genomic data reveal ancient microendemism in forest ... data reveal ancient microendemism in forest...

Genomic data reveal ancient microendemism in forestscorpions across the California Floristic Province

ROBERT W. BRYSON JR. , * WARREN E. SAVARY,† AMANDA J. ZELLMER,‡ R. BRUCE BURY§ and

JOHN E. MCCORMACK‡ ¶*Department of Biology and Burke Museum of Natural History and Culture, University of Washington, Box 351800, Seattle,

WA 98195-1800, USA, †Department of Entomology, California Academy of Sciences, 55 Music Concourse Drive, Golden Gate

Park, San Francisco, CA 94118, USA, ‡Department of Biology, Occidental College, 1600 Campus Road, Los Angeles, CA 90041,

USA, §41410 NW 12th Street, Corvallis, OR 97330, USA, ¶Moore Laboratory of Zoology, Occidental College, 1600 Campus

Road, Los Angeles, CA 90041, USA

Abstract

The California Floristic Province (CFP) in western North America is a globally signifi-

cant biodiversity hotspot. Elucidating patterns of endemism and the historical drivers

of this diversity has been an important challenge of comparative phylogeography for

over two decades. We generated phylogenomic data using ddRADseq to examine

genetic structure in Uroctonus forest scorpions, an ecologically restricted and dispersal-

limited organism widely distributed across the CFP north to the Columbia River. We

coupled our genetic data with species distribution models (SDMs) to determine climat-

ically suitable areas for Uroctonus both now and during the Last Glacial Maximum.

Based on our analyses, Uroctonus is composed of two major genetic groups that likely

diverged over 2 million years ago. Each of these groups itself contains numerous

genetic groups that reveal a pattern of vicariance and microendemism across the CFP.

Migration rates among these populations are low. SDMs suggest forest scorpion habi-

tat has remained relatively stable over the last 21 000 years, consistent with the genetic

data. Our results suggest tectonic plate rafting, mountain uplift, river drainage forma-

tion and climate-induced habitat fragmentation have all likely played a role in the

diversification of Uroctonus. The intricate pattern of genetic fragmentation revealed

across a temporal continuum highlights the potential of low-dispersing species to shed

light on small-scale patterns of biodiversity and the underlying processes that have

generated this diversity in biodiversity hotspots.

Keywords: arachnid, California Floristic Province, dispersal, endemism, phylogeography

RADseq, species distribution model, Uroctonus

Received 14 December 2015; revision accepted 3 May 2016

Introduction

The California Floristic Province (CFP) in western North

America is a globally significant biodiversity hotspot

that extends across more than 70% of California and

parts of Oregon, Nevada and Baja California in Mexico

(Myers et al. 1999). It is one of only five regions in the

world with a Mediterranean-type climate and encom-

passes a variety of diverse habitats, from coastal

chaparral to montane conifer forests (Myers et al. 1999;

Baldwin 2014). Over 5000 species of plants and verte-

brates are found within the CFP, over 40% of which are

endemic (Myers et al. 1999). More than 30% of the

known insect species north of Mexico are found within

the CFP (Conservation International 2011).

Understanding the historical processes generating the

remarkable diversity of the CFP has been a frequent

study in phylogeography over the past two decades

(e.g. Rodr�ıguez-Robles et al. 1999; Calsbeek et al. 2003;

Lapointe & Rissler 2005; Polihronakis & Caterino 2010).

California’s complex geological history, dynamicCorrespondence: Robert W. Bryson, Jr., Fax: 206 616 2011;

E-mail: [email protected]

© 2016 John Wiley & Sons Ltd

Molecular Ecology (2016) 25, 3731–3751 doi: 10.1111/mec.13707

climatic fluctuations and varied habitats together cre-

ated numerous opportunities for species diversification

across the CFP. Uplift of the Coastal and Transverse

Ranges and parts of the Sierra Nevada during the Late

Miocene and Pliocene around 3–8 million years ago

(Huber 1981; Unruh 1991; Lock et al. 2006) had pro-

found impacts on regional climate and created sharp

elevation and environmental gradients (Raven & Axel-

rod 1978). This period of landscape change was fol-

lowed by dynamic climate shifts associated with the ice

ages and interglacial periods. Fluctuations in Pacific

Ocean currents beginning in the Pliocene, and amplified

during the Pleistocene, led to aridification across much

of California (Ravelo et al. 1997; Herbert et al. 2001).

Coincident with those changes were increases in the

amplitude of glacial cycles, which repeatedly frag-

mented, expanded and restructured species assem-

blages (Raven & Axelrod 1978; Keeley & Swift 1995;

Minnich 2007).

Although California biodiversity is relatively well

described at the regional level (Hickerson et al. 2010),

studies of dispersal-limited taxa continue to provide

new insight into the historical processes that generated

species diversity across the CFP (e.g. Mart�ınez-Solano

et al. 2007; Polihronakis & Caterino 2010; Polihronakis

et al. 2010; Hedin et al. 2013; Reilly & Wake 2015). As

argued by Hedin et al. (2013), the signature of genetic

structure at relatively small spatial scales (i.e. within

the CFP) is more likely to be found in sedentary species

with poor dispersal abilities. Because dispersal across

barriers is limited, divergences in low-dispersing spe-

cies can be remarkably fine-grained and extend across

both deep and shallow timescales (Hedin et al. 2013).

As a result, low-dispersing taxa have greater potential

to reveal biogeographical patterns at multiple scales of

space and time. Fine-scale endemism across the CFP

has been found in a variety of dispersal-limited ani-

mals, including spiders (Starrett & Hedin 2007; Hedin

et al. 2013; Satler et al. 2013), flightless beetles (Polihron-

akis & Caterino 2010), salamanders (Mart�ınez-Solano

et al. 2007; Kuchta et al. 2009a; Reilly & Wake 2015) and

lizards (Leavitt et al. 2007; Parham & Papenfuss 2009).

Forest scorpions of the genus Uroctonus are ecologi-

cally specialized and low-dispersing organisms that are

widely distributed across the CFP north to the Colum-

bia River (Fig. 1). The genus has been redefined over

the past four decades (Stahnke 1974; Williams & Savary

1991; Soleglad & Fet 2004) and currently includes three

species (Uroctonus mordax, Uroctonus franckei and Uroc-

tonus grahami). Uroctonus mordax, comprised of two sub-

species, is broadly distributed across the mountainous

regions of central California, Oregon and southern

Washington (Gertsch & Soleglad 1972; Hjelle 1972). It is

associated with humid microenvironments within a

variety of broader habitats, including coastal scrub, cha-

parral, oak grasslands, and pine-oak, redwood and

mixed-conifer forests (Gertsch & Soleglad 1972; Hjelle

1972). Populations of U. mordax from the Santa Cruz

Mountains along the southern Coastal Range of Califor-

nia are considered a distinct subspecies, U. m. pluridens,

primarily based on the differences in the number of

internal denticles on the fingers of the pedipalp (Hjelle

1972; Soleglad & Fet 2004). Uroctonus franckei inhabits

high-elevation (>2100 m) mixed-conifer forest along the

steep eastern slopes of the Sierra Nevada (Williams

1986). Uroctonus grahami is a rare cave-dwelling scor-

pion known only from Samwel Cave in northern Cali-

fornia (Gertsch & Soleglad 1972; Sissom & Reddell

2009). Although relatively little has been published

about the ecology of Uroctonus, their ecomorphotype

(heavy body, robust pedipalps and relatively short

metasoma) are typical of burrowing scorpions with lim-

ited dispersal abilities (Polis 1990). In one population of

U. mordax in the Coastal Range of California, individu-

als had very small home ranges (less than a few square

metres), marked burrow specificity and a low tolerance

to hot and dry microenvironments (Bacon 1972).

Phylogeographical patterns of species distributed

across the CFP have largely been based on one or a few

genetic loci, usually mitochondrial DNA (mtDNA).

New evidence suggests this reliance on a single gene

might have misled prior work that found congruent lin-

eage divergence across the CFP (Myers et al. 2013)

because of asymmetrical gene flow, introgression and

other stochastic processes that affect mtDNA dispropor-

tionately (Funk & Omland 2003; Edwards & Bensch

2009). Here, we used phylogenomic data to examine

genetic structure in Uroctonus scorpions and species dis-

tribution models (SDMs) to determine climatically suit-

able areas for Uroctonus both now and during the last

glacial maximum (LGM). Results allowed use to assess

several competing hypotheses. Because forest scorpions

are habitat specialists, one hypothesis is that they

would closely track the geographical distribution of

their habitat through time. In this scenario, change in

the location of their habitat from the LGM to present

would have led to dispersal over a landscape already

shaped by Earth history events, thus creating shallow

genetic divergences. Such postglacial habitat tracking

has been inferred for other scorpions (Yamashita &

Rhoads 2013), including several species in western

North America (Graham et al. 2013a,b). Another possi-

bility is that habitats have not shifted dramatically from

the LGM to present day, in which case forest scorpion

genetic divergences are predicted to be older and per-

haps even reflect the timing of Earth history events

causing vicariance. An alternate hypothesis is that forest

scorpion habitats have shifted dramatically from the


3732 R. W. BRYSON ET AL.

STG

JNL

ROG

CCL

CTW

WKY

MAU

SONMDB

AVY

CAM

PAS

PLA

JAK

CRD

BGP

BRM

LAB

LAH

MGV

CAL

NEL

CATFRI

POW

TEJ

SHA

RED

BAL

SPV

WHP

SVE

WEE

COR

CAR

DET

GEY

PCY

MYC

SAM

0 100 200 300 40050km

124° W 122° W 120° W 118° W

124° W 122° W 120° W 118° W

46° N

34° N

36° N

38° N

40° N

42° N

44° N

46° N

34° N

36° N

38° N

40° N

Uroctonus mordaxUroctonus franckeiUroctonus grahami

Washington

Oregon

California

Eel River

Nevada

KlamathMtns

Cascades

Cascades

CoastalRange

CoastalRange

SierraNevada

TehachapiMtns

CALIFORNIA FLORISTICPROVINCE

CoastalRange

Fig. 1 Sampling localities of Uroctonus across the California Floristic Province (modified from UNEP-WCMC 2013). The Eel River

across the northern Coastal Range of California marks the inferred western boundary between the two major clades of Uroctonus

described in the text.


MICROENDEMISM IN FOREST SCORPIONS 3733

LGM to present, but that the scorpions have not tracked

these broadscale changes and instead have persisted in

suitable microhabitats. This hypothesis would find sup-

port if the SDMs for the LGM and present day are dra-

matically different, but if the genetic data nonetheless

support deep divergences congruent with ancient

vicariance.

Materials and methods

Taxon sampling and DNA sequencing

We collected 193 samples of Uroctonus from 40 localities

throughout their distribution (Fig. 1, Table S1, Support-

ing information). We sampled all described taxa in the

genus, including the rare cave-adapted species Uroc-

tonus grahami. The regions between the southern Coastal

Range and the Tehachapi Mountains in western Califor-

nia and between the northern Sierra Nevada and south-

ern Cascades in eastern California correspond to

geographical gaps in the known distribution of Uroc-

tonus mordax (Gertsch & Soleglad 1972; Hjelle 1972).

Our attempts to find this scorpion in these areas were

unsuccessful, and none were present in the collection of

over 1200 Uroctonus in the California Academy of

Sciences invertebrate collection examined by one of us

(WES). The appearance of a similar burrow-dwelling

scorpion (Anuroctonus pococki) and shift to a drier cha-

parral-dominated community along the Salinian Block

of the southern Coastal Range and an abundance of

ultisol soils in the northern Sierra Nevada may be rea-

sons why U. mordax is seemingly absent from these

regions. The higher-level taxonomic placement of Uroc-

tonus has been debated in recent years, and this genus

has been placed in either Vaejovidae (e.g. Stockwell

1989; Sissom 2000; Prendini & Wheeler 2005) or Chacti-

dae (Soleglad & Fet 2003, 2004). Our own unpublished

data suggest that Uroctonus may be a vaejovid distantly

related to other putative ‘Uroctonini’ (sensu Stockwell

1989) but with no close phylogenetic relationship to any

extant species.

