PREDICTING ADAPTATION UNDER MIGRATION LOAD: THE ROLE OF GENETIC SKEW

Effect of the Seed Bank on Evolutionary Rescue in Small Populations: Univariate and Multivariate Demogenetic Dynamics

AbstractUnder global change, the impact of seed banks on evolutionary rescue is uncertain. They buffer plant populations from demographic and genetic stochasticity but extend generation time and can become a reservoir of maladapted alleles. We built analytical and individual-based models to predict the effect of seed banks on the persistence of small annual plant populations facing an abrupt or sustained directional change in uni- or multivariate trait optima. Demogenetic dynamics predict that under most scenarios seed banks increase the lag yet enhance persistence to 200-250 years by absorbing demographic losses. Simulations indicate that the seed bank has a minimal impact on the genetic skew, although we suggest that this result could depend on the fitness component under selection. Our multivariate model reveals that by enlarging and reshaping the G matrix, seed banks can diminish the impact of mutational correlation and even accelerate adaptation under antagonistic pleiotropy relative to populations without a bank. We illustrate how the magnitude of optimum fluctuations, type and degree of optimum change, selection strength, and vital rates are weights that tip the scales determining persistence. Finally, our work highlights that migration from the past is not maladaptative when optimum fluctuations are large enough to create stepping stones to the new optimum.

Microgeographic variation in early fitness traits of Pinus sylvestris from contrasting soils

PREMISE

The possibility of fine-scale intraspecific adaptive divergence under gene flow is established by theoretical models and has been confirmed empirically in tree populations distributed along steep altitudinal clines or across extreme edaphic discontinuities. However, the possibility of microgeographic adaptive divergence due to less severe but more frequent kinds of soil variation is unclear.

METHODS

In this study, we looked for evidence of local adaptation to calcareous versus siliceous soil types in two nearby Mediterranean Pinus sylvestris populations connected via pollen flow. Using a greenhouse experiment, we tested for variation in early (up to three years of age) seedling performance among open-pollinated maternal families originating from each edaphic provenance when experimentally grown on both types of natural local substrate.

RESULTS

Although seedlings were clearly affected by the edaphic environment, exhibiting lower and slower emergence as well as higher mortality on the calcareous than in the siliceous substrate, neither the performance on each substrate nor the plasticity among substrates varied significantly with seedling edaphic provenance.

CONCLUSIONS

We found no evidence of local adaptation to a non-extreme edaphic discontinuity over a small spatial scale, at least during early stages of seedling establishment. Future studies on microgeographic soil-driven adaptation should consider long-term experiments to minimize maternal effects and allow a potentially delayed expression of edaphic adaptive divergence.

The effect of migration and variation on populations of Escherichia coli adapting to complex fluctuating environments

Migration, a critical evolutionary force, can have contrasting effects on adaptation. It can aid as well as impede adaptation. The effects of migration on microbial adaptation have been studied primarily in simple constant environments. Very little is known about the effects of migration on adaptation to complex, fluctuating environments. In our study, we subjected replicate populations of Escherichia coli, adapting to complex and unpredictably fluctuating environments to different proportions of clonal ancestral immigrants. Contrary to the results from simple/constant environments, the presence of clonal immigrants reduced all measured proxies of fitness. However, migration from a source population with a greater variance in fitness resulted in no change in fitness with respect to the no-migration control, except at the highest level of migration. Thus, the presence of variation in the immigrants could counter the adverse effects of migration in complex and unpredictably fluctuating environments. Our study demonstrates that the effects of migration are strongly dependent on the nature of the destination environment and the genetic makeup of immigrants. These results enhance our understanding of the influences of migrating populations, which could help better predict the consequences of migration.

Evolutionary dynamics of complex traits in sexual populations in a heterogeneous environment: how normal?

