The evolution of genetic architecture under frequency-dependent disruptive selection

We propose a model to analyze a quantitative trait under frequency-dependent disruptive selection. Selection on the trait is a combination of stabilizing selection and intraspecific competition, where competition is maximal between individuals with equal phenotypes. In addition, there is a density-dependent component induced by population regulation. The trait is determined additively by a number of biallelic loci, which can have different effects on the trait value. In contrast to most previous models, we assume that the allelic effects at the loci can evolve due to epistatic interactions with the genetic background. Using a modifier approach, we derive analytical results under the assumption of weak selection and constant population size, and we investigate the full model by numerical simulations. We find that frequency-dependent disruptive selection favors the evolution of a highly asymmetric genetic architecture, where most of the genetic variation is concentrated on a small number of loci. We show that the evolution of genetic architecture can be understood in terms of the ecological niches created by competition. The phenotypic distribution of a population with an adapted genetic architecture closely matches this niche structure. Thus, evolution of the genetic architecture seems to be a plausible way for populations to adapt to regimes of frequency-dependent disruptive selection. As such, it should be seen as a potential evolutionary pathway to discrete polymorphisms and as a potential alternative to other evolutionary responses, such as the evolution of sexual dimorphism or assortative mating.     

Evolution and maintenance of the environmental component of the phenotypic variance: benefit of plastic traits under changing environments

How environmental variances in quantitative traits are influenced by variable environments is an important problem in evolutionary biology. In this study, the evolution and maintenance of phenotypic variance in a plastic trait under stabilizing selection are investigated. The mapping from genotypic value to phenotypic value of the quantitative trait is approximated by a linear reaction norm, with genotypic effects on its phenotypic mean and sensitivity to environment. The environmental deviation is assumed to be decomposed into environmental quality, which interacts with genotypic value, and residual developmental noise, which is independent of genotype. Environmental quality and the optimal phenotype of stabilizing selection are allowed to randomly fluctuate in both space and time, and individuals migrate equally before development and reproduction among different niches. Analyses show that phenotypic plasticity is adaptive within variable environments if correlations have become established between the optimal phenotype and environmental quality in space and/or time. The evolved plasticity increases with variances in optimal phenotypes and correlations between optimal phenotype and environmental quality; this further induces increases in mean fitness and the environmental variance in the trait. Under certain circumstances, however, the environmental variance may decrease with increase in variation in environmental quality.     

Niche construction and the environmental term of the price equation: How natural selection changes when organisms alter their environments

Organisms construct their own environments and phenotypes through the adaptive processes of habitat choice, habitat construction, and phenotypic plasticity. We examine how these processes affect the dynamics of mean fitness change through the environmental change term of the Price Equation. This tends to be ignored in evolutionary theory, owing to the emphasis on the first term describing the effect of natural selection on mean fitness (the additive genetic variance for fitness of Fisher's Fundamental Theorem). Using population genetic models and the Price Equation, we show how adaptive niche constructing traits favorably alter the distribution of environments that organisms encounter and thereby increase population mean fitness. Because niche-constructing traits increase the frequency of higher-fitness environments, selection favors their evolution. Furthermore, their alteration of the actual or experienced environmental distribution creates selective feedback between niche constructing traits and other traits, especially those with genotype-by-environment interaction for fitness. By altering the distribution of experienced environments, niche constructing traits can increase the additive genetic variance for such traits. This effect accelerates the process of overall adaption to the niche-constructed environmental distribution and can contribute to the rapid refinement of alternative phenotypic adaptations to different environments. Our findings suggest that evolutionary biologists revisit and reevaluate the environmental term of the Price Equation: owing to adaptive niche construction, it contributes directly to positive change in mean fitness; its magnitude can be comparable to that of natural selection; and, when there is fitness G × E, it increases the additive genetic variance for fitness, the much-celebrated first term.     

