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Parallel Patterns of Host-Specific Morphology and Genetic Admixture in Sister Lineages of a Commensal Barnacle.

Abstract. Symbiotic relationships are often species specific, allowing symbionts to adapt to their host environments. Host generalists, on the other hand, have to cope with diverse environments. One coping strategy is phenotypic plasticity, defined by the presence of host-specific phenotypes in the absence of genetic differentiation. Recent work indicates that such host-specific phenotypic plasticity is present in the West Pacific lineage of the commensal barnacle Chelonibia testudinaria (Linnaeus, 1758). We investigated genetic and morphological host-specific structure in the genetically distinct Atlantic sister lineage of C. testudinaria. We collected adult C. testudinaria from loggerhead sea turtles, horseshoe crabs, and blue crabs along the eastern U.S. coast between Delaware and Florida and in the Gulf of Mexico off Mississippi. We find that shell morphology, especially shell thickness, is host specific and comparable in similar host species between the Atlantic and West Pacific lineages. We did not detect significant genetic differentiation related to host species when analyzing data from 11 nuclear microsatellite loci and mitochondrial sequence data, which is comparable to findings for the Pacific lineage. The most parsimonious explanation for these parallel patterns between distinct lineages of C. testudinaria is that C. testudinaria maintained phenotypic plasticity since the lineages diverged 4-5 mya.

Introduction

Symbiotic relationships are prevalent in nature and are often concomitant with host specialization of the symbionts (Pry, 1996). Such specialization might allow the symbiont to perform better on the host habitat, but specialist species face a higher extinction risk (McKinney, 1997; Julliard et al., 2004; Safi and Kerth, 2004; Williams, 2005; Walker and Preston, 2006). Host generalists, on the other hand, are able to utilize multiple hosts, with each host species potentially representing a distinct habitat. Host specialists might initially have been generalists with regard to their hosts and become locally adapted to fewer host species over time. Local adaptation leads to reduced gene flow at the loci responsible for adaptive phenotypes (e.g., Egan et al., 2008) and could subsequently reduce overall gene flow between symbiont races (Rundle and Nosil, 2005). In this case, host generalization is not evolutionarily stable but is superseded by specialization. Aphids adapting to novel host plants are a well-studied example of this pathway (Dres and Mallet, 2002; Ferrari et al., 2006). Alternatively to becoming host specialists, commensals might be phenotypically plastic, responding to the distinct host environments by changing their phenotype without host-specific population differentiation (Amarillo-Suarez and Fox, 2006; Cheang et al., 2013). Such true host generalists might be rare (Krasnov, 2008), but identifying whether symbionts are host generalists or host specialists has historically been difficult. Recent advances in molecular techniques allow us to detect limitations to gene flow between populations associated with different host species, which would indicate genetic host specialization.

Many thoracican barnacles are symbionts on other animals and plants, as either commensals or parasites (Darwin, 1851, 1854). The distinction between commensal and parasite is often hard to make because it is unclear whether barnacles harm their hosts by attaching to them (Rees et al., 2014). Some symbiotic barnacle species appear to be very host specific. For example, species of the genus Coronilla attach only to the skin of cetaceans (Scarff, 1986; Carrillo et al., 2015), and many coral barnacles bore only into certain coral species (Mokady and Brickner, 2001; Tsang et al., 2009, 2014; Simon-Blecher et al., 2016), Other symbiotic barnacle species attach to a diverse array of marine animals and plants (Mokady et ai. 1999; Hayashi, 2013). In most cases, host specificity has been assessed by morphology alone, which is highly variable in barnacles (Dawin, 1851, 1854). Phenotypic plasticity is widespread in barnacles, leading to much of the difficulty in identifying and describing species (Darwin, 1851, 1854). For example, several species grow taller instead of wider in dense aggregations, a behavior known as hummocking (Bertness et al., 1998; Silina and Ovsyannikova, 2000; Lopez et al., 2001)', the intertidal barnacle Chthamalus anisopoma grows its operculum sideways to avoid predation (Lively, 1986a. b); and feeding appendages grow shorter under increasing wave exposure (Arsenault et al., 2001; Marchinko and Palmer. 2003; Hoch, 2011; Hoch and Reyes, 2015).

