doi: 10.1111/jeb.12170
Parallel speciation or long-distance dispersal? Lessons
from seaweeds (Fucus) in the Baltic Sea
~ R*, D. JOHANSSON*, H. FORSLUND†, L. KAUTSKY†,
R . T . P E R E Y R A * , C . H U E N C H U NI
P. R. JONSSON* & K. JOHANNESSON*
*Department of Biological and Environmental Sciences – Tj€arn€o, University of Gothenburg, Str€omstad, Sweden
†Department of Botany, Stockholm University, Stockholm, Sweden
Keywords:
Abstract
biophysical ocean modelling;
clonality;
Fucus radicans;
Fucus vesiculosus;
long-distance drift;
parallel divergence.
Parallel evolution has been invoked as a forceful mechanism of ecotype and
species formation in many animal taxa. However, parallelism may be difficult to separate from recently monophyletically diverged species that are
likely to show complex genetic relationships as a result of considerable
shared ancestral variation and secondary hybridization in local areas. Thus,
species’ degrees of reproductive isolation, barriers to dispersal and, in particular, limited capacities for long-distance dispersal will affect demographical
structures underlying mechanisms of divergent evolution. Here, we used
nine microsatellite DNA markers to study intra- and interspecific genetic
diversity of two recently diverged species of brown macroalgae, Fucus radicans (L. Bergstr€
om & L. Kautsky) and F. vesiculosus (Linnaeus), in the Baltic
Sea. We further performed biophysical modelling to identify likely connectivity patterns influencing the species’ genetic structures. For each species,
we found intraspecific contrasting patterns of clonality incidence and population structure. In addition, strong genetic differentiation between the two
species within each locality supported the existence of two distinct evolutionary lineages (FST = 0.15–0.41). However, overall genetic clustering analyses across both species’ populations revealed that all populations from one
region (Estonia) were more genetically similar to each other than to their
own taxon from the other two regions (Sweden and Finland). Our data support a hypothesis of parallel speciation. Alternatively, Estonia may be the
ancestral source of both species, but is presently isolated by oceanographic
barriers to dispersal. Thus, a limited gene flow in combination with genetic
drift could have shaped the seemingly parallel structure.
Introduction
Explaining the evolution and coexistence of closely
related species is central in biology, particularly to
understand how new biodiversity is formed. Addressing
these issues in recently branched evolutionary lineages
across their distributional ranges provides opportunities
to discern the mechanisms that explain their divergence
and to identify potential factors influencing the
formation of barriers to gene exchange (Nosil et al.,
Correspondence: Ricardo T. Pereyra, Department of Biological and
Environmental Sciences – Tj€arn€
o, University of Gothenburg, SE 452 96
Str€
omstad, Sweden. Tel.: +46 (0) 31 7869617; fax: +46 526 68607;
e-mail: [email protected]
2009; Via, 2009). In particular, broadly distributed taxa
living in sympatry provide insight into the historical
factors that brought them into contact and the current
forces driving and maintaining their divergence (Machado & Hey, 2003; Landry et al., 2007). However, gene
flow between incipient species, local adaptation and
genetic drift accompanying the divergence may result
in complex evolutionary histories to interpret. Under
either scenario, natural selection can prevent gene flow
at genomic regions associated with specific adaptations,
maintaining the divergence at some genes even in the
presence of gene flow at other genes (Machado et al.,
2002; Smadja & Butlin, 2011). Furthermore, reproductive isolation between independent species pairs in
sympatric populations may evolve repeatedly due to
ª 2013 THE AUTHORS. J. EVOL. BIOL.
JOURNAL OF EVOLUTIONARY BIOLOGY ª 2013 EUROPEAN SOCIETY FOR EVOLUTIONARY BIOLOGY
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R. T. PEREYRA ET AL.
similar divergent selection pressures resulting in parallel
speciation (Johannesson, 2001; McKinnon et al., 2004).
Parallel speciation (also referred to as ‘convergent evolution’; see Johannesson et al., 2010 for discussion) is
commonly invoked in animal systems (e.g. Schluter &
Nagel, 1995; Rundle & Nosil, 2005; Schluter, 2009),
many of which are well documented with strong
evidence. Among the most studied systems are the
‘benthic’ and ‘limnetic’ ecotypes of threespine sticklebacks in the British Columbian lakes (McKinnon &
Rundle, 2002), the marine snail Littorina ecotypes on
European rocky coasts (Panova et al., 2006; Quesada
et al., 2007), lake whitefish (Østbye et al., 2006) and
walking sticks (Nosil et al., 2002). However, cases of
parallel speciation in plants (or algae) are rare (Ostevik
et al., 2012) possibly the most compelling case being
the tall and dwarf Eucalyptus inhabiting granite headlands (Foster et al., 2007).
