Vol. 601: 153–166, 2018 MARINE ECOLOGY PROGRESS SERIES Published August 9 https://doi.org/10.3354/meps12648 Mar Ecol Prog Ser

OPENPEN ACCESSCCESS

Complex genetic structure revealed in the circum-Antarctic broadcast spawning sea urchin Sterechinus neumayeri

Karen J. Miller1,*, Helena P. Baird2, Jake van Oosterom3, Julie Mondon3, Catherine K. King2

1Australian Institute of Marine Science, UWA Oceans Institute, 35 Stirling Highway, Crawley, WA 6009, Australia 2Australian Antarctic Division, 203 Channel Highway, Kingston, TAS 7050, Australia 3Centre for Integrative Ecology, School of Life and Environmental Sciences, Deakin University, Geelong, VIC 3216, Australia

ABSTRACT: Patterns and mechanisms of gene flow and larval dispersal in the Antarctic marine environment are still poorly understood, despite the current threat of rapid climate change and the need for such information to inform conservation and management efforts. Studies on Antarctic brooding marine invertebrates have demonstrated limited connectivity, concurrent with life his- tory expectations; however, no equivalent data are available for broadcast spawning species for which we might expect a higher capacity for larval dispersal. Here, we have used microsatellite DNA markers and mitochondrial DNA sequence data to explore patterns of genetic structure and infer larval dispersal patterns across spatial scales of <500 m to 1400 km in the broadcast spawn- ing sea urchin Sterechinus neumayeri. We show genetic differentiation at small spatial scales (<1 km), but genetic homogeneity over moderate (1−25 km) and large spatial scales (1000 km), consistent with patterns described as chaotic genetic patchiness. Self-recruitment appears com- mon in S. neumayeri, and genotypes of larvae collected from the water column provide prelimi- nary evidence that the adult population structure is maintained through variability among larval cohorts. Genetic similarity at large spatial scales may represent evolutionary connectivity on a circum-Antarctic scale, and likely also reflects a history of shelf recolonisation after isolation in glacial refugia.

KEY WORDS: Gene flow · Larval dispersal · Migration · Chaotic genetic patchiness · Microsatellites · Echinoid

INTRODUCTION structure, while planktotrophic species with long- lived planktonic embryonic and larval phases Gene flow in the marine environment underpins achieve genetic homogeneity over large scales (see the maintenance of genetic diversity and resilience to Hunt 1993, Teske et al. 2007, Underwood et al. 2009, change, and has long been considered to reflect the Haye et al. 2014, Weber et al. 2015 for comparisons). dispersal potential determined by life history charac- However, studies that contradict this rule abound, teristics (Roberts 1997, Faurby & Barber 2012). and a paradigm shift is gaining momentum. In partic- Indeed, there is much empirical evidence supporting ular, broadcast-spawning species with long pelagic a correlation between the length of a pelagic larval larval phases often show surprising levels of genetic phase and the extent of genetic exchange between differentiation over small spatial scales (e.g. Taylor populations. Direct-developing lecithotrophic and & Hellberg 2003, Miller et al. 2009, Sá-Pinto et al. brooding species generally display high genetic 2012, Penant et al. 2013).

© The authors 2018. Open Access under Creative Commons by *Corresponding author: [email protected] Attribution Licence. Use, distribution and reproduction are un - restricted. Authors and original publication must be credited. Publisher: Inter-Research · www.int-res.com 154 Mar Ecol Prog Ser 601: 153–166, 2018

Several factors have been identified that may limit studies of larval genetic structure are needed (Bro- gene flow in benthic marine species with long quet et al. 2013). pelagic larval phases and high dispersal potential. The vast majority of research on larval dispersal Larval retention, localised adaptation, dispersal bar- and genetic connectivity patterns has focused on riers such as abyssal depths and convergence zones, temperate and tropical species (Hess et al. 1988, and the timing of reproductive events can all isolate McCartney et al. 2000, Lessios et al. 2001, Addison & populations (Reeb & Avise 1990, Palumbi 1994, Hart 2004, Duran et al. 2004, Waters & Roy 2004, Lessios et al. 1999, McCartney et al. 2000, Hunter & Banks et al. 2007, Yasuda et al. 2009, Kelly & Palumbi Halanych 2008, 2010, Miller & Ayre 2008, Thornhill 2010, Maltagliati et al. 2010). Despite being under et al. 2008, Calderon & Turon 2010, Kelly & Palumbi greater immediate threat from environmental 2010, Maltagliati et al. 2010, Hoffman et al. 2011, change (Peck 2005), Antarctic benthic fauna remain Ni et al. 2011). However, an increasing number of much less understood in this respect. The nature of broadcast-spawning species are found to be gen - Antarctic waters provides unique conditions that etically differentiated at the smallest spatial scale may influence genetic structure: extremely low and studied, with apparent connectivity over larger stable temperatures, a coastline spanning only a few scales (e.g. Hedgecock 1994, Hogan et al. 2010, Lar- degrees of latitude, and the presence of strong cir- son & Julian 1999). Such patterns, referred to as cumpolar currents. In combination, these factors chaotic genetic patchiness (Johnson & Black 1982), might be expected to homogenise populations; how- prove challenging to explain, yet are likely to be ever, the history of glacial cycles that have drastically found frequently as more studies focus at a fine spa- reduced available benthic habitat may have isolated tial resolution (e.g. Arnaud-Haond et al. 2008, Miller populations and reduced genetic diversity. That very et al. 2009). few studies of fine-scale genetic structure exist for Chaotic genetic patchiness encompasses the ca- Antarctic marine invertebrates limits our capacity to pacity for larval dispersal to homogenise populations incorporate small-scale patterns in management and over large scales, while temporal and spatial varia- planning (Féral 2002, Palumbi 2003, Palsbøll et al. tion in the availability and genetic composition of 2007). Of the few studies that do exist, most focus on larvae may still result in fine-scale genetic structure brooding species, which have no larval stage and (Johnson & Black 1982). Several pre-settlement therefore very low dispersal potential, and, unsur- mechanisms have been hypothesised to drive this prisingly, show evidence of fine genetic structure variation in larval recruits (see Hogan et al. 2010). (Hunter & Halanych 2010, Arango et al. 2011, Baird These include localised natural selection acting on et al. 2012, Ledoux et al. 2012). Studies of broadcast- larval cohorts, ‘sweepstake reproductive success’ spawning Antarctic benthic invertebrates with plank - (variability in reproductive success of source pop- tonic larvae have mainly focused on large-scale con- ulations), and collective dispersal of larval cohorts nectivity across major oceanographic barriers (e.g. from spatially/temporally distinct source populations. Thornhill et al. 2008). To our knowledge, only a Sweepstake reproductive success has perhaps re- single study has identified fine-scale population ceived the most attention (Hedgecock 1982, Hedge- structure in a broadcast-spawning Antarctic benthic cock & Pudovkin 2011) and predicts that large invertebrate, the mollusc Nacella concinna; however, variances in reproductive success occur due to the drivers of this structure remain unknown (Hoff- ‘sweepstakes’ where only a small number of indi- man et al. 2012). viduals synchronise reproduction with optimal oce - The Antarctic echinoid Sterechinus neumayeri is an anographic conditions necessary for successful re - ideal organism for testing the predictions of life cruitment. This results in a reduction in effective history characteristics on population genetic structure population size; and is accompanied by reduced in an Antarctic benthic marine broadcast spawner. genetic diversity in larval cohorts compared to adult This species is an abundant and dominant component populations (Hedgecock 1994, Hedgecock & Pudov- of the nearshore benthos, with a circum-Antarctic dis- kin 2011). Most processes leading to chaotic genetic tribution (Brey et al. 1995, Sahade et al. 1998), and is patchiness are contingent upon the persistence of well studied with regards to its environmental sensi- cohesive, genetically differentiated cohorts of larvae tivities (e.g. King & Riddle 2001, Lister et al. 2010, remaining aggregated in the water column. There Ericson et al. 2012, Byrne et al. 2013, Lister et al. 2015, is only limited empirical evidence of this to date Foo et al. 2016). It reproduces annually during the (Johnson et al. 1993, Riquet et al. 2017) as planktonic austral summer from November to De cember (Pearse larvae are notoriously difficult to collect, and more et al. 1991), and larvae spend approximately 4 mo in Miller et al.: Genetic differentiation in an Antarctic sea urchin 155

