Defining the landscape of adaptive genetic diversity

Whether they are used to describe fitness, genome architecture or the spatial distribution of environmental variables, the concept of a landscape has figured prominently in our collective reasoning. The tradition of landscapes in evolutionary biology is one of fitness mapped onto axes defined by phenotypes or molecular sequence states. The characteristics of these landscapes depend on natural selection, which is structured across both genomic and environmental landscapes, and thus, the bridge among differing uses of the landscape concept (i.e. metaphorically or literally) is that of an adaptive phenotype and its distribution across geographical landscapes in relation to selective pressures. One of the ultimate goals of evolutionary biology should thus be to construct fitness landscapes in geographical space. Natural plant populations are ideal systems with which to explore the feasibility of attaining this goal, because much is known about the quantitative genetic architecture of complex traits for many different plant species. What is less known are the molecular components of this architecture. In this issue of Molecular Ecology, Parchman et al. (2012) pioneer one of the first truly genome-wide association studies in a tree that moves us closer to this form of mechanistic understanding for an adaptive phenotype in natural populations of lodgepole pine (Pinus contorta Dougl. ex Loud.).     

Adaptive landscapes in evolving populations of Pseudomonas fluorescens

The repeatability of adaptive evolution depends on the ruggedness of the underlying adaptive landscape. We contrasted the relative ruggedness of two adaptive landscapes by measuring the variance in fitness and metabolic phenotype within and among genetically distinct strains of Pseudomonas fluorescens in two environments differing only in the carbon source provided (glucose vs. xylose). Fitness increased in all lines, plateauing in one environment but not the other. The pattern of variance in fitness among replicate lines was unique to the selection environment; it increased over the course of the experiment in xylose but not in glucose. Metabolic phenotypes displayed two results: (1) populations adapted via changes that were distinctive to their selection environment, and (2) endpoint phenotypes were less variable in glucose than in xylose. These results indicate that although the response to selection is highly repeatable at the level of fitness, the underlying genetic routes taken were different for each environment and more variable in xylose. We suggest that this reflects a more rugged adaptive landscape in xylose compared to glucose. Our study demonstrates the utility of using replicate selection lines with different evolutionary starting points to try and quantify the relative ruggedness of adaptive landscapes.     

The genetic architecture of novel trophic specialists: larger effect sizes are associated with exceptional oral jaw diversification in a pupfish adaptive radiation

The genetic architecture of adaptation is fundamental to understanding the mechanisms and constraints governing diversification. However, most case studies focus on loss of complex traits or parallel speciation in similar environments. It is still unclear how the genetic architecture of these local adaptive processes compares to the architecture of evolutionary transitions contributing to morphological and ecological novelty. Here, we identify quantitative trait loci (QTL) between two trophic specialists in an excellent case study for examining the origins of ecological novelty: a sympatric radiation of pupfishes endemic to San Salvador Island, Bahamas, containing a large‐jawed scale‐eater and a short‐jawed molluscivore with a skeletal nasal protrusion. These specialized niches and trophic traits are unique among over 2000 related species. Measurements of the fitness landscape on San Salvador demonstrate multiple fitness peaks and a larger fitness valley isolating the scale‐eater from the putative ancestral intermediate phenotype of the generalist, suggesting that more large‐effect QTL should contribute to its unique phenotype. We evaluated this prediction using an F2 intercross between these specialists. We present the first linkage map for pupfishes and detect significant QTL for sex and eight skeletal traits. Large‐effect QTL contributed more to enlarged scale‐eater jaws than the molluscivore nasal protrusion, consistent with predictions from the adaptive landscape. The microevolutionary genetic architecture of large‐effect QTL for oral jaws parallels the exceptional diversification rates of oral jaws within the San Salvador radiation observed over macroevolutionary timescales and may have facilitated exceptional trophic novelty in this system.     