Brown algae of the genus Fucus show examples of
recent divergence within large open marine systems in
the North Atlantic (Coyer et al., 2003; Pereyra et al.,
2009; Billard et al., 2010; Zardi et al., 2011) and are good
candidates to study repeated species divergence in different geographical regions. Here we study the Fucus of the
Baltic Sea, a large and young (post-glacial) brackish
water basin of the NE Atlantic where genetic divergence
is expected due to local adaptation driven by topography
or salinity regimes, life history strategies or the species
dispersal potential modified by hydrodynamic conditions
(Luttikhuizen et al., 2003; Johannesson & Andr
e, 2006;
Nikula et al., 2008). The Baltic Sea hosts a low number
of marine species (Ojaveer et al., 2010) and has a salinity
gradient that spans more than an order of magnitude
(~2–30 practical salinity units, psu) from the inner parts
to the North Sea, causing strong local adaptation in most
of the marine lineages that survived the marine/brackish
transition 4000 years ago (Johannesson & Andr
e, 2006;
Larsen et al., 2008; Nielsen et al., 2009). Here, two
closely related species of fucoid algae, namely Fucus vesiculosus and the dwarfed species Fucus radicans, live sympatrically (Bergstr€
om et al., 2005; Johannesson et al.,
2011) (Fig. 1). The bladder wrack Fucus vesiculosus is the
most dominant and ecologically important large
seaweed within the Baltic Sea (Kalvas & Kautsky,
1993). It is dioecious, perennial and reproduces mainly
sexually, although low levels of vegetative reproduction
(clonal) via reattachment of adventitious branches have
been documented in the central Baltic Sea (Tatarenkov
et al., 2005). Fucus vesiculosus is characterized by high
genetic subdivision at short geographical distances
(10 m–100 km) (Tatarenkov et al., 2007), consistent
with low dispersal capacity (Serr~ao et al., 1996). It is also
common in the sub-Arctic and temperate regions of the
northern Atlantic, and it colonized the Baltic after the
last glaciation 6500 years ago (Andren et al., 2000). In
contrast, F. radicans has a very recent evolutionary history, having diverged from F. vesiculosus inside the Baltic
Fig. 1 Fucus radicans and F. vesiculosus. Individuals of both species
from the Estonian Baltic coast of Saaremaa Island attached to the
same rock.
within the last 2500 years (Pereyra et al., 2009). Fucus
radicans is known to reproduce mainly asexually (clonal)
in Sweden and northern Finland (75–90% asexually
recruited thalli) (Tatarenkov et al., 2005; Johannesson
et al., 2011), whereas populations in Estonia and along
the south-east Finnish coast show none or significantly
lower incidence of asexual reproduction (~10–30%,
Johannesson et al., 2011). In contrast to the pan-Atlantic distribution of F. vesiculosus, F. radicans is endemic to
the Baltic Sea (Pereyra et al., 2009). However, because
suitable habitat for both species in the Baltic is largely
spatially segregated, species’ distributions are largely
sympatric but geographically spread out. Therefore,
given both species’ poor dispersal capabilities, their sympatric occurrence at different segregated geographical
regions of the Baltic remains to be explained.
Here, we investigated whether the repeated sympatric distribution of F. vesiculosus and F. radicans in different geographical regions is the result of parallel
divergence, long-distance dispersal or their evolutionary
history within the Baltic Sea. Due to their recent divergence, previous studies using sequence data have not
resolved the evolutionary relationships between the
two species (Coyer et al., 2006; C
anovas et al., 2011).
Therefore, we used a set of nine microsatellite loci to
examine the patterns of population genetic differentiation within and between species in three regions where
they co-occur in the Baltic. We also analysed the patterns of clonal distribution to assess the impact of
reproductive mode in the species’ long-distance
dispersal and maintenance of reproductive isolation.
And finally, we incorporated a biophysical modelling
approach based on ocean circulation to assess the
relative influence of abiotic factors such as local ocean
currents in the dispersal capabilities of these species.
ª 2013 THE AUTHORS. J. EVOL. BIOL. doi: 10.1111/jeb.12170
JOURNAL OF EVOLUTIONARY BIOLOGY ª 2013 EUROPEAN SOCIETY FOR EVOLUTIONARY BIOLOGY
Parallel speciation in Fucus?
Materials and methods
Morphological analysis
Sample collection
Individuals of F. radicans and F. vesiculosus were
collected from seven localities in three regions of the
Baltic Sea (Fig. 2) where both species occur in sympatry. With the exception of two Estonian localities, all
other sampled localities are sympatric, that is, thalli of
the two species are commonly found at distances
< 1 m. Sampled regions were defined as the three
countries: Sweden (West Baltic), Finland (East Baltic)
and Estonia (Central Baltic, Fig. 2). In Sweden, three
€
localities were sampled: Oregrund
(‘Swe1’) with four
replicates separated by 2.5 km; Djursten (‘Swe2’) at
€
5 km from Oregrund
and B€
onhamn (‘Swe3’) at
€
~300 km north of Oregrund.
