Congruence between fine-scale genetic breaks and
dispersal potential in an estuarine seaweed across
multiple transition zones

Katy R Nicastro, Jorge Assis, Ester Álvares Serrão, Gareth A. Pearson, João

Neiva, Myriam Valero, Rita Jacinto, Gerardo I Zardi

<figure><img src="image_1.png" /></figure>

To cite this version:

Katy R Nicastro, Jorge Assis, Ester Álvares Serrão, Gareth A. Pearson, João Neiva, et al.. Congruence between fine-scale genetic breaks and dispersal potential in an estuarine seaweed across multiple transition zones. ICES Journal of Marine Science, 2020, 77 (1), pp.371-378. 10.1093/icesjms/fsz179 . hal-02406672

HAL Id: hal-02406672

https://hal.science/hal-02406672

Submitted on 12 Dec 2019

**HAL** is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire **HAL**, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_2.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
<figure><img src="image_3.png" /></figure>

Congruence between fine-scale genetic breaks and dispersal potential in an estuarine seaweed across multiple transition zones.

<table><tr><td>Journal:</td><td>ICES Journal of Marine Science</td></tr><tr><td>Manuscript ID</td><td>ICESJMS-2019-167.R2</td></tr><tr><td>Manuscript Types:</td><td>Original Article</td></tr><tr><td>Date Submitted by the Author:</td><td>04-Sep-2019</td></tr><tr><td>Complete List of Authors:</td><td>Nicastro, Katy; CCMAR<br>Assis, Jorge; CCMAR<br>Serrão, Ester; University of Algarve, CCMAR- Centre of Marine Sciences<br>Pearson, Gareth; CCMAR<br>Neiva, Joao; CCMAR<br>Jacinto, Rita; CCMAR<br>Valero, Myriam; CNRS<br>Zardi, Gerardo; Rhodes University, Dept Zoology and Entomology</td></tr><tr><td>Keyword:</td><td>Biogeography, physical modelling, gene flow, Fucus spp.</td></tr></table>

SCHOLARONE™
Manuscripts
1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

58

59

60

1

Congruence between fine-scale genetic breaks and dispersal potential in an estuarine seaweed across multiple transition zones.

2

3

4

Katy R. Nicastro¹, Jorge Assis¹, Ester A. Serrão¹, Gareth A. Pearson¹, João Neiva¹, Myriam

5

Valero², Rita Jacinto¹, Gerardo I. Zardi³*

6

¹CCMAR-CIMAR – Associated Laboratory, University of Algarve, Campus de Gambelas,

7

Faro, 8005–139, Portugal

8

²UMI 3614 Evolutionary Biology and Ecology of Algae, CNRS, Sciences Sorbonne

9

Université, UC, UACH, Station Biologique de Roscoff, Roscoff Cedex, France

10

³Department of Zoology and Entomology, Rhodes University, Grahamstown, 6140, South

11

Africa

12

*corresponding author: zardi73@yahoo.it, +351 927738340

13

14

Additional emails:

15

KRN: katynicastro@gmail.com

16

JA: jorgemfa@me.com

17

EAS: eserrao@ualg.pt

18

GAP: gpearson@ualg.pt

19

JN: jmneiva@ualg.pt

20

MV: myriam.valero@sb-rocoff.fr

21

RJ: ritajacinto85@gmail.com

22

Running head: Congruence between fine-scale genetic breaks and dispersal potential.

23

Keywords: Biogeography, physical modelling, gene flow, Fucus spp.

24
25 ABSTRACT

26 Genetic structure in biogeographical transition zones can be shaped by several factors
27 including limited dispersal across barriers, admixture following secondary contact, differential
28 selection and mating incompatibility. A striking example is found in Northwest France and
29 Northwest Spain, where the estuarine seaweed *Fucus ceranoides* L. exhibits sharp, regional
30 genetic clustering. This pattern has been related to historical population fragmentation and
31 divergence into distinct glacial refugia, followed by post-glacial expansion and secondary
32 contact. The contemporary persistence of sharp ancient genetic breaks between nearby
33 estuaries has been attributed to prior colonization effects (density barriers) but the effect of
34 oceanographic barriers has not been tested. Here, through a combination of mesoscale
35 sampling (15 consecutive populations) and population genetic data (mtIGS) in NW France,
36 we define regional genetic disjunctions similar to those described in NW Iberia. Most
37 importantly, using high resolution dispersal simulations for Brittany and Iberian populations,
38 we provide evidence for a central role of contemporary hydrodynamics in maintaining genetic
39 breaks across these two major biogeographic transition zones. Our findings further show the
40 importance of a comprehensive understanding of oceanographic regimes in hydrodynamically
41 complex coastal regions to explain the maintenance of sharp genetic breaks along
42 continuously populated coastlines.

44 INTRODUCTION

45 Fueled by current concerns about the impacts of global change on biodiversity, there is a
46 renewed interest in understanding the processes affecting a species' range dynamics as well
47 as the factors shaping its genetic diversity. Generally, both historical and contemporary
48 processes are invoked to explain the distribution and phylogeography of a species. Tectonic
49 events and past climate fluctuations created topographic, environmental and hydrologic
50 barriers that were key in shaping phylogeographic structure of many plant and animal species.
51 Of these, the Last Glacial Maximum is probably the most significant and recent historical event
1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

58

59

60

52 (e.g., Hewitt, 2000; Barnes et al., 2002; Liang et al., 2017; Neiva et al., 2018). During this time, ice sheets covered much of current cold and temperate zones of the Northern Hemisphere, triggering range fragmentation and contractions of entire ecosystems to more southern latitudes, while during the present interglacial, widespread range shifts and poleward expansions have occurred.

57 It is predicted that genetic diversity is lowest in recently colonized areas and highest in refugial areas where long-term persistence was possible (e.g., Hewitt, 1996; Comps et al., 2001; Hewitt, 2004; Kennedy et al., 2017). However, contemporary demographic processes can either mask or even erase genetic signatures of population expansions or retreats (Smith et al., 2011). High levels of gene flow may homogenize genetic diversity among previously structured populations. On the other hand, nonrandom mating with individuals in close geographic proximity can generate genetic structuring within a continuous population (Slatkin, 1993). Intrinsic characteristics of the species such as dispersal ability, migration patterns and changes in population densities can further confound any historical signature (e.g., Mims et al., 2015; Chust et al., 2016; Assis et al., 2018).

67 Biogeographical transition regions provide a good framework for exploring and understanding genetic structuring of species through space and time. These are areas of overlap and segregation between different biotic components, and geographically separated clades often coincide with these transition zones (Ferro and Morrone, 2014). In the marine realm, phylogeographic breaks in biogeographical transition regions are generally attributed to historical processes or contemporary dispersal barriers, such as upwelling phenomena and currents that may limit along-shore dispersal, environmental differences boosting local adaptation and/or reproductive strategies maintaining self-recruitment (Gilg and Hilbish, 2003; Zardi et al., 2007; Selkoe et al., 2010).

76 There are well known biogeographical boundaries in all oceans, some of which are associated with oceanographic features that generate contemporary barriers to dispersal. For example, the strong southward-flowing Agulhas Current, which runs about 10 km offshore along most of South Africa's east and southeast coast, impedes larval dispersal and thus promotes local
1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

58

59

60

80 adaptation (Teske et al., 2011; Zardi et al., 2011). Dispersal and gene flow around Point Conception in southern California are also strongly affected by extensive upwelling of colder sub-surface waters and by the southward California Current (Wares et al., 2001; Hohenlohe, 2004; Johansson et al., 2015).

84 Here, we investigated the contribution of contemporary oceanographic connectivity in maintaining geographically separated genetic clades within a continuously distributed seaweed species along the biogeographic transition areas of Brittany (northwest France, Europe) and northwest Iberia (northern Spain, Europe; Fig. 1). These two areas are highly relevant for studying this question and marine connectivity in general. Both areas delimit the boundaries between cold-temperate and warm-temperate regions (Spalding et al., 2007), they are refugial zones for numerous species (Provan, 2013) and, over the past decades, they have undergone significant changes in macroalgae assemblages due to climate change (Nicastro et al., 2013; Gallon et al., 2014; Assis et al., 2017).

93 In this study, we use phylogeographic analyses and Lagrangian Particle Simulations (LPS) coupled with network analyses to evaluate the levels of congruence between dispersal potential and the patterns of present-day genetic differentiation and diversity in the estuarine seaweed *Fucus ceranoides* along these two biogeographic transition zones. This species is perennial, dioecious and restricted to estuarine intertidal areas. Fucoid seaweeds have no planktonic dispersal stage and have restricted gamete dispersal (Serrão et al., 1997). However, adult individuals can achieve long distance gene flow via the rafting of whole or partially detached thalli with reproductive structures (Thiel and Haye, 2006; McKenzie and Bellgrove, 2008), a form of population connectivity strongly influenced by hydrodynamic forces and coastal topography. Currently, *F. ceranoides* is distributed from northern Portugal to northern Norway (Lein, 1984) and Iceland (Munda, 1999), covering both past non-glaciated and glaciated regions of Europe. Previous studies have shown the occurrence of two divergent genetic lineages in this species between the south and the north of Europe, the phylogeographic break being localized in Northwest France near the English Channel (Neiva et al., 2012a; Neiva et al., 2012b). Specifically, the dominant Northwest Iberian haplotypes of
1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

58

59

60

108

this species was found in southern Brittany but not after the genetic break in northern Brittany (Neiva et al., 2010). We discuss three scenarios for the concordance between present-day oceanographic dispersal barriers and the observed genetic differentiation among *F. ceranoides* estuarine populations: 1) Contemporary oceanographic barriers to dispersal are responsible for the origin, the position and the maintenance (i.e. delaying genetic homogenization) of the genetic differentiation; 2) Contemporary oceanographic circulation patterns explain the position, the maintenance but not the origin of the genetic differentiation; 3) Reproductive isolation, in addition to contemporary oceanographic patterns, limits genetic homogenisation thus contributing to the position and the maintenance of the genetic differentiation.

108

109

110

111

112

113

114

115

116

117

118

119

## MATERIALS

120

### Genetic data

121

The two study areas (NW France and NW Spain) are peninsulas characterized by complex and variable circulation patterns (Puillat et al., 2004; Varela et al., 2005; Ruiz-Villarreal et al., 2006; Ayata et al., 2011). Because of that, sampling of only a limited number of localities would be inappropriate. We therefore decided to sample a small number of individuals at as many sites along the two coastlines as possible, rather than obtaining large numbers of individuals from a limited number of sites (e.g., Sotka et al., 2004; Teske et al., 2007). This decision was also supported by the very low genetic diversity within localities for this species (Neiva et al., 2010; 2012b; Neiva et al., 2012a). As a result, two sets of sequences of *Fucus ceranoides* were prepared and analyzed separately. The first data set (Data set 1) comprised sequences of individuals collected in the estuaries of all major rivers between Hennebont (HB, southern Brittany) and Camarel (CM, northern Brittany) in northwest France (n = 2 from each site; Table S1). The second dataset (Data set 2) consisted of sequences previously analysed in Neiva et al. (Neiva et al., 2010; 2012b; Neiva et al., 2012a) and sampled across northern Iberia between Viana do Castelo (VIA, northern Portugal) and Porcia (POR, northern Spain). To

122

123

124

125

126

127

128

129

130

131

132

133

134
allow a comparison between data sets, a random subsample of 2 individuals from each site was used for Data set 2. The random subsampling in NW Spain was repeated to ensure consistency in the results obtained.

Sampling was performed in 2014-2015 and conducted with similar *criteria* for individuals used in both data sets. All collection sites were characterized by monospecific belts of *F. ceranoides* attached to hard substrata and were exposed to steep salinity fluctuations throughout the tidal cycle. At each site, 5-10 cm tips of apical vegetative tissue were collected from individuals sampled in the mid distributional range of the species. Neighboring sites were at an average proximity of about 50 (±15) and 33 (±17) km for Data sets 1 and 2 respectively. All samples were individually stored dehydrated in silica-gel crystals until DNA extraction.

