Abstract

We investigate the phylogeny, biogeography, time of origin and diversification, ancestral area reconstruction and large-scale distributional patterns of an ancient group of arachnids, the harvestman suborder Cyphophthalmi. Analysis of molecular and morphological data allow us to propose a new classification system for the group; Pettalidae constitutes the infraorder Scopulophthalmi new clade, sister group to all other families, which are divided into the infraorders Sternophthalmi new clade and Boreophthalmi new clade. Sternophthalmi includes the families Troglosironidae, Ogoveidae, and Neogoveidae; Boreophthalmi includes Stylocellidae and Sironidae, the latter family of questionable monophyly. The internal resolution of each family is discussed and traced back to its geological time origin, as well as to its original landmass, using methods for estimating divergence times and ancestral area reconstruction. The origin of Cyphophthalmi can be traced back to the Carboniferous, whereas the diversification time of most families ranges between the Carboniferous and the Jurassic, with the exception of Troglosironidae, whose current diversity originates in the Cretaceous/Tertiary. Ancestral area reconstruction is ambiguous in most cases. Sternophthalmi is traced back to an ancestral land mass that contained New Caledonia and West Africa in the Permian, whereas the ancestral landmass for Neogoveidae included the south-eastern USA and West Africa, dating back to the Triassic. For Pettalidae, most results include South Africa, or a combination of South Africa with the Australian plate of New Zealand or Sri Lanka, as the most likely ancestral landmass, back in the Jurassic. Stylocellidae is reconstructed to the Thai-Malay Penisula during the Jurassic. Combination of the molecular and morphological data results in a hypothesis for all the cyphophthalmid genera, although the limited data available for some taxa represented only in the morphological partition negatively affects the phylogenetic reconstruction by decreasing nodal support in most clades. However, it resolves the position of many monotypic genera not available for molecular analysis, such as Iberosiro, Odontosiro, Speleosiro, Managotria or Marwe, although it does not place Shearogovea or Ankaratra within any existing family. The biogeographical data show a strong correlation between relatedness and formerly adjacent landmasses, and oceanic dispersal does not need to be postulated to explain disjunct distributions, especially when considering the time of divergence. The data also allow testing of the hypotheses of the supposed total submersion of New Zealand and New Caledonia, clearly falsifying submersion of the former, although the data cannot reject the latter.

INTRODUCTION

The harvestman suborder Cyphophthalmi (Fig. 1) constitutes an ancient lineage of arachnids and was probably one of the earliest inhabitants of terrestrial ecosystems. Currently distributed on all continental landmasses (with the exception of Antarctica) and on most large islands of continental origin, the group is considered to have been in close association to these landmasses since its origins (Juberthie & Massoud, 1976; Boyer et al., 2007b). The fact that deep genetic divergences in cytochrome c oxidase subunit I (COI) have been reported within one species (Boyer, Baker & Giribet, 2007a), and are suspected for many others (R. Clouse & P. Sharma, unpubl. data), corroborates the observations that individuals may live a long time (Juberthie, 1960b) and do not disperse far during the course of life history. These, together with the old history of the group [a Burmese amber specimen probably belonging to Stylocellidae is known from the Early Cretaceous (Poinar, 2008) and the origins of the group has been estimated to have taken place during the Devonian or Carboniferous using molecular dating techniques (Giribet et al., 2010)] have resulted in a broad use of Cyphophthalmi for biogeographical inferences and zoogeographical discussions (Rambla, 1974; Juberthie & Massoud, 1976; Boyer, Karaman & Giribet, 2005; Boyer & Giribet, 2007; Clouse & Giribet, 2007; Giribet & Kury, 2007; Boyer et al., 2007b; Boyer & Giribet, 2009; Clouse, de Bivort & Giribet, 2009; Karaman, 2009; Murienne & Giribet, 2009; Sharma & Giribet, 2009a; Clouse & Giribet, 2010; de Bivort & Giribet, 2010; Murienne, Karaman & Giribet, 2010b; Clouse et al., 2011). These include some recent and more general debates on the total submersion of large fragment islands such as New Caledonia and New Zealand (Sharma & Giribet, 2009a; Giribet & Boyer, 2010; Giribet et al., 2010).

Figure 1

Habitus. A, Karripurcellia harveyi (Pettalidae) from Warren National Park, Western Australia, July 2004. B, Pettalus thwaitesi (Pettalidae) from Peradeniya Botanical Gardens, Central Province, Sri Lanka, October 2007. C, Rakaia pauli (Pettalidae) from Kelcey's bush, near Waimate, North Island, New Zealand, February 2008. D, Aoraki longitarsa (Pettalidae) from Governor's bush, Mt Cook, South Island, New Zealand, January 2006. E, male Pettalus thwaitesi (Pettalidae) from Peradeniya Botanical Gardens, Central Province, Sri Lanka, June 2004. F, Ogovea cameroonensis (Ogoveidae) from Ototomo Forest, Central province, Cameroon, June 2009. G, Parogovia sp. (Neogoveidae) from Mt. Koupé, South-West Province, Cameroon, June 2009. H, two species of Parogovia from Campo Reserve, Littoral Province, Cameroon, June 2009; upper left, adult specimen of Parogovia n. sp.; lower right, juvenile specimen of Parogovia cf. sironoides. I, juvenile specimen of Paramiopsalis ramulosus (Sironidae) from P.N. Peneda Gerés, Portugal, May 2008. J, Paramiopsalis ramulosus (Sironidae) from P.N. Peneda Gerés, Portugal, May 2008. K, Parasiro minor (Sironidae) from Monte Rasu, Sardinia, Italy, March 2008. L, Suzukielus sauteri (Sironidae) from Mt. Takao, Tokyo Prefecture, Honshu, Japan, April 2005. M, juvenile specimen of Leptopsalis sp. (Stylocellidae) from Bantimurung-Bulusaraung N.P., Sulawesi Selatan, Indonesia, June 2006. N, female Leptopsalis sp. (Stylocellidae) from Bantimurung-Bulusaraung N.P., Sulawesi Selatan, Indonesia, June 2006.

Figure 1

Habitus. A, Karripurcellia harveyi (Pettalidae) from Warren National Park, Western Australia, July 2004. B, Pettalus thwaitesi (Pettalidae) from Peradeniya Botanical Gardens, Central Province, Sri Lanka, October 2007. C, Rakaia pauli (Pettalidae) from Kelcey's bush, near Waimate, North Island, New Zealand, February 2008. D, Aoraki longitarsa (Pettalidae) from Governor's bush, Mt Cook, South Island, New Zealand, January 2006. E, male Pettalus thwaitesi (Pettalidae) from Peradeniya Botanical Gardens, Central Province, Sri Lanka, June 2004. F, Ogovea cameroonensis (Ogoveidae) from Ototomo Forest, Central province, Cameroon, June 2009. G, Parogovia sp. (Neogoveidae) from Mt. Koupé, South-West Province, Cameroon, June 2009. H, two species of Parogovia from Campo Reserve, Littoral Province, Cameroon, June 2009; upper left, adult specimen of Parogovia n. sp.; lower right, juvenile specimen of Parogovia cf. sironoides. I, juvenile specimen of Paramiopsalis ramulosus (Sironidae) from P.N. Peneda Gerés, Portugal, May 2008. J, Paramiopsalis ramulosus (Sironidae) from P.N. Peneda Gerés, Portugal, May 2008. K, Parasiro minor (Sironidae) from Monte Rasu, Sardinia, Italy, March 2008. L, Suzukielus sauteri (Sironidae) from Mt. Takao, Tokyo Prefecture, Honshu, Japan, April 2005. M, juvenile specimen of Leptopsalis sp. (Stylocellidae) from Bantimurung-Bulusaraung N.P., Sulawesi Selatan, Indonesia, June 2006. N, female Leptopsalis sp. (Stylocellidae) from Bantimurung-Bulusaraung N.P., Sulawesi Selatan, Indonesia, June 2006.

However, to use a system for biogeographical inferences, a sound systematic hypothesis of the group is required. The taxonomy of Cyphophthalmi has benefitted from the contributions of many studies, especially the synthetic work of Hansen & Sørensen (1904), who produced the first and still best monograph on the group, and established the first classification system of the suborder Cyphophthalmi with one family, Sironidae, and two subfamilies, Stylocellini (including the genera StylocellusWestwood, 1874, Ogovia Hansen & Sørensen, 1904, which was pre-occupied and became Ogovea Roewer, 1923, and Miopsalis Thorell, 1890) and Sironini (including Pettalus Thorell, 1876, PurcelliaHansen & Sørensen, 1904, Siro Latreille, 1796, and ParasiroHansen & Sørensen, 1904). Another major contributor was Juberthie, who described and monographed many genera (e.g. Juberthie, 1956, 1958, 1960a, 1961, 1962, 1969, 1970a, b; Juberthie & Muñoz-Cuevas, 1970; Juberthie, 1979) in addition to his contributions to the biology of the group; the regional work of Forster (1948, 1952) in New Zealand, that of Lawrence (1931, 1933, 1939, 1963) in South Africa, that of Rambla (Rambla & Fontarnau, 1984, 1986; Rambla, 1991, 1994) in the Iberian Peninsula and southeast Asia, to mention just a few of them. More recently, Shear has contributed with descriptions of numerous species in almost all cyphophthalmid families (Shear, 1977, 1979a, b, 1985, 1993a, b, c; Shear & Gruber, 1996). He also proposed the bases of modern cyphophthalmid systematics in a seminal first cladistic analysis of the group (Shear, 1980), with five families, three of which were new, and two infraorders, equivalent to Hansen and Sørensen's subfamilies (Table 1). A sixth family, Troglosironidae, was also proposed a few years later (Shear, 1993b).

Table 1

Classification system of Shear (1980, 1993)

Suborder Cyphophthalmi 
Infraorder Tropicophthalmi Shear, 1980 
Superfamily Stylocelloidea Hansen & Sørensen, 1904 
Family Stylocellidae Hansen & Sørensen, 1904 
Superfamily Ogoveoidea Shear, 1980 
Family Ogoveidae Shear, 1980 
Family Neogoveidae Shear, 1980 
Infraorder Temperophthalmi Shear, 1980 
Superfamily Sironoidea Simon, 1879 
Family Sironidae Simon, 1879 
Family Pettalidae Shear, 1980 
Family Troglosironidae Shear, 1993 
Suborder Cyphophthalmi 
Infraorder Tropicophthalmi Shear, 1980 
Superfamily Stylocelloidea Hansen & Sørensen, 1904 
Family Stylocellidae Hansen & Sørensen, 1904 
Superfamily Ogoveoidea Shear, 1980 
Family Ogoveidae Shear, 1980 
Family Neogoveidae Shear, 1980 
Infraorder Temperophthalmi Shear, 1980 
Superfamily Sironoidea Simon, 1879 
Family Sironidae Simon, 1879 
Family Pettalidae Shear, 1980 
Family Troglosironidae Shear, 1993 

Two decades after Shear's classification system appeared, Giribet (2000) compiled all the cyphophthalmid literature to date, recognizing 113 species in 26 genera. A subsequent analysis including representatives of most genera and based on a numerical cladistic analysis of 32 morphological characters (Giribet & Boyer, 2002) recognized most of the families erected by Shear (1980) but also challenged some of his systematic propositions because the root of the tree, based on a limited molecular data set also published in the same study, was placed between stylocellids and the rest (rendering Tropicophthalmi paraphyletic) or between pettalids and the rest (rendering Temperophthalmi paraphyletic). Shear (1993b) had also proposed the new family Troglosironidae as sister to (Pettalidae + Sironidae) and this result was refuted by Giribet & Boyer (2002), who found it nested within an unresolved Neogoveidae. After some minor familial reassignments –Huitaca Shear, 1979 was removed from Ogoveidae (Giribet & Prieto, 2003) and subsequently included in Neogoveidae (Giribet, 2007b); FangensisRambla, 1994 was transferred from Sironidae to Stylocellidae (Schwendinger & Giribet, 2005); Metasiro was transferred from Sironidae to Neogoveidae (Giribet, 2007b); Meghalaya Giribet, Sharma & Bastawade, 2007 was included in Stylocellidae (Clouse et al., 2009); and Shearogovea mexasca (Shear, 1977) was excluded from Neogoveidae (Benavides & Giribet, 2007; Giribet, 2011) – the families are currently considered to be stable.

Recent phylogenetic analyses based on nucleotide sequence data have resolved the relationship among some of these families, providing strong support for a relationship of Troglosironidae and Neogoveidae (Boyer et al., 2007b; Boyer & Giribet, 2009; Sharma & Giribet, 2009a; Giribet et al., 2010), a result also obtained in a recent analysis of morphometric characters (de Bivort, Clouse & Giribet, 2010). Monophyly of Pettalidae is well supported both by discrete and continuous morphological characters (Giribet & Boyer, 2002; Giribet, 2003a; Boyer & Giribet, 2007; de Bivort et al., 2010; de Bivort & Giribet, 2010), as well as a diversity of molecular analyses (Boyer & Giribet, 2007, 2009; Boyer et al., 2007b; Giribet et al., 2010). Stylocellidae is also well supported based on morphology (Giribet & Boyer, 2002; Clouse et al., 2009) and molecules (Schwendinger & Giribet, 2005; Clouse & Giribet, 2007; Boyer et al., 2007b; Clouse et al., 2009; Clouse & Giribet, 2010; Giribet et al., 2010). However, monophyly of Sironidae, especially the membership of the Mediterranean genus Parasiro and the Japanese Suzukielus Juberthie, 1970, remains controversial, both based on morphology (Giribet & Boyer, 2002; de Bivort & Giribet, 2004; de Bivort et al., 2010), as well as on molecular analyses (Boyer et al., 2005; Boyer & Giribet, 2007; Giribet et al., 2010).

In addition to the uncertainty about the monophyly of Sironidae, which we approach here by including an expanded taxon sampling in problematic genera previously represented by a single species (Parasiro), we include a much larger diversity of Neogoveidae, both from the Neotropics (29 species versus six used in Boyer et al., 2007b; including data on the new Brazilian genus CangaDaSilva, Pinto-da-Rocha & Giribet, 2010) and from the Afrotropics (12 terminals versus seven used in Boyer et al., 2007b). Most importantly, we include the first molecular data on the family Ogoveidae, from specimens collected in Cameroon in 2009. In total, we provide novel sequence data for 34 species (of a total of 162 molecular terminals), include 27 genera and a family previously unsampled, and include new landmasses (Mindanao, the eastern Neotropics, the westernmost distribution of the Afrotropics) not considered in previous phylogenetic analyses. The present study also provides the first total evidence analysis of molecules and morphology for the whole suborder Cyphophthalmi and new data on the timing of diversification and cladogenesis of the group, aiming to revisit interesting biogeographical topics. Finally, we provide an estimate of the ancestral area for each lineage and present the first habitat suitability and distributional patterns analysis for this dispersal-limited, yet globally-distributed group of arthropods. Studying macroecological patterns in Cyphophthalmi is complicated as a result of the scarce occurrence data for most species. Thus, species-level assessment of large-scale distributional patterns and their primary ecological and evolutionary drivers is difficult. Recently, theoretical and practical arguments for the utility of modelling distributional patterns or even ecological niche characteristics above the species level have been proposed (Heino & Soininen, 2007; Hadly, Spaeth & Li, 2009; Diniz, De Marco & Hawkins, 2010). Despite some obvious limitations (Diniz et al., 2010), this approach may be very useful to evaluate patterns in groups with limited distributional data such as insects and other arthropods including Cyphophthalmi.

MATERIAL AND METHODS

Specimens

Most specimens used in the molecular part of this study (Fig. 2) were collected by one or more of the authors through direct sifting of leaf litter and transferred to approximately 95% ethanol for molecular and morphological study. Museum specimens have also been used for the morphological studies. A detailed discussion of the specimen collecting effort is provided in the Supporting information (

).

Figure 2

Distribution map of the sampled specimens for the molecular study (Table 2). Pettalidae are represented in red, Troglosironidae in purple, Ogoveidae in cyan, Neogoveidae in green, Sironidae in orange, and Stylocellidae in navy blue.

Figure 2

Distribution map of the sampled specimens for the molecular study (Table 2). Pettalidae are represented in red, Troglosironidae in purple, Ogoveidae in cyan, Neogoveidae in green, Sironidae in orange, and Stylocellidae in navy blue.

The study includes the first molecular data for the family Ogoveidae (Ogovea cameroonensisGiribet & Prieto, 2003) and includes additional sampling within all other families, building upon previous studies on the phylogenies of Pettalidae (Boyer & Giribet, 2007; Boyer et al., 2007b). Stylocellidae (Clouse et al., 2009; Clouse & Giribet, 2010; Clouse et al., 2011), Troglosironidae (Sharma & Giribet, 2009a), and Sironidae (Boyer et al., 2005; Giribet & Shear, 2010; Murienne et al., 2010b). However, data for Neogoveidae were restricted to a single previous study (Boyer et al., 2007b), and the family was poorly sampled. For the African diversity, we are now able to add data on another described species, Parogovia gabonica (Juberthie, 1969), from near its type locality (Ipassa Reserve, Makokou, Gabon). We also add new data on two new species from Mount Koupé and the Campo reserve, in Cameroon, and an additional specimen of Parogovia cf. sironoides also from the Campo reserve in Cameroon. The third African species, Parogovia pabsgarnoniLegg, 1990, is known only from its type locality in Sierra Leone, resulting in a large biogeographical gap from the known distribution of species in the Gulf of Guinea, and differs morphologically from the other species in the genus in many key characters, showing very different spermatopositor from the species in the Gulf of Guinea (Legg & Pabs-Garnon, 1989; Legg, 1990). A possible close relative to this species is included here, based on data from a female collected in Ivory Coast. The South American sampling has also been enriched considerably. The monotypic genus Huitaca is now represented by data from seven species all from Colombia, including the nominal Huitaca ventralis Shear, 1979. Metagovea is now represented by 13 specimens in 12 putative new species, including one from Guyana. These include the Colombian species identified as Neogovea in our previous studies, although they appear to be related to Metagovea. A large biogeographical gap in our previous studies was the easternmost distribution of the genus Neogovea (type species Neogovea immsi Hinton, 1938, from Amapá, Brazil). We now include putative representatives of this clade based on specimens collected in French Guiana and Guyana, including specimens from the recently described N. virginie Jocqué & Jocqué, 2011. With the exception of one specimen from Guyana clustering with Metagovea, these specimens group with the unidentified juvenile from Venezuela used in Boyer et al. (2007b) and with a species from the ‘Tepuis’ in Colombia, which we reassign here to the genus Brasilogovea Martens, 1969, previously considered a synonym of Neogovea (Shear, 1980; Giribet, 2000). Finally, we were able to include data on the monotypic genus Canga based on a specimen from its type locality (DaSilva et al., 2010). However, large areas of the Neotropics with known specimens of Neogoveidae remain unsampled in our molecular phylogeny, and they should be included in future studies (Benavides & Giribet, 2007: fig. 1).

