Modular chromosome rearrangements reveal parallel and nonparallel adaptation in a marine fish

Genomic architecture and standing variation can play a key role in ecological adaptation and contribute to the predictability of evolution. In Atlantic cod (Gadus morhua), four large chromosomal rearrangements have been associated with ecological gradients and migratory behavior in regional analyses. However, the degree of parallelism, the extent of independent inheritance, and functional distinctiveness of these rearrangements remain poorly understood. Here, we use a 12K single nucleotide polymorphism (SNP) array to demonstrate extensive individual variation in rearrangement genotype within populations across the species range, suggesting that local adaptation to fine‐scale ecological variation is enabled by rearrangements with independent inheritance. Our results demonstrate significant association of rearrangements with migration phenotype and environmental gradients across the species range. Individual rearrangements exhibit functional modularity, but also contain loci showing multiple environmental associations. Clustering in genetic distance trees and reduced differentiation within rearrangements across the species range are consistent with shared variation as a source of contemporary adaptive diversity in Atlantic cod. Conversely, we also find that haplotypes in the LG12 and LG1 rearranged region have diverged across the Atlantic, despite consistent environmental associations. Exchange of these structurally variable genomic regions, as well as local selective pressures, has likely facilitated individual diversity within Atlantic cod stocks. Our results highlight the importance of genomic architecture and standing variation in enabling fine‐scale adaptation in marine species.     

In the presence of population structure: From genomics to candidate genes underlying local adaptation

Understanding the genomic signatures, genes, and traits underlying local adaptation of organisms to heterogeneous environments is of central importance to the field evolutionary biology. To identify loci underlying local adaptation, models that combine allelic and environmental variation while controlling for the effects of population structure have emerged as the method of choice. Despite being evaluated in simulation studies, there has not been a thorough investigation of empirical evidence supporting local adaptation across these alleles. To evaluate these methods, we use 875 Arabidopsis thaliana Eurasian accessions and two mixed models (GEMMA and LFMM) to identify candidate SNPs underlying local adaptation to climate. Subsequently, to assess evidence of local adaptation and function among significant SNPs, we examine allele frequency differentiation and recent selection across Eurasian populations, in addition to their distribution along quantitative trait loci (QTL) explaining fitness variation between Italy and Sweden populations and cis‐regulatory/nonsynonymous sites showing significant selective constraint. Our results indicate that significant LFMM/GEMMA SNPs show low allele frequency differentiation and linkage disequilibrium across locally adapted Italy and Sweden populations, in addition to a poor association with fitness QTL peaks (highest logarithm of odds score). Furthermore, when examining derived allele frequencies across the Eurasian range, we find that these SNPs are enriched in low‐frequency variants that show very large climatic differentiation but low levels of linkage disequilibrium. These results suggest that their enrichment along putative functional sites most likely represents deleterious variation that is independent of local adaptation. Among all the genomic signatures examined, only SNPs showing high absolute allele frequency differentiation (AFD) and linkage disequilibrium (LD) between Italy and Sweden populations showed a strong association with fitness QTL peaks and were enriched along selectively constrained cis‐regulatory/nonsynonymous sites. Using these SNPs, we find strong evidence linking flowering time, freezing tolerance, and the abscisic‐acid pathway to local adaptation.     

Broad Concordance in the Spatial Distribution of Adaptive and Neutral Genetic Variation across an Elevational Gradient in Deer Mice

When species are continuously distributed across environmental gradients, the relative strength of selection and gene flow shape spatial patterns of genetic variation, potentially leading to variable levels of differentiation across loci. Determining whether adaptive genetic variation tends to be structured differently than neutral variation along environmental gradients is an open and important question in evolutionary genetics. We performed exome-wide population genomic analysis on deer mice sampled along an elevational gradient of nearly 4,000 m of vertical relief. Using a combination of selection scans, genotype−environment associations, and geographic cline analyses, we found that a large proportion of the exome has experienced a history of altitude-related selection. Elevational clines for nearly 30% of these putatively adaptive loci were shifted significantly up- or downslope of clines for loci that did not bear similar signatures of selection. Many of these selection targets can be plausibly linked to known phenotypic differences between highland and lowland deer mice, although the vast majority of these candidates have not been reported in other studies of highland taxa. Together, these results suggest new hypotheses about the genetic basis of physiological adaptation to high altitude, and the spatial distribution of adaptive genetic variation along environmental gradients.     

