Phylogeography of Peromyscus schmidlyi : an endemic of the Sierra Madre...

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Phylogeography of Peromyscus schmidlyi: an endemic of the Sierra MadreOccidental, MexicoAuthor(s): Celia López-González , Miguel M. Correa-Ramírez , and Diego F. García-MendozaSource: Journal of Mammalogy, 95(2):254-268. 2014.Published By: American Society of MammalogistsDOI: http://dx.doi.org/10.1644/13-MAMM-A-166URL: http://www.bioone.org/doi/full/10.1644/13-MAMM-A-166

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Journal of Mammalogy, 95(2):254–268, 2014

Phylogeography of Peromyscus schmidlyi: an endemic of the SierraMadre Occidental, Mexico

CELIA LOPEZ-GONZALEZ,* MIGUEL M. CORREA-RAMIREZ, AND DIEGO F. GARCIA-MENDOZA

Centro de Interdisciplinario de Investigacion para el Desarrollo Integral Regional (CIIDIR) Unidad Durango, InstitutoPolitecnico Nacional, Sigma 119 Fraccionamiento 20 de Noviembre II Durango, Durango 34220, Mexico

* Correspondent: [email protected]

Peromyscus schmidlyi is an endemic rodent from the forested highlands of the Sierra Madre Occidental (SMO)

in Mexico. Using 2 genetic markers (cytochrome-b and D-loop) we explored the possible relationship between a

recently proposed division of pine–oak forests of the SMO into specific regional communities and patterns of

genetic and morphometric variation in P. schmidlyi. We found no genetic structure or significant relationships

between either marker and ecological or morphometric variation. Phylogenetic and haplotypic network analyses

revealed no geographically structured clusters; phylogenetic trees were shallow and networks were star-shaped.

No signal of selection was detected for either marker at the local level. All available evidence suggests that the

current distribution of P. schmidlyi is the result of dispersal into the SMO followed by rapid population

expansion throughout the area in the late Pleistocene, following the glacial cooling of the SMO highlands.

Key words: gene flow, historic demography, mitochondrial DNA, phylogeny, pine–oak forests, Schmidly’s deer mouse

� 2014 American Society of Mammalogists

DOI: 10.1644/13-MAMM-A-166

Schmidly’s deermouse (Peromyscus schmidlyi) is a common

rodent distributed throughout the highlands of the Sierra Madre

Occidental (SMO) in Mexico. Its description, based on

molecular and karyotypic data (Bradley et al. 2004), and

further morphological characterization (Lopez-Gonzalez et al.

2013), resolved a number of issues regarding the identity of

several specimens previously collected from the western slope

of the SMO, and explained some of the observed patterns of

variation in ‘‘Peromyscus boylii’’ from the SMO (e.g., Drake

1958; Baker and Greer 1962; Lee et al. 1972; Schmidly and

Schroeter 1974; Alvarez and Polaco 1984; Bradley et al. 2004).

The currently known distribution of this species spans from

north-central Chihuahua and eastern Sonora to Zacatecas and

northern Jalisco (Ordonez-Garza and Bradley 2011; Lopez-

Gonzalez et al. 2013; Fig. 1).

The SMO spans more than 1,200 km from northwest to

southeast, covering approximately 108 of latitude (roughly

from 218N to 30.58N), and more than 200 km in width. The

highlands are covered with an assortment of plant associations

where the physiognomically dominant elements are conifers,

mainly pines (Pinus), and oaks (Quercus). In general, Mexican

pine–oak communities are extremely diverse and exhibit a very

high degree of endemism. They are home to approximately

44% and 30% of the world’s pine and oak species, respectively

(Little 1971, 1976, 1977). In particular, the SMO harbors at

least 24 species of pines (Pinus, 46% of the Mexican species),

54 oaks (Quercus, 34%), and 7 madrones (Arbutus, 100%—

Gonzalez-Elizondo et al. 2012). These forests also contain the

highest floristic diversity in Mexico (Rzedowski 1978; Bye

1995), in part because of the large size of the mountain range,

and in part because it is located at the confluence of tropical

and semiarid biomes (Gonzalez-Elizondo et al. 2012).

Recently, based on vegetation data, Gonzalez-Elizondo et al.

(2013) classified the SMO into 7 major ecological regions (Fig.

1). P. schmidlyi occurs in the highlands, in the 3 regions where

pine and oak associations dominate. The 1st and northernmost

region is the Madrean-North region, including eastern Sonora

and western Chihuahua south to the Urique canyon (between

278N and 288N). With a mean elevation of 2,350 m, this region

has colder and more continental climates than the rest of the

SMO. The pine Pinus yecorensis and the berry Vacciniumchihuahuense are characteristic of the zone. This region also

shares a number of species with the Madrean Archipelago to

the north (e.g., Juniperus scopulorum and Quercus gambelii).The 2nd region is the Madrean-Central, which runs from

southwestern Chihuahua to southern Durango and eastern

Sinaloa, to the Mezquital-San Pedro River. In this region,

climates are more mesic and mean elevation is 2,650 m,

w w w . m a m m a l o g y . o r g

254

http://www.mammalogy.org

although it includes peaks above 3,200 m. Many plant species

and a genus (Megacorax) are endemic to this area. The 3rd

region is the Madrean-South, comprising southern Durango

southeast of the Mezquital Basin, western Zacatecas, and

northern Jalisco (Fig. 1). This is a rugged zone with deep and

wide canyons through which the tropical and xerophylous

zones converge. It also harbors a high diversity of endemic

plants (e.g., Pinus maximartinezii), as well as of madrones

(Arbutus) and agaves (Agave). This division of the highlands is

at least partially consistent with the findings of phylogeo-

graphic analyses on some vertebrates (Bryson and Riddle

2011; Wood et al. 2011; Bryson et al. 2012a, 2012b) and plants

(Jaramillo-Correa et al. 2006; Rodrıguez-Banderas et al. 2009;

Gugger et al. 2011). Similarly, a morphometric analysis of

geographic variation across the distributional range of P.

schmidlyi (Lopez-Gonzalez et al. 2013) showed significant

morphological variation between Madrean-North individuals

and the remaining populations, which suggests a certain degree

of population differentiation between ecological zones.

Historically, the origin of the distinct regional pine–oak

communities in North America is primarily attributed to the

fragmentation of the once continentally distributed Tertiary

forests, resulting from late Miocene and Pliocene (14–2.5

million years ago) orogeny and expansion of the Basin-and-

Range region in western North America (Graham 1999). In

contrast, it has been hypothesized that Quaternary climatic

FIG. 1.—Ecoregions of the Sierra Madre Occidental according to Gonzalez-Elizondo et al. (2013) and sampling localities of Peromyscusschmidlyi analyzed for this study. The currently known distribution of this mouse includes the Madrean-North, Madrean-Central, and Madrean-

South regions (Lopez-Gonzalez et al. 2013). Locality codes as in Table 1.