the water column before metamorphosis and settle- and were returned live to the laboratory for process- ment (Bosch et al. 1987, Brey et al. 1995). This ex- ing. All individuals were considered mature based on tended larval stage and development time likely re- the presence of sperm or eggs in gonad tissue, and flects their reduced metabolic rate in cold waters, as were 4−16 cm in test diameter. A small sample of well as providing a strategy for planktotrophic larvae gonad tissue was dissected from each individual and to exploit the highly seasonal planktonic food sources stored in 95% ethanol for DNA extraction and of Antarctic waters (Bosch et al. 1987, Brey et al. 1995, genetic analysis. Brockington et al. 2007). The larval phase of S. neu- Echinoplutei larvae were collected from plankton mayeri confers a high dispersal potential compared tows in the Vestfold Hills region during the 2009/ to related broadcast-spawning temperate and tropi- 2010 summer field season at 2 sampling locations cal echinoids, in which larvae remain in the water col- approximately 1 km apart (Fig. 1). Larvae were col- umn for only days or weeks. In addition, the presence lected from 3 plankton tows: 2 conducted near Kazak of the Antarctic Circumpolar Current (ACC) poten- Island on 4 February 2010 and 8 February 2010, and tially provides a mechanism for westward offshore 1 near Hawker Island on 9 February 2010 (Fig. 1); larval transport, which encompasses the entire conti- additional plankton tows in the region yielded no nent (Nowlin & Klinck 1986). Previous studies at the echinoplutei. All tows were carried out within 0.5 m phylogenetic level based on mitochondrial DNA sug- of the water’s surface, and were continued for gest that S. neumayeri may sustain considerable con- 20−50 m, using a 200 µm mesh net with a circular nectivity on a circum-Antarctic scale (Díaz et al. opening of 0.5 m and a 500 ml cod end. Plankton that 2011), yet have reduced genetic diversity due to his- accumulated in the cod end and on the internal net torical population reductions during glacial cycles surface was rinsed into a collection jar. Samples were (González-Wevar et al. 2012). fixed with 95% ethanol and sorted under a dissecting In the present study, we used microsatellite and microscope (10×). As S. neumayeri is the only species mitochondrial DNA markers to provide a compre- of regular echinoid found in shallow nearshore wa - hensive analysis of genetic structure and connectiv- ters of Antarctica (Dell et al. 1972), all echinoplutei ity at small and large scales in S. neumayeri from larvae found in samples were assumed to be S. neu- East Antarctica. Additionally, we determined genetic mayeri and were removed and stored individually in structure of larval cohorts to explore the potential 95% ethanol. All larvae collected were 4- to 8-armed role of chaotic genetic patchiness in structuring pluteus stages, with estimated age between 40 and Antarctic benthic communities. 100 d, and likely to have spent 1–3 mo dispersing in the water column prior to collection.

MATERIALS AND METHODS DNA extraction and genotyping Sample collection DNA was extracted from gonad tissue using Qia- Samples of adult Sterechinus neumayeri were col- gen DNeasy Blood and Tissue extraction kits follow- lected in East Antarctica during the 2008/2009 sum- ing the manufacturer’s protocols. Larval DNA extrac- mer field season at Casey station in the Windmill tions were performed using whole echinoplutei and Islands (66° S, 110° E) and the 2009/2010 summer Qiagen QIAamp DNA Micro extraction kits as per field season at Davis station in the Vestfold Hills the manufacturer’s protocol. Genomic DNA was (68° S, 78° E; Fig. 1). In order to partition microsatel- quantified using a Nanodrop 8000 Spectrophotome- lite variation into different spatial scales to infer pat- ter (Thermo Scientific). terns of larval dispersal, a hierarchical sampling To assess genetic patterns at the regional scale (i.e. design was used. Region represented the largest between the Windmill Islands and Vestfold Hills), we spatial scale, between the Windmill Islands and Vest- sequenced the mitochondrial gene regions cyto- fold Hills, which are separated by approximately chrome oxidase sub-unit 1 (CO1) and ribosomal sub- 1400 km. Sampling within the Windmill Islands was unit 16S from a sub-set of the adult samples from from 2 locations 9 km apart and within the Vestfold each region using urchin-specific primers and uni- Hills from 5 locations separated by 5−30 km (Fig. 1). versal primers, respectively (Table S1 in the supple- Within each location, 25−50 individuals were col- ment at www-int-res.com/articles/suppl/m601p153_ lected from up to 3 sites approximately 500 m apart, supp.pdf). Bidirectional sequencing was performed by dip netting, snorkeling, or surface-supply divers, by the Australian Genome Research Facility (Bris- 156 Mar Ecol Prog Ser 601: 153–166, 2018

Fig. 1. Sites in the Vestfold Hills and Windmill Islands regions of East Antarctica where Sterechinus neumayeri were collected. Red markers: adult collections; blue markers: echinoplutei collections. N: number of individuals genotyped from up to 3 sites in each location. Grey shading in left panel: sea ice

bane) on an Applied Biosystems 3730 DNA Analyzer Ten microgrammes of genomic DNA was analysed on automated sequencer, using the same primers speci- a Roche 454 GS-FLX platform (Roche) using a 1/16th fied for PCR amplification. Sequence chromatograms run and the GS FLX titanium reagents. A total of were manually inspected to confirm quality, and 38 053 reads, with an average length of 294 bp, were contiguous sequences were created using MEGA 4.0 completed. Fragments were screened for micro - (Tamura et al. 2007), aligned using the ClustalW satellite inserts; a total of 312 suitable candidates algorithm, and truncated to a consistent length for were discovered. Primers were designed for 24 of comparison. The final data comprised 813 bp of CO1 these, which were then tested for polymorphism. (72% of inter-primer region) and 294 bp of 16S (51% Eleven loci were deemed suitable for this study and of inter primer region). BLAST searches were per- were amplified in 4 multiplex PCRs (Table S2). PCRs formed to confirm that DNA sequence results were completed in a total volume of 20 µl using matched with published sequences of S. neumayeri. Qiagen Multiplex PCR kits containing a final concen- Regional-level and fine-scale genetic structure in S. tration of 3 mM MgCl, 100−300 ηg of template DNA neumayeri adults and larvae were assessed using and one unit HotStar Taq DNA Polymerase. Primer microsatellite DNA markers. Microsatellite loci were concentrations were varied between multiplex reac- developed by Ecogenics GmbH (Zurich, Switzerland) tions to maintain product concentrations within read- based on 15 individuals utilising the high-throughput able limits of the sequencer. Analysis of PCR products genomic sequencing approach (Abdelkrim et al. 2009). was carried out on a CEQ 8000 Genetic Analysis Sys- Miller et al.: Genetic differentiation in an Antarctic sea urchin 157

tem (Beckman Coulter) automated sequencer by cap- Genetic differentiation among adult populations of illary separation, and alleles were scored as fragment S. neumayeri was explored using the Stepwise Muta- size using CEQ 8000 Genetic Analysis System soft- tion Model (RST; Slatkin 1985b) and the Infinite Allele ware (ver. 8.0). Each fragment was visually checked Model (FST; Kimura & Crow 1964) using SPAGeDi 1.4 for scoring errors and stutter peaks. Micro-checker (Hardy & Vekemans 2002), with 10 000 permutations 2.2.3 (Van Oosterhout et al. 2004) was used to check to assess significance. As high within-population for stutter bands and the presence of null alleles. variability of microsatellites can reduce the magni-

Loci were also tested for linkage disequilibrium in tude of FST (Hedrick 2005), the standardised measure Genepop 4.0.10 (Raymond & Rousset 1995), with the of differentiation, F’ST, was also calculated in critical level p < 0.05 adjusted for multiple compar- Genalex 6.5 (Peakall & Smouse 2012). A further isons, using the sequential Bonferroni procedure. measure of differentiation, Jost’s D, was calculated, as it may be more robust to the high heterozygote frequencies commonly found in microsatellites (Jost Statistical analysis 2008, Ryman & Leimar 2009, Whitlock 2011). Jost’s

unbiased D(DEST) was calculated in R using the We calculated FST and used analysis of molecular package DEMEtics (Gerlach et al. 2010) with 10 000 variance (AMOVA) in ARLEQUIN 3.5 (Excoffier & bootstrap resampling steps. To determine which pop- Lischer 2010) to test the hypothesis of no genetic ulations were genetically distinct from one another,