Ecological genomics of local adaptation in Cornus florida L. by genotyping by sequencing

Discovering local adaptation, its genetic underpinnings, and environmental drivers is important for conserving forest species. Ecological genomic approaches coupled with next‐generation sequencing are useful means to detect local adaptation and uncover its underlying genetic basis in nonmodel species. We report results from a study on flowering dogwood trees (Cornus florida L.) using genotyping by sequencing (GBS). This species is ecologically important to eastern US forests but is severely threatened by fungal diseases. We analyzed subpopulations in divergent ecological habitats within North Carolina to uncover loci under local selection and associated with environmental–functional traits or disease infection. At this scale, we tested the effect of incorporating additional sequencing before scaling for a broader examination of the entire range. To test for biases of GBS, we sequenced two similarly sampled libraries independently from six populations of three ecological habitats. We obtained environmental–functional traits for each subpopulation to identify associations with genotypes via latent factor mixed modeling (LFMM) and gradient forests analysis. To test whether heterogeneity of abiotic pressures resulted in genetic differentiation indicative of local adaptation, we evaluated F_st per locus while accounting for genetic differentiation between coastal subpopulations and Piedmont‐Mountain subpopulations. Of the 54 candidate loci with sufficient evidence of being under selection among both libraries, 28–39 were Arlequin–BayeScan F_st outliers. For LFMM, 45 candidates were associated with climate (of 54), 30 were associated with soil properties, and four were associated with plant health. Reanalysis of combined libraries showed that 42 candidate loci still showed evidence of being under selection. We conclude environment‐driven selection on specific loci has resulted in local adaptation in response to potassium deficiencies, temperature, precipitation, and (to a marginal extent) disease. High allele turnover along ecological gradients further supports the adaptive significance of loci speculated to be under selection.     

Altitudinal and seasonal variation in microsatellite allele frequencies of Drosophila buzzatii

Variation in climate, particularly temperature, is known to affect the genetic composition of populations. Although there have been many studies of latitudinal variation, comparisons of populations across altitudes or seasons, particularly for animal species, are less common. Here, we study genetic variation (microsatellite markers) in populations of Drosophila buzzatii collected along altitudinal gradients and in different seasons. We found no differences in genetic variation between 2 years or between seasons within years. However, there were numerous cases of significant associations between allele frequencies or expected heterozygosities and altitude, with more than half showing nonlinear relationships. While these associations indicate possible selection and local altitudinal adaptation, direct tests gave strong evidence for selection affecting two loci and weaker evidence for five other loci. Two loci that are located within an inversion (including the one with strongest evidence for selection) show a linear increase in genetic diversity with altitude, likely due to thermal selection. Parallel associations with altitude here and with latitude in Australian populations indicate that selection is operating on chromosomal regions marked by some of the loci.     

