Discussion
We report on the first investigation of population genetic diversity and
structure among all three spawning ecotypes of pike (freshwater,
anadromous and brackish water resident) using information based on both
neutral and adaptive molecular markers (RADseq SNPs). We document
patterns of genetic structure at different spatial scales and identify
the eco-evolutionary drivers of the genetic differentiation among and
within ecotypes. Besides providing rare evidence of contrasting patterns
of neutral and adaptive genetic structure, results exemplify how
separate analyses of coding and non-coding variation can help
disentangle the complex interplay of different stochastic and
deterministic contributing processes. Specifically, we found that for
neutral differentiation allopatry seems to play an important role. For
the sympatric Baltic Sea populations, IBD did not explain the genetic
structure. Results instead pointed to effects of ecotype (IBE) and
spatial sorting (Berggren, Tinnert, &
Forsman, 2012; Shine, Brown, & Phillips,
2011), and indicated that IBT might also influence the neutral genetic
structure in pike. For adaptive differentiation, temperature and
salinity appear to be two key environmental factors driving local
adaptations (IBA). Below, we discuss our findings in relation to
previous studies and predictions from theory, and their implications for
management.
Within population
diversity
Observed within population heterozygosity (HO )
for the full dataset (0.17 - 0.28, Table 1 ) were considerably
lower than reported in previous microsatellite studies of Baltic Sea
pike (0.22 - 0.66; Bekkevold et al., 2015;
Nordahl et al., 2019;
Sunde et al., 2020a;
Wennerström et al., 2016). This may in
part reflect the use of different markers. This interpretation is
supported by the results from the study by
Sunde et al. (2020a), in which both
microsatellites and RADseq were utilized to study genetic diversity and
structure of three pike populations (that are also included in the
present study). The results revealed similar estimates of SNP
heterozygosity as in the present study, and microsatellite
heterozygosity estimates that are comparable to those obtained in the
other studies utilizing microsatellites (0.40 - 0.57). Regardless of
marker type, both the present (Table 1 ) and previous studies
show that within-study estimates of HO andHE are similar, which indicates that the
populations do not interbreed to a large extent (indicated byHO > HE ), and
do not show any clear signs of inbreeding (indicated byHO < HE ).
Diversity is imperative for eco-evolutionary success. Theory and
empirical evidence concur that larger genetic and phenotypic variation
among individuals within populations may promote establishment success,
stabilize population dynamics, allow for faster range expansions, and
reduce extinction risk (Des Roches et al.,
2018; Forsman, 2014;
Forsman & Wennersten, 2016;
Hughes, Inouye, Johnson, Underwood, &
Vellend, 2008; Waldman, Wilson, Mather,
& Snyder, 2016). Our present estimates do not indicate any clear
differences in intrapopulation diversity among the ecotypes, neither for
estimates based on the full nor on the adaptive dataset (Table
1 ). However, within ecotypes, some populations seem to harbor larger
genetic diversity than others, which might reflect more heterogeneous
environments or result from a higher degree of gene flow. Yet, these
conclusions must be tentative because of the relatively low number of
adaptive loci and the unbalanced sampling design, with varying numbers
of populations representing the three ecotypes.
Allopatric freshwater populations were strongly neutrally
differentiated
We found that all populations were significantly differentiated (based
on FST ; Figure 2 ), which is consistent
with previous studies (Bekkevold et al.,
2015; Larsson et al., 2015;
Möller et al., 2020;
Nordahl et al., 2019;
Sunde et al., 2020a;
Wennerström et al., 2016). Levels of
pairwise population differentiation ranged from low to high
(FST 0.06 - 0.25), and the highest levels of
differentiation were found in the comparisons including either the
anadromous population Harfjärden, or at least one freshwater lake
population (Figure 2 ). This, together with the finding that all
three freshwater populations were strongly differentiated from each
other, and distinct from the other two ecotypes point to an important
effect of allopatry.
It has been suggested that pike experienced drastic population declines
and/or bottlenecks following postglacial recolonization across the
Northern Hemisphere (Jacobsen, Hansen, &
Loeschcke, 2004), and that the succeeding isolation of local river and
lake systems might have resulted in genetic drift and differentiation
among freshwater populations (Bekkevold et
al., 2015). Along this line of argument, the substantial
differentiation among the freshwater populations likely reflects the
combined effects of founder events, genetic drift, low gene flow, more
distinct reproductive isolation, divergent selection, and longer time
since divergence (because the freshwater ecotype is the original
ecotype).
