Genomic insights into hybrid zone formation: The role of climate, landscape, and demography in the emergence of a novel hybrid lineage.

Population demographic changes, alongside landscape, geographic and climate heterogeneity, can influence the timing, stability and extent of introgression where species hybridise. Thus, quantifying interactions across diverged lineages, and the relative contributions of interspecific genetic exchange and selection to divergence at the genome-wide level is needed to better understand the drivers of hybrid zone formation and maintenance. We used seven latitudinally arrayed transects to quantify the contributions of climate, geography and landscape features to broad patterns of genetic structure across the hybrid zone of Populus trichocarpa and P. balsamifera and evaluated the demographic context of hybridisation over time. We found genetic structure differed among the seven transects. While ancestry was structured by climate, landscape features influenced gene flow dynamics. Demographic models indicated a secondary contact event may have influenced contemporary hybrid zone formation with the origin of a putative hybrid lineage that inhabits regions with higher aridity than either of the ancestral groups. Phylogenetic relationships based on chloroplast genomes support the origin of this hybrid lineage inferred from demographic models based on the nuclear data. Our results point towards the importance of climate and landscape patterns in structuring the contact zones between P. trichocarpa and P. balsamifera and emphasise the value whole genome sequencing can have to advancing our understanding of how neutral processes influence divergence across space and time.

From common gardens to candidate genes: exploring local adaptation to climate in red spruce.

Local adaptation to climate is common in plant species and has been studied in a range of contexts, from improving crop yields to predicting population maladaptation to future conditions. The genomic era has brought new tools to study this process, which was historically explored through common garden experiments. In this study, we combine genomic methods and common gardens to investigate local adaptation in red spruce and identify environmental gradients and loci involved in climate adaptation. We first use climate transfer functions to estimate the impact of climate change on seedling performance in three common gardens. We then explore the use of multivariate gene-environment association methods to identify genes underlying climate adaptation, with particular attention to the implications of conducting genome scans with and without correction for neutral population structure. This integrative approach uncovered phenotypic evidence of local adaptation to climate and identified a set of putatively adaptive genes, some of which are involved in three main adaptive pathways found in other temperate and boreal coniferous species: drought tolerance, cold hardiness, and phenology. These putatively adaptive genes segregated into two 'modules' associated with different environmental gradients. This study nicely exemplifies the multivariate dimension of adaptation to climate in trees.

Headwater Stream Microbial Diversity and Function across Agricultural and Urban Land Use Gradients.

Anthropogenic activity impacts stream ecosystems, resulting in a loss of diversity and ecosystem function; however, little is known about the response of aquatic microbial communities to changes in land use. Here, microbial communities were characterized in 82 headwater streams across a gradient of urban and agricultural land uses using 16S rRNA gene amplicon sequencing and compared to a rich data set of physicochemical variables and traditional benthic invertebrate indicators. Microbial diversity and community structures differed among watersheds with high agricultural, urban, and forested land uses, and community structure differed in streams classified as being in good, fair, poor, and very poor condition using benthic invertebrate indicators. Microbial community similarity decayed with geodesic distance across the study region but not with environmental distance. Stream community respiration rates ranged from 21.7 to 1,570 mg O2 m-2 day-1 and 31.9 to 3,670 mg O2 m-2 day-1 for water column and sediments, respectively, and correlated with nutrients associated with anthropogenic influence and microbial community structure. Nitrous oxide (N2O) concentrations ranged from 0.22 to 4.41 µg N2O liter-1; N2O concentration was negatively correlated with forested land use and was positively correlated with dissolved inorganic nitrogen concentrations. Our findings suggest that stream microbial communities are impacted by watershed land use and can potentially be used to assess ecosystem health.IMPORTANCE Stream ecosystems are frequently impacted by changes in watershed land use, resulting in altered hydrology, increased pollutant and nutrient loads, and habitat degradation. Macroinvertebrates and fish are strongly affected by changes in stream conditions and are commonly used in biotic indices to assess ecosystem health. Similarly, microbes respond to environmental stressors, and changes in community composition alter key ecosystem processes. The response of microbes to habitat degradation and their role in global biogeochemical cycles provide an opportunity to use microbes as a monitoring tool. Here, we identify stream microbes that respond to watershed urbanization and agricultural development and demonstrate that microbial diversity and community structure can be used to assess stream conditions and ecosystem functioning.

