Spatial and temporal population genetic structure of the butterfly Aglais urticae L. (Lepidoptera,...

Molecular Ecology (2009) 18, 2165–2184 doi: 10.1111/j.1365-294X.2009.04169.x

© 2009 Blackwell Publishing Ltd

Blackwell Publishing LtdSpatial and temporal population genetic structure of four northeastern Pacific littorinid gastropods: the effect of mode of larval development on variation at one mitochondrial and two nuclear DNA markers

HYUK JE LEE* and ELIZABETH G. BOULDINGDepartment of Integrative Biology, University of Guelph, Guelph, ON, Canada N1G 2W1

Abstract

We investigated the effect of development mode on the spatial and temporal populationgenetic structure of four littorinid gastropod species. Snails were collected from the samethree sites on the west coast of Vancouver Island, Canada in 1997 and again in 2007. DNAsequences were obtained for one mitochondrial gene, cytochrome b (Cyt b), and for up totwo nuclear genes, heat shock cognate 70 (HSC70) and aminopeptidase N intron (APN54).We found that the mean level of genetic diversity and long-term effective population sizes(Ne) were significantly greater for two species, Littorina scutulata and L. plena, that had aplanktotrophic larval stage than for two species, Littorina sitkana and L. subrotundata, thatlaid benthic egg masses which hatched directly into crawl-away juveniles. Predictably, twopoorly dispersing species, L. sitkana and L. subrotundata, showed significant spatial geneticstructure at an 11- to 65-km geographical scale that was not observed in the two planktotrophicspecies. Conversely, the two planktotrophic species had more temporal genetic structure overa 10-year interval than did the two direct-developing species and showed highly significanttemporal structure for spatially pooled samples. The greater temporal genetic variation of thetwo planktotrophic species may have been caused by their high fecundity, high larval dispersal,and low but spatially correlated early survivorship. The sweepstakes-like reproductive successof the planktotrophic species could allow a few related females to populate hundreds of kilo-metres of coastline and may explain their substantially larger temporal genetic variance butlower spatial genetic variance relative to the direct-developing species.

Keywords: ecological genetics, invertebrates, life-history evolution, molluscs, phylogeography,population genetics — empirical

Received 30 November 2008; revision received 18 February 2009; accepted 20 February 2009

Introduction

The population genetic structure of a species is comprisedof spatial as well as temporal genetic variation. Many speciesof marine benthic invertebrates have limited capacity formovement as adults (e.g. Janson 1983; Johnson et al. 2001),therefore the presence or absence of a long-lived, free-swimming and feeding (i.e. planktotrophic) larval phasehas been shown to be an important factor determining the

degree of spatial population structure of a species (Avise2004). In planktotrophic species, dispersal by oceanic currentsduring their planktonic larval period connects geographicallyseparated populations, resulting in spatial homogeneity oftheir genetic structure (Waples 1998; Bohonak 1999). In con-trast, invertebrate species without a planktonic larval stageare expected to show substantial spatial population structureon even very small geographical scales as many species areslow moving or sessile as adults (e.g. Snyder & Gooch 1973;Tatarenkov & Johannesson 1994; Sokolova & Boulding2004a). Numerous comparative population genetics studiesof marine benthic invertebrate species support the hypothesisthat direct-developing species have lower potential for geneflow by demonstrating higher degrees of spatial population

Correspondence: Elizabeth G. Boulding, Fax: 1-519-767-1656; E-mail: [email protected]

*Present address: Evolutionsbiologie, Department of Biology, Univer-sity of Konstanz, Universitätsstraße 10, D-78457 Konstanz, Germany

mailto:[email protected]

2166 H . J . L E E and E . G . B O U L D I N G


structure relative to planktotrophic species (e.g. gastropods:Janson 1987a; Hoskin 1997; Kyle & Boulding 2000; Collin2001; bryozoans: Goldson et al. 2001; Watts & Thorpe 2006;sea cucumbers: Arndt & Smith 1998; sea stars: Hunt 1993;solitary corals: Hellberg 1996).

Despite these efforts to advance our understanding ofspatial population genetic structure of marine species, littleattention has been paid to understanding how the popula-tion genetic structure of marine species changes through timeand whether temporal variation is more common in plank-totrophic species than in direct-developing species. Tem-poral sampling of the adults of several marine species with aplanktonic larval phase has revealed that allele frequenciessometimes change dramatically within several generations(e.g. Hedgecock 1994; Chapman et al. 2002; Hauser et al. 2002;Turner et al. 2002; Robainas et al. 2005; Florin & Höglund 2007;Lee & Boulding 2007). These changes in allele frequenciesover a short time period could be caused by strong geneticdrift. Marine planktotrophic species typically show extremelyhigh fecundity and very high mortality during their earlylife-history stages. Consequently, only a small portion ofparents may genetically contribute to the next generation,which can substantially reduce the effective population size(Ne) over the short-term (Waples 2002; Hedrick 2005). Thepossibility of a small number of parents replacing the entirepopulation in each generation by a sweepstakes-chancematching of reproductive activity with oceanographic con-ditions conductive to spawning, fertilization, larval survival,and successful recruitment has been called the ‘sweepstakeshypothesis’ (Hedgecock 1994). A second and related hypo-thesis is that groupings of settling larvae (i.e. recruits) maydiffer genetically over space and time — either due to theirdifferent origins or because of natural selection while theyare in the plankton — which can result in detectable temporalgenetic structure (Johnson & Black 1982, 1984; Johnson &Wernham 1999). A third hypothesis is that catastrophicevents (e.g. El Niño, hurricanes) in the marine environmentmay alter the pattern of year-to-year return of planktoniclarvae (e.g. Robainas et al. 2005). These stochastic environ-mental events can cause temporal variation in the amountof successful recruitment by the pelagic larvae to the benthicadult life-history stage, which will eventually create temporalgenetic structure. However, until now, there have been noreports of temporal genetic variation in direct-developingspecies.

What data are available suggest that compared to plank-totrophic species, direct-developing species have much lowerfecundity for their size, but higher early survivorship (Thor-son 1946, 1950; Crisp 1974; Strathmann 1985; Pechenik 1999).Strathmann (1985) argued that the daily mortality rate ofbenthic eggs and early juveniles of direct-developing spe-cies was substantially lower than that of the planktonic eggsand larvae of planktotrophic species. The ecological charac-teristics — ‘lower fecundity, but higher early survivorship’

— may provide an opportunity for a lower variance inreproductive success among females of direct-developingspecies than planktotrophic species, which may allow fortheir relatively stable temporal genetic structure. Low immi-gration rates into local populations of direct-developing spe-cies may also contribute to the high temporal stability of theirgenetic structure. Low levels of gene flow among populationsof direct-developing species may substantially decrease thechance that immigrants with unique alleles from other popu-lations will become dominant within a population, as mayroutinely occur in planktotrophic species. The hypothesisof high temporal stability of genetic structure in direct-developing species is supported by the observation thatdifferences in allele frequencies between upper shore andlower shore ecotypes of a direct-developing species, Littorinasaxatilis, were similar in 1989 and in 2003 (Rolán-Alvarezet al. 2004). However, allele frequencies were stable only solong as the non-neutral allozyme locus Pgm-2 (phosphoglu-cose mutase) was excluded from the analysis (Rolán-Alvarezet al. 2004). This suggests that temporal variation may beeasier to interpret if it occurs in molecular markers that havebeen shown to be selectively neutral.

The Ne of benthic invertebrate species with a planktoniclarval phase has been believed to be much larger than thoseof direct-developing species because planktonic species gen-erally have higher fecundities, and larger geographical dis-tributions (Reid 1996; Pechenik 1999). However, all that isknown for sure is that if populations are tentatively definedas demographically independent units that experience lessthan 10% immigration (m < 0.1) (Waples & Gaggiotti 2006),then the higher dispersal potential of the planktotrophicspecies during their free-swimming larval stage results inthem having a much larger average census population sizes,Nc. Ne has been predicted using simple algebraic equationsincorporating temporal variation in Nc, variation in sex ratio,and variance in family size (reviewed by Hartl & Clark 1997).The hypothesis of larger Ne of planktotrophic species issupported by the empirical observation that planktotrophicspecies generally possess a much greater amount of geneticdiversity per population than do direct-developing species(Foltz 2003; Foltz et al. 2004). Ewens (1972) has theoreticallydemonstrated that at mutation–drift equilibrium, finitesamples of a particular size taken from populations with alarger Ne will show a larger number of alleles than will sam-ples taken from populations with a smaller Ne. Accordingto this theory, the observation of many rare alleles/haplo-types that have been generally detected in the populationsof planktotrophic species are believed to be a genetic signalindicating a very large Ne (e.g. Kyle & Boulding 2000; Uthicke& Benzie 2003; Cassone & Boulding 2006; Zane et al. 2006).Some recent studies that estimated Ne using temporal geneticdata have provided evidence supporting this notion of alarge Ne in marine planktotrophic species (e.g. the Atlanticcod: Poulsen et al. 2006). However, this conventional wisdom

T E M P O R A L S T R U C T U R E O F F O U R M A R I N E G A S T R O P O D S 2167


has been challenged by evidence for small Ne in two marinefish species (Hauser et al. 2002; Turner et al. 2002), in a marineplanktotrophic gastropod species (Lee & Boulding 2007),and in a European flat oyster species (Hedgecock et al. 2007).

Here we examine and compare genetic diversity andspatial and temporal population genetic structure of fournortheastern Pacific marine gastropod species, Littorinasitkana, L. subrotundata, L. scutulata and L. plena, which nor-mally inhabit mid- to high rocky intertidal habitats (Reid1996). The first two species produce benthic and gelatinousegg masses from which the juvenile snails hatch directly(i.e. direct developers), whereas the latter two species layplanktonic egg capsules from which veliger larvae hatch,which undergo subsequent development and feeding inthe water column (i.e. planktotrophic developers) (Reid1996). Under laboratory conditions, the length of the larvalperiod was found to be similar for the two planktotrophicspecies: from 37 to 70 days for L. scutulata (N = 8) and 64 daysfor the single L. plena that successfully metamorphosed(Hohenlohe 2002). These four littorinid gastropod speciesare known to share similar ecological niches (BehrensYamada 1992; Reid 1996). For example, their vertical inter-tidal distributions strongly overlap at any given location,their body sizes are similar, and they all feed on micro- ormacro-algae (Reid 1996). The phylogenetic relationshipsamong these Littorina species have been estimated and thetwo planktotrophic species are sister taxa, while the twodirect-developing species are members of the same clade(Reid et al. 1996). To our knowledge, no studies to datehave evaluated the temporal genetic structure for a direct-developing marine species. Thus, this study is the firstto analyse the temporal genetic structure of both directlydeveloping and planktotrophically developing speciestogether in a comparative context.

