Using Statistical Phylogeography to Infer Population History: Case Studies on Pimelia Darkling Beetles from the Canary Islands

ARTICLE IN PRESS

Journal of Arid Environments Journal of Arid Environments 66 (2006) 477–497 www.elsevier.com/locate/jnlabr/yjare

Using statistical phylogeography to infer population history: Case studies on Pimelia darkling beetles from the Canary Islands

O´ . Moyaa, H.G. Contreras-Dı´ aza,b, P. Oromı´ b, C. Juana,Ã

aDepartament de Biologia, Universitat de les Illes Balears, 07122 Palma de Mallorca, Spain bDepartamento de Biologı´a Animal, Facultad de Biologı´a, Universidad de La Laguna, 38205 La Laguna, Tenerife, Spain

Available online 3 March 2006

Abstract

Sequence data from a 200 bp fragment of the Cytochrome Oxidase I mitochondrial gene was derived from endemic populations of the darkling beetle Pimelia laevigata (Coleoptera, Tenebrionidae) from the volcanic islands of La Gomera, La Palma and El Hierro and from three related congeneric species of Tenerife (Canary Islands). Statistical phylogeographic methods and estimates of demographic parameters suggest that there is a higher genetic variation and geographical structure in two of the Tenerife nominal species than in populations of P. laevigata in the western islands. In La Gomera, La Palma and El Hierro, the patterns are consistent with relatively recent colonizations, followed by range expansions. The results show that hypotheses based on coalescent theory can be useful to reconstruct historic biogeographical events of oceanic islands in a range of different organisms provided that the sample design is adequate and enough genetic resolution is present. However, some speciﬁc problems arise when interpreting the inference key applied to the volcanic islands populations. r 2006 Elsevier Ltd. All rights reserved.

Keywords: Mitochondrial DNA; Nested clade phylogeographic analysis; Colonization; Population expansion; Arid regions; Darkling beetles

ÃCorresponding author. Tel.: +34 971173425; fax: +34 971173184. E-mail address: [email protected] (C. Juan).

1. Introduction

The application of phylogenetic methods to understand the extent of genetic variation in space and time among populations or related taxa has emerged as a major issue in evolutionary and conservation biology. Different theoretical approaches exist in relation to this topic, but the more common and recent uses coalescent theory (Kingman, 1982a, b) as a conceptual framework to estimate different population parameters and understand demographic histories (see Emerson et al., 2001; Knowles, 2004). The inferences obtained by these methods are based on statistical tests of historical hypotheses and estimates of demographic parameters, in contrast with the ‘‘classical’’ intuitive phylogeographic methodology developed by Avise (1998), which is based on inferring the causes of an association between observed patterns of genetic variation and the geographical distribution of populations (Knowles, 2004). Nested clade phylogeographic analysis (NCPA) is one of the statistical approaches applied to intraspecific or closely related species gene genealogies. It combines genealogical data through haplotype networks obtained using statistical parsimony and geographical information to infer historical range distribution of haplotypes and range movements (Templeton et al., 1995; Templeton, 1998, 2004; Posada and Crandall, 2001). The Hawaiian, Gala´ pagos and Canary volcanic island chains have become models in evolutionary studies, as they are true microcosms of evolutionary processes (Emerson, 2002). Recently, the ease in obtaining DNA sequence data, and the improvement of phylogenetic methods, have promoted their application to many different speciose endemic organisms from the Canary and other Macaronesian archipelagos, including vertebrate and arthropod groups (e.g. Juan et al., 1995, 1998, 2000; Brown and Pestano, 1998; Emerson et al., 1999, 2000a–c; Carranza et al., 2001; Rees et al., 2001a, b; Contreras-Dı´ az et al., 2003). The molecular phylogenies provide a hypothesis of relationships of taxa, that can be used for testing the mono- or polyphyly of a particular group of taxa on the islands, understanding colonization sequences, disentangling extinction, hybridization and lineage sorting effects, or even comparing island specia- tion rates with the corresponding continental relatives (Emerson, 2002). Several studies have used Canary Island beetles and mitochondrial DNA sequences at the population or the species level, to study the geographical distribution of genetic diversity (phylogeography). They generally have found consistencies with the known geographical volcanic evolution of the island chain or different volcanic regions within a single island. For example, two clear divergent mitochondrial lineages in Pimelia (Coleoptera, Tenebrionidae) from Tenerife were deduced to relate to expansion from the older isolated areas of the island (Juan et al., 1996). In the Fuerteventura and Lanzarote endemic darkling beetle Hegeter deyrollei (formerly H. politus), a sequential expansion of the populations concomitant with the cessation of volcanism was inferred (Juan et al., 1998). Emerson et al. (2000a) showed for the weevil Brachyderes rugatus that the mitochondrial haplotypes of populations from the four subspecies occurring in Gran Canaria, Tenerife, La Palma and El Hierro belong to two different monophyletic clades and suggested a recent origin and a possible colonization sequence for this group in the Canary Islands. Darkling beetles (Coleoptera, Tenebrionidae) constitute important elements of the arid and semi-arid terrestrial ecosystems, because of their high biomass and role as detritivores (De los Santos et al., 2000, 2002a, b). They show adaptations such as diurnal and seasonal ARTICLE IN PRESS O´. Moya et al. / Journal of Arid Environments 66 (2006) 477–497 479 rhythms of activity, resistance to desiccation and adaptation to high temperatures and ultra-violet light (Cloudsley-Thompson, 1964) as well as tolerance to low temperatures on high mountains (Ottesen and Sømme, 1987). The study of genetic diversity within darkling beetle species and populations can help not only to understand adaptive trends in these insects in relation to environmental factors, but also to give a historic perspective to the biogeography of these key organisms in arid/semi-arid environments. For example, in a previous study we analysed the phylogeography of the Pimelia endemic species of the island of Gran Canaria (Contreras-Dı´ az et al., 2003) and the results helped to establish evolutionary units for conservation purposes. Here we have studied populations of Pimelia species endemic to four islands of the Canary archipelago. New samples of three species (Pimelia canariensis, P. ascendens and P. radula) occurring on Tenerife are added to a previous mitochondrial sequence data set published elsewhere (Juan et al., 1996). Using these more extensive population and species samples, a re-analysis is performed using new phylogeographic approaches (Templeton, 2004). Pimelia canariensis is included in the List of Threatened Species in the Canaries as a ‘‘species sensitive to habitat disturbance’’. We also analyse populations of P. laevigata,a species endemic to the three westernmost Canary islands, which according to immunological and numerical taxonomy studies (Oromı´ , 1979) and in agreement with a previous morphological taxonomy (Espanõl, 1961) includes three different subspecies. Pimelia l. ssp. validipes is present in La Gomera (another Pimelia species occurs in this island but it derives from an independent colonization event, see Contreras-Dı´ az et al., 2003), Pimelia l. ssp. laevigata in La Palma and P. l. ssp. costipennis in El Hierro. The three subspecies of P. laevigata are broadly distributed on their correspondent islands, occurring from arid and semi-arid lowland environments to high altitude alpine dry areas, but always avoiding forests. In a previous study based on mitochondrial DNA sequences, the three P. laevigata subspecies were shown to form a monophyletic group apparently derived from Tenerife ancestors, following the east to west and older to younger island general colonization pattern (Juan et al., 1995). The Canary Islands are of independent volcanic origin, so colonization has to be performed across the deep waters separating them. Although we do not have a priori knowledge of when colonization of La Gomera took place, this island has been available for a much longer period to support founders than the two other islands. La Gomera has been estimated to be of a maximum age about 10 million years ago (Ma), while La Palma has been dated at 2 Ma and El Hierro less than 1 Ma (Ancochea et al., 1990; Fuster et al., 1993; Carracedo et al., 1998). We have sampled P. laevigata populations on the above three islands, to include a representation of the entire geographic range of the species, and we obtained DNA sequences for a short fragment of about 200 bp of Cytochrome Oxidase I (COI) mitochondrial gene. This fragment showed enough variation to resolve the major mitochondrial lineages of closely related species and populations of Tenerifean Pimelia in a previous study (Juan et al., 1996), so its use here allows a comparison of P. laevigata sequence diversity with that previously obtained for their Tenerife relatives. The main questions we want to address are: (i) What is the genetic differentiation among P. laevigata subspecies? (ii) Is there geographical structuring among P. laevigata populations within each of the three islands where they occur? and (iii) Can NCPA and demographic inferences help to elucidate the population history processes of relatively recent colonizers, such as the diversification of Pimelia beetles in Tenerife and their relation to western Canary Islands taxa? ARTICLE IN PRESS 480 O´. Moya et al. / Journal of Arid Environments 66 (2006) 477–497

