A Link Between Host Dispersal and Parasite Diversity in Two Sympatric Cichlids of Lake Tanganyika

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Freshwater Biology (2015) 60, 323–335 doi:10.1111/fwb.12492

A link between host dispersal and parasite diversity in two sympatric cichlids of Lake Tanganyika

, † € , ‡ , § , ¶ ARNOUT F. GREGOIR* , PASCAL I. HABLUTZEL*,MAARTENP.M.VANHOVE* , ‡ ANTOINE PARISELLE**, JOLIEN BAMPS , FILIP A. M. VOLCKAERT* AND †† JOOSTA.M.RAEYMAEKERS*, *Laboratory of Biodiversity and Evolutionary Genomics, University of Leuven, Leuven, Belgium † Laboratory of Aquatic Ecology, Evolution and Conservation, University of Leuven, Leuven, Belgium ‡ Biology Department, Royal Museum for Central Africa, Tervuren, Belgium §Department of Botany and Zoology, Faculty of Science, Masaryk University, Brno, Czech Republic ¶Institute of Marine Biological Resources and Inland Waters, Hellenic Centre for Marine Research, Anavyssos, Greece **Institut des Sciences de l’Evolution, IRD, CNRS, B.P. 1857, Universite Montpellier 2, Yaounde, Cameroon †† Zoological Institute, University of Basel, Basel, Switzerland

SUMMARY

1. A major goal in ecology is to unravel how species assemblages emerge and how they are struc- tured across the landscape. Host–parasite systems are particularly interesting in this context, as limited host dispersal may promote the differentiation of parasite communities. 2. We examined whether the patterns of species diversity in Cichlidogyrus, a genus of monogenean parasitic flatworms with a direct life cycle, are consistent with the hypothesis that parasite diversity is driven by host dispersal. This was carried out by comparing two sympatric cichlid hosts (Tropheus moorii and Simochromis diagramma) with contrasting dispersal abilities. Genetic connectivity among host populations along the Zambian shoreline of Lake Tanganyika was estimated using microsatellite genotyping. Cichlidogyrus parasites were isolated and identified morphologically to the species level. 3. Simochromis diagramma, a host with a high dispersal capacity, was infected by a low number of Cichlidogyrus species, and the parasite assemblages were similar among host populations. In contrast, T. moorii, a host with a low dispersal capacity, was infected by a large number of Cichlidogyrus species, and the parasite assemblages differed strongly among host populations. These outcomes were thus as expected from the hypothesis. 4. Because of the strong host specificity of these Cichlidogyrus species, a lack of connectivity among host populations might facilitate allopatric speciation of the parasite.

Keywords: Cichlidogyrus, ectoparasite, host–parasite interactions, Simochromis diagramma, Tropheus moorii

(Kawecki & Ebert, 2004), leading to behavioural (Moore, Introduction 2002; Eizaguirre et al., 2011; Karvonen & Seehausen, Explaining drivers of species diversity is a major topic 2012) or immunogenetic changes (Eizaguirre & Lenz, in ecological and evolutionary research. Diversity is dri- 2010) and might even lead to reproductive isolation ven by extrinsic environmental factors as well as intrin- between host populations (Eizaguirre et al., 2009, 2012). sic factors such as life-history traits (Wagner et al., 2013). In turn, hosts might also enhance the diversiﬁcation of The intimate relationship between hosts and parasites their parasites (Huyse, Poulin & Theron, 2005). Factors results in strong ecological and evolutionary interactions such as the density and distribution of hosts and the (Poulin & Morand, 2000; Decaestecker et al., 2013). Selec- connectivity between host populations might signiﬁ- tion by parasites can induce local adaptation of the host cantly affect the population genetic structure or the

Correspondence: Arnout F. Gregoir, Laboratory of Aquatic Ecology, Evolution and Conservation, University of Leuven, Ch. Deberiotstraat 32, B-3000 Leuven, Belgium. E-mail: [email protected]

