Advertisement
Research Article

Mitochondrial and Nuclear DNA Survey of Zootoca vivipara across the Eastern Italian Alps: Evolutionary Relationships, Historical Demography and Conservation Implications

  • Luca Cornetti,

    Affiliations: Department of Biodiversity and Molecular Ecology - Centre for Research and Innovation, Fondazione Edmund Mach, S. Michele all’Adige, Italy, Department of Life Sciences and Biotechnology, Università di Ferrara, Ferrara, Italy

    X
  • Michele Menegon,

    Affiliation: Museo di Scienze, Trento, Italy

    X
  • Giovanni Giovine,

    Affiliation: Stazione sperimentale regionale per lo studio e la conservazione degli anfibi in Lombardia, Lago di Endine – Casazza, Bergamo, Italy

    X
  • Benoit Heulin,

    Affiliation: Station Biologique, CNRS UMR 6553, Paimpont, France

    X
  • Cristiano Vernesi mail

    cristiano.vernesi@fmach.it

    Affiliation: Department of Biodiversity and Molecular Ecology - Centre for Research and Innovation, Fondazione Edmund Mach, S. Michele all’Adige, Italy

    X
  • Published: January 17, 2014
  • DOI: 10.1371/journal.pone.0085912

Abstract

The European common lizard Zootoca vivipara exhibits reproductive bimodality, with populations being either viviparous or oviparous. In the central-eastern Italian Alps oviparous populations (Z. v. carniolica) and viviparous populations (Z. v. vivipara) partly overlap geographically. Studying the evolutionary relationship between these taxa presents an interesting opportunity to gain insight into the evolution of this trait. We aim to: i) test whether Z. v. carniolica, which is endangered, constitutes an ESU (Evolutionary Significant Unity); ii) infer mtDNA divergence time between the Z. v. carniolica clade and all the other Z. vivipara subspecies with the aid of an external calibration point; and iii) describe the phylogeographical and demographic scenarios in the area. To do so we sequenced about 200 individuals for mitochondrial variation; 64 of them were also analysed for three nuclear genes. Furthermore, we analysed the same nuclear markers in 17 individuals from the other oviparous subspecies Z. v. louislantzi and 11 individuals of Z. v. vivipara from widespread geographical origins. The mtDNA and nDNA loci that we examined supported the monophyly of Z. v. carniolica. The mtDNA-based estimate of divergence time between Z. v. carniolica and all the other subspecies indicated a separation at 4.5 Mya (95% CI 6.1–2.6), with about 5% of sequence divergence. Considering that Z. v. carniolica harbours higher genetic diversity, while Z. v. vivipara from central-eastern Alps shows a signature of recent population and spatial expansion, we argue that Z. v. carniolica represents a distinct evolutionary unit, with a presumably long-term evolutionary history of separation. Z. v. carniolica populations, occurring at higher latitudes and altitudes than insofar supposed, live in peat bogs, a seriously threatened habitat: taking into account also its evolutionary distinctness, specific conservation measures should be considered.

Introduction

The Eurasian common lizard, Zootoca vivipara (Jacquin, 1787), is among the few squamate reptiles displaying reproductive bimodality at the intraspecific level.

Viviparous (or better ‘lecithotrophic viviparity’, i.e. live-bearing with nutrition from the yolk, [1]) populations, ascribed to the nominotypical subspecies Zootoca vivipara vivipara, are widely distributed from the British Isles and central France to Scandinavia and north-eastern Asia as far as Japan [2]. Oviparous populations are restricted to the southern edges of the range, in two disjunct areas: southern France-northern Spain and northern Italy-southern Austria-Slovenia-Croatia. The French-Spanish oviparous populations have been recently attributed to the subspecies Z. v. louislantzi [3], whose range is clearly geographically separated from viviparous Z. v. vivipara populations [3][6]. All the other oviparous populations are included in the subspecies Z. v. carniolica [13]: in this case, the range has been described as parapatric to Z. v. vivipara [7][9] (Figure S1). However, a contact zone between Z. v. vivipara and Z. v. carniolica has been recently found in Carinthia, Austria [10].

Using karyotype [11] and mitochondrial DNA (mtDNA) sequence variation [7], [12][13], several studies have addressed the phylogenetic relationships between the different subspecies. The scenario can be summarised as follows: the two oviparous subspecies, Z. v. louislantzi and Z. v. carniolica are not reciprocally monophyletic. Considering the most comprehensive mtDNA survey [13], it appears that Z. v. carniolica is sister to all the other subspecies, namely Z. v. vivipara, Z. v. louislantzi and Z. v. pannonica ([14]: in this study the term used was still the former, Lacerta vivipara pannonica). Therefore, neither the oviparous (Z. v. carniolica and Z. v. louislantzi) nor viviparous subspecies (Z. v. vivipara and Z.v. pannonica) form monophyletic groups, making a single transition from oviparity to viviparity unlikely.

Z. v. carniolica has been considered as an Evolutionarily Significant Unit (ESU) sensu Moritz (1994) [15]. However, none of the aforementioned studies included nuclear DNA sequence variation. Proving the ESU status for this subspecies would significantly support the conclusions of earlier studies pointing out that Z. v. carniolica would deserve specific conservation measures [9].

Z. v. carniolica has been found from Piedmont via northern Italy and Austrian Carnian Alps to Slovenia and north-west Croatia, and its northern limit appears to correspond with the Italian Prealps, while the southern limit is represented by a few wetland areas in the Po Valley. The high degree of fragmentation of these low-mid-altitude wetland areas, affected by both climate change and human activities, might pose a serious threat to Z. v. carniolica persistence, as highlighted by some local extinction documented in the Po Valley area [16], [17].

The main aim of this work was to test the ESU hypothesis for Z. v. carniolica by contrasting patterns of DNA sequence variation at nuclear and mitochondrial markers in 92 and 230 individuals, respectively, of Z. vivipara spp. from different European regions. Moreover, we specifically focused on the evolutionary history of Z. v. carniolica at both macro- and micro-scale by: a) inferring mtDNA divergence time between the Z. v. carniolica clade and all the other Z. vivipara subspecies with the aid of an external calibration point; b) describing the phylogeographical and demographic scenarios in an area of partial distribution overlap - central-eastern Italian Alps- between the oviparous populations of Z. v. carniolica and the viviparous populations of Z. v. vivipara.

Materials and Methods

Ethics Statement

All conducted experiments complied with the current laws of Italy. The Italian Ministry of Environment and the Environmental Unit of the Autonomous Province of Trento approved capture, handling, and tissue sampling (DPN/2D/2003/2267 and 4940-57/B-09-U265-LS-fd). In this study we did not apply laboratory techniques on living animals, therefore authorization from the Italian Ministry of Health was not required.