Functional performance of turtle humerus shape across an ecological adaptive landscape

The concept of the adaptive landscape has been invaluable to evolutionary biologists for visualizing the dynamics of selection and adaptation, and is increasingly being used to study morpho‐functional data. Here, we construct adaptive landscapes to explore functional trade‐offs associated with variation in humerus morphology among turtles adapted to three different locomotor environments: marine, semiaquatic, and terrestrial. Humerus shape from 40 species of cryptodire turtles was quantified using a pseudolandmark approach. Hypothetical shapes were extracted in a grid across morphospace and four functional traits (strength, stride length, mechanical advantage, and hydrodynamics) measured on those shapes. Quantitative trait modeling was used to construct adaptive landscapes that optimize the functional traits for each of the three locomotor ecologies. Our data show that turtles living in different environments have statistically different humeral shapes. The optimum adaptive landscape for each ecology is defined by a different combination of performance trade‐offs, with turtle species clustering around their respective adaptive peak. Further, species adhere to pareto fronts between marine–semiaquatic and semiaquatic–terrestrial optima, but not between marine–terrestrial. Our study demonstrates the utility of adaptive landscapes in informing the link between form, function, and ecological adaptation, and establishes a framework for reconstructing turtle ecological evolution using isolated humeri from the fossil record.     

Fitness-associated recombination on rugged adaptive landscapes

A negative correlation between fitness and recombination rates seems to exist in various organisms. In this article we suggest that a correlation of that kind may play an important role in the evolution of complex traits. We study the effects of such fitness-associated recombination (FAR) in a simple two-locus deterministic model, as well as in a multi-loci NK rugged adaptive landscape. In both models studied, FAR results in faster adaptation and higher average population fitness, compared with uniform-rate recombination.     

The population genetics of adaptation on correlated fitness landscapes: the block model

Several recent theoretical studies of the genetics of adaptation have focused on the mutational landscape model, which considers evolution on rugged fitness landscapes (i.e., ones having many local optima). Adaptation in this model is characterized by several simple results. Here I ask whether these results also hold on correlated fitness landscapes, which are smoother than those considered in the mutational landscape model. In particular, I study the genetics of adaptation in the block model, a tunably rugged model of fitness landscapes. Considering the scenario in which adaptation begins from a high fitness wild-type DNA sequence, I use extreme value theory and computer simulations to study both single adaptive steps and entire adaptive walks. I show that all previous results characterizing single steps in adaptation in the mutational landscape model hold at least approximately on correlated landscapes in the block model; many entire-walk results, however, do not.     

Possible human impacts on adaptive radiation: beak size bimodality in Darwin's finches

Adaptive radiation is facilitated by a rugged adaptive landscape, where fitness peaks correspond to trait values that enhance the use of distinct resources. Different species are thought to occupy the different peaks, with hybrids falling into low-fitness valleys between them. We hypothesize that human activities can smooth adaptive landscapes, increase hybrid fitness and hamper evolutionary diversification. We investigated this possibility by analysing beak size data for 1755 Geospiza fortis measured between 1964 and 2005 on the island of Santa Cruz, Galápagos. Some populations of this species can display a resource-based bimodality in beak size, which mirrors the greater beak size differences among species. We first show that an historically bimodal population at one site, Academy Bay, has lost this property in concert with a marked increase in local human population density. We next show that a nearby site with lower human impacts, El Garrapatero, currently manifests strong bimodality. This comparison suggests that bimodality can persist when human densities are low (Academy Bay in the past, El Garrapatero in the present), but not when they are high (Academy Bay in the present). Human activities may negatively impact diversification in 'young' adaptive radiations, perhaps by altering adaptive landscapes.     

Simulating natural selection in landscape genetics

Linking landscape effects to key evolutionary processes through individual organism movement and natural selection is essential to provide a foundation for evolutionary landscape genetics. Of particular importance is determining how spatially-explicit, individual-based models differ from classic population genetics and evolutionary ecology models based on ideal panmictic populations in an allopatric setting in their predictions of population structure and frequency of fixation of adaptive alleles. We explore initial applications of a spatially-explicit, individual-based evolutionary landscape genetics program that incorporates all factors--mutation, gene flow, genetic drift and selection--that affect the frequency of an allele in a population. We incorporate natural selection by imposing differential survival rates defined by local relative fitness values on a landscape. Selection coefficients thus can vary not only for genotypes, but also in space as functions of local environmental variability. This simulator enables coupling of gene flow (governed by resistance surfaces), with natural selection (governed by selection surfaces). We validate the individual-based simulations under Wright-Fisher assumptions. We show that under isolation-by-distance processes, there are deviations in the rate of change and equilibrium values of allele frequency. The program provides a valuable tool (cdpop v1.0; http://cel.dbs.umt.edu/software/CDPOP/) for the study of evolutionary landscape genetics that allows explicit evaluation of the interactions between gene flow and selection in complex landscapes.     