Samples from Finland
came from Southern Vallgrund (‘Fin’). Estonian samples belonged to Triigi (‘Est1’), exclusively inhabited by
F. radicans; at Pulli Panki (‘Est2’), 18 km from Triigi,
both species occur sympatrically and K~
oiguste (‘Est3’)
at ~50 km from Pulli Panki along the coastline, only
F. vesiculosus occurs. Assigned codes for localities and
number of sampled individuals are provided in Table 1.
To identify potentially misclassified individuals or the
presence of hybrids, two morphological variables were
measured for each individual: (1) frond width, midway
between the youngest and next youngest dichotomy,
and measured at three separate branches; (2) distance
between dichotomies, measured from the second oldest
dichotomy and onward, five repeated measurements.
These variables have previously proven diagnostic for
morphological discrimination between F. radicans and
F. vesiculosus (Bergstr€
om et al., 2005). These data were
analysed by factor analysis using principal components
performed in MYSTAT 12 (Cranes Software Intl., Bangalore, India) to detect intermediate or misclassified
morphotypes.
Genotyping
DNA was extracted from dried algal tissue using DNeasy
Plant MiniKit, and samples were genotyped at nine
microsatellites developed from fucoid species (Engel
et al., 2003; Perrin et al., 2007) and previously used in
other studies (Pereyra et al., 2009; Johannesson et al.,
1.00
0.80
0.60
0.40
0.20
0.00
1.00
Fig. 2 Sampling localities and perlocality interspecific genetic
differentiation. Map of the Baltic Sea
showing the main sampling localities in
Sweden, Finland and Estonia. Localities’
abbreviations as in Table 1. Histograms
of Bayesian individual assignment tests
illustrate species’ genotypic clustering at
each locality based on allele frequencies
[repeated genotypes (clones) were
excluded from this analysis]. Each bar
represents an individual, and its
assignment probability into a genetic
cluster represented by different colours
(Fucus radicans–yellow; Fucus vesiculosus–
red/blue). More than one colour per
individual indicates genetic admixture.
3
1.00
0.80
0.60
0.40
0.20
0.00
0.80
0.60
0.40
0.20
0.00
1.00
0.80
0.60
0.40
0.20
0.00
ª 2013 THE AUTHORS. J. EVOL. BIOL. doi: 10.1111/jeb.12170
JOURNAL OF EVOLUTIONARY BIOLOGY ª 2013 EUROPEAN SOCIETY FOR EVOLUTIONARY BIOLOGY
1.00
0.80
0.60
0.40
0.20
0.00
4
R. T. PEREYRA ET AL.
Table 1 Distribution of genetic diversity per population for each species.
Fucus radicans
Region
Sweden
Finland
Estonia
Fucus vesiculosus
Locality
psu
n*
n
Ho
He
Clones (%)
n*
n
Ho
He
Clones (%)
€
Swe1 (Oregrund)
Swe2 (Djursten)
€nhamn)
Swe3 (Bo
Fin (S. Vallgrund)
Est1 (Triigi)
Est2 (Pulli Panki)
~iguste)
Est3 (Ko
5.0
5.0
3.8
4.3
5.6
5.8
5.2
144
49
78
100
25
15
NA
27
17
17
17
25
15
NA
0.57
0.66
0.56
0.42
0.53
0.54
NA
0.43
0.50
0.45
0.39
0.62
0.62
NA
90.3
79.6
87.1
96.0
0
0
NA
144
51
34
16
NA
9
25
122
32
29
11
NA
9
24
0.50
0.63
0.48
0.72
NA
0.30
0.50
0.63
0.57
0.56
0.53
NA
0.53
0.59
15.3
52.9
26.5
50
NA
0
8.3
Ten-year average salinity during June in practical salinity units (psu), sample sizes used to determine the percentage of clonality in a population, that is, the total number of sampled units from each localities including the repeated genotypes (n*), sample sizes (n) corresponding
exclusively to analysed data including one individual of each clone and all unique genotypes, mean observed (Ho) and expected (He) heterozygosity and percentage of individuals with repeated genotypes due to asexual reproduction within a population (Clones%).
2011). PCR amplifications were performed also as in Johannesson et al. (2011). Labelled products were multiplexed and resolved on a Beckman Coulter automated
sequencer, and CEQMAN 8000 software (Beckman Coulter Inc., Fullerton, CA, USA) was used for allele sizing.