Latitudinal clines in bud flush phenology reflect genetic variation in chilling requirements in balsam poplar, Populus balsamifera.

PREMISE: Boreal and northern temperate forest trees possess finely tuned mechanisms of dormancy, which match bud phenology with local seasonality. After winter dormancy, the accumulation of chilling degree days (CDD) required for rest completion before the accumulation of growing degree days (GDD) during quiescence is an important step in the transition to spring bud flush. While bud flush timing is known to be genetically variable within species, few studies have investigated variation among genotypes from different climates in response to variable chilling duration. METHODS: We performed a controlled environment study using dormant cuttings from 10 genotypes of Populus balsamifera, representing a broad latitudinal gradient (43-58°N). We exposed cuttings to varying amounts of chilling (0-10 weeks) and monitored subsequent GDD to bud flush at a constant forcing temperature. RESULTS: Chilling duration strongly accelerated bud flush timing, with increasing CDD resulting in fewer GDD to flush. Genotypic variation for bud flush was significant and stratified by latitude, with southern genotypes requiring more GDD to flush than northern genotypes. The latitudinal cline was pronounced under minimal chilling, whereas genotypic variation in GDD to bud flush converged as CDD increased. CONCLUSIONS: We demonstrate that increased chilling lessens GDD to bud flush in a genotype-specific manner. Our results emphasize that latitudinal clines in bud flush reflect a critical genotype-by-environment interaction, whereby differences in bud flush between southern vs. northern genotypes depend on chilling. Our results suggest selection has shaped chilling requirements and depth of rest as an adaptive strategy to avoid precocious flush in climates with midwinter warming.

StomataCounter: a neural network for automatic stomata identification and counting.

Stomata regulate important physiological processes in plants and are often phenotyped by researchers in diverse fields of plant biology. Currently, there are no user-friendly, fully automated methods to perform the task of identifying and counting stomata, and stomata density is generally estimated by manually counting stomata. We introduce StomataCounter, an automated stomata counting system using a deep convolutional neural network to identify stomata in a variety of different microscopic images. We use a human-in-the-loop approach to train and refine a neural network on a taxonomically diverse collection of microscopic images. Our network achieves 98.1% identification accuracy on Ginkgo scanning electron microscropy micrographs, and 94.2% transfer accuracy when tested on untrained species. To facilitate adoption of the method, we provide the method in a publicly available website at http://www.stomata.science/.

Adaptive introgression and maintenance of a trispecies hybrid complex in range-edge populations of Populus.

In hybrid zones occurring in marginal environments, adaptive introgression from one species into the genomic background of another may constitute a mechanism facilitating adaptation at range limits. Although recent studies have improved our understanding of adaptive introgression in widely distributed tree species, little is known about the dynamics of this process in populations at the margins of species ranges. We investigated the extent of introgression between three species of the genus Populus sect. Tacamahaca (P. balsamifera, P. angustifolia and P. trichocarpa) at the margins of their distributions in the Rocky Mountain region of the United States and Canada. Using genotyping by sequencing (GBS), we analysed ~ 83,000 single nucleotide polymorphisms genotyped in 296 individuals from 29 allopatric and sympatric populations of the three species. We found a trispecies hybrid complex present throughout the zone of range overlap, including early as well as advanced generation backcross hybrids, indicating recurrent gene flow in this hybrid complex. Using genomic cline analysis, we found evidence of non-neutral patterns of introgression at 23% of loci in hybrids, of which 47% and 8% represented excess ancestry from P. angustifolia and P. balsamifera, respectively. Gene ontology analysis suggested these genomic regions were enriched for genes associated with photoperiodic regulation, metal ion transport, maintenance of redox homeostasis and cell wall metabolites involved in regulation of seasonal dormancy. Our study demonstrates the role of adaptive introgression in a multispecies hybrid complex in range-edge populations and has implications for understanding the evolutionary dynamics of adaptation in hybrid zones, especially at the margins of species distributions.

Genomic Admixture Between Locally Adapted Populations of Arabidopsis thaliana (mouse ear cress): Evidence of Optimal Genetic Outcrossing Distance.