When studying the dynamics of trait distribution of populations in a heterogeneous environment, classical models from quantitative genetics choose to look at its system of moments, specifically the first two ones. Additionally, in order to close the resulting system of equations, they often assume the local trait distributions are Gaussian [see for instance Ronce and Kirkpatrick (Evolution 55(8):1520-1531, 2001. https://doi.org/10.1111/j.0014-3820.2001.tb00672.x.37 )]. The aim of this paper is to introduce a mathematical framework that follows the whole trait distribution (without prior assumption) to study evolutionary dynamics of sexually reproducing populations. Specifically, it focuses on complex traits, whose inheritance can be encoded by the infinitesimal model of segregation (Fisher in Trans R Soc Edinb 52(2):399-433, 1919. https://doi.org/10.1017/S0080456800012163 ). We show that it allows us to derive a regime in which our model gives the same dynamics as when assuming Gaussian local trait distributions. To support that, we compare the stationary problems of the system of moments derived from our model with the one given in Ronce and Kirkpatrick (Evolution 55(8):1520-1531, 2001. https://doi.org/10.1111/j.0014-3820.2001.tb00672.x.37 ) and show that they are equivalent under this regime and do not need to be otherwise. Moreover, under this regime of equivalence, we show that a separation bewteen ecological and evolutionary time scales arises. A fast relaxation toward monomorphism allows us to reduce the complexity of the system of moments, using a slow-fast analysis. This reduction leads us to complete, still in this regime, the analytical description of the bistable asymmetrical equilibria numerically found in Ronce and Kirkpatrick (Evolution 55(8):1520-1531, 2001. https://doi.org/10.1111/j.0014-3820.2001.tb00672.x.37 ). More globally, we provide explicit modelling hypotheses that allow for such local adaptation patterns to occur.

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.

Evolution of Specialization in Heterogeneous Environments: Equilibrium Between Selection, Mutation and Migration

Adaptation in spatially heterogeneous environments results from the balance between local selection, mutation, and migration. We study the interplay among these different evolutionary forces and demography in a classical two-habitat scenario with asexual reproduction. We develop a new theoretical approach that goes beyond the Adaptive Dynamics framework, and allows us to explore the effect of high mutation rates on the stationary phenotypic distribution. We show that this approach improves the classical Gaussian approximation, and captures accurately the shape of this equilibrium phenotypic distribution in one- and two-population scenarios. We examine the evolutionary equilibrium under general conditions where demography and selection may be nonsymmetric between the two habitats. In particular, we show how migration may increase differentiation in a source-sink scenario. We discuss the implications of these analytic results for the adaptation of organisms with large mutation rates, such as RNA viruses.

Do replicates of independent guppy lineages evolve similarly in a predator-free laboratory environment?

The Trinidadian guppy is emblematic of parallel and convergent evolution, with repeated demonstrations that predation regime is a driver of adaptive trait evolution. A classic and foundational experiment in this system was conducted by John Endler 40 years ago, where male guppies placed into low-predation environments in the laboratory evolved increased color in a few generations. However, Endler's experiment did not employ the now typical design for a parallel/convergent evolution study, which would employ replicates of different ancestral lineages. We therefore implemented an experiment that seeded replicate mesocosms with small founding populations of guppies originating from high-predation populations of two very different lineages. The different mesocosms were maintained identically, and male guppy color was quantified every four months. After one year, we tested whether male color had increased, whether replicates within a lineage had parallel phenotypic trajectories, and whether the different lineages converged on a common phenotype. Results showed that male guppy color generally increased through time, primarily due to changes in melanic color, whereas the other colors showed inconsistent and highly variable trajectories. Most of the nonparallelism in phenotypic trajectories was among mesocosms containing different lineages. In addition to this mixture of parallelism and nonparallelism, convergence was not evident in that the variance in color among the mesocosms actually increased through time. We suggest that our results reflect the potential importance of high variation in female preference and stochastic processes such as drift and founder effects, both of which could be important in nature.

Integrating Genetic and Demographic Effects of Connectivity on Population Stability: The Case of Hatchery Trucking in Salmon

Connectivity among populations can have counteracting effects on population stability. Demographically, connectivity can rescue local populations but increase the synchrony across populations. Genetically, connectivity can counteract drift locally but homogenize genotypes across populations. Population independence and diversity underlies system-level buffering against environmental variability, termed the portfolio effect. The portfolio effect has declined in California fall-run Chinook salmon, possibly in part because of the trucking of juvenile hatchery-reared fish for downstream release, which reduces juvenile mortality but increases the connectivity between rivers. We use a dynamical population model to test whether this increased connectivity can explain the loss of the portfolio effect and quantify the relative demographic and genetic contributions to portfolio effect erosion. In the model, populations experience different within-population environmental conditions and the same time-variable ocean conditions, the response to which can depend on a quantitative genetic trait. We find that increased trucking for one population's hatchery can lead to a loss of the portfolio effect, with a system-level trade-off between increased average abundance and increased variability in abundance. This trade-off is much stronger when we include the effects of genetic homogenization than when we consider demographic synchronization alone. Therefore, genetic homogenization can outweigh demographic synchrony in determining the system-level effect of connectivity.

