Megadiverse insect groups present special difficulties for biogeographers because poor classification, incomplete knowledge of taxonomy, and many undescribed species can introduce a priori sampling bias to any analysis. The historical biogeography of Sericini, a tribe of melolonthine scarabs comprising about 4000 species, was investigated using the most comprehensive and time-calibrated molecular phylogeny available today. Problems arising through nomenclatural confusion were overcome by extensive sampling (665 species) from all major lineages of the tribe. A West Gondwanan origin of Sericini (c. 112 Ma) was reconstructed using maximum parsimony, maximum-likelihood and model-based ancestral area estimation. Vicariance in the tribe's earliest history separated Neotropical and Old World Sericini, whereas subsequent lower Cretaceous biogeography of the tribe was characterized by repeated migrations out of Africa, resulting in the colonization of Eurasia and Madagascar. North America was colonized from Asia during the Cenozoic and a lineage of “Modern Sericini” reinvaded Africa. Diversification dynamics revealed three independent shifts to increased speciation rates: in African ant-adapted Trochalus, Oriental Tetraserica, and Asian and African Sericina. Southern Africa is proposed as both cradle and refuge of Sericini. This area has retained many old lineages that portray the evolution of the African Sericini fauna as a series of taxon pulses.

Introduction

With nearly 4000 described species, Sericini chafers (Coleoptera: Scarabaeidae) represent a megadiverse tribe of beetles with a nearly worldwide distribution that is absent only in Australia and circumpolar regions (Ahrens, 2006c). Most extant species are found in a monophyletic lineage (“modern Sericini”; Ahrens, 2006c; Ahrens and Vogler, 2008). It comprises two large palaeotropical subtribes, Sericina and Trochalina, which number about 3000 species and 370 species, respectively. The phytophagous Sericini belong to the lineage of pleurostict chafers (Scarabaeidae) that are thought to have greatly diversified with the rise of angiosperms around 108 Ma (Farrell, 1998; Ahrens et al., 2014b; Eberle et al., 2014). Compared to the soil-dwelling larval stage, the emergence of adults is short. The beetles are generally fully winged but commonly exhibit restricted distribution patterns or even high endemism (e.g. Ahrens, 2004; Liu et al., 2015). Their poor dispersal capacity is underlined by their absence on most oceanic islands and archipelagos (e.g. Lesser Antilles, Papua New Guinea, Canary Islands) and by high regional endemism (Ahrens, 2004), and makes them highly interesting for the study of biogeographical patterns.

The origin of Sericini was proposed to be in Africa because of the exclusively African distribution of Ablaberini, the sister group of Sericini (Ahrens, 2006c). The divergence of Sericini from Ablaberini dates back to c. 100 Ma (Ahrens et al., 2014b), which makes the group suitable for exploring biogeographical processes since the breakup of Gondwana, an event that profoundly influenced distribution patterns of organisms in the southern hemisphere (Bossuyt et al., 2006; Waters and Craw, 2006). Knowledge of the timing, modes and routes of dispersal from Africa to other regions is crucial for a deeper understanding of the evolution of this group. In particular, the colonization of the Asian subcontinent, where Sericini are highly diverse, is of major interest to provide a primer for investigating the causes of their exceptional species richness. The signal of past biogeographical processes that is observed in distribution patterns of extant species may be overlain by subsequent dispersal events and their inference requires robust phylogenetic hypotheses (Givnish and Renner, 2004; McGlone, 2005). Previous considerations of Sericini biogeography were based on morphology-based phylogenetic hypotheses (Ahrens, 2006a,b,c,d, 2007a,b) that were expected to be influenced strongly by homoplasy (Ahrens and Vogler, 2008).

Most current knowledge of historical biogeography comes from vertebrates and plants with well-known distributions (Holt et al., 2013) and considerable fossil records. Evidence based on invertebrate data is rather rare despite their enormous species richness and ecological diversity (Sanmartín and Ronquist, 2004; Monaghan et al., 2007; Schaefer and Renner, 2008; Kodandaramaiah and Wahlberg, 2009; Kodandaramaiah et al., 2010; Bukontaite et al., 2014; Struempher et al., 2014; Kim and Farrell, 2015). Among the reasons for this may be poor knowledge of species' phylogenetic relationships and taxonomy. Fragmented knowledge of species and their distributions may hamper capture of their diversity in space and time, and this is particularly true in megadiverse groups with significant numbers of undescribed species. Externally homogeneous morphology and strong homoplasy in the few existing diagnostic features (e.g. genitalia) aggravates the issue. In our study group, the scarab tribe Sericini, about 60% of the genera were erected as monotypic (Ahrens, 2007c,d; D. Ahrens unpublished data), particularly in island faunas. In contrast, large and long-recognized genera of Sericini have been found to be para- or polyphyletic, with many smaller genera nested within these larger collective groups (Ahrens and Vogler, 2008; Liu et al., 2015). Therefore, sampling based on such an error-prone taxonomy could easily lead to biased a priori assumptions. This is predictably true when only few species of widespread genera are included in an analysis or if certain clades, particularly those containing nested genera, are inadvertently over-sampled.

Notwithstanding this, megadiverse groups are a valuable resource of information for biogeographical studies because they provide an enormous diversity of species with comparable vagility and dispersal capability (e.g. Bossuyt et al., 2006; Linder, 2008; Albert et al., 2011). Therefore, these groups are well suited not only for the detection of historically common, but also, in particular, of less-frequented biogeographical dispersal routes. Sampling as many species as possible within a group without discarding congeneric species a priori not only overcomes the above-mentioned taxonomic sampling issues, but also naturally increases the probability of biogeographical events being reflected in its phylogenetic relationships. Observed biogeographical patterns should be spatially more clearly resolved than they would in a species-poor clade, in particular if high endemism prevails within the group. On the one hand, multiple occurrences of a specific event will provide strong evidence for a frequent dispersal route, and on the other, the lack of a dispersal event will be a stronger indication for a less likely route than might be seen in a species-poor clade.

