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Biological Journal of the Linnean Society, 2011, 102, 130-143. With 3 figures

The birth of an endemic species flock: demographic history of the Bellamya group (Gastropoda, Viviparidae) in Lake Malawi

ROLAND SCHULTHEIB1*, THOMAS WILKE1, ASLAK J0RGENSEN2 and CHRISTIAN ALBRECHT1

department of Animal Ecology and Systematics, Justus Liebig University Giessen, Heinrich-Buff-Ring 26-32 (IFZ), D-35392 Giessen, Germany 2The Molecular Systematic Laboratory, The Natural History Museum of Denmark, S0lvgade 83, DK-1307 Copenhagen K, Denmark

Received 27 May 2010; accepted for publication 9 August 2010

Changes in habitat stability may significantly shape evolutionary patterns and processes in ancient lakes. In the present study, we use a hierarchical combination of molecular phylogenetic and coalescent approaches to inves tigate the evolutionary history of the endemic species of the gastropod genus Bellamya in the African rift-lake Malawi. By integrating our findings with reported palaeontological and palaeolimnological data, we demonstrate that all but one evolutionary lineage of the Pliocene Bellamya fauna in Lake Malawi became extinct. Coalescent analyses indicate that the modern radiation underwent both a sudden demographic and a spatial expansion after a genetic bottleneck. We argue that a reflooding of the lake after severe Pleistocene low stands offers a straightforward explanation for this pattern and may have triggered speciation processes in the modern endemic Bellamya radiation in Lake Malawi. © 2010 The Linnean Society of London, Biological Journal of the Linnean Society, 2011, 102, 130-143.

ADDITIONAL KEYWORDS: ancient lake - biogeography - extinction - lake level changes - parallel evolution - radiation - speciation.

INTRODUCTION elements or by triggering rapid speciation events during the conquest of new niches (e.g. Verheyen The longevity of ancient lakes (i.e. their continuous et al., 2003). As such, habitat changes may play a existence of often millions of years) was and still is decisive role in our understanding of emerging evo seen as an important factor for promoting high lutionary patterns. degrees of biodiversity and endemism (Michel, 1994; In quasi insular habitats such as ancient lakes, Schon & Martens, 2004; Albrecht & Wilke, 2008). these patterns are governed by three fundamental However, longevity does not necessarily imply habitat processes: speciation, immigration, and extinction stability. Indeed, habitat stability may change dra (MacArthur & Wilson, 1967; Whittaker et al., 2007). matically as a result of fluctuations in abiotic and All three processes often take place within a short biotic parameters over time (Scholz et al., 2007; time frame compared to the age of an ancient lake Stager & Johnson, 2008), thus affecting biodiversity and their scattered occurrence over time poses several in ancient lakes by, for example, erasing faunal challenges to their study: (1) understanding the speciation process itself requires demographic informa tion that will be lost once intraspecific lineage sorting Corresponding author. is completed (Avise, 2000); (2) extinctions, on the E-mail: [email protected] other hand, are difficult to detect using molecular

13 0 © 2010 The Linnean Society of London, Biological Journal of the Linnean Society, 2011, 102, 130-143 EVOLUTION OF BELLAMYA SPP. IN LAKE M ALAW I 131 phylogenetic inferences (Paradis, 2004); and (3) immi mechanisms for putative speciation processes (Irwin, gration, in turn, is difficult to distinguish from 2002). anagenesis if only fossil data are available (Van In the present study, we use a hierarchical com Bocxlaer, Van Damme & Feibel, 2008; Wesselingh & bination of molecular phylogenetic and coalescent Renema, 2009). Hence, an understanding of evolu approaches to test these predictions. By integrating tionary processes in ancient lakes requires a synopsis our findings with reported palaeontological and of two different methodological concepts: Deep-time, palaeolimnological data, we first examine the faunal large-scale phylogenetic information is needed to change from Pliocene to modern times using a rift- frame speciation, immigration, and extinction events wide multilocus molecular phylogeny to trace poten in a geographical and temporal context, whereas an tial extinction and immigration events in the history understanding of the short-term, small-scale demog of the endemic Malawian Bellamya group. In a raphy is essential to reveal the mode of speciation second step, we investigate the timing and mode of processes. recent speciation processes by examining the demo In the present study, we take advantage of both graphic history of the present radiation in a coales- concepts to investigate the evolutionary history of cent framework. Finally, we discuss our findings in the gastropod genus Bellamya Jousseaume, 1886 the context of reports from other evolutionary (Viviparidae) in the African rift-lake Malawi. studies on the endemic fauna of Lake Malawi. The Pliocene fossil beds in Northern Malawi bear witness synopsis of these approaches may not only help to to a rich Bellamya fauna in the lake with an age of enlighten the history of a remarkable endemic up to four million years (Schrenk et al., 1995). This invertebrate assemblage in Lake Malawi, but also fauna, however, resembles only in part the modern may contribute to our general understanding of radiation. Indeed, the morphological comparison of the timing and mode of evolutionary processes in both assemblages reveals a complete loss of shell ancient lakes. ornamentation in the modern group (and thus the loss of a potential anti-predator device), as well as changes in shell shape (a potential adaptation to MATERIAL AND METHODS different hydrological conditions) (Schrenk et al., 1995; Van Damme & Pickford, 1999). To date, Sam plin g neither the nature of this remarkable faunal change, Four species of the genus Bellamya Jousseaume, 1886 nor its timing, is known. However, lake level are described from Lake Malawi (Mandahl-Barth, changes offer a potential starting point for relevant 1972; Brown, 1994): the three endemics Bellamya investigations. jeffreysi (Frauenfeld, 1865, Vivipara), Bellamya rob- The modern Lake Malawi is among the largest and ertsoni (Frauenfeld, 1865, Vivipara), and Bellamya deepest lakes in the world (570 km long, maximum ecclesi (Crowley & Pain, 1964, Neothauma), as well as depth 706 m) but it has faced tremendous lake level the widely distributed Bellamya capillata (Frauen- drops of up to 600 m throughout its history (Cohen feld, 1865, Vivipara). Specimens of these taxa were et al., 2007; Scholz et al., 2007). Although it reached collected in 2006, 2007, and 2008 at 25 localities from deep water conditions approximately 4.5 Mya (Ring & Lake Malawi and its surroundings, from the Shire Betzler, 1995), it has been argued that some of the River, Lake Kazuni, Lake Malombe, and from the extant radiations have evolved only in the aftermath satellite-lake Chilingali (all Republic of Malawi; of Pleistocene lake level low stands (Sturmbauer Figs 1, 2). Additionally, we included specimens from et al., 2001; Seehausen, 2006; Cohen et al., 2007; Lake Albert (Uganda), Lake Mweru (Zambia), Lake SchultheiB et al., 2009). Because Malawi’s lake level Victoria (Uganda, Tanzania), and from the Okavango drops did not result in basin fragmentation, a reflood Delta and the Zambezi River (Namibia, Botswana, ing allows species to explore newly-emerging habitats Zambia) in our phylogenetic analyses, as well as without facing secondary contact as expected from NCBI GenBank sequences of eight specimens from basin separation as in, for example, Lake Tanganyika Lake Bangweulu, Lake Kariba, Lake Mweru (all (Marijnissen et al., 2006; Egger et al., 2008). This Zambia), and Lake Victoria (Uganda). Because of the leads to testable predictions concerning the expected ambiguous phylogenetic relationship between the evolutionary patterns of this habitat change: taxa genera Bellamya and Neothauma (Sengupta et al., following the expansion of the lake margin should 2009), we also included Neothauma tanganyicense experience: (1) a rapid increase in population size and Smith, 1880 from Lake Tanganyika (Tanzania; (2) a spatial expansion. The resulting consecutive Fig. 1). founder events at the edge of the expansion front in Specimens were determined on the basis of shell combination with an increase of isolation by distance characters as described in the original literature. between populations pose straightforward candidate Shell and soft tissue vouchers are deposited at the

