Direct observation of adaptive tracking on ecological time scales in Drosophila

Evolutionary radiation strategy revealed in the Scarabaeidae with evidence of continuous spatiotemporal morphology and phylogenesis

Evolutionary biology faces the important challenge of determining how to interpret the relationship between selection pressures and evolutionary radiation. The lack of morphological evidence on cross-species research adds to difficulty of this challenge. We proposed a new paradigm for evaluating the evolution of branches through changes in characters on continuous spatiotemporal scales, for better interpreting the impact of biotic/abiotic drivers on the evolutionary radiation. It reveals a causal link between morphological changes and selective pressures: consistent deformation signals for all tested characters on timeline, which provided strong support for the evolutionary hypothesis of relationship between scarabs and biotic/abiotic drivers; the evolutionary strategies under niche differentiation, which were manifested in the responsiveness degree of functional morphological characters with different selection pressure. This morphological information-driven integrative approach sheds light on the mechanism of macroevolution under different selection pressures and is applicable to more biodiversity research.

Rapid response of fly populations to gene dosage across development and generations

Although the effects of genetic and environmental perturbations on multicellular organisms are rarely restricted to single phenotypic layers, our current understanding of how developmental programs react to these challenges remains limited. Here, we have examined the phenotypic consequences of disturbing the bicoid regulatory network in early Drosophila embryos. We generated flies with two extra copies of bicoid, which causes a posterior shift of the network's regulatory outputs and a decrease in fitness. We subjected these flies to EMS mutagenesis, followed by experimental evolution. After only 8-15 generations, experimental populations have normalized patterns of gene expression and increased survival. Using a phenomics approach, we find that populations were normalized through rapid increases in embryo size driven by maternal changes in metabolism and ovariole development. We extend our results to additional populations of flies, demonstrating predictability. Together, our results necessitate a broader view of regulatory network evolution at the systems level.

Naturally segregating genetic variants contribute to thermal tolerance in a Drosophila melanogaster model system

Thermal tolerance is a fundamental physiological complex trait for survival in many species. For example, everyday tasks such as foraging, finding a mate, and avoiding predation are highly dependent on how well an organism can tolerate extreme temperatures. Understanding the general architecture of the natural variants within the genes that control this trait is of high importance if we want to better comprehend thermal physiology. Here, we take a multipronged approach to further dissect the genetic architecture that controls thermal tolerance in natural populations using the Drosophila Synthetic Population Resource as a model system. First, we used quantitative genetics and Quantitative Trait Loci mapping to identify major effect regions within the genome that influences thermal tolerance, then integrated RNA-sequencing to identify differences in gene expression, and lastly, we used the RNAi system to (1) alter tissue-specific gene expression and (2) functionally validate our findings. This powerful integration of approaches not only allows for the identification of the genetic basis of thermal tolerance but also the physiology of thermal tolerance in a natural population, which ultimately elucidates thermal tolerance through a fitness-associated lens.

Rapid evolutionary change, constraints and the maintenance of polymorphism in natural populations of Drosophila melanogaster

Allele frequencies can shift rapidly within natural populations. Under certain conditions, repeated rapid allele frequency shifts can lead to the long-term maintenance of polymorphism. In recent years, studies of the model insect Drosophila melanogaster have suggested that this phenomenon is more common than previously believed and is often driven by some form of balancing selection, such as temporally fluctuating or sexually antagonistic selection. Here we discuss some of the general insights into rapid evolutionary change revealed by large-scale population genomic studies, as well as the functional and mechanistic causes of rapid adaptation uncovered by single-gene studies. As an example of the latter, we consider a regulatory polymorphism of the D. melanogaster fezzik gene. Polymorphism at this site has been maintained at intermediate frequency over an extended period of time. Regular observations from a single population over a period of 7 years revealed significant differences in the frequency of the derived allele and its variance across collections between the sexes. These patterns are highly unlikely to arise from genetic drift alone or from the action of sexually antagonistic or temporally fluctuating selection individually. Instead, the joint action of sexually antagonistic and temporally fluctuating selection can best explain the observed rapid and repeated allele frequency shifts. Temporal studies such as those reviewed here further our understanding of how rapid changes in selection can lead to the long-term maintenance of polymorphism as well as improve our knowledge of the forces driving and limiting adaptation in nature.

Agricultural insect pests as models for studying stress-induced evolutionary processes

Agricultural insect pests (AIPs) are widely successful in adapting to natural and anthropogenic stressors, repeatedly overcoming population bottlenecks and acquiring resistance to intensive management practices. Although they have been largely overlooked in evolutionary studies, AIPs are ideal systems for understanding rapid adaptation under novel environmental conditions. Researchers have identified several genomic mechanisms that likely contribute to adaptive stress responses, including positive selection on de novo mutations, polygenic selection on standing allelic variation and phenotypic plasticity (e.g., hormesis). However, new theory suggests that stress itself may induce epigenetic modifications, which may confer heritable physiological changes (i.e., stress-resistant phenotypes). In this perspective, we discuss how environmental stress from agricultural management generates the epigenetic and genetic modifications that are associated with rapid adaptation in AIPs. We summarise existing evidence for stress-induced evolutionary processes in the context of insecticide resistance. Ultimately, we propose that studying AIPs offers new opportunities and resources for advancing our knowledge of stress-induced evolution.

Transgenerational epigenetic inheritance increases trait variation but is not adaptive

Understanding processes that can produce adaptive phenotypic shifts in response to rapid environmental change is critical to reducing biodiversity loss. The ubiquity of environmentally induced epigenetic marks has led to speculation that epigenetic inheritance could potentially enhance population persistence in response to environmental change. Yet, the magnitude and fitness consequences of epigenetic marks carried beyond maternal inheritance are largely unknown. Here, we tested how transgenerational epigenetic inheritance (TEI) shapes the phenotypic response of Daphnia clones to the environmental stressor Microcystis. We split individuals from each of eight genotypes into exposure and control treatments (F0 generation) and tracked the fitness of their descendants to the F3 generation. We found transgenerational epigenetic exposure to Microcystis led to reduced rates of survival and individual growth and no consistent effect on offspring production. Increase in trait variance in the F3 relative to F0 generations suggests potential for heritable bet hedging driven by TEI, which could impact population dynamics. Our findings are counter to the working hypothesis that TEI is a generally adaptive mechanism likely to prevent extinction for populations inhabiting rapidly changing environments.