© 2014 John Wiley & Sons Ltd 323 324 A. F. Gregoir et al. species composition of parasite assemblages (Gregory, cific, often only infecting a single host species (Pariselle 1990; Nadler, 1995; Jarne & Theron, 2001; Brouat & Du- & Euzet, 2009). To date, 95 species have been described plantier, 2007; Blasco-Costa, Waters & Poulin, 2012). The (Pariselle & Euzet, 2009; Vanhove, Volckaert & Pariselle, contribution of host-related factors might become partic- 2011b; Gillardin et al., 2012; Muterezi Bukinga et al., ularly strong in highly host-specific parasites with a 2012; Pariselle, Bitja Nyom & Bilong Bilong, 2013, 2014; direct life cycle, which cannot disperse through a sec- Rehulkova, Mendlova& Simkova, 2013; Pariselle et al., ond, potentially more dispersive, host species (Pariselle 2014, in press). Cichlidogyrus species occur at high preva- et al., 2003; Nieberding et al., 2004; Blasco-Costa et al., lence and exhibit high infection intensities (Paperna, 2012). Population structure and species assemblages in 1996). Outcrossing is obligatory in the hermaphrodite such taxa might be constrained by the degree of diver- adults (Paperna, 1996). The eggs are shed into the water gence between host populations (Dres & Mallet, 2002; column (Paperna, 1996) and sink to the bottom, where Criscione, Poulin & Blouin, 2005; Huyse et al., 2005; they hatch after a few days (Bychowsky, 1957). Newly Khan, 2012). Since parasites generally have shorter life hatched larvae have to find a suitable host within 4–6h, cycles and tend to evolve faster than their hosts, their on which they mature and complete their life cycle evolutionary history might bear the signature of the (Pariselle et al., 2003). degree of host isolation (Moran, Von Dohlen & Given the limited dispersal capacity of the parasites Baumann, 1995; Page et al., 1998; Nieberding et al., themselves and their direct life cycle (i.e. no intermedi- 2004). In the long run, increased isolation might even ate host is involved), the biogeography of Cichlidogyrus lead to speciation due to drift and the accumulation of species should be directly linked to host dispersal (Pari- genetic incompatibilities between populations. selle et al., 2003, 2011; Vignon, Pariselle & Vanhove, Despite high phenotypic differentiation (Meyer, 1993; 2011). As previously found at the within-species level Muschick, Indermaur & Salzburger, 2012), most cichlid for bird ticks, host dispersal might have a large impact fish species of the East African Great Lakes are closely on the population genetic structure of their parasites related and radiated rapidly (Salzburger et al., 2002). (McCoy et al., 2003; Kempf et al., 2009). In view of the Their marked ecological specialisation provides a power- contrasting biology of the host species, we anticipated ful framework for investigating fundamental evolution- finding more differentiation among parasite assem- ary questions (Kornfield & Smith, 2000). In Lake blages of the philopatric T. moorii, than of the eurytopic Tanganyika, two closely related sympatric cichlids with S. diagramma. contrasting dispersal capacities, Tropheus moorii and Sim- We examined the effect of host dispersal by compar- ochromis diagramma, are found in the patchily distributed ing the Cichlidogyrus species richness and assemblage rocky littoral, which is separated by stretches of sand. composition in sympatric T. moorii and S. diagramma These so-called aufwuchs feeders scrape algae from rock populations from southern Lake Tanganyika. To do so, surfaces. Their phylogenetic relatedness (c. 2.5 MY; Ko- we first assessed the degree of population genetic struc- blmuller€ et al., 2010) and their similar feeding behaviour ture in both host species across six sampling locations. (Yamaoka, 1983, 1997) make them ideal for studying the At each of these locations, we then quantified the Cich- effect of host mobility on parasite diversification with lidogyrus species composition in both host species. Two few confounding factors. Tropheus moorii exhibits highly locations where only the dispersal-limited host occurred philopatric behaviour and is unable to cross unsuitable were also investigated. patches of sand, resulting in limited dispersal, as evidenced by the high degree of genetic structure among populations (Baric, Salzburger & Sturmbauer, 2003; Sefc Methods et al., 2007; Koblmuller€ et al., 2011; Raeymaekers et al., Fish sampling and dissection 2013). Simochromis diagramma, in contrast, is more eurytopic (Yamaoka, 1983). It is frequently observed on sedi- The data for this study were collected in parallel with ment-rich stretches of shoreline and disperses freely, as the study by Raeymaekers et al. (2013), who described evidenced by its weak population structure (Meyer, the variation in ecto- and endoparasite assemblages Knowles & Verheyen, 1996; Wagner & McCune, 2009). among allopatric colour morphs of T. moorii. Populations Both species are heavily infected by monogenean par- of this species were sampled using gill nets in August– asitic flatworms of the genus Cichlidogyrus (Vanhove September 2011 at eight sites along the Zambian shore et al., 2011a; Raeymaekers et al., 2013; Hablutzel€ et al., of Lake Tanganyika (Table 1). At six of these sites, 2014). Species of this gill parasite are highly host spe- S. diagramma was sampled as well. No S. diagramma

