Genetics, adaptation, and invasion in harsh environments

Adaptive colonization across a parasitism-mutualism gradient

Adaptive colonization is a process wherein a colonizing population exhibits an adaptive change in response to a novel environment, which may be critical to its establishment. To date, theoretical models of adaptive colonization have been based on single-species introductions. However, given their pervasiveness, symbionts will frequently be co-introduced with their hosts to novel areas. We present an individual-based model to investigate adaptive colonization by hosts and their symbionts across a parasite-mutualist continuum. The host must adapt in order to establish itself in the novel habitat, and the symbiont must adapt to track evolutionary change in the host. First, we classify the qualitative shifts in the outcome that can potentially be driven by non-neutral effects of the symbiont-host interaction into three main types: parasite-driven co-extinction, parasite release, and mutualistic facilitation. Second, we provide a detailed description of a specific example for each type of shift. Third, we disentangle how the interplay between symbiont transmissibility, host migration, and selection strength determines: (a) which type of shift is more likely to occur and (b) the size of the interaction effects necessary to produce it. Overall, we demonstrate the crucial role of host and symbiont dispersal scales in shaping the impacts of parasitism and mutualism on adaptive colonization.

Demographic feedbacks during evolutionary rescue can slow or speed adaptive evolution

Populations declining toward extinction can persist via genetic adaptation in a process called evolutionary rescue. Predicting evolutionary rescue has applications ranging from conservation biology to medicine, but requires understanding and integrating the multiple effects of a stressful environmental change on population processes. Here we derive a simple expression for how generation time, a key determinant of the rate of evolution, varies with population size during evolutionary rescue. Change in generation time is quantitatively predicted by comparing how intraspecific competition and the source of maladaptation each affect the rates of births and deaths in the population. Depending on the difference between two parameters quantifying these effects, the model predicts that populations may experience substantial changes in their rate of adaptation in both positive and negative directions, or adapt consistently despite severe stress. These predictions were then tested by comparison to the results of individual-based simulations of evolutionary rescue, which validated that the tolerable rate of environmental change varied considerably as described by analytical results. We discuss how these results inform efforts to understand wildlife disease and adaptation to climate change, evolution in managed populations and treatment resistance in pathogens.

Independently evolved pollution resistance in four killifish populations is largely explained by few variants of large effect

The genetic architecture of phenotypic traits can affect the mode and tempo of trait evolution. Human-altered environments can impose strong natural selection, where successful evolutionary adaptation requires swift and large phenotypic shifts. In these scenarios, theory predicts that adaptation is due to a few adaptive variants of large effect, but empirical studies that have revealed the genetic architecture of rapidly evolved phenotypes are rare, especially for populations inhabiting polluted environments. Fundulus killifish have repeatedly evolved adaptive resistance to extreme pollution in urban estuaries. Prior studies, including genome scans for signatures of natural selection, have revealed some of the genes and pathways important for evolved pollution resistance, and provide context for the genotype-phenotype association studies reported here. We created multiple quantitative trait locus (QTL) mapping families using progenitors from four different resistant populations, and using RAD-seq genetically mapped variation in sensitivity (developmental perturbations) following embryonic exposure to a model toxicant PCB-126. We found that one to two large-effect QTL loci accounted for resistance to PCB-mediated developmental toxicity. QTLs harbored candidate genes that govern the regulation of aryl hydrocarbon receptor (AHR) signaling. One QTL locus was shared across all populations and another was shared across three populations. One QTL locus showed strong signatures of recent natural selection in the corresponding wild population but another QTL locus did not. Some candidate genes for PCB resistance inferred from genome scans in wild populations were identified as QTL, but some key candidate genes were not. We conclude that rapidly evolved resistance to the developmental defects normally caused by PCB-126 is governed by few genes of large effect. However, other aspects of resistance beyond developmental phenotypes may be governed by additional loci, such that comprehensive resistance to PCB-126, and to the mixtures of chemicals that distinguish urban estuaries more broadly, may be more genetically complex.

Evolutionary rescue on genotypic fitness landscapes

Populations facing adverse environments, novel pathogens or invasive competitors may be destined to extinction if they are unable to adapt rapidly. Quantitative predictions of the probability of survival through adaptation, evolutionary rescue, have been previously developed for one of the most natural and well-studied mappings from an organism's traits to its fitness, Fisher's geometric model (FGM). While FGM assumes that all possible trait values are accessible via mutation, in many applications only a finite set of rescue mutations will be available, such as mutations conferring resistance to a parasite, predator or toxin. We predict the probability of evolutionary rescue, via de novo mutation, when this underlying genetic structure is included. We find that rescue probability is always reduced when its genetic basis is taken into account. Unlike other known features of the genotypic FGM, however, the probability of rescue increases monotonically with the number of available mutations and approaches the behaviour of the classical FGM as the number of available mutations approaches infinity.

