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.     

Water availability drives signatures of local adaptation in whitebark pine (Pinus albicaulis Engelm.) across fine spatial scales of the Lake Tahoe Basin,USA

Patterns of local adaptation at fine spatial scales are central to understanding how evolution proceeds, and are essential to the effective management of economically and ecologically important forest tree species. Here, we employ single and multilocus analyses of genetic data (n = 116 231 SNPs) to describe signatures of fine‐scale adaptation within eight whitebark pine (Pinus albicaulis Engelm.) populations across the local extent of the environmentally heterogeneous Lake Tahoe Basin, USA. We show that despite highly shared genetic variation (F_ST = 0.0069), there is strong evidence for adaptation to the rain shadow experienced across the eastern Sierra Nevada. Specifically, we build upon evidence from a common garden study and find that allele frequencies of loci associated with four phenotypes (mean = 236 SNPs), 18 environmental variables (mean = 99 SNPs), and those detected through genetic differentiation (n = 110 SNPs) exhibit significantly higher signals of selection (covariance of allele frequencies) than could be expected to arise, given the data. We also provide evidence that this covariance tracks environmental measures related to soil water availability through subtle allele frequency shifts across populations. Our results replicate empirical support for theoretical expectations of local adaptation for populations exhibiting strong gene flow and high selective pressures and suggest that ongoing adaptation of many P. albicaulis populations within the Lake Tahoe Basin will not be constrained by the lack of genetic variation. Even so, some populations exhibit low levels of heritability for the traits presumed to be related to fitness. These instances could be used to prioritize management to maintain adaptive potential. Overall, we suggest that established practices regarding whitebark pine conservation be maintained, with the additional context of fine‐scale adaptation.     

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.     

The potential for arms race and Red Queen coevolution in a protist host–parasite system

The dynamics and consequences of host–parasite coevolution depend on the nature of host genotype‐by‐parasite genotype interactions (G × G) for host and parasite fitness. G × G with crossing reaction norms can yield cyclic dynamics of allele frequencies (“Red Queen” dynamics) while G × G where the variance among host genotypes differs between parasite genotypes results in selective sweeps (“arms race” dynamics). Here, we investigate the relative potential for arms race and Red Queen coevolution in a protist host–parasite system, the dinoflagellate Alexandrium minutum and its parasite Parvilucifera sinerae. We challenged nine different clones of A. minutum with 10 clones of P. sinerae in a fully factorial design and measured infection success and host and parasite fitness. Each host genotype was successfully infected by four to ten of the parasite genotypes. There were strong G × Gs for infection success, as well as both host and parasite fitness. About three quarters of the G × G variance components for host and parasite fitness were due to crossing reaction norms. There were no general costs of resistance or infectivity. We conclude that there is high potential for Red Queen dynamics in this host–parasite system.     

Detecting adaptive evolution based on association with ecological gradients: Orientation matters!

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.     

The genetic consequences of spatially varying selection in the panmictic American eel (Anguilla rostrata)

Our understanding of the genetic basis of local adaptation has recently benefited from the increased power to identify functional variants associated with environmental variables at the genome scale. However, it often remains challenging to determine whether locally adaptive alleles are actively maintained at intermediate frequencies by spatially varying selection. Here, we evaluate the extent to which this particular type of balancing selection explains the retention of adaptive genetic variation in the extreme situation of perfect panmixia, using the American eel (Anguilla rostrata) as a model. We first conducted a genome scan between two samples from opposite ends of a latitudinal environmental gradient using 454 sequencing of individually tagged cDNA libraries. Candidate SNPs were then genotyped in 992 individuals from 16 sampling sites at different life stages of the same cohort (including larvae from the Sargasso Sea, glass eels, and 1-year-old individuals) as well as in glass eels of the following cohort. Evidence for spatially varying selection was found at 13 loci showing correlations between allele frequencies and environmental variables across the entire species range. Simulations under a multiple-niche Levene's model using estimated relative fitness values among genotypes rarely predicted a stable polymorphic equilibrium at these loci. Our results suggest that some genetic-by-environment interactions detected in our study arise during the progress toward fixation of a globally advantageous allele with spatially variable effects on fitness.     