In the present study, we examine historical biogeographical processes that led to the current distribution of Sericini lineages in the context of a newly developed time-calibrated molecular phylogenetic hypothesis. We attempt to reconstruct major global scale migrations of the main lineages of Sericini, with the objective of capturing parallels or dissimilarities compared to current knowledge which is mainly derived from better-known vertebrates. We further investigate the dynamics of the extensive diversification of Sericini in the context of their historical biogeography. Efficient algorithms and increasing computational power enable us to overcome biases of phylogeny-dependent analyses from a partly artificial generic classification and from large numbers of undescribed species by extensive sampling of all lineages without discarding congeneric species a priori.

Material and methods

Sampling and molecular lab procedures

The present study greatly extends the sampling of previous molecular phylogenies of Sericini (Ahrens and Vogler, 2008; Liu et al., 2015) in terms of taxa and geography (Table S1; Fig. S1). It includes 872 specimens from 46 countries representing 665 morphospecies of all major lineages of Sericini (Tables S1 and S4). Specimen collection, preservation and DNA extraction followed Ahrens and Vogler (2008). Vouchers are deposited in the collections of the Zoological Research Museum A. Koenig, Bonn (ZFMK). Two mitochondrial markers, the 3′ end of cytochrome oxidase subunit 1 (cox1) and 16S ribosomal DNA (rrnL), and a fragment of nuclear 28S rDNA, containing the variable domains D3–D6 were used in our analysis. Fieldwork in South Africa was enabled by the following collection permits: Eastern Cape (Permit No.: WRO 122/07WR and WRO123/07WR), Gauteng (Permit No.: CPF6 1281), Limpopo (Permit No.: CPM-006-00001), Mpumalangma (Permit No.: MPN-2009-11-20-1232) and Kwazulu-Natal (Permit Nos OP3752/2009, 1272/2007, 3620/2006).

Specimens were preserved in 96% ethanol and identified by examining male genitalia. Species were sorted to morphospecies if identification to a described species was impossible. DNA was extracted from the left mid-leg and from thoracic flight muscles of ethanol-preserved specimens with Qiagen^® DNeasy Blood & Tissue Kits using standard protocols. Subsequently, the genitalia were glued on a card and dry-mounted on the same pin as the specimen. The mitochondrial markers and nuclear DNA fragments, as described above, were amplified with polymerase chain reaction (PCR; see Table S5 for PCR protocols). Qiagen^® Multiplex PCR Kits were used with primers stevPat and stevJerry for cox1 (Timmermans et al., 2010), 16Sar and 16sB2 for rrnL (Simon et al., 1994), and FF and DD (Monaghan et al., 2007) for 28S. Forward and reverse strands were sequenced by Macrogen (Seoul, South Korea) using the same primers. Sequences were edited manually in Geneious 7.1.8.

Multiple sequence alignment and phylogenetic inference

Because multiple sequence alignment can be problematic for large datasets, especially when markers with highly variable regions such as rrnL are included, we employed the divide-and-conquer realignment technique implemented in SATé-II (v.2.2.7; Liu et al., 2012). This method simultaneously estimates a phylogenetic tree and the alignment in multiple iterations, and can lead to great improvements in hard-to-align data sets by deconstructing the alignment into smaller, closely related subsets of sequences (subproblems), which are separately aligned and subsequently merged. We ran 10 iterations on the multilocus data set, aligning subproblems with a maximum size of 200 individuals with MAFFT (v.6.717; Katoh and Toh, 2008, 2010). Subproblems were generated by the centroid strategy and remerged with Muscle (version 3.7, Edgar, 2004a,b). The simultaneous tree estimation was done with FastTree (version 2.1.4, Price et al., 2010).

Phylogenetic relationships were inferred using maximum-likelihood (ML) in RAxML (v.8.0.20; Stamatakis, 2014). The combined matrix was partitioned for the three markers and the tree was estimated under the GTR+CAT model (Stamatakis, 2006) with final optimization under the GTR+Γ model. Base frequencies were estimated for each partition. Branch support was assessed by the nonparametric Shimodaira–Hasegawa-like implementation (SHL; Guindon et al., 2010) of the approximate likelihood-ratio test (aLRT; Anisimova and Gascuel, 2006), which is much faster than traditional bootstrapping (Anisimova and Gascuel, 2006; Guindon et al., 2010; Anisimova et al., 2011) and more robust against model violations (Anisimova et al., 2011). We adopt a conservative approach by considering branches with SHL values > 85 as strongly supported (Guindon et al., 2010; Anisimova et al., 2011; Pyron and Wiens, 2011; Pyron, 2014).

Well-supported phylogenetic information is mandatory for correct reconstruction of historical biogeography (Santos and Amorim, 2007). Only small deviations in the topology of the Sericini phylogeny would imply different biogeographical conclusions for the colonization of the Oriental region. Therefore, site bootstrapping was performed in CONSEL (Shimodaira and Hasegawa, 2001) on two alternative tree hypotheses that were inferred by constrained RAxML analyses of the same dataset. Scenarios of monophyly (i) of the Oriental Sericina clades II and III and (ii) of African “Modern Sericini” (i.e. Trochalina + Sericina clade I; Fig. 1) were compared to the unconstrained scenario.