Table 1 Sampling localities along the Zambian shoreline of Lake Tanganyika, with indicated sam- Simochromis ple sizes (number of host or parasite specimens) Tropheus moorii diagramma per population; n = number of genotyped fish; 1 Site Coordinates n n n n n n n n = 1 2 3 4 1 2 3 4 n2 number of fish of whose total number of = 0 0 Cichlidogyrus was counted, n3 number of fish Chilanga 08°33 22.4″S, 30°37 09.7″E 24 40 5 145 –––– hosts whose Cichlidogyrus were identified to the Linangu 08°32003.5″S, 30°38025.2″E24401361–––– = 0 0 species level, n4 number of Cichlidogyrus individ- Tumbi 08°42 10.7″S, 30°55 20.9″E24411266322919144 uals identified to species level Katoto 08°47051.6″S, 31°01011.8″E 24 40 10 103 32 35 18 116 Mbita Island 08°44057.1″S, 31°05014.2″E24421184323414109 Wonzye 08°43007.6″S, 31°08012.6″E2440116832218 35 Muzumwa 08°42005.7″S, 31°11059.8″E 24 45 11 176 32 32 13 65 Toby’s Place 08°37018.9″S, 31°11059.9″E2440145032341036

were found at the two westernmost sites (Chilanga DNA extraction and genotyping of host species Rocks and Linangu). Per site, 50 T. moorii and 35 S. diagramma were caught and transported in well-oxygenated To measure the dispersal of the two host species along water to our field base. There, they were kept alive in the Zambian shoreline of Lake Tanganyika, a population tanks of 0.77 or 1.28 m3 prior to dissection. genetic approach was carried out. Genomic DNA was Individuals of T. moorii and S. diagramma were dis- isolated from 10 to 20 mg fin tissue with the Nucleo- â sected in alternating order if possible. First, they were spin Tissue kit (Macherey & Nagel, Duren,€ Germany) anaesthetised using an overdose of MS222. Immediately following the manufacturer’s recommendations. Ten after death, gills and a finclip were removed and fixed neutral microsatellite loci were selected and distributed in 100% analytical ethanol (EtOH). Fish were sexed by in three multiplex reactions (UME003: Lee & Kocher, visual inspection of the genital papilla and the gonads. 1996; UNH130: Parker & Kornfield, 1996; TmoM11: Zar- To check for changes in the Cichlidogyrus assemblage doya et al., 1996; Pzeb3: Van Oppen et al., 1997; Ppun5, while fish were kept alive in the tanks, the day of dissec- Ppun7, Ppun21: Taylor et al., 2002; HchiST06, HchiST38, tion (i.e. 0, 1 or 2 of days after capture) was recorded. In HchiST68, HchiST94: Maeda et al., 2008). For these mul- â the laboratory, stored gills were screened for Cichlidogy- tiplex PCRs, the QIAGEN PCR kit was used, following rus flatworms, using an Olympus SZX-12 stereoscope. the manufacturer’s recommendations, with the exception Per sampling site and host species, at least 30 specimens of the annealing temperature (54–56 °C, depending on were screened to assess prevalence, mean abundances the loci). For all loci, the annealing temperature as and median infection intensity following the terminol- described in their original papers was applied. Genotyp- ogy of Rosza, Reiczigel & Majoros (2000). Subsequently, ing was performed using an ABI 3130 Sequencer â 5–19 host individuals were randomly selected (Table 1), (Applied Biosystems , Foster City, California, USA). and all Cichlidogyrus were isolated from the gills using Allele sizes were estimated using GENEMAPPER v4.0 â dissection needles. Isolated parasites were mounted on (Applied Biosystems ) and verified visually. slides in an ammonium picrate–glycerine solution (Malmberg, 1957). Data analysis

Cichlidogyrus assemblage analysis. Overall Cichlidogyrus Cichlidogyrus identification infection parameters were assessed for both host species Although none of the Cichlidogyrus species found has separately. Infection presence was analysed with a gen- been formally described, species could be clearly sepa- eralised linear mixed model assuming a binomial error rated based on shape and size of the hard parts of the distribution using proc GLIMMIX in SAS (version 9.1; attachment organ (haptor) and, above all, on those of SAS Institute, Cary, NC, U.S.A.). Site, sex and day of the male copulatory apparatus (e.g. Gillardin et al., dissection were included in the model as fixed factors 2012). Both structures are sclerotised and were clearly and observer as a random block factor. The standard distinguishable using an Olympus SX-50 microscope length of the fish was added to the model as a covariate. (Olympus, Hamburg, Germany) under 10009 magnifica- Abundance and infection intensity were square-root- tion using phase contrast. Per host population, 35–176 transformed to improve normality and compared Cichlidogyrus individuals were identified (Table 1). between sites using a general linear mixed model using