Broad-scale adaptive genetic variation in alpine plants is driven by temperature and precipitation

Identifying adaptive genetic variation is a challenging task, in particular in non-model species for which genomic information is still limited or absent. Here, we studied distribution patterns of amplified fragment length polymorphisms (AFLPs) in response to environmental variation, in 13 alpine plant species consistently sampled across the entire European Alps. Multiple linear regressions were performed between AFLP allele frequencies per site as dependent variables and two categories of independent variables, namely Moran's eigenvector map MEM variables (to account for spatial and unaccounted environmental variation, and historical demographic processes) and environmental variables. These associations allowed the identification of 153 loci of ecological relevance. Univariate regressions between allele frequency and each environmental factor further showed that loci of ecological relevance were mainly correlated with MEM variables. We found that precipitation and temperature were the best environmental predictors, whereas topographic factors were rarely involved in environmental associations. Climatic factors, subject to rapid variation as a result of the current global warming, are known to strongly influence the fate of alpine plants. Our study shows, for the first time for a large number of species, that the same environmental variables are drivers of plant adaptation at the scale of a whole biome, here the European Alps.     

Landscape genomics and a common garden trial reveal adaptive differentiation to temperature across Europe in the tree species Alnus glutinosa

The adaptive potential of tree species to cope with climate change has important ecological and economic implications. Many temperate tree species experience a wide range of environmental conditions, suggesting high adaptability to new environmental conditions. We investigated adaptation to regional climate in the drought‐sensitive tree species Alnus glutinosa (Black alder), using a complementary approach that integrates genomic, phenotypic and landscape data. A total of 24 European populations were studied in a common garden and through landscape genomic approaches. Genotyping‐by‐sequencing was used to identify SNPs across the genome, resulting in 1990 SNPs. Although a relatively low percentage of putative adaptive SNPs was detected (2.86% outlier SNPs), we observed clear associations among outlier allele frequencies, temperature and plant traits. In line with the typical drought avoiding nature of A. glutinosa, leaf size varied according to a temperature gradient and significant associations with multiple outlier loci were observed, corroborating the ecological relevance of the observed outlier SNPs. Moreover, the lack of isolation by distance, the very low genetic differentiation among populations and the high intrapopulation genetic variation all support the notion that high gene exchange combined with strong environmental selection promotes adaptation to environmental cues.     

Locally Adaptive Inversions Modulate Genetic Variation at Different Geographic Scales in a Seaweed Fly

Across a species range, multiple sources of environmental heterogeneity, at both small and large scales, create complex landscapes of selection, which may challenge adaptation, particularly when gene flow is high. One key to multidimensional adaptation may reside in the heterogeneity of recombination along the genome. Structural variants, like chromosomal inversions, reduce recombination, increasing linkage disequilibrium among loci at a potentially massive scale. In this study, we examined how chromosomal inversions shape genetic variation across a species range and ask how their contribution to adaptation in the face of gene flow varies across geographic scales. We sampled the seaweed fly Coelopa frigida along a bioclimatic gradient stretching across 10° of latitude, a salinity gradient, and a range of heterogeneous, patchy habitats. We generated a chromosome-level genome assembly to analyze 1,446 low-coverage whole genomes collected along those gradients. We found several large nonrecombining genomic regions, including putative inversions. In contrast to the collinear regions, inversions and low-recombining regions differentiated populations more strongly, either along an ecogeographic cline or at a fine-grained scale. These genomic regions were associated with environmental factors and adaptive phenotypes, albeit with contrasting patterns. Altogether, our results highlight the importance of recombination in shaping adaptation to environmental heterogeneity at local and large scales.     

Signatures of local adaptation along environmental gradients in a range‐expanding damselfly (Ischnura elegans)

Insect distributions are shifting rapidly in response to climate change and are undergoing rapid evolutionary change. We investigate the molecular signatures underlying local adaptation in the range‐expanding damselfly, Ischnura elegans. Using a landscape genomic approach combined with generalized dissimilarity modelling (GDM), we detect selection signatures on loci via allelic frequency change along environmental gradients. We analyse 13,612 single nucleotide polymorphisms (SNPs), derived from restriction site‐associated DNA sequencing (RADseq), in 426 individuals from 25 sites spanning the I. elegans distribution in Sweden, including its expanding northern range edge. Environmental association analysis (EAA) and the magnitude of allele frequency change along the range expansion gradient revealed significant signatures of selection in relation to high maximum summer temperature, high mean annual precipitation and low wind speeds at the range edge. SNP annotations with significant signatures of selection revealed gene functions associated with ongoing range expansion, including heat shock proteins (HSP40 and HSP70), ion transport (V‐ATPase) and visual processes (long‐wavelength‐sensitive opsin), which have implications for thermal stress response, salinity tolerance and mate discrimination, respectively. We also identified environmental thresholds where climate‐mediated selection is likely to be strong, and indicate that I. elegans is rapidly adapting to the climatic environment during its ongoing range expansion. Our findings empirically validate an integrative approach for detecting spatially explicit signatures of local adaptation along environmental gradients.     