Genetic Architecture of Flowering Time Differs Between Populations With Contrasting Demographic and Selective Histories

Understanding the evolutionary factors that impact the genetic architecture of traits is a central goal of evolutionary genetics. Here, we investigate how quantitative trait variation accumulated over time in populations that colonized a novel environment. We compare the genetic architecture of flowering time in Arabidopsis populations from the drought-prone Cape Verde Islands and their closest outgroup population from North Africa. We find that trait polygenicity is severely reduced in the island populations compared to the continental North African population. Further, trait architectures and reconstructed allelic histories best fit a model of strong directional selection in the islands in accord with a Fisher-Orr adaptive walk. Consistent with this, we find that large-effect variants that disrupt major flowering time genes (FRI and FLC) arose first, followed by smaller effect variants, including ATX2 L125F, which is associated with a 4-day reduction in flowering time. The most recently arising flowering time-associated loci are not known to be directly involved in flowering time, consistent with an omnigenic signature developing as the population approaches its trait optimum. Surprisingly, we find no effect in the natural population of EDI-Cvi-0 (CRY2 V367M), an allele for which an effect was previously validated by introgression into a Eurasian line. Instead, our results suggest the previously observed effect of the EDI-Cvi-0 allele on flowering time likely depends on genetic background, due to an epistatic interaction. Altogether, our results provide an empirical example of the effects demographic history and selection has on trait architecture.

Quantitative trait loci mapping reveals an oligogenic architecture of a rapidly adapting trait during the European invasion of common ragweed

Biological invasions offer a unique opportunity to investigate evolution over contemporary timescales. Rapid adaptation to local climates during range expansion can be a major determinant of invasion success, yet fundamental questions remain about its genetic basis. This study sought to investigate the genetic basis of climate adaptation in invasive common ragweed (Ambrosia artemisiifolia). Flowering time adaptation is key to this annual species' invasion success, so much so that it has evolved repeated latitudinal clines in size and phenology across its native and introduced ranges despite high gene flow among populations. Here, we produced a high-density linkage map (4493 SNPs) and paired this with phenotypic data from an F2 mapping population (n = 336) to identify one major and two minor quantitative trait loci (QTL) underlying flowering time and height differentiation in this species. Within each QTL interval, several candidate flowering time genes were also identified. Notably, the major flowering time QTL detected in this study was found to overlap with a previously identified haploblock (putative inversion). Multiple genetic maps of this region identified evidence of suppressed recombination in specific genotypes, consistent with inversions. These discoveries support the expectation that a concentrated genetic architecture with fewer, larger, and more tightly linked alleles should underlie rapid local adaptation during invasion, particularly when divergently adapting populations experience high levels of gene flow.

How does genetic architecture affect eco-evolutionary dynamics? A theoretical perspective

Recent studies have revealed the importance of feedbacks between contemporary rapid evolution (i.e. evolution that occurs through changes in allele frequencies) and ecological dynamics. Despite its inherent interdisciplinary nature, however, studies on eco-evolutionary feedbacks have been mostly ecological and tended to focus on adaptation at the phenotypic level without considering the genetic architecture of evolutionary processes. In empirical studies, researchers have often compared ecological dynamics when the focal species under selection has a single genotype with dynamics when it has multiple genotypes. In theoretical studies, common approaches are models of quantitative traits where mean trait values change adaptively along the fitness gradient and Mendelian traits with two alleles at a single locus. On the other hand, it is well known that genetic architecture can affect short-term evolutionary dynamics in population genetics. Indeed, recent theoretical studies have demonstrated that genetic architecture (e.g. the number of loci, linkage disequilibrium and ploidy) matters in eco-evolutionary dynamics (e.g. evolutionary rescue where rapid evolution prevents extinction and population cycles driven by (co)evolution). I propose that theoretical approaches will promote the synthesis of functional genomics and eco-evolutionary dynamics through models that combine population genetics and ecology as well as nonlinear time-series analyses using emerging big data.

This article is part of the theme issue ‘Genetic basis of adaptation and speciation: from loci to causative mutations’.

Symbiosis and stress: how plant microbiomes affect host evolution

Existing paradigms for plant microevolution rarely acknowledge the potential impacts of diverse microbiomes on evolutionary processes. Many plant-associated microorganisms benefit the host via access to resources, protection from pathogens, or amelioration of abiotic stress. In doing so, they alter the plant's perception of the environment, potentially reducing the strength of selection acting on plant stress tolerance or defence traits or altering the traits that are the target of selection. We posit that the microbiome can affect plant microevolution via (1) manipulation of plant phenotypes in ways that increase plant fitness under stress and (2) direct microbial responses to the environment that benefit the plant. Both mechanisms might favour plant genotypes that attract or stimulate growth of the most responsive microbial populations or communities. We provide support for these scenarios using infectious disease and quantitative genetics models. Finally, we discuss how beneficial plant-microbiome associations can evolve if traditional mechanisms maintaining cooperation in pairwise symbioses, namely partner fidelity, partner choice and fitness alignment, also apply to the interactions between plants and diverse foliar and soil microbiomes. To understand the role of the plant microbiome in host evolution will require a broad ecological understanding of plant-microbe interactions across both space and time. This article is part of the theme issue 'The role of the microbiome in host evolution'.

Different genetic basis for alcohol dehydrogenase activity and plasticity in a novel alcohol environment for Drosophila melanogaster

Phenotypic plasticity is known to enhance population persistence, facilitate adaptive evolution and initiate novel phenotypes in novel environments. How plasticity can contribute or hinder adaptation to different environments hinges on its genetic architecture. Even though plasticity in many traits is genetically controlled, whether and how plasticity's genetic architecture might change in novel environments is still unclear. Because much of gene expression can be environmentally influenced, each environment may trigger different sets of genes that influence a trait. Using a quantitative trait loci (QTL) approach, we investigated the genetic basis of plasticity in a classic functional trait, alcohol dehydrogenase (ADH) activity in D. melanogaster, across both historical and novel alcohol environments. Previous research in D. melanogaster has also demonstrated that ADH activity is plastic in response to alcohol concentration in substrates used by both adult flies and larvae. We found that across all environments tested, ADH activity was largely influenced by a single QTL encompassing the Adh-coding gene and its known regulatory locus, delta-1. After controlling for the allelic variation of the Adh and delta-1 loci, we found additional but different minor QTLs in the 0 and 14% alcohol environments. In contrast, we discovered no major QTL for plasticity itself, including the Adh locus, regardless of the environmental gradients. This suggests that plasticity in ADH activity is likely influenced by many loci with small effects, and that the Adh locus is not environmentally sensitive to dietary alcohol.

