What genomic data can reveal about eco-evolutionary dynamics

Intraspecific diversity is critical to population-level risk assessments

Environmental risk assessment (ERA) is critical for protecting life by predicting population responses to contaminants. However, routine toxicity testing often examines only one genotype from surrogate species, potentially leading to inaccurate risk assessments, as natural populations typically consist of genetically diverse individuals. To evaluate the importance of intraspecific variation in translating toxicity testing to natural populations, we quantified the magnitude of phenotypic variation between 20 Daphnia magna clones exposed to two levels of microcystins, a cosmopolitan cyanobacterial toxin. We observed significant genetic variation in survival, growth, and reproduction, which increased under microcystins exposure. Simulations of survival showed that using a single genotype for toxicity tolerance estimates on average failed to produce accurate predictions within the 95% confidence interval over half of the time. Whole genome sequencing of the 20 clones tested for correlations between toxicological responses and genomic divergence, including candidate loci from prior gene expression studies. We found no overall correlations, indicating that clonal variation, rather than variation at candidate genes, predicts population-level responses to toxins. These results highlight the importance of incorporating broad intraspecific genetic variation, without focusing specifically on variation in candidate genes, into ERAs to more reliably predict how local populations will respond to contaminants.

Ecological and evolutionary processes involved in shaping microbial habitat generalists and specialists in urban park ecosystems

Microbiomes are integral to ecological health and human well-being; however, their ecological and evolutionary drivers have not been systematically investigated, especially in urban park ecosystems. As microbes have different levels of tolerance to environmental changes and habitat preferences, they can be categorized into habitat generalists and specialists. Here, we explored the ecological and evolutionary characteristics of both prokaryotic and microeukaryotic habitat generalists and specialists from six urban parks across five habitat types, including moss, soil, tree hole, water, and sediment. Our results revealed that different ecological and evolutionary processes maintained and regulated microbial diversity in urban park ecosystems. Under ecological perspective, community assembly of microbial communities was mainly driven by stochastic processes; however, deterministic processes were higher for habitat specialists than generalists. Microbial interactions were highly dynamic among habitats, and habitat specialists played key roles as module hubs in intradomain networks. In aquatic interdomain networks, microeukaryotic habitat specialists and prokaryotic habitat specialists played crucial roles as module hubs and connectors, respectively. Furthermore, analyzing evolutionary characteristics, our results revealed that habitat specialists had a much higher diversification potential than generalists, while generalists showed shorter phylogenetic branch lengths as well as larger genomes than specialists. This study broadens our understanding of the ecological and evolutionary features of microbial habitat generalists and specialists in urban park ecosystems across multi-habitat.

IMPORTANCE

Urban parks, as an important urban greenspace, play essential roles in ecosystem services and are important hotspots for microbes. Microbial diversity is driven by different ecological and evolutionary processes, while little is currently known about the distinct roles of ecological and evolutionary features in shaping microbial diversity in urban park ecosystems. We explored the ecological and evolutionary characteristics of prokaryotic and microeukaryotic habitat generalists and specialists in urban park ecosystems based on a representative set of different habitats. We found that different ecological and evolutionary drivers jointly maintained and regulated microbial diversity in urban park microbiomes through analyzing the community assembly process, ecological roles in hierarchical interaction, and species diversification potential. These findings significantly advance our understanding regarding the mechanisms governing microbial diversity in urban park ecosystems.

Genomic evidence for rediploidization and adaptive evolution following the whole-genome triplication

Whole-genome duplication (WGD), or polyploidy, events are widespread and significant in the evolutionary history of angiosperms. However, empirical evidence for rediploidization, the major process where polyploids give rise to diploid descendants, is still lacking at the genomic level. Here we present chromosome-scale genomes of the mangrove tree Sonneratia alba and the related inland plant Lagerstroemia speciosa. Their common ancestor has experienced a whole-genome triplication (WGT) approximately 64 million years ago coinciding with a period of dramatic global climate change. Sonneratia, adapting mangrove habitats, experienced extensive chromosome rearrangements post-WGT. We observe the WGT retentions display sequence and expression divergence, suggesting potential neo- and sub-functionalization. Strong selection acting on three-copy retentions indicates adaptive value in response to new environments. To elucidate the role of ploidy changes in genome evolution, we improve a model of the polyploidization-rediploidization process based on genomic evidence, contributing to the understanding of adaptive evolution during climate change.

