Pascaline Dumas
email: pascalinedumas@gmail.com

Jérôme Barbut

Bruno Le Ru

Jean-François Silvain

Anne- Laure Laure Clamens

Gael Emmanuelle D'alençon

Kergoat

Bruno Le Ru

Emmanuelle D'alençon

Gael J Kergoat

Phylogenetic molecular species delimitations unravel potential new species in the pest genus Spodoptera Guenée, 1852 (Lepidoptera, Noctuidae)

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Though millions of species remain to be discovered and described [START_REF] Wilson | Taxonomy as a fundamental discipline[END_REF][START_REF] Joppa | Biodiversity hotspots house most undiscovered plant species[END_REF][START_REF] Mora | How many species are there on Earth and in the ocean?[END_REF][START_REF] Scheffers | What we know and don't know about Earth's missing biodiversity[END_REF], the discipline of finding, describing and naming species-Taxonomy-currently faces an important deficit in term of funding and manpower [START_REF] Godfray | Challenges for taxonomy[END_REF]. This 'taxonomy crisis' is a major issue because the speed at which species are being lost is much faster than the required time to find, describe and potentially protect them [START_REF] Mace | The role of taxonomy in species conservation[END_REF][START_REF] Padial | Integrative taxonomy reveals cryptic Amazonian species of Pristimantis (Anura: Strabomantidae)[END_REF]. The problem is also aggravated by the fact that traditional morphological studies are usually extremely time consuming, especially when dealing with hyper diverse groups such as insects or plants, or when assessing species complexes with superficially indistinguishable morphological attributes [START_REF] Bond | Cryptic speciation in the Anadenobolus excisus millipede species complex on the island of Jamaica[END_REF][START_REF] Collin | The utility of morphological characters in gastropod phylogenetics: an example from the Calyptraeidae[END_REF][START_REF] Álvarez | Sibling species of bean bruchids: a morphological and phylogenetic study of Acanthoscelides obtectus Say and Acanthoscelides obvelatus Bridwell[END_REF][START_REF] Huber | Speciation without changes in genital shape: a case study on Brazilian pholcid spiders (Araneae: Pholcidae)[END_REF][START_REF] Kodandaramaiah | Investigating concordance among genetic data, subspecies circumscriptions and hostplant use in the Nymphalid butterfly Polygonia faunus[END_REF][START_REF] Kergoat | Assessing the phylogenetic usefulness of a previously neglected morphological structure through elliptic Fourier analyses: a case study in Bruchus seed-beetles (Coleoptera: Chrysomelidae: Bruchinae)[END_REF]. Our lack of knowledge is even more problematic when facing species complexes that threaten public health [START_REF] Gentile | Genetic differentiation in the African Malaria vector, Anopheles gambiae s.s., and the problem of taxonomic status[END_REF][START_REF] Pringle | Cryptic speciation in the cosmopolitan and clonal human pathogenic fungus Aspergillus fumigatus[END_REF] or target important crops [START_REF] Armstrong | DNA barcodes for biosecurity: invasive species identification[END_REF][START_REF] Roe | Population structure and species boundary delimitation of cryptic Dioryctria moths: an integrative approach[END_REF][START_REF] Ross | Species delimitation: a case study in a problematic ant taxon[END_REF][START_REF] Frey | Developing diagnostic SNP panels for the identification of true fruit flies (Diptera: Tephritidae) within the limits of COI-based species delimitation[END_REF]. In this context, some hopes came from the use of molecular data in studies on taxonomy and systematics. Thanks to the increased availability of molecular data over the last decades, DNA-based taxonomy has been proposed as an elegant and effective solution to speed up species identifications and discoveries [START_REF] Blaxter | The promise of a DNA taxonomy[END_REF][START_REF] Dincă | Complete DNA barcode reference library for a country's butterfly fauna reveals high performance for temperate Europe[END_REF][START_REF] Hebert | The promise of DNA barcoding for taxonomy[END_REF][START_REF] Hebert | Barcoding animal life: cytochrome c oxidase subunit 1 divergences among closely related species[END_REF][START_REF] Hebert | Ten species in one: DNA barcoding reveals cryptic species in the neotropical skipper butterfly Astraptes fulgerator[END_REF][START_REF] Hebert | Identification of birds through DNA barcodes[END_REF][START_REF] Janzen | Integration of DNA barcoding into an ongoing inventory of complex tropical biodiversity[END_REF][START_REF] Prado | Beyond the colours: discovering hidden diversity in the Nymphalidae of the Yucatan peninsula in Mexico through DNA barcoding[END_REF]. However, this initiative was quickly criticized on both practical [START_REF] Will | The perils of DNA barcoding and the need for integrative taxonomy[END_REF][START_REF] Gompert | Identifying units for conservation using molecular systematics: the cautionary tale of the Karner blue butterfly[END_REF][START_REF] Meier | DNA barcoding and taxonomy in Diptera: a tale of high intraspecific variability and low identification success[END_REF][START_REF] Wiemers | Does the DNA barcoding gap exist?-a case study in blue butterflies (Lepidoptera: Lycaenidae)[END_REF][START_REF] Whitworth | DNA barcoding cannot reliably identify species of the blowfly genus Protocalliphora (Diptera: Calliphoridae)[END_REF] and theoretical [START_REF] Moritz | DNA barcoding: promise and pitfalls[END_REF][START_REF] Meyer | DNA barcoding: error rates based on comprehensive sampling[END_REF][START_REF] Hickerson | DNA barcoding will often fail to discover new animal species over broad parameter space[END_REF][START_REF] Lohse | Can mtDNA barcodes be used to delimit species? A response to Pons et al[END_REF][START_REF] Galtier | Mitochondrial DNA as a marker of molecular diversity: a reappraisal[END_REF][START_REF] Hendrich | Mitochondrial Cox1 sequence data reliably uncover patterns of insect diversity but suffer from high lineage-idiosyncratic error rates[END_REF][START_REF] Van Velzen | DNA barcoding of recently diverged species: relative performance of matching methods[END_REF] grounds, with numerous studies underlining the fact that molecular data alone (especially molecular barcodes) cannot solve the current taxonomic crisis [START_REF] Will | Myth of the molecule: DNA barcodes for species cannot replace morphology for identification and classification[END_REF][START_REF] Ebach | DNA barcoding is no substitute for taxonomy[END_REF][START_REF] Rubinoff | A genomic perspective on the shortcomings of mitochondrial DNA for "barcoding" identification[END_REF][START_REF] Dupuis | Multi-locus species delimitation in closely related animals and fungi: one marker is not enough[END_REF]. The general consensus that emerged from these debates was that faster and more accurate species identifications or delimitations can be achieved through the use of multiple complementary sources of information (e.g. behavioural, ecological, molecular, morphological) [START_REF] Roe | Population structure and species boundary delimitation of cryptic Dioryctria moths: an integrative approach[END_REF][START_REF] Padial | The integrative future of taxonomy[END_REF][START_REF] Gebiola | Integration of molecular, ecological, morphological and endosymbiont data for species delimitation within the Pnigalio soemius complex (Hymenoptera: Eulophidae)[END_REF], hence underlining the need for a more 'integrative' [START_REF] Dayrat | Towards integrative taxonomy[END_REF][START_REF] Schlick-Steiner | Integrative taxonomy: a multisource approach to exploring biodiversity[END_REF] or 'iterative' taxonomy [START_REF] Yeates | Integrative taxonomy, or iterative taxonomy?[END_REF].

