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Phylogeny and Historical Biogeography of Asian Pterourus Butterflies (Lepidoptera: Papilionidae): A Case of Intercontinental Dispersal from North America to East Asia

Phylogeny and Historical Biogeography of Asian Pterourus Butterflies (Lepidoptera: Papilionidae): A Case of Intercontinental Dispersal from North America to East Asia

  • Li-Wei Wu, 
  • Shen-Horn Yen, 
  • David C. Lees, 
  • Chih-Chien Lu, 
  • Ping-Shih Yang, 
  • Yu-Feng Hsu
PLOS
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Abstract

The phylogenetic status of the well-known Asian butterflies often known as Agehana (a species group, often treated as a genus or a subgenus, within Papilio sensu lato) has long remained unresolved. Only two species are included, and one of them especially, Papilio maraho, is not only rare but near-threatened, being monophagous on its vulnerable hostplant, Sassafras randaiense (Lauraceae). Although the natural history and population conservation of “Agehana” has received much attention, the biogeographic origin of this group still remains enigmatic. To clarify these two questions, a total of 86 species representatives within Papilionidae were sampled, and four genes (concatenated length 3842 bp) were used to reconstruct their phylogenetic relationships and historical scenarios. Surprisingly, “Agehana” fell within the American Papilio subgenus Pterourus and not as previously suggested, phylogenetically close to the Asian Papilio subgenus Chilasa. We therefore formally synonymize Agehana with Pterourus. Dating and biogeographic analysis allow us to infer an intercontinental dispersal of an American ancestor of Asian Pterourus in the early Miocene, which was coincident with historical paleo-land bridge connections, resulting in the present “East Asia-America” disjunction distribution. We emphasize that species exchange between East Asia and America seems to be a quite frequent occurrence in butterflies during the Oligocene to Miocene climatic optima.

Introduction

Morphological and/or molecular data analyses have provided strong support for many monophyletic clades within the family Papilionidae. There is now wide consensus that Papilionidae is sister to all other Papilionoidea, which include Hesperiidae and Hedylidae [13]. In the past decade, based on substantial sequence data and quite comprehensive taxon sampling, knowledge of swallowtail butterfly phylogeny has become increasingly robust [410]. Recently, tribal relationships within the largest subfamily Papilioninae have been revised, including Meandrusa and Teinopalpus [10]. These two Asian genera, classically treated as members of the tribe Papilionini [1113], are now placed in the tribe Teinopalpini [10].

The Papilio elwesi-species group [11] (as we refer to the most commonly used genus-group name Agehana Matsumura, 1936) has been considered an important lineage to include to clarify phylogenetic relationships within Papilio sensu lato [14]. This group is endemic to eastern Asia, and is morphologically very distinct from other Asian butterflies. Two species are recognized [15]: the continental species, P. elwesi Leech 1889, distributed from Southwest to Southeast mainland China, and the insular species, P. maraho, endemic to Taiwan. The latter species has the highest profile due to its rarity and listing as a vulnerable species in the IUCN Red Data Book [16], and it has been classified as an endangered species locally since 1994 [17]. Both species exhibit a fragmented distribution like their hosts, but P. elwesi has a larger population range than P. maraho. This is not surprising because immatures of the former can utilize both wider distributed Lauraceae (Sassafras tzumu) and Magnoliaceae (Liriodendron chinense, and Magnolia officinalis) [15], while the latter only feeds on an IUCN vulnerable plant, S. randaiense, sparsely distributed in sunny environments of forest gaps at medium elevations of the Central Mountain Range of Taiwan [18].

Presently Papilio sensu lato is divided into four major lineages [10, 14, 19]. The first is the subgenus Heraclides Hübner, 1819 (the Heraclides-clade), comprising 29 species and only occurs in the Americas. The second includes the subgenera Pterourus Scopoli, 1777 and Chilasa Moore, 1881 (the Pterourus-clade), which are respectively endemic to America (20 spp.) and Asia (13 spp.). The third is the largest lineage, consisting of Papilio Linnaeus, 1758 together with the subgenera Princeps Hübner, 1806, Achillides Hübner, (1819), Druryia Aurivillius, 1881, Menelaides Hübner, [1819], Princeps Hübner, (1807), Sinoprinceps Hancock, 1983, and Eleppone Hancock, 1979 (referred to hereafter as the machaon-clade, 143 spp.). The fourth lineage is the subgenus Alexanoria Koçak and Kemal, 2002, with just one species, P. alexanor. The phylogenetic position of the elwesi-species group is still ambiguous among different studies [11, 13, 19]. It has been treated as independent subgenus Agehana [13], or synonymized with the subgenus Chilasa [11].

Much effort has gone into assessing not only their classification and systematics, but also life cycle, ecology, and conservation evaluation of “Agehana” [13, 15, 20]. However, the precise placement of the elwesi-group has long remained enigmatic, despite a number of taxonomically quite densely sampled phylogenetic treatments of swallowtail butterflies in recent years, which did not however include this group [5, 14, 21]. Based on current evidence, the Old World danaine-mimetic subgenus Chilasa has been considered as the most plausible sister to this group [11, 13, 19]. The elwesi-group and Chilasa not only exhibit mimicry (the former have an Atrophaneura-like wing pattern), but also share a similar distribution [22]. However, the elwesi-group has very different larval and adult morphology to typical members of Chilasa [13]. Meanwhile, the specialized host-plant relationships of this elwesi-group could also shed light on its phylogenetic relationship, since both Sassafras spp. (Lauraceae) and Liriodendron spp. (Magnoliaceae), exhibit a disjunct distribution between Eastern Asia and North America [23], while only some Pterourus species (e.g. P. glaucus and P. troilus) have been recorded to use these two hostplant genera [24, 25]. The elwesi-species group has even been considered as a member of Pterourus in one work [26]. However, this phylogenetic hypothesis may be considered tentative only, because of no phylogenetic analyses on the elwesi-species group has ever been carried out with other Pterourus-clade members.

The possibility must then be considered that the elwesi-species group does not represent local evolution with Asian congeners. Recently, and not surprisingly, dispersal has been shown to be a major process shaping Papilio distributions [4, 21]. With increasing amount of molecular sequence data available for Papilionidae, the phylogenetic placement of the elwesi-group as well as the dispersal question can be objectively re-examined. Here, we take the opportunity to re-examine the relationships within the Pterourus-clade based on previous comprehensive phylogenetic analyses for the family Papilionidae [4, 14]. Then, we further revise the phylogenetic relationships of the Pterourus-clade and elucidate the historical biogeography of the elwesi-species group based on an evaluation of divergence times and the most probable historical scenario.