subdivision between regions based on mitochondrial pairwise FST between all sites was calculated in DNA haplotypes. Tests for departures of FST from Genalex using 10 000 permutations to assess sig- those expected under panmixis (i.e. FST = 0) were nificance. based on 10 000 permutations. Tajima’s D statistics In order to partition genetic variation among were not calculated as they would not have been regions, among locations within regions, and among meaningful given the extremely low variability of the sites within locations, a hierarchical AMOVA was sequence data (see Results). performed in R using the package Hierfstat (Goudet From the microsatellite genotypes, we calculated 2005). Boyd Island was excluded from this analysis as measures of genetic diversity including observed there was only one site sampled at this location. For heterozygosity (HO), expected heterozygosity (HE), each hierarchical level, 100 000 permutations were private alleles (PA) and allelic richness (AR) for adults used to determine significant departures from pan- from each site using Fstat 2.9.3.2 (Goudet 1995). Per- mixis. mutation tests were performed in Fstat to determine To determine whether genetic differentiation fol- whether the 3 diversity measures were significantly lowed an isolation by distance (IBD) pattern, a corre- different between the Windmill Islands and Vestfold lation between geographic distance and linearised Hills regions (10 000 permutations, 2-tailed p-value). genetic distance was assessed using Mantel tests im- To identify departures from Hardy-Weinberg equi- plemented in Genepop, with 100 000 permutations. librium (HWE), exact tests were carried out using Distance was represented by the shortest water- Gene pop, with 10 000 dememorization steps and 500 based route between sites; high-resolution data on Markov chains to improve standard error to below local ocean currents are unfortunately not available the 0.01 threshold. The fixation index (FIS) was used for the area. Mantel tests were performed within re- to determine the nature of the departures from HWE, gions to determine whether IBD was present at small where FIS > 0 indicates heterozygote deficiencies and scales, and across the entire data set to explore IBD FIS < 0 indicates heterozygote excess. Significant het- at a large scale. erozygote deficiencies were attributed to null alleles In order to estimate gene flow, the number of by Micro-checker at 8 out of the 11 loci (Stenum 03, migrants per generation (Nem) was calculated using 08, 06, 18, 04, 22, 19 and 21), and the Oosterhout cor- private alleles following the method of Slatkin rection algorithm was used to generate corrected (1985a) in Genepop. To explore migration within and allele frequencies for subsequent population-level between regions, Geneclass 2 (Piry et al. 2004) was comparisons. Loci were also tested for evidence of used to detect first generation migrants (F0) present selection in Lositan (Antao et al. 2008) using 20 000 in each site sampled. To account for the possibility of simulations and the recommended ‘neutral mean FST’ non-sampled source populations, migration detec- option (Hemond & Wilbur 2011). Selection was tion was calculated using the likelihood method assessed on the whole adult data set, as well as on L_home and an exclusion probability of 0.01 (Paetkau the 2 regional data sets separately. et al. 2004). The threshold for probability computa- 158 Mar Ecol Prog Ser 601: 153–166, 2018

tions was set to 0.05 with 10 000 simulated indi - 5 from East Antarctica; however, we were unable to viduals. Individuals identified as F0 migrants were compare these sequences to our own as they are not removed from the data set and re-assigned following publically available. the frequency-based method of Paetkau et al. (2004) The 16S sequences were slightly more variable with 100 000 simulated individuals and a type 1 error than CO1, with 4 haplotypes across 24 individuals rate of 0.05. from both regions, and 3 polymorphic sites. The most In order to identify underlying genetic structure, common 16S haplotype (represented by 21 of the 24 the program STRUCTURE 2.3.3 was used to deter- individuals) has also been recorded from the Antarc- mine the number of genetic populations within the tic Peninsula (GenBank accession HM467250.1) and sample, and whether these populations related to the Ross Sea (GenBank accession GU226984.1). geographical sampling locations (Pritchard et al. Unsurprisingly, there was no significant genetic dif- 2000, Falush et al. 2003, 2007, Hubisz et al. 2009). ference between the Windmill Islands and Vestfold Twenty iterations for a K-value of 1−20 were per- Hills regions based on either the CO1 or the 16S formed with a burn-in period of 50 000 and 500 000 sequence data (FST = 0, p = 1.00 and FST = 0.071, p = Markov chain Monte Carlo steps. Likelihood esti- 0.483, respectively). All unique haplotypes gener- mates of K-values were generated in Structure Har- ated in this study are available on GenBank (acces- vester (Earl & vonHoldt 2011) using the delta K sion MH669388–MH669393). method of Evanno et al. (2005). Measures of genetic diversity and HWE in larval samples were calculated as described for the adult Genetic diversity and differentiation inferred from data set. To test for significant differences in diversity microsatellite data measures between larval samples and adult popula- tions from the Vestfold Hills region, permutation tests In total, 545 S. neumayeri adults from East Antarc- for AR, HO and HE were implemented in Fstat 2.9.3.2. tica were genotyped. There was no evidence of link- Genetic differentiation statistics FST, RST, F’ST and age disequilibrium using the default parameters in Jost’s DEST were calculated as for adults, both glob- any of the 11 loci tested. The total number of alleles ally and pairwise between samples. We used assign- found at each locus was moderate, ranging from 6 to ment tests in GeneClass2 to determine the likely 19 with an average of 10 alleles per locus (Table S2). population of origin of larvae, assigned as individuals Nineteen private alleles were found across all popu- and as sampling groups, using the methods as out- lations. Genetic diversity was not significantly differ- lined above for adults. We also assessed the pairwise ent between regions (for comparisons of HO, HE and relatedness among larvae using the Wang estimator AR, p = 0.059, p = 0.162 and p = 0.814, respectively; in COANCESTRY V1.0.1.8 (Wang 2011), and tested Table S3). for differences in the relatedness within and among Populations were largely in HWE, with only 51 of larval samples for any evidence of kin-aggregated 220 locus-by-site tests showing departures from dispersal. HWE (Table S4). Departures from HWE were spread over nearly all sites and loci, yet only one site (Trig- well Island 3) showed departures at more than half RESULTS of the loci tested. After Bonferroni correction, 42 comparisons remained significant, and of these, the Large-scale patterns of genetic differentiation vast majority (40) represented heterozygote deficits. inferred from mitochondrial DNA These were largely attributed to the presence of null alleles and the data were adjusted accordingly prior Across 24 individuals and 2 regions in East Antarc- to further analysis. tica there were only 2 CO1 haplotypes with a single In contrast to results from mitochondrial DNA polymorphic site representing a synonymous substi- analysis, we found significant genetic differentiation tution. The common CO1 haplotype from both in adult S. neumayeri among sites based on micro- regions (represented by 23 of 24 individuals) has satellite data (FST = 0.010, RST = 0.016, DEST = 0.025, been recorded from the Antarctic Peninsula (Gen- F’ST = 0.024; p < 0.001 for all; Table 1). There was no Bank accession HM467227.1) and several locations evidence of selection acting on any of the loci when within the Ross Sea (GenBank accession GU227089.1, the entire data set was tested, yet balancing selection KF21457.1). Díaz et al. (2011) reported a total of 21 was detected at Stenum 13 and Stenum 15 (at a sig- CO1 haplotypes in Sterechinus neumayeri, including nificance level of p < 0.01) within the Vestfold Hills Miller et al.: Genetic differentiation in an Antarctic sea urchin 159

Table 1. Genetic differentiation at each of 11 microsatellite than among sites in the Vestfold Hills, yet values for loci among all adult populations of the Antarctic echinoid both regions were considered equally significant Sterechinus neumayeri. These results are from the data set after adjusting for null alleles. Negative values are con- (Windmill Islands: FST = 0.013, DEST = 0.019, p < 0.001; verted to 0. Significance: *p ≤ 0.05, **p ≤ 0.01,***p ≤ 0.001. Vestfold Hills: FST = 0.005, DEST = 0.009, p < 0.001). FST: differentiation based on the Infinite Allele model; When the 2 loci suspected to be under balancing RST: differentiation based on the Stepwise Mutation Model; selection were removed from the data set, values D : Jost’s unbiased D; F’ : standardised measure of EST ST were more similar within the 2 regions (Windmill differentiation Islands: FST = 0.009, DEST = 0.018, p < 0.001; Vestfold Hills: FST = 0.007, DEST = 0.012, p < 0.001). Locus FST RST DEST F ’ST

