MARINE ECOLOGY PROGRESS SERIES Mar Ecol Prog Ser
Vol. 485: 143–154, 2013 doi: 10.3354/meps10313
Published June 27
Population genetic structure and modes of dispersal for the colonial ascidian Botryllus schlosseri along the Scandinavian Atlantic coasts Eitan Reem1, 3,*, Ipsita Mohanty1, Gadi Katzir2, 3, Baruch Rinkevich1 1
Israel Oceanography and Limnological Research, National Institute of Oceanography, Tel Shikmona, PO Box 8030, Haifa 31080, Israel 2 Department of Marine Biology, Faculty of Science and Science Education, University of Haifa, Haifa 31905, Israel 3 Department of Evolutionary and Environmental Biology, Faculty of Science and Science Education, University of Haifa, Haifa 31905, Israel
ABSTRACT: The colonial ascidian Botryllus schlosseri is a well-known cosmopolitan invader of sheltered temperate marine communities which has garnered major scientific attention. We analyzed modes of dispersal and population genetic structures for 11 populations of B. schlosseri along the Scandinavian coasts, using 5 microsatellite loci. The analysis revealed high polymorphism, resulting in 108 different alleles (of which 58 were private alleles), positive correlations between the number of sites shared by specific alleles and their mean frequencies, and lower genetic diversity values than in previously studied worldwide populations. A complex network of gene flow among sampled populations was revealed, with 2 clades, southeastern and northwestern, and higher genetic variation in the latter clade due to either restricted gene flow or more intensive genetic drift. A detailed analysis of allele frequencies revealed possible ancestral alleles. By using Bayesian analysis, 9 previously studied populations from Britain and European Atlantic coasts were compared, encompassing a single geographical entity along thousands of kilometers from Gibraltar (36° 8’ N) to Ålesund, Norway (62° 29’ N). Results showed a high connectivity among distant localities, most probably due to extensive human-mediated transport. This refutes isolation by distance, with a higher intensity of gene flow among Scandinavian sites compared to the other European sites. Bayesian clustering computation assembled the whole data set of 19 populations into 14 clusters and 2 major northern and southern clades. KEY WORDS: Invasive species · Bayesian clustering · Ancestral alleles · Isolation by distance · Gene flow · Genetic diversity Resale or republication not permitted without written consent of the publisher
Species and population expansion, as well as increasing biological invasions, have stimulated considerable interest among biologists. Today, these phenomena are being investigated using population genetics tools (Kolbe et al. 2004, Stepien et al. 2005, Lavergne & Molofsky 2007, Roman & Darling 2007, Puillandre et al. 2008). Such tools enable reconstruc-
ting invasion routes, recording various levels of connectivity among populations of species with various life history traits, and elucidating levels of genetic diversity within populations of introduced species (reviewed in Estoup & Guillemaud 2010). The increase in ocean water temperatures, one of the results of global climatic change (Anadón et al. 2007), has also affected the trajectories and magnitude of biological invasions, causing northward
*Email:
[email protected]
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INTRODUCTION
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Mar Ecol Prog Ser 485: 143–154, 2013
movements of more southern species in the northern hemisphere, followed by the establishment of nonindigenous species in both terrestrial and marine ecosystems (Franke & Gutow 2004, Parmesan 2006, Anadón et al. 2007). In many coastal communities, invasion rates are enhanced by substantial global shipping traffic, as many organisms of a wide spectrum of taxa foul ship hulls, are conveyed in ballast water, or are transported on hauled edible invertebrates, such as oysters (Ruiz et al. 2000, Lambert 2001, Dijkstra et al. 2007). The colonial ascidian Botryllus schlosseri is a worldwide invader, commonly found in sheltered temperate marine communities, primarily marinas and harbors, in the northern and southern hemispheres (Berrill 1950, Ruiz et al. 2000, Lambert 2001, Stoner et al. 2002, Paz et al. 2003, Ben-Shlomo et al. 2006, 2010, Simkanin et al. 2012), and successfully reproducing at 11 to 28°C (Brunetti 1974, Grosberg 1988, Chadwick-Furman &Weissman 1995, Rinkevich et al. 1998a,b). In the northern hemisphere, B. schlosseri populations are distributed from the southern coast of India (8° 22’ N latitude; Meenakshi & Senthamarai 2006), where sea water temperature ranges from 24 to 29.5°C (Damotharan et al. 2010), to the Norwegian sea ports (> 62° N) with sea water temperatures ranging between 3 and 17°C (Nair 1962). In natural environments, they can be found below and above stones, on exposed natural rocky habitats and down to 200 m depth (Ben-Shlomo et al. 2006). In harbors and marinas, colonies are found submerged on