Regional heterogeneity and gene flow maintain variance in a quantitative trait within populations of lodgepole pine

Drivers of genomic differentiation landscapes in populations of disparate ecological and geographical settings within mainland Apis cerana

Elucidating the evolutionary processes that drive population divergence can enhance our understanding of the early stages of speciation and inform conservation management decisions. The honeybee Apis cerana displays extensive population divergence, providing an informative natural system for exploring these processes. The mainland lineage A. cerana includes several peripheral subspecies with disparate ecological and geographical settings radiated from a central ancestor. Under this evolutionary framework, we can explore the patterns of genome differentiation and the evolutionary models that explain them. We can also elucidate the contribution of non-genomic spatiotemporal mechanisms (extrinsic features) and genomic mechanisms (intrinsic features) that influence these genomic differentiation landscapes. Based on 293 whole genomes, a small part of the genome is highly differentiated between central-peripheral subspecies pairs, while low and partial parallelism partly reflects idiosyncratic responses to environmental differences. Combined elements of recurrent selection and speciation-with-gene-flow models generate the heterogeneous genome landscapes. These elements weight differently between central-island and other central-peripheral subspecies pairs, influenced by glacial cycles superimposed on different geomorphologies. Although local recombination rates exert a significant influence on patterns of genomic differentiation, it is unlikely that low-recombination rates regions were generated by structural variation. In conclusion, complex factors including geographical isolation, divergent ecological selection and non-uniform genome features have acted concertedly in the evolution of reproductive barriers that could reduce gene flow in part of the genome and facilitate the persistence of distinct populations within mainland lineage of A. cerana.

Whole-Genome Sequencing Reveals That Regulatory and Low Pleiotropy Variants Underlie Local Adaptation to Environmental Variability in Purple Sea Urchins

AbstractOrganisms experience environments that vary across both space and time. Such environmental heterogeneity shapes standing genetic variation and may influence species' capacity to adapt to rapid environmental change. However, we know little about the kind of genetic variation that is involved in local adaptation to environmental variability. To address this gap, we sequenced the whole genomes of 140 purple sea urchins (Strongylocentrotus purpuratus) from seven populations that vary in their degree of pH variability. Despite no evidence of global population structure, we found a suite of single-nucleotide polymorphisms (SNPs) tightly correlated with local pH variability (outlier SNPs), which were overrepresented in regions putatively involved in gene regulation (long noncoding RNA and enhancers), supporting the idea that variation in regulatory regions is important for local adaptation to variability. In addition, outliers in genes were found to be (i) enriched for biomineralization and ion homeostasis functions related to low pH response, (ii) less central to the protein-protein interaction network, and (iii) underrepresented among genes highly expressed during early development. Taken together, these results suggest that loci that underlie local adaptation to pH variability in purple sea urchins fall in regions with potentially low pleiotropic effects (based on analyses involving regulatory regions, network centrality, and expression time) involved in low pH response (based on functional enrichment).

Reduced within-population quantitative genetic variation is associated with climate harshness in maritime pine

How evolutionary forces interact to maintain genetic variation within populations has been a matter of extensive theoretical debates. While mutation and exogenous gene flow increase genetic variation, stabilizing selection and genetic drift are expected to deplete it. To date, levels of genetic variation observed in natural populations are hard to predict without accounting for other processes, such as balancing selection in heterogeneous environments. We aimed to empirically test three hypotheses: (i) admixed populations have higher quantitative genetic variation due to introgression from other gene pools, (ii) quantitative genetic variation is lower in populations from harsher environments (i.e., experiencing stronger selection), and (iii) quantitative genetic variation is higher in populations from heterogeneous environments. Using growth, phenological and functional trait data from three clonal common gardens and 33 populations (522 clones) of maritime pine (Pinus pinaster Aiton), we estimated the association between the population-specific total genetic variances (i.e., among-clone variances) for these traits and ten population-specific indices related to admixture levels (estimated based on 5165 SNPs), environmental temporal and spatial heterogeneity and climate harshness. Populations experiencing colder winters showed consistently lower genetic variation for early height growth (a fitness-related trait in forest trees) in the three common gardens. Within-population quantitative genetic variation was not associated with environmental heterogeneity or population admixture for any trait. Our results provide empirical support for the potential role of natural selection in reducing genetic variation for early height growth within populations, which indirectly gives insight into the adaptive potential of populations to changing environments.

Immigration counter-acts local micro-evolution of a major fitness component: Migration-selection balance in free-living song sparrows

Ongoing adaptive evolution, and resulting “evolutionary rescue” of declining populations, requires additive genetic variation in fitness. Such variation can be increased by gene flow resulting from immigration, potentially facilitating evolution. But, gene flow could in fact constrain rather than facilitate local adaptive evolution if immigrants have low additive genetic values for local fitness. Local migration‐selection balance and micro‐evolutionary stasis could then result. However, key quantitative genetic effects of natural immigration, comprising the degrees to which gene flow increases the total local additive genetic variance yet counteracts local adaptive evolutionary change, have not been explicitly quantified in wild populations. Key implications of gene flow for population and evolutionary dynamics consequently remain unclear. Our quantitative genetic analyses of long‐term data from free‐living song sparrows (Melospiza melodia) show that mean breeding value for local juvenile survival to adulthood, a major component of fitness, increased across cohorts more than expected solely due to drift. Such micro‐evolutionary change should be expected given nonzero additive genetic variance and consistent directional selection. However, this evolutionary increase was counteracted by negative additive genetic effects of recent immigrants, which increased total additive genetic variance but prevented a net directional evolutionary increase in total additive genetic value. These analyses imply an approximate quantitative genetic migration‐selection balance in a major fitness component, and hence demonstrate a key mechanism by which substantial additive genetic variation can be maintained yet decoupled from local adaptive evolutionary change.