From sub-Saharan Africa to China: Evolutionary history and adaptation of Drosophila melanogaster revealed by population genomics

Drosophila melanogaster is a widely used model organism for studying environmental adaptation. However, the genetic diversity of populations in Asia is poorly understood, leaving a notable gap in our knowledge of the global evolution and adaptation of this species. We sequenced genomes of 292 D. melanogaster strains from various ecological settings in China and analyzed them along with previously published genome sequences. We have identified six global genetic ancestry groups, despite the presence of widespread genetic admixture. The strains from China represent a unique ancestry group, although detectable differentiation exists among populations within China. We deciphered the global migration and demography of D. melanogaster, and identified widespread signals of adaptation, including genetic changes in response to insecticides. We validated the effects of insecticide resistance variants using population cage trials and deep sequencing. This work highlights the importance of population genomics in understanding the genetic underpinnings of adaptation, an effort that is particularly relevant given the deterioration of ecosystems.

Population genetic simulation: Benchmarking frameworks for non-standard models of natural selection

Population genetic simulation has emerged as a common tool for investigating increasingly complex evolutionary and demographic models. Software capable of handling high-level model complexity has recently been developed, and the advancement of tree sequence recording now allows simulations to merge the efficiency and genealogical insight of coalescent simulations with the flexibility of forward simulations. However, frameworks utilizing these features have not yet been compared and benchmarked. Here, we evaluate various simulation workflows using the coalescent simulator msprime and the forward simulator SLiM, to assess resource efficiency and determine an optimal simulation framework. Three aspects were evaluated: (1) the burn-in, to establish an equilibrium level of neutral diversity in the population; (2) the forward simulation, in which temporally fluctuating selection is acting; and (3) the final computation of summary statistics. We provide typical memory and computation time requirements for each step. We find that the fastest framework, a combination of coalescent and forward simulation with tree sequence recording, increases simulation speed by over twenty times compared to classical forward simulations without tree sequence recording, although it does require six times more memory. Overall, using efficient simulation workflows can lead to a substantial improvement when modelling complex evolutionary scenarios-although the optimal framework ultimately depends on the available computational resources.

Genetic basis of variation in thermal developmental plasticity for Drosophila melanogaster body pigmentation

Seasonal differences in insect pigmentation are attributed to the influence of ambient temperature on pigmentation development. This thermal plasticity is adaptive and heritable, and thereby capable of evolving. However, the specific genes contributing to the variation in plasticity that can drive its evolution remain largely unknown. To address this, we analysed pigmentation and pigmentation plasticity in Drosophila melanogaster. We measured two components of pigmentation in the thorax and abdomen: overall darkness and the proportion of length covered by darker pattern elements (a trident in the thorax and bands in the abdomen) in females from two developmental temperatures (17 or 28°C) and 191 genotypes. Using a GWAS approach to identify the genetic basis of variation in pigmentation and its response to temperature, we identified numerous dispersed QTLs, including some mapping to melanogenesis genes (yellow, ebony, and tan). Remarkably, we observed limited overlap between QTLs for variation within specific temperatures and those influencing thermal plasticity, as well as minimal overlap between plasticity QTLs across pigmentation components and across body parts. For most traits, consistent with selection favouring the retention of plasticity, we found that lower plasticity alleles were often at lower frequencies. The functional analysis of selected candidate QTLs and pigmentation genes largely confirmed their contributions to variation in pigmentation and/or pigmentation plasticity. Overall, our study reveals the existence and underlying basis of extensive and trait-specific genetic variation for pigmentation and pigmentation plasticity, offering a rich reservoir of raw material for natural selection to shape the evolution of these traits independently.

Continuously fluctuating selection reveals extreme granularity and parallelism of adaptive tracking

Temporally fluctuating environmental conditions are a ubiquitous feature of natural habitats. Yet, how finely natural populations adaptively track fluctuating selection pressures via shifts in standing genetic variation is unknown. We generated high-frequency, genome-wide allele frequency data from a genetically diverse population of Drosophila melanogaster in extensively replicated field mesocosms from late June to mid-December, a period of ∼12 generations. Adaptation throughout the fundamental ecological phases of population expansion, peak density, and collapse was underpinned by extremely rapid, parallel changes in genomic variation across replicates. Yet, the dominant direction of selection fluctuated repeatedly, even within each of these ecological phases. Comparing patterns of allele frequency change to an independent dataset procured from the same experimental system demonstrated that the targets of selection are predictable across years. In concert, our results reveal fitness-relevance of standing variation that is likely to be masked by inference approaches based on static population sampling, or insufficiently resolved time-series data. We propose such fine-scaled temporally fluctuating selection may be an important force maintaining functional genetic variation in natural populations and an important stochastic force affecting levels of standing genetic variation genome-wide.

Threshold shifts and developmental temperature impact trade-offs between tolerance and plasticity

Mounting evidence suggests that ectotherms are already living close to their upper physiological thermal limits. Phenotypic plasticity has been proposed to reduce the impact of climate change in the short-term providing time for adaptation, but the tolerance-plasticity trade-off hypothesis predicts organisms with higher tolerance have lower plasticity. Empirical evidence is mixed, which may be driven by methodological issues such as statistical artefacts, nonlinear reaction norms, threshold shifts or selection. Here, we examine whether threshold shifts (organisms with higher tolerance require stronger treatments to induce maximum plastic responses) influence tolerance-plasticity trade-offs in hardening capacity for desiccation tolerance and critical thermal maximum (CTMAX) across Drosophila species with varying distributions/sensitivity to desiccation/heat stress. We found evidence for threshold shifts in both traits; species with higher heat/desiccation tolerance required longer hardening treatments to induce maximum hardening responses. Species with higher heat tolerance also showed reductions in hardening capacity at higher developmental acclimation temperatures. Trade-off patterns differed depending on the hardening treatment used and the developmental temperature flies were exposed to. Based on these findings, studies that do not consider threshold shifts, or that estimate plasticity under a narrow set of environments, will have a limited ability to assess trade-off patterns and differences in plasticity across species/populations more broadly.