Sympatric Baltic Sea populations were also
differentiated
Estimates of population differentiation in Baltic Sea pike differ
markedly among studies. Notably, studies on smaller spatial scales
report higher levels of differentiation
(0.026 - 0.394 in Bekkevold et al., 2015;
0.013 - 0.396 in Nordahl et al., 2019)
than those conducted on large spatial scales
(0.005 - 0.135 in Laikre et al., 2005;
and -0.003 - 0.14 in Wennerström et al.,
2016). The values in the present study are relatively high compared to
the other large-scale studies (0.06 - 0.22). While it is possible that
the use of different markers influence the estimates ofFST , Sunde et al.
(2020a) arrived at similar FST -values for
microsatellites and RADseq SNPs, indicating consistency across the
markers. So far, few attempts have been made to compare the resolution
yielded by various genetic markers, and little is therefore known about
whether the use of different marker types contributes to heterogeneity
of results among studies of other organisms
(Sunde et al., 2020a).
Accurate estimation of genetic differentiation requires correct
population assignments of individuals. In our study system, where
individuals only separate during spawning, sampling during foraging
season entail the risk of erroneously grouping individuals from several
populations, which results in underestimations of differentiation. In
the present study, the anadromous individuals were therefore sampled in
their freshwater spawning habitats to assure accurate population
assignment. Previous studies differ in their sampling regimes/designs,
which might have affected differentiation estimates, and complicates
comparisons among studies. That we found stronger population
differentiation than reported before for large-scale studies of Baltic
Sea pike nevertheless indicates that the populations are more isolated
than previously believed. This can have implications for management, as
it indicates that each population should be considered as a separate
unit. The importance of sampling scheme and associated implications for
interpretation of result pertaining to population structure potentially
extend also to other migrating species
(such as whitefish Coregonus maraena,
Olsson, Florin, Mo, Aho, & Ryman, 2012;
and perch Perca fluviatilis, Olsson, Mo,
Florin, Aho, & Ryman, 2011), but to our knowledge this issue has not
been systematically evaluated.
The analyses of genetic structure based on the full dataset showed signs
of genetic clustering for the anadromous ecotype (Figure 1 and
S4-S5 ), which is indicative of gene flow and/or recent divergence. All
populations that were assigned to the shared ’anadromous genetic
cluster’ spawn in localities on the Swedish mainland, and even the
population from Ängerån (which resides in the north of the Baltic Sea)
was assigned to this cluster. The two anadromous populations that were
not assigned to the shared cluster (Askeby from Denmark and Harfjärden
from the island of Öland) were the only two anadromous populations not
spawning in localities on the Swedish mainland. Genetic clustering of
populations along the coast have also been reported in previous
large-scale studies of pike (Laikre et
al., 2005; Wennerström et al., 2016).
It has also been shown for pikeperch (Sander lucioperca ) in the
northern part of the Baltic Sea in a study by
Säisä, Salminen, Koljonen, and Ruuhijärvi
(2010), who showed that coastal populations formed one genetic cluster,
whilst freshwater lake populations showed strong genetic differentiation
and formed distinct clusters.
All the anadromous populations were differentiated from each other
(Figure 2 ), and previous studies report low levels of gene flow
among anadromous pike populations (Nordahl
et al., 2019; Sunde et al., 2020a;
Tibblin et al., 2015). It is therefore
unlikely that gene flow is sufficient to explain the clustering of
anadromous populations. Coherent with previous studies based on
mitochondrial DNA from pike across Northern Europe
(Maes, Van Houdt, De Charleroy, &
Volckaert, 2003; Skog, Vøllestad,
Stenseth, Kasumyan, & Jakobsen, 2014), the results from the
phylogenetic analysis revealed low levels of genetic variation and
shallow branching among the populations (Figure. 5 ), which is
indicative of recent divergence. However, the results did not provide
any firm evidence for more recent divergence among the mainland
populations. The use of more dense SNP data or longer reads might allow
for the detection of clearer phylogenetic signals and higher resolution
(Cariou, Duret, & Charlat, 2013).