Until recently, the cosmopolitan epizoic barnacle species Chelonibia testudinaria (Linnaeus, 1758), Chelonibia manati (Gruvel, 1903), and Chelonibia patula (Ranzani, 1818) were considered host specialists, restricted to sea turtles, manatees, and crabs (including horseshoe crabs), respectively (Dawin, 1854; Hayashi, 2013). Recent molecular phylogenetic studies discovered a lack of genetic divergence between these species despite extensive morphological differentiation (Cheang et al., 2013; Zardus et al., 2014). Following the suggestions of Cheang et al. (2013)and Zardus. et al. (2014), we synonymize C. patula and C. manati with the most senior name, C. testudinaria, and use this name for individuals from all host species. These studies revealed, however, three geographically distinct lineages; an Atlantic lineage, a West Pacific lineage, and an East Pacific lineage. A genome scan of the West Pacific lineage with amplified fragment length polymorphism (AFLP) markers and mitochondrial sequence data found little evidence for locus-specific adaptation to host species, making phenotypic plasticity the likely cause for extensive morphological differentiation (Cheang et al., 2013). The question remains whether the same pattern holds for other lineages of C. testudinaria. In the present study, we assessed population genetic and morphological host-specific divergence in the Atlantic lineage and compared our results with the available morphological data for the West Pacific lineage.

Materials and Methods

Specimen collection

We collected 436 specimens of Chelonibia testudinaria along the eastern U.S. coast from Delaware to Florida as well as along the Gulf of Mexico coast of Mississippi (Fig. 1), either in collaboration with organizations working on the host species or under our own collection permits. We removed 215 barnacles from horseshoe crabs (Limulus polyphemus [Linnaeus, 1758]), 79 from blue crabs (Callinectes sapidus [Rathbun, 1896]), and 142 from loggerhead sea turtles (Caretta caretta [Linnaeus, 1758]) and preserved them in 95% ethanol. We assigned each of the sampling locations to one of four broad geographic regions; Delaware to Virginia (DE-VA); South Carolina to Georgia, including northern Florida (SC-GA); southern Florida (FL); and Mississippi (MS) (Fig. 1). This allowed us to treat sampling location as a categorical variable in the population genetic analyses.

Molecular techniques

We extracted genomic DNA from feeding appendages of barnacles with the Chelex method (Walsh et al., 1991) and amplified 11 microsatellite markers (Ctest07, Ctest09, Ctest10, Ctest11, Ctest12, Ctest16, Ctest18, Ctest31, Ctest32, Ctest36, and Ctest47) following the protocols of Ewers-Saucedo et al. (2016). For a subset of individuals, we also amplified partial mitochondrial cytochrome oxidase subunit I (COI) gene sequences following the protocol of Rawson et al. (2003). We combined the new COI sequence data with 10 GenBank sequences of Atlantic C. testudlnarla (Zardus et al., 2014). We trimmed, aligned, and error-checked sequences in Geneious software (ver. 8.1) (Kearse et al., 2012). We calculated nucleotide and haplotype diversity (Nei, 1987) with the function nuc.div and Tajima's D with the function tajima.test (Tajima, 1989) of the package pegas (Paradis, 2010) in the R environment (R Development Core Team, 2016).

Genetic host specificity

Even though the three host species--loggerhead sea turtles, horseshoe crabs, and blue crabs--are relatively abundant and accessible, we were unable to collect barnacles from all host species in all four geographic regions (Fig. 1). The lack of full-factorial sampling of regions and hosts makes it difficult to disentangle the effects of each. We employed two different strategies to deal with this difficulty: (1) we used both geographic region and host species as explanatory variables on the complete data set and (2) we subset the data, using only the SC-GA region, where we were able to collect C. testudinaria from all host species. The latter approach eliminates the potentially confounding effect of geography. We carried out all analyses on the mitochondrial and nuclear microsatellite data sets separately. We tested the extent of host-specific population differentiation with an analysis of molecular variance (AMOVA) (Excoffier et al., 1992) based on the genetic distances between individuals. We assessed significance by randomizing the genotypes to host species in 1000 Monte Carlo permutations. In the complete data set, both geographic regions and host species were explanatory variables. This multivariate AMOVA approach is implemented by the function adonis of the R package vegan (Oksanen et al., 2015). The dependent variable is a genetic distance matrix, and the explanatory variables were geographic region and host species. Because explanatory variables are added sequentially, the order of adding new variables can have an impact on the significance levels. Therefore, we added either host or region first and compared the results. In the SC-GA data set, host species was the only explanatory variable, and we used the function amova of the R package pegas (Paradis, 2010).

