Two general conclusions emerge from our comparison of Baltic–Atlantic population genetic structures over a wide range of taxa: (i) Baltic populations have generally lower genetic diversity than Atlantic populations, and (ii) a majority of taxa studied show strong differentiation over the Baltic–North Sea border. Moreover, the low diversity of Baltic populations is unrelated to taxonomic group, generation time and capacity of dispersal, while strongly related to type of genetic marker. Although extensive work would be needed to identify the specific mechanisms generating the observed patterns in each species, we discuss below some likely processes. We also review studies of some species for which more comprehensive work has been undertaken to explain Baltic–Atlantic population genetic structures.
Loss of diversity through genetic drift
Baltic Sea populations had in general less genetic diversity than North Sea/Atlantic populations. Assuming that the North Sea–Atlantic populations owing to the relative stability gained by large sizes have not increased their genetic diversity over the 8000 years since the opening of the Baltic Sea, the observed lower diversity of Baltic Sea populations must be explained by a loss of genetic variation in Baltic populations, before, during, or after the colonization. If lost before the Baltic Sea was invaded, the populations must have been separated from the Atlantic populations already at an earlier stage, which indeed is a likely scenario for some of the species (see below).
For populations that lost genetic variation during or after their establishment in the Baltic Sea, two observations suggest that genetic drift played a primary role. Primarily, populations have lost substantially more genetic diversity at mitochondrial genes compared to nuclear genes. As the effective population size of uniparentally inherited loci is only one-fourth that of nuclear loci (Ne), random loss of diversity should be correspondingly higher (4×) in mtDNA genes than in, for example, microsatellite and allozyme genes (Avise 1994). Indeed, we found the average loss of diversity at nuclear loci to be 11% (allozymes) and 12% (microsatellites) while at mitochondrial loci 50% was lost, which is almost exactly the relationship predicted by theory. Second, loss of diversity was at similar levels in coding (allozyme) and noncoding (microsatellite) loci. Variation in the coding allozyme loci would potentially be affected by natural selection, while the noncoding microsatellite loci would presumably not be affected. Thus, no difference in loss of diversity between these markers suggests that selection is not an important mechanism explaining loss of molecular genetic variation in Baltic Sea populations.
As drift eliminates variation per generation, populations with short generation times are expected to lose more diversity than long-lived organisms per unit time (Fig. 6). We did not find support for such a pattern, however, possibly because species with short generation time also tend to have larger effective population sizes, Ne (e.g. invertebrates and annual algae).
Figure 6. Expected losses of gene diversity (HE) in populations isolated over 8000 years, and unaffected by mutation and migration. Losses of mtDNA and nuclear DNA diversity are calculated for various magnitudes of effective population sizes (Ne), for species with short generation time (1 year, nonoverlapping generations) and long generation time (5 years, nonoverlapping generations). Observed levels of gene diversity loss in Baltic populations (50% in mtDNA and 10% in nuclear DNA; Table 2) are indicated to show mean effective population sizes that will generate losses of these magnitudes.
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Another prediction is that species with high dispersal capacity should lose less diversity owing to larger effective population sizes, but again we found no support for this expectation (Table 2). Perhaps this is explained by subdivision of populations of poor dispersing species into semi-isolated subpopulations may in fact increase Ne, and thereby promote maintenance of genetic variation (Nunney & Campbell 1993). Moreover, we used type of reproductive strategy as the criterion to characterize species as having poor or good dispersal, but strategy (planktonic vs. nonplanktonic) might not be a good enough estimator of gene flow (Knutsen et al. 2003; Colson & Hughes 2004). Indeed, species with a low dispersal potential did not show stronger isolation-by-distance effects than species with high dispersal capacity (Table 3).
With two exceptions (the barnacle Balanus improvisus and the bivalve Mya arenaria), all species included in the analyses have an early history of colonization in the Baltic, most probably dating back to the Littorina period (8000–4000 bp). Baltic populations may have lost genetic diversity compared to Atlantic populations due to varying degrees of isolation over 8000 years and relatively small population sizes, and occasional population bottlenecks. We calculated stochastic losses of haplotype (mtDNA) and allele (nuclear DNA) diversity in populations of various sizes assuming complete isolation and no new mutations during 8000 years (Fig. 6). The rate of loss under these circumstances is proportional to the effective population size (Ne) and the number of generations elapsed (T):
Our observations showed that on average, Baltic populations had lost about 50% of Atlantic diversity in mtDNA loci (Table 2). Bringing this value into the theoretical relationship (Fig. 6) this corresponds to a mean effective size (Ne) of around 11 000 in a species with a short life cycle (1 year, nonoverlapping generations), and 5000 in a species with a long life cycle (5 years, nonoverlapping generations). For nuclear loci, the average loss was 11–12% (Table 2) corresponding to a mean effective size of 13 000 in ‘annual’ and 7000 in ‘multiyear’ species (Fig. 6). Effective population sizes (Ne) are probably magnitudes smaller than census sizes (N) of adult populations (Turner et al. 2002), and thus our calculations fits well with a scenario of genetic drift as a contributor to diversity loss in Baltic Sea populations that have been at least partly isolated since established. Occasional bottlenecks might have contributed to further reduction of the genetic variation (Chakraborty & Nei 1977), while intermittent periods of more effective genetic exchange with Atlantic populations would have opposed this by re-introducing Atlantic genes.