Because of their ever-increasing accessibility and decreasing cost, it is no wonder that molecular data are now routinely incorporated into taxonomy studies [START_REF] Padial | Integrative taxonomy reveals cryptic Amazonian species of Pristimantis (Anura: Strabomantidae)[END_REF][START_REF] Roe | Population structure and species boundary delimitation of cryptic Dioryctria moths: an integrative approach[END_REF][START_REF] Gebiola | Integration of molecular, ecological, morphological and endosymbiont data for species delimitation within the Pnigalio soemius complex (Hymenoptera: Eulophidae)[END_REF][START_REF] Ru | Integrative taxonomy of Acrapex stem borers (Lepidoptera, Noctuidae, Apameini): combining morphology and Poisson tree process analyses[END_REF][START_REF] Lumley | Integrating morphology and mitochondrial DNA for species delimitation within the spruce budworm (Choristoneura fumiferana) cryptic species complex (Lepidoptera: Tortricidae)[END_REF][START_REF] Melville | The role of integrative taxonomy in the conservation management of cryptic species: the taxonomic status of endangered earless dragons (Agamidae: Tympanocryptis) in the grasslands of Queensland, Australia[END_REF][START_REF] Rougerie | Morphology and molecules reveal unexpected cryptic diversity in the enigmatic genus Sinobirma Bryk, 1944 (Lepidoptera: Saturniidae)[END_REF]. Of particular interest is the fact that multiple analytic procedures have been explicitly developed to delimit species boundaries using molecular data [START_REF] O'meara | Testing for different rates of continuous trait evolution using likelihood[END_REF][START_REF] Pons | Sequence-based species delimitation for the DNA taxonomy of undescribed insects[END_REF][START_REF] Yang | Bayesian species delimitation using multilocus sequence data[END_REF][START_REF] Ence | SpedeSTEM: a rapid and accurate method for species delimitation[END_REF][START_REF] Puillandre | ABGD, Automatic Barcode Gap Discovery for primary species delimitation[END_REF]. A first class of approaches-referred to as species discovery procedures-assigns samples to putative species clusters without a priori information [START_REF] Carstens | How to fail at species delimitation[END_REF]. A second class of approaches-referred to as species validation proceduresrequires an a priori assignation of samples to putative species clusters, which can be later validated [START_REF] Carstens | How to fail at species delimitation[END_REF]. Both species discovery and species validation approaches can rely on molecular phylogenies, which are increasingly used to help identifying or delimiting species [START_REF] Roe | Population structure and species boundary delimitation of cryptic Dioryctria moths: an integrative approach[END_REF][START_REF] Pons | Sequence-based species delimitation for the DNA taxonomy of undescribed insects[END_REF][START_REF] Yang | Bayesian species delimitation using multilocus sequence data[END_REF][START_REF] Ence | SpedeSTEM: a rapid and accurate method for species delimitation[END_REF][START_REF] Hamback | Bayesian species delimitation reveals generalist and specialist parasitic wasps on Galerucella beetles (Chrysomelidae): sorting by herbivore or plant host[END_REF][START_REF] Zhang | A general species delimitation method with applications to phylogenetic placements[END_REF]. All tree-based species delimitation methods usually rely on the 'phylogenetic species concept' (sensu De Queiroz [START_REF] Queiroz | Species concepts and species delimitation[END_REF]), within a coalescent framework [START_REF] Yang | Bayesian species delimitation using multilocus sequence data[END_REF][START_REF] Rannala | Bayes estimation of species divergence times and ancestral population sizes using DNA sequences from multiple loci[END_REF][START_REF] Knowles | Delimiting species without monophyletic gene trees[END_REF], whose central aim is to identify independently evolving lineages without gene flow, in which selection and drift operate, each representing a putative species [START_REF] Fujita | Coalescent-based species delimitation in an integrative taxonomy[END_REF]. Tree-based species delimitation methods can operate with single or multi locus data; the use of multi locus data is mandatory for species validation procedures and optional for species discovery approaches [START_REF] Carstens | How to fail at species delimitation[END_REF]. For species discovery procedures, the use of multi locus data is usually advocated because of its superior power to resolve complex evolutionary histories resulting from recent episodes of radiation, incomplete lineage sorting, gene introgression or species hybridization [START_REF] Carstens | How to fail at species delimitation[END_REF][START_REF] Dupuis | Multi-locus species delimitation in closely related animals and fungi: one marker is not enough[END_REF][START_REF] Funk | Species-level paraphyly and polyphyly: frequency, causes, and consequences, with insights from animal mitochondrial DNA[END_REF]. All these processes usually generate discordance between gene trees and species trees [START_REF] Hailer | Nuclear genomic sequences reveal that polar bears are an old and distinct bear lineage[END_REF], which can biases the inference of putative species clusters. Nonetheless, single locus data have been proved useful to provide robust inferences of evolutionary histories [START_REF] Avise | Phylogeography: retrospect and prospect[END_REF] and quick assessments of species boundaries and diversity [START_REF] Janzen | Integration of DNA barcoding into an ongoing inventory of complex tropical biodiversity[END_REF][START_REF] Barraclough | Inferring evolutionarily significant units of bacterial diversity from broad environmental surveys of single-locus data[END_REF][START_REF] Avise | Phylogeography: retrospect and prospect[END_REF][START_REF] Hebert | DNA barcodes for 1/1000 of the animal kingdom[END_REF][START_REF] Haussmann | DNA barcoding the geometrid fauna of Bavaria (Lepidoptera): successes, surprises, and questions[END_REF]. More recently they have been also associated with concise morphological descriptions to produce rapid descriptions of new species, an approach referred to as turbo-taxonomy [START_REF] Butcher | A turbo-taxonomic study of Thai Aleiodes (Aleiodes) and Aleiodes (Arcaleiodes) (Hymenoptera: Braconidae: Rogadinae) based largely on COI barcoded specimens, with rapid descriptions of 179 new species[END_REF][START_REF] Riedel | a) One hundred and one new species of Trigonopterus weevils from New Guinea[END_REF][START_REF] Riedel | Integrative taxonomy on the fast track-towards more sustainability in biodiversity research[END_REF]. Finally the use of single locus data also benefits from the fact that several genes (e.g. 16S ribosomal RNA) are well represented in large public databases such as GenBank (http://www.ncbi.nlm.nih.gov/genbank/) or the Barcode of Life Database (BOLD; http://www.boldsystems.org/; for the mitochondrial cytochrome c oxidase subunit I gene (COI)).

