Glacial cycles have played a dominant role in shaping the genetic structure and distribution of biota in northwestern North America. The two major ice age refugia of Beringia and the Pacific Northwest were connected by major mountain chains and bordered by the Pacific Ocean. As a result, numerous refugial options were available for the regions taxa during glacial advances. We reviewed the importance of glaciations and refugia in shaping northwestern North America's phylogeographic history. We also tested whether ecological variables were associated with refugial history. The recurrent phylogeographic patterns that emerged were the following: (i) additional complexity, i.e. refugia within refugia, in both Beringia and the Pacific Northwest; and (ii) strong evidence for cryptic refugia in the Alexander Archipelago and Haida Gwaii, the Canadian Arctic and within the ice-sheets. Species with contemporary ranges that covered multiple refugia, or those with high dispersal ability, were significantly more likely to have resided in multiple refugia. Most of the shared phylogeographic patterns can be attributed to multiple refugial locales during the last glacial maximum or major physiographic barriers like rivers and glaciers. However, some of the observed patterns are much older and appear connected to the orogeny of the Cascade-Sierra chain or allopatric differentiation during historic glacial advances. The emergent patterns from this review suggest we should refine the classic Beringian-southern refugial paradigm for northwestern North American biota and highlight the ecological and evolutionary consequences of colonization from multiple refugia.

The global loss of biodiversity continues at an alarming rate. Genomic approaches have been suggested as a promising tool for conservation practice, and we discuss how scaling-up to genome-wide inference can benefit traditional conservation genetic approaches and provide qualitatively novel insights. Yet, the generation of genomic data and subsequent analyses and interpretations are still challenging and largely confined to academic research in ecology and 20evolution. This generates a gap between basic research and applicable solutions for conservation managers faced with multifaceted problems. Before the real-world conservation potential of genomic research can be realized, we suggest that current infrastructures need to be modified, methods must mature, analytical pipelines need to be developed, and successful case studies must be disseminated to practitioners. 3 Conservation biology and genomicsLike most of the life sciences, conservation biology is being confronted with the challenge of how to integrate the collection and analysis of large-scale genomic data into its toolbox. Conservation biologists pull from a wide array of disciplines in an effort to preserve biodiversity and ecosystem services [1]. Genetic data have helped in this regard by 30 detecting, for example, population substructure, measuring genetic connectivity, and identifying potential risks associated with demographic change and inbreeding [2]. Traditionally, conservation genetics (see Glossary) has relied on a handful of molecular markers ranging from a few allozymes to dozens of microsatellites [3]. But for close to a decade [4], genomics -broadly defined high-throughput sampling of nucleic acids [5] -has been touted as an important advancement to the field, a panacea of sorts for the unresolved conservation problems typically addressed 35 with genetic data [6,7]. This transition has led to much promise, but also hyperbole, where concrete empirical examples of genomic data having a conservation impact remain rare.Under the premise that assisting conservation of the world's biota is its ultimate purpose, the emerging field of conservation genomics must openly and pragmatically discuss its potential contribution towards this goal. While there 40are prominent examples where genetic approaches have made inroads influencing conservation efforts (e.g., Florida panther augmentation [8,9]) and wildlife enforcement (i.e., detecting illegal harvest [10]), it is not immediately clear that the conservation community and society more broadly have embraced genomics as a useful tool for conservation.Maintaining genetic diversity has largely been an afterthought when it comes to national biodiversity policies [11,12], and attempts to identify areas that might prove to be essential for conserving biological diversity rarely mention 45 genomics (e.g. [13,14]). An obvious reason for this disconnect is that many of the pressing conservation issues (e.g., [15,16]) simply do not need genomics, but instead need political will.The traditional use of gene...

Ecologically mediated selection has increasingly become recognised as an important driver of speciation. The correlation between neutral genetic differentiation and environmental or phenotypic divergence among populations, to which we collectively refer to as isolation-by-ecology (IBE), is an indicator of ecological speciation. In a meta-analysis framework, we determined the strength and commonality of IBE in nature. On the basis of 106 studies, we calculated a mean effect size of IBE with and without controlling for spatial autocorrelation among populations. Effect sizes were 0.34 (95% CI 0.24-0.42) and 0.26 (95% CI 0.13-0.37), respectively, indicating that an average of 5% of the neutral genetic differentiation among populations was explained purely by ecological contrast. Importantly, spatial autocorrelation reduced IBE correlations for environmental variables, but not for phenotypes. Through simulation, we showed how the influence of isolation-by-distance and spatial autocorrelation of ecological variables can result in false positives or underestimated correlations if not accounted for in the IBE model. Collectively, this meta-analysis showed that ecologically induced genetic divergence is pervasive across time-scales and taxa, and largely independent of the choice of molecular marker. We discuss the importance of these results in the context of adaptation and ecological speciation and suggest future research avenues.