Selective Sweep at a QTL in a Randomly Fluctuating Environment

Adaptation is mediated by phenotypic traits that are often near continuous, and undergo selective pressures that may change with the environment. The dynamics of allelic frequencies at underlying quantitative trait loci (QTL) depend on their own phenotypic effects, but also possibly on other polymorphic loci affecting the same trait, and on environmental change driving phenotypic selection. Most environments include a substantial component of random noise, characterized both by its magnitude and its temporal autocorrelation, which sets the timescale of environmental predictability. I investigate the dynamics of a mutation affecting a quantitative trait in an autocorrelated stochastic environment that causes random fluctuations of an optimum phenotype. The trait under selection may also exhibit background polygenic variance caused by many polymorphic loci of small effects elsewhere in the genome. In addition, the mutation at the QTL may affect phenotypic plasticity, the phenotypic response of given genotype to its environment of development or expression. Stochastic environmental fluctuations increase the variance of the evolutionary process, with consequences for the probability of a complete sweep at the QTL. Background polygenic variation critically alters this process, by setting an upper limit to stochastic variance of population genetics at the QTL. For a plasticity QTL, stochastic fluctuations also influences the expected selection coefficient, and alleles with the same expected trajectory can have very different stochastic variances. Finally, a mutation may be favored through its effect on plasticity despite causing a systematic mismatch with optimum, which is compensated by evolution of the mean background phenotype.

Enduring extreme climate: Effects of severe drought on Triatoma brasiliensis populations in wild and man-made habitats of the Caatinga

Background

Triatoma brasiliensis, a triatomine-bug vector of Chagas disease, evolved in the semiarid Caatinga, where it occupies rocky outcrops, shrubby cacti, and human dwellings. Dwellings and rocks are considered high-quality microhabitats for this saxicolous species, whereas cacti probably represent secondary, lower-quality microhabitats. This ‘microhabitat-quality hierarchy’ hypothesis predicts that T. brasiliensis populations occupying dwellings or rocks should endure harsh environmental conditions better than their cactus-living relatives.

Methods/Findings

We tested this prediction by comparing T. brasiliensis infestation (proportion of microhabitats with bugs), density (bugs per microhabitat), and crowding (bugs per infested microhabitat) in dwellings, rocks, and cacti sampled before and during the extreme drought that ravaged the Caatinga in 2012–2016. We used random-intercepts generalized linear mixed models to account for microhabitat spatial clustering and for variations in bug-catch effort; we assessed model performance and computed model-averaged effect estimates using Akaike’s information criterion. Pre-drought infestation was similar across microhabitat types; during the drought, infestation remained stable in dwellings and rocks but dropped in cacti. Pre-drought bug density declined from dwellings to rocks to cacti; an additional decline associated with the drought was largely comparable across microhabitats, albeit perhaps somewhat larger in cacti. Finally, pre-drought bug crowding was higher in dwellings than in rocks or cacti and changed little during the drought–possibly with a downward trend in dwellings and an upward trend in cacti.

Conclusions

Triatoma brasiliensis populations fared better in dwellings and rocks than in cacti during extreme drought. Estimates of microhabitat and drought effects on infestation, density, and crowding suggest that only a few cacti (versus many rocks and dwellings) represent good-quality habitat under such extremely harsh conditions. Our findings provide empirical support to the microhabitat-quality hierarchy hypothesis, and imply that T. brasiliensis can endure extreme climate by exploiting high-quality microhabitats, whether wild or man-made, in the semiarid Caatinga.

Triatomine bugs, the vectors of Chagas disease, feed on vertebrate blood and occupy diverse microhabitats in close association with their hosts. Each bug species is adapted to particular, ‘primary’ microhabitats. Many species, however, also use ‘secondary’ microhabitats, sometimes including man-made structures. Secondary wild microhabitats are probably of lower overall quality than primary microhabitats, whereas human dwellings can be of higher overall quality if they provide a stable and abundant blood supply. This suggests that there may be a ‘hierarchy’ of triatomine microhabitat quality–top-quality dwellings, high-quality primary microhabitats, and low-quality secondary wild microhabitats. To test this hypothesis, we measured the impact of a severe drought on Triatoma brasiliensis populations living in dwellings and wild habitats, both primary (rocks) and secondary (shrubby cacti). Dwelling and rock bug populations remained largely stable during the drought, whereas most cactus-living populations either became extinct or shrunk to an undetectable size. A few cacti, however, supported relatively large bug colonies even during the drought, suggesting that they were of higher-than-average quality. Our findings provide support to the microhabitat-quality hierarchy hypothesis, and show that T. brasiliensis (and perhaps other triatomines) can endure extreme climate by exploiting (natural or man-made) high-quality microhabitats.