Stenum 03 0.013*** 0.002 0.046*** 0.052** Stenum 08 0.004 0.033*** 0.008 0.011 Gene flow in S. neumayeri Stenum 11 0.007 0.014* 0.001 0.006 Stenum 06 0.006 0.005 0.035 0.024 Gene flow in S. neumayeri appears limited. Be - Stenum 13 0.005 0.009 0.006 0.011 Stenum 18 0.020*** 0.021** 0.033*** 0.050*** tween 72 and 88% of individuals were assigned to Stenum 04 0.007** 0.016* 0.068** 0.034*** their natal populations (Table 2) although the overall Stenum 15 0 0 0 0 Nem of 6.1 calculated from private alleles suggests Stenum 22 0.008* 0.016* 0.015* 0.013* sufficient gene flow to reduce the effects of inbreed- Stenum 19 0.017*** 0.023** 0.046*** 0.055*** Stenum 21 0.018*** 0.014 0.016*** 0.022*** ing associated with local recruitment (inbreeding Total 0.010*** 0.016*** 0.025*** 0.024*** connectivity, Nem > 1) but not to counteract the diver- gence of populations through genetic drift (drift con-

nectivity, Nem > 10; Lowe & Allendorf 2010). Within region alone. Hierarchical AMOVA revealed that dif- the Vestfold Hills region, 20% of individuals were ferentiation was not significant between the 2 identified as first generation migrants, as were 22% regions (FST = 0.005, p = 0.169) nor among locations of individuals within the Windmill Islands region within regions (FST = 0, p = 0.470), but was significant (Table 2). The assigned source populations for these among sites within locations (FST = 0.008, p < 0.001), migrants indicates that gene flow within the Vestfold i.e. the smallest spatial scale (Table S7). This result Hills region appears to occur more frequently was the same whether the raw data set or the data set between sites in different locations (separated by adjusted for null alleles was tested. However, given moderate distances of 1−25 km) than between sites that there were only 2 regions at the highest level, within locations (at small distances of 0.5−1 km), fur- the lack of significant differences between regions ther supporting the hierarchical genetic differen- may be linked to low statistical power, and should be tiation results. Only 7.5% of the total identified interpreted with caution. There was no isolation by migrants at Vestfold Hills were assigned to a source distance among locations across the entire data set population from the Windmill Islands; however, (R2 = 0.304, p = 0.071), nor among sites within each migrants within the Windmill Islands region were region (Windmill Islands R2 = 0.062, p = 0.596; Vest- assigned almost exclusively to Vestfold Hills popula- fold Hills R2 = 0.023; p = 0.825). The absence of large- tions (Table 2). scale population structure within the entire data set was also evident in the STRUCTURE analysis, which indicated K = 1 as the most likely number of popula- The relationship between larval and adult tions (based on log likelihood values) and K = 2 based populations of S. neumayeri on delta K (noting the Evanno method cannot resolve K = 1). However, there was no relationship between A total of 26 echinoplutei larvae from 3 separate population structure and geographic location, with sampling events were genotyped. There was signifi- all populations showing genetic admixture (Fig. S1). cant genetic differentiation between the 3 larval Within regions, pairwise population estimates of samples, although sample size was low. Populations

FST showed that 80% of sites within the Windmill from Kazak Island 2 and Hawker Island were signifi- Islands, and only 30% of sites in the Vestfold Hills, cantly differentiated based both on FST and DEST, and were significantly differentiated (Table S5). This pat- Kazak Island 1 and 2 (the same site sampled 4 days tern was also evident when comparing pairwise DEST apart) were significantly differentiated based on DEST values (Table S5).. Values of FST and DEST were gen- alone (Table 3). Since DEST is generally considered erally higher among sites in the Windmill Islands a superior estimation of genetic differentiation for 160 Mar Ecol Prog Ser 601: 153–166, 2018

Table 2. Assignment of F0 migrants to source populations of the Antarctic echinoid Sterechinus neumayeri. Values represent percentage of individuals collected from locations, assigned to a source population, and unassigned. Values on the diagonal (in bold) represent the proportion of the population that are not F0 migrants. Italicised values represent first-generation migra- tion between regions. Locations in the Vestfold Hills region are: Old Wallow (OW), Boyd Island (BO), Ellis Fjord (EL), Trigwell Island (TR), and Zappit Point (ZP). Locations in the Windmill Islands region are Browning Peninsula (BP) and Sparkes Bay (SB)

Location Assigned origin Not collected Vestfold Hills Region Windmill Islands Region assigned OW1 OW2 BO1 EL1 EL2 EL3 TR1 TR2 TR3 ZP1 ZP2 ZP3 BP1 BP2 BP3 SB1 SB2

OW1 76.67 3.33 3.33 6.67 10 OW2 77.14 2.86 2.86 17.14 BO1 82.14 3.57 14.29 EL1 73.33 3.33 3.33 3.33 16.67 EL2 78.57 21.43 EL3 4.17 4.17 83.33 4.17 4.17 0 TR1 3.57 78.57 3.57 3.57 10.71 TR2 3.33 83.33 3.33 3.33 6.67 TR3 2.13 2.13 78.72 2.13 2.13 12.77 ZP1 74.29 25.71 ZP2 2.94 2.94 82.35 11.76 ZP3 88.24 11.76 BP1 3.85 3.85 76.92 15.38 BP2 2.86 2.86 2.86 80 11.43 BP3 2.03 3.03 81.82 12.12 SB1 3.13 3.13 3.13 71.88 18.75 SB2 2.78 2.78 2.78 2.78 2.78 77.78 8.33

Table 3. Pairwise genetic differentiation (as FST, DEST and and 0.364, respectively; diversity values for larvae F’ST) between larval cohorts of the Antarctic echinoid are provided in Table S6) but observed heterozygos- Sterechinus neumayeri sampled in 2010 from Hawker Island ity was higher in larvae than in adults (adults H = on 9 February (n = 13), Kazak Island (1) on 4 February (n = O 7), and again from Kazak Island (2) on 8 February (n = 6). 0.429, larvae HO = 0.467, p < 0.01). The relatedness Significance: *p ≤ 0.05, **p ≤ 0.01 among larvae within a single plankton tow (mean = −0.0779) was not significantly different to the relat-

FST DEST F’ST edness among adults within a site (mean = −0.0682; Fig. S2a). Hawker Island Kazak Island 1 0 0 0 Of the 26 larvae genotyped, only 14 could be Hawker Island Kazak Island 2 0.063** 0.133** 0.140 assigned unambiguously to a single population of Kazak Island 1 Kazak Island 2 0.038 0.138* 0.096 origin, with 5 originating from Ellis Fjord Site 1, 3 from Trigwell Island Site 1, 3 from Zappit Point Site 1, 2 from Boyd Island and 1 from Zappit Point Site 2 polymorphic markers (Gerlach et al. 2010), this tem- (Table S8). The remaining larvae were assigned with poral differentiation is likely to reflect real differ- equally high probability (80−90%) to multiple popu- ences in larval composition, with FST more likely to lations, providing little insight into larval dispersal be affected by low sample size. F’ST values were also processes. However, when larvae were assigned as generally in accordance with DEST (Table 3). groups (based on plankton tow), the Hawker Island There were significant genetic differences be - larvae were highly likely (61%) to have originated tween the Vestfold Hills larvae and adult populations from Ellis Fjord Site 1, Kazak Island 1 larvae from

(AMOVA, FST = 0.148, p = 0.001) and pairwise com- Zappit Point Site 1 (99.2% likelihood), and Kazak parisons indicated that this was the case for all Island 2 larvae from Zappit Point Site 2 (99.9% likeli- adult−larval comparisons (FST = 0.080−0.150, p = hood). Larvae within a sampling group were also 0.010; DEST = 0.181−0.336, p = 0.010), although the more closely related to each other (mean relatedness small samples sizes preclude major inference from = −0.0673) than to larvae from other groups (mean these results. Genetic diversity was not significantly relatedness = −0.1434; Fig. S2b), although notably different between larvae and adults at Vestfold Hills these relatedness values are negative, indicating

(for comparisons of HE, HO and AR, p = 0.962, 0.203 larvae are not close kin. Miller et al.: Genetic differentiation in an Antarctic sea urchin 161