In this study, we aim to assess the effect of the presenceor absence of a planktotrophic larval phase on the level ofgenetic diversity and the spatial and temporal genetic struc-ture of the four different littorinid gastropod species. Wepredict that two direct developers, L. sitkana and L. subrotun-data, will show much higher levels of spatial structure thanwill do two planktotrophic developers, L. scutulata and L.plena, because of their poorer ability to disperse. Direct andindirect methods have shown that Littorina snails that lacka free-swimming larval stage typically disperse only a fewmetres per generation (e.g. Janson 1983; Boulding et al. 2007).We also predict that the two direct-developers will exhibitlower levels of temporal structure, because of lower variancein reproductive success among mothers that is caused bya lower fecundity, a higher egg to juvenile survivorship, anda lower migration rate. The specific objectives of this study areto (i) examine and compare the levels of within-populationgenetic diversities between the two direct-developingand two planktotrophic Littorina species; (ii) investigate thetemporal population genetic structure of these species

between sampling periods that were 10 years apart (1997vs. 2007) by analysing data on a portion of the mtDNA Cytb gene as well as two single-copy nuclear DNA loci(scnDNA — heat shock cognate 70: HSC70; intron of amino-peptidase N: APN54); (iii) assess the degree of spatialpopulation genetic structure of the four Littorina species atan 11- to 65-km geographical scale within sampling periods;and (iv) estimate long-term Ne for the three geographicalsamples of each species, based on coalescent theory (Beerli& Felsenstein 2001).

Materials and methods

Study sites and collection of organisms

Four littorinid gastropod species were re-sampled in August2007 from three sites that had been sampled in August 1997(Kyle & Boulding 2000). The three sites chosen were alllocated on the west coast of Vancouver Island, British Colum-bia, Canada and consisted of (i) Cape Beale (location code:CB, coordinate: 48°47′08′′N, 125°12′54′′W); (ii) Pachena Point(PP, 48°43′29′′N, 125°06′16′′W); (iii) Port Renfrew (PR,48°31′23′′N, 124°25′20′′W) (Fig. 1). The sampled snails includetwo direct-developing species, Littorina sitkana and L. subro-tundata, and two planktotrophic species, Littorina scutulataand L. plena. However, no samples of L. sitkana were obtainedfrom CB in 1997. The geographical distance between CB andPP, between PP and PR, and between CB and PR is approxi-mately 11, 55, and 65 km, respectively. The geographicalsurface distance in kilometres between sampling sites wasestimated from the website, http://chemical-ecology.net/java/lat-long.htm, based on the latitude and longitude foreach site.

We predicted that both direct-developing species mightshow microgeographical population structure because oftheir limited ability to disperse, and that such microgeo-graphical structure might make it difficult to differentiatespatial variation in genetic structure from temporal variation.To eliminate this, we attempted to collect the second samples(i.e. 2007 samples) from exactly the same microhabitats asthe previous samples from 1997. The microhabitats had beeninitially chosen using a comprehensive sampling methodof selecting two or three subsampling sites at each site atrandom then randomly collecting the snails from the sub-sampling sites with forceps (Kyle & Boulding 2000). Todetermine the consequences of not finding the same exactmicrohabitat, we then tested whether there was genetic dif-ferentiation among the subsamples within the sites in the2007 samples for the two direct-developing species. We foundno genetic differentiation among the subsamples within allthe three sites for either species (i.e. no microgeographicalstructure; Lee 2008), allowing us to rule out a confoundingspatial effect. All snails were kept alive until they were frozenwhole at –20 °C or –80 °C.

http://chemical-ecology.net/java/lat-long.htm

http://chemical-ecology.net/java/lat-long.htm



DNA extraction, polymerase chain reaction, sequencing and editing

Genomic DNA of the 1997 samples had been extracted usinga labourious methylene chloride/isoamyl alcohol (MCIA)protocol (Kyle & Boulding 1998) and stored at –80 °C whichmeant that most templates were still usable. In the past10 years, DNA isolation techniques for molluscs have becomemore efficient. Therefore, the genomic DNA of the 2007samples was extracted from only 5–10 mg of thawed tissuefrom the side of the foot using a Chelex protocol with 6%InstaGene. Matrix (Bio-Rad). The Chelex protocol was per-formed according to the manufacturer’s directions exceptfor an increase in incubation time (50–60 min instead of 15–30 min at 56 °C) and an increase in the amount of Chelexmatrix for each sample (300 μL instead of 200 μL). Polymerasechain reaction (PCR) amplification for the mtDNA Cyt bgene and two scnDNA loci, HSC70 and APN54, were carriedout in separate 50-μL reactions comprising 100–200 ng ofDNA template, 1× PCR buffer (20 mm Tris-HCl, pH 8.4;50 mm KCl; 0.0125 mm MgCl2; 0.1% Triton X), 20 μm of eachdNTP, 1.75 mm MgCl2, 0.3 U Taq polymerase (Invitrogen)and 10 pmol of each of the forward and reverse primers.Primer sequences, annealing temperatures (Ta), and thermalregime for PCR amplification are shown in Table S1,Supporting information. All PCR amplification was con-ducted in a Robocycler Gradient 96 (Stratagene). Each PCRproduct was mixed with 1 μL of 6× gel-loading buffer (0.25%bromophenol blue, 0.25% xylene cyanol FF and 30% glycerolin water), and electrophoresed in a 2% agarose gel (Invitro-gen) stained with 2 μL ethidium bromide in 1× TAE buffer.Electrophoresis was performed at 65–67 V for about 40 minat room temperature.

To prepare samples for DNA sequencing, every amplifiedproduct was purified directly from the PCR using the GFXPCR DNA and Gel Band Purification Kit (GE Healthcare)according to the manufacturer’s instructions, except for thefinal elution which was carried out using 40 μL of ultrapure water (Invitrogen). The purified mtDNA and scnDNAfragments were subject to direct sequencing using 5 pmol ofthe respective forward primer and the BigDye Terminator3.1 Cycle Sequencing Ready Reaction Kit (Applied Bio-systems). This procedure was performed according to themanufacturer’s recommendations, except that we only used 1 μLof BigDye reaction mix per reaction. All reactions for DNAsequencing were run on a 3730 DNA Analyser (AppliedBiosystems) at the Genomics Facility at the University ofGuelph, and analysed with ABI PRISM DNA SequencingAnalysis Software version 3.4. The DNA sequences wereedited using Chromas version 2.01 computer software. Align-ment of sequences was conducted using ClustalW, version1.83 and then was verified by eye.

Haplotype identification

Mitochondrial Cyt b gene. A 414-bp sequence of the mtDNACyt b gene was obtained from all the 2007 samples. Sequencesfor the 1997 samples were retrieved from GenBank (Kyle &Boulding 2000; GenBank Accession nos AF089717–AF089718for L. sitkana; AF023603–AF023610 for L. subrotundata;AF077238–AF077255 for L. scutulata; AF077256–AF077291for L. plena). The identified haplotypes for the entire mtDNAdata set were given specific haplotype numbers as follows:(i) L. sitkana: MtK1–MtK4 (GenBank Accession nos FJ753671–FJ753674), (ii) L. subrotundata: MtR1–MtR11 (FJ753675–FJ753685), (iii) L. scutulata: MtT1–MtT31 (FJ753686–FJ753716),

Fig. 1 Sampling localities of four Littorinaspecies (L. sitkana, L. subrotundata, L. scutulata,and L. plena) on the west coast of VancouverIsland, British Columbia, Canada. The lati-tude and longitude of each location are asfollows: Cape Beale (location code: CB,48°47′08′′N, 125°12′54′′W); (ii) Pachena Point(PP, 48°43′29′′N, 125°06′16′′W); (iii) PortRenfrew (PR, 48°31′23′′N, 124°25′20′′W).



and (iv) L. plena: MtP1–MtP46 (FJ753717–FJ753762) (seeTable S2.1–S2.3, Supporting information).

Single-copy nuclear DNA (scnDNA) markers, HSC70 andAPN54. All of the HSC70 sequence that we used was fromthe exon. It was not possible to use the HSC70 intron becauseit contained many insertion or deletion mutations (= indels),which produced an unreadable DNA chromatogram down-stream of the indel location whenever individuals wereheterozygous for alleles that differed in length. Even theexon sequences were challenging because we needed todetermine the phase of the variable sites that made up eachallele. The gametic phase of the HSC70 exon alleles wasdetermined with the Excoffier–Laval–Balding (ELB) algori-thm (Excoffier et al. 2003), as implemented in Arlequin 3.11(Excoffier et al. 2005) and it was incapable of resolving afragment longer than 135 bp. Therefore, we only used 135 bpof sequence from the 5′ end of the coding strand of the HSC70exon to genotype the two planktotrophic species, L. scutulataand L. plena. Of 178 L. scutulata that we sequenced, 39 indi-viduals (≈ 22%) were in a heterozygous state at more than onenucleotide position, and therefore we had to use ELB todetermine their gametic phase. The remaining 139 indi-viduals provided full allelic information by inspection withoutaid of ELB. Similarly, of 106 L. plena that we sequenced, 35individuals (≈ 33%) were heterozygous at more than oneposition and therefore we had to use ELB to determine theirgametic phase. The determined alleles were given specificallele numbers for each species as follows: (i) L. scutulata:HSCT1–HSCT42 (GenBank Accession nos FJ753595–FJ753636), and (ii) L. plena: HSCP1–HSCP18 (FJ753637–FJ753654) (see Table S4.3–S4.4, Supporting information).