Figure 1. Multilocus Bayesian phylogeny of Bellamya spp. and Neothauma tanganyicense inferred from cytochrome oxidase subunit I, mitochondrial and nuclear large subunit of mitochondrial ribosomal RNA. The topology is largely congruent with the results from a maximum parsimony inference. Bayesian posterior probabilities (BPP) and bootstrap support values (BS) are given next to the nodes (only values above 0.7 BPP and 70 BS are shown). The tree was rooted with sequences of B. bengalensis. Clade colour on the phylogeny corresponds to the colour of the sampling localities from major water bodies in Central East Africa. Detailed locality information is provided in Table 1.

zoological collection of the Berlin Museum of Natural cytochrome oxidase subunit I (COI) gene using the History (Table 1). forward primer LCO1490 (Folmer et al., 1994) and a newly-designed reverse primer COX-B7R (5'- ACCACCAGCTGGATCAAAAA-3'). In addition, we D N A ISOLATION AND SEQUENCING amplified a fragment of the mitochondrial large DNA was isolated using a CTAB protocol (Wilke et al., subunit of ribosomal RNA (LSU rRNA) using the 2006). We amplified a fragment of the mitochondrial primer pair 16Sar-L and 16Sbr-H (Palumbi et al.,

Figure 2. Statistical parsimony haplotype network of the cytochrome oxidase subunit I dataset of all specimens collected from Lake Malawi’s drainage area (connection limit: 95%). Sampling localities are shown on the right (for detailed locality information, see Table 1). Haplotype colours correspond to Bellamya species; circle size indicates the number of identical haplotypes. Haplotype numbers correspond to the numbers of the Malawi clade in Figure 1.

1991) and a fragment of the nuclear LSU rRNA using the African Rift as well as from the Okavango Delta the primer pair F63.2-F and LSU3-R (Park & O and the Zambezi River (Fig. 1; locality details are Foighil, 2000). The polymerase chain reaction condi given in Table 1). We included only eight out of 65 tions employed were as described by SchultheiB et al. specimens from Lake Malawi (comprising all four (2008). Sequences (forward and reverse) were deter species) into the phylogenetic analyses to keep the mined using a Long ReadIR 4200 DNA sequencer rift-wide phylogenetic dataset balanced. As outgroup, (Li-Cor) and a Thermo Sequenase Fluorescent we chose B. bengalensis, available from NCBI Labeled Primer Cycle Sequencing kit (Amersham GenBank, which was shown to be the sister taxon to Pharmacia Biotech). Fragments were aligned using the African Viviparidae (Sengupta et al., 2009). A test CLUSTALW, version 1.4 (Thompson, Higgins & for substitution saturation for the relatively fast Gibson, 1994) as implemented in BIOEDIT, version evolving COI gene using the entropy-based index in 7.0.5.3 (Hall, 1999). Because the first base pairs of the DAMBE (Xia et al., 2003) did not reveal substantial sequences of the three fragments were difficult to saturation (Iss < Iss.c; P = 0.0036). For phylogenetic read, we cut off the first few base pairs, leaving (after reconstruction of the combined dataset, we conducted alignment) a 593-bp long, completely overlapping a partitioned Bayesian analysis with a flat Dirichlet fragment for the COI gene, a 436-bp long fragment for prior probability density using MrBayes 3.1.2 (Ron- the mitochondrial and a 1087-bp long fragment for quist & Huelsenbeck, 2003). Mixing of the MCMC the nuclear LSU rRNA. All sequences are available chains of the two independent runs was monitored from NCBI GenBank (Table 1). with TRACER, version 1.4.1 (Drummond & Rambaut, 2007) and the analysis was terminated after the Phylogenetic an alysis average standard deviation of the split frequencies The phylogenetic dataset comprised a total of 42 fell under 0.01. The first 10% of the sampled approxi specimens from most major water bodies of and along mately 10 million generations were discarded as