Phenological shifts of native and invasive species under climate change: insights from the Boechera-Lythrum model

Warmer and drier climates have shifted phenologies of many species. However, the magnitude and direction of phenological shifts vary widely among taxa, and it is often unclear when shifts are adaptive or how they affect long-term viability. Here, we model evolution of flowering phenology based on our long-term research of two species exhibiting opposite shifts in floral phenology: Lythrum salicaria, which is invasive in North America, and the sparse Rocky Mountain native Boechera stricta Genetic constraints are similar in both species, but differences in the timing of environmental conditions that favour growth lead to opposite phenological shifts under climate change. As temperatures increase, selection is predicted to favour earlier flowering in native B. stricta while reducing population viability, even if populations adapt rapidly to changing environmental conditions. By contrast, warming is predicted to favour delayed flowering in both native and introduced L. salicaria populations while increasing long-term viability. Relaxed selection from natural enemies in invasive L. salicaria is predicted to have little effect on flowering time but a large effect on reproductive fitness. Our approach highlights the importance of understanding ecological and genetic constraints to predict the ecological consequences of evolutionary responses to climate change on contemporary timescales.This article is part of the themed issue 'Human influences on evolution, and the ecological and societal consequences'.

The role of phenotypic plasticity on population differentiation

Several evolutionary processes shape the genetic and phenotypic differentiation of populations. Among them, the joint effects of gene flow, selection and phenotypic plasticity are poorly known, especially when trying to understand how maladaptive plasticity affects population divergence. We extended a quantitative genetic model of Hendry et al. (2001) to describe these joint effects on phenotypic and additive genetic divergence between two populations, and their phenotypic and genetic differentiation (PST and QST). With individual-based simulations, we tested our model predictions and further modeled allelic differentiation at neutral (FST) and adaptive (FSTQ) loci. While adaptive phenotypic plasticity allows for large phenotypic divergence and differentiation despite high gene flow, maladaptive plasticity promotes genetic divergence and generates countergradient variation, under extensive migration with phenotypic differences sometimes opposed to genetic differences. Maladaptive plasticity can also promote adaptive phenotypic divergence by reducing the effective gene flow. Overall, plasticity decouples genetic from phenotypic differences between populations, and blurs the correlation between phenotypic divergence and local adaptation. By deriving models of population differentiation for three different life cycles, we further describe the effect of a species' ecology on evolution in structured populations.

Genetics of dispersal

Dispersal is a process of central importance for the ecological and evolutionary dynamics of populations and communities, because of its diverse consequences for gene flow and demography. It is subject to evolutionary change, which begs the question, what is the genetic basis of this potentially complex trait? To address this question, we (i) review the empirical literature on the genetic basis of dispersal, (ii) explore how theoretical investigations of the evolution of dispersal have represented the genetics of dispersal, and (iii) discuss how the genetic basis of dispersal influences theoretical predictions of the evolution of dispersal and potential consequences.

Dispersal has a detectable genetic basis in many organisms, from bacteria to plants and animals. Generally, there is evidence for significant genetic variation for dispersal or dispersal‐related phenotypes or evidence for the micro‐evolution of dispersal in natural populations. Dispersal is typically the outcome of several interacting traits, and this complexity is reflected in its genetic architecture: while some genes of moderate to large effect can influence certain aspects of dispersal, dispersal traits are typically polygenic. Correlations among dispersal traits as well as between dispersal traits and other traits under selection are common, and the genetic basis of dispersal can be highly environment‐dependent.

By contrast, models have historically considered a highly simplified genetic architecture of dispersal. It is only recently that models have started to consider multiple loci influencing dispersal, as well as non‐additive effects such as dominance and epistasis, showing that the genetic basis of dispersal can influence evolutionary rates and outcomes, especially under non‐equilibrium conditions. For example, the number of loci controlling dispersal can influence projected rates of dispersal evolution during range shifts and corresponding demographic impacts. Incorporating more realism in the genetic architecture of dispersal is thus necessary to enable models to move beyond the purely theoretical towards making more useful predictions of evolutionary and ecological dynamics under current and future environmental conditions. To inform these advances, empirical studies need to answer outstanding questions concerning whether specific genes underlie dispersal variation, the genetic architecture of context‐dependent dispersal phenotypes and behaviours, and correlations among dispersal and other traits.

