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Aim Using sequences of complete mitochondrial genomes, our aims were: (1) to investigate the matrilineal phylogeographical structure, migration patterns and lineage coalescence times in a large, continuous population of brown bears (Ursus arctos); and (2) to develop a novel spatial genetic method to identify migration corridors and barriers. Location North‐western Eurasia: from eastern European Russia to the Baltic Sea. Methods We sequenced the complete mitochondrial genomes of 95 brown bears. The phylogeographical resolution of complete genomes was compared to that derived from subsets of the genome, including the most commonly used shorter sequences. We conducted network and Bayesian phylogeographical analyses and developed a novel, spatially explicit, individual‐based approach (called DResD) for identifying migration corridors and barriers. Results Analysis of mitogenome sequences revealed five haplogroups, specific to particular geographical areas, exhibiting far greater resolving power than shorter sequences. Estimated coalescence times for the haplogroups ranged from 7.7 to 15.2 ka, suggesting that their divergence took place after the last glaciation. We found several migration trends, including a large westward migration from eastern European Russia towards Finland. We also found evidence of a potential barrier and a migration corridor in the south‐west of the study area. Main conclusions The use of complete mitochondrial genomes from a brown bear population in north‐western Eurasia allowed us to identify phylogeographical structure, signatures of demographic history and spatial processes that had not previously been detected using shorter sequences. These findings have implications for studies on other species and populations, especially those exhibiting low mtDNA diversity. The relatively recent divergence estimates for haplogroups highlight the significance not only of the last glaciation but also of climatic fluctuations during the post‐glacial period for the divergence of mammal populations in Europe. Our spatial genetic method represents a new tool for the analysis of genetic data in a geographical context and is applicable to any data that yield genetic distance matrices, including microsatellites, amplified fragment length polymorphisms (AFLPs) and single‐nucleotide polymorphisms (SNPs).

Knowledge of population structure and genetic diversity and the spatio-temporal demographic processes affecting populations is crucial for effective wildlife preservation, yet these factors are still poorly understood for organisms with large continuous ranges. Available population genetic data reveal that widespread mammals have for the most part only been carefully studied at the local population scale, which is insufficient for understanding population processes at larger scales. Here, we provide data on population structure, genetic diversity and gene flow in a brown bear population inhabiting the large territory of northwestern Eurasia. Analysis of 17 microsatellite loci indicated significant population substructure, consisting of four genetic groups. While three genetic clusters were confined to small geographical areas-located in Estonia, southern Finland and Leningrad oblast, Russia-the fourth cluster spanned a very large area broadly falling between northern Finland and the Arkhangelsk and Kirov oblasts of Russia. Thus, the data indicate a complex pattern where a fraction of the population exhibits large-scale gene flow that is unparalleled by other wild mammals studied to date, while the remainder of the population appears to have been structured by a combination of demographic history and landscape barriers. These results based on nuclear data are generally in good agreement with evidence previously derived using mitochondrial markers, and taken together, these markers provide complementary information about female-specific and population-level processes. Moreover, this study conveys information about spatial processes occurring over multiple generations that cannot be readily gained using other approaches, e.g. telemetry.

Aim Climatic changes during the Late Pleistocene had major impacts on populations of plant and animal species. Brown bears and other large mammals are likely to have experienced analogous ecological pressures and phylogeographical processes. Here, we address several unresolved issues regarding the Late Pleistocene demography of brown bears: (1) the putative locations of refugia; (2) the direction of migrations across Eurasia and into North America; and (3) parallels with the demographic histories of other wild mammals and modern humans. Location Eurasia and North America. Methods We sequenced 110 complete mitochondrial genomes from Eurasian brown bears and combined these with published sequences from 138 brown bears and 33 polar bears. We used a Bayesian approach to obtain a joint estimate of the phylogeny and evolutionary divergence times. The inferred mutation rate was compared with estimates obtained using two additional methods. Results Bayesian phylogenetic analysis identified seven clades of brown bears, with most individuals belonging to a very large Holarctic clade. Bears from the widespread clade 3a1, which has a distribution from Europe across Asia to Alaska, shared a common ancestor about 45,000 years ago. Main conclusions We suggest that the Altai‐Sayan region and Beringia were important Late Pleistocene refuge areas for brown bears and propose large‐scale migration scenarios for bears in Eurasia and to North America. We also argue that brown bears and modern humans experienced a demographic standstill in Beringia before colonizing North America.

Spatial genetics is a relatively new field in wildlife and conservation biology that is becoming an essential tool for unravelling the complexities of animal population processes, and for designing effective strategies for conservation and management. Conceptual and methodological developments in this field are therefore critical. Here we present two novel methodological approaches that further the analytical possibilities of STRUCTURE and DResD. Using these approaches we analyse structure and migrations in a grey wolf ( Canis lupus ) population in north-eastern Europe. We genotyped 16 microsatellite loci in 166 individuals sampled from the wolf population in Estonia and Latvia that has been under strong and continuous hunting pressure for decades. Our analysis demonstrated that this relatively small wolf population is represented by four genetic groups. We also used a novel methodological approach that uses linear interpolation to statistically test the spatial separation of genetic groups. The new method, which is capable of using program STRUCTURE output, can be applied widely in population genetics to reveal both core areas and areas of low significance for genetic groups. We also used a recently developed spatially explicit individual-based method DResD, and applied it for the first time to microsatellite data, revealing a migration corridor and barriers, and several contact zones.