Details are in the caption following the image — **Figure 1**
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Time-calibrated phylogeny of Sericini chafers and biogeographical inferences. Colour codes for ancestral area reconstruction are explained upper left. Branches of the tree are coloured according to the maximum-likelihood ancestral range estimations of the subregions. Time slices with the respective palaeogeography (based on R. Blakey's maps; www.jan.ucc.nau.edu) including the stratification settings used in the BioGeoBEARS analysis are shown on the left: High dispersal probabilities (1.0) are indicated by thick and lower probabilities (0.5) by narrow arrows. Numbers on the tree mark nodes discussed more in detail in the text. Calibration points are indicated by an asterisk. [Color figure can be viewed at wileyonlinelibrary.com].

Divergence time estimation

Divergence times were estimated on the fixed topology of the RAxML tree with BEAST (v.1.7.5; Drummond et al., 2012). We used two calibration points: one fossil of Serica antediluviana Wickham, 1912 (Wickham, 1912; Krell, 2000) from Florissant, USA (37.2–33.9 Ma; http://fossilworks.org, accessed 8 May 2015), was used to calibrate the only clade of Nearctic Sericini (Fig. 1, node 19) with an exponential prior, because exponential distributions require only one parameter and no further information about the mode of the prior distribution was available (Ho and Phillips, 2009). The geographical occurrence of S. antediluviana makes it the only unambiguously assignable fossil of the group, because it is impossible to reliably determine clade affiliations of fossilized Sericini based on their homogeneous external morphology. The second calibration point was applied to the most recent common ancestor of Ablaberini and Sericini from a previous study (Ahrens et al., 2014b) with a lognormal distribution (mean=90.28, stdev=0.0635, offset=8.48) because divergence times estimated from molecular data typically exhibit lognormal distributions (Morrison, 2008). PartitionFinder (Lanfear et al., 2012, 2014) was used to infer optimal partition schemes and substitution models. Cox1 was divided into its codon positions because they are known to differ substantially in their substitution rates (Ho and Lanfear, 2010). Due to convergence issues with more complex substitution models (GTR+I+Γ and SYM+I+Γ) that were inferred with PartitionFinder, the simpler model HKY+Γ was set for all partitions. The data were subdivided into five partitions (rrnL, 28S, 3 codon positions of cox1) to agree with the PartitionFinder results as closely as possible. The uncorrelated lognormal relaxed clock model (Drummond et al., 2006) was used to estimate branch rates and the Yule process was set as tree prior. Two independent runs with 10⁸ generations each, sampling every 5000 generations, were performed on the high performance computing cluster at the ZFMK. Convergence and stationarity of all model parameters were assessed with Tracer (v. 1.6; Rambaut et al., 2014) by checking ESS values and visually inspecting the log-likelihood vs. generation plots. Based on the latter, a burnin of 10⁶ was discarded. The sampled trees of the individual runs were combined using LogCombiner and the maximum clade credibility tree with mean node heights was calculated using TreeAnnotator (Drummond et al., 2012).

Biogeographical analyses

Biogeographical regions have been defined mostly by high levels of endemism and distributional dissimilarity of organisms for quite some time (Wallace, 1876). Recent studies based on cluster analyses and dissimilarity of subregions (Linder et al., 2012; Procheş and Ramdhani, 2012), which also include phylogenetic turnover of assemblages of species (Holt et al., 2013), have shown that zoogeographical patterns are specific for individual groups of organisms, regardless of scale, whether it be global or continental. However, the principal borders of zoogeographical regions are consistent between groups (Linder et al., 2012; Procheş and Ramdhani, 2012; Holt et al., 2013). Ancestral ranges have mostly been inferred using ancestral state reconstruction under maximum parsimony (MP) or ML criteria without explicit models for range evolution. Meanwhile, several models describing biogeographical events (Ronquist, 1997; Ree and Smith, 2008; Landis et al., 2013; Matzke, 2013b) have been developed and these provide valuable extensions of ancestral range inference methods. The recently developed BioGeoBEARS (Matzke, 2013b) provides extensive models that incorporate all previously mentioned models extending them for founder-event speciation (long-distance or over-sea dispersal), which previously has not been considered explicitly (Matzke, 2012, 2013a). BioGeoBEARS therefore provides a well-suited framework for testing the fit of different models to the data.

Because all methods used to reconstruct the historical biogeography of the group have certain deficiencies, especially regarding model shortcomings and limitations for the number of areas under consideration, we employed multiple approaches to infer ancestral ranges. In contrast to reconstructions with ML and MP, model-based ancestral area estimation with BioGeoBEARS allows the inference of processes underlying a biogeographical event. It also allows stratification of the analysis over geological time, which may improve the inference by taking into account palaeogeography and continental drift (Buerki et al., 2011). Analyses were conducted in the R statistics environment using: (i) MP under the MPR (Hanazawa et al., 1995) and ACCTRAN (Farris, 1970; Swofford and Maddison, 1987) criteria in phangorn (Schliep, 2011); (ii) ML ancestral states estimation in APE (Paradis et al., 2004); and (iii) ancestral area estimation in BioGeoBEARS (Matzke, 2013b).