Materials and Methods

Sampling

This study adds sequences for new sampling of taxa both for the elwesi-group species (P. elwesi and P. maraho) and for seven related species, including six Chilasa members (C. agestor, C. slateri, C. osmana, C. paradoxa, C. veiovis, and C. laglaizei), and Papilio bootes. Other related species and outgroups were obtained using public domain sequences [2, 4, 8, 10, 14, 27] (species used in this study are listed in S1 Table). To evaluate the phylogenetic position of the elwesi-species group, a total of 42 species representatives were used (the 42-dataset; No. 1–42, S1 Table) based on previously reported phylogenetic relationships [4, 14]. In this 42-dataset, two species, Battus philenor and Meandrusa sciron, were set as functional outgroups [28] to investigate the phylogenetic position of the elwesi-group among the four major subdivision clades of Papilio [10, 14, 19]. Moreover, further taxa were added for calibrating dating points, this larger dataset is referred to as the 87-dataset, comprising 86 species including two specimens for the deep-branching species Baronia brevicornis (No. 1–87, S1 Table). This 87-dataset represents all butterfly families, including most major subfamilies and tribes of Papilionoidea for the dating estimation.

Ethics Statement

None of our sampled materials involve vertebrates or cephalopods. Papilio maraho was the only species on the list of protected species in Taiwan, and we had permission for sampling this species that was issued by the Council of Agriculture (Taiwan). All the other species used in the manuscript are not listed as endangered species and were not collected from any locations that are national parks or natural reserves, thus no specific permission was required for sampling these species. All field studies performed in the present study did not involve endangered or protected species except for P. maraho.

Molecular technologies

Genomic DNA was extracted from the thoracic muscle using the Purgene DNA Isolation kit (Gentra Systems, Minnesota, USA). Precipitated DNAs were resuspended in 50 μL of dH2O. The primers used for amplifying the mitochondrial cytochrome c oxidase 1 (cox1, 1530 bp), cytochrome c oxidase 2 (cox2, 681 bp), nuclear elongation factor 1 alpha (Ef-1α, 1225 bp) and wingless genes (wg, 403 bp) have been described previously [6, 15, 2931], and novel primers which were designed for the cox1-cox2 region of the Papilio elwesi-species group and for the partial Ef-1α gene of Chilasa members are listed in Table 1. Each polymerase chain reaction (PCR) was carried out in a final volume of 30 μL, with 0.2 μM of each primer. The following PCR settings were adopted: 2 min at 94°C, followed by 35 cycles of 30s at 94°C, 30s at 50–60°C, and 1–2 min at 72°C. The final elongation step was continued for 7 min at 72°C, and stopped at 4°C. If the above conditions failed, we amplified the fragments using a touchdown method: 2 min at 94°C, then following by 10 cycles of 30s at 94°C, 30s at 65°C decreasing 0.5°C degree each cycle, 1–2 min at 72°C, and then followed by 35 cycles of 30s at 94°C, 30s at 50°C, and 1–2.5 min at 72°C. The final elongation step was continued for 7 min at 72°C, and stopped at 4°C. The PCR products were run on 1.0% agarose gels in 1X TBE buffer to ensure that the lengths of PCR fragments were correctly amplified. DNA sequences were conducted using an ABI3730 DNA Analyzer (Applied Biosystems, Foster City, CA, USA).

Sequence treatment

Molecular sequences of cox1, cox2, Ef-, and wg genes were checked and assembled into contigs using Sequencher 4.8 (GeneCode, Boston, USA). Primer regions were cropped, and the uncompleted stop codons of cox1 and cox2 were removed to avoid length variation. The data sets were aligned according to amino sequence similarity by MUSCLE implied in MEGA5 [32]. Missing data and ambiguities were designated as IUPAC codes. All sequences were submitted to GenBank (GenBank accession numbers are listed in S1 Table; DNA alignment files can be obtained from S1 File). General sequence information was analyzed via the web server DIVEIN [33] and the results were double checked manually in Microsoft Excel. For phylogenetic analyses, aligned genes were concatenated via Microsoft Excel, and these datasets were converted to Fasta, Phylip, or Nexus format for further analyses.

Phylogenetic analyses

A range of phylogenetic methods were used to infer phylogenies on the 42-dataset (S1 Table; S1 File). Maximum parsimony (MP) was performed in PAUP*10b [34]. Bayesian inference (BI) was carried out using MrBayes v. 3.2.1 [35], and Maximum Likelihood (ML) was performed in RAxML Pthreads-based version 7.0.4 [36, 37]. In the MP method, Meandrusa sciron and Battus philenor were set as outgroups and the remaining taxa as ingroups. The MP trees were reconstructed using heuristic searches, with starting trees determined by 1,000 random taxon additions, using the tree bisection-reconnection (TBR) branch swapping algorithm. All characters were treated as equally weighted. A strict consensus tree was computed in cases where multiple equally parsimonious trees were obtained. Bootstrap analyses were performed using heuristic searches, 100 random taxon additions, and the TBR algorithm. The number of bootstrap replicates was set to 1000.

Different data partitioning and substitution models would lead to varying branch lengths and consequently provide different phylogenetic topologies and dating estimates [38, 39]. To test our likelihood methods, we firstly divided our data matrix into six partitioning strategies (PSs). These are referred to as (1) no partition: four genes concatenated into one, (2) two partitions, one for mitochondrial genes and one for nuclear genes, (3) three partitions, one for the cox1+cox2 genes, one for the Ef-1a gene, and one for the wg gene, (4) four partitions, for four genes, (5) nine partitions, for codon positions of cox1+cox2, Ef-1α, and wg genes, and (6) 12 partitions for codon positions of the four genes. The best-fit substitution model of each partition was evaluated by jModeltest 2 [40]. The 88 candidate models were set, and the corrected Akaike Information Criterion (AICc) was used to assign the optimal criterion (S2 Table). Moreover, we also used PartitionFinder 1.1.1 [41] to choose the best-fit substitution models and data partitions (hereafter referred to as best-fit PS). We divided our data matrix into 12 subsets (according to four genes and their codon positions) and relied on the PartitionFinder to estimate the best fit PS and substitution models. The result showed that there are eleven partitions and their best-fit substitution models are listed in S3 Table. To investigate which PS was the most strongly preferred [38], our seven PSs were all evaluated via the analysis of Bayes factors [42]. We took Bayes factors over ten as significantly different. Additional analysis details are described in our previous work [43].

