Large scale population structure and gene flow in the planktonic developing periwinkle, Littorina striata, in Macaronesia (Mollusca: Gastropoda)

LJournal of Experimental Marine Biology and Ecology246 (2000) 69–83

www.elsevier.nl / locate / jembe

Large scale population structure and gene flow in theplanktonic developing periwinkle, Littorina striata, in

Macaronesia (Mollusca: Gastropoda)a , a a,b*Hans De Wolf , Ron Verhagen , Thierry Backeljau

aEcophysiology and Biochemistry Group and Evolutionary Biology Group,University of Antwerp (RUCA) Groenenborgerlaan 171, B-2020 Antwerp, Belgium

bRoyal Belgian Institute of Natural Sciences (KBIN), Vautierstraat 29, B-1000 Brussels, Belgium

Abstract

Allozymes were used to investigate the genetic structure of 42 populations of the planktonicdeveloping, Macaronesian periwinkle Littorina striata, throughout its entire geographic range(Azores, Madeira, Canary Islands and Cape Verde Islands). This periwinkle is presumed to have ahigh dispersal and gene flow potential, because it has a planktonic development. It is thereforeexpected to show little population genetic differentiation. Indeed, based on Wright’s hierarchicalF-statistics, no significant genetic differentiation could be detected among populations, at any ofthe specified hierarchical levels (i.e. population, island, and archipelago). Nevertheless, the CapeVerde Islands seemed genetically more diverse (highest mean number of alleles per locus). Thenumber of loci revealing a significant genetic heterogeneity increased with increasing distancebetween populations, while private alleles based gene flow (Nm) estimates also revealed atendency towards a geographical pattern. The distribution of rare and private alleles, mightaccount for these observations which suggested some geographical effect. Because of the lowfrequency at which these alleles occur, their influence on the genetic population structure isnegligible, and not picked up by F-statistics. 2000 Elsevier Science B.V. All rights reserved.

Keywords: Allozymes; Gene flow; Littorina striata; Macrogeography; Planktonic development; Macaronesia

1. Introduction

Marine organisms with high dispersal potential often show only limited populationgenetic differentiation, because gene flow is usually positively correlated with dispersal

*Corresponding author. Tel.: 132-3-218-0347; fax: 132-3-218-0497.E-mail address: [email protected] (H. De Wolf,)

0022-0981/00/$ – see front matter 2000 Elsevier Science B.V. All rights reserved.PI I : S0022-0981( 99 )00177-X

70 H. De Wolf et al. / J. Exp. Mar. Biol. Ecol. 246 (2000) 69 –83

ability (e.g. Crisp, 1978; Palumbi, 1994, 1996). In marine gastropods, for example,species with planktonic dispersing larvae display higher levels of gene flow and lesspopulation genetic differentiation (e.g., Mitton et al., 1989; Benzie and Williams, 1992;Brown and Murray, 1995), than nonplanktonic developing species with poor dispersalcapacity (e.g. Johannesson et al., 1993; Johnson and Black, 1995; Rolan-Alvarez et al.,1995; Trussell, 1996). Nevertheless, even in species with high dispersal abilities thereare several factors that may limit actual dispersal and/or gene flow, thus creatingopportunities for genetic differentiation as well (Palumbi, 1994, 1996). These limitationsinclude: invisible gene flow barriers, isolation by distance, behavioral limits to dispersal,selection, and the recent history of a species (Palumbi, 1994, 1996).

For instance, in the Macaronesian (i.e. Azores [AZ], Madeira [MA], Canary Islands[CA] and Cape Verde Islands [CV]) planktonic developing periwinkle, Littorina striata,King and Broderip, 1832, no genetic population differentiation is detected at mi-crogeographical scales (i.e. 5–100 m) (De Wolf et al. 1998a), whereas preliminaryallozyme data tentatively suggest a tendency towards an isolation by distance (IBD)relationship among more distant populations (i.e. up to 500 km) within an archipelago(AZ) (Backeljau et al., 1995). In addition, esterase and random amplified polymorphicDNA (RAPD) patterns reveal a higher degree of genetic variability in the CV than in theother archipelagos (De Wolf et al. 1998b,c).

In this paper we explore the population genetics of L. striata at macrogeographicscales by surveying allozyme data from populations covering the entire knowngeographic distribution of the species (i.e. up to 2000 km). We particularly aim atassessing whether the allozyme variation reveals a macrogeographical patterning and ifso, whether this patterning is indeed related to IBD.