Molecular data

DNA extraction, amplification, and sequencing were performed as described in several of our previous studies on molecular systematics of Cyphophthalmi using the same markers (Schwendinger & Giribet, 2005; Boyer et al., 2007b; Boyer & Giribet, 2009; Sharma & Giribet, 2009a; Clouse & Giribet, 2010). We used the five markers as in these previous studies, including the nuclear ribosomal 18S and 28S rRNA, the nuclear protein-encoding histone H3, the mitochondrial ribosomal 16S rRNA, and the mitochondrial protein-encoding COI genes. For outgroups, we used seven noncyphophthalmid Opiliones from the suborders Eupnoi, Dyspnoi, and Laniatores (Table 2). Published sequence data from these studies and the novel data presented here are deposited in GenBank and are shown in Table 2.

Table 2

Specimen and collection data with GenBank accession numbers

 Voucher Locality Coordinates 18S rRNA 28S rRNA 16S rRNA COI H3 
FAMILY PETTALIDAE         
Aoraki calcarobtusa westlandica DNA101129 New Zealand −41.78387, 172.36903 EU673626 DQ518038 DQ518070 EU673667 EU673703 
Aoraki crypta DNA101289 New Zealand −37.53404, 175.74140 DQ518000 DQ518043 DQ518068 DQ518120 DQ518156 
Aoraki denticulata denticulata DNA100955 New Zealand −42.09283, 171.34096 EU673618 EU673654 EU673584 DQ992309 EU673698 
Aoraki denticulata major DNA100959 New Zealand −43.03408, 171.76464 EU673620 EU673656 EU673585 DQ992203 EU673700 
Aoraki granulosa DNA101841 New Zealand −39.93478, 175.64046 DQ517999 DQ518039 DQ518071 – – 
Aoraki healyi DNA100940 New Zealand −41.08673, 174.13826 DQ518002 DQ518042 DQ518067 DQ518122 DQ518160 
Aoraki inerma DNA100966 New Zealand −38.79686, 177.12472 EU673622 EU673658 – – EU673702 
Aoraki longitarsa DNA101806 New Zealand −43.73666, 170.09222 EU673613 EU673652 – DQ992313 EU673695 
Aoraki cf. tumidata DOC094 New Zealand −39.667, 175.637* EU673614 – – DQ992318 – 
Aoraki sp. DNA101126 New Zealand −41.08708, 174.13709 EU673624 EU673659 – DQ992319 – 
Austropurcellia arcticosa DNA100951 Queensland, Australia −16.16610, 145.41560 DQ517984 DQ518023 – DQ518111 DQ518147 
Austropurcellia daviesae DNA100947 Queensland, Australia −17.24560, 145.64207 DQ517985 DQ518024 – DQ518112 DQ518148 
Austropurcellia forsteri DNA100945 Queensland, Australia −16.06151, 145.46217 DQ517983 DQ518022 DQ518064 DQ518110 DQ518146 
Austropurcellia scoparia DNA100946 Queensland, Australia −16.59458, 145.27927 DQ517982 DQ518021 DQ518065 DQ518108 EU673678 
Chileogovea oedipus DNA100413 Chile −41.50833, −72.61666 DQ133721 DQ133733 DQ518055 DQ133745 – 
Chileogovea sp. DNA100490 Chile −39.66666, −73.28333* DQ133722 DQ133734 DQ518054 DQ133746 EU673672 
Karripurcellia harveyi DNA101303 Western Australia −34.49500, 115.97527 DQ517980 DQ518019 DQ518062 DQ518106 DQ518143 
Neopurcellia salmoni DNA100939 New Zealand −44.10780, 169.35527 DQ517998 EU673650 DQ518066 DQ825638 EU673694 
Parapurcellia monticola DNA100386 South Africa −29.05347, 29.38516 DQ518973 DQ518009 – DQ518098 DQ518135 
Parapurcellia silvicola DNA100385 South Africa −28.74421, 31.13763 AY639494 DQ518008 DQ518053 AY639582 DQ518136 
Pettalus thwaitesi DNA101223 Sri Lanka 7.27251, 80.59333 EU673592 EU673633 EU673569 EU673666 EU673677 
Pettalus sp. DNA101282 Sri Lanka 7.38483, 80.81696 DQ825537 EU673632 – DQ825636 EU673676 
Pettalus sp. DNA101283 Sri Lanka 7.38483, 80.81696 DQ517974 DQ518016 DQ518056 DQ518100 DQ518137 
Pettalus sp. DNA101285 Sri Lanka 6.92517, 80.81949 DQ517976 DQ518017 DQ518058 DQ518102 DQ518139 
Pettalus sp. DNA101286 Sri Lanka 6.92517, 80.81949 DQ517977 DQ518013 DQ518059 DQ518103 DQ518140 
Pettalus sp. DNA101287 Sri Lanka 6.82359, 80.84996 DQ517978 DQ518014 DQ518060 DQ518104 DQ518141 
Pettalus sp. DNA101288 Sri Lanka 6.55551, 80.37030 DQ517979 DQ518015 DQ518061 DQ518105 DQ518142 
Purcellia illustrans DNA100387 South Africa −33.98294, 18.42464 EU673589 EU673629 DQ518052 EU673665 EU673673 
Rakaia antipodiana DNA100957 New Zealand −43.25145, 171.36761 DQ517988 DQ518031 DQ518072 DQ518115 DQ518151 
Rakaia dorothea DNA100943 New Zealand −41.28163, 174.90961 DQ517990 DQ518033 DQ518077 DQ992331 – 
Rakaia florensis DNA101295 New Zealand −40.83258, 172.96896 DQ517986 DQ518025 DQ518083 DQ518113 DQ518149 
Rakaia lindsayi DNA101128 New Zealand −46.89327, 168.10398 DQ517995 DQ518027 DQ518081 DQ518118 DQ518154 
Rakaia macra DNA101808 New Zealand −45.92000, 170.02805 EU673596 EU673636 EU673571 EU673668 – 
Rakaia magna australis DNA100962 New Zealand −42.33225, 172.17126 EU673601 EU673640 EU673575 DQ992333 EU673684 
Rakaia media DNA101292 New Zealand −39.93478, 175.64046 DQ517996 DQ518030 DQ518074 DQ518125 DQ518157 
Rakaia minutissima DNA101291 New Zealand −39.41641, 175.21858 DQ517987 DQ518026 DQ518082 DQ518114 DQ518150 
Rakaia pauli DNA100968 New Zealand −44.70073, 170.96557 DQ517992 DQ518032 DQ518073 EU673670 DQ518161 
Rakaia solitaria DNA101294 New Zealand −41.46852, 175.44885 DQ517997 DQ518029 DQ518075 DQ518119 DQ518155 
Rakaia sorenseni sorenseni DNA100969 New Zealand −46.10967, 167.69034 DQ517993 DQ518036 DQ518079 DQ518116 DQ518153 
Rakaia sorenseni digitata DNA100970 New Zealand −46.58177, 169.20901 DQ517989 DQ518035 DQ518078 DQ518123 DQ518162 
Rakaia stewartiensis DNA100944 New Zealand −46.89327, 168.10398 DQ517994 DQ518028 DQ518080 DQ518117 – 
Rakaia uniloca DNA101812 New Zealand −41.22083, 173.43944 EU673599 EU673638 – EU673671 – 
Rakaia sp. DNA101297 New Zealand −40.97595, 175.11747 EU673608 EU673647 EU673579 DQ992344 EU673691 
Rakaia sp. DNA101807 New Zealand −45.90166, 169.46277 EU673606 EU673645 – – EU673689 
Rakaia sp. DNA100958 New Zealand −43.80869, 173.02144 EU673597 EU673637 EU673573 DQ992349 EU673681 
Rakaia sp. DNA101293 New Zealand −40.85181, 174.93233 EU673610 EU673649 EU673581 DQ992322 EU673693 
Rakaia sp. DNA100954 New Zealand −41.15757, 175.02168 EU673603 EU673642 EU673576 DQ992348 EU673686 
FAMILY SIRONIDAE         
Cyphophthalmus corfuanus DNA102111 Greece 39.61056, 20.33944 FJ946390 FJ946415 FJ946364 FJ946438 – 
Cyphophthalmus duricorius DNA100487 Slovenia 46.01667, 14.66667 AY639461 DQ513120 AY639526 AY639556 – 
Cyphophthalmus ere DNA100499 Serbia 43.83333, 20.05 AY639462 DQ825593 AY639527 AY639557 AY639444 
Cyphophthalmus cf. gjorgjevici DNA100498 Macedonia 41.96667, 21.35 AY639464 DQ825587 AY639529 AY639559 – 
Cyphophthalmus gordani DNA100495 Montenegro 42.45, 19.26667 AY639467 DQ825592 AY639532 – AY639446 
Cyphophthalmus hlavaci DNA102099 Croatia 43.41344, 16.91244 FJ946384 FJ946409 FJ946358 FJ946433 – 
Cyphophthalmus markoi DNA100497 Macedonia 41.41667, 22.26667 AY639469 AY639504 AY639534 AY639561 AY639447 
Cyphophthalmus martensi DNA100494 Montenegro 42.4, 18.76667 AY639471 DQ825589 AY639536 AY639563 AY639449 
Cyphophthalmus minutus DNA100493 Montenegro 42.65, 18.66667 AY639473 DQ825591 AY639537 AY639565 AY639450 
Cyphophthalmus ognjenovici DNA101039 Bosnia & Herzegovina 43.01667, 18.51667 AY639475 DQ825594  AY639567 AY639451 
Cyphophthalmus rumijae DNA100492 Montenegro 42.16667, 19.33333 AY639477 DQ825588 AY639539 AY639569 AY639453 
Cyphophthalmus serbicus DNA102098 Serbia 43.27917, 22.06389 FJ946383 FJ946408 FJ946357 FJ946432 – 
Cyphophthalmus teyrovskyi DNA100910 Montenegro 42.23333, 19.06667 AY639482 DQ513118 AY639544 AY639571 AY639454 
Cyphophthalmus trebinjanus DNA101038 Bosnia & Herzegovina 42.23333, 19.16667 AY639483 DQ513119  AY639572 – 
Cyphophthalmus zetae DNA100907 Montenegro 42.93333, 18.5 AY639485 AY639515 AY639546 AY639574 AY639456 
Paramiopsalis eduardoi DNA101878 Spain 43.41718, −8.06356 EU638284 EU638287 EU638281 EU638288 JF786415 
Paramiopsalis ramulosus DNA100459 Spain 42.31580, −8.48697 AY639489 DQ513121 AY639550 DQ825641 – 
Paramiopsalis ramulosus DNA103538 Portugal 41.56944, −8.14027 JF934956 JF934990 JF935023 JF786389 – 
Paramiopsalis sp. DNA104624 Spain 43.31968, −6.87282 JF934957 JF934991 JF935024 JF786390 JF786416 
Parasiro coiffaiti DNA101383 Spain 42.15251, 1.93039 AY918872 DQ513122 AY918877 DQ825642 AY918882 
Parasiro minor DNA103535 Sardinia, Italy 40.43047, 9.00948 JF934958 JF934992 JF935025 JF786391 – 
Siro acaroides DNA100488 Oregon, USA 44.5833, −123.5166* AY639490 DQ513128 AY639551 DQ825643 – 
Siro boyerae DNA101614 Washington, USA 46.99221, −121.84641 DQ513139 DQ513125 – DQ513112 – 
Siro calaveras DNA101623 California, USA 38.27744, −120.30543 DQ513146 DQ513133* – – – 
Siro exilis DNA100489 Maryland, USA 39.4833, −79.4333 AY639491 DQ825585 – AY639579  
Siro cf. kamiakensis DNA101611 Idaho, USA 47.74646, −116.70207 DQ513147 DQ513134* – DQ513115 – 
Siro kamiakensis DNA101613 Idaho, USA 46.86777, −117.15777 JF934959 JF934993 – – – 
Siro rubens DNA100457 France 44.08338, 3.58140 AY428818 DQ825584 – DQ513111 – 
Siro shasta DNA101622 California, USA 41.06367, −122.36045 DQ513149 DQ513136* – – – 
Siro valleorum DNA100461 Italy 45.9833, 9.8666* AY639492 DQ513123 AY639552 AY639580 AY639457.1 
Suzukielus sauteri DNA101543 Japan 35.63440, 139.24122 DQ513138 DQ513116 DQ518086 DQ513108 DQ518166 
Suzukielus sauteri DNA101550 Japan 34.83333, 138.93166 DQ825541 DQ825583 DQ825615 DQ825640 DQ825520 
FAMILY OGOVEIDAE         
Ogovea cameroonensis DNA104617 Cameroon 3.64621, 11.29079 JF934960 JF934994 JF935026 JF786392 JF786417 
FAMILY TROGLOSIRONIDAE         
Troglosiro aelleni DNA100345 New Caledonia −21.1833, 165.3059 AY639497 DQ825580 AY639555 AY639584 DQ518164 
Troglosiro juberthiei DNA100344 New Caledonia −22.0500, 166.4667 DQ825540 EU887121 EU887077 EU887047 – 
Troglosiro longifossa DNA100867 New Caledonia −22.3527, 166.9736 DQ518089 DQ825582 DQ518084 DQ825639 DQ518165 
Troglosiro monteithi DNA101580 New Caledonia −21.6000, 165.7167 EU887101 EU887116 EU887074 EU887043 – 
Troglosiro ninqua DNA100577 New Caledonia −21.7500, 166.1500 DQ518088 DQ825581 DQ518055 DQ518128 – 
Troglosiro urbanus DNA101710 New Caledonia −22.1945, 166.5017 EU887102 EU887119 EU887073 EU887040 JF786340 
Troglosiro wilsoni DNA102324 New Caledonia −22.1770, 166.5106 EU887107 EU887125 EU887075 EU887061 – 
FAMILY STYLOCELLIDAE         
Fangensis insulanus DNA100388, DNA101063 Thailand 7.885, 98.43694 GQ488337 DQ825551 – GQ488181 – 
Fangensis spelaeus DNA100669 Thailand 14.29972, 98.98306 DQ133712 DQ825554 GQ488195 AY639583 AY639460 
Leptopsalis lydekkeri DNA101064 New Guinea, Indonesia −2.71667, 134.5* DQ133717 GQ488439 – GQ488153 – 
Leptopsalis novaguinea DNA101510 New Guinea, Indonesia −0.8333, 134.0333* GQ488322 GQ488451 GQ488230 – – 
Leptopsalis sp. DNA101514 Borneo, Malaysia 1.76667, 110.31667 GQ488317 GQ488435 DQ825611 GQ488178 GQ488114 
Leptopsalis sp. DNA101932 Java, Indonesia −6.79833, 107.01583 GQ488264 GQ488382 GQ488206 GQ488144 GQ488121 
Leptopsalis sp. DNA101944, DNA101945 Java, Indonesia −6.75694, 106.52333 GQ488267 GQ488385 GQ488226 GQ488146 GQ488123 
Leptopsalis sp. DNA101093, DNA100496 Thailand 6.67, 101.15* GQ488283 GQ488402 GQ488221 GQ488137 – 
Leptopsalis sp. DNA101483 Malaysia 4.39694, 102.43056 DQ825532 GQ488454 DQ825610 GQ488182 GQ488128 
Leptopsalis sp. DNA101489 Malaysia 3.71639, 101.73861 DQ518095 GQ488456 DQ518087 GQ488184 – 
Leptopsalis sp. DNA101930 Java, Indonesia −6.74, 107.01278 GQ488262 GQ488380 GQ488204 – GQ488119 
Leptopsalis sp. DNA101937 Sulawesi, Indonesia 1.49028, 125.15278 GQ488298 GQ488422 GQ488211 GQ488167 GQ488132 
Leptopsalis sp. DNA101938 Sulawesi, Indonesia −5.0425, 119.73556 GQ488299 GQ488359 GQ488212 GQ488168 GQ488133 
Leptopsalis sp. DNA102032 Sumatra, Indonesia −0.10583, 100.66389 GQ488308 GQ488361 GQ488188 GQ488171 GQ488134 
Leptopsalis sp. DNA102033, DNA102048 Sumatra, Indonesia 0.34611, 100.06917 GQ488307 GQ488428 – GQ488170 – 
Leptopsalis sp. DNA102039 Sumatra, Indonesia −0.94583, 100.54361 GQ488250 GQ488433 GQ488190 GQ488175 – 
Leptopsalis sp. DNA102042 Sumatra, Indonesia 3.22111, 98.49722 GQ488314 GQ488434 GQ488213 GQ488176 GQ488136 
Leptopsalis sp. DNA102061 Sumatra, Indonesia −0.47722, 100.35389 GQ488312 GQ488432 – GQ488174 GQ488135 
Leptopsalis sp. DNA103250 Thailand 9.76667, 98.41389 GQ488278 GQ488394 GQ488192 GQ488155 – 
Meghalaya sp. DNA101094, DNA101500 Thailand 7.88528, 98.43722 DQ825534 GQ488352 – GQ488158 GQ488127 
Meghalaya sp. DNA101494, DNA101506, DNA101765 Thailand 9.91806, 98.94278 DQ825530 GQ488398 – DQ825632 – 
Meghalaya sp. DNA101767 Thailand 6.97, 100.10* GQ488276 GQ488390 – GQ488154 – 
Meghalaya sp. DNA102051 India 25.50778, 90.23167 GQ488261 GQ488379 – – GQ488118 
Meghalaya sp. DNA103242, DNA103243, DNA103244 China 27.68833, 98.27778 GQ488233 GQ488377 GQ488219 – GQ488117 
Meghalaya sp. DNA103251 Thailand 9.76667, 98.41389 GQ488280 GQ488396 GQ488196 – – 
Meghalaya sp. DNA103265 Thailand 14.25, 101.98* GQ488239 GQ488392 – – – 
Miopsalis sp. DNA101519 Borneo, Indonesia 0.64, 117.09* DQ825526 GQ488436 GQ488228 GQ488180 GQ488115 
Miopsalis sp. DNA103259 Borneo, Malaysia 5.81, 116.24* GQ488260 GQ488375 GQ488193 GQ488142 GQ488116 
Miopsalis sp. DNA101468, DNA101950 Borneo, Indonesia 0.64, 117.09* GQ488328 GQ488444 – – – 
Miopsalis sp. DNA101517 Borneo, Indonesia 1.06667, 117.83333* DQ825527.1 DQ825564 – GQ488179 DQ825508.1 
Miopsalis sp. DNA102032, DNA102053, DNA102058 Sumatra, Indonesia −0.10583, 100.66389 GQ488305 GQ488425 – – – 
Miopsalis sp. DNA103249 Borneo, Malaysia 6.01, 116.53* GQ488252 GQ488367 GQ488194 GQ488139 – 
Miopsalis sp. DNA103254 Borneo, Malaysia 1.75833, 110.32972 GQ488257 GQ488371 – – – 
Miopsalis sp. DNA104981 Mindanao, Philippines 6.48, 125.09* HQ593868 HQ593869 – HQ593870 HQ593871 
FAMILY NEOGOVEIDAE         
Brasilogovea sp. DNA101665 Colombia 0.17972, −72.62333 JF934963 JF935011 JF935028 JF786414 JF786430 
Brasilogovea’ sp. Tobogan DNA100869 Venezuela 5.65000, −67.63333 DQ825545 DQ825600 DQ825617 – – 
Canga renatae DNA105680 Brazil −6.41055, −50.32319 JF934964 JF934997 JF935029 JF786395 JF786420 
Huitaca ventralis DNA101674 Colombia 7.41667, −72.43333 JF934980 JF935014 – JF786399 – 
Huitaca sp. DNA101683 Colombia 3.55833, −76.58278 JF934979 JF935016 – JF786396 JF786421 
Huitaca sp. DNA101407 Colombia 5.77956, −73.45377 DQ518090 DQ825596 DQ518050 DQ518129 DQ518167 
Huitaca sp. DNA101681 Colombia 5.09956, −75.40594 JF934977 JF935015 JF935032 JF786397 JF786422 
Huitaca sp. DNA102150 Colombia 3.55833, −76.58278 JF934981 JF935012 JF935033 – JF786423 
Huitaca sp. DNA104646 Colombia 3.55833, −76.58278 JF934982 JF935017 JF935030 – – 
Huitaca sp. DNA101671 Colombia 7.41667, −72.43333 JF934978 JF935013 JF935031 JF786398 JF786424 
Metagovea sp. DNA101680 Colombia 5.09542, −75.39075 JF934972 JF934999 JF935036 JF786400 – 
Metagovea sp. DNA104647 Colombia 3.55833, −76.58278 JF934988 JF935003 JF935037 – – 
Metagovea spDNA104648 Colombia 3.55833, −76.58278 JF934989 JF935004 JF935038 – – 
Metagovea sp. DNA101408 Colombia −4.04495, −69.98979 DQ825543 DQ825598 DQ825618 – DQ825514 
Metagovea sp. DNA101410 Colombia 1.28500, −78.07367 DQ518091 DQ825597 JF935034 GQ912860 DQ518168 
Metagovea sp. DNA101654 Colombia 1.25, −78.25* JF934970 JF935000 JF935035 JF786401 JF786425 
Metagovea sp. DNA102151 Colombia 5.48583, −76.01667 JF934971 JF935001 – JF786402 – 
Metagovea sp. DNA101685 Colombia 3.56889, −76.58861 JF934973 JF934998 – JF786403 – 
Metagovea sp. DNA101670 Colombia 1.61639, −76.10417 JF934984–5 JF935002 – – – 
Metagovea sp. DNA101409 Colombia 1.28500, −78.07367 DQ825544 DQ825599 DQ825619 DQ825646 JF786426 
Metagovea sp. DNA101642 Colombia 3.55833, −76.58278 JF934986 JF935006 JF935042 – – 
Metagovea sp. DNA101686 Colombia 3.56889, −76.58861 JF934987 JF935005 – JF786404 – 
Metagovea sp. DNA105826 Guyana 1.33655, −58.96510 JF934983 JF935010 JF935041 JF786408 – 
Metasiro americanus DNA101532 Florida, USA 30.56489, −84.95163 DQ825542 DQ825595 DQ825616 DQ825645 DQ825513 
Metasiro americanus DNA105644 South Carolina, USA 35.06231, −82.795 JF934961 JF934995 – JF786393 JF786418 
Metasiro americanus DNA105645 South Carolina, USA 32.18923, −81.08 JF934962 JF934996 JF935027 JF786394 JF786419 
Neogovea virginie DNA104823 French Guiana 4.19511, −52.14936 JF934974 JF935007 – JF786405 – 
Neogovea virginie DNA105824 French Guiana 4.08813, −52.67520 JF934975 JF935008 JF935039 JF786406 – 
Neogovea sp. DNA105825 Guyana 1.38803, −58.94632 JF934976 JF935009 JF935040 JF786407 – 
Parogovia gabonica DNA104620 Gabon 0.50448, 12.79525 JF934969 JF935019 JF935047 JF786411 – 
Parogovia sironoides DNA101059 Bioko, Equatorial Guinea 3.72570, 8.83828 DQ518092 DQ825606 DQ518051 DQ518131 DQ518169 
Parogovia sironoides DNA101061 Bioko, Equatorial Guinea 3.70284, 8.87520 DQ825550 DQ825607 JF935043 DQ825650 DQ825519 
Parogovia cf. sironoides DNA100462 Equatorial Guinea 2.18305, 9.80305 AY639493 DQ825603 – – AY639459 
Parogovia cf. sironoides DNA101053 Equatorial Guinea 1.65815, 10.31143 DQ825548 DQ825604 DQ825623 – DQ825517 
Parogovia cf. sironoides DNA101056 Equatorial Guinea 1.44858, 9.78086 DQ825549 DQ825605 DQ825624 DQ825650 DQ825518 
Parogovia cf. sironoides DNA104619 Cameroon 2.74108, 9.88181 JF934967 JF935022 JF935045 JF786409 JF786428 
Parogovia sp. DNA101052 Equatorial Guinea 1.65815, 10.31143 DQ825546 DQ825601 DQ825620 DQ825648 DQ825515 
Parogovia sp. DNA101057 Equatorial Guinea 2.13119, 9.87187 DQ825547 DQ825602 DQ825621 – DQ825516 
Parogovia sp. DNA104615 Cameroon 4.80084, 9.66326 JF934966 JF935021 JF935044 JF786410 JF786427 
Parogovia sp. DNA104618 Cameroon 2.74108, 9.88181 JF934968 JF935020 JF935046 JF786412 JF786429 
Parogovia sp. DNA105671 Ivory Coast 5.83333, −7.35000* JF934965 JF935018 JF935048 JF786413 – 
OUTGROUPS         
Protolophus singularis DNA101033 California, USA  EF028095 EF028096 EF108581 EF108586 EF108592 