In total, six main regions and nine subregions were defined (Fig. 1), which were largely inherited from the statistically defined biogeographical regions of previous studies (Linder et al., 2012; Holt et al., 2013). Species were considered to occur only in one region at once. Major zoogeographical regions were derived from realms postulated by Holt et al. (2013); however, modifications were made to fit specific biogeographical patterns of Sericini. The Oriental region and the Sino-Japanese subregion, which belongs to the Palaearctic, were never isolated and had similar climates throughout their histories (Cox and Moore, 2010). As a result, they are very similar in species assemblages and are not more differentiated than the subregions of the Oriental realm (e.g. Indian vs. Indochinese subregion) such that a clear separation was not possible. The Sino-Japanese subregion and the Oriental region were therefore treated as one unit to satisfy computational limitations. Likewise, the Saharo-Arabian realm (Holt et al., 2013), which is represented by only three specimens in our sampling, was combined with the Palaearctic region. For the ancestral area reconstruction methods, which are not susceptible to the number of areas that are considered in the analysis (see below), the Mediterranean Basin and the Saharo-Arabian subregion were coded separately from the Palaearctic, and the Afrotropical region was further subdivided following Linder et al. (2012). Maladera affinis from Réunion Island was coded as an Oriental species because it was most likely introduced with sugar cane or moved by Indian immigrants (Ahrens, 2003).

The BioGeoBEARS analysis was stratified by setting different dispersal probabilities between regions for four geological time slices according to continental drift and ocean currents following Buerki et al. (2011) (Fig. 1, Table S2), with the best model chosen by its AIC score (Table S3). Seven models were compared and the best one was chosen by its AIC score: DEC (Ree and Smith, 2008), DEC+J, DIVA-like (Ronquist, 1997), DIVA-like+J, BayArea-like (Landis et al., 2013), BayArea-like+J, and a modified DEC+J model that only allowed simultaneous occupation of continuous landmasses (0–30 Ma: AD and EF; 30–60 Ma: AD and AE; 60–80 Ma: AD; and 80–120 Ma: AD and BF; Fig. 1). This way, migrations between continents that were not adjacent in the respective time slices were possible only by long-distance over-sea dispersal (founder events). Due to computational limitations, single species were maximally allowed to occupy two regions at one time.

Analysis of diversification

Sampled lineages of Sericini through time (LTT) of the BEAST tree were plotted with APE (v.3.3; Paradis et al., 2004). LTT plots of 100 evenly spaced subsamples of the BEAST post-burnin tree samples indicated the range of node divergence time. The same procedure was applied to the subclades of Sericina (node 14, 15, and 16), African Sericina clade IV (node 17), and Trochalina (node 11 and 12).

The dynamics of species diversification through time were inferred with BAMM (v.2.5.0; Rabosky et al., 2013; Rabosky, 2014; Shi and Rabosky, 2015). The fraction of the species sampled from the major sericine clades was roughly estimated based on a world species database of Sericini. The backbone sampling fraction was set as the ratio of species sampled to the total number of known Sericini species. These settings, and subsequent analysis of the BAMM results, have to be made with care because the systematic assignment of species to the various defined lineages is problematic in some cases (Liu et al., 2015). Furthermore, previous taxonomic revisions revealed large proportions of undescribed species (e.g. Ahrens, 2004, 2005; Ahrens et al., 2014a; Fabrizi and Ahrens, 2014; Liu et al., 2014) which could not be considered for yet unrevised groups. Ablaberini, as well as clearly duplicate species, were pruned from the tree prior to the analysis to avoid an overestimation of diversification rates. According to the number of species that were included in the analysis, the number of expected shifts was set to 5. Priors were optimized for the data with BAMMtools (v.2.1.0; Rabosky et al., 2014b). Four MCMC chains were run for 30 million generations each, at a temperature increment parameter of 0.01, with sampling every 15000 generations. Speciation rate shifts on tips were not considered (mincladesize=2). Convergence and stationarity of the run were assessed with CODA (v.0.18-1; Plummer et al., 2006) in R by visually inspecting the traces of the log-likelihood and the number of shifts and by calculating the post-burnin effective sample size. The output was summarized and visualized with BAMMtools, including speciation rate through time plots for the above-mentioned clades (LTT). Differences in the speciation rate dynamics of Sericini lineages were illustrated using a cohort analysis (Rabosky et al., 2014a).

Results

Phylogenetic inference

The phylogenetic relationships of the main Sericini lineages (Fig. 1), based on the alignment of 2063 base pairs, largely coincided with previous hypotheses (Ahrens and Vogler, 2008; Liu et al., 2015): Ablaberini was recovered as a sister group to Sericini. South American Sericini, represented by Astaena (i.e. 7 of about 170 species and 1 out of 4 genera; node 2) was consistently recovered as sister to all other Sericini. The remaining species grouped in the following clades (Fig. 1, Table 1): the Triodontella-group (nodes 3 + 4), the Omaloplia-group (nodes 5 + 6), the Madagascan Comaserica group comprising also Hyposerica (node 7), Hyboserica (node 8), Trochalina as sister to the Mesoserica-group (node 9 + 10) and Sericina. Trochalina and Sericina are the only two subtribes so far defined for Sericini (Machatschke, 1959). Tests of alternative constrained topologies of the oldest Sericina clades with CONSEL highly supported the unconstrained analysis (Table 2). Concordant with previous studies (Ahrens, 2004; Liu et al., 2015), the traditional generic classification of many taxa was found to be inconsistent with the tree. Besides many undescribed species, many genera were highly para- or polyphyletic and scattered over the tree.