In this study, we explore the potential interest and efficiency of species discovery approaches to assess species status in moths belonging to the genus Spodoptera (Lepidoptera, Noctuidae). This genus encompasses 30 species [START_REF] Pogue | A world revision of the genus Spodoptera Guenée (Lepidoptera: Noctuidae)[END_REF], and includes several species whose status has been questioned in the past based on biological [START_REF] Lalanne-Cassou | Mécanismes d'isolement reproducteur chez les espèces du complexe Neotropical Spodoptera latifascia-S. cosmioides-S. descoinsi (Lepidoptera: Noctuidae)[END_REF][START_REF] Groot | Host strain specific sex pheromone variation in Spodoptera frugiperda[END_REF][START_REF] Schöfl | Time-shifted reproductive behaviours among fall armyworm (Noctuidae: Spodoptera frugiperda) host strains: evidence for differing modes of inheritance[END_REF], morphological [START_REF] Brown | The genus Spodoptera (Lepidoptera: Noctuidae) in Africa and the Near East[END_REF][START_REF] Todd | Keys and illustrations for the armyworm moths of the Noctuid genus Spodoptera Guenée from the western hemisphere[END_REF] and molecular evidence [START_REF] Silvain | Distinction entre Spodoptera latifascia (Walker) et Spodoptera cosmioides (Walker), bona species (Lepidoptera, Noctuidae)[END_REF][START_REF] Martinelli | Molecular variability of Spodoptera frugiperda (Lepidoptera: Noctuidae) populations associated to maize and cotton crops in Brazil[END_REF][START_REF] Salinas-Hernandez | Haplotype identification within Spodoptera frugiperda (J.E. Smith) (Lepidoptera: Noctuidae) corn and rice strains from Colombia[END_REF][START_REF] Kergoat | Disentangling dispersal, vicariance and adaptive radiation patterns: a case study using armyworms in the pest genus Spodoptera (Lepidoptera: Noctuidae)[END_REF]. Clarifying Spodoptera species boundaries is of prime importance because half of known Spodoptera species are pests of economic importance that target major crops such as beans, cotton, maize, millet, rice, sorghum, soybean or tomatoes [START_REF] Pogue | A world revision of the genus Spodoptera Guenée (Lepidoptera: Noctuidae)[END_REF][START_REF] Greenberg | Feeding and life history of Spodoptera exigua (Lepidoptera: Noctuidae) on different host plants[END_REF][START_REF] Barros | Development of Spodoptera frugiperda on different hosts and damage to reproductive structures in cotton[END_REF]. A particular focus will be made on the fall armyworm (FAW) Spodoptera frugiperda, whose identity is particularly debated [START_REF] Drès | Host races in plant-feeding insects and their importance in sympatric speciation[END_REF][START_REF] Prowell | Multilocus genetic analysis of host use, introgression, and speciation in host strains of fall armyworm (Lepidoptera: Noctuidae)[END_REF][START_REF] Bolnick | Sympatric speciation: models and empirical evidence[END_REF][START_REF] Juárez | Population structure of Spodoptera frugiperda maize and rice host forms in South America: are they host strains?[END_REF]. The fall armyworm is a widespread and well-known agricultural pest in the Western hemisphere [START_REF] Pogue | A world revision of the genus Spodoptera Guenée (Lepidoptera: Noctuidae)[END_REF][START_REF] Barros | Development of Spodoptera frugiperda on different hosts and damage to reproductive structures in cotton[END_REF]. It is an extremely polyphagous species, which is known to develop on about 100 different plants species from 27 plant families [START_REF] Pogue | A world revision of the genus Spodoptera Guenée (Lepidoptera: Noctuidae)[END_REF]. Several features of the biology and the ecology of fall armyworm indicate that this species is composed of two morphologically undistinguishable ecological races ('corn form' and 'rice form' sensu Juarez et al., [START_REF] Juárez | Population structure of Spodoptera frugiperda maize and rice host forms in South America: are they host strains?[END_REF]), with distinct host-preferences [START_REF] Pashley | Host-associated genetic differentiation in fall armyworm (Lepidoptera: Noctuidae): a sibling species complex?[END_REF][START_REF] Prowell | Multilocus genetic analysis of host use, introgression, and speciation in host strains of fall armyworm (Lepidoptera: Noctuidae)[END_REF][START_REF] Meagher | Oviposition choice of two fall armyworm (Lepidoptera: Noctuidae) host strains[END_REF]. The use of diagnostic molecular markers [START_REF] Lu | Distinguishing fall armyworm (Lepidoptera: Noctuidae) strains using a diagnostic mitochondrial DNA marker[END_REF][START_REF] Mcmichael | Differences in amplified fragment-length polymorphisms in fall armyworm (Lepidoptera: Noctuidae) host strains[END_REF][START_REF] Levy | Strain identification of Spodoptera frugiperda (Lepidoptera: Noctuidae) insects and cell line: pcr-RFLP of cytochrome oxidase C subunit I gene[END_REF][START_REF] Meagher | Identifying host strains of fall armyworm (Lepidoptera: Noctuidae) in Florida using mitochondrial markers[END_REF][START_REF] Nagoshi | Structure and distribution of a strain-biased tandem repeat element in fall armyworm (Lepidoptera: Noctuidae) populations in Florida, Texas, and Brazil[END_REF] have indicated that both strains are generally found in sympatry [START_REF] Pashley | Host-associated genetic differentiation in fall armyworm (Lepidoptera: Noctuidae): a sibling species complex?[END_REF][100][101], hence leading some authors to argue that they could constitute a potential example of ongoing or sympatric speciation [START_REF] Groot | Host strain specific sex pheromone variation in Spodoptera frugiperda[END_REF][START_REF] Drès | Host races in plant-feeding insects and their importance in sympatric speciation[END_REF]. Both strains also exhibit a high level of genetic differentiation [START_REF] Kergoat | Disentangling dispersal, vicariance and adaptive radiation patterns: a case study using armyworms in the pest genus Spodoptera (Lepidoptera: Noctuidae)[END_REF]. In addition to the case of S. frugiperda, we will also pay attention to five other Spodoptera species, whose species status is still disputed [START_REF] Todd | Keys and illustrations for the armyworm moths of the Noctuid genus Spodoptera Guenée from the western hemisphere[END_REF]. It is the case of S. marima and S. ornithogalli, which are morphologically related and possibly correspond to geographic races, as they have allopatric distributions and only differ by the absence of sexual dimorphism in S. marima males [START_REF] Pogue | A world revision of the genus Spodoptera Guenée (Lepidoptera: Noctuidae)[END_REF][START_REF] Todd | Keys and illustrations for the armyworm moths of the Noctuid genus Spodoptera Guenée from the western hemisphere[END_REF]. These two species were not found reciprocally monophyletic in a recent multilocus phylogenetic study [START_REF] Kergoat | Disentangling dispersal, vicariance and adaptive radiation patterns: a case study using armyworms in the pest genus Spodoptera (Lepidoptera: Noctuidae)[END_REF], so we expect additional clarifications with the molecular species delimitation procedures. Another species pair (S. cosmiodes and S. descoinsi) was also recovered paraphyletic with a strong support in the study of Kergoat et al., [START_REF] Kergoat | Disentangling dispersal, vicariance and adaptive radiation patterns: a case study using armyworms in the pest genus Spodoptera (Lepidoptera: Noctuidae)[END_REF], but similarly to the case of S. frugiperda, additional evidences (differences in pheromone blends, allochronism of females) led to think that these two entities could possibly constitute valid species [START_REF] Pogue | A world revision of the genus Spodoptera Guenée (Lepidoptera: Noctuidae)[END_REF][START_REF] Lalanne-Cassou | Mécanismes d'isolement reproducteur chez les espèces du complexe Neotropical Spodoptera latifascia-S. cosmioides-S. descoinsi (Lepidoptera: Noctuidae)[END_REF]. Finally, the last case that remains to be investigated is the status of Western populations (from East Africa, Mauritius, the Malagasy Republic, and the Reunion Island) and Eastern populations (from the Indomalayan and Australasian regions) of S. mauritia, which may constitute valid species of their own [START_REF] Brown | The genus Spodoptera (Lepidoptera: Noctuidae) in Africa and the Near East[END_REF]. Here we will explore Spodoptera species boundaries by using two different tree-based approaches that have drawn much attention in recent years [102-110]: the general mixed Yule-coalescent (GMYC) model [START_REF] Pons | Sequence-based species delimitation for the DNA taxonomy of undescribed insects[END_REF]108] and the Poisson-Tree-Processes (PTP) [START_REF] Zhang | A general species delimitation method with applications to phylogenetic placements[END_REF]. The GMYC model uses the distinct branching patterns between a Yule model (modelling interspecific speciation events) and a coalescent model (modelling expected coalescent times of genes at an intraspecific level) to distinguish between species and population processes. This model is fitted to an ultrametric tree (a tree where all the path-lengths from the root to the tips are equal) and optimized under maximum likelihood to find the threshold time (T), which corresponds to the transition between the two distinct branching patterns. It is possible to visualise this transition with a lineage-through-time plot, in which a sharp increase in branching rates is expected at T. Potential species clusters are then determined by identifying the clades (or single lineages) that originate after this putative threshold. The PTP is a recently developed method, which has the advantage of not requiring an ultrametric tree (inferring an ultrametric tree is usually a time-consuming and potentially error-prone process [103,110]); instead the PTP model uses branch lengths to estimate the mean expected number of substitutions per site between two branching events. The model assumes that each substitution has a small probability of generating a speciation event; hence the number of substitutions between species is expected to be significantly higher than those within species [START_REF] Zhang | A general species delimitation method with applications to phylogenetic placements[END_REF]. The model then implements two independent classes of Poisson processes (one describing speciation and the other describing within species branching events) and searches for transition points between interspecific and intraspecific branching patterns. Potential species clusters are then determined by identifying the clades (or single lineages) that originate after these transition points. Because both methods efficiently deal with large single-locus datasets [110], they can readily benefit from the mass of sequence data generated through the Barcode of Life (BoL) initiative or deposited on public database such as GenBank. Here we combine Spodoptera sequences generated from previous studies that are available on GenBank or BOLD with newly generated sequences for the COI gene. The resulting dataset will be used to: (i) infer putative species boundaries in the genus Spodoptera by applying species discovery methods particularly suitable to deal with large single-locus datasets; (ii) to test the reliability and the usefulness of these species discovery methods by comparing our results with other sources of information.