AMOVA uses genetic distance matrices between all pairs of individual genotypes to assess differentiation between barnacles from different host species. For the microsatellite data, we calculated these individual distance matrices on the basis of Nei's distance (Nei, 1972, 1978); the genetic distance of Cavalli-Sforza and Edwards (1967), which is the least sensitive to the presence of null alleles (Chapuis and Estoup, 2007); and genetic distance based on relative dissimilarity (Prevosti et al., 1975) with the functions nei.dist, edwards.dist, and provesti.dist, respectively, of the package Poppr (Kamvar et al., 2014) in the R environment. ANOVAs were carried out with each of these distance matrices. For the mitochondrial COI sequence data, we used the Bayesian information criterion (BIG) of jModelTest (ver. 2.1.5) (Darriba et al., 2012) to choose the most appropriate model of sequence evolution. The BIG was lowest for the transversional model of sequence evolution (Kimura, 1980), and we computed genetic distances on the basis of this DNA sequence model (function dist.dna, R package ape, model = "K80").

We further investigated the presence of host-induced population structure of the microsatellite data with a discriminant analysis of principal components (DAPG), implemented by the function dapc in the R package adegenet (Jombart, 2008; Jombart et al., 2010). The DAPG algorithm summarizes the genotypic data and can identify alleles that best differentiate preassigned groupings. In our case, the preassigned groupings are based on host species. We conducted a DAPG with the complete data set and with a data set subset to the SC-GA region. The number of principal components to be retained was calculated on the basis of the alpha score (Jombart et al., 2010), implemented by the function optima score of the R package adegenet (Jombart, 2008; Jombart et al., 2010). We calculated the mean assignment probability for each individual. If this probability is high, groups are well discriminated by the genetic data. In addition, we calculated the contribution that each allele had in defining the preassigned groupings. Alleles with large contributions are useful in differentiating the data and may indicate parts of the genome with host-limited gene flow. Identifying the extent to which frequencies of alleles with significant contributions change among groups further highlights their relative significance. The principal components and assignment probabilities of a DAPC with preassigned groupings represent the maximal differentiation of the data with regard to the preassigned groupings. This distinguishes this implementation of DAPC from a STRUCTURE analysis (Pritchard et al., 2000), which aims to identify groupings that fit the data best. We also assessed geographic differentiation between populations in the DAPG framework. First, we used the complete data set, with geographic locations as preassigned groupings. Next, we split the data set by host species and repeated the analyses to remove the effect of host species. We visualized the complete COI data set with a haplotype network (Templeton et al., 1992) using the functions haplotype and haploNet in the R package pegas (Paradis, 2010).

Morphological host specificity

Populations of C. testudinaria consist of hermaphrodites, which attach directly to their host, and dwarf males (complemental males sensu Darwin, 1854), which attach to hermaphrodites (Grisp, 1983; Zardus and Hadfield, 2004; Cheang et al., 2013; Zardus et al., 2014). Males could have different morphologies because their attachment location represents a different environment. We thus restricted our morphological analyses to hermaphrodites of C. testudinaria. We measured maximal basal shell diameter, maximal operculum length, shell height, and shell thickness to the closest 0.1 mm with digital vernier calipers (Fig. 2). We excluded individuals with irregular shells from our analyses. Barnacle shells were irregular when they grew wedged between shell or carapace plates. We measured the length of the feeding appendage IV (hereafter, "cirral length") with a ruler to the closest millimeter (Fig. 2). We measured shell and cirral characters on 98 Atlantic barnacles, 41 barnacles from blue crabs, 32 barnacles from horseshoe crabs, and 25 barnacles from loggerhead sea turtles. We also weighed a small subset of barnacle bodies (excluding egg masses and shells) from different host species to assess whether internal basal diameter is a good approximation of the weight of the barnacle body--and therefore of barnacle size--using linear regression. As we measured the same shell and cirral traits as Cheang et al. (2013), we included their data on all host species for which more than five barnacles had been sampled: 59 barnacles from the swimming crab Scylla serrata (Forskal, 1775) and 17 from the green turtle Chelonia mydas (Linnaeus, 1758) (for sampling sites of the West Pacific population, see appendix S1 of Cheang et al., 2013). From the measurements, we calculated the internal basal diameter.