© 2014 John Wiley & Sons Ltd, Freshwater Biology, 60, 323–335 326 A. F. Gregoir et al. proc MIXED in SAS. The same factors as above were prior for all K’s. The results of the structure analysis included in the model. were visualised in DISTRUCT (Rosenberg, 2004). Dissimilarities in Cichlidogyrus assemblage composition between host individuals were assessed by calculat- Host dispersal versus structure of Cichlidogyrus ing Bray–Curtis distances based on proportional species assemblages occurrences, using the R library vegan (Oksanen et al., 2007). To estimate Bray–Curtis distances between sam- Mantel tests, using the Kendall method and 104 permu- pling sites, mean interindividual proportional abun- tations, were performed to investigate the correlation dances were calculated for each site. A permutational between host dispersal (quantified as pairwise Gst or multivariate analysis of variance on Bray–Curtis dis- Jost’s Dest (Jost, 2008) and the Cichlidogyrus assemblage tances with factors host sampling location, host sex, day differentiation (quantified as pairwise Bray–Curtis dis- of dissection and size as a covariate was performed tances). The analysis was performed with the vegan using the Adonis function in VEGAN (Anderson, 2001). library in R v2.15. The analysis was conducted separately for S. diagramma and T. moorii. For T. moorii, the MANOVA was repeated after the exclusion of the two sites where no S. diagram- Results ma were collected. Statistical significance was obtained Composition of Cichlidogyrus assemblages through 104 permutations of the data. All statistical analyses were conducted in R v2.15 (R Core Develop- Cichlidogyrus species. Based on the unique morphology ment Team, 2012). of the male copulatory apparatus, 10 distinct Cichlidogy- rus species could be identified (Fig. 1). Three morpho- Population genetic analysis. The expected and observed species of Cichlidogyrus, provisionally called ‘Sp. 1’, ‘Sp. heterozygosity was calculated for all loci and for all 2’ and ‘Sp. 3’, were specific to S. diagramma and were sampling sites using Arlequin v3.5 (Excoffier, Laval & found at all six sites (Fig. 2). On T. moorii, we distin- Schneider, 2005). Allelic richness was calculated in FStat guished seven different morphospecies of Cichlidogyrus. (Goudet, 1995), using a rarefaction method to correct for They are provisionally referred to as ‘Sp. A’, ‘Sp. B’, ‘Sp. different sampling sizes (Hurlbert, 1971). Tests for link- C’, ‘Sp. D’, ‘Sp. E’, ‘Sp. F’ and ‘Sp. G’. The geographical age disequilibrium among all pairs of loci were per- distribution of these species was patchier than for the formed using the Markov chain algorithm implemented Cichlidogyrus species encountered on S. diagramma in Genepop v4.0 (Rousset, 2008), with 104 dememorisa- (Fig. 2). Infection levels (prevalence, mean abundance tions, 500 batches and 5000 iterations per batch. To test and median infection intensity) for the various Cichlido- for significant deviations from Hardy–Weinberg equilib- gyrus species together were often higher and more rium, the exact test in Genepop v4.0 was used, with 106 variable in T. moorii than in S. diagramma (Table 2). Dif- steps in the Markov chain and 104 dememorisations per ferences in abundance and infection intensity were population. For both species, a global test across popula- highly significant among T. moorii populations, but mod- tions was also performed, using the same settings. erately significant (infection intensity) to non-significant To assess population differentiation, overall and pair- (abundance) in S. diagramma (Table 3). wise Gst values (the standardised variance in allele frequencies among populations) were calculated in the Structure of Cichlidogyrus assemblages. When correcting hierfstat package in R v2.15. As Gst tends to decrease for host size, sex and dissection day, variation in Cichlid- with allelic richness (Hedrick, 2005; Jost, 2008; Raeymae- ogyrus species assemblages between sites was highly sig- kers et al., 2012), Dest (genetic differentiation among pop- nificant in T. moorii. Host size also turned out to be a ulations) was also calculated, using the diveRsity significant factor (Table 4). In S. diagramma, there was no package in R. Population structure was assessed in significant site (location) (Table 4). Only dissection day STRUCTURE v2.3 (Pritchard et al., 2000). The program was significant (P = 0.0356). was run from K = 1toK = 6 for S. diagramma and from None of the five neighbouring populations of S. dia- K = 1toK = 8 for T. moorii. For every K, five iterations gramma were infected by significantly different Cichlido- with 106 steps after a burnin of 105 steps were done. As gyrus communities (Fig. 3). In contrast, significantly we were dealing with closely related populations, the different Cichlidogyrus communities were observed for analysis was run with correlated allele frequencies. Opti- four of seven neighbouring population pairs of T. moorii. mal K was chosen using Bayes’ rule, setting a uniform The lowest differentiation between parasite assemblages