2. Material and methods

2.1. Sampling

Beetles were collected in Tenerife, La Gomera, La Palma and El Hierro islands of the Canary archipelago. Fig. 1 shows the locations and codes of the samples obtained in this study along with those sampled by Juan et al. (1996). Details of collection localities, geographic co-ordinates, haplotype denominations and sample sizes are given in Appendix A. Samples were stored in absolute ethanol until DNA extractions were performed.

2.2. DNA extractions, PCR ampliﬁcations and sequencing

A leg or head from each specimen was used for DNA puriﬁcation with a standard protocol (see Contreras-Dı´ az et al., 2003). In some cases, the DNeasy Tissue extraction kit (Qiagen) was used following the manufacturer’s recommendations. Pellets were resuspended in 25–50 mL of Tris-EDTA buffer and 1 mL of the dilution was used for PCR ampliﬁcation of the fragment of COI with one unit of Taq DNA polymerase (Ecogen). The primers used were: (50-ACAGGAATTAAAGTTTTTAGATGATTAGC-30) and (50-ATAGGGGGAATCAGTGAACTAGTCC-30)(Juan et al., 1996). PCR conditions

Fig. 1. Map indicating the sampling design and the areas successfully surveyed in Tenerife, La Gomera, La Palma and El Hierro. Codes included in rectangles correspond to samples obtained in Tenerife in the previous study (Juan et al., 1996). Symbols refer to the different species/subspecies as follows: filled squares P. ascendens, empty squares P. canariensis, empty circle P. r. radula, filled circle P. r. oromii, and filled triangles for P. laevigata. The population codes correspond to the ones listed in Appendix A. ARTICLE IN PRESS O´. Moya et al. / Journal of Arid Environments 66 (2006) 477–497 481 were as follows: 4 min at 95 1C followed by 35 cycles of denaturation at 95 1C for 30 s, annealing at 50 1C for 1 min, and extension at 72 1C for 1 min, with a final single extra extension step at 72 1C for 10 min. PCR products were checked in a 1% agarose gel and the products of the expected length were precipitated with ammonium acetate 5 M and isopropanol. The forward, and reverse strands in the cases where sequence ambiguities were detected, were cycle-sequenced using an Applied Biosystems ABI Prism DYE Terminator Cycle Sequencing Reaction Kit and sequenced in an ABI 377 automated sequencer. A common fragment of about 200 bp was sequenced for all samples. An alignment of all the sequences used in this study has been deposited in the EMBL database under accession number ALIGN-000819.

2.3. Phylogenetic analyses

Sequences were aligned using the ClustalX program (Thompson et al., 1997) and no length differences were found in the alignments. ModelTest (version. 3.06; Posada and Crandall, 1998) was used to select the substitution model(s) that best described the data under the Akaike information criterion, and PAUP* vs. 4.0b10 (Swofford, 2002) was used to calculate sequence divergences and obtain phylogenetic trees. Neighbour-joining (NJ) and maximum parsimony trees were obtained, the latter using heuristic searches with tree- bisection-reconnection as the branch-swapping algorithm and the starting tree was obtained via stepwise addition with random addition of sequences with 100 replicates. The sequence from P. lutaria, endemic to Fuerteventura and basal to all congeneric Canarian species, as was demonstrated by using different mitochondrial and nuclear markers (Pons et al., 2004), was used as outgroup. Bootstrap values were estimated with heuristic searches using 500 pseudo-replicates.