hard substrata such as stones, pontoons, wharfs and ropes. The life history of B. schlosseri includes a stage of short-lived (~1 h) pelagic larvae that settle in close proximity to parental colonies (Grosberg 1987, Rinkevich & Weissman 1987), thus restricting their long-range dispersal. Adult colonies are dispersed mainly via attachment to ship hulls, floating objects and edible invertebrates, such as crabs and oysters, which are shipped between distant sites (Paz et al. 2003, Bernier et al. 2009, Lacoursière-Roussel et al. 2012). Recent studies (Cohen & Carlton 1995, Ruiz et al. 2006, Locke et al. 2009) have revealed new B. schlosseri introductions in colder sites in the northern hemisphere. Despite ample information on the global distribution of Botryllus schlosseri, there is no consensus for its site of origin. Citing Van Name (1945) and Berrill (1950), studies have claimed Mediterranean and European Atlantic waters as B. schlosseri sites of origin, whereas Carlton (2005) proposed a Pacific Ocean hub of origin. The distribution of B. schlosseri along the European Atlantic coasts has been documented
since the eighteenth century from Falmouth Bay in England (Pallas 1766), from the Faeroe Islands and western and southern Norway to the Mediterranean, Adriatic and Black seas (Van Name 1945, Berrill 1950). Nevertheless, while there is wide knowledge of the distribution of this species along the western coasts of Europe, only a few studies have elucidated its population genetic profiles in European waters (Rinkevich et al. 2001, Ben-Shlomo et al. 2006, López-Legentil et al. 2006, Bock et al. 2012). Despite the current interest in the northward movement of marine species, the distribution of B. schlosseri along the northern European coasts, such as along the western coasts of Scandinavia, has been little studied. Previous population genetic studies of B. schlosseri using microsatellites (Stoner et al. 2002, Paz et al. 2003, Ben-Shlomo et al. 2010) revealed high polymorphism and heterozygote deficiency as general attributes of all studied populations. Two of those studies (Stoner et al. 2002, Ben-Shlomo et al. 2010) indicated possible routes of invasion patterns and connectivity between sites on the Pacific and Atlantic coasts of the Americas, Europe, and New Zealand. The presence of Botryllus schlosseri along the Scandinavian coasts has only been mentioned anecdotally. Van Name (1945) and Berrill (1950) referred to it as appearing in ‘western and southern Norway’ (supported by the observations of Nair 1962 and Dybern 1967). Nair (1962) mentioned it among other fouling organisms from 4 sampling stations in the fjords of the Bergen area, demonstrating that colonies are active only during the summer and fall periods when water temperatures are > 9°C and disappear for the winter months, probably hibernating (Brunetti et al. 1980). Following this limited knowledge, the aim of this study was to investigate population genetics of B. schlosseri along the Atlantic coasts of Scandinavia to elucidate patterns of connectivity and possible gene-flow trajectories among sampling sites from Öckerö on the southern west coast of Sweden to Ålesund in Norway beyond 62° latitude. In addition, based on information from BenShlomo et al. (2006). We aimed to examine possible connectivity routes between Scandinavian sites and some European Atlantic and British sites.
MATERIALS AND METHODS Sampling Colonies of Botryllus schlosseri (N = 319) were sampled in the summer of 2005 from 5 sites along
Reem et al.: Genetic structure and dispersal of Botryllus schlosseri in Scandinavia
145
Microsatellite typing
Fig. 1. Sampled sites in Scandinavia
the Atlantic coast of Sweden, and in the summer of 2007 from 6 sites along the Atlantic coasts of Norway (Fig. 1, Table 1). Samples were taken from submerged parts of docks or ropes, 0.1 to 0.5 m below sea level and only from colonies that were >1 m apart, in order to avoid sampling kin colonies that may be identical by descent (see Grosberg 1987), chimeras, or ramets of the same genotype. Sampling efforts were aimed at collecting between 30 and 50 different colonies but in some of the sites colonies were rare, resulting in a reduced number of samples. Whole colonies or colony fragments were removed from their substrates by single-edge razor blade. Each sample was placed separately in a 1.5 ml vial containing 200 µl lysis buffer (0.25 M Tris borate, 0.1 M EDTA, 2% wt/vol SDS, 0.1 M NaCl, adjusted to pH 8.2) and 40 µl NaClO4 (5 M). Samples were homogenized and DNA was extracted with 200 µl phenol:chloroform:isoamyl alcohol solution (25:24:1 vol:vol:vol) (Graham 1978, Paz et al. 2003). The vials were shipped to the laboratory at the National Institute of Oceanography in Israel for further work. In the laboratory, DNA isolation was completed as described by Paz et al. (2003). DNA concentration was approximately ~5 µg µl−1. Samples were kept as stock at 4°C. For microsatellite typing, we used DNA diluted 1:100 in sterile double-distilled water (DDW).