Admixture can break up divergent genetic architectures between populations, resulting in phenotypic novelty and generating raw material for environmental selection. The contribution of admixture to progeny trait variation and fitness varies based on the degree of genetic isolation between the parental populations, for which most studies have used geographic distance as a proxy. A novel approach is to estimate optimal crossing distance using the adaptive genetic distance between mates estimated from loci that contribute directly to local adaptation. Here, we aim to understand the effect of admixture on disrupting local adaptation of ecotypes of Arabidopsis thaliana separated along gradients of geographic, background, and locally adaptive genetic distances. We created experimental F1 hybrids between ecotypes that vary in geographic distance and used SNP data to estimate background (putatively neutral) and adaptive genetic distance. Hybrids were grown under controlled conditions, and fitness, growth, and phenology traits were measured. The different traits measured showed a clear effect of adaptive genetic distance, but not geographic distance. The earliest bolting hybrids were intermediate in the adaptive genetic distance between their parents, and also had higher biomass and fitness in terms of fruit and seed production. Our results suggest that disruption of locally adaptive genomic loci decreases the performance of offspring between distantly related parents, but that crosses between very closely related parents also reduce performance, likely through the expression of deleterious recessive alleles. We conclude that during admixture, selection may have to balance the consequences of disrupting local adaption while also avoiding inbreeding depression.

Influence of Range Position on Locally Adaptive Gene-Environment Associations in Populus Flowering Time Genes.

Local adaptation is pervasive in forest trees, which are characterized by large effective population sizes spanning broad climatic gradients. In addition to having relatively contiguous populations, many species also form isolated populations along the rear edge of their range. These rear-edge populations may contain unique adaptive diversity reflecting a history of selection in marginal environments. Thus, discovering genomic regions conferring local adaptation in rear edge populations is a key priority for landscape genomics to ensure conservation of genetic resources under climate change. Here, we report on adaptive gene-environment associations in single nucleotide polymorphisms (SNPs) from 27 genes in the Populus flowering time gene network, analyzed on a range-wide collection of >1000 balsam poplar trees, including dense sampling of the southern range edge. We use a combined approach of local adaptation scans to identify candidate SNPs, followed by modeling the compositional turnover of adaptive SNPs along multivariate climate gradients using gradient forests (GF). Flowering time candidate genes contained extensive evidence of climate adaptation, namely outlier population structure and gene-environment associations, along with allele frequency divergence between the core and edge of the range. GF showed strong allele frequency turnover along gradients of elevation and diurnal and temperature variability, as well as threshold responses to summer temperature and precipitation, with turnover especially strong in edge populations that occur at high elevation but southerly latitudes. We discuss these results in light of how climate may disrupt locally adaptive gene-environment relationships, and suggest that rear edge populations hold climate-adaptive variants that should be targeted for conservation.

Geographic origins and population genetics of bats killed at wind-energy facilities.

An unanticipated impact of wind-energy development has been large-scale mortality of insectivorous bats. In eastern North America, where mortality rates are among the highest in the world, the hoary bat (Lasiurus cinereus) and the eastern red bat (L. borealis) comprise the majority of turbine-associated bat mortality. Both species are migratory tree bats with widespread distributions; however, little is known regarding the geographic origins of bats killed at wind-energy facilities or the diversity and population structure of affected species. We addressed these unknowns by measuring stable hydrogen isotope ratios (δ2 H) and conducting population genetic analyses of bats killed at wind-energy facilities in the central Appalachian Mountains (USA) to determine the summering origins, effective size, structure, and temporal stability of populations. Our results indicate that ~1% of hoary bat mortalities and ~57% of red bat mortalities derive from non-local sources, with no relationship between the proportion of non-local bats and sex, location of mortality, or month of mortality. Additionally, our data indicate that hoary bats in our sample consist of an unstructured population with a small effective size (Ne ) and either a stable or declining history. Red bats also showed no evidence of population genetic structure, but in contrast to hoary bats, the diversity contained in our red bat samples is consistent with a much larger Ne that reflects a demographic expansion after a bottleneck. These results suggest that the impacts of mortality associated with intensive wind-energy development may affect bat species dissimilarly, with red bats potentially better able to absorb sustained mortality than hoary bats because of their larger Ne . Our results provide important baseline data and also illustrate the utility of stable isotopes and population genetics for monitoring bat populations affected by wind-energy development.

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.

Local adaptation in the flowering-time gene network of balsam poplar, Populus balsamifera L.