Living on the edge: Crayfish as drivers to anoxification of their own shelter microenvironment

Burrowing is a common trait among crayfish thought to help species deal with adverse environmental challenges. However, little is known about the microhabitat ecology of crayfish taxa in relation to their burrows. To fill this knowledge gap, we assessed the availability of oxygen inside the crayfish shelter by series of in-vivo and in-silico modelling experiments. Under modeled condition, we found that, except for the entrance region of the 200 mm, a flooded burrow microenvironment became anoxic within 8 h, on average. Multiple 12-hour day-night cycles, with burrows occupied by crayfish for 12 h and empty for 12 h, were not sufficient for refreshing the burrow microenvironment. We then examined the degree to which crayfish species with different propensities for burrowing are tolerant of self-created anoxia. From these experiments, primary and secondary burrowers showed best and most consistent tolerance-exhibiting ≥ 64% survival to anoxia and 25-91% survival of ≥ 9 h at anoxia, respectively. Tertiary burrowers exhibited little to no tolerance of anoxia with 0-50% survival to anoxia and only one species exhibiting survival (2%) of ≥ 9 h at anoxia. Results suggest that moderate to strongly burrowing crayfish can quickly draw down the dissolved oxygen in burrow water but appear to have conserved a legacy of strong tolerance of anoxia from their monophyletic ancestors-the lobsters-whereas tertiary burrowers have lost (or never evolved) this ability.

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-evolution from deep time to contemporary dynamics: The role of timescales and rate modulators

Eco-evolutionary dynamics, or eco-evolution for short, are often thought to involve rapid demography (ecology) and equally rapid heritable phenotypic changes (evolution) leading to novel, emergent system behaviours. We argue that this focus on contemporary dynamics is too narrow: Eco-evolution should be extended, first, beyond pure demography to include all environmental dimensions and, second, to include slow eco-evolution which unfolds over thousands or millions of years. This extension allows us to conceptualise biological systems as occupying a two-dimensional time space along axes that capture the speed of ecology and evolution. Using Hutchinson's analogy: Time is the 'theatre' in which ecology and evolution are two interacting 'players'. Eco-evolutionary systems are therefore dynamic: We identify modulators of ecological and evolutionary rates, like temperature or sensitivity to mutation, which can change the speed of ecology and evolution, and hence impact eco-evolution. Environmental change may synchronise the speed of ecology and evolution via these rate modulators, increasing the occurrence of eco-evolution and emergent system behaviours. This represents substantial challenges for prediction, especially in the context of global change. Our perspective attempts to integrate ecology and evolution across disciplines, from gene-regulatory networks to geomorphology and across timescales, from today to deep time.

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.

High speciation rate of niche specialists in hot springs

Ecological and evolutionary processes simultaneously regulate microbial diversity, but the evolutionary processes and their driving forces remain largely unexplored. Here we investigated the ecological and evolutionary characteristics of microbiota in hot springs spanning a broad temperature range (54.8-80 °C) by sequencing the 16S rRNA genes. Our results demonstrated that niche specialists and niche generalists are embedded in a complex interaction of ecological and evolutionary dynamics. On the thermal tolerance niche axis, thermal (T) sensitive (at a specific temperature) versus T-resistant (at least in five temperatures) species were characterized by different niche breadth, community abundance and dispersal potential, consequently differing in potential evolutionary trajectory. The niche-specialized T-sensitive species experienced strong temperature barriers, leading to completely species shift and high fitness but low abundant communities at each temperature ("home niche"), and such trade-offs thus reinforced peak performance, as evidenced by high speciation across temperatures and increasing diversification potential with temperature. In contrast, T-resistant species are advantageous of niche expansion but with poor local performance, as shown by wide niche breadth with high extinction, indicating these niche generalists are "jack-of-all-trades, master-of-none". Despite of such differences, the T-sensitive and T-resistant species are evolutionarily interacted. Specifically, the continuous transition from T-sensitive to T-resistant species insured the exclusion probability of T-resistant species at a relatively constant level across temperatures. The co-evolution and co-adaptation of T-sensitive and T-resistant species were in line with the red queen theory. Collectively, our findings demonstrate that high speciation of niche specialists could alleviate the environmental-filtering-induced negative effect on diversity.