© 2010 The Linnean Society of London, Biological Journal of the Linnean Society, 2011, 102, 130-143 134 R. SCHULTHEIB ETAL. Collection number GenBank number ncLSU GenBank number mtLSU GenBank number COI India Sundarbans FJ405878 FJ405735 FJ405623 Zambia Lake MweruZambiaZimbabwe Lake Mweru Lake Kariba FJ405840 FJ405694 FJ405867 FJ405838 FJ405710 FJ405595 FJ405689 FJ405591 FJ405620 1*11* India1 Tanzania Sundarbans Uganda1 Lake Victoria Uganda Lake Victoria1 33.79654 Lake Tanzania Albert1 -2.26658 Lake Tanganyika Botswana 30.89265 HQ012712 29.69946 Zambezi1* Zambia HQ012680 1.42904 -4.785431* FJ405877 HQ012714 Lake HQ012716 Mweru Zambia 25.12985 FJ405847 Zambia HQ012682 FJ405724 HQ012683 -17.81595 Lake Mweru 28.73133 FJ405714 HQ012798 Lake Mweru -9.34801 FJ405622 HQ012706 HQ012684 ZMB 113499 HQ012719 FJ405613 ZMB 113503 HQ012708 ZMB 113500 ZMB 113505 FJ405842 FJ405844 FJ405695 ZMB 113509 FJ405596 FJ405592 2* 22 Uganda2 Tanzania Lake Albert2 Lake Tanganyika Zambia 30.91564 29.69946 Zambezi Zambia 1.44854 -4.785432* HQ0127152* Lake HQ012717 Mweru 25.86266 HQ012681 -17.92190 28.73133 HQ012799 HQ012705 -9.34801 HQ012685 HQ012720 ZMB HQ012707 113501 HQ012688 ZMB 113504 ZMB 113506 ZMB 1135010 52 Zambia57 Zambia Lake Mweru Namibia Zambezi 29.04460 Namibia Okavango Delta -9.04567 Zambezi 25.86266 21.58754 HQ012724 -17.92190 -18.12071 24.25615 HQ012727 HQ012730 -17.48629 HQ012694 HQ012732 HQ012710 ZMB 113514 ZMB ZMB 113517 113520 ZMB 113522 Haplotype 44* Botswana Zambezi34 25.129856 -17.81595 Zambia Botswana HQ012718 Zambia Lake Mweru Okavango Delta HQ012687 Lake 23.49086 Mweru 29.04460 -19.94043 -9.04567 29.04460 HQ012723 HQ012722 -9.04567 HQ012691 HQ012690 HQ012725 ZMB 113508 HQ012692 ZMB 113513 ZMB 113512 ZMB 113515 33* Uganda3 Zambia Lake Albert3 Lake Tanganyika Namibia 30.89265 Okavango Delta Zambia 1.42904 21.58754 HQ012713 Lake Mweru -18.12071 HQ012800 28.73133 FJ405843 HQ012686 -9.34801 FJ405709 HQ012721 HQ012709 HQ012689 FJ405598 ZMB 113507 ZMB 113502 ZMB 113511 346 Namibia Namibia Zambezi Namibia Zambezi Zambezi 23.33815 23.33815 -17.98192 24.25615 -17.98192 HQ012728 -17.48629 HQ012729 HQ012695 HQ012731 HQ012696 ZMB 113518 ZMB 113519 ZMB 113521 number Country Locality Longitude Latitude List of specimens analyzed in the course of this study (shell and tissue vouchers are deposited at the zoological collection of the Berlin Museum of sp. 1 Botswana Okavango Delta 23.49086 -19.94043 HQ012726 HQ012693 ZMB 113516 cf. 1* Zambia Lake Bangweulu FJ405874 FJ405693 FJ405594 bengalensis trochlearis tanganyicense monardi mweruensis costulata rubicunda crawshayi capillata pagodifonnis Species Table 1. Natural History; ZMB) Bellamya Bellamya Bellamya Bellamya Bellamya Bellamya Bellamya Bellamya Bellamya Bellamya Neothauma