Table 1. Timing of stem group origins of principal Sericini lineages with the respective biogeographical event inferred by BioGeoBEARS and current distribution

Node	Clade	Distribution	Biogeographical event	Origin of stem group (Ma)	95% HPD (Ma)
1	Sericini	worldwide except Australia	-	111.60	101.19–121.13
2	Neotropical Sericini	Neotropic	vicariance	102.85	92.53–112.45
3	Triodontella group partim	A	dispersal - extinction	89.51	79.37–100.63
4	Triodontella group partim	Mediterranean	dispersal - extinction	“	“
5	Omaloplia group partim	P	dispersal - extinction	78.79	63.61–90.98
6	Omaloplia group partim	southern Africa	dispersal - extinction	“	“
7	Comaserica group	Madagascar	founder event	82.28	73.49–90.61
8	Hyboserica	South Africa	-	79.19	71.43–88.00
9	Mesoserica group partim	Madagascar	founder event	53.6	42.64–64.69
10	Mesoserica group partim	South Africa	-	“	“
11	Trochalina clade I	A	-	70.61	63.13–78.78
12	Trochalina clade II	A	-	“	“
13	modern Sericini	P, O, A, N	-	73.45	65.52–81.73
14	Sericina clade I	A	-	67.64	59.72–76.76
15	Sericina clade II	SE Asia	dispersal - extinction	“	“
16	Sericina clade III	P, O, A, N	dispersal - extinction	73.50	65.11–81.18
17	Sericina clade IV	A	dispersal - extinction	39.91	35.01–45.03
18	Euserica	Mediterranean	founder event	46.84	40.68–83.70
19	Sericina clade V	N	founder event	43.16	39.13–47.69

A, Afrotropic; N, Nearctic; O, Oriental; P, Palaearctic.

Table 2. Parametric bootstrapping support of the CONSEL analysis for topologies from constrained analyses that imply alternative biogeographical conclusions for the colonization of Asia. The P-values of the approximately unbiased test (au) and the bootstrap probability (np) are shown

Topology constraints	au	np
Unconstrained	1.000	1.000
Sericina clade II and III monophyletic	< 0.000	< 0.000
Trochalina and African Sericina clade I monophyletic	< 0.000	< 0.000

Biogeographical inferences and divergence times

The widely and intensely sampled and well-resolved phylogenetic tree allowed exploration of the historical timescale of biogeographical patterns in Sericini (Fig. S2). The different methods of ancestral area inference (Figs 1, S3, S4) yielded similar results, except for the exact origin (biogeographical subregion) of the subtribe Trochalina and the colonization mode of the Oriental region (see below). Inferences considering selected biogeographical subregions (Africa and the Mediterranean) were based on ancestral state inference (ML and MP) methods only (Figs 1 and S4). ML and MP analyses consistently resulted in the southern African subregion as the area of origin of Sericini and all of its African lineages, except for Sericina clade IV (node 16; origin in the Zambesian subregion), as well as the ancestor of Trochalina. For the latter, however, MP reconstruction with MPR was ambiguous whereas ACCTRAN optimization predicted the origin in the Zambesian subregion (Fig. S4).

BioGeoBEARS analyses on the six main regions (Figs 1 and S3) fitted the data best under the DEC+J model (Table S3). Models including cladogenetic dispersal by founder events (+J; Matzke, 2012) always fitted the data better than the respective alternatives without founder events (Table S3). The common ancestor of all Sericini occurred on the West Gondwanan landmass (Africa and South America; Fig. 1). The divergence between the Afrotropical Ablaberini and Sericini is dated back to 111.6 Ma (Table 1). The most basal split of Sericini (node 1, 93–112 Ma 95% HPD), separating the Neotropical genus Astaena from the remaining Sericini, was inferred as a vicariance process and coincides with the breakup of West Gondwana at about 105 Ma (Sanmartín and Ronquist, 2004; Cox and Moore, 2010).

The subsequent biogeographical history of the remaining Sericini was characterized by repeated migrations out of Africa and back again. The two oldest lineages of Old World Sericini (i.e. the Triodontella group (node 3+4) and the Omaloplia group (node 5+6)) showed similar distribution patterns of their two respectively vicariant clades. Ancestors of both lineages were inferred to have occurred in both the Palaearctic and Africa (64–101 Ma). In contrast to the African lineage of the Triodontella group (node 3), which is today distributed throughout Sub-Saharan Africa, Pleophylla (node 6) occurs only in forest remnants of southern Africa northward to the Albertine Rift Mountains in Rwanda, so that the extant distribution of the Omaloplia group has to be considered strongly disjunctive. Madagascar appeared to be invaded twice by a founder event (i.e, long-distance over-sea dispersal) by two independent lineages: the Comaserica group (node 7) and the Madagascan clade of the Mesoserica group (node 9). Invasion by the latter species-poor clade took place about 30 Myr after the first invasion (Table 1).

The mode of colonization of the Oriental region by Sericina could not be unambiguously resolved. Because relationships between basal Sericina were found to be stable according to SH-like aLRT branch support and the outcome of the CONSEL analysis, two scenarios of the colonization are plausible: (1) an ancestor of all Sericina populated Africa, and the Oriental region was invaded twice, or (2) the ancestor of Sericina dispersed to the Oriental region only once and Sericina clade I reinvaded Africa (result of the ML reconstruction, however, with low certainty, and MP reconstruction under ACCTRAN; Fig. S4). BioGeoBEARS inferred (with high uncertainty) scenario (1) with a vicariant split of the basal Sericina lineages (nodes 14 + 15 and 16) and subsequent jump dispersal (Matzke, 2014) to the Oriental region (node 15) (Fig. S3).