Seasonal ecosystem linkages contribute to the maintenance of migratory polymorphism in a salmonid population

The influence of resource subsidies on animal growth, survival and reproduction is well understood, but their ultimate effects on life history have been less explored. Some wild species have a partially migratory life history, wherein migration is dictated based upon threshold traits regulated in part by the seasonal availability of resources. We conducted a large-scale field manipulation experiment where we provided a terrestrial invertebrate subsidy to red-spotted masu salmon. Individuals in stream reaches that received a subsidy had, on average, a 53% increase in growth rate relative to those in control reaches. This increased growth resulted in a greater proportion of individuals reaching the threshold body size and smolting in the autumn. Consequently, 19-55% of females in subsidized reaches became migratory, whereas 0-14% became migratory in the control reaches. Our findings highlight seasonal ecosystem linkage as a key ecosystem property for maintaining migratory polymorphism in partially migratory animals.

Allele frequencies and selection coefficients in locally adapted populations

Understanding the role of natural selection in driving evolutionary change requires accurate estimates of the strength of selection acting at the genetic level in the wild. This is challenging to achieve but may be easier in the case of populations in migration-selection balance. When two populations are at equilibrium under migration-selection balance, there exist loci whose alleles are selected different ways in the two populations. Such loci can be identified from genome sequencing by their high values of F_ST. This raises the question of what is the strength of selection on locally-adaptive alleles. To answer this question we analyse a 1-locus 2-allele model of a population distributed between two niches. We show by simulation of selected cases that the outputs from finite-population models are essentially the same as those from deterministic infinite-population models. We then derive theory for the infinite-population model showing the dependence of selection coefficients on equilibrium allele frequencies, migration rates, dominance and relative population sizes in the two niches. An Excel spreadsheet is provided for the calculation of selection coefficients and their approximate standard errors from observed values of population parameters. We illustrate our results with a worked example, with graphs showing the dependence of selection coefficients on equilibrium allele frequencies, and graphs showing how F_ST depends on the selection coefficients acting on the alleles at a locus. Given the extent of recent progress in ecological genomics, we hope our methods may help those studying migration-selection balance to quantify the advantages conferred by adaptive genes.

Genome-phenotype-environment associations identify signatures of selection in a panmictic population of threespine stickleback

Adaptive genetic divergence occurs when selection imposed by the environment causes the genomic component of the phenotype to differentiate. However, genomic signatures of natural selection are usually identified without information on which trait is responding to selection by which selective agent(s). Here, we integrate whole-genome sequencing with phenomics and measures of putative selective agents to assess the extent of adaptive divergence in threespine stickleback occupying the highly heterogeneous lake Mývatn, NE Iceland. We find negligible genome wide divergence, yet multiple traits (body size, gill raker structure and defence traits) were divergent along known ecological gradients (temperature, predatory bird densities and water depth). SNP based heritability of all measured traits was high (h²  = 0.42-0.65), indicating adaptive potential for all traits. Environment-association analyses further identified thousands of loci putatively involved in selection, related to genes linked to, for instance, neuron development and protein phosphorylation. Finally, we found that loci linked to water depth were concurrently associated with pelvic spine length variation - supporting the conclusion that divergence in pelvic spine length occurred in the face of gene flow. Our results suggest that whilst there is substantial genetic variation in the traits measured, phenotypic divergence of Mývatn stickleback is mostly weakly associated with environmental gradients, potentially as a result of substantial gene flow. Our study illustrates the value of integrative studies that combine genomic assays of multivariate trait variation with landscape genomics.

Population Genomic Time Series Data of a Natural Population Suggests Adaptive Tracking of Fluctuating Environmental Changes

Natural populations are constantly exposed to fluctuating environmental changes that negatively affect their fitness in unpredictable ways. While theoretical models show the possibility of counteracting these environmental changes through rapid evolutionary adaptations, there have been few empirical studies demonstrating such adaptive tracking in natural populations. Here, we analyzed environmental data, fitness-related phenotyping and genomic time-series data sampled over 3 years from a natural Chironomus riparius (Diptera, Insecta) population to address this question. We show that the population's environment varied significantly on the time scale of the sampling in many selectively relevant dimensions, independently of each other. Similarly, phenotypic fitness components evolved significantly on the same temporal scale (mean 0.32 Haldanes), likewise independent from each other. The allele frequencies of 367,446 SNPs across the genome showed evidence of positive selection. Using temporal correlation of spatially coherent allele frequency changes revealed 35,574 haplotypes with more than one selected SNP. The mean selection coefficient for these haplotypes was 0.30 (s.d. = 0.68). The frequency changes of these haplotypes clustered in 46 different temporal patterns, indicating concerted, independent evolution of many polygenic traits. Nine of these patterns were strongly correlated with measured environmental variables. Enrichment analysis of affected genes suggested the implication of a wide variety of biological processes. Thus, our results suggest overall that the natural population of C. riparius tracks environmental change through rapid polygenic adaptation in many independent dimensions. This is further evidence that natural selection is pervasive at the genomic level and that evolutionary and ecological time scales may not differ at all, at least in some organisms.