In the BI method, a total of seven PSs were performed with eight chains (seven heated and one cold) and run for ten million generations and sampled trees every 100 generations. The convergence test of Marko Chain Monte Carlo (MCMC) chains was checked using Tracer 1.6 [44], and analyzed results (S2 File) were examined in AWTY [45]. When stationarity of MCMC processes was reached, the first 25% of sampled trees was discarded and the remaining trees were used for representing the posterior probability. For accessing high quality Bayesian phylogenies, the effective sample size (ESS) of each parameter was checked to ensure that all parameters were over 200. For both BI and ML methods, the single-outgroup setting was set to Battus philenor. In the ML method, seven partitioning strategies were set with the model of GTRGAMMA to each partition. All model parameters were estimated by RAxML. Nodal supports were evaluated using 1000 bootstrap replicates with 10 additional ML searches of each replicate.

Estimation of divergence time

We took the 87-dataset and used relaxed Bayesian clock analysis to estimate divergence times using the software BEAST v1.8 [46]. The best-fit PS was found by PartitionFinder, which has eleven partitions divided by codon positions of each gene, except for the combined one including the third codon position of the cox1 and cox2 genes. The xml-file of this PS was created in the platform BEAUti, and used the following non-default settings: a relaxed clock using uncorrelated lognormal was selected; a speciation tree prior was set to Yule Process; the substitution model of each PS partition was set to best-fit models (S3 Table), and the prior parameters of “ucld.mean” were set to “lognormal” distributions. The analysis ran for 100 million generations, sampled every 1000 generations. Once the ESS values of parameters all exceeded 200, the first 10% of sampled trees was discarded and the remaining trees were used for dating purposes.

For molecular dating calibration, we used three butterfly fossils and set these calibration points following the rationale of Ho and Phillips [47]. The minimum age of divergence between Parnassiinae and Papilioninae was set to 48 Ma based on the fossil genus Praepapilio [48]. The minimum divergence boundary of Pierini was set to 34 Ma, based on the fossils of Stolopsyche libytheoides and Oligodonta florissantensis, which were recorded near the Eocene-Oligocene transition [49]. The third setting was the minimum divergence of Vanessa which was set to 34 Ma based on the fossil Vanessa amerindica, which was recorded at the Eocene-Oligocene boundary [50]. The maximum age of each fossil calibration point was set to 183 Ma based on the inferred origin of angiosperm diversification [51] although we note that this is likely to be an upper boundary as it predates the fossil history of flowering plants by at least 40 Ma.

Finally, to evaluate the effect of different PSs on the dating estimation, the PS1 to PS6 datasets were used for inferring dating schemes. The prior settings were set as the same as the best-fit PS, but substitution models of each PS were set to best estimate inferred by jModelTest (S2 Table).

Biogeographical analysis

Biogeographic reconstruction was performed using a dispersal-vicariance analysis [52] through a Bayesian MCMC process (Bayes-DIVA). This method can improve reliability because it provides clade posterior probabilities and phylogenetic uncertainties when multiple equally parsimonious reconstructions occur [39]. The current zoogeographic regions [53] were followed, but some regions were modified to suit our focal species (Fig 1): Afrotropical and Madagascan regions were combined into “I”; Oceanian and Australian regions were combined into “H”; Sino-Japanese and East Palearctic regions into “E”, whereas Saharo-Arabian and West Palearctic regions were combined into “D”. Nine areas were defined and showed in Fig 1. The consensus topology was inferred by the best-fit BI trees. The occurrence of each ancestral area was assigned a fractional ratio when multiple ancestral areas are present on a node [39]. We ran this analysis using the Reconstruct Ancestral State in Phylogenies software (RASP) [54]. With the non-default setting of one million MCMC generations, the temperature was set to 0.2, and the first 25% of trees was discarded. The model frequencies were set to “F81” and rate variation among sites was set to the Gamma distribution.

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Fig 1. Defined Zoogeographic regions in this study.

A: Nearctic region; B: Panamanian region; C: Neotropical region; D: West Palearctic and Saharo-Arabian regions; E: Sino-Japanese and East Palearctic regions; F: India; G: Oriental region; H: Oceanian and Australian regions; I: Afrotropical and Madagascan regions. The drawn map was modified from the time zone map of the World Factbook (https://www.cia.gov/library/publications).

https://doi.org/10.1371/journal.pone.0140933.g001

Results

Phylogenetic analyses

In the 42-dataset, the total alignment matrix contained 3842 bp (with 10% missing data), of which 1530 bp is from cox1, 684 bp from cox2, 1225 bp from Ef-1α, and 403 bp from wg gene. No stop codon was found throughout the whole dataset. A total of 1381 variable sites, with 1027 informative sites were found. In the 87-dataset (with 20% missing data), the alignment matrix and the aligned length of each gene are identical to the 42-dataset. The sum of total sampled lengths has 1755 variable sites, with 1495 informative sites.

Phylogenetic relationships inferred by the best-fit BI and ML methods were congruent (Fig 2). Four major lineages were recognized, and the Heraclides-clade represents the sister lineage to the remaining three major clades. This four-clade relationship is also confirmed by other PS datasets (S3 File), except for the PS1 dataset, which presented the machaon-clade as sister to the other three clades. However, all the PS datasets showed that the relationships among the four major lineages had weak nodal supports. Focusing on the Pterourus-clade, the subgenus Chilasa and the elwesi-group grouped robustly within this clade, and the most intriguing finding was that inclusion of the elwesi-group within Pterourus, split this subgenus into two clades (Pterourus Group A and Group B; Fig 2). High support values showed that Pterourus Group B is more closely related to the elwesi-group than it is to Pterourus Group A. Moreover, the Asian Chilasa represents a sister clade to the remaining members in the Pterourus-clade.

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Fig 2. Phylogenetic relationships inferred by Bayesian best-fit PS and models.

Bayesian posterior probabilities and ML bootstrap values are shown above the branches.

https://doi.org/10.1371/journal.pone.0140933.g002

In the MP method, the whole combined dataset resulted in one most equally parsimonious tree (S1 Fig, tree length = 5329 steps, CI = 0.358, RI = 0.439). The relationships of four major clades represented in the MP topology are mostly concordant with the results inferred by BI and ML methods. A significantly different relationship inferred by MP method is that the elwesi-group grouped with Pterourus Group B, whereas Pterourus Group A was grouped with Chilasa. However, the support values on those relationships were low.

