Traditional methods for characterizing genetic differentiation among populations rely on a priori grouping of individuals. Bayesian clustering methods avoid this limitation by using linkage and Hardy-Weinberg disequilibrium to decompose a sample of individuals into genetically distinct groups. There are several software programs available for Bayesian clustering analyses, all of which describe a decrease in the ability to detect distinct clusters as levels of genetic differentiation among populations decrease. However, no study has yet compared the performance of such methods at low levels of population differentiation, which may be common in species where populations have experienced recent separation or high levels of gene flow. We used simulated data to evaluate the performance of three Bayesian clustering software programs, PAR-TITION, STRUCTURE, and BAPS, at levels of population differentiation below F ST =0.1. PARTITION was unable to correctly identify the number of subpopulations until levels of F ST reached around 0.09. Both STRUCTURE and BAPS performed very well at low levels of population differentiation, and were able to correctly identify the number of subpopulations at F ST around 0.03. The average proportion of an individual's genome assigned to its true population of origin increased with increasing F ST for both programs, reaching over 92% at an F ST of 0.05. The average number of misassignments (assignments to the incorrect subpopulation) continued to decrease as F ST increased, and when F ST was 0.05, fewer than 3% of individuals were misassigned using either program. Both STRUCTURE and BAPS worked extremely well for inferring the number of clusters when clusters were not well-differentiated (F ST =0.02-0.03), but our results suggest that F ST must be at least 0.05 to reach an assignment accuracy of greater than 97%.

Identifying and monitoring locally adaptive genetic variation can have direct utility for conserving species at risk, especially when management may include actions such as translocations for restoration, genetic rescue, or assisted gene flow. However, genomic studies of local adaptation require careful planning to be successful, and in some cases may not be a worthwhile use of resources. Here, we offer an adaptive management framework to help conservation biologists and managers decide when genomics is likely to be effective in detecting local adaptation, and how to plan assessment and monitoring of adaptive variation to address conservation objectives. Studies of adaptive variation using genomic tools will inform conservation actions in many cases, including applications such as assisted gene flow and identifying conservation units. In others, assessing genetic diversity, inbreeding, and demographics using selectively neutral genetic markers may be most useful. And in some cases, local adaptation may be assessed more efficiently using alternative approaches such as common garden experiments. Here, we identify key considerations of genomics studies of locally adaptive variation, provide a road map for successful collaborations with genomics experts including key issues for study design and data analysis, and offer guidelines for interpreting and using results from genomic assessments to inform monitoring programs and conservation actions.

Quaternary climatic oscillations greatly influenced the present-day population genetic structure of animals and plants. For species with high dispersal and reproductive potential, phylogeographic patterns resulting from historical processes can be cryptic, overshadowed by contemporary processes. Here we report a study of the phylogeography of Odocoileus hemionus, a large, vagile ungulate common throughout western North America. We examined sequence variation of mitochondrial DNA (control region and cytochrome b) within and among 70 natural populations across the entire range of the species. Among the 1766 individual animals surveyed, we recovered 496 haplotypes. Although fine-scale phylogenetic structure was weakly resolved using phylogenetic methods, network analysis clearly revealed the presence of 12 distinct haplogroups. The spatial distribution of haplogroups showed a strong genetic discontinuity between the two morphological types of O. hemionus, mule deer and black-tailed deer, east and west of the Cascade Mountains in the Pacific Northwest. Within the mule deer lineage, we identified several haplogroups that expanded before or during the Last Glacial Maximum, suggesting that mule deer persisted in multiple refugia south of the ice sheets. Patterns of genetic diversity within the black-tailed deer lineage suggest a single refugium along the Pacific Northwest coast, and refute the hypothesis that black-tailed deer persisted in one or more northern refugia. Our data suggest that black-tailed deer recolonized areas in accordance with the pattern of glacial retreat, with initial recolonization northward along a coastal route and secondary recolonization inland.

We compare the two main classes of measures of population structure in genetics: (i) fixation measures such as FST,GST, and θ and (ii) allelic differentiation measures such as Jost's D and entropy differentiation. These two groups of measures quantify complementary aspects of population structure, which have no necessary relationship with each other. We focus especially on empirical aspects of population structure relevant to conservation analyses. At the empirical level, the first set of measures quantify nearness to fixation, while the second set of measures quantify relative degree of allelic differentiation. The two sets of measures do not compete with each other. Fixation measures are often misinterpreted as measures of allelic differentiation in conservation applications; we give examples and theoretical explanations showing why this interpretation can mislead. This misinterpretation has led to the mistaken belief that the absolute number of migrants determines allelic differentiation between demes when mutation rate is low; we show that in the finite island model, the absolute number of migrants determines nearness to fixation, not allelic differentiation. We show that a different quantity, the factor that controls Jost's D, is a good predictor of the evolution of the actual genetic divergence between demes at equilibrium in this model. We also show that when conservation decisions require judgments about differences in genetic composition between demes, allelic differentiation measures should be used instead of fixation measures. Allelic differentiation of fast‐mutating markers can be used to rank pairs or sets of demes according to their differentiation, but the allelic differentiation at coding loci of interest should be directly measured in order to judge its actual magnitude at these loci.

Individual-based landscape genetic methods have become increasingly popular for quantifying fine-scale landscape influences on gene flow. One complication for individual-based methods is that gene flow and landscape variables are often correlated with geography. Partial statistics, particularly Mantel tests, are often employed to control for these inherent correlations by removing the effects of geography while simultaneously correlating measures of genetic differentiation and landscape variables of interest. Concerns about the reliability of Mantel tests prompted this study, in which we use simulated landscapes to evaluate the performance of partial Mantel tests and two ordination methods, distance-based redundancy analysis (dbRDA) and redundancy analysis (RDA), for detecting isolation by distance (IBD) and isolation by landscape resistance (IBR). Specifically, we described the effects of suitable habitat amount, fragmentation and resistance strength on metrics of accuracy (frequency of correct results, type I/II errors and strength of IBR according to underlying landscape and resistance strength) for each test using realistic individual-based gene flow simulations. Mantel tests were very effective for detecting IBD, but exhibited higher error rates when detecting IBR. Ordination methods were overall more accurate in detecting IBR, but had high type I errors compared to partial Mantel tests. Thus, no one test outperformed another completely. A combination of statistical tests, for example partial Mantel tests to detect IBD paired with appropriate ordination techniques for IBR detection, provides the best characterization of fine-scale landscape genetic structure. Realistic simulations of empirical data sets will further increase power to distinguish among putative mechanisms of differentiation.