Genetic diversity
Raw data were checked and corrected for null alleles,
allele dropouts or genotyping errors using 1000 randomizations in MICRO-CHECKER 2.2.3 (van Oosterhout et al.,
2004). In addition, we estimated the proportion of clones
for each species as the probability that two genotypes are
identical by chance (clones are genotypes identical by
common ancestry) using GENCLONE 2.0 (Arnaud-Haond &
Belkhir, 2007). Once clones were determined, only one
individual of each clone was used and the remaining
genotype copies were removed for subsequent analyses.
All the remainder unique genotypes were included.
Allele variation, estimates of genetic diversity, tests for
linkage disequilibrium, Hardy–Weinberg departures and
their statistical significance were obtained with ARLEQUIN
3.11 (Excoffier et al., 2005).
Population differentiation
To examine and identify the distribution of genetic
diversity at each region, analyses of molecular variance
(AMOVA) were performed with ARLEQUIN 3.11. We
obtained measures of genetic differentiation at different
hierarchical levels (across species, species’ populations
and regions), and separate AMOVA for each taxon were
performed to assess detailed patterns of differentiation.
To explain these patterns, F-statistics were calculated
using ARLEQUIN 3.11 that provides Bonferroni-corrected
significance levels (Excoffier et al., 2005). A Bayesian
assignment analysis was performed using STRUCTURE
2.2 (Pritchard et al., 2000) with a burn-in period of
50 000 and 1 000 000 iterations, to infer a genetic classification of sympatric individuals for each separate
locality and for the complete data set. We estimated Δk,
proposed by Evanno et al. (2005), to determine the
overall most likely number of k and given a potential
ambiguity it was also carried out for locality ‘Swe1’. For
the overall analysis, we also used BAPS 5.3 with the
‘Clustering of individuals’ option (Corander et al., 2008)
as an alternative approach to infer the whole optimum
number of k clusters across species and localities. This
method does not assume a fixed k (as STRUCTURE does)
and thus allows for the direct inference of the most
likely k (Latch et al., 2006; Guillot et al., 2009). A ‘gene
flow network’ (Tang et al., 2009) was also generated
with this program based on the estimated individual
ancestries to further illustrate the admixture of each
sampled region. Finally, a neighbour-joining (NJ) tree
was constructed using Cavalli-Sforza genetic distances
with 1000 iterations using POPULATIONS (http://bioinformatics.org/~tryphon/populations/) to further assess
the overall genetic affinities between species and
geographical regions.
Biophysical model of Fucus dispersal
Dispersal and connectivity of Fucus radicans/vesiculosus was
simulated with a biophysical model based on ocean circulation and drift in surface waters (0–6 m). Drift of particles
(Fucus prolifications and fragments of thalli) was
simulated using velocity fields from the 3-dimensional
ocean circulation Rossby Centre Ocean model (RCO) for
the Baltic Sea (described in D€
oscher et al., 2002). RCO
was applied in hindcast mode for 25 years (1981–2005)
with a horizontal resolution of 3.7 km (2 nm), a vertical
resolution of 3–12 m and a temporal resolution of 6 h.
Dispersal in surface waters was simulated as particle trajectories lasting for 21 days calculated with the Lagrang€s
ian trajectory model TRACMASS, which is based on D€
oo
(1995). Trajectories were simulated in offline mode using
the velocity fields generated by the RCO model. Dispersal
from each of the 5168 grid cells in the Baltic Sea with a
mean depth above 12 m was simulated by releasing 140
ª 2013 THE AUTHORS. J. EVOL. BIOL. doi: 10.1111/jeb.12170
JOURNAL OF EVOLUTIONARY BIOLOGY ª 2013 EUROPEAN SOCIETY FOR EVOLUTIONARY BIOLOGY
Parallel speciation in Fucus?
particles distributed across one grid cell and depth
between 0 and 6 m. This was repeated at 25 time points
(in spring) within each year and repeated for all 25 years
resulting in a total of 87 500 trajectories per grid cell
and for the whole model domain 452 200 000
trajectories. Dispersal probabilities between all grid cells
(depth 12 m) were calculated as the proportion of trajectories starting at grid cell j and ending in grid cell i, and
then summarized in a 5168 9 5168 connectivity matrix.
The distribution of dispersal distances, estimated from the
trajectories, showed a positive skew with the 50th percentile at 10 km and the 90th percentile at 46 km. For each
of the seven sample locations (Fig. 5), we then projected
the dispersal probability distribution after five dispersal
events by successive multiplication of the connectivity
matrix by a population vector. As we did not include any
population parameters, the dispersal probabilities from
the sample locations only give relative probabilities
assuming identical population density and rates of reproduction and mortality. We also acknowledge that the
exact correlation between water advection and dispersal
rate of vegetative parts, for example, adventitious
branches, is not known, and dispersal probabilities should
only be interpreted on a relative timescale.