April 2014 255LOPEZ-GONZALEZ ET AL.—PHYLOGEOGRAPHY OF P. SCHMIDLYI

cycles had a different effect on the Madrean pine–oak areas

(McDonald 1993; Spellman and Klicka 2007), where the

cooling associated with glacial advances did not result in the

contraction of pine–oak areas, but instead they remained

relatively stable and in some cases may have expanded in

response to the cooler temperatures (McDonald 1993). A

consequence of these changes would have been the division of

pine–oak forests into specific regional communities with (at

least partially) separate histories (Spellman and Klicka 2007).

Despite the size and complexity of the Madrean mountain

range, relatively little is known about the biogeography of the

region. Most studies to date have focused on the ‘‘sky islands’’

or Madrean Archipelago of the northwestern end (see DeBano

and Ffolliott [2005] for a summary). Other than that, the SMO

usually is analyzed as a barrier between Mexican Plateau and

Pacific Plateau populations (e.g., Riddle et al. 2000; Jaeger et

al. 2005), or as a part of larger-scale studies (e.g., Morrone

2005; McCormack et al. 2008; Bryson et al. 2011; Gugger et

al. 2011), but few analyses deal with the SMO as a biographic

unit in itself. This might be the result of a paucity of data that

results in lack of understanding of its complexity and history.

Particularly lacking is basic knowledge of the spatial and

temporal scale of population differentiation, which might

provide insights into the roles of mountain-building, climatic

shifts, or geographic isolation in divergence and speciation

(McCormack et al. 2008). A phylogeographic approach also

might help discriminate between competing models of

diversification, such as those that emphasize geological

processes such as mountain uplift (Morafka 1977; Jaeger et

al. 2005) versus those that focus on habitat fluctuations caused

by Pleistocene climate change (Mengel 1970; Hewitt 1996;

Lessa et al. 2003; Johnson and Cicero 2004).

In this study we examined 2 mitochondrial DNA fragments

(cytochrome-b [Cytb] and D-loop) and morphometric variation

(from Lopez-Gonzalez et al. 2013) in P. schmidlyi to provide

insights into the evolutionary history of the species on the

highlands of the SMO. We explore the possible correspon-

dence between genetic and morphological variation and the

proposed ecological division of the SMO highlands. We would

expect that if P. schmidlyi evolved in these forests while

floristic differentiation occurred, we would observe divergent

lineages with clear phenotypic and genetic breaks coincident

with ecological breaks, rather than continuous or clinal

variation.

MATERIALS AND METHODS

Sample collection and DNA extraction.—Samples of P.schmidlyi from most of its distribution range were included

(Fig. 1). For Cytb, 26 individuals of P. schmidlyi from 10

populations (Table 1), and 1 P. gratus and 1 P. eremicus used

as outgroups in the phylogenetic analysis, were collected

(Table 1). Samples consisted of tissue preserved in 95%

ethanol, frozen tissue, and skin clips from individuals prepared

as museum specimens. Eighteen more sequences of the Cytbgene of P. schmidlyi published elsewhere, including the type

material (Bradley et al. 2004; Cabrera et al. 2007) were used as

well, for a total of 44. For D-loop we sequenced the 23

individuals reported above plus 12 specimens previously

reported in the literature, for a total of 35 plus the 2

outgroup specimens. Vouchers are deposited at the Mammal

Collection, CIIDIR Unidad Durango, Instituto Politecnco

Nacional, Durango, Mexico (CRD); the Natural Sciences

Research Laboratory at The Museum of Texas Tech

University, Lubbock, Texas (TTU); or the Mammal

Collection, Centro de Investigaciones Biologicas del

Noroeste, La Paz, Baja California, Mexico (CIB). Specimens

collected by us and deposited at CRD were captured and

processed following guidelines of the American Society of

Mammalogists (Sikes et al. 2011).

Laboratory procedures.—The DNA was extracted from

approximately 10 mg of skeletal muscle or skin clip using a

Promega kit (Promega, Madison, Wisconsin) and the

methodology described in Correa-Ramırez et al. (2010). We

amplified a 1,051–base-pair (bp) fragment of the Cytb gene

using forward primers L-14115 (50-GAT ATG AAA AAC CAT

CGT TG-30—Palumbi 1996), H-15288 (50-ACA AGA CCA

GAG TAA TGT TTA TAC TAT C-30), MVZ16 (50-AAA TAG

GAA RTA TCA YTC TGG TTT RAT-30—Smith and Patton

1999; Martin et al. 2000), or CBPrmF (50-CCC ATC CAA CAT

CTC ATC-30); and CBPrmR (50-GTA GCT GAT GGA GGC

TAG TT-30) as reverse primer. The primer pair for the D-loop

fragment (PrmsRCF [50-TTA GGG CAT CAA GAA GGA AG-

30] forward, and PrmsR D-loop 1 [50-TTG CTT TTG GGG TTT

GTC AA-30] reverse) was newly generated for this study and

allowed for amplification and sequencing of most of the D-loop

gene (750 bp).

Polymerase chain reactions were performed in a Labnet

9600 thermal cycler (Labnet International, Inc., Edison, New

Jersey) using 30–50 ng of DNA, 0.40 lM of each primer, 2.5

mM of MgCl2, 0.2 mM of each deoxynucleoside triphosphate

(Promega, Madison Wisconsin), 1x of polymerase chain

reaction buffer, and 1 U of Taq polymerase (Promega) in a

volume of 50 ll of sterile water. The polymerase chain reaction

was run with an initial denaturation step at 958C for 2.5 min,

followed by 45 cycles of 30 s of initial denaturation at 958C, 60

s of annealing at 508C (Cytb)/528C (D-loop), 60 s of extension

at 728C, and a final step of extension at 728C for 5 min.

Double-stranded products were purified using the Wizard SV

Gel and PCR Clean-Up System (Promega). Both strands of the

purified polymerase chain reaction products were sequenced in

an Applied Biosystems 310 Genetic Analyzer sequencer using

Big Dye chain terminators (Applied Biosystems Inc., Foster

City, California). Sequence files were edited and aligned using

Sequencher 4.1 (Gene Codes Corporation 2010). The resulting

Cytb sequences were translated into proteins to confirm the

identity of the fragments (Wernersson and Pedersen 2003).

Multiple alignments were performed in individual gene

fragments using Clustal X (Thompson et al. 1997), with gap

opening costs ¼ 50, gap extension ¼ 6.6, delay divergent

sequences¼ 30%, and DNA transition weight¼ 0.5 (Harrison

and Langdale 2006).