2010 The Linnean Society of London, Biological Journal of the Linnean Society, 2011, 102, 130-143 1 Malawi Ma05 33.64470 2 Malawi Ma05 33.64470 8 Malawi Mal5 34.91818 9 Malawi Mal2 34.80871 121011 Malawi Malawi Malawi M al4 Mal217 Ma04 Malawi 34.84807 18 34.80871 Ma08 34.09455 Malawi Ma08 34.29794 34.29794 2524232021 Malawi22 Malawi Malawi Malawi Mal2 Malawi Mal2 Malawi Mal25a Ma025b Ma045c Ma075d 34.80871 5e Malawi 34.80871 Malawi 34.80871 28 Malawi 33.95576 27 Malawi Ma22 34.09455 Malawi Ma22 34.21051 Ma25 Malawi Ma23 Malawi Mal7 Ma08 35.24633 Ma08 35.24633 34.86306 35.22272 34.91693 34.29794 34.29794 30 Malawi M al8 34.93017 3a3b Malawi Malawi Ma23 Ma22 35.22272 4a 35.24633 4b4c306a Malawi6b Malawi Malawi Malawi Ma06 Malawi Ma07 Malawi Ma07 Mal7 Ma22 Ma24 34.21240 34.21051 34.21051 34.91693 35.24633 34.90498 19a19b19c19d19e Malawi19f Malawi17a Malawi17b Malawi MaOl17c Malawi Ma0317d Malawi Ma0317e Malawi MaOl17f Malawi Ma04 Malawi Ma04 Malawi Ma02 33.88786 Malawi M all 33.93944 Malawi M all 33.93944 Mal2 33.88786 M al4 34.09455 Mal4 34.09455 33.95576 34.52530 34.52530 34.80871 34.84807 34.84807 26a26b Malawi Malawi Ma09 Ma09 34.29539 34.29539

capillata jeffreysi Malawi dataset Bellamya Bellamya Bellamya ecclesi

2010 The Linnean Society of London, Biological Journal of the Linnean Society, 2011, 102, 130-143 -14.08923 HQ012733 HQ012697 ZMB 113523 -11.14642 HQ012741 ZMB 113524 -11.14642 HQ012742 ZMB 113525 -15.05699 HQ012743 ZMB 113526 -14.45179 HQ012744 ZMB 113527 -9.75928 HQ012764 ZMB 113528 -9.97632 HQ012765 ZMB 113529 -9.97632 HQ012766 ZMB 113530 -9.75928 HQ012767 ZMB 113531 -10.21013 HQ012769 HQ012703 ZMB 113532 -10.21013 HQ012768 ZMB 113533 -9.94260 HQ012773 ZMB 113534 -13.98395 HQ012774 ZMB 113535 -13.98395 HQ012775 ZMB 113536 -14.25598 HQ012776 ZMB 113537 -14.01498 HQ012777 ZMB 113538 -14.01498 HQ012778 ZMB 113539 -12.92109 HQ012760 ZMB 113540 -12.92050 HQ012761 ZMB 113541 VLTO OFEVOLUTION -12.92050 HQ012762 ZMB 113542 -14.07031 HQ012763 ZMB 113543 -14.45179 HQ012759 ZMB 113544 -15.38884 HQ012734 HQ012699 HQ012711 ZMB 113545 -14.05723 HQ012757 ZMB 113546 -14.25598 HQ012747 ZMB 113547 -14.25598 HQ012738 ZMB 113548 -14.25598 HQ012739 ZMB 113549 BELLAMYA -9.94260 HQ012770 ZMB 113550 -10.21013 HQ012737 HQ012702 ZMB 113551 -12.92050 HQ012771 ZMB 113552 -14.01498 HQ012753 ZMB 113553

-14.25598 HQ012756 ZMB 113554 135 MALAWI LAKE SPP. IN -14.25598 HQ012754 ZMB 113555 -10.21013 HQ012755 ZMB 113556 -14.45179 HQ012784 ZMB 113557 -14.45179 HQ012785 ZMB 113558 -15.44576 HQ012786 ZMB 113559 -15.05699 HQ012787 ZMB 113560 -14.07031 HQ012788 ZMB 1135561 -12.88355 HQ012736 HQ012701 ZMB 113562 -12.88355 HQ012749 ZMB 113563 -12.88355 HQ012748 ZMB 113564 -12.92552 HQ012750 ZMB 113565 -12.92552 HQ012751 ZMB 113566 -12.88355 HQ012735 HQ012700 ZMB 113567 136 R. SCHULTHEIB ETAL. MalawiMalawi Ma20 Ma20 34.92824 34.92824 -14.11128 -14.11128 HQ012794 HQ012795 ZMB 113581 ZMB 113582 7 Malawi M al9 34.93279 -14.09622 HQ012758 ZMB 113585 1715161413 Malawi Malawi Malawi Mal3 Malawi M al6 Malawi Ma20 M al8 34.82940 Mal8 34.92632 34.92824 -14.03115 34.93017 -14.06407 34.93017 -14.11128 HQ012772 -14.08923 HQ012780 -14.08923 HQ012781 HQ012779 HQ012752 HQ012698 ZMB 113570 ZMB 113574 ZMB 113571 ZMB 113572 ZMB 113573 295a5b5c5d Malawi5e Malawi5f Malawi5g Mal3 Malawi5h M al8 Malawi5i M al8 Malawi M al8 34.82940 M al8 34.930175b M al8 Malawi 34.93017 -14.03115 Malawi 34.93017 -14.08923 34.93017 Ma20 -14.08923 34.93017 HQ012740 Mal8 Malawi -14.08923 HQ012789 -14.08923 HQ012790 34.92824 -14.08923 Ma07 HQ012791 34.93017 HQ012792 HQ012793 -14.11128 34.21051 -14.08923 HQ012796 -12.92050 HQ012797 HQ012783 HQ012704 ZMB 113575 ZMB 113576 ZMB 113577 ZMB 113578 ZMB 113579 ZMB 113580 ZMB 113584 ZMB 113583 ZMB 113587 3a3b Malawi Malawi Mal7 Ma20 34.91693 34.92824 -14.07031 -14.11128 HQ012745 HQ012746 ZMB 113568 ZMB 113569 Haplotype GenBank GenBank GenBank Collection Continued sp. 5a Malawi Ma07 34.21051 -12.92050 HQ012782 ZMB 113586 Species number Country Locality Longitude Latitude number COI vouchers DNA are stored in number the collection mtLSUof the Department of Animal Ecology and Justus Biodiversity, Liebig University Giessen, Germany number ncLSU number Specimens Specimens from GenBank are marked with an asterisk (*); Ma numbers for specimens from Malawi refer to the localities in Figure 2. COI, cytochrome oxidase subunit I; mtLSU, Table 1. Bellamya robertsoni Bellamya mitochondrial large subunit ofribosomal RNA; ncLUS, nuclear large subunit ofribosomal RNA.