Greater certainty is seen in the recolonization of Africa by Sericina clade IV (node 17). However, SH-like aLRT supports are low at node 17 and its ancestral nodes (Fig. S4) and one species of Maladera (DA3821) from Africa seemed to distort the BioGeoBEARS analyses seriously. It is nested in the neighbourhood of the previously mentioned clades containing Asian species and led BioGeoBEARS to spurious results (i.e. much earlier dispersal to Africa implying five re-dispersals to Asia and the Eastern Mediterranean). The sister group of Sericina clade IV is Maladera (subgenus Macroserica), which has its extant distribution in the eastern Mediterranean subregion.

The colonization of North America was inferred to occur about 43 Ma (HPD: c. 39–48 Ma), at a time when the Bering Strait was mostly traversable, while the still present Turgai Sea and the expanding Norwegian Sea inhibited interchange between Asia, Europe and eastern North America (Cox and Moore, 2010). An eastward migration along the Bering Strait of today's Nearctic Sericina (node 19) is likely. Members of the genus Euserica (node 18), all inhabiting the Mediterranean subregion, diverged from its Asian sister group around 47 Ma, when the Turgai Sea still existed.

Analysis of diversification

Four rate shifts were found in the highest probability rate shift configuration (posterior probability = 0.13) with BAMM (Fig. 2). Medium high speciation rates were inferred for ancient Sericini lineages including Astaena, the Triodontella group and the Omaloplia group, followed by a slowdown of speciation rate. Distinct shifts to higher speciation rates were found for the genus Trochalus (Trochalina clade II, node 12, without basal lineage), the derived genus Tetraserica, which is nested within Sericina clade II (node 15), and the Asian Sericina clade III (node 16) except its basal lineage. Mean speciation rates increased conspicuously from c. 62 to 50 Ma, in particular in Sericina clade III (node 16; Fig. 3) which is concordant with a remarkable slowdown in the accumulation of lineages through time from 65 to 60 Ma (Fig. 3) after the Cretaceous–Palaeogene mass extinction (Schulte et al., 2010). Although speciation rates have decreased in Sericina clades III and IV since 50 Ma, they slightly increased in Trochalina clades I and II (Fig. 3). At 30 Ma a subtle slowdown of lineage aggregation is visible for all clades examined. A corresponding signal in the diversification rates (Fig. 3) is very weak but still present.

The cohort analysis clearly identified differing macroevolutionary dynamics for lineages with an inferred rate shift (Fig. S5), but also identified lineages with subtler deviations in rate dynamics, for instance, Sericina clade IV, which reinvaded Africa in the middle Eocene. Examining this clade alone revealed exceptionally high but steadily decreasing rates of speciation (Fig. 3).

Discussion

The present study is the first comprehensive biogeographical study of Sericini chafers, a megadiverse group of beetles with an as yet poorly resolved taxonomy. In addition to incomplete sampling and data support, and therefore possibly uncertain phylogenetic information, choice of biogeographical reconstruction methods and models, and unknown extinction events may obscure crucial biogeographical events (Heath et al., 2008; Crisp et al., 2011; Matzke, 2013a, 2014). Our results demonstrate how extensive sampling may help to overcome sampling-induced biases that originate from poor classification and taxonomic knowledge in phylogeny-dependent biogeographical analyses. This “as-complete-as-reasonably-possible sampling” approach also helped to minimize long-branch attraction effects (Bergsten, 2005) and to overcome problems of sequence alignment (Philippe et al., 2011). The divide-and-conquer realignment technique with simultaneous tree estimation (SATé-II; Liu et al., 2012) that we employed here may lead to great improvements, especially in hard-to-align data sets. Branch support was reasonable for the major clades that were used for biogeographical inferences. The basal position of the Neotropical genus Astaena had low aLRT support but is backed up by previous molecular and morphological studies (Ahrens, 2006c; Ahrens and Vogler, 2008; Liu et al., 2015). The same applies to the sister-group relationships of lineages within the Triodontella and the Omaloplia groups (nodes 3, 4, 5 and 6); however, the position of Hyboserica (node 8) has to be treated with care. All of this helped to facilitate the inference of the complex phylogenetic history of the large radiation of Sericini beetles, for which many of the commonly used algorithms would reach computational limits (Varón et al., 2010; Ronquist et al., 2012).

The historical biogeography of Sericini was discovered to be characterized by repeated migrations out of Africa with a huge radiation in Southeast Asia, from where they (re-)colonized distant regions, including Africa. The West Gondwanan (i.e. African) origin of Sericini revealed here by several methods is backed by the exclusively Afrotropical distribution of Ablaberini, the sister tribe of Sericini. The age of Sericini (c. 112 Ma) was inferred to be about 10 Myr older than previously estimated (Ahrens et al., 2014b), scarcely pre-dating the separation of South America from Africa (c. 105 Ma; Sanmartín and Ronquist, 2004; Cox and Moore, 2010). The divergence of the South American Sericini (c. 103 Ma) appeared to be more likely the result of vicariance (Fig. S3) rather than that of long-distance over-sea dispersal (Rage, 1988; Mourer-Chauviré, 1999), which was hypothesized previously (Ahrens, 2006c). Because morphological evidence strongly supports the monophyly of the South American Sericini (Ahrens, 2006c), this hypothesis is unlikely to be rejected based on a more representative sampling of the Neotropical fauna. Although movements of vertebrates between post-Gondwanan fragments were rare and mainly dispersals “out-of-Africa”, interchanges between Africa and Laurasia were numerous and bidirectional during the Cretaceous and the Palaeogene (Gheerbrant and Rage, 2006). Dispersal over diverse routes (e.g. trans-Tethyan dispersals via the Mediterranean Tethyan Sill) by amphibians, dinosaurs and mammals have been described from the earliest Cretaceous (Gheerbrant and Rage, 2006), even for those considered to be poor dispersers. Likewise, all of the six global-scale migrations of Sericini during the Cretaceous and early Palaeogene were dispersals “out of Africa”. More recent trans-Tethyan migrations of vertebrates in the Eocene were bidirectional (Gheerbrant and Rage, 2006) or happened in the northern Hemisphere (e.g. nodes 18 and 19). This is supported by the re-colonization of Africa by Sericini (node 17) and also by a dispersal of nymphalid butterflies from Africa to Asia around the same time (Kodandaramaiah and Wahlberg, 2007; Aduse-Poku et al., 2009).