Fig. 1 Schematic sketch of the male copulatory apparatus of the 10 identiﬁed Cichlidogyrus morphospecies. The heel is in black, the accessory piece in grey and the penis itself in white. Sp. ‘A’–Sp. ‘G’ were found on Tropheus moorii and Sp. ‘1’–Sp. ‘3’ on Simochromis diagramma.

Fig. 2 Graphical representation of the proportional abundances of each Cichlido- gyrus species in the eight populations, with an increasing circle diameter repre- senting a higher proportional abundance. Absences of circles indicate the absences of observations.

Table 2 Genetic characteristics of populations of two cichlid species, Tropheus moorii and Simochromis diagramma, and their overall Cichlido- gyrus infection parameters

T. moorii S. diagramma

Site Hexp Hnb Hobs AR Pr MA MI Hexp Hnb Hobs AR Pr MA MI

Chilanga 0.769 0.785 0.800 11.90 97.5 20.4 17 ––– –––– Linangu 0.797 0.814 0.800 13.10 81.4 3.4 4 ––– –––– Tumbi 0.809 0.827 0.821 14.00 88.4 6.8 5.5 0.764 0.777 0.748 14.78 89.7 6.6 3.5 Katoto 0.793 0.810 0.833 12.40 100 15.1 11 0.746 0.758 0.736 14.64 77.1 5.2 4 Mbita Island 0.789 0.806 0.800 13.50 79.1 5.4 6 0.763 0.775 0.759 14.39 77.1 7.1 6 Wonzye 0.771 0.788 0.779 13.70 95.6 6.8 6 0.775 0.788 0.781 14.77 77.3 3.3 4 Muzumwa 0.714 0.729 0.733 9.70 95.6 14.5 10 0.757 0.770 0.729 14.05 68.6 4.0 3.5 Toby’s Place 0.771 0.787 0.775 12.80 76.20 3.0 3 0.764 0.776 0.740 14.59 50.00 1.7 3

Hexp, expected heterozygosity; Hnb, non-biased heterozygosity; Hobs, observed heterozygosity; AR, allelic richness; Pr, Cichlidogyrus prevalence; MA, mean Cichlidogyrus abundance; MI, median Cichlidogyrus infection intensity.

Table 3 Fixed effects of general and generalised Infection linear models for Cichlidogyrus infection levels in Prevalence Abundance intensity six Simochromis diagramma and eight Tropheus moorii populations. Fixed effects included sampling Host Factor DF Den DF FP FP FP site, processing day, sex and standard length (SL). S. Site 5 163/114 0.75 0.5889 2 0.0816 2.47 0.0363 Observer effects were included as random (not diagramma Day 2 163/114 2.22 0.1114 1.05 0.3526 0.67 0.5121 shown). The model for prevalence assumes a bino- Sex 1 163/114 0.16 0.9606 0.32 0.5711 1.9 0.1704 mial distribution and models the logit of the prob- SL 1 163/114 14.73 0.0002 42.07 <0.0001 26.53 <0.0001 ability of infection. For the models for abundance Tropheus Site 7 309/279 1.5 0.165 16.17 <0.0001 14.78 <0.0001 and infection intensity, the dependent variable moorii Day 2 309/279 2.75 0.065 6.03 0.0027 2.76 0.0653 was square-root-transformed Sex 1 309/279 1.1 0.295 7.51 0.0065 5.11 0.0246 SL 1 309/279 4.28 0.0394 55.9 <0.0001 54.38 <0.0001

Note that the denominator degrees of freedom (Den DF) are higher for the prevalence and abundance model (before the dash) than for the infection intensity model (after the dash). P-values in bold indicate signiﬁcance at a = 0.05.