Selection experiments and the study of phenotypic plasticity1

Abstract Laboratory selection experiments are powerful tools for establishing evolutionary potentials. Such experiments provide two types of information, knowledge about genetic architecture and insight into evolutionary dynamics. They can be roughly classified into two types: (1) artificial selection in which the experimenter selects on a focal trait or trait index, and (2) quasi‐natural selection in which the experimenter establishes a set of environmental conditions and then allows the population to evolve. Both approaches have been used in the study of phenotypic plasticity. Artificial selection experiments have taken various forms including: selection directly on a reaction norm, selection on a trait in multiple environments, and selection on a trait in a single environment. In the latter experiments, evolution of phenotypic plasticity is investigated as a correlated response. Quasi‐natural selection experiments have examined the effects of both spatial and temporal variation. I describe how to carry out such experiments, summarize past efforts, and suggest further avenues of research.     

The evolution of genetic canalization under fluctuating selection

Abstract.— If the direction of selection changes from generation to generation, the ability to respond to selection is maladaptive: the response to selection in one generation leads to reduced fitness in the next. Because the response is determined by the amount of genetic variance expressed at the phenotypic level, rapidly fluctuating selection should favor modifier genes that reduce the phenotypic effect of alleles segregating at structural loci underlying the trait. Such reduction in phenotypic expression of genetic variation has been named "genetic canalization." I support this argument with a series of two- and multilocus models with alternating linear selection and Gaussian selection with fluctuating optimum. A canalizing modifier gene affects the fitness of its carriers in three ways: (1) it reduces the phenotypic consequences of genetic response to previous selection; (2) it reduces the genetic response to selection, which is manifested as linkage disequilibrium between the modifier and structural loci; and (3) it reduces the phenotypic variance. The first two effects reduce fitness under directional selection sustained for several generations, but improve fitness when the direction of selection has just been reversed. The net effect tends to favor a canalizing modifier under rapidly fluctuating selection regimes (period of eight generations or less). The third effect improves fitness of the modifier allele if the fitness function is convex and reduces it if the function is concave. Under fluctuating Gaussian selection, the population is more likely to experience the concave portion of the fitness function when selection is stronger. Therefore, only weak to moderately strong fluctuating Gaussian selection favors genetic canalization. This paper considerably broadens the conditions that favor genetic canalization, which so far has only been postulated to evolve under long-term stabilizing selection.     

Flowering time plasticity in Arabidopsis thaliana: a reanalysis of Westerman & Lawrence (1970)

Environmental variation in temperature can have dramatic effects on plant morphology, phenology, and fitness, and for this reason it is important to understand the evolutionary dynamics of phenotypic plasticity in response to temperature. We investigated constraints on the evolution of phenotypic plasticity in response to a temperature gradient in the model plant Arabidopsis thaliana by applying modern analytical tools to the classic data of Westerman & Lawrence (1970). We found significant evidence for two types of constraints. First, we detected numerous significant genetic correlations between plastic responses to temperature and the mean value of a trait across all environments, which differed qualitatively in pattern between the set of ecotypes and the set of mutant lines in the original sample. Secondly, we detected significant costs of flowering time plasticity in two of the three experimental environments, and a net pattern of selection against flowering time plasticity in the experiment overall. Thus, when explored with contemporary methods, the prescient work of Westerman & Lawrence (1970) provides new insights about evolutionary constraints on the evolution of plasticity.     

The adaptive dynamics of niche constructing traits in spatially subdivided populations: evolving posthumous extended phenotypes

Niche construction, by which organisms modify the environment in which they live, has been proposed to affect the evolution of many phenotypic traits. But what about the evolution of a niche constructing trait itself, whose expression changes the pattern of natural selection to which the trait is exposed in subsequent generations? This article provides an inclusive fitness analysis of selection on niche constructing phenotypes, which can affect their environment from local to global scales in arbitrarily spatially subdivided populations. The model shows that phenotypic effects of genes extending far beyond the life span of the actor can be affected by natural selection, provided they modify the fitness of those individuals living in the future that are likely to have inherited the niche construction lineage of the actor. Present benefits of behaviors are thus traded off against future indirect costs. The future costs will generally result from a complicated interplay of phenotypic effects, population demography and environmental dynamics. To illustrate these points, I derive the adaptive dynamics of a trait involved in the consumption of an abiotic resource, where resource abundance in future generations feeds back to the evolutionary dynamics of the trait.     