2.4. Molecular diversity and population dynamics

Estimates of mean nucleotide and haplotype diversities within each species and populations were obtained with the program DnaSP vs. 4.0 (Rozas et al., 2003). Mismatch analysis of COI mitochondrial sequences (frequency of pairwise differences between haplotypes) was performed to explore the demographic history of the studied populations. This method is based on the assumption that population growth or decline leave distinctive signatures in the DNA sequences compared to constant population size. A recent growth is expected to generate a unimodal distribution of pairwise differences between sequences (Rogers and Harpending, 1992). The distribution is compared to that expected under a model of population expansion (Rogers, 1995) calculating the estimator of the time of expansion (t) and the mutation parameter (y) according to Schneider and Excoffier (1999). The formula t ¼ t=ð2uÞ is used to estimate the timing of population expansions. We assume a substitution rate per site per lineage of 0.0107 per million years (equivalent to a pairwise divergence of 2.15%/Ma assumed to be the average for insect mitochondrial DNA) (De Salle et al., 1987; Brower, 1994), so the mutation rate u in our 200 bp COI sequence is 2.15 106 per generation, assuming a generation time of 1 year. Confidence intervals for the parameters of the distributions were obtained by parametric bootstrap (1000 replicates) using Arlequin vs. 2.000 (Schneider et al., 2000). If population growth applies, the validity of a stepwise expansion model is tested using the same bootstrap approach by a goodness-of-fit statistic (P), representing the probability that the variance of ARTICLE IN PRESS 482 O´. Moya et al. / Journal of Arid Environments 66 (2006) 477–497 the simulated data set is equal or greater than the observed data set. We also computed the raggedness index (r) of the distribution and its significance, as implemented in Arlequin vs. 2.000. The mismatch analysis has been shown to be very conservative, having a low statistical power in the case of low sample sizes (Ramos-Onsins and Rozas, 2002). For this reason, other tests have been proposed for detecting past population growth such as Fu’s F (Fu, 1997)orR2 which have been shown to be superior for small sample sizes (Ramos- Onsins and Rozas, 2002). For this reason, we also computed Fu’s test of neutrality as implemented in Arlequin vs. 2.000 (Schneider et al., 2000).

2.5. Network estimation and nested clade phylogeographic analysis

The network of mitochondrial Pimelia haplotypes was inferred using statistical parsimony (Templeton et al., 1992) as implemented in the program TCS vs. 1.13 (Clement et al., 2000). The method links haplotypes with the smallest number of differences as defined by a 95% confidence criterion. NCPA was used (Templeton et al., 1995) to infer the population history of studied species of Pimelia. The NCPA first tests the null hypothesis of no association between haplotype variation and geography, and then proceeds to interpret the significant association patterns (Crandall and Templeton, 1993). The NCPA nesting design was constructed by hand using the statistical parsimony network following the rules given in Templeton (1998). In essence, the nesting procedure consists of nesting n-step clades or haplotype groups, where n is correlated with the number of nucleotide mutations separating haplotypes (Crandall, 1996). The procedure begins from the external (tip) clades and proceeds to the interior (clades joined to one or more clades by a single step). The haplotypes are nested in increasing step-levels until all the data become nested into a single clade, the total cladogram. The software GeoDis vs. 2.1 (Posada et al., 2000) was used to calculate the NCPA distance measures and their statistical significance. This method uses geographical distances between the sampled locations and estimates four basic statistics: Dc, Dn, IT-Dc and IT-Dn. Dc or clade distance measures the average distance of all clade members from its geographical centre of distribution. Dn or nested clade distance measures how widespread is a particular clade relative to the distribution of its sister clades in the same nesting group. IT-Dc and IT-Dn constitute similar distances considering tips and interiors differentially. The distinction between tip (with only one connection to the remaining network) and interior (with two or more connections) haplotype groups in the context of the coalescent theory allows testing the hypothesis of random geographical distribution by permutational tests (we performed 10,000 permutations). The predictions from the coalescent can be summarized as follows: (i) on average, haplotypes with higher frequency tend to be older and have a greater probability of being interior, (ii) older haplotypes will be more broadly geographically distributed, (iii) haplotypes with greater frequency will tend to have more mutational connections and (iv) unique haplotypes (singletons) are more likely to be joined to non-unique ones than to other singletons, and to haplotypes from the same population (Posada and Crandall, 2001). Using the updated version of the inference key in Templeton (2004) we can deduce which factor(s) could plausibly account for the spatial and/or temporal significant association of haplotypes. In this way, we can distinguish historical (fragmentation, range expansion) from current (gene flow, genetic drift) processes responsible for the observed pattern of genetic variation (Templeton, 2004). ARTICLE IN PRESS O´. Moya et al. / Journal of Arid Environments 66 (2006) 477–497 483

3. Results

3.1. Genetic diversity

For this study, 32 localities were sampled in the four western Canary Islands and 143 individuals have been analysed (see Fig. 1, Table 1 and Appendix A). COI sequences were obtained for 129 individuals of P. laevigata from 27 localities across the three islands where this species occurs (La Gomera, La Palma and El Hierro). From the sampling made in Tenerife, we obtained 14 further individuals of P. radula and P. canariensis to complete the geographical range of the 61 samples already sequenced in the previous study (see Fig. 1 in Juan et al., 1996). These 75 individuals are now a good representation of the three different nominal species present in Tenerife, one of which is split into two subspecies. Considering that a taxonomy redefinition has been recently proposed, the haplotypes have been arranged differently to the denominations used by Juan et al. (1996) (see Vinõlas, 1994; Oromı´ and Garcı´ a, 1995). We obtained 83 different haplotypes in our total Pimelia data set (excluding sites with missing data) that showed considerable genetic diversity. Of those, 36 were exclusive to Tenerife beetles and the remaining 47 belonged to P. laevigata from the westernmost islands. Table 1 shows molecular diversity estimates for the sequence data obtained across all Pimelia samples within Tenerife, within each of the Tenerife species, and within the three different island populations of P. laevigata. Haplotype diversities are lower within P. canariensis (Tenerife) (a fact that could be due to the lower sample size in this case), and in P. l. costipennis (El Hierro) and P. l. laevigata (La Palma), suggesting a relatively recent diversification of these populations.