The spatial scale of local adaptation in a stochastic environment

The distribution of phenotypes in space will be a compromise between adaptive plasticity and local adaptation increasing the fit of phenotypes to local conditions and gene flow reducing that fit. Theoretical models on the evolution of quantitative characters on spatially explicit landscapes have only considered scenarios where optimum trait values change as deterministic functions of space. Here, these models are extended to include stochastic spatially autocorrelated aspects to the environment, and consequently the optimal phenotype. Under these conditions, the regression of phenotype on the environmental variable becomes steeper as the spatial scale on which populations are sampled becomes larger. Under certain deterministic models - such as linear clines - the regression is constant. The way in which the regression changes with spatial scale is informative about the degree of phenotypic plasticity, the relative scale of effective gene flow and the environmental dependency of selection. Connections to temporal models are discussed.

Trait dimensionality explains widespread variation in local adaptation

All species are locked in a continual struggle to adapt to local ecological conditions. In cases where species fail to locally adapt, they face reduced population growth rates, or even local extinction. Traditional explanations for limited local adaptation focus on maladaptive gene flow or homogeneous environmental conditions. These classical explanations have, however, failed to explain variation in the magnitude of local adaptation observed across taxa. Here we show that variable levels of local adaptation are better explained by trait dimensionality. First, we develop and analyse mathematical models that predict levels of local adaptation will increase with the number of traits experiencing spatially variable selection. Next, we test this prediction by estimating the relationship between dimensionality and local adaptation using data from 35 published reciprocal transplant studies. This analysis reveals a strong correlation between dimensionality and degree of local adaptation, and thus provides empirical support for the predictions of our model.

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.

Evolution of Quantitative Traits under a Migration-Selection Balance: When Does Skew Matter?

Quantitative-genetic models of differentiation under migration-selection balance often rely on the assumption of normally distributed genotypic and phenotypic values. When a population is subdivided into demes with selection toward different local optima, migration between demes may result in asymmetric, or skewed, local distributions. Using a simplified two-habitat model, we derive formulas without a priori assuming a Gaussian distribution of genotypic values, and we find expressions that naturally incorporate higher moments, such as skew. These formulas yield predictions of the expected divergence under migration-selection balance that are more accurate than models assuming Gaussian distributions, which illustrates the importance of incorporating these higher moments to assess the response to selection in heterogeneous environments. We further show with simulations that traits with loci of large effect display the largest skew in their distribution at migration-selection balance.

Multidimensional (co)evolutionary stability

The complexity of biotic and abiotic environmental conditions is such that the fitness of individuals is likely to depend on multiple traits. Using a synthetic framework of phenotypic evolution that draws from adaptive dynamics and quantitative genetics approaches, we explore how the number of traits under selection influences convergence stability and evolutionary stability in models for coevolution in multidimensional phenotype spaces. Our results allow us to identify three different effects of trait dimensionality on stability. First are (i) a "combinatorial effect": without epistasis and genetic correlations, a higher number of trait dimensions offers more opportunities for equilibria to be unstable; and (ii) epistatic interactions, that is, fitness interactions between traits, which tend to destabilize evolutionary equilibria; this effect increases with the dimension of phenotype space. These first two effects influence both convergence stability and evolutionary stability, while (iii) genetic correlations (due, e.g., to pleiotropy or linkage disequilibrium) can affect only convergence stability. We illustrate the general prediction that increased dimensionality destabilizes evolutionary equilibria using examples drawn from well-studied classical models of frequency-dependent competition for resources, adaptation to a spatially heterogeneous environment, and antagonistic coevolution. In addition, our analyses show that increased dimensionality can favor diversification, for example, in the form of local adaptation, as well as evolutionary escape.