Genomic and phenotypic divergence unveil microgeographic adaptation in the Amazonian hyperdominant tree Eperua falcata Aubl. (Fabaceae)

Plant populations can undergo very localized adaptation, allowing widely distributed populations to adapt to divergent habitats in spite of recurrent gene flow. Neotropical trees-whose large and undisturbed populations often span a variety of environmental conditions and local habitats-are particularly good models to study this process. Here, we explore patterns of adaptive divergence from large (i.e., regional) to small (i.e., microgeographic) spatial scales in the hyperdominant Amazonian tree Eperua falcata Aubl. (Fabaceae) under a replicated design involving two microhabitats (~300 m apart) in two study sites (~300 km apart). A three-year reciprocal transplant illustrates that, beyond strong maternal effects and phenotypic plasticity, genetically driven divergence in seedling growth and leaf traits was detected both between seedlings originating from different regions, and between seedlings from different microhabitats. In parallel, a complementary genome scan for selection was carried out through whole-genome sequencing of tree population pools. A set of 290 divergence outlier SNPs was detected at the regional scale (between study sites), while 185 SNPs located in the vicinity of 106 protein-coding genes were detected as replicated outliers between microhabitats within regions. Outlier-surrounding genomic regions are involved in a variety of physiological processes, including plant responses to stress (e.g., oxidative stress, hypoxia and metal toxicity) and biotic interactions. Together with evidence of microgeographic divergence in functional traits, the discovery of genomic candidates for microgeographic adaptive divergence represents a promising advance in our understanding of local adaptation, which probably operates across multiple spatial scales and underpins divergence and diversification in Neotropical trees.

Microgeographic adaptation and the effect of pollen flow on the adaptive potential of a temperate tree species

In species with long-distance dispersal capacities and inhabiting a large ecological niche, local selection and gene flow are expected to be major evolutionary forces affecting the genetic adaptation of natural populations. Yet, in species such as trees, evidence of microgeographic adaptation and the quantitative assessment of the impact of gene flow on adaptive genetic variation are still limited. Here, we used extensive genetic and phenotypic data from European beech seedlings collected along an elevation gradient, and grown in a common garden, to study the signature of selection on the divergence of eleven potentially adaptive traits, and to assess the role of gene flow in resupplying adaptive genetic variation. We found a significant signal of adaptive differentiation among plots separated by < 1 km, with selection acting on growth and phenological traits. Consistent with theoretical expectations, our results suggest that pollen dispersal contributes to increase genetic diversity for these locally differentiated traits. Our results thus highlight that local selection is an important evolutionary force in natural tree populations and suggest that management interventions to facilitate movement of gametes along short ecological gradients would boost genetic diversity of individual tree populations, and enhance their adaptive potential to rapidly changing environments.

Genetic diversity and population structure of Hibiscus aridicola, an endangered ornamental species in dry-hot valleys of Jinsha River

Hibiscus aridicola is an endangered ornamental shrub of the family Malvaceae that is endemic to the dry-hot valleys of Jinsha River in southwestern China. This species is a typical plant species with extremely small populations (PSESP). To support and monitor future conservation, develop management measures, and genotype this species, we performed extensive field studies together with genetic analyses. Specifically, we screened eleven microsatellite loci of 69 individuals of H. aridicola from four accessions. The population genetics analyses indicated that H. aridicola possesses high genetic diversity at both the population (0.6962-0.7293) and species level (0.7837) compared to other endemic/endangered species in China. The low differentiation of populations (Fst = 0.0971) and the high gene flow between populations of H. aridicola (Nm = 2.3236) could be due to its distribution along rivers in the hot-valleys of the Jinsha River and the wind-mediated dispersal of its seeds. Furthermore, the genetic diversity of H. aridicola is slightly positively correlated with geographic distance. Two populations are undergoing a genetic bottleneck, and require more specific attention from conservationists. Additionally, our analyses of the population genetics of H. aridicola demonstrate that the declines in populations are not the result of the internal genetics of these populations but due to external human activities over the past decades.

Eco-evolutionary community turnover following environmental change

Co-occurring species often differ in intraspecific genetic diversity, which in turn can affect adaptation in response to environmental change. Specifically, the simultaneous evolutionary responses of co-occurring species to temporal environmental change may influence community dynamics. Local adaptation along environmental gradients combined with gene flow can enhance genetic diversity of traits within populations. Quantitative genetic theory shows that having greater gene flow results in (a) lower equilibrium population size due to maladaptive immigrant genotypes (migration load), but (b) faster adaptation to changing environments. Here, I build off this theory to study community dynamics of locally adapted species in response to temporal environmental changes akin to warming temperatures. Although an abrupt environmental change leaves all species initially maladapted, high gene flow species subsequently adapt faster due to greater genetic diversity. As a result, species can transiently reverse their relative abundances, but sometimes only after long lag periods. If constant temporal environmental change is applied, the community exhibits a shift toward stable dominance by species with intermediate gene flow. Notably, fast-adapting high gene flow species can increase in absolute abundance under environmental change (although often only for a transient period) because the change suppresses superior competitors with lower gene flow. This eco-evolutionary competitive release stabilizes ecosystem function. The eco-evolutionary community turnover studied here parallels the purely ecological successional dynamics following disturbances. My results demonstrate how interspecific variation in life history can have far-reaching impacts on eco-evolutionary community response to environmental change.

Gene Flow and Genetic Variation Explain Signatures of Selection across a Climate Gradient in Two Riparian Species

Many species occur across environmental gradients and it is expected that these species will exhibit some signals of adaptation as heterogeneous environments and localized gene flow may facilitate local adaptation. While riparian zones can cross climate gradients, many of which are being impacted by climate change, they also create microclimates for the vegetation, reducing environmental heterogeneity. Species with differing distributions in these environments provide an opportunity to investigate the importance of genetic connectivity in influencing signals of adaptation over relatively short geographical distance. Association analysis with genomic data was used to compare signals of selection to climate variables in two species that have differing distributions along a river traversing a climate gradient. Results demonstrate links between connectivity, standing genetic variation, and the development of signals of selection. In the restricted species, the combination of high gene flow in the middle and lower catchment and occurrence in a microclimate created along riverbanks likely mitigated the development of selection to most climatic variables. In contrast the more widely distributed species with low gene flow showed a stronger signal of selection. Together these results strengthen our knowledge of the drivers and scale of adaptation and reinforce the importance of connectivity across a landscape to maintain adaptive potential of plant species.