Estimation of divergence time

The BEAST result inferred by the PS5 dataset has a high enough ESS value, and thus we take PS5 instead of the best-fit PS dataset to interpret our dating estimation (also see Bayes factor below). Our estimation of divergence times and their credibility intervals is shown in Fig 3 and S4 Table). The root of the tree was estimated at 69 Ma (node 40), whereas Papilionidae began to diversify at around 57 Ma (node 39). Focusing on the Pterourus-clade, this began to diverge as separated endemic lineages to Asia (Chilasa) and to America (Pterourus Group A and B) near the Oligocene-Miocene transition, approximately 23 Ma (node 20), a little before the divergence between the elwesi-group and Pterourus group B (Fig 2), circa 18 Ma (node 8).

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Fig 3. Calibration times and Bayes-DIVA results on inferred Bayesian consensus tree.

Horizontal bars at nodes are 95% confidence intervals of estimated times. Regional codes are shown in the map, and the major fractional values from Bayes-DIVA are shown near the codes. Light brown bar: “Late Oligocene Climatic Optimum”.

https://doi.org/10.1371/journal.pone.0140933.g003

In our BEAST analysis, we found that using many parameters in two PSs, the best-fit PS and PS6, we could not recover a high enough ESS value (below 100). Even when we increased the number of generations or turned off these low-ESS parameters, the ESS values resulting from these priors were still low. These outcomes might be caused by an incomplete data matrix (20% missing data, some gene sequences were not amplified; S1 Table), or by more partitioning strategies that would acquire smaller datasets to evaluate their parameters.

Dispersal-Vicariance analysis

Focusing on the Pterourus-clade, the Bayes-DIVA outcomes (Fig 3 and S5 Table) postulates that the ancestor of the elwesi-group diversified in the East Asia (node 7, the fraction of E: 0.71, and EG: 0.20) and the most possible origin of the elwesi-group is in America with probabilities over 0.45 (node 8, A: 0.12, B: 0.22, and AB: 0.11). On the contrary, the ancestor of Chilasa diversified in the region spanning the Oriental region to India (node 19, FG: 0.91 and G: 0.03). Although its origin is still unclear (node 20, Fig 3), the diversification shows a dispersal trend from the region “EFG” towards the proximate Australian regions (GH and H) while that of the subgenus Pterourus (Group A and B) trends in the direction from Panamanian (B) to Nearctic (A) region (Fig 1).

Bayes factors

In the 42-datasets for BI phylogenetic reconstruction, Bayes factors for our seven different PSs are shown in Table 2. These comparisons show that more partitioned datasets are strongly preferred over less partitioned ones. One exception is that best-fit PS (11 partitions) and PS5 (9 partitions) performed significantly better than PS6 (12 partitions). The former two PSs are also the most preferred strategies, whereas the combined datasets (PS1) comprise the least preferred one. In the 87-datasets for BEAST analysis, Bayes factors show that the dating scheme inferred by PS5 is most preferred strategy for our dataset, whereas the combined dataset (PS1) produced a significantly worse one (Table 3).

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Table 2. Bayes factor comparisons between PSs of the 42-dataset.

The rank of preference in PS is “best-fit = PS5 > PS6 > PS4 = PS3 = PS2 > PS1”. HM: harmonic mean; M1: model likelihood 1; M2: model likelihood 2.

https://doi.org/10.1371/journal.pone.0140933.t002

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Table 3. Bayes factor comparisons between PSs of the 87-dataset.

The rank of preference PS is “PS5 = best-fit PS>PS2 = PS3>PS4>PS1”. HM: harmonic mean; M1: model likelihood 1; M2: model likelihood 2.

https://doi.org/10.1371/journal.pone.0140933.t003

Effect of different PSs on dating results

Our results show that more partitioned PSs tend to obtain a younger dating scheme, and the range of 95% HPD would be narrower than for less partitioned strategies (Fig 4). The rooting point of Papilionoidea (node 40, Fig 3) is 69 Ma (95% HPD range 62–78 Ma) in PS5, but the values changed to 73 Ma (95% HPD range 61–88 Ma) in PS4, 80 Ma (95% HPD range 63–100 Ma) in PS3, 85 Ma (95% HPD range 65–110 Ma) in PS2, and 96 Ma (95% HPD range 67–128 Ma) in PS1. Similar tendencies are also found in other estimated dating points in Fig 4.

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Fig 4. Comparisons of BEAST results among different partitioning strategies.

(a): harmonic means; (b): estimated age at node 37; (c): estimated age at node 39; (d): estimated age at node 40.

https://doi.org/10.1371/journal.pone.0140933.g004

Discussion

Phylogenetic relationships

The monophyly of the large genus Papilio sensu lato, which comprises four major lineages, has been reported by Zakharov et al. [14] and is not in dispute. Our results are congruent with that study, but add more details for the Pterourus-clade. The most noteworthy finding is that the two Old World subgenera, Chilasa and Agehana (the elwesi-group), are both sister groups to the New World subgenus Pterourus, but that the placement of the elwesi-group causes the fission of Pterourus (Fig 2). This highly supported outcome suggests that the commonly used genus-group name, Agehana, should be synonymized with Pterourus. Another possible treatment, however, is to combine Agehana and Pterourus Group B within the subgenus Pyrrhosticta Butler, 1872 and to restrict the subgenus Pterourus to Pterourus Group A (Fig 2). We currently favor the former outcome as less disruptive to current subgeneric nomenclature, and we go as far as to propose a formal synonymy that can be tested with future data. Note that only about half of the American Pterourus species have been sampled. Papilio zagreus, for example, has been considered to represent another species-group [11]. This lineage should be added to clarify the phylogenetic relationships within the subgenus Pterourus and to confirm whether our radical proposal here that Papilio (Pterourus) should encompass both the Americas and South-East Asia and that subgenus Agehana be sunk and referred to in future as the Papilio (Pterourus) elwesi-species group, is borne out. Here, we treat the Pterourus-clade as comprising two reciprocal monophyletic subgenera (Pterourus and Chilasa), and delineate several species-groups for further classification (Table 4). Moreover, although previous morphological studies which attempted to subdivide Papilio sensu lato seem inconclusive [1113], we notice that the elwesi-species group has strikingly similar larval stages to American Pterourus Group B [55, 56], supporting our nomenclatural proposal. It seems unlikely that such similarity would have arrived by mimetic convergence in different biogeographic regions, due to different sets of predators, and an alternative scenario is that the generalist adaptive qualities (e.g. snake mimicry) of a common ancestor were sufficiently repellent to predators to have been retained. Especially within the P. homerus-species group (Table 4), many species have double eye-spots on the prothorax and an “X”-shaped marking on the dorsal abdomen with blue spots (S2 Fig). In addition, the elwesi-group and their relatives have unusual hostplant associations (Lauraceae and Magnoliaceae) different from other Papilio swallowtails, which principally feed on Rutaceae [24, 25].