Novel trophic niches drive variable progress towards ecological speciation within an adaptive radiation of pupfishes

Adaptive radiation is recognized by a rapid burst of phenotypic, ecological and species diversification. However, it is unknown whether different species within an adaptive radiation evolve reproductive isolation at different rates. We compared patterns of genetic differentiation between nascent species within an adaptive radiation of Cyprinodon pupfishes using genotyping by sequencing. Similar to classic adaptive radiations, this clade exhibits rapid morphological diversification rates and two species are novel trophic specialists, a scale‐eater and hard‐shelled prey specialist (durophage), yet the radiation is <10 000 years old. Both specialists and an abundant generalist species all coexist in the benthic zone of lakes on San Salvador Island, Bahamas. Based on 13 912 single‐nucleotide polymorphisms (SNPs), we found consistent differences in genetic differentiation between each specialist species and the generalist across seven lakes. The scale‐eater showed the greatest genetic differentiation and clustered by species across lakes, whereas durophage populations often clustered with sympatric generalist populations, consistent with parallel speciation across lakes. However, we found strong evidence of admixture between durophage populations in different lakes, supporting a single origin of this species and genome‐wide introgression with sympatric generalist populations. We conclude that the scale‐eater is further along the speciation‐with‐gene‐flow continuum than the durophage and suggest that different adaptive landscapes underlying these two niche environments drive variable progress towards speciation within the same habitat. Our previous measurements of fitness surfaces in these lakes support this conclusion: the scale‐eating fitness peak may be more distant than the durophage peak on the complex adaptive landscape driving adaptive radiation.     

The sensory ecology of adaptive landscapes

In complex environments, behavioural plasticity depends on the ability of an animal to integrate numerous sensory stimuli. The multidimensionality of factors interacting to shape plastic behaviour means it is difficult for both organisms and researchers to predict what constitutes an adaptive response to a given set of conditions. Although researchers may be able to map the fitness pay-offs of different behavioural strategies in changing environments, there is no guarantee that the study species will be able to perceive these pay-offs. We thus risk a disconnect between our own predictions about adaptive behaviour and what is behaviourally achievable given the umwelt of the animal being studied. This may lead to erroneous conclusions about maladaptive behaviour in circumstances when the behaviour exhibited is the most adaptive possible given sensory limitations. With advances in the computational resources available to behavioural ecologists, we can now measure vast numbers of interactions among behaviours and environments to create adaptive behavioural surfaces. These surfaces have massive heuristic, predictive and analytical potential in understanding adaptive animal behaviour, but researchers using them are destined to fail if they ignore the sensory ecology of the species they study. Here, we advocate the continued use of these approaches while directly linking them to perceptual space to ensure that the topology of the generated adaptive landscape matches the perceptual reality of the animal it intends to study. Doing so will allow predictive models of animal behaviour to reflect the reality faced by the agents on adaptive surfaces, vastly improving our ability to determine what constitutes an adaptive response for the animal in question.     

Environmental change exposes beneficial epistatic interactions in a catalytic RNA

Natural selection drives populations of individuals towards local peaks in a fitness landscape. These peaks are created by the interactions between individual mutations. Fitness landscapes may change as an environment changes. In a previous contribution, we discovered a variant of the Azoarcus group I ribozyme that represents a local peak in the RNA fitness landscape. The genotype at this peak is distinguished from the wild-type by four point mutations. We here report ribozyme fitness data derived from constructing all possible combinations of these point mutations. We find that these mutations interact epistatically. Importantly, we show that these epistatic interactions change qualitatively in the three different environments that we studied. We find examples where the relative fitness of a ribozyme can change from neutral or negative in one environment, to positive in another. We also show that the fitness effect of a specific GC-AU base pair switch is dependent on both the environment and the genetic context. Moreover, the mutations that we study improve activity at the cost of decreased structural stability. Environmental change is ubiquitous in nature. Our results suggest that such change can facilitate adaptive evolution by exposing new peaks of a fitness landscape. They highlight a prominent role for genotype-environment interactions in doing so.     