Material and Methods

Sampling design

The sampling for this study covers 27 of the 30 known Spodoptera species [START_REF] Pogue | A world revision of the genus Spodoptera Guenée (Lepidoptera: Noctuidae)[END_REF]. We were unable to acquire sequence data for three species: S. compta (Walker, 1869) (from Peru), S. malagasy Viette, 1967 (from Madagascar) and S. roseae (Schaus, 1923) (from the Galapagos Islands). Both S. compta and S. roseae are extremely rare in collections (especially S. compta which is only known from three specimens collected in the 19 th century). As for S. malagasy, previous sequencing attempts on several old museum specimens have been unsuccessful [START_REF] Kergoat | Disentangling dispersal, vicariance and adaptive radiation patterns: a case study using armyworms in the pest genus Spodoptera (Lepidoptera: Noctuidae)[END_REF]. For this study we generated 86 new sequences for specimens obtained from the Muséum National d'Histoire Naturelle in Paris (MNHN). In addition we used 118 sequences from the study of Kergoat et al., [START_REF] Kergoat | Disentangling dispersal, vicariance and adaptive radiation patterns: a case study using armyworms in the pest genus Spodoptera (Lepidoptera: Noctuidae)[END_REF], 463 additional sequences from GenBank and five sequences from BOLD. The resulting dataset encompasses 672 Spodoptera specimens, with a mean number of 24 individuals per species (from two individuals for S. apertura (Walker, 1865), S. pecten Guenée, 1852, S. pulchella (Herrich-Schäffer, 1868) and S. triturata (Walker, 1857) to 101 in S. frugiperda; S1 Table ). All specimens, their geographic origin and the corresponding sequence accession number are listed in a supplementary table (S1 Table ). For outgroup choice we used the results of the study of Mitchell et al.,[111] to select the following seven noctuid taxa: Agrotis ipsilon (Hufnagel, 1766) (Noctuinae), Helicoverpa armigera (Hübner, 1805) (Heliothinae), Heliothis virescens (Fabricius, 1777) (Heliothinae), Mythimna unipuncta (Haworth, 1809) (Hadeninae), Noctua atlantica (Warren, 1905) (Noctuinae), Psychomorpha epimenis (Drury, 1782) (Agaristinae), Sesamia inferens (Walker, 1856) (Xyleninae). Based on Mitchell et al., [111] all trees were rooted with Psychomorpha epimenis, which belongs to a clade that is sister to the clade including both Spodoptera spp. and the subfamilies Hadeninae, Heliothinae, Noctuinae and Xyleninae.