Importance of interindividual interactions in eco-evolutionary population dynamics: The rise of demo-genetic agent-based models

The study of eco-evolutionary dynamics, that is of the intertwinning between ecological and evolutionary processes when they occur at comparable time scales, is of growing interest in the current context of global change. However, many eco-evolutionary studies overlook the role of interindividual interactions, which are hard to predict and yet central to selective values. Here, we aimed at putting forward models that simulate interindividual interactions in an eco-evolutionary framework: the demo-genetic agent-based models (DG-ABMs). Being demo-genetic, DG-ABMs consider the feedback loop between ecological and evolutionary processes. Being agent-based, DG-ABMs follow populations of interacting individuals with sets of traits that vary among the individuals. We argue that the ability of DG-ABMs to take into account the genetic heterogeneity-that affects individual decisions/traits related to local and instantaneous conditions-differentiates them from analytical models, another type of model largely used by evolutionary biologists to investigate eco-evolutionary feedback loops. Based on the review of studies employing DG-ABMs and explicitly or implicitly accounting for competitive, cooperative or reproductive interactions, we illustrate that DG-ABMs are particularly relevant for the exploration of fundamental, yet pressing, questions in evolutionary ecology across various levels of organization. By jointly modelling the effects of management practices and other eco-evolutionary processes on interindividual interactions and population dynamics, DG-ABMs are also effective prospective and decision support tools to evaluate the short- and long-term evolutionary costs and benefits of management strategies and to assess potential trade-offs. Finally, we provide a list of the recent practical advances of the ABM community that should facilitate the development of DG-ABMs.

Minimal overall divergence of the gut microbiome in an adaptive radiation of Cyprinodon pupfishes despite potential adaptive enrichment for scale-eating

Adaptive radiations offer an excellent opportunity to understand the eco-evolutionary dynamics of gut microbiota and host niche specialization. In a laboratory common garden, we compared the gut microbiota of two novel derived trophic specialist pupfishes, a scale-eater and a molluscivore, to closely related and distant outgroup generalist populations, spanning both rapid trophic evolution within 10 kya and stable generalist diets persisting over 11 Mya. We predicted an adaptive and highly divergent microbiome composition in the trophic specialists reflecting their rapid rates of craniofacial and behavioral diversification. We sequenced 16S rRNA amplicons of gut microbiomes from lab-reared adult pupfishes raised under identical conditions and fed the same high protein diet. In contrast to our predictions, gut microbiota largely reflected phylogenetic distance among species, rather than generalist or specialist life history, in support of phylosymbiosis. However, we did find significant enrichment of Burkholderiaceae bacteria in replicated lab-reared scale-eater populations. These bacteria sometimes digest collagen, the major component of fish scales, supporting an adaptive shift. We also found some enrichment of Rhodobacteraceae and Planctomycetia in lab-reared molluscivore populations, but these bacteria target cellulose. Overall phylogenetic conservation of microbiome composition contrasts with predictions of adaptive radiation theory and observations of rapid diversification in all other trophic traits in these hosts, including craniofacial morphology, foraging behavior, aggression, and gene expression, suggesting that the functional role of these minor shifts in microbiota will be important for understanding the role of the microbiome in trophic diversification.

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’.

Rapid evolution of life-history traits in response to warming, predation and competition: A meta-analysis

Although studies quantifying evolutionary change in response to the selective pressures that organisms face in the wild have demonstrated that organisms can evolve rapidly, we lack a systematic assessment of the frequency, magnitude and direction of rapid evolutionary change across taxa. To address this gap, we conducted a meta-analysis of 58 studies that document the effects of warming, predation or competition on the evolution of body size, development rate or fecundity in natural or experimental animal populations. We tested whether there was a consistent effect of any selective agent on any trait, whether the direction of these effects align with theoretical predictions, and whether the three agents select in opposing directions on any trait. Overall, we found weak effects of all three selective agents on trait evolution: none of our nine traits by selective agent combinations had an overall effect that differed from zero, only 31% of studies had a significant within-study effect, and attributes of the included studies generally did not account for between-study variation in results. One notable exception was that predation targeting adults consistently resulted in the evolution of smaller prey body size. We discuss potential causes of these generally weak responses and consider how our results inform the ongoing development of eco-evolutionary research.