Is local adaptation in Mimulus guttatus caused by trade‐offs at individual loci?

Local adaptation is considered to be the result of fitness trade‐offs for particular phenotypes across different habitats. However, it is unclear whether such phenotypic trade‐offs exist at the level of individual genetic loci. Local adaptation could arise from trade‐offs of alternative alleles at individual loci or by complementary sets of loci with different fitness effects of alleles in one habitat but selective neutrality in the alternative habitat. To evaluate the genome‐wide basis of local adaptation, we performed a field‐based quantitative trait locus (QTL) mapping experiment on recombinant inbred lines (RILs) created from coastal perennial and inland annual races of the yellow monkeyflower (Mimulus guttatus) grown reciprocally in native parental habitats. Overall, we detected 19 QTLs affecting one or more of 16 traits measured in two environments, most of small effect. We identified 15 additional QTL effects at two previously identified candidate QTLs [DIV ERGENCE (DIV)]. Significant QTL by environment interactions were detected at the DIV loci, which was largely attributable to genotypic differences at a single field site. We found no detectable evidence for trade‐offs for any one component of fitness, although DIV2 showed a trade‐off involving different fitness traits between sites, suggesting that local adaptation is largely controlled by non‐overlapping loci. This is surprising for an outcrosser, implying that reduced gene flow prevents the evolution of individuals adapted to multiple environments. We also determined that native genotypes were not uniformly adaptive, possibly reflecting fixed mutational load in one of the populations.     

Finding needles in a genomic haystack: targeted capture identifies clear signatures of selection in a nonmodel plant species

Teasing apart neutral and adaptive genomic processes and identifying loci that are targets of selection can be difficult, particularly for nonmodel species that lack a reference genome. However, identifying such loci and the factors driving selection have the potential to greatly assist conservation and restoration practices, especially for the management of species in the face of contemporary and future climate change. Here, we focus on assessing adaptive genomic variation within a nonmodel plant species, the narrow‐leaf hopbush (Dodonaea viscosa ssp. angustissima), commonly used for restoration in Australia. We used a hybrid‐capture target enrichment approach to selectively sequence 970 genes across 17 populations along a latitudinal gradient from 30°S to 36°S. We analysed 8462 single‐nucleotide polymorphisms (SNPs) for F_ST outliers as well as associations with environmental variables. Using three different methods, we found 55 SNPs with significant correlations to temperature and water availability, and 38 SNPs to elevation. Genes containing SNPs identified as under environmental selection were diverse, including aquaporin and abscisic acid genes, as well as genes with ontologies relating to responses to environmental stressors such as water deprivation and salt stress. Redundancy analysis demonstrated that only a small proportion of the total genetic variance was explained by environmental variables. We demonstrate that selection has led to clines in allele frequencies in a number of functional genes, including those linked to leaf shape and stomatal variation, which have been previously observed to vary along the sampled environmental cline. Using our approach, gene regions subject to environmental selection can be readily identified for nonmodel organisms.     

Genomewide scan for adaptive differentiation along altitudinal gradient in the Andrew's toad Bufo andrewsi

Recent studies of humans, dogs and rodents have started to discover the genetic underpinnings of high altitude adaptations, yet amphibians have received little attention in this respect. To identify possible signatures of adaptation to altitude, we performed a genome scan of 15 557 single nucleotide polymorphisms (SNPs) obtained with restriction site‐associated DNA sequencing of pooled samples from 11 populations of Andrew's toad (Bufo andrewsi) from the edge of the Tibetan Plateau, spanning an altitudinal gradient from 1690 to 2768 m.a.s.l. We discovered significant geographic differentiation among all sites, with an average F_ST = 0.023 across all SNPs. Apart from clear patterns of isolation by distance, we discovered numerous outlier SNPs showing strong associations with variation in altitude (1394 SNPs), average annual temperature (1859 SNPs) or both (1051 SNPs). Levels and patterns of genetic differentiation in these SNPs were consistent with the hypothesis that they have been subject to directional selection and reflect adaptation to altitudinal variation among the study sites. Genes with footprints of selection were significantly enriched in binding and metabolic processes. Several genes potentially related to high altitude adaptation were identified, although the identity and functional significance of most genomic targets of selection remain unknown. In general, the results provide genomic support for results of earlier common garden and low coverage genetic studies that have uncovered substantial adaptive differentiation along altitudinal and latitudinal gradients in amphibians.     