Adaptation to local climate in multi-trait space: evidence from silver fir (Abies alba Mill.) populations across a heterogeneous environment

Heterogeneous environments, such as mountainous landscapes, create spatially varying selection pressure that potentially affects several traits simultaneously across different life stages, yet little is known about the general patterns and drivers of adaptation in such complex settings. We studied silver fir (Abies alba Mill.) populations across Switzerland and characterized its mountainous landscape using downscaled historical climate data. We sampled 387 trees from 19 populations and genotyped them at 374 single-nucleotide polymorphisms (SNPs) to estimate their demographic distances. Seedling morphology, growth and phenology traits were recorded in a common garden, and a proxy for water use efficiency was estimated for adult trees. We tested whether populations have more strongly diverged at quantitative traits than expected based on genetic drift alone in a multi-trait framework, and identified potential environmental drivers of selection. We found two main responses to selection: (i) populations from warmer and more thermally stable locations have evolved towards a taller stature, and (ii) the growth timing of populations evolved towards two extreme strategies, 'start early and grow slowly' or 'start late and grow fast', driven by precipitation seasonality. Populations following the 'start early and grow slowly' strategy had higher water use efficiency and came from inner Alpine valleys characterized by pronounced summer droughts. Our results suggest that contrasting adaptive life-history strategies exist in silver fir across different life stages (seedling to adult), and that some of the characterized populations may provide suitable seed sources for tree growth under future climatic conditions.

Measuring viability selection from prospective cohort mortality studies: A case study in maritime pine

By changing the genetic background available for selection at subsequent life stages, stage-specific selection can define adaptive potential across the life cycle. We propose and evaluate here a neutrality test and a Bayesian method to infer stage-specific viability selection coefficients using sequential random genotypic samples drawn from a longitudinal cohort mortality study, within a generation. The approach is suitable for investigating selective mortality in large natural or experimental cohorts of any organism in which individual tagging and tracking are unfeasible. Numerical simulation results indicate that the method can discriminate loci under strong viability selection, and provided samples are large, yield accurate estimates of the corresponding selection coefficients. Genotypic frequency changes are largely driven by sampling noise under weak selection, however, compromising inference in that case. We apply the proposed methods to analyze viability selection operating at early recruitment stages in a natural maritime pine (Pinus pinaster Ait.) population. We measured temporal genotypic frequency changes at 384 candidate-gene SNP loci among seedlings sampled from the time of emergence in autumn until the summer of the following year, a period with high elimination rates. We detected five loci undergoing allele frequency changes larger than expected from stochastic mortality and sampling, with putative functions that could influence survival at early seedling stages. Our results illustrate how new statistical and sampling schemes can be used to conduct genomic scans of contemporary selection on specific life stages.

Evolutionary potential varies across populations and traits in the neotropical oak Quercus oleoides

Heritable variation in polygenic (quantitative) traits is critical for adaptive evolution and is especially important in this era of rapid climate change. In this study, we examined the levels of quantitative genetic variation of populations of the tropical tree Quercus oleoides Cham. and Schlect. for a suite of traits related to resource use and drought resistance. We tested whether quantitative genetic variation differed across traits, populations and watering treatments. We also tested potential evolutionary factors that might have shaped such a pattern: selection by climate and genetic drift. We measured 15 functional traits on 1322 1-year-old seedlings of 84 maternal half-sib families originating from five populations growing under two watering treatments in a greenhouse. We estimated the additive genetic variance, coefficient of additive genetic variation and narrow-sense heritability for each combination of traits, populations and treatments. In addition, we genotyped a total of 119 individuals (with at least 20 individuals per population) using nuclear microsatellites to estimate genetic diversity and population genetic structure. Our results showed that gas exchange traits and growth exhibited strikingly high quantitative genetic variation compared with traits related to leaf morphology, anatomy and photochemistry. Quantitative genetic variation differed between populations even at geographical scales as small as a few kilometers. Climate was associated with quantitative genetic variation, but only weakly. Genetic structure and diversity in neutral markers did not relate to coefficient of additive genetic variation. Our study demonstrates that quantitative genetic variation is not homogeneous across traits and populations of Q. oleoides. More importantly, our findings suggest that predictions about potential responses of species to climate change need to consider population-specific evolutionary characteristics.

Gene flow improves fitness at a range edge under climate change

Populations at the margins of a species' geographic range are often thought to be poorly adapted to their environment. According to theoretical predictions, gene flow can inhibit these range edge populations if it disrupts adaptation to local conditions. Alternatively, if range edge populations are small or isolated, gene flow can provide beneficial genetic variation and may facilitate adaptation to environmental change. We tested these competing predictions in the annual wildflower Clarkia pulchella using greenhouse crosses to simulate gene flow from sources across the geographic range into two populations at the northern range margin. We planted these between-population hybrids in common gardens at the range edge and evaluated how genetic differentiation and climatic differences between edge populations and gene flow sources affected lifetime fitness. During an anomalously warm study year, gene flow from populations occupying historically warm sites improved fitness at the range edge and plants with one or both parents from warm populations performed best. The effects of the temperature provenance of gene flow sources were most apparent at early life history stages, but precipitation provenance also affected reproduction. We also found benefits of gene flow that were independent of climate: after climate was controlled for, plants with parents from different populations performed better at later lifestages than those with parents from the same population, indicating that gene flow may improve fitness via relieving homozygosity. Further supporting this result, we found that increasing genetic differentiation of parental populations had positive effects on fitness of hybrid seeds. Gene flow from warmer populations, when it occurs, is likely to contribute adaptive genetic variation to populations at the northern range edge as the climate warms. On heterogeneous landscapes, climate of origin may be a better predictor of gene flow effects than geographic proximity.