We sequenced two scnDNA gene fragments, HSC70 andAPN54, for the two direct-developing species, L. sitkana andL. subrotundata. We needed to analyse the same size of HSC70gene fragment for all four species. Therefore we defined allelesfor the two direct-developing species based on only 135 bpof the HSC70 exon, even though longer reads of fragmentsincluding 234 bp of the exon and 326 bp (L. sitkana) to 330 bp(L. subrotundata) of noncoding region (intron) downstreamof the exon location were produced by the designed primers.The identified alleles were given specific allele numbersfor each species: (i) L. sitkana: HSCK1 (only a single allelewas observed; GenBank Accession nos FJ753590), and (ii)L. subrotundata: HSCR1–HSCR4 (FJ753591–FJ753594) (TableS4.2, Supporting information).

We also sequenced a 532- to 537-bp piece of the APN54intron for both direct-developing species. We determinedthe haplotype number for each allele using the informationin GenBank (Sokolova & Boulding 2004b; GenBank Acces-sion nos AY357322–AY357323 for L. sitkana; AY357317–AY357319 for L. subrotundata). Two and three alleles had beenpreviously identified for the APN54 intron fragment in L.sitkana and L. subrotundata, respectively (Sokolova & Boulding

2004b). In this study, we detected five new alleles for L. sitkana(total seven alleles) and six new alleles for L. subrotundata(total nine alleles). The identified alleles were given specificallele numbers for each species: (i) L. sitkana: APNK1–APNK7(GenBank Accession nos FJ753655–FJ753661), and (ii) L. sub-rotundata: APNR1–APNR9 (FJ753662–FJ753670) (Table S4.1–S4.2, Supporting information). We did not sequence theAPN54 fragment for the two planktotrophic species becauseit was too variable to be useful for studying temporal geneticvariation and spatial genetic variation at the 11- to 65-kmgeographical scale.

Statistical analyses

For mtDNA Cyt b, the number of polymorphic sites, numberof mtDNA haplotypes, haplotype diversity (h), and nucleo-tide diversity (π) were calculated for each sample as well asfor the entire pooled population of each species using Arle-quin. Molecular distances for π were estimated using themost appropriate DNA substitution model as determinedby Modeltest 3.7 (Posada & Crandall 1998). The distancescalculated for L. subrotundata, L. scutulata and L. plena, usedthe Tamura & Nei (1993) DNA substitution model withgamma shape parameter = 0 (i.e. equal substitution ratesfor all nucleotide sites except for L. plena where the gammashape parameter = 0.859). However, the distance calculatedfor L. sitkana used Felsenstein’s (1981) model with gammashape parameter = 0. The rarefaction method was employedusing Contrib 1.02 (Petit et al. 1998) to calculate haplotyperichness (HR) that was corrected for unequal sample sizesfor each species.

For scnDNA HSC70 and APN54, nuclear allelic DNAdiversity within samples of each species was estimated asthe number of alleles per locus (Na), observed heterozygosity(HO), expected heterozygosity (HE), and allelic richness (AR)using fstat 2.9.3.2 (Goudet 2001). The π was also calcu-lated within samples of each species at HSC70 using Arle-quin. Deviations from Hardy–Weinberg equilibrium (HWE)were estimated for each sample by calculating Weir & Cock-erham 1984) inbreeding coefficient f (equivalent to Wright’sFIS), as implemented in GenePop 4.0 (Rousset 2008). Depar-tures from HWE expectations were assessed using exact testswith statistical significance determined by 10 000 demem-orizations with 10 000 iterations of a Markov chain method.GenePop was also used to test the genotypes at the twoscnDNA loci, HSC70 and APN54, for linkage disequilibrium(LD) for each sample as well as for the entire pooled popu-lation for the direct-developing species, L. subrotundata.HSC70 was not polymorphic for L. sitkana. As a result, onlythe APN54 data were used in all further formal analysesfor L. sitkana. HSC70 was used only for the long-term Ne

estimates.To test whether or not there were significant differences

in the levels of genetic diversity per population (i.e. sample)



among the four Littorina species at mtDNA Cyt b, two differ-ent analyses of variance (anova) were performed separatelyby treating HR and π per sample as a dependent variableand population as an independent variable, using the systat10.0 statistical package. Multiple comparisons were thenanalysed using the Tukey’s HSD test. These analyses werealso carried out for scnDNA HSC70.

In order to explore the phylogenetic relationships amongthe mtDNA haplotypes within species, a network approachwas employed using tcs 1.21 (Clement et al. 2000). Ambi-guous connections in the haplotype network generated bytcs were resolved following the criteria outlined in Tem-pleton & Sing (1993) and Crandall & Templeton (1993): (i)haplotypes are more likely to be connected to interior(ancestral) than to exterior (recent) haplotypes, and (ii)haplotypes are more likely to be connected to haplotypesfrom the same population than to haplotypes from differ-ent populations.

The selective neutrality of the DNA sequence poly-morphisms at each molecular marker was tested using two dif-ferent methods. The Ewen–Watterson homozygosity method(Ewens 1972; Watterson 1978) with 10 000 permutations ofthe data was first used to test the selective neutrality of distri-butions of mtDNA haplotypes and scnDNA alleles for eachsample and was then used for the entire pooled populationof each species. However, no test could be performed forL. sitkana at HSC70 as only a single allele was present. Thesecond method used to test the selective neutrality of theDNA sequence polymorphisms was the McDonald–Kreitmantest (McDonald & Kreitman 1991). According to their model,if the observed substitutions are neutral, the ratio of non-synonymous (replacement) to synonymous fixed differencesbetween the Littorina species should be the same as the ratioof nonsynonymous to synonymous polymorphisms withineach species (McDonald & Kreitman 1991). The McDonald–Kreitman tests for the sequence polymorphisms observedin the Cyt b and HSC70 genes were conducted using DnaSP4.10 (Rozas et al. 2003). As before the McDonald–Kreitmantest for HSC70 could only be conducted for three species:L. subrotundata, L. scutulata and L. plena.

A hierarchical analysis of molecular variance (amova;Excoffier et al. 1992) was performed using Arlequin to esti-mate spatial and temporal population genetic structure ofeach species at each locus. However, one direct-developingspecies, L. sitkana, was not included in this amova or in furthergenetic differentiation analyses at mtDNA Cyt b, becausethe mtDNA Cyt b sequences for this species were not strictlypolymorphic [i.e. the most common haplotype (MtK1)averaged more than 95% of the total sample; see Table S2.1].The spatial and temporal amova analyses were carried outby grouping the three geographical samples (CB, PP andPR) according to sampling time (1997 and 2007): the 1997group comprised CB97, PP97 and PR97, and the 2007 groupcomprised CB07, PP07 and PR07 (Fig. 1 shows sampling

sites and location codes). These amova analyses partitionedthe total molecular variance between temporal groups(FCT = temporal genetic variation), among geographicalsamples within temporal groups (FSC = spatial geneticvariation), and among samples whatever the groups (FST).

To estimate spatial and temporal genetic differentiationbetween samples, exact tests for population differentiation(Raymond & Rousset 1995) as well as calculation of pairwiseestimates of FST (Weir & Cockerham 1984) were carried outseparately for each species at each locus using GenePop.Pairwise comparisons between two different geographicalsamples from different sampling times (total six comparisons;e.g. CB97 vs. PP07) were not of interest, and therefore theresults of these were not presented. Further exact testswere then calculated only for the two planktotrophic spe-cies, L. scutulata and L. plena, by pooling the three geograph-ical samples within sampling periods (1997 and 2007) whichcould be justified because the amova of both Cyt b andHSC70 had shown no significant spatial variation withintime periods for both species. All exact tests were con-ducted by 10 000 dememorizations with 10 000 iterationsof a Markov chain method. For these analyses involvingmultiple tests, the 95% significance levels for every pairwiseexact test of genetic differentiation were conservativelyadjusted, using a Bonferroni correction (i.e. spatial compar-isons: P = 0.05/6 = 0.0083; temporal comparisons: P = 0.05/3 = 0.0167).

The long-term Ne (historical Ne over an evolutionary times-cale) were calculated for the three geographical samples ofeach species using the equation for mtDNA Cyt b: Θ (theta)= Neμ and for scnDNA HSC70: Θ = 4Neμ (Beerli & Felsen-stein 2001) and the coalescent program, Migrate 2.1.3 (Beerli2004). This method assumes that populations have reachedequilibrium between migration and drift and also thatpopulations have constant sizes and have exchangedconstant gene flow over the coalescent period (Beerli &Felsenstein 2001). The mutation rates (μ) of the mtDNA Cyt bgene were calculated using estimated sequence divergencerates of the mtDNA Cyt b gene, which range from 0.74%(transversions) to 7.6% (transitions) per million years forLittorina species (Reid et al. 1996). The μ values of the scnDNAHSC70 were not available, and thus were estimated fromanother nuclear gene, histone H3, for bivalve molluscs (familyArcidae), which range from 0.02% to 0.20% per million year(Marko 2002). Migrate runs were begun with initial valuesof θ and M (migration) based on FST estimates and used 10short chains (500 genealogies used out of 10 000 sampled)and three long chains (5000 genealogies used out of 100 000sampled). Three runs were performed separately to see if theresults were consistent. Unfortunately, only two differentpopulations, PP and PR, could be used to estimate long-termNe for L. sitkana at mtDNA Cyt b. The CB population couldnot be used because no 1997 sample had been collected forthis species (Kyle & Boulding 2000).



Results

Levels of genetic diversities among the four Littorina species

Overall, levels of genetic diversity (i.e. HR/AR, h and π) forthe samples within species were much greater for the twoplanktotrophic species, Littorina scutulata and L. plena, thanfor the two direct-developing species, Littorina sitkana andL. subrotundata (Table 1). As a result, highly significant differ-ences were found in HR/AR and π per sample among thefour Littorina species at both marker-set (mtDNA Cyt b — HR:anova, F3,21 = 13.110, P < 0.001, π: F3,21 = 38.981, P < 0.001;scnDNA HSC70 — AR: F2,17 = 35.401, P < 0.001, π: F2,17 = 28.741,P < 0.001; Fig. 2). At the Cyt b, no significant differenceswere found in HR within the same modes of larval develop-ment, whereas a significant difference was detected in π

between two planktotrophic species (Tukey HSD, L. scutulatavs. L. plena: P = 0.003; Fig. 2). At the HSC70, the highest levelof AR was observed in L. scutulata, intermediate in L. plenaand the lowest in L. subrotundata (when we excluded L.sitkana), while significantly greater level of π was found forL. plena than for L. scutulata (Tukey HSD, L. scutulata vs. L.plena: P = 0.016; Fig. 2).