Sampling

Approximately 1 cm of tail was collected from 191 specimens of Z. vivipara coming from 51 locations throughout the central eastern Alps and Prealps (Figure 1 and Table S1a). All animals were released in their own habitat after pouring liquid sterilizer on the tail. Tissue samples were preserved in 95% ethanol and then stored at –80°C until molecular analyses were performed. To have a good representation of the whole geographic distribution and of the known subspecies within the Zootoca genus, 39 additional specimens were included in the nuclear marker analyses: their geographical origin and the subspecies they belong to is reported in Table S1b along with their mtDNA haplogroup (previously determined in [13], [18]).

thumbnail

Figure 1. Sampling sites of Zootoca vivipara sp. in Northern Italy.

Label, site names and coordinates are listed in Table S1a. Circles and triangles indicate locations where we found Z. v. vivipara and Z. v. carniolica, respectively, according to cytb results. The white line represents the Brenner line. Asterisks indicate locations for which at least one sample was analysed for nuclear genes.

doi:10.1371/journal.pone.0085912.g001

DNA Extraction, Amplification and Sequencing

DNA was extracted with the commercial QIAGEN DNeasy Tissue Kit (QIAGEN Inc., Hilden, Germany) according to manufacturer’s protocol. A 385 base pair (bp) fragment of mtDNA cytb gene was amplified using MVZ04 and MVZ05 primers [19]. The PCR amplification was carried out in a 20 µl reaction mix containing: 1 µl template DNA, HotMaster™ Taq Buffer 25 mM Mg2 (Eppendorf), 100 µM dNTPs, 10 µM of each primer, 0.5 mg/ml BSA and 1 unit of HotMaster™ Taq. The thermocycling regime consisted of incubation at 94°C for 10 min, followed by 35 cycles of 94°C for 1 min, 59°C for 45 s, and 65°C for 1 min, with a final extension of 65°C for 10 min. Moreover, three nuclear genes were investigated. A 572 bp fragment of oocyte maturation factor (C-mos) coding gene, a 447 bp fragment of acetylcholinergic receptor M4 (ACM4) gene and a portion of 579 bp of melanocortin receptor 1 (Mc1r) gene were amplified. All these nuclear sequences have been already used as phylogenetic markers in lacertid species [20], [21]. The amplification protocol consisted of an initial denaturation step at 94°C for 10 min, followed by 35 cycles of the series: 94°C for 1 min, annealing temperature (57°C for Hcmos3 and L-1zmos (C-mos, [20]); 59°C for MC1RF and MC1RR (Mc1r, [22]); 59°C for tg-F and tg-R (ACM4, [23]) for 45 s and 65°C for 1 min; then, a final extension step at 65°C for 10 min. For all amplifications, contamination was rigorously checked by means of blank samples in both extraction and PCR. Before sequencing, the excess primers and dNTPs were removed using ExoSAP-IT (USB Corporation, Cleveland, OH). Sequencing of double-stranded DNA was performed in both directions using a Big Dye Terminator cycle sequencing kit (Applied Biosystems) following manufacturer’s instructions; the sequencing reaction products were run on an ABI Prism 310 Genetic Analyzer (Applied Biosystems). The resulting sequences were edited with FinchTV version 1.4.0 (open source application developed by Geospiza Research Team), sequence fragments were assembled using Sequencher version 4.7 (Gene Codes. Corporation, USA), aligned using Clustal X [24], and checked by eye. All sequences have been deposited in GenBank database under Accession No. KF886538–KF886566.

Phylogenetic Analysis and Estimation of Divergence Time

We inferred phylogenetic relationships and divergence-times using a relaxed Bayesian molecular clock with an Uncorrelated Lognormal model (BEAST version 1.6; [25]) on a cytb dataset comprising 96 unique haplotypes (Z. vivipara of our study plus deposited sequences of Z. vivipara spp., Podarcis peloponnesiaca, Podarcis cretensis and Lacerta viridis as outgroup (GenBank accession numbers: Z. vivipara: AY714882–AY714929, Podarcis peloponnesiaca: AY896117–AY896123, Podarcis cretensis: AF486191–AF4861220 and Lacerta viridis: EU116514). JModelTest version 1.0.1 [26] was used to select the appropriate model of evolution for cytb gene under the Akaike Information Criterion AIC [27]. The GTR model of nucleotide substitution with gamma rate heterogeneity among sites and, as a prior, a Yule pure birth model of speciation to estimate the time of divergence between Z. v. carniolica and all the others Z. vivipara subspecies were used. The analysis was calibrated by setting an age prior on a single node: the divergence of Podarcis peloponnesiaca from Podarcis cretensis [28]. This divergence can be approximately posed during the Messinian geological events that occurred in Mediterranean Sea at around 5.2+− 0.1 Mya, when Crete became isolated from Peloponnese [29]. We adopted the vicariant event as the most likely explanation for biogeography of Mediterranean Isles as outlined by a previous study [30]. Posterior distributions for each parameter were obtained using a Monte Carlo Markov Chain (MCMC), which was run for 100 million generations, and sampled every 10000 generations. Inspection of the results using Tracer version 1.5 [31] confirmed that stationarity was achieved in all cases and that effective sample sizes (ESS) were adequate (all higher than 200). Trees were summarized as maximum clade credibility trees using the TreeAnnotator program which forms part of the BEAST package, and visualized using FigTree version 1.3.1 (http://tree.bio.ed.ac.uk/software/figtre​e). In each case, the first 10% of samples was discarded to avoid sampling the burn-in phase. A Bayesian Skyline Plot was also constructed with the software BEAST version 1.6 [25] using the GTR+G evolutionary model, a log-normal relaxed molecular clock with a mean substitution rate of 7.8×10e-9 per site per year and visualized with Tracer version 1.5 [25]. The evolutionary rate was calculated on the basis of the P. peloponnesiaca and P. cretensis divergence time. This analysis was run multiple times to check for convergence with 50 million iterations and samples drawn every 5000 MCMC steps, after a discarded burn-in of 5 million steps.

To confirm BEAST results and to get Bayesian posterior probability values of the tree we also applied MrBayes version 3.1.2 [32]. We ran the same dataset with 10 million generations (after this number of generations the standard deviation of split frequencies had reduced to less than 1%) with a sampling frequency of 1000, to be sure that a good sample of the posterior distribution had been obtained. The first 2500 sampled trees were discarded as ‘burn-in’ and posterior probabilities were calculated and reported on a 50% majority rule consensus tree of the remaining 7501 trees in the sample. The GTR+G evolutionary model was used. Moreover, a Maximum Likelihood analysis was performed with PAUP* version 4.0 [33] using tree-bisection-reconnection (TBR) branch swapping with 1000 rearrangements and 100 bootstrap replicates.