3.2. Phylogenetic analyses

Overall, 60 variable positions are present in the ingroup sequence data set (of which 47 are parsimoniously informative). Sequences are AT-biased (65.8%); with most changes

Table 1 Summary of mean nucleotide and haplotype diversities of the different Pimelia species sequenced for the mitochondrial COI fragment

Species/populations N Haplotypes Nucleotide diversity7S.D. Haplotype diversity7S.D.

P. ascendens 34 21 0.017070.0020 0.91170.042 P. canariensis 8 2 0.005870.0013 0.53670.123 P. radula 33 13 0.026470.0038 0.77770.069 Total Tenerife 75 36 0.051170.0019 0.93370.017 La Gomera P. l. validipes 47 21 0.012670.0019 0.84370.049 La Palma P. l. laevigata 44 15 0.008770.0012 0.79570.057 El Hierro P. l. costipennis 38 11 0.008070.0010 0.83570.047

Total P. laevigata 129 47 0.027870.0008 0.94270.010 Total 204 83 0.053370.0018 0.96870.005 ARTICLE IN PRESS 484 O´. Moya et al. / Journal of Arid Environments 66 (2006) 477–497

Fig. 2. Fifty per cent majority rule consensus phylogenetic topology of the 29 maximum parsimony trees (CI ¼ 0.322; RI ¼ 0.836) obtained based on the COI mitochondrial DNA sequence data set. Bootstrap support (first number) of 500 pseudo-replicates and Bremer support values (second number) are indicated for the relevant nodes. Nodes discussed in the text are labelled with letters (A and B) and numbers. Symbols at the terminal nodes refer to the different species/subspecies as indicated in Fig. 1 from which the haplotypes were obtained. ARTICLE IN PRESS O´. Moya et al. / Journal of Arid Environments 66 (2006) 477–497 485 corresponding to synonymous substitutions at third codon positions (81.7%). The consensus maximum parsimony tree obtained shows the haplotypes arranged into two major sister clades (Fig. 2). Clade A includes haplotypes of P. r. oromii (north-east Tenerife) and P. r. radula (north Tenerife), and clade B is formed by P. ascendens (west and central regions), P. canariensis (southern arid coastal areas) plus P. laevigata mitochondrial haplotypes from the three western islands. Haplotypes of P. r. radula from La Matanza (MT in Tenerife) are present in clades A1 and A2. In addition, P. canariensis haplotypes are polyphyletic with P. ascendens haplotypes, despite being the former markedly differentiated in morphology from the high altitude P. ascendens populations (see Espanõl, 1961). In fact, P. ascendens had been considered just a subspecies of P. radula when only morphological characters were used (Espanõl, 1961); later immunological studies showed higher differences between the two taxa and suggested their independent species status (Oromı´ , 1979), which was finally established (Oromı´ and Garcı´ a, 1995) after better supported differences based on mtDNA sequences (Juan et al., 1995). Increased sampling of this coastal species and the use of additional molecular markers could clarify if P. canariensis represents an ecotype of P. ascendens. Within clade B, the phylogenetic relationships are not well resolved—what is not surprising given the short DNA sequence used and the relatively low divergence observed. Uncorrected distances between different Pimelia species from the easter and central Canary Islands haplotypes ranged from 0.005 to 0.14, and the mean distance between ingroup taxa and the outgroup P. lutaria was 0.12 (0.09–0.16 range). The optimal substitution model for the complete data set (including the outgroup) is the General Time Reversible (GTR, Rodrı´ guez et al., 1990) with a proportion of invariable sites (I) of 0.595 and a value for the G distribution of 1.002 using the Akaike information criterion. The NJ topology using these distances and parameters was similar to the one obtained by maximum parsimony. A likelihood ratio test using the likelihood scores of the original tree with branch lengths estimated implementing the GTR+I+G model assuming no molecular clock and constraining rate constancy indicated that the data is consistent with a molecular clock (2DL ¼ 120:88 at df ¼ 110; p ¼ 0:22).

3.3. Demographic inferences

The frequency of pairwise differences between haplotypes of each species within Tenerife, or island populations of P. laevigata, showed mismatch distributions consisting of unimodal curves (except for P. radula that shows two modal peaks, Figs. 3a–e). Both the variance (SSD) and raggedness index (r) tests suggested that the curves do not signiﬁcantly differ from the distributions under the model of population expansions (PSSD ¼ 0:1820:94 and Pr ¼ 0:1720:91, see legend to Fig. 3) in accordance with the corresponding Fu’s FS tests. The P. radula mismatch distribution shows two waves of expansion (Fig. 3b), possibly corresponding to the geographically structured clades A1 and A2. Accordingly, the more stringent Fu’s test of neutrality (Fu, 1997) gave a statistically signiﬁcant negative value indicating sudden population growth (F S ¼4:86; p ¼ 0:041). However, when this test was performed for the P. r. radula and P. r. oromii haplotypes separately, the distribution for P. r. oromii was not statistically different than the one expected under a scenario of constant population size (F S ¼ 0:65; p ¼ 0:62). A similar result was obtained for P. canariensis (F S ¼1:09; p ¼ 0:08), although in this case the test can be compromised due to the low sample size. Assuming a stepwise expansion model, the ARTICLE IN PRESS 486 O´. Moya et al. / Journal of Arid Environments 66 (2006) 477–497

Fig. 3. Mismatch distributions for Pimelia COI DNA sequence subsets. The curves represent the observed relative frequencies of nucleotide differences between pairs of individuals and the distribution ﬁtted to the data under the assumption of a model of population expansion. p-Value represents the probability that the variance of the simulated data set is equal or greater than the observed one. (a) P. ascendens; (b) P. radula including the two subspecies; (c) P. l. validipes; (d) P. l. laevigata (e) P. l. costipennis. Pimelia canariensis was not included in this analysis due to the low number of individuals of the sample.