2. Materials and methods

2.1. Sampling sites

Forty-two populations of L. striata (n 5 1640) were collected at comparable wave-exposed sites in 13 Macaronesian Islands, including the archipelagos of the AZ, MA,

˜CA and CV. Sampled islands included: in AZ, Sao Miguel (AZ1–12), Pico: (AZ13–14),˜Santa Maria (AZ15), Faial (AZ16–18), and Sao Jorge (AZ19–20); in MA, Madeira

(MA1–2), Porto Santo (MA3) and Deserta Grande (MA4); in CA, Tenerife (CA1–4)˜and Gran Canaria (CA5–6); and finally in CV, Sao Nicolau (CV1–2), Sal (CV3–7), and

˜Sao Vicente (CV8–12) (Table 1).

2.2. Allozyme electrophoresis

After field collecting, periwinkles were starved for 4 days and subsequently frozenand stored at 2 808C. Sample preparation and protocols for vertical polyacrylamide gelelectrophoresis were as described by Backeljau and Warmoes (1992). Five polymorphicenzyme loci were analyzed. Glucose phosphate isomerase (GPI, E.C. 5.3.1.9), 6-phosphogluconate dehydrogenase (PGD, E.C. 1.1.1.44), and malate dehydrogenase

H. De Wolf et al. / J. Exp. Mar. Biol. Ecol. 246 (2000) 69 –83 71

Table 1Populations that were analysed with their corresponding abbreviations

Archipelago Island Sampling site Abbreviation

˜Azores (AZ) Sao Miguel (SM) Mosteiros AZ1–AZ2Capellas AZ3Santana AZ4Villa de Nordeste AZ5Faial da Terra AZ6

˜Povocao AZ7Caloura AZ8Lagoa AZ9Santa Clara AZ10Feteiras AZ11Ferereia AZ12

Santa Maria (SAM) Anjos AZ13˜Sao Jorge (SJ) F. da St. Cristo AZ14

Urzelina AZ15Pico (PI) Lajes AZ16

Calhau AZ17Faial (FA) P. da Almoxariffe AZ18

Capelinhos AZ19P. da Espalama AZ20

Madeira (MA) Madeira (MA) Canicio de Baixo MA1P. de St. Caterina MA2

Porto Santo (POS) Porto Santo MA3Deserta Grande (DEG) Doca MA4

Canary Is. (CA) Gran Canaria (GRC) Agoustin CA1–CA4Tenerife (TEN) Playa da America CA5–CA6

˜Cape Verde Is. (CV) Sao Nicolau (SAN) Harbour CV1–CV2Sal (SAL) Santa Maria CV3–CV4

Jose Fonseca CV5–CV6Pedro de Lumen CV7

˜Sao Vicente (SAV) Baia das Gatas CV8–CV9Mindelo CV10–CV11Calhau CV12

(MDH, E.C. 1.1.1.37) were resolved in a continuous (gel and tray buffer are identical)Tris–citric acid buffer at pH 8.0, while hydroxybutyric acid dehydrogenase (HBDH,E.C. 1.1.1.30) was resolved in a continuous Tris–boric acid /EDTA buffer at pH 5 8.9.Mannose phosphate isomerase (MPI, E.C. 5.3.1.8) was analyzed using a discontinuousbuffer system with a Tris–glycine tray buffer and a Tris–HCl gel buffer, both at pH 9.0.Enzyme stainings were adapted from Harris and Hopkinson (1976).

2.3. Statistical analysis

Allele frequencies, mean numbers of alleles per locus (MNA) and heterozygositylevels (H 5 observed, H 5 expected) were estimated with the BIOSYS programobs exp

(Swofford and Selander, 1989). Genotype frequency departures from Hardy–Weinberg


(HW) equilibrium conditions were tested with exact probability tests, implemented bythe GENEPOP software v. 1.1 (Raymond and Rousset, 1995), which applies the Markovchain method proposed by Guo and Thompson (1992).