Historical biogeography of the Pterourus-clade

Our phylogeny of the Pterourus-clade illuminates biogeographic events between East Asia and America. A previous study hypothesized that two Old World lineages of this clade, Chilasa and Alexanoria, diverged from their New World relatives (Pterourus) around 24 Ma [21], and that their current disjunct distribution is a result of dispersal through the Bering land-bridge (BLB), following climate cooling events. Our results support this scenario, but we find that ensuing warming periods also provide gateways [57] that allowed the common ancestor of the elwesi-species group to disperse intercontinentally. In our case, we infer the divergence and diversification of the ancestor of the elwesi-species group from its sister, the Pterourus Group B (Fig 2), to have started around 18 Ma (Fig 3), a date that coincides with the early Miocene climatic optimum. During this period, deciduous and evergreen mixed forest reached relatively high paleolatitudes [57], and zoofaunal exchange became possible via BLB [58]. Our results are consistent with a dispersal of the elwesi-group ancestor to Eurasia through BLB. The ensuing global-cooling event [59] would have reduced and fragmented the butterflies’ ranges, accounting for their current relict East Asia-America distribution. This novel phylogenetic relationship showing the P. elwesi-group to be internal to Pterourus, contradicts the assertion that Pterourus butterflies only became isolated and diversified in Nearctic regions [21].

In contrast to the elwesi-species group, the diversification of Chilasa happened earlier, as we infer around 23 Ma (Fig 3 and S4 Table). The biogeographic scenario for Chilasa is a dispersal event from an ancestor among their American relatives during the Oligocene/Miocene transition, a period of warming (i.e. the Late Oligocene Climatic Optimum). This result is concordant with the previous study [21]. The hypothesis that Chilasa was Gondwanan in origin and dispersed from Australia to Southeast and India [11, 26] is clearly refuted by our dating results as well as previous dating estimates for Papilionidae [4, 21]. Instead, our Bayes-DIVA analysis allows us to infer a directional tendency of the diversification from East or Southeast Asia to Australian regions.

The diversification of American Pterourus dates back to around 21 Ma (Fig 3) from our analysis, by which time the island arc of proto-Central America had formed [60], followed by the “Great American Biotic Interchange” [61, 62]. Our results show that the Pterourus group formerly supposed to be endemic to the Americas comprises at least two monophyletic subunits (Fig 2). The diversification of Group A (14–22 Ma) shows a slight northward direction (Fig 3), and one lineage of group B (P. multicaudata, P. rutulus, P. canadensis, and P. glaucus) shows a pattern of diversification northward to North America (A). However, our sampling being incomplete for American taxa, we interpret these inferred directions and times of diversification with caution.

Hostplant associations

Many Pterourus clade members (e.g. P. glaucus, and P. scamander) are moderately polyphagous butterflies as for the elwesi-group [24, 55, 63, 64]. The major hostplants for these Asian Pterourus butterflies are Sassafras and Liriodendron, and recently the immatures of P. elwesi were found on Magnolia officinalis (Magnoliaceae) [15]. Interesting, these hostplants all show a similar disjunct distribution between East Asia and North America [23]. Most recent dating studies reveal splits in two of these plant genera estimated at around 14 Ma for Sassafras and Liriodendron [65, 66], and around 18.5 Ma for Magnolia [66]. Interestingly, this dating estimate is very close to the divergence between the P. elwesi-group and its American relatives Group B in the early Miocene (18 Ma). Therefore, based on currently known hostplant records, and from our phylogenetic topologies, the current hostplant relationships of the Pterourus-clade suggest that their most recent common ancestor was also polyphagous, and also that the ancestor of the elwesi-species group might have had a broader host repertoire in the past, even though the two descendant species are quite narrowly specialized.

Species within the East Asia-America disjunct distribution

Geology and climate change are evidently two of the most important factors promoting plant diversification and intercontinental exchange. Plants seem to be among the best model organisms for studying biogeographic disjunction between East Asia and North America [23], but an increasing number of zoofaunal examples point to common patterns of intercontinental disjunction and underlying historical biogeography, and are also important for unraveling the interplay between regional biodiversity and evolutionary processes [4, 58]. Currently, two phytophagous insect groups, aphids [67] and leaf beetles [68] seem to show a congruent biogeographic pattern with their hosts, emphasizing the significance of host distribution for diversification of specialized phytophagous insects. In our case study, the phylogenetic relationships and asymmetric distribution of Pterourus butterflies reveals the importance of ancient dispersal processes affecting butterfly composition in East Asia. Different climate warming periods are likely to have permitted exchanges of butterflies between East Asia and America. Most of those cases suggest diversification in Asia and dispersal of a few members to America [69, 70]. The classic documented case until now is the dispersal to the New World of Polyommatus butterflies no less than five separate times during the Miocene-Pleistocene [69]. So far only a few cases like our study and that of the satyrid Palaeonympha opalina [71] reveal clearly ancient dispersal events in the Asia-wards direction during the Oligocene to Miocene climatic optimum, whereas Asian-American riodinids show a striking intercontinental dispersal case that began as a diversification in the Neotropics, with a dispersal to Asia (~74 Ma) and a back dispersal to the Neotropics in late Eocene [72], In general, data for butterflies are still too few to suggest any clear trend in the past directionality of biotic exchange.

Conclusions

Historical biogeographic analysis in the Pterourus-clade butterflies highlights the phenomenon of intercontinental exchange of tropical or subtropical taxa during paleoclimatic warming periods. Our study shows that the current distribution of the P. elwesi-group (now Asian representatives of Pterourus) represents a case of intercontinental dispersal from America. From a taxonomic viewpoint, we suggest that the genus-group name Agehana should be synonymized with Pterourus based on strong molecular support for monophyly and in accordance with larval morphology. This new arrangement communicates well their intriguing biogeographic history.

Supporting Information

S1 Fig. The most parsimonious topology.