Testing for local adaptation and evolutionary potential along altitudinal gradients in rainforest Drosophila: beyond laboratory estimates

Predicting how species will respond to the rapid climatic changes predicted this century is an urgent task. Species distribution models (SDMs) use the current relationship between environmental variation and species’ abundances to predict the effect of future environmental change on their distributions. However, two common assumptions of SDMs are likely to be violated in many cases: (i) that the relationship of environment with abundance or fitness is constant throughout a species’ range and will remain so in future and (ii) that abiotic factors (e.g. temperature, humidity) determine species’ distributions. We test these assumptions by relating field abundance of the rainforest fruit fly Drosophila birchii to ecological change across gradients that include its low and high altitudinal limits. We then test how such ecological variation affects the fitness of 35 D. birchii families transplanted in 591 cages to sites along two altitudinal gradients, to determine whether genetic variation in fitness responses could facilitate future adaptation to environmental change. Overall, field abundance was highest at cooler, high‐altitude sites, and declined towards warmer, low‐altitude sites. By contrast, cage fitness (productivity) increased towards warmer, lower‐altitude sites, suggesting that biotic interactions (absent from cages) drive ecological limits at warmer margins. In addition, the relationship between environmental variation and abundance varied significantly among gradients, indicating divergence in ecological niche across the species’ range. However, there was no evidence for local adaptation within gradients, despite greater productivity of high‐altitude than low‐altitude populations when families were reared under laboratory conditions. Families also responded similarly to transplantation along gradients, providing no evidence for fitness trade‐offs that would favour local adaptation. These findings highlight the importance of (i) measuring genetic variation in key traits under ecologically relevant conditions, and (ii) considering the effect of biotic interactions when predicting species’ responses to environmental change.     

Coherent synthesis of genomic associations with phenotypes and home environments

Local adaptation is often studied via (i) multiple common garden experiments comparing performance of genotypes in different environments and (ii) sequencing genotypes from multiple locations and characterizing geographic patterns in allele frequency. Both approaches aim to characterize the same pattern (local adaptation), yet the complementary information from each has not yet been coherently integrated. Here, we develop a genome‐wide association model of genotype interactions with continuous environmental gradients (G × E), that is reaction norms. We present an approach to impute relative fitness, allowing us to coherently synthesize evidence from common garden and genome–environment associations. Our approach identifies loci exhibiting environmental clines where alleles are associated with higher fitness in home environments. Simulations show our approach can increase power to detect loci causing local adaptation. In a case study on Arabidopsis thaliana, most identified SNPs exhibited home allele advantage and fitness trade‐offs along climate gradients, suggesting selective gradients can maintain allelic clines. SNPs exhibiting G × E associations with fitness were enriched in genic regions, putative partial selective sweeps and associations with an adaptive phenotype (flowering time plasticity). We discuss extensions for situations where only adaptive phenotypes other than fitness are available. Many types of data may point towards the loci underlying G × E and local adaptation; coherent models of diverse data provide a principled basis for synthesis.     

