However, only the southern Sierras
received support from both marker types, whereas
diversity in the Transverse Ranges was supported by
the COI data only. Evidence for other evolutionary
hotspots (sensu Davis et al., 2008) within the southern CFP is equivocal; other recognized areas for
which our data might be pertinent (i.e. the central
coast ranges, the San Bernardino Mountains, and
San Jacinto Valley) showed little above baseline levels
of diversity in either locus.
EVIDENCE
FOR CRYPTIC SPECIES?
Although some of the suggested morphological characters separating the three species N. carinata, N.
vandykei, and N. aequicollis are relatively discernable, high variation in N. carinata precludes their
consistent application. Two of the main characters
originally cited to distinguish N. vandykei from N.
carinata are the former’s comparatively slender, less
robust form, and less pronounced frontal carina
(ridge) on the head (Blaisdell, 1931). However, both
these characters vary considerably within N. carinata, such that some specimens are easily diagnosed,
whereas others are not. The uncertainty surrounding
the morphological distinctions was not necessarily
clarified by the genetic data. In the COI gene tree,
‘N. vandykei’ specimens were paraphyletic with
respect to N. carinata specimens from the Tehachapi
and Breckenridge Mountains, whereas, in the GFT
network, the ‘N. vandykei’ individuals are monophyletic and deeply diverged from the rest of the individuals sampled (discussed above). The uncertainty
surrounding N. aequicollis is even greater as a result
of its very close ties with populations in the central
portion of the Transverse Ranges according to the
GFT gene, at the same time as being quite distinct
from most other lineages in the COI tree (but grouped
with the south-west Sierra and Tehachapi clade with
midpoint rooting).
Aside from the questionable status of the named
species, high divergence among mtDNA haplotypes
was also initially suggestive of additional cryptic
species within N. carinata. Where populations were
monophyletic, average uncorrected distances to neighbouring populations exceeded 0.05 in all cases
(Caterino & Chatzimanolis, 2009). The high divergence of the two most northerly and southerly populations (northern Santa Lucias and San Jacinto
Mountains, respectively), in particular, suggested that
these lineages represented genealogically distinct
units as a result of allopatric divergence. However, this
hypothesis was not supported by the nuclear data,
437
which revealed that many of the individuals from both
of these populations shared identical haplotypes with
neighbouring populations. Mitochondrial studies of
other arthropod taxa in the CFP have found levels
much lower than this to correspond with well differentiated subspecies (e.g. 0.014 in the yucca moth
Tegiticula maculata; Segraves & Pellmyr, 2001), and
for comparable divergences to correspond to fully distinct species (0.08 in a species complex of the California turret spider, Antrodiaetus riversi; Starrett &
Hedin, 2007). In the latter case, nuclear data were
fully concordant with the mitochondrial, offering a
stark contrast to the situation in N. carinata.
GENETIC
VARIATION: MITOCHONDRIAL VERSUS
NUCLEAR DATA
It is often assumed that large-scale population-level
processes will result in relatively parallel patterns
between marker types, although this is not always
the case (Ballard, Chernoff & James, 2002; Bensch
et al., 2006; Weisrock et al., 2006). Thus, the most
difficult questions for multilocus phylogeography are
what differences are expected, what differences
exceed expectations, and what are the underlying
causes in either case (Hudson & Turelli, 2003; Zink &
Barrowclough, 2008). Most of the expected differences
between mitochondrial and nuclear markers in the
present study likely arise from two factors: differential mutation rates and uneven effective population
sizes (Forister et al., 2004). In general, the possibility
of recombination in nuclear loci and selection in both
marker types should also be considered, although we
found no evidence for either of these in our dataset.
There are little data on expected mutation rates in
nuclear introns relative to mitochondrial proteincoding sequences (Zhang & Hewitt, 2003) but the
background rate should be significantly lower,
perhaps one-tenth the mtDNA rate (Hare & Palumbi,
2003). The interaction of mutation generation and
maintenance via larger Ne is generally expected to
yield lower variation in nuclear haplotypes in a population sample (Zink & Barrowclough, 2008), although
just how much less will be determined by many
additional factors (Hudson & Turelli, 2003).