Data for Baltic Sea harbour seals (Phoca vitulina) support a scenario of diversity loss due to genetic drift and repeated bottlenecks (Härkönen et al. 2005). Baltic population sizes have been estimated from archaeological and hunting data since the seals were established in the Baltic Sea 8000 years ago. Moreover, historic data show that harbour seals were absent in the Kattegat and Skagerrak during most of the period 8000–200 bp, and thus the Baltic Sea population has been effectively isolated from Atlantic populations. Effective population size was inferred from behavioural studies (Härkönen et al. 2005), and estimated population sizes (including a recent population bottleneck) explain well the 20% loss of genetic diversity observed in microsatellite loci of the Baltic Sea population (Goodman 1998; Härkönen et al. 2005).
An example of a recently introduced species, the small planktonic crustacean Cercopagis pengoi, show that founding a new Baltic Sea population might involve severe population bottlenecks that substantially reduce genetic diversity. This species was unintentionally introduced to the Baltic Sea in 1992 from the Black Sea/Caspian Sea. Of seven mtDNA haplotypes present in the ancestral populations, only one is found in the Baltic Sea population (Cristescu et al. 2001).
Overall, genetic drift clearly seems the most important process eliminating genetic diversity in isolated and size-restricted Baltic Sea populations. Despite this, life-history characteristics, such as dispersal potential, generation time and taxonomic group seems marginally, if at all, important.
Loss of diversity through asexual reproduction
Increased frequency of asexual reproduction further reduces genetic variation. Noticeably, among facultative asexual species, populations living in marginal environments tend to reproduce asexually to a higher degree than central populations (Eckert 2002; Billingham et al. 2003; Kearney 2003) In the Baltic Sea, a number of plant and algal species reproduce asexually more frequently than elsewhere (Hällefors et al. 1981; Malm et al. 2001). Serrão et al. (1996, 1999) argue convincingly that it is the harsh brackish-water conditions that restrain sexual reproduction. Several species included in the present study show evidence of increased clonality inside the Baltic Sea. Zostera marina populations close to Åland (Fig. 1), at the border of the species’ distribution, for example, consist of 95% clonal plants, as compared to near zero clonality in the North Sea (Reusch et al. 2000). In Fucus vesiculosus, the northernmost population (Öregrund, close to Åland) has 30% cloned individuals: a unique finding since nowhere outside the Baltic Sea clonal reproduction of new attached plants has been found in this species (Tatarenkov et al. 2005). Also, the new species Fucus radicans so far only found in the northernmost part of the Baltic Sea (at salinities < 6) has populations with 80% asexually reproducing plants (Bergström et al. 2005; Tatarenkov et al. 2005). Baltic populations of the red alga Ceramium tenuicorne are dominated by individuals that reproduce vegetatively, while in the Skagerrak reproduction is to a large extent (> 95%) sexual (Gabrielsen et al. 2002; Bergström et al. 2003). Both Z. marina and F. vesiculosus show significantly less genetic diversity in Baltic populations compared to North Sea populations (Table 2), and in C. tenuicorne there is a tendency for loss of genetic diversity as estimated from the number of RAPD bands (P = 0.11).
Processes generating Atlantic–Baltic Sea differentiation
About half of the 20 species analysed showed a steepened genetic cline at or somewhat outside the Baltic Sea entrance. Such clines may form either as a consequence of gradient selection followed by a successively impeded gene flow (primary cline), or where genetically separated lineages of a species meet and hybridize (secondary clines) (Coyne & Orr 2004). Primary clines mainly evolve as a consequence of divergent natural selection acting on specific traits in a continuously distributed population (Endler 1977). It is expected that neutral loci will not, in the first place, be affected by divergent selection, but linkage to selected loci or as a consequence of impeded gene flow owing to partial reproductive barriers generated by selection on ecological traits, will result in differentiation also in neutral markers in primary clines (Johannesson 2001; Rolán-Alvarez et al. 2004). Primary clines are likely to be connected to strong environmental gradients (ecotones), being the ultimately cause of the cline (Endler 1977). Secondary clines form when and where evolutionary lineages that have evolved in allopatry come into secondary contact and hybridize. Secondary zones are initially characterized by congruent clines of selected and neutral markers, but neutral clines are expected to fade out over time by gene flow (Futuyma 2005). Both primary and secondary clines might be expected at the entrance of a marginal environment, which is ecologically aberrant and partly isolated.