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Species that inhabit naturally fragmented environments are expected to be spatially structured and exhibit reduced genetic diversity at the periphery of their range. Patterns of differentiation may also reflect historical processes such as recolonization from glacial refugia. We examined the relative importance of these factors in shaping the spatial patterns of genetic differentiation across the range of an alpine specialist, the North American mountain goat (Oreamnos americanus). Contrary to fossil evidence that suggests a single southern refugium, we detected evidence for additional refugia in northern British Columbia and the Alaskan coast using both mitochondrial and microsatellite DNA. A core area of elevated genetic diversity characterized both regions, and molecular dating suggested a recent Pleistocene split was followed by demographic expansion. Across their range, mountain goats were highly genetically structured and displayed the expected pattern of declining diversity toward the periphery. Gene flow was high within contiguous mountain ranges, but cross-assignments paradoxically suggest that long-distance contemporary dispersal movements are not uncommon. These results improve our understanding of how historical vicariance and contemporary fragmentation influence population differentiation, and have implications for conserving the adaptive potential of alpine populations and habitat.K E Y W O R D S : Biogeography, center-marginal hypothesis, isolation-by-distance, mountain goats, population structure, refugia.

Landscape heterogeneity plays an integral role in shaping ecological and evolutionary processes. Despite links between the two disciplines, ecologists and population geneticists have taken different approaches to evaluating habitat selection, animal movement, and gene flow across the landscape. Ecologists commonly use statistical models such as resource selection functions (RSFs) to identify habitat features disproportionately selected by animals, whereas population genetic approaches model genetic differentiation according to the distribution of habitat variables. We combined ecological and genetic approaches by using RSFs to predict genetic relatedness across a heterogeneous landscape. We constructed sex- and season-specific resistance surfaces based on RSFs estimated using data from 102 GPS (global positioning system) radio-collared mountain goats (Oreamnos americanus) in southeast Alaska, USA. Based on mountain goat ecology, we hypothesized that summer and male surfaces would be the best predictors of relatedness. All individuals were genotyped at 22 microsatellite loci, which we used to estimate genetic relatedness. Summer resistance surfaces derived from RSFs were the best predictors of genetic relatedness, and winter models the poorest. Mountain goats generally selected for areas close to escape terrain and with a high heat load (a metric related to vegetative productivity and snow depth), while avoiding valleys. Male- and female-specific surfaces were similar, except for winter, for which male habitat selection better predicted genetic relatedness. The null models of isolation-by-distance and barrier only outperformed the winter models. This study merges high-resolution individual locations through GPS telemetry and genetic data, that can be used to validate and parameterize landscape genetics models, and further elucidates the relationship between landscape heterogeneity and genetic differentiation.

Approximate Bayesian computation (ABC) is a powerful tool for model-based inference of demographic histories from large genetic data sets. For most organisms, its implementation has been hampered by the lack of sufficient genetic data. Genotyping-by-sequencing (GBS) provides cheap genome-scale data to fill this gap, but its potential has not fully been exploited. Here, we explored power, precision and biases of a coalescent-based ABC approach where GBS data were modelled with either a population mutation parameter (θ) or a fixed site (FS) approach, allowing single or several segregating sites per locus. With simulated data ranging from 500 to 50 000 loci, a variety of demographic models could be reliably inferred across a range of timescales and migration scenarios. Posterior estimates were informative with 1000 loci for migration and split time in simple population divergence models. In more complex models, posterior distributions were wide and almost reverted to the uninformative prior even with 50 000 loci. ABC parameter estimates, however, were generally more accurate than an alternative composite-likelihood method. Bottleneck scenarios proved particularly difficult, and only recent bottlenecks without recovery could be reliably detected and dated. Notably, minor-allele-frequency filters - usual practice for GBS data - negatively affected nearly all estimates. With this in mind, we used a combination of FS and θ approaches on empirical GBS data generated from the Atlantic walrus (Odobenus rosmarus rosmarus), collectively providing support for a population split before the last glacial maximum followed by asymmetrical migration and a high Arctic bottleneck. Overall, this study evaluates the potential and limitations of GBS data in an ABC-coalescence framework and proposes a best-practice approach.