GENOTYPE-ENVIRONMENT INTERACTION AND THE EVOLUTION OF PHENOTYPIC PLASTICITY

Studies of spatial variation in the environment have primarily focused on how genetic variation can be maintained. Many one-locus genetic models have addressed this issue, but, for several reasons, these models are not directly applicable to quantitative (polygenic) traits. One reason is that for continuously varying characters, the evolution of the mean phenotype expressed in different environments (the norm of reaction) is also of interest. Our quantitative genetic models describe the evolution of phenotypic response to the environment, also known as phenotypic plasticity (Gause, 1947), and illustrate how the norm of reaction (Schmalhausen, 1949) can be shaped by selection. These models utilize the statistical relationship which exists between genotype-environment interaction and genetic correlation to describe evolution of the mean phenotype under soft and hard selection in coarse-grained environments. Just as genetic correlations among characters within a single environment can constrain the response to simultaneous selection, so can a genetic correlation between states of a character which are expressed in two environments. Unless the genetic correlation across environments is ± 1, polygenic variation is exhausted, or there is a cost to plasticity, panmictic populations under a bivariate fitness function will eventually attain the optimum mean phenotype for a given character in each environment. However, very high positive or negative correlations can substantially slow the rate of evolution and may produce temporary maladaptation in one environment before the optimum joint phenotype is finally attained. Evolutionary trajectories under hard and soft selection can differ: in hard selection, the environments with the highest initial mean fitness contribute most individuals to the mating pool. In both hard and soft selection, evolution toward the optimum in a rare environment is much slower than it is in a common one. A subdivided population model reveals that migration restriction can facilitate local adaptation. However, unless there is no migration or one of the special cases discussed for panmictic populations holds, no geographical variation in the norm of reaction will be maintained at equilibrium. Implications of these results for the interpretation of spatial patterns of phenotypic variation in natural populations are discussed.     

Scaling up phenotypic plasticity with hierarchical population models

Individuals respond to different environments by developing different phenotypes, which is generally seen as a mechanism through which individuals can buffer adverse environmental conditions and increase their fitness. To understand the consequences of phenotypic plasticity it is necessary to study how changing a particular trait of an individual affects either its survival, growth, reproduction or a combination of these demographic vital rates (i.e. fitness components). Integrating vital rate changes due to phenotypic plasticity into models of population dynamics allows detailed study of how phenotypic changes scale up to higher levels of integration and forms an excellent tool to distinguish those plastic trait changes that really matter at the population level. A modeling approach also facilitates studying systems that are even more complex: traits and vital rates often co-vary or trade-off with other traits that may show plastic responses over environmental gradients. Here we review recent developments in the literature on population models that attempt to include phenotypic plasticity with a range of evolutionary assumptions and modeling techniques. We present in detail a model framework in which environmental impacts on population dynamics can be followed analytically through direct and indirect pathways that importantly incorporate phenotypic plasticity, trait-trait and trait-vital rate relationships. We illustrate this framework with two case studies: the population-level consequences of phenotypic responses to nutrient enrichment of plant species occurring in nutrient-poor habitats and of responses to changes in flooding regimes due to climate change. We conclude with exciting prospects for further development of this framework: selection analyses, modeling advances and the inclusion of spatial dynamics by considering dispersal traits as well.     

Phenotypic plasticity and population viability: the importance of environmental predictability

Phenotypic plasticity plays a key role in modulating how environmental variation influences population dynamics, but we have only rudimentary understanding of how plasticity interacts with the magnitude and predictability of environmental variation to affect population dynamics and persistence. We developed a stochastic individual-based model, in which phenotypes could respond to a temporally fluctuating environmental cue and fitness depended on the match between the phenotype and a randomly fluctuating trait optimum, to assess the absolute fitness and population dynamic consequences of plasticity under different levels of environmental stochasticity and cue reliability. When cue and optimum were tightly correlated, plasticity buffered absolute fitness from environmental variability, and population size remained high and relatively invariant. In contrast, when this correlation weakened and environmental variability was high, strong plasticity reduced population size, and populations with excessively strong plasticity had substantially greater extinction probability. Given that environments might become more variable and unpredictable in the future owing to anthropogenic influences, reaction norms that evolved under historic selective regimes could imperil populations in novel or changing environmental contexts. We suggest that demographic models (e.g. population viability analyses) would benefit from a more explicit consideration of how phenotypic plasticity influences population responses to environmental change.     