Values at nodes are bootstrap values.

https://doi.org/10.1371/journal.pone.0140933.s001

(EPS)

S2 Fig. The larval appearances of P. maraho (the elwesi-species group) and P. garamas (the P. homerus-species group).

https://doi.org/10.1371/journal.pone.0140933.s002

(TIF)

S1 File. Associated alignment datasets and tree files used in this study.

These comprise the 42-dataset and the 87-dataset mentioned in the text and eight tree files which were generated from PS1-PS6 and best-fit.

https://doi.org/10.1371/journal.pone.0140933.s003

(RAR)

S2 File. Convergence output of seven PS datasets.

https://doi.org/10.1371/journal.pone.0140933.s004

(PDF)

S3 File. Bayesian and Maximum Likelihood trees based on PS1-6.

Values at nodes correspond to posterior probabilities or ML bootstrap.

https://doi.org/10.1371/journal.pone.0140933.s005

(PDF)

S1 Table. Species list used in this study.

GenBank accession numbers of each gene are listed.

https://doi.org/10.1371/journal.pone.0140933.s006

(XLSX)

S2 Table. Substitution model of each partition.

The models were inferred by jModelTest 2 and judged by AICc using a corrected version for small samples.

https://doi.org/10.1371/journal.pone.0140933.s007

(XLSX)

S3 Table. Substitution models of best-fit PS.

The best-fit partitions and models were inferred by PartitionFinder using the AICc criterion.

https://doi.org/10.1371/journal.pone.0140933.s008

(XLSX)

S4 Table. Divergence times (Ma) with their 95% HPD intervals at nodes of Fig 3.

https://doi.org/10.1371/journal.pone.0140933.s009

(XLSX)

S5 Table. The possible ancestral areas inferred by Bayes-DIVA at nodes of Fig 3.

“*”: uncertainty fraction

https://doi.org/10.1371/journal.pone.0140933.s010

(XLSX)

Acknowledgments

We thank Mr. S.-M. Wang (Taiwan Forestry Bureau, Council of Agriculture (COA), Taipei, Taiwan) for issuing collecting permits for the Agehana maraho. Ms. P. Yang (Chongqing Station of Pests Control and Quarantine, Chongqing, China), and Mr. Z. Qian (Institute of Agricultural Sciences of Lishui, Lishui, China) assisted with field work. Ms. T.-W. Chen (National Taiwan Normal University, Taipei, Taiwan) dealt with some molecular work, Ms. H.-C. Cheng drew the beautiful larval pictures, and Mr. J.-R. Chen provide excellent photos of Papilio immatures.

Author Contributions

Conceived and designed the experiments: L-WW S-HY DCL Y-FH. Performed the experiments: L-WW C-CL Y-FH. Analyzed the data: L-WW. Contributed reagents/materials/analysis tools: L-WW S-HY C-CL P-SY Y-FH. Wrote the paper: L-WW DCL Y-FH. Obtained collection permit: C-CL Y-FH.