Effect of migration and environmental heterogeneity on the maintenance of quantitative genetic variation: a simulation study

The paradox of high genetic variation observed in traits under stabilizing selection is a long-standing problem in evolutionary theory, as mutation rates appear too low to explain observed levels of standing genetic variation under classic models of mutation-selection balance. Spatially or temporally heterogeneous environments can maintain more standing genetic variation within populations than homogeneous environments, but it is unclear whether such conditions can resolve the above discrepancy between theory and observation. Here, we use individual-based simulations to explore the effect of various types of environmental heterogeneity on the maintenance of genetic variation (V_A ) for a quantitative trait under stabilizing selection. We find that V_A is maximized at intermediate migration rates in spatially heterogeneous environments and that the observed patterns are robust to changes in population size. Spatial environmental heterogeneity increased variation by as much as 10-fold over mutation-selection balance alone, whereas pure temporal environmental heterogeneity increased variance by only 45% at max. Our results show that some combinations of spatial heterogeneity and migration can maintain considerably more variation than mutation-selection balance, potentially reconciling the discrepancy between theoretical predictions and empirical observations. However, given the narrow regions of parameter space required for this effect, this is unlikely to provide a general explanation for the maintenance of variation. Nonetheless, our results suggest that habitat fragmentation may affect the maintenance of V_A and thereby reduce the adaptive capacity of populations.

Effects of zoochory on the spatial genetic structure of plant populations

Spatial genetic structure (SGS) of plants results from the nonrandom distribution of related individuals. SGS provides information on gene flow and spatial patterns of genetic diversity within populations. Seed dispersal creates the spatial template for plant distribution. Thus, in zoochorous plants, dispersal mode and disperser behaviour might have a strong impact on SGS. However, many studies only report the taxonomic group of seed dispersers, without further details. The recent increase in studies on SGS provides the opportunity to review findings and test for the influence of dispersal mode, taxonomic affiliation of dispersers and their behaviour. We compared the proportions of studies with SGS among groups and tested for differences in strength of SGS using Sp statistics. The presence of SGS differed among taxonomic groups, with reduced presence in plants dispersed by birds. Strength of SGS was instead significantly influenced by the behaviour of seed dispersal vectors, with higher SGS in plant species dispersed by animals with behavioural traits that result in short seed dispersal distances. We observed high variance in the strength of SGS in plants dispersed by animals that actively or passively accumulate seeds. Additionally, we found SGS was also affected by pollination and marker type used. Our study highlights the importance of vector behaviour on SGS even in the presence of variance created by other factors. Thus, more detailed information on the behaviour of seed dispersers would contribute to better understand which factors shape the spatial scale of gene flow in animal-dispersed plant species.

Grow with the flow: a latitudinal cline in physiology is associated with more variable precipitation in Erythranthe cardinalis

Local adaptation is commonly observed in nature: organisms perform well in their natal environment, but poorly outside it. Correlations between traits and latitude, or latitudinal clines, are among the most common pieces of evidence for local adaptation, but identifying the traits under selection and the selective agents is challenging. Here, we investigated a latitudinal cline in growth and photosynthesis across 16 populations of the perennial herb Erythranthe cardinalis (Phrymaceae). Using machine learning methods, we identify interannual variation in precipitation as a likely selective agent: southern populations from more variable environments had higher photosynthetic rates and grew faster. We hypothesize that selection may favour a more annualized life history - grow now rather than save for next year - in environments where severe droughts occur more often. Thus, our study provides insight into how species may adapt if Mediterranean climates become more variable due to climate change.

Coarse climate change projections for species living in a fine-scaled world

Accurately predicting biological impacts of climate change is necessary to guide policy. However, the resolution of climate data could be affecting the accuracy of climate change impact assessments. Here, we review the spatial and temporal resolution of climate data used in impact assessments and demonstrate that these resolutions are often too coarse relative to biologically relevant scales. We then develop a framework that partitions climate into three important components: trend, variance, and autocorrelation. We apply this framework to map different global climate regimes and identify where coarse climate data is most and least likely to reduce the accuracy of impact assessments. We show that impact assessments for many large mammals and birds use climate data with a spatial resolution similar to the biologically relevant area encompassing population dynamics. Conversely, impact assessments for many small mammals, herpetofauna, and plants use climate data with a spatial resolution that is orders of magnitude larger than the area encompassing population dynamics. Most impact assessments also use climate data with a coarse temporal resolution. We suggest that climate data with a coarse spatial resolution is likely to reduce the accuracy of impact assessments the most in climates with high spatial trend and variance (e.g., much of western North and South America) and the least in climates with low spatial trend and variance (e.g., the Great Plains of the USA). Climate data with a coarse temporal resolution is likely to reduce the accuracy of impact assessments the most in the northern half of the northern hemisphere where temporal climatic variance is high. Our framework provides one way to identify where improving the resolution of climate data will have the largest impact on the accuracy of biological predictions under climate change.

Adaptive dynamics of cuticular hydrocarbons in Drosophila

Cuticular hydrocarbons (CHCs) are hydrophobic compounds deposited on the arthropod cuticle that are of functional significance with respect to stress tolerance, social interactions and mating dynamics. We characterized CHC profiles in natural populations of Drosophila melanogaster at five levels: across a latitudinal transect in the eastern United States, as a function of developmental temperature during culture, across seasonal time in replicate years, and as a function of rapid evolution in experimental mesocosms in the field. Furthermore, we also characterized spatial and temporal changes in allele frequencies for SNPs in genes that are associated with the production and chemical profile of CHCs. Our data demonstrate a striking degree of parallelism for clinal and seasonal variation in CHCs in this taxon; CHC profiles also demonstrate significant plasticity in response to rearing temperature, and the observed patterns of plasticity parallel the spatiotemporal patterns observed in nature. We find that these congruent shifts in CHC profiles across time and space are also mirrored by predictable shifts in allele frequencies at SNPs associated with CHC chain length. Finally, we observed rapid and predictable evolution of CHC profiles in experimental mesocosms in the field. Together, these data strongly suggest that CHC profiles respond rapidly and adaptively to environmental parameters that covary with latitude and season, and that this response reflects the process of local adaptation in natural populations of D. melanogaster.