Geographic variation in the adaptive landscape for seed size at dispersal in the myrmecochorous <Emphasis Type="Italic">Helleborus foetidus</Emphasis>

Literature on seed dispersal mutualisms suggests that plant populations should hardly adapt to their current dispersers. We address the predictions that selection pressures exerted by ants on dispersal-related diaspore traits of the ant-dispersed Helleborus foetidus are highly variable in space, and that geographic (inter-population) variation in these traits is unrelated to selection by current dispersers. To test these predictions we use the concept of the quantitative adaptive landscape for seed size at dispersal. Such landscape depicts the relationship between the population’s mean trait value (mean seed size in the present study) and the population’s mean fitness (mean dispersal probability in the present study). Adaptive landscapes make it possible to assess whether the mean population’s phenotype agrees with one favored by selection. We first analyse, in 12 populations of H. foetidus from southern Spain, the extent of divergence among populations in seed and elaiosome size, and the abundance, composition, and behavior of the ant communities. Seeds from a fixed set of five of these populations were offered to ants in all the study sites to fit the adaptive landscape for seed size. In addition, seeds from the local population were also offered in each site. Our results show that seed size has undergone a larger divergence among populations than elaiosome size. Despite geographic variation in ant assemblages, the adaptive landscapes for seed size at dispersal were remarkably similar among sites: ants create disruptive selection on seed size in 10 out of 12 study sites. As predicted, the basic features of these adaptive landscapes (curvature and location of the minimum) varied geographically in accordance with variation in the size of seed dispersers. Also as predicted, in most populations, the observed mean seed size does not agree with that expected from the adaptive landscapes at dispersal. However, the relevance of dispersers for seed size evolution should not be neglected since the agreement between observed and optimum seed size was stronger where dispersers were more abundant. Thus, against the general view, our results evidence that, in H. foetidus, the observed geographic variation in dispersal-related plant traits is partly linked to selection exerted by current dispersers. Geographic variation in ant assemblages determines both the existence of a selection mosaic and the degree of adjustment of populations to the patterns of selection in the mosaic.     

Measure dynamics on a one-dimensional continuous trait space: theoretical foundations for adaptive dynamics

The measure dynamics approach to modelling single-species coevolution with a one-dimensional trait space is developed and compared to more traditional methods of adaptive dynamics and the Maximum Principle. It is assumed that individual fitness results from pairwise interactions together with a background fitness that depends only on total population size. When fitness functions are quadratic in the real variables parameterizing the one-dimensional traits of interacting individuals, the following results are derived. It is shown that among monomorphisms (i.e. measures supported on a single trait value), the continuously stable strategy (CSS) characterize those that are Lyapunov stable and attract all initial measures supported in an interval containing this trait value. In the cases where adaptive dynamics predicts evolutionary branching, convergence to a dimorphism is established. Extensions of these results to general fitness functions and/or multi-dimensional trait space are discussed.     

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.     

Divergent selection drives the adaptive radiation of crossbills

Abstract Knowledge of how phenotype influences fitness is necessary if we are to understand the basis of natural selection and how natural selection contributes to adaptive radiations. Here I quantify selection on a wild population of red crossbills ( Loxia curvirostra complex) in the South Hills, Idaho. Bill depth is the target of selection and selection on bill depth is stabilizing. I then show how fitness is related to both bill depth and performance. I use these and previously published relationships to estimate a fitness surface for five species of red crossbills that are part of an ongoing adaptive radiation in western North America. The fitness surface for crossbills has distinct peaks and valleys, with each crossbill species residing on or very near the summits. This work strongly supports a key tenet of the ecological theory of adaptive radiations; namely, divergent selection for utilizing alternative resources is the ultimate cause of adaptive radiations.     

Terrestrial insects and climate change: adaptive responses in key traits

Understanding and predicting how adaptation will contribute to species' resilience to climate change will be paramount to successfully managing biodiversity for conservation, agriculture, and human health‐related purposes. Making predictions that capture how species will respond to climate change requires an understanding of how key traits and environmental drivers interact to shape fitness in a changing world. Current trait‐based models suggest that low‐ to mid‐latitude populations will be most at risk, although these models focus on upper thermal limits, which may not be the most important trait driving species' distributions and fitness under climate change. In this review, we discuss how different traits (stress, fitness and phenology) might contribute and interact to shape insect responses to climate change. We examine the potential for adaptive genetic and plastic responses in these key traits and show that, although there is evidence of range shifts and trait changes, explicit consideration of what underpins these changes, be that genetic or plastic responses, is largely missing. Despite little empirical evidence for adaptive shifts, incorporating adaptation into models of climate change resilience is essential for predicting how species will respond under climate change. We are making some headway, although more data are needed, especially from taxonomic groups outside of Drosophila, and across diverse geographical regions. Climate change responses are likely to be complex, and such complexity will be difficult to capture in laboratory experiments. Moving towards well designed field experiments would allow us to not only capture this complexity, but also study more diverse species.     