We generated genomewide single nucleotide poly-

morphism (SNP) data using the double-digest restric-

tion-digest-associated DNA marker (ddRADseq)

protocol of Peterson et al. (2012). We extracted high-

molecular weight genomic DNA from pedipalp tissue

using Qiagen DNeasy Blood & Tissue Kits (Qiagen

Inc.). Extractions were run out on 1.8% agarose gels to

visually inspect DNA quality. We digested 200–500 ng

of DNA (up to 43 lL total) for 2 h at 37 °C using 20

units each of the restriction enzymes SbfI-HF and MspI

(New England Biolabs) and 5 lL Cutsmart Buffer (New

England Biolabs) in a single 50 lL reaction. We cleaned

digestions with home-made Serapure beads (Rohland &

Reich 2012; Faircloth & Glenn 2014), quantified concen-

trations using a Qubit fluorometer and then ligated bar-

coded Illumina adaptors onto the fragments.

Afterwards, we combined eight uniquely barcoded

samples into individual pools, cleaned these pools with

Serapure beads and then used a Pippin Prep (Sage

Science) to size-select fragments of 415–515 base pairs.

We then used limited-cycle PCR amplification to add

Illumina-indexed primers and increase concentrations

of sequencing libraries. We used a combination of eight

unique barcodes and 12 Illumina indexes to multiplex

96 samples for a single sequencing lane. PCRs consisted

of a 40 lL reaction volume containing 1 lL dNTPs

(10 mM), 2.0 lL each primer (10 lM), 10 lL Phusion HF

Buffer (59), 0.5 lL Phusion DNA polymerase (Phusion)

and 5–10 ng template DNA (up to 34.5 lL). We ran 11

cycles of PCR using the recommended Phusion condi-

tions. Finally, we cleaned the completed reactions with

Serapure beads and ran samples on an Agilent 2200

TapeStation to quantify the concentration and fragment

size distribution of each pool. We sent pooled ddRAD

libraries to the Vincent J. Coates Genomics Sequencing

Laboratory at UC Berkeley for 100-base single-end

sequencing on an Illumina HiSeq 2000 (12 pooled

libraries per lane).

We also sequenced a fragment of the mitochondrial

gene cytochrome c oxidase subunit I (CO1) from a sub-

set of samples (1–6 per locality, n = 80). This allowed us

to compare phylogeographical structure and estimated

divergence dates between SNPs and mtDNA. The single

sample of U. grahami included in our study was col-

lected after ddRADseq data were generated; however,

we were able to sequence CO1. PCRs contained 6.25 lLTakara ExTaq Polymerase Premix (Takara Mirus Bio

Inc.), 4.25 lL double-distilled water, 0.5 lL each primer

(10 lM) and 1.0 lL of template DNA. We used the pri-

mers CO1modF and LE1r (Bryson et al. 2013). Cycling

conditions included an initial denaturation at 94 °C for

2.5 min, followed by 35 cycles of denaturation at 94°Cfor 30 s, annealing at 54°C for 30 s and extension at

72°C for 1 min, with a final 10-min extension at 72°C.PCR products were checked by electrophoresis on 1.8%

agarose gels and then sent to High-Throughput Geno-

mics Center (University of Washington, Seattle) for

sequencing. We edited and manually aligned the for-

ward and reverse sequences for each individual using

SEQUENCHER v.5.0 (Gene Codes Corporation).

Single nucleotide polymorphism data assembly

We demultiplexed and processed Illumina reads using

the software pipeline PYRAD v.2.16.1 (Eaton & Ree 2013;

Eaton 2014). Nucleotide base calls with a Phred quality

score below 20 were replaced with ‘N’s, and reads with



more than 10% ‘N’s were discarded. Sequences were

clustered at 90% similarity within samples using USE-

ARCH v.7.0.1090 (Edgar 2010) and aligned with MUSCLE

v.3.8.31 (Edgar 2004). Error rate and heterozygosity

were jointly estimated from the base counts in each site

across all clusters. Consensus sequences with less than

five reads, more than five undetermined sites, more

than five heterozygous sites or more than two haplo-

types were discarded. Consensus sequences were then

clustered across samples using the same 90% similarity

threshold and aligned. Any locus with a site appearing

heterozygous across more than 50% of samples was dis-

carded as likely representing a clustering of paralogs.

We set the minimum number of samples in a final locus

to 96, allowing up to 50% missing data per locus.

Although the full impact of missing data on phyloge-

netic analyses of SNP data remains unknown (Huang &

Knowles 2016), several studies suggest relatively high

levels of missing data (up to 80% per locus) do not

appear to negatively affect topology or population clus-

tering and may increase phylogenetic resolution (Rubin

et al. 2012; Wagner et al. 2013; Streicher et al. 2014;

Leach�e et al. 2014; but see Streicher et al. 2016). After

data filtering in PYRAD, we output two main types of

data for downstream analyses: (i) all RAD loci, includ-

ing variant and invariant sites, and (ii) unlinked SNPs

(one SNP per locus). We visualized missing data across

the complete data matrix using the ‘mdPlot’ function in

R (R Development Core Team 2014) and discarded sam-

ples with >75% missing data.

RADseq data are prone to allele dropout as diver-

gence depth increases due to mutations at restriction

sites (Arnold et al. 2013). This dropout decreases the

number of orthologous sequences obtained across sam-

ples and results in large amounts of nonrandom miss-

ing data shared by individuals that have mutations at

the same loci. After inferring major phylogenetic clades

using all RAD loci (see below), we reassembled the data

in PYRAD, including only demultiplexed Illumina reads

for samples within the same clade to reduce allelic

dropout. We used the same paralog filters as above,

allowed up to 50% missing data per locus and output

several types of data files derived from unlinked SNPs

(e.g. .str and .migrate) for downstream analyses.

Phylogenetic inference

We estimated time-calibrated Bayesian phylogenies for

the RAD loci and mtDNA using BEAST v.1.8.1 (Drum-

mond et al. 2012) on the CIPRES v.3.3 computing cluster

(Miller et al. 2010). We used JMODELTEST v.2.1.7 (Guindon

& Gascuel 2003; Darriba et al. 2012) to select the best-fit

model of evolution, based on the Bayesian information

criterion (BIC), for the concatenated RAD loci

(HKY + I + G) and 1st + 2nd (HKY + I) and 3rd

(HKY + G) codon positions of the CO1 gene. To cali-

brate each phylogeny, we utilized previously published

substitution rates estimated from buthid scorpions pre-

sumably sundered by the same biogeographical events

(Gantenbein & Keightley 2004; Gantenbein et al. 2005).

Although these rates were calculated from buthid scor-

pions distantly related to Uroctonus, no other DNA sub-

stitution rates have been estimated for scorpions. For

the RAD phylogeny, we gave the ucld.mean parameter

a lognormal distribution with a mean of 0.0024 substitu-

tions/site/million years and standard deviation of 0.43,

resulting in a 95% highest probability density (HPD)

ranging from 0.0011 to 0.0044 and spanning mean sub-

stitution rates previously calculated for nine nuclear

genes (concatenated introns, 0.0044; synonymous sites

of concatenated protein-coding genes, 0.0023; nonsyn-

onymous sites of concatenated protein-coding genes,

0.0012; Gantenbein & Keightley 2004). We gave the

ucld.stdev parameter a gamma distribution with a

mean of 0.45 after examining trace plots of the posterior

distributions of preliminary runs. For the mtDNA phy-

logeny, we gave the ucld.mean parameter a lognormal

distribution with a mean of 0.007 and standard devia-

tion of 0.3 (95% HPD = 0.0040–0.0109), centred around

the mean substitution rate of 0.007 previously calcu-

lated for CO1 (Gantenbein et al. 2005). We used a log-

normal relaxed clock model and a constant-size

coalescent (RAD loci) or Yule process (mtDNA) tree

prior and ran analyses for 80 million generations,

retaining trees and parameters every 10 000 steps.

Results were displayed in TRACER v.1.6 (Rambaut &

Drummond 2007) to assess convergence and effective

sample sizes for all estimated parameters. We discarded

the first 25% of trees as burn-in and summarized the

maximum clade credibility tree with median heights

using TREEANNOTATOR v.1.8.1 (Drummond et al. 2012).

Each analysis was repeated with random starting seeds

to confirm adequate mixing and consistent results.

Recent studies have found concatenation of phyloge-

nomic data can lead to overestimated credibility values

in phylogenetic trees (e.g. Song et al. 2012; Xi et al.

2014). We therefore reconstructed a species tree using

the multispecies coalescent model implemented in the

SNAPP v.1.1.6 (Bryant et al. 2012) plugin in BEAST v.2.1.3

(Bouckaert et al. 2014). To reduce computational bur-

den, we grouped 54 samples into nine geographical

groups (six samples each) based on the BEAST analyses

of RAD loci (see below). We used a gamma prior for h(a = 10, b = 1000) and default settings for all other

parameters and ran analyses for 4 million generations,

sampling every 1000 steps, using BEAST v.2.2.1 (Bouck-

aert et al. 2014). We verified MCMC convergence and

acceptable ESS values for parameters in TRACER; ESS



values in the final run exceeded 2000 for all parameters.

We summarized the maximum clade credibility tree

using TREEANNOTATOR and visualized the posterior distri-

bution of species trees after a 25% burn-in using DEN-

SITREE v.2.1.11 (Bouckaert 2010). We ran the analysis

multiple times using different starting seeds, different

priors for h and different priors for the forward and

reverse mutation rates to confirm consistent tree struc-

ture.

To explore the possible impacts of sample size and

allelic dropout on our species-tree reconstruction, we ran

two additional sets of analyses with SNAPP. In the first,

we included all 191 samples, each assigned to one of the

nine geographical groups. In the second, we included all

individuals but used the clade-specific data assemblies,

which increased the number of unlinked SNPs analysed.

We used a gamma prior for h (a = 10, b = 1000), default

settings for all other parameters, and, because of compu-

tational limitations, stopped analyses (sampling every

1000 steps) once ESS values for all parameters were

above 200. For the full data set, this took 430 000 genera-

tions and over 3 months of run-time using 16 processors

on a Titan X250 with two Intel Xeon E5-2440 processors;

it took 400 000 generations and approximately 3 weeks

of run-time for the clade-specific data sets.

Population structure

We used a hierarchical approach to estimate population

structuring within each of the two major clades (north-

ern and southern clades, detailed below) using unlinked

SNPs. Although somewhat laborious, hierarchical

approaches have been shown to detect fine-scale genetic

structuring in taxa with complex evolutionary histories

(e.g. Coulon et al. 2008; Levy et al. 2012; Lambert et al.

2013). Further, hierarchical approaches should mitigate

the spurious effects of isolation by distance on cluster-

ing (Blair et al. 2012). We used STRUCTURE v.2.3.4 (Pritch-

ard et al. 2000; Falush et al. 2003, 2007) to first estimate

range-wide population structuring within each clade.

We ran initial analyses of K = 1–20 using an admixture

model with uncorrelated allele frequencies for 100 000

MCMC generations. However, global analysis in STRUC-

TURE may only identify top-level geographical structure

when hierarchical population structure exists (Waples

& Gaggiotti 2006; Coulon et al. 2008; Papadopoulou &

Knowles 2015). Following Gowen et al. (2014), we sub-

sequently conducted runs of K = 2 on successively

smaller clusters of individuals within each clade until

no geographical clustering was discernable or only one

locality remained. We used an admixture model with

uncorrelated allele frequencies and ran analyses for

1 million generations after a 10% burn-in. Each analysis

was run four times, and clusters of individuals in the

iteration with the highest likelihood were used for

sequential runs.

