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  • Original Paper
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Lack of genetic differentiation after host range extension argues for the generalist nature of Pityogenes chalcographus (Curculionidae: Scolytinae)

Abstract

Context

The bark beetle, Pityogenes chalcographus, is one of the main pests in Picea abies stands, and it has also been found on other European Pinaceae species. With massive introductions of North American conifer species into European forests, this insect has extended its host range to exotic Pinaceae species.

Aim

This study assessed whether a wider host range has influenced the genetic structure of P. chalcographus and has led to host specialization.

Methods

Insects were collected from two different regions of France, where eight native and exotic conifer species coexist and were analyzed using mitochondrial and nuclear genetic markers.

Results

Considerable haplotypic diversity was observed within the regions and within host species from where P. chalcographus populations were collected. No genetic differentiation, especially with respect to host species associations, could be detected. Moreover, no relationship could be established between closely related P. chalcographus haplotypes and taxonomically related conifer species.

Conclusion

The capacity of P. chalcographus for host shifting and dispersal may have played a key role in the rapid extension of its host range. These findings are important for pest management in forests and health and phytosanitary measures in the timber trade, especially for risk assessment in mixed coniferous forests including tree species of major economic importance.

1 Introduction

Many phytophagous insects exploit a limited number of host plants, mostly belonging to the same genus (monophagous species) or the same family (oligophagous species) (Schoonhoven et al. 2005). They have a well-defined host range corresponding to the major physiological and behavioral adaptive traits of the insects (Vanbergen et al. 2003). According to Diegisser et al. (2009), the incorporation of a new host into the host range of phytophagous insects could result in two types of consequences differing significantly in their evolutionary implications. The first scenario, host-range expansion, suggests that insect populations are able to use the new host without losing any of their ability to exploit their natural hosts (Hare 1990). This outcome may be observed if no new morphological or physiological adaptations are required or if adaptations evolve without decreasing their fitness to the natural host. In both cases, the populations with a wide host range are not expected to be genetically differentiated (Diegisser et al. 2009). On the other hand, the second scenario, host shift, proposes that insects may not be able to adapt to a new host while remaining adapted to their natural hosts. Adaptations to one host are often maladaptions for other hosts, resulting in host plant associated fitness trade-offs (Via 1990), which may lead to specialized populations via selection pressure, sympatric speciation, and possibly to the formation of host races (Drès and Mallet 2002; Jaenike 1990).The apple maggot, Rhagoletis pomonella Walsh (Diptera: Tephritidae) is a well-known example of phytophagous insect speciation by adaptation to new host plants. This species shifted from its ancestral host, hawthorn, Crataegus spp., to the newly introduced Palearctic apple, Malus pumila Walsh, resulting in two host races (Feder et al. 1994, 1988; McPheron et al. 1988).

Shared chemical, physical, and ecological characteristics in the natural and new hosts are important for increasing the probability of an insect adapting to a new host plant (Becerra 1997; Lopez-Vaamonde et al. 2003; Strong et al. 1984); among others). Such similarities can arise between related plants, belonging to the same genus or family. Host taxonomic proximity is, therefore, one of the main controlling factors involved in successful host shift in phytophagous insects. Although it is not uncommon to find taxonomically distant plant species sharing similar secondary compounds (Becerra 1997; Strong et al. 1984), host shifts in phytophagous insects tend to occur between closely related host plants (Degomez and Wagner 2001; Lopez-Vaamonde et al. 2003; Strong et al. 1984; among others).

The European six-toothed bark beetle, Pityogenes chalcographus L. (Curculionidae, Scolytinae) is one of the main pests of the Norway spruce, Picea abies L. karst., forests. Although P. abies is its preferred host and the most suitable for its development (Bertheau et al. 2009a), it is not strictly a monophagous species. This beetle has been frequently reported using other European Pinaceae species as alternative hosts, such as Scots pine, Pinus sylvestris L., European Silver-fir, Abies alba mill. and European Larch, Larix decidua mill. (Pfeffer 1994). Moreover, with the intensive reforestation of European forests (Zobel et al. 1987), P. chalcographus has extended its host range to various exotic North American Pinaceae species belonging to the genus Picea, Pinus, Abies, and Pseudotsuga (Pfeffer 1994). P. chalcographus thus constitutes a useful model for testing whether a population’s genetic structure can be modified by the introduction of a new host species into the existing host range. Behavioral assays on both native and exotic Pinaceae species within the P. chalcographus host range showed that the two exotic species Picea sitchensis (Bong.) Carrière and Pseudotsuga menziesii (Mirb.) Franco were the second and the third choices of P. chalcographus after its main host P. abies and that the fitness was similar or only slightly lower than on P. abies (Bertheau et al. 2009a). The ability of P. chalcographus to colonize and develop on exotic Pinaceae species reveals a rapid adaptation to new hosts over a period of nearly 200 years in extensive plantations of North American conifers in Europe (Agnoletti and Anderson 2000). A combination of a wide range of suitable hosts and good fitness to exotic hosts might be expected to lead to a lack of genetic differentiation between P. chalcographus populations. However, bark beetles have an endophytic life cycle and spend most of their life under the bark. This high degree of intimacy with their hosts may reinforce local adaptation (Kerdelhué et al. 2002; Mopper 1996) and favor host specialization, leading to genetic differentiation between populations. So far, the potential effect on the population genetics of the insect of introducing a new tree species into the insect’s host range has not been studied for bark beetles, despite their significant impact on the economics of European forestry.