The stationary distribution of a continuously varying strategy in a class-structured population under mutation-selection-drift balance

Many traits and/or strategies expressed by organisms are quantitative phenotypes. Because populations are of finite size and genomes are subject to mutations, these continuously varying phenotypes are under the joint pressure of mutation, natural selection and random genetic drift. This article derives the stationary distribution for such a phenotype under a mutation-selection-drift balance in a class-structured population allowing for demographically varying class sizes and/or changing environmental conditions. The salient feature of the stationary distribution is that it can be entirely characterized in terms of the average size of the gene pool and Hamilton's inclusive fitness effect. The exploration of the phenotypic space varies exponentially with the cumulative inclusive fitness effect over state space, which determines an adaptive landscape. The peaks of the landscapes are those phenotypes that are candidate evolutionary stable strategies and can be determined by standard phenotypic selection gradient methods (e.g. evolutionary game theory, kin selection theory, adaptive dynamics). The curvature of the stationary distribution provides a measure of the stability by convergence of candidate evolutionary stable strategies, and it is evaluated explicitly for two biological scenarios: first, a coordination game, which illustrates that, for a multipeaked adaptive landscape, stochastically stable strategies can be singled out by letting the size of the gene pool grow large; second, a sex-allocation game for diploids and haplo-diploids, which suggests that the equilibrium sex ratio follows a Beta distribution with parameters depending on the features of the genetic system.     

REDUCED GENETIC VARIANCE AMONG HIGH FITNESS INDIVIDUALS: INFERRING STABILIZING SELECTION ON MALE SEXUAL DISPLAYS IN DROSOPHILA SERRATA

Directional selection is prevalent in nature, yet phenotypes tend to remain relatively constant, suggesting a limit to trait evolution. However, the genetic basis of this limit is unresolved. Given widespread pleiotropy, opposing selection on a trait may arise from the effects of the underlying alleles on other traits under selection, generating net stabilizing selection on trait genetic variance. These pleiotropic costs of trait exaggeration may arise through any number of other traits, making them hard to detect in phenotypic analyses. Stabilizing selection can be inferred, however, if genetic variance is greater among low‐ compared to high‐fitness individuals. We extend a recently suggested approach to provide a direct test of a difference in genetic variance for a suite of cuticular hydrocarbons (CHCs) in Drosophila serrata. Despite strong directional sexual selection on these traits, genetic variance differed between high‐ and low‐fitness individuals and was greater among the low‐fitness males for seven of eight CHCs, significantly more than expected by chance. Univariate tests of a difference in genetic variance were nonsignificant but likely have low power. Our results suggest that further CHC exaggeration in D. serrata in response to sexual selection is limited by pleiotropic costs mediated through other traits.     

Evolutionary advantage of small populations on complex fitness landscapes

Recent experimental and theoretical studies have shown that small asexual populations evolving on complex fitness landscapes may achieve a higher fitness than large ones due to the increased heterogeneity of adaptive trajectories. Here, we introduce a class of haploid three-locus fitness landscapes that allow the investigation of this scenario in a precise and quantitative way. Our main result derived analytically shows how the probability of choosing the path of the largest initial fitness increase grows with the population size. This makes large populations more likely to get trapped at local fitness peaks and implies an advantage of small populations at intermediate time scales. The range of population sizes where this effect is operative coincides with the onset of clonal interference. Additional studies using ensembles of random fitness landscapes show that the results achieved for a particular choice of three-locus landscape parameters are robust and also persist as the number of loci increases. Our study indicates that an advantage for small populations is likely whenever the fitness landscape contains local maxima. The advantage appears at intermediate time scales, which are long enough for trapping at local fitness maxima to have occurred but too short for peak escape by the creation of multiple mutants.