At the intraspecific level, the mtDNA Cyt b haplotype net-work for each of the four species was centred on the mostcommon haplotype (i.e. haplotype number 1 for each species:MtK1 for L. sitkana, MtR1 for L. subrotundata, MtT1 for L. scutu-lata and MtP1 for L. plena). The most common haplotypespredominated with a frequency of approximately 95% (139out of total 146 samples) for L. sitkana, 83% (191 out of 229)for L. subrotundata, 78% (207 out of 265) for L. scutulata, and46% (71 out of 153) for L. plena, respectively. For all four spe-cies the most common haplotype occurred in all three geo-graphical locations that we sampled both in 1997 and in2007 (Fig. 3; see Table S3.1–S3.3, Supporting information).

All of the sequence polymorphisms that we observed inmtDNA Cyt b and scnDNA HSC70 genes were selectivelyneutral based on the McDonald–Kreitman tables. For themtDNA Cyt b, exact tests between the six species pairingswere always nonsignificant after a Bonferroni correction formultiple testing. Similarly, an analysis of the HSC70 showedthat the exact tests between L. subrotundata, L. scutulata andL. plena were not significant. Indeed, no fixed differencesin nonsynonymous and synonymous substitutions weredetected between any of the three different species pairings.

Littorina sitkana, a direct developer

Of the three molecular markers, mtDNA Cyt b, scnDNAHSC70 and APN54 that we analysed, only APN54 showedsufficient polymorphism that allowed for estimation of thepopulation genetic structure of the direct-developer, L. sitkana.APN54 showed eight-point mutations at eight differentpolymorphic sites in the 532-bp intron fragment, plus twoindels. A total of seven alleles were identified in a sample of139 individuals, and two of them (APNK1 and APNK2)dominated in the samples. The alleles, APNK1 and APNK2differed by four nucleotide substitutions and a short indel(three nucleotide deletions in APNK2). The frequencies ofAPNK1 and APNK2 were approximately 58% and 39% of thetotal sample, respectively. AR within a given sample rangedfrom 2.8 to 4.0, with no evidence of departures from HWEin any of the samples (Table 1).

In contrast, an analysis of variation in the mtDNA Cyt brevealed only three-point mutations at three different poly-morphic nucleotide positions in the 414-bp fragment; twoof the three mutations were nonsynonymous substitutions(Table 1). The overall values of h and π for the entire pooledmtDNA data set were 0.0932 ± 0.0329, and 0.0004 ± 0.0006,respectively. Finally, L. sitkana showed no variation at the

Fig. 2 The average haplotype/allelic richness (HR/AR) andnucleotide diversity (π) per sample for four Littorina species atmtDNA Cyt b (414 bp) and scnDNA HSC70 (135 bp). (a) Averagehaplotype/allelic richness per sample; (b) average nucleotidediversity (π) per sample. Different letters above the solid bars atthe graphs (small letters: species comparisons at mtDNA Cyt b;capital letters: species comparisons at HSC70) represent significantdifferences among the species. The error bars indicate standarddeviations of the mean for each species. Littorina sitkana had onlya single allele at HSC70 so is not shown.



Table 1 Summary of the level of genetic diversity in four Littorina species at mtDNA Cyt b and two single-copy nuclear DNA loci. APN54locus was not analysed for two planktotrophic species, L. scutulata and L. plena

Locus Genetic diversity CB97 CB07 PP97 PP07 PR97 PR07

L. sitkana, a direct developer N —* —* 49 27 46 24Mitochondrial DNA Cyt b (total no. of haplotypes: 4)

No. of polymorphic sites 2 1 2 1No. of haplotypes 2 2 2 2Haplotype richness 0.490 0.991 0.899 1.000Haplotype diversity (h) 0.0408 0.1425 0.1246 0.0833Nucleotide diversity (π) 0.0002 0.0003 0.0006 0.0002

HSC70† (total no. of alleles: 1) N —* 26 22 29 30 23No. of alleles (Na) 1 1 1 1 1HW tests (P) — — — — —HE — — — — —HO — — — — —Allelic richness — — — — —

APN54 (total no. of alleles: 7) N —* 36 24 30 25 24No. of alleles (Na) 4 4 3 2 3HW tests (P) 1.0000 0.4562 0.1123 0.6244 0.7804HE 0.3494 0.5479 0.2130 0.4114 0.4938HO 0.3611 0.4583 0.2000 0.4800 0.5833Allelic richness 3.559 4.000 2.800 2.000 3.000

L. subrotundata, a direct developer N 51 29 51 31 37 30Mitochondrial DNA Cyt b (total no. of haplotypes: 11)

No. of polymorphic sites 2 3 2 3 3 5No. of haplotypes 3 3 3 4 4 6Haplotype richness 1.137 2.000 1.815 2.869 2.916 4.900Haplotype diversity (h) 0.0776 0.1355 0.2792 0.2430 0.4474 0.6115Nucleotide diversity (π) 0.0002 0.0005 0.0007 0.0008 0.0012 0.0024

HSC70 (total no. of alleles: 4) N 38 24 38 30 27 28No. of alleles (Na) 2 3 2 3 3 2HW tests (P) 0.3970 1.0000 1.0000 1.0000 1.0000 1.0000HE 0.3930 0.3289 0.1695 0.0661 0.2048 0.2747HO 0.4737 0.3750 0.1842 0.0667 0.2222 0.3214Allelic richness 2.000 3.000 1.999 2.600 2.889 2.000

APN54 (total no. of alleles: 9) N 35 41 35 32 26 29No. of alleles (Na) 7 6 3 4 2 3HW tests (P) 0.6563 0.9821 0.1399 0.3051 0.2566 0.5498HE 0.5810 0.5766 0.4903 0.6186 0.5098 0.5185HO 0.6000 0.6098 0.4571 0.5625 0.3846 0.4483Allelic richness 6.029 5.389 2.992 3.750 2.000 2.828

L. scutulata, a planktotrophic developer N 48 46 45 30 49 47Mitochondrial DNA Cyt b (total no. of haplotypes: 31)


HSC70 (total no. of alleles: 42) N 26 40 21 29 23 39No. of alleles (Na) 16 13 10 9 10 14HW tests (P) 0.5949 0.6699 0.0827 0.2554 0.2948 0.1132HE 0.7376 0.4696 0.5238 0.4682 0.5150 0.5155HO 0.6923 0.4250 0.3810 0.3793 0.4783 0.4359Allelic richness 13.998 8.699 10 7.679 9.548 9.629

L. plena, a planktotrophic developer N 19 14 25 31 44 20Mitochondrial DNA Cyt b (total no. of haplotypes: 46)




HSC70 (total no. of alleles: 18) N 11 10 11 32 26 16No. of alleles (Na) 10 6 7 7 7 6HW tests (P) 0.8398 0.9405 0.5734 0.0205 0.0508 0.0030HE 0.8139 0.8211 0.8485 0.7986 0.7632 0.7923HO 0.8182 0.7000 0.9091 0.5938 0.6154 0.5000Allelic richness 9.359 6.000 6.814 5.503 5.315 5.776

For the Cyt b gene, sample sizes (N), number of polymorphic sites, number of haplotypes, haplotype richness and genetic diversity indices within a given sample of each species are provided. For the two scnDNA loci, sample sizes (N), observed number of alleles per locus (Na), P values of exact tests for deviations from Hardy–Weinberg equilibrium (HW test; Guo & Thompson 1992), expected (HE) and observed heterozygosity (HO) and allelic richness within a given sample of each species per locus are provided. Location codes are shown in Fig. 1. (See Supporting information for haplotype codes and haplotype frequencies at each sampling site). *No samples were collected for CB97, and no mtDNA data were obtained for CB07 in L. sitkana. †Only a single allele was observed within the entire samples of L. sitkana at HSC70 so that no H-W tests were performed. Also allelic richness could not be calculated.

Locus Genetic diversity CB97 CB07 PP97 PP07 PR97 PR07

Fig. 3 Haplotype networks of the mitochondrial Cyt b fragment for the four Littorina species: (a) L. sitkana (b) L. subrotundata (c) L. scutulata,and (d) L. plena. Each line in the network represents a single mutational step between haplotypes irrespective of its length. Numbers showneither inside a circle or at the tip of the solid line represent haplotype numbers. Only haplotype numbers are given in the network becauseof space limitation (e.g. MtK1 → 1). The area of the circle is proportional to individual numbers found for the respective haplotype. Numberswithin parentheses denote the number of individuals that belong to the respective haplotype, which were given only for the haplotypesthat possess more than 10 individuals [e.g. for L. sitkana, 1 (MtK1): 139 individuals]. Haplotypes that are not circled are singletons. Small,filled circles indicate intermediate haplotypes that are not present in our samples, but are necessary to connect all the observed haplotypesto the network (see Table S2.1–S2.3).

Table 1 Continued



exon of HSC70 (135 bp). A single allele, HSCK1 was fixedin the entire samples examined (N = 130).

The Ewens–Watterson tests of selective neutrality for L.sitkana showed that the observed APN54 allele distributionsfollow the expected distributions of selectively neutral allelesin all samples. All P values of the Watterson F statistic for eachsample were inside the top and bottom 2.5% (i.e. 0.025–0.975),suggesting neutral distributions of the APN54 alleles [rangeof the P value of the Watterson F: 0.2237 (PR97)–0.7587 (PP07)].

The hierarchical amova of APN54 revealed no significanttemporal variation in genetic structure between the samplingyears of 1997 and 2007, but highly significant spatial genetic

structure within each of the time periods (Table 2). The pair-wise estimates of FST between samples showed highly sig-nificant population differentiation at APN54 in two out ofthe four spatial comparisons (CB07 vs. PR07: FST = 0.324,P < 0.001; PP07 vs. PR07: FST = 0.447, P < 0.001; Table 3).Interestingly, exact tests found highly significant temporalgenetic differentiation at PP between the 1997 and 2007samples (FST = 0.333, P < 0.001) but no significant temporaldifferentiation at PR (FST = –0.0001, P = 0.404) (Table 3).

The approximate range of the estimated long-term Ne forL. sitkana was (× 103): 105–1400 at mtDNA Cyt b and 100–2625at HSC70 (Table 4).