Table 2 Summary of parameters estimated assuming a stepwise population growth model in several Pimelia species from the Canary Islands. The estimator of the expansion time (t) and the mutation parameters before (y0) and after (y1) the expansions are given according to Schneider and Excofﬁer (1999). The formula t ¼ t=ð2uÞ was used to estimate the time of population expansions taking a generation time of 1 year, where u corresponds to the mutation rate for the DNA sequence used per generation. Conﬁdence intervals for t are based on the maximum–minimum nucleotide substitution rate values for arthropod mitochondrial DNA

Species y0 y1 t Time (Ma)

P. ascendens 4.116 42.461 2.213 0.5370.04 P. radula 0.004 7.525 12.204 2.9170.20 P. l. validipes 0.509 60.439 2.847 0.6870.05 P. l. laevigata 0.451 19.441 3.104 0.7470.05 P. l. costipennis 0.000 3278.750 1.752 0.4270.03 ARTICLE IN PRESS O´. Moya et al. / Journal of Arid Environments 66 (2006) 477–497 487 oldest population growth in Tenerife is estimated at about 2.970.2 Ma for P. radula. This estimate is based on a time of the expansion t value of 12.204 and a mutation rate for the considered sequence of u ¼ 2.15 106 per generation (see Material and Methods and Table 2). Similarly, in P. ascendens the expansion could be dated at 0.670.04 Ma, while P. laevigata expansions are estimated to be 0.6870.05 Ma for P. l. validipes (La Gomera) and 0.7470.05 Ma for P. l. laevigata (La Palma) and 0.470.03 Ma for P. l. costipennis (El Hierro).

3.4. Population history inferences from NCPA

The limit of mutational connections (probabilityX95% of being connected in a parsimonious way) for our data set was five nucleotide substitutions using statistical parsimony. The parsimony networks of COI haplotypes were resolved except for some loops of ambiguity (haplotypes with more than one most parsimonious connection to the rest of the network). We present in Fig. 4 the results for the preferred network, based on geographical distribution of the mitochondrial genotypes and haplotype frequency criteria (see Material and Methods). Four major subnetworks were obtained connected by more than five steps. Haplotype group 5.1 includes all P. laevigata haplotypes and 5.2 contain P. ascendens and P. canariensis haplotypes (equivalent to clade B1 in the tree of Fig. 2). Group 5.3 contains P. r. radula and P. r. oromii haplotypes (corresponding to clade A2 in the tree of Fig. 2) and 5.4 P. r. radula (Clade A1) exclusively. We used the maximum parsimony tree (Fig. 2) to compute the steps connecting these higher categories; clades 5.1 and 5.2 are connected by nine steps, 5.3 and 5.4 by 10, and 6.1 and 6.2 are joined by 18 nucleotide substitutions. At the total cladogram level, we explored two nesting alternatives. The more conservative nesting option was considering the four 5-levels as unconnected (nesting I in Fig. 4). The second option (nesting II in Fig. 4) was to build the last two nesting levels connecting the clades 5.1–5.2 and 5.3–5.4 to obtain the higher 6.1 and 6.2 clades, respectively, at the total cladogram level. These connections have a high probability of being affected by homoplastic changes, but still this nesting design is a plausible representation of the phylogenetic relationships if we take into account previous phylogenetic information (Pons et al., 2004) and geographic-paleogeological considera- tions (i.e. distance between islands and their age of emergence; Juan et al., 1995; Juan et al., 2000). In addition, distinguishing tip and interior clades at this nesting levels can be ambiguous based on the tree of Fig. 2 or in the distance analysis, as the phylogenetic relationships of clades A and B in are not well supported. For example, some haplotypes (GM27) seem to be as close to the outgroup as any haplotype in clades A1 or A2. Instead, we used a more robust Pimelia species-phylogeny using mitochondrial (COI+cytochrome b, 16S RNA) and nuclear (28S RNA+Histone 3) sequences (Pons et al., 2004) to root at clade 5.4 (P. r. radula) in nesting I option, while clade 6.2 was the root (interior) and 6.1 tip in nesting II. The association between genetic and geographic distribution was rejected at most low nesting levels (1step clades) showing haplotypic variation. In the few cases where significant associations were obtained, many gave inconclusive outcomes after following the inference key of Templeton (2004) probably due to an inadequate sample design. Contingency tests showed significant geographical associations of haplotypes contained within some higher nesting levels, for example, 5.1 (P. laevigata), 5.2 (Tenerife clade B1) ARTICLE IN PRESS 488 O´. Moya et al. / Journal of Arid Environments 66 (2006) 477–497

Fig. 4. Statistically preferred parsimony network and associated nesting design. The numbers included in circles correspond to the haplotypes in each island (codes listed in Appendix A without the island identifying letters for simplicity). The size of the circle is scaled to the number of individuals possessing that haplotype. Numbers with an asterisk correspond to different haplotypes listed in Appendix A that are collapsed by the program TCS due to nucleotide (nt) sequence size differences and consequently with missing data at particular nucleotide sites. Empty circles indicate haplotype intermediates not present in the sample. Each connecting line represents a single mutational step between any two given haplotypes. Dotted lines represent alternative ambiguous connections (loops). The nested design is represented by increasing levels of nested boxes (see Material and Methods for details). Clades for which significant association between genotypes and geography were obtained are labelled with two numbers. The first one refers to the nesting level, and the second number identifies a particular clade at this level (the missing ones gave non-significant results). A1, B, B1 and B2 relate to the particular clades in Fig. 2 and the island-specific haplotypes of P. laevigata are separated by three thick lines, the name of each island from which the haplotypes come is indicated for clarity. The inset shows the two alternative nestings (I and II) at the total cladogram level (see text for details). Connections by broken lines join major subnetworks separated by a number of mutational steps higher than the limit of parsimony in alternative II. Two asterisks indicate root clades deduced from the phylogeny obtained in Pons et al. (2004).

and 5.3 (Tenerife clade A2) (see Table 3). Using geographic distance analysis, the oldest inferred event corresponding to the total cladogram was independent of the nesting design. Both I and II nestings point to long distance colonizations from the north-east tip of Tenerife to the west (see Fig. 5) although an alternative explanation of past fragmentation followed by range expansion cannot be completely ruled out (see Discussion). The long distance movement inference is obtained at other nesting levels as well for the clades within 6.1 (Nesting II), that is, Tenerife seems to have been the source of colonizers that populated La Gomera. From the latter, subsequent distance dispersals colonized possibly La Palma ﬁrst (clade 5.1, inference of long distance colonization from La Gomera to La Palma, see Fig. 5). This inference is reinforced by the result obtained at the 4.2 level, ARTICLE IN PRESS O´. Moya et al. / Journal of Arid Environments 66 (2006) 477–497 489