Mitochondrial (mtDNA) and nuclear DNA (nuDNA) markers were used to analyze P. chalcographus populations within two regions in France (Limousin and Jura) that have undergone intensive reforestation with exotic North American conifers. The first objective was to evaluate the genetic variability among populations on native and exotic host species. The second objective was to test whether any genetic differentiation among P. chalcographus samples grouped by host species was correlated with taxonomic proximity between the associated host species. Despite a rather low number of analyzed insects due to the necessity of sampling from several different tree species within each region, the results should improve our understanding of how a host range expands with new conifer species after recent extensive reforestation and how this may influence the genetic structure of this bark beetle.

2 Materials and methods

2.1 Beetle sampling

During 2006 and 2007, 61 P. chalcographus adults were obtained from trap trees in 17 sites in two regions of France (Limousin and Jura), which were chosen for the abundance of exotic North American and native conifers. In each region, the samples came from single species stands of native conifers (P. abies, P. sylvestris, and A. alba) and exotic conifers [P. sitchensis, Pinus strobus L., Abies grandis Douglas ex (D. Don) Lindl., P. menziesii (Mirb.) Franco, and Thuja plicata Donn ex D. Don.]. The minimum and maximum distances between each stand in each region were 0.06–45 km in Limousin and 0.05–11 km in the Jura. This study considered a site to be a given conifer species stand from which bark beetles samples were taken. Only one individual per mother gallery was collected to prevent the sampling of siblings. Samples were stored in absolute ethanol immediately after collection. Six additional samples of P. chalcographus, whose DNA extracts were given by C. Stauffer (Vienna, Boku University), were included in the analyses. These samples, chosen in different European countries to represent the major clades identified by Avtzis et al. (2008a) in a previous phylogeography study, may help in haplotype assignation to particular P. chalcographus reference lineage previously designed. All the sampling sites and host conifer species are given in Table 1.

Table 1 Characteristics of P. chalcographus sampling sites listed by host conifer species and host origin (native or exotic)

2.2 DNA extraction, PCR amplification, and DNA sequencing

Genomic DNA was extracted from the head of the insects using the GenElute Mammalian Genomic DNA miniprep kit (Sigma-Aldrich, France) as described by the manufacturer. DNA was eluted in 100 μl of the elution solution provided in the kit and stored at −20°C. The remaining parts of the body were stored at −80°C and kept as vouchers at Orleans University.

A 676-bp fragment of the mitochondrial gene of the cytochrome oxidase subunit 2 (COII) was amplified by polymerase chain reaction (PCR), using the Sigma Red Taq package (Sigma-Aldrich, France) for up to five individuals for each population (Table 1). The first experiment produced only a few sequences using the non-specific primers C2-J-3138 (Simon et al. 1994) and TK-N-3782 (Bogdanowicz et al. 1993). Two microliters of DNA extraction in 50-μl reaction volumes containing 1.5 mM MgCl2, 100 μM dNTPs, and 0.4 μM of the primers were used as templates for 35 cycles of amplification. The reaction was performed under the following conditions: denaturation step at 95°C for 1 min, annealing at 46°C for 1 min, and extension at 72°C for 1 min 30 s. The initial cycle was 3 min denaturation at 95°C, and the final cycle had an extension step of 72°C for 10 min. New P. chalcographus-specific primers C2PcF 5′-TAGAACAACTAAATTTCTTCCATG-3′ and C2PcR 5′-GTCATCTAATGAGGTTT TATCTGTGG-3′ were designed using OLIGO© (Rychlik 2007) to amplify a 670-pb sequence in the same conditions as above but with the annealing temperature set to 61°C.

Amplification of the full ITS2 region, including the end of the 5.8S and the beginning of the 28S ribosomal gene, was carried out for 50-μl reaction volumes containing 1.5 mM MgCl2, 100 μM dNTPs, 0.2 μM of the primers ITS2F and ITS2R (Campbell et al. 1993), and 1 U of Red Taq Polymerase (Sigma-Aldrich, France). The reaction was performed under the following conditions: denaturation step at 95°C for 1 min, annealing at 51°C for 1 min, and extension at 72°C for 1 min for 30 cycles. The initial cycle had 3 min denaturation at 95°C, and the final cycle had an extension step of 72°C for 5 min.

All PCR products were purified using the GenElute PCR Clean-Up kit (Sigma-Aldrich, France) and directly sequenced with the corresponding amplification primers. Sequencing was performed using the BigDye Terminator sequencing kit (Applied Biosystems, France) and carried out with an ABI 3100 automatic sequencer. All sequences were carefully checked by hand and then aligned using ClustalW (Thompson et al. 1994) as implemented in BIOEDIT version 7.0.9 (Hall 1999). The alignments were straightforward because no gaps occurred. Due to the inability to have a COII sequence of another Pityogenes species, no outgroup species could be used in this study and take another Scolytinae species as outgroup would not be enough close to allow inference from sequence or trait data.

2.3 Data analyses

2.3.1 Phylogenetic reconstructions and haplotype network estimation

Maximum parsimony (MP) and maximum likelihood (ML) tree reconstructions were produced using PAUP* 4.0 beta 10 (Swofford 2002). The ML trees were generated using the nucleotide substitution model that had the best fit for the data, using the hierarchical likelihood ratio test (hLRT) criterion, determined using MODELTEST v3.7 (Posada and Crandall 1998). MP tree reconstruction used a heuristic search method with 1,000 random-addition sequence replicates and explored tree space by tree bisection and reconnection branch swapping. The robustness of the trees was assessed by 1,000 bootstrap replicates. To test for constancy in rates of COII evolution between lineages, maximum likelihood trees were constructed, with and without a molecular clock enforced, using PAUP. A likelihood ratio test (Felsenstein 1988) was used with a homogeneous rate of evolution as the null hypothesis. The likelihood ratio was defined as twice the difference of log-likelihood scores from constrained and unconstrained trees and compared to a χ 2 distribution with N − 2 degrees of freedom (N = number of sequences in the tree). Uncorrected “p” genetic distances were calculated using PAUP* 4.0 beta 10.