Primary zones of hybridization
The steep clines in allozyme, haemoglobin and microsatellite loci in cod are likely examples of primary genetic clines over the Baltic-Atlantic transition. These three clines coincide at the Baltic entrance while the mtDNA cline seems less sharp and somewhat shifted towards the North Sea (Fig. 5). There are indications of selection acting directly on part of the allozyme variation, and on the haemoglobin variation (Sick 1965; Mork & Sundnes 1985). In addition, an efficient barrier to gene flow has evolved as a consequence of divergent selection on reproductive traits, such as egg buoyancy, sperm motility (Nissling & Westin 1997) and spawning season; the NE Atlantic cod spawn during winter while the Baltic cod spawn during summer (Wieland et al. 2000). These ecological differences have probably evolved as a consequence of adaptation to different environments, and are likely to act as barriers to gene flow, resulting in accumulated differences also in neutral markers such as microsatellite and mtDNA (Nielsen et al. 2003; Árnason 2004; see Fig. 5).
Herring also reveals a pattern of similar allozyme and microsatellite clines at the Baltic entrance (Fig. 5). As for cod, both congruent clines and the relatively low magnitude of differentiation suggest a primary hybrid zone being formed without a preceding stage of lineage separation.
Secondary zones of hybridization
The Baltic–Atlantic genetic shift of the bivalve species Macoma balthica is a clear-cut example of a secondary cline. The genetic differences between the two seas are very strong in both allozyme and mtDNA loci, and in between are sharp genetic clines (Fig. 5). Earlier studies indicate the presence of two evolutionary lineages, one present in the NE Atlantic and one in the Baltic Sea. The lineages were separated at least 10 million years ago, and have come into secondary contact after extensive isolation (Väinölä & Varvio 1989a; Luttikhuizen et al. 2003; Väinölä 2003). In fact, the central and northern Baltic Macoma balthica populations are more closely related to populations in the White Sea and Alaska than to North Sea populations in both allozyme and mtDNA loci. It is suggested that repeated invasions of this species from the Pacific to the Atlantic, gave rise to two separate lineages (Luttikhuizen et al. 2003; Väinölä 2003). These lineages are still interfertile and hybridize upon secondary contact. For some reasons, the Baltic and White Seas are the only areas in which the most recent invading lineage is found at present.
Similar patterns are seen in the blue mussel, Mytilus edulis, with steep clines in several allozyme loci around the entrance of the Baltic Sea (Väinölä & Hvilsom 1991). Here, again two distinct evolutionary lineages, M. edulis and Mytilus trossulus (Varvio et al. 1988), that separated 3.5 million years ago or earlier (Riginos & Cunningham 2005), are in secondary contact. The two lineages have introgressed heavily, as particularly evident in the structure of mtDNA variation with no uncontaminated individuals of trossulus genotype found even deep inside the Baltic Sea (reviewed by Riginos & Cunningham 2005). Also, nuclear DNA loci show evidence of substantial introgression of edulis alleles into the Baltic Sea (Riginos et al. 2002; Riginos & Cunningham 2005). On the other hand, allozymes of trossulus-type dominate completely inside and edulis-type outside the Baltic Sea. The explanation for the maintenance of these differences is likely differential selection acting directly on the allozyme loci or on loci strongly linked to these (Theisen 1978; Johannesson et al. 1990; Riginos & Cunningham 2005).
It is noteworthy that for both bivalve species, the most recently invading lineage from the Pacific occupies the innermost part of the North Sea–Baltic Sea region. A likely explanation is that these lineages had a much wider northern Atlantic distribution following the last glacial retreat but were outcompeted by older Atlantic lineages that expanded northwards following temperature increase after the last glacial period (Väinölä 2003). However, the Baltic became a blind alley on the route north and a particularly harsh environment for the southern lineages, while the northern lineages here found a refuge, probably by being better adapted to the extreme Baltic environment. Contrastingly, in Nova Scotia the situation is reversed with M. trossulus occupying the more saline open-coast areas and M. edulis the low-saline estuarine areas (Riginos & Cunningham 2005). This suggests that adaptation of M. trossulus to the low-saline Baltic environment is a secondary effect.
A similar scenario of repeated trans-Arctic invasions has been proposed for the red alga Phycodrys rubens (van Oppen et al. 1995), although a more extensive analysis is needed to reconstruct the phylogeography of the two European clades of this species. In contrast, very little DNA sequence differences has been found between Atlantic and Pacific individuals of the seagrass, Zostera marina, suggesting that Atlantic populations might be the result of a recent, or even currently open, trans-Arctic connection to the Pacific Sea (Olsen et al. 2004).