2010 The Linnean Society of London, Biological Journal of the Linnean Society, 2011, 102, 130-143 EVOLUTION OF BELLAMYA SPP. IN LAKE M ALAW I 1 3 7 burn-in. Additionally, a maximum parsimony analysis lamya species was evaluated after running the was carried out using heuristic searches (tree Markov chain for 1 000 000 steps. bisection-reconnection branch swapping) and 100 Demographic and spatial histories of populations replications of random stepwise additions with were studied utilizing mismatch analyses. Whereas a PAUP* 4.0b10 (Swofford, 2003). Clade support values demographic equilibrium (i.e. constant population were calculated from 1000 bootstrap replicates. size) generates a multimodal distribution of pairwise nucleotide differences among specimens, unimodal mismatch distributions indicate demographic expan

N e tw o r k a n alysis sion (Rogers & Harpending, 1992). Schneider & Excoffier (1999) and Excoffier (2004) extended this Whereas both the mitochondrial as well as the approach, allowing estimations of demographic nuclear LSU rRNA were informative for the rift-wide parameters from a pure demographic expansion phylogenetic analysis (see above), they showed almost model and a spatial expansion model by a generalized no genetic variation among specimens from Lake nonlinear least-square approach. We tested the Malawi and its surroundings. For subsequent analy spatial expansion model for the entire Malawi group ses of the Malawian Bellamya, we hence used the COI because, in contrast to the subsequent tests, this dataset exclusively, comprising a total of 65 sequences model allows for restricted gene flow between groups. (hereafter termed the Malawi group). Hence, it does not require panmixia but assumes that A statistical parsimony haplotype-network of the the sampled group is subdivided into an infinite COI dataset was constructed using TCS, version 1.21 number of demes that exchange a fraction, m, of (Clement, Posada & Crandall, 2000) with the connec migrants. The model has also been shown to be robust tion limit set to 95%. Cladogram ambiguities were to fluctuations in ancient population sizes and to resolved sensu Pfenninger & Posada (2002). potential genetic bottlenecks subsequent to the onset of the range expansion (Excoffier, 2004). In a second step, we tested the model of a demographic expansion D em ographic h isto r y a n d su m m a r y statistics for each of the three species separately because this To trace the demographic history of the Malawi model requires panmixia, an assumption that is vio group, we first tested for a genetic structure in the lated given the highly significant genetic differentia COI dataset. We therefore grouped all individuals to tion between the three species (for details, see the nominal species B. capillata (38 specimens), B. Results). We also provide the results from these esti jeffreysi (6 specimens), and B. robertsoni (18 speci mations for B. jeffreysi but are aware that the limited mens; Table 1). Note that we did not include B. ecclesi number of specimens probably leads to an unstable in the subsequent analyses because we found only a distribution of nucleotide pairwise differences. The single specimen of this taxon and we also excluded obtained parameters should therefore be treated with two individuals from the analyses that could not be caution (Schneider & Excoffier, 1999). determined. To examine the amount of molecular Confidence intervals (CI) for both models were differentiation between the species, we performed an derived using coalescent simulations with 10 000 analysis of molecular variance (AMOVA) as imple replicates. Apart from the mutation parameter 9, mented in ARLEQ U IN , version 3.5 (Excoffier, Laval & the models also estimate time since expansion: Schneider, 2005). This analysis decomposes the total t = 2t\i, where t is time in generations and m is the genetic variance in the dataset into covariance total mutation rate per generation per gene (Rogers components of inter-individual differences and inter & Harpending, 1992; Schneider & Excoffier, 1999). group differences (Excoffier, Smouse & Quattro, In the absence of a Bellamya-specific mutation rate, 1992). We performed a hierarchical AMOVA with a we applied a trait specific COI Protostomia rate of distance matrix of pairwise differences and tested the 1.22% ± 0.27% sequence divergence per million years significance of the F statistic by generating a null- for the Jukes-Cantor model to our dataset (Wilke, distribution based on 10 000 permutations of the SchultheiB & Albrecht, 2009). This rate has been original dataset. shown to be robust among invertebrate taxa with As a second approach of inferring genetic differen similar biological and life-history characteristics (i.e. tiation among nominal Bellamya species, we per dioeceous tropical or subtropical taxa with a genera formed an exact test sensu Raymond & Rousset tion time of approximatey 1 year and a body size of (1995) and implemented in ARLEQUIN, version 3.5. approximately 2-50 mm). All these criteria are met As an analogue to Fisher’s exact test, the hypothesis by African Bellamya (Brown, 1994). of a random distribution of k different haplotypes To give meaningful 95% CIs for our time estimates, among r populations (i.e. panmixia) is tested. The we need to account for the error of the t estimate significance of differentiation between the three Bel- (At) as well as for the error of the mutation rate