We investigated host-specific barnacle morphology with multivariate analysis of variance (MANOVA) and with multivariate linear regressions. We tested the effect of host species, internal basal diameter, and their interaction term on any of the morphological traits (Fig. 2). Internal basal diameter was used to account for size differences between individuals. Using the host-specific regression slopes, we normalized all morphological measurements to correspond to the median size calculated for all barnacles. Then we carried out ANOVAs on the normalized measurements and calculated Tukey honest significant differences (HSDs) for all host pairs when the ANOVA indicated significant differences. This allowed us to identify the specific host pairs that contributed to the morphological differentiation of their attached barnacles.

Results

Molecular techniques

We genotyped a total of 382 individuals. We successfully amplified all 11 microsatellite loci for 92 individuals, more than seven loci for 272 individuals, and more than five loci for 364 individuals. These results are consistent with a previously inferred prevalence of null alleles (Ewers-Saucedo et al., 2016), which is typical for populations with a large effective population size (Chapuis and Estoup, 2007). Amplification success was independent of the host species: 93.9% of barnacles from blue crabs, 97.7% of barnacles from horseshoe crabs, and 90.7% of barnacles from loggerhead sea turtles amplified at more than five loci. We ran all analyses allowing for different amounts of missing data. The results were quantitatively the same, and we report the results of the analyses that included individuals that amplified at more than five loci. Allele calls and collecting information for all individuals used in the analyses are available online (Ewers-Saucedo, 2017b). This microsatellite data set included 25-132 individuals per geographic region and host species (Table 1). The number of alleles per locus ranged from 7 to 61. These allele numbers compare favorably with the results of a smaller set of individuals used to characterize the microsatellite loci (Ewers-Saucedo et al., 2016), and we direct readers interested in detailed analyses to Ewers-Saucedo et al. (2016). We generated 157 COI sequences from individuals of all three host species throughout their range (Table 1). We detected neither indels nor stop codons in the COI alignment. Final sequence length of the alignment was 642 bp. Taken together with the 10 GenBank sequences, the sequences belonged to 91 haplotypes (Fig. 3). Nucleotide diversity was 0.0027, haplotype diversity was 0.0064, and Tajima's D was -2.8944 (P = 0.0038). Sequences are available at GenBank under accession numbers KT793179-KT79336, and additional collecting information is available online (Ewers-Saucedo 2017b).

Genetic host specificity

On the basis of the results of the AMOVA, host-specific population structure was not detectable for the microsatellite data (P > 0.900 for all distance matrices) or the COI data (P = 0.452) when only the SC-GA region was considered, nor was it detectable when the complete geographic range was considered for the microsatellite data set (P > 0.281 for all distance matrices) or the COI data set (P = 0.374). For both the complete data set and the SC-GA data set, the DAPC did not cluster individuals very well by their host species (Fig. 4A), nor did it assign individuals to their host species with high probability (complete: P = 0.625; SC-GA; P = 0.595) (Fig. 4B). The proportion of preserved variance was high (complete: P = 0.884; SC-GA: P = 0.805). Few alleles contributed to observed host-specific clustering (Fig. 4C), and their allele frequencies differed maximally 0.1653 between any of the host populations (Fig. 4D). Thus, the host-specific clustering observed in Figure 4A and B is merely the result of these few alleles, which differ little in allele frequency between barnacles from different host species. Results were quantitatively the same when using the complete data set (Fig. A1). The haplotype network of the mitochondrial COI data did not indicate host-specific haplotype separation; the most abundant haplotypes were equally common among barnacles from any host species. All results failed to indicate significant population genetic structure between barnacles from different host species. Similarly, we did not detect significant population genetic structure between barnacles from different geographic regions (see Figs. A2-A5).