A statistical parsimony network was calculated using TCS version 1.21 (Clement et al. 2000), and topological, geographical, and frequency criteria (Crandall and Templeton 1993) were used to solve the few cladogram ambiguities that occurred.

All these analyses were intended for both markers, but were mostly done for the mtDNA fragment due to the lack of polymorphism of the ITS2.

2.3.2 Population genetic parameters and analyses of population structure

The haplotype diversity H d (mean ± SD), nucleotide diversity π (mean ± SD), and mean number of pairwise differences (mean ± SD) were calculated using ARLEQUIN 3.11 (Excoffier et al. 2005) for both COII and ITS2 sequences. They were calculated first for each region and secondly for each host tree species. When samples were grouped by tree host species, the corresponding allelic richness r was calculated from the haplotype frequencies using the rarefaction method proposed by (Petit et al. 1998) using CONTRIB (http://www.pierroton.inra.fr/genetics/labo/Software/Contrib/). The rarefaction size r was set to 5 among the groups for the mtDNA marker and to 4 for the nuclear marker. The occurrence of a significant phylogeographic structure was assessed by testing whether Gst (coefficient of genetic variation over all populations) was significantly smaller than Nst (equivalent coefficient taking into account the similarities between haplotypes) using 1,000 permutations (see Pons and Petit 1996) in the program PERMUT (http://www.pierroton.inra.fr/genetics/labo/Software/Permut/).

Analysis of molecular variance (AMOVA; Excoffier et al. 1992) was used to partition the molecular variance into different hierarchical levels using ARLEQUIN 3.11. Samples were grouped either according to the region (Jura and Limousin), conifer species, or host origin (native vs. exotic). The significance level of F ST-statistics was determined using a non-parametric permutation procedure with 1,000 randomizations, also implemented in ARLEQUIN.

An exact test of population differentiation based on haplotype frequencies (Raymond and Rousset 1995) was performed to test the null hypothesis of random distribution of individuals between pairs of sites.

2.3.3 Correlation matrix

The study tested whether the genetic divergence between the samples from different host conifer species was influenced by the taxonomic proximity between tree species. To determine whether there was any specialization of P. chalcographus onto its various host species, it was assumed that, for more genetically distant conifer species, there would be greater genetic differences between P. chalcographus samples developing on those conifer species. First, pairwise values of Kimura-2 parameter genetic distances (Kimura 1980) between the eight conifer species were taken from Bertheau et al. (2009b), who had performed such analyses using the DNA sequences from GenBank. The dissimilarity matrix including all possible tree species pairs was constructed from these genetic distances. Secondly, pairwise ΦST values were calculated for P. chalcographus samples grouped by host species using ARLEQUIN 3.11. In addition to using the variation in haplotype frequencies, as in conventional F ST statistics, the index ΦST takes into account pairwise differences between haplotypes, which makes it the molecular analogy of Wright’s fixation index (Excoffier et al. 1992). Finally, a permutation test strategy (10,000 permutations; (Smouse et al. 1986)) was used to carry out Mantel tests to determine whether the matrix of genetic distances between host species was correlated with each of the independent matrices of genetic divergence between P. chalcographus samples, using XLSTAT 7.1.

3 Results

3.1 Mitochondrial DNA

3.1.1 Sequence alignment and haplotypes reconstruction

The final alignment of the COII sequences comprised 638-bp, with a total of 34 (5.3%) polymorphic nucleotides of which 23 were parsimony informative (21 transitions and two transversions). Twenty-five different haplotypes within P. chalcographus were identified and named Pc1 to Pc25 (Table 1). They are available from GenBank under accession numbers JQ066282 to JQ066306. One main haplotype Pc1 was shared by 29 individuals; six were shared by two to three individuals (Pc4, Pc9, Pc10, Pc12, Pc17, and Pc18); and 18 haplotypes were found only once (Table 1). All the haplotypes gave clear, unambiguous sequence chromatograms, and no indicator of pseudogenes was observed (see Zhang and Hewitt 1996). There are non-synonymous mutations but with no major changes of the COII amino acid structure. Our findings are in agreement with those found by Arthofer et al. (2010) where no pseudogene was detected in the COI sequences of P. chalcographus. The geographic distribution of the 25 haplotypes is shown Fig. 1a. The widespread haplotype Pc1 was observed for both native and exotic conifer species, in all sites studied except in three populations of Jura, on P. sylvestris (native), A. grandis, and T. plicata (exotic). Overall, the haplotype distribution of P. chalcographus did not appear to be correlated with geographic origin or host species (Fig. 1a, Table 1).

Fig. 1
figure 1

Haplotype distribution and haplotype network of the 61 Pityogenes chalcographus cytochrome oxidase II (COII) sequences. a Geographical distribution of the haplotypes among the 17 sampled populations. Population frequencies are approximated by the area of the circle. Each population and haplotype is defined as in Table 1 and color codes are the same as for the haplotype network. b Haplotype network of the 25 haplotypes detected in P. chalcographus with different symbol codes for each host conifer species, Picea abies (empty square), Picea sitchensis (filled square), Pinus sylvestris (empty star), Pinus strobus (filled star), Abies alba (empty circle), Abies grandis (filled circle), Pseudotsuga menziesii (filled diamond), and Thuja plicata (filled drop). Haplotype frequencies are represented by the area of the circle. Each line corresponds to a mutational step and each empty circle to a missing intermediate