Interarchipelago differences in MNA or H were investigated by means of twoobs

analyses of variance, using the software package STATISTICA v. 5.0 (Statsoft, 1995).Genetic population differentiation can be expressed by means of hierarchical F-

statistics. When a hierarchical arrangement of populations is assumed, in this casepopulations (P) being placed within islands (I), archipelagos (A) and total distributionarea (T), the variance of the observed genetic differentiation among the populations(var ) can be split up into its variance components. A series of F-statistics can beST

obtained (e.g., F , F , F and F ), of which the terms in the following equationPI IA PT AT

(1 2 F ) 5 (1 2 F ) ? (1 2 F ) ? (1 2 F )PT PI IA AT

represent respectively: total differentiation, differentiation among populations withinislands, differentiation among islands within archipelagos, and differentiation amongarchipelagos. These F-values are not additive. Hence, F reflects only the additionalIA

variance among islands beyond that which exists among populations, and F reflectsAT

only additional variance among archipelagos beyond that which exists among islands(Wolf and Campbell, 1995). F-values and corresponding variance components werecalculated with the WRIGHT78 option in BIOSYS (Swofford and Selander, 1989).

Allele frequency heterogeneities among the four archipelagos, were evaluated withFisher exact tests applied to R3C contingency tables as implemented by the GENEPOPv. 1.1 software (Raymond and Rousset, 1995).

The differentiation among islands was further analyzed by means of correspondenceanalysis, executed with the NTSYS v. 1.80 software (Rohlf, 1993).

Gene flow (Nm) among archipelagos was estimated using private allele frequencies(Slatkin, 1985; Slatkin and Barton, 1989). Pairwise Nm values were plotted againstpairwise geographical distances, enabling us to calculate the correlation coefficient andcorresponding regression equation.

A significance level of 5% was used throughout. The sequential Bonferroni techniquewas employed to correct for false assignments of significance by chance alone (multipletest problems) (Rice, 1989).

3. Results

Allele frequencies, H , H , and the results of the HW-tests are given in Table 2.obs exp

Six deviations from HW equilibrium were detected, yet none of these remainedsignificant after Bonferroni correction. Eight alleles were unique to the CV archipelago(GPI-G, MPI-F, PGD-B, PGD-F, MDH-B, MDH-C, MDH-E and HBDH-F) and twoalleles were unique to the AZ (MDH-A, HBDH-A). Private allele frequencies used forestimating Nm among archipelagos are given in Table 4 (below).

MNA differed among the four archipelagos, with CV appearing genetically morediverse (overall MNA54.2), than the other archipelagos (overall MNA53.2) (Fig. 1).


Table 2Allele frequencies, observed (H ) and expected (H ) heterozygosity levels and exact probabilities (P-ext)obs exp

for deviation of Hardy–Weinberg equilibria (population abbreviations see Table 1)

Locus AZ1 AZ2 AZ3 AZ4 AZ5 AZ6 AZ7 AZ8 AZ9 AZ10

GPI (N) 38 37 37 38 38 40 37 34 39 36A 0.026 0.014 0.014 0.013 0.026 0.013 0.027 0.029 0.000 0.014B 0.303 0.297 0.284 0.434 0.237 0.325 0.297 0.309 0.244 0.236C 0.039 0.000 0.000 0.013 0.079 0.000 0.000 0.015 0.077 0.069D 0.593 0.689 0.688 0.514 0.632 0.612 0.622 0.544 0.653 0.653E 0.000 0.000 0.000 0.000 0.013 0.000 0.000 0.000 0.000 0.000F 0.039 0.000 0.014 0.026 0.013 0.050 0.054 0.103 0.026 0.028G 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000H 0.711 0.297 0.405 0.474 0.474 0.475 0.432 0.588 0.333 0.556obs

H 0.554 0.436 0.444 0.547 0.538 0.517 0.522 0.597 0.507 0.512exp

P-ext 0.065 0.044 0.729 0.711 0.061 0.743 0.501 0.910 0.001 0.341

MPI (N) 39 40 40 32 38 40 40 39 37 40A 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000B 0.051 0.138 0.125 0.094 0.053 0.075 0.087 0.115 0.108 0.075C 0.949 0.862 0.875 0.906 0.947 0.912 0.913 0.885 0.892 0.912D 0.000 0.000 0.000 0.000 0.000 0.013 0.000 0.000 0.000 0.013E 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000F 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000H 0.103 0.225 0.200 0.188 0.105 0.150 0.175 0.231 0.216 0.175obs