Table 3 Results of the nested cladistic phylogeographic analyses for Pimelia samples. Only instances of statistically significant results obtained by geographical distance analysis are shown. The results at the one-step level are not shown due to the low number of individuals (see Results). w2 statistics and the associated p-values were obtained by permutational contingency tests with 10,000 replications. This test was non-significant only for clades 2.1 and 2.3, being the geographical distance analysis using Dc and Dn distances statistically significant

Clade w2 p-Value Inference chain Inference

Clades within 25.8678 0.2250 1–2–11–17-No Inconclusive outcome 2.1 Clades within 5.0000 0.4010 1–2–11–12-No Contiguous range expansion 2.3 Clades within 91.0350 0.0000 1–2–11–12-No Contiguous range expansion 2.9 Clades within 9.0000 0.0450 1–19–20–2–11–12-No Contiguous range expansion 2.12 Clades within 14.1429 0.0150 1–2–11–17-No Inconclusive outcome 2.15 Clades within 19.9500 0.0250 1–2–3–4-No Restricted gene flow with 3.4 isolation by distance Clades within 63.6849 0.0000 1–2–11–12-No Contiguous range expansion 3.5 Clades within 18.0556 0.0270 1–2–3–4-No Restricted gene flow with 3.10 isolation by distance Clades within 127.9667 0.0000 1–2–3–5–6-Too few clades-7- Restricted gene flow/Dispersal 4.2 Yes but with some long distance dispersal Clades within 20.3667 0.0000 1–2–11–12-No Contiguous range expansion 4.3 Clades within 16.0000 0.0010 1–19–20–2–3–4–9-No Allopatric fragmentation 4.4 Clades within 121.0933 0.0000 1–2–3–5–15–21-Yes Long distance colonisation 5.1 Clades within 21.8169 0.0010 1–2–3–4-No Restricted gene flow with 5.2 isolation by distance Clades within 171.0000 0.0000 1–19–20–2–11–12–13–21-Yes Long distance colonisation 6.1 Clades within 27.5550 0.0000 1–2–11–12-No Contiguous range expansion 6.2 Total cladogram 578.3400 0.0000 1–2–11–12–13–21-No Long distance movements or I combined effects of gradual movement during a past range expansion and fragmentation Total cladogram 204.0000 0.0000 1–19–20–2–11–12–13–21-No Long distance movements or II combined effects of gradual movement during a past range expansion and fragmentation

including haplotypes of P. laevigata from the three islands. Besides these results, two instances of restricted gene ﬂow with isolation by distance (clades 3.10 and 5.2) and one of allopatric fragmentation (clade 4.4) are inferred within Tenerife. Most other nesting levels ARTICLE IN PRESS 490 O´. Moya et al. / Journal of Arid Environments 66 (2006) 477–497

Fig. 5. Schematic representation of the Pimelia NCPA inferences overlaid on a map of the western Canary Islands. Several instances of contiguous range expansion (CRE) are deduced within each island, and cases of restricted gene flow with isolation by distance (RGF) in Tenerife and El Hierro. At least three long distance colonizations (LDC) are inferred, represented in the figure showing east–west direction, although an alternative explanation for the one at the total cladogram level is also possible (see Discussion). The origin of colonization for El Hierro remains unclear. Numbers for each inference refer to nesting groups presented in Fig. 4 and Table 3. with significant associations of genotypes with geography provide the general common inference of contiguous range expansion in Tenerife (clades 6.2 north–north-east, and 4.3 in the central region), La Gomera (clades 3.5 and 2.12), La Palma (clade 2.3) and El Hierro (clade 2.9). In the latter, a case of restricted gene flow with isolation by distance is deduced (clade 3.4) between the south-west localities and the rest of the island. Clades 2.1 and 2.15 showed inconclusive results.