DISCUSSION The numerous underlying mechanisms proposed for this pattern, however, often lack empirical evidence. The Antarctic echinoid Sterechinus neumayeri is Broquet et al. (2013) suggested that the genetic struc- characterised by fine-scale population structure. This ture of larvae be explored to tease out factors such as is unexpected given its planktotrophic development sweepstake reproductive success in driving chaotic and larval dispersal period of up to 4 mo. Sites sepa- genetic patchiness. Here, we have provided prelimi- rated by <1 km within both the Windmill Islands and nary evidence that larval cohorts of S. neumayeri do Vestfold Hills regions showed low but highly signifi- not have depressed genetic diversity when compared cant genetic differentiation, and there was evidence to adult populations, as might be expected through that populations are largely self-recruiting. How- sweepstakes reproductive success (Li & Hedgecock ever, despite small-scale heterogeneity (at scales of 1998), and larval groups do not represent aggrega- <1 km), populations from locations within Windmill tions of kin; both factors providing little support for Islands and Vestfold Hills separated by tens of kilo- sweepstakes reproductive success as the driver of the metres showed no significant genetic differentiation, chaotic genetic structure in this species (but noting consistent with a pattern of chaotic genetic patchi- the limited inference from our small sample size). ness (Johnson & Black 1982). Genetic differentiation However, there may be other selective or stochastic found among collections of S. neumayeri larvae, and processes that occur in late-stage larvae and prior to between larvae and adults, is also consistent with settlement that we have not been able to examine models such as chaotic genetic patchiness. We found here, and, notably, different processes may affect lar- similar levels of genetic diversity in adults and larvae val success among years, which we are unable to and no evidence of kin aggregation in larvae, a test, as we only sampled in a single year. There is pattern that would not be expected if sweepstakes generally limited support for sweepstakes reproduc- reproductive success was leading to chaotic genetic tive success in studies of temperate echinoids, with patchiness (Hedgecock & Pudovkin 2011). This sug- similar levels of genetic diversity found among differ- gests that other mechanisms are driving this patchi- ent age classes (e.g. Paracentrotus lividus: Calderon ness such as collective dispersal of larvae, and pre- or & Turon 2010, Calderon et al. 2012; Strongylocentro- post-settlement selection (Eldon et al. 2016). Genetic tus purpuratus: Flowers et al. 2002 − all based on similarity across regional scales (1000 km) based juvenile data not larvae), and also in a recent study of both on microsatellite and mitochondrial DNA data larval genetic diversity in green shore crabs (Corn- may reflect occasional long-distance larval transport, well et al. 2016). low levels of drift in isolated populations, and/or his- We have also shown some evidence that larvae of torical signatures. The latter is apparent in numerous S. neumayeri collected at the same location 4 d apart Antarctic benthic invertebrates and may indicate iso- and at different locations 1 d apart are genetically lation in glacial refugia during the last glacial maxi- differentiated, although sample sizes were small and mum, followed by circum-Antarctic recolonisation were from only one reproductive season, limiting (see Allcock & Strugnell 2012, Carrea et al. 2016). strong inference. This suggests that differences in the genetic composition of settling larvae may drive patterns of chaotic genetic patchiness in S. neumay- Fine-scale structure despite high eri, although we cannot completely rule out the role dispersal potential of other mechanisms including pre- or post-settle- ment selection. The concept of collective dispersal of Despite possessing a long pelagic larval phase, S. larvae in the water column has been demonstrated in neumayeri populations are genetically differentiated other marine organisms (lobster: Iacchei et al. 2013; over small distances (<1 km) with a high degree of fish: Selwyn et al. 2016; barnacles: Veliz et al. 2006; natal retention (up to 88%) and no signal of isolation gastropods: Riquet et al. 2017) and predicted for sea by distance. Similarly, unexpected genetic structure urchins (e.g. Moberg & Burton 2000), and is hypo - with greater differentiation between neighboring thesised to reflect spatial and temporal variation in than between distant populations has been found in the oceanographic processes that transport larvae a wide range of other marine taxa with high dispersal (Selkoe et al. 2006). That the larval groups of S. neu- potential (e.g. crab: Cornwell et al. 2016; damselfish: mayeri had similar levels of within-population relat- Hogan et al. 2010; lobster: Iacchei et al. 2013; kelp edness to that observed in adult populations, but bass: Gosling & Wilkins 1985, Selkoe et al. 2006, were more related within their larval group than Hogan et al. 2010; marine goby: Selwyn et al. 2016). between larval groups, supports the concept of col- 162 Mar Ecol Prog Ser 601: 153–166, 2018

lective dispersal of larvae spawned within a popula- neumayeri may also be related to the limited move- tion leading to chaotic genetic patchiness. ment and narrow habitat ranges of adults (e.g. Inter-annual variation in oceanic currents around Dumont et al. 2006). Antarctica is well established (White & Peterson 1996), and inter-annual variability in the recruitment success of S. neumayeri has been documented (Brey Large-scale homogeneity et al. 1995, Bowden et al. 2009), but the high degree of self-recruitment evident in this study suggests that In contrast to the fine-scale structure among sites in localised currents may facilitate the retention of lar- S. neumayeri, populations are not significantly differ- vae in natal populations (see Sponaugle et al. 2002). entiated either at the location or regional scale; Furthermore, the fact that the larval populations indeed, the hierarchical AMOVA showed levels of were genetically differentiated from adults, noting FST at the largest scale to be lower than that at the that no adults were sampled in the immediate vicin- smallest within-site scale, contrary to expectations ity of larval collections, is also in keeping with the under a model of isolation by distance. Microsatellite pattern of local recruitment. It is interesting that the variation generally reflects contemporary processes larvae collected from Hawker Island were assigned (Selkoe & Toonen 2006), which implies that larval to Ellis Fjord, the most proximal adult population, dispersal may be occurring between the Windmill although larvae collected at Kazak Island were Islands and Vestfold Hills regions. This is counter- assigned to Zappit Point, the most distant adult pop- intuitive given the high degree of natal retention and ulation. Notably, the collection point of larvae in the small-scale structure highlighted above. However, water column may be very different to the final set- only very low levels of migration (i.e. 1 to 10 migrants tlement site after 4 mo in the plankton, and hydrolog- per generation) are necessary to prevent differentia- ical data at fine spatial scales that might inform our tion through genetic drift (Mills & Allendorf 1996) understanding of fine-scale dispersal processes is yet and our assignment tests suggest a small percentage to be generated for nearshore East Antarctica. of sea urchins in the Windmill Islands may have orig- Larval behaviour of S. neumayeri is poorly under- inated from the Vestfold Hills. This is in accordance stood but may also be important in shaping adult with the direction of the ACC and the 4 mo larval population structure. Larval stages of many fish and pelagic phase of S. neumayeri. In addition, iceberg some invertebrate species display the ability to drift as a surrogate for current flow has shown a detect and respond to environmental gradients, potential mechanism for the transport of larvae from actively influencing dispersal (Kingsford et al. 2002, the nearshore via re-circulation from the Antarctic Paris & Cowen 2004). A recent study on the echinoid Coastal Current out to the ACC (Aoki et al. 2010). Strongylocentrotus droebachiensis showed that lar- This would provide a means of easterly passive trans- vae have the ability to control buoyancy and position port of larvae at speeds of at least 0.2 m s−1 (Hofmann in the water column based on current speed 1985), facilitating the 1400 km journey between the (Sameoto et al. 2010). The ability to detect and Vestfold Hills and the Windmill Islands. Contempo- respond to such environmental gradients has not rary larval dispersal would also explain the genetic been shown for S. neumayeri larvae; however, it may similarity among regions revealed in the mitochon - provide a mechanism for cohorts to disperse and set- drial DNA data. tle as a group, leading to the fine-scale structure Equally plausible, however, is that populations in observed in adults. Of interest is that Bowden et al. the Vestfold Hills and Windmill Islands are isolated, (2009) found high densities of S. neumayeri larvae but there are only low levels of genetic drift or weak (~80 larvae/5 m3) close to the seabed and in Novem- selection such that the populations have not ber, whereas we sampled at the surface in February diverged. In the absence of contemporary gene flow, and only found ~4 larvae/5 m3. This suggests that the presence of identical mitochondrial haplotypes at many larvae may actually be retained close to or on the Windmill Islands and Vestfold Hills is likely to the seabed, with only a few larvae dispersing in the represent historical patterns. The observation of low water column. These behavioural observations may diversity and a dominant, widespread haplotype with help explain the high levels of self-recruitment indi- one or more closely related, rare haplotypes is a com- cated by the adult genetic data, which appears con- mon phenomenon in Antarctic marine benthic inver- trary to the inference of dispersal from the assign- tebrates (see Allcock & Strugnell 2012). It is thought ment of larvae found in the water column to distant to reflect founder effects from the wide recolonisa- populations. The small-scale genetic structure of S. tion of the Antarctic shelf by these species after their Miller et al.: Genetic differentiation in an Antarctic sea urchin 163