Megalopsalis spDNA100783 SI, New Zealand  EF108573 EF108576 EF108582 EF108587 EF108593 
Hesperonemastoma modestum DNA100312 Oregon, USA  AF124942 EF108577 EF108583 EF108588 EF108594 
Dendrolasma parvulum DNA100318 Japan  EF108574 EF108578 EF108584 EF108589 – 
Equitius doriae DNA100607 Australia  U37003 EF108579 – EF108590 EF108595 
Sandokan malayanus DNA100321 Malaysia  EF108575 EF108580 EF108585 EF108591 EF108596 
 Voucher Locality Coordinates 18S rRNA 28S rRNA 16S rRNA COI H3 
FAMILY PETTALIDAE         
Aoraki calcarobtusa westlandica DNA101129 New Zealand −41.78387, 172.36903 EU673626 DQ518038 DQ518070 EU673667 EU673703 
Aoraki crypta DNA101289 New Zealand −37.53404, 175.74140 DQ518000 DQ518043 DQ518068 DQ518120 DQ518156 
Aoraki denticulata denticulata DNA100955 New Zealand −42.09283, 171.34096 EU673618 EU673654 EU673584 DQ992309 EU673698 
Aoraki denticulata major DNA100959 New Zealand −43.03408, 171.76464 EU673620 EU673656 EU673585 DQ992203 EU673700 
Aoraki granulosa DNA101841 New Zealand −39.93478, 175.64046 DQ517999 DQ518039 DQ518071 – – 
Aoraki healyi DNA100940 New Zealand −41.08673, 174.13826 DQ518002 DQ518042 DQ518067 DQ518122 DQ518160 
Aoraki inerma DNA100966 New Zealand −38.79686, 177.12472 EU673622 EU673658 – – EU673702 
Aoraki longitarsa DNA101806 New Zealand −43.73666, 170.09222 EU673613 EU673652 – DQ992313 EU673695 
Aoraki cf. tumidata DOC094 New Zealand −39.667, 175.637* EU673614 – – DQ992318 – 
Aoraki sp. DNA101126 New Zealand −41.08708, 174.13709 EU673624 EU673659 – DQ992319 – 
Austropurcellia arcticosa DNA100951 Queensland, Australia −16.16610, 145.41560 DQ517984 DQ518023 – DQ518111 DQ518147 
Austropurcellia daviesae DNA100947 Queensland, Australia −17.24560, 145.64207 DQ517985 DQ518024 – DQ518112 DQ518148 
Austropurcellia forsteri DNA100945 Queensland, Australia −16.06151, 145.46217 DQ517983 DQ518022 DQ518064 DQ518110 DQ518146 
Austropurcellia scoparia DNA100946 Queensland, Australia −16.59458, 145.27927 DQ517982 DQ518021 DQ518065 DQ518108 EU673678 
Chileogovea oedipus DNA100413 Chile −41.50833, −72.61666 DQ133721 DQ133733 DQ518055 DQ133745 – 
Chileogovea sp. DNA100490 Chile −39.66666, −73.28333* DQ133722 DQ133734 DQ518054 DQ133746 EU673672 
Karripurcellia harveyi DNA101303 Western Australia −34.49500, 115.97527 DQ517980 DQ518019 DQ518062 DQ518106 DQ518143 
Neopurcellia salmoni DNA100939 New Zealand −44.10780, 169.35527 DQ517998 EU673650 DQ518066 DQ825638 EU673694 
Parapurcellia monticola DNA100386 South Africa −29.05347, 29.38516 DQ518973 DQ518009 – DQ518098 DQ518135 
Parapurcellia silvicola DNA100385 South Africa −28.74421, 31.13763 AY639494 DQ518008 DQ518053 AY639582 DQ518136 
Pettalus thwaitesi DNA101223 Sri Lanka 7.27251, 80.59333 EU673592 EU673633 EU673569 EU673666 EU673677 
Pettalus sp. DNA101282 Sri Lanka 7.38483, 80.81696 DQ825537 EU673632 – DQ825636 EU673676 
Pettalus sp. DNA101283 Sri Lanka 7.38483, 80.81696 DQ517974 DQ518016 DQ518056 DQ518100 DQ518137 
Pettalus sp. DNA101285 Sri Lanka 6.92517, 80.81949 DQ517976 DQ518017 DQ518058 DQ518102 DQ518139 
Pettalus sp. DNA101286 Sri Lanka 6.92517, 80.81949 DQ517977 DQ518013 DQ518059 DQ518103 DQ518140 
Pettalus sp. DNA101287 Sri Lanka 6.82359, 80.84996 DQ517978 DQ518014 DQ518060 DQ518104 DQ518141 
Pettalus sp. DNA101288 Sri Lanka 6.55551, 80.37030 DQ517979 DQ518015 DQ518061 DQ518105 DQ518142 
Purcellia illustrans DNA100387 South Africa −33.98294, 18.42464 EU673589 EU673629 DQ518052 EU673665 EU673673 
Rakaia antipodiana DNA100957 New Zealand −43.25145, 171.36761 DQ517988 DQ518031 DQ518072 DQ518115 DQ518151 
Rakaia dorothea DNA100943 New Zealand −41.28163, 174.90961 DQ517990 DQ518033 DQ518077 DQ992331 – 
Rakaia florensis DNA101295 New Zealand −40.83258, 172.96896 DQ517986 DQ518025 DQ518083 DQ518113 DQ518149 
Rakaia lindsayi DNA101128 New Zealand −46.89327, 168.10398 DQ517995 DQ518027 DQ518081 DQ518118 DQ518154 
Rakaia macra DNA101808 New Zealand −45.92000, 170.02805 EU673596 EU673636 EU673571 EU673668 – 
Rakaia magna australis DNA100962 New Zealand −42.33225, 172.17126 EU673601 EU673640 EU673575 DQ992333 EU673684 
Rakaia media DNA101292 New Zealand −39.93478, 175.64046 DQ517996 DQ518030 DQ518074 DQ518125 DQ518157 
Rakaia minutissima DNA101291 New Zealand −39.41641, 175.21858 DQ517987 DQ518026 DQ518082 DQ518114 DQ518150 
Rakaia pauli DNA100968 New Zealand −44.70073, 170.96557 DQ517992 DQ518032 DQ518073 EU673670 DQ518161 
Rakaia solitaria DNA101294 New Zealand −41.46852, 175.44885 DQ517997 DQ518029 DQ518075 DQ518119 DQ518155 
Rakaia sorenseni sorenseni DNA100969 New Zealand −46.10967, 167.69034 DQ517993 DQ518036 DQ518079 DQ518116 DQ518153 
Rakaia sorenseni digitata DNA100970 New Zealand −46.58177, 169.20901 DQ517989 DQ518035 DQ518078 DQ518123 DQ518162 
Rakaia stewartiensis DNA100944 New Zealand −46.89327, 168.10398 DQ517994 DQ518028 DQ518080 DQ518117 – 
Rakaia uniloca DNA101812 New Zealand −41.22083, 173.43944 EU673599 EU673638 – EU673671 – 
Rakaia sp. DNA101297 New Zealand −40.97595, 175.11747 EU673608 EU673647 EU673579 DQ992344 EU673691 
Rakaia sp. DNA101807 New Zealand −45.90166, 169.46277 EU673606 EU673645 – – EU673689 
Rakaia sp. DNA100958 New Zealand −43.80869, 173.02144 EU673597 EU673637 EU673573 DQ992349 EU673681 
Rakaia sp. DNA101293 New Zealand −40.85181, 174.93233 EU673610 EU673649 EU673581 DQ992322 EU673693 
Rakaia sp. DNA100954 New Zealand −41.15757, 175.02168 EU673603 EU673642 EU673576 DQ992348 EU673686 
FAMILY SIRONIDAE         
Cyphophthalmus corfuanus DNA102111 Greece 39.61056, 20.33944 FJ946390 FJ946415 FJ946364 FJ946438 – 
Cyphophthalmus duricorius DNA100487 Slovenia 46.01667, 14.66667 AY639461 DQ513120 AY639526 AY639556 – 
Cyphophthalmus ere DNA100499 Serbia 43.83333, 20.05 AY639462 DQ825593 AY639527 AY639557 AY639444 
Cyphophthalmus cf. gjorgjevici DNA100498 Macedonia 41.96667, 21.35 AY639464 DQ825587 AY639529 AY639559 – 
Cyphophthalmus gordani DNA100495 Montenegro 42.45, 19.26667 AY639467 DQ825592 AY639532 – AY639446 
Cyphophthalmus hlavaci DNA102099 Croatia 43.41344, 16.91244 FJ946384 FJ946409 FJ946358 FJ946433 – 
Cyphophthalmus markoi DNA100497 Macedonia 41.41667, 22.26667 AY639469 AY639504 AY639534 AY639561 AY639447 
Cyphophthalmus martensi DNA100494 Montenegro 42.4, 18.76667 AY639471 DQ825589 AY639536 AY639563 AY639449 
Cyphophthalmus minutus DNA100493 Montenegro 42.65, 18.66667 AY639473 DQ825591 AY639537 AY639565 AY639450 
Cyphophthalmus ognjenovici DNA101039 Bosnia & Herzegovina 43.01667, 18.51667 AY639475 DQ825594  AY639567 AY639451 
Cyphophthalmus rumijae DNA100492 Montenegro 42.16667, 19.33333 AY639477 DQ825588 AY639539 AY639569 AY639453 
Cyphophthalmus serbicus DNA102098 Serbia 43.27917, 22.06389 FJ946383 FJ946408 FJ946357 FJ946432 – 
Cyphophthalmus teyrovskyi DNA100910 Montenegro 42.23333, 19.06667 AY639482 DQ513118 AY639544 AY639571 AY639454 
Cyphophthalmus trebinjanus DNA101038 Bosnia & Herzegovina 42.23333, 19.16667 AY639483 DQ513119  AY639572 – 
Cyphophthalmus zetae DNA100907 Montenegro 42.93333, 18.5 AY639485 AY639515 AY639546 AY639574 AY639456 
Paramiopsalis eduardoi DNA101878 Spain 43.41718, −8.06356 EU638284 EU638287 EU638281 EU638288 JF786415 
Paramiopsalis ramulosus DNA100459 Spain 42.31580, −8.48697 AY639489 DQ513121 AY639550 DQ825641 – 
Paramiopsalis ramulosus DNA103538 Portugal 41.56944, −8.14027 JF934956 JF934990 JF935023 JF786389 – 
Paramiopsalis sp. DNA104624 Spain 43.31968, −6.87282 JF934957 JF934991 JF935024 JF786390 JF786416 
Parasiro coiffaiti DNA101383 Spain 42.15251, 1.93039 AY918872 DQ513122 AY918877 DQ825642 AY918882 
Parasiro minor DNA103535 Sardinia, Italy 40.43047, 9.00948 JF934958 JF934992 JF935025 JF786391 – 
Siro acaroides DNA100488 Oregon, USA 44.5833, −123.5166* AY639490 DQ513128 AY639551 DQ825643 – 
Siro boyerae DNA101614 Washington, USA 46.99221, −121.84641 DQ513139 DQ513125 – DQ513112 – 
Siro calaveras DNA101623 California, USA 38.27744, −120.30543 DQ513146 DQ513133* – – – 
Siro exilis DNA100489 Maryland, USA 39.4833, −79.4333 AY639491 DQ825585 – AY639579  
Siro cf. kamiakensis DNA101611 Idaho, USA 47.74646, −116.70207 DQ513147 DQ513134* – DQ513115 – 
Siro kamiakensis DNA101613 Idaho, USA 46.86777, −117.15777 JF934959 JF934993 – – – 
Siro rubens DNA100457 France 44.08338, 3.58140 AY428818 DQ825584 – DQ513111 – 
Siro shasta DNA101622 California, USA 41.06367, −122.36045 DQ513149 DQ513136* – – – 
Siro valleorum DNA100461 Italy 45.9833, 9.8666* AY639492 DQ513123 AY639552 AY639580 AY639457.1 
Suzukielus sauteri DNA101543 Japan 35.63440, 139.24122 DQ513138 DQ513116 DQ518086 DQ513108 DQ518166 
Suzukielus sauteri DNA101550 Japan 34.83333, 138.93166 DQ825541 DQ825583 DQ825615 DQ825640 DQ825520 
FAMILY OGOVEIDAE         
Ogovea cameroonensis DNA104617 Cameroon 3.64621, 11.29079 JF934960 JF934994 JF935026 JF786392 JF786417 
FAMILY TROGLOSIRONIDAE         
Troglosiro aelleni DNA100345 New Caledonia −21.1833, 165.3059 AY639497 DQ825580 AY639555 AY639584 DQ518164 
Troglosiro juberthiei DNA100344 New Caledonia −22.0500, 166.4667 DQ825540 EU887121 EU887077 EU887047 – 
Troglosiro longifossa DNA100867 New Caledonia −22.3527, 166.9736 DQ518089 DQ825582 DQ518084 DQ825639 DQ518165 
Troglosiro monteithi DNA101580 New Caledonia −21.6000, 165.7167 EU887101 EU887116 EU887074 EU887043 – 
Troglosiro ninqua DNA100577 New Caledonia −21.7500, 166.1500 DQ518088 DQ825581 DQ518055 DQ518128 – 
Troglosiro urbanus DNA101710 New Caledonia −22.1945, 166.5017 EU887102 EU887119 EU887073 EU887040 JF786340 
Troglosiro wilsoni DNA102324 New Caledonia −22.1770, 166.5106 EU887107 EU887125 EU887075 EU887061 – 
FAMILY STYLOCELLIDAE         
Fangensis insulanus DNA100388, DNA101063 Thailand 7.885, 98.43694 GQ488337 DQ825551 – GQ488181 – 
Fangensis spelaeus DNA100669 Thailand 14.29972, 98.98306 DQ133712 DQ825554 GQ488195 AY639583 AY639460 
Leptopsalis lydekkeri DNA101064 New Guinea, Indonesia −2.71667, 134.5* DQ133717 GQ488439 – GQ488153 – 
Leptopsalis novaguinea DNA101510 New Guinea, Indonesia −0.8333, 134.0333* GQ488322 GQ488451 GQ488230 – – 
Leptopsalis sp. DNA101514 Borneo, Malaysia 1.76667, 110.31667 GQ488317 GQ488435 DQ825611 GQ488178 GQ488114 
Leptopsalis sp. DNA101932 Java, Indonesia −6.79833, 107.01583 GQ488264 GQ488382 GQ488206 GQ488144 GQ488121 
Leptopsalis sp. DNA101944, DNA101945 Java, Indonesia −6.75694, 106.52333 GQ488267 GQ488385 GQ488226 GQ488146 GQ488123 
Leptopsalis sp. DNA101093, DNA100496 Thailand 6.67, 101.15* GQ488283 GQ488402 GQ488221 GQ488137 – 
Leptopsalis sp. DNA101483 Malaysia 4.39694, 102.43056 DQ825532 GQ488454 DQ825610 GQ488182 GQ488128 
Leptopsalis sp. DNA101489 Malaysia 3.71639, 101.73861 DQ518095 GQ488456 DQ518087 GQ488184 – 
Leptopsalis sp. DNA101930 Java, Indonesia −6.74, 107.01278 GQ488262 GQ488380 GQ488204 – GQ488119 
Leptopsalis sp. DNA101937 Sulawesi, Indonesia 1.49028, 125.15278 GQ488298 GQ488422 GQ488211 GQ488167 GQ488132 
Leptopsalis sp. DNA101938 Sulawesi, Indonesia −5.0425, 119.73556 GQ488299 GQ488359 GQ488212 GQ488168 GQ488133 
Leptopsalis sp. DNA102032 Sumatra, Indonesia −0.10583, 100.66389 GQ488308 GQ488361 GQ488188 GQ488171 GQ488134 
Leptopsalis sp. DNA102033, DNA102048 Sumatra, Indonesia 0.34611, 100.06917 GQ488307 GQ488428 – GQ488170 – 
Leptopsalis sp. DNA102039 Sumatra, Indonesia −0.94583, 100.54361 GQ488250 GQ488433 GQ488190 GQ488175 – 
Leptopsalis sp. DNA102042 Sumatra, Indonesia 3.22111, 98.49722 GQ488314 GQ488434 GQ488213 GQ488176 GQ488136 
Leptopsalis sp. DNA102061 Sumatra, Indonesia −0.47722, 100.35389 GQ488312 GQ488432 – GQ488174 GQ488135 
Leptopsalis sp. DNA103250 Thailand 9.76667, 98.41389 GQ488278 GQ488394 GQ488192 GQ488155 – 
Meghalaya sp. DNA101094, DNA101500 Thailand 7.88528, 98.43722 DQ825534 GQ488352 – GQ488158 GQ488127 
Meghalaya sp. DNA101494, DNA101506, DNA101765 Thailand 9.91806, 98.94278 DQ825530 GQ488398 – DQ825632 – 
Meghalaya sp. DNA101767 Thailand 6.97, 100.10* GQ488276 GQ488390 – GQ488154 – 
Meghalaya sp. DNA102051 India 25.50778, 90.23167 GQ488261 GQ488379 – – GQ488118 
Meghalaya sp. DNA103242, DNA103243, DNA103244 China 27.68833, 98.27778 GQ488233 GQ488377 GQ488219 – GQ488117 
Meghalaya sp. DNA103251 Thailand 9.76667, 98.41389 GQ488280 GQ488396 GQ488196 – – 
Meghalaya sp. DNA103265 Thailand 14.25, 101.98* GQ488239 GQ488392 – – – 
Miopsalis sp. DNA101519 Borneo, Indonesia 0.64, 117.09* DQ825526 GQ488436 GQ488228 GQ488180 GQ488115 
Miopsalis sp. DNA103259 Borneo, Malaysia 5.81, 116.24* GQ488260 GQ488375 GQ488193 GQ488142 GQ488116 
Miopsalis sp. DNA101468, DNA101950 Borneo, Indonesia 0.64, 117.09* GQ488328 GQ488444 – – – 
Miopsalis sp. DNA101517 Borneo, Indonesia 1.06667, 117.83333* DQ825527.1 DQ825564 – GQ488179 DQ825508.1 
Miopsalis sp. DNA102032, DNA102053, DNA102058 Sumatra, Indonesia −0.10583, 100.66389 GQ488305 GQ488425 – – – 
Miopsalis sp. DNA103249 Borneo, Malaysia 6.01, 116.53* GQ488252 GQ488367 GQ488194 GQ488139 – 
Miopsalis sp. DNA103254 Borneo, Malaysia 1.75833, 110.32972 GQ488257 GQ488371 – – – 
Miopsalis sp. DNA104981 Mindanao, Philippines 6.48, 125.09* HQ593868 HQ593869 – HQ593870 HQ593871 
FAMILY NEOGOVEIDAE         
Brasilogovea sp. DNA101665 Colombia 0.17972, −72.62333 JF934963 JF935011 JF935028 JF786414 JF786430 
Brasilogovea’ sp. Tobogan DNA100869 Venezuela 5.65000, −67.63333 DQ825545 DQ825600 DQ825617 – – 
Canga renatae DNA105680 Brazil −6.41055, −50.32319 JF934964 JF934997 JF935029 JF786395 JF786420 
Huitaca ventralis DNA101674 Colombia 7.41667, −72.43333 JF934980 JF935014 – JF786399 – 
Huitaca sp. DNA101683 Colombia 3.55833, −76.58278 JF934979 JF935016 – JF786396 JF786421 
Huitaca sp. DNA101407 Colombia 5.77956, −73.45377 DQ518090 DQ825596 DQ518050 DQ518129 DQ518167 
Huitaca sp. DNA101681 Colombia 5.09956, −75.40594 JF934977 JF935015 JF935032 JF786397 JF786422 
Huitaca sp. DNA102150 Colombia 3.55833, −76.58278 JF934981 JF935012 JF935033 – JF786423 
Huitaca sp. DNA104646 Colombia 3.55833, −76.58278 JF934982 JF935017 JF935030 – – 
Huitaca sp. DNA101671 Colombia 7.41667, −72.43333 JF934978 JF935013 JF935031 JF786398 JF786424 
Metagovea sp. DNA101680 Colombia 5.09542, −75.39075 JF934972 JF934999 JF935036 JF786400 – 
Metagovea sp. DNA104647 Colombia 3.55833, −76.58278 JF934988 JF935003 JF935037 – – 
Metagovea spDNA104648 Colombia 3.55833, −76.58278 JF934989 JF935004 JF935038 – – 
Metagovea sp. DNA101408 Colombia −4.04495, −69.98979 DQ825543 DQ825598 DQ825618 – DQ825514 
Metagovea sp. DNA101410 Colombia 1.28500, −78.07367 DQ518091 DQ825597 JF935034 GQ912860 DQ518168 
Metagovea sp. DNA101654 Colombia 1.25, −78.25* JF934970 JF935000 JF935035 JF786401 JF786425 
Metagovea sp. DNA102151 Colombia 5.48583, −76.01667 JF934971 JF935001 – JF786402 – 
Metagovea sp. DNA101685 Colombia 3.56889, −76.58861 JF934973 JF934998 – JF786403 – 
Metagovea sp. DNA101670 Colombia 1.61639, −76.10417 JF934984–5 JF935002 – – – 
Metagovea sp. DNA101409 Colombia 1.28500, −78.07367 DQ825544 DQ825599 DQ825619 DQ825646 JF786426 
Metagovea sp. DNA101642 Colombia 3.55833, −76.58278 JF934986 JF935006 JF935042 – – 
Metagovea sp. DNA101686 Colombia 3.56889, −76.58861 JF934987 JF935005 – JF786404 – 
Metagovea sp. DNA105826 Guyana 1.33655, −58.96510 JF934983 JF935010 JF935041 JF786408 – 
Metasiro americanus DNA101532 Florida, USA 30.56489, −84.95163 DQ825542 DQ825595 DQ825616 DQ825645 DQ825513 
Metasiro americanus DNA105644 South Carolina, USA 35.06231, −82.795 JF934961 JF934995 – JF786393 JF786418 
Metasiro americanus DNA105645 South Carolina, USA 32.18923, −81.08 JF934962 JF934996 JF935027 JF786394 JF786419 
Neogovea virginie DNA104823 French Guiana 4.19511, −52.14936 JF934974 JF935007 – JF786405 – 
Neogovea virginie DNA105824 French Guiana 4.08813, −52.67520 JF934975 JF935008 JF935039 JF786406 – 
Neogovea sp. DNA105825 Guyana 1.38803, −58.94632 JF934976 JF935009 JF935040 JF786407 – 
Parogovia gabonica DNA104620 Gabon 0.50448, 12.79525 JF934969 JF935019 JF935047 JF786411 – 
Parogovia sironoides DNA101059 Bioko, Equatorial Guinea 3.72570, 8.83828 DQ518092 DQ825606 DQ518051 DQ518131 DQ518169 
Parogovia sironoides DNA101061 Bioko, Equatorial Guinea 3.70284, 8.87520 DQ825550 DQ825607 JF935043 DQ825650 DQ825519 
Parogovia cf. sironoides DNA100462 Equatorial Guinea 2.18305, 9.80305 AY639493 DQ825603 – – AY639459 
Parogovia cf. sironoides DNA101053 Equatorial Guinea 1.65815, 10.31143 DQ825548 DQ825604 DQ825623 – DQ825517 
Parogovia cf. sironoides DNA101056 Equatorial Guinea 1.44858, 9.78086 DQ825549 DQ825605 DQ825624 DQ825650 DQ825518 
Parogovia cf. sironoides DNA104619 Cameroon 2.74108, 9.88181 JF934967 JF935022 JF935045 JF786409 JF786428 
Parogovia sp. DNA101052 Equatorial Guinea 1.65815, 10.31143 DQ825546 DQ825601 DQ825620 DQ825648 DQ825515 
Parogovia sp. DNA101057 Equatorial Guinea 2.13119, 9.87187 DQ825547 DQ825602 DQ825621 – DQ825516 
Parogovia sp. DNA104615 Cameroon 4.80084, 9.66326 JF934966 JF935021 JF935044 JF786410 JF786427 
Parogovia sp. DNA104618 Cameroon 2.74108, 9.88181 JF934968 JF935020 JF935046 JF786412 JF786429 
Parogovia sp. DNA105671 Ivory Coast 5.83333, −7.35000* JF934965 JF935018 JF935048 JF786413 – 
OUTGROUPS         
Protolophus singularis DNA101033 California, USA  EF028095 EF028096 EF108581 EF108586 EF108592 
Megalopsalis spDNA100783 SI, New Zealand  EF108573 EF108576 EF108582 EF108587 EF108593 
Hesperonemastoma modestum DNA100312 Oregon, USA  AF124942 EF108577 EF108583 EF108588 EF108594 
Dendrolasma parvulum DNA100318 Japan  EF108574 EF108578 EF108584 EF108589 – 
Equitius doriae DNA100607 Australia  U37003 EF108579 – EF108590 EF108595 
Sandokan malayanus DNA100321 Malaysia  EF108575 EF108580 EF108585 EF108591 EF108596 