(Dm = 0.27%). Accordingly, we calculated the propaga Table 2. Results from the analysis of molecular variance: tion of uncertainty based on the partial derivates of all Malawian specimens with the exception of the Bel the underlying function (i.e. t = t/2u). Sensu Rogers & lamya ecclesi individual and two undetermined individu Harpending (1992: 562), u equals mT|m, where m T is als where grouped to the three endemic species Bellamya the number of base pairs in the fragment under capillata, Bellamya jeffreysi, and Bellamya robertsoni (for consideration (here: 593 bp) and m is the mutation details, see text) rate per nucleotide (here: 1.22%). Hence, the under lying function (without errors) is: Source of Sum of Variance Variation variation d.f. squares components [%]

T ( t , | i)= T 2mT|i Among groups 2 16.062 0.40712 23.39 Within groups 59 78.664 1.33328 76.61 Using the partial derivates of this function, we can Total 61 94.726 1.74040 100 calculate the total error of the time estimate as:

dG A \2 fd G A >2 these major groups with respect to branching pattern AT = + U r A|11 (probably as a result of short internal branches), as 2 2 well as with respect to support values (all BPP values ( 1 -A’ -A|i < 0.71; BS values < 70). We therefore collapsed these branches into a polytomy (for a discussion on the Note that the variables t and m are not correlated impact of internal branch lengths on phylogenetic and, hence, their covariance does not need to be taken accuracy, see Kolaczkowski & Thornton, 2004). into account. Notably, specimens of B. capillata from Lake Malawi Finally, we tested for indications of past demo do not cluster with individuals initially determined as graphic events or influences of selection using Taji- B. capillata from other water bodies in Central-East m a’s D statistic: Under neutral expectations, the Africa. Because Lake Malawi is the type locality of average number of pairwise nucleotide differences (p) the species, the latter specimens are labelled B. cf. and the number of segregating sites (S ) are both capillata in Figure 1. unbiased estimates of 9 (i.e. the product of the effec tive population size Ne and the mutation rate m) N e tw o r k an alysis (Tajima, 1989b). Departures from this neutral expec The statistical parsimony network of the Malawi tation may indicate a locus under selection or changes group revealed 30 different haplotypes from a total of in population size (for a summary, see Ramirez- 65 CoI sequences. The network comprises not only all Soriano et al., 2008). We used Tajima’s D statistic as sampled specimens from the lake itself but also from implemented in ARLEQUIN, version 3.5 to test the Lake Malawi’s drainage system and the Shire River neutral model for each of the three species. Signifi (Fig. 2). In concordance with the inferred phylogeny, cances of the statistic were inferred using coalescent the most aberrant haplotype is a specimen of B. simulations with 10 000 replicates. robertsoni (h13), which is separated from its closest neighbour by five mutational steps. Note that the RESULTS sequence divergence of 5.9% between a B. robertsoni specimen (ht3 in Fig. 2, Table 1) and other Malawian Phylogenetic an alysis Bellamya individuals as reported by Sengupta et al. Phylogenetic inferences of the partitioned dataset (2009) could not be confirmed after resequencing that with a total of 2086 bp revealed six well supported specimen. major clusters (Fig. 1). These groups largely corre spond to the major lake systems of and along the African Rift and are monophyletic for lakes Malawi Demographic history and summary statistics [Bayesian posterior probability (BPP) 1.00; bootstrap AMoVA revealed a highly significant amount of support (BS) 100] and Tanganyika (BPP 1.00; BS 99) genetic differentiation among nominal species as well as for the Victoria-Albert system (BPP 0.99; (P < 0.0001): 23.39% of the total variation is distrib BS 99). Specimens from the Zambezi River are para- uted among the species (Table 2). This number is phyletic (two major clusters; both BPP 1.00; BS 100), identical to the inferred fixation index (FST) and, by with one group being in close relationship to the following the qualitative guidelines of Wright (1978), likewise paraphyletic Mweru-Bangweulu assem indicates great genetic differentiation. The exact test blage. Bayesian and maximum parsimony inferences of sample differentiation rejected the null hypothesis were inconclusive about the basal relationships of of panmixia between B. capillata and B. jeffreysi

Table 3. Estimated parameters of the spatial expansion model of the entire Malawi group and the demographic expansion model for three endemic Malawian Bellamya species based on the distribution of pairwise nucleotide differences

Species t t (CI) SSD P (SSD) RI P (RI) T [y] AT [y]

Spatial expansion Malawi group 1.40 0.74-4.09 0.001 0.76 0.01 0.79 96 757 ±117 955 Demographic expansion Bellamya capillata 2.89 1.53-3.95 0.002 0.70 0.02 0.69 199 734 ±94 590 Bellamya jeffreysi 6.75 0.08-10.52 0.070 0.40 0.18 0.57 - - Bellamya robertsoni 1.48 0.37-2.89 0.018 0.36 0.05 0.83 102 286 ±89 976

For details on the estimation of T as time subsequent to expansion in years [y] and its confidence intervals, see Material and methods. CI, confidence interval; P, significance of the respective parameter (level 0.05); RI, raggedness index; SSD, sum of squared deviations from the respective model.