Results
Distribution of genetic diversity, clonality and
morphology
In total, 690 Fucus individual thalli were genotyped
from which 345 individuals with unique genotypes
were analysed after removal of repeated genotypes
(clones), and the results are summarized in Table 1. All
nine loci were polymorphic for both species in the
three regions. Heterozygosity values (He) ranged from
0.39 to 0.62 in F. radicans and in F. vesiculosus were
between 0.53 and 0.63. Overall observed heterozygosity
was highest in F. radicans from ‘Swe2’ and in F.
5
vesiculosus from Finland. After removal of clones, significant deviations from Hardy–Weinberg expectations
(HWE) were detected at some loci, mainly observed in
the Swedish populations of both species, whereas only
two loci (Fsp1 and Fsp2) appeared deviated from HWE
in Estonia and none showed significant deviation in the
Finnish populations (data not shown). Results from
MICRO-CHECKER showed no scoring errors owing to large
allele dropout or stuttering at any loci. Locus Fsp1 and
Fsp2 showed possible null alleles with a frequency of
0.125 and 0.176, but due to its low frequency and the
minor effect that these null alleles may have on the
detection of genetic differentiation (Carlsson, 2008),
these loci were kept for subsequent analysis.
The proportion of clones varied noticeably among the
geographical regions sampled within and between
species (Table 1). High clonality characterized Swedish
and Finnish F. radicans (range from 79 to 96%),
whereas no clonality was found in Estonian F. radicans.
In contrast, low to intermediate levels of clonality were
found in Swedish and Finnish F. vesiculosus (range from
15.3 to 50%), and only one pair of clones were
detected in Estonian F. vesiculosus.
We only used the two most distinctive morphological
traits reported by Bergstr€
om et al. (2005) to characterize
F. radicans and F. vesiculosus. Overall, these characters
show significant distinction between the two species
(Fig. 3). These traits were generally uniform across the
species’ distributional ranges with no discernible population differences in morphology within each species.
However, F. radicans individuals were more aggregated
in comparison with F. vesiculosus individuals that were
morphologically more variable.
Intraspecific differentiation
Population differentiation within each species varied
contrastingly (Table 2). AMOVA results showed that
although F. radicans had relatively large and significant
Fig. 3 Plot of two morphological
variables in Fucus radicans and
F. vesiculosus. Results from a principal
component analysis based on two
morphological variables with five
measurements. Abbreviations from
series legends are according to Table 1.
ª 2013 THE AUTHORS. J. EVOL. BIOL. doi: 10.1111/jeb.12170
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R. T. PEREYRA ET AL.
Table 2 Results of the hierarchical AMOVA analysis. Three separate models for both Fucus species together and for each species. The
significance was tested through 1000 permutations.
Model
Partitioning
Variation (%)
F-statistic
P
Both species
Between species
Among populations within species
Within populations
Among regions
Among populations within regions
Within populations
Among regions
Among populations within regions
Within populations
6.53
19.86
86.67
30.39
1.24
70.84
3.50
13.28
83.22
FCT = 0.065
FSC = 0.186
FST = 0.133
FCT = 0.303
FST = 0.017
FIS = 0.291
FCT = 0.035
FST = 0.137
FIS = 0.167
0.658
< 0.001
< 0.001
0.043
0.643
< 0.001
0.186
< 0.001
< 0.001
F. radicans
F. vesiculosus
Table 3 Pairwise FST values of population differentiation.
Swe2Frad
Swe3Frad
Swe1Fves
Swe2Fves
Swe3Fves
FinFrad
FinFves
Est2Frad
Est1Frad
Est2Fves
Est3Fves
Swe1Frad
Swe2Frad
Swe3Frad
Swe1Fves
Swe2Fves
Swe3Fves
FinFrad
FinFves
0.04
0.01
0.15*
0.17*
0.23*
0.10
0.41*
0.28*
0.30*
0.26*
0.24*
0.02
0.10*
0.12*
0.23*
0.07*
0.35
0.21*
0.23*
0.22*
0.18*
0.13*
0.15*
0.22*
0.04
0.38*
0.26*
0.28*
0.26*
0.24*
0.05*
0.15*
0.17*
0.19*
0.10*
0.12*
0.13*
0.10*
0.19*
0.20*
0.30*
0.19*
0.22*
0.15*
0.18*
0.28*
0.24*
0.23*
0.23*
0.25*
0.23*
0.39*
0.30*
0.32*
0.28*
0.25*
0.18*
0.20*
0.31
0.22*
Est2Frad
0.01
0.16
0.09*
Est1Frad
Est2Fves
0.20*
0.09*
0.05
Asterisks indicate significant P-values after Bonferroni correction (P 0.05).