extensive population reduction and isolation in ice- The cyclonic circulation in the Australian−Antarctic free refugia during the last glacial maximum (see basin simulated by an eddy-resolving general circulation model. Ocean Dyn 60: 743−757 Thatje et al. 2005). Our results therefore concur with Arango CP, Soler-Membrives A, Miller KJ (2011) Genetic those of studies from the Ross Sea and Antarctic differentiation in the circum—Antarctic sea spider Peninsula (Díaz et al. 2011, González-Wevar et al. Nymphon australe (Pycnogonida; Nymphonidae). Deep 2012) that indicate that S. neumayeri recolonised the Sea Res II 58:212−219 Arnaud-Haond S, Vonau V, Rouxel C, Bonhomme F, Prou J, shelf from glacial refugia to achieve its current Goyard E, Boudry P (2008) Genetic structure at different circum-Antarctic distribution, and this is similar to spatial scales in the pearl oyster (Pinctada margaritifera patterns found in other echinoids (Carrea et al. 2016). cumingii) in French Polynesian lagoons: beware of sam- In summary, our study provides one of the first pling strategy and genetic patchiness. Mar Biol 155: examples of fine-scale genetic structure in a broad- 147−157 Aronson RB, Thatje S, McClintock JB, Hughes KA (2011) cast-spawning Antarctic benthic invertebrate, and Anthropogenic impacts on marine ecosystems in Antarc- lends support to a growing paradigm shift away from tica. Ann NY Acad Sci 1223: 82−107 the assumption that the duration of the planktonic Baird HP, Miller KJ, Stark JS (2012) Genetic population larval phase is a direct predictor of gene flow in mar- structure in the Antarctic benthos: insights from the widespread amphipod, Orchomenella franklini. PLOS ine organisms. Based on our results, we propose that, ONE 7: e34363 despite the potential for long-distance larval disper- Banks SC, Piggott MP, Williamson JE, Bové U, Holbrook NJ, sal in S. neumayeri, most larvae recruit locally and Beheregaray LB (2007) Oceanic variability and coastal long-distance dispersal is rare. Genetic similarities at topography shape genetic structure in a long-dispersing the regional scale reinforce the importance of glacial sea urchin. Ecology 88: 3055−3064 Bosch I, Beauchamp KA, Steele ME, Pearse JS (1987) Devel- refugia in shaping modern-day populations. Given opment, metamorphosis, and seasonal abundance of the importance of maintaining gene flow in manag- embryos and larvae of the Antarctic sea urchin Sterechi- ing marine populations, particularly in Antarctica, a nus neumayeri. Biol Bull 173:126−135 region currently threatened by particularly rapid cli- Bowden DA, Clarke A, Peck LS (2009) Seasonal variation in the diversity and abundance of pelagic larvae of Antarc- mate change (IPCC 2001, 2007, Aronson et al. 2011), tic marine invertebrates. Mar Biol 156: 2033−2047 it is vital that we develop a more complete under- Brey T, Pearse J, Basch L, McClintock JB, Slattery M (1995) standing of the processes governing genetic diversity Growth and production of Sterechinus neumayeri (Echi- and gene flow in marine fauna. noidea: Echinodermata) in McMurdo Sound, Antarctica. Mar Biol 124: 279−292 Brockington S, Peck LS, Tyler PA (2007) Gametogenesis and Acknowledgements. This study was funded by the Aus- gonad mass cycles in the common circumpolar Antarctic tralian Government through an Australian Antarctic Science echinoid Sterechinus neumayeri. Mar Ecol Prog Ser 330: Grant (AAS 3051). We thank the Australian Antarctic Divi- 139−147 sion for logistical and operational support for the project, Broquet T, Viard F, Yearsley JM (2013) Genetic drift and col- and the Casey 08/09 and Davis 09/10 marine teams, espe- lective dispersal can result in chaotic genetic patchiness. cially Jonny Stark, Glenn Johnstone, Chris Gillies, Ben Evolution 67: 1660−1675 Coombe, Simon Reeves, Patti Virtue, Natalie Moltschani- Byrne M, Ho MA, Koleits L, Price C, and others (2013) Vul- wskyj and Bianca Sfiligoj. We also thank Adam Smolenski nerability of the calcifying larval stage of the Antarctic (University of Tasmania) for support with the molecular lab- sea urchin Sterechinus neumayeri to near-future ocean oratory analysis. acidification and warming. Glob Chang Biol 19: 2264−2275 Calderón I, Turon X (2010) Temporal genetic variability in LITERATURE CITED the Mediterranean common sea urchin Paracentrotus lividus. Mar Ecol Prog Ser 408: 149−159 Abdelkrim J, Robertson BC, Stanton JAL, Gemmell NJ Calderón I, Pita L, Brusciotti S, Palacín C, Turon X (2012) (2009) Fast, cost-effective development of species- Time and space: genetic structure of the cohorts of the specific microsatellite markers by genomic sequencing. common sea urchin Paracentrotus lividus in Western Biotechniques 46: 185−192 Mediterranean. Mar Biol 159:187–197 Addison JA, Hart MW (2004) Analysis of population genetic Carrea C, Burridge CP, King CK, Miller KJ (2016) Popula- structure of the green sea urchin (Strongylocentrotus tion structure and long-term decline in three species of droebachiensis) using microsatellites. Mar Biol 144: heart urchins Abatus spp. near-shore in the Vestfold 243−251 Hills region, East Antarctica. Mar Ecol Prog Ser 545: Allcock AL, Strugnell JM (2012) Southern Ocean diversity: 227−238 new paradigms from molecular ecology. Trends Ecol Cornwell BH, Fisher JL, Morgan SG, Neigel JE (2016) Evol 27: 520−528 Chaotic genetic patchiness without sweepstakes repro- Antao T, Lopes A, Lopes R, Beja-Pereira A, Luikart G (2008) duction in the shore crab Hemigrapsus oregonensis. Mar LOSITAN: a workbench to detect molecular adaptation Ecol Prog Ser 548: 139−152 based on a FST-outlier method. BMC Bioinformatics 9: 323 Dell RK (1972) Antarctic benthos. In: Russell FS, Yonge M Aoki S, Sasai Y, Sasaki H, Mitsudera H, Williams GD (2010) (eds) Advances in marine biology, Vol 10. Academic 164 Mar Ecol Prog Ser 601: 153–166, 2018