Asterisks indicate approximate coordinates.

All sequence files for each gene were prepared with MacGDE (Linton, 2005). 18S rRNA sequence data were divided into six fragments and it was available for 170 terminals. The 28S rRNA fragment was divided into ten regions and was available for 169 terminals. 16S rRNA was divided into eight fragments and was available for 127 terminals. All the ribosomal genes were submitted to direct optimization or to multiple sequence alignment for homology assignment. The 143 COI sequences, unlike in many other organisms, show clade-specific considerable sequence length variation, and hence the gene was divided into seven fragments and analyzed under dynamic homology (Wheeler, 2005) or submitted to multiple sequence alignment. The histone H3 data were available for 108 terminals and were treated as prealigned in all analyses because they show no length variation.

Morphological data matrix

A morphological matrix of 62 characters was compiled for 161 taxa based in part on our previous studies (Giribet & Boyer, 2002; Giribet, 2003a; de Bivort & Giribet, 2004; Boyer & Giribet, 2007; de Bivort & Giribet, 2010), direct observation of specimens, mostly through scanning electron microscopy, and complemented by some new literature sources (Karaman, 2009). All 19 multistate characters were unordered. Spermatogenesis in Cyphophthalmi is a promising source of phylogenetic characters, as recently outlined by Alberti, Giribet & Gutjahr (2009; see also Juberthie & Manier, 1976; Juberthie, Manier & Boissin, 1976; Juberthie & Manier, 1978; Alberti, 1995, 2005), although taxon sampling is still sparse and these characters were not considered in this data set (G. Alberti & G. Giribet, unpubl. data). We did not have access to specimens of a few species that were included in the data matrix based entirely on literature sources. These have missing data for several characters, especially those observed through scanning electron microscopy, such as the prosomal sternal characters. These species include Ankaratra franziShear & Gruber, 1996, Manangotria taolanaroShear & Gruber, 1996, and Odontosiro lusitanicusJuberthie, 1961. Similarly, several Cyphophthalmus Joseph, 1868 species, included in our molecular matrix, were not scored for several morphological characters because males were never available for examination, and their published descriptions do not include scanning electron micrographs of the relevant characters and their descriptions and illustrations are inadequate for scoring those features. Finally, a few species scored in the matrix are not known for one gender, and therefore the corresponding scorings are missing. The total number of missing cells was thus 1798 (17% of cells). In the present study, we were not able to use morphometrics, as we have done in previous studies (Clouse, 2010; de Bivort et al., 2010; de Bivort & Giribet, 2010), as a result of the larger number of specimens based on literature sources and the lack of scanning electron micrographs of several species.

When selecting the morphological terminals, we attempted to maximize overlapping with the molecular matrix and also attempted to include the type species of each genus, with a few exceptions. All monotypic genera were also included, irrespective of whether molecular data were available or not. Monotypic genera not represented by molecular data are AnkaratraShear & Gruber, 1996, Iberosirode Bivort & Giribet, 2004, ManangotriaShear & Gruber, 1996, MarweShear, 1985, OdontosiroJuberthie, 1961, SpeleosiroLawrence, 1931, and Stylocellus. Similarly, Shearogovea mexasca, now not considered as a member of Neogoveidae or Neogovea (Benavides & Giribet, 2007; Giribet, 2011), is not represented by molecular data but was included in the combined analysis.

When a species was represented by multiple molecular terminals, the morphological data matrix was replicated so all molecular terminals were represented by the same morphological codings. This applies to the three populations of Metasiro americanus (Davis, 1933), the two specimens of Parogovia sironoides Hansen, 1921 and four specimens of P. cf. sironoides, the two specimens of Metagovea sp. (DNA104648 and DNA104647), two specimens of Neogovea virginie, and two specimens of Suzukielus sauteri (Roewer, 1916).

The annotated morphological data matrix has been deposited in Morphobank (morphobank.org) with accession number P199 (http://morphobank.org/permalink/?P199).

Phylogenetic analysis: dynamic homology under parsimony

Parsimony analysis under direct optimization (Wheeler, 1996) used the software POY, version 4.1.2 (Varón, Sy Vinh & Wheeler, 2010) on six processors on a Quad-Core Intel Xeon 3 GHz Mac Pro or on 40 processors in the Odyssey cluster at Harvard University FAS Research computing facility. Timed searches (multiple Wagner trees followed by SPR + TBR + ratchet and tree fusing) of 6–12 h each were run for the combined analyses of all molecules under six analytical parameter sets (see below). Two additional rounds of sensitivity analysis tree fusing (SATF) (Giribet, 2007a), taking all input trees from the previous round of analyses, were conducted for the combined analysis of molecules under the multiple parameter sets evaluated. These were also 6-h timed searches, and the results of these were plotted to check for stability in the results. Once a parameter set stabilized and the optimal result was found multiple times, we stopped that inquiry but continued with additional rounds of searches for those parameter sets that continued improving or that found the optimal solution only once. The results of these analyses are shown in Table 3.

Table 3

Search strategy and tree length stabilization after subsequent rounds of sensitivity analysis tree fusing (TFN) for each parameter set

 TF4 TF5 TF6 TF7 TF8 TF9 
111 27101 27074 27074 – – – 
121 41849 41773 41773 – – – 
211 28975 28944 28940 28940 – – 
221 45211 45179 45131 45118 45115 45115 
3221 55982 55744 55729 55729 – – 
3211 43121 42874 42854 42854 – – 
 TF4 TF5 TF6 TF7 TF8 TF9 
111 27101 27074 27074 – – – 
121 41849 41773 41773 – – – 
211 28975 28944 28940 28940 – – 
221 45211 45179 45131 45118 45115 45115 
3221 55982 55744 55729 55729 – – 
3211 43121 42874 42854 42854 – – 

111 and 121 stabilized after five rounds of tree fusing; 221 stabilized after eight rounds of tree fusing

Because a broad parameter space has already been explored in detail in earlier studies (Boyer et al., 2007b), we restricted the dynamic homology analyses to six parameter sets, named 111, 121, 211, 221, 3221, and 3211. Parameter set 3221 (indel opening cost = 3; indel extension cost = 1; transversions = transitions = 2) has been favoured in many analyses and has been justified philosophically as the best way of analyzing data under direct optimization (De Laet, 2010). In addition, we explored a parameter set, named 3211, where transversions and transitions receive different costs (indel opening cost = 3; indel extension cost = 1; transversion cost = 2; transition cost = 1), extending the idea of mixed-parameter sets of Sharma et al. (2011). Four other parameter sets 111, 121, 211, and 221, optimal in the analyses of Boyer et al. (2007b) and aiming to limit the difference between indel costs and transformation costs (Spagna & Álvarez-Padilla, 2008), were explored. To calculate the WILD (Wheeler, 1995; Sharma et al., 2011) each individual partition, or the combination of the two nuclear ribosomal RNA partitions, were run with a similar search strategy as described above with a 2-h timed search. The resulting WILD values are shown in Table 4.