Genetic by environment interactions affect plant–soil linkages

The role of plant intraspecific variation in plant–soil linkages is poorly understood, especially in the context of natural environmental variation, but has important implications in evolutionary ecology. We utilized three 18‐ to 21‐year‐old common gardens across an elevational gradient, planted with replicates of five Populus angustifolia genotypes each, to address the hypothesis that tree genotype (G), environment (E), and G × E interactions would affect soil carbon and nitrogen dynamics beneath individual trees. We found that soil nitrogen and carbon varied by over 50% and 62%, respectively, across all common garden environments. We found that plant leaf litter (but not root) traits vary by genotype and environment while soil nutrient pools demonstrated genotype, environment, and sometimes G × E interactions, while process rates (net N mineralization and net nitrification) demonstrated G × E interactions. Plasticity in tree growth and litter chemistry was significantly related to the variation in soil nutrient pools and processes across environments, reflecting tight plant–soil linkages. These data overall suggest that plant genetic variation can have differential affects on carbon storage and nitrogen cycling, with implications for understanding the role of genetic variation in plant–soil feedback as well as management plans for conservation and restoration of forest habitats with a changing climate.     

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.     

Evolutionary mismatch along salinity gradients in a Neotropical water strider

The evolution of local adaptation is crucial for the in situ persistence of populations in changing environments. However, selection along broad environmental gradients could render local adaptation difficult, and might even result in maladaptation. We address this issue by quantifying fitness trade‐offs (via common garden experiments) along a salinity gradient in two populations of the Neotropical water strider Telmatometra withei—a species found in both fresh (FW) and brackish (BW) water environments across Panama. We found evidence for local adaptation in the FW population in its home FW environment. However, the BW population showed only partial adaptation to the BW environment, with a high magnitude of maladaptation along naturally occurring salinity gradients. Indeed, its overall fitness was ~60% lower than that of the ancestral FW population in its home environment, highlighting the role of phenotypic plasticity, rather than local adaptation, in high salinity environments. This suggests that populations seemingly persisting in high salinity environments might in fact be maladapted, following drastic changes in salinity. Thus, variable selection imposed by salinization could result in evolutionary mismatch, where the fitness of a population is displaced from its optimal environment. Understanding the fitness consequences of persisting in fluctuating salinity environments is crucial to predict the persistence of populations facing increasing salinization. It will also help develop evolutionarily informed management strategies in the context of global change.     

Local adaptation and ecological differentiation under selection,migration, and drift in Arabidopsis lyrata*

How the balance between selection, migration, and drift influences the evolution of local adaptation has been under intense theoretical scrutiny. Yet, empirical studies that relate estimates of local adaptation to quantification of gene flow and effective population sizes have been rare. Here, we conducted a reciprocal transplant trial, a common garden trial, and a whole‐genome‐based demography analysis to examine these effects among Arabidopsis lyrata populations from two altitudinal gradients in Norway. Demography simulations indicated that populations within the two gradients are connected by gene flow (0.1 < 4N_em < 11) and have small effective population sizes (N_e < 6000), suggesting that both migration and drift can counteract local selection. However, the three‐year field experiments showed evidence of local adaptation at the level of hierarchical multiyear fitness, attesting to the strength of differential selection. In the lowland habitat, local superiority was associated with greater fecundity, while viability accounted for fitness differences in the alpine habitat. We also demonstrate that flowering time differentiation has contributed to adaptive divergence between these locally adapted populations. Our results show that despite the estimated potential of gene flow and drift to hinder differentiation, selection among these A. lyrata populations has resulted in local adaptation.     

Genome-wide association mapping of canopy wilting in diverse soybean genotypes

Key message

Genome-wide association analysis identified 61 SNP markers for canopy wilting, which likely tagged 51 different loci. Based on the allelic effects of the significant SNPs, the slowest and fastest wilting genotypes were identified.