256 Vol. 95, No. 2JOURNAL OF MAMMALOGY

Population analyses.—Unless otherwise specified,

population analyses were performed for each fragment and

sampling locality using Arlequin version 3.5.1.21 (Excoffier

and Lischer 2010) or DnaSP version 5.1 (Librado and Rozas

2009). Genetic diversity within populations was measured as

haplotype diversity (h), number of private haplotypes (P), and

nucleotide diversity (p). For each fragment, population

structure was explored via analysis of molecular variance

(AMOVA) using Arlequin version 3.5.1.21 (Excoffier and

Lischer 2010). We tested for genetic structure among

ecoregions and among populations within ecoregions. A

spatial analysis of molecular variance (SAMOVA),

TABLE 1.—Sampling sites and GenBank accession numbers for 46 specimens examined in this work. Specimens belong to Peromyscusschmidlyi unless otherwise stated. ID refers to locality codes in Fig. 1. Museum numbers of vouchers are provided as well. Museum acronyms are

defined in the ‘‘Materials and Methods.’’ Cytb ¼ cytochrome-b.

ID Locality (by state) Latitude Longitude Museum no. Cytb D-loop

Durango

O 12 km E Ojitos 25.09431 �106.14033 TTU81603 AY322519a KC403915

O 12 km E Ojitos 25.09431 –106.14033 TTU81605 AY322522a KC403913

O 30 km SW Ojitos 24.96856 –106.29367 TTU81703 AY322524a KC403903

O 30 km SW Ojitos 24.96856 –106.29367 CRD1806 AY322514a KC403907





T 10.63 km N, 20.3 km W Otinapa 24.15473 –105.20687 CRD7938 KC403897 KC403928




S 20 km SW San Miguel de Cruces 24.28583 –105.97967 CRD6136 KC403882 KC403904




S 7.5 km S, 8 km W San Miguel de Cruces 24.35433 –105.92333 CRD6061 KC403889 KC403929

L Las Ramadas 23.03133 –104.67817 CRD8541 KC403883 KC403906




H 3.8 mi (6.1 km) W Coyotes, Hacienda Coyotes 23.82085 –105.33472 TTU81610 AY322517a KC403914




H 3.8 mi (6.1 km) W Coyotes, Hacienda Coyotes 23.82085 –105.33472 TTU81617b AY370610a —

Sonora

Y 0.8 km N, 1.4 km E Yecora 28.37722 –108.90889 CIB10888 EU234539c —





Chihuahua

N 2 km S Norogachi 27.26033 –107.13300 CRD4025 KC403885 KC403930

N 2 km S Norogachi 27.26033 –107.13300 CRD4036 KC403899 KC403933

N 2 km S Norogachi 27.26033 –107.13300 CRD4050 KF322235 —

N 2 km S Norogachi 27.26033 –107.13300 CRD3614 KF322233 KF322240

B 1.5 km S, 5.6 km W Basıhuare 27.45383 –107.54383 CRD4937 KC403892 KC403926

B 1.5 km S, 5.6 km W Basıhuare 27.45383 –107.54383 CRD4938 KC403893 KC403927

C 2.1 km NW Choguita 27.46900 –107.29617 CRD3812 KC403900 KC403932

C 2.75 km N, 3.6 km W Choguita 27.48017 –107.31900 CRD3807 KF322236 —

C 2.75 km N, 3.6 km W Choguita 27.48017 –107.31900 CRD3811 KF322234 KF322237

C 5 km S, 2 km W Rejogochi 27.37450 –107.50017 CRD3463 KF322231 —

V 3.2 km S, 0.8 km E Hueleyvo 27.23633 –107.39917 CRD4001 KC403898 KC403924

V 3.2 km S, 0.8 km W Hueleyvo 27.23633 –107.39917 CRD4000 KF322230 KF322238

V 3.7 km S, 0.9 km W Hueleyvo 27.23283 –107.40083 CRD4005 KF322232 KF322239

— 2 km S Norogachi (P. gratus, outgroup) 27.26033 –107.133 CRD3595 KC403901 KC403934

Sinaloa

— 0.75m km E Camotete (P. eremicus, outgroup) 25.26760 –107.57345 CRD3512 KC403902 KC403935

a Sequences from Bradley et al. (2004).b Type specimen.c Sequences from Cabrera et al. (2007).


implemented in the program SAMOVA 1.0 (Dupanloup et al.

2002; de Thoisy et al. 2010), was used to find combinations of

sampling sites that are maximally differentiated from each

other without a priori assumption about population structure.

This analysis allowed us to explore genetic structures other

than the one proposed initially. The method is based on a

simulated annealing procedure that maximizes the proportion

of genetic variance that can be explained by differences

between groups of populations (de Thoisy et al. 2010). Genetic

variance is the among-group genetic variation (hCT) coefficient

as estimated by AMOVA (Excoffier et al. 1992). We repeated

the SAMOVA analyses with different numbers of groups, from

K¼ 2 to K¼ 9 samples for Cytb and from K¼ 2 to K¼ 8 (same

samples except the Yecora population) samples for D-loop

(Saeki et al. 2011).

For each data set, we calculated the sum of squares deviation

(SSD) and Harpending’s raggedness index (RI—Harpending

1994) to assess the fit of the observed data to a model of

sudden expansion. The mismatch distribution, based on the

number of observed nucleotide differences between pairs of

sequences, was compared to the distributions expected under

models of pure demographic expansion (Rogers and Harpend-

ing 1992) and sudden spatial expansion (Excoffier 2004; Rozas

2009). Model parameters (h0, h1, and s) were estimated using a

generalized nonlinear least-squares approach with confidence

intervals obtained through parametric bootstrapping with 1,000

replicates (Schneider and Excoffier 1999). The SSDs of

bootstrapped replicates were used to calculate the significance

of the fit between the observed and expected mismatch

distributions (Slatkin and Hudson 1991; Schneider and

Excoffier 1999).

To test for deviations from neutrality, Tajima’s D (Tajima

1983, 1989) and Fu’s FS (Fu 1997) statistics were calculated

for Cytb and D-loop sequences by population and for the

complete sample of P. schmidlyi. Significant deviations from

neutrality may be caused by selection or historic demographic

fluctuations such as population bottlenecks or population

expansion (Aris-Brosou and Excoffier 1996; Fu 1997).

Statistical significance was assessed by comparing the

observed statistic values to expected values based on 1,000

neutral coalescent simulations. We estimated gene flow by

calculating the number of migrants per generation (Nm) based

on FST-values, using the model of Hudson et al. (1992)

estimated from the formula proposed by Wright (1951). Nm is

an indirect measure of gene flow among populations under

Wright’s island model of population subdivision (Slatkin

1985). It assumes an infinite number of equal-sized populations

that exchange migrants at a constant rate (Wright 1951, 1965).