The clearest finding supported by both genes was
the generally low population connectedness. Both FST
and autocorrelation analyses indicated rapid attenuation of similarity with distance. This indicates that
the shared haplotypes or related haplotypes we
observed across populations did not result from recent
gene flow. This is further supported by COI relationships, where such geographic discordance was most
obvious (San Bernardino haplotypes in the San Jacintos; Central Transverse Range haplotypes in the Tehachapis). In no cases were ‘rogue’ haplotypes identical
© 2010 The Linnean Society of London, Biological Journal of the Linnean Society, 2010, 99, 424–444
438
M. POLIHRONAKIS and M. S. CATERINO
to any in their source areas, indicating that we
sampled descendants of the original contact, and that
the observed relationships resulted from either
ancient migration or the retention of ancestral polymorphism from a more broadly-distributed historical
population. In the GFT network, these particular sets
of areas shared common haplotypes but did not share
any of the more recently derived variants within their
respective groups. This supports the latter scenario
suggesting these populations were broadly connected
in the past.
Further work resolving details of the evolutionary
history in this group would continue to solidify
support for the importance of this region with regard
to the unique evolutionary dynamics and species
diversity patterns found in the present study. Specifically, we need a more robust outgroup for this species,
which may be difficult as a result of the fact that it is
the only genus in its tribe worldwide. However,
because of the relatively low variation of the nuclear
gene in the present study, it may be possible to use
species in related tribes of Pimeliinae to root the N.
carinata nuclear gene tree. Increased taxon sampling
in areas of high diversity, such as the southern Sierra
Nevada, and throughout the more peripheral parts of
the range would also provide further insight into
important evolutionary processes in the species and
the region.
ACKNOWLEDGEMENTS
Our field collections were assisted and facilitated by
numerous individuals and agencies. We thank R.
Aalbu, S. Chatzimanolis, K. Hopp, P. Jump, S.
Mulqueen, S. Russell, P. Russell, A. Short, K. Will, the
California Department of Fish and Game, Los Padres
National Forest, Angeles National Forest, Sequoia
National Forest, San Bernardino National Forest,
San Dimas Experimental Forest, Arroyo Hondo Preserve (Land Trust for Santa Barbara County), Camp
Cedar Falls, the UC McLaughlin Reserve, UC Sedgwick Reserve, UC Whitaker Forest, the UC James
Reserve, and the UC Santa Cruz Island Reserve. We
appreciate the assistance of I. Ouzounov and G.
Betzholtz in the laboratory, J. Q. Richmond for help
with the data interpretation, and V. Krauss for
sharing his Tribolium intron data. This work was
supported by the Schlinger Foundation, a bequest
from G. Ostertag, and National Science Foundation
award DEB0447694 to M. Caterino.
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© 2010 The Linnean Society of London, Biological Journal of the Linnean Society, 2010, 99, 424–444
PHYLOGEOGRAPHY OF N. CARINATA
441
APPENDIX
SAMPLING
LOCALITIES BY REGION, WITH HAPLOTYPES REPRESENTED IN EACH (LOCALITY NUMBERS REFER
TO POINTS ON FIG.
Population
1)
N
Locality
Coordinates
COI haplotypes
GFT haplotypes
1. Northern
Santa Lucias
10
1.1 – CA: Monterey
Co., Arroyo Seco
County Park
36.2341°N,
121.4886°W
N88, N89, N90, N91
G04, G55, G56, G57
Total
2. Southern
Santa Lucias
10
5
2.1 – CA: San Luis
Obispo Co., LPNF,
Cuesta Ridge
2.2 – CA: San Luis
Obispo Co., Santa
Rosa Creek
35.3731°N,
120.6859°W
N13, N14, N15
G04, G09, G10
35.5861°N,
121.0057°W
N93
G60
3.1 – CA: Fresno Co.,
Sequoia NF, SE of
Hume Lake
3.2 – CA: Tulare Co.,
Sequoia NF, UC
Whitaker Forest
3.2 – CA: Tulare Co.,
Sequoia NF, F.S.
14S75
36.7718°N,
118.8854°W
N78, N79
G39, G40, G41, G42
36.7025°N,
118.9322°W
N72, N73, N74, N75,
N76, N77
G32, G33, G34, G35,
G36, G37, G38, G49
36.6720°N,
118.9798°W
N80
G43
4.1 – CA: Kern Co.,
Sequoia NF, Kern
Cyn.
35.4753°N,
118.7284°W
N02
–
5.1 – CA: Kern Co.,
Oak Creek Cyn.
5.1 – CA: Kern Co.,
Oak Creek Cyn.