### DNA isolation and sequencing of data set 1

To compile Data set 1, genomic DNA was extracted from approximately 10 mg of dried tissue using the Nucleospin® Multi-96 plant kit (Macherey-Nagel Duren, Germany), according to the manufacturer's protocol. Individuals were sequenced for the mitochondrial 23 S/trnK intergenic spacer (mtIGS, Neiva et al., 2010). Primer sequences and amplification details were the same as in Neiva et al. (Neiva et al., 2010; 2012b; Neiva et al., 2012a). Amplified fragments were run in an ABI PRISM 3130xl automated capillary sequencer (Applied Biosystems, CCMAR Portugal). MtDNA sequences were aligned, proofread and edited in GENEIOUS 3.8 (Drummond et al., 2011).

### Data analyses

For both data sets, haplotype frequencies were estimated using DnaSP 5.0 (Librado and Rozas, 2009). The relationships among the MtIGS haplotypes were inferred using statistical parsimony with Tcs v. 1.13 (Clement et al., 2000). Because additional subsampled dataset for the Iberia provided similar results (Table SI2 and Fig. SI1), only one was used for the simulations.

### Dispersal simulations

The main oceanographic regions in northwest France and northwest Iberia (~550km and ~600km of coastlines, respectively) were identified by coupling Lagrangian Particle
1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

58

59

60

163

Simulations (LPS) with network analyses (least cost distance and community algorithm, e.g., Assis et al., 2015; Klein et al., 2016; Assis et al., 2018). The simulations used daily data of ocean currents assembled from the Hybrid Coordinate Ocean Model (HYCOM), a resolution product with a spatial resolution of 0.08° (approx. 6–9 km), forced by wind speed, wind stress, precipitation and heat flux. This model can resolve oceanic fronts, meandering currents, filaments and eddies (Chassignet et al., 2007), important mesoscale processes to properly simulate ocean dispersal (Assis et al., 2015; Klein et al., 2016).

170

Both regions of simulation were gridded to a common spatial resolution of 0.01° (approx. 1km). A polygon representing global coastlines - OpenStreetMap geographic information (Haklay and Weber, 2008)- was used to define intertidal source and sink cells. Passive particles simulating rafts of *F. ceranoides* adult individuals were released from each gridded cell every 12 hours and allowed to drift for 60 full days; an extreme period for long-lived rafts of brown macroalgae (Monteiro et al., 2016; Assis et al., 2018). This approach aimed to capture the rare, long-distance dispersal events, allowing gene flow at the scales of both regions (Monteiro et al., 2016; Assis et al., 2018). After the 60 days period, or when ending up on shore, the particles were removed from the simulation. The geographic position of all particles was calculated every hour with bilinear interpolation on the ocean velocity fields (with a spatial resolution of 0.08°), while combining a 4th Order Runge-Kutta adaptive time-step on the path equations (e.g., Lett et al., 2008; Klein et al., 2016).

171

172

173

174

175

176

177

178

179

180

181

182

The degree of connectivity between all pairs of gridded cells was determined by dividing the number of unique particles released from cell i that ended up in cell j, by the total number of particles released from cell i. To account for the inter-annual variability in the ocean data, the simulations ran independently per year (from January to December), for the most recent 10-year period of data, available in HYCOM (i.e., 2003 to 2012). Asymmetrical connectivity matrices were determined by averaging the outcomes of the annual simulations.

183

184

185

186

187

188

The connectivity matrices were used in network analyses (i.e., graph theory) to infer the major oceanographic regions of northwest Iberia and northwest France. To this end, network percolation removed weak probabilities to a threshold maintaining all cells (nodes) connected

189

190
1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

58

59

60

191

into a single network (Rozenfeld et al. 2008; Cunha et al., 2017), while maximizing modularity, which quantified the strength of the backbone structure (or goodness of fit) of the networks (Newman, 2006). This allowed the removal of surplus connections with unimportant information. The leading eigenvector algorithm (Newman, 2006) was applied to the percolated networks to assign a unique membership to the nodes. This approach allowed the detection of communities in the networks (e.g., Munwes et al., 2010), which in practice translated into a delineation of oceanographic regions in northwest Iberia and northwest France structured by connectivity of ocean currents (Assis et al., 2018). The statistical significance of the membership assignment to the nodes was inferred by testing the proportion of 9999 membership randomizations that retrieved a higher modularity than that observed.

201

Lagrangian Particle Simulations and network analyses were performed in R (R Development Core Team, 2016) using the packages: data.table (Dowle et al., 2019), dismo (Hijmans et al., 2017), igraph (Kamvar et al., 2014), parallel (Team, 2018), raster (Lamigueiro et al., 2018) and vegan (Oksanen et al., 2018).

205

206

## RESULTS

207

In Data set 1 (NW France), six mtIGS haplotypes were identified in 30 individuals of *Fucus ceranoides* in 15 sampled sites. In NW France, the network analyses showed two dominant haplotypes (A and D) plus three derived ones (B, C and E), each private to one population (Fig 1a). Haplotype frequency distribution revealed a geographical segregation of the two main haplotypes. Haplotype 1 was present in individuals from regions R1 and R2 while Haplotype D was restricted to more northern sites within region R3.

208

209

210

211

212

213

Out of 415 sequences retrieved from the GenBank, 52 sequences were randomly selected for Data set 2 (northwest Iberia). The network showed seven main haplotypes of which two were shared among six to ten populations and three were shared by two to three populations. The remaining two haplotypes were private to one single population. In the frequency distribution, the main haplotype was restricted to region R5 and haplotype F was present only in region

214

215

216

217
R4. Haplotype A was present in regions R3 and R1 while haplotype B was confined to region

## R2. Dispersal simulations

The LPS using HYCOM ocean currents over the 10-year period released 7300 particles per cell (7.80e10⁶ and 7.88e10⁶ particles in total in northwest France and northwest Iberia, respectively). Particles drifted for longer distances in northwest Iberia than in northwest France (up to 431.2 km; Table 1; Fig. SI2). The maximum period of drifting time was also higher in northwest Iberia (26.7 days), but on average, particles drifted for longer periods in northwest France (3.61±2.63 days). The maximum probability of connectivity between the pairs of cells was observed in northwest France (western Britany; 0.721). However, the average cell probabilities within regions did not vary considerably (Table 1; Fig. SI2).

The assignment of oceanographic regions performed by the leading eigenvector algorithm (network analysis) for northwest France and northwest Iberia showed significant modularity values of 0.41 and 0.57 (p-values < 0.001), respectively. The algorithm identified three regions in northwest France (Fig. 1a), with breaks in Penmarch and Porspoder, and five regions in northwest Iberia (Fig. 1b), with breaks in Ria de Arousa, Corrubedo, Camelle (northern Costa da Morte) and Cabo Ortegal (Cariño). The average probability of connectivity within the oceanographic regions of northwest France (diagonal of Fig. 1d) was 10-fold higher than between regions, with the exception of those between R1 and R2 (Fig. 1d), which were of the same order of magnitude. Following a similar pattern, the probabilities of connectivity in northwest Iberia were 10 to 100-fold higher within regions than between regions (diagonal of Fig. 1e), with a marked increase as the distance between groups increased.

## DISCUSSION

Our results show an overall strong match between oceanographic regions identified by dispersal simulations and fine-scale genetic discontinuities in the estuarine seaweed *Fucus ceranoides* inhabiting north Atlantic shores (Fig. 1).
Predictions of oceanographic transport made with Lagrangian particle simulations are highly sensitive to the inner spatial and temporal resolution of circulation models (Putman and He, 2013). While we preserved the raw circulation processes modelled by Hycom at the scales of days and tens of kilometers, a main limitation may arise if additional oceanographic processes occurring at smaller scales are important for realistic connectivity events shaping the genetic structure of *F. ceranoides*. For instance, circulation models with coarse spatial resolutions may underestimate drifting times up to a factor of ~2. In the same way, weekly or even daily temporal time steps may not be a realistic representation of what organisms continuously experience (Fossette et al., 2012). Regardless of such potential limitations, our results compared with independent genetic data, as well as additional studies comparing connectivity estimates with satellite-tracked organisms (e.g., Fossette et al., 2012) suggest that, overall, particles advected by Hycom data provide a reliable estimate of the main processes shaping current flow.

Previous studies have shown that mtIGS differentiation and contemporary *F. ceranoides* genetic structuring in NW Iberia is most likely the result of complex, past range dynamics (Neiva et al., 2012a). High levels of endemism and diversity highlighted by genetic analyses of *F. ceranoides* populations inhabiting this region indicate long-term persistence in glacial refugia. Despite the refugial role played by NW Iberia, sea level changes associated with glacial/inter-glacial expansion and melting of ice-sheets had significant effects on near-shore habitats (Chao et al., 2002; Roucoux et al., 2005). The current fine-scale genetic breaks in Iberian *F. ceranoides* are the result of past fragmentation and divergence of populations into distinct refugia (estuarine refugia within regional refugia), followed by expansion and secondary contact of vicariant phylogroups (Neiva et al., 2012b).

In addition to southern European refugia, the ice-free paleo-shores of northwest France (western Brittany) together with south western Ireland and the English Channel have been recognized as northern periglacial refugia for several species (*Palmaria palmata* (Provan et al., 2005); *Celleporella hyalina* (Gomez et al., 2007); *Fucus serratus* (Hoarau et al., 2007); *Neomysis integer* (Remerie et al., 2009); *Ascophyllum nodosum* (Olsen et al., 2010)
contribute to reduced dispersal efficiency and the variable patterns of gene flow between coastal and estuarine habitats (Zardi et al., 2013).

Density barrier effects are usually particularly marked in species such as *F. ceranoides* characterized by rapid population growth and consequent habitat saturation. The dense, monospecific *F. ceranoides* canopies typical of European northern Atlantic estuaries act as a demographic buffer against numerically rare inter-estuarine immigrants favoring the conservation of pre-existing genetic structure.

Clearly, the abundance of estuaries and their proximity strongly suggest that distance can be excluded from the list of determinants maintaining *F. ceranoides* genetic breaks along these shores. In NW Iberia, the mean distance between populations inhabiting neighboring estuaries is not significantly different than that between bordering populations across phylogeographic breaks (Neiva et al., 2012b). Similar distributional patterns can be found in Brittany where several edge populations are spatially closer to populations across regional genetic disjunctions than they are to their adjacent population within the same genetic clade. While some studies carried out between cold- and warm-temperate marine ecosystems along the northwest coast of France have invoked distinct mesoscale hydrographic features as drivers of genetic patterns (Goldson et al., 2001; Jolly et al., 2005; Couceiro et al., 2013; Almeida et al., 2017), others have highlighted lack of evidence for the role of hydrodynamics as dispersal determinants for the observed genetic discontinuities along NW Iberian shores (Neiva et al., 2012b). The latter works have also stressed the difficulties to track drifters' movements at a scale relevant for the organism to estimate migration rates among estuaries and phylogroups. In NW Iberia, circulation dynamics are complex with high seasonal variability and lack of persistent oceanographic patterns (Ruiz-Villarreal et al., 2006; Alvarez et al., 2009). Here, through the use of large scale, dispersal simulations we reveal several oceanographic regions matching haplotype segregation. Our findings add important evidence to previous conclusions and support the scenario of key, mesoscale oceanographic processes having a determinant role in explaining the position of the observed high levels of regional genetic divergence. We also hypothesized that mesoscale oceanographic dispersal barriers
1
2
3 328 are key to the maintenance of inter-estaurine genetic differentiation. In a neutral model of
4
5 secondary contact following allopatric differentiation, signs of secondary intergradation are
6
7 generally observed around oceanographic barriers (Woodruff, 1973; Barton and Hewitt, 1985;
8
9 Bierne et al., 2011). Admixed nuclear background has only been reported between two
10
11 neighboring *F. ceranoides* Iberian populations (Neiva et al., 2012b), indicating that individuals
12
13 belonging to distinct phylogroups can interbreed. However, no signs of hybridization have
13
14 been observed in other Iberian or French populations. The geographically restricted and
15
16 limited lineage admixture suggests that other factors may be at play in maintaining fine-scale
17
18 genetic differentiation. In particular, incipient reproductive isolation (pre- or post-zygotic) can
19
20 depress gene flow between divergent phylogroups (e.g., Tellier et al., 2011). Under this
21
22 scenario, limited dispersal across oceanographic barriers explains the position of the genetic
23
24 discontinuity while the delay in homogenisation is mainly explained by endogenous
25
26 components of reproductive isolation. Future studies assessing spatial and temporal
27
28
29 reproductive dynamics of distinct *F. ceranoides* lineages will be crucial to provide a direct
30
31
32 testing of this hypothesis.
33
34
35