Identifying the signature and targets of local adaptation is an increasingly important goal in empirical population genetics. Using data from 443 balsam poplar Populus balsamifera trees sampled from 31 populations, we tested for evidence of geographically variable selection shaping diversity at 27 homologues of the Arabidopsis flowering-time network. These genes are implicated in the control of seasonal phenology, an important determinant of fitness. Using 335 candidate and 412 reference single nucleotide polymorphisms (SNPs), we tested for evidence of local adaptation by searching for elevated population differentiation using F(ST)-based outlier analyses implemented in BayeScan or a Hierarchical Model in Arelquin and by testing for significant associations between allele frequency and environmental variables using BAYENV. A total of 46 SNPs from 14 candidate genes had signatures of local adaptation-either significantly greater population differentiation or significant covariance with one or more environmental variable relative to reference SNP distributions. Only 11 SNPs from two genes exhibited both elevated population differentiation and covariance with one or more environmental variables. Several genes including the abscisic acid gene ABI1B and the circadian clock genes ELF3 and GI5 harbored a large number of SNPs with signatures of local adaptation-with SNPs in GI5 strongly covarying with both latitude and precipitation and SNPs in ABI1B strongly covarying with temperature. In contrast to several other systems, we find little evidence that photoreceptors, including phytochromes, play an important role in local adaptation. Our results additionally show that detecting local adaptation is sensitive to the analytical approaches used and that model-based significance thresholds should be viewed with caution.

The adaptive potential of Populus balsamifera L. to phenology requirements in a warmer global climate.

The manner in which organisms adapt to climate change informs a broader understanding of the evolution of biodiversity as well as conservation and mitigation plans. We apply common garden and association mapping approaches to quantify genetic variance and identify loci affecting bud flush and bud set, traits that define a tree's season for height growth, in the boreal forest tree Populus balsamifera L. (balsam poplar). Using data from 478 genotypes grown in each of two common gardens, one near the southern edge and another near the northern edge of P. balsamifera's range, we found that broad-sense heritability for bud flush and bud set was generally high (H(2) > 0.5 in most cases), suggesting that abundant genetic variation exists for phenological response to changes in the length of the growing season. To identify the molecular genetic basis of this variation, we genotyped trees for 346 candidate single nucleotide polymorphisms (SNPs) from 27 candidate genes for the CO/FT pathway in poplar. Mixed-model analyses of variance identified SNPs in 10 genes to be associated with variation in either bud flush or bud set. Multiple SNPs within FRIGIDA were associated with bud flush, whereas multiple SNPs in LEAFY and GIGANTEA 5 were associated with bud set. Although there was strong population structure in stem phenology, the geographic distribution of multilocus association SNP genotypes was widespread except at the most northern populations, indicating that geographic regions may harbour sufficient diversity in functional genes to facilitate adaption to future climatic conditions in many sites.

Admixture mapping and selection scans identify genomic regions associated with stomatal patterning and disease resistance in hybrid poplars.

Variation in fitness components can be linked in some cases to variation in key traits. Metric traits that lie at the intersection of development, defense, and ecological interactions may be expected to experience environmental selection, informing our understanding of evolutionary and ecological processes. Here, we use quantitative genetic and population genomic methods to investigate disease dynamics in hybrid and non-hybrid populations. We focus our investigation on morphological and ecophysiological traits which inform our understanding of physiology, growth, and defense against a pathogen. In particular, we investigate stomata, microscopic pores on the surface of a leaf that regulate gas exchange during photosynthesis and are sites of entry for various plant pathogens. Stomatal patterning traits were highly predictive of disease risk. Admixture mapping identified a polygenic basis of disease resistance. Candidate genes for stomatal and disease resistance map to the same genomic regions and experienced positive selection. Genes with functions to guard cell homeostasis, the plant immune system, components of constitutive defenses, and growth-related transcription factors were identified. Our results indicate positive selection acted on candidate genes for stomatal patterning and disease resistance, potentially acting in concert to structure their variation in naturally formed backcrossing hybrid populations.

Bayesian inference of a complex invasion history revealed by nuclear and chloroplast genetic diversity in the colonizing plant, Silene latifolia.