Five Botryllus schlosseri microsatellite loci, PBC-1, PB-29, PB-41, PB-49 (Stoner et al. 1997), and BS-811 (Pancer et al. 1994) were amplified by polymerase chain reaction (PCR) with specific fluorescent primers (Agentech) using the following conditions: 94°C for 2 min, followed by 32 cycles at 94°C for 1 min, 52°C for 1 min and 72°C for 1 min, and a final extension step at 72°C for 45 min followed by storage at 10°C. The 16 µl reaction mixture contained 8 µl PCR mix (R2523-100 RXNREDTaq ReadyMix, Sigma), 5 pmol fluorescent primer (Applied Biosystems), 6 µl DDW and 1 µl DNA solution (1:100). A loading cocktail was prepared by adding 1 µl of PCR product to 12 µl formamide and 0.5 µl size standard (Genescan 400HD[ROX] 402985, Applied Biosystems). Vials with the cocktail were heated to 92°C for 2 min and cooled to 4°C. Microsatellite allele lengths of the samples were analyzed using 3130 Genetic Analyzer and Genotyper software (Applied Biosystems). To avoid scoring errors due to stutters appearing in the chromatograms that might obscure the real reading of the microsatellite, we employed Micro-Checker software (Van Oosterhout et al. 2004) to score errors and null alleles. Suspected samples were re-genotyped and double-checked by 2 researchers until a consensus was reached.
Data analysis Data were analyzed by GenAlEx version 6.2 software (Peakall & Smouse 2006) and by Tools for Population Genetic Analyses (TFPGA) software version 1.3 (Miller 1997). The significance level of population differentiation (pairwise analysis of all populations; exact test, Raymond & Rousset 1995) was determined after 1000 dememorization steps and 10 batches of 2000 permutations per batch, using TFPGA; the Bonferroni correction method for multiple comparisons was applied. The same software was employed to assess isolation by distance Mantel test. Geographical distances were measured using Google Earth program with the application that enables drawing a line along the coastline contour between 2 points, resulting in direct reading of the distance. In addition, the population differentiation Dest was calculated according to Jost (2008) and by SMOGD version 1.2.5 software (Crawford 2010). The genetic variation, Fst, and overall inbreeding coefficient Fis were calculated via analysis of molecular variance (AMOVA) proce-
Sweden Strömstad
Norway Risør
Norway Fevik
Norway Tananger
Norway Håkonshella
Norway Dolvik
Norway Florø
Norway Ålesund
4
5
6
7
8
9
10
11
Total
Sweden 58°33’ 11°16’ Hamburgsund
3
62°28’ 6°09’
61°31’ 5°02’
60°19’ 5°15’
60°20’ 5°11’
58°56’ 5°34’
58°22’ 8°40’
58°43’ 9°14’
58°56’ 11°10’
58°14’ 11°27’
Sweden Fiskebäckskil
2
57°42’ 11°39’
Sweden Öckerö Island
Coordinates N E
1
No. Name
No data
small dock, many on Laminaria
marina, many colonies, most on Laminaria blades
Marina, many colonies, samples collected from a pipe along the dock
harbor, shallow water, from hard substrata (ropes, Laminaria, bivalves), abundant
marina, also fresh water
marina, also fresh water, dispersed population
marina, from shallow and deep water, many colonies
marina, from shallow water, many colonies
marina, from shallow water, many colonies
marina, on ropes
Site Description
25/07/07
26/08/07
24/08/07
24/08/07
29/08/07
31/08/07
01/09/07
09/03/05
06/09/05
30/08/05
01/09/05
319
32
35
22
40
18
30
29
48
18
22
25
Sample Date Size
34
25
33
37
31
24
25
32
36
38
38
No. of alleles
27
22
25
27
28
22
22
27
28
29
31
79
88
76
73
90
92
88
84
78
76
82
Shared alleles with other sites No. %
58
6
6
6
8
3
1
4
7
1
7
9
No. of private alleles
Fis
0.332 0.620 6.418 6.642 3.327 0.439 ± 0.025 ± 0.029 ± 0.436 ±1.412 ± 0.228 ± 0.037
0.353 0.658 6.800 4.816 3.288 0.494 ± 0.106 ± 0.077 ±1.828 ± 0.849 ± 0.507 ± 0.124
0.290 0.668 5.000 4.869 3.326 0.548 ± 0.109 ± 0.073 ± 0.837 ± 0.815 ± 0.653 ± 0.158
0.339 0.703 6.600 5.889 3.698 0.490 ± 0.109 ± 0.061 ±1.249 ±1.108 ± 0.691 ± 0.157
0.330 0.662 7.400 5.847 3.617 0.470 ± 0.046 ± 0.091 ± 2.379 ±1.703 ± 0.769 ± 0.072
0.311 0.587 6.200 5.052 0497 0.420 ± 0.089 ± 0.098 ±1.319 ±1.042 ± 0.497 ± 0.133
0.282 0.490 4.800 4.125 2.519 0.421 ± 0.089 ± 0.139 ±1.200 ± 0.997 ± 0.565 ± 0.101
0.456 0.636 5.000 4.712 2.860 0.232 ± 0.081 ± 0.057 ± 0.837 ± 0.771 ± 0.418 ± 0.170
0.341 5.562 6.400 5.052 3.051 0.396 ± 0.105 ± 0.125 ±1.691 ±1.251 ± 0.880 ± 0.115
0.342 0.623 7.200 5.524 3.385 0.377 ± 0.079 ± 0.113 ±1.020 ± 0.769 ± 0.724 ± 0.147
0.300 0.597 7.600 5.738 3.767 0.471 ± 0.090 ± 0.128 ±1.720 ±1.319 ±1.190 ± 0.121
0.312 0.630 0.760 6.589 4.294 0.514 ± 0.076 ± 0.136 ±1.833 ±1.616 ±1.360 ± 0.079
