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Understanding how dispersal and gene flow link geographically separated the populations over evolutionary history is challenging, particularly in migratory marine species. In southern right whales (SRWs, Eubalaena australis), patterns of genetic diversity are likely influenced by the glacial climate cycle and recent history of whaling. Here we use a dataset of mitochondrial DNA (mtDNA) sequences (n = 1327) and nuclear markers (17 microsatellite loci, n = 222) from major wintering grounds to investigate circumpolar population structure, historical demography and effective population size. Analyses of nuclear genetic variation identify two population clusters that correspond to the South Atlantic and Indo-Pacific ocean basins that have similar effective breeder estimates. In contrast, all wintering grounds show significant differentiation for mtDNA, but no sex-biased dispersal was detected using the microsatellite genotypes. An approximate Bayesian computation (ABC) approach with microsatellite markers compared the scenarios with gene flow through time, or isolation and secondary contact between ocean basins, while modelling declines in abundance linked to whaling. Secondary-contact scenarios yield the highest posterior probabilities, implying that populations in different ocean basins were largely isolated and came into secondary contact within the last 25,000 years, but the role of whaling in changes in genetic diversity and gene flow over recent generations could not be resolved. We hypothesise that these findings are driven by factors that promote isolation, such as female philopatry, and factors that could promote dispersal, such as oceanographic changes. These findings highlight the application of ABC approaches to infer the connectivity in mobile species with complex population histories and, currently, low levels of differentiation.

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The study of local adaptation is rendered difficult by many evolutionary confounding phenomena (for example, genetic drift and demographic history). When complex traits are involved in local adaptation, phenomena such as phenotypic plasticity further hamper evolutionary biologists to study the complex relationships between phenotype, genotype and environment. In this perspective paper, we suggest that the common garden experiment, specifically designed to deal with phenotypic plasticity, has a clear role to play in the study of local adaptation, even (if not specifically) in the genomic era. After a quick review of some high-throughput genotyping protocols relevant in the context of a common garden, we explore how to improve common garden analyses with dense marker panel data and recent statistical methods. We then show how combining approaches from population genomics and genome-wide association studies with the settings of a common garden can yield to a very efficient, thorough and integrative study of local adaptation. Especially, evidence from genomic (for example, genome scan) and phenotypic origins constitute independent insights into the possibility of local adaptation scenarios, and genome-wide association studies in the context of a common garden experiment allow to decipher the genetic bases of adaptive traits.

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Fidelity to migratory destinations is an important driver of connectivity in marine and avian species. Here we assess the role of maternally directed learning of migratory habitats, or migratory culture, on the population structure of the endangered Australian and New Zealand southern right whale. Using DNA profiles, comprising mitochondrial DNA (mtDNA) haplotypes (500 bp), microsatellite genotypes (17 loci) and sex from 128 individually-identified whales, we find significant differentiation among winter calving grounds based on both mtDNA haplotype (FST = 0.048, ΦST = 0.109, p < 0.01) and microsatellite allele frequencies (FST = 0.008, p < 0.01), consistent with long-term fidelity to calving areas. However, most genetic comparisons of calving grounds and migratory corridors were not significant, supporting the idea that whales from different calving grounds mix in migratory corridors. Furthermore, we find a significant relationship between δ(13)C stable isotope profiles of 66 Australian southern right whales, a proxy for feeding ground location, and both mtDNA haplotypes and kinship inferred from microsatellite-based estimators of relatedness. This indicates migratory culture may influence genetic structure on feeding grounds. This fidelity to migratory destinations is likely to influence population recovery, as long-term estimates of historical abundance derived from estimates of genetic diversity indicate the South Pacific calving grounds remain at <10% of pre-whaling abundance.

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Population genetic signatures of local adaptation are frequently investigated by identifying loci with allele frequencies that exhibit high correlation with ecological variables. One difficulty with this approach is that ecological associations might be confounded by geographic variation at selectively neutral loci. Here, we consider populations that underwent spatial expansion from their original range, and for which geographical variation of adaptive allele frequency coincides with habitat gradients. Using range expansion simulations, we asked whether our ability to detect genomic regions involved in adaptation could be impacted by the orientation of the ecological gradients. For three ecological association methods tested, we found, counter-intuitively, fewer false-positive associations when ecological gradients aligned along the main axis of expansion than when they aligned along any other direction. This result has important consequences for the analysis of genomic data under non-equilibrium population genetic models. Alignment of gradients with expansion axes is likely to be common in scenarios in which expanding species track their ecological niche during climate change while adapting to changing environments at their rear edge.

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We describe a method for making inferences about the factors that influence colonization processes in natural populations. We consider the general situation where we have genetic data from a newly colonized population and also from I source populations that may have contributed individuals to the founding group that established the new population. The model assumes that p (biotic/abiotic) factors, G(1), ... ,G(p) may have influenced some individuals in some of the source populations to find a new habitat patch where they could establish a new population. The aim of the method is to determine the composition of the founding group and to ascertain if the aforementioned factors have indeed played a role in the colonization event. We investigate the performance of our method using simulated data sets and illustrate its application with data from the grey seal Halichoerus grypus. These applications demonstrate that the method can identify accurately those factors that are most important for the founding of new populations. This is the case even when genetic differentiation among source populations is low. The estimates of the contribution that each source population makes to the founding groups is somewhat sensitive to the degree of genetic differentiation but it is still possible to identify the sources that are the main contributors to the founding group, even when genetic differentiation is low (F(ST) = 0.01).

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In this paper, we derive the expectation of two popular genetic distances under a model of pure population fission allowing for unequal population sizes. Under the model, we show that conventional genetic distances are not proportional to the divergence time and generally overestimate it due to unequal genetic drift and to a bottleneck effect at the divergence time. This bias cannot be totally removed even if the present population sizes are known. Instead, we present a method to estimate the divergence times between populations which is based on the average number of nucleotide differences within and between populations. The method simultaneously estimates the divergence time, the ancestral population size and the relative sizes of the derived populations. A simulation study revealed that this method is essentially unbiased and that it leads to better estimates than traditional approaches for a very wide range of parameter values. Simulations also indicated that moderate population growth after divergence has little effect on the estimates of all three estimated parameters. An application of our method to a comparison of humans and chimpanzee mitochondrial DNA diversity revealed that common chimpanzees have a significantly larger female population size than humans.

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We compare the performance of Nm estimates based on FST and RST obtained from microsatellite data using simulations of the stepwise mutation model with range constraints in allele size classes. The results of the simulations suggest that the use of microsatellite loci can lead to serious overestimations of Nm, particularly when population sizes are large (N > 5000) and range constraints are high (K < 20). The simulations also indicate that, when population sizes are small (N /= 50) and many loci (nl >/= 20), RST performs better than FST for most of the parameter space. However, FST-based estimates are always better than RST when sample sizes are moderate or small (ns

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