Additionally, we performed phylogenetic analyses based on three nuclear genes (C-mos, ACM4, Mc1r) on a subset of 92 samples of the entire dataset (64 samples from eastern Alps and 28 from the whole distributional range of the species), selected to include all the major cytb mtDNA clades. We performed phylogenetic tree reconstructions for each single nuclear gene and for a concatenated sequence of 1598 bp. We first applied PartitionFinder version 1.1.1 [34] in order to test the best partition scheme for codon positions and different single gene models of molecular evolution using the Bayesian information criterion (BIC). Four partitions were identified in nuclear sequences: ACM4 and C-mos 1st position (GTR+I+G), C-mos 2nd position (JC), C-mos 3rd position and Mc1r 3rd position (GTR) and Mc1r 1st and 2nd positions (HKY+I). These partitions and models were applied for performing phylogenetic reconstruction for each single nuclear gene and for the concatenated sequence using MrBayes version 3.1.2 [32] for Bayesian analyses with the same settings as for mtDNA; for Maximum Likelihood analyses we used RAxML (version 7.4.2, [35]) and each partition was run under GTR+G model. For nuclear phylogenetic reconstructions, we used Atlantolacerta andreanskyi as outgroup (accession numbers: JX485363, JX462052, JX461870), being the phylogenetically closest lacertid lizard with all three nuclear genes available [21]. We chosen not to concatenate mtDNA and nuclear genes, since we focused cytb analysis on the estimation of divergence time between Z. v. carniolica and Z. v. vivipara taking advantage of a calibrated external node dated on the divergence time between P. peloponnesiaca and P. cretensis. The three nuclear genes we analysed were not available for the latter species, therefore we ran nuclear analyses separately.

Using the median-joining algorithm in the Network version 4.5.1.0 software [36] we inferred a cytb mtDNA haplotype network, combining our sequences with all those already deposited in public repositories. After phasing nuclear genes with PHASE version 2.1 [37], Network version 4.5.1.0 [36] was also used to obtain haplotype networks of the three nuclear genes. Net nucleotide divergence (Da [38]), defined as distance between cytb clades, was calculated with MEGA version 4 [39]. Standard and molecular diversity indices, neutrality tests and mismatch distribution were calculated using ARLEQUIN version 3.11 [40]. Specific analyses on C-mos sequences for estimating the ratio, ω, between the rate of non-synonymous, dN, and synonymous, dS, substitutions were performed with DNAsp version 5 [41]. The gametic phase of nuclear markers was not considered in phylogenetic analyses.

Results

Cytb

A 385 bp portion of the mtDNA cytb gene was examined in our 191 Italian samples. A total of 28 polymorphic sites, all of which were parsimony-informative, and 11 haplotypes were identified. Five of these were new haplotypes, since no match was found with any previous published haplotype (Table S2). No deletions or insertions were observed in our dataset. Mean nucleotide percentage composition was T, 35.5; C, 25.3; A, 26.7; G, 12.4; the estimated transition/transversion ratio was 8.36. We reconstructed a phylogenetic tree using Italian samples from this study and deposited sequences from different clades and origins. The phylogenetic tree obtained using BEAST, ML and Bayesian inference (Figure 2), with Lacerta viridis as the outgroup, was topologically similar to others reported in the literature [12], [13]. Indeed, analyses showed clear separation between the clade A, including only Z. v. carniolica haplotypes and the remaining clades B, C, D, E and F, comprising all the other European Z. vivipara subspecies, which was well supported by bootstrap and posterior probability values. All Italian specimens clustered in two distinct clades: 42 were grouped in clade A, while 149 were placed in clade E, the western European viviparous clade in which only Z. v. vivipara individuals have been insofar included.

thumbnail

Figure 2. Maximum clade credibility tree from Bayesian analysis of mitochondrial cyt b with chronogram.

Bar around the 4.5Z. vivipara sp. vs Z. v. carniolica shows the 95% Credibility Interval. Bootstrap support values of Maximum Likelihood analysis >70% are shown above the branches, while posterior probability values of Bayesian Inference >0.7 are shown below the branches. Clade names as in Surget-Groba et al. (2002).

doi:10.1371/journal.pone.0085912.g002

Estimation of the divergence time between the Z. v. carniolica clade A and the clades (B, C, D, E and F) comprising all the other subspecies, namely Z. v. vivipara, Z v. louislantzi, and Z. v. pannonica was obtained by adding a prior of 5.2+- 0.1 Mya on the node separating P. cretensis from P. peloponnessiaca. Using this calibration, the divergence time between A and all the other clades was found to be 4.5 Mya with a 95% credibility interval between 6.1 and 2.6 Mya (Figure 2).

The median joining network (Figure 3) confirmed the clear separation in different clades. As before, 42 individuals of our data set were grouped into clade A, formed by Z. v. carniolica haplotypes from Slovenia, Italy and southern Austria [13], while the other 149 were included in clade E, consisting of haplotypes of Z. v. vivipara from northern and western Europe. This viviparous clade E showed a distinctive “star-shape” topology, suggesting that populations of this clade might have experienced a recent demographic expansion. Assuming neutrality, population expansion gives rise to an increase in the number of rarer haplotypes in the population under examination (star-shaped network), which also leads to a unimodal mismatch distribution. To further confirm this demographic scenario, we calculated the mismatch distribution (Figure 4) and the values of the D [42] and Fs [43] statistics, both of which were significantly negative: Tajima’s D = −2.207 and Fs = −24.700 (p<0.01). In the absence of selection, significantly negative values for both statistics are usually interpreted as a signature of population expansion events. Moreover, a confirmation of this demographic expansion was gained through the Bayesian coalescent-based skyline plot (Figure 4, inset a), showing a clear pattern of effective population size (Ne) increase in the last tens thousands years. In contrast to clade E, clade A (corresponding to subspecies Z. v. carniolica) did not present a star-shape topology (Figure 3) and both Tajima’s D and Fu’s Fs were not significantly different than 0 (data not shown), thus not showing any departure from neutrality. In addition, clade A showed a multimodal mismatch distribution (Figure S4) and no evidence of expansion through Bayesian skyline plot (Figure S4, inset a).

thumbnail

Figure 3. Median joining network of mtDNA cty b haplotypes.

Circles represent haplotypes, area is proportional to frequency and colour indicates the subspecies (black, Z. v. vivipara; white, Z. v. carniolica; grey, other subspecies or European populations).

doi:10.1371/journal.pone.0085912.g003
thumbnail

Figure 4. Z. v. vivipara (Clade E) cyt b mismatch distribution.