Varying selection differential throughout the climatic range of Norway spruce in Central Europe

Predicting species distribution changes in global warming requires an understanding of how climatic constraints shape the genetic variation of adaptive traits and force local adaptations. To understand the genetic capacity of Norway spruce populations in Central Europe, we analyzed the variation in tree heights at the juvenile stage in common garden experiments established from the species' warm‐dry to cold‐moist distribution limits. We report the following findings: First, 47% of the total tree height variation at trial sites is attributable to the tree populations irrespective of site climate. Second, tree height variation within populations is higher at cold‐moist trial sites than at warm‐dry sites and higher within populations originating from cold‐moist habitats than from warm‐dry habitats. Third, for tree ages of 7–15 years, the variation within populations increases at cold‐moist trial sites, whereas it remains constant at warm‐dry sites. Fourth, tree height distributions are right‐skewed at cold‐moist trial sites, whereas they are nonskewed, but platykurtic at warm‐dry sites. Our results suggest that in cold environments, climatic conditions impose stronger selection and probably restrict the distribution of spruce, whereas at the warm distribution limit, the species' realized niche might rather be controlled by external drivers, for example, forest insects.

Natural quantitative genetic variance in plant growth differs in response to ecologically relevant temperature heterogeneity

Adaptation to large‐scale spatial heterogeneity in the environment accounts for a major proportion of genetic diversity within species. Theory predicts the erosion of adaptive genetic variation on a within‐population level, but considerable genetic diversity is often found locally. Genetic diversity could be expected to be maintained within populations in temporally or spatially variable conditions if genotypic rank orders vary across contrasting microenvironmental settings. Taking advantage of fine‐resolution environmental data, we tested the hypothesis that temperature heterogeneity among years could be one factor maintaining quantitative genetic diversity within a natural and genetically diverse plant population. We sampled maternal families of Boechera stricta, an Arabidopsis thaliana relative, at one location in the central Rocky Mountains and grew them in three treatments that, based on records from an adjacent weather station, simulated hourly temperature changes at the native site during three summers with differing mean temperatures. Treatment had a significant effect on all traits, with 2–3‐fold increase in above‐ and belowground biomass and the highest allocation to roots observed in the treatment simulating the warmest summer on record at the site. Treatment affected bivariate associations between traits, with the weakest correlation between above‐ and belowground biomass in the warmest treatment. The magnitude of quantitative genetic variation for all traits differed across treatments: Genetic variance of biomass was 0 in the warmest treatment, while highly significant diversity was found in average conditions, resulting in broad‐sense heritability of 0.31. Significant genotype × environment interactions across all treatments were found only in root‐to‐shoot ratio. Therefore, temperature variation among summers appears unlikely to account for the observed levels of local genetic variation in size in this perennial species, but may influence family rank order in growth allocation. Our results indicate that natural environmental fluctuations can have a large impact on the magnitude of within‐population quantitative genetic variance.

Assessing spatial covariance among time series of abundance

For species of conservation concern, an essential part of the recovery planning process is identifying discrete population units and their location with respect to one another. A common feature among geographically proximate populations is that the number of organisms tends to covary through time as a consequence of similar responses to exogenous influences. In turn, high covariation among populations can threaten the persistence of the larger metapopulation. Historically, explorations of the covariance in population size of species with many (>10) time series have been computationally difficult. Here, we illustrate how dynamic factor analysis (DFA) can be used to characterize diversity among time series of population abundances and the degree to which all populations can be represented by a few common signals. Our application focuses on anadromous Chinook salmon (Oncorhynchus tshawytscha), a species listed under the US Endangered Species Act, that is impacted by a variety of natural and anthropogenic factors. Specifically, we fit DFA models to 24 time series of population abundance and used model selection to identify the minimum number of latent variables that explained the most temporal variation after accounting for the effects of environmental covariates. We found support for grouping the time series according to 5 common latent variables. The top model included two covariates: the Pacific Decadal Oscillation in spring and summer. The assignment of populations to the latent variables matched the currently established population structure at a broad spatial scale. At a finer scale, there was more population grouping complexity. Some relatively distant populations were grouped together, and some relatively close populations – considered to be more aligned with each other – were more associated with populations further away. These coarse‐ and fine‐grained examinations of spatial structure are important because they reveal different structural patterns not evident in other analyses.

Adaptation of lodgepole pine and interior spruce to climate: implications for reforestation in a warming world

We investigated adaptation to climate in populations of two widespread tree species across a range of contrasting environments in western Canada. In a series of common garden experiments, bud phenology, cold hardiness, and seedling growth traits were assessed for 254 populations in the interior spruce complex (Picea glauca, P. engelmannii, and their hybrids) and for 281 populations of lodgepole pine (Pinus contorta). Complex multitrait adaptations to different ecological regions such as boreal, montane, coastal, and arid environments accounted for 15-20% of the total variance. This population differentiation could be directly linked to climate variables through multivariate regression tree analysis. Our results suggest that adaptation to climate does not always correspond linearly to temperature gradients. For example, opposite trait values (e.g., early versus late budbreak) may be found in response to apparently similar cold environments (e.g., boreal and montane). Climate change adaptation strategies may therefore not always be possible through a simple shift of seed sources along environmental gradients. For the two species in this study, we identified a relatively small number of uniquely adapted populations (11 for interior spruce and nine for lodgepole pine) that may be used to manage adaptive variation under current and expected future climates.

Spatiotemporal environmental heterogeneity and the maintenance of the tailspot polymorphism in the variable platyfish (Xiphophorus variatus)

Genetic variation is critical for adaptive evolution. Despite its importance, there is still limited evidence in support of some prominent theoretical models explaining the maintenance of genetic polymorphism within populations. We examined 84 populations of Xiphophorus variatus, a livebearing fish with a genetic polymorphism associated with physiological performance, to test: (1) whether niche differentiation explains broad-scale maintenance of polymorphism, (2) whether polymorphism is maintained among populations by local adaptation and migration, or (3) whether heterogeneity in explicit environmental variables could be linked to levels of polymorphism within populations. We found no evidence of climatic niche differentiation that could generate or maintain broad geographic variation in polymorphism. Subsequently, hierarchical partitioning of genetic richness and partial mantel tests revealed that 76% of the observed genetic richness was partitioned within populations with no effect of geographic distance on polymorphism. These results strongly suggest a lack of migration-selection balance in the maintenance of polymorphism, and model selection confirmed a significant relationship between environmental heterogeneity and genetic richness within populations. Few studies have demonstrated such effects at this scale, and additional studies in other taxa should examine the generality of gene-by-environment interactions across populations to better understand the dynamics and scale of balancing selection.