As an alternative method to infer clusters of geneti-

cally related individuals within each clade, we used k-

means clustering of principal components implemented

in the R package ADEGENET v.1.4.2 (Jombart & Ahmed

2011). The number of clusters was estimated using the

‘find.clusters’ function with the maximum number of

clusters set to 20. We used all principal components of

PCA and ran 20 iterations, logging the K with the low-

est BIC score for each run. To decrease the complexity

of the data set, we repeated analyses using samples

from each of the nine geographical groups comprised

of more than one population inferred from BEAST analy-

ses of RAD loci. We then used discriminant analysis of

principal components (DAPC) to describe the diversity

between inferred clusters. We used one-fourth of the

principal components of PCA from the preliminary

variable transformation as input to DAPC.

Population migration

We used the coalescence-based program MIGRATE-N

v.3.6.6 (Beerli & Felsenstein 2001; Beerli 2006) to esti-

mate migration rates between populations within each

of the major geographical groups inferred from BEAST

analyses of RAD loci. We limited analyses to popula-

tions with three or more individuals and groups com-

prised of more than one population. We used PYRAD to

create the MIGRATE-N in files, and set the minimum clus-

ter size option to one for all populations (meaning that

only loci with data for at least one individual across all

populations were included in each data set). Appropri-

ate prior boundaries were determined from preliminary

exploratory analyses. We evaluated a full migration

model with unrestricted migration among all popula-

tions. Initial start values of h and M were set to 0.001

and 1000, and mutation rates were estimated from the

data. We used diffuse uniform prior distributions for h(0.00001–0.01, d = 0.001) and M (0–1000, d = 100). We

conducted analyses using four heated chains (1.0, 1.2,

3.0, and 10000.0) ran for 20 000 steps, sampling every

100 generations, after 20 000 steps were discarded as

burn-in. We confirmed stationarity of the Markov

chains by verifying ESS values were >100 000 and that

posterior distribution plots for each parameter were

smooth and unimodal. Each analysis was repeated with

random starting seeds to validate convergence and con-

sistency of parameter estimates. We translated estimates

of mutation-scaled immigration rate M output by MI-

GRATE-N into the effective number of migrants per gener-

ation (Nm) by multiplying M with theta (Θ) of the

receiving population and dividing by four (the inheri-

tance scalar for diploid SNP data).



Species distribution modelling

To investigate the role of climatic changes in the diver-

sification of Uroctonus, we compared SDMs of each

clade for both contemporary climatic conditions and

historical climatic conditions at the LGM (21 kya). The

SDMs allowed us to predict suitable habitat at the LGM

and test for both environmental and spatial overlap

between the clades. We generated SDMs using MAXENT

v.3.3.3 (Phillips et al. 2006). This method uses georefer-

enced specimen locations along with environmental

data layers to create a model of current probability of

occurrence for a species based on environmental condi-

tions. We then used the model for the current distribu-

tion to predict the historical probability of occurrence

based on historical environmental conditions.

For our locality data, we used 360 occurrences for

Uroctonus obtained from three sources, including litera-

ture records (Gertsch & Soleglad 1972; Hjelle 1972;

Crawford 1990), specimens in the California Academy

of Sciences Entomology Collection and samples col-

lected during the study in developing distribution mod-

els (Table S2, Supporting information). Each point was

georeferenced to within 1 km, and no two points occu-

pied the same pixel of the 1 km resolution climate data.

The precise boundary between the northern and south-

ern clades along the northern Coastal Range is

unknown based on our sampling (see results). Several

codistributed, dispersal-limited taxa display distinct

genetic breaks in this region (Shaffer et al. 2004; Starrett

& Hedin 2007; Kuchta et al. 2009b; Reilly & Wake 2015),

often attributed to the Eel River drainage (Fig. 1). We

therefore assigned georeferenced samples north of the

Eel River to the northern clade, and samples south of

the drainage to the southern clade. We created SDMs

using a random subset of 80% of the localities and used

the remaining 20% of localities to test the validity of the

models.

The environmental data included a total of 19 biocli-

matic variables and five landscape variables describing

current conditions at a 30-arcsec resolution (Table S3,

Supporting information). For the historical SDMs, we

used only the 19 bioclimatic variables reconstructed for

21 kya at a 2.5-min resolution (Hijmans et al. 2005;

Table S3, Supporting information). Since past climate

reconstructions are sensitive to the general circulation

models (GCMs) used (Varela et al. 2015), we used three

separate GCMs to validate our historical distribution

reconstructions. The three GCMs used include CCSM4,

MIROC-ESM and MPI-ESM-P (described in Varela et al.

2015) and were downloaded from worldclim.org (Hij-

mans et al. 2005). We elected to include all variables in

the Maxent analyses when possible, as recent research

suggests that overparamaterized models consistently

perform better than underparamaterized models (War-

ren & Seifert 2011). We used R v.3.0.1 (R Development

Core Team 2013) for all manipulation and visualization

of spatial environmental data and niche models. Scripts

are available upon request.

Results

Genetic data

The number of raw reads per individual after demulti-

plexing ranged from 232 863 to 4 196 982

(mean = 1 319 919), and mean cluster depth ranged

from 2.7 to 38.6 (mean = 14.5). One sample (sky436

CAR) had more than 75% missing data (Fig. S1, Sup-

porting information) and was discarded. The final

aligned data set with all RAD loci contained 191 indi-

viduals, 45 785 nucleotides, 497 loci, 6762 SNPs and 493

unlinked SNPs (Table S4, Supporting information). The

Bayesian phylogenetic analysis revealed two major

clades (detailed below). When analysed alone, the

‘northern’ clade contained 95 taxa, 1002 loci, 6659 SNPs

and 974 unlinked SNPs. The ‘southern’ clade, mean-

while, contained 96 taxa, 1344 loci, 14 706 SNPs and

1332 unlinked SNPs. Assembling the data set by clade

produced 1.68–3.01 (mean = 2.46) times more loci per

individual (Table S4, Supporting information), suggest-

ing that RAD loci were being lost due to accumulation

of mutations to the restriction sites leading to dropped

loci. The mtDNA data set contained 806 bp of CO1

data. The uncorrected p-distance between the two main

clades was 5.3%. Aligned data sets were deposited in

Dryad (doi:10.5061/dryad.58sn8), and CO1 sequences

were deposited in GenBank (Accession nos. KX171074–KX171153).

Phylogenetic inference

Bayesian phylogenetic analysis of the RAD loci data set

(191 taxa, 45 785 bp) revealed two major clades with

strong geographical structure within each clade

(Fig. 2a). A ‘northern’ clade consisted of 95 individuals

from 21 localities in southern Washington, Oregon and

northern California. A ‘southern’ clade consisted of 96

individuals from 18 localities in northern and central

California.

We found a strong correspondence between geogra-

phy and genetic lineages within both clades. Four

strongly supported, geographically structured groups

were present within the northern clade (Fig. 3). Samples

of U. mordax from two localities in the northeastern

Cascades of Oregon near the edge of the Columbia

Basin formed a strongly supported group (‘northeastern

Cascades’). Samples from the northwestern Cascades in



http://dx.doi.org/10.5061/dryad.58sn8

http://www.ncbi.nlm.nih.gov/nuccore/KX171074


U. franckei

(a) RAD loci, BEAST

(b) mtDNA, BEAST

(c) unlinked SNPs, SNAPP

No

rthe

rn C

lad

e

Southern Cascades +northeastern Coastal Range

Klamath Mtns

Northeastern Cascades

Northeastern Sierra Nevada

Northwestern Cascades +Oregon Coastal Range

Southern Sierra Nevada

Southern Coastal Range

Northern Coastal Range

Northwestern Sierra Nevada

0 Mya123456

sky383 PLA

sky194 GEY

sky463 BGP

sky340 BAL

sky417 COR

sky445 WHP

sky380 MDB

sky320 DET

sky338 RED

sky214 RED

sky474 CTW

sky312 WEE

sky484 SON

sky457 JNL

sky310 WEE

sky447 WKY

sky399 CRD

sky477 CTW

sky220 MYC

sky348 WEE

sky381 PLA

sky315 WEE

sky345 BAL

sky378 MDBsky289 MDB

sky450 ROG

sky341 BAL

sky385 PAS

sky365 SPV

sky253 LAH

sky336 RED

sky210 TEJ

sky372 CAM

sky316 WEE

sky356 SVE

sky347 BAL

sky448 WKY

sky379 MDB

sky458 JNL

sky58 BGP

sky452 JNL

sky387 PAS

sky490 SON

sky354 SVE

sky281 PAS

sky335 RED

sky480 STG

sky212 SVE

sky406 CAL

sky294 CAR

sky213 CAR

sky403 MYC

sky411 GEY

sky355 SVE

sky245 MGV

sky404 CAL

sky360 SPV

sky221 SHA

sky219 SPV

sky292 CAR

sky346 BAL

sky400 LAH

sky373 CAM

sky224 CRD

sky278 CAM

sky324 DET

sky330 RED

sky222 CAT

sky367 PCY

sky377 AVY

sky444 WHP

sky295 CAR

sky473 CTW

sky209 WEE

sky478 STG

sky361 SPV

sky486 SON

sky298 MYC

sky262 SHA

sky321 DET

sky461 BGP

sky460 JNL

sky323 DET

sky401 LAH

sky344 BAL

sky413 GEY

sky375 AVY

sky242 CAL

sky223 POW

sky260 NEL

sky303 FRI

sky370 CAM

sky362 SPV

sky343 BAL

sky488 SON

sky357 SVE

sky369 PCY

sky459 JNL

sky475 CTW

sky325 DET

sky416 COR

sky442 WHP

sky327 SHA

sky309 DET

sky271 GEY

sky317 WEE

sky443 WHP

sky384 PAS

sky306 DET

sky358 SVE

sky476 CTW

sky405 CAL

sky485 SON

sky382 PLA

sky300 MYC

sky217 DET

sky424 PCY

sky456 JNL

sky440 WHP

sky328 SHA

sky280 PLA

sky332 RED

sky304 FRI

sky218 WEE

sky279 AVY

sky318 WEE

sky258 MYC

sky453 JNL

sky337 REDsky59 JAK

sky371 CAM

sky265 BRM

sky376 AVY

sky364 SPV

sky297 CARsky293 CAR

sky435 NEL

sky282 POW

sky491 SON

sky441 WHP

sky462 BGP

sky195 PCY

sky439 WHP

sky408 TEJ

sky301 COR

sky257 LAB

sky299 MYC

sky308 DET

sky415 MAU

sky296 CAR

sky363 SPV

sky215 BAL

sky352 SVE

sky269 MGV

sky479 STG

sky449 CCL

sky302 COR

sky374 CAM

sky305 FRI

sky331 RED

sky409 GEY

sky414 MAU

sky334 RED

sky322 DET

sky353 SVE

sky412 GEY

sky451 JNL

sky291 CAR

sky386 PAS

sky455 JNL

sky446 WHP

sky339 BAL

sky230 NEL

sky261 PCY

sky216 COR

sky350 SVE

sky267 WHP

sky290 CAR

sky326 SHA

sky311 WEE

sky319 DET

sky423 MGV

sky307 CAT

sky351 SVE

sky418 COR

sky407 TEJ

sky359 SPV

sky329 SHA

sky333 RED

sky402 MYC

sky454 JNL

3.68 [1.13, 7.56]

6.38 [2.20, 13.60]

4.56 [1.40, 9.54]

northeastern Cascades

Southern Cascades + northeasternCoastal Range

Northwestern Cascades + Oregon Coastal Range


Northern CoastalRange

Southern SierraNevada

sky463 BGP

sky445 WHP

sky457 JNL

sky458 JNL

sky58 BGPy

sky452 JNLk

sky444 WHP

y

sky461 BGPy

sky460 JNLy

sky459 JNLy

k

sky442 WHPsky443 WHP

y

k

sky456 JNL

sky440 WHP

sky453 JNLy

sky441 WHPk

sky462 BGPk

y

sky439 WHPy

k

sky451 JNLk

y

sky455 JNLy

sky446 WHPy

k

sky267 WHPk

y

sky454 JNLk

y

7.95 [3.39, 14.66]

10.41 [4.52, 18.67]

7.59 [3.30, 13.70]