Abstract

Drought stress is a major global constraint for crop production, and slow canopy wilting is a promising trait for improving drought tolerance. The objective of this study was to identify genetic loci associated with canopy wilting and to confirm those loci with previously reported canopy wilting QTLs. A panel of 373 maturity group (MG) IV soybean genotypes was grown in four environments to evaluate canopy wilting. Statistical analysis of phenotype indicated wide variation for the trait, with significant effects of genotype (G), environment (E), and G × E interaction. Over 42,000 SNP markers were obtained from the Illumina Infinium SoySNP50K iSelect SNP Beadchip. After filtration for quality control, 31,260 SNPs with a minor allele frequency (MAF) ≥5% were used for association mapping using the Fixed and random model Circulating Probability Unification (FarmCPU) model. There were 61 environment-specific significant SNP-canopy wilting associations, and 21 SNPs that associated with canopy wilting in more than one environment. There were 34 significant SNPs associated with canopy wilting when averaged across environments. Together, these SNPs tagged 23 putative loci associated with canopy wilting. Six of the putative loci were located within previously reported chromosomal regions that were associated with canopy wilting through bi-parental mapping. Several significant SNPs were located within a gene or very close to genes that had a reported biological connection to transpiration or water transport. Favorable alleles from significant SNPs may be an important resource for pyramiding genes to improve drought tolerance and for identifying parental genotypes for use in breeding programs.

     

Genotype‐by‐genotype specificity remains robust to average temperature variation in an aphid/endosymbiont/parasitoid system

Genotype‐by‐genotype interactions demonstrate the existence of variation upon which selection acts in host–parasite systems at respective resistance and infection loci. These interactions can potentially be modified by environmental factors, which would entail that different genotypes are selected under different environmental conditions. In the current study, we checked for a G × G × E interaction in the context of average temperature and the genotypes of asexual lines of the endoparasitoid wasp Lysiphlebus fabarum and isolates of Hamiltonella defensa, a protective secondary endosymbiont of the wasp's host, the black bean aphid Aphis fabae. We exposed genetically identical aphids harbouring different isolates of H. defensa to three asexual lines of the parasitoid and measured parasitism success under three different temperatures (15, 22 and 29 °C). Although there was clear evidence for increased susceptibility to parasitoids at the highest average temperature and a strong G × G interaction between the host's symbionts and the parasitoids, no modifying effect of temperature, that is, no significant G × G × E interaction, was detected. This robustness of the observed specificity suggests that the relative fitness of different parasitoid genotypes on hosts protected by particular symbionts remains uncomplicated by spatial or temporal variation in temperature, which should facilitate biological control strategies.     

Identification of loci governing eight agronomic traits using a GBS‐GWAS approach and validation by QTL mapping in soya bean

Soya bean is a major source of edible oil and protein for human consumption as well as animal feed. Understanding the genetic basis of different traits in soya bean will provide important insights for improving breeding strategies for this crop. A genome‐wide association study (GWAS) was conducted to accelerate molecular breeding for the improvement of agronomic traits in soya bean. A genotyping‐by‐sequencing (GBS) approach was used to provide dense genome‐wide marker coverage (>47 000 SNPs) for a panel of 304 short‐season soya bean lines. A subset of 139 lines, representative of the diversity among these, was characterized phenotypically for eight traits under six environments (3 sites × 2 years). Marker coverage proved sufficient to ensure highly significant associations between the genes known to control simple traits (flower, hilum and pubescence colour) and flanking SNPs. Between one and eight genomic loci associated with more complex traits (maturity, plant height, seed weight, seed oil and protein) were also identified. Importantly, most of these GWAS loci were located within genomic regions identified by previously reported quantitative trait locus (QTL) for these traits. In some cases, the reported QTLs were also successfully validated by additional QTL mapping in a biparental population. This study demonstrates that integrating GBS and GWAS can be used as a powerful complementary approach to classical biparental mapping for dissecting complex traits in soya bean.     