Abbreviations indicate F. radicans (Frad) and F. vesiculosus (Fves) and localities as in Table 1.
variation among sampling regions (i.e. Sweden, Estonia
and Finland; 30.39%, P < 0.04), and low nonsignificant
variation within regions (1.24%, P = 0.65), F. vesiculosus showed comparatively less and nonsignificant differences among regions (3.50%, P = 0.19) but a larger
significant differentiation among populations within
regions (13.28%, P < 0.001). Results from pairwise
FST values gave further insight into these patterns
(Table 3). Fucus radicans showed no significant genetic
structure among Swedish populations and also between
Swedish and Finnish populations. On the other hand,
high and significant genetic differences between Estonian localities and the other two regions largely
accounted for the large variation within F. radicans. In
contrast, F. vesiculosus only showed no genetic structure
between the Estonian populations, whereas all other
pairwise comparisons were significantly different.
Interspecific genetic differentiation
Both species were well differentiated genetically in each
sympatric locality (Fig. 2). Results from STRUCTURE analysis by locality showed clear separation between species
when occurring sympatrically, except in ‘Swe1’ where
k = 3 appeared as the most likely number of clusters
(Fig. S1), showing additional variation within F. vesiculosus (Fig. 2, blue bars). Yet, these analyses consistently
showed cohesiveness of F. radicans clusters in each
locality (red clusters, Fig. 2). The results from the macrogeographical clustering analysis across species’ populations using BAPS showed that, in addition, Swedish
and Finnish F. radicans populations formed a single
cluster separated from Estonian F. radicans, whereas
Swedish, Finnish and Estonian F. vesiculosus conformed
three separate genetic clusters (Fig. 4a). The allelebased neighbour-joining tree confirmed these results
but it also showed stronger affinities between F. radicans and F. vesiculosus from Estonia than with their own
taxon from either the Finnish or Swedish populations
(Fig. 4b). In addition, this tree shows a split of two
lineages, each with both taxa evolving in parallel
within the Baltic Sea. Finally, the gene flow network
(Fig. 4c) offers potential directions of earlier and present population connectivity, showing F. radicans from
the Gulf of Bothnia (Sweden/Finland) and F. vesiculosus
from Sweden as sink populations, bearing genetic variation from the other sampled localities (Finnish and
Estonian F. vesiculosus and the Estonian F. radicans).
These latter localities, on the other hand, primarily
appeared as sources of genetic variation.
ª 2013 THE AUTHORS. J. EVOL. BIOL. doi: 10.1111/jeb.12170
JOURNAL OF EVOLUTIONARY BIOLOGY ª 2013 EUROPEAN SOCIETY FOR EVOLUTIONARY BIOLOGY
Parallel speciation in Fucus?
7
(a)
(b)
Fig. 4 Overall genetic differentiation between Fucus species in the Baltic Sea. (a) Combined histogram of Bayesian individual assignment
test to illustrate the overall genotypic clustering of both species from all the sampling localities. Bars represent individual assignment
probability into different genetic clusters depicted with colours, as in Fig. 2. (b) Neighbour-joining microsatellite-based population tree
calculated with Cavalli-Sforza genetic distances. Out-group locations are indicated in Fig. 4c. (c) Map of the Baltic Sea with a superimposed
gene flow network identifying the genetic sources among species and populations. Arrow thickness is proportional to the amount of gene
flow to the indicated direction. Numbers 1 and 2 correspond to out groups Fucus vesiculosus from Eggholmen, Norway and Fiskeb€
ackskil,
west Sweden, respectively.
Dispersal simulations
Our simulations based on the ocean circulation model
showed limited dispersal probability from Sweden
towards Finland or Estonia (Fig. 5a–c), but thalli fragments from Finland are likely to disperse towards the
coast of Sweden (Fig. 5d). Our results also show that
dispersal from Estonia towards northern localities in Finland and Sweden is unlikely (Fig. 5e), whereas some
dispersal towards the Gulf of Finland may occur (Fig. 5f,
g), suggesting a strong barrier that currently isolates
Estonian populations from those in the Bothnian Sea.
Discussion
In this study, we found that populations of F. vesiculosus
and F. radicans from one region, Estonia, despite having
evolved a barrier to current gene flow, appear genetically more closely related to each other than to any of
the other populations of this study (from Sweden or
Finland) of their own taxon. In addition, our results of
intraspecific population differentiation also revealed
continuous gene flow between Swedish and Finnish
populations of F. radicans in the northern Baltic Sea,
whereas F. vesiculosus appeared highly genetically structured over its whole distribution.