The number of nucleotide site differences between pair of individuals and the frequency of observation, are reported on the x- and y-axis respectively. Dashed and thick lines represent observed and expected (under sudden expansion model) distribution, respectively. In the inset: a) Bayesian skyline plot with median value and 95% Credibility Interval; b) mismatch distribution under demographic and spatial expansion model as in Excoffier (2004).

doi:10.1371/journal.pone.0085912.g004

Finally, we estimated the average number of nucleotide differences between the two groups (clade A and clade E) in which all our Italian individuals were divided: it was equal to 20.801+/−3.974 (SD), hence 0.054 per site. The number of net nucleotide substitutions per site between groups, Da, was 0.049, indicating an average difference of about 5%. The two groups did not share any substitution. The results, reported in Table 1, indicate that despite the lower number of individuals analysed, there was much higher genetic variation within Z. v. carniolica clade than in Z. v. vivipara clade E.

thumbnail

Table 1. Indices of genetic variability for the two subspecies at cyt b and nuclear markers.

doi:10.1371/journal.pone.0085912.t001

Nuclear Genes

We successfully analysed 92 samples (30 individuals belonging to clade A, 17 to clade B, 4 to clade D, 39 to clade E and 2 to clade F) with three different nuclear genes: C-mos, ACM4 and Mc1r.

In some Lacertid species the presence of several functional and non-functional copies of the C-mos gene has been reported [44]. Before any phylogenetic analysis, it is therefore important to verify that only orthologous C-mos sequences are used for comparisons. None of our sequences presented deletion, insertion or internal stop codons. The ratio ω (dN/dS) was significantly higher than 1, thus rejecting the hypothesis of neutrally evolving sequences, as expected in case of non-functional copies. We concluded that all our C-mos sequences were functional copies of the C-mos gene, being therefore orthologous.

The median joining network of the phased alleles of C-mos and Mc1r, showed that individuals belonging to mtDNA clade A (Z. v. carniolica) do not share any allele with individuals from other clades (Figure S2). In contrast, two out of five ACM4 alleles (ACM4_4 and ACM4_6) are shared among individuals of Z. v. carniolica and individuals of clades B (Z. v. louislantzi), D (Z. v. vivipara), E (Z. v. vivipara) and F (Z. v. vivipara). Similarly, phylogenetic trees obtained from each single nuclear gene suggested a highly supported (bootstrap and Bayesian posterior probability higher than 97% and 0.97, respectively) monophyly of Z. v. carniolica in C-mos and Mc1r (Figure S3), but not in ACM4. Phased alleles along with their accession numbers were listed in Table S2.

After concatenating the three genes, we obtained a 1598 bp sequence. Thirty-two variants out of the 92 sequences were identified. The tree topology obtained with different methods was concordant so that only the Maximum Clade Credibility Tree is presented in Figure 5. The tree showed two well supported clades. The first composed only of individuals belonging to mtDNA clade A, that is the Z. v. carniolica clade (90% and 0.84, bootstrap and Bayesian posterior probability, respectively), whilst the second consisted of individuals with mtDNA belonging to all the other clades, namely B (Z. v. louislantzi), D (Z. v. vivipara), E (Z. v. vivipara) and F (Z. v. vivipara). We did not get any reliable nuclear sequences from the only two individuals of clade C (Z. v. pannonica) at our disposal. Analysis of these nuclear markers, thus, confirmed the monophyly of Z. v. carniolica. At the same time, it confirmed that the other oviparous subspecies, Z. v. louislantzi, is much more closely related to the viviparous subspecies. Nuclear markers, therefore, indicated a likely reversal from viviparity to oviparity, as originally hypothesised by mtDNA results [13].

thumbnail

Figure 5. Maximum clade credibility tree of Bayesian analysis of three concatenated nuclear genes variants (C-mos, ACM4 and Mc1r).

Bootstrap support values of Maximum Likelihood analysis >70% are shown above the branches, while posterior probability values of Bayesian Inference >0.7 are shown below the branches. Atlantolacerta andreanskyi was used as outgroup.

doi:10.1371/journal.pone.0085912.g005

Discussion

ESU Status

Considering not only the reproductive mode but also mtDNA and karyological features, Surget-Groba et al. (2002) [9] proposed to consider Z. v. carniolica populations from Slovenia and northwestern/northeastern Italy as an Evolutionarily Significant Unit (ESU) following Moritz (1994) [15]. According to this definition, ESU status is evaluated by taking into account both mtDNA and nuclear loci: two populations would be considered ESUs if reciprocally monophyletic at mtDNA alleles and showing significant divergence of allele frequencies at nuclear loci [15]. Although Moritz’s ESU definition has been debated (e.g. [45]), it is nonetheless widely used in the conservation field. In particular, contrasting the patterns of mtDNA and nuclear variation is routine for testing the distinctiveness of natural populations (see [46]). Due to differences in effective population size and mutation rate, nuclear DNA loci attain monophyly at a considerably slower pace than mtDNA haplotypes. Instances of concomitant monophyly at mtDNA and nuclear loci imply, therefore, a long-term history of evolutionary separation. While it is arguable whether such a separation is sufficient for the recognition of different taxonomic units (e.g., under the genealogical species concept, [47]), its importance from an evolutionary and conservation perspective cannot be neglected.

In this survey we considered all the subspecies of the Zootoca genus: the results showed that Z. v. carniolica monophyly is strongly supported by both mtDNA (cytb; Fig. 2) and nuclear markers (C-mos, ACM4 and Mc1r; Figure 5) trees. In the concatenated nuclear markers tree, the other known oviparous subspecies, Z. v. louislantzi (mtDNA clade B), clustered within the same clade as Z. v. vivipara, (mtDNA clades D, E and F) from different origins within its distribution range. We could not incorporate any individual from the Z. v. pannonica subspecies (mtDNA clade C) due to poor DNA quality. However, if we consider the concordance between the mitochondrial- and nuclear-based phylogeny and the previously demonstrated inclusion of Z. v. pannonica in the same mtDNA clade as Z. v. vivipara and Z. v. louislantzi [13], this omission would not be expected to alter the overall scenario. To the best of our knowledge, this is the first phylogenetic inference based on nuclear DNA in Zootoca genus. The nuclear and mitochondrial DNA tree topologies support Z. v. carniolica monophyly, which is also essentially confirmed by the extent of nuclear allele sharing. Z. v. carniolica individuals do not share any allele with individuals from other subspecies at C-mos and Mc1r genes; just two out of the five alleles of ACM4, on the other hand, are shared among individuals of Z. v. carniolica, Z v. louislantzi and Z. v. vivipara, most likely due to the retention of ancestral polymorphism. Finally, the concordance between mitochondrial and nuclear markers confirms the reliability of mtDNA-based discrimination of the different subspecies. This can help to assess the geographic occurrence of Z. vivipara subspecies that, otherwise, might be problematic if based only on morphology.

Evolutionary, Demographic and Phylogeographical Scenarios

Adopting the mtDNA clades definition of Surget-Groba et al. (2006) [13], our investigation has been concentrated on clade A (eastern oviparous) and clade E (western viviparous) in a specific area (central-eastern Italian Alps) where distributions partially overlap.