Table 2 amova of spatial and temporal population genetic structure in four Littorina species using the mtDNA Cyt b gene as well as twosingle-copy nuclear DNA loci. APN54 locus was not analysed for the two planktotrophic species, L. scutulata and L. plena. The analyses wereperformed separately for each species by grouping three geographical samples from Cape Beale (CB), Pachena Point (PP), and Port Renfrew(PR) by sampling times (1997 and 2007): the 1997 group comprised CB97, PP97 and PR97, and the 2007 group comprised CB07, PP07 andPR07. However, only PP and PR were grouped within the sampling times for L. sitkana. Permutations (16 000) were separately carried outfor each amova

Locus Source of variation d.f.Sum of squares

Variance components

Percentage of variation

Fixation indices P

L. sitkana* — a direct-developer APN54 Between temporal groups 1 4.333 0.00177 Va 0.63 FCT = 0.006 0.666

Among samples within temporal groups 2 8.218 0.07637 Vb 27.24 FSC = 0.274 < 0.001Within samples 202 40.842 0.20219 Vc 72.13 FST = 0.279 < 0.001

L. subrotundata — a direct-developerMitochondrial DNA Cyt b

Between temporal groups 1 0.288 −0.00235 Va −1.58 FCT = −0.016 0.513Among samples within temporal groups 4 2.232 0.011 Vb 7.36 FSC = 0.073 < 0.001Within samples 223 31.384 0.14074 Vc 94.21 FST = 0.058 < 0.001

HSC70 Between temporal groups 1 0.297 −0.00133 Va −1.05 FCT = −0.011 0.605Among samples within temporal groups 4 2.136 0.00677 Vb 5.39 FSC = 0.053 < 0.001Within samples 364 43.751 0.12019 Vc 95.67 FST = 0.043 0.001

APN54 Between temporal groups 1 0.900 −0.00661 Va −2.22 FCT = −0.022 0.800Among samples within temporal groups 4 8.607 0.02871 Vb 9.64 FSC = 0.094 < 0.001Within samples 390 107.571 0.27582 Vc 92.58 FST = 0.074 < 0.001

L. scutulata — a planktotrophic developerMitochondrial DNA Cyt b

Between temporal groups 1 0.760 0.00463 Va 2.36 FCT = 0.024 0.078Among samples within temporal groups 4 0.600 −0.00098 Vb −0.50 FSC = −0.005 0.745Within samples 259 49.976 0.19296 Vc 98.14 FST = 0.019 0.089

HSC70 Between temporal groups 1 0.627 0.00152 Va 0.57 FCT = 0.006 0.099Among samples within temporal groups 4 1.488 0.00181 Vb 0.67 FSC = 0.007 0.129Within samples 350 92.874 0.26535 Vc 98.76 FST = 0.012 0.043

L. plena — a planktotrophic developerMitochondrial DNA Cyt b

Between temporal groups 1 1.719 0.01680 Va 4.24 FCT = 0.042 0.095Among samples within temporal groups 4 1.804 0.00311 Vb 0.78 FSC = 0.008 0.205Within samples 147 55.339 0.37646 Vc 94.98 FST = 0.05 0.005

HSC70 Between temporal groups 1 1.416 0.00820 Va 2.00 FCT = 0.020 0.197Among samples within temporal groups 4 2.058 0.00367 Vb 0.89 FSC = 0.009 0.182Within samples 206 82.154 0.39880 Vc 97.11 FST = 0.029 0.017

*The other two loci were not strictly polymorphic [frequencies of the most common haplotype (MtK1) and allele (HSCK1) for mtDNA Cyt b and HSC70 were 95% and 100% of the total sample, respectively] so that amova analyses were not conducted for these loci.



Littorina subrotundata, a direct developer

An analysis of variation in the mtDNA Cyt b gene for thesecond direct developer, L. subrotundata revealed a total of11 haplotypes in a sample of 229 individuals (Table 1). Atotal of 10 point mutations were detected at 10 polymorphicsites in the Cyt b gene fragment and every observed mutationwas a synonymous substitution. The transition to transver-

sion ratio was approximately 4:1. The overall values of hand π for the entire mtDNA data set were 0.2974 ± 0.0386,and 0.0009 ± 0.0010, respectively.

A total of four alleles were identified for HSC70. Themost common allele, HSCR1 predominated across samplesand the frequency of HSCR1 was approximately 86% of thetotal sample. A total of three-point mutations were detectedat three polymorphic sites. Two of these mutations were

Table 3 Spatial and temporal genetic differentiation between samples of four Littorina species from the mtDNA Cyt b as well as two single-copy nuclear DNA loci (scnDNA; heat shock cognate 70: HSC70; intron of aminopeptidase N: APN54). The pairwise FST values betweensamples were calculated according to Weir & Cockerham (1984). Numbers above the diagonal represent FST values based on scnDNAmarkers, and numbers below the diagonal represent FST values based on mtDNA Cyt b. The pairwise estimates of FST between two differentgeographical samples from different sampling times are not presented. Significant deviations from genetic homogeneity by exact tests areshown in upper case letters that are given above each FST value

CB97‡ PP97 PR97 CB07 PP07 PR07

L. sitkana,† a direct developerCB97‡PP97 0.0453NS — 0.3329*** —PR97 — — −0.0001NS

CB07 0.0092NS 0.3242***PP07 0.4472***PR07

L. subrotundata,§ a direct developerCB97 0.0854NS 0.0659NS 0.0365** — —

0.0094NS 0.0888*** –0.0098NS — —PP97 0.0451NS −0.0127NS — 0.0236NS —

0.0518NS — 0.1119*** —PR97 0.1259NS 0.0024NS — — –0.0002NS

— — –0.0144NS

CB07 –0.0066NS — — 0.0757NS 0.0019NS

0.0916*** 0.1087***PP07 — –0.0125NS — –0.0014NS 0.0886*

0.2035***PR07 — — 0.0218* 0.1408NS 0.0896NS

L. scutulata,¶ a planktotrophic developerCB97 0.0237NS 0.0302NS 0.0381NS — —PP97 0.0072NS –0.0065NS — –0.0022NS —PR97 –0.0074NS –0.0014NS — — –0.0058NS

CB07 0.0102** — — –0.0085NS –0.0067NS

PP07 — 0.0473* — –0.0065NS –0.0097NS

PR07 — — 0.0097NS –0.0080NS –0.0125NS

L. plena¶ — a planktotrophic developerCB97 0.0372NS 0.0030NS 0.0084NS — —PP97 0.0626NS –0.0044NS — –0.0094NS —PR97 0.0404NS –0.0130NS — — –0.0014NS

CB07 0.0460* — — –0.0090NS –0.0286NS

PP07 — 0.0454* — –0.0223NS 0.0156NS

PR07 — — 0.0770*** –0.0026NS –0.0026NS

†Only APN54 data were used to estimate FST values for Littorina sitkana because the other two loci, mtDNA Cyt b and HSC70 were not strictly polymorphic. ‡No samples were collected for CB97 in L. sitkana. §Above diagonal (upper row): FST values based on variation at HSC70; above diagonal (lower row): FST values based on variation at APN54; below diagonal: FST values based on variation at mtDNA Cyt b gene. ¶Above diagonal: FST values based on variation at HSC70; below diagonal: FST values based on variation at mtDNA Cyt b gene. The significant levels were adjusted, using the Bonferroni correction for multiple testing. NS, not significant; * significant at P = 0.05 level; ** significant at P = 0.01 level; *** significant at P = 0.001 level.



nonsynonymous substitutions and one was a synonymoussubstitution.

As was seen in L. sitkana, the APN54 locus in L. subrotun-data showed a higher nucleotide polymorphism relative toCyt b and HSC70. A total of 22 point mutations were observedat 22 polymorphic sites in 537 bp of the APN54 fragment,plus three different deletion mutations. Despite theseobserved high DNA polymorphisms, only a total of ninealleles were identified, and two of them, APNR1 and APNR2,were dominantly distributed across the samples. The fre-quencies of these alleles were approximately 30% and 56%of the total sample, respectively. These two alleles showedlarge sequence divergence: they differ by 16 nucleotide sub-stitutions and two indels (one nucleotide deletion in APNR1and seven nucleotide deletions in APNR2; see Table S4.2).

The Ewens–Watterson tests of selective neutrality for L.subrotundata showed that the HSC70 and APN54 alleles fol-low the expected distributions of selective neutral alleles inall samples except for PP07 at HSC70 (P of Watterson F =1.0000) and PR97 at APN54 (P of Watterson F = 0.0077). Inaddition, all samples of L. subrotundata conformed to HWEexpectations at both APN54 and HSC70 (Table 1). Tests ofLD within samples between HSC70 and APN54 indicated

no significant association of alleles except for CB97 (P = 0.01).A further test of LD across all samples showed no signi-ficant result (P = 0.15), suggesting that these two loci can betreated as independent markers.

The hierarchical spatial and temporal amova analyses ofthe three molecular markers for L. subrotundata revealed thesame pattern. There was no significant genetic variationbetween the temporal groups, but highly significant spatialgenetic variation among the three geographical sampleswithin the temporal groups (Table 2).