Evidence for evolutionary change associated with the recent range expansion of the British butterfly, Aricia agestis, in response to climate change

Poleward range expansions are widespread responses to recent climate change and are crucial for the future persistence of many species. However, evolutionary change in traits such as colonization history and habitat preference may also be necessary to track environmental change across a fragmented landscape. Understanding the likelihood and speed of such adaptive change is important in determining the rate of species extinction with ongoing climate change. We conducted an amplified fragment length polymorphism (AFLP)‐based genome scan across the recently expanded UK range of the Brown Argus butterfly, Aricia agestis, and used outlier‐based (DFDIST and BayeScan) and association‐based (Isolation‐By‐Adaptation) statistical approaches to identify signatures of evolutionary change associated with range expansion and habitat use. We present evidence for (i) limited effects of range expansion on population genetic structure and (ii) strong signatures of selection at approximately 5% AFLP loci associated with both the poleward range expansion of A. agestis and differences in habitat use across long‐established and recently colonized sites. Patterns of allele frequency variation at these candidate loci suggest that adaptation to new habitats at the range margin has involved selection on genetic variation in habitat use found across the long‐established part of the range. Our results suggest that evolutionary change is likely to affect species’ responses to climate change and that genetic variation in ecological traits across species’ distributions should be maximized to facilitate range shifts across a fragmented landscape, particularly in species that show strong associations with particular habitats.     

Outlier analyses to test for local adaptation to breeding grounds in a migratory arctic seabird

Investigating the extent (or the existence) of local adaptation is crucial to understanding how populations adapt. When experiments or fitness measurements are difficult or impossible to perform in natural populations, genomic techniques allow us to investigate local adaptation through the comparison of allele frequencies and outlier loci along environmental clines. The thick‐billed murre (Uria lomvia) is a highly philopatric colonial arctic seabird that occupies a significant environmental gradient, shows marked phenotypic differences among colonies, and has large effective population sizes. To test whether thick‐billed murres from five colonies along the eastern Canadian Arctic coast show genomic signatures of local adaptation to their breeding grounds, we analyzed geographic variation in genome‐wide markers mapped to a newly assembled thick‐billed murre reference genome. We used outlier analyses to detect loci putatively under selection, and clustering analyses to investigate patterns of differentiation based on 2220 genomewide single nucleotide polymorphisms (SNPs) and 137 outlier SNPs. We found no evidence of population structure among colonies using all loci but found population structure based on outliers only, where birds from the two northernmost colonies (Minarets and Prince Leopold) grouped with birds from the southernmost colony (Gannet), and birds from Coats and Akpatok were distinct from all other colonies. Although results from our analyses did not support local adaptation along the latitudinal cline of breeding colonies, outlier loci grouped birds from different colonies according to their non‐breeding distributions, suggesting that outliers may be informative about adaptation and/or demographic connectivity associated with their migration patterns or nonbreeding grounds.     

Climate‐associated genetic variation in Fagus sylvatica and potential responses to climate change in the French Alps

Local adaptation patterns have been found in many plants and animals, highlighting the genetic heterogeneity of species along their range of distribution. In the next decades, global warming is predicted to induce a change in the selective pressures that drive this adaptive variation, forcing a reshuffling of the underlying adaptive allele distributions. For species with low dispersion capacity and long generation time such as trees, the rapidity of the change could impede the migration of beneficial alleles and lower their capacity to track the changing environment. Identifying the main selective pressures driving the adaptive genetic variation is thus necessary when investigating species capacity to respond to global warming. In this study, we investigate the adaptive landscape of Fagus sylvatica along a gradient of populations in the French Alps. Using a double‐digest restriction‐site‐associated DNA (ddRAD) sequencing approach, we identified 7,000 SNPs from 570 individuals across 36 different sites. A redundancy analysis (RDA)‐derived method allowed us to identify several SNPs that were strongly associated with climatic gradients; moreover, we defined the primary selective gradients along the natural populations of F. sylvatica in the Alps. Strong effects of elevation and humidity, which contrast north‐western and south‐eastern site, were found and were believed to be important drivers of genetic adaptation. Finally, simulations of future genetic landscapes that used these findings allowed identifying populations at risk for F. sylvatica in the Alps, which could be helpful for future management plans.     