No

rthe

rn C

lad

eSo

uth

ern

Cla

de

0 Mya12345678910

sky269 MGV

sky474 CTW

sky258 MYC

sky463 BGP

sky341 BAL

sky407 TEJ

sky242 CAL

sky453 JNL

sky280 PLA

sky253 LAH

sky210 TEJsky265 BRM

sky454 JNL


sky260 NEL

sky448 WKY

sky194 GEY

sky195 PCY

sky220 MYC

sky223 POW

sky221 SHA

sky59 JAK

sky209 WEE

sky58 BGP

sky452 JNL

sky480 STG

sky479 STG

sky217 DET

sky214 RED

sky376 AVY

sky257 LAB

sky224 CRD

sky473 CTW

sky455 JNL

sky359 SPV

sky375 AVY

sky213 CAR

sky278 CAM

sky370 CAM

sky441 WHP

sky449 CCL

sky450 ROG

sky451 JNL

sky415 MAU

sky351 SVE

sky289 MDB

sky218 WEE

sky447 WKY

sky212 SVE

sky371 CAM

sky521 SAM

sky279 AVY

sky475 CTW

sky271 GEY

sky462 BGP

sky282 POW

sky440 WHP

sky281 PAS

sky262 SHA

sky443 WHP

sky303 FRI

sky461 BGP

sky215 BAL

sky304 FRI

sky219 SPV

sky485 SON

sky340 BAL

sky222 CAT

sky350 SVE

sky490 SON

sky245 MGV

sky414 MAU

sky408 TEJ

sky439 WHP

sky230 NEL

sky360 SPV

sky478 STG

sky216 COR

sky261 PCY

Northeastern Cascades

Klamath Mtns



NorthernCoastal Range

* Northeastern Sierra Nevada

Southern Sierra Nevada**

*

*

**

**

U. grahami

sky453 JNL

sky454 JNLsky452 JNL

sky455 JNL

y

sky451 JNL


sky441 WHP


sky439 WHP

sky463 BGPsky58 BGP

y

sky462 BGPsky461 BGP

U. franckei

Klamath Mtns

NorthwesternSierra Nevada


NorthwesternSierra Nevada

Southern Cascades + northeasternCoastal Range

No

rthe

rn C

lad

eSo

uth

ern

Cla

de

NortheasternCascades

Southern Cascades +northeastern CoastalRange

Klamath Mtns

Northeastern SierraNevada

Southern SierraNevada

Southern CoastalRange

Northern CoastalRange

Northwestern SierraNevada

Northern Clade Southern Clade

Sou

the

rn C

lad

e


Fig. 2 Phylogenetic relationships in Uroctonus. (a) Time-calibrated BEAST tree inferred from concatenated RAD loci. (b) Time-calibrated

BEAST tree inferred from mitochondrial DNA. Mean estimated divergence dates and 95% posterior credibility intervals (in brackets)

shown for the basal divergence and two major clades of Uroctonus. Samples of Uroctonus franckei delineated with grey boxes to high-

light paraphyly. (c) Cloudograms of posterior estimates of species trees reconstructed from unlinked single nucleotide polymor-

phisms using SNAPP (top estimated from the reduced data set; bottom from clade-specific data sets). In all trees, nodes with black

dots received ≥0.95 posterior probability support, and major geographical groups match those in Fig. 3. See Fig. S2 (Supporting

information) for larger versions of (a) and (b).



southern Washington and Oregon and the adjacent

Coastal Range of Oregon formed a strongly supported

group (‘northwestern Cascades + Oregon Coastal

Range’). This group contained the largest number of

samples (44 samples from 10 localities) and largest

number of admixed localities (six of the eight

Northern CladeNortheastern Cascades


Klamath Mountains

Southern Cascades + northeastern Coastal Range

Southern Clade

Southern Sierra Nevada


Northwestern Sierra Nevada


Northern Coastal Range

Fig. 3 Distribution of major geographical

groups within the northern and southern

clades of Uroctonus. Geographical groups

inferred from Bayesian phylogenetic

analysis of the RAD loci data set and

match those in Fig. 2.



represented by >1 individual). Uroctonus mordax from

four localities in the Klamath Mountains in southern

Oregon and northern California comprised a strongly

supported group (‘Klamath Mountains’). The remaining

samples from the southern Cascades and northeastern

Coastal Range in northern California formed the fourth

strongly supported geographical group (‘southern Cas-

cades + northeastern Coastal Range’). Within the south-

ern clade, we inferred five strongly supported

geographically structured groups (Fig. 3). Samples of

U. mordax from the Coastal Range of northern Califor-

nia formed two strongly supported groups: a ‘northern

Coastal Range’ group comprised of samples from seven

localities, and a ‘southern Coastal Range’ group com-

prised of samples from a single locality in the Santa

Cruz Mountains. Uroctonus franckei from the eastern

slopes of the Sierra Nevada did not form a mono-

phyletic group. Samples from the two northernmost

localities (June Lake and Big Pine, the type locality for

the species) formed a strongly supported geographical

group (‘northeastern Sierra Nevada’). Samples from the

southernmost locality (Whitney Portal) grouped with

samples of U. mordax from three localities on the oppo-

site slopes of the southern Sierra Nevada and adjacent

Tehachapi Mountains (‘southern Sierra Nevada’). The

remaining samples from the northwestern slopes of the

Sierra Nevada formed a strongly supported clade

(‘northwestern Sierra Nevada’).

Phylogeographical structure inferred from the

mtDNA data set (80 individuals, 805 bp of CO1) was

generally consistent with results from RAD loci. The

same northern and southern clades were recovered with

moderate support (0.87 and 0.92 posterior probability,

respectively) along with substantial geographical struc-

ture within each clade (Fig. 2b). However, nodal sup-

port across the mtDNA tree was low, especially

towards the base of the tree. Seven of the nine geo-

graphical groups inferred from analysis of the RAD loci

were recovered, although three received <0.95 probabil-

ity support. The southern Sierra Nevada geographical

group was rendered paraphyletic by the inclusion of

samples of U. franckei from June Lake. Phylogenetic

analyses of RAD loci placed U. franckei from June Lake

with U. franckei from Big Pine in a well-supported

northeastern Sierra Nevada geographical group

(Fig. 2a). Relationships among geographical groups

were poorly supported across the mtDNA tree except

for the sister relationship between the northeastern Cas-

cades group and northwestern Cascades + Oregon

Coastal Range group. This result strongly conflicted

with the placement of these two groups in the RAD loci

tree (Fig. 2a). Uroctonus grahami was weakly supported

(0.57 posterior probability) as sister to the clade com-

prised of nearby localities in southern Oregon and

northern California (Klamath Mountains and southern

Cascades + northeastern Coastal Range groups).

Estimated dates of divergences differed between the

RAD loci and mtDNA data sets. Whereas estimated

mean divergences among geographical groups based on

analyses of the RAD loci occurred around 2.8–4.5 Mya

during the Pliocene (Fig. 2a), mean estimates based on

mtDNA pre-dated the Pliocene, occurring around 5.0–7.9 (Fig. 2b). However, 95% posterior credibility inter-

vals for divergence date estimates from both data sets

were large and overlapping. We cautiously interpret

these results to suggest that divergences among geo-

graphical groups within Uroctonus probably pre-dated

the Pleistocene, but acknowledge the large uncertainty

surrounding this inference.

Phylogenetic relationships estimated using the multi-

species coalescent model in SNAPP varied depending on

the number of unlinked SNPs analysed. The reduced

data set with 54 individuals contained 312 unlinked SNPs

after sites with missing data were removed by SNAPP.

Although support for the northern and southern clades

was high, support for relationships among the nine geo-

graphical groups within these clades was low (Fig. 2c), in

strong contrast to the tree estimated from the concate-

nated RAD loci (Fig. 2a). Species-tree analyses using the

full data set (all 191 individuals) contained 300 unlinked

SNPs after sites with missing data were removed by

SNAPP. Relationships within the southern clade were iden-

tical to the species tree estimated from the reduced data

set both in terms of topology and low nodal support (tree

not shown). Relationships within the northern clade,

however, matched those in the concatenated RAD loci

tree (Fig. 2a) and were moderately supported (0.92 poste-

rior probability). The species tree estimated for each indi-

vidual clade (Fig. 2c) matched the tree inferred from

concatenated RAD loci (Fig. 2a). The northern clade data

set contained 688 unlinked SNPs, and the southern clade

contained 1088 unlinked SNPs – over two and three times

the number in the full data set. Based on the topological

congruence between these clade-specific species trees

and the concatenated phylogeny, we interpret the con-

catenated phylogeny (Fig. 2a) as our best estimate of

phylogenetic relationships in Uroctonus.

Population structure

STRUCTURE analyses. Analyses in STRUCTURE on each clade

found the optimal K to be 2 based on the DK statistic

(Evanno et al. 2005) as implemented in STRUCTURE HAR-

VESTER v.0.6.94 (Earl & vonHoldt 2012). However, exami-

nation of higher numbers of K indicated additional

geographical clusters were present within both clades.

At K = 4 for the northern clade and K = 5 for the south-

ern clade, clusters matched the major geographical



groups inferred from BEAST analyses of RAD loci. The

K = 2 hierarchical clustering revealed additional fine-

scale genetic structure (Figs. 4 and 5). In both clades,

nearly every sampling locality was identified as a dis-

tinct cluster with little or no admixture found among

localities. In total, 15 clusters were identified within the

northern clade and 18 clusters were identified within

the southern clade. Only the northern clade contained

single clusters comprised of individuals from multiple

localities.

The amount of missing data in successive iterations

increased as samples were removed. If the distribution

of missing data was nonrandom among samples (e.g.

shared among individuals in a population), STRUCTURE

may have been biased towards grouping samples with

similar patterns of missing data (Pritchard et al. 2010).

To test this possibility, we ran samples from three pairs

of nonadmixed geographically proximate localities

(WEE-NEL, PLA-PAS and AVY-SON) through PYRAD

and removed missing data by setting the minimum

number of samples in a final locus to equal the total

number of samples. If STRUCTURE was clustering individ-

uals from each locality based on nonrandom missing

data, then we expected to find more admixture between

localities after missing data were removed. In all three

examples, results with no missing data showed no

admixture between locality pairs, consistent with

previous results.

ADEGENET analyses. Iterative runs of k-means clustering in

ADEGENET failed to converge on similar numbers or compo-

sitions of clusters of individuals within each clade.

Northern Cladehierarchical K = 2 clustering

CAR CORDET CATFRI WKYCCL MYCROG POW

MYC ROGPOW

ROG POW

ROG POW (1)

POW (1)

MYCCAR CORDET CATFRI WKYCCL

WEE NELSTG JAKMAU CTWRED SHACRD PLAPAS

WEE NELSTG JAKMAU CTW

WEE NELSTG JAK

WEE NEL

WEE

NEL

STG JAK

STG

JAK

MAU CTW

MAU

CTW

RED SHACRD PLAPAS

PAS

RED SHACRD PLA

SHA

RED CRDPLA

PLA

RED CRD

RED

CRD

STG

ROG

CCL

CTW

WKY

MAU

PAS

PLA

JAK

CRD

NEL

CATFRI

POW

SHA

RED

WEE

COR

CAR

DET

MYCPOW

Fig. 4 Results from STRUCTURE runs of hierarchical K = 2 clustering of individuals within the northern clade of Uroctonus. Bold font

indicates the smallest cluster inferred with no discernable geographical clustering or comprised of only one locality.



Results indicated the K with the lowest BIC score for the

northern clade varied between 7 and 12 (mode = 9; BIC

scores = 299.0365–301.4418). The K with the lowest BIC

score for the southern clade varied between 9 and 15

(mode = 12; BIC scores = 316.5692–320.1720). The assign-

ment of localities and individuals to clusters was also

variable between runs of the same K. For example, runs

with the lowest BIC score of K = 9 for the southern clade

inconsistently grouped samples from several localities in

the Sierra Nevada (SPV, AVY, and BGP) in either individ-

ual clusters or together with geographically proximate

samples. A similar pattern was evident for several locali-

ties in the Coastal Range (e.g. GEY, PCY and MDB). At

higher values of K, samples from the same locality were

sometimes split into two independent clusters; in other

runs of the same K, these same samples were grouped

together along with samples from nearby areas. Spurious

clusters, oversplitting and instability between runs are

among the known confounding effects of isolation by dis

tance on nonspatial clustering methods (e.g. Frantz et al.