The results of mtDNA and C-mos, in particular, showed much greater genetic variability in populations of Z. v. carniolica than in those of Z. v. vivipara (see Table 1), even though a far lower number of individuals of the latter have been analysed. Gene diversity was significantly higher in carniolica than in vivipara (z-test, p<0.05), in both the cytb and the C-mos.

Greater genetic diversity can be related to a longer evolutionary history (see [48]). In this case, the molecular data would confirm the phenotypic data with respect to reproductive mode, with oviparity being the ancestral condition. The reduced genetic variation of clade E (Z. v. vivipara) compared with clade A (Z. v. carniolica) could be associated to a small effective population size during the divergence from an oviparous form, followed by a more recent demographic expansion (see below) after the retreat of the ice from western central Europe.

From the phylogenetic tree (Figure 2) it emerges that oviparous clade A and viviparous clade E are not sister clades. It is, however, worth noting that the overall cytb phylogeny of the different oviparous (A and B) and viviparous (C, D, E and F) clades clearly shows that clade A is the sister clade to all the others. Our inference places the divergence of clade A at approximately 4.5 Mya (95% CI 6.1-2.6 Mya) that is during the Pliocene. This estimation should not be over-emphasized or, even worse, taken at face value. We obtained this estimated divergence time after setting, as geological calibration on the node separating P. cretensis from P. peloponnesiaca, the date the island of Crete presumably separated from the Peloponnese, according to geological evidence [29], that is 5.2 Mya before the present day. While having a more refined calibration would improve our estimate of the divergence time (see [49]), it nonetheless can be said that the sister oviparous clade A had a long evolutionary history since the original split from all the other clades of the species.

Another indication of the deep evolutionary distance between clade A and E stems from the number of differences in the cytb fragment. The average number of nucleotide differences between the two clades was 20.801+/−3.974 (hence 0.05403 per site), with a net nucleotide divergence of approximately 5% (Da = 0.049), which, for the mitochondrial cytb gene, indicates a rather large divergence. These figures are similar to observations between two distinct species belonging to a genus “close” to Zootoca: P. peloponnesiaca and P. cretensis. They showed an average number of nucleotide differences of 17.589+/−3.292 and Da of 0.047 for the same cytb marker [50].

The haplotype cytb network (Figure 3) shows another striking difference between the two subspecies: all our Z. v. vivipara individuals harbour haplotypes clustering in clade E, that is, according to its original definition [12], the western viviparous group. This clade is characterized by a “star-shape” topology, suggesting recent population expansion [51]. In contrast, all our Z. v. carniolica individuals have haplotypes belonging to clade A [12], and whose network does not present any particular topology. The indication of a demographic expansion in clade E can be further evaluated through the mismatch distribution graph (Figure 4). This graph shows a unimodal trend, which is again considered a signature of a recent demographic expansion [52]. Our distribution is not in contradiction with the theoretical model of Excoffier (2004) [52], describing an instantaneous range expansion in a two-dimensional stepping-stone model, with large migration rates and recent expansion (Figure 4, inset b). A plausible scenario would thus imply that, with the retreat of the ice in the post-Pleistocene era, populations of Z. v. vivipara belonging to clade E were able to spread into northwestern Europe (see [6]), leading to a simultaneous population and spatial expansion. The signature of this demographic expansion appears robust as it is also supported by the results of the neutrality tests (both Tajima’s D and Fu’s Fs, statistically significant and negative) and of the coalescent-based skyline plot [25] that shows a pattern of a relatively recent increase of Ne within clade E (Figure 4, inset a).

All the aforementioned demographic inferences are based on the assumption of neutrality for mtDNA cytb. Although the mitochondrial cytb marker was considered neutral in most of the previous studies on the phylogeography of Z. vivipara [9], [12], [13], a recent paper, focussed on a contact zone of two mtDNA Z. v. louislantzi lineages [18], questioned this assumption. The authors hypothesised a kind of thermal-related selection for explaining the differential survival of two subadults’ cytb haplogroups living in syntopy, in a secondary contact zone. It appears at least advisable to wait for new evidence (comparison of survivorship over a longer period) supporting this hypothesis. Moreover, we think that even if there is selection acting locally on mtDNA at a contact zone, it does not mean that we cannot recover a historical pattern (e.g. expansion) from other wider regions and for other lineages with allopatric distributions. Thus, we think that cytb can still be used for general demographic and phylogeographical inferences, especially if they are confirmed by other markers, like in our study.

Biogeographical Distribution

According to our results, 149 out of 191 individuals of our Italian samples were assigned to the subspecies Z. v. vivipara and 42 to the subspecies Z. v. carniolica. This allowed clarification of the situation surrounding the distribution of the two subspecies in the 51 sites sampled. In 15 sites only the subspecies Z. v. carniolica was found, while in 36 sites only the subspecies Z. v. vivipara was present (Figure 1).

According to our study, in the central-eastern Italian Alps Z. v. vivipara, on average, tends to live at higher altitudes (mean 1701 m) than Z. v. carniolica (mean 1210 m). Z. v. carniolica populations can be found at higher altitudes than initially thought: at sites above 1400 m in Trentino (Tremalzo 1545 m, Lago Nero 1625 m, Palù Longa 1435 m), in Veneto (Monte Grappa 1700 m), and in Lombardy (Branzi 1800 m, Ardesio 1600 m, Roncobello 1880 m). A high altitude (1900 m) population of Z. v. carniolica was also identified in Piedmont (northwestern Italy) by Ghielmi et al. [53], [54]. Z.v. carniolica and Z. v. vivipara exhibit an indisputable overlap of their altitudinal distributions in the Italian Alps, similarly to other areas such as Carinthia, Austria, where the two subspecies have even been found in syntopy in a site at 1575 m [10].

The geographical distribution of the different haplotypes (Figure 3) corresponds to a biogeographical limit called the ‘Brenner line’ (i.e. a longitudinal line from the Adige Valley up to the Brenner Pass, Figure 1). This line has been recognized as delimiting eastern and western distributions of many plant species since the 19th century ([55] and see other examples below). All populations of Z. v. vivipara on the east of this line have VB11 (or derived haplotypes), while all population on the west have VB1 (or derived haplotypes). The only exception is one sample in population 12, which is on the west but shows VB11. The same pattern of east-west division by the Brenner line seems to hold for our Z. v. carniolica haplotypes of clade A. In this case, haplotypes OS8 and OT_11 belong only to individuals from sites east of this line. These two haplotypes cluster together with OS9, a haplotype described by Surget-Groba et al., (2006) [13] and found in individuals from the Italian province of Udine that is located far east of the Brenner line.

The nuclear marker phylogenetic tree does not present the same biogeographical pattern: it is likely that the slow mutation rate of these markers limits their phylogeographical informativeness.