That the anadromous populations from Öland and Denmark were distinct
from the other anadromous populations may reflect different evolutionary
histories, and a combination of founder events followed by divergent
selection and stochastic processes. That the populations inhabiting the
East Coast of Öland show strong differentiation from the mainland
populations in the Kalmar sound region has been reported previously
(Nordahl et al., 2019), and it has been
suggested to result from the open water between the Sweish mainland and
the island acting as a reproductive barrier. Similarly, the open water
between Denmark and Sweden may constitute a reproductive barrier that
has facilitated differentiation. In addition, previous work has shown
that the population from Öland and one of the mainland anadromous
populations experience different environmental conditions during
spawning, and that this has resulted in the evolution of local
adaptations during early fry development
(temperature, Sunde et al., 2019;
salinity, Sunde et al., 2018). It is
therefore possible that the high level of differentiation partly
reflects IBE/IBA, in addition to geographic separation. The population
on Öland generally spawns earlier than the mainland populations
(Sunde et al., 2019), and it is possible
that IBT also has contributed to the genetic differentiation among
anadromous pike populations reproducing in localities on the mainland
and the island of Öland. To the extent that the timing of spawning
migration is heritable (Tibblin et al. 2016), differences in timing of
reproduction among populations may impair the success of individuals
that attempt to spawn in a population different from where they were
born, and thereby reduce gene flow. An alternative explanation is that
this pattern reflects multiple evolutionary origins of anadromy.
Skog et al. (2014) suggest that there are
two clades of pike in the Baltic Sea, and it is possible that anadromy
has evolved independently within the clades, but our present results do
not provide conclusive evidence.
Taken togehter, more recent divergence of the anadromous mainland
populations, different evolutionary histories, or multiple evolutionary
origins all remain plausible explanations for the observed structure and
differentiation, but we are unable to discriminate among them based on
existing data. Future studies that include data for additional resident,
anadromous and freshwater populations from other regions around the
Baltic Sea are required to formally evaluate the competing hypotheses.
That the two Denmark populations (Stege Nor and Askeby) clustered
together, despite belonging to different ecotypes, suggests that, in
addition to ecotype, geography influence the genetic structure. Unlike
previous large-scale studies of pike
(Laikre et al., 2005;
Wennerström et al., 2016), we found no
evidence of IBD. This lack of IBD is perhaps partly explained by the
long geographic distances between many of the populations. Patterns of
IBD are more pronounced for more closely located populations, and
gradually disappear with increasing geographic separation
(Hutchison & Templeton, 1999;
Meirmans, 2012;
Tinnert, Hellgren, Lindberg,
Koch-Schmidt, & Forsman, 2016; van
Strien, Holderegger, & Van Heck, 2015). Consistent with this notion,
the results from fastSTRUCTURE showed some signs of gene flow between
the more closely located populations (Figure 1 ). It is
therefore likely that IBD is of importance for local genetic
structuring, but that other processes such as selection and drift have
stronger effects on large scales.
The db-RDA for the full dataset indicated that both ecotype and latitude
influence neutral genetic structuring. Results further indicate that
whereas ecotype might be one of the main factors influencing neutral
genetic structure, latitude appear to explain variation among
populations within the anadromous ecotype.
Taken together, the findings reported in the present and previous
studies suggest that the patterns of genetic structure observed in
Baltic Sea pike have been shaped by an interplay between geography and
divergent selection associated with the environments occupied by the
different ecotypes (i.e., combined contributions of IBD, IBE, IBA, and
IBT), as discussed below.
Adaptive genetic variation and
structure
When the adaptive dataset (comprising outlier loci) was analysed, some
contrasting patterns of structuring emerged. The clustering of the
anadromous mainland populations that was evident for the neutral dataset
was not present in the adaptive dataset (Figure 1 ). Instead, a
main pattern of structuring associated with latitude appeared. The
importance of latitude on adaptive differentiation was also evidenced by
the db-RDA, which revealed a direction of separation associated with
latitude that corresponded relatively well with the CAP1 axis
(Figure 3b ). The effect of latitude appeared to be especially
important within the anadromous ecotype, which was indicated by the
direction of separation associated with latitude aligning with the
separation among the anadromous individuals. This likely reflects that
the anadromous populations included in this study covered a latitudinal
range along the environmental clines in the Baltic Sea.