Ho
Mean diversity parameters and inbreeding coefficients ± SE He Na AR Ne
Table 1. Botryllus schlosseri. Sampling sites, allelic distribution and genetic diversity parameters for 11 Scandinavian populations. Abbreviations: Ho: observed heterozygosity; He: unbiased expected heterozygosity = 2N · (2N − 1)–1) × (1 − Sum π 2); Na: number of different alleles; Ne: number of effective alleles = (Sum π 2)–1; Fis: inbreeding coefficient = 1 − (Ho/He); AR: mean allelic richness over loci based on minimal sample size of 14 diploid individuals and on the rarefaction approach; SE: standard error
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Reem et al.: Genetic structure and dispersal of Botryllus schlosseri in Scandinavia
dure among all sampling sites (each sampling site was considered a group), following the methods of Michalakis & Excoffier (1996) with 999 permutations using GenAlEx 6.2 software. The significance levels of Hardy Weinberg tests for heterozygote deficiency and for Fis were determined by Genepop ver. 4.0.10 (Raymond & Rousset 1995, Rousset 2008). Allelic richness was estimated by FSTAT software (Goudet 2002) using the rarefaction approach (El Mousadik & Petit 1996) to avoid bias due to different sampling sizes. Bayesian partitioning was calculated by using BAPS v.5.3 software (Corander et al. 2009). Possible connectivity among sites was calculated and plotted following Tang et al. (2009) and implemented in the same software. Both calculations are based on group level mixture and admixture analyses. An additional Bayesian analysis with Structure 2.3.1 software (Pritchard et al. 2000) was employed to further assess the outcomes. Statistical normality of distribution test and t-test computations for differentiation significance between genetic diversity parameters from different geographical regions and for correlations were performed using SPSS 16 software.
RESULTS All 5 microsatellite loci were highly polymorphic, altogether showing 108 different alleles out of 1595
147
scored alleles (319 specimens, 5 microsatellite loci). Locus BS-811 emerged as the most polymorphic with 49 alleles, while loci PB-49, PBC-1, PB-41 and PB-29, comprised 20, 20, 12 and 7 alleles, respectively (Table S1 in the supplement at www.intres.com/articles/suppl/m485p143_supp.pdf). Each of the 11 sampling sites had 1 to 9 private alleles (8 to 27% of alleles per site) summing to 58 at all sites (Table 1). Seventeen alleles were found to be shared by 73% of the sites (8 out of 11 sites) and 15 by at least 82% of the sites (8/11 and 9/11, respectively; Table 2). The overall mean frequency of the alleles that appeared in at least 8/11 and 9/11 of the populations was 0.26 and 0.30, respectively. Furthermore, in 49% of the cases presented in Table 2, the allele frequency was > 0.2. Thirty-two out of 1595 scored alleles, composing 2% of the total, failed to amplify and were defined as null alleles. We found a positive correlation (Spearman rho = 0.982, p < 0.01) between the number of sites sharing specific alleles and the mean frequency of these common alleles. Private alleles showed a low mean frequency of 0.038, while common alleles in 10 and 11 Scandinavian sites showed mean frequencies > 0.2, i.e. they were an order of magnitude more frequent. Exact tests for population differentiation (Raymond & Rousset 1995) among all pair-populations showed highly significant results (p < 0.001), even after performing the Bonferroni correction for multiple test-
Table 2. Botryllus schlosseri. Alleles that appeared in 8 to 11 of the 11 sampling populations and their frequencies. Frequencies > 0.25 are in bold, and frequencies between 0.20 to 0.25 are underlined. Abbreviations: Nor = Norway; Swd = Sweden; Hak = Håkonshella; Dol = Dolvik; Flo = Florø; Ale = Ålesund; Tan = Tananger; Fev = Fevik; Ris = Risør; Fis = Fiskebäckskil; Ock = Öckerö; Str = Strömstad; Ham = Hamburgsund. Based on all 5 microsatellite loci Locus Allele size
Swd Ock
Swd Fis
Swd Ham
Swd Str
Nor Ris
Nor Fev
Nor Tan
Nor Hak
Nor Dol
Nor Flo
Nor Ale
PB41 PB29 PB29 BS811 PBC1 PB49 PBC1 BS811 PB49 PBC1 PB49 PB49 PB49 BS811 PB41 BS811 PBC1
0.660 0.720 0.260 0.063 0.180 0.260 0.260 0.396 0.280 0.300 0.140 0.240 0.020 0.021 – 0.042 0.040
0.386 0.318 0.591 0.357 0.295 – – 0.214 0.452 – 0.143 – 0.214 0.071 0.045 – 0.045
0.156 0.583 0.361 0.308 0.441 0.118 0.118 0.077 0.176 0.235 0.412 – 0.235 0.154 0.125 0.154 0.088
0.313 0.229 0.771 0.489 0.448 0.185 0.125 0.152 0.239 0.010 0.261 0.033 0.228 0.033 0.271 0.033 –