Time to get moving: assisted gene flow of forest trees

Geographic variation in trees has been investigated since the mid-18th century. Similar patterns of clinal variation have been observed along latitudinal and elevational gradients in common garden experiments for many temperate and boreal species. These studies convinced forest managers that a 'local is best' seed source policy was usually safest for reforestation. In recent decades, experimental design, phenotyping methods, climatic data and statistical analyses have improved greatly and refined but not radically changed knowledge of clines. The maintenance of local adaptation despite high gene flow suggests selection for local adaptation to climate is strong. Concerns over maladaptation resulting from climate change have motivated many new genecological and population genomics studies; however, few jurisdictions have implemented assisted gene flow (AGF), the translocation of pre-adapted individuals to facilitate adaptation of planted forests to climate change. Here, we provide evidence that temperate tree species show clines along climatic gradients sufficiently similar for average patterns or climate models to guide AGF in the absence of species-specific knowledge. Composite provenancing of multiple seed sources can be used to increase diversity and buffer against future climate uncertainty. New knowledge will continue to refine and improve AGF as climates warm further.

Bayesian inference of selection in a heterogeneous environment from genetic time-series data

Evolutionary geneticists have sought to characterize the causes and molecular targets of selection in natural populations for many years. Although this research programme has been somewhat successful, most statistical methods employed were designed to detect consistent, weak to moderate selection. In contrast, phenotypic studies in nature show that selection varies in time and that individual bouts of selection can be strong. Measurements of the genomic consequences of such fluctuating selection could help test and refine hypotheses concerning the causes of ecological specialization and the maintenance of genetic variation in populations. Herein, I proposed a Bayesian nonhomogeneous hidden Markov model to estimate effective population sizes and quantify variable selection in heterogeneous environments from genetic time-series data. The model is described and then evaluated using a series of simulated data, including cases where selection occurs on a trait with a simple or polygenic molecular basis. The proposed method accurately distinguished neutral loci from non-neutral loci under strong selection, but not from those under weak selection. Selection coefficients were accurately estimated when selection was constant or when the fitness values of genotypes varied linearly with the environment, but these estimates were less accurate when fitness was polygenic or the relationship between the environment and the fitness of genotypes was nonlinear. Past studies of temporal evolutionary dynamics in laboratory populations have been remarkably successful. The proposed method makes similar analyses of genetic time-series data from natural populations more feasible and thereby could help answer fundamental questions about the causes and consequences of evolution in the wild.

Local Adaptation by Alleles of Small Effect

Population genetic models predict that alleles with small selection coefficients may be swamped by migration and will not contribute to local adaptation. But if most alleles contributing to standing variation are of small effect, how does local adaptation proceed? Here I review predictions of population and quantitative genetic models and use individual-based simulations to illustrate how the architecture of local adaptation depends on the genetic redundancy of the trait, the maintenance of standing genetic variation (V(G)), and the susceptibility of alleles to swamping. Even when population genetic models predict swamping for individual alleles, considerable local adaptation can evolve at the phenotypic level if there is sufficient V(G). However, in such cases the underlying architecture of divergence is transient: F(ST) is low across all loci, and no locus makes an important contribution for very long. Because this kind of local adaptation is mainly due to transient frequency changes and allelic covariances, these architectures will be difficult--if not impossible--to detect using current approaches to studying the genomic basis of adaptation. Even when alleles are large and resistant to swamping, architectures can be highly transient if genetic redundancy and mutation rates are high. These results suggest that drift can play a critical role in shaping the architecture of local adaptation, both through eroding V(G) and affecting the rate of turnover of polymorphisms with redundant phenotypic effects.

Molecular proxies for climate maladaptation in a long-lived tree (Pinus pinaster Aiton, Pinaceae)

Understanding adaptive genetic responses to climate change is a main challenge for preserving biological diversity. Successful predictive models for climate-driven range shifts of species depend on the integration of information on adaptation, including that derived from genomic studies. Long-lived forest trees can experience substantial environmental change across generations, which results in a much more prominent adaptation lag than in annual species. Here, we show that candidate-gene SNPs (single nucleotide polymorphisms) can be used as predictors of maladaptation to climate in maritime pine (Pinus pinaster Aiton), an outcrossing long-lived keystone tree. A set of 18 SNPs potentially associated with climate, 5 of them involving amino acid-changing variants, were retained after performing logistic regression, latent factor mixed models, and Bayesian analyses of SNP-climate correlations. These relationships identified temperature as an important adaptive driver in maritime pine and highlighted that selective forces are operating differentially in geographically discrete gene pools. The frequency of the locally advantageous alleles at these selected loci was strongly correlated with survival in a common garden under extreme (hot and dry) climate conditions, which suggests that candidate-gene SNPs can be used to forecast the likely destiny of natural forest ecosystems under climate change scenarios. Differential levels of forest decline are anticipated for distinct maritime pine gene pools. Geographically defined molecular proxies for climate adaptation will thus critically enhance the predictive power of range-shift models and help establish mitigation measures for long-lived keystone forest trees in the face of impending climate change.

Cross-species outlier detection reveals different evolutionary pressures between sister species

Lodgepole pine (Pinus contorta var. latifolia) and jack pine (Pinus banksiana) hybridize in western Canada, an area of recent mountain pine beetle range expansion. Given the heterogeneity of the environment, and indications of local adaptation, there are many unknowns regarding the response of these forests to future outbreaks. To better understand this we aim to identify genetic regions that have adaptive potential. We used data collected on 472 single nucleotide polymorphism (SNP) loci from 576 tree samples collected across 13 lodgepole pine-dominated sites and four jack pine-dominated sites. We looked at the relationship of genetic diversity with the environment, and we identified candidate loci using both frequency-based (arlequin and bayescan) and correlation-based (matsam and bayenv) methods. We found contrasting relationships between environmental variation and genetic diversity for the species. While we identified a number of candidate outliers (34 in lodgepole pine, 25 in jack pine, and 43 interspecific loci), we did not find any loci in common between lodgepole and jack pine. Many of the outlier loci identified were correlated with environmental variation. Using rigorous criteria we have been able to identify potential outlier SNPs. We have also found evidence of contrasting environmental adaptations between lodgepole and jack pine which could have implications for beetle spread risk.