2009;Safner et al. 2011; Putman & Carbone 2014).

In contrast, iterative runs of k-means clustering on

data sets scaled down to the main geographical group-

ings within each clade yielded more consistent and bio-

logically reasonable results (Fig. 6) that were largely

congruent with results from STRUCTURE. Two of the main

geographical groups consisted of two localities each, the

northeastern Cascades + Oregon Coastal Range (MAU

and CTW) and the northeastern Sierra Nevada (BGP

and JNL). Results suggested the former consisted of

only one cluster, whereas the latter was split into two

clusters (BGP and JNL). One geographical group in the

southern clade (southern Coastal Range) consisted of

individuals from only one locality (SVE) and was not

analysed. In total, 15 clusters were identified within the

northern clade, and 12 clusters were identified within

the southern clade. Eight of the 15 clusters within the

northern clade matched clusters inferred with STRUCTURE.

JNLSONMDB

AVY

CAM

BGP

BRM

LAB

LAH

MGV

CAL

TEJ

BAL

SPV

WHP

SVE

GEY

PCY

SVE GEYPCY CALMGV LAHLAB MDB

SVE

GEY PCYCAL MGVLAH LABMDB

CAL MGVLAH LABMDB

LAH LABMDB

LAH MDB

LAH

MDB

LAB

CAL MGV

CAL

MGV

GEY PCY

GEY

PCY

TEJ SPVBRM WHPJNL BGPBAL CAMAVY SON

BAL CAMAVY SON

BAL

CAM AVYSON

CAM

AVY SON

AVY

SON

TEJ SPVBRM WHPJNL BGP

JNL

TEJ SPVBRM WHPBGP

WHP BGP

TEJ SPVBRM

SPV

TEJ BRM

TEJ

BRMSouthern Cladehierarchical K = 2 clustering

WHP

BGP

Fig. 5 Results from STRUCTURE runs of hierarchical K = 2 clustering of individuals within the southern clade of Uroctonus. Bold font

indicates the smallest cluster inferred with no discernable geographical clustering or comprised of only one locality.



Ten of the 12 clusters within the southern clade

matched clusters inferred with STRUCTURE. Differences

were attributable to ADEGENET splitting up the single

large cluster of admixed samples from the northwestern

Cascades and Oregon Coastal Range and lumping sev-

eral adjacent localities into single clusters.

Population migration

Results from MIGRATE-N revealed very little migration

among populations with three or more individuals, con-

sistent with findings of little to no admixture between

clusters inferred during hierarchical clustering in STRUC-

TURE. The estimated effective number of migrants per

generation (Nm) was <0.4 between all populations

except for two (Table S5, Supporting information). Both

of these populations were in the northwestern Cascades

and Oregon Coastal Range group and consisted of sam-

ples from seven localities across a large region of the

northwestern Cascades in southern Washington and

western Oregon and adjacent Coastal Range in one pop-

ulation, and samples from Myrtle Creek at the intersec-

tion of the Cascades and Oregon Coastal Range in the

second. In contrast, migration was lowest (Nm ≤ 0.15)

between the two populations of U. franckei in the north-

eastern Sierra Nevada group.

Species distribution modelling

The predicted current distributions for the northern

and southern clades of Uroctonus (Fig. 7) generally

matched their expected distributions (Fig. 3). How-

ever, predicted suitable habitat for the southern clade

included the distributional gap along the northern

Sierra Nevada between Red Bluff (RED) and Camino

(CAM; Fig. 1), and the Transverse Ranges in southern

California where the species is not known to occur.

There was little overlap between the predicted distri-

butions of the two clades, except for small regions of

northern California along the Coastal Range near the

Eel River drainage and along the northern Sierra

Nevada distributional gap. No evidence of genetic

mixing was detected between the northern and south-

ern clades in this area (Fig. 2). The contributions of

each variable to the predicted distributions for both

the northern and southern clades are listed in

Table S6 (Supporting information).

For both the northern and southern clades, the three

alternative historical reconstructed distributions based

on different GCMs were each in agreement (Fig. S3,

Supporting information), suggesting that the historical

reconstructions were robust to variations in the GCMs.

The predicted distribution of the northern clade at the

Nor

ther

n Cl

ade

Sout

hern

Cla

de

Northwestern Sierra NevadaSouthern Sierra NevadaNorthern Coastal Range

Southern Cascades + northeastern Coastal RangeKlamath MountainsNorthwestern Cascades + Oregon Coastal Range

ROG

CAR DET (1)CAT FRI

POW

MYC

CCL

COR DET WKY

STG

NEL WEE

JAK PAS

SHA

RED CRD

PLA

SON

AVY

CAM

BALTEJ BRM

SPV

WHP

PCY

GEY

CAL MGV LAH LAB MDB

Fig. 6 Discriminant analysis of principal components (DAPC) scatter plots showing genetic variation between clusters of Uroctonus

estimated using k-means clustering in ADEGENET. Each scatter plot shows the two first principal components of the DAPC and the

number of genetic clusters with the lowest Bayesian information criterion score within each geographical group. Not shown are the

geographical groups with only two localities, for which only a single discriminant function was retained (northeastern Sierra Nevada

and northeastern Cascades), and for the group comprised of only one locality (southern Coastal Range). Population locations are

shown in Fig. 1.



LGM was near the southern portion of their current dis-

tribution. The predicted historical distribution of south-

ern clade shifted slightly southward and inland (Fig. 7).

Both the northern and southern clade distribution mod-

els were well supported for both the training data

(AUC = 0.99 each) and the test data (AUC = 0.98 each).

Discussion

Ancient genetic divergences in forest scorpions acrossthe CFP

Results from our study suggest that the evolution of

California’s landscape dramatically affected the diversi-

fication of forest scorpions. We found that genetic

divergences in Uroctonus are remarkably fine-scaled and

ancient, consistent with the phylogeographies of other

low-dispersing species (Mart�ınez-Solano et al. 2007;

Hedin et al. 2013; Reilly & Wake 2015). Mountain uplift

caused by tectonic plate reorganizations in the Late

Miocene and Pliocene (Lock et al. 2006; Cassel et al.

2012) likely triggered this early diversification. These

ancient divergences suggest that populations have

remained in place for millions of years, in agreement

with our SDMs that predict general habitat stability

since the LGM 21 kya.

Based on our phylogenetic analyses, Uroctonus con-

tains two main clades that probably diverged during

the Late Miocene (Fig. 2). The geographical boundaries

of these clades in northern California (Figs 1 and 3) and

the inferred timing of their split implicate the develop-

ment and northward migration of the Mendocino Triple

Junction as a probable driver of this divergence. The

Mendocino Triple Junction was formed in the Early

Miocene around 27 Mya by the collision of three tec-

tonic plates along the Mendocino Fracture Zone (Fur-

long & Schwartz 2004; Lock et al. 2006; Gottscho 2016).

Following this collision, the Mendocino Triple Junction

began migrating northward. At around 8–5 Mya, it

accelerated and caused the uplift of the California

Coastal Range near the Eel River drainage (Lock et al.

2006; Fig. 1). Continued tectonic plate movements dur-

ing this time caused topographic uplift and valley inci-

sions along the Sierra Nevada (Wakabayashi & Sawyer

2001; Cassel et al. 2012), a long-standing topographic

feature since 16 Mya (Chamberlain & Poage 2000). At

around 2 Mya, the Eel River emerged as the primary

river draining the Coast Range (Lock et al. 2006), which

likely reinforced the separation of northern and south-

ern clades of Uroctonus. To the east, the Feather and

Yuba River drainages that deeply incised the Sierra

Nevada following uplift similarly reinforced separation.

Following the divergence of the northern and south-

ern clades, regional geographical groups within each

clade emerged. Within the southern clade, the develop-

ment of the Central Valley following Late Miocene and

Pliocene uplift (Huber 1981; Unruh 1991; Chamberlain

& Poage 2000) undoubtedly isolated Uroctonus on the

Coastal Range from populations along the Sierra

Nevada, as seen in the high percentage of codistributed

taxa across these mountain ranges (Rissler et al. 2006).

Across the Coastal Range, two groups north and south

of the San Francisco Bay separated sometime during the

Pliocene or Early Pleistocene (Fig. 2a). The geographical

group south of the Bay represents the subspecies

U. m. pluridens, a morphologically distinct subspecies

endemic to the Santa Cruz Mountains (Hjelle 1972; Sole-

glad & Fet 2004). The Santa Cruz Mountains formed

during a westward bend of the San Andreas Fault 2.8–5 Mya (Sarna-Wojcicki et al. 1985; Griscom & Jachens

1989; Dupr�e et al. 1991) and were subsequently isolated

when the Central Valley started draining into the San

Francisco Bay (Sarna-Wojcicki et al. 1985; Dupr�e et al.

1991). Around this same time, geographical groups of

Uroctonus in the Sierra Nevada to the east diverged

(Fig. 2a). The early divergence of Uroctonus in the

northwestern Sierra Nevada may have been caused by

restructuring and vertical rising of the San Joaquin

River following Pliocene uplift of the Sierra Nevada

(Wakabayashi & Sawyer 2001). The increased elevation

of the Sierra Nevada likely further isolated this group

from Uroctonus along the eastern slopes. Similarly,

sharp environmental gradients that developed along the

steep eastern slope after uplift may have caused the

subsequent Pliocene and Early Pleistocene separation of

Uroctonus in the southern Sierra Nevada from popula-

tions along the northeastern slopes of the Sierra

Nevada. These sharp gradients are reflected in the pre-

sent-day narrow sliver of predicted suitable habitat

along the eastern slopes of the Sierra Nevada (Fig. 7).

Divergences among the four geographical groups in

the northern clade of Uroctonus appear also to be

linked to regional uplift during Late Miocene and

Pliocene tectonic plate reorganizations. This uplift pro-

duced regional climate change and the development

of abrupt environmental transitions across the Cas-

cades and Oregon Coastal Range (Wolfe 1969; Nielson

et al. 2001). The early divergence of the group of

Uroctonus in the northeastern Cascades from the other

groups primarily west of the Cascades may have been

caused by a strong rain shadow effect created by the

increase in elevation across the Cascades (Graham

1999; Nielson et al. 2006). Current boundaries of the

remaining three geographical groups and the cave-

dwelling U. grahami are clustered around the Klamath

Mountains (Figs 1 and 3), a regional hotspot for verte-

brate endemism and diversity (Bury & Pearl 1999;

Rissler et al. 2006; Olson et al. 2012). Numerous



phylogeographical lineages of salamanders also meet

near the Klamath Mountains (Rissler et al. 2006;

Kuchta et al. 2009a; Reilly et al. 2013; Reilly & Wake

2015). Although these topographically complex moun-

tains formed well over 10 Mya, renewed Late

Miocene–Pliocene uplifting and restructuring of drai-

nages (Mortimer & Coleman 1985; Aalto 2006) may

have isolated Uroctonus in the Klamath Mountains

from nearby groups to the south and north (Fig. 3).