In Fucus species that release gametes under relatively
calm water conditions (e.g. F. vesiculosus and F. spiralis),
population divergence is expected given the poor
dispersal of their gametes and zygotes (negatively buoyant and rapidly sinking zygotes) (Coleman & Brawley,
2005), and previous population genetic studies have
confirmed these expectations over short geographical
distances (Perrin et al., 2007; Tatarenkov et al., 2007)
and other species (F. serratus, Coyer et al., 2003). Thus,
the high gene flow among Bothnian populations of
F. radicans (i.e. Swedish and Finnish) is to some extent
unexpected. Clonality may account for these patterns,
as it could be an alternative strategy for long-distance
dispersal (van der Merwe et al., 2010). Generally in fucoids, whole thalli as well as fragments may well survive
while drifting long distances (Buchanan & Zuccarello,
2012), but only F. radicans – and Baltic Sea F. vesiculosus
to a lesser extent – has been reported largely capable of
producing prolifications (adventitious branches) or
small fragments that are able to reattach to the substrate and establish clonal individuals ecologically
equivalent to sexually recruited individuals (Tatarenkov
ª 2013 THE AUTHORS. J. EVOL. BIOL. doi: 10.1111/jeb.12170
JOURNAL OF EVOLUTIONARY BIOLOGY ª 2013 EUROPEAN SOCIETY FOR EVOLUTIONARY BIOLOGY
8
R. T. PEREYRA ET AL.
(a)
(b)
(e)
(d)
(c)
(f)
(g)
Fig. 5 Results from dispersal simulations using ocean circulation biophysical modelling. Dispersal of algal fragments is depicted in colours
in a relative scale of probability, where probability of dispersal and connectivity is illustrated with coloured dots from highest to lowest
probability as follows: Brown–orange–yellow–green–light blue–navy blue–purple–pink. Localities used for simulated release of algal
fragments are the same as the sampled localities in the following order:
(a) Swe1, (b) Swe2, (c) Swe3, (d) Fin, (e) Est1, (f) Est2, (g) Est3.
et al., 2005). Therefore, as clonality increases, the
potential for successful establishment following longdistance dispersal is also expected to increase. Our
results support this hypothesis by showing high incidence of clonality in Swedish and Finnish F. radicans
populations (89% and 94%, respectively), whereas in
Estonian F. radicans, there is no clonal reproduction
and the gene flow is restricted. Furthermore, previous
findings have shown individual clones extensively distributed and relatively common in Bothnian coasts of
Finland and Sweden (Johannesson et al., 2011) suggesting that indeed clonality may promote gene flow linked
to long-distance dispersal.
In the light of this, the limited gene flow from Bothnian to Estonian populations may seem puzzling. However, our oceanographic simulations show that the
circulation patterns in the northern Baltic promote
gene flow within the Bothnian Sea, but opposed currents from the Baltic Proper generate a strong barrier
that restricts dispersal from and towards Estonia. Hence,
the oceanographic conditions raise natural physical
boundaries that largely prevent gene flow between the
Gulf of Riga (Estonia) and the northern Baltic Sea, the
Gulf of Bothnia. These conditions include the topography that divides the water body into a series of basins
separated by shallow areas that combined with winds
and freshwater inflow produce general patterns of
water circulation and a marked permanent salinity
stratification that divide the mentioned regions
(Kullenberg & Jacobsen, 1981; Zill
en et al., 2008). Thus,
the incidence of clonality and hydrographical dynamics
are key factors to explain the connectivity among Baltic
Fucus populations.
Still unclear, however, is the closer relationship
between Estonian F. vesiculosus and F. radicans than to
any other population from their own taxon. These patterns may be explained by the occurrence of two
(or more) independent events of divergence of F. radicans from F. vesiculosus (‘parallel speciation’) in different
geographical regions. Schluter & Nagel (1995) proposed
three main criteria for parallel speciation: (1) related
lineages in new descendant populations in similar environments must be phylogenetically independent; (2)
descendant populations must be reproductively isolated
from ancestral populations; and (3) descendant populations in similar environments must not be reproductively isolated from one another. They add that an
adaptive mechanism must be identified to establish that
natural selection is the cause of parallel evolution.
Given the recent origin of F. radicans (2500 years ago),
this hypothesis requires the assumption that the
selective forces acted independently and fast enough in
different places to cause the rapid parallel divergence
and evolution of reproductive isolation. Similar postglacial systems such as the sticklebacks have evolved
different ‘ecotypes’ in parallel, and the reproductive isolation driven by selection has evolved quickly in parallel as well in independent populations within similar
ª 2013 THE AUTHORS. J. EVOL. BIOL. doi: 10.1111/jeb.12170
JOURNAL OF EVOLUTIONARY BIOLOGY ª 2013 EUROPEAN SOCIETY FOR EVOLUTIONARY BIOLOGY
Parallel speciation in Fucus?
environments (McKinnon & Rundle, 2002). In our case
study, our NJ tree shows that F. radicans has diverged
independently in two lineages within the Baltic Sea.