3.1.2 Phylogenetic trees and haplotype network

For the hierarchical likelihood ratio tests, MODELTEST analyses revealed that the most appropriate sequence evolution model was the K81uf + I model, including invariable sites (I = 0.90) with unequal base frequencies (freqA = 0.3524; freqC = 0.1870; freqT = 0.3489; freqG = 0.1116). The likelihood ratio test supported a molecular clock model for P. chalcographus (χ 2 = 32.29, df = 23, P < 0.05). Both ML and MP phylogenetic analyses gave congruent trees, which differed only in the placement of haplotypes within clades (Supplementary Information, Fig. S1). Three clades were identified and labeled from A to C. Clade A comprised 23 haplotypes, corresponding to 59 individuals from the eight native and exotic host conifer species. Nineteen haplotypes belonged to French individuals and the four others to Germany, Italy, Lithuania, and Poland. Clade B regrouped two haplotypes, a unique one Pc20 belonging to a French specimen sampled on the exotic tree species P. menziesii and the haplotype It1-II from Italy collected on P. abies. Clade C had six haplotypes with five unique (Pc21, Pc22, Pc23, Pc24, and Pc25) from French individuals sampled both in Limousin and Jura, and one corresponding to a Norwich specimen (No-I), all collected on the native P. abies. The distribution of haplotypes within each group was not restricted to one particular locality since they were found in both Limousin and the Jura. However, although clade A appeared to be a generalist clade (with all native and exotic conifers represented) and clade C appeared to be a specialist clade (with only P. abies), this structure was not correlated with the ability to use host trees. Instead, they rather matched with the structure obtained in the European phylogeography of P. chalcographus, sampled on P. abies only and analyzed with the COI gene (Avtzis et al. 2008a). Indeed, by adding to our analyses, these individuals from Norway, Lithuania, Poland, Germany, and Italy, and analyzing them with COII, it became possible to associate our clades A, B, and C to the clades IIIa, II, and I, respectively, published in the European phylogeography study (Avtzis et al. 2008a, Fig. S1, Supporting Information). Bootstrap values of the ML and MP phylogenetic trees were similar and supported the phylogenetic structure between the three clades. Genetic p-distances between all haplotypes, between and within the three clades, were calculated and are shown in Table 2.

Table 2 Comparison of average (min–max) genetic p-distance, within each clade, between clades, and between all haplotypes

The 25 haplotypes were joined into a single haplotype network with 95% probability, which showed the host plant association and phylogenetic relationships of all haplotypes (Fig. 1b). This network revealed three haplotype groups corresponding to the three previously defined clades (A, B, and C). Clades B and C diverged by six mutation steps from clade A. As mentioned above, the structure of haplotypes corresponded to the three clades of the European phylogeographic study (Avtzis et al. 2008a) and not associated with the host plants.

3.1.3 Population genetic parameters and analyses of population structure

The proportion of the various haplotypes yielded a high haplotype diversity of 0.77 ± 0.06. However, nucleotide diversity (π = 0.008 ± 0.001) and mean number of pairwise differences (4.87 ± 2.41) were generally low. The indices of population structure Gst and Nst were 0 and 0.042, respectively, and did not differ significantly from each other, indicating a weak phylogeographical structure. The within-population diversity indices were summarized per region and per host in Table 3. The haplotype diversity was higher in the Jura than in Limousin, while the nucleotide diversity and the mean number of pairwise nucleotide differences between haplotypes showed a similar pattern in the two regions. The haplotype diversity (H d) within host species groups ranged from 0.39 to 0.90 with an average of 0.73. The lowest H d was found in the exotic species P. sitchensis, with two different haplotypes out of nine sampled individuals. H d was high for the native P. abies and the three exotic species A. grandis, P. menziesii, and P. strobus. According to the values of the allelic richness after rarefaction, individuals from P. abies did not have more haplotypes when the number of samples was similar for each host species. Nevertheless, allelic richness was still high for most host species, since more than two haplotypes were found on average for only five individuals.

Table 3 Within-population diversity indices of P. chalcographus samples for COII and for ITS2: because of unequal sampling size for different host species, allelic richness was calculated using rarefaction size as indicated between square brackets

AMOVA results for all three grouping options are presented in Table 4. When populations were grouped “by region,” “by host,” or “by host origin,” the main part of the observed variability was due to the genetic difference within populations (97%, 98%, and 98%, respectively), but the results were not significant. Moreover, the exact test of differentiation among sites was not significant (P = 0.35149).

Table 4 Analysis of molecular variance (AMOVA) between French populations of Pityogenes chalcographus, with grouping by region, host species, and host origin

3.1.4 Correlation matrix

The genetic distances between the six host tree species were not correlated with the ΦST genetic differentiation indices between P. chalcographus samples grouped by host species (Mantel test, r S = 0.022, P = 0.99), indicating that tree species taxonomically close to each other did not tend to be exploited by genetically close insect populations.

3.2 Nuclear DNA

3.2.1 Sequence alignment and alleles reconstruction

Twenty-nine ITS2 sequences were aligned over 512-bp. No insertion and deletion of sequence was observed between the individuals analyzed. Only five distinct alleles were obtained (GenBank accession numbers JQ066307-JQ066311) with four polymorphic sites (one of which was parsimony informative) and all substitutions were transitions. No heterozygous individual was observed in P. chalcographus. This phenomenon was not rare due to concerted evolution which usually results in the presence of a single dominant ITS allele per individual, with little intra-specific variation (Hillis and Dixon 1991). Three alleles were found only once, two on P. abies coded Ia and IIa and one on P. menziesii coded Ib, whereas both alleles I and II were found in 13 individuals and were observed in the two regions and on both native and exotic conifer species (Table 1).