A cosmopolitan inversion facilitates seasonal adaptation in overwintering Drosophila

Fluctuations in the strength and direction of natural selection through time are a ubiquitous feature of life on Earth. One evolutionary outcome of such fluctuations is adaptive tracking, wherein populations rapidly adapt from standing genetic variation. In certain circumstances, adaptive tracking can lead to the long-term maintenance of functional polymorphism despite allele frequency change due to selection. Although adaptive tracking is likely a common process, we still have a limited understanding of aspects of its genetic architecture and its strength relative to other evolutionary forces such as drift. Drosophila melanogaster living in temperate regions evolve to track seasonal fluctuations and are an excellent system to tackle these gaps in knowledge. By sequencing orchard populations collected across multiple years, we characterized the genomic signal of seasonal demography and identified that the cosmopolitan inversion In(2L)t facilitates seasonal adaptive tracking and shows molecular footprints of selection. A meta-analysis of phenotypic studies shows that seasonal loci within In(2L)t are associated with behavior, life history, physiology, and morphological traits. We identify candidate loci and experimentally link them to phenotype. Our work contributes to our general understanding of fluctuating selection and highlights the evolutionary outcome and dynamics of contemporary selection on inversions.

Genomic evidence for domestication selection in three hatchery populations of Chinook salmon, Oncorhynchus tshawytscha

Fish hatcheries are widely used to enhance fisheries and supplement declining wild populations. However, substantial evidence suggests that hatchery fish are subject to differential selection pressures compared to their wild counterparts. Domestication selection, or adaptation to the hatchery environment, poses a risk to wild populations if traits specific to success in the hatchery environment have a genetic component and there is subsequent introgression between hatchery and wild fish. Few studies have investigated domestication selection in hatcheries on a genomic level, and even fewer have done so in parallel across multiple hatchery-wild population pairs. In this study, we used low-coverage whole-genome sequencing to investigate signals of domestication selection in three separate hatchery populations of Chinook salmon, Oncorhynchus tshawytscha, after approximately seven generations of divergence from their corresponding wild progenitor populations. We sequenced 192 individuals from populations across Southeast Alaska and estimated genotype likelihoods at over six million loci. We discovered a total of 14 outlier peaks displaying high genetic differentiation (F ST) between hatchery-wild pairs, although no peaks were shared across the three comparisons. Peaks were small (53 kb on average) and often displayed elevated absolute genetic divergence (D xy) and linkage disequilibrium, suggesting some level of domestication selection has occurred. Our study provides evidence that domestication selection can lead to genetic differences between hatchery and wild populations in only a few generations. Additionally, our data suggest that population-specific adaptation to hatchery environments likely occurs through different genetic pathways, even for populations with similar standing genetic variation. These results highlight the need to collect paired genotype-phenotype data to understand how domestication may be affecting fitness and to identify potential management practices that may mitigate genetic risks despite multiple pathways of domestication.

Effective fitness under fluctuating selection with genetic drift

The natural environment fluctuates for virtually every population of organisms. As a result, the fitness of a mutant may vary temporally. While commonly used for summarizing the effect of fluctuating selection on the mutant, geometric mean fitness can be misleading under some circumstances due to the influence of genetic drift. Here, we show by mathematical proof and computer simulation that, with genetic drift, the geometric mean fitness does not accurately reflect the overall effect of fluctuating selection. We propose an alternative measure based on the average expected allele frequency change caused by selection and demonstrate that this measure-effective fitness-better captures the overall effect of fluctuating selection in the presence of drift.

Intraspecific genetic variation is critical to robust toxicological predictions of aquatic contaminants

Environmental risk assessment is a critical tool for protecting aquatic life and its effectiveness is predicated on predicting how natural populations respond to contaminants. Yet, routine toxicity testing typically examines only one genotype, which may render risk assessments inaccurate as populations are most often composed of genetically distinct individuals. To determine the importance of intraspecific variation in the translation of toxicity testing to populations, we quantified the magnitude of genetic variation within 20 Daphnia magna clones derived from one lake using whole genome sequencing and phenotypic assays. We repeated these assays across two exposure levels of microcystins, a cosmopolitan and lethal aquatic contaminant produced by harmful algal blooms. We found considerable intraspecific genetic variation in survival, growth, and reproduction, which was amplified by microcystins exposure. Finally, using simulations we demonstrate that the common practice of employing a single genotype to calculate toxicity tolerance failed to produce an estimate within the 95% confidence interval over half of the time. These results illuminate the importance of incorporating intraspecific genetic variation into toxicity testing to reliably predict how natural populations will respond to aquatic contaminants.

Non-additive effects between genotypes: Implications for competitive fitness assays

Competitive fitness assays are widely used in evolutionary biology and typically rely on a reference strain to compare different focal genotypes. This approach implicitly relies on the absence of interaction between the competing genotypes. In other words, the performance of the reference strain must not depend on the competitor. This report scrutinized this assumption by competing diverged Drosophila simulans populations against a common reference strain. We detected strong evidence for interaction between the competing genotypes: (1) Frequency-dependent selection was common with opposite effects in genetically diverged populations. (2) Temporal heterogeneity of fitness estimates, which can be partially attributed to a competitor-specific delay in the eclosion of the reference strain. We propose that this inconsistent behavior of the reference strain can be considered a specific case of a genotype × environment interaction. Focal populations could modify the environment of the reference strain, either indirectly by altering the microbiome composition and food availability or directly by genotype-specific cannibalism. Our results provide new insights into the interaction of diverged genotypes and have important implications for the interpretation of competitive fitness assays.

Genomic Diversity Illuminates the Environmental Adaptation of Drosophila suzukii

Biological invasions carry substantial practical and scientific importance, and represent natural evolutionary experiments on contemporary timescales. Here, we investigated genomic diversity and environmental adaptation of the crop pest Drosophila suzukii using whole-genome sequencing data and environmental metadata for 29 population samples from its native and invasive range. Through a multifaceted analysis of this population genomic data, we increase our understanding of the D. suzukii genome, its diversity and its evolution, and we identify an appropriate genotype-environment association pipeline for our data set. Using this approach, we detect genetic signals of local adaptation associated with nine distinct environmental factors related to altitude, wind speed, precipitation, temperature, and human land use. We uncover unique functional signatures for each environmental variable, such as a prevalence of cuticular genes associated with annual precipitation. We also infer biological commonalities in the adaptation to diverse selective pressures, particularly in terms of the apparent contribution of nervous system evolution to enriched processes (ranging from neuron development to circadian behavior) and to top genes associated with all nine environmental variables. Our findings therefore depict a finer-scale adaptive landscape underlying the rapid invasion success of this agronomically important species.