Further research with markers better suited for fine-scale population genetics analyses, such as microsatellites, could confirm this preliminary indication of a possible east-west differentiation along the Brenner line. This pattern would be in line with what have been already found in the high-altitude butterfly, Erebia euryale [56], in an Alpine form of rampion, Phyteuma globulariifolium, in the alpine speedwell, Veronica alpina, [57], [58] and in many other plant species [59], [60].

Implications for Conservation

Considering the evidence from karyotype to cytb variation, and the results of our study, the distinction between Z. v. vivipara and Z. v. carniolica can be regarded as evolutionarily substantial. While it is arguable whether such distinction deserves a taxonomical revision, we think that nonetheless it has some important consequences for conservation. In our view, proposing specific conservation action for Z. v. carniolica is further strengthened by a number of important aspects.

The low and medium altitude peatland habitats that Z. v. carniolica prefers are already thought to be at high risk of extinction [61]. Indeed, the European Habitats Directive 43/92/CEE has classified active raised bogs (Natura Code 2000: 7110), transition and quaking bogs (7140), and alkaline fens (7230) as either threatened (7140, 7230) or even seriously threatened (7110). In particular, peatlands across the Alps are suffering from a reduction in both the surface area of individual peatlands and their total number.

Moreover, a study on the peat bogs of Italian Alps [62] revealed that heat waves, like that of 2003, affected the survival of organisms such as peat mosses (genus Sphagnum), which play a crucial role in maintaining bog functionality (i.e. carbon storage). Such a drastic change in mountain peat bogs due to just a single summer of higher temperatures and reduced rainfall represents a major concern with respect to the conservation status of this habitat. Exceptionally hot European summers, like that of 2003, may occur more frequently given recent climatic changes, bringing perilous consequences for mountain peatlands and their associated flora and fauna like Z. v. carniolica.

Conclusions

The main conclusion of our study is that the reciprocal monophyly between the oviparous subspecies Z. v. carniolica and all the other Z. vivipara subspecies has been proved for the first time using nuclear DNA markers This now makes it possible to properly consider Z. v. carniolica as an ESU. The macro- and micro-scale analysis of the evolutionary history of Z. v. carniolica allowed us to reach the following conclusions: i) according to an external fossil calibration, the divergence time between Z. v. carniolica and all the other subspecies took place at least 2.6 millions years before the present day, thus corresponding to a relatively long time of evolutionary separation; ii) also in terms of demographic history, there is a remarkable difference: Z. v. carniolica does not show any signature of expansion as it occurs in the most widespread Z. v. vivipara clade (clade E of central-northern Europe); iii) the genetic evidence of this study, together with the vulnerability of Z. v. carniolica most suitable habitats (i.e. low-mid altitudes peat bog), suggests specific action tailored to this subspecies.

While future studies could better address the recent findings of sintopy and of possible hybridization between Z. v. carniolica and Z. v. vivipara [10], a clear evolutionarily and demographic distinction has now been demonstrated, much likely prompting a taxonomical revision.

Supporting Information

Figure S1.

Distribution of Zootoca subspecies. Highlighted rectangle represents the area of the study.

doi:10.1371/journal.pone.0085912.s001

(TIF)

Figure S2.

Median joining network of three nuclear genes. Circles represent phased alleles, area is proportional to frequency and colour indicates the mtDNA clade (see legend).

doi:10.1371/journal.pone.0085912.s002

(TIF)

Figure S3.

Maximum clade credibility trees of Bayesian analyses of three nuclear genes. Bootstrap support values of Maximum Likelihood analysis >70% are shown above the branches, while posterior probability values of Bayesian Inference >0.7 are shown below the branches. Atlantolacerta andreanskyi was used as outgroup.

doi:10.1371/journal.pone.0085912.s003

(TIF)

Figure S4.

Z. v. carniolica (Clade A) cyt b mismatch distribution. The number of nucleotide site differences between pair of individuals and the frequency of observation, are reported on the x- and y-axis respectively. Dashed and thick lines represent observed and expected (under sudden expansion model) distribution, respectively. In the inset a) the Bayesian skyline plot and 95% Credibility Interval.

doi:10.1371/journal.pone.0085912.s004

(TIF)

Table S1.

Tables S1a and S1b. a. (Supporting Figure 1) Sampling sites details across Italian Alps. Number of samples collected for each site (N), GPS Coordinates, Altitude and mtDNA cyt b haplotype and alleles observed for each nuclear gene. Numbers in brackets refer to allele frequencies. Table S1b. (Supporting Figure S1) Sampling sites details across Europe. Number of samples for each site (N), Country, subspecies, mtDNA clade and alleles observed for each nuclear gene. Numbers in brackets refer to haplotypes (mtDNA) and allele frequencies (nuclear genes). * Heulin et al. (2011) § Surget-Groba et al. (2006).

doi:10.1371/journal.pone.0085912.s005

(PDF)

Table S2.

Sequence accession numbers. MtDNA haplotypes and phased nuclear alleles sequences found in this study and their relative database accession number.

doi:10.1371/journal.pone.0085912.s006

(PDF)

Acknowledgments

Barbara Crestanello and Alexis Marchesini are warmly thanked for their help during sampling, molecular and data analyses. Map of sampling sites and editing of figures have been made possible with the help of Clara Tattoni and Andrea Gandolfi. Thanks are due to Samuele Ghielmi for comments and information on sampling sites. Giorgio Bertorelle, Gabriele Gentile, Jim P. Arntzen and Sean Hoban provided us with helpful suggestions that significantly improved an earlier version of the manuscript. We also thank Dan Sargent for the final linguistic revision. Finally, we would like to thank the contribution of two anonymous reviewers that helped us significantly improve the manuscript.

Author Contributions

Conceived and designed the experiments: LC CV. Performed the experiments: LC. Analyzed the data: LC CV. Contributed reagents/materials/analysis tools: MM GG BH. Wrote the paper: LC BH CV.