Table 4

Tree lengths for different data partitions (rib, nuclear ribosomal genes; coi, cytochrome c oxidase subunit I; 16s, 16S rRNA; h3, histone H3; mol, all molecular partitions) analyzed and incongruence length differences (ILD) between the data sets

 rib coi 16s h3 Mol wILD 
111 5852 12315 6857 1449 27074 0.02220 
121 8846 18664 11350 1974 41773 0.02248 
211 6659 12502 7692 1449 28940 0.02205 
221 10312 18890 12897 1974 45115 0.02310 
3211 9268 18810 11861 1967 42851 0.02205 
3221 12212 24996 14397 2898 55713 0.02172 
 rib coi 16s h3 Mol wILD 
111 5852 12315 6857 1449 27074 0.02220 
121 8846 18664 11350 1974 41773 0.02248 
211 6659 12502 7692 1449 28940 0.02205 
221 10312 18890 12897 1974 45115 0.02310 
3211 9268 18810 11861 1967 42851 0.02205 
3221 12212 24996 14397 2898 55713 0.02172 

Parameter set 3221 (in italics) minimizes the ILD value.

A jackknife resampling analysis (Farris et al., 1996) with 1000 replicates and a probability of deletion of each character of 0.36 was applied to assess nodal support. Because resampling techniques may be meaningless under dynamic homology, different strategies can be applied. Dynamic characters can be converted to a static set, although this tends to inflate support values because it is based on the implied alignment that favours the topology. Instead, we resample characters that were static a priori (morphology and pre-aligned protein-encoding genes), as well as fragments of the dynamic characters by both using the number of fragments (eight fragments for 16S rRNA, six fragments for 18S rRNA, and ten fragments for 28S rRNA), as well as the command auto_sequence_partition, which evaluates each predetermined fragment. If a long region appears to have no indels, then the fragment is broken inside that region.

Phylogenetic analysis: probabilistic approaches

Maximum likelihood (ML) analyses were conducted on static alignments, which were inferred as follows. Sequences of ribosomal genes were aligned using MUSCLE, version 3.6 (Edgar, 2004) with default parameters, and subsequently treated with GBLOCKS, version 0.91b (Castresana, 2000) to cull positions of ambiguous homology. For these genes, indels were permitted within blocks. Sequences of the protein-encoding genes COI and histone H3 were aligned using MUSCLE, version 3.6 with default parameters as well, although alignments were confirmed using protein sequence translations before treatment with GBLOCKS, and no gaps were permitted within blocks (COI has length variation, so these regions were excluded in GBLOCKS). The size of data matrices for each gene before and subsequent to treatment with GBLOCKS is provided in the Appendix (Table A1).

ML analysis was conducted using RaxML, version 7.2.7 (Stamatakis, 2006) on 40 CPUs of a cluster at Harvard University, FAS Research Computing (http://rc.fas.harvard.edu/faq/odyssey). For the maximum likelihood searches, a unique GTR model of sequence evolution with corrections for a discrete gamma distribution (GTR +Γ) was specified for each data partition, and 500 independent searches were conducted. Nodal support was estimated via the rapid bootstrap algorithm (1000 replicates) using the GTR-CAT model (Stamatakis, Hoover & Rougemont, 2008), through the CIPRES, version 3, gateway, using the Abe Dell Intel 64 Linux teragrid cluster housed at the National Center for Supercomuting Applications (University of Illinois). Bootstrap resampling frequencies were thereafter mapped onto the optimal tree from the independent searches.

Estimation of divergence times

Ages of clades were inferred using BEAST, version 1.6.1 (Drummond et al., 2006; Drummond & Rambaut, 2007). We assigned the best fitting models (a GTR model of sequence evolution with corrections for a discrete gamma distribution and a proportion of invariant sites, GTR +Γ+ I) selected by MODELTEST, version 3.7 (Posada & Crandall, 1998; Posada, 2005) to each partition. Protein-encoding genes were partitioned into two sets by codon positions, separating third codon positions from the set of first and second positions. An uncorrelated lognormal clock model was inferred for each partition, and a Yule speciation process was assumed for the tree prior. We selected the uncorrelated lognormal model because its accuracy is comparable to an uncorrelated exponential model, although it has narrower 95% highest posterior density (HPD) intervals. Additionally, the variance of the uncorrelated lognormal model can better accommodate data that are already clock-like (Drummond et al., 2006). Priors were sequentially optimized in a series of iterative test runs (data not shown). Markov chains were run for 50 000 000 generations, sampling every 1000 generations. Convergence diagnostics were assessed using TRACER, version 1.5 (Rambaut & Drummond, 2007).

Fossil taxa were used to calibrate divergence times. We constrained the age of Eupnoi to 410 Mya using the Devonian harvestman Eophalangium sheari[Dunlop et al. 2004[Dunlop et al., 2003; 2004 (for 2003)]; a normal distribution with a standard deviation of 5 Myr was applied to this node to account for uncertainty in estimation of fossil age. Dyspnoi were constrained using a normal distribution with a mean of 300 Mya and a standard deviation of 10 Myr, on the basis of the Carboniferous fossils Eotrogulus fayoli Thevenin, 1901 and Nemastomoides elaveris Thevenin, 1901 (Dunlop, 2007).

We explored constraining the family Stylocellidae using the Early Cretaceous Burmese amber fossil Palaeosiro burmanicumPoinar, 2008 (Poinar, 2008)1. We used a gamma distribution with shape parameters (α, β) = (8, 14), and an offset of 105 Myr for the diversification of Stylocellidae; such a prior distribution establishes a floor in the age of stylocellids (105 Mya), at the same time enabling estimates of diversification as early as the Late Permian, in accordance with previous estimates (Boyer et al., 2007b; Clouse & Giribet, 2010). However, because the inclusion of this last constraint did not affect the age estimate of Stylocellidae, we ultimately did not include it in the analysis.

Ancestral area reconstruction

Likelihood analysis of ancestral area reconstruction was conducted using the software LAGRANGE (Ree et al., 2005; Ree & Smith, 2008). We divided the dated tree from BEAST analysis into three parts for analytical tractability: (1) the Pettalidae subtree; (2) the (Troglosironidae + Ogoveidae + Neogoveidae) subtree; and (3) the (Sironidae + Stylocellidae) subtree. For each subtree, we implemented stratified dispersal constraint matrices for multiple spans of time for the relevant areas inhabited by the constituent taxa of each subtree. Geological events used to delimit the time spans are sensuSanmartín & Ronquist (2004) and Hall (2002). The maximum number of areas in ancestral ranges was held at two (this convention reflects empirical observations of Cyphophthalmi species, the majority of which are narrowly distributed endemics), and dispersal constraints were set to 1.0 (if landmasses were connected), 0.1 (if landmasses were disjunct) or 0 (if landmasses did not exist). Areas and geological intervals for each subtree are indicated in the Appendix Table A2 (the Python scripts specifying dispersal constraint matrices are available upon request from the authors).

Habitat suitability and distribution modelling

To generate predictions of habitat suitability and potential lineage distributions, habitat suitability models (HSMs) of the major lineages of Cyphophthalmi were reconstructed using the 19 bioclimatic variables of Hijmans et al. (2005: http://www.worldclim.org/). These variables provide a summary of the monthly temperature and precipitation worldwide. These variables are well documented and are widely used in studies relaying on niche and distribution modelling (Evans et al., 2009; Smith & Donoghue, 2010). By contrast to the raw temperature and precipitation data, they do provide biologically relevant information. We have used all 19 variables at 10 arc minutes resolution. In addition, analyses with a subset of the environmental variables representing only the most important variables were performed (thus reducing the dimensionality of the analyses and the risk of over fitting) and the results obtained were compared. To evaluate the variables significance, we used jackknife (as implemented in MAXENT).

HSMs were built using the maximum entropy algorithm implemented in MAXENT, version 3.3.3a (Phillips, Anderson & Schapire, 2006; Phillips & Dudik, 2008). Maximum entropy has shown a high performance score in comparison with other methods (Araujo & Rahbek, 2006) and also allows working with fewer data points (Pearson et al., 2007). The total number of unique localities with occurrence observations used for the modelling of habitat suitability was: Pettalidae, N = 107; Sironidae, N = 60; Stylocellidae, N = 127; and Sternophthalmi, N = 90. To evaluate the performance of the model, cross-validation as implemented in MAXENT (ten replicates) was used in all runs.

To test the sensitivity of the results to the modelling algorithm, we have run the same set of analysis using the simpler BIOCLIM (Nix, 1986) profile method as implemented in openModeller, version 1.1.0 (de Souza Muñoz et al., 2011). Climatic envelopes' extent and distribution were modelled worldwide to compare the actual linage distributions with the distribution of potentially suitable climates.

The software package ENMTools, version 1.3 (Warren, Glor & Turelli, 2010) was used to access climatic envelopes' differentiation. ENMTools implements the I, Schoener's D and relative rank metrics to compare models predictions (Schoener, 1968; Warren, Glor & Turelli, 2008). The three indices measure similarity of predicted habitat suitability distributions and range from 0, indicating no overlap, to 1, indicating complete overlap. In addition, habitat suitability score differences were evaluated by comparing the similarity indices (models overlap) for the models built from the actual occurrences of the two species to a null distribution generated by nonparametric resampling. Comparisons were performed using the niche identity test (Warren et al., 2008) implemented in ENMTools.

RESULTS

Analysis of the combined molecular data matrix under selected parameter sets for direct optimization resulted in topologies that agree on several basic aspects of cyphophthalmid phylogeny, including monophyly of the suborder, a sister group relationship of Pettalidae to all other families, and a clade containing all members of the families Troglosironidae, Ogoveidae, and Neogoveidae. All parameter sets also resulted in very similar WILD numbers, with 3221 being slightly favoured above all others (WILD = 0.02172; the worst parameter set being 121, with WILD = 0.02248). Stabilization of parameter set 3221 occurred after nine rounds of tree fusing. The optimal tree, along with the Navajo rugs (Giribet, 2003b) for the familial monophyly and relationships, is presented in Figure 3. A clade containing the families Sironidae and Stylocellidae is also found under most analytical conditions (Fig. 3).

Figure 3

Phylogenetic tree based on the parsimony direct optimization analysis of molecular data under parameter set 3221 (55 713 weighted steps). Clade colours correspond to those in Fig. 2. Navajo rugs indicate monophyly (black) or non-monophyly (white) of a given node under the parameter set specified in the legend. Numbers above nodes indicate jackknife support values.

Figure 3

Phylogenetic tree based on the parsimony direct optimization analysis of molecular data under parameter set 3221 (55 713 weighted steps). Clade colours correspond to those in Fig. 2. Navajo rugs indicate monophyly (black) or non-monophyly (white) of a given node under the parameter set specified in the legend. Numbers above nodes indicate jackknife support values.

Monophyly of Pettalidae, Troglosironidae, Stylocellidae, and Ogoveoidea (= Ogoveidae + Neogoveidae) is supported under every analyzed parameter set, as are many internal clades within the families Stylocellidae, Sironidae, and Neogoveidae. However, Sironidae is not monophyletic under any parameter set when combining all data (Sironidae is monophyletic when nuclear ribosomal genes are analyzed alone). In this case, a clade containing the genera Siro, Paramiopsalis, and Cyphophthalmus is stable to parameter variation, although Parasiro and Suzukielus often appear at the base of Stylocellidae, or as sister to a clade including the families Stylocellidae, Troglosironidae, Ogoveidae, and Neogoveidae (parameter set 3211). The North American Siro and the European Siro form reciprocally monophyletic groups and this clade is sister to Paramiopsalis+Cyphophthalmus. In the case of Neogoveidae, most parameter sets find Metasiro to be the sister genus to all other neogoveids but, under parameter sets 111 and 211, Ogovea appears as sister to the African genus Parogovia, both forming the sister clade to Metasiro. These are the only parameter sets that find monophyly of the South American neogoveids, with Canga as sister genus to all other South American genera. All other parameter sets instead support monophyly of Neogoveidae, Metasiro as the sister genus to all other species, the Brazilian genus Canga as sister to the African genus Parogovia, and the stable relationship of ((Brasilogovea, Neogovea) (Huitaca, Metagovea)). Relationships of Stylocellidae are well resolved, as: (Fangensis (Meghalaya (Miopsalis, Leptopsalis))). Although all pettalid genera are supported, their relationships remain unstable to parameter set variation, and stable are only the sister group relationships of Purcellia to ChileogoveaRoewer, 1961 and of Karripurcellia Giribet, 2003 to Pettalus. Two genera appear as candidate sister groups to all other pettalids, the South African genus Parapurcellia Rosas Costa, 1950 or the north-eastern Australian endemic Austropurcellia Juberthie, 1988. Jackknife support values for the pettalid generic relationships are, for the most part, below 50%.

The maximum likelihood analysis resulted in a tree topology with lnL = −103 563.078879. The likelihood tree topology (Fig. 4) is largely comparable to results from parsimony analyses but notably recovers a monophyletic Sironidae (i.e. including the genera Parasiro and Suzukielus), albeit with low nodal support (BS = 44%). As in the direct optimization optimal tree, Parapurcellia is sister to all other pettalid genera, and Purcellia+Chileogovea form a supported clade (66% bootstrap support; BS), whereas Karripurcellia and Pettalus form a clade without significant nodal support. No other generic relationships find high support. Troglosironidae is sister to Ogoveoidea (84% BS), and the structure of Neogoveidae is almost identical to that of the optimal direct optimization tree, with the exception that Brasilogovea is here monophyletic (the sequences for one terminal are based on a juvenile specimen, so the assignment to this genus is tentative). Within Sironidae, Parasiro is sister to all other genera, followed by Suzukielus, although bootstrap support for these basal nodes is low, as is the clade including the remaining sironid genera. In this case, there is also reciprocal monophyly of the European and North American Siro, and these form the sister group of Paramiopsalis+Cyphophthalmus. Structure of the genera within Stylocellidae matches that of the direct optimization analyses.

Figure 4

Single most likely tree (lnL = −103 563.078879) for the combined molecular data set aligned using MUSCLE and subsequently trimmed with GBLOCKS and analyzed in RAxML under GTR +Γ. Clade colours correspond to those in Fig. 2. Bootstrap support values are represented above each node; asterisks indicate 100% bootstrap value.

Figure 4

Single most likely tree (lnL = −103 563.078879) for the combined molecular data set aligned using MUSCLE and subsequently trimmed with GBLOCKS and analyzed in RAxML under GTR +Γ. Clade colours correspond to those in Fig. 2. Bootstrap support values are represented above each node; asterisks indicate 100% bootstrap value.

The run of BEAST reached stationarity after 10 000 000 generations; 20 000 000 generations were discarded as burn-in. The tree topology recovered by BEAST (Fig. 5) is almost identical to that of the parsimony analysis under the parameter set 3221, with Parasiro and Suzukielus forming a paraphyletic grade at the base of Stylocellidae, although posterior probabilities for the corresponding nodes are low (0.788 and 0.880, respectively). In all other aspects, it also resembles the topology of the maximum likelihood analysis, especially in the internal relationships among the pettalid genera.

Figure 5

Evolutionary time-tree of Cyphophthalmi inferred from BEAST analysis of all molecular data. Clade colours correspond to those in Fig. 2. Coloured bars indicate 95% highest posterior density (HPD) intervals for nodes of interest. Number on nodes indicate posterior probabilities; asterisks indicate posterior probability of 1.00.

Figure 5

Evolutionary time-tree of Cyphophthalmi inferred from BEAST analysis of all molecular data. Clade colours correspond to those in Fig. 2. Coloured bars indicate 95% highest posterior density (HPD) intervals for nodes of interest. Number on nodes indicate posterior probabilities; asterisks indicate posterior probability of 1.00.

The diversification of Cyphophthalmi is estimated at approximately 332 Mya (95% HPD: 297–362 Mya). Diversification times for the described families of Cyphophthalmi are estimated as: Neogoveidae, 236 Mya (95% HPD: 208–266 Mya); Pettalidae, 183 Mya (95% HPD: 148–218 Mya); Sironidae (excluding Parasiro and Suzukielus), 278 Mya (95% HPD: 243–311 Mya); Stylocellidae, 167 Mya (95% HPD: 140–195 Mya); and Troglosironidae, 57 Mya (95% HPD: 40–73 Mya). Ogoveidae, represented by a single exemplar, diverged from Neogoveidae 261 Mya (95% HPD: 231–292 Mya), and Troglosironidae diverged from Ogoveoidea 279 Mya (95% HPD: 248–311 Mya). These results largely corroborate previous estimates of divergence times (Boyer et al., 2007b; Giribet et al., 2010), with the exception of Stylocellidae, the diversification of which is recovered as younger than previously reported (Clouse & Giribet, 2010). Although some species represented by multiple terminals are young (e.g. Suzukielus sauteri, Neogovea virginie, Parogovia sironoides), Metasiro americanus is an old species, perhaps reflecting the existence of cryptic species along its range.

All probabilistic approaches recognize a clade of trans-Tasman Cyphophthalmi (the Australian and New Zealand genera), although none of these landmasses or their constituent terranes appears monophyletic (Fig. 6). The ancestral area reconstruction of this clade is ambiguous, with the highest probability for an origin in the Australian plate of New Zealand. The ancestral area of the family shows more ambiguity, the three most likely scenarios being a mixed South Africa/New Zealand Australian plate (P = 0.291), South African (P = 0.207) or mixed South Africa/Sri Lankan (P = 0.194). The ancestral area reconstruction of the clade including the three families with sternal opisthosomal gland openings (Fig. 7) is mostly West African/New Caledonian (P = 0.787), with the ogoveoid families being most likely West African (P = 0.662) or mixed between West Africa and the south-eastern USA (P = 0.206), the latter being once connected to West Africa. A South American (Amazonian) origin of the family Neogoveidae receives little support.

Figure 6

Ancestral range reconstructions for Pettalidae inferred by Lagrange analysis, using stratified models. Coloured squares at terminals indicate ranges occupied by sampled species. Coloured squares on nodes indicate ranges reconstructed for hypothetical ancestors. Numbers on nodes indicate relative probability of ranges reconstructed.

Figure 6

Ancestral range reconstructions for Pettalidae inferred by Lagrange analysis, using stratified models. Coloured squares at terminals indicate ranges occupied by sampled species. Coloured squares on nodes indicate ranges reconstructed for hypothetical ancestors. Numbers on nodes indicate relative probability of ranges reconstructed.

Figure 7

Ancestral range reconstructions for Sternophthalmi (Troglosironidae, Ogoveidae, Neogoveidae) inferred by Lagrange analysis, using stratified models. Coloured squares at terminals indicate ranges occupied by sampled species. Coloured squares on nodes indicate ranges reconstructed for hypothetical ancestors. Numbers on nodes indicate relative probability of ranges reconstructed.

Figure 7

Ancestral range reconstructions for Sternophthalmi (Troglosironidae, Ogoveidae, Neogoveidae) inferred by Lagrange analysis, using stratified models. Coloured squares at terminals indicate ranges occupied by sampled species. Coloured squares on nodes indicate ranges reconstructed for hypothetical ancestors. Numbers on nodes indicate relative probability of ranges reconstructed.

Combined analysis of molecules and morphology

The position of morphology-only taxa was unstable in the first rounds of analyses, which (for example) did not group the two Ogovea species, one represented by morphology only, whereas the other one was represented by molecules and morphology, despite being almost identical for the morphological data matrix. This appears to be a problem of the Wagner addition, as designed in most phylogenetic software, and was resolved by fusing a jackknife tree and a first tree obtained during a normal search, as described above. The resulting trees of each subsequent analysis were then fused to the previous pool of trees until results (topology and tree length) stabilized. The combined analysis of molecules and morphology in POY required eight rounds of tree fusing until stabilizing in a tree length of 56 984 weighted steps and finding three trees differing only in the position of some of the morphology-only taxa (Fig. 9).

Figure 9

Combined analysis of morphology and molecules. Strict consensus of three optimal trees based on the parsimony direct optimization analysis under parameter set 3221 (56 984 weighted steps). Clade colours correspond to those in Fig. 2; taxa in red are represented by morphology only. Numbers above nodes indicate jackknife support values.

Figure 9

Combined analysis of morphology and molecules. Strict consensus of three optimal trees based on the parsimony direct optimization analysis under parameter set 3221 (56 984 weighted steps). Clade colours correspond to those in Fig. 2; taxa in red are represented by morphology only. Numbers above nodes indicate jackknife support values.

The overall topology is very similar to those of the analyses with molecular data only, with a few exceptions, and lowered jackknife support values. Pettalidae is monophyletic (63%), and includes both Speleosiro and Manangotria from the morphology-only taxa. Speleosiro appears as sister to Purcellia and Managotria is sister to Karripurcellia, although these relationships, as with most other intergeneric pettalid relationships, receive low support. Ankaratra does not appear within Pettalidae and, instead, is basal to the clade containing Sironidae and Stylocellidae.

Troglosironidae appears as sister to Ogoveoidea, although this tree differs from all previous trees in that Neogoveidae is paraphyletic with respect to Ogovea, which is sister to Parogovia, constituting an African clade, sister to all the American species, with Canga as the sister group to Metasiro, and this clade being sister to the remaining neogoveids [56% jackknife frequency (JF)]. The type species and morphology-only species of Neogovea and Brasilogovea appear in a clade, although there is little correspondence between the complete taxa and those represented by morphology only (i.e. Neogovea and Brasilogovea are not reciprocally monophyletic).

Ankaratra and Shearogovea form a grade at the base of the Sironidae – Stylocellidae clade, with Sironidae paraphyletic, as in the prior POY and BEAST analyses. Marwe and Iberosiro form a clade with Paramiopsalis, and Odontosiro forms a clade with Parasiro. Stylocellidae is monophyletic (63% JF), including the morphology-only species Stylocellus sumatranusWestwood, 1874, Meghalaya annandalei Giribet, Sharma & Bastawade, 2007, Miopsalis pulicaria Thorell, 1890, and Leptopsalis beccariiThorell, 1882–1883. Stylocellus sumatranus, the type species of Stylocellus, appears nested within the molecular Meghalaya clade; Meghalaya annandalei, the type species of Meghalaya, appears unresolved at the base of the molecular Leptopsalis clade; Miopsalis pulicaria and Leptopsalis beccarii, the type species of their respective genera, appear nested deep within the clade Leptopsalis. Although the stylocellid results make little sense, this may be a result of the lack of discrete characters useful for resolving their phylogenetic relationships (see below).

A new classification system for Cyphophthalmi

Based on the results reported above, we provide a new classification system for Cyphophthalmi, introducing three new infraorders: Scopulophthalmi new clade, Sternophthalmi new clade, and Boreophthalmi new clade (Table 6). Scopulophthalmi is diagnosed as Pettalidae, and the name refers to the presence of a scopula in the anal region of the male in many pettalid species. Sternophthalmi includes the families Troglosironidae, Ogoveidae, and Neogoveidae, with its etymology referring to the presence of an exocrine gland opening in the opisthosomal sternal region of males in all troglosironids, all ogoveids, and most neogoveids, as opposed to the other three families where the opisthosomal exocrine glands, when present, open in the posterior tergites. We maintain Shear's superfamily Ogoveoidea, and restrict Sironoidea to the family Sironidae and Stylocelloidea to the family Stylocellidae, although we do not introduce other superfamilies because they would each contain a single family. Boreophthalmi includes the families Stylocellidae and Sironidae, which subsequent to Hansen & Sørensen's (1904), had been considered the representatives of the two main cyphophthalmid clades (Shear, 1980). The term refers to the mostly northern hemisphere distribution of these two families, although the origin of Stylocellidae can be probably traced to northern Gondwana (Clouse & Giribet, 2010). Sternophthalmi is sister group to Boreophthalmi.

Table 6

Classification system for Cyphophthalmi, using established family and superfamily names

Suborder Cyphophthalmi 
Infraorder Scopulophthalmi new clade 
Family Pettalidae Shear, 1980 
Infraorder Sternophthalmi new clade 
Family Troglosironidae Shear, 1993 
Superfamily Ogoveoidea Shear, 1980 
Family Ogoveidae Shear, 1980 
Family Neogoveidae Shear, 1980 
Infraorder Boreophthalmi new clade 
Superfamily Stylocelloidea Hansen & Sørensen, 1904 new composition 
Family Stylocellidae Hansen & Sørensen, 1904 
Superfamily Sironoidea Simon, 1879 new composition 
Family Sironidae Simon, 1879 
Suborder Cyphophthalmi 
Infraorder Scopulophthalmi new clade 
Family Pettalidae Shear, 1980 
Infraorder Sternophthalmi new clade 
Family Troglosironidae Shear, 1993 
Superfamily Ogoveoidea Shear, 1980 
Family Ogoveidae Shear, 1980 
Family Neogoveidae Shear, 1980 
Infraorder Boreophthalmi new clade 
Superfamily Stylocelloidea Hansen & Sørensen, 1904 new composition 
Family Stylocellidae Hansen & Sørensen, 1904 
Superfamily Sironoidea Simon, 1879 new composition 
Family Sironidae Simon, 1879 

The following taxa are thus abandoned as a result of being non-monophyletic according to our phylogenetic results: Infraorder Tropicophthalmi Shear, 1980 and Infraorder Temperophthalmi Shear, 1980. Shear's infraorders do not reflect the phylogenetic relationships obtained here, as suggested in previous studies (Giribet & Boyer, 2002; Boyer et al., 2007b; Giribet et al., 2010).

Distribution modelling and habitat suitability overlap

Habitat suitability models predicted by both the MAXENT and BIOCLIM methods were highly congruent and therefore we present only results from MAXENT (Fig. 10) because it was found to outperform other modelling algorithms (Elith et al., 2006). Model predictions were significantly distinct from random and area under the curve (AUC) values were high or moderately high (in the range 0.84–0.99) in all runs independently of the modelling algorithm and the set of variables used to build the model. For the analyses with a reduced number of variables, we kept all variables that had jackknife regularized training gain greater than one. As expected, when correlation among variables is present, using a lower number of variables does not change significantly the AUC values but reduces over-fitting; hence, the resulting models find broader areas with suitable conditions. These are, however, congruent with results from models built with all BIOCLIM variables and differences are generally associated with areas where habitat suitability is low (Fig. 10).

Figure 10

MAXENT models of habitat suitability. Left column with all bioclim variables, right column with variables with jackknife regularized training gain greater than one. Warmer (red-yellow) colours represent more suitable habitats. Maps in miniature represent actual presence observations. A, Pettalidae; B, Sironidae; C, Stylocellidae; D, Sternophthalmi (Troglosironidae + Ogoveidae + Neogoveidae).

Figure 10

MAXENT models of habitat suitability. Left column with all bioclim variables, right column with variables with jackknife regularized training gain greater than one. Warmer (red-yellow) colours represent more suitable habitats. Maps in miniature represent actual presence observations. A, Pettalidae; B, Sironidae; C, Stylocellidae; D, Sternophthalmi (Troglosironidae + Ogoveidae + Neogoveidae).

The variables with highest average relative contribution to the MAXENT habitat suitability model for Pettalidae were isothermality (33.8%), precipitation of the driest month (22.8%) and annual mean temperature (9.2%). Jackknife tests of variable importance indicate that temperature seasonality had the highest gain in isolation. Mean diurnal temperature range decreased the gain the most when omitted, suggesting that it contained the most information not present in the other variables. For Sironidae, the precipitation of the coldest quarter (40.0%), mean temperature of the coldest quarter (16.3%), and annual mean temperature were the variables with highest contribution. Mean temperature of the coldest quarter had the highest gain in isolation, and annual precipitation decreased the gain the most when omitted. The variables with highest contribution for Stylocellidae were temperature seasonality (42.9%), annual precipitation (26.3%), and precipitation of the warmest quarter (11.8%). Annual precipitation had the highest gain in isolation, and precipitation of the warmest quarter decreased the gain the most when omitted. For the clade Sternophthalmi, the variables with the highest contribution were annual precipitation (33.8%), precipitation of the driest quarter (24.1%), and isothermality (13.9%). Temperature annual range had the highest gain in isolation and also reduced gain the most when omitted.

Results of the identity test for the MAXENT models based on all variables are shown in Table 5. Results from the analysis using the Bioclim algorithm are congruent (not shown). The identity test shows that, when considering relative ranks, the calculated habitat suitability scores for most of the groups are significantly distinct except for Stylocellidae versus Sternophthalmi, the two tropical clades. Habitat suitability identity cannot be rejected either for Pettalidae versus Stylocellidae at the 0.01% significance level. The higher values for I and D in those two cases also show that there is significant overlap of the suitable habitat of these clades. Pettalidae versus Sternophthalmi shows also high values of I and D but identity tests reject the null hypothesis of habitat suitability identity.

Table 5

Habitat suitability overlap statistics based on the MAXENT analysis with all bioclim variables

Clade Relative rank I D 
Pettalidae versus Sironidae 0.727** 0.392 0.187 
Pettalidae versus Stylocellidae 0.826* (P = 0.015) 0.525 0.234 
Pettalidae versus Sternophthalmi 0.832** 0.638 0.329 
Sironidae versus Stylocellidae 0.666** 0.126 0.038 
Sironidae versus Sternophthalmi 0.768** 0.292 0.114 
Stylocellidae versus Sternophthalmi 0.836 (P = 0.133) 0.819 0.554 
Clade Relative rank I D 
Pettalidae versus Sironidae 0.727** 0.392 0.187 
Pettalidae versus Stylocellidae 0.826* (P = 0.015) 0.525 0.234 
Pettalidae versus Sternophthalmi 0.832** 0.638 0.329 
Sironidae versus Stylocellidae 0.666** 0.126 0.038 
Sironidae versus Sternophthalmi 0.768** 0.292 0.114 
Stylocellidae versus Sternophthalmi 0.836 (P = 0.133) 0.819 0.554 

Relative rank significance calculated using ENMtools identity test results. *0.01 < P < 0.05, **P < 0.01. I, the I statistic (Warren et al., 2008); D, Schoener's D (Schoener, 1968).

DISCUSSION

The present data, of worldwide scope, and spanning the geological scale from the Palaeozoic to the present, allow us to study a group of soil arthropods to a level of detail rarely seen in biogeographical and phylogenetic studies. Taxonomic representation in the molecular data includes species from all non-monotypic genera and several monotypic genera; all genera are represented in the morphological data set. Geographical coverage includes all known world regions where Cyphophthalmi have been reported, with the exception of Mexico (a few specimens from two caves; Shear, 1977, 1980), Madagascar (four specimens known in total for two species; Shear & Gruber, 1996), Kenya (five specimens known from a single cave; Shear, 1985), and the Philippine island of Palawan (a single adult specimen known; Shear, 1993c).

Our phylogenetic results provide the basis for a new classification of the suborder Cyphophthalmi. The results also set the geological time framework for the origin and diversification of each family and the evolution of the niche preference in selected families or suprafamilial clades. This allows testing specific biogeographical hypotheses, such as the supposed total submersion of New Caledonia (Murienne et al., 2005) or New Zealand (Goldberg, Trewick & Paterson, 2008), or the reconstruction of the ancestral areas of each cyphophthalmid lineage.

Direct optimization analysis

To a lesser degree than for static homology, dynamic homology searches are difficult to evaluate in terms of optimality. In the present study, we used a strategy of SATF with multiple rounds of analyses to decide when to stop the searches, and saw that searches of 6–12 h run on a desktop computer stabilized after five to ten rounds, depending on the parameter set. The stability of the results is used here as a criterion for reporting results, in the same fashion that driven searches and similar techniques have been applied to the computational problem of tree searching (Giribet, 2007a; Goloboff, Farris & Nixon, 2008).

In previous studies of cyphophthalmid and harvestmen data, analyses based on direct optimization have yielded results sometimes differing from those of analyses based on static homology (Boyer et al., 2007b; Giribet et al., 2010). However, this is not the case in the present study, where taxon sampling and geographical representation have been thoroughly optimized. One major difference remains, the monophyly of Sironidae (see below), although some of the static homology analyses (Fig. 5) are congruent with the direct optimization tree (Fig. 3), whereas the maximum likelihood tree (Fig. 4) differs from the Bayesian estimate (Fig. 5). Another major difference (but, again, among analyses, and not necessarily the result of differences between dynamic and static notions of homology) is the internal resolution of the pettalid genera (see below).

Systematics

The monophyly of Cyphophthalmi has been well supported in all morphological analyses (Giribet & Boyer, 2002), as well as from the earliest molecular analyses using just a few sequences in the families Sironidae and Stylocellidae (Giribet et al., 1999; Shultz & Regier, 2001; Giribet et al., 2002), a few representatives of the suborder (Giribet & Boyer, 2002) or, more recently, in several much denser analyses (Boyer et al., 2007b; Giribet et al., 2010). Our new data add corroboration to this well-delimited taxon, with the familial inter-relationships and their internal structure being the real focus of the study, although, in the combined analysis including taxa with morphological data only, support for the monophyly of Cyphophthalmi decreases to 61%, probably as a result of some effects of the missing data (see below). Among these, Pettalidae, Stylocellidae, Troglosironidae, and Neogoveidae are monophyletic in most of our analyses (but see discussion on Neogoveidae), Ogoveidae is represented by a single specimen in the molecular analyses, and Sironidae remains contentious, especially with respect to the placement of the two genera Suzukielus and Parasiro.

One of the outstanding issues in cyphophthalmid phylogenetics has been the placement of the root, which was suggested to occur: (1) between Stylocellidae and the remaining families; (2) between Pettalidae and the remaining families; or (3) between a clade containing Suzukielus and Pettalidae and the remaining families (Giribet & Boyer, 2002), based on the molecular rooting of a morphological tree, because most cyphophthalmid morphological characters are inapplicable or meaningless outside the suborder. Subsequent analyses found alternative resolutions placing the root between Pettalidae and the rest or between Stylocellidae and the rest (Boyer et al., 2007b), depending on the analysis and optimality criterion employed. Different studies have assumed either one of these alternative rootings until a recent broader Opiliones study found the root between Pettalidae and the rest (Sternophthalmi + Boreophthalmi), this time without distinction among optimality criteria or method of analysis (Giribet et al., 2010). This latter result is further corroborated in the present study. This position of Pettalidae as sister group to all other cyphophthalmid families falsifies the two infraorders introduced by Shear (1980), which should be abandoned, and allows for a much clearer reconstruction of the cyphophthalmid ancestor, which must have had laterally positioned simple ocelli (Alberti, Lipke & Giribet, 2008), a lamelliform adenostyle in the male fourth tarsus, and opisthosomal exocrine glands opening in the anal region in the male.

Internal resolution of Pettalidae does not differ considerably from the source studies of this pettalid data set (Boyer & Giribet, 2007, 2009) and, as in these studies, South Africa, New Zealand and Australia are not monophyletic. Diversification of the family started 183 Mya, and therefore paralogy of some of its landmasses is easily explained by cladogenesis prior to the split of Gondwana into its current continents. Nonetheless, relationships within Pettalidae remain unstable or poorly supported and important African diversity is missing from the molecular sampling, both from South Africa (de Bivort & Giribet, 2010) and Madagascar (Shear & Gruber, 1996), although the combined analyses with morphology place Speleosiro as sister group to Purcellia (64% JF) (Giribet, 2003a; de Bivort et al., 2010; de Bivort & Giribet, 2010), and Manangotria as sister group to Karripurcellia, although with low nodal support.

Results within Pettalidae are congruent among methods of analysis in the monophyly of each genus, although their relationships remain contentious. A trans-Tasman clade is found, albeit with low support, in the probabilistic analyses but not in the direct optimization analysis. Similarly, the most-basal position of Parapurcellia is not universally accepted. Other relationships discussed above are poorly supported, with the exception of a Chileogovea+Purcellia clade. Whether the deficient sampling in South Africa (whose genera appear to have influence at the base of the tree) or perhaps lineage extinction during the cooling of Antarctica are responsible for the lack of resolution in the pettalid relationships, remains untested.

The present study introduces the first genetic data for the monogeneric family Ogoveidae, which clearly forms part of the previously established Troglosironidae–Neogoveidae clade (Boyer et al., 2007b; Sharma & Giribet, 2009a), now named Sternophthalmi. Ogoveidae forms a clade with Neogoveidae in all analyses, corroborating Shear's superfamily Ogoveoidea, although not his infraorder Tropicophthalmi, because Stylocellidae are unrelated to Ogoveoidea. Ogoveoidea is thus a Pantropical clade of probable African origin, although its original diversification dates back to 261 Mya. Some analyses (two suboptimal parameter sets under direct optimization) place Ogoveidae as ingroup Neogoveidae, although most analyses support monophyly of Neogoveidae. This is also found in the combined analysis with morphology, where Ogovea and Parogovia form a clade of African Ogoveoidea, although support for this clade is low. The latter clade is sister to a clade of American neogoveids. However, because of the unique morphology of ogoveids (Juberthie, 1969; Giribet & Prieto, 2003), and monophyly of Neogoveidae in most analyses, the family Ogoveidae is maintained as valid (after rediagnosis from Giribet & Prieto, 2003). Shear (1980) included the genus Huitaca in this family, although, earlier, he had postulated a sister group relationship of Huitaca and Metagovea (Shear, 1979a), as shown in our analyses.

Neogoveidae began its own diversification soon after (236 Mya), long before the opening of the Atlantic Ocean, as illustrated by the amphi-Atlantic clade relating the Eastern Brazilian genus Canga with the African Parogovia (specimens from Cameroon, Gabon, and Equatorial Guinea), or the sister group relationships of the North American genus Metasiro to the Amazonian/West African clade. The specimen from Ivory Coast, probably related to P. pabsgarnoni, constitutes a new genus that will be described elsewhere. Other than Canga, the South American species form a well supported clade that we currently assign to four genera: Brasilogovea, which we resurrect here, includes species from Amazonia and the ‘Tepuis’ region of Colombia; Neogovea, represented by two species from Guyana and French Guiana; Huitaca, still endemic to Colombia, including a large number of undescribed species; and Metagovea, including not only most specimens from the Andean region, but also some Amazon specimens from Leticia and a specimen from Guyana, with the latter being sister to all other Metagovea and possibly constituting another new genus (L. Benavides & G. Giribet, unpubl. data). This species is clearly unrelated to the genus Neogovea, occurring in this part of the Neotropics, and it is characterized by a conspicuous opisthosomal mid-dorsal longitudinal sulcus; an adenostyle ending in a brush of setae and located at the base or towards the centre of the dorsal side of tarsus IV; absence of opisthosomal exocrine glands; and a spermatopositor complex with a crown-shaped structure at the tip, with additional perpendicular projections (L. Benavides & G. Giribet, unpubl. data). Our Metagovea clade includes specimens that we previously placed in the genera Metagovea and Neogovea (Boyer et al., 2007b; Giribet et al., 2010) because they differ considerably in their anatomy. Further subdivision of Metagovea may be warranted, although not until specimens from the Manaus area (Brazil) are available for molecular study. Nonetheless, relationships among the four genera are well established, with Brasilogovea+Neogovea being the sister group to a clade including Huitaca and Metagovea, and the latter genus generally divided among small species, or ‘typical’Metagovea and larger species more similar to Neogovea. The large sampling within the superfamily, including all the currently recognized genera, and new data for many mostly undescribed species and genera not represented in previous studies, allows us to provide a more comprehensive understanding of this Pantropical group. The addition of morphological data of the types of the genera Neogovea and Brasilogovea did not fully resolve this clade, although this is considered to be a result of the poor preservation of these specimens (missing the ventral opisthosomal region) that does not allow examination of key characters such as the sternum or the opisthosomal exocrine glands.

The sister group of Ogoveoidea is without doubt the New Caledonia endemic genus Troglosiro, and both separated approximately 279 Mya at a time when New Caledonia was geographically located at the eastern margin of Gondwana. Diversification of Troglosironidae is, however, much more recent (57 Mya) and the error associated with this date does not allow for an unambiguous interpretation of the postulated total submersion of the island (Grandcolas et al., 2008; Murienne et al., 2008; Murienne, 2009). The analyses recognize a group with sternal opisthosomal depressions associated with the sternal exocrine glands of the males, sensuSharma & Giribet (2009a).

Stylocellidae have gone from being the most poorly-known group to arguably the most stable and best understood phylogenetically. The results of the present study corroborate those from the recent studies mostly by R. Clouse (Clouse & Giribet, 2007; Clouse et al., 2009; Clouse, 2010; Clouse & Giribet, 2010; Clouse et al., 2011), from which all the data included here were derived; see also Schwendinger & Giribet (2005). Fangensis, a clade with its origins in the terrane that today constitutes the Thai-Malay peninsula, is sister to all other stylocellids, which diversified towards the north in the genus Meghalaya and towards the south in the genera Miopsalis and Leptopsalis, the former mostly found on Borneo, although giving rise to species in the Philippines and Sumatra, and the latter radiating rapidly as Sumatra, Java, and Sulawesi became accessible, and also extending to New Guinea. The family diversified 167 Mya and includes the only reported cases of possible transoceanic dispersal in Cyphophthalmi (Clouse & Giribet, 2007; see also Clouse et al., 2011). Morphological analysis of discrete character data also support earlier studies excluding the nominal genus Stylocellus from any of the four genera adopted here, with Stylocellus remaining monotypic (Clouse et al., 2009). However, the addition of the type species of the genera Leptopsalis, Meghalaya, Miopsalis, and Stylocellus, not available for molecular analysis, does not result in a well-resolved taxonomy. The problem, however, lies in the nature of the data because the type of Stylocellus, an old, pinned, deformed specimen, is difficult to position based on discrete-characters only (Clouse et al., 2009), whereas the type of Miopsalis is a female and thus misses most discrete characters coded for other specimens, and was not available to be included in the morphometric analyses of Clouse et al. (2009). Leptopsalis is, however, well placed within its supposed molecular clade, although the type of Meghalaya does not find good support.

Sironidae monophyly has been disputed in previous analyses based on morphology and molecules, where two genera, Parasiro and Suzukielus, often do not cluster with the remaining sironids (in the genera Siro, Cyphophthalmus, Paramiopsalis, and Iberosiro) (Giribet & Boyer, 2002; de Bivort & Giribet, 2004; Boyer et al., 2007b; Giribet et al., 2010). Odontosiro, never included in a molecular analysis, is sister to Parasiro outside of the typical sironids. The Kenyan Marwe has been placed within sironids in some analyses based on morphological data (de Bivort & Giribet, 2004), as also shown here, and appears related to Paramiopsalis and Iberosiro. Sironids found their monophyly, however, in a recent morphological analysis of continuous characters (de Bivort et al., 2010) and in the maximum likelihood analysis of Giribet et al. (2010), as does the maximum likelihood analysis of the present data set, albeit with bootstrap support below 50%. Monophyly of Sironidae is also found in the analysis of the nuclear ribosomal data under direct optimization, suggesting that the non-monophyly of the family may be an artefact introduced most probably by their unusual COI evolution (Boyer et al., 2005). However, the membership in Sironidae of the genera Iberosiro, Odontosiro, or even Marwe remains untested with molecular data and future sampling effort in the north-western Iberian Peninsula and in Kenya should focus on these highly controversial genera.

Morphological data

It is well known that combined analyses of molecules and morphology are fundamental for understanding the systematics of groups that include many taxa for which molecular data cannot be obtained (Eernisse & Kluge, 1993; Nixon & Carpenter, 1996). A typical example of the latter case is provided by fossil taxa (Giribet, 2010; Murienne, Edgecombe & Giribet, 2010a; Pyron, 2011). When dealing with such taxa, missing data can become a concern, although it has been shown, both with simulation and with empirical results, that missing data in and of themselves are not always problematic; instead, it is information content in the data at hand what really matters (Wiens, 2003; Goloboff et al., 2009; Hejnol et al., 2009; Wiens, 2009).

The fossil record of Cyphophthalmi is scarce (Dunlop & Giribet, 2003; Poinar, 2008; Dunlop & Mitov, 2011), and it does not add important diversity that can be coded into an explicit data matrix. However, the problem of missing data is of great importance in Cyphophthalmi as a result of the group's almost global but highly localized distribution, making collecting an arduous task. For these reasons, many species are known only from old museum material, from a single male, or even from only females or juveniles, making it impossible to include them in the molecular matrix or presenting considerable amounts of missing data in our morphological matrix. To mention just a few examples, the type species of the genera Miopsalis and Ogovea are known only from female individuals (Thorell, 1890–1891; Hansen & Sørensen, 1904); the second species in the genus Pettalus, Pettalus brevicaudaPocock 1897, was based on a juvenile specimen (Giribet, 2008); Stylocellus sumatranus, currently the only species in the genus, is based on a deformed specimen in very poor condition (Clouse et al., 2009); and several monotypic genera have never been examined under a scanning electron microscope: Ankaratra, Manangotria, Marwe, and Odontosiro.

When trying to maximize the diversity represented in the present study, we included all currently recognized genera in our morphological matrix, although some of the species representing these genera are missing important characters. Despite this problem, we followed earlier recommendations into a combined analysis in POY under the optimal parameter set and submitted it to a jackknife analysis. The resulting tree was not too different from that of an early analysis of all cyphophthalmid genera (Giribet & Boyer, 2002) with respect to the lack of resolution for many clades, which is otherwise well supported by the molecular data sets. Notable results are the placement of Managotria taolanaro within Pettalidae (63% jackknife support), the monophyly of Stylocellidae (including the types of the genera Leptopsalis, Meghalaya, Miopsalis, and Stylocellus, despite the lack of molecular data; 63% jackknife support) or the monophyly of the Neotropical Neogoveidae (excepting Canga), including the types and morphology-only species of Neogovea[N. immsi, Neogovea kartabo (Davis, 1937)], Neogovea kamakusaShear, 1977), and Brasilogovea microphaga Martens, 1969 (56% jackknife support). The inclusion of Parogovia pabsgarnoni affects the monophyly of the African neogoveids, as Parogovia sp. DNA105671 does not form a clade with the other Parogovia (54% jackknife support). However, the instability of species such as Shearogovea mexasca and Ankaratra franzi affects the monophyly of groups that are otherwise robust to molecular analysis such as Sternophthalmi + Boreophthalmi, Sternophthalmi, Ogoveoidea, Neogoveidae or Boreophthalmi.

The current results combining morphology with molecules lowered overall support for the tree. This is an unfortunate result because simulations have shown that the accuracy in the phylogenetic placement of fossils often improves or stays the same when using molecular data and that only in a few cases accuracy was significantly decreased (Wiens, 2009). The problem here may be related to the low numbers of discrete morphological characters available for these Opiliones, often limited to variation among groups of species; hence, the recent use of continuous characters in some analyses of the group (Clouse et al., 2009; de Bivort et al., 2010; de Bivort & Giribet, 2010). Some characters show low levels of homoplasy, greatly structuring the data (some of these characters were the basis for older classification systems) but many of our wild taxa show ‘unexpected’ states in these characters. Character 7 is notable in this respect. The coxae of the walking legs of Cyphophthalmi show different degrees of fusion, with coxae III and IV of each side always fused and coxae I remaining moveable. Coxa II can be free (state 0) or fused to coxae III and IV; among the former are most members of the families Pettalidae, Troglosironidae, and Sironidae (except for the genera Paramiopsalis and Iberosiro); among the latter are the members of the families Ogoveidae, Stylocellidae, and Neogoveidae (except for Canga and Metasiro). It is therefore not unexpected that this character defined the major groups Sironoidea and Stylocelloidea sensuHansen & Sørensen (1904), and that a genus such as Metasiro was considered a member of Sironidae in previous studies, nor that these genera are among the most unstable ones when morphology is used. The presence/absence of eyes (character 1), ozophore type (character 2), and spiracle shape (character 49) are also characters with relatively low levels of homoplasy, which have played an important role in cyphophthalmid systematics, and, again, it is not unexpeced that the taxa that present odd character states become unstable.

Biogeographical patterns in continents

Cyphophthalmi have been shown to present a high correlation of their systematic position and landmass affinity (Juberthie & Massoud, 1976; Shear, 1980; Giribet, 2000), to show strong genetic structure across short distances (Boyer et al., 2007a), and have been used as models to study vicariance biogeography (Giribet, 2003a; Boyer et al., 2005; Boyer & Giribet, 2007; Giribet & Kury, 2007; Boyer et al., 2007b; Boyer & Giribet, 2009; Clouse et al., 2009; Sharma & Giribet, 2009a; Clouse, 2010; Clouse & Giribet, 2010; de Bivort & Giribet, 2010; Murienne et al., 2010b; Clouse et al., 2011). This study corroborates earlier findings that suggest a temperate Gondwanan clade (Pettalidae; Fig. 6), a Pantropical clade (Sternophthalmi; Fig. 7), one clade originating in the Thai-Malay Peninsula (Stylocellidae; Fig. 8), and two or more Laurasian clades whose ancestral area is difficult to reconstruct with high probability but that includes the Iberian Peninsula, North America, and Western Europe (Sironidae; Fig. 8). The origin of all these clades is ancient, preceding the fragmentation of Pangea and therefore suggesting that many cladogenetic events were older than the vicariant events that followed. This has important biogeographical implications with respect to using vicariant events as calibration points because the mismatch between the two events could be very large (Kodandaramaiah, 2011).

Figure 8

Ancestral range reconstructions for Boreophthalmi (Sironidae, Stylocellidae) inferred by Lagrange analysis, using stratified models. Coloured squares at terminals indicate ranges occupied by sampled species. Coloured squares on nodes indicate ranges reconstructed for hypothetical ancestors. Numbers on nodes indicate relative probability of ranges reconstructed.

Figure 8

Ancestral range reconstructions for Boreophthalmi (Sironidae, Stylocellidae) inferred by Lagrange analysis, using stratified models. Coloured squares at terminals indicate ranges occupied by sampled species. Coloured squares on nodes indicate ranges reconstructed for hypothetical ancestors. Numbers on nodes indicate relative probability of ranges reconstructed.

Most biogeographical patterns observed, in conjunction with a well-dated phylogenetic hypothesis and a reconstruction of the ancestral landmasses for each clade, allow a thorough explanation of each clade. The ancestral area reconstruction of the family Pettalidae (Fig. 6) involves several cladogenetic events at the genus-level because each genus is currently recognized to be restricted to a single landmass or to adjacent terranes (Boyer & Giribet, 2007). Although resolution among the genera finds low support, most analyses suggest the South African genus Parapurcellia to be the sister group to all other genera, and place the other South African genus, Purcellia, in that clade, lending support to South Africa as one of the possible centres of origin of the family. A relationship between South Africa (Purcellia) and South America (Chileogovea) is found in most analyses, as is also found in the members of the peripatopsid Onychophora, with similar distribution and habitat requirements as pettalids (Allwood et al., 2010). It is also notable that the two Australian genera Austropurcellia (Queensland) and Karripurcellia (Western Australia) never form a clade, supporting earlier views about using microareas in biogeographical studies of small soil organisms (Giribet & Edgecombe, 2006). A relationship of Sri Lanka–Australia–New Zealand is found in several analyses.

The biogeographical patterns of Sternophthalmi (Fig. 7) are easily reconstructed, with two ancestral lineages occurring in the Neotropics (Canga is sister to the African Parogovia clade), two ancestral lineages in Africa (Ogovea and Parogovia), and one lineage in North America (Metasiro), which separated from the remaining neogoveids during the Triassic. Although older analyses suggested a relationship of Metasiro to Parogovia, this was based on analyses without several neogoveid lineages and without ogoveids, and the current results are very stable. The sister group relationship of Ogoveoidea to the New Caledonian endemic genus Troglosiro has been found in previous studies and it is discussed in more detail below. No paralogy is needed in this tree when considering the timing of the diversification events, as the separation of the Neotropics from the Afrotropics is dated at 95 Mya (Raven & Axelrod, 1972; Sanmartín, 2002).

Stylocellid biogeography and their ancestral areas have been discussed recently (Clouse & Giribet, 2010) and our results corroborate this earlier analysis. The Thai-Malay Peninsula is reconstructed as the ancestral terrane for the family with subsequent expansions to the Eastern Himalayas during the Cretaceous/Tertiary boundary, and radiations into the Borneo/Philippine plate and into the Indo-Malay Archipelago during the Cretaceous. Several lineages may have returned to the Thai-Malay Peninsula or moved between islands around the Cretaceous/Tertiary boundary during a period in which south-east Asia was subjected to drastic changes and the Indo-Malay Archipelago variously connected (Hall, 2002; Ali & Aitchison, 2008).

Reconstruction of the biogeographical history of Sironidae remains hindered by the instability of the relationships of Suzukielus and Parasiro; the former endemic to Japan and the latter found in the Iberian and Mediterranean plates. Parasiro has its origins in the Jurassic/Cretaceous of the Iberian Peninsula, where cyphophthalmids are so far restricted to areas with Paleozoic rocks (Murienne & Giribet, 2009). The main sironid clade includes three genera found in North America (Siro), Western Europe (Siro), the Iberian Peninsula (Paramiopsalis), and the Balkan region and Eastern Europe (Cyphophthalmus). Siro shows reciprocal monophyly of the two landmasses, the lineages separating during the Triassic, a result not supported in a recent analysis of the North American diversity (Giribet & Shear, 2010). The sister-group relationship of the Iberian/Balkan clade has been discussed thoroughly in recent studies (Boyer et al., 2005; Murienne et al., 2010b), which have also illustrated a correlation between an evolutionary explosion and the coming into contact of ancestral landmasses in the Mediterranean region (Murienne et al., 2010b). From a geological point of view, the Balkan Peninsula, supporting the explosive evolution of Cyphophthalmus, includes the margin of both Eurasia (the Moesian microplate) and Gondwana (the Adria microplate), as well as remnants of the Tethys and related marginal seas (made up of oceanic crust) (Karamata, 2006). The Adria microplate is the largest lithospheric fragment in the Central Mediterranean region. It was connected to Iberia in the west and to north-west Africa in the south (Wortmann et al., 2001) until the Middle–Late Triassic episodes of rifting and breakup (Channell, D'Argenio & Horváth, 1979; Pamic, Gusic & Jelaska, 1998), around the cladogenesis time for the split between Paramiopsalis and Cyphophthalmus. For most of the time, the Adria microplate was in a shallow-water environment (Scheibner & Speijer, 2008) in which the Southern Tethyan Megaplatform formed before disintegrating into several carbonate platforms in the Early Jurassic (Vlahovic et al., 2005), before the diversification of Cyphophthalmus during the Jurassic/Cretaceous, when cycles of land submergence and emergence have been recorded in some carbonate platforms (Vlahovic et al., 2005; Márton et al., 2008). The ancestral area of the family is however difficult to infer, perhaps, amongst other factors, as a result of the large number of terranes that existed around the Tethys.

Biogeography in continental islands: the cases of New Caledonia and New Zealand

Cyphophthalmi are present in most islands of continental origin (fragment islands sensuGillespie & Roderick, 2002), including Sri Lanka (Pocock, 1897; Sharma & Giribet, 2006; Giribet, 2008; Sharma, Karunarathna & Giribet, 2009), Chiloé (Roewer, 1961; Juberthie & Muñoz-Cuevas, 1970; Shear, 1993a), Corsica and Sardinia (Simon, 1872; Juberthie, 1958), Honshu (Roewer, 1916; Juberthie, 1970b; Suzuki & Ohrui, 1972; Giribet, Tsurusaki & Boyer, 2006), and the Indo-Malay archipelago (Westwood, 1874; Thorell, 1882–1883; Pocock, 1897; Hansen & Sørensen, 1904; Shear, 1979b; Rambla, 1991; Shear, 1993c; Giribet, 2002; Schwendinger & Giribet, 2005; Clouse & Giribet, 2007; Clouse et al., 2009; Clouse & Giribet, 2010), and, in all these cases, their presence in these islands is best explained as a result of vicariance. Similarly, New Caledonia and New Zealand host a considerable diversity of Cyphophthalmi, although their presence in these islands as a result of one or more vicariant evens has been recently disputed.

New Caledonia currently has 13 described species in the genus Troglosiro, the only genus in the family Troglosironidae (Juberthie, 1979; Shear, 1993b; Sharma & Giribet, 2005, 2009a; Sharma & Giribet, 2009b) considered to be endemic to the Grande Terre and unambiguously recovered as the sister group to the Equatorial Ogoveoidea from Equatorial West Africa and the Equatorial Neotropical belt. Geological data on the origins of the New Caledonian biodiversity argue in favour of a series of submersions during the Palaeocene and Eocene (Paris, Andreieff & Coudray, 1979; Aitchison et al., 1998; Pelletier, 2006), which has been used to support a total submersion of the island, re-emerging 37 Mya (Murienne et al., 2005; Grandcolas et al., 2008; Murienne et al., 2008). Indeed, molecular dating analyses of several New Caledonian clades has supported diversification processes post-dating the critical date of 37 Mya (Murienne et al., 2005; Page et al., 2005; Murienne et al., 2008; Espeland & Johanson, 2010; Murienne, Edgecombe & Giribet, 2011), which has led some studies to suggest that the entirety of the New Caledonian terrestrial biota must have arrived to the islands via dispersal and that no trace of ancient vicariance is left. One notable exception may be the family Troglosironidae, whose diversification has been dated at 28–49 Mya by Boyer et al. (2007b) and 52–102 Mya by Giribet et al. (2010), although these studies used few troglosironid samples. Refined analyses here suggest a Late Cretaceous–Early Tertiary diversification of the family (57 Mya), predating the supposed re-emergence of New Caledonia, although the error associated with this date does not allow unambiguous distinction of the hypothesis owing to the temporal proximity of the re-emergence of the island (37 Mya) and the floor of the diversification age estimate (95% HPD: 40–73 Mya). The ancestral area reconstruction for the split between Troglosironidae and Ogoveoidea is supported as a contiguous landmass containing West Africa and New Caledonia, deep in the Permian, indicating that the range of the clade was much broader than it currently is (Figs 5, 7), and that massive extinctions may have occurred during the period comprised between 279–57 Mya. However, relict taxa (and Troglosironidae certainly is such an example) and the problem of extinction, especially in the absence of a fossil record, are mysteries that are difficult to address in biogeography (Crisp, Trewick & Cook, 2011). This is indeed a unique case, where Troglosironidae constitute a special lineage in this respect.

Another possibility is a trans-Pacific dispersal, again during the 279–57 Mya period, a phenomenon also observed in at least two other opilionid lineages (e.g. the families Zalmoxidae and Samoidae; Sharma & Giribet, 2011). However, dispersals in the Cenozoic are possible to reconstruct unambiguously in Zalmoxidae and Samoidae insofar as lineages in one part of the Pacific form a grade with respect to a clade in another part of the Pacific. In both these cases, Neotropical lineages form the paraphyletic grade with respect to Pacific island lineages, rendering the ancestral area reconstruction for the origin of these radiations as Neotropical. By contrast, Troglosironidae and the clade (Ogoveidae + Neogoveidae) form reciprocally monophyletic groups that diverged 279 Mya, which is inconsistent with recent dispersal. Moreover, the Permian origin of Troglosironidae also suggests that any putative dispersal event had to have occurred sometime between 279–57 Mya, a hypothesis that is difficult to test. As stated previously, we submit that the biogeographical history of Troglosironidae is inherently difficult to reconstruct as a result of the relictual nature of this lineage (Sharma & Giribet, 2009a).

A similar case has been proposed for New Zealand, which includes 29 species in three pettalid genera (Aoraki, Neopurcellia, and Rakaia) (Forster, 1948, 1952; Boyer & Giribet, 2003, 2007) found in two geological terranes (the Australian plate and the Pacific plate) (Boyer & Giribet, 2009). New Zealand's geology and biota reflect a dynamic history of ancient Gondwanan origin, long-term isolation from other continental landmasses, marine inundating during the Oligocene, glaciation during the Pleistocene, and evolutionary radiations that have produced a spectacular proportion of endemic species (Gibbs, 2006). Studies have focused on New Zealand's biogeography with particular vigour over the past two decades because molecular systematics has provided new tools with which to approach evolutionary questions. Molecular systematists have addressed topics such as the number and location of Pleistocene refugia (Marske et al., 2009; Buckley, Marske & Attanayake, 2010), the Alpine Fault Hypothesis (Heads & Craw, 2004), and, most contentiously, a vicariance versus dispersal-based origin of New Zealand's terrestrial biota (Trewick, Paterson & Campbell, 2007; Phillips et al., 2010). Although studies have long recognized that land area was drastically reduced (i.e. to less than 15% of its current size) during the marine incursions of the Oligocene (Cooper & Cooper, 1995), more recently Waters & Craw (2006) have suggested that there is no strong evidence for continuously emergent land throughout the period (Landis et al., 2008). Trewick et al. (2007) and Wallis & Trewick (2009) asserted that the preponderance of biogeographical evidence favours a scenario of complete submergence during the Oligocene, and some studies have gone further, suggesting that the entire terrestrial biota arrived via dispersal during the last 22 Myr (Landis et al., 2008), and that it is therefore more like that of an oceanic archipelago than a continent (Goldberg et al., 2008). Few have questioned this new trend in New Zealand biogeography (Knapp et al., 2007; Edgecombe & Giribet, 2008; Boyer & Giribet, 2009; Allwood et al., 2010; Giribet & Boyer, 2010).

The evolutionary history of the New Zealand cyphophthalmid genera (Aoraki, Rakaia, and Neopurcellia) has long been of interest as part of the evaluation of a hypothesis proposing total submersion of New Zealand in the Oligocene (Waters & Craw, 2006; Trewick et al., 2007; Goldberg et al., 2008; Landis et al., 2008; Wallis & Trewick, 2009; Giribet & Boyer, 2010; Phillips et al., 2010). The persistence of these lineages through the Oligocene bottleneck was considered to represent evidence of incomplete submersion of this landmass (Boyer & Giribet, 2007, 2009), although this hypothesis was not previously accompanied by molecular dating. Consequently, the ages of diversification of these lineages have been open to interpretation as very young (e.g. approximately 5 Mya; Goldberg et al., 2008). Moreover, Crisp et al. (2011) suggested that an important criterion for evidence of vicariance events is diversification time coincident with the timing of the geological event that precipitated the vicariance; in this case, the rifting of Zealandia from the Australian plate approximately 85 Mya, although cladogenesis could be expected to be much older than the vicariant event in taxa with low vagility and small distribution ranges.

The present study, utilizing a robust methodology for simultaneous estimation of tree topology and clade divergence times (sensuCrisp et al., 2011), and calibrated using fossil taxa exclusively (Kodandaramaiah, 2011), obtains the following diversification times for the New Zealand endemic genera Rakaia and Aoraki: 91 Mya (95% HPD: 72–108 Mya) and 90 Mya (95% HPD: 75–108 Mya), respectively. These diversification age estimates coincide with the rifting of Zealandia in the Late Cretaceous. We present evidence, therefore, based upon tree topology and clade divergence times, of the persistence of multiple lineages through the Oligocene. In addition, the present study reconstructs the origin of the genus Aoraki to the Australian plate during the Cretaceous and that of the genus Rakaia to a composite terrane in the Pacific and Australian plate also in the middle of the Cretaceous, although, later on, our study clearly assigns a clade to each terrane (Figs 5, 6). Unfortunately, the generic relationships are highly unstable across methods and parameter sets and further speculation about the relationships of the Australian and New Zealand genera awaits further data. We submit that these data falsify the hypothesis of complete submersion of New Zealand during the Oligocene Drowning. Recent and forthcoming studies of other invertebrate lineages (Allwood et al., 2010; Giribet & Boyer, 2010; Murienne et al., 2010a; Marshall, 2011) are anticipated to corroborate this conclusion.

Habitat suitability models

One common characteristic of all models that we present here is the larger suitable habitat than the area actually occupied by the four clades of interest. This constitutes further evidence for the old cladogenesis and low dispersal abilities of Cyphophthalmi because many areas of suitable habitat have never been in contact with a landmass occupied by the clade of interest. This pattern also corroborates the hypothesis that tectonic movements and vicariance events have defined distributions and driven diversification in this group of soil arthropods. Mysteries remain because certain temperate clades have migrated to warmer climates (e.g. Pettalus in Sri Lanka or Austropurcellia in Queensland, Australia), whereas others may not have been able to adapt to changing climates. This suggests that, in several lineages, processes of niche evolution might have taken place. However, the lack of detailed occurrence observations for many species does not currently allow studying the niche evolution in Cyphophthalmi in greater detail.

Concluding remarks

Cyphophthalmi constitute an ancient lineage of Opiliones distributed in temperate to tropical rainforests worldwide but restricted for the most part to continents and islands of continental origin, representing an ideal group of organisms for studying vicariance biogeography. Both phylogenetic patterns derived from molecular and morphological data and molecular dating using Opiliones fossils as calibration points corroborate the old age of the group and of its constituent clades. Ancestral area reconstruction further corroborates our biogeographical predictions by requiring only minimal switches between landmasses, most of them through contiguous land, therefore showing that the actual distribution is much more restricted than the potential distribution defined by the modelled habitat suitability for the different familial/suprafamilial clades. The data also permit tests of more general biogeographical hypotheses, such as the total submersion of New Caledonia and New Zealand and, at least in the former case, contradict a scenario of complete inundation. The present study provides refinement not only of the phylogenetic relationships and taxonomy of the group, but also its evolutionary and biogeographical history.

ACKNOWLEDGEMENTS

This work is the result of more than a decade of intense research on Cyphophthalmi and many individuals and institutions have contributed to it. First and foremost, this work has been possible in large part as a result of grants from the National Science Foundation (DEB-0236871 to G.G., DEB-0508789 to S.B. and G.G., and DEB-0205982 to M. Sharkey) and to numerous Putnam Expeditions Grants from the Museum of Comparative Zoology to collect in Australia, Cameroon, Gabon, Indonesia, New Zealand, South Africa, and Sri Lanka. J.M. was supported by a Marie Curie International Outgoing Fellowship (grant 221099) within the 7th European Community Framework Program. Many colleagues have assisted us in the field, and they are acknowledged in our previous papers. We want to emphasize, however, the help of Carlos Prieto for work in Equatorial Guinea, Indika Karunarathna for work in Sri Lanka, Cahyo Rahmadi for work in Indonesia, Nobuo Tsurusaki for work in Japan, Phil Sirvid and Ricardo Palma for work in New Zealand, Hervé Jourdan for work in New Caledonia, Nono Legrand for work in Cameroon, and many other colleagues who provided samples, especially Louis Deharverg for south-east Asian samples, Mike Sharkey for his Colombian samples, Rudy Jocqué for samples from Ivory Coast and Guyana, Eduardo Mateos for Spanish samples, and Ricardo Pinto-da-Rocha for Brazilian samples. Greg Edgecombe, Salvador Carranza, and Michele Nishiguchi accompanied us on many collecting trips. We are also indebted to many museums and curators for their long-term loans that made this research possible, especially Lorenzo Prendini and Norman Platnick from the American Museum of Natural History, New York, NY; Charles Griswold from the California Academy of Sciences, San Francisco, CA; Petra Sierwald from the Field Museum, Chicago, IL; Jan Beccaloni from The Natural History Museum, London; Arturo Muñoz Cuevas from the Muséum national d'Histoire naturelle, Paris; Phil Sirvid from Te Papa Tongarewa, Wellington; Jonathan Coddington from the US National Museum (Smithsonian Institution), Washington, DC; Nikolaj Scharff from the Zoological Museum, Natural History Museum of Denmark, Copenhagen; and Jason Dunlop from the Zoologischen Museums, Berlin. Finally, Laura Leibensperger has assisted with specimen loans during all these years. The editor John A. Allen, an anonymous reviewer, and Gustavo Hormiga provided comments that helped to improve upon an earlier version of this manuscript.

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Footnotes

1
Palaeosiro burmanicumPoinar, 2008 was placed within Sironidae in the original description based on the lack of a sternal apophysis with gland pores and dentition on the tarsal claw of leg II, although these only rule out placement within Troglosironidae and Neogoveidae. Moreover, the shape and position of the ozophores, the presence of eyes, the carina of the anal plate (similar to some FangensisSchwendinger & Giribet, 2005), and the collecting locality of the fossil, are all consistent with an early diverging lineage of Stylocellidae.

Appendix

Table A1

Size of data matrices for each gene before and subsequent to treatment with GBLOCKS

Data partition Number of positions after treatment with MUSCLE Number of positions after treatment with GBLOCKS 
16S rRNA 598 403 
18S rRNA 1769 1769 
28S rRNA 2267 2016 
COI 820 657 
Histone H3 327 327 
Data partition Number of positions after treatment with MUSCLE Number of positions after treatment with GBLOCKS 
16S rRNA 598 403 
18S rRNA 1769 1769 
28S rRNA 2267 2016 
COI 820 657 
Histone H3 327 327 
Table A2

Lagrange analyses.

Subtree: Pettalidae 
Areas: 
(a) South Africa 
(b) Chile 
(c) Eastern Australia 
(d) Western Australia 
(e) New Zealand, Australian plate 
(f) New Zealand, Pacific plate 
(g) Sri Lanka 
Geological intervals: 
(1) 0–35 Ma (disconnection of all landmasses) 
(2) 35–60 Ma (fragmentation of transantarctic connections between Australian plate and temperate South America) 
(3) 60–75 Ma (disconnection of Australia and Zealandia) 
(4) 75–110 Ma (disconnection of South America and West Africa) 
(5) 110–120 Ma (Sri Lanka + Madagascar + India separated from Africa) 
(6) 120–167 Ma (East Gondwana separated from West Gondwana) 
(7) 167–184 Ma (connection of all landmasses) 
Subtree: Sternophthalmi 
Areas: 
(a) Southeast USA 
(b) Amazonia 
(c) Tropical West Africa 
(d) New Caledonia 
Geological intervals: 
(1) 0–35 Ma (disconnection of all three landmasses) 
(2) 35–45 Ma (submersion of New Caledonia) 
(3) 45–60 Ma (New Caledonia emergent and disconnected) 
(4) 60–75 Ma (submersion of New Caledonia) 
(5) 75–110 Ma (transantarctic connections between the Australian plate and temperate South America; disconnection of South America and West Africa) 
(6) 110–206 Ma (connection of all landmasses) 
Subtree: Boreophthalmi 
Areas: 
(a) Thai-Malay Peninsula 
(b) Eastern Himalayas 
(c) Borneo 
(d) Indo-Malay Archipelago 
(e) North America 
(f) Western Europe 
(g) Mediterranean 
(h) Balkans 
(i) Iberia 
(j) Japan 
Geological intervals 
0–35 Ma (separation of Mediterranean plate from Western Europe; separation of Japan from Eurasia; connection of Iberia to Eurasia) 
35–45 Ma (separation of Borneo and Indo-Malay Archipelago from Eurasia) 
45–60 Ma (Balkans connected to Western Europe; Iberia connected to Mediterranean plate, Balkans and Japan) 
60–75 Ma (Iberia separated from Mediterranean plate, Balkans and Japan; North America separated from Western Europe; emergence of Indo-Malay Archipelago) 
75–110 Ma (Mediterranean plate separated from North America; Iberia connected to western Laurasia; Balkans separated from North America and Western Europe) 
110–120 Ma (Iberia disconnected from other landmasses; Western Europe, Mediterranean plate and North America separated from Eastern Laurasia; emergence of Borneo; Indo-Malay Archipelago nonexistent) 
120–180 Ma (Iberia disconnected from other landmasses; Western Europe, Mediterranean plate and North America separated from Eastern Laurasia; Borneo and Indo-Malay Archipelago nonexistent) 
180–250 Ma (Thai-Malay Peninsula disconnected from other landmasses; Eastern Himalayas disconnected from North America, Western Europe and Iberia; Borneo and Indo-Malay Archipelago nonexistent) 
250–296 Ma (Borneo and Indo-Malay Archipelago nonexistent; other landmasses connected) 
Subtree: Pettalidae 
Areas: 
(a) South Africa 
(b) Chile 
(c) Eastern Australia 
(d) Western Australia 
(e) New Zealand, Australian plate 
(f) New Zealand, Pacific plate 
(g) Sri Lanka 
Geological intervals: 
(1) 0–35 Ma (disconnection of all landmasses) 
(2) 35–60 Ma (fragmentation of transantarctic connections between Australian plate and temperate South America) 
(3) 60–75 Ma (disconnection of Australia and Zealandia) 
(4) 75–110 Ma (disconnection of South America and West Africa) 
(5) 110–120 Ma (Sri Lanka + Madagascar + India separated from Africa) 
(6) 120–167 Ma (East Gondwana separated from West Gondwana) 
(7) 167–184 Ma (connection of all landmasses) 
Subtree: Sternophthalmi 
Areas: 
(a) Southeast USA 
(b) Amazonia 
(c) Tropical West Africa 
(d) New Caledonia 
Geological intervals: 
(1) 0–35 Ma (disconnection of all three landmasses) 
(2) 35–45 Ma (submersion of New Caledonia) 
(3) 45–60 Ma (New Caledonia emergent and disconnected) 
(4) 60–75 Ma (submersion of New Caledonia) 
(5) 75–110 Ma (transantarctic connections between the Australian plate and temperate South America; disconnection of South America and West Africa) 
(6) 110–206 Ma (connection of all landmasses) 
Subtree: Boreophthalmi 
Areas: 
(a) Thai-Malay Peninsula 
(b) Eastern Himalayas 
(c) Borneo 
(d) Indo-Malay Archipelago 
(e) North America 
(f) Western Europe 
(g) Mediterranean 
(h) Balkans 
(i) Iberia 
(j) Japan 
Geological intervals 
0–35 Ma (separation of Mediterranean plate from Western Europe; separation of Japan from Eurasia; connection of Iberia to Eurasia) 
35–45 Ma (separation of Borneo and Indo-Malay Archipelago from Eurasia) 
45–60 Ma (Balkans connected to Western Europe; Iberia connected to Mediterranean plate, Balkans and Japan) 
60–75 Ma (Iberia separated from Mediterranean plate, Balkans and Japan; North America separated from Western Europe; emergence of Indo-Malay Archipelago) 
75–110 Ma (Mediterranean plate separated from North America; Iberia connected to western Laurasia; Balkans separated from North America and Western Europe) 
110–120 Ma (Iberia disconnected from other landmasses; Western Europe, Mediterranean plate and North America separated from Eastern Laurasia; emergence of Borneo; Indo-Malay Archipelago nonexistent) 
120–180 Ma (Iberia disconnected from other landmasses; Western Europe, Mediterranean plate and North America separated from Eastern Laurasia; Borneo and Indo-Malay Archipelago nonexistent) 
180–250 Ma (Thai-Malay Peninsula disconnected from other landmasses; Eastern Himalayas disconnected from North America, Western Europe and Iberia; Borneo and Indo-Malay Archipelago nonexistent) 
250–296 Ma (Borneo and Indo-Malay Archipelago nonexistent; other landmasses connected)