The significant interaction effect between midrange salinity and
latitude indicates that the importance of these two factors differs
according to the level of structuring, and further shows that salinity
alone does not explain the patterns. Instead, selection associated with
multiple environmental factors that co-vary with latitude (e.g.temperature and salinity) probably contributes to adaptive genetic
structure. This is in agreement with previous findings that salinity and
temperature regimes have resulted in locally adapted populations
(Sunde et al., 2019;
Sunde et al., 2018). Previous studies
have also reported on evolution associated with salinity tolerance in
other fish species in the Baltic Sea, including three-spined stickleback
(Guo et al., 2015;
Hasan et al., 2017), European flounder
(Momigliano et al., 2017), and Atlantic
herring (Berg, Slotte, Andersson, &
Folkvord, 2019; Lamichhaney et al.,
2012), emphasizing the general importance of salinity.
The role of environmental conditions in shaping adaptive structure was
further supported by the finding that two of the freshwater populations
(Kosta and Hamnaryd) that showed strong neutral differentiation shared
an adaptive genetic cluster (Figure 1 ). This suggests that,
despite being geographically and reproductively separated, similarities
in environmental conditions between these two freshwater lakes have
resulted in adaptive similarity via convergent evolution. The
contribution of convergent evolution was further supported by the
finding that the db-RDA based on the adaptive dataset showed
considerably more overlap between populations (including the two
freshwater populations sharing a genetic cluster in fastSTRUCTURE) and
ecotypes compared to analysis of the full dataset (Figure 3 ).
The conclusion that environmental conditions, and in particular
salinity, influence genetic structure was corroborated by the the
outlier analyses (Table 2 and 3 ). The results specifically
revealed that outliers residing in genes that have been suggested to be
associated with salinity tolerance were identified in both analyses.The
remainder of the SNPs might reside in genes that have not yet been
identified in the pike genome, but it is also possible that these are
non-coding loci linked to regions under selection.
Implications for
management
Biodiversity is under threat worldwide by natural and anthropogenic
environmental makeovers, climate change, and overexploitation. The level
of genetic diversity within and among populations can influence the
eco-evolutionary success of species, as well as the functioning of
ecosystems, and this must inform management and protection of fish and
the ecosystem services they provide. Genetic and phenotypic variation is
required for populations to respond to selection and adapt to changing
and novel environmental conditions
(Charlesworth & Charlesworth, 2017;
Roff, 1997;
Wennersten & Forsman, 2012). There is
also potential for the consequences of genetic variation to go beyond
the level of the species, as it can influence community structure and
ecosystem functioning (Des Roches et al.,
2018; Hughes et al., 2008). Being
important predators, competitors, and prey to other species, there are
many ways by which pike and other species of fish can affect the
functioning of lakes, rivers, coastal ecosystems and open oceans
(Brodersen, Howeth, & Post, 2015;
Donadi et al., 2017;
Nilsson et al., 2019;
Post, Palkovacs, Schielke, & Dodson,
2008; Tamario, Sunde, Petersson,
Tibblin, & Forsman, 2019). There are thus several reasons as to why
the genetic diversity among and within ecotypes of pike reported in this
and previous studies must not be depleted.
A key challenge for conservation is to design management actions that
maintain functional genetic and phenotypic diversity both within and
among populations (Hutchinson, 2008;
Larsson et al., 2015;
Nordahl et al., 2019;
Stephenson, 1999;
Tamario et al., 2019;
Wright, Bishop, Matthee, & von der
Heyden, 2015). The rates and directions of genetic exchange between
populations may be a natural outcome of dispersal or result from
management actions, such as removal of migration barriers, compensatory
breeding, supplementary stocking, (re-)introductions, and translocations
(Gjedrem, Gjøen, & Gjerde, 1991;
McClelland & Naish, 2007;
McGinnity et al., 2009;
Seddon, Armstrong, & Maloney, 2007).
While genetic diversity is beneficial, restoration efforts may not
always generate the desirable outcome
(McClelland & Naish, 2007;
Verhoeven, Macel, Wolfe, & Biere, 2011;
Whitlock et al., 2013). Our finding in
the present study that patterns of neutral and adaptive genetic
diversity differed, which has also been reported in previous studies
(Leinonen, O’Hara, Cano, & Merilä, 2008;
Reed & Frankham, 2001), indicates that
neutral variation is not necessarily reflective of adaptive variation.
Given that it is adaptive, not neutral, variation that determines the
evolvability of populations and influences their capability of coping
with changed environmental conditions, this emphasizes the importance
for management to base descisions on analyses of adaptive genetic
diversity.