0.875 0.446 0.536 0.115 0.276 0.018 0.345 0.519 0.036 0.034 0.071 0.018 0.411 0.038 0.036 0.077 0.207
0.950 0.883 0.117 0.466 0.133 0.467 0.217 0.172 0.017 0.433 0.017 0.317 0.167 0.121 – 0.069 0.033
0.611 0.333 0.667 0.306 0.278 0.194 0.556 – 0.389 0.083 – 0.278 0.028 0.361 0.222 – –
0.885 0.750 0.238 0.150 0.513 0.325 0.113 0.200 0.163 0.200 0.163 0.150 0.075 0.088 – 0.125 0.025
0.909 0.705 0.136 0.071 0.227 0.455 0.159 0.286 0.182 0.159 0.205 0.136 – 0.095 0.045 – 0.068
0.943 0.571 0.386 0.561 0.157 0.529 0.286 – 0.162 0.114 0.162 0.029 0.059 0.182 0.057 0.076 0.043
0.683 0.875 0.094 0.387 0.094 0.100 0.328 0.129 0.150 0.250 0.150 0.317 0.217 0.226 0.017 0.097 0.016
169 162 155 174 198 211 210 178 209 179 201 213 205 186 171 176 201
Overall Appeamean rance frequency ratio 0.670 0.583 0.378 0.297 0.277 0.265 0.251 0.238 0.204 0.182 0.172 0.169 0.165 0.126 0.102 0.084 0.063
11/11 11/11 11/11 11/11 11/11 10/11 10/11 9/11 11/11 10/11 10/11 9/11 10/11 11/11 8/11 8/11 9/11
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ing. In addition, overall variation measure (Fst = 0.137; p < 0.001) and the overall differentiation measure (Dest = 0.265, CI = 0.229 to 0.331), point at first glance to a modest genetic structure in the entire studied area. However, dividing the whole sampled area into 2 regions, one including the 6 sites in southeastern Scandinavia along the coasts of the Skagerrak bight, and the other encompassing the northwestern sites along the Atlantic coastal fjords of Norway, resulted in a higher Fst and Dest in the northern versus southern region: 0.129 (p < 0.001) versus 0.087 (p < 0.001) for Fst, and 0.269 (CI = 0.183 to 0.407) versus 0.153 (CI = 0.063 to 0.237) for Dest, respectively. Both population parameters, therefore, show the same trend: higher genetic variation due to either restricted connectivity or higher genetic drift among the northwest sites, which caused higher differentiation in the northwestern region as compared to the southeastern region. Based on the same geographical criterion, Nei genetic distance revealed a similar outcome: mean genetic distance among southeastern sites was 0.192 versus 0.360 among northwestern sites (Tables S2 & S3 in the supplement). Genetic diversity parameters, including mean numbers of different (Na) and effective (Ne) alleles, observed and unbiased expected heterozygosity (Ho and He, respectively), the mean inbreeding coefficients F is (also known as system of mating inbreeding coefficient f [Templeton 2006]) values, and allelic richness (AR) based on the rarefaction approach (El Mousadik & Petit 1996) were calculated (Table 1). Hardy Weinberg exact test resulted in heterozygote deficiency for all loci in all populations (p < 0.001 Genepop ver. 4.0.10; Raymond & Rousset 1995, Rousset 2008), meaning that Botryllus schlosseri populations in Scandinavia deviate from Hardy Weinberg equilibrium, as already recorded in other B. schlosseri populations worldwide (Ben-Shlomo et al. 2001, 2006, 2010, Stoner et al. 2002, Paz et al. 2003, Johnson & Yund 2007), thus weakening the possibility for heterozygote deficiency due to null alleles. Overall Fis value calculated via AMOVA was 0.452 (p < 0.001). Genetic diversity parameters He and AR (Table 1) between southeastern and northwestern Scandinavian sites revealed no statistical difference (p = 0.06 for He; p = 0.99 for AR). Mantel test for correlation between geographic and genetic distances (TFPGA; Miller 1997) also revealed (Fig. 2) that isolation by distance is not characteristic for the sampled Scandinavian populations (p = 0.12 and r = 0.158), further indicating that the effect of geographical distance does not explain the variance in genetic distance. We performed 2 additional independent
0.7
Nei genetic distance
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0.6 0.5 0.4 0.3 0.2 0.1 0
0
200
400
600
800
1000
Geographic distance (km) Fig. 2. Botryllus schlosseri. Mantel test for isolation by distance among populations. r = 0.158, p = 0.12, Z from original data: 8748.776, mean Z after 9999 permutations: 8312.651