Return of the Lemnaceae: duckweed as a model plant system in the genomics and postgenomics era

The aquatic Lemnaceae family, commonly called duckweed, comprises some of the smallest and fastest growing angiosperms known on Earth. Their tiny size, rapid growth by clonal propagation, and facile uptake of labeled compounds from the media were attractive features that made them a well-known model for plant biology from 1950 to 1990. Interest in duckweed has steadily regained momentum over the past decade, driven in part by the growing need to identify alternative plants from traditional agricultural crops that can help tackle urgent societal challenges, such as climate change and rapid population expansion. Propelled by rapid advances in genomic technologies, recent studies with duckweed again highlight the potential of these small plants to enable discoveries in diverse fields from ecology to chronobiology. Building on established community resources, duckweed is reemerging as a platform to study plant processes at the systems level and to translate knowledge gained for field deployment to address some of society's pressing needs. This review details the anatomy, development, physiology, and molecular characteristics of the Lemnaceae to introduce them to the broader plant research community. We highlight recent research enabled by Lemnaceae to demonstrate how these plants can be used for quantitative studies of complex processes and for revealing potentially novel strategies in plant defense and genome maintenance.

Meta-analysis: Congruence of genomic and phenotypic differentiation across diverse natural study systems

Linking genotype to phenotype is a primary goal for understanding the genomic underpinnings of evolution. However, little work has explored whether patterns of linked genomic and phenotypic differentiation are congruent across natural study systems and traits. Here, we investigate such patterns with a meta-analysis of studies examining population-level differentiation at subsets of loci and traits putatively responding to divergent selection. We show that across the 31 studies (88 natural population-level comparisons) we examined, there was a moderate (R 2 = 0.39) relationship between genomic differentiation (F ST ) and phenotypic differentiation (P ST ) for loci and traits putatively under selection. This quantitative relationship between P ST and F ST for loci under selection in diverse taxa provides broad context and cross-system predictions for genomic and phenotypic adaptation by natural selection in natural populations. This context may eventually allow for more precise ideas of what constitutes "strong" differentiation, predictions about the effect size of loci, comparisons of taxa evolving in nonparallel ways, and more. On the other hand, links between P ST and F ST within studies were very weak, suggesting that much work remains in linking genomic differentiation to phenotypic differentiation at specific phenotypes. We suggest that linking genotypes to specific phenotypes can be improved by correlating genomic and phenotypic differentiation across a spectrum of diverging populations within a taxon and including wide coverage of both genomes and phenomes.

Genetic signatures of divergent selection in European beech (Fagus sylvatica L.) are associated with the variation in temperature and precipitation across its distribution range

High genetic variation and extensive gene flow may help forest trees with adapting to ongoing climate change, yet the genetic bases underlying their adaptive potential remain largely unknown. We investigated range-wide patterns of potentially adaptive genetic variation in 64 populations of European beech (Fagus sylvatica L.) using 270 SNPs from 139 candidate genes involved either in phenology or in stress responses. We inferred neutral genetic structure and processes (drift and gene flow) and performed differentiation outlier analyses and gene-environment association (GEA) analyses to detect signatures of divergent selection. Beech range-wide genetic structure was consistent with the species' previously identified postglacial expansion scenario and recolonization routes. Populations showed high diversity and low differentiation along the major expansion routes. A total of 52 loci were found to be putatively under selection and 15 of them turned up in multiple GEA analyses. Temperature and precipitation related variables were equally represented in significant genotype-climate associations. Signatures of divergent selection were detected in the same proportion for stress response and phenology-related genes. The range-wide adaptive genetic structure of beech appears highly integrated, suggesting a balanced contribution of phenology and stress-related genes to local adaptation, and of temperature and precipitation regimes to genetic clines. Our results imply a best-case scenario for the maintenance of high genetic diversity during range shifts in beech (and putatively other forest trees) with a combination of gene flow maintaining within-population neutral diversity and selection maintaining between-population adaptive differentiation.

Broad geographic sampling reveals the shared basis and environmental correlates of seasonal adaptation in Drosophila

To advance our understanding of adaptation to temporally varying selection pressures, we identified signatures of seasonal adaptation occurring in parallel among Drosophila melanogaster populations. Specifically, we estimated allele frequencies genome-wide from flies sampled early and late in the growing season from 20 widely dispersed populations. We identified parallel seasonal allele frequency shifts across North America and Europe, demonstrating that seasonal adaptation is a general phenomenon of temperate fly populations. Seasonally fluctuating polymorphisms are enriched in large chromosomal inversions, and we find a broad concordance between seasonal and spatial allele frequency change. The direction of allele frequency change at seasonally variable polymorphisms can be predicted by weather conditions in the weeks prior to sampling, linking the environment and the genomic response to selection. Our results suggest that fluctuating selection is an important evolutionary force affecting patterns of genetic variation in Drosophila.