The proportion of different alleles in the samples yielded a genetic diversity of 0.615 ± 0.052, and the nucleotide diversity was very low with a value of 0.0014 ± 0.0012. The genetic distances between all alleles calculated with the p-distance model ranged from 0.002 to 0.006, with an average of 0.004. All phylogenetic analyses as well as the network described no obvious pattern of host-associated group (data not shown).

3.2.2 Population genetic parameters

The diversities within population are shown by region and by host in Table 3. The diversities within regions were approximately similar, and the genetic and nucleotide diversities within regions corresponded to those of the total genetic and nucleotide diversities over all regions. P. menziesii and P. sitchensis showed higher genetic diversity per host species than A. grandis and P. abies. Nevertheless, values of the allelic richness after rarefaction ranged from 1 to 1.6 among the host species tested. Given the low polymorphism level in ITS2 sequences, no further analyses of genetic structure were performed.

4 Discussion

The diversity of European and North American conifer species in France made it possible to estimate whether the expansion of the insect host range following extensive reforestation with exotic conifers may have contributed to the differentiation of populations of P. chalcographus. The COII gene was useful because of its high variability and its ability to explain recent historical events. Conversely, the nuclear marker ITS2, mainly used to highlight cryptic species, did not provide any additional information in this study. The sampling size was limited by the following criteria: (1) individuals were sampled in sympatric areas on a total of eight native and exotic host species; (2) the colonization rate on the different host tree species studied varied because the beetles preferred and better performed their development and fecundity with some tree species, which led to different sample sizes (Bertheau et al. 2009a, b). Despite this limitation, our results tended to show that the host tree species may not constitute an effective isolating barrier between P. chalcographus populations.

One finding that emerged from this study was the low nucleotide diversity with few mutations observed in the COII gene sequences as opposed to the high haplotypic diversity in the P. chalcographus samples. This significant haplotype diversity expressed as the number of haplotypes (25 haplotypes for 61 individuals) is in agreement with the diversity observed with COI gene sequences for the same species (58 haplotypes for 262 individuals, in Avtzis et al. 2008a); more than 140 haplotypes for 523 individuals, in Bertheau, personal communication). Based on COI and/or COII gene diversity, P. chalcographus had the highest haplotype richness compared to other European bark beetles species studied, such as Ips typographus (Stauffer et al. 1999), Tomicus destruens Woll. (Horn et al. 2006) or Tomicus piniperda L. (Horn et al. 2009). The wider diet breadth of the bark beetle may explain this genetic diversity. Gaete-Eastman et al. (2004) highlighted that local aphids populations with broadest diet breadth showed higher genetic diversity compared to a strict specialist aphid species. This could be the case of P. chalcographus since it has broader host range than the other bark beetles mentioned above (Bertheau et al. 2009b; Pfeffer 1994).

Despite a rather low sampling size per host tree species, a general tendency to an absence of global genetic differentiation among insect populations appears through the genetic analyses. First, AMOVA showed that the greatest genetic diversity was found within populations, whatever the grouping factor tested (i.e., region, host species, or host origin). A similar pattern has been found in T. destruens (75–82% variation within populations, Kerdelhué et al. 2002) and in Orthotomicus erosus Woll. (87–93% variation within populations, Pointeau et al., personal communication). Secondly, the phylogenetic analyses as well as the haplotype network also reflected the lack of differentiation since the main clade (A) grouped individuals from different localities (Limousin and Jura) and from different host species (native and exotic) (Fig. 1). Nuclear DNA sequencing confirmed these results since the main two alleles I and II were observed whatever the sampling site (region) and host species (Table 1). Although the diet breadth is known to play a significant role in structuring bark beetle populations (Cognato and Sperling 2000; Sturgeon and Mitton 1986), the lack of differentiation by host is not rare, especially for beetle species living in regions under strong human pressure from major reforestation and wood transport. For example, the lineage diversification of Ips confusus Leconte was not greatly influenced by the host specificity (Cognato et al. 2003); no difference was found between populations of Dendroctonus jeffreyi Hopkins or D. ponderosae Hopkins collected from sympatric host species (Kelley et al. 2000), and no host effect was observed in Polygraphus grandiclava Thomson populations (Avtzis et al. 2008b). Finally, the Mantel test did not provide any correlation between genetic distances between host tree species and genetic differentiation among P. chalcographus samples grouped by host tree species. Even if the sampling needs to be completed to assess this assumption, it seems plausible to say that taxonomically closely related tree species did not tend to be exploited by genetically closely related insect populations.

Subject to confirmation using a larger sampling size, the high genetic diversity associated with the lack of genetic differentiation of P. chalcographus populations might result from certain gene flow between the populations on the various host species exploited by the beetle. There may be several explanations for this pattern. The dispersal ability of phytophagous insects appears to be an important ecological factor determining population structure (Peterson and Denno 1998). These authors showed that species with moderate mobility may undergo a significant decline in gene flow with distance, while more vagile species display a complete lack of isolation by distance. Comparably high effective dispersal abilities with lack of genetic differentiation have generally been reported for bark beetle species such as I. typographus (Sallé et al. 2007), T. piniperda (Kerdelhue et al. 2006) and O. erosus (Pointeau et al., personal communication). P. chalcographus is known to have considerable dispersal ability since it is able to fly as far as 86 km (Nilssen 1984). Like most bark beetle species confined to weakened or felled trees, especially on broken tops and branches and on logging waste for P. chalcographus (Hedgren et al. 2003), this high dispersal ability may be the result of an adaptation to a patchy, ephemeral breeding resource. Selection pressure and evolution may increase dispersal abilities in insects for which availability of suitable hosts is unpredictable in space and time (Gandon et al. 1998). In addition to natural dispersal capacities, the transportation of cut trees via human activities such as wood trade could play a significant role in increasing the movement of the beetles (Kerdelhue et al. 2006). The short distances between studied plots in each region compared to the P. chalcographus flight distance could also facilitate displacement between the various available tree species. All these factors would have homogenized P. chalcographus populations.