4. Discussion

In this study we have extended Juan et al.’s surveys (1995, 1996) of western Canary Pimelia species by widening the sampling in Tenerife and collecting in the other three western islands, where the related species P. laevigata occurs in unforested areas. If we take into account geography, age of the islands and genetic data, P. laevigata populations in the western islands seem to derive from a Tenerifean ancestor (Juan et al., 1995, 1996, this work). The alternative hypothesis seems more unlikely as it would imply a back- colonization from these islands to Tenerife. Although the DNA fragment sequenced is too short to provide enough phylogenetic information to support each P. laevigata island population as unequivocally monophyletic, other genetic markers point to the independence of the three clades (Pons et al., 2004). The presence in La Gomera of two haplotypes (GM26 and GM27) that are relatively divergent from the remaining haplotypes sampled on the island make it ambiguous to postulate a single colonization event and/or estimate date(s) for them in this island. As pointed out by Emerson et al. (2000c), the effect of existing genetic diversity in the ARTICLE IN PRESS O´. Moya et al. / Journal of Arid Environments 66 (2006) 477–497 491 ancestral population and the possibility of lineage extinction, complicate the inference of colonization events from one island to another in a given phylogeny. In Tenerife, the results obtained elsewhere (Juan et al., 1996) pointing out the existence of two very divergent mitochondrial lineages are confirmed with our present more comprehensive sampling. Lineage A includes P. radula haplotypes, with the current subspecies designation not completely coincidental with lineages A1 and A2 since haplotypes of P. r. radula are in both groups. This can be explained either by retention of ancestral polymorphisms or, more probably, by mitochondrial introgression. Nevertheless, after the analysis of the geographically intermediate, newly discovered population in La Matanza (MT, Tenerife), we can state that the morphological characters on which the two subspecies are based show a clinal variation along the north–north-east region of Tenerife. On the other hand, Tenerife mitochondrial lineage B1 is the sister group of P. laevigata, including P. ascendens distributed at relatively high altitude localities, and P. canariensis present along the south-east to south-west coastal arid areas of the island. In addition, the tree topology suggests that colonization to the western islands (being probably La Gomera first to be colonized) was by ancestors of the B1 Tenerife lineage. Pairwise differences between sampled DNA sequences (Fig. 3) show that in all the studied cases, mitochondrial mismatch distributions are compatible with historic population expansions or bottlenecks followed by a return to the original population size (Slatkin and Hudson, 1991; Rogers and Harpending, 1992). Estimates for the corresponding dates of population expansion are in good accordance with the island dates of formation (Table 2). For example, population expansion is inferred to be older for the A lineage of Tenerife compared to one of the remaining species, while the P. laevigata expansion in the El Hierro population is deduced to be more recent and explosive (Table 2). This result is in accordance with the younger age for the subaerial formation of this island and, therefore, within the time frame in which colonization was possible. One objective of this paper was to assess the validity of nested phylogeographical cladistic analysis (Templeton et al., 1995; Templeton, 2004) in order to infer historical population events in an a priori scenario of recurrent long distance dispersal, such as the one assumed to explain colonization and diversification of an oceanic archipelago. The Canary Islands are of independent volcanic origin and have never been connected by the effect of sea level oscillations, with the possible exception of Fuerteventura and Lanzarote that are separated by a very shallow strait, but whose populations are not included in this study. As expected, molecular phylogenies show that in the Canaries the general pattern of colonization in a diversity of terrestrial organisms is consistent with dispersal from older to younger islands, westwards along the island chain (Juan et al., 2000). NCPA infers long distance movements in cases of a large nesting distance (Dn) in a clade with small clade distance (Dc) (though extinction of intermediate populations in organisms with low vagility can also be compatible with this pattern). This inference is expected to occur, for example, if a peripheral population has a unique haplotype, but a reduced geographical distribution with respect to that of the haplotypes from which it derived, while, on the contrary, concordant Dc and Dn values suggest short distance movements (Masta et al., 2003). Assuming an adequate geographical sampling, NCPA should distinguish between the above alternatives, but cases of misinterpretation have been shown to occur in situations of gradual expansions or re-invasions of previous ranges (Masta et al., 2003). In ARTICLE IN PRESS 492 O´. Moya et al. / Journal of Arid Environments 66 (2006) 477–497 the present data set, the NCPA analysis can detect at least three instances in which geographical association of genotypes could be explained by long distance movements of the species. Alternatively, the pattern could be explained by the combined effects of gradual movement during a past range expansion and a subsequent fragmentation (step 21 in the NCPA updated inference key, Templeton, 2004). The discrimination between the two alternatives has shown to be only possible using outside independent information (Masta et al., 2003; Templeton, 2004). Pimelia species are flightless, so passive dispersal has to be invoked for these organisms, possibly through floating vegetation drifted by the prevailing north-east–south-west sea currents in this part of the Atlantic. In fact, the Canary archipelago has been colonized primarily by single or multiple continental dispersal events in terrestrial organisms even in animals with low vagility (Juan et al., 2000; Emerson, 2002). On the other hand, in a scenario of islands of independent volcanic origin, the possibility of range expansions followed by fragmentation has to be in principle discarded to explain haplotype distribution patterns among islands. Because of that, all the instances in which both alternative scenarios were suggested by the inference key for clades including different islands were considered as long distance movements. Nevertheless, colonization events of the western islands of La Gomera, La Palma and El Hierro consistent with a minimum of two eastward long distance dispersals, were recovered by the NCPA analysis, although the origin of colonization for El Hierro remains unclear. Another inference frequently obtained at other nesting levels (6.2, 4.3, 3.5, 2.12, 2.9 and 2.3) is contiguous range expansion, deduced to have occurred more than once in Tenerife and in each of P. laevigata island populations, presumably after the original colonizations. These inferences are consistent with the deduced population growth by mismatch distribution analyses in the same clades (Fig. 3). Finally, in Tenerife a particular case of allopatric fragmentation of the Izanã (IZ) locality, and two instances of restricted gene flow with isolation by distance are deduced. This can be related to the complex geological dynamics of the island, in which geographical barriers and local extinctions due to volcanism are expected to have been particularly frequent. NCPA has indeed limitations inherent to the sampling scheme (size and number of sites) and cases in which there is not enough resolution to detect past events (Templeton, 2004). In addition, more serious limitations of the analysis occur when false inferences or biological misidentifications are obtained. The original inference key (Templeton et al., 1995) has been validated using biological examples for which strong prior evidence existed for particular past events such as range expansion or fragmentation and updated to avoid errors or ambiguities (Templeton, 1998, 2001, 2004). Cross-validation obtaining multi- locus data from independently segregating DNA regions, is recommended for obtaining robust inferences (Templeton, 2004). In our case, sampling size is scarce from some of the geographical sites, and although the number of sampled localities is relatively high, a more comprehensive sample scheme would be needed to cover the geographic micro-scale of the high altitude regions in the western islands. These sampling limitations resulted in few cases of significant geographical associations of haplotypes for which inconclusive outcomes are obtained, although the low nesting level in which they occur is irrelevant for the main conclusions of NCPA. Our results also show that there is enough variation in the 200 bp fragment and the pooling of data from a previous study allowed a comprehensive NCPA. However, the relatively high divergence of mitochondrial lineages within Tenerife, and the ones corresponding to island populations of P. laevigata, make the connections ARTICLE IN PRESS O´. Moya et al. / Journal of Arid Environments 66 (2006) 477–497 493 and designation of interior-tip status at the higher nesting level ambiguous and dependant on external previous information. Better genetic resolution by longer mitochondrial DNA sequences and independent genetic markers would clarify the above points further. Finally, NCPA and the associated inference key present some difficulties when applied to populations present in several volcanic islands as the ones studied here. Creer et al. (2001) studied the phylogeography of bamboo viper in Taiwan and in the offshore Pacific, Orchid and Green islands. Haplotypes of the two latter populations were omitted from the NCPA analysis because the islands are of volcanic origin and never have been connected to Taiwan and the study focused on historical terrestrial migrations. As mentioned above, in the colonization and diversification of an oceanic archipelago, the a priori hypothesis is long distance dispersal, but if the clades within a nesting clade are found in separate islands (so in separate areas with no overlap by definition) the inference is allopatric fragmentation. In addition, the inferences of long distance colonization with subsequent fragmentation or past fragmentation followed by range expansion are implicitly applied to historical terrestrial situations, being the application to oceanic islands somewhat elusive. In summary statistical phylogeography—and more specifically nested phylogeographic cladistic analysis, provides an excellent opportunity to contrast current and historical causes for the genetic and geographical distribution of darkling beetles in the Canary Islands. There is a considerable genetic variation and geographical structure both in low and high altitude arid region populations of the ancient, geologically complex island of Tenerife. In contrast, the younger western islands show evidences of more recent colonizations and subsequent range expansions of Pimelia populations derived from a Tenerife ancestor, and, therefore, limited geographical structuring.