AFLPs and mitochondrial haplotypes reveal local adaptation to extreme thermal environments in a freshwater gastropod

The way environmental variation shapes neutral and adaptive genetic variation in natural populations is a key issue in evolutionary biology. Genome scans allow the identification of the genetic basis of local adaptation without previous knowledge of genetic variation or traits under selection. Candidate loci for divergent adaptation are expected to show higher F_ST than neutral loci influenced solely by random genetic drift, migration and mutation. The comparison of spatial patterns of neutral markers and loci under selection may help disentangle the effects of gene flow, genetic drift and selection among populations living in contrasting environments. Using the gastropod Radix balthica as a system, we analyzed 376 AFLP markers and 25 mtDNA COI haplotypes for candidate loci and associations with local adaptation among contrasting thermal environments in Lake Mývatn, a volcanic lake in northern Iceland. We found that 2% of the analysed AFLP markers were under directional selection and 12% of the mitochondrial haplotypes correlated with differing thermal habitats. The genetic networks were concordant for AFLP markers and mitochondrial haplotypes, depicting distinct topologies at neutral and candidate loci. Neutral topologies were characterized by intense gene flow revealed by dense nets with edges connecting contrasting thermal habitats, whereas the connections at candidate loci were mostly restricted to populations within each thermal habitat and the number of edges decreased with temperature. Our results suggest microgeographic adaptation within Lake Mývatn and highlight the utility of genome scans in detecting adaptive divergence.

Sequence-related amplified polymorphism (SRAP) markers: A potential resource for studies in plant molecular biology(1.)

In the past few decades, many investigations in the field of plant biology have employed selectively neutral, multilocus, dominant markers such as inter-simple sequence repeat (ISSR), random-amplified polymorphic DNA (RAPD), and amplified fragment length polymorphism (AFLP) to address hypotheses at lower taxonomic levels. More recently, sequence-related amplified polymorphism (SRAP) markers have been developed, which are used to amplify coding regions of DNA with primers targeting open reading frames. These markers have proven to be robust and highly variable, on par with AFLP, and are attained through a significantly less technically demanding process. SRAP markers have been used primarily for agronomic and horticultural purposes, developing quantitative trait loci in advanced hybrids and assessing genetic diversity of large germplasm collections. Here, we suggest that SRAP markers should be employed for research addressing hypotheses in plant systematics, biogeography, conservation, ecology, and beyond. We provide an overview of the SRAP literature to date, review descriptive statistics of SRAP markers in a subset of 171 publications, and present relevant case studies to demonstrate the applicability of SRAP markers to the diverse field of plant biology. Results of these selected works indicate that SRAP markers have the potential to enhance the current suite of molecular tools in a diversity of fields by providing an easy-to-use, highly variable marker with inherent biological significance.

Adaptive genetic divergence along narrow environmental gradients in four stream insects

A central question linking ecology with evolutionary biology is how environmental heterogeneity can drive adaptive genetic divergence among populations. We examined adaptive divergence of four stream insects from six adjacent catchments in Japan by combining field measures of habitat and resource components with genome scans of non-neutral Amplified Fragment Length Polymorphism (AFLP) loci. Neutral genetic variation was used to measure gene flow and non-neutral genetic variation was used to test for adaptive divergence. We identified the environmental characteristics contributing to divergence by comparing genetic distances at non-neutral loci between sites with Euclidean distances for each of 15 environmental variables. Comparisons were made using partial Mantel tests to control for geographic distance. In all four species, we found strong evidence for non-neutral divergence along environmental gradients at between 6 and 21 loci per species. The relative contribution of these environmental variables to each species' ecological niche was quantified as the specialization index, S, based on ecological data. In each species, the variable most significantly correlated with genetic distance at non-neutral loci was the same variable along which each species was most narrowly distributed (i.e., highest S). These were gradients of elevation (two species), chlorophyll-a, and ammonia-nitrogen. This adaptive divergence occurred in the face of ongoing gene flow (Fst = 0.01-0.04), indicating that selection was strong enough to overcome homogenization at the landscape scale. Our results suggest that adaptive divergence is pronounced, occurs along different environmental gradients for different species, and may consistently occur along the narrowest components of species' niche.

Space, time and complexity in plant dispersal ecology

Dispersal of pollen and seeds are essential functions of plant species, with far-reaching demographic, ecological and evolutionary consequences. Interest in plant dispersal has increased with concerns about the persistence of populations and species under global change. We argue here that advances in plant dispersal ecology research will be determined by our ability to surmount challenges of spatiotemporal scales and heterogeneities and ecosystem complexity. Based on this framework, we propose a selected set of research questions, for which we suggest some specific objectives and methodological approaches. Reviewed topics include multiple vector contributions to plant dispersal, landscape-dependent dispersal patterns, long-distance dispersal events, spatiotemporal variation in dispersal, and the consequences of dispersal for plant communities, populations under climate change, and anthropogenic landscapes.

Evolutionary and plastic responses to climate change in terrestrial plant populations

As climate change progresses, we are observing widespread changes in phenotypes in many plant populations. Whether these phenotypic changes are directly caused by climate change, and whether they result from phenotypic plasticity or evolution, are active areas of investigation. Here, we review terrestrial plant studies addressing these questions. Plastic and evolutionary responses to climate change are clearly occurring. Of the 38 studies that met our criteria for inclusion, all found plastic or evolutionary responses, with 26 studies showing both. These responses, however, may be insufficient to keep pace with climate change, as indicated by eight of 12 studies that examined this directly. There is also mixed evidence for whether evolutionary responses are adaptive, and whether they are directly caused by contemporary climatic changes. We discuss factors that will likely influence the extent of plastic and evolutionary responses, including patterns of environmental changes, species' life history characteristics including generation time and breeding system, and degree and direction of gene flow. Future studies with standardized methodologies, especially those that use direct approaches assessing responses to climate change over time, and sharing of data through public databases, will facilitate better predictions of the capacity for plant populations to respond to rapid climate change.