Genetic diversity of marginal marine ecosystems
To our knowledge, no similar study has previously reviewed genetic structures of multiple species inhabiting the same marginal ecosystem. However, there are examples of clinal genetic structures of marine species living in marginal marine environments, typically estuaries, characterized by strong salinity gradients. Most of these examples are bivalve species from the Mytilus group such as M. edulis/M. trossulus, but also M. galloprovincialis and Perna canaliculus show clinal patterns in estuarine habitats in Norway (Ridgway & Nævdal 2004), New Zealand (Gardner & Kathiravetpillai 1997; Gardner & Palmer 1998) and the US East Coast (Koehn et al. 1980). Moreover, estuarine sites in Holland reveal genetic alterations in species such as Macoma balthica (Luttikhuizen et al. 2003) and Littorina littorea (de Wolf et al. 2003). Notably, all these species have broadcasting larvae able to travel hundreds of kilometres between place of birth and place of settlement, and despite this, there are pronounced local-scale genetic structures. These observations corroborate our results from the Baltic Sea and suggest that species characteristics, such as dispersal potential and generation time, have no big impact on the genetic structuring of populations in a marginal habitat. Instead, physical properties of the environment, such as geographic or ecological periphery, is perhaps more important in promoting isolation and genetic perturbation.
Managing Baltic Sea biodiversity
Until recently, species diversity has been the main focus for the conservation of Baltic Sea biodiversity. Laikre et al. (2005), however, reviewed genetic diversity of Baltic Sea fish populations and stressed the importance of including information on genetic variation in stock management. Our review clearly supports this notion and pinpoints the necessity of a wide geographic reference (e.g. Baltic Sea–North Sea). Comparative studies can teach us much about evolutionary processes and phylogeographic relationships by combining genetic data with distributional data (e.g. Bernatchez & Wilson 1998). Moreover, observations of lost genetic diversity and genetic breaks across multiple species will have strong implications for ecosystem management.
The Baltic Sea ecosystem is fragile with much reduced species-richness and thus a low resistance to local extinctions. Here, the genetic dimension will be of particular concern, first because it has implications for ecosystem function (Hughes & Stachowicz 2004; Reusch et al. 2005), and second because genetic isolation of several populations implies restricted exchange of individuals (in this case between North Sea and Baltic Sea populations). Thus, in the event of local extinctions, we cannot expect a rapid recolonization of Baltic Sea areas. Furthermore, owing to different genetic histories, there is a risk that North Sea individuals, if introduced to the Baltic, would be genetically suboptimal and contribute maladaptive genes to surviving fragments of marginal Baltic populations (outbreeding depression, see, e.g. McKay et al. 2005). If, for example, individuals of North Sea cod were introduced into a diminishing Baltic stock, there is a risk that Baltic genotypes giving rise to locally adapted traits, such as summer instead of winter spawning (Wieland et al. 2000) and eggs with neutral buoyancy at lower salinities than elsewhere (Nissling & Westin 1997) would be broken down and important traits eroded.
The best strategy to promote long-term survival of Baltic Sea populations is therefore to protect and sustain local populations. Considering the relationship between census and effective population sizes (Turner et al. 2002), this means that actual population sizes must be orders of magnitude larger than 10 000–50 000 for most populations. It should also be noted that for some species there is not only one but several genetically distinct populations inside the Baltic Sea. This is certainly the case for salmon (Nilsson et al. 2001), herring (Jørgensen et al. 2005), Fucus vesiculosus (Tatarenkov et al. personal communication) and Zostera marina (Olsen et al. 2004), and probably for a range of other species as well. If needed, populations must be restored by individuals from as close as possible populations, and individuals from outside the Baltic Sea avoided.
For some species, the Baltic Sea contains unique lineages, separate from those currently dominating in the Atlantic. For example, the two bivalve species Mytilus edulis and Macoma balthica have established unique evolutionary lineages in the Baltic that are rarely found elsewhere in the NE Atlantic. Indeed, the closest relatives to these Baltic Sea populations are instead found in NE Canada and Alaska. Additionally, a cryptic species of brown alga, Fucus radicans, has recently been discovered in the northern Baltic Sea (Åland and northward), where it is the dominating macro-alga (Bergström et al. 2005; Tatarenkov et al. 2005). This species has hitherto not been found outside the Baltic, and it remains to be established if it is endemic to the Baltic Sea or a remnant Arctic species.
Evidently, a marginal ecosystem such as the Baltic Sea, might thus be of great concern in conservation and management, not only because of populations here being more vulnerable, but also because such an ecosystem might both produce and protect more or less extreme evolutionary lineages. Consequently, far greater focus than today has to be put on the management of intraspecific diversity of species living in marginal ecosystems, such as the Baltic Sea.