Quantifying the efficacy of genetic shifting in control of mosquito-borne diseases

Many of the world's most prevalent diseases are transmitted by animal vectors such as dengue transmitted by mosquitoes. To reduce these vector-borne diseases, a promising approach is "genetic shifting": selective breeding of the vectors to be more resistant to pathogens and releasing them to the target populations to reduce their ability to transmit pathogens, that is, lower their vector competence. The efficacy of genetic shifting will depend on possible counterforces such as natural selection against low vector competence. To quantitatively evaluate the potential efficacy of genetic shifting, we developed a series of coupled genetic-demographic models that simulate the changes of vector competence during releases of individuals with low vector competence. We modeled vector competence using different genetic architectures, as a multilocus, one-locus, or two-locus trait. Using empirically determined estimates of model parameters, the model predicted a reduction of mean vector competence of at least three standard deviations after 20 releases, one release per generation, and 10% of the size of the target population released each time. Sensitivity analysis suggested that release efficacy depends mostly on the vector competence of the released population, release size, release frequency, and the survivorship of the released individuals, with duration of the release program less important. Natural processes such as density-dependent survival and immigration from external populations also strongly influence release efficacy. Among different sex-dependent release strategies, releasing blood-fed females together with males resulted in the highest release efficacy, as these females mate in captivity and reproduce when released, thus contributing a greater proportion of low-vector-competence offspring. Conclusions were generally consistent across three models assuming different genetic architectures of vector competence, suggesting that genetic shifting could generally apply to various vector systems and does not require detailed knowledge of the number of loci contributing to vector competence.

Pulsed Immigration Events Can Facilitate Adaptation to Harsh Sink Environments

In nature, rates of dispersal vary greatly over time, yet most theoretical explorations of ecological and evolutionary dynamics to date have assumed constant movement rates. Here we examine how a particular pattern of temporal variation-periodic pulses of immigration-influences adaptation to a harsh environment, in which a species experiences conditions outside its niche requirements. Using both deterministic models and stochastic individual-based simulations, we show that for many ecological and genetic scenarios, temporally spacing out immigration events increases the probability that local adaptation is sufficient for persistence (i.e., niche evolution). When immigration events are too frequent, gene flow can hamper local adaptation in sexual species, but sufficiently infrequent pulses of immigration allow for repeated opportunities for adaptation with temporary escapes from gene flow during which local selection is unleashed. We develop versions of our models with and without density dependence for three different assumptions about the genetics underlying fitness (haploid, diploid, and quantitative genetic variation) so that our results may be applicable to a wide range of natural systems. Our study adds to a growing body of literature showing that temporal variation in migration rates can have significant effects on local adaptation and is among the first to show how such variation affects niche evolution.

Estimation of Genetic Variance in Fitness, and Inference of Adaptation, When Fitness Follows a Log-Normal Distribution

Additive genetic variance in relative fitness (σA2(w)) is arguably the most important evolutionary parameter in a population because, by Fisher’s fundamental theorem of natural selection (FTNS; Fisher RA. 1930. The genetical theory of natural selection. 1st ed. Oxford: Clarendon Press), it represents the rate of adaptive evolution. However, to date, there are few estimates of σA2(w) in natural populations. Moreover, most of the available estimates rely on Gaussian assumptions inappropriate for fitness data, with unclear consequences. “Generalized linear animal models” (GLAMs) tend to be more appropriate for fitness data, but they estimate parameters on a transformed (“latent”) scale that is not directly interpretable for inferences on the data scale. Here we exploit the latest theoretical developments to clarify how best to estimate quantitative genetic parameters for fitness. Specifically, we use computer simulations to confirm a recently developed analog of the FTNS in the case when expected fitness follows a log-normal distribution. In this situation, the additive genetic variance in absolute fitness on the latent log-scale (σA2(l)) equals (σA2(w)) on the data scale, which is the rate of adaptation within a generation. However, due to inheritance distortion, the change in mean relative fitness between generations exceeds σA2(l) and equals (exp⁡(σA2(l))−1). We illustrate why the heritability of fitness is generally low and is not a good measure of the rate of adaptation. Finally, we explore how well the relevant parameters can be estimated by animal models, comparing Gaussian models with Poisson GLAMs. Our results illustrate 1) the correspondence between quantitative genetics and population dynamics encapsulated in the FTNS and its log-normal-analog and 2) the appropriate interpretation of GLAM parameter estimates.

A general framework for modelling the impact of co-infections on pathogen evolution

Theoretical models suggest that mixed-strain infections, or co-infections, are an important driver of pathogen evolution. However, the within-host dynamics of co-infections vary enormously, which complicates efforts to develop a general understanding of how co-infections affect evolution. Here, we develop a general framework which condenses the within-host dynamics of co-infections into a few key outcomes, the most important of which is the overall R₀ of the co-infection. Similar to how fitness is determined by two different alleles in a heterozygote, the R₀ of a co-infection is a product of the R₀ values of the co-infecting strains, shaped by the interaction of those strains at the within-host level. Extending the analogy, we propose that the overall R₀ reflects the dominance of the co-infecting strains, and that the ability of a mutant strain to invade a population is a function of its dominance in co-infections. To illustrate the utility of these concepts, we use a within-host model to show how dominance arises from the within-host dynamics of a co-infection, and then use an epidemiological model to demonstrate that dominance is a robust predictor of the ability of a mutant strain to save a maladapted wild-type strain from extinction (evolutionary emergence).