Species invading new ranges are subject to a series of demographic events that can strongly shape genetic diversity. Describing this demographic history is important for understanding where invasive species come from and how they spread, and is critical to testing hypotheses of postinvasion adaptation. Here, we analyse nuclear and chloroplast genetic diversity to study the invasion history of the widespread colonizing weed, Silene latifolia (Caryophyllaceae). Bayesian clustering and PCA revealed strong population structure in the native range of Europe, and although genotypes from multiple native sources were present in the introduced range of North America, the spatial distribution of genetic variance was dramatically reorganized. Using approximate Bayesian computation (ABC), we compared support for different invasion scenarios, including the number and size of independent introduction events and the amount of admixture occurring between sources of introduced genotypes. Our results supported independent introductions into eastern and western North America, with the latter forming a bridgehead for a secondary invasion into the Great Lakes region of central North America. Despite small estimated founder population sizes, the duration of the demographic bottleneck after the initial introduction appeared extremely short-lived. This pattern of repeated colonization and rapid expansion has effectively eroded the strong population structure and cytonuclear associations present in Europe, but has retained overall high genetic diversity since invasion. Our results highlight the flexibility of the ABC approach for constructing a narrative of the demographic history of species invasions and provide baseline for future studies of evolutionary changes in introduced S. latifolia populations.

Seeing the forest for the trees: Assessing genetic offset predictions from gradient forest.

Gradient Forest (GF) is a machine learning algorithm designed to analyze spatial patterns of biodiversity as a function of environmental gradients. An offset measure between the GF-predicted environmental association of adapted alleles and a new environment (GF Offset) is increasingly being used to predict the loss of environmentally adapted alleles under rapid environmental change, but remains mostly untested for this purpose. Here, we explore the robustness of GF Offset to assumption violations, and its relationship to measures of fitness, using SLiM simulations with explicit genome architecture and a spatial metapopulation. We evaluate measures of GF Offset in: (1) a neutral model with no environmental adaptation; (2) a monogenic "population genetic" model with a single environmentally adapted locus; and (3) a polygenic "quantitative genetic" model with two adaptive traits, each adapting to a different environment. We found GF Offset to be broadly correlated with fitness offsets under both single locus and polygenic architectures. However, neutral demography, genomic architecture, and the nature of the adaptive environment can all confound relationships between GF Offset and fitness. GF Offset is a promising tool, but it is important to understand its limitations and underlying assumptions, especially when used in the context of predicting maladaptation.

Genotypic variation and plasticity in climate-adaptive traits after range expansion and fragmentation of red spruce (Picea rubens Sarg.).

Shifting range limits are predicted for many species as the climate warms. However, the rapid pace of climate change will challenge the natural dispersal capacity of long-lived, sessile organisms such as forest trees. Adaptive responses of populations will, therefore, depend on levels of genetic variation and plasticity for climate-responsive traits, which likely vary across the range due to expansion history and current patterns of selection. Here, we study levels of genetic and plastic variation for phenology and growth traits in populations of red spruce (Picea rubens), from the range core to the highly fragmented trailing edge. We measured more than 5000 offspring sampled from three genetically distinct regions (core, margin and edge) grown in three common gardens replicated along a latitudinal gradient. Genetic variation in phenology and growth showed low to moderate heritability and differentiation among regions, suggesting some potential to respond to selection. Phenology traits were highly plastic, but this plasticity was generally neutral or maladaptive in the effect on growth, revealing a potential liability under warmer climates. These results suggest future climate adaptation will depend on the regional availability of genetic variation in red spruce and provide a resource for the design and management of assisted gene flow. This article is part of the theme issue 'Species' ranges in the face of changing environments (Part II)'.

High quality haplotype-resolved genome assemblies of Populus tomentosa Carr., a stabilized interspecific hybrid species widespread in Asia.

Populus has a wide ecogeographical range spanning the Northern Hemisphere, and interspecific hybrids are common. Populus tomentosa Carr. is widely distributed and cultivated in the eastern region of Asia, where it plays multiple important roles in forestry, agriculture, conservation, and urban horticulture. Reference genomes are available for several Populus species, however, our goals were to produce a very high quality de novo chromosome-level genome assembly in P. tomentosa genome that could serve as a reference for evolutionary and ecological studies of hybrid speciation throughout the genus. Here, combining long-read sequencing and Hi-C scaffolding, we present a high-quality, haplotype-resolved genome assembly. The genome size was 740.2 Mb, with a contig N50 size of 5.47 Mb and a scaffold N50 size of 46.68 Mb, consisting of 38 chromosomes, as expected with the known diploid chromosome number (2n = 2x = 38). A total of 59,124 protein-coding genes were identified. Phylogenomic analyses revealed that P. tomentosa is comprised of two distinct subgenomes, which we deomonstrate is likely to have resulted from hybridization between Populus adenopoda as the female parent and Populus alba var. pyramidalis as the male parent, with an origin of approximately 3.93 Ma. Although highly colinear, significant structural variation was found between the two subgenomes. Our study provides a valuable resource for ecological genetics and forest biotechnology.