Conclusions

36
37 Our study highlights the need to combine evidence from multiple sources for a comprehensive
38
39 understanding of ecological and evolutionary mechanisms linked to phylogeographic breaks.
40
41 These conclusions are of great significance for other organisms with sporadic and spatially
42
43 limited dispersal, helping clarify the apparent inconsistency of extensive and sharp genetic
44
45 differentiation in geographically restricted regions. In addition to theoretical evolutionary
46
47 relevance, the identification of contemporary dynamics contributing to the maintenance of
48
49 significant units of intraspecific biodiversity is critical for efficient approaches of management
50
51
52 and conservation efforts.
53
54
55
56
57
58
59
60

ACKNOWLEDGMENTS
354 This research was funded through projects BIODIVERSA/004/2015,
4
5 IF/01413/2014/CP1217/CT0004 and UID/Multi/04326/2019 by the Foundation for Science
6 and Technology (FCT - MEC, Portugal) and further supported by the National Research
7
8 Foundation of South Africa (Grant number 64801) and through the fellowship grant
9
10 SFRH/BPD/88935/2012 funded by FCT and SFRH/BPD/111003/2015 jointly funded by a
11
12 Pew Marine Fellowship (USA) and FCT. We thank two anonymous reviewers for their
13
14 suggestions and comments.
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60

361

REFERENCES

363 Almeida, S. C., Nicastro, K. R., Zardi, G. I., Pearson, G. A., Valero, M., and Serrão, E. A.
2017. Reproductive strategies and population genetic structure of Fucus spp. across a
northeast Atlantic biogeographic transition. Aquatic Living Resources, 30: 16.
364
365 Alvarez, I., Ospina-Alvarez, N., Pazos, Y., Bernardez, P., Campos, M., Gomez-Gesteira, J.,
366 Alvarez-Ossorio, M., et al. 2009. A winter upwelling event in the Northern Galician Rias:
frequency and oceanographic implications. Estuarine, Coastal and Shelf Science, 82: 573-
367
368
369 582.
370 Assis, J., Berecibar, E., Claro, B., Alberto, F., Reed, D., Raimondi, P., and Serrão, E. 2017.
371 Major shifts at the range edge of marine forests: the combined effects of climate changes
372 and limited dispersal. Scientific Reports, 7: 44348.
373 Assis, J., Serrão, E. A., Coelho, N. C., Tempera, F., Valero, M., Claro, B., and Alberto, F.
374 2018. Past climate changes and strong oceanographic barriers structured low latitude
375 genetic relics for the golden kelp Laminaria ochroleuca. Journal of Biogeography.
376 Assis, J., Zupan, M., Nicastro, K. R., Zardi, G. I., McQuaid, C. D., and Serrão, E. A. 2015.
377 Oceanographic conditions limit the spread of a marine invader along southern African
378 shores. PLoS ONE, 10(6):e0128124.
1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

58

59

60

379 Ayata, S.-D., Stolba, R., Comtet, T., and Thiébaut, É. 2011. Meroplankton distribution and its relationship to coastal mesoscale hydrological structure in the northern Bay of Biscay (NE Atlantic). Journal of Plankton Research, 33: 1193-1211.

382 Barnes, I., Matheus, P., Shapiro, B., Jensen, D., and Cooper, A. 2002. Dynamics of Pleistocene Population Extinctions in Beringian Brown Bears. Science, 295: 2267-2270.

383 Barton, N. H., and Hewitt, G. M. 1985. Analysis of hybrid zones. Annual Review of Ecology and Systematics, 16: 113-148.

386 Bierne, N., Welch, J., Loire, E., Bonhomme, F., and David, P. 2011. The coupling hypothesis: why genome scans may fail to map local adaptation genes. Molecular Ecology, 20: 2044-2072.

389 Chao, R. B., Casais, M. C., Cortizas, A. M. n., Alberti, A. P., and Paz, M. V. 2002. Holocene evolution on Galician coast (NW Spain): an example of paraglacial dynamics. Quaternary International, 93: 149-159.

392 Chassignet, E. P., Hurlburt, H. E., Smedstad, O. M., Halliwell, G. R., Hogan, P. J., Wallcraft, A. J., Baraille, R., et al. 2007. The HYCOM (hybrid coordinate ocean model) data assimilative system. Journal of Marine Systems, 65: 60-83.

395 Chust, G., Villarino, E., Chenuil, A., Irigoien, X., Bizsel, N., Bode, A., Broms, C., et al. 2016.

396 Dispersal similarly shapes both population genetics and community patterns in the marine realm. Scientific reports, 6: 28730.

398 Clement, M., Posada, D., and Crandall, K. A. 2000. TCS: a computer program to estimate gene genealogies. Molecular Ecology, 9: 1657-1659.

400 Comps, B., Gömöry, D., Letouzey, J., Thiébaut, B., and Petit, R. 2001. Diverging trends between heterozygosity and allelic richness during postglacial colonization in the European beech. Genetics, 157: 389-397.

403 Couceiro, L., Robuchon, M., Destombe, C., and Valero, M. 2013. Management and conservation of the kelp species *Laminaria digitata*: using genetic tools to explore the potential exporting role of the MPA "Parc naturel marin d'Iroise". Aquatic Living Resources, 26: 197-205.
407 Day, J. W., Hall, C. A. S., Kemp, W. M., and A., Y.-A. 1989. Estuarine Ecology, John Wiley

408 and Sons, New York.

409 Dowle, M., Srinivasan, A., Gorecki, J., Chirico, M., Stetsenko, P., Short, T., Lianoglou, S., et al. 2019. Package 'data. table'. Extension of 'data. frame'.

411 Drummond, A., Ashton, B., Buxton, S., Cheung, M., Cooper, A., Duran, C., Field, M., et al. 2011. *Geneious* v5. 4.

413 Ferro, I., and Morrone, J. J. 2014. *Biogeographical transition zones: a search for conceptual synthesis.* Biological Journal of the Linnean Society, 113: 1-12.

415 Fossette, S., Putman, N. F., Lohmann, K. J., Marsh, R., and Hays, G. C. 2012. A biologist's guide to assessing ocean currents: a review. Marine Ecology Progress Series, 457: 285-301.

417 Gallon, R. K., Robuchon, M., Leroy, B., Le Gall, L., Valero, M., and Feunteun, E. 2014.

418 Twenty years of observed and predicted changes in subtidal red seaweed assemblages along a biogeographical transition zone: inferring potential causes from environmental data.

420 Journal of Biogeography, 41: 2293-2306.

421 Gilg, M. R., and Hilbish, T. J. 2003. The geography of marine larval dispersal: coupling genetics with fine-scale physical oceanography. Ecology, 84: 2989-2998.

423 Goldson, A., Hughes, R., and Gliddon, C. 2001. Population genetic consequences of larval dispersal mode and hydrography: a case study with bryozoans. Marine Biology, 138: 1037-1042.

425 1042.

426 Gomez, A., Hughes, R. N., Wright, P. J., Carvalho, G. R., and Lunt, D. H. 2007.

427 Mitochondrial DNA phylogeography and mating compatibility reveal marked genetic structuring and speciation in the NE Atlantic bryozoan *Celleporella hyalina*. Molecular Ecology, 16: 2173-2188.

430 Haklay, M., and Weber, P. 2008. Openstreetmap: User-generated street maps. IEEE Pervasive Computing, 7: 12-18.

432 Hewitt, G. 2000. The genetic legacy of the Quaternary ice ages. Nature, 405: 907-913.

433 Hewitt, G. M. 1996. Some genetic consequences of ice ages, and their role in divergence and speciation. Biological Journal of the Linnean Society, 58: 247-276.
1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

58

59

60

435 Hewitt, G. M. 2004. Genetic consequences of climatic oscillations in the Quaternary.

436 Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences,

437 359: 183-195.

438 Hijmans, R. J., Phillips, S., Leathwick, J., Elith, J., and Hijmans, M. R. J. 2017. Package

439 'dismo'. Circles, 9: 1-68.

440 Hoarau, G., Coyer, J. A., Veldsink, J. H., Stam, W. T., and Olsen, J. L. 2007. Glacial refugia

441 and recolonization pathways in the brown seaweed *Fucus serratus*. Molecular Ecology, 16:

442 3606-3616.

443 Hohenlohe, P. A. 2004. Limits to gene flow in marine animals with planktonic larvae: models

444 of Littorina species around Point Conception, California. Biological Journal of the Linnean

445 Society, 82: 169-187.

446 Johansson, M. L., Alberto, F., Reed, D. C., Raimondi, P. T., Coelho, N. C., Young, M. A.,

447 Drake, P. T., et al. 2015. Seascape drivers of *Macrocystis pyrifera* population genetic

448 structure in the northeast Pacific. Molecular Ecology, 24: 4866-4885.

449 Jolly, M. T., Jollivet, D., Gentil, F., Thiébaut, É., and Viard, F. 2005. Sharp genetic break

450 between Atlantic and English Channel populations of the polychaete *Pectinaria koreni*, along

451 the North coast of France. Heredity, 94: 23.

452 Kamvar, Z. N., Tabima, J. F., and Grünwald, N. J. 2014. Poppr: an R package for genetic

453 analysis of populations with clonal, partially clonal, and/or sexual reproduction. PeerJ, 2:

454 e281.

455 Kennedy, J. P., Garavelli, L., Truelove, N. K., Devlin, D. J., Box, S. J., Chérubin, L. M., and

456 Feller, I. C. 2017. Contrasting genetic effects of red mangrove (*Rhizophora mangle* L.) range

457 expansion along West and East Florida. Journal of Biogeography, 44: 335-347.

458 Klein, M., Teixeira, S., Assis, J., Serrão, E. A., Gonçalves, E. J., and Borges, R. 2016. High

459 interannual variability in connectivity and genetic pool of a temperate clingfish matches

460 oceanographic transport predictions. PloS one, 11: e0165881.

461 Lamigueiro, O. P., Hijmans, R., and Lamigueiro, M. O. P. 2018. Package 'rasterVis'.
462 Lein, T. E. 1984. Distribution, reproduction, and ecology of *Fucus ceranoides*

463 L.(Phaeophyceae) in Norway. Sarsia, 69: 75-81.

464 Lett, C., Verley, P., Mullon, C., Parada, C., Brochier, T., Penven, P., and Blanke, B. 2008. A

465 Lagrangian tool for modelling ichthyoplankton dynamics. Environmental Modelling & Software, 23: 1210-1214.

467 Liang, Y., He, D., Jia, Y., Sun, H., and Chen, Y. 2017. Phylogeographic studies of schizothoracine fishes on the central Qinghai-Tibet Plateau reveal the highest known glacial microrefugia. Scientific Reports, 7: 10983.

470 Librado, P., and Rozas, J. 2009. DnaSP v5: a software for comprehensive analysis of DNA polymorphism data. Bioinformatics, 25: 1451-1452.

472 McKenzie, P. F., and Bellgrove, A. 2008. Dispersal of Hormosira banksii (Phaeophyceae) via detached fragments: reporductive viability and longevity. Journal of Phycology, 44: 1108-1115.

475 Mims, M. C., Phillipsen, I. C., Lytle, D. A., Kirk, E. E. H., and Olden, J. D. 2015. Ecological strategies predict associations between aquatic and genetic connectivity for dryland amphibians. Ecology, 96: 1371-1382.

478 Monteiro, C. A., Paulino, C., Jacinto, R., Serrão, E. A., and Pearson, G. A. 2016. Temporal windows of reproductive opportunity reinforce species barriers in a marine broadcast spawning assemblage. Scientific reports, 6: 29198.

481 Muhlin, J. F., Engel, C. R., Stessel, R., Weatherbee, R. A., and Brawley, S. H. 2008. The influence of coastal topography, circulation patterns, and rafting in structuring populations of an intertidal alga. Molecular Ecology, 17: 1198-1210.

484 Munda, I. M. 1999. The benthic algal vegetation of land-locked fjords in southeastern Iceland. Hydrobiologia, 393: 169.

486 Munwes, I., Geffen, E., Roll, U., Friedmann, A., Daya, A., Tikochinski, Y., and Gafny, S.

487 2010. The change in genetic diversity down the core-edge gradient in the eastern spadefoot toad (*Pelobates syriacus*). Molecular Ecology, 19: 2675-2689.
1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

58

59

60

489 Neiva, J., Paulino, C., Nielsen, M. M., Krause-Jensen, D., Saunders, G. W., Assis, J.,

490 Bárbara, I., et al. 2018. Glacial vicariance drives phylogeographic diversification in the

491 amphi-boreal kelp *Saccharina latissima*. Scientific reports, 8: 1112.