H 0.097 0.237 0.219 0.170 0.100 0.162 0.160 0.204 0.193 0.162exp

P-ext 1.000 0.548 0.473 1.000 1.000 0.083 1.000 1.000 1.000 1.000

PGD (N) 38 38 39 37 37 38 34 35 34 37A 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000B 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000C 1.000 0.974 1.000 0.946 0.986 0.974 0.971 0.977 0.956 1.000D 0.000 0.026 0.000 0.027 0.014 0.000 0.000 0.000 0.029 0.000E 0.000 0.000 0.000 0.027 0.000 0.026 0.029 0.043 0.015 0.000F 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000H – 0.053 – 0.054 0.027 0.053 0.059 0.086 0.088 –obs

H – 0.051 – 0.102 0.027 0.051 0.057 0.082 0.085 –exp

P-ext – 1.000 – 0.028 – 1.000 1.000 1.000 1.000 –

MDH (N) 40 37 39 37 40 39 36 37 37 40A 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.014 0.000 0.000B 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000C 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000D 1.000 1.000 1.000 1.000 1.000 1.000 1.000 0.986 1.000 1.000E 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000H – – – – – – – 0.027 – –obs

H – – – – – – – 0.027 – –exp

P-ext – – – – – – – – – –

HBDH (N) 36 40 40 39 37 38 36 35 40 40A 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000B 0.000 0.038 0.025 0.013 0.027 0.013 0.042 0.014 0.025 0.000C 0.986 0.899 0.899 0.884 0.865 0.961 0.902 0.986 0.962 0.949D 0.014 0.000 0.013 0.026 0.027 0.000 0.014 0.000 0.000 0.013E 0.000 0.063 0.063 0.077 0.081 0.026 0.042 0.000 0.013 0.038F 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000H 0.028 0.200 0.200 0.231 0.270 0.079 0.194 0.029 0.075 0.100obs

H 0.027 0.185 0.185 0.211 0.244 0.077 0.181 0.028 0.073 0.096exp

P-ext – 1.000 1.000 1.000 1.000 1.000 1.000 – 1.000 1.000


Table 2. Continued

Locus AZ11 AZ12 AZ13 AZ14 AZ15 AZ16 AZ17 AZ18 AZ19 AZ20


H 0.442 0.591 0.544 0.533 0.518 0.422 0.498 0.568 0.478 0.497exp

P-ext 0.664 0.028 0.430 0.537 0.736 0.926 0.234 0.769 0.280 0.592

MPI (N) 39 38 37 39 40 33 38 40 39 38A 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000B 0.115 0.132 0.108 0.128 0.063 0.106 0.132 0.063 0.141 0.158C 0.885 0.868 0.892 0.872 0.937 0.894 0.868 0.932 0.846 0.842D 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.013 0.000E 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000F 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000H 0.231 0.211 0.162 0.256 0.075 0.212 0.211 0.125 0.231 0.263obs

H 0.204 0.229 0.193 0.224 0.117 0.190 0.229 0.117 0.264 0.266exp

P-ext 1.000 0.493 0.344 1.000 0.124 1.000 0.493 1.000 0.084 1.000

PGD (N) 34 37 33 37 40 39 38 39 36 36A 0.000 0.014 0.000 0.014 0.000 0.000 0.000 0.000 0.000 0.000B 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000C 0.985 0.959 0.955 0.958 0.937 0.987 0.961 0.962 0.988 0.988D 0.000 0.000 0.000 0.014 0.000 0.013 0.000 0.038 0.014 0.000E 0.015 0.027 0.045 0.014 0.063 0.000 0.039 0.000 0.028 0.042F 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000H 0.029 0.081 0.091 0.081 0.125 0.026 0.079 0.077 0.083 0.083obs

H 0.029 0.079 0.087 0.079 0.117 0.025 0.076 0.074 0.081 0.080exp

P-ext – 1.000 1.000 1.000 1.000 – 1.000 1.000 1.000 1.000

MDH (N) 40 39 33 39 40 39 38 39 40 38A 0.000 0.013 0.000 0.013 0.000 0.000 0.013 0.000 0.000 0.000B 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000C 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000D 1.000 0.987 1.000 0.987 1.000 1.000 0.987 1.000 1.000 1.000E 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000H – 0.026 – 0.026 – – 0.026 – – –obs