Multiscale landscape genomic models to detect signatures of selection in the alpine plant Biscutella laevigata

Plant species are known to adapt locally to their environment, particularly in mountainous areas where conditions can vary drastically over short distances. The climate of such landscapes being largely influenced by topography, using fine‐scale models to evaluate environmental heterogeneity may help detecting adaptation to micro‐habitats. Here, we applied a multiscale landscape genomic approach to detect evidence of local adaptation in the alpine plant Biscutella laevigata. The two gene pools identified, experiencing limited gene flow along a 1‐km ridge, were different in regard to several habitat features derived from a very high resolution (VHR) digital elevation model (DEM). A correlative approach detected signatures of selection along environmental gradients such as altitude, wind exposure, and solar radiation, indicating adaptive pressures likely driven by fine‐scale topography. Using a large panel of DEM‐derived variables as ecologically relevant proxies, our results highlighted the critical role of spatial resolution. These high‐resolution multiscale variables indeed indicate that the robustness of associations between genetic loci and environmental features depends on spatial parameters that are poorly documented. We argue that the scale issue is critical in landscape genomics and that multiscale ecological variables are key to improve our understanding of local adaptation in highly heterogeneous landscapes.     

Neutral and adaptive genomic signatures of rapid poleward range expansion

Many species are expanding their range polewards, and this has been associated with rapid phenotypic change. Yet, it is unclear to what extent this reflects rapid genetic adaptation or neutral processes associated with range expansion, or selection linked to the new thermal conditions encountered. To disentangle these alternatives, we studied the genomic signature of range expansion in the damselfly Coenagrion scitulum using 4950 newly developed genomic SNPs and linked this to the rapidly evolved phenotypic differences between core and (newly established) edge populations. Most edge populations were genetically clearly differentiated from the core populations and all were differentiated from each other indicating independent range expansion events. In addition, evidence for genetic drift in the edge populations, and strong evidence for adaptive genetic variation in association with the range expansion was detected. We identified one SNP under consistent selection in four of the five edge populations and showed that the allele increasing in frequency is associated with increased flight performance. This indicates collateral, non‐neutral evolutionary changes in independent edge populations driven by the range expansion process. We also detected a genomic signature of adaptation to the newly encountered thermal regimes, reflecting a pattern of countergradient variation. The latter signature was identified at a single SNP as well as in a set of covarying SNPs using a polygenic multilocus approach to detect selection. Overall, this study highlights how a strategic geographic sampling design and the integration of genomic, phenotypic and environmental data can identify and disentangle the neutral and adaptive processes that are simultaneously operating during range expansions.     

Ecological genomics meets community‐level modelling of biodiversity: mapping the genomic landscape of current and future environmental adaptation

Local adaptation is a central feature of most species occupying spatially heterogeneous environments, and may factor critically in responses to environmental change. However, most efforts to model the response of species to climate change ignore intraspecific variation due to local adaptation. Here, we present a new perspective on spatial modelling of organism–environment relationships that combines genomic data and community‐level modelling to develop scenarios regarding the geographic distribution of genomic variation in response to environmental change. Rather than modelling species within communities, we use these techniques to model large numbers of loci across genomes. Using balsam poplar (Populus balsamifera) as a case study, we demonstrate how our framework can accommodate nonlinear responses of loci to environmental gradients. We identify a threshold response to temperature in the circadian clock gene GIGANTEA‐5 (GI5), suggesting that this gene has experienced strong local adaptation to temperature. We also demonstrate how these methods can map ecological adaptation from genomic data, including the identification of predicted differences in the genetic composition of populations under current and future climates. Community‐level modelling of genomic variation represents an important advance in landscape genomics and spatial modelling of biodiversity that moves beyond species‐level assessments of climate change vulnerability.     