Acknowledgements

Giulia Paroni helped us with laboratory techniques. Heriberto Lo´ pez, Antonio J. Pe´ rez, Antonio Camacho, Rube´ n Barone and Jesu´ s Alonso contributed collecting specimens. We thank the suggestions made by Eduard Petitpierre and Jesu´ sGo´ mez-Zurita. The comments of David Posada and of an anonymous referee on a previous version of the manuscript helped to improve the paper. This study is supported by the Spanish Ministerio de Educacio´ n y Ciencia including European Union FEDER funds (project REN2003-00024). The permits to collect beetles in the protected areas were obtained from the Viceconsejerı´ a de Medio Ambiente del Gobierno de Canarias and the corresponding Cabildos of the islands, which occasionally provided accommodation.

Appendix A

Summary of Pimelia sampling in the western Canary Islands and in Tenerife. Species localities and their codes, co-ordinates, haplotype distribution (number of individuals with the same haplotype in parenthesis) and number of individuals collected at a given locality are given. Total number of haplotypes is higher than the ﬁgures given in Table 1 because the haplotypes with missing data were excluded from the analysis of nucleotide and haplotype diversities. (Table A1) ARTICLE IN PRESS 494 O´. Moya et al. / Journal of Arid Environments 66 (2006) 477–497

Table A1

Localities Code Co-ordinates Haplotypes N

Tenerife Pimelia ascendens Bco. Natero BN 16.841/28.284 TF15 1 IzanãIZ16.500/28.305 TF1, TF2(2), TF3, TF7, TF12(2), 11 TF19, TF20, TF21, TF23 Las Canãdas CD 16.623/28.223 TF1(2), TF2(5), TF3, TF13, TF18 10 Las Manchas MN 16.800v28.283 TF14, TF17 2 Pinar Chio PC 16.763/28.240 TF3 1 Puerto Erjos PE 16.802/28.317 TF16, TF25 2 San Jose´ de los Llanos SJ 16.785/28.325 TF8(2), TF9, TF10, TF11, TF22, 7 TF24 Pimelia canariensis Armen˜ime AM 16.761/28.122 TF5, TF27 2 Faro de Rasca FA 16.695/27.999 TF5 1 Malpaı´ sdeGu¨ ı´ mar MG 16.367/28.310 TF4 1 Mnã. Roja MR 16.541/28.035 TF4, TF26(3) 4 Pimelia radula oromii Las Teresitas TE 16.185/28.507 TF6(5), TF38 6 Las Lagunetas LG 16.409/28.413 TF6, TF28, TF29(2), TF30, TF31, 8 TF35, TF36 Sta. Cruz SC 16.251/28.453 TF6, TF39(2) 3 Los Rodeos RD 16.348/28.478 TF6(3), TF33, TF34, TF40 6 Pimelia radula radula La Matanza MT 16.460/28.442 TF32, TF37, TF41, TF42 4 La Vera VE 16.536/28.400 TF43(5), TF44 6 La Gomera Pimelia laevigata validipes Cementerio Arure CA 17.318/28.130 GM3, GM8, GM18,GM25, 5 GM26 Lomo de la PecenãLP17.286/28.124 GM2, GM3(2), GM4(3), GM15 7 El Apartadero AP 17.267/28.108 GM2(2), GM4, GM8, GM12, 8 GM21, GM22, GM23 La Cruz de Marı´ aCR17.256/28.112 GM2, GM14, GM16, GM17, 6 GM20, GM24 Lomo de los Cardos LO 17.249/28.098 GM5(2), GM6(2), GM19, GM27 6 Toria´ nTO17.241/28.107 GM1(5), GM9, GM13 7 Pajarito PA 17.233/28.108 GM1, GM7(2) 3 Majona MJ 17.122/28.128 GM1(3), GM10, GM11 5 La Palma Pimelia laevigata laevigata Los Llanos LL 17.912/28.659 LP1(3), LP5(3), LP21 7 El Remo RM 17.855/28.552 LP1, LP5(2), LP6 4 El Paso EP 17.852/28.657 LP3, LP15, LP16, LP17, LP24, 7 LP25, LP26 Fuencaliente FU 17.845/28.494 LP3(2), LP7(2), LP13, LP14 6 Refugio del Pilar RP 17.835/28.614 LP1 1 Casas de Taburiente CT 17.894/28.704 LP1, LP20 2 El Riachuelo RI 17.846/28.680 LP1, LP4(2), LP18 4 Puntagorda PU 17.999/28.760 LP1, LP11, LP22, LP23 4 ARTICLE IN PRESS O´. Moya et al. / Journal of Arid Environments 66 (2006) 477–497 495

Table A1 (continued )

Localities Code Co-ordinates Haplotypes N

Roque de los Muchachos RO 17.906/28.769 LP2, LP8, LP10, LP12 4 Mazo MA 17.792/28.539 LP2, LP6, LP9, LP12, LP19 5 El Hierro Pimelia laevigata costipennis Frontera FR 17.997/27.799 EH1, EH3 2 La Caleta LC 17.890/27.801 EH1, EH2, EH3, EH9 4 Nisdafe NI 17.961/27.769 EH1(2), EH2(2) 4 La Restinga RE 17.982/27.644 EH2(2), EH8(3) 5 El Pinar PI 17.981/27.712 EH2(2), EH6(3), EH7(4) 9 Jinama JI 17.981/27.763 EH2(4), EH12, EH14 6 Sabinosa SA 18.097/27.665 EH4(3), EH5(2) 5 Montan˜a Caracol MC 18.124/27.728 EH11, EH13 2 Roque Salmor RS 18.005/27.821 EH10 1

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