In a previous behavioral study of P. chalcographus, Bertheau et al. (2009a) showed that, although P. abies was the preferred and most suitable host of P. chalcographus, all conifer species tested were colonized. Furthermore, little or no difference was found in beetle fitness on P. sitchensis and P. menziesii. The similarities between its natural and alternative host species, such as morphological characteristics (i.e., thin bark thickness) and probably chemical compounds, provided good conditions for adaptation to new hosts (Bertheau et al. 2009a). All these considerations, together with its biological and behavioral traits and its tendency to a lack of population genetic differentiation, suggest that P. chalcographus may use alternative hosts without losing any ability to exploit its natural host P. abies. A more complete sampling, combined with more polymorphic markers (as microsatellites) would permit to draw more general conclusions. Nevertheless, these findings are important to consider for forest pest management, health, and phytosanitary measures for the timber trade, especially for risk assessment in mixed coniferous forests.

References

  • Agnoletti M, Anderson S (2000) Forest history: international studies on socioeconomic and forest ecosystem change CAB International. CAB International, Wallingford

    Book  Google Scholar 

  • Arthofer W, Avtzis DN, Riegler M, Stauffer C (2010) Mitochondrial phylogenies in the light of pseudogenes and Wolbachia: re-assessment of a bark beetle dataset. ZooKeys 56:269–280

    Article  PubMed  Google Scholar 

  • Avtzis DN, Arthofer W, Stauffer C (2008a) Sympatric occurrence of diverged mtDNA lineages of Pityogenes chalcographus (Coleoptera, Scolytinae) in Europe. Biol J Linn Soc 94:331–340

    Article  Google Scholar 

  • Avtzis DN, Knizek M, Hellrigl K, Stauffer C (2008b) Polygraphus grandiclava (Coleoptera: Curculionidae) collected from pine and cherry trees: A phylogenetic analysis. Eur J Entomol 105:789–792

    Google Scholar 

  • Becerra JX (1997) Insects on plants: macroevolutionary chemical trends in host use. Science 276:253–256

    Article  PubMed  CAS  Google Scholar 

  • Bertheau C, Sallé A, Roux-Morabito G, Garcia J, Certain G, Lieutier F (2009a) Preference-performance relationship and influence of plant relatedness on host use by Pityogenes chalcographus L. (Coleoptera: Scolytinae). Agric For Entomol 11:89–396

    Article  Google Scholar 

  • Bertheau C, Sallé A, Rossi JP, Bankhead-Dronnet S, Pineau X, Roux-Morabito G, Lieutier F (2009b) Colonisation of native and exotic conifers by indigenous bark beetles (Coleoptera: Scolytinae) in France. For Ecol Manage 258:1619–1628

    Article  Google Scholar 

  • Bogdanowicz SM, Wallner WE, Bell J, O’ Dell TM, Harrison RG (1993) Asian gypsy moths (Lepidoptera, Lymantriidae) in North America—evidence from molecular data. Ann Entomol Soc Am 86:710–715

    CAS  Google Scholar 

  • Campbell JC, Steffen-Campbell JD, Werren JH (1993) Phylogeny of the Nasonia species complex (Hymenoptera: Pteromalidae) inferred from internal transcribed spacer (ITS2) and 28rDNA sequences. Ins Mol Biol 2:225–237

    Article  CAS  Google Scholar 

  • Clement M, Posada D, Crandall KA (2000) TCS: a computer program to estimate gene genealogies. Mol Ecol 9:1657–1659

    Article  PubMed  CAS  Google Scholar 

  • Cognato AI, Harlin AD, Fisher ML (2003) Genetic structure among pinyon pine beetle populations (Scolytinae: Ips confusus). Environ Entomol 32:1262–1270

    Article  Google Scholar 

  • Cognato AI, Sperling FAH (2000) Phylogeny of Ips DeGeer species (Coleoptera: Scolytidae) inferred from mitochondrial cytochrome oxidase I DNA sequence. Mol Phylogenet Evol 14:445–460

    Article  PubMed  CAS  Google Scholar 

  • Crandall KA, Templeton AR (1993) Empirical tests of some predictions from coalescent theory with applications to intraspecific phylogeny reconstruction. Genetics 134:959–969

    PubMed  CAS  Google Scholar 

  • Diegisser T, Tritsch C, Seitz A, Johannesen J (2009) Infestation of a novel host plant by Tephritis conura (Diptera: Tephritidae) in northern Britain: host-range expansion or host shift? Genetica 137:87–97

    Article  PubMed  CAS  Google Scholar 

  • Degomez T, Wagner MR (2001) Arthropod diversity of exotic vs. native Robinia species in northern Arizona. Agric For Entomol 3:19–27

    Article  Google Scholar 

  • Drès M, Mallet J (2002) Host races in plant-feeding insects and their importance in sympatric speciation. Phil Trans Roy Soc Lond B Biol Sci 357:471–492

    Article  Google Scholar 

  • Excoffier L, Laval G, Schneider S (2005) Arlequin (version 3.0): an integrated software package for population genetics data analysis. Evol BioinformOnline 1:47–50

    CAS  Google Scholar 

  • Excoffier L, Smouse PE, Quattro JM (1992) Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction data. Genetics 131:479–491