Emergent fine-scale endemism during the Pleistocene

Pleistocene climate cycles had a strong impact on the

geographical distribution and genetic structure of many

Nor

ther

n Cl

ade

Sout

hern

Cla

de

Current Last Glacial Maximum

1.00

0.75

0.50

0.25

0.00

1.00

0.75

0.50

0.25

0.00

1.00

0.75

0.50

0.25

0.00

1.00

0.75

0.50

0.25

0.00

Fig. 7 Species distribution models for the current and historical (Last Glacial Maximum, ca. 21 kya) predicted distributions of the

northern and southern clades of Uroctonus. Warmer colours indicate higher probability of occurrence as predicted using Maxent. Pre-

dicted distribution at the Last Glacial Maximum based on the CCSM4 general circulation model; see Fig. S3 (Supporting information)

for reconstructions with other models.



taxa in western North America (Knowles 2000; Johnson

& Cicero 2004; Shafer et al. 2010). Increases in the inten-

sity of glacial cycles during the Pleistocene repeatedly

fragmented, expanded and restructured species assem-

blages in the CFP (Raven & Axelrod 1978; Keeley &

Swift 1995; Minnich 2007). Our results reveal that strong

phylogeographical structure emerged within the

broader and more ancient genetic groups of Uroctonus

during the past 2 million years (Fig. 2a). Given the gen-

eral absence of clear geographical barriers between

these populations (Figs 4 and 5), most of this genetic

structure probably arose as a result of the episodic frag-

mentation of large tracts of woodland forest, as has

been suggested for other species (Schoville et al. 2012;

Devitt et al. 2013). Although it is generally accepted that

the climate of California was colder during Pleistocene

glacial periods, there is disagreement on whether or not

it was also wetter (Minnich 2007). Because of their poor

dispersal ability and reliance on a humid microhabitat,

populations of Uroctonus would have become more

fragmented during a colder, drier glacial climate.

Shrinking forested habitats during warmer interglacials

may have generated a patchwork of exposed drier

microhabitats, further limiting dispersal and isolating

populations. This mosaic of fragmented woodlands is

evident across the current interglacial distribution of

Uroctonus, especially in the southern part of their range.

Our SDMs support the hypothesis that in broadscale,

forest scorpion habitat has remained relatively stable

over the last 21 000 years (Fig. 7). This finding is consis-

tent with the genetic data which suggest these scorpi-

ons have remained in their current habitats for millions

of years, with ancient genetic divergences being congru-

ent with the development of ancient geological features.

The single exception is within the northern clade, where

our genetic data support a northern postglacial expan-

sion for one subgroup currently distributed across the

northwestern Cascades and adjacent Coastal Range.

Despite the large distributional range of this group,

genetic diversity is low and sequenced individuals

within this group form a large, relatively shallow clade

of admixed localities (Figs 2a, 3 and 4). Postglacial

expansion may have occurred from a refugial area in

northern California, a pattern both supported by our

SDMs (Fig. 7) and inferred for other regional taxa (e.g.

Steele & Storfer 2006; Reilly et al. 2013). The low topo-

graphical relief and cooler, humid climate throughout

the Willamette Valley of Oregon and adjacent foothills

could have enabled this rapid post-LGM expansion.

Microendemism and taxonomy

The combination of limited dispersal and microhabitat

preference of Uroctonus has created a spatial clumping

of populations across the CFP that is distinctly revealed

in the genetic structure of these scorpions. Based on our

results, Uroctonus exhibit strong hierarchical genetic

structure at sequentially smaller geographical scales.

Each major clade contains numerous geographical

groups, and each geographical group is comprised of

multiple distinct populations. In general, sequenced

individuals from nearly all sampled sites form mono-

phyletic genetic clusters (Figs 4–6). Several of these sites

are separated by <20 km. Migration rates among these

populations are also low, typically <0.4 migrants per

generation (Table S5, Supporting information).

Microendemism across the CFP has been found in a

number of other dispersal-limited species, particularly

salamanders (e.g. Mart�ınez-Solano et al. 2007; Kuchta

et al. 2009a; Reilly & Wake 2015) and arachnids (e.g.

Stockman & Bond 2007; Satler et al. 2011; Hedin et al.

2013; Emata & Hedin 2016). These taxa and Uroctonus

all appear to be moisture-sensitive microhabitat special-

ists. A reliance on a humid substrate combined with

their low dispersal has generated intricate patterns of

genetic fragmentation. The complex genetic architecture

contained within these species can reveal novel insight

into the formation of barriers to dispersal that led to

diversification (e.g. Hedin et al. 2013). Within Uroctonus,

we found evidence for divergences correlated with tec-

tonic plate rafting, mountain uplift, the evolution of

river drainages and habitat fragmentation. Although

these same historical events likely also affected higher-

dispersing codistributed species, the genetic footprint of

vicariance in these species may have eroded through

time during bouts of gene flow (Manthey et al. 2012).

The observed microendemism in Uroctonus presents a

challenge to the taxonomy of the genus. Our results

strongly suggest geography is a better predictor of phy-

logenetic relationships than the morphological charac-

ters mostly related to the metasoma previously used to

delineate species (Gertsch & Soleglad 1972; Hjelle 1972;

Soleglad & Fet 2004). Uroctonus mordax and Uroctonus

franckei are paraphyletic, and the cave-specialist Uroc-

tonus grahami is nested within the northern clade of

U. mordax (Fig. 2). Scorpions are characterized by a

notoriously conserved morphology (Sharma et al. 2015

and references therein), and future integrative research

is needed to develop a taxonomy that better reflects the

evolutionary history of Uroctonus. In practice, however,

delineating species boundaries in highly fragmented,

dispersal-limited taxa is operationally difficult, espe-

cially in the absence of any perceived morphological

differentiation. Studies of mygalomorph spiders (e.g.

Satler et al. 2011; Hedin et al. 2015) highlight the inher-

ent need to incorporate population structure as a

parameter in multispecies coalescent methods for highly

fragmented systems with extremely low gene flow



among allopatric populations. Such a methodology may

become a powerful tool for species delimitation in Uroc-

tonus and other microendemic species. Iterative sam-

pling across sampling gaps will also be important to

assess potential contact zones and refine gene flow esti-

mates (Hedin et al. 2013).

Our results also highlight the need to cautiously inter-

pret phylogenetic relationships in scorpions recon-

structed from mtDNA. Although mtDNA has been the

workhorse for phylogeographical and phylogenetic anal-

yses of scorpions for over two decades, mtDNA recombi-

nation and selective sweeps caused by maternally

inherited bacterial endosymbionts can result in anoma-

lous mtDNA gene trees for scorpions (Bryson 2014). Phy-

logenetic relationships inUroctonus inferred from the CO1

gene differ from those based on 497 RAD loci and over

900 unlinked SNPs (Fig. 2). This suggests that mtDNA

may be tracking a different and anomalous evolutionary

history inconsistent with population- / species-level

divergences in these scorpions. Future phylogeographic

studies of scorpions should be aware of the varied

stochastic processes affecting the mitochondrial genome

and employ a multilocus approach to estimate phyloge-

nies.

Acknowledgements

For assistance in the field and for providing specimens, we thank

D. Clayton, A. Silva, R. Demmer, B. L. Rust, T. E. Johnson, D.

Young, L. Henderson, M. A. Bryson, S. E. Bryson, M. R. Graham,

R. W. Hansen, M. Olenchalk, J. Shedd, R. Schneider, E. Connors

and S. Walker. For other help with the project, we thank C. J. Bat-

tey, P. Beerli, R. Crawford, M. Harvey, J. Klicka, and the Klicka

and Leach�e Labs at UW. Three anonymous reviewers provided

helpful comments that greatly improved the final manuscript.

This work used the Vincent J. Coates Genomics Sequencing Lab-

oratory at UC Berkeley, supported by NIH S10 Instrumentation

Grants S10RR029668 and S10RR027303.

References

Aalto KR (2006) The Klamath peneplain: a review of J.S. Dil-

ler’s classic erosion surface. Geological Society of America Spe-

cial Papers, 410, 451–463.Arnold B, Corbett-Detig RB, Hartl D, Bomblies K (2013) RAD-

seq underestimates diversity and introduces genealogical

biases due to nonrandom haplotype sampling. Molecular

Ecology, 22, 3179–3190.Bacon AD (1972) Ecological studies on a population of Uroctonus

mordax Thorell. M.A. thesis, San Francisco State University,

California.

Baldwin BG (2014) Origins of plant diversity in the California

Floristic Province. Annual Review of Ecology, Evolution, and

Systematics, 45, 347–369.Beerli P (2006) Comparison of Bayesian and maximum likeli-

hood inference of population genetic parameters. Bioinformat-

ics, 22, 341–345.

Beerli P, Felsenstein J (2001) Maximum likelihood estimation of

a migration matrix and effective population sizes in n sub-

populations by using a coalescent approach. Proceedings of

the National Academy of Sciences of the United States of America,

98, 4563–4568.Blair C, Weigel D, Balazik M et al. (2012) A simulation-based

evaluation of methods for inferring linear barriers to gene

flow. Molecular Ecology Resources, 12, 822–833.Bouckaert RR (2010) DensiTree: making sense of sets of phylo-

genetic trees. Bioinformatics, 26, 1372–1373.Bouckaert R, Heled J, K€uhnert D et al. (2014) BEAST 2: a soft-

ware platform for Bayesian evolutionary analysis. PLOS

Computational Biology, 10, e1003537.

Bryant D, Bouckaert R, Felsenstein J, Rosenberg NA,

RoyChoudhury A (2012) Inferring species trees directly from

biallelic genetic markers: bypassing gene trees in a full coa-

lescent analysis. Molecular Biology & Evolution, 29, 1917–1932.Bryson RW (2014) Bacterial endosymbiont infections in ‘living

fossils’: a case study of North American vaejovid scorpions.

Molecular Ecology Resources, 14, 789–793.Bryson RW, Riddle BR, Graham MR, Smith BT, Prendini L

(2013) As old as the hills: montane scorpions in southwest-

ern North America reveal ancient associations between biotic

diversification and landscape history. PLoS ONE, 8, e52822.

Bury RB, Pearl CA (1999) The Klamath-Siskiyou herpetofauna:

biogeographic patterns and conservation strategies. Natural

Areas Journal, 19, 341–348.Calsbeek R, Thompson JN, Richardson JE (2003) Patterns of

molecular evolution and diversification in a biodiversity hot-

spot: the California Floristic Province. Molecular Ecology, 12,

1021–1029.Cassel EJ, Graham SA, Chamberlain CP, Henry CD (2012)

Early Cenozoic topography, morphology, and tectonics of

the northern Sierra Nevada and western Basin and Range.

Geosphere, 8, 229–249.Chamberlain CP, Poage MA (2000) Reconstructing the paleoto-

pography of mountain belts from the isotopic composition of

authigenic minerals. Geology, 28, 115–118.Conservation International (2011). Biological diversity in the Cali-

fornia Floristic Province. Retrieved from http://

www.eoearth.org/view/article/150634 (Accessed 5 August

2015).

Coulon A, Fitzpatrick JW, Bowman R et al. (2008) Congruent

population structure inferred from dispersal behaviour and

intensive genetic surveys of the threatened Florida scrub-jay

(Aphelocoma coerulescens). Molecular Ecology, 17, 1685–1701.Crawford RL (1990) Discovery of Uroctonus mordax Thorell in

Washington, with notes on habitat and distribution (Scorpi-

onida, Vaejovidae). Pan-Pacific Entomologist, 66, 254–255.Darriba D, Taboada GL, Doallo R, Posada D (2012) jModelTest

2: more models, new heuristics and parallel computing. Nat-

ure Methods, 9, 772.

Devitt T, Cameron Devitt S, Hollingsworth B, McGuire J, Mor-

itz C (2013) Montane refugia predict population genetic

structure in the Large-blotched Ensatina Salamander. Molecu-

lar Ecology, 22, 1650–1665.Drummond AJ, Suchard MA, Xie D, Rambaut A (2012) Baye-

sian phylogenetics with BEAUti and the BEAST 1.7. Molecu-

lar Biology & Evolution, 29, 1969–1973.Dupr�e WR, Morrison RB, Clifton HE et al. (1991) Quaternary

geology of the Pacific margin. In: The Geology of North



http://www.eoearth.org/view/article/150634

http://www.eoearth.org/view/article/150634

America, Vol. K-2, Quaternary Nonglacial Geology: Conterminous

U.S (ed. Morrison RB), pp. 141–214. Geological Society of

America, Boulder, Colorado.