5.1 – CA: Kern Co.,
Tehachapi Mountain
Park
5.1 – CA: Kern Co.,
Woodford-Tehachapi
Rd
35.0487°N,
118.3605°W
35.0506°N,
118.3567°W
35.0673°N,
118.4820°W
N61, N62
G01
N61, N63
G01
N81, N82
G01, G44, G45, G46,
G47
35.1807°N,
118.5150°W
N81
G45, G48
34.4855°N,
120.1423°W
N64, N65, N66
–
34.4855°N,
120.1417°W
N7, N8
G07
34.47°N,
119.73°W
N44
G14
34.5009°N,
119.3899°W
34.4504°N,
119.1207°W
34.293°N,
119.204°W
N50, N51, N52, N53,
N54
N42
G26, G05, G04, G27,
G17, G28
G05, G22
N28, N29, N30
G05, G17, G01, G18
1
Total
3. Southwestern
Sierra Nevada
6
2
8
1
Total
4. Breckenridge
Mountains
Total
5. Tehachapi
Mountains
11
2
2
2
5
3
1
Total
6. Santa Ynez
Mountains
11
3
2
1
5
1
3
6.1 – CA: Santa
Barbara Co., Arroyo
Hondo Preserve
6.1 – CA: Santa
Barbara Co., Arroyo
Hondo Preserve
6.2 – CA: Santa
Barbara Co., Santa
Barbara
6.3 – CA: Ventura Co.,
LPNF, Murrietta Tr.
6.4 – CA: Ventura Co.,
Upper Ojai Valley
6.5 – CA: Ventura Co.,
Ventura
© 2010 The Linnean Society of London, Biological Journal of the Linnean Society, 2010, 99, 424–444
442
M. POLIHRONAKIS and M. S. CATERINO
APPENDIX Continued
Population
N
Total
7. Northwest
Transverse
Ranges
15
1
1
2
1
1
1
1
2
1
1
1
1
1
2
2
1
Total
8. Central
Transverse
Ranges
20
2
4
Locality
Coordinates
COI haplotypes
GFT haplotypes
7.1 – CA: Santa
Barbara Co., UC
Sedgwick Reserve
7.1 – CA: Santa
Barbara Co., UC
Sedgwick Reserve
7.1 – CA: Santa
Barbara Co., UC
Sedgwick Reserve
7.1 – CA: Santa
Barbara Co., UC
Sedgwick Reserve
7.1 – CA: Santa
Barbara Co., UC
Sedgwick Reserve
7.1 – CA: Santa
Barbara Co., UC
Sedgwick Reserve
7.1 – CA: Santa
Barbara Co., UC
Sedgwick Reserve
7.1 – CA: Santa
Barbara Co., UC
Sedgwick Reserve
7.1 – CA: Santa
Barbara Co., UC
Sedgwick Reserve
7.1 – CA: Santa
Barbara Co., UC
Sedgwick Reserve
7.1 – CA: Santa
Barbara Co., UC
Sedgwick Reserve
7.2 – CA: Santa
Barbara Co., LPNF,
Sunset Valley
7.3 – CA: Santa
Barbara Co., LPNF,
Rancho Alegre
7.4 – CA: Santa
Barbara Co., LPNF,
Big Pine Mountain
7.4 – CA: Santa
Barbara Co., LPNF,
Big Pine Mountain
7.5 – CA: Ventura Co.,
LPNF, north slope
Pine Mountain
34.6796°N,
120.0387°W
N9
G04
34.6825°N,
120.0445°W
N9
34.6842°N,
120.0459°W
N11, N12
G04
34.6889°N,
120.0428°W
N49
G24, G25
34.7127°N,
120.0396°W
N35
G04, G20
34.7132°N,
120.0395°W
N41
G04
34.7164°N,
120.0396°W
N23
G04, G13
34.7197°N,
120.0366°W
N31, N39
G04
34.7261°N,
120.0483°W
N43
G20, G23
34.7269°N,
120.0474°W
N9
G04, G08
34.7197°N,
120.0415°W
–
G04
34.7538°N,
119.9429°W
N3
G04
34.5410°N,
119.9110°W
N24
G14, G15
34.7021°N,
119.6547°W
N4
G04
34.7032°N,
119.6526°W
N36, N38
G04
34.6585°N,
119.3800°W
N1
–
8.1 – CA: Kern Co.,
LPNF, Tecuya Rd.