    PubMed  CAS  Google Scholar 

  • Feder JL, Opp S, Wlazlo B, Reynolds K, Go W, Spisak S (1994) Host fidelity is an effective pre-mating barrier between sympatric races of the apple maggot fly. Proc Natl Acad Sci USA 91:7990–7994

    Article  PubMed  CAS  Google Scholar 

  • Feder JL, Chilcote CA, Bush GL (1988) Genetic differentiation between sympatric host races of Rhagoletis pomonella. Nature 336:61–64

    Article  Google Scholar 

  • Felsenstein J (1988) Phylogenies from molecular sequences: inferences and reliability. Annu Rev Genet 22:521–565

    Article  PubMed  CAS  Google Scholar 

  • Gaete-Eastman C, Figueroa CC, Olivares-Donoso R, Niemeyer HM, Ramírez CC (2004) Diet breadth and its relationship with genetic diversity and differentiation: the case of southern beech aphids (Hemiptera: Aphididae). Bull Entomol Res 94:219–227

    Article  PubMed  CAS  Google Scholar 

  • Gandon S, Ebert D, Olivieri I, Michalakis Y (1998) Differential adaptation in spatially heterogeneous environments and host-parasite coevolution. In: Mopper S, Strauss S (eds) Genetic structure and local adaptation in natural insect populations. Chapman and Hall, London, pp 325–340

    Google Scholar 

  • Hall TA (1999) BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT. Nucl Acids Symp Ser 41:95–98

    CAS  Google Scholar 

  • Hare JD (1990) Ecology and management of the Colorado potato beetle. Annu Rev Entomol 35:81–100

    Article  Google Scholar 

  • Hedgren PO, Weslien J, Schroeder LM (2003) Risk for attacks and tree mortality caused by Pityogenes chalcographus L. (Col.: Scolytidae) on young Norway spruce close to cut trees. Scand J For Res 18:39–44

    Google Scholar 

  • Hillis DM, Dixon MT (1991) Ribosomal DNA: molecular evolution and phylogenetic inference. Q Rev Biol 66:411–453

    Article  PubMed  CAS  Google Scholar 

  • Horn A, Stauffer C, Lieutier F, Kerdelhué C (2009) Complex postglacial history of the temperate bark beetle Tomicus piniperda L. (Coleoptera, Scolytinae). Heredity 103:238–247

    Article  PubMed  CAS  Google Scholar 

  • Horn A, Roux-Morabito G, Lieutier F, Kerdelhué C (2006) Phylogeographic structure and past history of the circum-Mediterranean species Tomicus destruens Woll. (Coleoptera: Scolytinae). Mol Ecol 15:1603–1615

    Article  PubMed  CAS  Google Scholar 

  • Jaenike J (1990) Host specialization in phytophagous insects. Annu Rev Ecol Syst 21:243–273

    Article  Google Scholar 

  • Kelley ST, Farrell B, Mitton JB (2000) Effects of specialization on genetic differentiation in sister species of bark beetles. Heredity 84:218–227

    Article  PubMed  Google Scholar 

  • Kerdelhue C, Magnoux E, Lieutier F, Roques A, Rousselet J (2006) Comparative population genetic study of two oligophagous insects associated with the same hosts. Heredity 97:38–45

    Article  PubMed  CAS  Google Scholar 

  • Kerdelhué C, Roux-Morabito G, Forichon J, Chambon JM, Robert A, Lieutier F (2002) Population genetic structure of Tomicus piniperda L. (Curculionidae: Scolytidae) on different pine species and validation of T. destruens (Woll.). Mol Ecol 11:483–494

    Article  PubMed  Google Scholar 

  • Kimura M (1980) A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences. J Mol Evol 16:111–120

    Article  PubMed  CAS  Google Scholar 

  • Lopez-Vaamonde C, Charles H, Godfray J, Cook JM (2003) Evolutionary dynamics of host-plant use in a genus of leaf-minig moths. Evolution 57:1804–1821

    PubMed  Google Scholar 

  • McPheron BA, Smith DC, Berlocher SH (1988) Genetic differences between host races of Rhagoletis Pomonella. Nature 336:64–66

    Article  Google Scholar 

  • Mopper S (1996) Adaptive genetic structure in phytophagous insect population. Trends Ecol Evol 11:235–238

    Article  PubMed  CAS  Google Scholar 

  • Nilssen AC (1984) Long-range aerial dispersal of bark beetles and bark weevils (Coleoptera, Scolytidae and Curculionidae) in northern Finland. Ann Entomol Fenn 50:37–42

    Google Scholar 

  • Peterson MA, Denno RF (1998) The influence of dispersal and diet breadth on patterns of genetic isolation by distance in phytophagous insects. Am Nat 152:428–446

    Article  PubMed  CAS  Google Scholar 

  • Petit RJ, El MA, Pons O (1998) Identifying populations for conservation on the basis of genetic markers. Conserv Biol 12:844–855

    Article  Google Scholar 

  • Pfeffer A (1994) Zentral- und westpalaarktische Borken- und Kernkafer (Coleoptera: Scolytidae, Platypodidae). In: Brancucci M, Wittmer M (eds) Entomologica Basiliensia 17. Naturhistorisches Museum Basel, Basel, pp 5–310

    Google Scholar 

  • Pons O, Petit RJ (1996) Measuring and testing genetic differentiation with ordered versus unordered alleles. Genetics 144:1237–1245

    PubMed  CAS  Google Scholar 

  • Posada D, Crandall KA (1998) MODELTEST: testing the model of DNA substitution. Bioinformatics 14:817–818

    Article  PubMed  CAS  Google Scholar 

  • Raymond M, Rousset F (1995) GENEPOP: population genetics software for exact tests and eucumenicism. J Heredity 86:248–249