H – 0.025 – 0.025 – – 0.026 – – –exp

P-ext – 1.000 – 1.000 – – 1.000 – – –


H 0.163 0.270 0.056 0.186 0.153 0.097 0.110 0.193 0.190 0.218exp

P-ext 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000


Table 2. Continued

Locus MA1 MA2 MA3 MA4 CA1 CA2 CA3 CA4 CA5 CA6


H 0.452 0.509 0.566 0.530 0.423 0.560 0.495 0.497 0.544 0.521exp

P-ext 0.692 0.017 0.141 0.785 0.408 0.801 0.436 0.221 0.698 0.568

MPI (N) 40 40 40 40 39 40 37 20 40 37A 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000B 0.087 0.112 0.100 0.063 0.103 0.075 0.095 0.075 0.075 0.176C 0.913 0.888 0.900 0.937 0.897 0.912 0.905 0.925 0.925 0.824D 0.000 0.000 0.000 0.000 0.000 0.013 0.000 0.000 0.000 0.000E 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000F 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000H 0.125 0.225 0.200 0.125 0.154 0.175 0.189 0.150 0.150 0.297obs

H 0.160 0.200 0.180 0.117 0.184 0.162 0.171 0.138 0.139 0.290exp

P-ext 0.249 1.000 1.000 1.000 0.328 1.000 1.000 1.000 1.000 1.000

PGD (N) 36 35 34 30 37 34 37 20 38 37A 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000B 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000C 0.958 0.957 0.926 0.884 0.986 0.975 0.932 0.950 0.961 0.918D 0.042 0.029 0.059 0.083 0.000 0.000 0.027 0.025 0.000 0.014E 0.000 0.014 0.015 0.033 0.014 0.015 0.041 0.025 0.039 0.068F 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000H 0.083 0.086 0.147 0.233 0.027 0.059 0.135 0.100 0.079 0.162obs

H 0.080 0.083 0.138 0.212 0.027 0.058 0.126 0.096 0.076 0.151exp

P-ext 1.000 1.000 1.000 1.000 – 1.000 1.000 1.000 1.000 1.000

MDH (N) 40 38 40 36 35 38 40 20 37 34A 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000B 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000C 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000D 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000E 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000H – – – – – – – – – –obs

H – – – – – – – – – –exp

P-ext – – – – – – – – – –


H 0.214 0.176 0.232 0.106 0.127 0.156 0.245 0.141 0.172 0.187exp

P-ext 1.000 1.000 1.000 1.000 1.000 1.000 0.548 1.000 0.261 1.000


Table 2. Continued

Locus CV1 CV2 CV3 CV4 CV5 CV6 CV7 CV8 CV9 CV10 CV11 CV12

GPI (N) 38 38 40 40 40 39 40 39 40 40 40 34A 0.026 0.039 0.038 0.025 0.013 0.013 0.038 0.026 0.025 0.038 0.025 0.015B 0.316 0.158 0.273 0.274 0.200 0.244 0.400 0.474 0.325 0.250 0.450 0.397C 0.026 0.132 0.013 0.000 0.050 0.038 0.000 0.026 0.000 0.000 0.000 0.015D 0.566 0.579 0.613 0.650 0.652 0.615 0.562 0.397 0.550 0.612 0.474 0.544E 0.013 0.066 0.025 0.013 0.050 0.064 0.000 0.026 0.025 0.000 0.013 0.000F 0.053 0.013 0.038 0.038 0.025 0.013 0.000 0.051 0.075 0.075 0.038 0.029G 0.000 0.013 0.000 0.000 0.013 0.013 0.000 0.000 0.000 0.025 0.000 0.000H 0.605 0.533 0.475 0.575 0.500 0.462 0.425 0.641 0.550 0.550 0.575 0.353obs

H 0.576 0.616 0.546 0.500 0.532 0.556 0.522 0.621 0.585 0.555 0.570 0.553exp

P-ext 0.046 0.311 0.338 0.101 0.156 0.196 0.179 0.106 0.789 0.669 1.000 0.003

MPI (N) 33 37 36 38 40 39 40 40 38 40 40 40A 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000B 0.076 0.054 0.056 0.053 0.138 0.115 0.038 0.063 0.066 0.125 0.075 0.125C 0.924 0.946 0.944 0.947 0.862 0.885 0.962 0.925 0.934 0.875 0.913 0.875D 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.013 0.000E 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000F 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.013 0.000 0.000 0.000 0.000H 0.091 0.108 0.111 0.105 0.175 0.231 0.075 0.150 0.132 0.200 0.175 0.250obs