492 Neiva, J., Pearson, G. A., Valero, M., and Serrão, E. A. 2010. Surfing the wave on a

493 borrowed board: range expansion and spread of introgressed organellar genomes in the

494 seaweed *Fucus ceranoides* L. Molecular Ecology, 19: 4812-4822.

495 Neiva, J., Pearson, G. A., Valero, M., and Serrão, E. A. 2012a. Drifting fronds and drifting

496 alleles: range dynamics, local dispersal and habitat isolation shape the population structure

497 of the estuarine seaweed *Fucus ceranoides*. Journal of Biogeography, 39: 1167-1178.

498 Neiva, J., Pearson, G. A., Valero, M., and Serrão, E. A. 2012b. Fine-scale genetic breaks

499 driven by historical range dynamics and ongoing density-barrier effects in the estuarine

500 seaweed *Fucus ceranoides* L. BMC Evolutionary Biology, 12: 78.

501 Newman, M. E. 2006. Modularity and community structure in networks. Proceedings of the

502 national academy of sciences, 103: 8577-8582.

503 Nicastro, K. R., Zardi, G. I., McQuaid, C. D., Teske, P. R., and Barker, N. P. 2008. Coastal

504 topography drives genetic structure in marine mussels. Marine Ecology Progress Series,

505 368: 189-195.

506 Nicastro, K. R., Zardi, G. I., Teixeira, S., Neiva, J., Serrão, E. A., and Pearson, G. A. 2013.

507 Shift happens: trailing edge contraction associated with recent warming trends threatens a

508 distinct genetic lineage in the marine macroalga *Fucus vesiculosus*. BMC Biology, 11: 6.

509 Oksanen, J., Blanchet, F., Friendly, M., Kindt, R., Legendre, P., McGlinn, D., Minchin, P., et

510 al. 2018. vegan: a community ecology package. R package verions 2.4-6.

511 Olsen, J. L., Zechman, F. W., Hoarau, G., Coyer, J. A., Stam, W. T., Valero, M., and Åberg,

512 P. 2010. The phylogeographic architecture of the fucoid seaweed *Ascophyllum nodosum*: an

513 intertidal ‘marine tree’and survivor of more than one glacial-interglacial cycle. Journal of

514 Biogeography, 37: 842-856.

515 Pardo, C., Guillemin, M.-L., Pena, V., Barbara, I., Valero, M., and Barreiro, R. 2019. Local

516 coastal configuration rather than latitudinal gradient shape clonal diversity and genetic
1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

58

59

60

517 structure of *Phymatolithon calcareum* maerl beds in North European Atlantic. Frontiers in Marine Science, 6: 149.

519 Provan, J. 2013. The effects of past, present and future climate change on range-wide genetic diversity in northern North Atlantic marine species. Frontiers of Biogeography, 5(1).
520
521 Provan, J., Wattier, R. A., and Maggs, C. A. 2005. Phylogeographic analysis of the red seaweed *Palmaria palmata* reveals a Pleistocene marine glacial refugium in the English Channel. Molecular Ecology, 14: 793-803.

524 Puillat, I., Lazure, P., Jégou, A., Lampert, L., and Miller, P. 2004. Hydrographical variability on the French continental shelf in the Bay of Biscay, during the 1990s. Continental Shelf Research, 24: 1143-1163.

527 Putman, N. F., and He, R. 2013. Tracking the long-distance dispersal of marine organisms: sensitivity to ocean model resolution. Journal of the Royal Society Interface, 10: 20120979.

529 Remerie, T., Vierstraete, A., Weekers, P. H., Vanfleteren, J. R., and Vanreusel, A. 2009. Phylogeography of an estuarine mysid, *Neomysis integer* (Crustacea, Mysida), along the north-east Atlantic coasts. Journal of Biogeography, 36: 39-54.

532 Roucoux, K., De Abreu, L., Shackleton, N., and Tzedakis, P. 2005. The response of NW Iberian vegetation to North Atlantic climate oscillations during the last 65kyr. Quaternary Science Reviews, 24: 1637-1653.

535 Ruiz-Villarreal, M., González-Pola, C., del Río, G. D., Lavin, A., Otero, P., Piedracoba, S., and Cabanas, J. 2006. Oceanographic conditions in North and Northwest Iberia and their influence on the Prestige oil spill. Marine Pollution Bulletin, 53: 220-238.

538 Selkoe, K. A., Watson, J. R., HORIN, T. B., IACCHEI, M., MITARAI, S., SIEGEL, D. A., GAINES, S. D., et al. 2010. Taking the chaos out of genetic patchiness: seascape genetics reveals ecological and oceanographic drivers of genetic patterns in three temperate reef species. Molecular Ecology, 19: 3708-3726.

542 Serrão, E. A., Kautsky, L., Lifvergren, T., and Brawley, S. H. 1997. Gamete dispersal and pre-recruitment mortality in Baltic *Fucus vesiculosus*. Phycologia, 36 101-102.
1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

58

59

60

544 Slatkin, M. 1993. Isolation by distance in equilibrium and non-equilibrium populations.

545 Evolution, 47: 264-279.

546 Smith, B. T., Escalante, P., Baños, B. E. H., Navarro-Sigüenza, A. G., Rohwer, S., and

547 Klicka, J. 2011. The role of historical and contemporary processes on phylogeographic

548 structure and genetic diversity in the Northern Cardinal, Cardinalis cardinalis. BMC

549 Evolutionary Biology, 11: 136.

550 Sotka, E. E., Wares, J. P., Barth, J. A., Grosberg, R. K., and Palumbi, S. R. 2004. Strong

551 genetic clines and geographical variation in gene flow in the rocky intertidal barnacle

552 Balanus glandula. Molecular Ecology, 13: 2143-2156.

553 Spalding, M. D., Fox, H. E., Allen, G. R., Davidson, N., Ferdana, Z. A., Finlayson, M.,

554 Halpern, B. S., et al. 2007. Marine ecoregions of the world: a bioregionalization of coastal

555 and shelf areas. Bioscience, 57: 573-583.

556 Team, R. C. 2018. R: A language and environment for statistical computing; 2015.

557 Tellier, F., Tapia, J., Faugeron, S., Destombe, C., and Valero, M. 2011. The * lessonia*

558 *nigrescens* species complex (laminariales, phaeophyceae) shows strict parapatry and

559 complete reproductive isolation in a secondary contact zone 1. Journal of Phycology, 47:

560 894-903.

561 Teske, P., Papadopoulos, I., Zardi, G., McQuaid, C., Edkins, M., Griffiths, C., and Barker, N.

562 2007. Implications of life history for genetic structure and migration rates of southern African

563 coastal invertebrates: planktonic, abbreviated and direct development. Marine Biology, 152:

564 697-711.

565 Teske, P. R., Von Der Heyden, S., McQuaid, C. D., and Barker, N. P. 2011. A review of

566 marine phylogeography in southern Africa. South African Journal of Science, 107: 43-53.

567 Thiel, M., and Haye, P. 2006. The ecology of rafting in the marine environment-III.

568 Biogeographical and evolutionary consequences (in Oceanography and marine biology: An

569 annual review-Volume 48, pp. 323-429).
1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

58

59

60

570 Varela, R. A., Rosón, G., Herrera, J. L., Torres-López, S., and Fernández-Romero, A. 2005.

571 A general view of the hydrographic and dynamical patterns of the Rías Baixas adjacent sea area. Journal of Marine Systems, 54: 97-113.

573 Wares, J. P., Gaines, S., and Cunningham, C. W. 2001. A comparative study of asymmetric migration events across a marine biogeographic boundary. Evolution, 55: 295-306.

574 Woodruff, D. S. 1973. Natural hybridization and hybrid zones. Systematic Biology, 22: 213-218.

575 Zardi, G., McQuaid, C., Teske, P., and Barker, N. 2007. Unexpected genetic structure of mussel populations in South Africa: indigenous *Perna perna* and invasive *Mytilus galloprovincialis*. Marine Ecology Progress Series, 337: 135-144.

580 Zardi, G., Nicastro, K., McQuaid, C., Hancke, L., and Helmuth, B. 2011. The combination of selection and dispersal helps explain genetic structure in intertidal mussels. Oecologia, 165: 947-958.

583 Zardi, G. I., Nicastro, K. R., Ferreira Costa, J., Serrão, E. A., and Pearson, G. A. 2013.

584 Broad scale agreement between intertidal habitats and adaptive traits on a basis of contrasting population genetic structure. Estuarine, Coastal and Shelf Science, 131: 140-148.

587

588

589
590 FIGURE LEGEND

591 Fig. 1. Haplotype distribution of *Fucus ceranoides* in the coastlines of (a) Northwester France and (panel b) Northwest Iberia. The colors along coastlines (a, b) depict the different oceanographic regions (R) identified in network analysis. A pairwise matrix of directional connectivity between oceanographic regions identified in (d) western Brittany and (e) northwest Iberia. Matrix header colors according to the oceanographic regions depicted in the top panels a and b. Haplotype frequency and differentiation degree in (f) western Brittany and (g) northwest Iberia. Note that there is no correspondence of haplotypes between the two panels (i.e., each dataset was treated separately).

599

600 TABLES

601 Table 1. Maximum and average distances (km), drifting time (days) and probabilities produced by the particles connecting different cells for the lagrangian particle simulations running in Northwest France and Northwest Spain..

604

<table><thead><tr><th rowspan="2">Region</th><th colspan="2">Distance (km)</th><th colspan="2">Time (days)</th><th colspan="2">Probability</th></tr><tr><th>Maximum</th><th>Mean (±SD)</th><th>Maximum</th><th>Mean (±SD)</th><th>Maximum</th><th>Mean (±SD)</th></tr></thead><tbody><tr><td>W Brittany</td><td>382.6</td><td>62.6±54.6</td><td>24.6</td><td>3.61±2.63</td><td>0.721</td><td>0.004±0.020</td></tr><tr><td>NW Iberia</td><td>431.2</td><td>105.9±90.8</td><td>26.7</td><td>2.09±1.81</td><td>0.607</td><td>0.004±0.021</td></tr></tbody></table>

605
<figure><img src="image_4.png" /></figure>

<figure><img src="image_5.png" /></figure>

d)

Ocean connectivity Brittany

<table><thead><tr><th></th><th>R1</th><th>R2</th><th>R3</th></tr></thead><tbody><tr><th>R1</th><td>2.87e<sup>-3</sup></td><td>1.02e<sup>-3</sup></td><td>3.02e<sup>-4</sup></td></tr><tr><th>R2</th><td>6.34e<sup>-4</sup></td><td>1.93e<sup>-3</sup></td><td>9.06e<sup>-4</sup></td></tr><tr><th>R3</th><td>1.13e<sup>-4</sup></td><td>3.68e<sup>-4</sup></td><td>1.93e<sup>-3</sup></td></tr></tbody></table>

e)

Ocean connectivity NW Iberia

<table><thead><tr><th></th><th>R1</th><th>R2</th><th>R3</th><th>R4</th><th>R5</th></tr></thead><tbody><tr><th>R1</th><td>1.46e<sup>-3</sup></td><td>4.82e<sup>-4</sup></td><td>2.97e<sup>-4</sup></td><td>9.61e<sup>-3</sup></td><td>3.45e<sup>-5</sup></td></tr><tr><th>R2</th><td>9.35e<sup>-4</sup></td><td>3.12e<sup>-3</sup></td><td>3.13e<sup>-4</sup></td><td>1.27e<sup>-4</sup></td><td>3.26e<sup>-5</sup></td></tr><tr><th>R3</th><td>2.52e<sup>-4</sup></td><td>1.38e<sup>-4</sup></td><td>2.67e<sup>-3</sup></td><td>5.91e<sup>-4</sup></td><td>7.37e<sup>-5</sup></td></tr><tr><th>R4</th><td>3.90e<sup>-5</sup></td><td>4.21e<sup>-5</sup></td><td>6.79e<sup>-5</sup></td><td>2.39e<sup>-3</sup></td><td>2.46e<sup>-4</sup></td></tr><tr><th>R5</th><td>4.03e<sup>-5</sup></td><td>5.94e<sup>-5</sup></td><td>8.72e<sup>-5</sup></td><td>2.44e<sup>-4</sup></td><td>2.66e<sup>-3</sup></td></tr></tbody></table>

<figure><img src="image_6.png" /></figure>

<figure><img src="image_7.png" /></figure>

<figure><img src="image_8.png" /></figure>

Haplotype id Brittany

<figure><img src="image_9.png" /></figure>

Haplotype id NW Iberia

<figure><img src="image_10.png" /></figure>

1 mutation

<figure><img src="image_11.png" /></figure>

Frequency

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

58

59

60
1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

58

59

60

1

Congruence between fine-scale genetic breaks and dispersal potential in an estuarine seaweed across multiple transition zones.