Morphological host specificity

The barnacles we measured ranged in basal diameter from 2 to 60 mm. The basal shell diameter of West Pacific barnacles ranged from 2.7 to 65.6 mm. Internal basal diameter was a good predictor of body weight ([R.sup.2] = 0.6503, P < 0.001), and we used it to approximate barnacle size and to nomialize our data. Morphological measurements and collecting information are available online, as are the body weight measurements (Ewers-Saucedo, 2017a-c). All morphological traits increased with internal basal diameter (P < 0.001 for all morphological traits) (Fig. 5). Host-specific differences in shell thickness were pronounced (P < 0.001; interaction term: P < 0.001) (Fig. 5A). We identified three distinct host groupings based on the Tukey HSD test: barnacles on sea turtles had the thickest shells, barnacles on horseshoe crabs had shells of intermediate thickness, and barnacles on true crabs had thin shells (Fig. 6A). Shell height also differed significantly between hosts (P = 0.041), with shell height increasing differently in barnacles from different host species (P = 0.024) (Fig. 5B). The Tukey HSD test of normalized shell height revealed significant differences between barnacles on West Pacific swimming crabs and barnacles on Atlantic blue crabs and horseshoe crabs (Fig. 6B). Opercular length itself was not host specific (P = 0.213), but the interaction term was (P < 0.001). Specifically, opercula of barnacles from the two sea turtle species grew relatively less than opercula of barnacles on the other hosts (Fig. 5C), an effect apparent only in very large specimens. Cirral length differed only marginally between barnacles from different host species (P = 0.077) (Fig. 5D).

Discussion

In the present study, we investigated the morphological and genetic host specificity of a commensal barnacle that uses a wide range of host species (Zardus et al., 2014). We did not find signs of host-associated genetic differentiation between barnacles from blue crabs, horseshoe crabs, and loggerhead sea turtles. These negative results are not caused by a lack of variability in the genetic markers; the applied nuclear microsatellite markers and mitochondrial COI sequences had a large number of alleles and haplotypes, respectively. A potential point of concern is that we were unable to amplify all microsatellite loci in all individuals, which had already been observed when the markers were characterized initially (Ewers-Saucedo et al., 2016). As discussed by Ewers-Saucedo et al. (2016), this is likely due to a high prevalence of null alleles, which is expected for populations that have a large effective population size, such as Chelonibia testudinaria. Null alleles lead to an upward bias of population differentiation (Chapuis and Estoup, 2007), which means that our estimates of population differentiation are potentially overestimates. The presence of null alleles does therefore not alter our conclusion that host-associated population differentiation is lacking. The mitochondrial sequence data corroborate the microsatellite marker results: the AMOVAs did not identify significant host-associated structure, and the haplotype network highlights haplotype admixture among barnacles from different host species. We identified two common COI haplotypes in C. testudinaria barnacles from the East Coast of the United States, as did a phylogeographic study using COI on C. testudinaria from loggerhead sea turtles (Rawson et al., 2003). Rawson et al. (2003) showed that the presence of the two major haplotypes was the result of historical vicariant and migratory events of loggerhead sea turtles between the eastern coast of North America and the Mediterranean. Our genetic results are indicative of strong and ongoing gene flow between barnacles from different hosts, and Atlantic C. testudinaria does not form host races. Given our relatively small number of genetic markers, we cannot exclude the possibility that some loci in the genome are responsible for host-specific morphology. If this were the case, postsettlement mortality would remove individuals without the appropriate host-specific alleles. This costly strategy could be alleviated by host-specific settlement, but host-specific settlement would lead to assortative mating in this copulating species and reduced gene flow between barnacles on different hosts, which we did not detect. Therefore, it seems more likely that genetic host specificity is absent in Atlantic C. tesliidinaha, which is in congruence with the findings of an earlier study of the Atlantic lineage that used few mitochondrial and nuclear sequence markers (Zardus etal, 2014) and a genome-wide AFLP scan of the West Pacific lineage (Cheang et al., 2013).

In contrast to the genetic admixture, we identified host-specific morphology. Shell thickness differed between barnacles from all three hosts. It is questionable whether the significant differences in the other morphological traits are biologically meaningful given their small effect size (Figs. 5, 6). This conclusion differs from the findings of Cheang et al. (2013), who identified significant differences between West Pacific C. testudinaria from sea turtles and crabs in all morphological traits. This difference is caused by different normalization procedures: Cheang et al. (2013) normalized morphological measurements by external basal diameter, whereas we chose to use internal basal diameter. External shell diameter is influenced by shell thickness, so if shell thickness differs between hosts, so does the normalizing factor and any trait that is normalized by it. In addition to being independent of shell thickness, our data show that internal basal diameter correlates well with barnacle body weight, making it an appropriate normalizing factor.