Although vicariance sometimes displaced trans-oceanic dispersal as an explanation for observed disjunct distributions, the latter has been resurrected by various authors in an attempt to explain the colonization of distant regions (Givnish and Renner, 2004; De Queiroz, 2005; Matzke, 2012; Pyron, 2014). Similarly, in the present study, biogeographical models including founder event speciation always fit the data best (Table S3). In particular, the colonization of Madagascar was recently explained by trans-oceanic dispersal from Africa (Ali and Huber, 2010; Tolley et al., 2013), as was also found in the present study for both Madagascan lineages. This was consistent with other studies showing that founder event speciation is an important biogeographical process (i.e. colonization) for oceanic islands, but is also apparent in terrestrial or global systems (Matzke, 2013a,b, 2014; Pyron, 2014). Although land bridges to Madagascar, such as the Davie Ridge (Taquet, 1982) have been suggested, the divergence dates of these dispersal events more likely overlap with the timing of the prevailing west to east (Africa to Madagascar) palaeo-currents (Ali and Huber, 2010). Similar evidence also exists for vertebrates and other invertebrates (Vences et al., 2003; Esser and Cumberlidge, 2011; Samonds et al., 2012; Tolley et al., 2013). Because the Madagascan lineages considered in the present study only cover a small part of the genera of the highly endemic fauna, some uncertainty about the exact number of such independent colonizations remains. Based on preliminary morphological evidence we may definitively exclude any of the Madagascan species as belonging to either Sericina or Trochalina, which has a significant impact on the reconstruction of the colonization of Asia.

Several routes have been proposed for the colonization of Southeast Asia from Africa, including trans-Tethyan dispersal, long-distance over-sea dispersal and “out of India” rafting (Karanth, 2006). Dispersal over the Tethyan Sill would be the only scenario fitting the BioGeoBEARS inference for early Sericini (Figs 1 and S3); this route was still available for Sericini in the Late Cretaceous. Generally, different patterns of distributions of the two main Asian clades with prevalence for the Indomalay archipelago and Indochina (node 15) and the Asian mainland (node 16), respectively, make a second subsequent colonization of Southeast Asia of Sericina clade II (node 15) more likely than a re-colonization of Africa by clade I composed of mostly southern African species. Competitive exclusion of earlier and later colonizers might be a plausible cause shaping such patterns (Hardin, 1960; Waters, 2011). With the Somalian route, a second variant has been proposed for an “out of India” scenario (Chatterjee and Scotese, 1999; Mehrotra, 2003). Because this fits the timing of the Asian invasion as well, the “out of India” hypotheses cannot be rejected convincingly without more comprehensive sampling of the southern Indian Sericini fauna, represented in our study by only a few Maladera species (Fig. S1, Table S1). In the same way, this might help to overcome the ambiguity for the precise reconstruction of the colonization of Asia (see above).

By the middle Eocene, the reinvasion of Africa by Sericina very likely happened via the Iranian route that connected Africa with southeastern Europe and southwestern Asia (Gheerbrant and Rage, 2006) because the sister of the African clade IV (node 17) is distributed in the eastern Mediterranean. Discounting some uncertainty due to the phylogenetic misplacement of one Angolan Maladera species, the success of this re-colonization is impressive compared to other groups (Monaghan et al., 2007): clade IV is present in Africa with c. 300 species, nearly the same amount as that of autochthonous Trochalina.

During the period of North American colonization, the Bering Strait was mostly traversable, while the Turgai Sea was still present and the expanding Norwegian Sea inhibited an interchange between Asia, Europe and eastern North America (Cox and Moore, 2010). Given that Euserica (node 18) is not directly related to the North America species (clade V), an eastward-directed migration from Asia along the Bering Strait of today's Nearctic Sericina (node 19) is most likely. The few Asian species in the European fauna have very wide ranges and very likely invaded Europe after the Pleistocene from eastern Siberia. In contrast, exchange between North and South America never occurred, most likely due to the young age of the land connection and the Central American deserts (Howden, 1966).

Analyses considering the various subregions placed the origin of many older lineages (nodes 3, 6, 8, 10, 11 and 12) and that of Sericini itself in the southern African subregion. Strong exchange apparent between Afrotropical subregions (Fig. 1) makes it likely that the ancestors of these lineages were widely distributed and became extinct in other regions. This hypothesis is supported by the disjunct distribution of old lineages (e.g. Triodontella group, Omaloplia group), a pattern more commonly observed in ancient lineages that faced ecological pressures over long time periods, followed by extinction in intervening areas (Pyron, 2014). For example, the African lineage of the Omaloplia group Pleophylla (node 6), is presently distributed only in forest remnants in South Africa and the Albertine Rift Valley mountains in East Africa (J. Eberle, M. Beckett, A. Özguel-Siemund, J. Frings, S. Fabrizi, and D. Ahrens, unpublished data). Climatic refugia in southern Africa during the Last Glacial Maximum are evident for mammals, reptiles and insects (Lawes et al., 2007; Lorenzen et al., 2010, 2012; Barlow et al., 2013; Huntley et al., 2014; Switala et al., 2014) and low rates of extinction through climatic long-term stability in the Cape region (Schnitzler et al., 2011) might have promoted persistence of old lineages. Ancient relics (e.g. Hyboserica, Pleophylla) highlight the evolution of the African Sericini fauna as a series of large taxon pulses (Erwin, 1981, 1985) whose general patterns might be highly relevant for identification of high priority conservation zones with reference to phylogenetic diversity (Sechrest et al., 2002).