Strong environmental memory revealed by experimental evolution in static and fluctuating environments

Evolution in a static environment, such as a laboratory setting with constant and uniform conditions, often proceeds via large-effect beneficial mutations that may become maladaptive in other environments. Conversely, natural settings require populations to endure environmental fluctuations. A sensible assumption is that the fitness of a lineage in a fluctuating environment is the time-average of its fitness over the sequence of static conditions it encounters. However, transitions between conditions may pose entirely new challenges, which could cause deviations from this time-average. To test this, we tracked hundreds of thousands of barcoded yeast lineages evolving in static and fluctuating conditions and subsequently isolated 900 mutants for pooled fitness assays in 15 environments. We find that fitness in fluctuating environments indeed often deviates from the expectation based on static components, leading to fitness non-additivity. Moreover, closer examination reveals that fitness in one component of a fluctuating environment is often strongly influenced by the previous component. We show that this environmental memory is especially common for mutants with high variance in fitness across tested environments, even if the components of the focal fluctuating environment are excluded from this variance. We employ a simple mathematical model and whole-genome sequencing to propose mechanisms underlying this effect, including lag time evolution and sensing mutations. Our results demonstrate that environmental fluctuations have large impacts on fitness and suggest that variance in static environments can explain these impacts.

Ecology, the pace-of-life, epistatic selection and the maintenance of genetic variation in life-history genes

Evolutionary genetics has long struggled with understanding how functional genes under selection remain polymorphic in natural populations. Taking as a starting point that natural selection is ultimately a manifestation of ecological processes, we spotlight an underemphasized and potentially ubiquitous ecological effect that may have fundamental effects on the maintenance of genetic variation. Negative frequency dependency is a well-established emergent property of density dependence in ecology, because the relative profitability of different modes of exploiting or utilizing limiting resources tends to be inversely proportional to their frequency in a population. We suggest that this may often generate negative frequency-dependent selection (NFDS) on major effect loci that affect rate-dependent physiological processes, such as metabolic rate, that are phenotypically manifested as polymorphism in pace-of-life syndromes. When such a locus under NFDS shows stable intermediate frequency polymorphism, this should generate epistatic selection potentially involving large numbers of loci with more minor effects on life-history (LH) traits. When alternative alleles at such loci show sign epistasis with a major effect locus, this associative NFDS will promote the maintenance of polygenic variation in LH genes. We provide examples of the kind of major effect loci that could be involved and suggest empirical avenues that may better inform us on the importance and reach of this process.

SEED: A framework for integrating ecological stoichiometry and eco-evolutionary dynamics

Characterising the extent and sources of intraspecific variation and their ecological consequences is a central challenge in the study of eco-evolutionary dynamics. Ecological stoichiometry, which uses elemental variation of organisms and their environment to understand ecosystem patterns and processes, can be a powerful framework for characterising eco-evolutionary dynamics. However, the current emphasis on the relative content of elements in the body (i.e. organismal stoichiometry) has constrained its application. Intraspecific variation in the rates at which elements are acquired, assimilated, allocated or lost is often greater than the variation in organismal stoichiometry. There is much to gain from studying these traits together as components of an 'elemental phenotype'. Furthermore, each of these traits can have distinct ecological effects that are underappreciated in the current literature. We propose a conceptual framework that explores how microevolutionary change in the elemental phenotype occurs, how its components interact with each other and with other traits, and how its changes can affect a wide range of ecological processes. We demonstrate how the framework can be used to generate novel hypotheses and outline pathways for future research that enhance our ability to explain, analyse and predict eco-evolutionary dynamics.

Eco-evolutionary maintenance of diversity in fluctuating environments

Growing evidence suggests that temporally fluctuating environments are important in maintaining variation both within and between species. To date, however, studies of genetic variation within a population have been largely conducted by evolutionary biologists (particularly population geneticists), while population and community ecologists have concentrated more on diversity at the species level. Despite considerable conceptual overlap, the commonalities and differences of these two alternative paradigms have yet to come under close scrutiny. Here, we review theoretical and empirical studies in population genetics and community ecology focusing on the 'temporal storage effect' and synthesise theories of diversity maintenance across different levels of biological organisation. Drawing on Chesson's coexistence theory, we explain how temporally fluctuating environments promote the maintenance of genetic variation and species diversity. We propose a further synthesis of the two disciplines by comparing models employing traditional frequency-dependent dynamics and those adopting density-dependent dynamics. We then address how temporal fluctuations promote genetic and species diversity simultaneously via rapid evolution and eco-evolutionary dynamics. Comparing and synthesising ecological and evolutionary approaches will accelerate our understanding of diversity maintenance in nature.

Beyond simple adaptation: Incorporating other evolutionary processes and concepts into eco-evolutionary dynamics

Studies of eco-evolutionary dynamics have integrated evolution with ecological processes at multiple scales (populations, communities and ecosystems) and with multiple interspecific interactions (antagonistic, mutualistic and competitive). However, evolution has often been conceptualised as a simple process: short-term directional adaptation that increases population growth. Here we argue that diverse other evolutionary processes, well studied in population genetics and evolutionary ecology, should also be considered to explore the full spectrum of feedback between ecological and evolutionary processes. Relevant but underappreciated processes include (1) drift and mutation, (2) disruptive selection causing lineage diversification or speciation reversal and (3) evolution driven by relative fitness differences that may decrease population growth. Because eco-evolutionary dynamics have often been studied by population and community ecologists, it will be important to incorporate a variety of concepts in population genetics and evolutionary ecology to better understand and predict eco-evolutionary dynamics in nature.