References

  1. 1. Mutanen M, Wahlberg N, Kaila L. Comprehensive gene and taxon coverage elucidates radiation patterns in moths and butterflies. Proc R Soc B. 2010;277(1695):2839–48. pmid:20444718
  2. 2. Heikkilä M, Kaila L, Mutanen M, Peña C, Wahlberg N. Cretaceous origin and repeated tertiary diversification of the redefined butterflies. Proc R Soc B. 2012;279(1731):1093–9. pmid:21920981
  3. 3. Kawahara AY, Breinholt JW. Phylogenomics provides strong evidence for relationships of butterflies and moths. Proc R Soc B. 2014;281(1788):20140970. pmid:24966318
  4. 4. Condamine FL, Sperling FA, Wahlberg N, Rasplus JY, Kergoat GJ. What causes latitudinal gradients in species diversity? Evolutionary processes and ecological constraints on swallowtail biodiversity. Ecol Lett. 2012;15(3):267–77. pmid:22251895
  5. 5. Condamine FL, Toussaint EF, Cotton AM, Genson GS, Sperling FA, Kergoat GJ. Fine‐scale biogeographical and temporal diversification processes of peacock swallowtails (Papilio subgenus Achillides) in the Indo‐Australian Archipelago. Cladistics. 2013;29(1):88–111.
  6. 6. Caterino MS, Sperling FAH. Papilio phylogeny based on mitochondrial cytochrome oxidase I and II genes. Mol Phylogenet Evol. 1999;11(1):122–37. pmid:10082616
  7. 7. Braby MF, Trueman JWH, Eastwood R. When and where did troidine butterflies (Lepidoptera: Papilionidae) evolve? Phylogenetic and biogeographic evidence suggests an origin in remnant Gondwana in the Late Cretaceous. Invertebr Syst. 2005;19(2):113–43.
  8. 8. Wahlberg N, Braby MF, Brower AV, de Jong R, Lee MM, Nylin S, et al. Synergistic effects of combining morphological and molecular data in resolving the phylogeny of butterflies and skippers. Proc R Soc B. 2005;272(1572):1577–86. pmid:16048773
  9. 9. Nazari V, Zakharov EV, Sperling FA. Phylogeny, historical biogeography, and taxonomic ranking of Parnassiinae (Lepidoptera, Papilionidae) based on morphology and seven genes. Mol Phylogenet Evol. 2007;42(1):131–56. pmid:16919972
  10. 10. Simonsen TJ, Zakharov EV, Djernaes M, Cotton AM, Vane‐Wright R, Sperling FAH. Phylogenetics and divergence times of Papilioninae (Lepidoptera) with special reference to the enigmatic genera Teinopalpus and Meandrusa. Cladistics. 2010;27(2):113–37.
  11. 11. Hancock DL. Classification of the Papilionidae (Lepidoptera): a phylogenetic approach. Smithersia. 1983;2:1–48.
  12. 12. Miller JS. Phylogenetic studies in the Papilioninae (Lepidoptera, Papilionidae). Bull Am Mus Nat Hist. 1987;186:365–512.
  13. 13. Igarashi S. The classification of the Papilionidae mainly based on the morphology of their immature stage. Tyô to Ga. 1984;34:41–96.
  14. 14. Zakharov EV, Caterino MS, Sperling FA. Molecular phylogeny, historical biogeography, and divergence time estimates for swallowtail butterflies of the genus Papilio (Lepidoptera: Papilionidae). Syst Biol. 2004;53(2):193–215. pmid:15205049
  15. 15. Lu CC, Wu LW, Jiang GF, Deng HL, Wang LH, Yang PS, et al. Systematic status of Agehana elwesi f. cavaleriei based on morphological and molecular evidence. Zool Stud. 2009;48(2):270–9.
  16. 16. Collins NM, Morris MG. Threatened swallowtail butterflies of the world: the IUCN Red Data Book: IUCN; 1985.
  17. 17. Yen S-H, Yang PS. Illustrated identification guide to insects protected by the CITES and Wildlife Conservation Law of Taiwan. Taipei, Taiwan: Council of Agriculture, Executive Yuan; 2001.
  18. 18. Lu C-C, Pan FJ. Sassafras randaiense. IUCN 2011 IUCN Red List of Threatened Species. 1998 [cited 2015 May 5]. Available from: http://www.iucnredlist.org.
  19. 19. Häuser C, de Jong R, Lamas G, Robbins R, Smith C, Vane-Wright R. Papilionidae–revised GloBIS/GART species checklist (2nd draft). 2005 [cited 2015 May 5]. Available from: http://www.insects-online.de/frames/papilio.htm.
  20. 20. Wang LH. Study on ecological requirements and behaviors of Agehana maraho [Master]: National Taiwan Normal University; 2008.
  21. 21. Condamine FL, Sperling FAH, Kergoat GJ, Riddle B. Global biogeographical pattern of swallowtail diversification demonstrates alternative colonization routes in the Northern and Southern hemispheres. J Biogeogr. 2013;40:9–23.
  22. 22. Tsukada E, Nishiyama Y. Butterflies of the South East Asian Islands. Vol. 1 Papilionidae. Plapac Co., Tokyo.1982.
  23. 23. Wen J. Evolution of eastern Asian and eastern North American disjunct distributions in flowering plants. Annu Rev Ecol Syst. 1999;30:421–55.
  24. 24. Scott JA. The butterflies of North America. A natural history and field guide. Stanford, California: Stanford University Press; 1986.
  25. 25. Robinson GS, Ackery PR, Kitching IJ, Beccaloni GW, Hernández LM. HOSTS―a Database of the World’s Lepidopteran Hostplants 2010 [cited 2015 May 5]. Available from: http://www.nhm.ac.uk/hosts.
  26. 26. Hancock D. Relationships of the swallowtail 'genera' Agehana Matsumura, Chilasa Moore and Eleppone Hancock (Lepidoptera: Papilionidae). Aust Entomol. 2009;36(1):7–12.
  27. 27. Wahlberg N, Leneveu J, Kodandaramaiah U, Pena C, Nylin S, Freitas AV, et al. Nymphalid butterflies diversify following near demise at the Cretaceous/Tertiary boundary. Proc R Soc B. 2009;276(1677):4295–302. pmid:19793750
  28. 28. Smith AB. Rooting molecular trees: problems and strategies. Biol J Linn Soc. 1994;51(3):279–92.
  29. 29. Campbell DL, Brower AV, Pierce NE. Molecular evolution of the wingless gene and its implications for the phylogenetic placement of the butterfly family Riodinidae (Lepidoptera: Papilionoidea). Mol Biol Evol. 2000;17(5):684–96. pmid:10779529
  30. 30. Kandul NP, Lukhtanov VA, Dantchenko AV, Coleman JW, Sekercioglu CH, Haig D, et al. Phylogeny of Agrodiaetus Hübner 1822 (Lepidoptera: Lycaenidae) inferred from mtDNA sequences of COI and COII and nuclear sequences of EF1-α: karyotype diversification and species radiation. Syst Biol. 2004;53(2):278–98. pmid:15205053
  31. 31. Wu L-W, Lees DC, Yen S-H, Hsu Y-F. The complete mitochondrial genome of the near-threatened swallowtail, Agehana maraho (Lepidoptera: Papilionidae): evaluating sequence variability and suitable markers for conservation genetic studies. Entomol News. 2010;121(3):267–80.
  32. 32. Tamura K, Peterson D, Peterson N, Stecher G, Nei M, Kumar S. MEGA5: molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods. Mol Biol Evol. 2011;28(10):2731–9. pmid:21546353
  33. 33. Deng W, Maust BS, Nickle DC, Learn GH, Liu Y, Heath L, et al. DIVEIN: a web server to analyze phylogenies, sequence divergence, diversity, and informative sites. BioTechniques. 2010;48(5):405. pmid:20569214
  34. 34. Swofford DL. PAUP*: Phylogenetic analysis using parsimony (*and other methods). Version 4. Sunderland, Massachusetts: Sinauer Associates; 2003.
  35. 35. Ronquist F, Teslenko M, van der Mark P, Ayres DL, Darling A, Höhna S, et al. MrBayes 3.2: efficient Bayesian phylogenetic inference and model choice across a large model space. Syst Biol. 2012;61(3):539–42. pmid:22357727