DNA extraction, Polymerase chain reactions and Sequencing

Total genomic DNA of new samples was extracted by grinding up hind legs using DNAeasy Blood and Tissue Kit (Qiagen). Partial fragments of the COI gene were amplified following Kergoat et al., [START_REF] Greenberg | Feeding and life history of Spodoptera exigua (Lepidoptera: Noctuidae) on different host plants[END_REF]. The polymerase chain reaction (PCR) mix (25 μL) consisted of 1xPCR buffer, 1.5mM MgCl2, 0.1mM of each desoxynucleotide triphosphates, 1μM of each primer, 1 unit of Taq DNA polymerase (Qiagen) and 2 μL (diluted to tenth) of extracted DNA and nucleasefree water to 25 μL. PCR cycling conditions were the following: initial denaturation step at 95°C for 3 min followed by 35 cycles including a denaturation step at 92°C for 1 min, an annealing step at 48°C for 1 min, and an elongation step at 72°C for 1 min and a final elongation step at 72°C for 10 min. The resulting PCR products were processed by Eurofins MWG Synthesis GmbH (Ebersberg, Germany). Both strands were sequenced for all specimens to minimize PCR artifacts and ambiguities.

Sequences of complementary strands were edited and reconciled using Geneious v5.1 software (available at: www.geneious.com/). The alignment of all sequences was carried out using MAFFT 7 [112] with default option settings. No gap was present in the corresponding alignment. We then used Mesquite v3.0 [113] to check the coding frame for possible errors or stop codons. Additional sequences generated for the study were deposited to GenBank under numbers KF854152 to KF854234. The final dataset encompasses 679 individuals and 658 aligned characters.

Gene tree inference

Phylogenetic analyses were conducted using Maximum likelihood (ML) and Bayesian inference (BI). For both methods we carried out partitioned analyses to improve phylogenetic accuracy [114]. Partitions and substitution models were determined using PartitionFinder v1. 1.1 [115]. The corrected Akaike information criterion (AICc; [116]) was used as a metric for ML analyses whereas the Bayesian information criterion (BIC) was used for BI analyses.

Maximum Likelihood analyses were performed using RAxML v8 [117]. Based on the AICc results (S2 Table ) we used only one partition with a General time reversible (GTR) model. Instead of using a standard GTR+G+I model we used the GTR CAT approximation model that accommodate searches incorporating rate heterogeneity with faster inference times and better maximum likelihood values [118]. The best ML tree was obtained using a heuristic search implementing 100 random-addition replicates. Clade support was then assessed using a nonparametric bootstrap procedure (1,000 replicates were used). Nodes supported by bootstrap values (BV) ! 70% were considered as strongly supported following Hillis and Bull [119].

Bayesian inference analyses were carried out using MrBayes 3.2.2 [120] and BEAST 1.8 [121]. Based on the BIC results (S2 Table ) we used three partitions. For MrBayes analyses, instead of using a specific model for each partition we used the mixed model option. The latter allows to sample across the substitution model space in the Bayesian Markov Chains Monte Carlo (MCMC) analysis itself, removing the need for a priori model testing [122]. We conducted two independent runs with four MCMC (one cold and three incrementally heated) that ran for 50 million generations, with trees sampled every 1,000 generations. A conservative burn-in of 25% was then applied after checking for stability on the log-likelihood curves and the split-frequencies of the runs under MrBayes (a threshold of 0.05 was used). For the BEAST analyses, we implemented the models selected by PartitionFinder (S2 Table ). Following Tang et al., [110] we also relied on distinct sets of models to infer trees with branch lengths proportional to time. To limit the size of parameter space the majority-rule consensus topology from MrBayes analyses was used as a guide tree. We alternatively used a strict clock model or an uncorrelated lognormal (UCLN) relaxed clock as clock priors, and a bird-death (BD) model as tree prior. The corresponding analyses were carried out using two independent runs of 50 million generations, with trees sampled every 1,000 generations. A conservative burn-in of 25% was then applied after checking for the effective sampling sizes (ESS) of parameters (a threshold of 200 was used). Support of nodes for both MrBayes and BEAST analyses was provided by clade posterior probabilities (PP) as directly estimated from the majority-rule consensus topology. Nodes supported by PP ! 0.95 were considered as strongly supported following Erixon et al., [123].

We followed the recommendations of Tang et al., [110], who advocated the use of model-based gene trees (generated with programs such as MrBayes or RAxML) for PTP analyses and the use of ultrametric trees generated with BEAST for the GMYC analyses. Poisson-Tree-Processes molecular species delimitations were conducted on the Web server of the Exelixis Lab (http:// species.h-its.org/ptp/), with default settings. The corresponding analyses were carried out using trees either the best tree from the ML analyses or the majority-rule consensus topology resulting from the BI analyses. To avoid biases that may arise if some of the outgroup taxa are too distantly related from ingroup taxa, outgroups were pruned before conducting the PTP analyses for both ML and BI trees. General mixed Yule-coalescent analyses were performed under R (R Development Core Team 2010) using the latest implementation of the GMYC procedure [108], which relies on the following packages: splits [124], APE [125] and apTreeshape [126]. All corresponding analyses were carried out using a single threshold with a confidence interval falling within 2 log-likelihood units of the ML solution [START_REF] Pons | Sequence-based species delimitation for the DNA taxonomy of undescribed insects[END_REF].