Further, there are two pieces of evidence for isolation
between F. radicans and F. vesiculosus. First, in all three
geographical regions examined, it is clear from the
genetic data that there is currently very limited or no
gene flow between F. vesiculosus and F. radicans. Second, Estonian F. radicans and F. vesiculosus show reproductive asynchrony, F. radicans reproducing later than
F. vesiculosus (Forslund & Kautsky, 2013). However, the
compatibility among F. radicans populations from different regions and the adaptive mechanism producing the
F. radicans divergence are yet to be confirmed. In addition, the possibility that a similar phylogenetic pattern
may have been produced by secondary contact cannot
be ruled out at this moment. However, this seems unlikely, as the presence of hybrids would be expected
under such scenario. The sticklebacks show differences
(ecological, morphological and/or genetic) although
inhabiting clearly different spatial and ecological environments within the same geographical space. In contrast, F. vesiculosus and F. radicans share the same
ecological environment and depth distribution by living
side by side in sympatry, but still show genetic, morphological and physiological differences (Lago-Lest
on
et al., 2010; Gylle et al., 2011), and the factors behind
some of these differences remain unknown.
An alternative explanation for the seemingly parallel
pattern observed arises from one major feature identified by our gene flow network analysis map showing
that the Estonian populations have been genetic sources
for both species in Sweden and F. radicans in Finland.
This suggests that Estonia (or in any case, the southeastern Baltic Sea) is the geographical origin of both
species within the Baltic Sea. This is corroborated by the
geological history of the Baltic Sea showing that the
southern part was the first colonized by marine species
6500 years ago after the last glaciation (Bj€
orck, 1995),
and analyses of sediment cores suggest that this colonization followed a coastal pathway along the southeastern region (Gdansk sub-basin, Poland) (Zill
en et al.,
2008). Hence, F. vesiculosus from the North Sea may
have colonized Estonia before the Bothnian Sea sometime between 4000 and 6500 years ago when the surface water of the Baltic was at least 7–8 psu more saline
than at present (Zillen et al., 2008) and major marine
colonizations occurred (Andren et al., 2000). As salinity
levels dropped ~4000 years ago, F. vesiculosus inside the
Baltic may have evolved asexual reproduction as an
alternative to gamete production following reduced
gamete performance and egg polyspermy at low salinities (Serr~ao et al., 1996, 1999). After the divergence of
F. radicans approximately 2500 years ago (Pereyra et al.,
2009), different waves of few genetically distinct colonizers from both recently diverged entities may have
established in Finland and Sweden giving shape to the
9
present-day genetic structure and diversity distribution.
Under this evolutionary scenario, differences by genetic
drift between species and among localities are still
expected largely due to allele frequency distributions
and not due to private alleles, as observed in the present
study (Table S1). Nonetheless, this hypothesis remains
to be tested with phylogeographical studies to corroborate the population divergences with historical events.
In summary, we investigated the mechanisms behind
the repeated sympatric distribution of F. vesiculosus and
F. radicans in different geographical regions in the Baltic
Sea. We showed that populations with high clonality
increase their ability for long-distance dispersal and
show continuous gene flow, potentially enhanced by
ocean circulation patterns. In contrast, highly sexual
populations appear locally restricted by zygotes’ low
dispersal and by strong physical barriers produced by
the ocean current system. Finally, the population
genetic affinities within and between species and their
sympatric reproductive isolation strongly suggest that
their repeated sympatric distribution may be the result
of parallel speciation but the reproductive compatibility
among independent parallel populations remains to be
confirmed.
Acknowledgments
We thank L. Bergstr€
om for providing samples,
B. J€
onsson for assistance in the laboratory, J. Perus for
€s for assistance
assistance in the field and Kristofer D€
oo
with trajectory modelling. Our research was performed
within the Linnaeus Centre for Marine Evolutionary
Biology at the University of Gothenburg (http://www.
cemeb.science.gu.se), financially supported by a Linnaeus grant from the Swedish Research Councils VR and
Formas and by the European Community’s Seventh
Framework Programme (FP/2007-2013) under grant
agreement no. 217246 made with the joint Baltic Sea
research and development programme BONUS, within
the BALTGENE project (http://www.tmbl.gu.se/BaltGene/index.html). PRJ was supported by the Swedish
Research Councils VR and Formas.
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Supporting information
Additional Supporting Information may be found in the
online version of this article:
Figure S1 Delta k in Swe1. Most likely number of clusters in Swe1 determined by Δk.
Figure S2 Overall genetic differentiation between Fucus
species in the Baltic Sea.
Figure S3 Delta k overall populations.
Figure S4 Simulated seasonal variability of dispersal
with ocean circulation biophysical modelling.
Table S1 Populations allele frequencies.
Data deposited at Dryad: doi: 10.5061/dryad.v17q6
Received 29 November 2011; revised 4 March 2013; accepted
28 March 2013
ª 2013 THE AUTHORS. J. EVOL. BIOL. doi: 10.1111/jeb.12170
JOURNAL OF EVOLUTIONARY BIOLOGY ª 2013 EUROPEAN SOCIETY FOR EVOLUTIONARY BIOLOGY