Press, New York, NY, p 1−216 Gosling EM, Wilkins NP (1985) Genetics of settling cohorts Díaz A, Féral JP, David B, Saucède T, Poulin E (2011) Evolu- of Mytilus edulis: preliminary observations. Aquaculture tionary pathways among shallow and deep-sea echi- 44: 115−123 noids of the genus Sterechinus in the Southern Ocean. Goudet J (1995) Fstat version 1.2: a computer program to Deep Sea Res II 58:205−211 calculate F-statistics. J Hered 86: 485−486 Dumont CP, Himmelman JH, Russell MP (2006) Daily move- Goudet J (2005) Hierfstat, a package for R to compute and ment of the sea urchin Strongylocentrotus droebachien- test hierarchical F-statistics. Mol Ecol Notes 5:184−186 sis in different subtidal habitats in eastern Canada. Mar Hardy OJ, Vekemans X (2002) Spagedi: a versatile com- Ecol Prog Ser 317:87–99 puter program to analyse spatial genetic structure at the Duran S, Palacín C, Becerro MA, Turon X, Giribet G (2004) individual or population levels. Mol Ecol Notes 2: Genetic diversity and population structure of the com- 618−620 mercially harvested sea urchin Paracentrotus lividus Haye PA, Segovia NI, Muñoz-Herrera NC, Gálvez FE, and (Echinodermata, Echinoidea). Mol Ecol 13: 3317−3328 others (2014) Phylogeographic structure in benthic mar- Earl DA, vonHoldt BM (2012) STRUCTURE HARVESTER: a ine invertebrates of the southeast Pacific coast of Chile website and program for visualizing STRUCTURE output with differing dispersal potential. PLOS ONE 9:e88613 and implementing the Evanno method. Conserv Genet Hedgecock D (1982) Genetic consequences of larval reten- Resour 4:359–361 tion: theoretical and methodological aspects. In: Kennedy Eldon B, Riquet F, Yearsley J, Jollivet D, Broquet T (2016) VS (ed) Estuarine comparisons. Academic Press, New Current hypotheses to explain genetic chaos under the York, NY, p 553−568 sea. Curr Zool 62: 551−566 Hedgecock D (1994) Does variance in reproductive success Ericson J, Ho M, Miskelly A, King C, Virtue P, Tilbrook B, limit effective population size of marine organisms? In: Byrne M (2012) Combined effects of two ocean change Beaumont A (ed) Genetics and evolution of aquatic stressors, warming and acidification, on fertilization and organisms. Chapman & Hall, London, p 122–134 early development of the Antarctic echinoid Sterechinus Hedgecock D, Pudovkin AI (2011) Sweepstakes reproduc- neumayeri. Polar Biol 35: 1027−1034 tive success in highly fecund marine fish and shellfish: a Evanno G, Regnaut S, Goudet J (2005) Detecting the num- review and commentary. Bull Mar Sci 87:971−1002 ber of clusters of individuals using the software STRUC- Hedrick PW (2005) A standardized genetic differentiation TURE: a simulation study. Mol Ecol 14: 2611−2620 measure. Evolution 59: 1633−1638 Excoffier L, Lischer HEL (2010) Arlequin suite ver 3.5: a new Hemond EM, Wilbur AE (2011) Microsatellite loci indicate series of programs to perform population genetics analy- population structure and selection between Atlantic and ses under Linux and Windows. Mol Ecol Resour 10: Gulf of Mexico populations of the bay scallop Argo - 564−567 pecten irradians. Mar Ecol Prog Ser 423:131–142 Falush D, Stephens M, Pritchard JK (2003) Inference of pop- Hess H, Bingham B, Cohen S, Grosberg RK, Jefferson W, ulation structure using multilocus genotype data: linked Walters L (1988) The scale of genetic differentiation of loci and correlated allele frequencies. Genetics 164: Leptosynapta clarki (Heding), an infaunal brooding 1567−1587 holothuroid. J Exp Mar Biol Ecol 122:187−194 Falush D, Stephens M, Pritchard JK (2007) Inference of pop- Hoffman JI, Peck LS, Linse K, Clarke A (2011) Strong popu- ulation structure using multilocus genotype data: domi- lation genetic structure in a broadcast-spawning antarc- nant markers and null alleles. Mol Ecol Notes doi: tic marine invertebrate. J Hered 102:55−66 10.1111/j.1471-8286.2007.01758.x Hoffman JI, Clarke A, Clark MS, Fretwell P, Peck LS (2012) Faurby S, Barber PH (2012) Theoretical limits to the correla- Unexpected fine-scale population structure in a broad- tion between pelagic larval duration and population cast-spawning antarctic marine mollusc. PLOS ONE 7: genetic structure. Mol Ecol 21:3419−3432 e32415. doi:32410.31371/journal.pone.0032415 Féral JP (2002) How useful are the genetic markers in Hofmann EE (1985) The large-scale horizontal structure of attempts to understand and manage marine biodiversity? the Antarctic Circumpolar Current from FGGE drifters. J Exp Mar Biol Ecol 268: 121−145 J Geophys Res 90: 7080−7097 Foo SA, Sparks KM, Uthicke S, Karelitz S, Barker M, Byrne Hogan JD, Thiessen RJ, Heath DD (2010) Variability in con- M, Lamare M (2016) Contributions of genetic and envi- nectivity indicated by chaotic genetic patchiness within ronmental variance in early development of the Antarc- and among populations of a marine fish. Mar Ecol Prog tic sea urchin Sterechinus neumayeri in response to Ser 417: 263−275 increased ocean temperature and acidification. Mar Biol Hubisz MJ, Falush D, Stephens M, Pritchard JK (2009) Infer- 163: 130 ring weak population structure with the assistance of Flowers JM, Schroeter SC, Burton RS (2002) The recruit- sample group information. Mol Ecol Resour 9:1322−1332 ment sweepstakes has many winners: genetic evidence Hunt A (1993) Effects of contrasting patterns of larval dis- from the sea urchin Strongylocentrotus purpuratus. Evo- persal on the genetic connectedness of local populations lution 56:1445–1453 of two intertidal starfish, Patiriella calcar and P. exigua. Gerlach G, Jueterbock A, Depperman J, Harmand P (2010) Mar Ecol Prog Ser 92: 179−186 Calculations of population differentiation based on GST Hunter RL, Halanych KM (2008) Evaluating connectivity in and D: forget GST but not all of statistics! Mol Ecol 19: the brooding brittle star Astrotoma agassizii across the 3845−3852 Drake Passage in the Southern Ocean. J Hered 99: González-Wevar CA, Diaz A, Gerard K, Cañete JI, Poulin E 137−148 (2012) Divergence time estimations and contrasting pat- Hunter RL, Halanych KM (2010) Phylogeography of the terns of genetic diversity between Antarctic and south- Antarctic planktotrophic brittle star Ophionotus victoriae ern South America benthic invertebrates. Rev Chil Hist reveals genetic structure inconsistent with early life his- Nat 85: 445−456 tory. Mar Biol 157:1693−1704 Miller et al.: Genetic differentiation in an Antarctic sea urchin 165

Iacchei M, Ben-Horin T, Selkoe KA, Bird CE, Garcia- Lowe WH, Allendorf FW (2010) What can genetics tell us Rodriguez FJ, Toonen RJ (2013) Combined analyses of about population connectivity? Mol Ecol 19:3038−3051 kinship and FST suggest potential drivers of chaotic Maltagliati F, Di Giuseppe G, Barbieri M, Castelli A, Dini F genetic patchiness in high gene-flow populations. Mol (2010) Phylogeography and genetic structure of the edi- Ecol 22: 3476−3494 ble sea urchin Paracentrotus lividus (Echinodermata: IPCC (2001) Synthesis report. A contribution of working Echinoidea) inferred from the mitochondrial cytochrome groups I, II and III to the third assessment report of the b gene. Biol J Linn Soc 100:910−923 Intergovernmental Panel on Climate Change. Cam- McCartney MA, Keller G, Lessios HA (2000) Dispersal bar- bridge University Press, Cambridge riers in tropical oceans and speciation in Atlantic and IPCC (2007) The fourth assessment report of the Intergov- eastern Pacific sea urchins of the genus Echinometra. ernmental Panel on Climate Change. Cambridge Uni- Mol Ecol 9: 1391−1400 versity Press, Cambridge Miller KJ, Ayre DJ (2008) Population structure is not a Iuri V, Patti FP, Procaccini G (2007) Phylogeography of the simple function of reproductive mode and larval type: sea urchin Paracentrotus lividus (Lamarck) (Echinoder- insights from tropical corals. J Anim Ecol 77:713−724 mata: Echinoidea): first insights from the South Tyrrhen- Miller KJ, Maynard BT, Mundy CN (2009) Genetic diversity ian Sea. Dev Hydrobiol 193: 77−84 and gene flow in collapsed and healthy abalone fish- Johnson MS, Black R (1982) Chaotic genetic patchiness in eries. Mol Ecol 18: 200−211 an intertidal limpet, Siphonaria sp. Mar Biol 70:157−164 Mills LS, Allendorf FW (1996) The one-migrant-per-genera- Johnson MS, Holborn K, Black R (1993) Fine-scale genetic tion rule in conservation and management. Conserv Biol patchiness and genetic heterogeneity of recruits of the co- 10: 1509−1518 rallivorous gastropod Drupella cornus. Mar Biol 117: 91−96 Moberg PE, Burton RS (2000) Genetic heterogeneity among Jost L (2008) GST and its relatives do not measure differen - adult and recruit red sea urchins, Strongylocentrotus tiation. Mol Ecol 17:4015−4026 franciscanus. Mar Biol 136:773–784 Kelly RP, Palumbi SR (2010) Genetic structure among 50 Ni L, Li Q, Kong L (2011) Microsatellites reveal fine-scale species of the northeastern pacific rocky intertidal com- genetic structure of the Chinese surf clam Mactra chi- munity. PLOS ONE 5: e8594 nensis (Mollusca, Bivalvia, Mactridae) in Northern Kimura M, Crow J (1964) The number of alleles that can be China. Mar Ecol 32: 488−497 maintained in a finite population. Genetics 49: 725−738 Nowlin WD, Klinck JM (1986) The physics of the Antarctic King CK, Riddle MJ (2001) Effects of metal contaminants on Circumpolar Current. Rev Geophys 24:469−491 the development of the common Antarctic sea urchin Paetkau D, Slade R, Burden M, Estoup A (2004) Direct Sterechinus neumayeri and comparisons of sensitivity real-time estimation of migration rate using assignment with tropical and temperate echinoids. Mar Ecol Prog Ser methods: a simulation based exploration of accuracy and 215: 143−154 power. Mol Ecol 13: 55−65 Kingsford MJ, Leis JM, Shanks AL, Lindeman KC, Morgan Palsbøll PJ, Be’rube M, Allendorf FW (2007) Identification of SG, Pineda J (2002) Sensory environments, larval abili- management units using population genetic data. Trends ties and local self-recruitment. Bull Mar Sci 70:309−340 Ecol Evol 22: 11−16 Larson RJ, Julian RM (1999) Spatial and temporal genetic Palumbi SR (1994) Genetic divergence, reproductive isola- patchiness in marine populations and their implications tion and marine speciation. Annu Rev Ecol Syst 25: for fisheries management. CCOFI Rep 40:94−99 547−572 Ledoux JB, Tarnowska K, Gérard K, Lhuillier E and others Palumbi SR (2003) Population genetics, demographic con- (2012) Fine-scale spatial genetic structure in the brood- nectivity, and the design of marine reserves. Ecol Appl ing sea urchin Abatus cordatus suggests vulnerability of 13: S146−S158 the Southern Ocean marine invertebrates facing global Paris CB, Cowen RK (2004) Direct evidence of a biophysical change. Polar Biol 35: 611−623 retention mechanism for coral reef fish larvae. Limnol Lessios HA, Kessing D, Robertson R, Oaulay G (1999) Phylo- Oceanogr 49:1964−1979 geography of the pantropical sea urchin Eucidaris in Peakall R, Smouse PE (2012) GenAlEx 6.5: genetic analysis relation to land barriers and ocean currents. Evolution in Excel. Population genetic software for teaching and 53: 806−817 research—an update. Bioinformatics 28:2537–2539 Lessios HA, Kessing D, Pearse S (2001) Population structure Pearse J, McClintock JB, Bosch I (1991) Reproduction of and speciation in tropical seas: global phylogeography of antarctic benthic marine invertebrates: tempos, modes, the sea urchin Diadema. Evolution 55:955−975 and timing. Am Zool 31: 65−80 Li G, Hedgecock D (1998) Genetic heterogeneity, detected Peck LS (2005) Prospects for survival in the Southern Ocean: by PCR-SSCP, among samples of larval Pacific oysters vulnerability of benthic species to temperature change. (Crassostrea gigas) supports the hypothesis of large vari- Antarct Sci 17: 497−507 ance in reproductive success. Can J Fish Aquat Sci 55: Penant G, Aurelle D, Feral JP, Chenuil A (2013) Planktonic 1025–1033 larvae do not ensure gene flow in the edible sea urchin Lister KN, Lamare MD, Burritt DJ (2010) Sea ice protects the Paracentrotus lividus. Mar Ecol Prog Ser 480: 155−170 embryos of the Antarctic sea urchin Sterechinus neu- Piry S, Alapetite A, Cornuet JM, Paetkau D, Baudouin L, mayeri from oxidative damage due to naturally en- Estoup A (2004) GeneClass2: a software for genetic hanced levels of UV-B radiation. J Exp Biol 213: assignment and first-generation migrant detection. 1967−1975 J Hered 95: 536−539 Lister KN, Lamare MD, Burritt DJ (2015) Pollutant resilience Pritchard JK, Stephens M, Donnelly P (2000) Inference of in embryos of the Antarctic sea urchin Sterechinus neu- population structure using multilocus genotype data. mayeri reflects maternal antioxidant status. Aquat Toxi- Genetics 155:945−959 col 161: 61−72 Raymond M, Rousset F (1995) GENEPOP (version 1.2): pop- 166 Mar Ecol Prog Ser 601: 153–166, 2018