    Google Scholar 

  • Rychlik W (2007) OLIGO 7 Primer Analysis Software. In: Yuryev A (ed) Methods in molecular biology, vol 402, PCR primer design. Humana, Totowa, pp 35–59

    Google Scholar 

  • Sallé A, Arthoffer W, Lieutier F, Stauffer C, Kerdelhué C (2007) Phylogeography of a species-specific insect: genetic structure of Ips typographus in Europe does not reflect the past fragmentation of its host. Biol J Linn Soc 90:239–246

    Article  Google Scholar 

  • Schoonhoven LM, van Loon JJA, Dicke M (2005) Insect–plant biology. Oxford University Press, New York, p 440

    Google Scholar 

  • Simon C, Frati F, Beckenbach A, Crespi B, Liu H, Flook P (1994) Evolution, weighting, and phylogenetic utility of mitochondrial gene sequences and a compilation of conserved polymerase chain reaction primers. Ann Entomol Soc Am 87:651–701

    CAS  Google Scholar 

  • Smouse PE, Long JC, Sokal RR (1986) Multiple regression and correlation extensions of the Mantel Test of matrix correspondence. Syst Zool 35:627–632

    Article  Google Scholar 

  • Stauffer C, Lakatos E, Hewitt GM (1999) Phylogeography and postglacial colonization routes of Ips typographus L. (Coleoptera, Scolytidae). Mol Ecol 8:763–773

    Article  Google Scholar 

  • Strong DR, Lawton JH, Southwood TRE (1984) Insects on plants. Blackwell Scientific, Oxford, p 313

    Google Scholar 

  • Sturgeon KB, Mitton JB (1986) Allozyme and morphological differentiation of mountain pine beetles Dendroctonus ponderosae Hopkins (Coleoptera: Scolytidae) associated with host tree. Evolution 40:290–302

    Article  Google Scholar 

  • Swofford DL (2002) PAUP*: Phylogenetic Analysis Using Parsimony (*and other methods). Sinauer Associates, Sunderland, p 142

    Google Scholar 

  • Thompson JD, Higgins DG, Gibson TJ (1994) Clustal W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, positions-specific gap penalties and weight matrix choice. Nucleic Acids Res 22:4673–4680

    Article  PubMed  CAS  Google Scholar 

  • Vanbergen AJ, Hodgson DJ, Thurlow M, Hartley SE, Watt AD (2003) Food-plant effects on larval performance do not translate into differences in fitness between populations of Panolis flammea (Lepidoptera: Noctuidae). Bull Entomol Res 93:553–559

    Article  PubMed  CAS  Google Scholar 

  • Via S (1990) Ecological genetics and host adaptation in herbivorous insects: the experimental study of evolution in natural and agricultural systems. Annu Rev Entomol 35:4421–4446

    Article  Google Scholar 

  • Zhang DX, Hewitt GM (1996) Nuclear integrations: challenges for mitochondrial DNA markers. Trends Eco Evol 11:247–251

    Article  CAS  Google Scholar 

  • Zobel BG, Van Wyk G, Stahl P (1987) Growing exotic forests. Wiley, New York, p 508

    Google Scholar 

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Acknowledgments

This work is part of the PhD thesis of C. Bertheau carried out under the direction of F. Lieutier with the participation of G. Roux-Morabito as a co-supervisor. We are grateful to Philippe Massot and Dominique Jacquin (Office National des Forêts) for their help in choosing the experimental plots and obtaining coniferous trees and to Jacques Garcia (INRA Orléans) for his field assistance. We thank Christian Stauffer (Vienna, Boku University) for providing European samples. We also thank Emmanuelle Magnoux (INRA Orléans) for her assistance with the ABI 3100 automatic sequencer and Vincent Lesieur (Orléans University trainee) for his technical participation. We are grateful to Dimitrios Avtzis (Vienna, Boku University) for his fruitful discussions and to Christian Stauffer (Vienna, Boku University) for his valuable remarks on the previous manuscript, as well as the two anonymous reviewers for their very useful and constructive comments.

Funding

The work was supported by grants from the French Ministry for Agriculture, Fisheries and Rural Affairs (General Directorate of Forests and Rural Affairs), from the French Ministry of Research and Education and from the Austrian Science Foundation (FWF) P 21147-B17.

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Correspondence to Coralie Bertheau.

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Contribution of the co-authors

Coralie Bertheau: was a PhD student in the University of Orléans (France) when the experiments took place. Now she is a post-doctoral research associate at the Institute of Forest Entomology, Forest Pathology and Forest Protection, Boku, University of Natural Resources and Life Sciences in Vienna (Austria). She coordinated the project from its elaboration until the submission of the paper. She designed the experiments, sampled beetles, did technical experiments and phylogenetic data analyses, and wrote the paper.

Stéphanie Bankhead-Dronnet: is Assistant Professor at the University of Orléans. She contributed in phylogenetic data analyses and in writing of the paper.

Carine Martin: is a technical assistant at the University of Orléans and participated to the sampling and the experimental work.

François Lieutier: is a Professor at the University of Orléans. He led this project, supervised the work, helped in beetles sampling and read, corrected, discussed and approved the final version of the paper.

Geraldine Roux-Morabito: is Assistant Professor at the University of Orléans and conducts her research at the INRA Orléans in the units of forest zoology. She led the project, supervised the word and participated in the sampling, in phylogenetic data analyses and in writing of the paper.

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Bertheau, C., Bankhead-Dronnet, S., Martin, C. et al. Lack of genetic differentiation after host range extension argues for the generalist nature of Pityogenes chalcographus (Curculionidae: Scolytinae). Annals of Forest Science 69, 313–323 (2012). https://doi.org/10.1007/s13595-011-0161-4

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