Selection on skewed characters and the paradox of stasis

Observed phenotypic responses to selection in the wild often differ from predictions based on measurements of selection and genetic variance. An overlooked hypothesis to explain this paradox of stasis is that a skewed phenotypic distribution affects natural selection and evolution. We show through mathematical modeling that, when a trait selected for an optimum phenotype has a skewed distribution, directional selection is detected even at evolutionary equilibrium, where it causes no change in the mean phenotype. When environmental effects are skewed, Lande and Arnold's (1983) directional gradient is in the direction opposite to the skew. In contrast, skewed breeding values can displace the mean phenotype from the optimum, causing directional selection in the direction of the skew. These effects can be partitioned out using alternative selection estimates based on average derivatives of individual relative fitness, or additive genetic covariances between relative fitness and trait (Robertson–Price identity). We assess the validity of these predictions using simulations of selection estimation under moderate sample sizes. Ecologically relevant traits may commonly have skewed distributions, as we here exemplify with avian laying date — repeatedly described as more evolutionarily stable than expected — so this skewness should be accounted for when investigating evolutionary dynamics in the wild.     

When three traits make a line: evolution of phenotypic plasticity and genetic assimilation through linear reaction norms in stochastic environments

Genetic assimilation emerges from selection on phenotypic plasticity. Yet, commonly used quantitative genetics models of linear reaction norms considering intercept and slope as traits do not mimic the full process of genetic assimilation. We argue that intercept–slope reaction norm models are insufficient representations of genetic effects on linear reaction norms and that considering reaction norm intercept as a trait is unfortunate because the definition of this trait relates to a specific environmental value (zero) and confounds genetic effects on reaction norm elevation with genetic effects on environmental perception. Instead, we suggest a model with three traits representing genetic effects that, respectively, (i) are independent of the environment, (ii) alter the sensitivity of the phenotype to the environment and (iii) determine how the organism perceives the environment. The model predicts that, given sufficient additive genetic variation in environmental perception, the environmental value at which reaction norms tend to cross will respond rapidly to selection after an abrupt environmental change, and eventually becomes equal to the new mean environment. This readjustment of the zone of canalization becomes completed without changes in genetic correlations, genetic drift or imposing any fitness costs of maintaining plasticity. The asymptotic evolutionary outcome of this three‐trait linear reaction norm generally entails a lower degree of phenotypic plasticity than the two‐trait model, and maximum expected fitness does not occur at the mean trait values in the population.     

GENERALISTS,SPECIALISTS, AND THE EVOLUTION OF PHENOTYPIC PLASTICITY IN SYMPATRIC POPULATIONS OF DISTINCT SPECIES

The evolution of phenotypic plasticity is studied in a model with two reproductively isolated “species” in a coarse-grained environment, consisting of two types of habitats. A quantitative genetic model for selection was constructed, in which habitats differ in the optimal value for a focal trait, and with random dispersal among habitats. The main interest was to study the effects of different selection regimes. Three cases were investigated: (1) without any limits to plasticity; (2) without genetic variation for plasticity; and (3) with a fitness cost for phenotypically plastic reactions. In almost all cases a generalist strategy to exploit both habitats emerged. Without any limits to plasticity, optimal adaptive reactions evolved. Without any genetic variation for plasticity, a compromise strategy with an intermediate, fixed phenotype evolved, whereas in the presence of costs a plastic compromise between the demands of the habitats and the costs associated with plasticity was found. Specialization and phenotypic differentiation was only found when selection within habitats was severe and optimal phenotypes for different habitats were widely different. Under soft selection (local regulation of population numbers in each habitat) the specialists coexisted; under hard selection (global regulation of population numbers) one specialist outcompeted the other. The prevalent evolutionary outcome of compromises rather than specialization implies that costs or constraints are not necessarily detectable as local adaptation in transplantation or translocation experiments.     