Table 4 Permutational multivariate analysis of Num Den 2 variance on Bray–Curtis distances (based on pro- Host Effect DF DF SS MS FRP portional species abundances) between Cichlidogy- S. diagramma Site 5 72 0.99 0.19 1.66 0.09 0.1007 rus communities in individuals from six Day 2 72 0.66 0.33 2.75 0.06 0.0356 Simochromis diagramma populations and six or Sex 1 72 0.11 0.12 0.96 0.01 0.3866 eight Tropheus moorii populations. The model SL 1 72 0.30 0.3 2.53 0.03 0.0942 included sampling site, processing day, sex and T. moorii (six sites) Site 5 68 3.17 0.63 2.99 0.18 <0.0001 standard length (SL) Day 2 68 0.56 0.28 1.33 0.03 0.2258 Sex 1 68 0.25 0.25 1.15 0.01 0.3344 SL 1 68 1.44 1.44 6.80 0.08 <0.0001 T. moorii (eight sites) Site 7 75 6.44 0.92 4.38 0.26 <0.0001 Day 2 75 0.54 0.27 1.29 0.02 0.2353 Sex 1 75 0.16 0.16 0.76 0.01 0.5765 SL 1 75 1.76 1.76 8.38 0.07 <0.0001

P-values in bold are significant. of T. moorii populations (0.167) was found between the T. moorii populations, whereas a significant heterozygote populations at Mbita Island and Wonzye, the only sam- deficiency (P < 0.01) was detected for the S. diagramma pling sites that are not separated by a sand bar (Fig. 3). populations at Tumbi and Muzumwa.

All pairwise Gst’s were highly signiﬁcant for T. moorii (28 comparisons), whereas only four of 15 compari- Host dispersal sons for S. diagramma yielded a signiﬁcant Gst

All microsatellite loci were polymorphic in both species, (Table 5). Gst values were usually more than 10-fold with a minimum of four and a maximum of 38 alleles. larger in T. moorii than in S. diagramma. Populations Allelic richness was higher in S. diagramma than in from neighbouring sites were always significantly dif- T. moorii (14.05–14.78 versus 9.7–14.0). Genetic differenti- ferentiated in T. moorii, while they were never signifi- ation among T. moorii populations was stronger than cant in S. diagramma (Table 5; Fig. 4). The same = among S. diagramma populations [T. moorii: Dest 0.204 patterns were evident for Dest. Pairwise values of Dest – = = – = (0.179 0.228), P 0.001; Gst 0.038 (0.035 0.042), P between neighbouring populations were always at least = – = 0.001; S. diagramma: Dest 0.004 (0.001 0.006), P 0.021; 10-fold higher in T. moorii, with the exception of the = – = – Gst 0.036 (0.016 0.058), P 0.003]. After correction for Mbita Island Wonzyez pair. This value was nearly the multiple testing (T. moorii: 360 tests, S. diagramma: 270 same in both the species and was markedly lower than tests), we found no evidence for linkage disequilibrium other pairwise Dest values in T. moorii (0.006 versus across all loci pairs and all populations of both species >0.01). (data not shown). There were no significant deviations Bayesian clustering analyses on S. diagramma showed from Hardy–Weinberg equilibrium in any of the an optimal likelihood value for K = 1, indicating that

Fig. 3 Genetic structure of Tropheus moorii and Simochromis diagramma populations along the Zambian shoreline. Note the absence of different clusters in S. diagramma. The Bray–Curtis distances between neighbouring populations based on the Cichlidogyrus communities are provided with an indicated signiﬁcance level (*P < 0.05; **P < 0.01; ***P < 0.001).

genetic differentiation between sites was too low to entiation (Gst, Dest) and geographical distance between detect subgroups (Fig. 3). In T. moorii, the analysis on sampling locations were weak and non-significant the full data set (with two extra populations compared (Table 6). In T. moorii, the correlation between differenti- to the S. diagramma data set) had the highest likelihood ation among Cichlidogyrus species assemblages and = for K 4, with a clear split between the four western genetic differentiation was significantly positive for Dest. and the four eastern subpopulations. The subpopula- For Gst, the correlation was weaker and non-significant tions of Chilanga and Linangu clustered together; these (Table 6). There was no significant correlation between from Tumbi and Katoto formed another cluster, as did differentiation among Cichlidogyrus species assemblages those from Mbita Island and Wonzye. The subpopula- and geographical distance (Table 6). tions of Muzumwa and Toby’s Place formed the fourth cluster. Discussion