Standing genomic variation within coding and regulatory regions contributes to the adaptive capacity to climate in a foundation tree species

Global climate is rapidly changing, and the ability for tree species to adapt is dependent on standing genomic variation; however, the distribution and abundance of functional and adaptive variants are poorly understood in natural systems. We test key hypotheses regarding the genetics of adaptive variation in a foundation tree: genomic variation is associated with climate, and genomic variation is more likely to be associated with temperature than precipitation or aridity. To test these hypotheses, we used 9,593 independent, genomic single-nucleotide polymorphisms (SNPs) from 270 individuals sampled from Corymbia calophylla's entire distribution in south-western Western Australia, spanning orthogonal temperature and precipitation gradients. Environmental association analyses returned 537 unique SNPs putatively adaptive to climate. We identified SNPs associated with climatic variation (i.e., temperature [458], precipitation [75] and aridity [78]) across the landscape. Of these, 78 SNPs were nonsynonymous (NS), while 26 SNPs were found within gene regulatory regions. The NS and regulatory candidate SNPs associated with temperature explained more deviance (27.35%) than precipitation (5.93%) and aridity (4.77%), suggesting that temperature provides stronger adaptive signals than precipitation. Genes associated with adaptive variants include functions important in stress responses to temperature and precipitation. Patterns of allelic turnover of NS and regulatory SNPs show small patterns of change through climate space with the exception of an aldehyde dehydrogenase gene variant with 80% allelic turnover with temperature. Together, these findings provide evidence for the presence of adaptive variation to climate in a foundation species and provide critical information to guide adaptive management practices.

Evolutionary Rescue in a Linearly Changing Environment: Limits on Predictability

Populations subject to substantial environmental change that decreases absolute fitness (expected number of offspring per individual) to less than one must adapt to persist. The probability of adaptive evolutionary rescue may be influenced by factors intrinsic to the organism itself, or by features specific to the individual population and its environment. An important question (given the increasing prevalence of environmental change) is the predictability of evolutionary rescue. We used an individual-based simulation model and a related analytic model to examine population persistence, given a continuously changing environment that leads to a linear change in the optimum for a phenotypic trait under selection. Population persistence was not well predicted by the population genetics at the start of environmental change, which contrasts strongly with the results shown in prior work for persistence after a sudden environmental change. Larger populations, which had a greater scope for the generation and maintenance of beneficial genetic variation, showed a clear advantage, but increasing the rate of environmental change always decreased the probability of persistence. Extinctions occurred throughout the period of continuous change, and populations that went extinct showed little sign of their eventual fate until shortly before extinction. Partially clonal populations showed less predictability and greater vulnerability to extinction when impacted by continuous change than did fully sexual populations-any advantage gained by the initial transmission of well-adapted phenotypes via clonal reproduction is lost as the phenotypic optimum continues to shift and the generation of novel variation is required for continuous adaptation.

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.

Evolutionary Rescue over a Fitness Landscape

Evolutionary rescue describes a situation where adaptive evolution prevents the extinction of a population facing a stressing environment. Models of evolutionary rescue could in principle be used to predict the level of stress beyond which extinction becomes likely for species of conservation concern, or, conversely, the treatment levels most likely to limit the emergence of resistant pests or pathogens. Stress levels are known to affect both the rate of population decline (demographic effect) and the speed of adaptation (evolutionary effect), but the latter aspect has received less attention. Here, we address this issue using Fisher's geometric model of adaptation. In this model, the fitness effects of mutations depend both on the genotype and the environment in which they arise. In particular, the model introduces a dependence between the level of stress, the proportion of rescue mutants, and their costs before the onset of stress. We obtain analytic results under a strong-selection-weak-mutation regime, which we compare to simulations. We show that the effect of the environment on evolutionary rescue can be summarized into a single composite parameter quantifying the effective stress level, which is amenable to empirical measurement. We describe a narrow characteristic stress window over which the rescue probability drops from very likely to very unlikely as the level of stress increases. This drop is sharper than in previous models, as a result of the decreasing proportion of stress-resistant mutations as stress increases. We discuss how to test these predictions with rescue experiments across gradients of stress.

Predicting evolutionary rescue via evolving plasticity in stochastic environments

Phenotypic plasticity and its evolution may help evolutionary rescue in a novel and stressful environment, especially if environmental novelty reveals cryptic genetic variation that enables the evolution of increased plasticity. However, the environmental stochasticity ubiquitous in natural systems may alter these predictions, because high plasticity may amplify phenotype-environment mismatches. Although previous studies have highlighted this potential detrimental effect of plasticity in stochastic environments, they have not investigated how it affects extinction risk in the context of evolutionary rescue and with evolving plasticity. We investigate this question here by integrating stochastic demography with quantitative genetic theory in a model with simultaneous change in the mean and predictability (temporal autocorrelation) of the environment. We develop an approximate prediction of long-term persistence under the new pattern of environmental fluctuations, and compare it with numerical simulations for short- and long-term extinction risk. We find that reduced predictability increases extinction risk and reduces persistence because it increases stochastic load during rescue. This understanding of how stochastic demography, phenotypic plasticity, and evolution interact when evolution acts on cryptic genetic variation revealed in a novel environment can inform expectations for invasions, extinctions, or the emergence of chemical resistance in pests.

Stochastic Evolutionary Demography under a Fluctuating Optimum Phenotype

Many natural populations exhibit temporal fluctuations in abundance that are consistent with external forcing by a randomly changing environment. As fitness emerges from an interaction between the phenotype and the environment, such demographic fluctuations probably include a substantial contribution from fluctuating phenotypic selection. We study the stochastic population dynamics of a population exposed to random (plus possibly directional) changes in the optimum phenotype for a quantitative trait that evolves in response to this moving optimum. We derive simple analytical predictions for the distribution of log population size over time both transiently and at stationarity under Gompertz density regulation. These predictions are well matched by population- and individual-based simulations. The log population size is approximately reverse gamma distributed, with a negative skew causing an excess of low relative to high population sizes, thus increasing extinction risk relative to a symmetric (e.g., normal) distribution with the same mean and variance. Our analysis reveals how the mean and variance of log population size change with the variance and autocorrelation of deviations of the evolving mean phenotype from the optimum. We apply our results to the analysis of evolutionary rescue in a stochastic environment and show that random fluctuations in the optimum can substantially increase extinction risk by both reducing the expected growth rate and increasing the variance of population size by several orders of magnitude.