H 0.140 0.102 0.105 0.100 0.237 0.204 0.072 0.140 0.123 0.219 0.162 0.219exp

P-ext 0.150 1.000 1.000 1.000 0.134 1.000 1.000 1.000 1.000 0.473 1.000 1.000

PGD (N) 39 39 40 37 33 39 40 37 38 39 40 39A 0.000 0.013 0.013 0.014 0.000 0.000 0.000 0.000 0.000 0.000 0.013 0.000B 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.026C 0.923 0.923 0.961 0.904 0.970 1.000 0.925 0.878 0.881 0.911 0.974 0.910D 0.000 0.000 0.000 0.041 0.015 0.000 0.000 0.027 0.066 0.000 0.000 0.013E 0.026 0.013 0.013 0.041 0.015 0.000 0.025 0.041 0.000 0.038 0.013 0.051F 0.051 0.051 0.013 0.000 0.000 0.000 0.050 0.054 0.053 0.051 0.000 0.000H 0.103 0.154 0.075 0.135 0.061 – 0.150 0.135 0.184 0.179 0.050 0.154obs

H 0.145 0.145 0.073 0.177 0.059 – 0.141 0.223 0.216 0.167 0.049 0.168exp

P-ext 0.091 1.000 1.000 0.161 1.000 – 1.000 0.001 0.219 1.000 1.000 0.255

MDH (N) 40 39 40 40 40 39 40 40 40 40 40 40A 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000B 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.013 0.000 0.000 0.000 0.000C 0.000 0.000 0.000 0.013 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000D 1.000 1.000 1.000 0.987 1.000 1.000 1.000 0.987 1.000 1.000 1.000 1.000E 0.000 0.000 0.000 0.000 0.013 0.000 0.000 0.000 0.000 0.000 0.000 0.000H – – – 0.025 0.025 – – 0.025 – – – –obs

H – – – 0.025 0.025 – – 0.025 – – – –exp

P-ext – – – 1.000 1.000 – – 1.000 – – – –

HBDH (N) 39 39 39 33 39 39 40 39 40 40 39 39A 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000B 0.013 0.026 0.013 0.000 0.000 0.013 0.000 0.038 0.038 0.038 0.038 0.000C 0.936 0.897 0.949 0.879 0.936 0.936 0.899 0.885 0.875 0.997 0.885 0.897D 0.000 0.000 0.000 0.015 0.000 0.013 0.038 0.000 0.000 0.000 0.000 0.013E 0.051 0.077 0.038 0.106 0.051 0.038 0.050 0.064 0.087 0.050 0.064 0.077F 0.000 0.000 0.000 0.000 0.013 0.000 0.013 0.013 0.000 0.025 0.013 0.013H 0.128 0.154 0.103 0.242 0.128 0.128 0.200 0.179 0.200 0.175 0.231 0.154obs

H 0.121 0.188 0.098 0.216 0.121 0.122 0.186 0.212 0.225 0.208 0.212 0.188exp

P-ext 1.000 0.328 1.000 1.000 1.000 1.000 1.000 0.046 0.047 0.208 1.000 0.328


Fig. 1. Graphical representation of mean number of alleles per locus at each of the four archipelagos(AZ5Azores; MA5Madeira; CA5Canary Islands; CV5Cape Verde Islands).

This difference was nearly significant (P50.0507) and therefore indicated a ‘‘ten-dency’’. In contrast, H did not differ significantly among the four archipelagosobs

(P50.4826). All F indices were small, indicating no population differentiation at anyxy

of the three analysed hierarchical levels (i.e. F 50.005; F 50.002; F ,0.001).PI IA AT

After Bonferroni correction, eight significant allele frequency heterogeneities weredetected when the archipelagos were compared: three (i.e. GPI, PGD, HBDH) amongCV and AZ, two (i.e. GPI, PGD) among CV and MA, one (i.e. PGD) among CV andCA, one (i.e. PGD) among MA and CA, and one among AZ and MA (i.e. PGD) (Table3).

The first axis of the correspondence analysis, which explained 33.19% of thevariation, separated the CV from the remaining Macaronesian Islands. This axis mainly

Table 3aExact tests of allele frequency heterogeneities, according to Guo and Thompson (1992)

GPI MPI PGD MDH HBDH

*AZ–MA 0.05076 0.79000 0.00036 1.00000 0.42472AZ–CA 0.84836 1.00000 0.27278 0.58522 0.41846

* * *AZ–CV 0.00001 0.05454 0.00001 0.03950 0.00046*MA–CA 0.13578 0.84030 0.00102 – 0.79490

* *MA–CV 0.00136 0.71848 0.00026 1.00000 0.55006*CA–CV 0.02208 0.27440 0.00182 1.00000 0.26526

* Significant after sequential Bonferroni correction.a AZ5Azores; MA5Madeira; CA5Canary Islands; CV5Cape Verde Islands.