Earl DA, vonHoldt BM (2012) STRUCTURE HARVESTER: a

website and program for visualizing STRUCTURE output

and implementing the Evanno method. Conservation Genetics

Resources, 4, 359–361.Eaton DAR (2014) PyRAD: assembly of de novo RADseq loci

for phylogenetic analyses. Bioinformatics, 30, 1844–1849.Eaton DAR, Ree RH (2013) Inferring phylogeny and introgres-

sion using RADseq data: an example from flowering plants

(Pedicularis: Orobanchaceae). Systematic Biology, 62, 689–706.Edgar RC (2004) MUSCLE: multiple sequence alignment with

high accuracy and high throughput. Nucleic Acids Research,

32, 1792–1797.Edgar RC (2010) Search and clustering orders of magnitude

faster than BLAST. Bioinformatics, 26, 2460–2461.Edwards S, Bensch S (2009) Looking forwards or looking back-

wards in avian phylogeography? A comment on Zink and

Barrowclough 2008. Molecular Ecology, 18, 2930–2933.Emata KN, Hedin M (2016) From the mountains to the coast

and back again: ancient biogeography in a radiation of short-

range endemic harvestmen from California. Molecular Phylo-

genetics and Evolution, 98, 233–243.Evanno G, Regnaut S, Goudet J (2005) Detecting the number of

clusters of individuals using the software STRUCTURE: a

simulation study. Molecular Ecology, 14, 2611–2620.Faircloth BC, Glenn TC (2014) Protocol: Preparation of an AMPure

XP substitute (AKA Serapure). doi: 10.6079/J9MW2F26.

Falush D, Stephens M, Pritchard JK (2003) Inference of popula-

tion structure using multilocus genotype data: linked loci

and correlated allele frequencies. Genetics, 164, 1567–1587.Falush D, Stephens M, Pritchard JK (2007) Inference of popula-

tion structure using multilocus genotype data: dominant

markers and null alleles. Molecular Ecology Notes, 7, 574–578.Frantz AC, Cellina S, Krier A, Schley L, Burke T (2009) Using

spatial Bayesian methods to determine the genetic structure

of a continuously distributed population: clusters or isolation

by distance? Journal of Applied Ecology, 46, 493–505.Funk D, Omland K (2003) Species-level paraphyly and poly-

phyly: frequency, causes, and consequences, with insights

from animal mitochondrial DNA. Annual Review of Ecology

and Evolutionary Systematics, 34, 397–423.Furlong KP, Schwartz SY (2004) Influence of the Mendocino

triple junction on the tectonics of coastal California. Annual

Review of Earth and Planetary Sciences, 32, 403–433.Gantenbein B, Keightley PD (2004) Rates of molecular evolu-

tion in nuclear genes of East Mediterranean scorpions. Evolu-

tion, 58, 2486–2497.Gantenbein B, Fet V, Gantenbein-Ritter IA, Balloux F (2005)

Evidence for recombination in scorpion mitochondrial DNA

(Scorpiones: Buthidae). Proceedings of the Royal Society B, Bio-

logical Sciences, 272, 697–704.Gertsch WJ, Soleglad ME (1972) Studies of North American

scorpions of the genera Uroctonus and Vejovis (Scorpionida,

Vejovidae). Bulletin American Museum of Natural History, 148,

549–608.Gottscho AD (2016) Zoogeography of the San Andreas Fault

system: Great Pacific Fracture Zones correspond with spa-

tially concordant phylogeographic boundaries in western

North America. Biological Reviews, 91, 235–254.

Gowen FC, Maley JM, Cicero C et al. (2014) Speciation in Wes-

tern Scrub-Jays, Haldane’s rule, and genetic clines in sec-

ondary contact. BMC Evolutionary Biology, 14, 135.

Graham A (1999) Late Cretaceous and Cenozoic History of North

American Vegetation. Oxford University Press, New York.

Graham MR, Jaeger JR, Prendini L, Riddle BR (2013a) Phylo-

geography of Beck’s Desert Scorpion, Paruroctonus becki,

reveals Pliocene diversification in the Eastern California

Shear Zone and postglacial expansion in the Great Basin

Desert. Molecular Phylogenetics and Evolution, 69, 502–513.Graham MR, Jaeger JR, Prendini L, Riddle BR (2013b) Phylo-

geography of the Arizona hairy scorpion (Hadrurus arizonen-

sis) supports a model of biotic assembly in the Mojave

Desert and adds a new Pleistocene refugium. Journal of Bio-

geography, 40, 1298–1312.Griscom A, Jachens RC (1989) Tectonic history of the north

portion of the San Andreas fault system, California, inferred

from gravity and magnetic anomalies. Journal of Geophysical

Research, 94, 3089–3099.Guindon S, Gascuel O (2003) A simple, fast and accurate

method to estimate large phylogenies by maximum-likeli-

hood. Systematic Biology, 52, 696–704.Hedin M, Starrett J, Hayashi C (2013) Crossing the uncrossable:

novel trans-valley biogeographic patterns revealed in the

genetic history of low dispersal mygalomorph spiders

(Antrodiaetidae, Antrodiaetus) from California. Molecular Ecol-

ogy, 22, 508–526.Hedin M, Carlson D, Coyle F (2015) Sky island diversification

meets the multispecies coalescent – divergence in the spruce-

fir moss spider (Microhexura montivaga, Araneae, Mygalomor-

phae) on the highest peaks of southern Appalachia. Molecular

Ecology, 24, 3467–3484.Herbert TD, Schuffert JD, Andreasen D et al. (2001) Collapse of

the California current during glacial maxima linked to cli-

mate change on land. Science, 293, 71–76.Hickerson MJ, Carstens BC, Cavender-Bares J et al. (2010) Phy-

logeography’s past, present, and future: 10 years after Avise

2000. Molecular Phylogenetics and Evolution, 54, 291–301.Hijmans RJ, Cameron SE, Parra JL, Jones PG, Jarvis A (2005)

Very high resolution interpolated climate surfaces for global

land areas. International Journal of Climatology, 25, 1965–1978.

Hjelle JT (1972) Scorpions of the Northern Californian coast

ranges. Occasional Papers of the California Academy of Sciences,

92, 1–59.Huang H, Knowles LL (2016) Unforeseen consequences of

excluding missing data from next-generation sequences: sim-

ulation study of RAD sequences. Systematic Biology, 65, 357–365.

Huber NK (1981) Amount and timing of late Cenozoic uplift and

tilt of the central Sierra Nevada, California—evidence from the

upper San Joaquin River basin. U.S. Geological Survey Profes-

sional Paper, 1197, 1–28.Johnson NK, Cicero C (2004) New mitochondrial DNA data

affirm the importance of Pleistocene speciation in North

American birds. Evolution, 58, 1122–1130.Jombart T, Ahmed I (2011) Adegenet 1.3-1: new tools for the

analysis of genome-wide SNP data. Bioinformatics, 27, 3070–3071.

Keeley JE, Swift CC (1995) Biodiversity and ecosystem func-

tioning in Mediterranean climate California. In: Biodiversity

and Function in Mediterranean-Type Ecosystems (eds Davis



http://dx.doi.org/10.6079/J9MW2F26

GW, Richardson DM), pp. 121–183. Springer, New York,

New York.

Knowles LL (2000) Tests of Pleistocene speciation in montane

grasshoppers (genus Melanoplus) from the sky islands of

Western North America. Evolution, 54, 1337–1348.Kuchta SR, Parks DS, Wake DB (2009a) Pronounced phylogeo-

graphic structure on a small spatial scale: geomorphological

evolution and lineage history in the salamander ring species

Ensatina eschscholtzii in central coastal California. Molecular

Phylogenetics and Evolution, 50, 240–255.Kuchta SR, Parks DS, Mueller RL, Wake DB (2009b) Closing

the ring: historical biogeography of the salamander ring spe-

cies Ensatina eschscholtzii. Journal of Biogeography, 36, 982–995.Lambert SM, Geneva AJ, Mahler DL, Glor RE (2013) Using

genomic data to revisit an early example of reproductive

character displacement in Haitian Anolis lizards. Molecular

Ecology, 22, 15.

Lapointe FJ, Rissler LJ (2005) Congruence, consensus, and the

comparative phylogeography of codistributed species in Cal-

ifornia. American Naturalist, 166, 290–299.Leach�e AD, Fujita MK, Minin VN, Bouckaert R (2014) Species

delimitation using genome-wide SNP data. Systematic Biol-

ogy, 63, 534542.

Leavitt DH, Bezy RL, Crandal KA, Sites JW Jr (2007) Multi-

locus DNA sequence data reveal a history of deep cryptic

vicariance and habitat-driven convergence in the desert night

lizard Xantusia vigilis species complex (Squamata: Xantusi-

idae). Molecular Ecology, 16, 4455–4481.Levy E, Kennington WJ, Tomkins JL, LeBas NR (2012) Phylo-

geography and population genetic structure of the ornate

dragon lizard, Ctenophorus ornatus. PLoS ONE, 7, e46351.

Lock J, Kelsey H, Furlong K, Woolace A (2006) Late Neogene

and quaternary landscape evolution of the northern California

Coast Ranges: evidence for Mendocino triple junction tecton-

ics. Geological Society of America Bulletin, 118, 1232–1246.Manthey JD, Klicka J, Spellman GM (2012) Is gene flow pro-

moting the reversal of Pleistocene divergence in the Moun-

tain Chickadee (Poecile gambeli)? PLoS ONE, 7, e49218.

Mart�ınez-Solano I, Jockusch EL, Wake DB (2007) Extreme pop-

ulation subdivision throughout a continuous range: phylo-

geography of Batrachoseps attenuatus (Caudata:

Plethodontidae) in western North America. Molecular Ecol-

ogy, 16, 4335–4355.Miller MA, Pfeiffer W, Schwartz T (2010) Creating the CIPRES

Science Gateway for inference of large phylogenetic trees. In:

Proceedings of the Gateway Computing Environments Workshop

(GCE), pp. 1–8. New Orleans, Louisiana.

Minnich RA (2007) California climate, paleoclimate and pale-

ovegetation. In: Terrestrial Vegetation of California (eds Bar-

bour MG, Keeler-Wolf T, Schoenherr AA), pp. 43–70.University of California Press, Berkeley, California.

Mortimer N, Coleman RG (1985) A Neogene structural dome

in the Klamath Mountains, California. Geology, 13, 253–256.Myers N, Mittermeier RA, Mittermeier CG, Da Fonseca GAB,

Kent J (1999) Biodiversity hotspots for conservation priori-

ties. Nature, 403, 853–858.Myers EA, Rodriguez-Robles JA, Denardo DF et al. (2013) Mul-

tilocus phylogeographic assessment of the California Moun-

tain Kingsnake (Lampropeltis zonata) suggests alternative

patterns of diversification for the California Floristic Pro-

vince. Molecular Ecology, 22, 5418–5429.

Nielson M, Lohman K, Sullivan J (2001) Phylogeography of the

tailed frog (Ascaphus truei): implications for the biogeography

of the Pacific Northwest. Evolution, 55, 147–160.Olson D, DellaSala DA, Noss RF et al. (2012) Climate change

refugia for biodiversity in the Klamath-Siskiyou ecoregion.

Natural Areas Journal, 32, 65–74.Papadopoulou A, Knowles LL (2015) Genomic tests of the spe-

cies-pump hypothesis: recent island connectivity cycles drive

divergence in Caribbean crickets across the Virgin Islands.

Evolution, 69, 1501–1517.Parham JF, Papenfuss TJ (2009) High genetic diversity among

fossorial lizard populations (Anniella pulchra) in a rapidly

developing landscape (Central California). Conservation

Genetics, 10, 169–176.Peterson BK, Weber JN, Kay EH, Fisher HS, Hoekstra HE

(2012) Double digest RADseq: an inexpensive method for de

novo SNP discovery and genotyping in model and non-

model species. PLoS ONE, 7, e37135.