Effects of Clonal Reproduction on Evolutionary Lag and Evolutionary Rescue

Evolutionary lag-the difference between mean and optimal phenotype in the current environment-is of keen interest in light of rapid environmental change. Many ecologically important organisms have life histories that include stage structure and both sexual and clonal reproduction, yet how stage structure and clonality interplay to govern a population's rate of evolution and evolutionary lag is unknown. Effects of clonal reproduction on mean phenotype partition into two portions: one that is phenotype dependent, and another that is genotype dependent. This partitioning is governed by the association between the nonadditive genetic plus random environmental component of phenotype of clonal offspring and their parents. While clonality slows phenotypic evolution toward an optimum, it can dramatically increase population survival after a sudden step change in optimal phenotype. Increased adult survival slows phenotypic evolution but facilitates population survival after a step change; this positive effect can, however, be lost given survival-fecundity trade-offs. Simulations indicate that the benefits of increased clonality under environmental change greatly depend on the nature of that change: increasing population persistence under a step change while decreasing population persistence under a continuous linear change requiring de novo variation. The impact of clonality on the probability of persistence for species in a changing world is thus inexorably linked to the temporal texture of the change they experience.

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.

Evolving mutation rate advances the invasion speed of a sexual species

Background

Many species are shifting their ranges in response to global climate change. Range expansions are known to have profound effects on the genetic composition of populations. The evolution of dispersal during range expansion increases invasion speed, provided that a species can adapt sufficiently fast to novel local conditions. Genetic diversity at the expanding range border is however depleted due to iterated founder effects. The surprising ability of colonizing species to adapt to novel conditions while being subjected to genetic bottlenecks is termed ‘the genetic paradox of invasive species’. Mutational processes have been argued to provide an explanation for this paradox. Mutation rates can evolve, under conditions that favor an increased rate of adaptation, by hitchhiking on beneficial mutations through induced linkage disequilibrium. Here we argue that spatial sorting, iterated founder events, and population structure benefit the build-up and maintenance of such linkage disequilibrium. We investigate if the evolution of mutation rates could play a role in explaining the ‘genetic paradox of invasive species’ for a sexually reproducing species colonizing a landscape of gradually changing conditions.

Results

We use an individual-based model to show the evolutionary increase of mutation rates in sexual populations during range expansion, in coevolution with the dispersal probability. The observed evolution of mutation rate is adaptive and clearly advances invasion speed both through its effect on the evolution of dispersal probability, and the evolution of local adaptation. This also occurs under a variable temperature gradient, and under the assumption of 90% lethal mutations.

Conclusions

In this study we show novel consequences of the particular genetic properties of populations under spatial disequilibrium, i.e. the coevolution of dispersal probability and mutation rate, even in a sexual species and under realistic spatial gradients, resulting in faster invasions. The evolution of mutation rates can therefore be added to the list of possible explanations for the ‘genetic paradox of invasive species’. We conclude that range expansions and the evolution of mutation rates are in a positive feedback loop, with possibly far-reaching ecological consequences concerning invasiveness and the adaptability of species to novel environmental conditions.

Electronic supplementary material

The online version of this article (doi:10.1186/s12862-017-0998-8) contains supplementary material, which is available to authorized users.

Evolution and the duration of a doomed population

Many populations are doomed to extinction, but little is known about how evolution contributes to their longevity. We address this by modeling an asexual population consisting of genotypes whose abundances change independently according to a system of continuous branching diffusions. Each genotype is characterized by its initial abundance, growth rate, and reproductive variance. The latter two components determine the genotype's "risk function" which describes its per capita probability of extinction at any time. We derive the probability distribution of extinction times for a polymorphic population, which can be expressed in terms of genotypic risk functions. We use this to explore how spontaneous mutation, abrupt environmental change, or population supplementation and removal affect the time to extinction. Results suggest that evolution based on new mutations does little to alter the time to extinction. Abrupt environmental changes that affect all genotypes can have more substantial impact, but, curiously, a beneficial change does more to extend the lifetime of thriving than threatened populations of the same initial abundance. Our results can be used to design policies that meet specific conservation goals or management strategies that speed the elimination of agricultural pests or human pathogens.

Rapid Adaptation of a Polygenic Trait After a Sudden Environmental Shift

Although a number of studies have shown that natural and laboratory populations initially well adapted to their environment can evolve rapidly when conditions suddenly change, the dynamics of rapid adaptation are not well understood. Here a population genetic model of polygenic selection is analyzed to describe the short-term response of a quantitative trait after a sudden shift of the phenotypic optimum. We provide explicit analytical expressions for the timescales over which the trait mean approaches the new optimum. We find that when the effect sizes are small relative to a scaled mutation rate, small to moderate allele frequency changes occur in the short-term phase in a synergistic fashion. In contrast, selective sweeps, i.e., dramatic changes in the allele frequency, may occur provided the size of the effect is sufficiently large. Applications of our theoretical results to the relationship between QTL and selective sweep mapping and to tests of fast polygenic adaptation are discussed.