The exact tests between temporal samples for mtDNACyt b showed significant differentiation in only one out ofthree comparisons (Table 3). However, two out of six spatialcomparisons at mtDNA Cyt b revealed a borderline sig-nificant differentiation after a Bonferroni correction (CB97 vs.PR97: FST = 0.1259, P = 0.0723; CB07 vs. PR07: FST = 0.1408,P = 0.0561). An analysis of HSC70 by the exact tests showedsignificant population differentiation in only one out of sixspatial comparisons, and in only one out of three temporalcomparisons (Table 3). However, APN54 showed significantdifferentiation in four out of six spatial comparisons, andone out of three temporal comparisons (Table 3). In fact, allthree geographical samples in 2007 were genetically different

Table 4 Estimates of long-term effective population sizes (Ne) for four northeastern Pacific Littorina species based on coalescent theory usingMigrate 2.1.3 (Beerli 2004). The Ne was calculated by the equation Θ = Neμ for mtDNA Cyt b and Θ = 4Neμ for scnDNA HSC70. The μ values(mutation rates) of the mtDNA Cyt b gene were calculated using estimated sequence divergence rates, which range from 0.74%(transversions) to 7.6% (transitions) per million year for Littorina species (Reid et al. 1996). The μ values of the scnDNA HSC70 were notavailable, and thus were estimated from another nuclear gene, histone H3, for bivalve molluscs (family Arcidae), which range from 0.02%to 0.20% per million year (Marko 2002). The location codes are shown in Fig. 1

Locus Developmental mode Species Location Theta (Θ)Ne (transversions) (μ = 0.74 × 10−8)

Ne (transitions) (μ = 7.6 × 10−8)

mtDNA Cyt b Direct development L. sitkana PP 0.0098 128 947 1 400 000PR 0.0080 105 263 1 142 857

L. subrotundata CB 0.0019 25 000 271 429PP 0.0071 93 421 1 014 286PR 0.0136 178 947 1 942 857

Planktotrophic development L. scutulata CB 0.0154 202 632 2 200 000PP 0.0069 90 790 985 714PR 0.0267 351 316 3 814 286

L. plena CB 0.0122 160 526 1 742 857PP 0.0533 701 316 7 614 286PR 0.2361 3 106 579 33 728 571

scnDNA HSC70 Direct development L. sitkana CB 0.0012 150 000 1 500 000PP 0.0008 100 000 1 000 000PR 0.0021 262 500 2 625 000

L. subrotundata CB 0.0024 300 000 3 000 000PP 0.0065 812 500 8 125 000PR 0.0026 325 000 3 250 000

Planktotrophic development L. scutulata CB 0.0758 9 475 000 94 750 000PP 0.0234 2 925 000 29 250 000PR 0.0387 4 837 500 48 375 000

L. plena CB 0.0777 9 712 500 97 125 000PP 0.0113 1 412 500 14 125 000PR 0.0104 1 300 000 13 000 000



from one another at APN54. The only inconsistent pairwiseFST values were detected between the two scnDNA loci, forexample, the sample of CB97 was genetically different fromCB07 at HSC70 (FST = 0.0365, P = 0.0089), but was geneticallyidentical to CB07 at APN54 (FST = –0.0098, P = 0.6289).

The approximate range of the long-term Ne estimate forL. subrotundata was (× 103): 25–1943 at mtDNA Cyt b and300–8125 at HSC70 (Table 4).

Littorina scutulata, a planktotrophic developer

A total of 31 mtDNA haplotypes were identified in a sampleof 265 individuals that we sequenced (Table 1). Seventeenout of 31 haplotypes were represented by only one individual(i.e. singletons). Forty polymorphic nucleotide positions weredetected, and seven out of 40 point mutations were nonsy-nonymous substitutions. The transition to transversion ratiowas approximately 5:1. The overall values of h and π for theentire mtDNA data set were 0.3889 ± 0.0391, and 0.0030 ±0.0021, respectively.

A total of 42 HSC70 alleles were determined in a sampleof 178 individuals by ELB (Table 1). Twenty-one out of 42alleles were confirmed from homozygotes or individuals thatwere in a heterozygous state at only one nucleotide posi-tion. The remaining 21 alleles were found in only 28 out of178 individuals, and most of them (17 of 21 alleles) weredetected in only one individual [except for four alleles,HSCT20 (five individuals), HSCT26 (3), HSCT32 (2) andHSCT39 (2)]. Similar to the pattern of mtDNA haplotypedistributions, the most common allele (HSCT1) predominatedin all samples (approximately 68% of the total sample). Therewas substantial genetic diversity in 135 bp of the exon ofHSC70 among 42 alleles [average pairwise sequence diver-gence among the 42 alleles was 2.6 ± 0.19% (± SD)]. Twenty-five polymorphic sites were observed, and the observed 33point mutations were all synonymous substitutions.

The Ewens–Watterson neutrality test for HSC70 revealedthat every sample of L. scutulata had non-neutral allele dis-tributions [mean P value of Watterson F-statistic acrosssamples = 0.9963 ± 0.0037 (± SD)]. In every sample, theobserved F-value (i.e. observed homozygosity) was greaterthan the expected F-value under the neutral model. However,all samples of L. scutulata conformed to HWE expectationsat HSC70 (Table 1).

The amova analyses of both mtDNA Cyt b and scnDNAHSC70 for L. scutulata revealed only a marginally significantdifference in its genetic structure between the 1997 and 2007groups when spatial structure was included (Table 2). How-ever, no significant genetic variation was detected amonggeographical samples within the temporal groups (Table 2).

Both the Cyt b and HSC70 revealed substantial temporalvariation in the genetic structure of L. scutulata when wepooled the geographical samples within the sampling timeperiods, likely because of the increase in sample size. The

exact test between the pooled 1997 and 2007 samples indi-cated highly significant genetic differentiation at both markerset (Cyt b: FST = 0.022, P < 0.0001; HSC70: FST = 0.007, P =0.0053). This significant temporal differentiation indicatedconsiderable temporal changes in haplotype and allele fre-quencies over the 10-year time interval (see Table S2.1).Furthermore, exact tests between samples at the Cyt b showedsignificant population differentiation in two out of threetemporal comparisons after a Bonferroni correction, whereasnone of the six spatial comparisons was significant (Table 3).In contrast, the exact test for HSC70 showed no significanttemporal differentiation between any pair of samples (Table 3).

The approximate range of the estimated long-term Ne forL. scutulata was (× 103): 91–3814 at mtDNA Cyt b and 2925–94 750 at HSC70 (Table 4).

Littorina plena, a planktotrophic developer

A total of 46 mtDNA haplotypes were identified in a sampleof 135 individuals (Table 1); however, 32 out of 46 haplotypeswere singletons. Fifty-three polymorphic sites were detected,and 11 out of 53 point mutations were nonsynonymous substi-tutions. The transition to transversion ratio was approximately17:1. The overall values of h and π for the entire mtDNA dataset were 0.7745 ± 0.0354, and 0.0063 ± 0.0037, respectively.

A total of 18 HSC70 alleles were identified in a sample of106 individuals by ELB (Table 1). Of 18 alleles, 10 were con-firmed from homozygotes or individuals that were in aheterozygous state at only one nucleotide position. Theremaining eight alleles were found only once each in asample of 106 individuals (except for allele HSCP16, whichoccurred twice). Interestingly, there were five common alleles,which were quite evenly distributed in the samples. Thefrequencies of these alleles, HSCP1–HSCP5 were approxi-mately 13%, 28%, 14%, 24% and 13% of the total sample,respectively. Eleven polymorphic sites were detected and twoout of 13 point mutations are nonsynonymous substitutions.An estimate of the average pairwise sequence divergenceamong the alleles was 2.1 ± 0.19% (± SD).

The Ewens–Watterson tests of selective neutrality for L.plena showed that the observed HSC70 alleles followed theexpectations of distributions of selective neutral alleles inall samples. All P values of the Watterson F statistic for eachsample were inside the top and bottom 2.5% (i.e. 0.025–0.975), suggesting neutral distributions of the observedHSC70 alleles [mean P value of Watterson F statistic acrosssamples = 0.2779 ± 0.3358 (± SD)]. Also, a majority of samplesof L. plena conformed to HWE expectations at HSC70 exceptfor PP07 and PR07 (Table 1).

The amova analysis of mtDNA Cyt b for L. plena indicatedonly a borderline significant difference in its temporalgenetic structure between the 1997 and 2007 groups whenspatial structure was included (Table 2). However, no signif-icant genetic variation was detected among geographical



samples within the temporal groups. The amova analysisof HSC70 revealed no significant spatial or temporal popu-lation genetic structure (Table 2).

As previously observed in L. scutulata, both Cyt b andHSC70 in the second planktotrophic species, L. plena, showedsubstantial temporal variation in genetic structure when wepooled the samples within time periods. The exact testsbetween the pooled 1997 and 2007 samples revealed highlysignificant differentiation at both marker-set (Cyt b: FST = 0.045,P < 0.0001; HSC70: FST = 0.0217, P = 0.0004). This observedsignificant temporal differentiation at both markers indi-cated significant temporal changes in haplotype and allelefrequencies over the 10-year time interval (see TableS2.2). Furthermore, the exact tests between samples at theCyt b showed significant differentiation in every case oftemporal comparisons after a Bonferroni correction, whilenone of the spatial comparisons were significant (Table 3).Yet analysis of HSC70 showed no significant differentiationbetween any pairs of samples (Table 3).

The approximate range of the estimated long-term Ne forL. plena was (× 103): 161–33 729 at mtDNA Cyt b and 1300–97 125 at HSC70 (Table 4).

Discussion

Mitochondrial and single-copy nuclear DNA polymorphisms

Our data clearly show that two planktotrophic species,Littorina scutulata and L. plena, had substantially higherlevels of within-population genetic diversities than did twodirect-developing species, Littorina sitkana and L. subrotundata,at both marker-set of mtDNA Cyt b and scnDNA HSC70.These higher levels of genetic diversities translated into largerlong-term (or historical) Ne for the planktotrophic speciesthan for the direct-developing species.

Several other comparative population genetics studies ofmarine benthic invertebrates have also provided evidencefor significantly higher genetic diversities for planktotrophicspecies than for direct-developing species (e.g. Hoskin 1997;Arndt & Smith 1998; Kyle & Boulding 2000). In contrast,Janson (1987a) observed the opposite pattern with greatergenetic diversity in populations of a direct-developing spe-cies, Littorina saxatilis, and lower genetic diversity in a plank-totrophic species, Littorina littorea. However, it is now knownthat several of 14 allozyme loci that she used respond tospatially varying selection in L. saxatilis (Johannesson et al.1995). Foltz (2003) conducted meta-analyses of previouslypublished mtDNA Cyt b data sets for three genera of gastro-pod molluscs including the four Littorina species examinedin this study, and observed that average levels of nucleotidediversity per population, P, were significantly greater forthe planktotrophic species (P = 0.0087) than for the direct-developing species (P = 0.0048). He argued that this sig-

nificant difference in genetic diversity is the outcome of thehigher Ne of the planktonic developers relative to the directdevelopers.