We found no signiﬁcant differentiation of the Cichlidogy- Host dispersal versus differentiation of Cichlidogyrus rus assemblage among S. diagramma populations, as assemblages Cichlidogyrus species occurred at similar proportions In S. diagramma, correlations between differentiation across sampling sites. In contrast, the Cichlidogyrus on among Cichlidogyrus species assemblages, genetic differ- T. moorii were signiﬁcantly different among sampling

Table 5 Genetic differentiation between Tropheus moorii (upper right corner) and Simochromis diagramma (lower left corner) populations

Chilanga Linangu Tumbi Katoto Mbita Wonzye Muzumwa Isanga

Chilanga 0.1188 0.0321 0.0441 0.1607 0.1113 0.0730 0.1343 0.0382 0.0264 0.0398 0.031 0.0477 0.0722 0.044 Linangu n/a 0.0598 0.1518 0.1054 0.0881 0.1481 0.0730 n/a 0.0196 0.042 0.0409 0.0624 0.0760 0.0409 Tumbi n/a n/a 0.0805 0.1110 0.1058 0.1740 0.1113 n/a n/a 0.0145 0.0248 0.0443 0.0755 0.0366 Katoto n/a n/a 0.0073 0.1394 0.1573 0.2528 0.1607 n/a n/a 0.0081 0.0266 0.0425 0.0818 0.0444 Mbita n/a n/a 0.0023 0.0001 0.0061 0.0812 0.0441 n/a n/a 0.0019 0.0016 0.0111 0.0420 0.0168 Wonzye n/a n/a <0.0001 0.0001 0.0056 0.0645 0.0321 n/a n/a 0.0011 0.0010 0.0002 0.0369 0.0111 Muzumwa n/a n/a 0.0048 0.0086 0.0411 0.0069 0.1187 n/a n/a 0.0006 0.0063 0.0088 <0.0001 0.0367 Isanga n/a n/a 0.0061 0.0133 0.0045 0.0187 0.0031 n/a n/a <0.0001 0.0067 0.0067 0.0019 <0.0001

Both Dest (upper value) and Gst (lower value) are provided. Gst values in bold are signiﬁcant after applying Holm’s correction for multiple testing. No P-values could be calculated for the Dest values. Values along the diagonal are from neighbouring populations.

Fig. 4 Genetic differentiation (assessed

as Gst and Dest, see Methods for details) between neighbouring sampling sites in two cichlid species. Whiskers delineate 95% CI as obtained by bootstrapping. sites. Genetic differentiation was weak among S. dia- Our results on the population genetic structure of both gramma populations and strong among T. moorii popula- host species conﬁrm earlier studies (Meyer et al., 1996; tions. Hence, Cichlidogyrus sp. assemblage differentiation Sefc et al., 2007; Wagner & McCune, 2009; Koblmuller€ mirrored the population genetic structure of the respec- et al., 2011; Nevado et al., 2013). Connectivity among tive host species. In addition, we found that T. moorii sub-populations of S. diagramma is high, consistent with and S. diagramma hosted seven and three morphologi- the lakewide distribution and the apparent lack of phe- cally distinct Cichlidogyrus species, respectively, but had notypic differentiation across the lake (Meyer et al., 1996; no species in common. Wagner & McCune, 2009). Therefore, we conclude that