Adaptive population divergence and directional gene flow across steep elevational gradients in a climate‐sensitive mammal

The ecological effects of climate change have been shown in most major taxonomic groups; however, the evolutionary consequences are less well‐documented. Adaptation to new climatic conditions offers a potential long‐term mechanism for species to maintain viability in rapidly changing environments, but mammalian examples remain scarce. The American pika (Ochotona princeps) has been impacted by recent climate‐associated extirpations and range‐wide reductions in population sizes, establishing it as a sentinel mammalian species for climate change. To investigate evidence for local adaptation and reconstruct patterns of genomic diversity and gene flow across rapidly changing environments, we used a space‐for‐time design and restriction site‐associated DNA sequencing to genotype American pikas along two steep elevational gradients at 30,966 SNPs and employed independent outlier detection methods that scanned for genotype‐environment associations. We identified 338 outlier SNPs detected by two separate analyses and/or replicated in both transects, several of which were annotated to genes involved in metabolic function and oxygen transport. Additionally, we found evidence of directional gene flow primarily downslope from high‐elevation populations, along with reduced gene flow at outlier loci. If this trend continues, elevational range contractions in American pikas will likely be from local extirpation rather than upward movement of low‐elevation individuals; this, in turn, could limit the potential for adaptation within this landscape. These findings are of particular relevance for future conservation and management of American pikas and other elevationally restricted, thermally sensitive species.     

Lineage‐specific adaptation to climate involves flowering time in North American Arabidopsis lyrata

Adaptation to local climatic conditions is commonly found within species, but whether it involves the same intraspecific genomic variants is unknown. We studied this question in North American Arabidopsis lyrata, whose current distribution is shaped by post‐glacial range expansion from two refugia, resulting in two distinct genetic clusters covering comparable climatic gradients. Using pooled whole‐genome sequence data of 41 outcrossing populations, we identified loci associated with three niche‐determining climatic variables in the two clusters and compared these outliers. Little evidence was found for parallelism in climate adaptation for single nucleotide polymorphisms (SNPs) and for genes with an accumulation of outlier SNPs. Significantly increased selection coefficients supported them as candidates of climate adaptation. However, the fraction of gene ontology (GO) terms shared between clusters was higher compared to outlier SNPs and outlier genes, suggesting that selection acts on similar pathways but not necessarily the same genes. Enriched GO terms involved responses to abiotic and biotic stress, circadian rhythm and development, with flower development and reproduction being among the most frequently detected. In line with GO enrichment, regulators of flowering time were detected as outlier genes. Our results suggest that while adaptation to environmental gradients on the genomic level are lineage‐specific in A. lyrata, similar biological processes seem to be involved. Differential loss of standing genetic variation, probably driven by genetic drift, can in part account for the lack of parallel evolution on the genomic level.     

Adaptive divergence along environmental gradients in a climate‐change‐sensitive mammal

In the face of predicted climate change, a broader understanding of biotic responses to varying environments has become increasingly important within the context of biodiversity conservation. Local adaptation is one potential option, yet remarkably few studies have harnessed genomic tools to evaluate the efficacy of this response within natural populations. Here, we show evidence of selection driving divergence of a climate‐change‐sensitive mammal, the American pika (Ochotona princeps), distributed along elevation gradients at its northern range margin in the Coast Mountains of British Columbia (BC), Canada. We employed amplified‐fragment‐length‐polymorphism‐based genomic scans to conduct genomewide searches for candidate loci among populations inhabiting varying environments from sea level to 1500 m. Using several independent approaches to outlier locus detection, we identified 68 candidate loci putatively under selection (out of a total 1509 screened), 15 of which displayed significant associations with environmental variables including annual precipitation and maximum summer temperature. These candidate loci may represent important targets for predicting pika responses to climate change and informing novel approaches to wildlife conservation in a changing world.