2

3

4

Katy R. Nicastro¹, Jorge Assis¹, Ester A. Serrão¹, Gareth A. Pearson¹, João Neiva¹, Myriam

5

Valero², Rita Jacinto¹, Gerardo I. Zardi³*

6

¹CCMAR-CIMAR – Associated Laboratory, University of Algarve, Campus de Gambelas,

7

Faro, 8005–139, Portugal

8

²UMI 3614 Evolutionary Biology and Ecology of Algae, CNRS, Sciences Sorbonne

9

Université, UC, UACH, Station Biologique de Roscoff, Roscoff Cedex, France

10

³Department of Zoology and Entomology, Rhodes University, Grahamstown, 6140, South

11

Africa

12

*corresponding author: zardi73@yahoo.it, +351 927738340

13

14

Additional emails:

15

KRN: katynicastro@gmail.com

16

JA: jorgemfa@me.com

17

EAS: eserrao@ualg.pt

18

GAP: gpearson@ualg.pt

19

JN: jmneiva@ualg.pt

20

MV: myriam.valero@sb-rocoff.fr

21

RJ: ritajacinto85@gmail.com

22

23

Running head: Congruence between fine-scale genetic breaks and dispersal potential.

24

Keywords: Biogeography, physical modelling, gene flow, Fucus spp.
25 ABSTRACT

26 Genetic structure in biogeographical transition zones can be shaped by several factors
27 including limited dispersal across barriers, admixture following secondary contact, differential
28 selection and mating incompatibility. A striking example is found in Northwest France and
29 Northwest Spain, where the estuarine seaweed *Fucus ceranoides* L. exhibits sharp, regional
30 genetic clustering. This pattern has been related to historical population fragmentation and
31 divergence into distinct glacial refugia, followed by post-glacial expansion and secondary
32 contact. The contemporary persistence of sharp ancient genetic breaks between nearby
33 estuaries has been attributed to prior colonization effects (density barriers) but the effect of
34 oceanographic barriers has not been tested. Here, through a combination of mesoscale
35 sampling (15 consecutive populations) and population genetic data (mtIGS) in NW France,
36 we define regional genetic disjunctions similar to those described in NW Iberia. Most
37 importantly, using high resolution dispersal simulations for Brittany and Iberian populations,
38 we provide evidence for a central role of contemporary hydrodynamics in maintaining genetic
39 breaks across these two major biogeographic transition zones. Our findings further show the
40 importance of a comprehensive understanding of oceanographic regimes in hydrodynamically
41 complex coastal regions to explain the maintenance of sharp genetic breaks along
42 continuously populated coastlines.

44 INTRODUCTION

45 Fueled by current concerns about the impacts of global change on biodiversity, there is a
46 renewed interest in understanding the processes affecting a species' range dynamics as well
47 as the factors shaping its genetic diversity. Generally, both historical and contemporary
48 processes are invoked to explain the distribution and phylogeography of a species. Tectonic
49 events and past climate fluctuations created topographic, environmental and hydrologic
50 barriers that were key in shaping phylogeographic structure of many plant and animal species.
51 Of these, the Last Glacial Maximum is probably the most significant and recent historical event
1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

58

59

60

52 (e.g., Hewitt, 2000; Barnes et al., 2002; Liang et al., 2017; Neiva et al., 2018). During this time, ice sheets covered much of current cold and temperate zones of the Northern Hemisphere, triggering range fragmentation and contractions of entire ecosystems to more southern latitudes, while during the present interglacial, widespread range shifts and poleward expansions have occurred.

57 It is predicted that genetic diversity is lowest in recently colonized areas and highest in refugial areas where long-term persistence was possible (e.g., Hewitt, 1996; Comps et al., 2001; Hewitt, 2004; Kennedy et al., 2017). However, contemporary demographic processes can either mask or even erase genetic signatures of population expansions or retreats (Smith et al., 2011). High levels of gene flow may homogenize genetic diversity among previously structured populations. On the other hand, nonrandom mating with individuals in close geographic proximity can generate genetic structuring within a continuous population (Slatkin, 1993). Intrinsic characteristics of the species such as dispersal ability, migration patterns and changes in population densities can further confound any historical signature (e.g., Mims et al., 2015; Chust et al., 2016; Assis et al., 2018).

67 Biogeographical transition regions provide a good framework for exploring and understanding genetic structuring of species through space and time. These are areas of overlap and segregation between different biotic components, and geographically separated clades often coincide with these transition zones (Ferro and Morrone, 2014). In the marine realm, phylogeographic breaks in biogeographical transition regions are generally attributed to historical processes or contemporary dispersal barriers, such as upwelling phenomena and currents that may limit along-shore dispersal, environmental differences boosting local adaptation and/or reproductive strategies maintaining self-recruitment (Gilg and Hilbish, 2003; Zardi et al., 2007; Selkoe et al., 2010).

76 There are well known biogeographical boundaries in all oceans, some of which are associated with oceanographic features that generate contemporary barriers to dispersal. For example, the strong southward-flowing Agulhas Current, which runs about 10 km offshore along most of South Africa's east and southeast coast, impedes larval dispersal and thus promotes local
adaptation (Teske et al., 2011; Zardi et al., 2011). Dispersal and gene flow around Point Conception in southern California are also strongly affected by extensive upwelling of colder sub-surface waters and by the southward California Current (Wares et al., 2001; Hohenlohe, 2004; Johansson et al., 2015).

Here, we investigated the contribution of contemporary oceanographic connectivity in maintaining geographically separated genetic clades within a continuously distributed seaweed species along the biogeographic transition areas of Brittany (northwest France, Europe) and northwest Iberia (northern Spain, Europe; Fig. 1). These two areas are highly relevant for studying this question and marine connectivity in general. Both areas delimit the boundaries between cold-temperate and warm-temperate regions (Spalding et al., 2007), they are refugial zones for numerous species (Provan, 2013) and, over the past decades, they have undergone significant changes in macroalgae assemblages due to climate change (Nicastro et al., 2013; Gallon et al., 2014; Assis et al., 2017).

In this study, we use phylogeographic analyses and Lagrangian Particle Simulations (LPS) coupled with network analyses to evaluate the levels of congruence between dispersal potential and the patterns of present-day genetic differentiation and diversity in the estuarine seaweed *Fucus ceranoides* along these two biogeographic transition zones. This species is perennial, dioecious and restricted to estuarine intertidal areas. Fucoid seaweeds have no planktonic dispersal stage and have restricted gamete dispersal (Serrão et al., 1997). However, adult individuals can achieve long distance gene flow via the rafting of whole or partially detached thalli with reproductive structures (Thiel and Haye, 2006; McKenzie and Bellgrove, 2008), a form of population connectivity strongly influenced by hydrodynamic forces and coastal topography. Currently, *F. ceranoides* is distributed from northern Portugal to northern Norway (Lein, 1984) and Iceland (Munda, 1999), covering both past non-glaciated and glaciated regions of Europe. Previous studies have shown the occurrence of two divergent genetic lineages in this species between the south and the *North-north* of Europe, the phylogeographic break being localized in Northwest France near the English Channel (Neiva et al., 2012a; Neiva et al., 2012b). Specifically, the dominant Northwest Iberian haplotypes of
1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

58

59

60

108

this species was found in southern Brittany but not after the genetic break in northern Brittany (Neiva et al., 2010). We discuss three scenarios for the concordance between present-day oceanographic dispersal barriers and the observed genetic differentiation among *F. ceranoides* estuarine populations: 1) Contemporary oceanographic barriers to dispersal are responsible for the origin, the position and the maintenance (i.e. delaying genetic homogenization) of the genetic differentiation; 2) Contemporary oceanographic circulation patterns explain the position, the maintenance but not the origin of the genetic differentiation; 3) Reproductive isolation, in addition to contemporary oceanographic patterns, limits genetic homogenisation thus contributing to the position and the maintenance of the genetic differentiation.

108

109

110

111

112

113

114

115

116

117

118

119

# MATERIALS

120

## Genetic data

121

The two study areas (NW France and NW Spain) are peninsulas characterized by complex and variable circulation patterns (Puillat et al., 2004; Varela et al., 2005; Ruiz-Villarreal et al., 2006; Ayata et al., 2011). Because of that, sampling of only a limited number of localities would be inappropriate. We therefore decided to sample a small number of individuals at as many sites along the two coastlines as possible, rather than obtaining large numbers of individuals from a limited number of sites (e.g., Sotka et al., 2004; Teske et al., 2007). This decision was also supported by the very low genetic diversity within localities for this species (Neiva et al., 2010; 2012b; Neiva et al., 2012a). As a result, two sets of sequences of *Fucus ceranoides* were prepared and analyzed separately. The first data set (Data set 1) comprised sequences of individuals collected in the estuaries of all major rivers between Hennebont (HB, southern Brittany) and Camarel (CM, northern Brittany) in northwest France (n = 2 from each site; Table S1). The second dataset (Data set 2) consisted of sequences previously analysed in Neiva et al. (Neiva et al., 2010; 2012b; Neiva et al., 2012a) and sampled across northern Iberia between Viana do Castelo (VIA, northern Portugal) and Porcia (POR, northern Spain). To

122

123

124

125

126

127

128

129

130

131

132

133

134
allow a comparison between data sets, a random subsample of 2 individuals from each site was used for Data set 2. The random subsampling in NW Spain was repeated to ensure consistency in the results obtained.

Sampling was performed in 2014-2015 and conducted with similar *criteria* for individuals used in both data sets. All collection sites were characterized by monospecific belts of *F. ceranoides* attached to hard substrata and were exposed to steep salinity fluctuations throughout the tidal cycle. At each site, 5-10 cm tips of apical vegetative tissue were collected from individuals sampled in the mid distributional range of the species. Neighboring sites were at an average proximity of about 50 (±15) and 33 (±17) km for Data sets 1 and 2 respectively. All samples were individually stored dehydrated in silica-gel crystals until DNA extraction.

## DNA isolation and sequencing of data set 1

To compile Data set 1, genomic DNA was extracted from approximately 10 mg of dried tissue using the Nucleospin® Multi-96 plant kit (Macherey-Nagel Duren, Germany), according to the manufacturer's protocol. Individuals were sequenced for the mitochondrial 23 S/trnK intergenic spacer (mtIGS, Neiva et al., 2010). Primer sequences and amplification details were the same as in Neiva et al. (Neiva et al., 2010; 2012b; Neiva et al., 2012a). Amplified fragments were run in an ABI PRISM 3130xl automated capillary sequencer (Applied Biosystems, CCMAR Portugal). MtDNA sequences were aligned, proofread and edited in GENEIOUS 3.8 (Drummond et al., 2011).

## Data analyses

For both data sets, haplotype frequencies were estimated using DnaSP 5.0 (Librado and Rozas, 2009). The relationships among the MtIGS haplotypes were inferred using statistical parsimony with Tcs v. 1.13 (Clement et al., 2000). Because additional subsampled dataset for the Iberia provided similar results (Table SI2 and Fig. SI1), only one was used for the simulations.

## Dispersal simulations

The main oceanographic regions in northwest France and northwest Iberia (~550km and ~600km of coastlines, respectively) were identified by coupling Lagrangian Particle
1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

58

59

60

163

Simulations (LPS) with network analyses - least cost and community algorithms (least cost distance and community algorithm, e.g., Assis et al., 2015; Klein et al., 2016; Assis et al., 2018). The simulations used daily data of ocean currents assembled from the Hybrid Coordinate Ocean Model (HYCOM), a high-resolution product with a spatial resolution of 0.08° (approx. 6–9 km), -forced by wind speed, wind stress, precipitation and heat flux. This model can resolve oceanic fronts, meandering currents, filaments and eddies (Chassignet et al., 2007), important mesoscale processes to properly simulate ocean dispersal (Assis et al., 2015; Klein et al., 2016).