References

  1. 1. Blackburn DG (1994) Discrepant usage of the term “ovoviviparity” in the herpetological literature. Herpetol J 4: 65–72.
  2. 2. Dely O, Böhme W (1984) Lacerta vivipara Jacquin, 1787, Waldeidechse, In: Handbuch der Reptilien und Amphibien Europas, 2–1, Echsen II, (Ed. W. Böhme), 362–393.
  3. 3. Arribas OJ (2009) Morphological variability of the Cantabro-Pyrenean populations of Zootoca vivipara (JACQUIN, 1787) with description of a new subspecies. Herpetozoa 21: 123–146.
  4. 4. Braña F, Bea A (1987) Bimodalite de reproduction chez Zootoca vivipara. Bulletin de la Société Herpétologique de France 44: 1–5.
  5. 5. Heulin B (1988) Donnees nouvelles sur les populations ovipares de Lacerta vivipara. C.R Acad Sci Pans 306 (ser III) 63–68.
  6. 6. Heulin B, Guillaume C, Bea A, Arrayago MJ (1993) Interprétation biogéographique de la bimodalité de reproduction du lézard Lacerta vivipara: un modèle pour l’étude de l’évolution de la viviparité. Biogeographica 69: 1–11.
  7. 7. Mayer W, Böhme W, Tiedemann F, Bischoff W (2000) On oviparous populations of Zootoca vivipara (Jacquin, 1787) in southeastern Central Europe and their phylogenetic relationship to neighbouring viviparous and Southwest European oviparous populations. Herpetozoa 13: 59–69.
  8. 8. Heulin B, Guillaume CP, Vogrin N, Surget-Groba Y, Tadic Z (2000) Further evidence of the existence of oviparous populations of Lacerta (Zootoca) vivipara in the NW of the Balkan Peninsula. Comptes Rendus de l’ Academie des Sciences. Serie III 5: 461–468. doi: 10.1016/s0764-4469(00)00155-4
  9. 9. Surget-Groba Y, Heulin B, Ghielmi S, Guillaume CP, Vogrin N (2002) Phylogeography and conservation of the populations of Zootoca vivipara carniolica. Biol Conserv 106: 365–372. doi: 10.1016/s0006-3207(01)00263-4
  10. 10. Lindtke D, Mayer W, Böhme W (2010) Identification of a contact zone between oviparous and viviparous common lizards (Zootoca vivipara) in central Europe: reproductive strategies and natural hybridization. Salamandra 46: 73–82.
  11. 11. Odierna G, Heulin B, Guillaume CP, Vogrin N, Aprea G, et al. (2001) Evolutionary and biogeographical implications of the karyological variations in the oviparous and viviparous forms of Lacerta vivipara. Ecography 24: 332–340. doi: 10.1034/j.1600-0587.2001.240311.x
  12. 12. Surget-Groba Y, Heulin B, Guillaume CP, Thorpe RS, Kupriyanova L, et al. (2001) Intraspecific Phylogeography of Lacerta vivipara and the Evolution of Viviparity. Mol Phylogenet Evol 18: 449–459. doi: 10.1006/mpev.2000.0896
  13. 13. Surget-Groba Y, Heulin B, Guillaume CP, Puky M, Semenov D, et al. (2006) Multiple origins of viviparity, or reversal from viviparity to oviparity? The European common lizard (Zootoca vivipara, Lacertidae) and the evolution of parity. Biol J Linn Soc 87: 1–11. doi: 10.1111/j.1095-8312.2006.00552.x
  14. 14. Lác J, Kluch E (1968) Die Bergeidechse der Ostslowakischen Tiefebene als selbstandige Unterart Lacerta vivipara pannonica n. subsp. Zoologicke listy 17: 157–173.
  15. 15. Moritz C (1994) Defining ‘evolutionary significant units’ for conservation. Trends Ecol Evol 9: 373–375. doi: 10.1016/0169-5347(94)90057-4
  16. 16. Giovine G (1989) Indagine preliminare su Lacerta (Zootoca) vivipara nelle Prealpi bergamasche e nelle aree limitrofe. Bollettino Gruppo R.A.N.A. 1: 59–67.
  17. 17. Mazzoni S, Stagni G (1993) Gli anfibi e i rettili dell’Emilia-Romagna (Amphibia, Reptilia). Quad. Stn. Ecol. civ. Mus. Stor. nat. Ferrara 5: 1–148. doi: 10.1163/156853895x00262
  18. 18. Heulin B, Surget-Groba Y, Sinervo B, Miles D, Guiller A (2011) Dynamics of haplogroup frequencies and survival rates in a contact zone of two mtDNA lineages of the lizard Lacerta vivipara. Ecography 34: 436–447. doi: 10.1111/j.1600-0587.2010.06540.x
  19. 19. Smith MF, Patton JL (1991) Variation in mitochondrial cytochrome b sequence in natural populations of South American akodontine rodents (Muridae: Sigmodontinae). Mol Biol Evol 8: 85–103.
  20. 20. Mayer W, Pavlicev M (2007) The phylogeny of the family Lacertidae (Reptilia) based on nuclear DNA sequences: convergent adaptations to arid habitats within the subfamily Eremiainae. Mol Phylogenet Evol 44: 1155–1163. doi: 10.1016/j.ympev.2007.05.015
  21. 21. Barata M, Carranza S, Harris DJ (2012) Extreme genetic diversity in the lizard Atlantolacerta andreanskyi (Werner, 1929): A montane cryptic species complex. BMC Evol Biol 12: 167. doi: 10.1186/1471-2148-12-167
  22. 22. Pinho C, Rocha S, Carvalho BM, Lopes S, Mourao S, et al. (2010) New primers for the amplification and sequencing of nuclear loci in a taxonomically wide set of reptiles and amphibians. Conserv Genet Res 2: 181–185. doi: 10.1007/s12686-009-9126-4
  23. 23. Gamble T, Bauer AM, Greenbaum E, Jackman TR (2008) Out of the blue: a novel, trans-Atlantic clade of geckos (Gekkota, Squamata). Zool Scr 37: 355–366. doi: 10.1111/j.1463-6409.2008.00330.x
  24. 24. Thompson JD, Gibson TJ, Plewniak F, Jeanmougin F, Higgins DG (1997) The ClustalX windows interface: flexible strategies for multiple sequence alignment aided by quality analysis tools. Nucleic Acids Res 24: 4876–4882. doi: 10.1093/nar/25.24.4876
  25. 25. Drummond AJ, Rambaut A (2007) BEAST: Bayesian evolutionary analysis by sampling trees. BMC Evol Biol 7: 214. doi: 10.1186/1471-2148-7-214
  26. 26. Posada D (2009) Selection of models of DNA evolution with JModelTest. Method Mol Biol 537: 93–112. doi: 10.1007/978-1-59745-251-9_5
  27. 27. Posada D, Buckley TR (2004) Model selection and model averaging in phylogenetics: Advantages of Akaike Information Criterion and Bayesian approaches over Likelihood Ratio Tests. Syst Biol 53: 793–808.
  28. 28. Lymberakis P, Poulakakis N, Kaliontzopoulou A, Valakos E, Mylonas M (2008) Two new species of Podarcis (Squamata; Lacertidae) from Greece. Syst Biodivers 6: 307–318. doi: 10.1017/s1477200008002727
  29. 29. Beerli P, Hotz H, Uzzell T (1996) Geologically dated sea barriers calibrate an average protein clock in water frogs of the Aegean region. Evolution 50: 1676–1687. doi: 10.2307/2410903