Results

Gene tree inference

The phylogenetic analyses in ML and BI show similar results (Fig 1 ; see also S1 and S2 Figs for details), which only differ by the position of some outgroups and the placement of two Spodoptera species (S. apertura and S. pecten). In both ML and BI analyses, the genus Spodoptera is recovered monophyletic. Support for Spodoptera monophyly was higher for the ML tree (BV of 95%) in comparison to the BI tree (PP of 0.94). The phylogenies are overall not resolved, except for the terminal nodes. Support values are equally high for the nodes leading to morphospecies (BV ! 70% for 23 out of the 27 corresponding nodes under ML; PP ! 0.95 for 21 out of the 27 corresponding nodes under BI).

Four of the 27 Spodoptera morphospecies (S. cosmiodes, S. descoinsi, S. marima and S. ornithogalli) are consistently recovered paraphyletic in all analyses. Out of the nine sampled S. descoinsi individuals (all from French Guiana), seven of them constitute a well-supported clade, sister to S. evanida Schaus, 1914 (specimens of S. evanida were collected in French Guiana and Peru). The two remaining specimens identified as S. descoinsi (voucher codes B19 and LSU30) are grouped in a moderately to highly supported clade (BV of 88%, PP of 0.87) that includes all sampled S. cosmiodes individuals (from Brazil and French Guiana). Regarding S. marima and S. ornithogalli, the four sampled specimens of S. marima (from French Guiana and Venezuela) are mixed with the 18 sampled specimens of S. ornithogalli (from Canada, Dominican Republic, Guatemala, French Guiana and USA) in a well-supported clade (BV of 100%, PP of 1.0).

Two distinct and well-supported clades were inferred for S. frugiperda (BV of 100 and PP of 1.0). A first clade (58 specimens) includes all the specimens that have been assigned to the 'rice form' in the studies of Nagoshi et al., [127] and Kergoat et al., [START_REF] Kergoat | Disentangling dispersal, vicariance and adaptive radiation patterns: a case study using armyworms in the pest genus Spodoptera (Lepidoptera: Noctuidae)[END_REF] whereas the other one (43 specimens) includes all the specimens previously assigned to the 'corn form'. Two distinct and well-supported clades were also recovered for S. mauritia. A first clade (BV of 96%, PP of 1.0) groups three specimens collected in the Réunion Island that belong to the nominate form (S. m. mauritia) distributed in Madagascar and neighboring islands (Comoro, Mauritius and Réunion). A second clade (BV of 98%, PP of 1.0) groups five specimens collected in Australia (KF389305), Japan (AB733407, AB733408 and AB733409) and Papua New Guinea (voucher code B152) that belong to S. m. acronyctoides, which is distributed in the Oriental, Indo-Australian and Pacific regions.

The results of phylogenetic molecular species delimitations were compared to morphological assignations that follow the checklist of species provided by Pogue [START_REF] Pogue | A world revision of the genus Spodoptera Guenée (Lepidoptera: Noctuidae)[END_REF].

Regarding the PTP analyses, at least 29 putative species clusters were recovered for the 67 specimens sampled from 27 Spodoptera morphospecies ( Two distinct putative species clusters were consistently found for the following three species: S. exigua, S. frugiperda and S. mauritia. In addition the two individuals of S. apertura were also recovered as distinct putative species in the analyses based on the ML tree. Regarding S. exigua, a putative species cluster groups the four sampled Australian specimens (KF522648, KF522649, KF522650 and KF522651) whereas a second one groups the remaining 27 S. exigua specimens. For S. frugiperda the two putative species clusters consist of 43 and 58 specimens, respectively. The smaller FAW cluster groups all individuals that have been assigned to the 'corn form' by previous studies [START_REF] Kergoat | Disentangling dispersal, vicariance and adaptive radiation patterns: a case study using armyworms in the pest genus Spodoptera (Lepidoptera: Noctuidae)[END_REF]127] whereas the bigger FAW cluster groups all individuals previously assigned to the 'rice form' [START_REF] Kergoat | Disentangling dispersal, vicariance and adaptive radiation patterns: a case study using armyworms in the pest genus Spodoptera (Lepidoptera: Noctuidae)[END_REF]127]. For S. mauritia the two ). When examining the taxa for which changes of status are suggested we found out that most changes are statistically supported (see S5 and S6 Figs). It is the case of the grouping of S. marima with S. ornithogalli and of the splits of S. exigua, S. frugiperda and S. mauritia. The only exception is the case of the grouping of the seven S. descoinsi individuals with the clade corresponding to S. evanida, which is not statistically supported.

Discussion

A cautionary tale of consistency

The results of our phylogenetic species delimitations analyses are remarkably congruent, as they recover the same species clusters (except for the case of S. apertura in one of the PTP analyses and the case of S. descoinsi and S. evanida in one of the GMYC analyses) whatever the set of parameters or methods used. The number of species clusters inferred using PTP procedures also falls well within the confidence interval of the GMYC analyses (27-31 and 27-30 for the strict clock/BD model and UCLN clock/BD model associations, respectively). Although our study may give the impression that the results of species discovery procedures are expected to be always consistent whatever the models and sets of parameters used, we would like to insist on the fact that reliable and consistent results cannot be always achieved. Several studies have clearly highlighted the fact that most molecular species delimitation approaches (including tree-based species delimitation procedures) are highly susceptible to multiple biases or to the way the analyses are parameterized (see the review of Carstens et al., [START_REF] Carstens | How to fail at species delimitation[END_REF]). For instance, model performances are known to be extremely sensitive to biases such as insufficient or unbalanced sampling [START_REF] Wiemers | Does the DNA barcoding gap exist?-a case study in blue butterflies (Lepidoptera: Lycaenidae)[END_REF][START_REF] Meyer | DNA barcoding: error rates based on comprehensive sampling[END_REF], heterogeneous rates of gene evolution [128], incomplete lineage sorting, or hybridization after introgression events [129]. Though rarely look upon, tree building procedures also matter, as different methods and sets of parameters can potentially yield very distinct topologies, which will likely generate contrasting putative species clusters. For example, a potential source of discrepancy is the estimation of branch lengths, as branch length estimates are known to be sensitive to the choice of substitution models [130-132] or partitioning strategies [133,134]. It is especially the case in phylogenetic analyses that use multiple partitions and/ or complex models, for which over-parameterization can potentially bias branch length estimates [134,135]. In addition, it has been recently demonstrated [136] that branch length priors (within a Bayesian framework) can significantly impact branch length estimation, with shorter priors generating shorter branch lengths and longer priors generating longer branch lengths.

Another potential source of discrepancy is the choice and parameterization of the ultrametrization procedures for methods (such as GMYC) that require ultrametric trees as input trees. In the study of Astrin et al.,[103] on cryptorhynchine weevils (Coleoptera) the authors used 21 distinct sets of parameters and methods. They showed that the number of putative species clusters inferred using GMYC could vary drastically with numbers varying from 5 to 564 depending on the choice of methods and parameters. Similarly Tang et al., [110] highlighted the fact that the branch smoothing procedures are a potential source of biases for the approaches that require ultrametric trees.