Fluctuations in population composition dampen the impact of phenotypic plasticity on trait dynamics in superb fairy-wrens

1. In structured populations, phenotypic change can result from changes throughout an individual's lifetime (phenotypic plasticity, age-related changes), selection and changes in population composition (environment- or density-driven fluctuations in age-structure). 2. The contribution of population dynamics to phenotypic change has often been ignored. However, for understanding trait dynamics, it is important to identify both the individual- and population-level mechanisms responsible for trait change, because they potentially reinforce or counteract each other. 3. We use 22 years of field data to investigate the dynamics of a sexually selected phenological trait, the timing of nuptial moult in superb fairy-wrens Malurus cyaneus. 4. We show that trait expression is both climate- and age-dependent, but that phenotypic plasticity in response to climate variability also varies with age. Old males can acquire nuptial plumage very early after high rainfall, but 1- to 2-year-olds cannot. However, males of all ages that defer moult to later in the year acquire nuptial plumage earlier when conditions are warmer. 5. The underlying mechanism appears to be that old males may risk moulting in the most challenging period of the year: in autumn, when drought restricts food abundance and during the cold winter. By contrast, young males always moult during the spring transition to benign - warmer and generally wetter - conditions. Temperature changes dominate this transition that heralds the breeding season, thereby causing both young and late-moulting older birds to be temperature sensitive. 6. Climate and age also affect trait dynamics via a population dynamical pathway. The same high rainfall that triggers early moulting in old males concurrently increases offspring recruitment and thereby reduces the average age of males in the population. Consequently, effects of rainfall on trait dynamics through phenotypic plasticity of old males are dampened by synchronous rejuvenation of the age-structure. 7. A long-term trend towards drier environments prompted phenotypic change because of plasticity, but this was masked by climate-driven demographic change (causing apparent stasis). This suggests a novel explanation for why trait change may fail to reflect the observed pattern of directional selection or phenotypic plasticity.     

WHEN DO ADAPTIVE PLASTICITY AND GENETIC EVOLUTION PREVENT EXTINCTION OF A DENSITY‐REGULATED POPULATION?

We study the dynamics of evolutionary recovery after an abrupt environmental shift in a density‐regulated population with evolving plasticity. Maladaptation to the new environment initially causes the population to decline, until adaptive phenotypic plasticity and genetic evolution restore positive population growth rate. We assume that selection on a quantitative trait is density‐independent and that the initial cost of plasticity is much lower than the benefit of the initial plastic response. The initial partially adaptive plasticity reduces the effective magnitude of the environmental shift, whereas evolution of plasticity increases the rate of adaptation. Both effects greatly facilitate population persistence. In contrast, density dependence of population growth always hinders persistence. With θ‐logistic population regulation, a lower value of θ produces a faster initial population decline and a higher extinction risk.     

EVOLUTION OF PHENOTYPE–ENVIRONMENT ASSOCIATIONS BY GENETIC RESPONSES TO SELECTION AND PHENOTYPIC PLASTICITY IN A TEMPORALLY AUTOCORRELATED ENVIRONMENT

Covariation between population‐mean phenotypes and environmental variables, sometimes termed a “phenotype–environment association” (PEA), can result from phenotypic plasticity, genetic responses to natural selection, or both. PEAs can potentially provide information on the evolutionary dynamics of a particular set of populations, but this requires a full theoretical characterization of PEAs and their evolution. Here, we derive formulas for the expected PEA in a temporally fluctuating environment for a quantitative trait with a linear reaction norm. We compare several biologically relevant scenarios, including constant versus evolving plasticity, and the situation in which an environment affects both development and selection but at different time periods. We find that PEAs are determined not only by biological factors (e.g., magnitude of plasticity, genetic variation), but also environmental factors, such as the association between the environments of development and of selection, and in some cases the level of temporal autocorrelation. We also describe how a PEA can be used to estimate the relationship between an optimum phenotype and an environmental variable (i.e., the environmental sensitivity of selection), an important parameter for determining the extinction risk of populations experiencing environmental change. We illustrate this ability using published data on the predator‐induced morphological responses of tadpoles to predation risk.     

Adaptive divergence in body size overrides the effects of plasticity across natural habitats in the brown trout

The evolution of life-history traits is characterized by trade-offs between different selection pressures, as well as plasticity across environmental conditions. Yet, studies on local adaptation are often performed under artificial conditions, leaving two issues unexplored: (i) how consistent are laboratory inferred local adaptations under natural conditions and (ii) how much phenotypic variation is attributed to phenotypic plasticity and to adaptive evolution, respectively, across environmental conditions? We reared fish from six locally adapted (domesticated and wild) populations of anadromous brown trout (Salmo trutta) in one semi-natural and three natural streams and recorded a key life-history trait (body size at the end of first growth season). We found that population-specific reaction norms were close to parallel across different streams and Q_ST was similar – and larger than F_ST – within all streams, indicating a consistency of local adaptation in body size across natural environments. The amount of variation explained by population origin exceeded the variation across stream environments, indicating that genetic effects derived from adaptive processes have a stronger effect on phenotypic variation than plasticity induced by environmental conditions. These results suggest that plasticity does not “swamp” the phenotypic variation, and that selection may thus be efficient in generating genetic change.     