  30. 30. Runemark A, Hey J, Hansson B, Svensson EI (2012) Vicariance divergence and gene flow among islet populations of an endemic lizard. Mol Ecol 21: 117–29. doi: 10.1111/j.1365-294x.2011.05377.x
  31. 31. Rambaut A, Drummond AJ (2007) Tracer v1.5 Available from http://beast.bio.ed.ac.uk/Tracer.Accessed 2013 Dec 11.
  32. 32. Ronquist F, Huelsenbeck JP (2003) MRBAYES 3: Bayesian phylogenetic inference under mixed models. Bioinformatics 19: 1572–1574. doi: 10.1093/bioinformatics/btg180
  33. 33. Swofford DL (2003) PAUP*. Phylogenetic Analysis Using Parsimony (*and Other Methods). Version 4. Sinauer Associates, Sunderland, Massachusetts.
  34. 34. Lanfear R, Calcott B, Ho SYW, Guindon S (2012) PartitionFinder: Combined Selection of Partitioning Schemes and Substitution Models for Phylogenetic Analyses. Mol Biol Evol 29: 1695–1701. doi: 10.1093/molbev/mss020
  35. 35. Stamatakis A (2006) RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models. Bioinformatics 22: 2688–2690. doi: 10.1093/bioinformatics/btl446
  36. 36. Bandelt HJ, Forster P, Röhl A (1999) Median-joining networks for inferring intraspecific phylogenies. Mol Biol Evol 16: 37–48. doi: 10.1093/oxfordjournals.molbev.a026036
  37. 37. Stephens M, Donnelly P (2003) A comparison of Bayesian methods for haplotype reconstruction from population genotype data. Am J Hum Genet 73: 1162–1169. doi: 10.1086/379378
  38. 38. Nei M (1987) Molecular Evolutionary Genetics. Columbia University Press, New York, NY.
  39. 39. Kumar S, Dudley J, Nei M, Tamura K (2008) MEGA: A biologist-centric software for evolutionary analysis of DNA and protein sequences. Brief Bioinform 9: 299–306. doi: 10.1093/bib/bbn017
  40. 40. Excoffier L, Laval G, Schneider S (2005) Arlequin ver. 3.0: An integrated software package for population genetics data analysis. Evol Bioinform Online 1: 47–50.
  41. 41. Librado P, Rozas J (2009) DnaSP v5: A software for comprehensive analysis of DNA polymorphism data. Bioinformatics 25: 1451–1452. doi: 10.1093/bioinformatics/btp187
  42. 42. Tajima F (1989) Statistical methods to test for nucleotide mutation hypothesis by DNA polymorphism. Genetics 123: 585–595.
  43. 43. Fu YX (1997) Statistical tests of neutrality of mutations against population growth, hitchhiking and background selection. Genetics 147: 915–925.
  44. 44. Pavlicev M, Mayer W (2006) Multiple copies of coding as well pseudogene c-mos sequence exist in three Lacertid species. J Exp Biol 360B: 539–550. doi: 10.1002/jez.b.21110
  45. 45. Crandall KA, Bininda-Emonds ORP, Mace GM, Wayne RK (2000) Considering evolutionary processes in conservation biology. Trends Ecol Evol 17: 390–395. doi: 10.1016/s0169-5347(00)01876-0
  46. 46. Frankham R, Ballou JD, Briscoe DA (2002) Introduction to Conservation Genetics. Cambridge University Press, Cambridge, UK.
  47. 47. Baum DA, Shaw KL (1995) Genealogical perspective on the species problem. In: Hoch, P.C and Stephenson A.G., eds. In: Experimental and molecular approaches to plant biosystematics. St. Louis (MO), Missouri Botanical Garden, 289–303.
  48. 48. Hartl DL, Clark AG (2006) Principles of Population Genetics. Sinauer Associates Inc, Sunderland, MA.
  49. 49. Yang Z, Yoder AD (2003) Comparison of Likelihood and Bayesian Methods for Estimating Divergence TimesUsing Multiple Gene Loci and Calibration Points, with Application to a Radiation of Cute-Looking Mouse Lemur Species. Syst Biol 52: 705–716.
  50. 50. Slatkin M, Hudson RR (1991) Pairwise comparisons of DNA mitochondrial sequences in stable and exponentially growing populations. Genetics 129: 555–562.
  51. 51. Rogers AR, Harpending H (1992) Population growth make waves in the distribution of pairwise genetic differences. Mol Biol Evol 9: 552–569.
  52. 52. Excoffier L (2004) Patterns of DNA sequence diversity and genetic structure after a range expansion: lessons from the infinite-island model. Mol Ecol 12: 853–64. doi: 10.1046/j.1365-294x.2003.02004.x
  53. 53. Ghielmi S, Heulin B, Surget-Groba Y, Guillaume CP (2001) Identification de populations ovipares de Lacerta (Zootoca vivipara) en Italie. Bull. Soc. Herpetol. Fr. 98: 19–29.
  54. 54. Ghielmi S, Bergò PE, Andreone F (2006) Nuove segnalazioni di Zootoca vivipara, Jaquin e di Vipera berus Linnaeus, in Piemonte, Italia nord-occidentale. Acta Herpetol 1: 29–36.
  55. 55. Kerner A (1870) Die natürlichen Floren im Gelände der Deutschen Alpen. Fromann, Jena.
  56. 56. Haubrich K, Schmitt T (2007) Cryptic differentiation in alpine-endemic, high-altitude butterflies reveals down-slope glacial refugia. Mol Ecol 16: 3643–3658. doi: 10.1111/j.1365-294x.2007.03424.x
  57. 57. Schönswetter P, Tribsch A, Barfuss M, Niklfeld H (2002) Several Pleistocene refugia detected in the high alpine plant Phyteuma globulariifolium Sternb. & Hoppe (Campanulaceaea) in the European Alps. Mol Ecol 11: 2637–2647. doi: 10.1046/j.1365-294x.2002.01651.x
  58. 58. Albach DC, Schönswetter P, Tribsch A (2006) Comparative phylogeography of the Veronica alpina complex in Europe and North America. Mol Ecol 15: 3269–3286. doi: 10.1111/j.1365-294x.2006.02980.x
  59. 59. Thiel-Egenter C (2007) Inter- and Intraspecific Differentiation and Genetic Diversity in Alpine Plants: When Phylogeography Meets Biogeography. PhD Thesis. University of Zurich, Zurich, Switzerland.
  60. 60. Thiel-Egenter C, Holderegger R, Brodbeck S, IntraBioDiv-Consortium, Gugerli F (2009) Concordant genetic breaks, identified by combining clustering tessellation methods, in two co-distributed alpine plant species. Mol Ecol 18: 4495–4507. doi: 10.1111/j.1365-294x.2009.04360.x
  61. 61. Moore PD (2002) The future of cool temperate bogs. Environ Conserv 29: 3–20. doi: 10.1017/s0376892902000024
  62. 62. Bragazza L (2008) A climatic threshold triggers the die-off of peat mosses during an extreme heat wave. Glob Change Biol 14: 2688–2695. doi: 10.1111/j.1365-2486.2008.01699.x