171

Both regions of simulation were gridded to a common spatial resolution of 0.01° (approx. 1km). A polygon representing global coastlines - OpenStreetMap geographic information (Haklay and Weber, 2008)- was used to define intertidal source and sink cells. Passive particles simulating rafts of *F. ceranoides* adult individuals were released from each gridded cell every 12 hours and allowed to drift for 60 full days; an extreme period for long-lived rafts of brown macroalgae (Monteiro et al., 2016; Assis et al., 2018). This approach aimed to capture the rare, long-distance dispersal events, allowing gene flow at the scales of both regions (Monteiro et al., 2016; Assis et al., 2018). After the 60 days period, or when ending up on shore, the particles were removed from the simulation. The geographic position of all particles was calculated every hour with bilinear interpolation on the ocean velocity fields (with a spatial resolution of 0.08°), while combining a 4th Order Runge-Kutta adaptive time-step on the path equations (e.g., Lett et al., 2008; Klein et al., 2016).

172

173

174

175

176

177

178

179

180

181

182

183

The degree of connectivity between all pairs of gridded cells was determined by dividing the number of unique particles released from cell i that ended up in cell j, by the total number of particles released from cell i. To account for the inter-annual variability in the ocean data, the simulations ran independently per year (from January to December), for the most recent 10-year period of data, available in HYCOM (i.e., 2003 to 2012). Asymmetrical connectivity matrices were determined by averaging the outcomes of the annual simulations.

184

185

186

187

188

189

The connectivity matrices were used in network analyses (i.e., graph theory) to infer the major oceanographic regions of northwest Iberia and northwest France. To this end, network

190
percolation removed weak probabilities to a threshold maintaining all cells (nodes) connected into a single network (Rozenfeld et al. 2008; Cunha et al., 2017), while maximizing modularity, which quantified the strength of the backbone structure (or goodness of fit) of the networks (Newman, 2006). This allowed the removal of surplus connections with unimportant information. The leading eigenvector algorithm (Newman, 2006) was applied to the percolated networks to assign a unique membership to the nodes. This approach allowed the detection of communities in the networks (e.g., Munwes et al., 2010), which in practice translated into a delineation of oceanographic regions in northwest Iberia and northwest France structured by connectivity of ocean currents (Assis et al., 2018). The statistical significance of the membership assignment to the nodes was inferred by testing the proportion of 9999 membership randomizations that retrieved a higher modularity than that observed.

Lagrangian Particle Simulations and network analyses were performed in R (R Development Core Team, 2016) using the packages: data.table (Dowle et al., 2019), dismo (Hijmans et al., 2017), igraph (Kamvar et al., 2014), parallel (Team, 2018), raster (Lamigueiro et al., 2018) and vegan (Oksanen et al., 2018).

## RESULTS

In Data set 1 (NW France), six mtIGS haplotypes were identified in 30 individuals of *Fucus ceranoides* in 15 sampled sites. In NW France, the network analyses showed two dominant haplotypes (A and D) plus three derived ones (B, C and E), each private to one population (Fig 1a). Haplotype frequency distribution revealed a geographical segregation of the two main haplotypes. Haplotype 1 was present in individuals from regions R1 and R2 while Haplotype D was restricted to more northern sites within region R3.

Out of 415 sequences retrieved from the GenBank, 52 sequences were randomly selected for Data set 2 (northwest Iberia). The network showed seven main haplotypes of which two were shared among six to ten populations and three were shared by two to three populations. The remaining two haplotypes were private to one single population. In the frequency distribution, the main haplotype was restricted to region R5 and haplotype F was present only in region
R4. Haplotype A was present in regions R3 and R1 while haplotype B was confined to region

## R2. Dispersal simulations

The LPS using HYCOM ocean currents over the 10-year period released 7300 particles per cell (7.80e10⁶ and 7.88e10⁶ particles in total in northwest France and northwest Iberia, respectively). Particles drifted for longer distances in northwest Iberia than in northwest France (up to 431.2 km; Table 1; Fig. SI2). The maximum period of drifting time was also higher in northwest Iberia (26.7 days), but on average, particles drifted for longer periods in northwest France (3.61±2.63 days). The maximum probability of connectivity between the pairs of cells was observed in northwest France (western Britany; 0.721). However, the average cell probabilities within regions did not vary considerably (Table 1; Fig. SI2).

The assignment of oceanographic regions performed by the leading eigenvector algorithm (network analysis) for northwest France and northwest Iberia showed significant modularity values of 0.41 and 0.57 (p-values < 0.001), respectively. The algorithm identified three regions in northwest France (Fig. 1a), with breaks in Penmarch and Porspoder, and five regions in northwest Iberia (Fig. 1b), with breaks in Ria de Arousa, Corrubedo, Camelle (northern Costa da Morte) and Cabo Ortegal (Cariño). The average probability of connectivity within the oceanographic regions of northwest France (diagonal of Fig. 1d) was 10-fold higher than between regions, with the exception of those between R1 and R2 (Fig. 1d), which were of the same order of magnitude. Following a similar pattern, the probabilities of connectivity in northwest Iberia were 10 to 100-fold higher within regions than between regions (diagonal of Fig. 1e), with a marked increase as the distance between groups increased.

## DISCUSSION

Our results show an overall strong match between oceanographic regions identified by dispersal simulations and fine-scale genetic discontinuities in the estuarine seaweed *Fucus ceranoides* inhabiting north Atlantic shores (Fig. 1).
Predictions of oceanographic transport made with Lagrangian particle simulations are highly sensitive to the inner spatial and temporal resolution of circulation models (Putman and He, 2013). While we preserved the raw circulation processes modelled by Hycom at the scales of days and tens of kilometers, a main limitation may arise if additional oceanographic processes occurring at smaller scales are important for realistic connectivity events shaping the genetic structure of *F. ceranoides*. For instance, circulation models with coarse spatial resolutions may underestimate drifting times up to a factor of ~2. In the same way, weekly or even daily temporal time steps may not be a realistic representation of what organisms continuously experience (Fossette et al., 2012). Regardless of such potential limitations, our results compared with independent genetic data, as well as additional studies comparing connectivity estimates with satellite-tracked organisms (e.g., Fossette et al., 2012) suggest that, overall, particles advected by Hycom data provide a reliable estimate of the main processes shaping current flow.

Previous studies have shown that mtIGS differentiation and contemporary *F. ceranoides* genetic structuring in NW Iberia is most likely the result of complex, past range dynamics (Neiva et al., 2012a). High levels of endemism and diversity highlighted by genetic analyses of *F. ceranoides* populations inhabiting this region indicate long-term persistence in glacial refugia. Despite the refugial role played by NW Iberia, sea level changes associated with glacial/inter-glacial expansion and melting of ice-sheets had significant effects on near-shore habitats (Chao et al., 2002; Roucoux et al., 2005). The current fine-scale genetic breaks in Iberian *F. ceranoides* are the result of past fragmentation and divergence of populations into distinct refugia (estuarine refugia within regional refugia), followed by expansion and secondary contact of vicariant phylogroups (Neiva et al., 2012b).

In addition to southern European refugia, the ice-free paleo-shores of northwest France (western Brittany) together with south western Ireland and the English Channel have been recognized as northern periglacial refugia for several species (*Palmaria palmata* (Provan et al., 2005); *Celleporella hyalina* (Gomez et al., 2007); *Fucus serratus* (Hoarau et al., 2007); *Neomysis integer* (Remerie et al., 2009); *Ascophyllum nodosum* (Olsen et al., 2010)
1
2
3 273 Potentially, periodic sea level changes associated to Pleistocene glacial/interglacial cycles
4
5 274 could have caused continuous rearrangements of estuaries triggering *F. ceranoides*
6
7 275 population contraction/expansion dynamics similar to those described for Iberian shores;
8
9 276 these rearrangements could have then eventually led to the sharp genetic differentiation in
10
11 277 Brittany reported here. In the light of these earlier findings and observations the scenario of
12
13 278 contemporary oceanographic barriers being responsible for the origin the genetic
14
15 279 differentiation among *F. ceranoides* estuarine populations is rejected. Our results point to the
16
17 280 preponderant role of oceanography in determining the position and possibly maintaining the
18
19 281 break between vicariant lineages. This is further supported by previous studies showing
20
21 282 shared haplotypes between Brittany (southern) and Iberia (Neiva et al., 2010; Neiva et al.,
22
23 283 2012a; Neiva et al., 2012b).

24
25
26 284 The persistent integrity of the sharp, fine-scale genetic discontinuities at secondary
27
28 285 contact zones can have a number of non-exclusive explanations. Previous studies assessing
29
30 286 this fine-scale phylogeographic structure within *F. ceranoides* in NW Iberia have highlighted
31
32 287 that contemporary dispersal between established populations is effectively too low to erase
33
34 288 historical divergence stemming from past fragmentation processes (Neiva et al., 2012b). In
35
36 289 this instance, sporadic inter-estuarine dispersal and density barriers have been invoked as the
37
38 290 main driver of limited connectivity.
39
40

41 291 Although post-glacial range expansion shows that *F. ceranoides* can effectively drift
42
43 292 across large spatial scales (Neiva et al., 2012a), dispersal among colonized estuaries is
44
45 293 expected to be limited. *F. ceranoides* is dioecious, and therefore prerequisites for successful
46
47 294 long-distance, inter-estuarine colonization are dispersal of fertile male and female fronds and
48
49 295 synchronous gamete release to produce zygotes at the new location. In addition, coastal
50
51 296 topography and estuarine morphology can curb circulation patterns, retention times and,
52
53 297 consequently, connectivity through drifting (Muhlin et al., 2008; Nicastro et al., 2008; Pardo et
54
55 298 al., 2019). The sheltered nature of estuarine habitats can significantly limit gamete dispersal
56
57 299 and the intrinsic features of geomorphology of each estuary can modulate circulation velocity
58
59 300 and intensity (Day et al., 1989). It has been suggested that pronounced meander curvatures
contribute to reduced dispersal efficiency and the variable patterns of gene flow between coastal and estuarine habitats (Zardi et al., 2013).

Density barrier effects are usually particularly marked in species such as *F. ceranoides* characterized by rapid population growth and consequent habitat saturation. The dense, monospecific *F. ceranoides* canopies typical of European northern Atlantic estuaries act as a demographic buffer against numerically rare inter-estuarine immigrants favoring the conservation of pre-existing genetic structure.

Clearly, the abundance of estuaries and their proximity strongly suggest that distance can be excluded from the list of determinants maintaining *F. ceranoides* genetic breaks along these shores. In NW Iberia, the mean distance between populations inhabiting neighboring estuaries is not significantly different than that between bordering populations across phylogeographic breaks (Neiva et al., 2012b). Similar distributional patterns can be found in Brittany where several edge populations are spatially closer to populations across regional genetic disjunctions than they are to their adjacent population within the same genetic clade. While some studies carried out between cold- and warm-temperate marine ecosystems along the northwest coast of France have invoked distinct mesoscale hydrographic features as drivers of genetic patterns (Goldson et al., 2001; Jolly et al., 2005; Couceiro et al., 2013; Almeida et al., 2017), others have highlighted lack of evidence for the role of hydrodynamics as dispersal determinants for the observed genetic discontinuities along NW Iberian shores (Neiva et al., 2012b). The latter works have also stressed the difficulties to track drifters' movements at a scale relevant for the organism to estimate migration rates among estuaries and phylogroups. In NW Iberia, circulation dynamics are complex with high seasonal variability and lack of persistent oceanographic patterns (Ruiz-Villarreal et al., 2006; Alvarez et al., 2009). Here, through the use of large scale, dispersal simulations we reveal several oceanographic regions matching haplotype segregation. Our findings add important evidence to previous conclusions and support the scenario of key, mesoscale oceanographic processes having a determinant role in explaining the position of the observed high levels of regional genetic divergence. We also hypothesized that mesoscale oceanographic dispersal barriers
1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

58

59

60

329

are key to the maintenance of inter-estaurine genetic differentiation. In a neutral model of

330

secondary contact following allopatric differentiation, signs of secondary intergradation are

331

generally observed around oceanographic barriers (Woodruff, 1973; Barton and Hewitt, 1985;

332

Bierne et al., 2011). Admixed nuclear background has only been reported between two

333

neighboring *F. ceranoides* Iberian populations (Neiva et al., 2012b), indicating that individuals

334

belonging to distinct phylogroups can interbreed. However, no signs of hybridization have

335

been observed in other Iberian or French populations. The geographically restricted and

336

limited lineage admixture suggests that other factors may be at play in maintaining fine-scale

337

genetic differentiation. In particular, incipient reproductive isolation (pre- or post-zygotic) can

338

depress gene flow between divergent phylogroups (e.g., Tellier et al., 2011). Under this

339

scenario, limited dispersal across oceanographic barriers explains the position of the genetic

340

discontinuity while the delay in homogenisation is mainly explained by endogenous

341

components of reproductive isolation. Future studies assessing spatial and temporal

342

reproductive dynamics of distinct *F. ceranoides* lineages will be crucial to provide a direct

343

testing of this hypothesis.