Climate-driven local adaptation of ecophysiology and phenology in balsam poplar, Populus balsamifera L. (Salicaceae).

PREMISE OF THE STUDY: During past episodes of climate change, many plant species experienced large-scale range expansions. Expanding populations likely encountered strong selection as they colonized new environments. In this study we examine the extent to which populations of the widespread forest tree Populus balsamifera L. have become locally adapted as the species expanded into its current range since the last glaciation. METHODS: We tested for adaptive variation in 13 ecophysiology and phenology traits on clonally propagated genotypes originating from a range-wide sample of 20 subpopulations. The hypothesis of local adaption was tested by comparing among-population variation at ecologically important traits (Q(ST)) to expected variation based on demographic history (F(ST)) estimated from a large set of nuclear single nucleotide polymorphism loci. KEY RESULTS: Evidence for divergence in excess of neutral expectations was present for eight of 13 traits. Bud phenology, petiole length, and leaf nitrogen showed the greatest divergence (all Q(ST) > 0.6), whereas traits related to leaf water usage showed the least (all Q(ST) ≤ 0.30) and were not different from neutrality. Strong correlations were present between traits, geography, and climate, and they revealed a general pattern of northern subpopulations adapted to shorter, drier growing seasons compared with populations in the center or eastern regions of the range. CONCLUSIONS: Our study demonstrates pronounced adaptive variation in ecophysiology and phenology among balsam poplar populations. These results suggest that as this widespread forest tree species expanded its range since the end of the last glacial maximum, it evolved rapidly in response to geographically variable selection.

Growth-defense trade-offs masked in unadmixed populations are revealed by hybridization.

Organisms are constantly challenged by pathogens and pests, which can drive the evolution of growth-defense strategies. Plant stomata are essential for gas exchange during photosynthesis and conceptually lie at the intersection of the physiological demands of growth and exposure to foliar fungal pathogens. Generations of natural selection for locally adapted growth-defense strategies can eliminate variation between traits, potentially masking trade-offs and selection conflicts that may have existed in the past. Hybrid populations offer a unique opportunity to reset the clock on selection and to study potentially maladaptive trait variation before selection removes it. We study the interactions of growth, stomatal, ecopysiological, and disease resistance traits in poplars (Populus) after infection by the leaf rust Melampsora medusae. Phenotypes were measured in a common garden and genotyped at 227K SNPs. We isolate the effects of hybridization on trait variance, discover correlations between stomatal, ecophysiology, and disease resistance, examine trade-offs and selection conflicts, and explore the evolution of growth-defense strategies potentially mediated by selection for stomatal traits on the upper leaf surface. These results suggest an important role for stomata in determining growth-defense strategies in organisms susceptible to foliar pathogens, and reinforces the contribution of hybridization studies toward our understanding of trait evolution.

Experimental support for genomic prediction of climate maladaptation using the machine learning approach Gradient Forests.

Gradient Forests (GF) is a machine learning algorithm that is gaining in popularity for studying the environmental drivers of genomic variation and for incorporating genomic information into climate change impact assessments. Here we (i) provide the first experimental evaluation of the ability of "genomic offsets" - a metric of climate maladaptation derived from Gradient Forests - to predict organismal responses to environmental change, and (ii) explore the use of GF for identifying candidate SNPs. We used high-throughput sequencing, genome scans, and several methods, including GF, to identify candidate loci associated with climate adaptation in balsam poplar (Populus balsamifera L.). Individuals collected throughout balsam poplar's range also were planted in two common garden experiments. We used GF to relate candidate loci to environmental gradients and predict the expected magnitude of the response (i.e., the genetic offset metric of maladaptation) of populations when transplanted from their "home" environment to the common gardens. We then compared the predicted genetic offsets from different sets of candidate and randomly selected SNPs to measurements of population performance in the common gardens. We found the expected inverse relationship between genetic offset and performance: populations with larger predicted genetic offsets performed worse in the common gardens than populations with smaller offsets. Also, genetic offset better predicted performance than did "naive" climate transfer distances. However, sets of randomly selected SNPs predicted performance slightly better than did candidate SNPs. Our study provides evidence that genetic offsets represent a first order estimate of the degree of expected maladaptation of populations exposed to rapid environmental change and suggests GF may have some promise as a method for identifying candidate SNPs.