ulation genetics software for exact tests and ecumeni- ware version 4.0. Molecular Biology and Evolution 24: cism. J Hered 86: 248−249 1596−1599 Reeb CA, Avise JC (1990) A genetic discontinuity in a con- Taylor MS, Hellberg ME (2003) Genetic evidence for local tinuosly distributed species: mitochondrial DNA in the retention of pelagic larvae in a Caribbean reef fish. Sci- American oyster Crassostrea virginica. Genetics 124: ence 299: 107−109 397−406 Teske PR, Papadopoulos I, Zardi GI, McQuaid CD, Edkins Riquet F, Comtet T, Broquet T, Viard F (2017) Unexpected MT, Griffiths CL, Barker NP (2007) Implications of life collective larval dispersal but little support for sweep- history for genetic structure and migration rates of south- stakes reproductive success in the highly dispersive ern African coastal invertebrates: planktonic, abbrevi- brooding mollusc Crepidula fornicata. Mol Ecol 26: ated and direct development. Mar Biol 152: 697−711 5467−5483 Thatje S, Hillenbrand CD, Larter R (2005) On the origin of Roberts CM (1997) Connectivity and management of carib- Antarctic marine benthic community structure. Trends bean coral reefs. Science 278: 1454−1457 Ecol Evol 20: 534−540 Ryman N, Leimar O (2009) GST is still a useful measure of Thornhill DJ, Mahon AR, Norenburg JI, Halanych KM genetic differentiation—a comment on Jost’s D. Mol Ecol (2008) Open-ocean barriers to dispersal: a test case with 18: 2084−2087 the Antarctic Polar Front and the ribbon worm Parborla- Sá-Pinto A, Branco MS, Alexandrino PB, Fontaine MC, sia corrugatus (Nemertea: Lineidae). Mol Ecol 17: Baird SJE (2012) Barriers to gene flow in the marine 5104−5117 environment: insights from two common intertidal limpet Underwood JN, Smith LD, van Oppen MJ, Gilmour JP species of the Atlantic and Mediterranean. PLOS ONE 7: (2009) Ecologically relevant dispersal of corals on iso- e50330 lated reefs: implications for managing resilience. Ecol Sahade R, Tatian M, Kowalke J, Kuhne S, Esnal GB (1998) Appl 19: 18−29 Benthic faunal associations on soft substrates at Van Oosterhout C, Hutchinson WF, Wills DPM, Shipley P Potter Cove, King George Island, Antarctica. Polar Biol (2004) Micro-checker: software for identifying and cor- 19:85−91 recting genotyping errors in microsatellite data. Mol Ecol Sameoto JA, Ross T, Metaxas A (2010) The effect of flow on Notes 4: 535−538 larval vertical distribution of the sea urchin, Strongylo- Veliz D, Duchesne P, Bourget E, Bernatchez L (2006) centrotus droebachiensis. J Exp Mar Biol Ecol 383: Genetic evidence for kin aggregation in the intertidal 156−163 acorn barnacle (Semibalanus balanoides). Mol Ecol 15: Selkoe KA, Toonen RJ (2006) Microsatellites for ecologists: a 4193–4202 practical guide to using and evaluating microsatellite Wang J (2011) COANCESTRY: a program for simulating, markers. Ecol Lett 9: 615−629 estimating and analysing relatedness and inbreeding Selkoe KA, Gaines SD, Caselle JE, Warner RR (2006) Cur- coefficients. Mol Ecol Resour 11: 141−145 rent shifts and kin aggregation explain genetic patchi- Waters JM, Roy MS (2004) Phylogeography of a high-disper- ness in fish recruits. Ecology 87: 3082−3094 sal New Zealand sea-star: does upwelling block gene- Selwyn JD, Hogan JD, Downey-Wall AM, Gurski LM, Port- flow? Mol Ecol 13:2797−2806 noy DS, Heath DD (2016) Kin-aggregations explain Weber AAT, Mérigot B, Valière S, Chenuil A (2015) Influ- Chaotic Genetic Patchiness, a commonly observed ence of the larval phase on connectivity: strong differ- genetic pattern, in a marine fish. PLOS ONE 11: ences in the genetic structure of brooders and broadcast- e0153381 ers in the Ophioderma longicauda species complex. Mol Slatkin M (1985a) Rare alleles as indicators of gene flow. Ecol 24: 6080−6094 Evolution 39: 53−65 White WB, Peterson RG (1996) An Antarctic circumpolar Slatkin M (1985b) Gene flow in natural populations. Annu wave in surface pressure, wind, temperature and sea-ice Rev Ecol Syst 16:393−430 extent. Nature 380: 699−702 Sponaugle S, Cowen RK, Shanks A, Morgan SG and others Whitlock MC (2011) G’ST and D do not replace FST. Mol Ecol (2002) Predicting self-recruitment in marine populations: 20: 1083−1091 biophysical correlates and mechanisms. Bull Mar Sci 70: Yasuda N, Nagai S, Hamaguchi M, Okaji K, Gérard K, 341–375 Nadaoka K (2009) Gene flow of Acanthaster planci (L.) in Tamura K, Dudley J, Nei M, Kumar S (2007) MEGA4: relation to ocean currents revealed by microsatellite Molecular Evolutionary Genetics Analysis (MEGA) soft- analysis. Mol Ecol 18:1574−1590

Editorial responsibility: Philippe Borsa, Submitted: February 20, 2017; Accepted: May 23, 2018, Montpellier, France Proofs received from author(s): July 26, 2018