The two clades of “modern Sericini”—Trochalina and, in particular, Sericina—include exceptionally species-rich radiations, which arose contemporaneously about 70 Ma. A rapid diversification was not evident in the early history of these clades, but younger lineages within them (Trochalus and Sericina clade III without basal lineage) did exhibit a strong diversity burst. Possible causes of extensive diversifications of Asian Sericina are radiations into new areas with strong tectonic dynamics (Besse and Courtillot, 1988; Ramstein et al., 1997; Tapponnier et al., 2001; Hall, 2002) or the development of evolutionary key innovations (Hunter, 1998), such as the mechanical defence mechanisms used against ants by members of the genus Trochalus. However, testing these hypotheses is a subject for future research. Remarkably, the increase of the number of African and Asian Sericini lineages through time stagnated for about 5 Myr after the Cretaceous–Tertiary (K–T) boundary (Fig. 3). This period is known for the Cretaceous–Palaeogene mass extinction whose causes (e.g. a single or multiple asteroid impacts, Deccan volcanism) that globally affected conditions for life and climate are still debated (Schulte et al., 2010). Studies on other phytophagous insect groups showed similar patterns, which were attributed to a distinct reduction of actual lineages followed by subsequent diversifications (Wahlberg et al., 2009). The increase of diversification rate in Sericini a few million years after the K–T event supports this hypothesis. The slowdown of diversification within African Sericini lineages during the late Miocene–Pliocene coincides with hypotheses of a globally cooling climate (Zachos et al., 2001) and with a changing environment in Africa. The cold upwelling Benguela current along the Namibian coast (Siesser, 1980) additionally cooled the southern African continental climate, resulting in aridification and marked seasonality (Goldblatt and Manning, 2000; Stuut et al., 2004). Open habitats, vegetated with more arid-adapted C4 grasses, and savannas expanded (Cerling et al., 1997; Verboom et al., 2014) and were colonized by Sericini, among which better dispersers and ant-adapted lineages were obviously favoured. Consequences for the Asian lineages might have been less strong. Possibly the impact of climate oscillations was buffered or compensated for by the presence of large mountain ranges throughout Asia. Future studies with more detailed geographical sampling should shed more light on this aspect of Sericine evolution. Refinement of paleogeographic scenarios by more intense geographical sampling, together with the interpretation of morphological evolution through more detailed morphological studies (e.g. Eberle et al., 2014), will likely help to further clarify the biogeographical history and the evolution of Sericini.

Acknowledgements

For providing us with research and collection permits in South Africa, we thank the various governmental institutions (electronic supplement material). We are grateful to Ruth Müller and James Harrison (Ditsong Museum Pretoria) for their logistic help and the numerous collectors for providing additional specimens. Reese Worthington provided valuable comments on an earlier version of this manuscript.

Data accessibility

DNA sequences were stored at Genbank (accessions KT302408 - KT304198; Table S1). Distributional data has been uploaded as part of the Supplementary Material (Table S1, Fig. S1).

Authors' contributions

Article conception and design: JE, DA; Data acquisition / drafting, revising, and approving the article: JE, DA, SF, PL; Analysis and interpretation of data: JE, DA.

Funding

The study was supported by the German Science Association (DFG; AH175/1-2 and AH/175/3) and with a travel grant to JE by the A. Koenig Gesellschaft.

Competing interests

We have no competing interests.

Supporting Information

Filename

Description

cla12162-sup-0001-SupInfo.pdfPDF document, 9.1 MB

Fig. S1. Sampling localities, Ablaberini and Sericini distributions, and areas used for ancestral area reconstructions and estimation.

Fig. S2. BEAST tree with mean node ages and 95% highest posterior density intervals depicted as bars at each node.

Fig. S3. (Left) Ancestral area estimation results from BioGeoBEARS under the best-fitting model (DEC+j) and (right) the respective percentage ancestral state likelihoods depicted as pie charts at each node and branch.

Fig. S4. Alternative ancestral range reconstructions on the BEAST tree: (left) maximum-likelihood (SHL supports > 50 are given at nodes) and maximum parsimony (middle) under the MPR optimality criterion and (right) the ACCTRAN optimality criterion. Colours correspond to Fig. S1 and to the main text.

Fig. S5. Macroevolutionary cohort matrix for Sericini based on the BAMM analysis. Values between 0 and 1 represent the pairwise probability of species for sharing macroevolutionary dynamics.

Table S1. Overview on taxon sampling: species identification, voucher number, GenBank accession number and sampling location for all specimens in the study.

Table S2. BioGeoBEARS dispersal matrices for four time slices.

Table S3. Likelihoods and AIC scores of seven models tested in BioGeoBEARS.

Table S4. Lineages discussed in the text and their generic composition. The node numbers correspond to the main text (Fig. 1, Table 1).

Table S5. PCR protocols.

Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

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Citing Literature

Volume33, Issue2

April 2017

Pages 183-197

A historical biogeography of megadiverse Sericini—another story “out of Africa”?

Abstract

Introduction