Quantitative trait loci mapping of phenotypic plasticity and genotype-environment interactions in plant and insect performance

Community genetic studies generally ignore the plasticity of the functional traits through which the effect is passed from individuals to the associated community. However, the ability of organisms to be phenotypically plastic allows them to rapidly adapt to changing environments and plasticity is commonly observed across all taxa. Owing to the fitness benefits of phenotypic plasticity, evolutionary biologists are interested in its genetic basis, which could explain how phenotypic plasticity is involved in the evolution of species interactions. Two current ideas exist: (i) phenotypic plasticity is caused by environmentally sensitive loci associated with a phenotype; (ii) phenotypic plasticity is caused by regulatory genes that simply influence the plasticity of a phenotype. Here, we designed a quantitative trait loci (QTL) mapping experiment to locate QTL on the barley genome associated with barley performance when the environment varies in the presence of aphids, and the composition of the rhizosphere. We simultaneously mapped aphid performance across variable rhizosphere environments. We mapped main effects, QTL × environment interaction (QTL×E), and phenotypic plasticity (measured as the difference in mean trait values) for barley and aphid performance onto the barley genome using an interval mapping procedure. We found that QTL associated with phenotypic plasticity were co-located with main effect QTL and QTL×E. We also located phenotypic plasticity QTL that were located separately from main effect QTL. These results support both of the current ideas of how phenotypic plasticity is genetically based and provide an initial insight into the functional genetic basis of how phenotypically plastic traits may still be important sources of community genetic effects.     

The timescale of environmental fluctuations determines the competitive advantages of phenotypic plasticity and rapid evolution

Organisms can respond to fluctuating environments by phenotypic plasticity and rapid evolution, both occurring on similar timescales to the environmental fluctuations. Because each adaptation mechanism has been independently studied, the effects of different adaptation mechanisms on ecological dynamics are not well understood. Here, using mathematical modeling, we compared the advantages of phenotypic plasticity and rapid evolution under conditions where the environment fluctuated between two states on various timescales. The results indicate that the advantages of phenotypic plasticity under environmental fluctuations on different timescales depend on the cost and the speed of plasticity. Both the speed of plastic adaptation and the cost of plasticity affect competition results, while the quantitative effects of them vary depending on the timescales. When the environment fluctuates on short timescales, the two populations with evolution and plasticity coexist, although the population with evolution is dominant. On moderate timescales, the two populations also coexist; however, the population with plasticity becomes dominant. On long timescales, whether the population with phenotypic plasticity or evolution is more advantageous depended on the cost of plasticity. Moreover, our results indicate that the mechanisms resulting in the dominance of the plastic population over the population with evolution are different depending on the timescales of environmental fluctuations. Therefore, the timescales of environmental fluctuations deserve more attention if we are to better understand the detailed competition results underlying phenotypic variation.     

Is photomorphogenic shade avoidance adaptive? Perspectives from population biology

Photomorphogenic shade avoidance responses provide an ideal model system for integrating genetic, physiological and population biology approaches to the study of adaptive plasticity. The adaptive plasticity hypothesis predicts that shade avoidance phenotypes induced by low ratios of red to far-red light (R:FR) will have high relative fitness in dense stands, but will suffer a fitness disadvantage at low density. Experiments with transgenic and mutant plants in which photomorphogenic genes are disabled, as well as phenotype manipulation by means of altered R:FR, strongly support the shade avoidance hypothesis. The observation of photomorphogenic ecotypes in different selective environments also suggests that the shade avoidance response has undergone adaptive evolution. Quantitative genetic variation in R:FR sensitivity has been detected in wild populations, indicating that the evolutionary potential exists for response to natural selection. However, evolutionary response may be constrained by genetic correlations among developmentally linked traits. Therefore it cannot be assumed that an observed suite of photomorphogenic responses represents an adaptive optimum for every trait.