Our results throw little light on the reason for host-specific differences in shell thickness. Shells are thickest in barnacles from loggerhead sea turtles, intermediate in barnacles from horseshoe crabs, and thinnest in barnacles from blue crabs. This order coincides with the longevity of the host species. If barnacle age were correlated with host age, differences in shell thickness would be the result of age differences; older barnacles would have thicker shells. This is not the case. In fact, age structure is comparable among C. testudinaria from all three host species, while their natural growth rates, measured as increases in their external shell diameter, differ (Ewers-Saucedo et al., 2015). In particular, barnacles from loggerhead sea turtles grow fastest, barnacles from sibility that some loci in the genome are responsible for host-specific morphology. If this were the case, postsettlement mortality would remove individuals without the appropriate host-specific alleles. This costly strategy could be alleviated by host-specific settlement, but host-specific settlement would lead to assortative mating in this copulating species and reduced gene flow between barnacles on different hosts, which we did not detect. Therefore, it seems more likely that genetic host specificity is absent in Atlantic C. testudinaria, which is in congruence with the findings of an earlier study of the Atlantic lineage that used few mitochondrial and nuclear sequence markers (Zardus et al., 2014) and a genome-wide AFLP scan of the West Pacific lineage (Cheang et al., 2013).

In contrast to the genetic admixture, we identified host-specific morphology. Shell thickness differed between barnacles from all three hosts. It is questionable whether the significant differences in the other morphological traits are biologically meaningful given their small effect size (Figs. 5, 6). This conclusion differs from the findings of Cheang et al. (2013), who identified significant differences between West Pacific C. testudinaria from sea turtles and crabs in all morphological traits. This difference is caused by different normalization procedures: Cheang et al. (2013) normalized morphological measurements by external basal diameter, whereas we chose to use internal basal diameter. External shell diameter is influenced by shell thickness, so if shell thickness differs between hosts, so does the normalizing factor and any trait that is normalized by it. In addition to being independent of shell thickness, our data show that internal basal diameter correlates well with barnacle body weight, making it an appropriate normalizing factor.

Our results throw little light on the reason for host-specific differences in shell thickness. Shells are thickest in barnacles from loggerhead sea turtles, intermediate in barnacles from horseshoe crabs, and thinnest in barnacles from blue crabs. This order coincides with the longevity of the host species. If barnacle age were correlated with host age, differences in shell thickness would be the result of age differences: older barnacles would have thicker shells. This is not the case. In fact, age structure is comparable among C. testudinaria from all three host species, while their natural growth rates, measured as increases in their external shell diameter, differ (Ewers-Saucedo et al., 2015). In particular, barnacles from loggerhead sea turtles grow fastest, barnacles from horseshoe crabs have an intermediate growth rate, and barnacles from blue crabs grow slowest. Thus, differences in shell thickness cannot be accounted for by differences in age but rather by differences in growth rate. Cheang et al. (2013) suggest that shell morphology develops in response to substratum, hydrostatic pressure, or flow velocity. Substratum is unlikely to cause the observed pattern because both horseshoe crabs and true crabs have a smooth chitinous shell, yet barnacle morphology differs significantly. Hydrostatic pressure and flow velocity, on the other hand, differ between the three host species: sea turtles dive deep, and horseshoe crabs presumably spend significant time in deep water. Blue crabs are generally shallow-water inhabitants, even though females migrate into deeper water to spawn. Similarly, sea turtles move faster than horseshoe crabs, and blue crabs move slowly (Renaud and Carpenter, 1994; Carr et al., 2004; Wrona, 2004; Hart et al., 2010; Watson and Chabot, 2010; Abecassis et al., 2013; Foley et al., 2013). Thus, we speculate that being in deep water or experiencing high flow velocities increases shell thickness.