Statistical methods to identify mechanisms in studies of eco-evolutionary dynamics

While the reciprocal effects of ecological and evolutionary dynamics are increasingly recognized as an important driver for biodiversity, detection of such eco-evolutionary feedbacks, their underlying mechanisms, and their consequences remains challenging. Eco-evolutionary dynamics occur at different spatial and temporal scales and can leave signatures at different levels of organization (e.g., gene, protein, trait, community) that are often difficult to detect. Recent advances in statistical methods combined with alternative hypothesis testing provides a promising approach to identify potential eco-evolutionary drivers for observed data even in non-model systems that are not amenable to experimental manipulation. We discuss recent advances in eco-evolutionary modeling and statistical methods and discuss challenges for fitting mechanistic models to eco-evolutionary data.

Naturally segregating genetic variants contribute to thermal tolerance in a D. melanogaster model system

Thermal tolerance is a fundamental physiological complex trait for survival in many species. For example, everyday tasks such as foraging, finding a mate, and avoiding predation, are highly dependent on how well an organism can tolerate extreme temperatures. Understanding the general architecture of the natural variants of the genes that control this trait is of high importance if we want to better comprehend how this trait evolves in natural populations. Here, we take a multipronged approach to further dissect the genetic architecture that controls thermal tolerance in natural populations using the Drosophila Synthetic Population Resource (DSPR) as a model system. First, we used quantitative genetics and Quantitative Trait Loci (QTL) mapping to identify major effect regions within the genome that influences thermal tolerance, then integrated RNA-sequencing to identify differences in gene expression, and lastly, we used the RNAi system to 1) alter tissue-specific gene expression and 2) functionally validate our findings. This powerful integration of approaches not only allows for the identification of the genetic basis of thermal tolerance but also the physiology of thermal tolerance in a natural population, which ultimately elucidates thermal tolerance through a fitness-associated lens.

Seasonal specialization drives divergent population dynamics in two closely related butterflies

Seasons impose different selection pressures on organisms through contrasting environmental conditions. How such seasonal evolutionary conflict is resolved in organisms whose lives span across seasons remains underexplored. Through field experiments, laboratory work, and citizen science data analyses, we investigate this question using two closely related butterflies (Pieris rapae and P. napi). Superficially, the two butterflies appear highly ecologically similar. Yet, the citizen science data reveal that their fitness is partitioned differently across seasons. Pieris rapae have higher population growth during the summer season but lower overwintering success than do P. napi. We show that these differences correspond to the physiology and behavior of the butterflies. Pieris rapae outperform P. napi at high temperatures in several growth season traits, reflected in microclimate choice by ovipositing wild females. Instead, P. rapae have higher winter mortality than do P. napi. We conclude that the difference in population dynamics between the two butterflies is driven by seasonal specialization, manifested as strategies that maximize gains during growth seasons and minimize harm during adverse seasons, respectively.

How predictable is adaptation from standing genetic variation? Experimental evolution in Drosophila highlights the central role of redundancy and linkage disequilibrium

Experimental evolution is well-suited to test the predictability of evolution without the confounding effects of inaccurate forecasts about future environments. Most of the literature about parallel (and thus predictable) evolution has been carried out in asexual microorganisms, which adapt by de novo mutations. Nevertheless, parallel evolution has also been studied in sexual species at the genomic level. Here, I review the evidence for parallel evolution in Drosophila, the best-studied obligatory outcrossing model for adaptation from standing genetic variation in the laboratory. Similar to asexual microorganisms, evidence for parallel evolution varies between the focal hierarchical levels. Selected phenotypes consistently respond in a very predicable way, but the underlying allele frequency changes are much less predictable. The most important insight is that the predictability of the genomic selection response for polygenic traits depends highly on the founder population and to a much lesser extent on the selection regime. This implies that predicting adaptive genomic response is challenging and requires a good understanding of the adaptive architecture (including linkage disequilibrium) in the ancestral populations. This article is part of the theme issue 'Interdisciplinary approaches to predicting evolutionary biology'.

The Genome-wide Signature of Short-term Temporal Selection

Despite evolutionary biology's obsession with natural selection, few studies have evaluated multi-generational series of patterns of selection on a genome-wide scale in natural populations. Here, we report on a nine-year population-genomic survey of the microcrustacean Daphnia pulex. The genome-sequences of > 800 isolates provide insights into patterns of selection that cannot be obtained from long-term molecular-evolution studies, including the pervasiveness of near quasi-neutrality across the genome (mean net selection coefficients near zero, but with significant temporal variance about the mean, and little evidence of positive covariance of selection across time intervals), the preponderance of weak negative selection operating on minor alleles, and a genome-wide distribution of numerous small linkage islands of observable selection influencing levels of nucleotide diversity. These results suggest that fluctuating selection is a major determinant of standing levels of variation in natural populations, challenge the conventional paradigm for interpreting patterns of nucleotide diversity and divergence, and motivate the need for the development of new theoretical expressions for the interpretation of population-genomic data.

Frank Beach Award Winner: The centrality of the hypothalamic-pituitary-adrenal axis in dealing with environmental change across temporal scales

Understanding if and how individuals and populations cope with environmental change is an enduring question in evolutionary ecology that has renewed importance given the pace of change in the Anthropocene. Two evolutionary strategies of coping with environmental change may be particularly important in rapidly changing environments: adaptive phenotypic plasticity and/or bet hedging. Adaptive plasticity could enable individuals to match their phenotypes to the expected environment if there is an accurate cue predicting the selective environment. Diversifying bet hedging involves the production of seemingly random phenotypes in an unpredictable environment, some of which may be adaptive. Here, I review the central role of the hypothalamic-pituitary-adrenal (HPA) axis and glucocorticoids (GCs) in enabling vertebrates to cope with environmental change through adaptive plasticity and bet hedging. I first describe how the HPA axis mediates three types of adaptive plasticity to cope with environmental change (evasion, tolerance, recovery) over short timescales (e.g., 1-3 generations) before discussing how the implications of GCs on phenotype integration may depend upon the timescale under consideration. GCs can promote adaptive phenotypic integration, but their effects on phenotypic co-variation could also limit the dimensions of phenotypic space explored by animals over longer timescales. Finally, I discuss how organismal responses to environmental stressors can act as a bet hedging mechanism and therefore enhance evolvability by increasing genetic or phenotypic variability or reducing patterns of genetic and phenotypic co-variance. Together, this emphasizes the crucial role of the HPA axis in understanding fundamental questions in evolutionary ecology.