(P = 0.0486), and B. capillata and B. robertsoni (P = 0.0003), although it did not reject the differen tiation between B. jeffreysi and B. robertsoni (P = 0.1105). The significance level for these and sub sequent analyses is 0.05. The mismatch distributions of all three species as well as of the entire Malawi group are unimodal (nonsignificant P -values of the Raggedness index; Table 3). The observed distribution did not reject the pure demographic expansion model or the spatial expansion model in favour of a demographic equilib rium in either test (sum of squared deviations and associated P -values are given in Table 3; see also Fig. 3). Note that the 95% CIs for the estimated parameter t are very high for B. jeffreysi. Moreover, given the probably unstable mismatch distribution of Figure 3. Mismatch distribution of the cytochrome this species (see Material and methods), we refrain oxidase subunit I dataset of the Malawi group. The dis from providing time estimates for this species because tribution of the pairwise nucleotide differences (white the abovementioned factors might render the estima bars) was tested against a model of a spatial expansion tion uninformative. The mean estimate of the onset of (black line). The 95% confidence interval of the coalescent the spatial expansion of the entire Malawi group is simulations with 10 000 replicates is indicated by dashed approximately 97 000 years. This event postdates the lines. The observed mismatch distribution of the Malawi onset of the demographic expansion of B. capillata group did not differ significantly from the model (sum of (approximately 200 000 years) but falls in a similar squared deviation was 0.001; for details, see Table 3). range to the demographic expansion of B. robertsoni (approximately 102 000 years; for exact values and ecclesi, B. jeffreysi, and B. robertsoni) and one as 95% CIs, see Table 3). widely distributed (B. capillata). Indeed, Brown Testing the neutral mutation hypothesis using Taji- (1994) considered the distribution of the latter to ma’s D revealed significant deviations from the model cover large parts of the distribution of the entire in B. capillata (D = -1 .7 4 , P = 0.02), and in B. robert genus on the African continent. The findings of the soni (D = -1 .5 7 , P = 0.04), but not in B. jeffreysi present study show, however, that all Bellamya speci (D = -0 .1 7 , P = 0.46). A genetic equilibrium is hence mens collected throughout the drainage area of Lake rejected for the former two species. Malawi form a monophyletic group (including B. capillata; Figs 1, 2) and, thus, that B. capillata is also DISCUSSION endemic. The endemism of this group is not restricted L evel of e n d e m ism a n d parallel e vo lu tio n to the lake proper but to the Lake Malawi drainage Former studies have recognized three Bellamya area. We have found specimens of this endemic group species inhabiting Lake Malawi as endemic (B. in tributary rivers, satellite lakes and in the Shire

River, which drains Lake Malawi in the South (i.e. at cated by the short internal branches (collapsed into a all localities shown in Fig. 2). polytomy in Fig. 1). Moreover, whereas the African Because the type locality of B. capillata is Lake rift-lakes are shown to harbour monophyletic groups Malawi and because specimens initially determined (Fig. 1), a paraphyletic and comparatively highly as B. capillata from other parts of Africa (labelled as diverse Bellamya fauna was found in the Zambezi B. cf. capillata in Fig. 1) do not form a monophyletic drainage system, This pattern provides a promising group, we conclude that this morphotype has evolved starting point for future studies on the historical either independently several times or represents a biogeography of this genus in Africa. plesiomorphy in shell morphology. The evidence of this cryptic species-complex reinforces the need for a DNA-based revision of the genus. Demographic history of the modern B e ll a m y a FAUNA IN LAKE MALAWI Our inferences of the demographic history of the Partial extinction of Pliocene B e l l a m y a and Malawian Bellamya species indicate a sudden recent ISOLATED EVOLUTION IN THE MALAWI RIFT increase in effective population size (Table 3). This With respect to the before mentioned three funda pattern may arise from two different evolutionary mental evolutionary processes in insular habitats, the processes: a founder event or a genetic bottleneck. present study provides new insights into their timing Both result in a loss of ancestral genetic diversity, and interplay in the endemic Bellamya group within with the extent of the loss depending on the relative the Malawi basin. We now discuss immigration and size of the founding population or on the severity and extinction events in the history of these species, duration of the bottleneck (Tajima, 1989a). Because whereas the issue of speciation is addressed in the any founding event constitutes in principle a genetic subsequent section. bottleneck, the biologically relevant difference lies The Malawi group descends from one deep phylo within the geographical context. Did the source popu genetic branch (Fig. 1), pointing towards a single and lation immigrate from a remote water body (founder ancient immigration event of the ancestors of the event) or did it face harsh conditions in its ancestral present radiation into the lake. From thereonward, environment (genetic bottleneck)? this lineage has likely evolved in isolation within the As outlined above, the phylogenetical pattern pre basin and has given rise to at least two radiations in sented here is consistent with a long, isolated history time (i.e. the Pliocene assemblage and the modern of the Malawian Bellamya fauna. The rapid expan group). Moreover, our analyses indicate that all but sion in population size happened thus most likely in one species of the reported Pliocene Bellamya fauna the aftermath of a severe bottleneck and testifies to a in Lake Malawi became extinct. Although the recovery of the group from harsh conditions in the Pliocene Bellamya fauna comprised two ornamented Malawi Rift. Although potential causes of a bottleneck species that are absent in the modern radiation (B. cf. are numerous, the most parsimonious assumption pagodiformis and B. cf. trochlearis), morphotypes of (which simultaneously explains the inferred rapid two unornamented species from the Pliocene beds are spatial expansion; Fig. 3, Table 3) is a drop in present in the lake today (B. cf. capillata and B. cf. Malawi’s lake level. A reflooding of the lake was robertsoni) (Gorthner, 1994; Schrenk et al., 1995; Van already suggested to have triggered the extant radia Damme & Pickford, 1999). However, given the distri tions in cichlid fishes (Owen et al., 1990; Sturmbauer bution of the pairwise nucleotide differences and the et al., 2001) and in the endemic species of the gastro time estimates from the expansion models (Fig. 3 and pod genus Lanistes (SchultheiB et al., 2009). It Table 3), we argue that the most recent common remains unknown, however, whether the ancestors of ancestor of the extant Malawi group must have lived the modern gastropod radiations survived the lake in the Pleistocene. Hence, only a single evolutionary level drop in the remnant of the lake or in the lake’s lineage survived from the Pliocene radiation and con drainage system. stitutes the ancestor of the modern group. In light of The palaeolimnological record bears witness to the well supported monophyly of the extant Malawi several dramatic low stands of Lake Malawi during group, we conclude that one of the two unornamented the past 200 000 years. Two of the most severe, morphotypes of the Pliocene assemblage gave rise to 135 000 and 75 000 years ago, involved drops of the modern Bellamya fauna, whereas the other mor- at least 600 and 350 m, respectively (Cohen et al., photype evolved via parallel evolution in time. 2007; Scholz et al., 2007). The estimates of the time In a rift-wide phylogenetic context, it is noteworthy since expansion for all models tested in the present that all colonizations of major water bodies along and study lies within this timeframe (Table 3). In particu within the rift by Bellamya spp. appear to have taken lar, the estimates for the spatial expansion of the place within a relatively short time frame, as indi entire Malawi group falls in between the abovemen