Analyzing the morphologies of West Pacific and Atlantic C. testudinaria together revealed that barnacle morphology was comparable between lineages once host effects were taken into account. We found that morphologies were not species specific per se but rather were host-type specific (Figs. 5, 6): barnacles attached to different species of sea turtles (Chelonia mydas and Caretta caretta) or to different species of crabs (Scylla serrata and Callinectes sapidus) were remarkably similar (Fig. 6A) despite the fact that the host pairs occur in different ocean basins.

Taken together, the lack of genetic differentiation and the morphological host-type specificity suggest that Chelonibia testudinaria is phenotypically plastic, altering its morphology depending on the host it attaches to, which is comparable to the results for the West Pacific lineage of C. testudinaria. This means either that phenotypic plasticity evolved in parallel in both lineages of C. testudinaria or that it evolved in the ancestor and has been maintained since the lineages diverged. Maintenance of this pattern is the more parsimonious explanation, as it requires only a single origin. Assuming a COI divergence rate of about 3% per million years (Wares, 2001), the two lineages diverged about 4-5 mya (Rawson et al., 2003; Cheang et al., 2013; Zardus et al., 2014), suggesting that C. testudinaria has retained phenotypic plasticity over millions of generations. A proximate explanation for this phenomenon is that C. testudinaria may be unable to distinguish between host species (Getty, 1996). If C. testudinaria cannot identify the host species it settles on, its environment would seem unpredictable. In this scenario, morphological host specificity arises as a response to environmental exposure rather than to a host cue itself (Moran, 1992). Ultimately, C. testudinaria might not be able to persist on any of the host species alone, either because their populations are not large enough and cannot guarantee sufficient settlement success, or because the hosts undergo fluctuations in abundance that make them temporarily unavailable as substrate. Consequently, any host specialization might eventually lead to the extinction of specialized host races.

Acknowledgments

This study would not have been possible without the many people who supported barnacle collections in the field, such as Pearse Webster (South Carolina Department of Natural Resources), Jeff Schwenter (South Carolina Department of Natural Resources), Mike Arendt (South Carolina Department of Natural Resources), Matt Ogburn (Smithsonian Environmental Research Center), Darcie Graham (University of Southern Mississippi), Emily Maung (University of Delaware), Matthew Godfrey (National Oceanic and Atmospheric Administration), Charles Manire (Logerhead MarineLife Center), Mike Seebo (Virginia Institute of Marine Science), and Riley Wares (born naturalist). We also acknowledge our funding sources, the National Science Foundation (NSF-OCE 1029526) and the University of Georgia Department of Genetics Hightower Award.

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Appendix

CHRISTINE EWERS-SAUCEDO (1,*) BENNY K. K. CHAN (2) JOHN D. ZARDUS (3), AND JOHN P. WARES (1)

(1) Department of Genetics, University of Georgia. 120 East Green Street, Athens. Georgia 30606: (2) Biodiversity Research Center. Academia Sinica, Nankang 115, Taiwan; and (3) Department of Biology, The Citadel. 171 Moultrie Street, Charleston, South Carolina 29407

Received 25 February 2017; Accepted 23 May 2017; Published online 14 August 2017.

(*) To whom correspondence should be addressed. Present address; Zoologisches Museum der Christian-Albrechts Universitat zu Kiel, Hegewischstra[beta]e. 24114 Kiel. E-mail: ewers.christine@gmail.com.

Abbreviations: AFLP, amplified fragment length polymorphism; AMOVA, analysis of molecular variance; BIC, Bayesian information criterion; COI, cytochrome oxidase subunit I: DAPC. discriminant analysis of principal components; HSD, honest significant difference; MANOVA, multivariate analysis of variance.
Table 1
Number of genotyped Chelonibia testudinaria individuals

                       Geographic region
Host species           DE-VA  GA-SC   FL     MS

Blue crab              53/19   43/11  NA/NA  20/12
Horseshoe crab         34/19  139/20  NA/NA  NA/NA
Loggerhead sea turtle  NA/NA   57/6   19/12  NA/NA

The first number corresponds to individuals genotyped with
microsatellite markers, and the second number corresponds to
individuals for which partial cytochrome oxidase subunit I sequences
are available. NA indicates that we were unable to collect barnacles
from a specific host at the geographic region. The geographic regions
delimit clusters of collection sites, as specified in Figure 1.
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Author:Ewers-Saucedo, Christine; Chan, Benny K.K.; Zardus, John D.; Wares, John P.
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