Project Baseline: An unprecedented resource to study plant evolution across space and time

PREMISE OF THE STUDY

Project Baseline is a seed bank that offers an unprecedented opportunity to examine spatial and temporal dimensions of microevolution during an era of rapid environmental change. Over the upcoming 50 years, biologists will withdraw genetically representative samples of past populations from this time capsule of seeds and grow them contemporaneously with modern samples to detect any phenotypic and molecular evolution that has occurred during the intervening time.

METHODS

We carefully developed this living genome bank using protocols to enhance its experimental value by collecting from multiple populations and species across a broad geographical range in sites that are likely to be preserved into the future. Seeds are accessioned with site and population data and are stored by maternal line under conditions that maximize seed longevity. This open-access resource will be available to researchers at regular intervals to evaluate contemporary evolution.

KEY RESULTS

To date, the Project Baseline collection includes 100-200 maternal lines of each of 61 species collected from over 831 populations on sites that are likely to be preserved into the future across the United States (∼78,000 maternal lines). Our strategically designed collection circumvents some problems that can cloud the results of "resurrection" studies involving naturally preserved or existing seed collections that are available fortuitously.

CONCLUSIONS

The resurrection approach can be coupled with long-established and newer techniques over the next five decades to elucidate genetic change and thereby vastly improve our understanding of temporal and spatial changes in phenotype and the evolutionary processes underlying it.

Is adaptation to climate change really constrained in niche specialists?

Species with restricted distributions make up the vast majority of biodiversity. Recent evidence suggests that Drosophila species with restricted tropical distributions lack genetic variation in the key trait of desiccation resistance. It has therefore been predicted that tropically restricted species will be limited in their evolutionary response to future climatic changes and will face higher risks of extinction. However, these assessments have been made using extreme levels of desiccation stress (less than 10% relative humidity (RH)) that extend well beyond the changes projected for the wet tropics under climate change scenarios over the next 30 years. Here, we show that significant evolutionary responses to less extreme (35% RH) but more ecologically realistic levels of climatic change and desiccation stress are in fact possible in two species of rainforest restricted Drosophila. Evolution may indeed be an important means by which sensitive rainforest-restricted species are able to mitigate the effects of climate change.

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.

Catch Me if You Can: Adaptation from Standing Genetic Variation to a Moving Phenotypic Optimum

Adaptation lies at the heart of Darwinian evolution. Accordingly, numerous studies have tried to provide a formal framework for the description of the adaptive process. Of these, two complementary modeling approaches have emerged: While so-called adaptive-walk models consider adaptation from the successive fixation of de novo mutations only, quantitative genetic models assume that adaptation proceeds exclusively from preexisting standing genetic variation. The latter approach, however, has focused on short-term evolution of population means and variances rather than on the statistical properties of adaptive substitutions. Our aim is to combine these two approaches by describing the ecological and genetic factors that determine the genetic basis of adaptation from standing genetic variation in terms of the effect-size distribution of individual alleles. Specifically, we consider the evolution of a quantitative trait to a gradually changing environment. By means of analytical approximations, we derive the distribution of adaptive substitutions from standing genetic variation, that is, the distribution of the phenotypic effects of those alleles from the standing variation that become fixed during adaptation. Our results are checked against individual-based simulations. We find that, compared to adaptation from de novo mutations, (i) adaptation from standing variation proceeds by the fixation of more alleles of small effect and (ii) populations that adapt from standing genetic variation can traverse larger distances in phenotype space and, thus, have a higher potential for adaptation if the rate of environmental change is fast rather than slow.

The extent of hybridization and its impact on the genetic diversity and population structure of an invasive tree, Ulmus pumila (Ulmaceae)

Ulmus pumila is considered an invasive tree in 41 of the United States. In this study, we examined the extent of hybridization in naturalized populations of U. pumila, its impact on genetic diversity and genetic structure and its potential role in explaining the invasion process of U. pumila. Genetic analyses indicated widespread hybridization with native Ulmus rubra in naturalized U. pumila populations. Hybridization increased the genetic diversity of U. pumila populations and affected their genetic structure. The level of genetic diversity in 'mature' accessions, many of which may represent original plantings throughout the USA, was high and similar to the diversity of East Asian accessions. Hybridization with the native red elm may play an important role in the success of Siberian elm as an invader in temperate regions of the USA.

Evolutionary rescue: linking theory for conservation and medicine

Evolutionary responses that rescue populations from extinction when drastic environmental changes occur can be friend or foe. The field of conservation biology is concerned with the survival of species in deteriorating global habitats. In medicine, in contrast, infected patients are treated with chemotherapeutic interventions, but drug resistance can compromise eradication of pathogens. These contrasting biological systems and goals have created two quite separate research communities, despite addressing the same central question of whether populations will decline to extinction or be rescued through evolution. We argue that closer integration of the two fields, especially of theoretical understanding, would yield new insights and accelerate progress on these applied problems. Here, we overview and link mathematical modelling approaches in these fields, suggest specific areas with potential for fruitful exchange, and discuss common ideas and issues for empirical testing and prediction.