Fluctuating selection and the determinants of genetic variation

Recent studies of cosmopolitan Drosophila populations have found hundreds to thousands of genetic loci with seasonally fluctuating allele frequencies, bringing temporally fluctuating selection to the forefront of the historical debate surrounding the maintenance of genetic variation in natural populations. Numerous mechanisms have been explored in this longstanding area of research, but these exciting empirical findings have prompted several recent theoretical and experimental studies that seek to better understand the drivers, dynamics, and genome-wide influence of fluctuating selection. In this review, we evaluate the latest evidence for multilocus fluctuating selection in Drosophila and other taxa, highlighting the role of potential genetic and ecological mechanisms in maintaining these loci and their impacts on neutral genetic variation.

Drosophilids with darker cuticle have higher body temperature under light

Cuticle pigmentation was shown to be associated with body temperature for several relatively large species of insects, but it was questioned for small insects. Here we used a thermal camera to assess the association between drosophilid cuticle pigmentation and body temperature increase when individuals are exposed to light. We compared mutants of large effects within species (Drosophila melanogaster ebony and yellow mutants). Then we analyzed the impact of naturally occurring pigmentation variation within species complexes (Drosophila americana/Drosophila novamexicana and Drosophila yakuba/Drosophila santomea). Finally we analyzed lines of D. melanogaster with moderate differences in pigmentation. We found significant differences in temperatures for each of the four pairs we analyzed. The temperature differences appeared to be proportional to the differently pigmented area: between Drosophila melanogaster ebony and yellow mutants or between Drosophila americana and Drosophila novamexicana, for which the whole body is differently pigmented, the temperature difference was around 0.6 °C ± 0.2 °C. By contrast, between D. yakuba and D. santomea or between Drosophila melanogaster Dark and Pale lines, for which only the posterior abdomen is differentially pigmented, we detected a temperature difference of about 0.14 °C ± 0.10 °C. This strongly suggests that cuticle pigmentation has ecological implications in drosophilids regarding adaptation to environmental temperature.

Understanding local plant extinctions before it is too late: bridging evolutionary genomics with global ecology

Understanding evolutionary genomic and population processes within a species range is key to anticipating the extinction of plant species before it is too late. However, most models of biodiversity risk under global change do not account for the genetic variation and local adaptation of different populations. Population diversity is critical to understanding extinction because different populations may be more or less susceptible to global change and, if lost, would reduce the total diversity within a species. Two new modeling frameworks advance our understanding of extinction from a population and evolutionary angle: Rapid climate change-driven disruptions in population adaptation are predicted from associations between genomes and local climates. Furthermore, losses of population diversity from global land-use transformations are estimated by scaling relationships of species' genomic diversity with habitat area. Overall, these global eco-evolutionary methods advance the predictability - and possibly the preventability - of the ongoing extinction of plant species.

Mixed support for an alignment between phenotypic plasticity and genetic differentiation in damselfly wing shape

The relationship between genetic differentiation and phenotypic plasticity can provide information on whether plasticity generally facilitates or hinders adaptation to environmental change. Here, we studied wing shape variation in a damselfly (Lestes sponsa) across a latitudinal gradient in Europe that differed in time constraints mediated by photoperiod and temperature. We reared damselflies from northern and southern populations in the laboratory using a reciprocal transplant experiment that simulated time-constrained (i.e. northern) and unconstrained (southern) photoperiods and temperatures. After emergence, adult wing shape was analysed using geometric morphometrics. Wings from individuals in the northern and southern populations differed significantly in shape when animals were reared in their respective native environment. Comparing wing shape across environments, we found evidence for phenotypic plasticity in wing shape, and this response differed across populations (i.e. G × E interactions). This interaction was driven by a stronger plastic response by individuals from the northern population and differences in the direction of plastic wing shape changes among populations. The alignment between genetic and plastic responses depended on the specific combination of population and rearing environment. For example, there was an alignment between plasticity and genetic differentiation under time-constrained, but not under non-time-constrained conditions for forewings. We thus find mixed support for the hypothesis that environmental plasticity and genetic population differentiation are aligned. Furthermore, although our laboratory treatments mimicked the natural climatic conditions at northern and southern latitudes, the effects of population differences on wing shape were two to four times stronger than plastic effects. We discuss our results in terms of time constraints and the possibility that natural and sexual selection is acting differently on fore- and hindwings.

Enrichment of Hard Sweeps on the X Chromosome in Drosophila melanogaster

The characteristic properties of the X chromosome, such as male hemizygosity and its unique inheritance pattern, expose it to natural selection in a way that can be different from the autosomes. Here, we investigate the differences in the tempo and mode of adaptation on the X chromosome and autosomes in a population of Drosophila melanogaster. Specifically, we test the hypothesis that due to hemizygosity and a lower effective population size on the X, the relative proportion of hard sweeps, which are expected when adaptation is gradual, compared with soft sweeps, which are expected when adaptation is rapid, is greater on the X than on the autosomes. We quantify the incidence of hard versus soft sweeps in North American D. melanogaster population genomic data with haplotype homozygosity statistics and find an enrichment of the proportion of hard versus soft sweeps on the X chromosome compared with the autosomes, confirming predictions we make from simulations. Understanding these differences may enable a deeper understanding of how important phenotypes arise as well as the impact of fundamental evolutionary parameters on adaptation, such as dominance, sex-specific selection, and sex-biased demography.

Rapid evolution of a coastal marsh ecosystem engineer in response to global change

There is increasing evidence that global change can alter ecosystems by eliciting rapid evolution of foundational plants capable of shaping vital attributes and processes. Here we describe results of a field-scale exposure experiment and multilocus assays illustrating that elevated CO₂ (eCO₂) and nitrogen (N) enrichment can result in rapid shifts in genetic and genotypic variation in Phragmites australis, an ecologically dominant plant that acts as an ecosystem engineer in coastal marshes worldwide. Compared to control treatments, genotypic diversity declined over three years of exposure, especially to N enrichment. The magnitude of loss also increased over time under conditions of N enrichment. Comparisons of genotype frequencies revealed that proportional abundances shifted with exposure to eCO₂ and N in a manner consistent with expected responses to selection. Comparisons also revealed evidence of tradeoffs that constrained exposure responses, where any particular genotype responded favorably to one factor rather than to different factors or to combinations of factors. These findings challenge the prevailing view that plant-mediated ecosystem outcomes of global change are governed primarily by differences in species responses to shifting environmental pressures and highlight the value of accounting for organismal evolution in predictive models to improve forecasts of ecosystem responses to global change.