Detecting small-scale genotype-environment interactions in apomictic dandelion (Taraxacum officinale) populations

Studies of genotype × environment interactions (G × E) and local adaptation provide critical tests of natural selection’s ability to counter opposing forces such as gene flow. Such studies may be greatly facilitated in asexual species, given the possibility for experimental replication at the level of true genotypes (rather than populations) and the possibility of using molecular markers to assess genotype–environment associations in the field (neither of which is possible for most sexual species). Here, we tested for G × E in asexual dandelions (Taraxacum officinale) by subjecting six genotypes to experimental drought, mown and benign (control) conditions and subsequently using microsatellites to assess genotype–environment associations in the field. We found strong G × E, with genotypes that performed poorly under benign conditions showing the highest performance under stressful conditions (drought or mown). Our six focal genotypes comprise > 80% of plants in local populations. The most common genotype in the field showed its highest relative performance under mown conditions (the most common habitat in our study area), and almost all plants of this genotype in the field were found growing in mowed lawns. Genotypes performing best under benign experimental conditions were found most frequently in unmown conditions in the field. These results are strongly indicative of local adaptation at a very small scale, with unmown microsites of only a few square metres typically embedded within larger mown lawns. By studying an asexual species, we were able to map genotypes with known ecological characteristics to environments with high spatial precision.     

Signatures of local adaptation in lowland and highland teosintes from whole‐genome sequencing of pooled samples

Spatially varying selection triggers differential adaptation of local populations. Here, we mined the determinants of local adaptation at the genomewide scale in the two closest maize wild relatives, the teosintes Zea mays ssp parviglumis and ssp. mexicana. We sequenced 120 individuals from six populations: two lowland, two intermediate and two highland populations sampled along two altitudinal gradients. We detected 8 479 581 single nucleotide polymorphisms (SNPs) covered in the six populations with an average sequencing depth per site per population ranging from 17.0× to 32.2×. Population diversity varied from 0.10 to 0.15, and linkage disequilibrium decayed very rapidly. We combined two differentiation‐based methods, and correlation of allele frequencies with environmental variables to detect outlier SNPs. Outlier SNPs displayed significant clustering. From clusters, we identified 47 candidate regions. We further modified a haplotype‐based method to incorporate genotype uncertainties in haplotype calling, and applied it to candidate regions. We retrieved evidence for selection at the haplotype level in 53% of our candidate regions, and in 70% of the cases the same haplotype was selected in the two lowland or the two highland populations. We recovered a candidate region located within a previously characterized inversion on chromosome 1. We found evidence of a soft sweep at a locus involved in leaf macrohair variation. Finally, our results revealed frequent colocalization between our candidate regions and loci involved in the variation of traits associated with plant–soil interactions such as root morphology, aluminium and low phosphorus tolerance. Soil therefore appears to be a major driver of local adaptation in teosintes.     

Contrasting patterns of local adaptation along climatic gradients between a sympatric parasitic and autotrophic tree species

Sympatric tree species are subject to similar climatic drivers, posing a question as to whether they display comparable adaptive responses. However, no study has explicitly examined local adaptation of co‐occurring parasitic and autotrophic plant species to the abiotic environment. Here we test the hypotheses that a generalist parasitic tree would display a weaker signal of selection and that genomic variation would associate with fewer climatic variables (particularly precipitation) but have similar spatial patterns to a sympatric autotrophic tree species. To test these hypotheses, we collected samples from 17 sites across the range of two tree species, the hemiparasite Nuytsia floribunda (n = 264) and sympatric autotroph Melaleuca rhaphiophylla (n = 272). We obtained 5,531 high‐quality genome‐wide single nucleotide polymorphisms (SNPs) for M. rhaphiophylla and 6,727 SNPs for N. floribunda using DArTseq genome scan technology. Population differentiation and environmental association approaches were used to identify signals of selection. Generalized dissimilarly modelling was used to detect climatic and spatial patterns of local adaptation across climatic gradients. Overall, 322 SNPs were identified as putatively adaptive for the autotroph, while only 57 SNPs were identified for the parasitic species. We found genomic variation to associate with different sets of bioclimatic variables for each species, with precipitation relatively less important for the parasite. Spatial patterns of predicted adaptive variability were different and indicate that co‐occurring species with disparate life history traits may not respond equally to selective pressures (i.e., temperature and precipitation). Together, these findings provide insight into local adaptation of sympatric parasitic and autotrophic tree species to abiotic environments.