© 2010 The Linnean Society of London, Biological Journal of the Linnean Society, 2011, 102, 130-143 EVOLUTION OF BELLAMYA SPP. IN LAKE M ALAW I 141 tioned severe lake level drops. Whereas this age is 2. The endemic Bellamya species of Lake Malawi are similar to the onset of a sudden demographic expan not restricted to the lake proper. This pattern has sion in B. robertsoni, the demographic expansion in B. also been reported for other endemic Malawian capillata started probably considerably earlier. More taxa: Endemic cichlid fishes as well as ostracods over, the former species appears to be restricted to the inhabit satellite water bodies (Martens, 2003; southern part of the lake, whereas the latter one was Genner et al., 2007a) and endemic Lanistes species sampled in the northern part of the lake, in the Shire have even been found throughout the Malawi rift River in the South, as well as in surrounding water (SchultheiB et al., 2009). Moreover, it is notewor bodies (e.g. Lake Chilingali and Lake Kazuni; R. thy that we have not found endemic and non SchultheiB, pers. observ.). endemic species in sympatry; neither in the case of Although we cannot provide meaningful time esti Lanistes, nor of Bellamya. mates for B. ecclesi and B. jeffreysi as a result of their 3. The evidence of parallel evolution of the B. capil- scarce occurrence, these species also appear to be lata morphotype calls former taxonomic and bio spatially restricted: B. ecclesi is mainly found in the geographic hypotheses of the genus into question. South and B. jeffreysi was only collected from the A similar case has been found for Malawian middle part of the lake (R. SchultheiB, pers. observ.; Lanistes and has also been discussed with respect for locality details, see Fig. 2 and Table 1). We are to the lake’s ostracod fauna (Martens, 2003). well aware that these observations are of anecdotic Hence, the degree of biodiversity in other inverte character. However, in light of the results presented brate taxa in the lake may also be underestimated here, the geographical distribution of the group points as a result of the existence of cryptic species toward a speciation mechanism that might have ini complexes. tiated the formation of this endemic species flock in the first place: isolation by distance after reflooding of SUMMARY AND CONCLUSIONS the lake. It is noteworthy, that the nominal species of the The present study demonstrates that all but one Malawi group do not fall into distinct clusters in the lineage of the Pliocene Bellamya fauna in Lake inferred network (Fig. 2). Although the AMOVA and Malawi became extinct. Furthermore, it suggests that the results from the exact test indicate substantial the onset of the modern radiation occurred relatively genetic differentiation between species (Table 2), the recently from a single surviving lineage (Fig. 1) and shared haplotypes in the network, as well as fre reveals a considerable increase in effective population quently occurring individuals with intermediate shell size, as well as a significant recent spatial expansion morphology (R. SchultheiB, pers. observ.), indicate (Table 3, Fig. 3). These findings corroborate the that the speciation process in the group might yet be hypothesis that the speciation processes leading to incomplete. the endemic modern Bellamya taxa were shaped by dramatic environmental events, such as lake level changes. Additionally, we conclude that the Bellamya lineage resided in isolation in the basin as well as in COMPARISON WITH OTHER MALAWIAN TAXA the lake’s drainage system and gave rise to at least The patterns found for the Bellamya group corrobo two different radiations over time (i.e. in the Pliocene rate the observations for other endemic Malawian and in the Pleistocene). Thus, the present study rein taxa and point towards general evolutionary patterns forces the importance of lake level changes for our in the lake: understanding of evolutionary processes governing 1. The accumulation of extant molecular diversity of the history of Lake Malawi’s endemic fauna. the Malawian Bellamya started considerably later than when the lake had reached deep water con ACKNOWLEDGEMENTS ditions 4.5 Mya, and falls within a similar time frame to that of the endemic Lanistes species We thank Frank Riedel, Thomas von Rintelen, and (SchultheiB et al., 2009) and the cichlid fishes in Ellinor Michel for providing materials, and Matthias the lake (Sturmbauer et al., 2001). Both studies Glaubrecht for access to the mollusc collection of the suggest an onset of diversification not later than Berlin Museum of Natural History. Friedemann approximately 500 000 years ago and both relate Schrenk, Thies Geertz, Harrison Simfukwe, Immacu this onset to Malawi’s Pleistocene lake level late Ssemmanda, Patrick Msoyhaya, and Dany changes. Note, however, that the Malawian taxa of Simbeye are gratefully acknowledged for their help in the gastropod genus Melanoides show a different the field, and Silvia Nachtigall is thanked for assis pattern and appear to have colonized the lake at tance in the laboratory. We thank Bert Van Bocxlaer least twice independently (Genner et al., 2007b). and Thies Geertz for fruitful discussions and two

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