  36. 36. Stamatakis A. RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models. Bioinformatics. 2006;22(21):2688–90. pmid:16928733
  37. 37. Ott M, Zola J, Stamatakis A, Aluru S, editors. Large-scale maximum likelihood-based phylogenetic analysis on the IBM BlueGene/L. Proceedings of the 2007 ACM/IEEE conference on Supercomputing; 2007: Reno, Nevada: ACM.
  38. 38. Brown JM, Lemmon AR. The importance of data partitioning and the utility of Bayes factors in Bayesian phylogenetics. Syst Biol. 2007;56(4):643–55. pmid:17661232
  39. 39. Nylander JA, Olsson U, Alstrom P, Sanmartin I. Accounting for phylogenetic uncertainty in biogeography: a Bayesian approach to dispersal-vicariance analysis of the thrushes (Aves: Turdus). Syst Biol. 2008;57(2):257–68. pmid:18425716
  40. 40. Darriba D, Taboada GL, Doallo R, Posada D. jModelTest 2: more models, new heuristics and parallel computing. Nat Meth. 2012;9(8):772.
  41. 41. Lanfear R, Calcott B, Ho SY, Guindon S. PartitionFinder: combined selection of partitioning schemes and substitution models for phylogenetic analyses. Mol Biol Evol. 2012;29(6):1695–701. pmid:22319168
  42. 42. Kass RE, Raftery AE. Bayes factors. J Am stat Assoc. 1995;90(430):773–95.
  43. 43. Wu L-W, Lin L-H, Lees DC, Hsu Y-F. Mitogenomic sequences effectively recover relationships within brush-footed butterflies (Lepidoptera: Nymphalidae). BMC Genomics. 2014;15(1):468.
  44. 44. Rambaut A, Suchard MA, Drummond AJ. Tracer v1.6 2014 [cited 2015 Aug 5]. Available from: http://tree.bio.ed.ac.uk/software/tracer/.
  45. 45. Nylander JA, Wilgenbusch JC, Warren DL, Swofford DL. AWTY (are we there yet?): a system for graphical exploration of MCMC convergence in Bayesian phylogenetics. Bioinformatics. 2008;24(4):581–3. pmid:17766271
  46. 46. Drummond AJ, Rambaut A. BEAST: Bayesian evolutionary analysis by sampling trees. BMC Evol Biol. 2007;7(1):214.
  47. 47. Ho SY, Phillips MJ. Accounting for calibration uncertainty in phylogenetic estimation of evolutionary divergence times. Syst Biol. 2009;58(3):367–80. pmid:20525591
  48. 48. Durden CJ, Rose H. Butterflies from the middle Eocene: the earliest occurrence of fossil Papilionoidea (Lepidoptera): Texas Memorial Museum; 1978.
  49. 49. Evanoff E, McIntosh WC, Murphey PC. Stratigraphic summary and 40Ar/39Ar geochronology of the Florissant Formation, Colorado. Evanoff E, Gregory-Wodzicki KM, Johnson KR, editors. Denver, Colorado: Denver Museum of Nature and Science; 2001. 1–16 p.
  50. 50. Emmel TC. Florissant butterflies: a guide to the fossil and present-day species of central Colorado: Stanford University Press; 1992.
  51. 51. Bell CD, Soltis DE, Soltis PS. The age and diversification of the angiosperms re-revisited. Am J Bot. 2010;97(8):1296–303. pmid:21616882
  52. 52. Ronquist F. Dispersal-vicariance analysis: a new approach to the quantification of historical biogeography. Syst Biol. 1997;46(1):195–203.
  53. 53. Holt BG, Lessard J-P, Borregaard MK, Fritz SA, Araújo MB, Dimitrov D, et al. An update of Wallace’s zoogeographic regions of the world. Science. 2013;339(6115):74–8. pmid:23258408
  54. 54. Yu Y, Harris AJ, He XJ. RASP (Reconstruct Ancestral State in Phylogenies): a tool for historical biogeography. Molecular Phylogeentics and Evolution. 2015;87:46–9.
  55. 55. Warren A, Davis K, Grishin N, Pelham J, Stangeland E. Interactive listing of American butterflies 2012 [cited 2015 Aug 5]. Available from: http://www.butterfliesofamerica.com.
  56. 56. Tyler HA, Brown KS, Wilson KH. Swallowtail butterflies of the Americas: a study in biological dynamics, ecological diversity, biosystematics, and conservation: Scientific Publishers; 1994.
  57. 57. Wolfe JA. Distribution of major vegetational types during the Tertiary. Sundquist ET, Broecker WS, editors. Washington, D. C.: American Geophysical Union; 1985. 357–75 p.
  58. 58. Sanmartín I. Patterns of animal dispersal, vicariance and diversification in the Holarctic. Biol J Linn Soc. 2001;73(4):345–90.
  59. 59. Miao Y, Herrmann M, Wu F, Yan X, Yang S. What controlled Mid–Late Miocene long-term aridification in Central Asia?—Global cooling or Tibetan Plateau uplift: A review. Earth-Science Reviews. 2012;112(3):155–72.
  60. 60. Pindell JL, Cande S, Pitman WC III, Rowley DB, Dewey JF, LaBrecque J, et al. A plate-kinematic framework for models of Caribbean evolution. Tectonophysics. 1988;155(1):121–38.
  61. 61. Marshall LG, Webb SD, Sepkoski JJ, Raup DM. Mammalian evolution and the great American interchange. Science. 1982;215(4538):1351–7. pmid:17753000
  62. 62. Coney PJ. Plate tectonic constraints on the biogeography of Middle America and the Caribbean region. Ann Mo Bot Gard. 1982;69:432–43.
  63. 63. Robinson GS, Ackery PR, Kitching I, Beccaloni G, Hernández L. Hostplants of the moth and butterfly caterpillars of the Oriental Region: Natural History Museum; 2001.
  64. 64. Robinson GS. Hostplants of the moth and butterfly caterpillars of America north of Mexico: American Entomological Institute; 2002.
  65. 65. Nie ZL, Wen J, Sun H. Phylogeny and biogeography of Sassafras (Lauraceae) disjunct between eastern Asia and eastern North America. Plant Syst Evol. 2007;267(1–4):191–203.
  66. 66. Nie ZL, Wen J, Azuma H, Qiu YL, Sun H, Meng Y, et al. Phylogenetic and biogeographic complexity of Magnoliaceae in the Northern Hemisphere inferred from three nuclear data sets. Mol Phylogenet Evol. 2008;48(3):1027–40. pmid:18619549
  67. 67. von Dohlen CD, Kurosu U, Aoki S. Phylogenetics and evolution of the eastern Asian–eastern North American disjunct aphid tribe, Hormaphidini (Hemiptera: Aphididae). Mol Phylogenet Evol. 2002;23(2):257–67. pmid:12069555
  68. 68. Sota T, Bocak L, Hayashi M. Molecular phylogeny and historical biogeography of the Holarctic wetland leaf beetle of the genus Plateumaris. Mol Phylogenet Evol. 2008;46(1):183–92. pmid:18054254
  69. 69. Vila R, Bell CD, Macniven R, Goldman-Huertas B, Ree RH, Marshall CR, et al. Phylogeny and palaeoecology of Polyommatus blue butterflies show Beringia was a climate-regulated gateway to the New World. Proc R Soc B. 2011;278(1719):2737–44. pmid:21270033
  70. 70. Mullen SP. Wing pattern evolution and the origins of mimicry among North American admiral butterflies (Nymphalidae: Limenitis). Mol Phylogenet Evol. 2006;39(3):747–58. pmid:16500119
  71. 71. Peña C, Nylin S, Freitas AVL, Wahlberg N. Biogeographic history of the butterfly subtribe Euptychiina (Lepidoptera, Nymphalidae, Satyrinae). Zool Scr. 2010;39(3):243–58.
  72. 72. Espeland M, Hall JP, DeVries PJ, Lees DC, Cornwall M, Hsu Y-F, et al. Ancient Neotropical origin and recent recolonisation: Phylogeny, biogeography and diversification of the Riodinidae (Lepidoptera: Papilionoidea). Mol Phylogenet Evol. 2015;93:296–306. pmid:26265256