8.1 – CA: Kern Co.,
LPNF, Tecuya Trail
34.8484°N,
119.0697°W
34.8300°N,
119.0078°W
N94, N96
G01
N94, N95
G01
© 2010 The Linnean Society of London, Biological Journal of the Linnean Society, 2010, 99, 424–444
PHYLOGEOGRAPHY OF N. CARINATA
443
APPENDIX Continued
Population
N
Total
9. Sierra
Pelona
6
7
Total
10. San Gabriel
Mountains
7
7
2
3
2
2
Total
11. San
Bernardino
Mountains
16
1
1
1
2
4
2
Total
Locality
Coordinates
COI haplotypes
GFT haplotypes
9.1 – CA: Los Angeles
Co., Angeles NF,
Grass Mountain
34.6408°N,
118.4148°W
N10, N18, N26, N37,
N46, N47, N48
G01, G02, G03
10.1 – CA: Los
Angeles Co.,
Placerita Cyn. Co.
Pk.
10.2 – CA: Los
Angeles Co.,
Angeles NF, Angeles
Crest Hwy.
10.2 – CA: Los
Angeles Co.,
Angeles NF, Hwy
N3
10.2 – CA: Los
Angeles Co.,
Angeles NF, Hwy
N3
10.3 – CA: Los
Angeles Co.,
Angeles NF, San
Dimas Exp. Forest
34.3764°N,
118.4403°W
N55, N56, N57, N58,
N59, N60
G01
34.2717°N,
118.0608°W
N25, N27
G16
34.2964°N,
118.1625°W
N25, N67, N68
G16, G29, G30
34.2910°N,
118.1695°W
N71, N85
G01, G50
34.2012°N,
117.7736°W
N86, N87
G51, G52, G53, G54
34.2955°N,
117.2134°W
N84
G05, G31
34.1864°N,
117.1836°W
N45
G05, G21
34.1741°N,
116.9844°W
N40
G06, G21
34.1678°N,
116.9143°W
N05, N06
G05, G06
34.1819°N,
116.8884°W
N06, N70
G05, G06
34.1646°N,
116.9366°W
N69
G05
11.1 – CA: San
Bernardino Co.,
SBNF, Hwy 173
11.2 – CA: San
Bernardino Co.,
SBNF, City Ck.
11.3 – CA: San
Bernardino Co.,
SBNF, Deer Creek
11.3 – CA: San
Bernardino Co.,
SBNF, W. of Barton
Flats
11.3 – CA: San
Bernardino Co.,
SBNF, Santa Ana R.
11.3 – CA: San
Bernardino Co.,
SBNF, Camp Cedar
Falls
11
© 2010 The Linnean Society of London, Biological Journal of the Linnean Society, 2010, 99, 424–444
444
M. POLIHRONAKIS and M. S. CATERINO
APPENDIX Continued
Population
12. San Jacinto
Mountains
N
8
1
1
1
Total
13. Santa Cruz
Islands
11
2
4
Total
Locality
Coordinates
COI haplotypes
GFT haplotypes
12.1 – CA: Riverside
Co., UC James
Reserve
12.1 – CA: Riverside
Co., UC James
Reserve
12.1 – CA: Riverside
Co., SBNF, F.S.
4S01
12.1 – CA: Riverside
Co., SBNF, Marion
Mountain
33.8092°N,
116.7650°W
N16, N17, N19, N20,
N21, N22
G05, G11
33.8081°N,
116.7784°W
N83
G11
33.8448°N,
116.7322°W
N19
G05
33.7949°N,
116.7214°W
N32
G05
34.0191°N,
119.6878°W
N33, N34
G04, G04, G19
34.0222°N,
119.6906°W
N97, N98, N99,
N100
G04, G19, G61, G62
13.1 – CA: Santa
Barbara Co., Santa
Cruz Islands
13.1 – CA: Santa
Barbara Co.,
Pelican Bay Tr.
6
SUPPORTING INFORMATION
Additional Supporting Information may be found in the online version of this article:
Appendix S1. Haplotypes and GenBank accession numbers. ‘N’ haplotypes refer to the Nyctoporis carinata COI
sequence; ‘G’ haplotypes refer to the Nyctoporis carinata GFT sequence.
Please note: Blackwell Publishing are not responsible for the content or functionality of any supporting
materials supplied by the authors. Any queries (other than missing material) should be directed to the
corresponding author for the article.
© 2010 The Linnean Society of London, Biological Journal of the Linnean Society, 2010, 99, 424–444