Mantel tests for association between geographic and genetic distances: one among the northwestern sampling sites and one among the southeastern sampling sites. Surprisingly, the results were not significant in the northwest (p = 0.09) but significant (p < 0.05) in the southeast (Figs. S1 & S2 in the Supplement a www.int-res.com/articles/suppl/m485p143_supp. pdf). Bayesian group clustering analysis disclosed 10 clusters out of 11 sampling sites (Fig. 3a), whereas the Norwegian and Swedish sites, Fevik and Hamburgsund, were grouped into one cluster, indicating a possible recent common ancestry or intensive interchange gene flow. Based on group level mixture analysis, the log marginal likelihood of optimal partition is −5115.62, with probabilities of 0.081 for 8 clusters and 0.919 for 10 clusters (BAPS 5.3 software; Corander et al. 2009). Interestingly, but not surprisingly, this outcome is in accordance with the results of the pairwise differentiation test D est (Jost 2008) and pairwise Nei genetic distance, which were found to be highly and significantly correlated (Table S4, Fig. S3 in the Supplement). Gene flow plots among Scandinavian clusters, computed by Bayesian clustering based on the parameters mentioned above (Fig. 3b), revealed a complex network of trajectories between clusters. However, 3 of the sites (Dolvik, Tananger, Risør) were 100% self-seeded, while at the other 8 sites, there was limited gene flow among the sites (90 to 97% self-seeding). Fig. 3b also reveals only a single gene-flow trajectory among 5 northwestern clusters, compared to 5 trajectories among the southeastern clusters and 10 trajectories between the northwest and southeast. The intensity (mean ± SE) of gene flow among southeastern clusters was 0.023 ± 0.007 and 0.018 ±
Reem et al.: Genetic structure and dispersal of Botryllus schlosseri in Scandinavia
a
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DISCUSSION The results of this study, which concentrated on 11 Scandinavian populations, revealed (1) high polymorphism and genetic variability, (2) that specific alleles shared by most sites have high frequency, (3) no isolation by distance, (4) a complex, although with limited intensity, network of gene flow among most sampling sites, and (5) 2 suggested distinct northwestern and southeastern clades.
b
Genetic diversity and possible ancestral alleles
Based on the same 5 microsatellite loci, genetic diversity values depicted for each of the Scandinavian populations (0.482 < He < 0.686; 4.13 < AR < 6.59) and their means (0.620 ± 0.029 and 5.29 ± 0.21, respectively; Table 1) were lower than values revealed in other Botryllus schlosseri populations, such as the Santa Cruz harbor (California, USA) population that was sampled over a period of 13 yr (0.718 < He < 0.802; 5.642 < AR < 8.216; Reem et al. 2013), and 3 sites studied along the Mediterranean coast of Israel (0.94 < He < 0.97; Paz et al. 2003). However, the Scandinavian population values were higher than those recorded for northern European and English populations (0.17 < He < 0.61; Ben-Shlomo et al. 2006). Fig. 3. Botryllus schlosseri. Bayesian clustering computation results among Botryllus schlosseri populations probaScandinavian sampling sites. (a) Nei genetic distances on phylogenetic bly occurred in Scandinavia earlier than tree of the 10 Scandinavian clusters. (b) Gene-flow plot among Scandinathe 1940s, when reported in southern vian clusters. Arrows indicate direction of gene flow. Numbers on arrows represent the mean contributions of source clusters among the individuals Norway (Van Name 1945, Berrill 1950), assigned to a target cluster. Threshold value for gene flow was set to 1% and at the approximate time that they (0.01). Based on admixture analysis among clusters, using BAPS v.5.3 were first recorded from California coasts software (p < 0.05) (Van Name 1945, Cohen & Carlton 1995). A possible explanation for the lower 0.002 between northwest and southeast clusters, genetic polymorphism recorded in the Scandinavian pointing to stronger gene flow in the southeastern versus other populations is based on environmental clusters. The difference, however, was not statisticonditions. While colonies of B. schlosseri in the cally significant (t-test; p = 0.34, df = 12, t = −0.998). Mediterranean Sea and in California are found yearAmong the 10 northwestern and southeastern trajecround (Chadwick-Furman & Weissman 1995, Stoner tories, 6 were from northwest to southeast with a et al. 2002, Paz et al. 2003), in Scandinavia the mean intensity of 0.016 ± 0.002 and 4 from southeast colonies are recorded only from July to December, to northwest with a mean intensity of 0.021 ± 0.003, when water temperatures are > 9°C, and disappear albeit the difference was not statistically significant when the water temperature drops (Nair 1962), prob(t-test; p = 0.19, df = 8, t = −1.419). ably going into hibernation (Brunetti et al. 1980).
