Understanding the population structure and patterns of gene flow within species is of fundamental importance to the study of evolution. In the fields of population and evolutionary genetics, measures of genetic differentiation are commonly used to gather this information. One potential caveat is that these measures assume gene flow to be symmetric. However, asymmetric gene flow is common in nature, especially in systems driven by physical processes such as wind or water currents. As information about levels of asymmetric gene flow among populations is essential for the correct interpretation of the distribution of contemporary genetic diversity within species, this should not be overlooked. To obtain information on asymmetric migration patterns from genetic data, complex models based on maximum‐likelihood or Bayesian approaches generally need to be employed, often at great computational cost. Here, a new simpler and more efficient approach for understanding gene flow patterns is presented. This approach allows the estimation of directional components of genetic divergence between pairs of populations at low computational effort, using any of the classical or modern measures of genetic differentiation. These directional measures of genetic differentiation can further be used to calculate directional relative migration and to detect asymmetries in gene flow patterns. This can be done in a user‐friendly web application called divMigrate‐online introduced in this study. Using simulated data sets with known gene flow regimes, we demonstrate that the method is capable of resolving complex migration patterns under a range of study designs.

Drivers of population genetic structure are still poorly understood in marine micro-organisms. We exploited the North Sea–Baltic Sea transition for investigating the seascape genetics of a marine diatom, Skeletonema marinoi. Eight polymorphic microsatellite loci were analysed in 354 individuals from ten locations to analyse population structure of the species along a 1500-km-long salinity gradient ranging from 3 to 30 psu. To test for salinity adaptation, salinity reaction norms were determined for sets of strains originating from three different salinity regimes of the gradient. Modelled oceanographic connectivity was compared to directional relative migration by correlation analyses to examine oceanographic drivers. Population genetic analyses showed distinct genetic divergence of a low-salinity Baltic Sea population and a high-salinity North Sea population, coinciding with the most evident physical dispersal barrier in the area, the Danish Straits. Baltic Sea populations displayed reduced genetic diversity compared to North Sea populations. Growth optima of low salinity isolates were significantly lower than those of strains from higher native salinities, indicating local salinity adaptation. Although the North Sea–Baltic Sea transition was identified as a barrier to gene flow, migration between Baltic Sea and North Sea populations occurred. However, the presence of differentiated neutral markers on each side of the transition zone suggests that migrants are maladapted. It is concluded that local salinity adaptation, supported by oceanographic connectivity patterns creating an asymmetric migration pattern between the Baltic Sea and the North Sea, determines genetic differentiation patterns in the transition zone.

Local biodiversity trends over time are likely to be decoupled from global trends, as local processes may compensate or counteract global change. We analyze 161 long-term biological time series (15-91 years) collected across Europe, using a comprehensive dataset comprising 6,200 marine, freshwater and terrestrial taxa. We test whether (i) local long-term biodiversity trends are consistent among biogeoregions, realms and taxonomic groups, and (ii) changes in biodiversity correlate with regional climate and local conditions. Our results reveal that local trends of abundance, richness and diversity differ among biogeoregions, realms and taxonomic groups, demonstrating that biodiversity changes at local scale are often complex and cannot be easily generalized. However, we find increases in richness and abundance with increasing temperature and naturalness as well as a clear spatial pattern in changes in community composition (i.e. temporal taxonomic turnover) in most biogeoregions of Northern and Eastern Europe.

Aim To test if a phytoplankton bloom is panmictic, or whether geographical and environmental factors cause spatial and temporal genetic structure.Location Baltic Sea.Method During four cruises, we isolated clonal strains of the diatom Skeletonema marinoi from 9 to 10 stations along a 1132 km transect and analysed the genetic structure using eight microsatellites. Using F-statistics and Bayesian clustering analysis we determined if samples were significantly differentiated. A seascape approach was applied to examine correlations between gene flow and oceanographic connectivity, and combined partial Mantel test and RDA based variation partitioning to investigate associations with environmental gradients. ResultsThe bloom was initiated during the second half of March in the southern and the northern-parts of the transect, and later propagated offshore. By mid-April the bloom declined in the south, whereas high phytoplankton biomass was recorded northward. We found two significantly differentiated populations along the transect. Genotypes were significantly isolated by distance and by the southnorth salinity gradient, which illustrated that the effects of distance and environment were confounded. The gene flow among the sampled stations was significantly correlated with oceanographic connectivity. The depletion of silica during the progression of the bloom was related to a temporal population genetic shift.Main conclusions A phytoplankton bloom may propagate as a continuous cascade and yet be genetically structured over both spatial and temporal scales. The Baltic Sea spring bloom displayed strong spatial structure driven by oceanographic connectivity and geographical distance, which was enhanced by the pronounced salinity gradient. Temporal transition of conditions important for growth may induce genetic shifts and different phenotypic strategies, which serve to maintain the bloom over longer periods.

A global trend of a warming climate may seriously affect species dependent on sea ice. We investigated the impact of climate on the Baltic ringed seals (Phoca hispida botnica), using historical and future climatological time series. Availability of suitable breeding ice is known to affect pup survival. We used detailed information on how winter temperatures affect the extent of breeding ice and a climatological model (RCA3) to project the expected effects on the Baltic ringed seal population. The population comprises of three sub-populations, and our simulations suggest that all of them will experience severely hampered growth rates during the coming 90 years. The projected 30 730 seals at the end of the twenty-first century constitutes only 16 % of the historical population size, and thus reduced ice cover alone will severely limit their growth rate. This adds burden to a species already haunted by other anthropogenic impacts.