Evolutionary responses of tree phenology to the combined effects of assortative mating, gene flow and divergent selection

The timing of bud burst (TBB) in temperate trees is a key adaptive trait, the expression of which is triggered by temperature gradients across the landscape. TBB is strongly correlated with flowering time and is therefore probably mediated by assortative mating. We derived theoretical predictions and realized numerical simulations of evolutionary changes in TBB in response to divergent selection and gene flow in a metapopulation. We showed that the combination of the environmental gradient of TBB and assortative mating creates contrasting genetic clines, depending on the direction of divergent selection. If divergent selection acts in the same direction as the environmental gradient (cogradient settings), genetic clines are established and inflated by assortative mating. Conversely, under divergent selection of the same strength but acting in the opposite direction (countergradient selection), genetic clines are slightly constrained. We explored the consequences of these dynamics for population maladaptation, by monitoring pollen swamping. Depending on the direction of divergent selection with respect to the environmental gradient, pollen filtering owing to assortative mating either facilitates or impedes adaptation in peripheral populations.

A two-locus model of spatially varying stabilizing or directional selection on a quantitative trait

The consequences of spatially varying, stabilizing or directional selection on a quantitative trait in a subdivided population are studied. A deterministic two-locus two-deme model is employed to explore the effects of migration, the degree of divergent selection, and the genetic architecture, i.e., the recombination rate and ratio of locus effects, on the maintenance of genetic variation. The possible equilibrium configurations are determined as functions of the migration rate. They depend crucially on the strength of divergent selection and the genetic architecture. The maximum migration rates are investigated below which a stable fully polymorphic equilibrium or a stable single-locus polymorphism can exist. Under stabilizing selection, but with different optima in the demes, strong recombination may facilitate the maintenance of polymorphism. However usually, and in particular with directional selection in opposite direction, the critical migration rates are maximized by a concentrated genetic architecture, i.e., by a major locus and a tightly linked minor one. Thus, complementing previous work on the evolution of genetic architectures in subdivided populations subject to diversifying selection, it is shown that concentrated architectures may aid the maintenance of polymorphism. Conditions are obtained when this is the case. Finally, the dependence of the phenotypic variance, linkage disequilibrium, and various measures of local adaptation and differentiation on the parameters is elaborated.

Evolutionary inferences from the analysis of exchangeability

Evolutionary inferences are usually based on statistical models that compare mean genotypes or phenotypes (or their frequencies) among populations. An alternative is to use the full distribution of genotypes and phenotypes to infer the "exchangeability" of individuals among populations. We illustrate this approach by using discriminant functions on principal components to classify individuals among paired lake and stream populations of threespine stickleback in each of six independent watersheds. Classification based on neutral and nonneutral microsatellite markers was highest to the population of origin and next highest to populations in the same watershed. These patterns are consistent with the influence of historical contingency (separate colonization of each watershed) and subsequent gene flow (within but not between watersheds). In comparison to this low genetic exchangeability, ecological (diet) and morphological (trophic and armor traits) exchangeability was relatively high-particularly among populations from similar habitats. These patterns reflect the role of natural selection in driving parallel adaptive changes when independent populations colonize similar habitats. Importantly, however, substantial nonparallelism was also evident. Our results show that analyses based on exchangeability can confirm inferences based on statistical analyses of means or frequencies, while also refining insights into the drivers of-and constraints on-evolutionary diversification.

The effects of stochastic and episodic movement of the optimum on the evolution of the G-matrix and the response of the trait mean to selection

Theoretical and empirical results demonstrate that the G-matrix, which summarizes additive genetic variances and covariances of quantitative traits, changes over time. Such evolution and fluctuation of the G-matrix could potentially have wide-ranging effects on phenotypic evolution. Nevertheless, no studies have yet addressed G-matrix stability and evolution when movement of an intermediate optimum includes large, episodic jumps or stochasticity. Here, we investigate such scenarios by using simulation-based models of G-matrix evolution. These analyses yield four important insights regarding the evolution and stability of the G-matrix. (i) Regardless of the model of peak movement, a moving optimum causes the G-matrix to orient towards the direction of net peak movement, so that genetic variance is enhanced in that direction (the variance enhancement effect). (ii) Peak movement skews the distribution of breeding values in the direction of movement, which impedes the response to selection. (iii) The stability of the G-matrix is affected by the overall magnitude and direction of peak movement, but modes and rates of peak movement have surprisingly small effects (the invariance principle). (iv) Both episodic and stochastic peak movement increase the probability that a population will fall below its carrying capacity and go extinct. We also present novel equations for the response of the trait mean to multivariate selection, which take into account the higher moments of the distribution of breeding values.