In summary all these studies underline that molecular species delimitation approaches should not be used blindly. They nonetheless constitute powerful tools that can be effectively used in a concerted way to assess species boundaries (e.g. [137]). In our study, a high level of consistency was likely achieved because of the size of our dataset and because we carefully followed some of the recommendations of Tang et al., [110]. Because the focus of our study was to reassess Spodoptera species boundaries, and not to explore the impact of tree building procedures on molecular species delimitations, we feel that our analytical pipeline is appropriate and allows us to discuss with some confidence the ambiguous species status of several taxa.

Spodoptera species boundaries, a reappraisal

A clear pattern is evidenced for the species that is the main focus of our study, Spodoptera frugiperda. Individuals are separated into two clusters that likely correspond to the two known host-forms (rice and corn) of S. frugiperda. Both PTP and GMYC analyses indicate that the level of genetic differentiation exhibited by the two host-forms is compatible with a potential sister-species status, with a significant statistical support under the GMYC procedure. This result is in agreement with the results of several studies that have highlighted the existence of prezygotic and postzygotic isolation between the two host-forms (Table 1). Different prezygotic isolation mechanisms have been found, including differences in the composition of females' pheromones [START_REF] Groot | Host strain specific sex pheromone variation in Spodoptera frugiperda[END_REF]138], allochronism in mating activity between the two strains [START_REF] Schöfl | Time-shifted reproductive behaviours among fall armyworm (Noctuidae: Spodoptera frugiperda) host strains: evidence for differing modes of inheritance[END_REF]139] and oviposition preferences [START_REF] Meagher | Oviposition choice of two fall armyworm (Lepidoptera: Noctuidae) host strains[END_REF]140]. Regarding postzygotic isolation, the success of mating between the two strains remains highly controversial. On the one hand Pashley and Martin [141] and Dumas et al.,[142] have observed unidirectional mating between corn females and rice males while the reciprocal cross gave viable offsprings. Furthermore, in backcrosses the hybrid

Genetic differentiation

Phylogenetic analyses ++ Kergoat et al., [START_REF] Kergoat | Disentangling dispersal, vicariance and adaptive radiation patterns: a case study using armyworms in the pest genus Spodoptera (Lepidoptera: Noctuidae)[END_REF] As indicated by the combination of pros and cons some results are more or less contradictory.

doi:10.1371/journal.pone.0122407.t001

females mated with low success with their brothers but not at all with males of either parental strain [140,141,143]. On the other hand, another study has shown that the two strains crossed successfully in both directions [144]. The latter is supported by the fact that a high proportion of hybrid has been evidenced is several surveys of natural populations [START_REF] Bolnick | Sympatric speciation: models and empirical evidence[END_REF]145]. Finally, a postzygotic isolation for several life-history traits in both host-forms has been also evidenced by Velasquez-Velez et al., [146] who identified a reduction of the number of hybrid females and a reduction in hybrid fertility in S. frugiperda. Taken altogether all these studies suggest that both host-forms are situated somewhere in between a 'continuum' of speciation [147]. In this context, the results of our study tend to favour the hypothesis that the two host-forms are well beyond the early steps of speciation as they present a level of genetic differentiation which is comparable with those observed between other distinct Spodoptera species.

In the case of Spodoptera mauritia, the results of all phylogenetic species delimitation procedures suggested that Western (S. m. mauritia sensu Fletcher [148]) and Eastern (S. m. acronyctoides sensu Fletcher [148]) populations should be considered as distinct species. Though we cannot exclude the hypothesis of a possible analytical bias resulting from our limited sampling (only three individuals from La Reunion for S. m. mauritia and five individuals from Australia, Japan and Papua New Guinea), the suggested split is nonetheless statistically supported. From a morphological point of view, several authors (e.g. Fletcher [148]) noted differences in forewing coloration, where the conspicuous white areas of the forewing of Western populations are reduced in extent in Eastern populations. However the examination of long series of specimens from the two distribution areas by Brown and Dewhurst [START_REF] Brown | The genus Spodoptera (Lepidoptera: Noctuidae) in Africa and the Near East[END_REF] did not reveal marked differences between putative subspecies. Additional studies are thus definitely required here to precise the status of both entities, such as comparisons of genitalia or pheromone compounds in female.

Regarding Spodoptera marima and Spodoptera ornithogalli, for which only few morphological (hindwing coloration and the lack of sexual dimorphism in S. marima [START_REF] Todd | Keys and illustrations for the armyworm moths of the Noctuid genus Spodoptera Guenée from the western hemisphere[END_REF]; differences exist, both analyses merge them into a single species cluster (with a significant statistical support under GMYC), hence providing more support to put these taxa into synonymy [START_REF] Kergoat | Disentangling dispersal, vicariance and adaptive radiation patterns: a case study using armyworms in the pest genus Spodoptera (Lepidoptera: Noctuidae)[END_REF]. Because the two species occur in different geographic areas-S. marima is only found in the Western and Eastern Neotropics whereas S. ornithogalli is found in the Northern Neotropics and in the South, Western and Eastern Nearctic [START_REF] Pogue | A world revision of the genus Spodoptera Guenée (Lepidoptera: Noctuidae)[END_REF]-they could be considered as distinct subspecies of S. ornithogalli (due to priority, as S. ornithogalli was described before S. marima).

Interestingly our analyses suggest that Spodoptera exigua, a taxon with no ambiguous status, seems well differentiated, and may correspond to two distinct species. 27 of the 31 sampled specimens (including specimens from Canada, Egypt, Germany, Kenya, India, Japan, Thailand and United States of America) constitute a first putative species cluster whereas the four specimens from Australia constitute another one (note that no Australian samples were included in the study of Kergoat et al., [START_REF] Kergoat | Disentangling dispersal, vicariance and adaptive radiation patterns: a case study using armyworms in the pest genus Spodoptera (Lepidoptera: Noctuidae)[END_REF]). This result is also statistically supported under GMYC and does not seem artefactual given the marked level of genetic differentiation between the two clades. It is also supported by additional researches on the Barcoding of life database (BOLD; available at http://www.boldsystems.org/); 81 S. exigua specimens from Australia are grouped into a distinct barcode cluster (BOLD:AAA6645) distinct from another barcode cluster (BOLD:AAA6644) grouping all remaining S. exigua individuals (n = 281). Obviously this result requires more investigation in order to determine whether these specimens correspond to a new species with marked morphological differences or to a case of cryptic species complex.