All population parameters were estimated using Arlequin

version 3.5.1.21 (Excoffier and Lischer 2010).

Correlation between genetic, geographic, and morphometricdistances.—For each marker, correlations between matrices of

genetic versus geographic and genetic versus morphometric

distances were assessed using Mantel’s test (Mantel 1967).

Using MEGA5 (Tamura et al. 2011) we calculated pairwise

genetic distances between populations using the Kimura 2-

parameter model. The model takes into account transitional and

transversional substitution rates, while assuming that the 4

nucleotide frequencies are the same and substitution rates do

not vary among sites. All ambiguous positions were removed

for each sequence pair (Tamura et al. 2011). Pairwise

geographic (Euclidian) distances (km) between sites were

calculated using Geographic Distance Matrix Generator

version 1.2.3 (Ersts 2012). Morphometric distances were

calculated using a subset (156 specimens) of the data from

the morphometric analysis by Lopez-Gonzalez et al. (2013)

that included only specimens corresponding to the localities

analyzed in this work (Table 1). The Yecora population was

not included because no specimens from that region were

examined by Lopez-Gonzalez et al. (2013). All cranial

morphometric variables used in that study were included. A

matrix of pair-wise Mahalanobis distances between localities

was built using PROC DISCRIM in SAS (SAS Institute Inc.

1995). Pooled within-group variance was used to estimate pair-

wise distances. Significance of correlations between matrices

was calculated by bootstrapping the samples 10,000 times in

Matlab for Windows, version 7.10.0.499 (R2010a—The

MathWorks Inc. 2010), using functions and scripts written

by the 1st author or Strauss (2013). An independent test for

significance of genetic versus geographic distance was run

using the MANTEL-STRUCT program from Alleles in Space

(AIS—Miller 2005). Unlike the tests described above, which

directly relate geographic and genetic distance, Miller’s test

compares within- versus among-population genetic distances

(Miller 1999), thus allowing comparisons with other studies.

Phylogenetic analysis.—For each fragment, a median-

joining network was constructed using NETWORK version

4.1.0.3 (Bandelt et al. 1999) to depict phylogeographic patterns

and potential ancestor–descendant relationships. To determine

the reliability of phylogenetic inferences, for each marker

sequences were tested for saturation (Hulsey et al. 2004).

To reconstruct phylogenetic relationships, we used maxi-

mum-likelihood and Bayesian inferences for the Cytb and D-

loop data sets separately. We used P. gratus and P. eremicus as

outgroups to polarize the characters within the populations of

P. schmidlyi. For maximum likelihood, a model of evolution

was selected using MODELTEST (Posada and Crandall 1998).

Maximum likelihood searches were conducted using

GTRGAMMA as model of nucleotide evolution and 10,000

bootstrap repetitions using RAxML version 7.0.4 (Stamatakis

2006; Stamatakis et al. 2008).

Bayesian analysis used the GTR model with invariant rate

heterogeneity. A posterior probability analysis (Rannala and

Yang 1996) was performed using the program MrBayes

version 3.0b4 (Ronquist and Huelsenbeck 2003). Bayesian

posterior probability calculations were implemented in a range

of ten million generations, sampling every 1,000 generations,

and discarding the first 1,000 trees sampled (as burn-in).

Support for nodes was determined by posterior probabilities

(Huelsenbeck et al. 2002; Ronquist and Huelsenbeck 2003).

For each method of reconstruction 3 independent runs were

conducted to get an impression of the robustness of the


phylogenetic reconstruction. To evaluate sufficient mixing,

stable convergence on a unimodal posterior probability curve,

and effective sample size (ESS) we used Tracer version 1.5

with EES . 200 (Rambaut and Drummond 2007). All null

hypotheses were rejected at a ¼ 0.05.

RESULTS

Genetic diversity.—Among the 44 individuals of P.schmidlyi examined for Cytb (Table 1), we detected 40

different haplotypes, 37 were private, 1 was shared among 3

localities geographically distant from each other (PsCB20 at

Hacienda Coyotes [H] and Las Ramadas [L], Durango, and

Basıhuare [B], Chihuahua), and 2 haplotypes were shared

between 2 localities (PsCB12 between Basıhuare [B] and

Otinapa [T], Durango, and PsCB14 between San Miguel de

Cruces [S], Durango, and Hueleyvo [V], Chihuahua), also

geographically distant from each other (Fig. 1).

Within-population haplotype diversity (Table 2) for the 10

sampling localities was 1.00 at each locality, that is, all

individual haplotypes within localities were different from each

other. Overall haplotype diversity was high (h ¼ 1), overall

nucleotide diversity was 0.0094. The AMOVA was significant

(Table 3) for differences among regions, but not for variation

among or within populations. Nucleotide diversity ranged from

0.0054 to 0.0119 (Table 2). The SAMOVA was significant for

combinations of populations in which Yecora (Y [Fig. 1]) was

considered as an independent group.

We detected 34 private D-loop haplotypes of P. schmidlyi(Table 2). Only 1 occurred in 2 localities geographically distant

(Hueleyvo [V] and Otinapa [T] [Fig. 2]). Nonetheless, for all

localities there is more than 1 haplotype per locality (Table 2).

Within-population haplotype diversity was 1.00 at each locality

(Table 2). Overall haplotype diversity also was high (h ¼ 1),

overall nucleotide diversity was 0.012. Unlike Cytb, the

AMOVA for D-loop (Table 3) was not significant, that is,

most variation was contained within populations. For this

analysis, significant results were obtained for all combinations

of populations, but no pattern was found.

Historic demography.—Mismatch analysis for both

fragments exhibited unimodal distributions that did not differ

significantly from the distribution expected under population

expansion (Fig. 2; average values Cytb, RI¼0.33, P¼ 0.19; D-

loop, RI¼ 0.34, P¼ 0.49). Parameters of the expansion model

were h0 ¼ 0.78, h1 ¼ 60,022.7, and s ¼ 6.28 for the Cytbfragment; and h0¼ 1.47, h1¼ 66,679.3, and s¼ 7.4 for D-loop.

Maximum sequence divergence between any 2 haplotypes was

2.7% (TTU81610 versus TTU81635) for Cytb and 2.8%

(TTU81635 versus TTU81634) for D-loop. Average number of

migrants per generation (Nm) for Cytb was 5.4, whereas for D-

loop, Nm was 10.31.

Values of Tajima’s D-test for neutrality were nonsignificant

and negative by locality (average for Cytb,�1.25, P¼ 0.1; D-

loop, �0.93, P ¼ 0.21) and significant for P. schmidlyi as a

whole for Cytb (�1.95, P¼ 0.007), but not for D-loop (�1.69,

P ¼ 0.11). Fu’s FS-tests of neutrality were negative and

nonsignificant for both fragments when estimated by locality

(Cytb, �2.37, P ¼ 0.1; D-loop, 0.61, P ¼ 0.37; Table 4), and

significant for P. schmidlyi as a whole for both Cytb (�24.95, P¼ 0.0) and D-loop (�24.57, P ¼ 0.0).

Genetic versus geographic and morphometric distances.—

Matrices of geographic and genetic distances were not

significantly correlated for Cytb (r ¼ 0.11, P ¼ 0.24), but

they were significantly correlated for D-loop (r ¼ 0.205, P ¼0.04). Correlation between genetic and morphometric distances

was not significant for any fragment (Cytb, r¼ 0.16, P¼ 0.24;

D-loop, r¼�0.02, P¼ 0.534). The Mantel test for correlation

among geographic and genetic distances using AIS was

nonsignificant for both markers (Cytb, r ¼ 0.11, P ¼ 0.91; D-

loop, r¼ 0.08, P ¼ 0.13).

TABLE 2.—Basic statistics for cytochrome-b (Cytb) and D-loop DNA fragments in 10 samples of Peromyscus schmidlyi. n, sample size; S,

number of segregating sites; Ts, number of transitions; Tv, number of transversions; ID, number of insertions–deletions; h, haplotype diversity; p,

nucleotide diversity; PA, private alleles. Mean and SD are provided; locality codes as in Table 1.

Statistics O T S L Y H N B C V X SD

Cytb

n 8 4 5 4 5 5 4 2 4 3 3.7 2.10

S 32 12 10 12 17 19 16 7 17 7 14.9 6.96

Ts 24 12 9 11 17 14 12 7 13 5 12.4 5.06

Tv 8 0 1 1 0 5 4 0 4 2 2.5 2.54

ID 0 0 0 0 0 0 0 0 0 0 0.0 0.00

h 1 1 1 1 1 1 1 1 1 1 1 0

p 0.0118 0.0080 0.0054 0.0108 0.0093 0.0106 0.0108 0.0091 0.0119 0.0060 0.0094 0.0023

PA 8 4 3 4 5 4 3 2 4 3 3.80 1.98

D-loop

n 8 4 5 4 — 4 3 2 2 3 3.89 1.73

S 35 14 15 26 — 15 25 12 12 11 18.33 7.86

Ts 31 13 13 22 — 13 19 11 9 10 15.67 6.72

Tv 4 1 2 4 — 2 6 1 3 1 2.67 1.64

ID 2 0 0 1 — 1 0 0 0 1 0.56 0.68

h 1 1 1 1 — 1 1 1 1 1 1.00 0.00

p 0.0143 0.0083 0.0083 0.0167 — 0.0098 0.0098 0.0161 0.0147 0.0098 0.012 0.0034

PA 8 3 5 4 — 4 3 2 2 2 3.67 1.73


Phylogeny.—The median-joining networks of Cytb and D-

loop haplotypes (Fig. 3) did not reveal divergent clusters of

haplotypes by locality or ecoregion. Rather, the Cytb network

is star-shaped (Avise 2000), whereas the network for D-loop

shows no structure. The saturation test showed that Cytb (index

of substitution saturation [ISS] ¼ 0.097, critical value [ISS.C] ¼0.82, P ¼ 0.0) and D-loop (ISS ¼ 0.06, ISS.C ¼ 0.81, P ¼ 0.0)

fragments presented little substitution saturation (Xia et al.

2003; Xia and Lemey 2009), indicating that the phylogenetic

information given by these sequences is adequate for

phylogenetic inference. For the Cytb fragment there was no

geographic clustering in the phylogenetic analyses (Fig. 4; only

results of Bayesian analysis are shown). The tree generated by

the Bayesian analyses is mostly unresolved, and the clusters

that are formed may or may not contain sequences from

different localities. The maximum-likelihood tree is resolved

but weakly supported, and clusters do not reflect geographic

structure. The only geographic cluster is that of the Yecora

specimens, although 1 of the specimens from this locality

clusters elsewhere. Results for the D-loop data set are similar,

there is little structure, and where there is some, clades are

weakly supported and include localities that are geographically

apart (Fig. 4).

DISCUSSION

Both mitochondrial DNA fragments presented a high

amount of genetic diversity. For P. schmidlyi, haplotype

diversity and nucleotide diversity estimates (Table 2) are

relatively high compared to most terrestrial vertebrates, but are

similar to those of the desert lizard Uta stanburiana (h¼0.979,

p¼0.007 for Cytb—Micheletti et al. 2012), and mammals such

as the squirrels Sciurus niger (h¼ 0.985, p¼ 0.023—Moncrief

et al. 2012) and S. carolinensis (h ¼ 0.853, p ¼ 0.017—

Moncrief et al. 2012). The high genetic diversity found is

unlikely to be due to sequencing error or artifact because

sequences were run in both directions, and we resequenced 10

samples to verify consistency of the results. We did not detect

heterozygote base calling (double peaks in any sequence

direction) in either mitochondrial DNA fragments. Further-

more, the Cytb data set was checked by amino acid translation

and we found no stop codons. D-loop sequences were verified

by blasting our sequences against D-loop sequences deposited

at GenBank.

Notwithstanding these high levels of variation, we were

unable to detect any structure in the data. We expected that the

pattern of genetic variation would reflect that of morphological,

geographic, or ecological variation. We found no relationship

between geographic or morphological variation and genetic

variation except for D-loop, which had a significant relation-

ship with geography in the direct test, but showed no

significance using the AIS test.

Within-population genetic variation was much higher than

variation among ecoregions (Table 3). Although for both

markers analyzed there is high haplotype diversity within

populations, most haplotypes occur in a single locality, and

TABLE 3.—Results of AMOVA and SAMOVA on 9 (cytochrome-b [Cytb] and 6 (D-loop) populations of Peromyscus schmidlyi. UST, fixation

index among groups; UCT, fixation index within groups; K, number of comparisons. Results of each test are based on 20,000 permutations.

Population groupings in AMOVA reflect the ecoregion subdivision of the Sierra Madre Occidental by Gonzalez-Elizondo et al. (2013). Population

codes are as in Table 1. Significant results at a ¼ 0.05 are indicated in boldface type.

d.f.

Sum of

squares

Variance

components % variation UST/UCT P Partition

AMOVA Cytb

Among ecoregions 2 13.29 0.22 5.62 0.056 0.044 (YþCþVþNþB)þ (OþTþSþH)þ(L)

Among populations within ecoregions 7 26.84 0.03 0.81 0.064 0.083

Within populations 34 125.65 3.70 93.56 0.009 0.067

Total 43 165.78 3.95

SAMOVA Cytb

K ¼ 2 1 8.07 0.57 13.27 0.13 0.0958 (C)þ(OþTþSþLþNþBþHþVþY)

K ¼ 3 2 19.15 0.59 14.39 0.14 0.0020 (Y)þ(NþCþV)þ(OþTþSþHþB)

K ¼ 4 3 24.27 0.54 13.83 0.14 0.0000 (Y)þ(OþH)þ(NþCþV)þ(TþSþLþB)

K ¼ 5 4 27.17 0.57 14.64 0.15 0.001 (Y)þ(NþCþV)þ(O)þ(TþSþLþB)þ(H)

K ¼ 6 5 30.70 0.62 15.96 0.16 0.000 (Y)þ(SþV)þ(O)þ(NþC)þ(H)þ(TþLþB)

K ¼ 7 6 33.93 0.71 18.34 0.18 0.000 (Y)þ(L)þ(O)þ(SþV)þ(H)þ(TþB)þ(NþC)

K ¼ 8 7 36.48 0.87 22.63 0.23 0.001 (NþV)þ(O)þ(TþB)þ(H)þ(S)þ(Y)þ(L)þC

K ¼ 9 8 37.39 0.59 15.31 0.15 0.062 (NþV)þ(O)þ(T)þ(B)þ(H)þ(S)þ(Y)þ(L)þC

AMOVA D-loop

Among ecoregions 2 12.96 0.21 4.20 0.04 0.06 (CþVþNþB)þ(OþTþSþH)þ(L)

Among populations within ecoregions 6 26.65 �0.16 �3.19 0.01 0.81

Within populations 26 131.49 5.058 98.99 �0.03 0.51

Total 34 171.10 5.11

K ¼ 2 1 10.30 0.68 12.09 0.12 0.03 (NþB)þ(OþTþSþLþHþVþC)

K ¼ 3 2 17.03 0.63 11.49 0.11 0.002 (NþB)þ(L)þ(OþTþSþHþVþC)

K ¼ 4 3 21.01 0.58 10.76 0.11 0.012 (N)þ(L)þ(B)þ(OþTþSþHþVþC)

K ¼ 5 4 26.04 0.54 10.09 0.10 0.005 (N)þ(L)þ(B)þ(C)þ(OþTþSþHþV)

K ¼ 6 5 29.73 0.53 10.24 0.10 0.00 (HþVþT)þ(NþB)þ(O)þ(S)þ(L)þC


those that occur in more than 1 locality are shared by

populations separated by large geographic distances along the

3 ecoregions. For instance, Cytb haplotypes are shared among

Basıhuare (Madrean-North), Hacienda Coyotes (Madrean-

Central), and Las Ramadas (Madrean-South [Fig. 1]); even

though Basıhuare and Las Ramadas are separated by more than

500 km. Mismatch results for both markers also are consistent

with the prediction of Slatkin (1993) that genetic relationships

among localities did not resemble an equilibrium state caused

by isolation by distance, that is, geographically close localities

can be as different as those that are geographically distant.

These results are confirmed by the median-joining networks

and phylogenetic trees. The median-joining networks for both

markers (Fig. 3) showed no divergent clusters of haplotypes by

locality or ecoregion, which suggests genetic continuity among

localities. Similarly, there was no geographic clustering in the

phylogenetic analyses (Fig. 4). Trees were mostly unresolved,

and clades may or may not contain sequences from

geographically distant localities. In the tree built from Cytbdata, the clade formed by sequences from Basıhuare and

Otinapa had 85% statistical support (Fig. 4a) even though

Basıhuare is more than 400 km southeast of Otinapa (Fig. 1).

The exception is the Yecora population, where 4 of the 5

specimens included in the analysis clustered together in the

Bayesian phylogeny; they constitute a statistically significant

cluster in the SAMOVA under various combinations of

populations, and account for the significance found among

regions in the Cytb AMOVA. This population is nearly 180 km

northwest from the closest locality sampled (Basıhuare).

Nonetheless, the Yecora specimens are not genetically different

from those of Basıhuare, nor from any of the Chihuahuan

populations; thus, the Yecora clade has no support (Fig. 4) and

is not consistent in the maximum-likelihood phylogeny.

Furthermore, this cluster is not evident in the haplotypic

network, which shows that the most dissimilar specimens are

from southern Chihuahua (Fig. 3a). Also, the SAMOVA

results indicate that these specimens are significantly different

from everything else, with no geographic structure. Therefore,

based on this sample, it is not possible to consider the Yecora

specimens as a phylogeographic unit.

Results for the D-loop data set are similar, there is little

structure, and where there is some, clades include localities that

are geographically apart; for instance, the clade including

Basıhuare and Otinapa had 96% support (Fig. 4b). In the

maximum-likelihood analysis most branches are weakly

supported, and the few localities with well-supported clades

include samples that are geographically separated (Fig. 4b). In

general, the genetic patterns obtained did not reflect the

ecological regionalization of Gonzalez-Elizondo et al. (2013).

Nevertheless, these data provide insights into the population

history of P. schmidlyi. In phylogenetic trees (Fig. 4) poorly

supported nodes were left in place for the purpose of

comparing the concordance between the trees and the

networks, but if they were to collapse, there would be a single

clade nested within a polytomy. The observed trees and

networks fit in category IV of the phylogeographic patterns

proposed by Avise (2000): shallow phylogenetic trees and a

star-shaped network for Cytb, and no discernible structure for

D-loop. These patterns are consistent with an explosive

increase in effective population size from a few individuals,

followed by an expansion of the range of the species in recent

evolutionary times. They also suggest that the population is

nearly panmictic (Avise 2000).

Tajima’s D and Fu’s F were all negative, but were not

significant for any marker when samples were considered. At

the species level, D-values were significant for Cytb, but not

for D-loop. Considering the associated probability of this test

(P ¼ 0.11), lack of significance might be a result of the small

population used to effect calculations. In general, Tajima’s Dand Fu’s F for the species, as well as mismatch distribution

analysis, high migration rate, lack of evidence of geographic

structuring, and presence of unique haplotypes in all localities

sampled support the idea that P. schmidlyi had a range

expansion in past times. Although both markers indicate recent

demographic expansion, the exact mode of growth (stepwise,

exponential, or logistic growth) cannot be distinguished

(Slatkin and Hudson 1991; Rogers and Harpending 1992;

Rogers 1995; Polanski et al. 1998; Schneider and Excoffier

1999). Nonetheless, there is a large difference between the

initial (Cytb, h0¼ 1.71; D-loop, h0¼ 1.47) and final (Cytb, h1¼

FIG. 2.—Mismatch frequency distribution for a) cytochrome-b(Cytb) and b) D-loop mitochondrial DNA haplotypes of Peromyscusschmidlyi. The black line indicates expected distribution based on a

model of exponential population growth; the gray line indicates

observed distribution.


60,022.7; D-loop, h1 ¼ 66,679.3; Table 3) values of the

estimates of effective population size. These values suggest an

explosive increase of population size across the species

distribution.

Nonsignificance of AMOVA and lack of correlations

between genetic and geographic distances in both data sets

(Cytb and D-loop), as well as good fit with an unimodal

distribution without elevated upper-tail probabilities (Fig. 2),

indicate that populations have high connectivity and that there

is gene flow across the species range, which is supported by the

Nm of both markers and high haplotype diversity. A

mechanism that may explain the observed pattern is long-

distance dispersal (Hewitt 1996). Under this model, a few

members of the pre-expansion population are successful long-

distance dispersers that establish new populations during range

expansion, producing the mismatch distribution for Cytb and

D-loop fragments observed in P. schmidlyi.High levels of gene flow might be thought to be inconsistent

with an animal such as P. schmidlyi. Drake (1958) estimated an

average home range of 688 square yards (575.25 m2) for males

and 533 square yards (445.6 m2) for females of this species.

Recent research, however, suggests that individuals of the

closely related species P. boylii increase their range propor-

tionally with population density (Abramson et al. 2013), and

that they can disperse more than 2,000 m at population density

peaks. If this is also true for P. schmidlyi, this behavior would

be expected in a period of expansion into new territories.

Furthermore, examination of the few data available indicates

that P. schmidlyi can have at least 3 reproductive periods a year

(Alvarez and Polaco 1984); thus, fecundity is high for this

rodent. Also, although little is known about its ecological

requirements, an analysis of stomach contents in a population

form southeastern Durango suggests that even though it is

primarily granivorous, P. schmidlyi is able to feed on insects or

fungi when availability of grasses is limited (Alvarez and

Polaco 1984). The ability to use a wide variety of available

resources to survive further supports the possibility of high

potential for dispersal even if individuals had restricted

movement during their lifetime.

We found no evidence of phenotypic and genetic differen-

tiation coincident with ecological breaks, but instead, a pattern

of sudden, relatively recent expansion and dispersal across the

SMO. We propose that the biogeographic history of P.schmidlyi is one of dispersal in the SMO followed by rapid

population expansion throughout the area in relatively recent

times, following the glacial cooling of the SMO highlands. The

most recent continental glaciation, the Wisconsinan (approx-

imately 0.11–0.85 thousand years ago), extended at its

maximum as far south as the Pacific northwestern coast of

the present-day United States. Southward into Mexico, and

eastward into the Great Plains, lowlands were colder than

today, but were not perpetually covered by ice. In Mexico, an

average decrease in temperature of 68C has been reported for

the Last Glacial Maximum, together with increased precipita-

tion in some areas (Bradbury 1997; Metcalfe 2006), and a

snow-line depression of 1,300 m (Lachniet and Vazquez-Selem

2005; Lozano-Garcıa and Vazquez-Selem 2005; Mark et al.

2005). There is strong evidence that this decrease in

TABLE 4.—Tajima’s D, Fu’s FS, mismatch analysis parameters (s, h0, h1), sum of squares deviations (SSDs), Harpending’s raggedness index

(RI) tests, and associated P-values for 10 populations of Peromyscus schmidlyi. Mean and SD are provided. Population codes are as in Table 1.

O T S L Y H N B C V X SD

Cytb

n 8 4 5 4 5 5 4 2 4 3 4.4 1.5

Tajima’s D �1.25 �0.58 �0.89 �0.33 �0.86 �0.74 �0.46 — �0.12 — �0.52 �0.39

P 0.14 0.49 0.28 0.49 0.28 0.31 0.41 — 0.64 — 0.14 0.49

Fu’s FS �2.37 �0.25 �1.63 �0.22 �0.79 �0.61 0.12 1.94 0.23 0.31 �2.37 1.11

P 0.10 0.23 0.06 0.20 0.12 0.17 0.26 0.54 0.39 0.32 0.10 0.23

s 4.33 5.21 4.75 6.33 8.43 10.98 9.82 — 7.95 5.06 6.28 3.00

h0 5.55 2.06 0.00 0.00 0.00 0.007 0.023 — 0.025 0.002 0.78 1.71

h1 1 3 105 1 3 105 1 3 105 1 3 105 45.47 26.46 160.85 — 1 3 105 1 3 105 60,022.7 48,960.8

SSD 0.046 0.11 0.11 0.22 0.05 0.05 0.12 — 0.14 0.33 0.12 0.09

P 0.23 0.34 0.11 0.18 0.73 0.79 0.33 — 0.44 0.10 0.23 0.34

RI 0.13 0.22 0.24 0.61 0.14 0.14 0.44 — 0.28 1.11 0.33 0.31

P 0.19 0.71 0.50 0.15 0.65 0.66 0.31 — 0.62 0.25 0.19 0.71

D-loop

n 8 4 5 4 — 4 3 2 2 3 3.89 1.73

Tajima’s D �0.93 �0.62 �0.41 �0.23 — �0.43 — — — — �0.29 0.33

P 0.21 0.43 0.45 0.59 — 0.43 — — — — 0.64 0.28

FS �1.89 �0.06 �0.87 0.71 — 0.12 1.65 2.48 2.48 0.90 0.61 1.39

P 0.11 0.29 0.23 0.32 — 0.35 0.45 0.59 0.50 0.44 0.37 0.16

s 5.67 7.45 9.34 8.48 — 9.18 18.06 — — 8.40 7.40 5.11

h0 7.11 0.01 0.002 6.06 — 0.00 0.0018 — — 0.0035 1.47 2.75

h1 1 3 105 1 3 105 120.16 1 3 105 — 1 3 105 1 3 105 — — 1 3 105 66,679.3 47,121.1

SSD 0.025 0.090 0.088 0.16 — 0.033 0.44 — — 0.39 0.13 0.16

P 0.60 0.60 0.17 0.31 — 0.88 0.03 — — 0.07 0.29 0.30

RI 0.046 0.22 0.18 0.28 — 0.11 1.11 — — 1.11 0.34 0.42

P 0.72 0.75 0.57 0.64 — 0.95 0.35 — — 0.31 0.49 0.32


temperature allowed temperate species of plants to migrate and

diversify southward into Mexico. Particularly in the highlands

of the Sierra Madre Occidental, the Douglas fir (Pseudotsuga

menziesii—Gugger et al. 2011), some species of pines

(Pinus—Moreno-Letelier and Pinero [2009] and references

therein), and their associated beetles (Dendroctonus—Andu-

cho-Reyes et al. 2008) show evidence of population expansion

in the late Pleistocene.

The degree of genetic differentiation between P. schmidlyi

and its closest living relative (Peromyscus levipes) is only

3.25% (Bradley et al. 2007), which supports the idea of a

recent speciation event. Examination of our data suggests that

it is possible that as temperate species expanded southward

with the cooling, P. schmidlyi expanded northward and upward

into the SMO from a small founding population with a

previously restricted distribution. Similar arguments have been

FIG. 3.—Median-joining haplotypic network constructed for a) cytochrome-b (Cytb) and b) D-loop mitochondrial DNA haplotypes of

Peromyscus schmidlyi. Circles represent haplotypes; area of circle is proportional to haplotypic frequency. Letters represent sampling localities as

in Table 1. Shading indicates the ecoregion of the locality according to Gonzalez-Elizondo et al. (2013): no shading¼Madrean-North (MN); light

gray ¼Madrean-Central (MC); dark gray ¼Madrean-South (MS).


proposed to explain the current distribution of species of the

Peromyscus aztecus group (Sullivan et al. 1997). Although

beyond the scope of this paper, it is reasonable to speculate that

an analogous process occurred in the Sierra Madre Occidental

with the populations that eventually would become P. levipes.

The Holocene postglacial heating of North America probably

restricted the distribution of P. schmidlyi to its current refuge in

the highlands of the SMO, as has been suggested for other

species of plants (Jaramillo-Correa et al. 2006; Gugger et al.

2011; Mastretta-Yanes et al. 2012) and animals (Anducho-

Reyes et al. 2008; McCormack et al. 2008; Bryson et al. 2011;

Wood et al. 2011). This hypothesis is further supported by

evidence indicating that at least part of the Mexican Plateau

and Chihuahuan Desert were covered by woodlands at this

time (Toledo 1982; Van Devender et al. 1987; Edwards and

Bradley 2002).

In summary, we propose that P. schmidlyi could have

expanded throughout the SMO in the late Pleistocene without

any significant or prolonged bottleneck-derived loss of genetic

diversity. The abundance of suitable pine and pine–oak forest

habitat in the SMO might have exerted little novel selective

pressures during the range expansion of P. schmidlyi, which

would explain the absence of any signal of selection. Although

P. schmidlyi seems to have a high potential for dispersal and

FIG. 4.—Bayesian consensus trees for a) a portion of the cytochrome-b (Cytb) gene and b) D-loop gene in Peromyscus schmidlyi. Bayesian

posterior probabilities are given for each clade with . 50% support. Trees were outgroup-rooted on P. gratus and P. eremicus. Distribution of

localities across ecoregions is as follows: Madrean-North (MN), Madrean-Central (MC), Madrean-South (MS).


use of a variety of resources, it is still restricted to the highlands

of the SMO. This suggests dependence, or at least preference,

for some forest-associated resource or small tolerance to the

higher temperatures of the lowlands. Unfortunately, very little

is known about the ecology and life histories of the mammals

of the highlands, even though at least 9 species are endemic to

this region (Lopez-Gonzalez and Garcıa-Mendoza 2012;

Garcıa-Mendoza and Lopez-Gonzalez 2013). The current rate

of deforestation and climatic change occurring on the highlands

of the SMO pose a significant threat to the populations of P.schmidlyi and other species of small mammals with similar

requirements, but very little is being done for the preservation

of these ecosystems. Six officially protected areas exist in the

region: La Michilıa, Basaseachic Falls, Campo Verde,

Papigochic, Tutuaca, and Janos (Comision Nacional de Areas

Naturales Protegidas 2013a). Although they cover a reasonable

portion of the SMO (about 1,216,400 ha all together—

Comision Nacional de Areas Naturales Protegidas 2013a),

there seem to be no effective conservation efforts and only

Janos has a management plan (Comision Nacional de Areas

Naturales Protegidas 2013b). A sound policy for management

and conservation is urgent if we expect at least to have a

general knowledge of the diversity of this complex mountain

system.

RESUMEN

Peromyscus schmidlyi es un roedor endemico de los bosques

de pino–encino de las partes altas de La Sierra Madre

Occidental (SMO), Mexico. Utilizando dos marcadores

moleculares (Citocromo B y D-loop), se evaluaron las posibles

relaciones entre la variacion genetica y morfometrica de las

poblaciones de P. schmidlyi y la recientemente propuesta

regionalizacion de las comunidades vegetales de las partes altas

de la sierra. No encontramos estructura genetica, ni relaciones

significativas entre la variacion genetica de ningun marcador y

la variacion ecologica o morfometrica. El analisis de filogenias

y redes haplotıpicas no revelo grupos significativos geo-

graficamente estructurados, mas bien, lo que se obtuvo fueron

arboles con poca profundidad y redes en forma de estrella.

Asimismo, las pruebas de neutralidad por localidad fueron no

significativas y no se encontro evidencia de seleccion en

ninguno de los marcadores. La evidencia disponible sugiere

que la distribucion actual de P. schmidlyi es resultado de

dispersion seguida de una rapida explosion de la poblacion

sobre las partes altas de la SMO a finales del Pleistoceno, como

resultado del enfriamiento glacial de las mismas.

ACKNOWLEDGMENTS

We thank R. J. Baker and H. Gardner of The Museum, Texas Tech

University, for allowing access to the specimens under their care.

Funding for this research was provided by Secretarıa de Inves-

tigacion y Posgrado, Instituto Politecnico Nacional (SIP 2010-0434,

2011-0349, 2012-1104, and 2013-0840 to CL-G), Comision

Nacional para el conocimiento y uso de la Biodiversidad (CON-

ABIO) (X011 and GT015 to CL-G), and Consejo Nacional de

Ciencia y Tecnologıa (CONACYT) (290662-IPN to MMC-R). We

thank S. Gonzalez-Elizondo and colleagues for allowing access to

the digital version of their vegetation and ecoregion maps for the

SMO, as well as L. Ruacho-Gonzalez for making the necessary

transformations for us to be able to use them. Specimens were

collected under Secretarıa de Medio Ambiente y Recursos Naturales

(SEMARNAT) permit FAUT-0085 to CL-G. Two anonymous

reviewers provided useful comments and suggestions that helped

improve the manuscript.

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Submitted 5 July 2013. Accepted 19 November 2013.

Associate Editor was Sharon A. Jansa.


Phylogeography of Peromyscus schmidlyi : an endemic of the Sierra Madre...

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