344

## Conclusions

345

Our study highlights the need to combine evidence from multiple sources for a comprehensive

346

understanding of ecological and evolutionary mechanisms linked to phylogeographic breaks.

347

These conclusions are of great significance for other organisms with sporadic and spatially

348

limited dispersal, helping clarify the apparent inconsistency of extensive and sharp genetic

349

clines differentiation in geographically restricted regions. In addition to theoretical evolutionary

350

relevance, the identification of contemporary dynamics contributing to the maintenance of

351

significant units of intraspecific biodiversity is critical for efficient approaches of management

352

and conservation efforts.

353

354

## ACKNOWLEDGMENTS
355 This research was funded through projects BIODIVERSA/004/2015,
4
5 IF/01413/2014/CP1217/CT0004 and UID/Multi/04326/2019 by the Foundation for Science
6 and Technology (FCT - MEC, Portugal) and further supported by the National Research
8
9 Foundation of South Africa (Grant number 64801) and through the fellowship grant
10 SFRH/BPD/88935/2012 funded by FCT and SFRH/BPD/111003/2015 jointly funded by a
12
13 Pew Marine Fellowship (USA) and FCT. We thank two anonymous reviewers for their
14
15 suggestions and comments.
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60

362

REFERENCES

364 Almeida, S. C., Nicastro, K. R., Zardi, G. I., Pearson, G. A., Valero, M., and Serrão, E. A.
2017. Reproductive strategies and population genetic structure of Fucus spp. across a
northeast Atlantic biogeographic transition. Aquatic Living Resources, 30: 16.
365
366 Alvarez, I., Ospina-Alvarez, N., Pazos, Y., Bernardez, P., Campos, M., Gomez-Gesteira, J.,
367 Alvarez-Ossorio, M., et al. 2009. A winter upwelling event in the Northern Galician Rias:
frequency and oceanographic implications. Estuarine, Coastal and Shelf Science, 82: 573-
368
369
370 582.
371 Assis, J., Berecibar, E., Claro, B., Alberto, F., Reed, D., Raimondi, P., and Serrão, E. 2017.
372 Major shifts at the range edge of marine forests: the combined effects of climate changes
and limited dispersal. Scientific Reports, 7: 44348.
373
374 Assis, J., Serrão, E. A., Coelho, N. C., Tempera, F., Valero, M., Claro, B., and Alberto, F.
375 2018. Past climate changes and strong oceanographic barriers structured low latitude
genetic relics for the golden kelp Laminaria ochroleuca. Journal of Biogeography.
376
377 Assis, J., Zupan, M., Nicastro, K. R., Zardi, G. I., McQuaid, C. D., and Serrão, E. A. 2015.
378 Oceanographic conditions limit the spread of a marine invader along southern African
shores. PLoS ONE, 10(6):e0128124.
379
1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

58

59

60

380 Ayata, S.-D., Stolba, R., Comtet, T., and Thiébaut, É. 2011. Meroplankton distribution and its relationship to coastal mesoscale hydrological structure in the northern Bay of Biscay (NE Atlantic). Journal of Plankton Research, 33: 1193-1211.

381 relationship to coastal mesoscale hydrological structure in the northern Bay of Biscay (NE Atlantic). Journal of Plankton Research, 33: 1193-1211.

382 Atlantic). Journal of Plankton Research, 33: 1193-1211.

383 Barnes, I., Matheus, P., Shapiro, B., Jensen, D., and Cooper, A. 2002. Dynamics of Pleistocene Population Extinctions in Beringian Brown Bears. Science, 295: 2267-2270.

384 Pleistocene Population Extinctions in Beringian Brown Bears. Science, 295: 2267-2270.

385 Barton, N. H., and Hewitt, G. M. 1985. Analysis of hybrid zones. Annual Review of Ecology and Systematics, 16: 113-148.

386 and Systematics, 16: 113-148.

387 Bierne, N., Welch, J., Loire, E., Bonhomme, F., and David, P. 2011. The coupling hypothesis: why genome scans may fail to map local adaptation genes. Molecular Ecology, 20: 2044-2072.

388 hypothesis: why genome scans may fail to map local adaptation genes. Molecular Ecology, 20: 2044-2072.

389 20: 2044-2072.

390 Chao, R. B., Casais, M. C., Cortizas, A. M. n., Alberti, A. P., and Paz, M. V. 2002. Holocene evolution on Galician coast (NW Spain): an example of paraglacial dynamics. Quaternary International, 93: 149-159.

391 evolution on Galician coast (NW Spain): an example of paraglacial dynamics. Quaternary International, 93: 149-159.

392 International, 93: 149-159.

393 Chassignet, E. P., Hurlburt, H. E., Smedstad, O. M., Halliwell, G. R., Hogan, P. J., Wallcraft, A. J., Baraille, R., et al. 2007. The HYCOM (hybrid coordinate ocean model) data assimilative system. Journal of Marine Systems, 65: 60-83.

394 A. J., Baraille, R., et al. 2007. The HYCOM (hybrid coordinate ocean model) data assimilative system. Journal of Marine Systems, 65: 60-83.

395 assimilative system. Journal of Marine Systems, 65: 60-83.

396 Chust, G., Villarino, E., Chenuil, A., Irigoien, X., Bizsel, N., Bode, A., Broms, C., et al. 2016. Dispersal similarly shapes both population genetics and community patterns in the marine realm. Scientific reports, 6: 28730.

397 Dispersal similarly shapes both population genetics and community patterns in the marine realm. Scientific reports, 6: 28730.

398 realm. Scientific reports, 6: 28730.

399 Clement, M., Posada, D., and Crandall, K. A. 2000. TCS: a computer program to estimate gene genealogies. Molecular Ecology, 9: 1657-1659.

400 gene genealogies. Molecular Ecology, 9: 1657-1659.

401 Comps, B., Gömöry, D., Letouzey, J., Thiébaut, B., and Petit, R. 2001. Diverging trends between heterozygosity and allelic richness during postglacial colonization in the European beech. Genetics, 157: 389-397.

402 between heterozygosity and allelic richness during postglacial colonization in the European beech. Genetics, 157: 389-397.

403 beech. Genetics, 157: 389-397.

404 Couceiro, L., Robuchon, M., Destombe, C., and Valero, M. 2013. Management and conservation of the kelp species *Laminaria digitata*: using genetic tools to explore the potential exporting role of the MPA "Parc naturel marin d'Iroise". Aquatic Living Resources, 26: 197-205.

405 conservation of the kelp species *Laminaria digitata*: using genetic tools to explore the potential exporting role of the MPA "Parc naturel marin d'Iroise". Aquatic Living Resources, 26: 197-205.

406 potential exporting role of the MPA "Parc naturel marin d'Iroise". Aquatic Living Resources, 26: 197-205.

407 26: 197-205.
408 Day, J. W., Hall, C. A. S., Kemp, W. M., and A., Y.-A. 1989. Estuarine Ecology, John Wiley

409 and Sons, New York.

410 Dowle, M., Srinivasan, A., Gorecki, J., Chirico, M., Stetsenko, P., Short, T., Lianoglou, S., et al. 2019. Package 'data. table'. Extension of 'data. frame'.

412 Drummond, A., Ashton, B., Buxton, S., Cheung, M., Cooper, A., Duran, C., Field, M., et al. 2011. *Geneious* v5. 4.

414 Ferro, I., and Morrone, J. J. 2014. Biogeographical transition zones: a search for conceptual synthesis. *Biological Journal of the Linnean Society*, 113: 1-12.

416 Fossette, S., Putman, N. F., Lohmann, K. J., Marsh, R., and Hays, G. C. 2012. A biologist's guide to assessing ocean currents: a review. *Marine Ecology Progress Series*, 457: 285-301.

418 Gallon, R. K., Robuchon, M., Leroy, B., Le Gall, L., Valero, M., and Feunteun, E. 2014.

419 Twenty years of observed and predicted changes in subtidal red seaweed assemblages along a biogeographical transition zone: inferring potential causes from environmental data.

421 *Journal of Biogeography*, 41: 2293-2306.

422 Gilg, M. R., and Hilbish, T. J. 2003. The geography of marine larval dispersal: coupling genetics with fine-scale physical oceanography. *Ecology*, 84: 2989-2998.

424 Goldson, A., Hughes, R., and Gliddon, C. 2001. Population genetic consequences of larval dispersal mode and hydrography: a case study with bryozoans. *Marine Biology*, 138: 1037-1042.

426 1042.

427 Gomez, A., Hughes, R. N., Wright, P. J., Carvalho, G. R., and Lunt, D. H. 2007.

428 Mitochondrial DNA phylogeography and mating compatibility reveal marked genetic structuring and speciation in the NE Atlantic bryozoan *Celleporella hyalina*. *Molecular Ecology*, 16: 2173-2188.

431 Haklay, M., and Weber, P. 2008. Openstreetmap: User-generated street maps. *IEEE Pervasive Computing*, 7: 12-18.

433 Hewitt, G. 2000. The genetic legacy of the Quaternary ice ages. *Nature*, 405: 907-913.

434 Hewitt, G. M. 1996. Some genetic consequences of ice ages, and their role in divergence and speciation. *Biological Journal of the Linnean Society*, 58: 247-276.
1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

58

59

60

436 Hewitt, G. M. 2004. Genetic consequences of climatic oscillations in the Quaternary.

437 Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences,

438 359: 183-195.

439 Hijmans, R. J., Phillips, S., Leathwick, J., Elith, J., and Hijmans, M. R. J. 2017. Package 'dismo'. Circles, 9: 1-68.

441 Hoarau, G., Coyer, J. A., Veldsink, J. H., Stam, W. T., and Olsen, J. L. 2007. Glacial refugia and recolonization pathways in the brown seaweed *Fucus serratus*. Molecular Ecology, 16:

443 3606-3616.

444 Hohenlohe, P. A. 2004. Limits to gene flow in marine animals with planktonic larvae: models of Littorina species around Point Conception, California. Biological Journal of the Linnean Society, 82: 169-187.

447 Johansson, M. L., Alberto, F., Reed, D. C., Raimondi, P. T., Coelho, N. C., Young, M. A., Drake, P. T., et al. 2015. Seascape drivers of *Macrocystis pyrifera* population genetic structure in the northeast Pacific. Molecular Ecology, 24: 4866-4885.

450 Jolly, M. T., Jollivet, D., Gentil, F., Thiébaut, É., and Viard, F. 2005. Sharp genetic break between Atlantic and English Channel populations of the polychaete *Pectinaria koreni*, along the North coast of France. Heredity, 94: 23.

453 Kamvar, Z. N., Tabima, J. F., and Grünwald, N. J. 2014. Poppr: an R package for genetic analysis of populations with clonal, partially clonal, and/or sexual reproduction. PeerJ, 2: e281.

456 Kennedy, J. P., Garavelli, L., Truelove, N. K., Devlin, D. J., Box, S. J., Chérubin, L. M., and Feller, I. C. 2017. Contrasting genetic effects of red mangrove (*Rhizophora mangle* L.) range expansion along West and East Florida. Journal of Biogeography, 44: 335-347.

459 Klein, M., Teixeira, S., Assis, J., Serrão, E. A., Gonçalves, E. J., and Borges, R. 2016. High interannual variability in connectivity and genetic pool of a temperate clingfish matches oceanographic transport predictions. PloS one, 11: e0165881.

462 Lamigueiro, O. P., Hijmans, R., and Lamigueiro, M. O. P. 2018. Package 'rasterVis'.
463 Lein, T. E. 1984. Distribution, reproduction, and ecology of *Fucus ceranoides*

464 L.(Phaeophyceae) in Norway. Sarsia, 69: 75-81.

465 Lett, C., Verley, P., Mullon, C., Parada, C., Brochier, T., Penven, P., and Blanke, B. 2008. A

466 Lagrangian tool for modelling ichthyoplankton dynamics. Environmental Modelling & Software, 23: 1210-1214.

468 Liang, Y., He, D., Jia, Y., Sun, H., and Chen, Y. 2017. Phylogeographic studies of schizothoracine fishes on the central Qinghai-Tibet Plateau reveal the highest known glacial microrefugia. Scientific Reports, 7: 10983.