For Spodoptera apertura, only one of the four distinct sets of analyses (PTP using the ML tree; S3 The situation is more complex in the case of Spodoptera cosmiodes and Spodoptera descoinsi, two taxa for which marked morphological and biological differences exist [START_REF] Pogue | A world revision of the genus Spodoptera Guenée (Lepidoptera: Noctuidae)[END_REF][START_REF] Lalanne-Cassou | Mécanismes d'isolement reproducteur chez les espèces du complexe Neotropical Spodoptera latifascia-S. cosmioides-S. descoinsi (Lepidoptera: Noctuidae)[END_REF]. Both phylogenetic species delimitation procedures suggested the existence of two distinct species clusters. Analyses following the GMYC procedure also included representatives of S. evanida in one of the two clusters (the one with seven specimens S. descoinsi) but this grouping seems artefactual as the two species are morphologically not related [START_REF] Pogue | A world revision of the genus Spodoptera Guenée (Lepidoptera: Noctuidae)[END_REF]; in addition a closer examination of the GMYC output indicates that this grouping is not statistically supported. If we consider the remaining specimens, we can distinguish two species clusters, one that groups seven S. descoinsi and another that groups all (n = 35) S. cosmiodes individuals plus two representatives of S. descoinsi. To precise the status of these two individuals, additional studies are likely required; we advocate for the use of species validation procedures (with packages such as [START_REF] Yang | Bayesian species delimitation using multilocus sequence data[END_REF] or Spe-deSTEM [START_REF] Ence | SpedeSTEM: a rapid and accurate method for species delimitation[END_REF]), using more specimens and a multi locus dataset. By doing so, it will be possible to better estimate the actual evolutionary lineages that compose the two species.

Conclusions

This study constitutes another case study that underlines the interest and effectiveness of fast species discovery procedures; the achieved results are congruent and reliable, irrespective of the set of parameters and phylogenetic models applied, even though we only relied on a single locus dataset. Our results unravel at least three potential new species clusters (for S. exigua, S. frugiperda and S. mauritia) and also support the synonymy of S. marima with S. ornithogalli. Though these redefined species boundaries have to be considered cautiously, they nonetheless constitute a new line of evidence that may fuel the debate on Spodoptera species boundaries and inspire future studies on species such as the beet armyworm S. exigua, for which a potential cryptic diversity was not expected. In contrast, the case of S. descoinsi is clearly more complex as illustrated by the inconsistencies between the results of PTP and GMYC procedures. Here further studies relying on additional markers and species validation procedures will be necessary to precise the status of this species.

Fig 2 ,

 2 S3 and S4 Figs and S3 Table). 30 putative species clusters were inferred for the analyses based on the best-fit ML tree (S3 Fig) while 29 putative species clusters were inferred for the analyses based on the BI majority-rule consensus topology (S4 Fig).

Fig 1 .

 1 Fig 1. COI-based phylogenetic relationships of Spodoptera species. The tree on the left summarizes the results of ML analyses while the tree on the right summarizes the results of BI analyses. Black dots indicate nodes supported by bootstrap values > 70% (ML tree) or supported by posterior probability > 0.95 (BI tree). doi:10.1371/journal.pone.0122407.g001

Fig 2 .

 2 Fig 2. Putative species clusters corresponding to: (i) morphological delineations (column 1); (ii) PTP analyses using either the majority-rule consensus topology resulting from the BI analyses (column 2) or the best tree from the ML analyses (column 3); (iii) GMYC analyses based either on a strict clock and a BD model (column 4) or on a UCLN clock and a BD model (column 5). The reference tree used here corresponds to the tree resulting from the BI analyses carried out with MrBayes. doi:10.1371/journal.pone.0122407.g002

  Fig) recovers two distinct species clusters for the two sampled specimens of the species. We suspect that this result is artefactual; it possibly results from an artefact in the estimation of branch lengths under ML, where the two terminal branches leading to both individuals are really unbalanced (S3 Fig) whereas there are balanced under BI (S4 Fig). Insufficient sampling (only two specimens from Australia were sequenced for this species) could also have caused this likely error.

Table 1 .

 1 List of evidences arguing in favor of a high level of differentiation between the two FAW strains.

	Suitability References

PLOS ONE | DOI:10.1371/journal.pone.0122407April 8, 2015

PLOS ONE | DOI:10.1371/journal.pone.0122407 April 8, 2015 / 20

Acknowledgments

We would to thank Diego Fontaneto and two anonymous reviewers for their numerous constructive comments on a previous version of the manuscript. Some of the molecular data used in this work were produced through technical facilities of the "Laboratoire d'Excellence-Centre Méditerranéen de l'Environnement et de la Biodiversité" (LabEx-CeMEB), Montpellier, France. The authors also wish to thank A. Dehne Garcia for his help on the CBGP HPC computational platform.

Part of the sequencing was supported by a Genoscope project @-Speed-Id (Accurate SPEciEs Delimitation and Identification of eukaryotic biodiversity using DNA markers) proposed by F-BoL, the French Barcode of life initiative and by the program 'Bibliothèque du Vivant' (Project SPODOBAR) supported by a joint "Centre national de la recherche scientifique", "Institut National de la Recherche Agronomique" and "Muséum national d'Histoire naturelle" consortium. The project was also supported by INRA (AAP SPE SPODOPTERA) and a grant from the French National Research Agency (ANR-12-BSV7-0004-01 ADA-SPODO).

All new sequences generated for the study are available from the GenBank database (accession numbers) KF854152 to KF854234.

Supporting Information

Putative species clusters are indicated using transitions between black-coloured to red-coloured branches. The inter-and intraspecific portions of the tree are divided with a dotted line (95% confidence intervals are figured using thinner dotted lines). (PDF) S6 Fig. Results of the GMYC analyses based on BEAST analyses with an UCLN clock model. Putative species clusters are indicated using transitions between black-coloured to redcoloured branches. The inter-and intraspecific portions of the tree are divided with a dotted line (95% confidence intervals are figured using thinner dotted lines). (PDF)

S1 Table . Taxon sampling. Sequences generated in a previous study of our research group are highlighted using ' Ã ' whereas newly generated sequences are highlighted using ' ÃÃ '. The Democratic Republic of the Congo was abbreviated using DRC. When the country of origin is known we also provide the corresponding ISO 3166 alpha-3 code. We used the following abbreviations for the repository institutes and collections: ACG: