SEARCH

SEARCH BY CITATION

Keywords:

  • Africa ;
  • climate change ;
  • divergence times ;
  • extinction ;
  • incomplete taxon sampling ;
  • Madagascar ;
  • Miocene ;
  • Pleistocene ;
  • radiation ;
  • speciation

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Material and Methods
  5. Results
  6. Discussion
  7. Conclusion and Prospects
  8. Acknowledgements
  9. References

Extant clades may differ greatly in their species richness, suggesting differential rates of species diversification. Based on phylogenetic trees, it is possible to identify potential correlates of such differences. Here, we examine species diversification in a clade of 82 tropical African forest butterfly species (Cymothoe), together with its monotypic sister genus Harma. Our aim was to test whether the diversification of the HarmaCymothoe clade correlates with end-Miocene global cooling and desiccation, or with Pleistocene habitat range oscillations, both postulated to have led to habitat fragmentation. We first generated a species-level phylogenetic tree for Harma and Cymothoe, calibrated within an absolute time scale, and then identified temporal and phylogenetic shifts in species diversification. Finally, we assessed correlations between species diversification and reconstructed global temperatures. Results show that, after the divergence of Harma and Cymothoe in the Miocene (15 Mya), net species diversification was low during the first 7 Myr. Coinciding with the onset of diversification of Cymothoe around 7.5 Mya, there was a sharp and significant increase in diversification rate, suggesting a rapid radiation, and correlating with a reconstructed period of global cooling and desiccation in the late Miocene, rather than with Pleistocene oscillations. Our estimated age of 4 Myr for a clade of montane species corresponds well with the uplift of the Eastern Arc Mountains where they occur. We conclude that forest fragmentation caused by changing climate in the late Miocene as well as the Eastern Arc Mountain uplift are both likely to have promoted species diversification in the Harma–Cymothoe clade. Cymothoe colonized Madagascar much later than most other insect lineages and, consequently, had less time available for diversification on the island. We consider the diversification of Cymothoe to be a special case compared with other butterfly clades studied so far, both in terms of its abrupt diversification rate increase and its recent occurrence (7 Myr). It is clear that larval host plant shift(s) cannot explain the difference in diversification between Cymothoe and Harma; however, such a shift(s) may have triggered differential diversification rates within Cymothoe. © 2013 The Linnean Society of London, Biological Journal of the Linnean Society, 2013, ●●, ●●–●●.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Material and Methods
  5. Results
  6. Discussion
  7. Conclusion and Prospects
  8. Acknowledgements
  9. References

Extant clades may differ greatly in their species richness, suggesting differential accumulation of species over time, i.e. rate of species diversification. Based on phylogenetic trees, it is possible to identify potential correlates of such differential diversification. For example, some studies have suggested that tropical clades show higher species diversification rates (Cardillo, Orme & Owens, 2005; Wiens, 2007; Mullen et al., 2011; Condamine et al., 2012); others have found correlation between rates of species diversification and intrinsic factors, such as sexual dimorphism in shorebirds (FitzJohn, Maddison & Otto, 2009), geographical range in Californian plant communities (Goldberg, Lancaster & Ree, 2011), phenology in plants (Warren et al., 2011), climatic niche in salamanders (Kozak & Wiens, 2006, 2010) and sexual recombination in primroses (Johnson et al., 2011). Extrinsic factors can be palaeogeographical events (Couvreur et al., 2008; Bryson & Riddle, 2012), fire (Schnitzler et al., 2011) and climate change (Verboom et al., 2009; Schoville, Roderick & Kavanaugh, 2012). Phylogenetic methods enable the estimation of branching times on an absolute time scale, allowing the reconstruction of temporal dynamics of diversification (Rabosky, 2006b; Ricklefs, 2007). For example, species numbers may accumulate gradually or abruptly (i.e. a radiation) (Rokas, Krüger & Carroll, 2005; Alfaro et al., 2009; Paradis, 2011). Obviously, species diversification is the net result of speciation and extinction (Magallon & Sanderson, 2001), but the resolution of their relative contribution on the basis of a phylogenetic tree is problematic, mainly because the estimation of the rates of extinction is challenging without clear fossil evidence of extinct lineages (Rabosky, 2010). Nevertheless, net species diversification can be reliably estimated as long as significant phylogenetic sampling is achieved (Rabosky, 2006b).

For butterflies, species diversification rates have been considered to be influenced by both ecological (e.g. host plant shifts; Weingartner, Wahlberg & Nylin, 2006; Fordyce, 2010) and environmental factors, such as the formation of mountains (Hall, 2005; Mallarino et al., 2005; Wahlberg & Freitas, 2007; Casner & Pyrcz, 2010) and changing climate (Peña & Wahlberg, 2008; Aduse-Poku, Vingerhoedt & Wahlberg, 2009; Müller & Beheregaray, 2010; Condamine et al., 2012).

Here, we explore factors correlating with rates of net species diversification in two sister lineages of African forest butterflies. We selected the genera Harma Doubleday, 1848 and Cymothoe Hübner, 1819 (Nymphalidae, Limenitidinae), comprising a clade of butterflies confined to the forested regions of tropical Africa and Madagascar. Within this clade, we see a sister relationship between monospecific Harma and Cymothoe, comprising approximately 82 species (Ackery, Smith & Vane-Wright, 1995; Williams, 2012). Apart from their obvious difference in net species diversification, Harma and Cymothoe also differ in larval host plant associations. Within Cymothoe, roughly one-half of the species are highly specialized on particular species of Rinorea Aubl. (Violaceae, Malpighiales). Most are even monophagous (Fontaine, 1982; Amiet & Achoundong, 1996; McBride, van Velzen & Larsen, 2009). The other species of Cymothoe feed exclusively on species of Achariaceae (also Malpighiales), which are also host to Harma (van Son, 1979; Kielland, 1990; Larsen, 1991; Pringle, Henning & Ball, 1994; Amiet & Achoundong, 1996), suggesting that Achariaceae is the ancestral host plant group. With one-half of the Cymothoe species feeding on Achariaceae, it is obvious that a host shift to Rinorea cannot explain the difference in diversification between Cymothoe and Harma, regardless of the phylogenetic distribution of associations. Therefore, we can rule out plant host shifts as the probable factor influencing the observed patterns. With respect to most other ecological and morphological traits, species of Cymothoe and Harma are highly similar: they are all forest butterflies, frugivorous and sexually dimorphic. This points to a high degree of niche conservatism and, indeed, multiple species can usually be found in syntopy (i.e. living together at the same locality) as long as the relevant host plants are available (Amiet & Achoundong, 1996; Larsen, 2005). Within Cymothoe, egg clutch size is variable, but correlated with host plant use: most species feeding on Rinorea lay single eggs, possibly to minimize the risk of predation, whereas some species associated with cyanogenic Achariaceae lay clutches with dozens of eggs on the same leaf and their larvae live gregariously (Amiet, 2000).

Because nearly all species of Harma and Cymothoe are confined to wet forests (Larsen, 2005), (historic) forest fragmentation could potentially have led to reproductive isolation with subsequent allopatric speciation in this clade. For example, sister species C. egesta Cramer, 1775 and C. confusa Aurivillius, 1887 show only a small zone of overlap in Cameroon, and population genetic analyses suggest that they have allopatric origins (McBride et al., 2009). In another case, the closely related species C. caenis Drury, 1773 and C. druryi van Velzen & Larsen, 2009 are also geographically separated (van Velzen, Larsen & Bakker, 2009), again suggesting allopatric speciation. Over geological time scales, Africa has experienced large fluctuations in climate and associated vegetation cover (Coetzee, 1993; Jacobs, 2004; Segalen, Lee-Thorp & Cerling, 2007). The earliest evidence for angiosperm rainforest in Africa is from the Palaeocene (55–65 Mya), after which the lowland forest biome reached a peak in the late Eocene and Oligocene (23–40 Mya; Jacobs, 2004). As a result of closing of the Tethys seaway and changes in tropical ocean currents and ensuing global cooling (Rommerskirchen et al., 2011; Zhang et al., 2011), the grass-dominated savannah biome began to expand in the middle Miocene (16 Mya). It became widespread in the late Miocene (8 Mya) at the expense of wet forest habitat (Morley & Richards, 1993; Senut, Pickford & Segalen, 2009). Subsequent Pleistocene climatic fluctuations are considered to have resulted in cycles of fragmentation and expansion of the areas occupied by lowland rain forest (Dupont et al., 2000; Cohen et al., 2007; Dupont, 2011). Given the apparent niche conservatism of Harma and Cymothoe with respect to forest habitats, and given the approximate age of Limenitidinae at around 57 Myr (Wahlberg et al., 2009), climatic events are therefore probable candidates of environmental factors influencing their diversification.

Our aims were to test whether the diversification of the HarmaCymothoe clade correlates with postulated habitat fragmentation caused by end-Miocene global cooling and desiccation, or with postulated Pleistocene habitat range oscillations. In order to address this, we: (1) generated a species-level molecular phylogenetic tree for Harma and Cymothoe, calibrated within an absolute time scale; (2) identified temporal and phylogenetic shifts in species diversification; and (3) assessed correlations between species diversification and reconstructed global temperatures and habitats.

Material and Methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Material and Methods
  5. Results
  6. Discussion
  7. Conclusion and Prospects
  8. Acknowledgements
  9. References

Taxon sampling

We included 52 species of Cymothoe (covering 63% of the known extant species) and monospecific Harma in our study, mostly from newly collected specimens, either collected by RvV or kindly donated by a network of collectors (see Acknowledgements), or from museum specimens obtained from the African Butterfly Research Institute (ABRI) (Nairobi, Kenya), Royal Museum for Central Africa (RMCA) (Tervuren, Belgium) and Natural History Museum (London, UK). Identifications were based on Larsen (2005), Vande Weghe (2010) and Berger (1981), and facilitated by a library of 1000+ Cymothoe DNA barcodes (van Velzen et al., unpubl. data). We effectively sampled all species that are morphologically divergent or represent major lineages based on adult and larval morphology (Amiet, 2000). Although relationships between the HarmaCymothoe clade and other Limenitidinae are largely unknown, we chose representatives from three different Limenitidinae tribes as outgroup: Neptis ida Moore, 1858 (Neptini), Lebadea martha Fabricius, 1787 (incertae sedis) and Limenitis reducta Staudinger, 1901 (Limenitidini), resulting in a total of 56 taxa for which the accession, locality and other meta data are given in Appendix 1.

Molecular methods

We extracted DNA from one or two legs, paper-dried or freshly preserved in 96% ethanol, using the QIAgen DNeasy Blood & Tissue Kit, according to the manufacturer's instructions. We sequenced five genes that are known to be informative at the species and genus level (Peña & Wahlberg, 2008; Wahlberg et al., 2009): cytochrome c oxidase subunit I (COI) from the mitochondrial genome; wingless (wgl), ribosomal protein S5 (RpS5), glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and isocitrate dehydrogenase (IDH) from the nuclear genome. Primers and laboratory protocols were taken from Wahlberg & Wheat (2008). Direct sequencing of polymerase chain reaction (PCR) products was performed on an Applied Biosystems 3170xl Genetic Analyser at the University of Turku, or sent to Macrogen (Seoul, South Korea) for sequencing. The resulting chromatograms were examined by eye in BioEdit (Hall, 1999). All five genes are protein coding, and thus alignment was trivial. GenBank accession numbers of the DNA sequences are given in Appendix 1.

Phylogenetic inference

Congruence tests

We tested the null hypothesis of congruence of the phylogenetic signal between genes using the incongruence length difference (ILD) test (Farris et al., 1994, 1995; Cunningham, 1997) as implemented by the partition homogeneity test in PAUP* 4.0b10 (Swofford, 2003). For all ILD tests, uninformative (invariant and autapomorphic) characters were excluded and heuristic searches with random taxon sampling and tree bisection–reconstruction branch swapping were conducted. To establish a null distribution for each test, 1000 randomized data partitions of equal size to the originals were generated and ILDs were calculated for each replicate. The threshold for significance was a P value of 0.01.

Model testing

We determined the relative fit of candidate models of nucleotide evolution for each gene and genomic compartment (mitochondrial versus nuclear) using JModelTest 0.1.1 (Posada, 2008). Three different substitution models (HKY, K80 and GTR) were tested, with or without estimated base frequencies, gamma-shaped distribution of rates (four categories) and proportion of invariant sites – amounting to assessments of 24 different models. Models were optimized on maximum likelihood (ML) trees, and best-fitting models of nucleotide evolution were selected on the basis of the Akaike Information Criterion (AIC). Best-fitting models per partition are given in Table 1.

Table 1. Character partitions, their characteristics and models selected for phylogenetic inference
PartitionNo. of taxaTotal no. of charactersNo. of informative charactersModel
  1. COI, cytochrome c oxidase subunit I; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; IDH, isocitrate dehydrogenase; RpS5, ribosomal protein S5; wgl, wingless.

mtDNA COI561475349HKY + G
nDNA562366391K80 + I + G
● wgl50363363SYM + I + G
● GAPDH46692104GTR + I + G
● RpS54959777GTR + I + G
● IDH21714116GTR + G
Inference

We estimated phylogenetic trees for each gene and genomic compartment using Bayesian inference (BI) and maximum likelihood (ML) methods. We performed BI using MrBayes 3.1.2 (Ronquist & Huelsenbeck, 2003), executing two independent Markov-chain Monte Carlo (MCMC) runs with four Metropolis-coupled chains each for 20 million generations and sampling every 1000 generations. Convergence of the two independent MCMC runs was assessed topologically (i.e. based on clade frequencies) using the online service AWTY (Nylander et al., 2008) and based on model parameters using Tracer 1.5 (Rambaut & Drummond, 2009). The first 2 million generations (10%) were discarded as burn-in before calculation of a 50% majority-rule consensus based on the posterior set of trees. We performed ML using Garli 2.0 (Zwickl, 2006) with 16 independent search replicates, random starting trees and stopping each search when no better tree was found in 20 000 generations. Population and mutation settings for the genetic algorithm in Garli were left at their default values. In case only one best tree was found, search replicates were incremented by eight until the best likelihood score was found multiple times independently. To estimate branch support, we performed 100 bootstrap pseudo-replicates with a single search per pseudo-replicate. Bootstrapped trees were combined into a single file to calculate bootstrap values for all nodes. All BI and ML analyses were run on the online CIPRES science gateway (Miller, Pfeiffer & Schwartz, 2010).

Congruent data were combined and partitioned according to gene and genomic compartment. Phylogenetic trees based on the combined data were inferred using BI with 40 million generations per MCMC run and ML with 16 search replicates. Partitioning schemes were compared using Bayes factors between BI marginal likelihoods.

Timing of divergences

Time-calibrated phylogenetic trees were inferred using BEAST (Drummond & Rambaut, 2007) at the online CIPRES science gateway (Miller et al., 2010). Analyses were based on combined data partitioned per genomic region and per gene. Because Limenitidinae fossils are unknown and hence unavailable for node calibration, we used a putative secondary time calibration based on a recent study of the evolutionary history of Nymphalidae using host plant ages and six butterfly fossils (Wahlberg et al., 2009). This study had an estimate for the HarmaCymothoe clade of 15.09 Mya [95% highest posterior density (HPD) interval = 8.21–22.77 Mya]. We set a prior distribution for the age of that clade accordingly, which followed a log-normal distribution with a log(mean) of 2.83 and a log(standard deviation) of 0.26 Mya. Relaxed log-normal clocks were estimated for each genomic region separately to accommodate differences in mean substitution rates between mitochondrial and nuclear DNA. The HarmaCymothoe clade was constrained to be monophyletic and we set a Yule prior on speciation with a uniform distribution between ‘0’ and ‘5’ for birth rate. To avoid problems associated with long branches, only Neptis was included as outgroup. Because uniform prior distributions for the mean substitution rates caused overestimation of age estimates in preliminary runs, we set a diffuse prior following a gamma distribution with a mean of unity and a shape parameter of 0.001. All other priors were left at their default settings. We performed four independent MCMC runs with random starting trees, 40 million generations per run and sampling every 10 000 generations. The first 4 million generations (10%) of each run were discarded as burn-in.

Diversification analyses

Adding missing taxa

Diversification measures assume complete species sampling, whereas our phylogenetic dataset includes only 63% of all extant species. Missing data are a common phenomenon in evolutionary studies and ignoring them can compromise analyses and produce incorrect results (Pybus & Harvey, 2000; Nakagawa & Freckleton, 2008; Garamszegi & Møller, 2011). There are various techniques for correcting incomplete species sampling in diversification studies. Some deal with missing species directly, either by assuming that species sampling is random (FitzJohn et al., 2009), or by considering clades with missing species as unresolved (‘terminally unresolved trees’) (Alfaro et al., 2009; FitzJohn et al., 2009). Others generate a null distribution by randomly pruning taxa from simulated data with complete sampling (Harmon et al., 2008), or add missing species to phylogenetic trees before analysis (e.g. Purvis, Nee & Harvey, 1995; Barraclough & Vogler, 2002; Day, Cotton & Barraclough, 2008). A problem here is that estimates of speciation and extinction rates can be influenced by the way in which missing species are placed on the phylogenetic tree (Cusimano, Stadler & Renner, 2012). Cusimano et al. (2012) proposed a technique of simulating missing species under speciation/extinction models, thereby overcoming this problem. However, the missing species are simulated as branching times only and thus cannot be used for topology-based analyses. We corrected for missing species by adding missing taxa as empty sequences at the tree inference stage in a Bayesian framework (Kuhn, Mooers & Thomas, 2011). This has the advantage that the full suite of Bayesian phylogenetic tools (e.g. clock models, molecular evolutionary parameters, priors on tree topology) can be incorporated into the tree-building process together with the missing taxa (Kuhn et al., 2011). In addition, it allows for the retention of data from all sampled species, contrary to the terminally unresolved tree approach (e.g. Alfaro et al., 2009; FitzJohn et al., 2009), thus taking all available phylogenetic data into account. We included 16 missing taxa in the dataset as three ‘N’ codes (for each of the markers COI, wgl, RpS5, GAPDH and IDH), and a short piece of COI (the DNA barcode) for an additional 13 species, amounting to a total of 82 species of Cymothoe. Phylogenetic placement of missing species was controlled through monophyly constraints derived from morphological and taxonomic information (Amiet, 2000; Larsen, 2005) and implemented in BEAST. Hence, MCMC operators could move missing taxa at liberty, but in accordance with monophyly constraints and the Yule prior on speciation (Kuhn et al., 2011). All other settings were the same as for the divergence time analyses. Obviously, because of the implementation of a Yule prior, the resulting posterior set of trees is biased towards a constant rate of diversification. Because rate constancy is the typical null model for diversification rate analyses, the bias will be conservative, however (Kuhn et al., 2011).

Temporal shifts in diversification

A lineage-through-time (LTT) plot based on the posterior set of trees with complete species sampling was generated using Tracer 1.5 (Rambaut & Drummond, 2009), and compared with trends of global temperatures using oxygen isotope fractionation data in Benthic foraminifera from Zachos et al. (2001), which serve as a proxy for the total global mass of glacial ice sheets and temperature.

To test for a temporal shift in diversification rate, we fitted a candidate set of rate-constant (Yule and birth–death) and rate-variable (DDX, DDL and Yule-2-rate) diversification models to the posterior set of trees using the R package LASER (Rabosky, 2006a). We recorded the decrease in AIC (ΔAIC) of the best-fitting rate-variable model compared with the best-fitting rate-constant model as the test statistic (better fitting models have lower AIC scores). In order to avoid Type I errors, the observed ΔAIC test statistics were compared with a null distribution of ΔAIC values based on fitting the same models on trees simulated under a constant-rate Yule model (Rabosky, 2006b).

Phylogenetic shifts in diversification

To test for branch-specific shifts in diversification rate, we fitted a candidate set of phylogenetically nested diversification models with increasing complexity to the posterior set of trees using stepwise AIC in the R package MEDUSA (Alfaro et al., 2009). We set the maximum of fitted models to five (modelLimit = 5) and selected the best-fitting model that resulted in an improvement in AIC score above a threshold of 4.248. This corrected threshold ensures a significant increase (P < 0.05) in model fit for trees with 82 tips, and was calculated automatically by MEDUSA.

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Material and Methods
  5. Results
  6. Discussion
  7. Conclusion and Prospects
  8. Acknowledgements
  9. References

Phylogenetic inference

Congruence tests

Although the ILD test is generally susceptible to Type I errors (Darlu & Lecointre, 2002) the null hypothesis of homogeneity between gene datasets was not rejected (P > 0.01; a < 0.001; see Table 2). Therefore, the gene datasets were combined to maximize explanatory power.

Table 2. P values of incongruence length difference (ILD) tests showing phylogenetic congruence between data partitions
 mtDNA COIwglGAPDHRpS5IDH
  1. COI, cytochrome c oxidase subunit I; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; IDH, isocitrate dehydrogenase; RpS5, ribosomal protein S5; wgl, wingless.

wgl0.9910    
GAPDH0.80400.0160   
RpS51.00000.05400.4720  
IDH1.00000.98601.00000.9960 
nDNA0.36800.29500.17400.23001.0000
Inference

Trees based on different genes and genomic compartments were congruent and we found no conflict between trees inferred under ML and BI. All BI converged, except for the analyses partitioned according to genes which, although they gave highest marginal likelihood values overall, experienced reduced convergence and mixing (measured as low effective parameter sampling sizes and exchange rates between chains). In order to improve exchange rates and mixing, we re-ran the analyses with a heating temperature reduced from 0.20 to 0.10, but to no effect. Overparameterization is known to impede convergence of Bayesian MCMC (Rannala, 2002), and we suspect that this is also the case here. For these reasons, we report BI results based on combined data partitioned according to genome, despite their smaller marginal likelihoods.

Phylogenetic patterns

All inferred phylogenetic trees confirm that Harma and Cymothoe are sisters on a relatively long branch within Limenitidinae, with Neptis ida as the closest outgroup. The backbone of the clade comprising Cymothoe is largely unresolved (i.e. its nodes have low or no support) with relatively short branches (see Fig. 1). Below this backbone, eight clades are recovered with high support [i.e. posterior probability (PP) of 1.00] and correlate with previous classifications based on morphology (Amiet, 2000). The Coccinata clade (COC) consists of species characterized by a small wing span and an orange to orangey-red ground colour of the males. The West African endemics C. hartigi Belcastro, 1990 and C. mabillei Overlaet, 1944 appear to be closely related and sister to all other species in the COC clade. The Adela clade (ADE; medium wing span, ochrous males) consists of two geographically separated pairs of sister species: a pair from West Africa, with C. adela occurring in the Liberian and C. aubergeri Plantrou, 1977 occurring in the Ghana subregion, and a pair from Central Africa, with C. fontainei Overlaet, 1952 occurring from Cameroon to central Democratic Republic of the Congo (DRC) and C. collarti Overlaet, 1942 occurring in the Kivu and Maniema provinces in eastern DRC and in Rwanda. The Sangaris clade (SAN; small, blood-red) consists of species whose males are highly similar, but whose females are morphologically variable. The morphologically similar C. ogova Plötz, 1880 and the divergent C. harmilla Hewitson, 1874 appear to be related to this SAN clade. The Egesta clade (EGE; large, yellow) consists of the sister species C. egesta and C. confusa, which are characterized by the males having an almost black transversal band over all wings. The morphologically similar but uncommon C. orphnina Karsch, 1894 (unsampled) is also expected to be a member of this clade. The Fumana clade (FUM; large, yellow) consists of C. fumana Westwood, 1850, C. haynae Dewitz, 1887 and C. superba Aurivilius, 1898, which are characterized by the males having a mostly dark hindwing. Within the Caenis clade (CAE; small, creamy-white), the morphologically similar C. consanguis Aurivillius, 1896 and C. althea Cramer, 1776 appear to be sisters. The Lurida clade (LUR; large, ochrous-yellow or ochrous-orange) is characterized by an acutely angled forewing apex. Within this clade, the ochrous-orange C. hesiodotus Staudinger, 1890 and C. nigeriensis Overlaet, 1942 appear to be closely related and sister to the four ochrous-yellow species. The extremely rare C. hesiodina Schultze, 1908 (unsampled) is probably also related to this clade. The Herminia clade (HER; small, creamy-white) consists of the morphologically similar sister species C. herminia Grose-Smith, 1887 and C. weymeri Suffert, 1904, which both occur from West Africa to the Albertine Rift, and of the East African C. coranus Grose-Smith, 1889. Relationships of morphologically divergent C. ochreata Grose-Smith, 1890, C. lucasi Doumet, 1859, C. heliada Hewitson, 1874, C. indamora Hewitson, 1866, C. beckeri Herrich-Schaeffer, 1858, C. jodutta Westwood, 1850, C. reinholdi Plötz, 1880, C. hyarbita Hewitson, 1866 and C. altisidora Hewitson, 1869 remain unresolved.

figure

Figure 1. Phylogenetic tree based on combined data partitioned according to genome. Branch labels indicate posterior clade probabilities higher than 0.50; highlighted clades have high support and are consistent with previous classifications based on morphology (Amiet, 2000).

Download figure to PowerPoint

Timing of divergences

The most recent common ancestor of extant lineages of Cymothoe is estimated at 7.13 Mya (see Fig. 2). Most crown clades described in the previous section originate not long after: CAE (see Fig. 2) is the oldest at 4.65 Myr, followed by AUR at 4.19 Myr, COC at 3.63 Myr, ADE at 2.85 Myr, HER at 2.39 Myr and LUR at 2.2 Myr. The clades FUM (1.23 Myr) and SAN (1.17 Myr) are the youngest. Isolated species are also relatively old within the genus, the lineage leading to the Malagasy endemic C. lambertoni Oberthür, 1923 being most notable with an estimated age of 7.13 Myr, but this may be an artefact of its proportionally long branch compared with all other species, pushing it backwards in time in the relaxed clock analysis. The lineage leading to C. indamora is 5.96 Myr old; C. heliada is 5.7 Myr old; C. jodutta is 5.4 Myr old; C. lucasii is 4.5 Myr old. The other morphologically divergent species C. beckeri, C. hyarbita, C. altisidora, C. oemilius and C. reinholdi appear as a clade here [PP = 0.94, the most recent common ancestor (TMRCA) = 4.8 Mya], with the last two species being sisters (PP = 0.98) of 3.1 Myr old. In addition, the East and South African endemics C. teita van Someren, 1939, C. baylissii ined. and C. alcimeda Godart, 1824 appear as a clade (PP = 0.94, TMRCA = 4.2 Mya). Other East African montane endemics, such as C. aurivillii Staudinger, 1899 (unsampled), are morphologically very similar to C. teita and are also expected to be members of this Aurivillius (AUR) clade.

figure

Figure 2. Time-calibrated maximum clade credibility tree. Branch labels indicate posterior clade probabilities higher than 0.50; vertical bars mark clades that have high support (posterior probability, 1.00) and are consistent with previous classifications based on morphology (Amiet, 2000). Inset shows species diversification rates in the Cymothoe and Harma clade (top) as a lineage-through-time (LTT) plot based on the posterior set of trees. Full line shows the number of lineages based on complete species sampling [shaded area indicates 95% highest posterior density (HPD) interval]; broken line shows number of lineages based on divergence time analysis with incomplete species sampling. Bottom: global temperature through time, as oxygen isotope fractionation patterns in Benthic foraminifera, which serve as a proxy for the total global mass of glacial ice sheets and temperature; redrawn from Zachos et al. (2001).

Download figure to PowerPoint

Diversification analyses

Temporal shifts in diversification

After the divergence of the Harma and Cymothoe lineages in the Miocene, net species diversification was low during the first 7 Myr, followed by a sharp increase coinciding with the onset of diversification of extant lineages of Cymothoe around 7.5 Mya (95% HPD interval = 3.68–11.97 Mya). The increased rate of net speciation correlates with a reconstructed global trend of gradual cooling (Zachos et al., 2001) (see Fig. 2), consistent with a late Miocene rather than Pleistocene timeframe.

Our LASER analyses indicated that rate-variable models of diversification fitted our data best in 14 272 of 14 400 posterior trees (99.1%), with pure-birth (i.e. Yule) being the best-fitting rate-constant model (97.8%) and Yule-2-rate being the best rate-variable model (99.7%). The mean ΔAIC was 5.94, indicating that rate-variable models have a much better fit to our data than rate-constant models (P = 0.070) (see Fig. 3). Fitting the Yule-2-rate model to our data revealed a temporal shift with a five-fold increase in the mean diversification rate.

figure

Figure 3. Temporal (inset) and phylogenetic shifts in diversification of the CymothoeHarma clade. Maximum clade credibility tree based on complete species sampling (i.e. including missing taxa). Branch colours indicate relative branch-specific diversification rates as reconstructed with MEDUSA: blue indicates low rates, red indicates high rates and black indicates generally high but sometimes low rates (see text). Broken lines subtend missing species for which only the cytochrome c oxidase subunit I (COI) DNA barcode was available; dotted lines subtend missing species for which no sequence data were available (empty sequences). Branch labels indicate posterior clade probabilities higher than 0.50; black squares indicate clade monophyly constraints restricting the phylogenetic placement of missing species. Please note that the placement of empty sequences is not based on data and that clades within constrained clades consequently have low posterior probabilities. Inset: deviation in ΔAIC values of a distribution based on empirical phylogenetic trees (green) from a null distribution based on trees simulated under a rate-constant (Yule) model (grey). AIC, Akaike Information Criterion.

Download figure to PowerPoint

Phylogenetic shifts in diversification

Our MEDUSA analyses indicated that a model incorporating branch-specific shifts in diversification rates gave a significantly better fit than a constant-rate model on all 14 400 posterior trees (100%). A single rate shift in diversification rate was optimized on 14 074 posterior trees (97.7%), two rate shifts on 324 (2.3%) trees and three rate shifts on the two remaining trees. The first (or only) shift constituted a rate increase coinciding with the Cymothoe clade (76.2%), or with the Cymothoe clade excluding the lineage leading to C. lambertoni (9.1%), C. indamora (5.4%) or both the C. lambertonii lineage and C. indamora (9.2%) (see Fig. 3). When two rate shifts were optimized, the second shift generally constituted a rate decrease coinciding with the C. lambertonii lineage (1.9%) or the C. lambertonii lineage and C. indamora combined (0.2%) within Cymothoe. As mentioned earlier, both lineages are subtended by relatively long branches, explaining their estimated low diversification rate compared with the rest of the Cymothoe clade.

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Material and Methods
  5. Results
  6. Discussion
  7. Conclusion and Prospects
  8. Acknowledgements
  9. References

Based on our analyses, we inferred a significant shift in species diversification rate of Cymothoe butterflies consistent with the late Miocene (7.5 Mya). To date, estimates of such diversifications in butterfly clades have been scarce (see below) and the pattern of diversification in Cymothoe and Harma is special in two ways. First, the estimated age is relatively young as, in general, most butterfly genera are thought to have diversified after the Cretaceous–Palaeogene (K/Pg) boundary at 65 Mya (Wahlberg, 2006; Heikkila et al., 2012). This is echoed from various dating studies conducted over the last decade, indicating Eocene to mid-Miocene timeframes for most butterfly clades. Within Papilionidae, the genus Papilio (193 spp.) is thought to have diversified in the Oligocene (23–35 Mya) and Parnassius (38 spp.) originated in the early Miocene (13–21 Mya) (Nazari & Sperling, 2007; Condamine et al., 2012). Within the Nymphalidae family, genera have diversified to produce extant species from the mid-Eocene (47 Mya) to present (Wahlberg et al., 2009). The subfamily Satyrinae diversified in the Oligocene (23–36 Mya), coinciding with the spread of their grass host plants (Peña & Wahlberg, 2008), with the Satyrini tribe undergoing a rapid radiation between 32 and 24 Mya (Peña, Nylin & Wahlberg, 2011) and the Dirini tribe experiencing elevated diversification rates at 24–29 Mya (Price et al., 2011). Genera of the Nymphalinae subfamily appear to have diversified during the early Miocene, with species diversification starting at 23 Mya in the American subtribe Phyciodina (89 spp.) (Wahlberg & Freitas, 2007), 21.7 Mya in Melitaea (Leneveu, Chichvarkhin & Wahlberg, 2009) and 20 Mya in Junonia (Kodandaramaiah & Wahlberg, 2007). Within Limenitidinae, the latitudinal gradient of species richness observed in Adelpha butterflies is the result of an increased diversification rate in the mid-Miocene (10–15 Mya) (Mullen et al., 2011). Finally, within the subfamily Danainae, the genera Ithomia (14.4 Mya) and Napeogenes (12.7 Mya) started to diversify in the Andes in the mid-Miocene (Elias et al., 2009). In contrast, the relatively young age of Cymothoe diversification appears to be rare and only consistent with two other studies: the Asian tropical Lycaenidae genus Arhopala (over 120 spp.), where large-scale climatic changes in the Miocene were hypothesized to have induced its initial diversification between 7 and 11 Mya (Megens et al., 2004), and the Indo-Australian Pieridae genus Delias Hübner (165+ spp.), where species diversification showed an increase during the Pliocene–Pleistocene, starting around 7 Mya (Braby & Pierce, 2007). However, the mean diversification rate in Cymothoe is much higher than that of Delias, as the latter already comprised around 25 species before the inferred rate increase (Braby & Pierce, 2007).

Second, the increase in Cymothoe diversification rate is abrupt. Not only is there a 5-fold increase in the mean rate of species diversification, it also appears to be instantaneous on an evolutionary timescale, suggesting a rapid radiation (Rokas et al., 2005). Most other species-level butterfly clades show a more gradual shift in diversification rates (e.g. Elias et al., 2009; Leneveu et al., 2009) and, although the rate of species diversification in the genus Arhopala, with 120 extant species in 11 Myr, has been higher than in Cymothoe, it is unclear whether it constitutes a significant shift when compared with diversification rates in sister clades within Lycaenidae–Theclinae (Megens et al., 2004).

Diversification rate versus phylogenetic resolution

The first branches within the Cymothoe clade have low phylogenetic resolution (Fig. 1), which can be attributed to a lack of data, or to a near-simultaneous divergence of multiple lineages (hard polytomies). Coalescent theory predicts that short internal branches are prone to incomplete lineage sorting effects (Degnan & Rosenberg, 2009). Because short internal branches are inherent to a high diversification rate, a negative correlation between diversification rate and phylogenetic resolution can be expected (Rokas et al., 2005; Whitfield & Kjer, 2008; Kodandaramaiah et al., 2010), which is confirmed by our data. We therefore hypothesize that the lack of resolution within Cymothoe is inherent to its phylogenetic structure and that the addition of more sequence data will not solve the gene incongruences because they might well be caused by incomplete lineage sorting. Methods have been developed that accommodate for incomplete lineage sorting by consolidating gene trees with a species tree (e.g. Liu & Pearl, 2007; Heled & Drummond, 2010). However, effective population size is an essential parameter for these methods and we expect that the estimation of ancestral population size for deeper internal branches is almost impossible. We therefore do not expect these methods to provide a solution to this problem, and conclude that the resolution of branches within a rapidly diversifying clade remains a methodological challenge, even at recent timescales.

Speciation versus extinction

Can the inferred shift in species diversification be explained by a difference in speciation rate or, alternatively, in extinction pruning lineages from the stem? Based on birth–death models, our estimates of extinction rates for Harma as well as for Cymothoe approach zero, suggesting that differences in diversification are mainly a result of speciation. There is a general notion, however, that phylogenetic methods are not adequate for the estimation of extinction rates (Rabosky, 2010), and this is probably even more true for stem groups. Nevertheless, elevated rates of extinction before the late Miocene seem to be less likely because the Miocene experienced a relatively stable hot and wet climate (Zachos et al., 2001), promoting habitats suitable for tropical forest butterflies. We therefore hypothesize that the diversification shift is mainly a result of an elevated rate of speciation rather than extinction of stem lineages.

Cymothoe diversification and climate change

We infer that the shift in species diversification within the CymothoeHarma clade correlates with a period of global cooling and desiccation since the late Miocene (see Fig. 2). Increased diversification continued into the Pleistocene and some of the younger clades (i.e. HER, LUR, FUM, SAN) appear to have a Pleistocene origin. Nevertheless, as the rate of diversification appears to decrease after the onset of the Pleistocene, the reconstructed shift of diversification in the HarmaCymothoe clade correlates with global cooling rather than with Pleistocene climatic oscillations (see Fig. 2). In Africa, end-Miocene climatological changes led, in part, to the expansion of savannah at the expense of forest (Jacobs, 2004; Segalen et al., 2007; Senut et al., 2009). Indeed, cuticle and pollen records from Nigeria suggest that late Miocene desiccation may have been responsible for the extinction of much of the West African humid tropical flora (Morley & Richards, 1993), and the forest habitat of Harma and Cymothoe, which must have been largely continuous throughout most of the Miocene, thus became fragmented (Jacobs, 2004). Given the niche conservatism within the HarmaCymothoe clade, we may assume that this led to reproductive isolation of populations. Indeed, many species of Cymothoe are currently confined to particular geographical regions (Larsen, 2005), suggesting a predominantly allopatric mode of speciation (McBride et al., 2009). For Cymothoe, important regions of endemism are found in West, Central and East Africa and on Madagascar, with closely related species often occurring in different regions (McBride et al., 2009; van Velzen et al., 2009). Similar patterns of major splits of forest lineages in the late Miocene have been found in African plants (Plana et al., 2004; Couvreur et al., 2011) and birds (Njabo, Bowie & Sorenson, 2008; Nguembock et al., 2009), suggesting that there may be a general trend for African lowland forest clades.

In Cymothoe, the AUR clade consists of species that are endemic to particular montane forests in the Eastern Arc Mountains. Its estimated age of 4.19 Myr correlates with the maximum of the Eastern Arc Mountain uplift (Sepulchre et al., 2006), suggesting that geology may have driven fragmentation and diversification in this clade. A similar case was found in the Andean butterfly genus Lymanopoda (Nymphalidae, Satyrinae), where species diversification was estimated to coincide with Andean orogeny (Casner & Pyrcz, 2010).

Species diversification in the lineage leading to the Malagasy endemics C. lambertoni and C. dujardini Viette, 1971 was inferred by us to be slow compared with most other Cymothoe clades. As rainforest fragmentation may have been much less severe on Madagascar than on continental Africa until the last few thousand years, reproductive isolation probably played a lesser role on the island. The stem age for the C. lambertonii lineage is estimated at 7.13 Myr, but it is well conceivable that the lineage colonized Madagascar long after this split, with subsequent extinction of the ancestor on the mainland. In any case, Cymothoe colonized Madagascar much later than most insect lineages (15–64 Mya) (Kodandaramaiah et al., 2010; Wirta et al., 2010; Sole et al., 2011; Condamine et al., 2012). Furthermore, where most other Malagasy clades are large (Vences et al., 2009), the C. lambertonii lineage consists of only two species. This can be attributed either to the fact that Cymothoe had less time to diversify, or encountered fewer unoccupied niches on the island. Given our age estimates and assuming exponential accumulation of species (sensu Magallon & Sanderson, 2001), the net diversification rate of Cymothoe (two species in 7 Myr) was comparable with that of Heteropsis (46 species in 20 Myr; Kodandaramaiah et al., 2010), suggesting that time was the overriding factor. An alternative, adaptationist, explanation is that, whereas Malagasy radiations usually comprise species adapted to the many different habitats on the island, the C. lambertonii lineage, stemming from a ‘true’ forest butterfly clade, apparently did not. Possibly, there are additional cryptic Cymothoe species on Madagascar, as was found for Malagasy Satyrines (Kodandaramaiah et al., 2010) and for other Cymothoe lineages in Africa (van Velzen, Bakker & van Loon, 2007; McBride et al., 2009; van Velzen et al., 2009). A better understanding of the evolution, specific status and historical biogeography of the C. lambertonii lineage requires future study with increased specimen sampling.

Alternative factors, such as changes in environmental niche (Kodandaramaiah et al., 2010) and habitat elevation (Hall, 2005), have been found to promote diversification in other butterfly clades. However, because all Cymothoe species appear to occupy the same niche within lowland rainforest habitats, we suspect that these factors did not play a major role in their diversification. Alternatively, wing colour was found to promote speciation in mimetic butterflies (Jiggins, 2008). Within Cymothoe, C. beckeri females mimicking the day-flying geometrid moths in the genus Otroeda (Larsen, 2005) are the only documented mimics. Females of most other species, including Harma theobene, are more or less cryptic. Therefore, crypsis and mimicry do not correlate with differential diversification in Cymothoe and Harma. We cannot rule out other, more ad hoc, explanations for the inferred high diversification rate in Cymothoe. For instance, premating behaviour (Merrill et al., 2011) and microhabitat (e.g. canopy versus understorey oviposition site) could have effects on speciation (Grill et al., 2006). In addition, past genetic ‘catastrophic’ events, such as chromosomal rearrangements (Kandul et al., 2007; Escudero et al., 2012), or the presence of Wolbachia (e.g. Werren, 2003), could have contributed to reproductive isolation, and hence elevated rates of net diversification. However, as we lack data on these factors in Cymothoe, we can only speculate here, and instead consider our inferred correlation with late Miocene climate change as the best possible explanation.

Why Harma has not responded similarly to African habitat fragmentation remains unclear. Harma theobene represents a ‘true’ species genetically as, based on extensive geographical sampling, no mitotypes were encountered (van Velzen et al., unpubl. data). Nevertheless, within the entire clade, it is currently the most widespread species geographically. In addition, in contrast with all Cymothoe (except C. caenis), which are confined to primary forests, H. theobene occurs in forests as well as in secondary habitats (Larsen, 2005). These observations suggest that Harma may be a better disperser and hence less prone to reproductive isolation, possibly explaining its lack of diversification in the last 15 million years.

Conclusion and Prospects

  1. Top of page
  2. Abstract
  3. Introduction
  4. Material and Methods
  5. Results
  6. Discussion
  7. Conclusion and Prospects
  8. Acknowledgements
  9. References

We conclude that forest fragmentation caused by changing climate in the late Miocene, as well as by Eastern Arc Mountain uplift, is likely to have promoted species diversification in Cymothoe. We consider the diversification of Cymothoe to be a special case when compared with other butterfly clades studied so far, both in terms of its abrupt diversification rate increase and its recent occurrence (7 Mya). Cymothoe colonized Madagascar much later than most other insect lineages and, consequently, had less time available for diversification on the island. It is clear that host shift(s) to Rinorea cannot explain the difference in diversification between Cymothoe and Harma; however, such a shift(s) may have triggered differential diversification rates within Cymothoe, which will be the subject of further study.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Introduction
  4. Material and Methods
  5. Results
  6. Discussion
  7. Conclusion and Prospects
  8. Acknowledgements
  9. References

We thank Pavel Matos for help in the laboratory. Specimens or samples used for this study were kindly donated by Julian Bayliss, Dries Bonte, Oskar Brattström, Steve Collins, Torben Larsen, Freerk Molleman, Renske Onstein, Sáfián Szabolcs, Robert Warren, Gael vandeWeghe, Steve Woodhall and Jan Wieringa. Marleen Botermans gave valuable comments on early drafts of the manuscript. RvV acknowledges the Alberta Mennega Foundation, Hugo de Vries Foundation, Systematics Research Fund (awarded jointly by the Systematics Association and the Linnean Society) and the European Commission's Research Infrastructure Action (SYNTHESYS grant numbers BE-TAF-3810 and GB-TAF-4003) for financial support. NW acknowledges funding from the Academy of Finland (grant number 129811).

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Material and Methods
  5. Results
  6. Discussion
  7. Conclusion and Prospects
  8. Acknowledgements
  9. References
  • Ackery PR, Smith CR, Vane-Wright RI. 1995. Carcasson's African butterflies: a catalogue of the Rhopalocera of the Afrotropical region. Melbourne: CSIRO.
  • Aduse-Poku K, Vingerhoedt E, Wahlberg N. 2009. Out-of-Africa again: a phylogenetic hypothesis of the genus Charaxes (Lepidoptera: Nymphalidae) based on five gene regions. Molecular Phylogenetics and Evolution 53: 463478.
  • Alfaro ME, Santini F, Brock C, Alamillo H, Dornburg A, Rabosky DL, Carnevale G, Harmon LJ. 2009. Nine exceptional radiations plus high turnover explain species diversity in jawed vertebrates. Proceedings of the National Academy of Sciences of the United States of America 106: 1341013414.
  • Amiet J-L. 2000. Les premiers états des Cymothoe: morphologie et intérêt phylogénique (Lepidoptera, Nymphalidae). Bulletin de la Société Entomologique de France 106: 349390.
  • Amiet J-L, Achoundong G. 1996. Un exemple de spécialisation trophique chez les Lépidoptères: les Cymothoe camerounaises inféodées aux Rinorea (Violacées) (Lepidoptera, Nymphalidae). Bulletin de la Société Entomologique de France 101: 449466.
  • Barraclough TG, Vogler AP. 2002. Recent diversification rates in North American tiger beetles estimated from a dated mtDNA phylogenetic tree. Molecular Biology and Evolution 19: 17061716.
  • Berger LA. 1981. Les papillons du Zaïre. Weissenbruch: Brussels.
  • Braby MF, Pierce NE. 2007. Systematics, biogeography and diversification of the Indo-Australian genus Delias Hübner (Lepidoptera: Pieridae): phylogenetic evidence supports an ‘out-of-Australia’ origin. Systematic Entomology 32: 225.
  • Bryson RW Jr, Riddle BR. 2012. Tracing the origins of widespread highland species: a case of Neogene diversification across the Mexican sierras in an endemic lizard. Biological Journal of the Linnean Society 105: 382394.
  • Cardillo M, Orme CDL, Owens IPF. 2005. Testing for latitudinal bias in diversification rates: an example using New World birds. Ecology 86: 22782287.
  • Casner KL, Pyrcz TW. 2010. Patterns and timing of diversification in a tropical montane butterfly genus, Lymanopoda (Nymphalidae, Satyrinae). Ecography 33: 251259.
  • Coetzee JA. 1993. African flora since the terminal Jurassic. New Haven, CT: Yale University Press.
  • Cohen AS, Stone JR, Beuning KRM, Park LE, Reinthal PN, Dettman D, Scholz CA, Johnson TC, King JW, Talbot MR, Brown ET, Ivory SJ. 2007. Ecological consequences of early Late Pleistocene megadroughts in tropical Africa. Proceedings of the National Academy of Sciences of the United States of America 104: 1642216427.
  • Condamine FL, Sperling FAH, Wahlberg N, Rasplus J-Y, Kergoat GJ. 2012. What causes latitudinal gradients in species diversity? Evolutionary processes and ecological constraints on swallowtail biodiversity. Ecology Letters 15: 267277.
  • Couvreur TLP, Chatrou LW, Sosef MSM, Richardson JE. 2008. Molecular phylogenetics reveal multiple tertiary vicariance origins of the African rain forest trees. BMC Biology 6: 54.
  • Couvreur TLP, Porter-Morgan H, Wieringa JJ, Chatrou LW. 2011. Little ecological divergence associated with speciation in two African rain forest tree genera. BMC Evolutionary Biology 11: 296.
  • Cunningham CW. 1997. Can three incongruence tests predict when data should be combined? Molecular Biology and Evolution 14: 733740.
  • Cusimano N, Stadler T, Renner SS. 2012. A new method for handling missing species in diversification analysis applicable to randomly or non-randomly sampled phylogenies. Systematic Biology 61: 785792.
  • Darlu P, Lecointre G. 2002. When does the incongruence length difference test fail? Molecular Biology and Evolution 19: 432437.
  • Day JJ, Cotton JA, Barraclough TG. 2008. Tempo and mode of diversification of Lake Tanganyika cichlid fishes. PLoS ONE 3: e1730.
  • Degnan JH, Rosenberg NA. 2009. Gene tree discordance, phylogenetic inference and the multispecies coalescent. Trends in Ecology and Evolution 24: 332340.
  • Drummond AJ, Rambaut A. 2007. BEAST: Bayesian evolutionary analysis by sampling trees. BMC Evolutionary Biology 7: 214.
  • Dupont L. 2011. Orbital scale vegetation change in Africa. Quaternary Science Reviews 30: 35893602.
  • Dupont LM, Jahns S, Marret F, Ning S. 2000. Vegetation change in equatorial West Africa: time-slices for the last 150 ka. Palaeogeography, Palaeoclimatology, Palaeoecology 155: 95122.
  • Elias M, Joron M, Willmott K, Silva-Brandao KL, Kaiser V, Arias CF, Pinerez LMG, Uribe S, Brower AVZ, Freitas AVL, Jiggins CD. 2009. Out of the Andes: patterns of diversification in clearwing butterflies. Molecular Ecology 18: 17161729.
  • Escudero M, Hipp AL, Waterway MJ, Valente LM. 2012. Diversification rates and chromosome evolution in the most diverse angiosperm genus of the temperate zone (Carex, Cyperaceae). Molecular Phylogenetics and Evolution 63: 650655.
  • Farris JS, Kallersjo M, Kluge AG, Bult C. 1994. Testing significance of incongruence. Cladistics—the International Journal of the Willi Hennig Society 10: 315319.
  • Farris JS, Kallersjo M, Kluge AG, Bult C. 1995. Constructing a significance test for incongruence. Systematic Biology 44: 570572.
  • FitzJohn RG, Maddison WP, Otto SP. 2009. Estimating trait-dependent speciation and extinction rates from incompletely resolved phylogenies. Systematic Biology 58: 595611.
  • Fontaine M. 1982. Genre Cymothoe Hübner. Lep. Nymphalidae – S. fam. Nymphalinae. Note sur les premiers états. Lambillionea 82: 6364, 67–72, 95–98.
  • Fordyce JA. 2010. Host shifts and evolutionary radiations of butterflies. Proceedings of the Royal Society B 277: 37353743.
  • Garamszegi LZ, Møller AP. 2011. Nonrandom variation in within-species sample size and missing data in phylogenetic comparative studies. Systematic Biology 60: 876880.
  • Goldberg EE, Lancaster LT, Ree RH. 2011. Phylogenetic inference of reciprocal effects between geographic range evolution and diversification. Systematic Biology 60: 451465.
  • Grill A, Schtickzelle N, Cleary DFR, Nève G, Menken SBJ. 2006. Ecological differentiation between the Sardinian endemic Maniola nurag and the pan-European M. jurtina. Biological Journal of the Linnean Society 89: 561574.
  • Hall JPW. 2005. Montane speciation patterns in Ithomiola butterflies (Lepidoptera : Riodinidae): are they consistently moving up in the world? Proceedings of the Royal Society B: Biological Sciences 272: 24572466.
  • Hall TA. 1999. BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT. Nucleic Acids Symposium 41: 9598.
  • Harmon LJ, Weir JT, Brock CD, Glor RE, Challenger W. 2008. GEIGER: investigating evolutionary radiations. Bioinformatics 24: 129131.
  • Heikkila M, Kaila L, Mutanen M, Peña C, Wahlberg N. 2012. Cretaceous origin and repeated tertiary diversification of the redefined butterflies. Proceedings of the Royal Society B: Biological Sciences 279: 10931099.
  • Heled J, Drummond AJ. 2010. Bayesian inference of species trees from multilocus data. Molecular Biology and Evolution 27: 570580.
  • Jacobs BF. 2004. Palaeobotanical studies from tropical Africa: relevance to the evolution of forest, woodland and savannah biomes. Philosophical Transactions of the Royal Society of London, Series B: Biological Sciences 359: 15731583.
  • Jiggins CD. 2008. Ecological speciation in mimetic butterflies. Bioscience 58: 541548.
  • Johnson MTJ, FitzJohn RG, Smith SD, Rausher MD, Otto SP. 2011. Loss of sexual recombination and segregation is associated with increased diversification in evening primroses. Evolution 65: 32303240.
  • Kandul NP, Lukhtanov VA, Pierce NE, Mooers A. 2007. Karyotypic diversity and speciation in Agrodiaetus butterflies. Evolution 61: 546559.
  • Kielland J. 1990. Butterflies of Tanzania. Melbourne: Hill House.
  • Kodandaramaiah U, Lees DC, Muller CJ, Torres E, Karanth KP, Wahlberg N. 2010. Phylogenetics and biogeography of a spectacular Old World radiation of butterflies: the subtribe Mycalesina (Lepidoptera: Nymphalidae: Satyrini). BMC Evolutionary Biology 10: 172.
  • Kodandaramaiah U, Wahlberg N. 2007. Out-of-Africa origin and dispersal-mediated diversification of the butterfly genus Junonia (Nymphalidae: Nymphalinae). Journal of Evolutionary Biology 20: 21812191.
  • Kozak KH, Wiens JJ. 2006. Does niche conservatism promote speciation? A case study in North American salamanders. Evolution 60: 26042621.
  • Kozak KH, Wiens JJ. 2010. Accelerated rates of climatic-niche evolution underlie rapid species diversification. Ecology Letters 13: 13781389.
  • Kuhn TS, Mooers AØ, Thomas GH. 2011. A simple polytomy resolver for dated phylogenies. Methods in Ecology and Evolution 2: 427436.
  • Larsen TB. 1991. The butterflies of Kenya and their natural history. Oxford: Oxford University Press.
  • Larsen TB. 2005. Butterflies of West Africa. Stenstrup: Apollo Books.
  • Leneveu J, Chichvarkhin A, Wahlberg N. 2009. Varying rates of diversification in the genus Melitaea (Lepidoptera: Nymphalidae) during the past 20 million years. Biological Journal of the Linnean Society 97: 346361.
  • Liu L, Pearl DK. 2007. Species trees from gene trees: reconstructing Bayesian posterior distributions of a species phylogeny using estimated gene tree distributions. Systematic Biology 56: 504514.
  • Magallon S, Sanderson MJ. 2001. Absolute diversification rates in Angiosperm clades. Evolution 55: 17621780.
  • Mallarino R, Bermingham E, Willmott KR, Whinnett A, Jiggins CD. 2005. Molecular systematics of the butterfly genus Ithomia (Lepidoptera : Ithomiinae): a composite phylogenetic hypothesis based on seven genes. Molecular Phylogenetics and Evolution 34: 625644.
  • McBride CS, van Velzen R, Larsen TB. 2009. Allopatric origin of cryptic butterfly species that were discovered feeding on distinct host plants in sympatry. Molecular Ecology 18: 36393651.
  • Megens HJ, van Moorsel CHM, Piel WH, Pierce NE, de Jong R. 2004. Tempo of speciation in a butterfly genus from the Southeast Asian tropics, inferred from mitochondrial and nuclear DNA sequence data. Molecular Phylogenetics and Evolution 31: 11811196.
  • Merrill RM, Gompert Z, Dembeck LM, Kronforst MR, McMillan WO, Jiggins CD. 2011. Mate preference across the speciation continuum in a clade of mimetic butterflies. Evolution 65: 14891500.
  • Miller MA, Pfeiffer W, Schwartz T. 2010. Creating the CIPRES Science Gateway for inference of large phylogenetic trees. Gateway Computing Environments Workshop (GCE) 2010: 18.
  • Morley RJ, Richards K. 1993. Gramineae cuticle: a key indicator of Late Cenozoic climatic change in the Niger Delta. Review of Palaeobotany and Palynology 77: 119127.
  • Mullen SP, Savage WK, Wahlberg N, Willmott KR. 2011. Rapid diversification and not clade age explains high diversity in neotropical Adelpha butterflies. Proceedings of the Royal Society B: Biological Sciences 278: 17771785.
  • Müller CJ, Beheregaray LB. 2010. Palaeo island-affinities revisited – biogeography and systematics of the Indo-Pacific genus Cethosia Fabricius (Lepidoptera: Nymphalidae). Molecular Phylogenetics and Evolution 57: 314326.
  • Nakagawa S, Freckleton RP. 2008. Missing inaction: the dangers of ignoring missing data. Trends in Ecology and Evolution 23: 592596.
  • Nazari V, Sperling FAH. 2007. Mitochondrial DNA divergence and phylogeography in western Palaearctic Parnassiinae (Lepidoptera : Papilionidae): how many species are there? Insect Systematics and Evolution 38: 121138.
  • Nguembock B, Cibois A, Bowie RCK, Cruaud C, Pasquet E. 2009. Phylogeny and biogeography of the genus Illadopsis (Passeriformes: Timaliidae) reveal the complexity of diversification of some African taxa. Journal of Avian Biology 40: 113125.
  • Njabo KY, Bowie RCK, Sorenson MD. 2008. Phylogeny, biogeography and taxonomy of the African wattle-eyes (Aves: Passeriformes: Platysteiridae). Molecular Phylogenetics and Evolution 48: 136149.
  • Nylander JAA, Wilgenbusch JC, Warren DL, Swofford DL. 2008. AWTY (are we there yet?): a system for graphical exploration of MCMC convergence in Bayesian phylogenetics. Bioinformatics 24: 581583.
  • Paradis E. 2011. Time-dependent speciation and extinction from phylogenies: a least squares approach. Evolution 65: 661672.
  • Peña C, Nylin S, Wahlberg N. 2011. The radiation of Satyrini butterflies (Nymphalidae: Satyrinae): a challenge for phylogenetic methods. Zoological Journal of the Linnean Society 161: 6487.
  • Peña C, Wahlberg N. 2008. Prehistorical climate change increased diversification of a group of butterflies. Biology Letters 4: 274278.
  • Plana V, Gascoigne A, Forrest LL, Harris D, Pennington RT. 2004. Pleistocene and pre-Pleistocene Begonia speciation in Africa. Molecular Phylogenetics and Evolution 31: 449461.
  • Posada D. 2008. jModelTest: phylogenetic model averaging. Molecular Biology and Evolution 25: 12531256.
  • Price BW, Villet MH, Walton SM, Barker NP. 2011. Using molecules and morphology to infer the phylogenetic relationships and evolutionary history of the Dirini (Nymphalidae: Satyrinae), a tribe of butterflies endemic to Southern Africa. Systematic Entomology 36: 300316.
  • Pringle E, Henning G, Ball J. 1994. Pennington's butterflies of Southern Africa. Cape Town: Struik Winchester.
  • Purvis A, Nee S, Harvey PH. 1995. Macroevolutionary inferences from primate phylogeny. Proceedings of the Royal Society of London, Series B: Biological Sciences 260: 329333.
  • Pybus OG, Harvey PH. 2000. Testing macro-evolutionary models using incomplete molecular phylogenies. Proceedings of the Royal Society of London, Series B: Biological Sciences 267: 22672272.
  • Rabosky DL. 2006a. LASER: a maximum likelihood toolkit for detecting temporal shifts in diversification rates from molecular phylogenies. Evolutionary Bioinformatics 2: 247250.
  • Rabosky DL. 2006b. Likelihood methods for detecting temporal shifts in diversification rates. Evolution 60: 11521164.
  • Rabosky DL. 2010. Extinction rates should not be estimated from molecular phylogenies. Evolution 64: 18161824.
  • Rambaut A, Drummond AJ. 2009. Tracer. version 1.4. Available at: http://tree.bio.ed.ac.uk/software/tracer/
  • Rannala B. 2002. Identifiability of parameters in MCMC Bayesian inference of phylogeny. Systematic Biology 51: 754760.
  • Ricklefs RE. 2007. Estimating diversification rates from phylogenetic information. Trends in Ecology and Evolution 22: 601610.
  • Rokas A, Krüger D, Carroll SB. 2005. Animal evolution and the molecular signature of radiations compressed in time. Science 310: 19331938.
  • Rommerskirchen F, Condon T, Mollenhauer G, Dupont L, Schefuss E. 2011. Miocene to Pliocene development of surface and subsurface temperatures in the Benguela Current system. Paleoceanography 26: PA3216.
  • Ronquist F, Huelsenbeck JP. 2003. MrBayes 3: Bayesian phylogenetic inference under mixed models. Bioinformatics 19: 15721574.
  • Schnitzler J, Barraclough TG, Boatwright JS, Goldblatt P, Manning JC, Powell MP, Rebelo T, Savolainen V. 2011. Causes of plant diversification in the Cape biodiversity hotspot of South Africa. Systematic Biology 60: 343357.
  • Schoville SD, Roderick GK, Kavanaugh DH. 2012. Testing the ‘Pleistocene species pump’ in alpine habitats: lineage diversification of flightless ground beetles (Coleoptera: Carabidae: Nebria) in relation to altitudinal zonation. Biological Journal of the Linnean Society 107: 95111.
  • Segalen L, Lee-Thorp JA, Cerling T. 2007. Timing of C-4 grass expansion across sub-Saharan Africa. Journal of Human Evolution 53: 549559.
  • Senut B, Pickford M, Segalen L. 2009. Neogene desertification of Africa. Comptes Rendus Geosciences 341: 591602.
  • Sepulchre P, Ramstein G, Fluteau F, Schuster M, Tiercelin JJ, Brunet M. 2006. Tectonic uplift and Eastern Africa aridification. Science 313: 14191423.
  • Sole CL, Wirta H, Forgie SA, Scholtz CH. 2011. Origin of Madagascan Scarabaeini dung beetles (Coleoptera: Scarabaeidae): dispersal from Africa. Insect Systematics and Evolution 42: 2940.
  • van Son G. 1979. The butterflies of Southern Africa, part 4, Nymphalidae: Nymphalinae. Pretoria: Transvaal Museum.
  • Swofford D. 2003. PAUP*: phylogenetic analysis using parsimony (*and other methods), 4.0B10 ed. Snuderland, MA: Sinauer Associates.
  • Vande Weghe GR. 2010. Les papillons du Gabon. Libreville: Wildlife Conservation Society.
  • van Velzen R, Bakker FT, van Loon JJA. 2007. DNA barcoding reveals hidden species diversity in Cymothoe (Nymphalidae). Proceedings of the Netherlands Entomological Society Meeting 18: 95103.
  • van Velzen R, Larsen TB, Bakker FT. 2009. A new hidden species of the Cymothoe caenis-complex (Lepidoptera: Nymphalidae) from western Africa. Zootaxa 2197: 5363.
  • Vences M, Wollenberg KC, Vieites DR, Lees DC. 2009. Madagascar as a model region of species diversification. Trends in Ecology and Evolution 24: 456465.
  • Verboom GA, Archibald JK, Bakker FT, Bellstedt DU, Conrad F, Dreyer LL, Forest F, Galley C, Goldblatt P, Henning JF, Mummenhoff K, Linder HP, Muasya AM, Oberlander KC, Savolainen V, Snijman DA, van der Niet T, Nowell TL. 2009. Origin and diversification of the Greater Cape flora: ancient species repository, hot-bed of recent radiation, or both? Molecular Phylogenetics and Evolution 51: 4453.
  • Wahlberg N. 2006. That awkward age for butterflies: insights from the age of the butterfly subfamily Nymphalinae (Lepidoptera : Nymphalidae). Systematic Biology 55: 703714.
  • Wahlberg N, Freitas AVL. 2007. Colonization of and radiation in South America by butterflies in the subtribe Phyciodina (Lepidoptera : Nymphalidae). Molecular Phylogenetics and Evolution 44: 12571272.
  • Wahlberg N, Leneveu J, Kodandaramaiah U, Peña C, Nylin S, Freitas AVL, Brower AVZ. 2009. Nymphalid butterflies diversify following near demise at the Cretaceous/Tertiary boundary. Proceedings of the Royal Society B 276: 42954302.
  • Wahlberg N, Wheat CW. 2008. Genomic outposts serve the phylogenomic pioneers: designing novel nuclear markers for genomic DNA extractions of lepidoptera. Systematic Biology 57: 231242.
  • Warren B, Bakker F, Bellstedt D, Bytebier B, ClaSZen-Bockhoff R, Dreyer L, Edwards D, Forest F, Galley C, Hardy C, Linder HP, Muasya AM, Mummenhoff K, Oberlander K, Quint M, Richardson J, Savolainen V, Schrire B, van der Niet T, Verboom GA, Yesson C, Hawkins J. 2011. Consistent phenological shifts in the making of a biodiversity hotspot: the Cape flora. BMC Evolutionary Biology 11: 39.
  • Weingartner E, Wahlberg N, Nylin S. 2006. Dynamics of host plant use and species diversity in Polygonia butterflies (Nymphalidae). Journal of Evolutionary Biology 19: 483491.
  • Werren JH. 2003. Invasion of the gender benders: by manipulating sex and reproduction in their hosts, many parasites improve their own odds of survival and may shape the evolution of sex itself. Natural History 112: 5863.
  • Whitfield JB, Kjer KM. 2008. Ancient rapid radiations of insects: challenges for phylogenetic analysis. Annual Review of Entomology 53: 449472.
  • Wiens JJ. 2007. Global patterns of diversification and species richness in amphibians. American Naturalist 170: S86S106.
  • Williams MC. 2012. Butterflies and skippers of the Afrotropical Region. A digital encyclopaedia. Available at http://www.atbutterflies.com
  • Wirta H, Viljanen H, Orsini L, Montreuil O, Hanski I. 2010. Three parallel radiations of Canthonini dung beetles in Madagascar. Molecular Phylogenetics and Evolution 57: 710727.
  • Zachos J, Pagani M, Sloan L, Thomas E, Billups K. 2001. Trends, rhythms, and aberrations in global climate 65 Ma to present. Science 292: 686693.
  • Zhang Z, Nisancioglu KH, Flatoy F, Bentsen M, Bethke I, Wang H. 2011. Tropical seaways played a more important role than high latitude seaways in Cenozoic cooling. Climate of the Past 7: 801813.
  • Zwickl DJ. 2006. Genetic algorithm approaches for the phylogenetic analysis of large biological sequence datasets under the maximum likelihood criterion. PhD Thesis, University of Texas at Austin, TX.
GenusSpeciesSexVoucherCollectorCollection dateCountryLocationCOIwglGAPDHRpS5IDH
CymothoeadelaMaleSS_041S. Szabolcs17–26 March 2009Sierra LeoneBelebuHE964949HE964890HE963090HE964843 
CymothoealcimedaFemaleSW_005S. Woodhall2006South AfricaPort St. JohnsHE964951HE964892HE963092HE964845 
CymothoealtheaMaleTL_011T. B. LarsenApril 2006Sierra LeoneGola ForestHE964953HE964893HE963093HE964847HE964799
Cymothoealticola           
CymothoealtisidoraMaleJW_023J. Wieringa1 February 2008GabonAlanga–Aboumi Rd.HE964926HE964871   
Cymothoeamaniensis           
CymothoeamenidesMaleRV_364R. van Velzen25 May 2006CameroonLondji 2HE964938HE964880HE963082HE964833 
Cymothoeangulifascia           
CymothoeanitorgisFemaleOB_023O. Brattström11 February 2009NigeriaAfi Mts.HE964927 HE963072  
CymothoearamisMaleOB_060O. Brattström28 April 2010NigeriaAfi Mts.HE964930HE964873HE963075HE964826HE964791
Cymothoearcuata           
CymothoeaubergeriFemaleCREO_110R. Onstein15 November 2009GhanaKakumHE964904HE964852HE963053HE964804HE964784
CymothoeaurivilliiMaleABRI_098M. Hassan2006TanzaniaKihansi ForestHE964899    
Cymothoebaylissii ined.FemaleJB_001J. BaylissNovember 2010MozambiqueMt. MabuHE964924HE964869HE963069HE964821 
CymothoebeckeriFemaleRV_386R. van Velzen2 June 2006CameroonNkoloHE964939HE964881HE963083HE964834HE964796
CymothoebouyeriMaleABRI_402R. DucarmeDecember 2008Democratic Republic of the Congo (DRC)KasuoBARCODE    
CymothoebutleriMaleRV_392R. van Velzen27 July 2008KenyaKakamega ForestHE964941HE964883HE963085HE964836 
Cymothoecaenis NW_10216F. Molleman UgandaKibale ForestGQ864754GQ864442GQ864952GQ865420GQ865083
CymothoecapellaFemaleGW_4401G. vandeWeghe7 January 2004DRCBondoHE964920HE964866HE963066HE964818 
CymothoecaprinaFemaleFM_180F. Molleman20 August 2004CameroonDoumo PierreHE964910 HE963058HE964809 
CymothoecoccinataFemaleRV_414R. van Velzen17 November 2010NigeriaOlogbo ForestHE964942HE964884HE963086HE964837HE964798
CymothoecollartiFemaleGW_13018G. vandeWeghe15 April 2007RwandaNyungwe ForestHE964915HE964861HE963062HE964813 
Cymothoecollinsi           
CymothoecolmantiMaleTB_8923T. BouyerJune 2011DRCMamoveBARCODE    
CymothoeconfusaFemaleRV_332R. van Velzen15 May 2006CameroonDucam-DuclairHE964937HE964879HE963081HE964832HE964795
CymothoeconsanguisMaleRW_052R. Warren9 April 2009NigeriaRhokoHE964946HE964888 HE964841 
CymothoecoranusMaleSW_13025S. Woodhall6 August 2006South AfricaUmdoni ParcHE964952  HE964846 
CymothoecottrelliMaleABRI_087S. C. CollinsJuly 2004MalawiNyikaBARCODE    
CymothoecroceaMaleFM_183F. Molleman26 August 2004CameroonDoumo PierreHE964911HE964857HE963059HE964810HE964786
CymothoecycladesFemaleABRI_330P. WalwandaFebruary 1996DRCMt. HoyoBARCODE    
CymothoedistinctaMaleFM_176F. Molleman26 August 2004CameroonDoumo PierreHE964909HE964856HE963057HE964808 
CymothoedruryiMaleTL_031T. B. LarsenApril 2006Sierra LeoneGola ForestHE964955HE964895HE963095  
Cymothoedujardini           
CymothoeegestaFemaleOB_058O. Brattström1 April 2010NigeriaRhokoHE964929HE964872HE963074HE964825 
CymothoeerisMaleRMCA_242Unknown15 July 1989CameroonMoloundouBARCODE    
Cymothoeeuthalioides           
CymothoeexcelsaMaleGW_14099G. vandeWeghe1 February 2008GabonLonminHE964916HE964862HE963063HE964814 
CymothoefontaineiFemaleGW_14237G. vandeWeghe4 February 2008GabonLonminHE964918HE964864HE963064HE964816 
CymothoefumanaMaleCREO_119R. Onstein29 November 2009GhanaKakumHE964905HE964853HE963054HE964805HE964785
CymothoehaimodiaMaleGW_14221G. vandeWeghe3 February 2008GabonLonminHE964917HE964863 HE964815HE964788
CymothoeharmillaFemaleGW_12490G. vandeWeghe28 September 2007GabonWakaHE964914HE964860HE963061HE964812 
CymothoehartigiMaleSS_042S. Szabolcs17–26 March 2009Sierra LeoneBelebuHE964950HE964891HE963091HE964844 
CymothoehaynaeMaleGW_4404G. vandeWeghe7 January 2004DRCBondoHE964921  HE964819 
CymothoeheliadaFemaleGW_10623G. vandeWeghe31 March 2007GabonWakaHE964912HE964858HE963060HE964811HE964787
CymothoeherminiaFemaleRV_226R. van Velzen28 April 2006CameroonMt. KalaHE964934HE964877HE963079HE964830 
Cymothoehesiodina           
CymothoehesiodotusFemaleFM_008F. Molleman1 September 2004CameroonDoumo PierreHE964908HE964855HE963056HE964807 
CymothoehobartiFemaleRV_390R. van Velzen27 July 2008KenyaKakamega ForestHE964940HE964882HE963084HE964835HE964797
Cymothoehowarthi           
CymothoehyarbitaMaleGW_9174G. vandeWeghe19 December 2006GabonTchimbéléHE964922HE964867HE963067  
CymothoehypathaFemaleGW_11340G. vandeWeghe22 April 2007GabonBatekéHE964913HE964859   
CymothoeindamoraMaleRW_030R. Warren25 March 2008NigeriaRhokoHE964943HE964885HE963087HE964838 
CymothoeisiroMaleABRI_060R. DucarmeDecember2006DRCBiakatuBARCODE    
CymothoejoduttaMaleRV_060R. van Velzen13 April 2006CameroonMt. KalaHE964932HE964875HE963077HE964828HE964792
CymothoelambertoniMaleABRI_075S. C. Collins24 October 2010MadagascarTsaratanana Mt.HE964898HE964848   
CymothoelucasiFemaleGW_9483G. vandeWeghe21 December 2007GabonTchimbéléHE964923HE964868HE963068HE964820HE964789
CymothoeluridaMaleTL_024T. B. LarsenApril 2007GhanaBobiri ForestHE964954HE964894HE963094  
CymothoemabilleiFemaleCREO_100R. Onstein26 October 2009GhanaAtewaHE964903HE964851HE963052HE964803HE964783
CymothoemagambaeMaleABRI_095T. C. E. Congdon16–30 March 2005TanzaniaSouth Pare Mts.BARCODE    
CymothoeMagnus           
CymothoemelanjaeMaleABRI_083UnknownMarch/April 2008MalawiMt. MulanjeBARCODE    
CymothoemeridionalisFemaleFM_167F. Molleman3 October 2004CameroonDoumo PierreBARCODE    
CymothoenigeriensisMaleRW_036R. Warren15 March 2008NigeriaOkomuHE964944HE964886HE963088HE964839 
CymothoeochreataFemaleABRI_328S. C. Collins26 November 2004UgandaBudongoHE964902HE964850 HE964802 
CymothoeoemiliusFemaleRV_322R. van Velzen12 May 2006CameroonDucam-DuclairHE964936HE964878HE963080HE964831HE964794
CymothoeogovaMaleJW_002J. Wieringa21 March 2007GabonEvoutaHE964925HE964870HE963070HE964822HE964790
CymothoeokomuFemaleRW_038R. Warren15 March 2008NigeriaOkomuHE964945HE964887HE963089HE964840 
CymothoeorphninaFemaleTB_8118T. BouyerMay 2011DRCMt. HoyoBARCODE    
CymothoeowassaeMaleABRI_048S. C. Collins8–13 March 2007Equatorial GuineaBioko; MokaBARCODE    
Cymothoepreussii           
Cymothoeradialis           
Cymothoereginae-elisabethaeMaleRD_077R. Ducarme3 September 2007NigeriaBiakatuBARCODE    
CymothoereinholdiiMaleRD_098R. Ducarme28 August 2007DRCBiakatuHE964931HE964874HE963076HE964827 
CymothoesangarisMaleRV_199R. van Velzen26 April 2006CameroonMt. KalaHE964933HE964876HE963078HE964829HE964793
Cymothoesassiana           
Cymothoeserpentina           
CymothoesuperbaMaleGW_14794G. vandeWeghe16 March 2008GabonLonminHE964919HE964865HE963065HE964817 
CymothoeteitaFemaleDB_003D. Bonte17 March 2006KenyaNgangaoHE964906 HE963055HE964806 
Cymothoevumbui           
Cymothoeweymeri SS_036S. Szabolcs29 March 2009GhanaTano OfinHE964948HE964889 HE964842 
CymothoezenkeriMaleABRI_058J. B. GaniotMay 2007Central African RepublicNdolokoHE964896  HE964800 
Cymothoezombana           
Harmatheobene NW102-8F. Molleman UgandaKibale ForestGQ864775GQ864463GQ864978GQ865447GQ865103
Lebadeamartha NW100-13T. B. Larsen12 April 2004BangladeshLowacherra ForestGQ864784GQ864472GQ864991GQ865460GQ865116
Limenitisreducta NW67-2N. Wahlberg26 April 2001FranceBagnoles, AudeAY090217AY090150EU141509EU141409EU141568
Neptisida NW98-3C. Schulze IndonesiaPalolo ValleyEU141369EU141250EU141526EU141432EU141591