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This shorter ecologically active period limits the accumulation of substantial genetic diversity. Another viable explanation is that Scandinavian populations were influenced by a small number of introduction events, partly supported by the constrained gene flow between sites. Analysis of allele distribution revealed 13 out of 108 different alleles that were common to most (10 to 11) Scandinavian sites, with overall mean frequencies between 0.13 and 0.67; in most of the cases the values were > 0.2. This, coupled with the positive correlation between the number of sites shared by the same alleles and mean frequency of those alleles (Spearman rho Correlation coefficient = 0.982; p < 0.01) suggest the possibility of these alleles being ancestral, or founding alleles of the Scandinavian populations.
Isolation by distance and gene flow among Scandinavian sites Overall Mantel test (Fig. 2) indicated no isolation by distance among the Scandinavian localities and connectivity among populations, a result supported by the Bayesian gene-flow outcomes among sampled Scandinavian populations (Fig. 3b). This is clearly illustrated when considering the closest Norwegian populations of Håkonshella and Dolvik (10 km apart). The Håkonshella population is genetically closer to the clusters of the southern region (Öckerö, Fiskebäckskil, Strömstad and Hamburgsund-Fevik), which are between 490 and 680 km away, than to the Dolvik cluster (Fig. 3a). Similarly, Fevik and Risør (60 km apart) are more divergent than Risør and Tananger, which are 360 km apart (Fig. 3a). At first glance, it seems that the Nei genetic distances in Fig. 3a and the gene-flow plots in Fig. 3b are not congruent in 2 cases: in Fig. 3a, Alesund and Dolvik are genetically similar, but no gene flow between these populations is shown in Fig 3b. The same applies to Risør and Tananger. However, as genetic similarity can be achieved by either gene flow or common ancestry of 2 groups that could have diverged relatively recently, the same outcome could reflect either cause. The gene-flow trajectory analysis (Fig. 3b) further supports restricted connectivity among the northwestern compared to the southeastern clusters, and the absence of isolation by distance. The extensive gene flow among populations over geographical scales of hundreds of kilometers is probably due to anthropogenically mediated dispersal, mainly continuous traffic of fouled vessels.
Botryllus schlosseri is currently found in northern sites from which it was probably absent in the past (B. Rinkevich unpubl. data) and is likely moving north in Scandinavia as shown by the gene-flow trajectories (Fig. 3b), reflecting the shifts in North Atlantic oscillation temperatures over the last 3 decades (Visbeck et al. 2001). An increase in sea water temperatures has been further documented in Scandinavia in the last decade, associated with several record heat waves (Mork et al. 2007). Nevertheless, dispersal into new sites is most likely not the outcome of expanding vanguard populations, but rather coincidental, depending on vessel traffic trajectories in Scandinavia. Fishing activities are restricted by international agreements that prohibit fisherman from crossing international marine borders. Therefore, we assume that recreation and motor boats fouled with colonies of Botryllus schlosseri that cross the Skagerrak during the summer, mainly from Norway and Denmark (H. Sköld, Gothenburg Univ., pers. comm.), and commercial ships from other parts of Europe are the main dispersal vectors. The notion of anthropogenic dispersal of botryllid ascidians is further supported by other publications (Locke et al. 2009, Bock et al. 2011, Lacoursière-Roussel et al. 2012). Despite the extensive gene flow between Scandinavian populations, the 11 examined populations eventually formed 10 clusters and 2 clades (Fig. 3a). The first included 5/6 southeastern populations and one (Håkonshella; Norway) from the northwest, and the second comprised the 4 remaining northwestern populations and one (Risør; Norway) from the southeast. This division is consistent with the results of the different Fst and Dest values in the northern and southern regions of Scandinavia. An additional Bayesian clustering analysis with Structure 2.3.1 software revealed similar, although not identical results (Fig. S4 in the Supplement). While less likely, it is possible that the 2 yr gap in sampling (Sweden — 2005, Norway — 2007) added some variation to the genetic structure among sites, due in part to changes that occurred over time, on top of the emerged inherent spatial differences at a single time point.