The ephemeral resource patch concept

Ephemeral resource patches (ERPs) - short lived resources including dung, carrion, temporary pools, rotting vegetation, decaying wood, and fungi - are found throughout every ecosystem. Their short-lived dynamics greatly enhance ecosystem heterogeneity and have shaped the evolutionary trajectories of a wide range of organisms - from bacteria to insects and amphibians. Despite this, there has been no attempt to distinguish ERPs clearly from other resource types, to identify their shared spatiotemporal characteristics, or to articulate their broad ecological and evolutionary influences on biotic communities. Here, we define ERPs as any distinct consumable resources which (i) are homogeneous (genetically, chemically, or structurally) relative to the surrounding matrix, (ii) host a discrete multitrophic community consisting of species that cannot replicate solely in any of the surrounding matrix, and (iii) cannot maintain a balance between depletion and renewal, which in turn, prevents multiple generations of consumers/users or reaching a community equilibrium. We outline the wide range of ERPs that fit these criteria, propose 12 spatiotemporal characteristics along which ERPs can vary, and synthesise a large body of literature that relates ERP dynamics to ecological and evolutionary theory. We draw this knowledge together and present a new unifying conceptual framework that incorporates how ERPs have shaped the adaptive trajectories of organisms, the structure of ecosystems, and how they can be integrated into biodiversity management and conservation. Future research should focus on how inter- and intra-resource variation occurs in nature - with a particular focus on resource × environment × genotype interactions. This will likely reveal novel adaptive strategies, aid the development of new eco-evolutionary theory, and greatly improve our understanding of the form and function of organisms and ecosystems.

Laplace's demon in biology: Models of evolutionary prediction

Our ability to predict natural phenomena can be limited by incomplete information. This issue is exemplified by "Laplace's demon," an imaginary creature proposed in the 18th century, who knew everything about everything, and thus could predict the full nature of the universe forward or backward in time. Quantum mechanics, among other things, has cast doubt on the possibility of Laplace's demon in the full sense, but the idea still serves as a useful metaphor for thinking about the extent to which prediction is limited by incomplete information on deterministic processes versus random factors. Here, we use simple analytical models and computer simulations to illustrate how data limits can be captured in a Bayesian framework, and how they influence our ability to predict evolution. We show how uncertainty in measurements of natural selection, or low predictability of external environmental factors affecting selection, can greatly reduce predictive power, often swamping the influence of intrinsic randomness caused by genetic drift. Thus, more accurate knowledge concerning the causes and action of natural selection is key to improving prediction. Fortunately, our analyses and simulations show quantitatively that reasonable improvements in data quantity and quality can meaningfully increase predictability.

Dietary restriction and ageing: Recent evolutionary perspectives

Dietary restriction (DR) represents one of the most robust interventions for extending lifespan. It is not known how DR increases lifespan. The prevailing evolutionary hypothesis suggests the DR response redirects metabolic resources towards somatic maintenance at the expense of investment in reproduction. Consequently, DR acts as a proximate mechanism which promotes a pro-longevity phenotype. This idea is known as resource reallocation. However, growing findings suggest this paradigm could be incomplete. It has been argued that during DR it is not always possible to identify a trade-off between reproduction and lifespan. It is also suggested the relationship between reproduction and somatic maintenance can be uncoupled by the removal or inclusion of specific nutrients. These findings have created an imperative to re-explore the nexus between DR and evolutionary theory. In this review I will address this evolutionary conundrum. My overarching objectives are fourfold: (1) to outline some of the evidence for and against resource reallocation; (2) to examine recent findings which have necessitated a theoretical re-evaluation of the link between life history theory and DR; (3) to present alternatives to the resource reallocation model; (4) to present emerging variables which potentially influence how DR effects evolutionary trade-offs.

Clinal variation as a tool to understand climate change

Clines are observable gradients that reflect continuous change in biological traits of species across geographical ranges. Clinal gradients could vary at geographic scales (latitude and altitude). Since clinal variations represent active genomic responses at the population level they (clines) provide an immense power to address questions related to climatic change. With the fast pace of climate change i.e. warming, populations are also likely to exhibit rapid responses; at both the phenotypic and genotypic levels. We seek to understand how clinal variation could be used to anticipate climatic responses using Drosophila, a pervasively used inter-disciplinary model system owing to its molecular repertoire. The genomic information coupled with the phenotypic variation greatly facilitates our understanding of the Drosophilidae response to climate change. We discuss traits associated with clinal variation at the phenotypic level as well as their underlying genetic regulators. Given prevailing climatic conditions and future projections for climate change, clines could emerge as monitoring tools to track the cross-talk between climatic variables and organisms.

Integrating eco-evolutionary dynamics and modern coexistence theory

Community ecology typically assumes that competitive exclusion and species coexistence are unaffected by evolution on the time scale of ecological dynamics. However, recent studies suggest that rapid evolution operating concurrently with competition may enable species coexistence. Such findings necessitate general theory that incorporates the coexistence contributions of eco-evolutionary processes in parallel with purely ecological mechanisms and provides metrics for quantifying the role of evolution in shaping competitive outcomes in both modelling and empirical contexts. To foster the development of such theory, here we extend the interpretation of the two principal metrics of modern coexistence theory-niche and competitive ability differences-to systems where competitors evolve. We define eco-evolutionary versions of these metrics by considering how invading and resident species adapt to conspecific and heterospecific competitors. We show that the eco-evolutionary niche and competitive ability differences are sums of ecological and evolutionary processes, and that they accurately predict the potential for stable coexistence in previous theoretical studies of eco-evolutionary dynamics. Finally, we show how this theory frames recent empirical assessments of rapid evolution effects on species coexistence, and how empirical work and theory on species coexistence and eco-evolutionary dynamics can be further integrated.