Molecular markers reveal narrow genetic base and culturing-associated genetic drift in Teretrius nigrescens Lewis populations released for the biological control of the larger grain borer in Africa

In biological control, successful establishment of a natural enemy species depends on its adaptability in the introduced range including its ability to re-establish desired ecological interactions with the pest. These are affected by genetic parameters hitherto largely unresolved in biological control. The larger grain borer (LGB), Prostephanus truncatus, an invasive species from meso-America, is the most important post-harvest pest of maize in Africa. We studied the genetic structure of Teretrius nigrescens, a predatory beetle previously released for the control of the pest in Africa, to test the hypothesis that establishment patterns were a result of ecotype-environment mismatch and to follow up on our earlier reports of distinct lineages of the predator. We studied 13 populations of T. nigrescens, using 16 polymorphic microsatellite markers. Five genetic populations with a hierarchical structure and significant isolation by distance were detected. The most diverse population was found in southern Mexico, consistent with earlier lineage coexistence observations. Populations introduced to Africa maintained genetic similarity to local geographic populations of their area of origin. The more successful Benin releases were also more genetically diverse. Loss of rare alleles and a higher frequency of existing private alleles in some populations indicated population expansions following bottleneck events. Sustainable biological control should accommodate pest and natural enemy species, and monitor genetic changes associated with introduction and release.

Quantitative genetic study of the adaptive process

The additive genetic variance with respect to absolute fitness, VA(W), divided by mean absolute fitness, , sets the rate of ongoing adaptation. Fisher's key insight yielding this quantitative prediction of adaptive evolution, known as the Fundamental Theorem of Natural Selection, is well appreciated by evolutionists. Nevertheless, extremely scant information about VA(W) is available for natural populations. Consequently, the capacity for fitness increase via natural selection is unknown. Particularly in the current context of rapid environmental change, which is likely to reduce fitness directly and, consequently, the size and persistence of populations, the urgency of advancing understanding of immediate adaptive capacity is extreme. We here explore reasons for the dearth of empirical information about VA(W), despite its theoretical renown and critical evolutionary role. Of these reasons, we suggest that expectations that VA(W) is negligible, in general, together with severe statistical challenges of estimating it, may largely account for the limited empirical emphasis on it. To develop insight into the dynamics of VA(W) in a changing environment, we have conducted individual-based genetically explicit simulations. We show that, as optimizing selection on a trait changes steadily over generations, VA(W) can grow considerably, supporting more rapid adaptation than would the VA(W) of the base population. We call for direct evaluation of VA(W) and in support of prediction of rates adaptive evolution, and we advocate for the use of aster modeling as a rigorous basis for achieving this goal.

Rapid evolution of quantitative traits: theoretical perspectives

An increasing number of studies demonstrate phenotypic and genetic changes in natural populations that are subject to climate change, and there is hope that some of these changes will contribute to avoiding species extinctions ('evolutionary rescue'). Here, we review theoretical models of rapid evolution in quantitative traits that can shed light on the potential for adaptation to a changing climate. Our focus is on quantitative-genetic models with selection for a moving phenotypic optimum. We point out that there is no one-to-one relationship between the rate of adaptation and population survival, because the former depends on relative fitness and the latter on absolute fitness. Nevertheless, previous estimates that sustainable rates of genetically based change usually do not exceed 0.1 haldanes (i.e., phenotypic standard deviations per generation) are probably correct. Survival can be greatly facilitated by phenotypic plasticity, and heritable variation in plasticity can further speed up genetic evolution. Multivariate selection and genetic correlations are frequently assumed to constrain adaptation, but this is not necessarily the case and depends on the geometric relationship between the fitness landscape and the structure of genetic variation. Similar conclusions hold for adaptation to shifting spatial gradients. Recent models of adaptation in multispecies communities indicate that the potential for rapid evolution is strongly influenced by interspecific competition.

Assessing strategies to minimize unintended fitness consequences of aquaculture on wild populations

Artificial propagation programs focused on production, such as commercial aquaculture or forestry, entail strong domestication selection. Spillover from such programs can cause unintended fitness and demographic consequences for wild conspecifics. The range of possible management practices to minimize such consequences vary in their control of genetic and demographic processes. Here, we use a model of coupled genetic and demographic dynamics to evaluate alternative management approaches to minimizing unintended consequences of aquaculture escapees. We find that, if strong natural selection occurs between escape and reproduction, an extremely maladapted (i.e., nonlocal-origin, highly domesticated) stock could have fitness consequences analogous to a weakly diverged cultured stock; otherwise, wild population fitness declines with increasing maladaptation in the cultured stock. Reducing escapees through low-level leakage is more effective than reducing an analogous number of escapees from large, rare pulses. This result arises because low-level leakage leads to the continual lowering of wild population fitness and subsequent increased proportional contribution of maladapted cultured escapees to the total population. Increased sterilization efficacy can cause rapid, nonlinear reductions in unintended fitness consequences. Finally, sensitivity to the stage of escape indicates a need for improved monitoring data on how the number of escapees varies across life cycle stages.

Non-adaptive phenotypic evolution of the endangered carnivore Lycaon pictus

Decline in wild populations as a result of anthropogenic impact is widely considered to have evolutionary consequences for the species concerned. Here we examine changes in developmental stability in the painted hunting dog (Lycaon pictus), which once occupied most of sub-Saharan Africa but has undergone a dramatic population decline in the last century. Fluctuating asymmetry (FA) was used as an indicator of developmental stability and measured in museum skull specimens spanning a hundred year period. A comparison with the more ubiquitous black-backed jackal (Canis mesomelas) revealed FA in L. pictus to be high. Furthermore, the data indicate a temporal increase in FA over time in L. pictus, corresponding to the period of its population decline. The high rate of change is compatible with genetic drift although environmental factors are also likely to be important. Lowering developmental stability over time may have direct fitness consequences and as such represents an unacknowledged threat to future resilience of the population.