Table 6 Mantel correlations between Cichlidogyrus community dif- their cichlid host), and host switches are not frequently ferentiation (in Bray–Curtis distances), genetic differentiation (as observed in Lake Tanganyika (Vanhove, 2012). Hence, it G and D ) and geographical distance (in km) between six allo- st est appears plausible that the distribution of Cichlidogyrus patric populations of the rock-dwelling cichlids Tropheus moorii and Simochromis diagramma species mainly depends on characteristics of their host. Complementary evidence for this pattern could be T. moorii S. diagramma obtained by investigating levels of gene flow between Comparison rPr P parasite populations, which should be lower in parasite – species living on host species with a low dispersal Gst Cichlidogyrus assemblage 0.3445 0.0758 0.039 0.4259 – Dest Cichlidogyrus assemblage 0.6762 0.0031 0.1148 0.7826 capacity than in parasite species living on host species Geographical distance – 0.1048 0.3082 0.0857 0.6671 with a high dispersal capacity. Cichlidogyrus assemblage The absence of shared Cichlidogyrus species and the Significant P-values are in bold. difference in species richness between both hosts suggest that speciation patterns and species diversity in Cichlido- gyrus are highly influenced by the unique histories of S. diagramma is a good disperser, even when major the host species, rather than by the presence of other, stretches of unsuitable habitat (sand, mud) separate sympatrically occurring, host species. Gillardin et al. rocky outcrops, their preferred feeding grounds (2012) examined the Cichlidogyrus species of three addi- (Table 2). In contrast, genetic differentiation between tional species of tropheine cichlids, namely Ctenochromis populations was high for T. moorii, consistent with horei, Limnotilapia dardennii and Gnathochromis pfefferi. results from previous studies (Ruber€ et al., 1998; Baric Similar to S. diagramma, these species are considered to et al., 2003; Sefc et al., 2007; Koblmuller€ et al., 2011; be fairly good dispersers (Meyer et al., 1996; Konings, Nevado et al., 2013). The weak dispersal in this species 1998; Koblmuller€ et al., 2010). Even though they exam- has been attributed to habitat fidelity caused by territo- ined individuals from distant localities throughout the rial behaviour (Kawanabe, 1981; Ruber€ et al., 1998; Stur- lake, only a single Cichlidogyrus species on each host mbauer et al., 2008) and nutritional stenotypy (Yamaoka, species was found (Gillardin et al., 2012). A low Cichlido- 1983). gyrus species diversity hence seems typical for highly The strong concordance between host genetic struc- mobile host species. Moreover, as with the species found ture and parasite assemblage structure is consistent with on T. moorii and S. diagramma, none of these species the hypothesis that weak host dispersal enhances para- have ever been recorded on an additional host species, site community differentiation. Differences in parasite suggesting a high host specificity of these Cichlidogyrus assemblage composition have been attributed to a com- species. bination of differences in local environmental conditions, Considering this apparent host specificity, we argue parasite characteristics and host characteristics (Sasal, that Cichlidogyrus parasites might be used to help disen- Niquil & Bartoli, 1999a; Sasal et al., 1999b; Ter Hofstede, tangle the often poorly resolved phylogenetic relation- Fenton & Whitaker, 2004; Raeymaekers et al., 2008). ships among closely related cichlids (see Koblmuller€ Here, we argue that the last mechanism is the main et al., 2010; Joyce et al., 2011; Wagner et al., 2013). Given driver of assemblage differentiation in Cichlidogyrus their shorter generation time in comparison with their infecting T. moorii. Even though local environmental hosts (Paperna, 1996), they evolve faster and might even conditions have not been measured, the even distribu- form new biological species before there is any visible tion of Cichlidogyrus infecting S. diagramma populations diversification among host species. Paugy et al. (1990), encountered at the same localities suggests that environ- for example, took advantage of the rapid evolution of mental differences do not contribute substantially to the monogenean flatworms to distinguish morphologically observed pattern. Parasite taxa may differ tremendously similar host species on the basis of contrasting parasite in their life-history traits, such as the ability to infect assemblages. Whereas S. diagramma has a pan-Tanganyi- other, sympatric, hosts or the use of an intermediate kan distribution (Meyer, 1993; Konings, 1998; Van Steen- host to complete their life cycle. Both characteristics may berge et al., 2011), the genus Tropheus can be split into alter the dispersal capacity of the parasite and can disen- numerous colour morphs with partially poorly resolved tangle it from the vagility of their primary host (Crisci- relationships (Konings, 1998; Baric et al., 2003; Schupke, one & Blouin, 2004; Barret et al., 2008; Bouzid et al., 2003; Sturmbauer et al., 2005; Egger et al., 2007). Studies 2008). Cichlidogyrus, however, has a direct life cycle on the phylogenetic history of rapidly evolving (including a short-lived free-living larval stage outside Cichlidogyrus, paralleling those of their cichlid host

© 2014 John Wiley & Sons Ltd, Freshwater Biology, 60, 323–335 332 A. F. Gregoir et al. (e.g. Koblmuller€ et al., 2011), might turn parasites into a the drift paradox in Trematode species. Molecular Ecology, useful tool for unravelling the evolutionary past of the 21, 207–217. Lake Tanganyika radiation. Bouzid W., Stefka J., Hypsa V., Lek S., Scholz T., Legal L. While we only selected a single weak disperser and a et al. (2008) Geography and host specificity: two forces single strong disperser for this study, our results sup- behind the genetic structure of the freshwater fish parasite Ligula intestinalis (Cestoda: Diphyllobothriidae). Inter- port the notion that host mobility may be an important national Journal for Parasitology, 38, 1465–1479. determinant of the composition of Cichlidogyrus assem- Brouat C. & Duplantier J.-M. (2007) Host habitat patchiness blages. 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