The differences in within-population genetic diversitybetween the two different modes of reproduction could beexplained by several hypotheses. The first hypothesis is thatcensus population sizes, Nc of the two planktotrophic Littorinaspecies are considerably larger than those of the two direct-developing species, resulting in higher Ne (Hartl & Clark1997) and therefore higher genetic diversity (Lewontin 1974;Foltz 2003). If populations are tentatively defined as unitsthat experience less than 10% immigration (m < 0.1) (Waples& Gaggiotti 2006) then the boundary of a single populationmay occur after less than 1 km for the direct-developingspecies (Sokolova & Boulding 2004a) and after hundreds ofkilometres for the planktotrophic species (Kyle & Boulding2000). Therefore the Nc of demographically independentunits for the planktotrophic species will include all the snailsalong long stretches of the Pacific coast whereas those of thepoorly dispersing species may include only the snails inhab-iting a single rocky point (e.g. Boulding et al. 2007).

According to population genetics theory, if Ne is larger inthe two planktotrophic species, L. scutulata and L. plena, thanin the two direct-developing species, L. sitkana and L. subro-tundata, then the effects of genetic drift might be greatlydiminished and thus rare mitochondrial and nuclear haplo-types/alleles will be more likely to persist in the plank-totrophic species (Slatkin 1985). The probability of ultimatefixation of a neutral haplotype/allele in a random-matingpopulation is 1/2Ne (Hartl & Clark 1997). Therefore theprobability of the persistence of a rare haplotype/allele(1–1/2Ne) over generations should be greater when Ne islarger. Local populations of the direct-developing species, L.sitkana and L. subrotundata, are more likely to experiencefluctuating demographic events such as episodes of localextinction followed by re-colonization (Johannesson et al.1995). Prolonged bottlenecks at a small Ne will eventuallydecrease the overall level of genetic diversity (Nei et al.1975). The low genetic diversity and low Ne of the directdevelopers may occur because their small Nc and poordispersal makes them vulnerable to genetic drift whichbecomes even stronger during extinction and re-colonizationevents on small islands (Janson 1987b). Nevertheless, it wassomewhat ironic that only the two planktotrophic developers,but not the two direct-developers, showed significanttemporal genetic differentiation (see below).

A second hypothesis is that there could be a considerabledifference in the ‘sampling’ of genetic diversity at thepopulation level between the two different modes of reproduc-tion. Our sampling was carried out on the same spatial scalefor all four species. Since most of the diversity in the twoplanktotrophic species may be detected among individualscollected at the same site owing to high gene flow, sequencepolymorphisms of the Cyt b and HSC70 genes from samples



at one site may provide a fair representation of entire species-level genetic diversity. On the other hand, for the two direct-developing species, genetic diversity may be partitionedamong local populations throughout the geographical rangeof the species, due to low gene flow. Therefore, the diversitysampled at three sites in Vancouver Island is unlikely toreflect species-level genetic diversity. However, this predic-tion of the ‘sampling artefacts on population-level diversity’hypothesis seems to be false because (i) we observed thatevery geographical site of the two planktotrophic species wesampled had unique haplotypes/alleles that we did notobserve elsewhere (see Appendices S4.2–S4.3 for mtDNAhaplotype distributions and S6.3–S6.4 for scnDNA HSC70allele distributions), suggesting that samples at one site donot seem to contain entire species-level diversity; and (ii) aprevious large-scale study (Kyle & Boulding 2000) also foundmuch higher genetic diversity for the two planktotrophicspecies (e.g. the number of haplotypes, L. scutulata: 18; L. plena:36) than for the two direct-developing species (the numberof haplotypes, L. sitkana: 2; L. subrotundata: 8) at a 1000-kmgeographical scale from Washington state to Alaska, basedon variation in the same mtDNA Cyt b gene fragment.

A third hypothesis is that the demographic history of theplanktotrophic and direct-developing species during the lastglacial maximum (LGM) could have been very differentowing to differences in dispersal capabilities, which could stillhave a residual effect on the observed patterns of geneticdiversity (Hewitt 2000). Because of their poor dispersalcapability of only a few metres per year (Boulding et al. 2007),the two direct-developing species likely experienced moresevere population bottlenecks during the LGM than did thetwo planktotrophic species. Larvae can disperse hundreds ofkilometres during one year under favourable oceanographicconditions (e.g. Cassone & Boulding 2006) and thereforeplanktotrophic species were able to quickly disperse awayfrom the poles and thereby maintain large population sizesduring the LGM. Since there has not yet been time for pointmutations to replenish this variation, the direct-developingspecies still retain relatively low levels of variation in theirmitochondrial and single-copy nuclear genes. This ‘historicaleffects on diversity from the LGM’ hypothesis is supported byour long-term Ne coalescent estimates being substantiallylarger for the planktotrophic species than for the direct-developing species. This is also supported by the typicallyhigher levels of genetic variation at the mtDNA COI genefor Littorina species from tropical regions than from temperateones (M. Stuckley, unpublished Ph.D. thesis, University ofWestern Australia).

Temporal population genetic structure

Our data show that two planktotrophic species, L. scutulataand L. plena, have higher levels of temporal variation in theirgenetic structure over a 10-year time interval than do two

direct-developing species, L. sitkana and L. subrotundata.Although multiple amova analyses of both mtDNA andscnDNA markers showed only marginally significant tem-poral structure in both planktotrophic species (except forHSC70 in L. plena), these results became highly significantfor both markers in both planktotrophic species when thedifferent population samples were pooled within each timeperiod. These data corroborate our previous findings oftemporal genetic heterogeneity over a 10-year interval inanother northeastern Pacific planktotrophic gastropod,Littorina keenae, based on variation in 762 bp of mtDNA ND6and Cyt b genes (Lee & Boulding 2007). In contrast, neitherdirect-developing species shows significant temporal vari-ation at any of the molecular markers they were genotyped for.

There is accumulating empirical evidence that marineplanktotrophic species sometimes have substantial temporalvariation in their genetic structure over short-time intervals,even though they do not have spatial variation at anyparticular time (e.g. Chapman et al. 2002; Robainas et al. 2005;Florin & Höglund 2007; Lee & Boulding 2007). Chapmanet al. (2002) found temporal heterogeneity coupled withspatial homogeneity in the genetic structure of red drum(Sciaenops ocellatus) along the Atlantic Coast of the USAfrom five microsatellite loci. Florin & Höglund (2007) alsoobserved a significant temporal variation in the populationstructure of turbot (Psetta maxima) despite a lack of spatialvariation among sites in the Baltic Sea from eight micro-satellite loci. The significant temporal variation observedin the two planktotrophic species may suggest that theirshort-term (or current) Ne values are small enough to permitappreciable genetic drift (Hedgecock 1994). The greatfecundity and very high larval mortality of both plank-totrophic species may cause substantial variance in thenumber of offspring contributed by adults to the nextgeneration (Fig. 4a). The reproductive success of a plank-totrophic species may be thus like a sweepstakes, in whichonly a small number of adults are responsible for producingoffspring that recruit to the entire population, while mostof them do not produce offspring at all (‘sweepstakes hypo-thesis’; Hedgecock 1994). In a particular year, an extremelysmall number of adults have very high reproductive success(a female with haplotype ‘A’ in Fig. 4a) and most adultshave zero reproductive success (a female with haplotype‘G’ at the top in Fig. 4a), which substantially reduces aNe within a short-time interval and eventually creates thedetectable temporal variation that we observed in bothplanktotrophic species (Fig. 4a). Their sweepstakes-likereproductive success may also result in cohorts of recruitsthat differ more in genetic composition from the age-structuredadult population than do cohorts of recruits produced bythe two direct-developing species.

Another hypothesis to explain the significant temporalstructure for the two planktotrophic species is that groupingsof their settling larvae (i.e. recruits) may differ genetically



over space and time because they originate from differentsource populations that also differ genetically over space andamong different age classes (Johnson & Black 1982, 1984;Johnson & Wernham 1999). Such spatial and temporal geneticvariation in recruits can lead to detectable temporal struc-ture of benthic adult populations. This hypothesis has beensupported by evidence that genetic composition is signifi-cantly different for different size classes (i.e. age classes) ofthe red sea urchin, Strongylocentrotus franciscanus (Moberg& Burton 2000) and for different size classes of the intertidalgastropod, Littorina keenae (H. J. Lee, unpublished data).

In contrast, the two direct-developing species, L. sitkana andL. subrotundata, did not show significant temporal variationin their genetic structure over a 10-year period. There couldbe several hypotheses that can account for the observed tem-poral stability in the genetic structure of both species. First,we propose the hypothesis that the two direct-developingspecies may have a lower variance in reproductive successamong female individuals than do the two planktotrophicspecies, which allows their higher temporal genetic stability(Fig. 4b). The lower variance in reproductive success for bothdirect-developing species may be caused by their lowerfecundity, and by the higher survival of their benthic

eggs and early juveniles, relative to planktotrophic species(Thorson 1946, 1950; Crisp 1974; Strathmann 1985; Pechenik1999). Thorson (1946) reported that of 37 prosobranchgastropod species in Denmark, direct-developing speciesproduce a small number of eggs (typically 10–103) per a singlebreeding season, whereas planktotrophic species producemore eggs (typically 103–109). Strathmann (1985) summarizedstudies on five direct-developing and 24 planktotrophicspecies that daily mortality rate of benthic eggs or earlyjuveniles of direct-developing species was on average 10times lower than that of larvae in the plankton. A moreconsistently even pattern of local recruitment from year toyear is observed more frequently for direct-developingspecies than for planktotrophic species (Behrens Yamada 1974;Johnson et al. 2001), which may further contribute to a lowervariance in reproductive success among mothers.

Second, we hypothesize that low migration rates by thetwo direct-developing species, L. sitkana and L. subrotundata,may contribute to the high temporal stability of their geneticstructure. These species disperse poorly among geographicalsites due to its lack of a larval phase. This will greatly diminishthe probability that immigrants with unique haplotypes/alleles will become dominant within a site, as may commonly

Fig. 4 Hypothesis explaining differences inreproductive success between planktotrophicand direct-developing females (the fecundityof planktotrophic developers is shown astwice that of direct developers. Veliger larvaoverlaid with a cross mark have died whilein the plankton). (a) The high temporal gene-tic variation of the planktotrophic developersmay occur when by chance the veliger larvaefrom a female with the less common ‘A’mtDNA haplotype encounter favourableoceanographic conditions that enable nearlyall of them to survive and metamorphoseinto juvenile snails. Spatial genetic variationis low since the larvae released by a singlefemale can be dispersed by currents alonghundreds of kilometres of coastline. (b) Thelow temporal genetic variation for the direct-developing species is caused by low variancein reproductive success among femalesbecause the higher yolk content of the eggsenables development directly into crawl-away juveniles inside the safety of gelatinousegg masses that are attached to the shore.Therefore, haplotype frequencies of thesepoorly dispersing snails change little fromgeneration to generation on a particular shorebut can differ substantially at sites more than1 km apart.



occur in planktotrophic species (Fig. 4b). In order to gener-alize our observation of the temporal genetic stability to alldirect-developing species, further studies on additional phylaof marine benthic invertebrates will be required.