Fig. 2. Regression analysis of pairwise Nm estimates against pairwise geographical distances.

expressed effects of PGD-F, GPI-A, GPI-E, and GPI-G. The second factor discriminatedthe MA from the other archipelagos, mainly on the basis of PGD-D and GPI-C. Thisfactor explained only an additional 18.14% of the variation making it less informative.

Both the regression analysis among pairwise Nm values and geographic distances(Fig. 2) as well as a plot of private alleles based gene flow estimates on a geographicmap of Macaronesia (Fig. 3), were reminiscent of IBD. Hence, the highest Nm valuewas observed among MA and CA, the lowest among AZ and CV (Fig. 3, Table 4).

4. Discussion

As in other planktonic developing species, population differentiation measured byF-statistics was negligible. With F values ranging from 0.005 to ,0.001, they fell wellxy

within the range of F values reported in other planktonic developers (e.g. Mitton et al.,xy

1989; Benzie and Williams, 1992; Johannesson, 1992; Stiven, 1992; Ford and Mitton,1993; Karakousis et al., 1993; Saavedra et al., 1993). This confirms the expectation, (e.g.Crisp, 1978; Mitton et al., 1989), that the planktonic development of L. striata decreasesthe likelihood of genetic population differentiation.

Although no significant genetic population differentiation was detected by F-statistics,there still were the following observations: (1) the nearly significant higher MNA in CV;(2) the number of loci showing allele frequency heterogeneities among archipelagos


Fig. 3. Graphical representation of gene flow intensities (bold lines) between the different Macaronesianarchipelagos, based on private allele frequencies. Dotted arrows indicate major oceanic sea currents (AZ5

Azores; MA5Madeira; CA5Canary Islands; CV5Cape Verde Islands; NAC5North Atlantic Sea Current;LC5Labrador Sea Current).

increasing with increasing geographic distance (from one among CV and CA to threeamong CV and AZ); (3) the separate ordination of CV in the correspondence analysis;and (4) the suggestive relationship among the private allele based Nm values and thegeographical distance, which needed to be explained.

These observations, none of which of is related to heterozygosity levels, might be

Table 4Gene flow (Nm) estimates based on the frequency of private alleles, P(1), according to Slatkin (1985) (I) and

aSlatkin and Barton (1989) (II), for each of the possible archipelago comparisons

N P(1) Nm I Nm II Pairwise geographicsam

distance (km)

AZ–MA 450.4 0.0018 120.5 37.8 960AZ–CA 478.9 0.0020 92.0 29.9 1200AZ–CV 610.2 0.0039 19.2 7.8 2400MA–CA 175.4 0.0020 251.2 81.7 432MA–CV 316.8 0.0051 21.8 9.7 1440CA–CV 306.6 0.0057 18.1 8.4 1200

a N 5actual average sample size; AZ5Azores; MA5Madeira; CA5Canary Islands; CV5Cape Verdesam

Islands.


explained by the distribution of rare alleles (i.e. alleles occurring at low frequencies) andprivate alleles (i.e. alleles that occur in a single population). In contrast to theF-statistics, all other statistics used in this study (i.e. MNA, genetic heterogeneityanalysis, correspondence analysis, P(1) based Nm estimation) might seriously beaffected by the presence /absence of alleles occurring at very low frequencies, which allprivate alleles in this study do. Effects of private alleles are not so much picked up byF-statistics, because with this approach, the variance in allele frequency amongpopulations at a given locus is standardized by its mean allele frequency. Effects of afew alleles occurring in a single or a few populations at small frequencies are overridenby the effects of alleles, occurring in all populations at consistently high frequencies.Private alleles were found at the CV archipelago (i.e. eight) and at the AZ (i.e. two), andaccounted for respectively 26.6% and 6.6% of all alleles found at both island groups.Hence, in contrast to the F-statistics, these alleles do seem to suggest a geographicalpattern. Obviously this suggestive distribution of private alleles remains to be explained,particularly as a parallel study of esterase variation suggested an increase in meannumber of esterase bands for the CV populations (De Wolf et al., 1998b), while a studyof RAPD loci revealed yet again a higher degree of genetic variability at the CVpopulations when compared to the other Macaronesian populations (De Wolf et al.1998c).