Genetic and plastic rewiring of food webs under climate change

Climate change is altering ecological and evolutionary processes across biological scales. These simultaneous effects of climate change pose a major challenge for predicting the future state of populations, communities and ecosystems. This challenge is further exacerbated by the current lack of integration of research focused on these different scales.

We propose that integrating the fields of quantitative genetics and food web ecology will reveal new insights on how climate change may reorganize biodiversity across levels of organization. This is because quantitative genetics links the genotypes of individuals to population‐level phenotypic variation due to genetic (G), environmental (E) and gene‐by‐environment (G × E) factors. Food web ecology, on the other hand, links population‐level phenotypes to the structure and dynamics of communities and ecosystems.

We synthesize data and theory across these fields and find evidence that genetic (G) and plastic (E and G × E) phenotypic variation within populations will change in magnitude under new climates in predictable ways. We then show how changes in these sources of phenotypic variation can rewire food webs by altering the number and strength of species interactions, with consequences for ecosystem resilience. We also find evidence suggesting there are predictable asymmetries in genetic and plastic trait variation across trophic levels, which set the pace for phenotypic change and food web responses to climate change. Advances in genomics now make it possible to partition G, E and G × E phenotypic variation in natural populations, allowing tests of the hypotheses we propose.

By synthesizing advances in quantitative genetics and food web ecology, we provide testable predictions for how the structure and dynamics of biodiversity will respond to climate change.

Back to the future: Reintegrating biology to understand how past eco-evolutionary change can predict future outcomes

During the last few decades, biologists have made remarkable progress in understanding the fundamental processes that shape life. But despite the unprecedented level of knowledge now available, large gaps still remain in our understanding of the complex interplay of eco-evolutionary mechanisms across scales of life. Rapidly changing environments on Earth provide a pressing need to understand the potential implications of eco-evolutionary dynamics, which can be achieved by improving existing eco-evolutionary models and fostering convergence among the sub-fields of biology. We propose a new, data-driven approach that harnesses our knowledge of the functioning of biological systems to expand current conceptual frameworks and develop corresponding models that can more accurately represent and predict future eco-evolutionary outcomes. We suggest a roadmap toward achieving this goal. This long-term vision will move biology in a direction that can wield these predictive models for scientific applications that benefit humanity and increase the resilience of natural biological systems. We identify short, medium, and long-term key objectives to connect our current state of knowledge to this long-term vision, iteratively progressing across three stages: 1) utilizing knowledge of biological systems to better inform eco-evolutionary models, 2) generating models with more accurate predictions, and 3) applying predictive models to benefit the biosphere. Within each stage, we outline avenues of investigation and scientific applications related to the timescales over which evolution occurs, the parameter space of eco-evolutionary processes, and the dynamic interactions between these mechanisms. The ability to accurately model, monitor, and anticipate eco-evolutionary changes would be transformational to humanity's interaction with the global environment, providing novel tools to benefit human health, protect the natural world, and manage our planet's biosphere.

Adaptive differentiation and rapid evolution of a soil bacterium along a climate gradient

Increasing evidence suggests that evolutionary processes frequently shape ecological patterns; however, most microbiome studies thus far have focused on only the ecological responses of these communities. By using parallel field experiments and focusing in on a model soil bacterium, we showed that bacterial “species” are differentially adapted to local climates, leading to changes in their composition. Furthermore, we detected strain-level evolution, providing direct evidence that both ecological and evolutionary processes operate on annual timescales. The consideration of eco-evolutionary dynamics may therefore be important to understand the response of soil microbiomes to future environmental change.

Microbial community responses to environmental change are largely associated with ecological processes; however, the potential for microbes to rapidly evolve and adapt remains relatively unexplored in natural environments. To assess how ecological and evolutionary processes simultaneously alter the genetic diversity of a microbiome, we conducted two concurrent experiments in the leaf litter layer of soil over 18 mo across a climate gradient in Southern California. In the first experiment, we reciprocally transplanted microbial communities from five sites to test whether ecological shifts in ecotypes of the abundant bacterium, Curtobacterium, corresponded to past adaptive differentiation. In the transplanted communities, ecotypes converged toward that of the native communities growing on a common litter substrate. Moreover, these shifts were correlated with community-weighted mean trait values of the Curtobacterium ecotypes, indicating that some of the trait variation among ecotypes could be explained by local adaptation to climate conditions. In the second experiment, we transplanted an isogenic Curtobacterium strain and tracked genomic mutations associated with the sites across the same climate gradient. Using a combination of genomic and metagenomic approaches, we identified a variety of nonrandom, parallel mutations associated with transplantation, including mutations in genes related to nutrient acquisition, stress response, and exopolysaccharide production. Together, the field experiments demonstrate how both demographic shifts of previously adapted ecotypes and contemporary evolution can alter the diversity of a soil microbiome on the same timescale.