Spatial population genetic structure

Our combined analyses of mitochondrial and nuclear DNAdata clearly indicate that the two direct-developing species,L. sitkana and L. subrotundata, have more spatial geneticstructure at an 11- to 65-km geographical scale, comparedto the two planktotrophic species, L. scutulata and L. plena.Our analysis also suggests that nearly all of the geneticvariation that we observed was selectively neutral. Only L.scutulata is possibly experiencing selection at HSC70, basedon the pattern of its allele distributions. However, if such selec-tion is occurring, it does not seem to be within the codingregion of HSC70 because all of the 33 point mutations thatwe observed at the HSC70 exon in L. scutulata were synony-mous substitutions. Hemmer-Hansen et al. (2007) foundadaptive divergence at the intron of HSC70, particularlybetween Baltic Sea and North Sea populations of the Euro-pean flounder (Platichthys flesus L.) despite its high gene flow.

Many comparative population genetics surveys ofmarine benthic invertebrate species have shown that direct-developing species have substantially greater levels ofspatial population structure than do planktotrophic species(e.g. Arndt & Smith 1998; Kyle & Boulding 2000; Collin2001; Watts & Thorpe 2006). This spatial structure observedfor the direct-developing species results from low levels ofgene flow, likely due to their poor dispersal capacity becausethey do not have the free-swimming larval phase that theplanktotrophic species have. Previous studies of the twodirect-developing species, L. sitkana and L. subrotundata, havealso shown significant spatial genetic differentiation atAPN54 on a 2- to 3-km geographical scale in Barkley Sound,British Columbia, Canada (Sokolova & Boulding 2004a).Moreover, a larger-scale study of L. sitkana by Zaslavskaya& Pudovkin (2005) found significant genetic differentiationat four allozyme loci [global GST (analogous to FST) = 0.31]over a 525-km geographical scale along the northwesternPacific coast. Our observed significant spatial genetic struc-ture at an 11- to 65-km scale in both direct-developing species,L. sitkana and L. subrotundata, is consistent with the previousstudies, supporting the hypothesis that their gene flow is lowbecause of their limited dispersal ability. In contrast, the twospecies having a planktotrophic larval stage, L. scutulata andL. plena, do not show spatial variation in their populationstructure. Overall, our spatial data substantiate that the pres-ence or absence of the planktotrophic larval phase is a keydeterminant of the magnitude of spatial population structurein marine benthic invertebrate species.

Since the two species within the same modes of reproduc-tion are phylogenetically more closely related to each other

(Reid et al. 1996), the observed similarities in the overallpatterns of genetic diversity and genetic structure for the twospecies of each reproductive mode might come from sharedcommon ancestry rather than from independently acquiredtraits. However, this hypothesis seems highly unlikelybecause (i) no haplotypes/alleles were found to be sharedby the two species of the same modes, (ii) the sequence diver-gence in the Cyt b and HSC70 genes between the speciespairs within the same modes was considerably large and wasroughly equivalent to between the species pairs betweenthe different modes (e.g. Cyt b — between L. sitkana and L.subrotundata: uncorrected p-distance: 9.5%; between L. sitkanaand L. scutulata, and between L. sitkana and L. plena: uncor-rected p-distance: 11.2% and 12.1%, respectively), and (iii) ourprevious study on another planktotrophic species, L. keenae,which is only phylogenetically distantly related to L. scutulataand L. plena, but showed exactly the same pattern of spatialand temporal genetic structure (Lee & Boulding 2007). Thesemultiple lines of evidence strongly suggest that the similargenetic patterns observed for two direct-developing and fortwo planktotrophic species are most likely caused by a differ-ence in the reproductive mode.

A seeming paradox in our data is that although the twoplanktotrophic Littorina species had larger historical Ne

(which reflects higher genetic diversity) than the two direct-developing species, the planktotrophic species showed moretemporal variation in their genetic structure (which mayimply a smaller current Ne). Our first hypothesis to explainthis paradox is that pulses of gene flow from other sites couldincrease the levels of genetic diversity, which would inflateour long-term Ne values for the planktotrophic species(Ovenden et al. 2007). Consequences for the planktotrophicspecies, the estimated Ne values for three geographicalsamples could represent historical Ne of all demographiccohorts and populations that make up the entire species,whereas the direct-developing species may show thesubstantial historical Ne of the local populations (Waples &Gaggiotti 2006). This hypothesis is supported by observationsthat snails of different sizes and presumably of differentcohorts differ in mitochondrial haplotype frequencies (H. J.Lee, unpublished data). A second but less likely hypothesisis that the two planktotrophic species have experienced arecent decline in population sizes. Prolonged bottlenecks inpopulation size have been shown to explain the differencebetween historical and current Ne (Nei et al. 1975). Furtherstudies on additional phyla of planktotrophic marine benthicinvertebrates are needed before we can convincingly con-clude that this observed pattern of the temporal geneticdivergence in planktotrophic littorinid gastropods (despitetheir high historical Ne) is common. We believe that ourstudy is a first step towards understanding how the presenceor absence of a planktotrophic larval phase influences thetemporal population genetic structure of marine benthicinvertebrate species.



In summary, our data demonstrate that two direct-developing species, L. sitkana, L. subrotundata, shows muchhigher levels of spatial genetic structure than do two plank-totrophic species, L. scutulata and L. plena. Conversely, thetwo planktotrophic species exhibit greater levels of temporalgenetic structure than do the two direct-developing species,and also paradoxically have larger historical Ne.

Acknowledgements

We are very grateful to J. Ballantyne, T. Crease, M. Culling, H. Freamo,Z. Gedalof, T. Hay, J. Kang and the members of the Bogart-Boulding-Fu-Heyland laboratory discussion group as well as T. Duda, M.Hansen and three anonymous reviewers for their suggestions forimproving the manuscript. We thank A. Holliss, E. Holmes and J.Zhang for electrophoresis of our DNA sequences and I. Smith forhelping format the final figures. We especially thank C. Kyle forallowing us to utilize his published data and for helping locate his1997 sampling sites. We also thank T. Hay for helping collect the2007 samples, and E.N. Hay for drawing Fig. 4. Finally, we thankthe director and staff of the Bamfield Marine Sciences Centre(BMSC) for their assistance. This study was supported by NSERCDiscovery and PREA grants to E.G.B.

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This work formed part of the PhD dissertation of Hyuk Je Lee whois interested in integrating modern molecular techniques withtraditional ecological approaches to better understand ecologicaland evolutionary aspects of marine or aquatic animals. His primaryresearch interest is to understand how genetic variation within andbetween natural populations of marine or aquatic species can beshaped by physical and biological processes at various spatial andtemporal scales. He is now a postdoctoral fellow in Axel Meyer’slaboratory at the University of Konstanz in Germany. ElizabethBoulding is a professor at the University of Guelph with broadresearch interests in conservation genetics, molecular ecology,quantitative genetics, and ecology of marine organisms.

Supporting information

The following supporting information is available for this article:

Table S1 PCR conditions for amplifying the mtDNA Cyt b as wellas two single-copy nuclear DNA loci (heat shock cognate 70:HSC70; intron of aminopeptidase N: APN54) for four Littorina species(L. sitkana, L. subrotundata, L. scutulata and L. plena).

Table S2.1 Haplotype definition of all obtained Cyt b mtDNAhaplotypes of two direct-developing Littorina species (L. sitkanaand L. subrotundata) showing the variable sites only.

Table S2.2 Haplotype definition of all obtained Cyt b mtDNAhaplotypes of Littorina scutulata showing the variable sites only.

Table S2.3 Haplotype definition of all obtained Cyt b mtDNAhaplotypes of Littorina plena showing the variable sites only.

Table S3.1 Frequency distribution of the Cyt b mtDNA haplo-types of two direct-developing Littorina species (L. sitkana and L.subrotundata) among samples.

Table S3.2 Frequency distribution of the Cyt b mtDNA haplo-types of Littorina scutulata among samples.

Table S3.3 Frequency distribution of the Cyt b mtDNA haplo-types of Littorina plena among samples.

Table S4.1 Allelic definition of all observed alleles from scnDNAAPN54 (intron of aminopeptidase N) for the direct-developingspecies, Littorina sitkana.

Table S4.2 Allelic definition of all observed alleles from twoscnDNA loci (heat shock cognate 70: HSC70; intron of amino-peptidase N: APN54) for the direct-developing species, Littorinasubrotundata.

Table S4.3 Allelic definition of all observed nuclear HSC70 (heatshock cognate 70) alleles for the planktotrophic species, Littorinascutulata.

Table S4.4 Allelic definition of all observed nuclear HSC70 (heatshock cognate 70) alleles for the planktotrophic species, Littorina plena.

Table S5.1 Frequency distributions of the nuclear APN54(intron of aminopeptidase N) alleles among samples of the direct-developing species, Littorina sitkana.

Table S5.2 Frequency distributions of the nuclear DNA allelesamong samples of the direct-developing species, Littorina subro-tundata: (a) HSC70, and (b) APN54.

Table S5.3 Frequency distributions of the nuclear HSC70 allelesamong samples of the planktotrophic species, Littorina scutulata.

Table S5.4 Frequency distributions of the nuclear HSC70 allelesamong samples of the planktotrophic species, Littorina plena.

Fig. S1 Temporal changes in the frequencies of the mtDNA haplo-types and nuclear HSC70 alleles between the 1997 and 2007 samplesin L. scutulata: (a) mtDNA Cyt b, and (b) scnDNA HSC70.

Fig. S2 Temporal changes in the frequencies of the mtDNA haplo-types and nuclear HSC70 alleles between the 1997 and 2007 samplesin L. plena: (a) mtDNA Cyt b, and (b) scnDNA HSC70.

Please note: Wiley-Blackwell are not responsible for the content orfunctionality of any supporting materials supplied by the authors.Any queries (other than missing material) should be directed tothe corresponding author for the article.

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