Landscape-scale eco-evolutionary dynamics: selection by seed predators and fire determine a major reproductive strategy

Recent work in model systems has demonstrated significant effects of rapid evolutionary change on ecological processes (eco-evolutionary dynamics). Fewer studies have addressed whether eco-evolutionary dynamics structure natural ecosystems. We investigated variation in the frequency of serotiny in lodgepole pine (Pinus contorta), a widespread species in which postfire seedling density and ecosystem structure are largely determined by serotiny. Serotiny, the retention of mature seeds in cones in a canopy seed bank, is thought to be an adaptation for stand-replacing fire, but less attention has been paid to the potential selective effects of seed predation on serotiny. We hypothesized that spatial variation in percentage serotiny in lodgepole pine forests results from an eco-evolutionary dynamic where the local level of serotiny depends on the relative strengths of conflicting directional selection from fire (favoring serotiny) and seed predation (favoring cones that open at maturity). We measured percentage serotiny, the abundance of American red squirrels (Tamiasciurus hudsonicus; the primary pre-dispersal seed predator of lodgepole pine), and several measures of forest structure in Yellowstone National Park, USA. Fire frequency strongly predicted the frequency of serotiny, a pattern that is well-supported in the literature. At sites with high fire frequency (return intervals of -135-185 years) where fire favors increased serotiny, squirrel abundance was negatively associated with serotiny, suggesting that selection from predation can overwhelm selection from fire when squirrels are abundant. At sites with low fire frequency (return intervals of -280-310 years), serotiny was nearly universally uncommon (< 10%). Finally, forest structure strongly predicted squirrel density independently of serotiny, and serotiny provided no additional explanatory power, suggesting that the correlation is caused by selection against serotiny exerted by squirrels, rather than squirrels responding to variation in percentage serotiny.

Potential for evolutionary responses to climate change - evidence from tree populations

Evolutionary responses are required for tree populations to be able to track climate change. Results of 250 years of common garden experiments show that most forest trees have evolved local adaptation, as evidenced by the adaptive differentiation of populations in quantitative traits, reflecting environmental conditions of population origins. On the basis of the patterns of quantitative variation for 19 adaptation-related traits studied in 59 tree species (mostly temperate and boreal species from the Northern hemisphere), we found that genetic differentiation between populations and clinal variation along environmental gradients were very common (respectively, 90% and 78% of cases). Thus, responding to climate change will likely require that the quantitative traits of populations again match their environments. We examine what kind of information is needed for evaluating the potential to respond, and what information is already available. We review the genetic models related to selection responses, and what is known currently about the genetic basis of the traits. We address special problems to be found at the range margins, and highlight the need for more modeling to understand specific issues at southern and northern margins. We need new common garden experiments for less known species. For extensively studied species, new experiments are needed outside the current ranges. Improving genomic information will allow better prediction of responses. Competitive and other interactions within species and interactions between species deserve more consideration. Despite the long generation times, the strong background in quantitative genetics and growing genomic resources make forest trees useful species for climate change research. The greatest adaptive response is expected when populations are large, have high genetic variability, selection is strong, and there is ecological opportunity for establishment of better adapted genotypes.

Adaptive evolution: evaluating empirical support for theoretical predictions

Adaptive evolution is shaped by the interaction of population genetics, natural selection and underlying network and biochemical constraints. Variation created by mutation, the raw material for evolutionary change, is translated into phenotypes by flux through metabolic pathways and by the topography and dynamics of molecular networks. Finally, the retention of genetic variation and the efficacy of selection depend on population genetics and demographic history. Emergent high-throughput experimental methods and sequencing technologies allow us to gather more evidence and to move beyond the theory in different systems and populations. Here we review the extent to which recent evidence supports long-established theoretical principles of adaptation.

Divergent selection and heterogeneous migration rates across the range of Sitka spruce (Picea sitchensis)

Gene flow and effective population size (N(e)) should depend on a population's position within its range: those near the edges are expected to have smaller N(e) and lower relative emigration rates, whereas those nearer the centre should have larger N(e) and higher relative emigration rates. In species with continuous ranges, this phenomenon may limit the ability of peripheral populations to respond to divergent selection. Here, we employ Sitka spruce as a model to test these predictions. We previously genotyped 339 single nucleotide polymorphisms (SNPs) in 410 individuals from 13 populations, and used these data to identify putative targets of divergent selection, as well as to explore the extent to which central-peripheral structure may impede adaptation. Fourteen SNPs had outlier F(ST) estimates suggestive of divergent selection, of which nine were previously associated with phenotypic variation in adaptive traits (timing of autumn budset and cold hardiness). Using coalescent simulations, we show that populations from near the centre of the range have higher effective populations sizes than those from the edges, and that central populations contribute more migrants to marginal populations than the reverse. Our results suggest that while divergent selection appears to have shaped allele frequencies among populations, asymmetrical movement of alleles from the centre to the edges of the species range may affect the adaptive capacity of peripheral populations. In southern peripheral populations, the movement of cold-adapted alleles from the north represents a significant impediment to adaptation under climate change, while in the north, movement of warm-adapted alleles from the south may enhance adaptation.

Long-distance gene flow and adaptation of forest trees to rapid climate change

Forest trees are the dominant species in many parts of the world and predicting how they might respond to climate change is a vital global concern. Trees are capable of long-distance gene flow, which can promote adaptive evolution in novel environments by increasing genetic variation for fitness. It is unclear, however, if this can compensate for maladaptive effects of gene flow and for the long-generation times of trees. We critically review data on the extent of long-distance gene flow and summarise theory that allows us to predict evolutionary responses of trees to climate change. Estimates of long-distance gene flow based both on direct observations and on genetic methods provide evidence that genes can move over spatial scales larger than habitat shifts predicted under climate change within one generation. Both theoretical and empirical data suggest that the positive effects of gene flow on adaptation may dominate in many instances. The balance of positive to negative consequences of gene flow may, however, differ for leading edge, core and rear sections of forest distributions. We propose future experimental and theoretical research that would better integrate dispersal biology with evolutionary quantitative genetics and improve predictions of tree responses to climate change.