Urban evolution of thermal physiology in a range-expanding, mycophagous fruit fly, Drosophila tripunctata

In Drosophila spp., their often high number of annual generations, large population sizes and large amounts of standing genetic variation should predispose them to undergo contemporary adaptation to climatic warming. However, a number of laboratory experimental evolution studies in this group of organisms suggest strong limits on the rate and magnitude of contemporary thermal adaptation. Here, we explore this discrepancy by examining the potential for rapid evolutionary divergence between wild populations of Drosophila tripunctata Loew, 1862 from rural and urban sites. We performed a multi-generation common garden study and found evidence for the evolution of higher heat tolerance (critical thermal maximum) in flies from urban populations. We also detected evolutionary divergence in cold resistance (chill coma recovery time), with diminished cold resistance in flies from urban populations, although the effect was weaker than the shift in heat tolerance. Our study provides evidence of contemporary urban thermal adaptation, although the magnitude of phenotypic change lagged the magnitude of environmental temperature change across the urbanization gradient, suggesting potential limits on the evolution of urban thermal physiology.

Unsupervised machine learning and geometric morphometrics as tools for the identification of inter and intraspecific variations in the Anopheles Maculipennis complex

Geometric morphometric analysis was combined with two different unsupervised machine learning algorithms, UMAP and HDBSCAN, to visualize morphological differences in wing shape among and within four Anopheles sibling species (An. atroparvus, An. melanoon, An. maculipennis s.s. and An. daciae sp. inq.) of the Maculipennis complex in Northern Italy. Specifically, we evaluated: 1) wing shape variation among and within species; 2) the consistencies between groups of An. maculipennis s.s. and An. daciae sp. inq. identified based on COI sequences and wing shape variability; and 3) the spatial and temporal distribution of different morphotypes. UMAP detected at least 13 main patterns of variation in wing shape among the four analyzed species and mapped intraspecific morphological variations. The relationship between the most abundant COI haplotypes of An. daciae sp. inq. and shape ordination/variation was not significant. However, morphological variation within haplotypes was reported. HDBSCAN also recognized different clusters of morphotypes within An. daciae sp. inq. (12) and An. maculipennis s.s. (4). All morphotypes shared a similar pattern of variation in the subcostal vein, in the anal vein and in the radio-medial cross-vein of the wing. On the contrary, the marginal part of the wings remained unchanged in all clusters of both species. Any spatial-temporal significant difference was observed in the frequency of the identified morphotypes.  Our study demonstrated that machine learning algorithms are a useful tool combined with geometric morphometrics and suggest to deepen the analysis of inter and intra specific shape variability to evaluate evolutionary constrains related to wing functionality.

Microbial experimental evolution in a massively multiplexed and high-throughput era

Experimental evolution with microbial model systems has transformed our understanding of the basic rules underlying ecology and evolution. Experiments leveraging evolution as a central feature put evolutionary theories to the test, and modern sequencing and engineering tools then characterized the molecular basis of adaptation. As theory and experimentations refined our understanding of evolution, a need to increase throughput and experimental complexity has emerged. Here, we summarize recent technologies that have made high-throughput experiments practical and highlight studies that have capitalized on these tools, defining an exciting new era in microbial experimental evolution. Multiple research directions previously limited by experimental scale are now accessible for study and we believe applying evolutionary lessons from in vitro studies onto these applied settings has the potential for major innovations and discoveries across ecology and medicine.

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’.

Designing a Seasonal Acclimation Study Presents Challenges and Opportunities

Organisms living in seasonal environments often adjust physiological capacities and sensitivities in response to (or in anticipation of) environment shifts. Such physiological and morphological adjustments (“acclimation” and related terms) inspire opportunities to explore the mechanistic bases underlying these adjustments, to detect cues inducing adjustments, and to elucidate their ecological and evolutionary consequences. Seasonal adjustments (“seasonal acclimation”) can be detected either by measuring physiological capacities and sensitivities of organisms retrieved directly from nature (or outdoor enclosures) in different seasons or less directly by rearing and measuring organisms maintained in the laboratory under conditions that attempt to mimic or track natural ones. But mimicking natural conditions in the laboratory is challenging—doing so requires prior natural-history knowledge of ecologically relevant body temperature cycles, photoperiods, food rations, social environments, among other variables. We argue that traditional laboratory-based conditions usually fail to approximate natural seasonal conditions (temperature, photoperiod, food, “lockdown”). Consequently, whether the resulting acclimation shifts correctly approximate those in nature is uncertain, and sometimes is dubious. We argue that background natural history information provides opportunities to design acclimation protocols that are not only more ecologically relevant, but also serve as templates for testing the validity of traditional protocols. Finally, we suggest several best practices to help enhance ecological realism.

Elevated Salinity Rapidly Confers Cross-Tolerance to High Temperature in a Splash-Pool Copepod

Accurate forecasting of organismal responses to climate change requires a deep mechanistic understanding of how physiology responds to present-day variation in the physical environment. However, the road to physiological enlightenment is fraught with complications: predictable environmental fluctuations of any single factor are often accompanied by substantial stochastic variation and rare extreme events, and several factors may interact to affect physiology. Lacking sufficient knowledge of temporal patterns of co-variation in multiple environmental stressors, biologists struggle to design and implement realistic and relevant laboratory experiments. In this study, we directly address these issues, using measurements of the thermal tolerance of freshly collected animals and long-term field records of environmental conditions to explore how the splash-pool copepod Tigriopus californicus adjusts its physiology as its environment changes. Salinity and daily maximum temperature-two dominant environmental stressors experienced by T. californicus-are extraordinarily variable and unpredictable more than 2-3 days in advance. However, they substantially co-vary such that when temperature is high salinity is also likely to be high. Copepods appear to take advantage of this correlation: median lethal temperature of field-collected copepods increases by 7.5°C over a roughly 120 parts-per-thousand range of ambient salinity. Complementary laboratory experiments show that exposure to a single sublethal thermal event or to an abrupt shift in salinity also elicits rapid augmentation of heat tolerance via physiological plasticity, although the effect of salinity dwarfs that of temperature. These results suggest that T. californicus's physiology keeps pace with the rapid, unpredictable fluctuations of its hypervariable physical environment by responding to the cues provided by recent sublethal stress and, more importantly, by leveraging the mechanistic cross-talk between responses to salinity and heat stress.