Phillips SJ, Anderson RP, Schapire RE (2006) Maximum

entropy modeling of species geographic distributions. Ecolog-

ical Modelling, 190, 231–259.Polihronakis M, Caterino MS (2010) Multilocus phylogeogra-

phy of the flightless darkling beetle Nyctoporis carinata

(Coleoptera: Tenebrionidae) in the California Floristic Pro-

vince: deciphering an evolutionary mosaic. Biological Journal

of the Linnaean Society, 99, 424–444.Polihronakis M, Caterino MS, Chatzimanolis S (2010) Elucidat-

ing the phylogeographic structure among a mosaic of unisex-

ual and bisexual populations of the weevil Geodercodes

latipennis (Coleoptera: Curculionidae) in the Transverse

Ranges of southern California. Biological Journal of the Lin-

naean Society, 101, 935–948.Polis GA (1990) Ecology. In: The Biology of Scorpions (ed. Polis GA),

pp. 247–293. Stanford University Press, Stanford, California.

Prendini L, Wheeler WC (2005) Scorpion higher phylogeny

and classification, taxonomic anarchy, and standards for peer

review in online publishing. Cladistics, 21, 446–494.Pritchard JK, Stephens M, Donnelly P (2000) Inference of population

structure usingmultilocus genotype data.Genetics, 155, 945–959.Pritchard JK, Wen W, Falush D (2010) Documentation for

STRUCTURE software: Version 2.3. Available from http://

pritch.bsd.uchicago.edu.

Putman AI, Carbone I (2014) Challenges in analysis and inter-

pretation of microsatellite data for population genetic stud-

ies. Ecology & Evolution, 4, 4399e4428.

R Development Core Team (2013) R: A Language and Environ-

ment for Statistical Computing. R Foundation for Statistical

Computing, Vienna, Austria.

R Development Core Team (2014) R: A Language and Environ-

ment for Statistical Computing. R Foundation for Statistical

Computing, Vienna, Austria.

Rambaut A, Drummond AJ (2007) Tracer v1.4. Available from

http://beast.bio.ed.ac.uk/Tracer

Ravelo AC, Lyle M, Koizumi I et al. (1997) Pliocene carbonate

accumulation along the California margin. Paleoceanography,

12, 729–741.Raven PH, AxelrodDI (1978) Origin and relationships of the Califor-

nia flora.University of California Publications in Botany, 72, 1–134.Reilly SB, Wake DB (2015) Cryptic diversity and biogeographic

patterns within the black salamander (Aneides flavipunctatus)

complex. Journal of Biogeography, 42, 280–291.



http://pritch.bsd.uchicago.edu

http://pritch.bsd.uchicago.edu

http://beast.bio.ed.ac.uk/Tracer

Reilly SB, Mulks MF, Reilly JM, Jennings WB, Wake DB (2013)

Genetic diversity of Black Salamanders (Aneides flavipuncta-

tus) across watersheds in the Klamath Mountains. Diversity,

5, 657–679.Rissler LJ, Hijmans RJ, Graham CH, Moritz C, Wake DB (2006)

Phylogeographic lineages and species comparisons in conser-

vation analyses: a case study of California herpetofauna. The

American Naturalist, 167, 655–666.Rodr�ıguez-Robles JA, Denardo DF, Staub RE (1999) Phylogeog-

raphy of the California mountain king snake, Lampropeltis

zonata (Colubridae). Molecular Ecology, 8, 1923–1934.Rohland N, Reich D (2012) Cost-effective, high-throughput

DNA sequencing libraries for multiplexed target capture.

Genome Research, 22, 939–946.Rubin BER, Ree RH, Moreau CS (2012) Inferring phylogenies

from RAD sequence data. PLoS ONE, 7, e33394.

Safner T, Miller MP, McRae BH, Fortin MJ, Manel S (2011)

Comparison of Bayesian clustering and edge detection meth-

ods for inferring boundaries in landscape genetics. Interna-

tional Journal Molecular Science, 12, 865–889.Sarna-Wojcicki AM, Meyer CE, Bowman HR et al. (1985) Corre-

lation of the Rockland ash bed, a 400,000-year-old strati-

graphic marker in northern California and western Nevada

and implications for middle Pleistocene paleogeography of

central California. Quaternary Research, 23, 236–257.Satler J, Starrett J, Hayashi C, Hedin M (2011) Inferring species trees

from gene trees in a radiation of California trapdoor spiders (Ara-

neae, Antrodiaetidae,Aliatypus).PLoSONE, 6, e25355.

Satler JD, Carstens BC, Hedin M (2013) Multilocus species

delimitation in a complex of morphologically conserved trap-

door spiders (Mygalomorphae, Antrodiaetidae, Aliatypus).

Systematic Biology, 62, 805–823.Schoville SD, Roderick GK, Kavanaugh DH (2012) Testing the

‘Pleistocene species pump’ in alpine habitats: lineage diversi-

fication of flightless ground beetles (Coleoptera: Carabidae:

Nebria) in relation to altitudinal zonation. Biological Journal of

the Linnean Society, 107, 95–111.Shafer ABA, Cullingham CI, Cot�e SD, Coltman DW (2010) Of

glaciers and refugia: a decade of study sheds new light on

the phylogeography of northwestern North America. Molecu-

lar Ecology, 19, 4589–4621.Shaffer HB, Fellers GM, Voss SR, Oliver JC, Pauly GB (2004)

Species boundaries, phylogeography and conservation genet-

ics of the red-legged frog (Rana aurora/draytonii) complex.

Molecular Ecology, 13, 2667–2677.Sharma PP, Fern�andez R, Esposito L, Gonz�alez-Santill�an E,

Monod L (2015) Phylogenomic resolution of scorpions

reveals multilevel discordance with morphological phyloge-

netic signal. Proceedings of the Royal Society of London B, Bio-

logical Sciences, 282, 2014–2953.Sissom WD (2000) Family Vaejovidae. In: Catalog of the Scorpi-

ons of the World (1758-1997) (eds Fet V, Sissom WD, Lowe G,

Braunwalder M), pp. 503–553. New York Entomological Soci-

ety, New York.

Sissom WD, Reddell JR (2009) Cave scorpions of Mexico and

the United States [Escorpiones de cuevas de M�exico y Esta-

dos Unidos]. Texas Memorial Museum, Speleological Monograph,

7, 19–32.Soleglad ME, Fet V (2003) High-level systematics and phy-

logeny of the extant scorpions (Scorpiones: Orthosterni). Eus-

corpius, 11, 1–175.

Soleglad ME, Fet V (2004) The systematics of the scorpion sub-

family Uroctoninae (Scorpiones: Chactidae). Revista Ib�erica de

Aracnolog�ıa, 10, 81–128.Song S, Liu L, Edwards SV, Wu S (2012) Resolving conflict in

eutherian mammal phylogeny using phylogenomics and the

multispecies coalescent model. Proceedings of the National Acad-

emy of Sciences of the United States of America, 109, 14942–14947.Stahnke HL (1974) Revision and keys to the higher categories

of Vejovidae. Journal of Arachnology, 1, 107–141.Starrett J, Hedin M (2007) Multilocus geneologies reveal multi-

ple cryptic species and biogeographical complexity in the

California turret spider Antrodiaetus riversi (Mygalomorphae,

Antrodiaetidae). Molecular Ecology, 16, 583–604.Steele CA, Storfer A (2006) Coalescent-based hypothesis testing

supports multiple Pleistocene refugia in the Pacific North-

west for the Pacific giant salamander (Dicamptodon tenebro-

sus). Molecular Ecology, 15, 2477–2487.Stockman AK, Bond JE (2007) Delimiting cohesion species:

extreme population structure and the role of ecological inter-

changeability. Molecular Ecology, 16, 3374–3392.Stockwell SA (1989) Revision of the phylogeny and higher classifi-

cation of Scorpions (Chelicerata). Ph.D. dissertation, University

of California, Berkeley.

Streicher JW, Devitt TJ, Goldberg CS, Malone JH, Blackmon H,

Fujita MK (2014) Diversification and asymmetrical gene flow

across time and space: lineage sorting and hybridization in

polytypic barking frogs. Molecular Ecology, 2, 3273–3291.Streicher JW, Schulte JA II, Wiens JJ (2016) How should genes

and taxa be sampled for phylogenomic analyses with miss-

ing data? An empirical study in iguanian lizards. Systematic

Biology, 65, 128–145.UNEP-WCMC (United Nations Environment Programme-

World Conservation Monitoring Centre) (2013) Centres of

plant diversity. In: Version 1.0 (Digital Reproduction of Centres

of Plant Diversity. 1994–1997) (eds Davis SD, Heywood VH,

Hamilton AC), World Wildlife Fund and IUCN, Gland,

Switzerland.

Unruh J (1991) The uplift of the Sierra Nevada and implica-

tions for late Cenozoic epeirogeny in the western Cordillera.

Geological Society of America Bulletin, 103, 1395–1404.Varela S, Lima-Ribeiro MS, Terribile LC (2015) A short guide

to the climatic variables of the Last Glacial Maximum for

biogeographers. PLoS ONE, 10, e0129037.

Wagner CE, Keller I, Wittwer S et al. (2013) Genome-wide

RAD sequence data provide unprecedented resolution of

species boundaries and relationships in the Lake Victoria

cichlid adaptive radiation. Molecular Ecology, 22, 787–798.Wakabayashi J, Sawyer TL (2001) Stream incision, tectonics,

uplift, and evolution of topography of the Sierra Nevada,

California. Journal of Geology, 109, 539–562.Waples RS, Gaggiotti O (2006) What is a population? An

empirical evaluation of some genetic methods for identifying

the number of gene pools and their degree of connectivity.

Molecular Ecology, 15, 1419–1439.Warren DL, Seifert SN (2011) Ecological niche modeling in

Maxent: the importance of model complexity and the perfor-

mance of model selection criteria. Ecological Applications, 21,

335–342.Williams SC (1986) A new species of Uroctonus from the Sierra

Nevada of California (Scorpiones: Vaejovidae). Pan-Pacific

Entomologist, 62, 359–362.



Williams SC, Savary WE (1991) Uroctonites, a new genus of

scorpion from Western North America (Scorpiones: Vaejovi-

dae). Pan-Pacific Entomologist, 67, 272–287.Wolfe JA (1969) Neogene floristic and vegetational history of

the Pacific Northwest. Madro~no, 20, 83–110.Xi Z, Liu L, Rest JS, Davis CC (2014) Coalescent versus con-

catenation methods and the placement of Amborella as sister

to water lilies. Systematic Biology, 63, 919–932.Yamashita T, Rhoads DD (2013) Species delimitation and mor-

phological divergence in the scorpion Centruroides vittatus

(Say, 1821): insights from phylogeography. PLoS ONE, 8,

e68282.

R.W.B., W.E.S. and J.E.M. designed the research; R.W.B.

and R.B.B. acquired the samples; R.W.B. generated the

genetic data; R.W.B. and A.J.Z. analysed the data;

R.W.B. led the writing. All authors contributed to the

text and approved the final manuscript.

Data accessibility

DNA sequences: Aligned data sets deposited in Dryad

(doi:10.5061/dryad.58sn8) and CO1 sequences depos-

ited in GenBank (Accession nos. KX171074–KX171153).Sampling locations and additional individuals included

in SDMs are uploaded as online Supporting

Information.

Supporting information

Additional supporting information may be found in the online ver-

sion of this article.

Fig. S1 Plot showing missing data across the complete data

matrix of 192 samples of Uroctonus.

Fig. S2 Larger versions of Bayesian phylogenetic trees shown

in Fig. 2.

Fig. S3 Historical reconstructed distributions with alternative

GCMs for the Last Glacial Maximum.

Table S1 Collection locality data for genetic samples of Uroc-

tonus used in this study and deposited in the California Acad-

emy of Sciences Entomological Collection.

Table S2 GPS points used for building species distribution

models for each clade of Uroctonus.

Table S3 Summary of climatic and landscape variables utilized

in the construction of species distribution models.

Table S4 Summary of ddRADseq data in the final assembly of

191 samples of Uroctonus.

Table S5 Estimated effective number of migrants per genera-

tion (Nm) between populations within each of the major geo-

graphical groups of Uroctonus (see Fig. 2).

Table S6 Percent contribution and permutation importance for

each variable used to construct the species distribution models

for the northern and southern clades of Uroctonus.



http://dx.doi.org/10.5061/dryad.58sn8



genomic data reveal ancient microendemism in forest ... data reveal ancient microendemism in forest...

Documents