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.

Genetic basis of adaptation in Arabidopsis thaliana: local adaptation at the seed dormancy QTL DOG1

Local adaptation provides an opportunity to study the genetic basis of adaptation and investigate the allelic architecture of adaptive genes. We study delay of germination 1 (DOG1), a gene controlling natural variation in seed dormancy in Arabidopsis thaliana and investigate evolution of dormancy in 41 populations distributed in four regions separated by natural barriers. Using F(ST) and Q(ST) comparisons, we compare variation at DOG1 with neutral markers and quantitative variation in seed dormancy. Patterns of genetic differentiation among populations suggest that the gene DOG1 contributes to local adaptation. Although Q(ST) for seed dormancy is not different from F(ST) for neutral markers, a correlation with variation in summer precipitation supports that seed dormancy is adaptive. We characterize dormancy variation in several F(2) -populations and show that a series of functionally distinct alleles segregate at the DOG1 locus. Theoretical models have shown that the number and effect of alleles segregatin at quantitative trait loci (QTL) have important consequences for adaptation. Our results provide support to models postulating a large number of alleles at quantitative trait loci involved in adaptation.

The genetic architecture of adaptation under migration-selection balance

Many ecologically important traits have a complex genetic basis, with the potential for mutations at many different genes to shape the phenotype. Even so, studies of local adaptation in heterogeneous environments sometimes find that just a few quantitative trait loci (QTL) of large effect can explain a large percentage of observed differences between phenotypically divergent populations. As high levels of gene flow can swamp divergence at weakly selected alleles, migration-selection-drift balance may play an important role in shaping the genetic architecture of local adaptation. Here, we use analytical approximations and individual-based simulations to explore how genetic architecture evolves when two populations connected by migration experience stabilizing selection toward different optima. In contrast to the exponential distribution of allele effect sizes expected under adaptation without migration (Orr 1998), we find that adaptation with migration tends to result in concentrated genetic architectures with fewer, larger, and more tightly linked divergent alleles. Even if many small alleles contribute to adaptation at the outset, they tend to be replaced by a few large alleles under prolonged bouts of stabilizing selection with migration. All else being equal, we also find that stronger selection can maintain linked clusters of locally adapted alleles over much greater map distances than weaker selection. The common empirical finding of QTL of large effect is shown to be expected with migration in a heterogeneous landscape, and these QTL may often be composed of several tightly linked alleles of smaller effect.

Contemporary temperature-driven divergence in a Nordic freshwater fish under conditions commonly thought to hinder adaptation

Background

Evaluating the limits of adaptation to temperature is important given the IPCC-predicted rise in global temperatures. The rate and scope of evolutionary adaptation can be limited by low genetic diversity, gene flow, and costs associated with adaptive change. Freshwater organisms are physically confined to lakes and rivers, and must therefore deal directly with climate variation and change. In this study, we take advantage of a system characterised by low genetic variation, small population size, gene flow and between-trait trade-offs to study how such conditions affect the ability of a freshwater fish to adapt to climate change. We test for genetically-based differences in developmental traits indicating local adaptation, by conducting a common-garden experiment using embryos and larvae from replicate pairs of sympatric grayling demes that spawn and develop in natural cold and warm water, respectively. These demes have common ancestors from a colonization event 22 generations ago. Consequently, we explore if diversification may occur under severely constraining conditions.

Results

We found evidence for divergence in ontogenetic rates. The divergence pattern followed adaptation predictions as cold-deme individuals displayed higher growth rates and yolk conversion efficiency than warm-deme individuals at the same temperature. The cold-deme embryos had a higher rate of muscle mass development. Most of the growth- and development differences occurred prior to hatch. The divergence was probably not caused by genetic drift as there was a strong degree of parallelism in the divergence pattern and because phenotypic differentiation (Q_ST) was larger than estimated genetic drift levels (microsatellite F_ST) between demes from different temperature groups. We also document that these particular grayling populations cannot develop successfully at temperatures above 12°C, whereas other European populations can, and that increasing the muscle mass development rate comes at the cost of some skeletal trait development rates.

Conclusions

This study shows that genetically based phenotypic divergence can prevail even under conditions of low genetic variation and ongoing gene flow. Furthermore, population-specific maximum development temperatures along with musculoskeletal developmental trade-offs may constrain adaptation.