Comparisons between Scandinavian and western European sites The meta-population structure of the cosmopolitan species Botryllus schlosseri is made up of many local populations that have colonized distant sites on different occasions, through dissimilar immigration vectors, all subjected to anthropogenic activities (Paz
Reem et al.: Genetic structure and dispersal of Botryllus schlosseri in Scandinavia
et al. 2003, Dijkstra et al. 2007, Bernier et al. 2009, Lacoursière-Roussel et al. 2012). This should be taken into consideration when evaluating population genetic properties and structures between remote populations. Previous population genetic analyses of B. schlosseri from the southern Atlantic coasts of Europe, the North Sea and the British Isles (BenShlomo et al. 2006; using 4/5 microsatellites and excluding locus PBC-1) provide us with the opportunity to extend the comparisons over a geographical scale of thousands of kilometers. Data of 8 sites from Spain to Scotland and Germany were compared with the 11
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sites in Scandinavia. Overall, Fst and Dest values for 8 western European sites combined were 0.419 (p < 0.001) and 0.749 (CI = 0.729 to 0.790), respectively, exhibiting a relatively strong European population structure with higher differentiation among sites as compared to Scandinavia, thus emphasizing the higher connectivity among Scandinavian populations in comparison to the connectivity among western European sites. Establishing a phylogenetic tree through Bayesian clustering, 14 clusters emerged out of the 19 Scandinavian and western European sites studied, with 2 distinct major clades (Fig. 4a). Of the 11 Scan-
Fig. 4. Botryllus schlosseri. Bayesian clustering computation results among western European and Scandinavian sites. (a) Nei genetic distances on phylogentic tree of all western European and Scandinavian clusters computed by Bayesian clustering method. Based on 4/5 microsatellites. English and European data are from Ben-Shlomo et al. (2006). (b) Gene-flow plot among Scandinavian and western European populations computed by Bayesian clustering. Arrows indicate direction of gene flow. Numbers on arrows represent the mean contributions of source clusters among the individuals assigned to a target cluster. Threshold value for gene flow was set to 1% (0.01). Based on admixture analysis among clusters, using BAPS v.5.3 software (p < 0.05)
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dinavian populations, 10 were clustered in a single clade; the exception being Risør (Norway) which was clustered with the other western European clade, on the same branch as Setubal (Portugal). Surprisingly, 3 populations from the south Iberian Peninsula (Faro, Portugal, Barbeta, Spain and Gibraltar) were clustered together with the ‘Scandinavian cluster’ (Fig. 4a). These results suggest a recent gene flow or common ancestry between Scandinavia and the south Iberian Peninsula, roughly 3000 km away when sailing along the coasts of western Europe, further demonstrating that human-mediated dispersal reduces the importance of geographical distance as a barrier for B. schlosseri dispersal. The 19 Scandinavian and western European sites studied included 11 man-made sites (harbors and marinas) from Scandinavia, 5 other man-made European sites and 3 natural European sites (intertidal rocky shores). Active larval dispersal is low due to the very brief planktonic phase of the tadpole larvae (~1 h), resulting in settlements close to parental colonies (Grosberg 1987, Rinkevich & Weissman 1987). Long-distance dispersal therefore depends solely on anthropogenically mediated activities. A number of maritime service companies operate shipping lines on a weekly basis from Portugal and Spain to Norway and Sweden (e.g. www.samskip. com; www.macandrews.com; www.dfdslogistics.com), thus supporting our findings. Furthermore, by analyzing gene flow among all 14 clusters that emerged from Bayesian clustering computation (Fig. 4b), the 3 populations inhabiting natural habitats (Auchenmalg, Scotland, Helgoland, Germany, and Plymouth, England), turned out to be genetically isolated from each other and from all of the other marina or harbor populations. This isolation, probably caused by a low frequency of vessel traffic, contributes to the stronger population structure and differentiation found among the western European populations. The results obtained here, coupled with previous studies on European and Mediterranean marine populations (Paz et al. 2003, Ben-Shlomo et al. 2006, López-Legentil et al. 2006), revealed some interesting genetic profiles of ancient and recently established Botryllus schlosseri populations. Further sampling and population genetic analyses of other, as yet unexplored sites in European seas (such as the northern coasts of the Mediterranean Sea and the Black Sea), are required to fully explore the population genetic characteristics of this globally distributed species, whose area of origin is still obscure.
Acknowledgements. We thank G. Paz for technical help and figure preparation and J. Douek for helping in genotyping analyses. This study is part of E.R.’s PhD dissertation and was supported by grants from the Israel Science Foundation (1342/08 and 68/10).
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