471 Librado, P., and Rozas, J. 2009. DnaSP v5: a software for comprehensive analysis of DNA polymorphism data. Bioinformatics, 25: 1451-1452.

473 McKenzie, P. F., and Bellgrove, A. 2008. Dispersal of Hormosira banksii (Phaeophyceae) via detached fragments: reporductive viability and longevity. Journal of Phycology, 44: 1108-1115.

476 Mims, M. C., Phillipsen, I. C., Lytle, D. A., Kirk, E. E. H., and Olden, J. D. 2015. Ecological strategies predict associations between aquatic and genetic connectivity for dryland amphibians. Ecology, 96: 1371-1382.

479 Monteiro, C. A., Paulino, C., Jacinto, R., Serrão, E. A., and Pearson, G. A. 2016. Temporal windows of reproductive opportunity reinforce species barriers in a marine broadcast spawning assemblage. Scientific reports, 6: 29198.

482 Muhlin, J. F., Engel, C. R., Stessel, R., Weatherbee, R. A., and Brawley, S. H. 2008. The influence of coastal topography, circulation patterns, and rafting in structuring populations of an intertidal alga. Molecular Ecology, 17: 1198-1210.

485 Munda, I. M. 1999. The benthic algal vegetation of land-locked fjords in southeastern Iceland. Hydrobiologia, 393: 169.

487 Munwes, I., Geffen, E., Roll, U., Friedmann, A., Daya, A., Tikochinski, Y., and Gafny, S.

488 2010. The change in genetic diversity down the core-edge gradient in the eastern spadefoot toad (*Pelobates syriacus*). Molecular Ecology, 19: 2675-2689.
1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

58

59

60

490 Neiva, J., Paulino, C., Nielsen, M. M., Krause-Jensen, D., Saunders, G. W., Assis, J.,

491 Bárbara, I., et al. 2018. Glacial vicariance drives phylogeographic diversification in the

492 amphi-boreal kelp *Saccharina latissima*. Scientific reports, 8: 1112.

493 Neiva, J., Pearson, G. A., Valero, M., and Serrão, E. A. 2010. Surfing the wave on a

494 borrowed board: range expansion and spread of introgressed organellar genomes in the

495 seaweed *Fucus ceranoides* L. Molecular Ecology, 19: 4812-4822.

496 Neiva, J., Pearson, G. A., Valero, M., and Serrão, E. A. 2012a. Drifting fronds and drifting

497 alleles: range dynamics, local dispersal and habitat isolation shape the population structure

498 of the estuarine seaweed *Fucus ceranoides*. Journal of Biogeography, 39: 1167-1178.

499 Neiva, J., Pearson, G. A., Valero, M., and Serrão, E. A. 2012b. Fine-scale genetic breaks

500 driven by historical range dynamics and ongoing density-barrier effects in the estuarine

501 seaweed *Fucus ceranoides* L. BMC Evolutionary Biology, 12: 78.

502 Newman, M. E. 2006. Modularity and community structure in networks. Proceedings of the

503 national academy of sciences, 103: 8577-8582.

504 Nicastro, K. R., Zardi, G. I., McQuaid, C. D., Teske, P. R., and Barker, N. P. 2008. Coastal

505 topography drives genetic structure in marine mussels. Marine Ecology Progress Series,

506 368: 189-195.

507 Nicastro, K. R., Zardi, G. I., Teixeira, S., Neiva, J., Serrão, E. A., and Pearson, G. A. 2013.

508 Shift happens: trailing edge contraction associated with recent warming trends threatens a

509 distinct genetic lineage in the marine macroalga *Fucus vesiculosus*. BMC Biology, 11: 6.

510 Oksanen, J., Blanchet, F., Friendly, M., Kindt, R., Legendre, P., McGlinn, D., Minchin, P., et

511 al. 2018. vegan: a community ecology package. R package verions 2.4-6.

512 Olsen, J. L., Zechman, F. W., Hoarau, G., Coyer, J. A., Stam, W. T., Valero, M., and Åberg,

513 P. 2010. The phylogeographic architecture of the fucoid seaweed *Ascophyllum nodosum*: an

514 intertidal 'marine tree'and survivor of more than one glacial-interglacial cycle. Journal of

515 Biogeography, 37: 842-856.

516 Pardo, C., Guillemin, M.-L., Pena, V., Barbara, I., Valero, M., and Barreiro, R. 2019. Local

517 coastal configuration rather than latitudinal gradient shape clonal diversity and genetic
1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

58

59

60

518

structure of *Phymatolithon calcareum* maerl beds in North European Atlantic. Frontiers in Marine Science, 6: 149.

520

Provan, J. 2013. The effects of past, present and future climate change on range-wide genetic diversity in northern North Atlantic marine species. Frontiers of Biogeography, 5(1).

522

Provan, J., Wattier, R. A., and Maggs, C. A. 2005. Phylogeographic analysis of the red seaweed *Palmaria palmata* reveals a Pleistocene marine glacial refugium in the English Channel. Molecular Ecology, 14: 793-803.

525

Puillat, I., Lazure, P., Jégou, A., Lampert, L., and Miller, P. 2004. Hydrographical variability on the French continental shelf in the Bay of Biscay, during the 1990s. Continental Shelf Research, 24: 1143-1163.

528

Putman, N. F., and He, R. 2013. Tracking the long-distance dispersal of marine organisms: sensitivity to ocean model resolution. Journal of the Royal Society Interface, 10: 20120979.

530

Remerie, T., Vierstraete, A., Weekers, P. H., Vanfleteren, J. R., and Vanreusel, A. 2009.

531

Phylogeography of an estuarine mysid, *Neomysis integer* (Crustacea, Mysida), along the north-east Atlantic coasts. Journal of Biogeography, 36: 39-54.

533

Roucoux, K., De Abreu, L., Shackleton, N., and Tzedakis, P. 2005. The response of NW Iberian vegetation to North Atlantic climate oscillations during the last 65kyr. Quaternary Science Reviews, 24: 1637-1653.

536

Ruiz-Villarreal, M., González-Pola, C., del Río, G. D., Lavin, A., Otero, P., Piedracoba, S., and Cabanas, J. 2006. Oceanographic conditions in North and Northwest Iberia and their influence on the Prestige oil spill. Marine Pollution Bulletin, 53: 220-238.

539

Selkoe, K. A., Watson, J. R., HORIN, T. B., IACCHEI, M., MITARAI, S., SIEGEL, D. A., GAINES, S. D., et al. 2010. Taking the chaos out of genetic patchiness: seascape genetics reveals ecological and oceanographic drivers of genetic patterns in three temperate reef species. Molecular Ecology, 19: 3708-3726.

543

Serrão, E. A., Kautsky, L., Lifvergren, T., and Brawley, S. H. 1997. Gamete dispersal and pre-recruitment mortality in Baltic *Fucus vesiculosus*. Phycologia, 36 101-102.

544
1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

58

59

60

545 Slatkin, M. 1993. Isolation by distance in equilibrium and non-equilibrium populations.

546 Evolution, 47: 264-279.

547 Smith, B. T., Escalante, P., Baños, B. E. H., Navarro-Sigüenza, A. G., Rohwer, S., and

548 Klicka, J. 2011. The role of historical and contemporary processes on phylogeographic

549 structure and genetic diversity in the Northern Cardinal, Cardinalis cardinalis. BMC

550 Evolutionary Biology, 11: 136.

551 Sotka, E. E., Wares, J. P., Barth, J. A., Grosberg, R. K., and Palumbi, S. R. 2004. Strong

552 genetic clines and geographical variation in gene flow in the rocky intertidal barnacle

553 Balanus glandula. Molecular Ecology, 13: 2143-2156.

554 Spalding, M. D., Fox, H. E., Allen, G. R., Davidson, N., Ferdana, Z. A., Finlayson, M.,

555 Halpern, B. S., et al. 2007. Marine ecoregions of the world: a bioregionalization of coastal

556 and shelf areas. Bioscience, 57: 573-583.

557 Team, R. C. 2018. R: A language and environment for statistical computing; 2015.

558 Tellier, F., Tapia, J., Faugeron, S., Destombe, C., and Valero, M. 2011. The * lessonia*

559 *nigrescens* species complex (laminariales, phaeophyceae) shows strict parapatry and

560 complete reproductive isolation in a secondary contact zone 1. Journal of Phycology, 47:

561 894-903.

562 Teske, P., Papadopoulos, I., Zardi, G., McQuaid, C., Edkins, M., Griffiths, C., and Barker, N.

563 2007. Implications of life history for genetic structure and migration rates of southern African

564 coastal invertebrates: planktonic, abbreviated and direct development. Marine Biology, 152:

565 697-711.

566 Teske, P. R., Von Der Heyden, S., McQuaid, C. D., and Barker, N. P. 2011. A review of

567 marine phylogeography in southern Africa. South African Journal of Science, 107: 43-53.

568 Thiel, M., and Haye, P. 2006. The ecology of rafting in the marine environment-III.

569 Biogeographical and evolutionary consequences (in Oceanography and marine biology: An

570 annual review-Volume 48, pp. 323-429).
1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

58

59

60

571 Varela, R. A., Rosón, G., Herrera, J. L., Torres-López, S., and Fernández-Romero, A. 2005.

572 A general view of the hydrographic and dynamical patterns of the Rías Baixas adjacent sea area. Journal of Marine Systems, 54: 97-113.

574 Wares, J. P., Gaines, S., and Cunningham, C. W. 2001. A comparative study of asymmetric migration events across a marine biogeographic boundary. Evolution, 55: 295-306.

576 Woodruff, D. S. 1973. Natural hybridization and hybrid zones. Systematic Biology, 22: 213-218.

578 Zardi, G., McQuaid, C., Teske, P., and Barker, N. 2007. Unexpected genetic structure of mussel populations in South Africa: indigenous *Perna perna* and invasive *Mytilus galloprovincialis*. Marine Ecology Progress Series, 337: 135-144.

581 Zardi, G., Nicastro, K., McQuaid, C., Hancke, L., and Helmuth, B. 2011. The combination of selection and dispersal helps explain genetic structure in intertidal mussels. Oecologia, 165: 947-958.

584 Zardi, G. I., Nicastro, K. R., Ferreira Costa, J., Serrão, E. A., and Pearson, G. A. 2013.

585 Broad scale agreement between intertidal habitats and adaptive traits on a basis of contrasting population genetic structure. Estuarine, Coastal and Shelf Science, 131: 140-148.

588

589

590

591

592

593

594

595

596

597

598

599

600
591 FIGURE LEGEND

592 **Fig. 1.** Haplotype distribution of *Fucus ceranoides* in the coastlines of (a) Northwester France and (panel b) Northwest Iberia. The colors along coastlines (a, b) depict the different oceanographic regions (R) identified in network analysis. A pairwise matrix of directional connectivity between oceanographic regions identified in (d) western Brittany and (e) northwest Iberia. Matrix header colors according to the oceanographic regions depicted in the top panels a and b. Haplotype frequency and differentiation degree in (f) western Brittany and (g) northwest Iberia. Note that there is no correspondence of haplotypes between the two panels (i.e., each dataset was treated separately).

600

601 TABLES

602 **Table 1.** Maximum and average distances (km), drifting time (days) and probabilities produced by the particles connecting different cells for the lagrangian particle simulations running in Northwest France and Northwest Spain..

605

<table><thead><tr><th rowspan="2">Region</th><th colspan="2">Distance (km)</th><th colspan="2">Time (days)</th><th colspan="2">Probability</th></tr><tr><th>Maximum</th><th>Mean (±SD)</th><th>Maximum</th><th>Mean (±SD)</th><th>Maximum</th><th>Mean (±SD)</th></tr></thead><tbody><tr><td>W Brittany</td><td>382.6</td><td>62.6±54.6</td><td>24.6</td><td>3.61±2.63</td><td>0.721</td><td>0.004±0.020</td></tr><tr><td>NW Iberia</td><td>431.2</td><td>105.9±90.8</td><td>26.7</td><td>2.09±1.81</td><td>0.607</td><td>0.004±0.021</td></tr></tbody></table>

606