Competitive history shapes rapid evolution in a seasonal climate

Eco-evolutionary dynamics will play a critical role in determining species' fates as climatic conditions change. Unfortunately, we have little understanding of how rapid evolutionary responses to climate play out when species are embedded in the competitive communities that they inhabit in nature. We tested the effects of rapid evolution in response to interspecific competition on subsequent ecological and evolutionary trajectories in a seasonally changing climate using a field-based evolution experiment with Drosophila melanogaster Populations of D. melanogaster were either exposed, or not exposed, to interspecific competition with an invasive competitor, Zaprionus indianus, over the summer. We then quantified these populations' ecological trajectories (abundances) and evolutionary trajectories (heritable phenotypic change) when exposed to a cooling fall climate. We found that competition with Z. indianus in the summer affected the subsequent evolutionary trajectory of D. melanogaster populations in the fall, after all interspecific competition had ceased. Specifically, flies with a history of interspecific competition evolved under fall conditions to be larger and have lower cold fecundity and faster development than flies without a history of interspecific competition. Surprisingly, this divergent fall evolutionary trajectory occurred in the absence of any detectible effect of the summer competitive environment on phenotypic evolution over the summer or population dynamics in the fall. This study demonstrates that competitive interactions can leave a legacy that shapes evolutionary responses to climate even after competition has ceased, and more broadly, that evolution in response to one selective pressure can fundamentally alter evolution in response to subsequent agents of selection.

Population Genomics of Plant Viruses: The Ecology and Evolution of Virus Emergence

The genomics era has revolutionized studies of adaptive evolution by monitoring large numbers of loci throughout the genomes of many individuals. Ideally, the investigation of emergence in plant viruses requires examining the population dynamics of both virus and host, their interactions with each other, with other organisms and the abiotic environment. Genetic mechanisms that affect demographic processes are now being studied with high-throughput technologies, traditional genetics methods, and new computational tools for big-data. In this review, we discuss the utility of these approaches to monitor and detect changes in virus populations within cells and individuals, and over wider areas across species and communities of ecosystems. The advent of genomics in virology has fostered a multidisciplinary approach to tackling disease risk. The ability to make sense of the information now generated in this integrated setting is by far the most substantial obstacle to the ultimate goal of plant virology to minimize the threats to food security posed by disease. To achieve this goal, it is imperative to understand and forecast how populations respond to future changes in complex natural systems.

What processes must we understand to forecast regional-scale population dynamics?

An urgent challenge facing biologists is predicting the regional-scale population dynamics of species facing environmental change. Biologists suggest that we must move beyond predictions based on phenomenological models and instead base predictions on underlying processes. For example, population biologists, evolutionary biologists, community ecologists and ecophysiologists all argue that the respective processes they study are essential. Must our models include processes from all of these fields? We argue that answering this critical question is ultimately an empirical exercise requiring a substantial amount of data that have not been integrated for any system to date. To motivate and facilitate the necessary data collection and integration, we first review the potential importance of each mechanism for skilful prediction. We then develop a conceptual framework based on reaction norms, and propose a hierarchical Bayesian statistical framework to integrate processes affecting reaction norms at different scales. The ambitious research programme we advocate is rapidly becoming feasible due to novel collaborations, datasets and analytical tools.

The importance of genomic variation for biodiversity, ecosystems and people

The 2019 United Nations Global assessment report on biodiversity and ecosystem services estimated that approximately 1 million species are at risk of extinction. This primarily human-driven loss of biodiversity has unprecedented negative consequences for ecosystems and people. Classic and emerging approaches in genetics and genomics have the potential to dramatically improve these outcomes. In particular, the study of interactions among genetic loci within and between species will play a critical role in understanding the adaptive potential of species and communities, and hence their direct and indirect effects on biodiversity, ecosystems and people. We explore these population and community genomic contexts in the hope of finding solutions for maintaining and improving ecosystem services and nature's contributions to people.