Strict IBD might explain the nonrandom allelic distribution, though seems unlikelygiven that only private alleles were nonrandomly distributed. If IBD would affect thedistribution of alleles, one would expect it to affect all alleles, which is clearly not thecase.

In the absence of any detailed information on the larval behaviour of L. striata, weassume that the distribution of private alleles in L. striata is affected by invisible barriersto gene flow (i.e. direction of the sea currents) and the recent history of the species.

As the present day clockwise oceanic circulation (Fig. 3) has not changed much sincethe opening of the North Atlantic, during the Jurassic (Berggren, 1980), it would seemthat larval dispersal patterns in Macaronesia may have been quite constant too. Thisseems somewhat problematic since: (1) the oldest fossil of L. striata is known fromtertiary deposits in the CV (Reid, 1996); (2) the CV, together with Fuerteventura andGomera (i.e. CA) are with their alleged Jurassic or Cretaceous origin the oldest

´Macaronesian Islands (Mitchell-Thome, 1976); (3) L. striata might possibly haveoccupied the Eocene and Oligocene Macaronesian shores (i.e. CV1Fuerteventura1

Gomera) (see Fig. 120 in Reid, 1996), long before the AZ emerged above sea level; and(4) the CV populations of L. striata are both morphologically and genetically morediverse than elsewhere (De Wolf et al., 1998b,c,d). All these observations suggest that L.striata colonized the AZ from the CV.

Yet the clockwise oceanic circulation seems contradictory with this idea for it requiresan extensively large dispersal route via the Caribbean and Gulf Stream. Nevertheless, inthe past the Atlantic Ocean did not have its present width (Adams, 1981), while pastsurface currents across the Atlantic were stronger than in present days (Scheltema, 1995;Reid, 1996). It seems therefore possible that larvae originating from the CV may havereached the AZ in pre- or early Miocene times via the westward clockwise circulation,which is also supposed to have been at the basis of the littorinid colonization of the


Pacific after an ancestral species migrated from the eastern Atlantic to the west coast ofNorth America via the Panama Strait (Reid, 1996).

The subsequent further widening of the Atlantic and the decrease in surface currentintensity may have gradually prevented continued gene flow from CV to AZ, so that CVno longer acted as source for gene flow to the north. This could explain: (1) the highernumber of private alleles in CV; and (2) the elevated genetic and morphologicaldiversity in CV.

A possible test for this hypothesis should include an estimation of the duration of thelarval dispersal stage and a survey of plankton following the westward currents from theCV. In addition, if this scenario would be correct, we would expect that the two AZprivate alleles are relatively recent and have not yet spread towards the south. Theproposed migration scenario is highly tentative and for example does not consider thepossibility of human transport, which cannot be a priori excluded given the intense navaltraffic in Macaronesia (Grunning, 1967).

In conclusion, this migration scenario only accounts for the distribution of the privatealleles. It does not suggest a hierarchical population genetic structuring, for such astructuring was not apparent. This was previously also reported by De Wolf et al.(1998b), who found no differentiation among radular myoglobin patterns among L.striata from the four archipelagos.

Finally the lack of genetic structuring does not necessarily mean that there is nostructure, especially as only five polymorphic enzyme loci were involved in thisanalysis, of which one was relatively invariable (i.e. MDH). Nevertheless similar results(i.e lack of genetic structuring and elevated genetic variability in CV) were obtained intwo other population genetic surveys, involving the analysis of esterase and RAPDprofiles (De Wolf et al. 1998b,c), suggesting that the present allozyme data is sufficientlyinformative, and that IBD is indeed not affecting the population genetic structure of L.striata.

Acknowledgements

This research was supported by the MAST 3 programme of the European Commissionunder contract number MAS3-CT95-0042 (AMBIOS) and PRAXIS XXI 2/2.1 /BIA/169/94 (Portugal). Travel expenses were partly covered by STRIDE, Portugal. Theauthors would like to thank D. Verbergt (Hogere Zeevaartschool, Antwerpen), P.G.B.Jones (Hydrographic office of the UK) and J. Geys (RUCA, Antwerpen) for providingus with background information and literature, while H. Van Paeschen (KBIN) kindlymade the drawings. H. De Wolf is a Postdoctoral Fellow of the Fund for ScientificResearch — Flanders (Belgium) (F.W.O.). [SS]

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Large scale population structure and gene flow in the planktonic developing periwinkle, Littorina striata, in Macaronesia (Mollusca: Gastropoda)