Interpreting empirical estimates of experimentally derived physiological and biological thermal limits in ectotherms

Whole-organism function is underpinned by physiological and biological processes, which respond to temperature over a range of time scales. Given that environmental temperature controls biological rates within ectotherms, different experimental protocols are needed to assess the ability of organisms to withstand extreme weather events versus gradual temperature change. Here we emphasize the importance of time in shaping ecological and evolutionary processes, and as an experimental parameter that is key when interpreting physiology studies reporting thermal limits. We discuss how acute and chronic thermal performance is underpinned by mechanisms operating at different time scales — resistance, acclimation, and adaptation. We offer definitions of common physiological and biological temperature metrics and identify challenges inherent to compiling the wealth of historical temperature limit data now available into meta-analytic frameworks. We use a case study, data across temperate fishes, to highlight that false positives may occur when differences in the thermal tolerances of species are in fact due to experimental protocols. We further illustrate that false negatives can arise if researchers fail to recognize differences in thermal limits of species emerging from macrophysiological approaches that are due to biological mechanisms. We strongly advocate for the careful design, interpretation, and reporting of experimental results to ensure that conclusions arising from data synthesis efforts are grounded in theory.

Urbanization without isolation: the absence of genetic structure among cities and forests in the tiny acorn ant Temnothorax nylanderi

Urban alteration of neutral and adaptive evolutionary processes is still underexplored. Using a genome-wide SNP dataset, we investigated (i) urban-induced modifications of population demography, genetic diversity and population structure and (ii) signature of divergent selection between urban and forest populations in the ant species, Temnothorax nylanderi. Our results did not reveal an impact of urbanization on neutral processes since we observed: (i) analogous genetic diversity among paired urban/forest sites and two control populations; (ii) weak population genetic structure explained neither by habitat (urban versus forest) nor by geography; (iii) a remarkably similar demographic history across populations with an ancestral growth followed by a recent decline, regardless of their current habitat or geographical location. The micro-geographical home range of ants may explain their resilience to urbanization. Finally, we detected 19 candidate loci discriminating urban/forest populations and associated with core cellular components, molecular function or biological process. Two of these loci were associated with a gene ontology term that was previously found to belong to a module of co-expressed genes related to caste phenotype. These results call for transcriptomics analyses to identify genes associated with ant social traits and to infer their potential role in urban adaptation.

Towards a New Generation of Trait-Flexible Vegetation Models

Plant trait variability, emerging from eco-evolutionary dynamics that range from alleles to macroecological scales, is one of the most elusive, but possibly most consequential, aspects of biodiversity. Plasticity, epigenetics, and genetic diversity are major determinants of how plants will respond to climate change, yet these processes are rarely represented in current vegetation models. Here, we provide an overview of the challenges associated with understanding the causes and consequences of plant trait variability, and review current developments to include plasticity and evolutionary mechanisms in vegetation models. We also present a roadmap of research priorities to develop a next generation of vegetation models with flexible traits. Including trait variability in vegetation models is necessary to better represent biosphere responses to global change.

Adaptation to the abiotic environment in insects: the influence of variability on ecophysiology and evolutionary genomics

Advances in tools to gather environmental, phenotypic, and molecular data have accelerated our ability to detect abiotic drivers of variation across the genome-to-phenome spectrum in model and non-model insects. However, differences in the spatial and temporal resolution of these data sets may create gaps in our understanding of linkages between environment, genotype, and phenotype that yield missed or misleading results about adaptive variation. In this review we highlight sources of variability that might impact studies of phenotypic and 'omic environmental adaptation, challenges to collecting data at relevant scales, and possible solutions that link intensive fine-scale reductionist studies of mechanisms to large-scale biogeographic patterns.

Population Genetics in the Human Microbiome

While the human microbiome's structure and function have been extensively studied, its within-species genetic diversity is less well understood. However, genetic mutations in the microbiome can confer biomedically relevant traits, such as the ability to extract nutrients from food, metabolize drugs, evade antibiotics, and communicate with the host immune system. The population genetic processes by which these traits evolve are complex, in part due to interacting ecological and evolutionary forces in the microbiome. Advances in metagenomic sequencing, coupled with bioinformatics tools and population genetic models, facilitate quantification of microbiome genetic variation and inferences about how this diversity arises, evolves, and correlates with traits of both microbes and hosts. In this review, we explore the population genetic forces (mutation, recombination, drift, and selection) that shape microbiome genetic diversity within and between hosts, as well as efforts towards predictive models that leverage microbiome genetics.

Microbiome composition shapes rapid genomic adaptation of Drosophila melanogaster

Population genomic data has revealed patterns of genetic variation associated with adaptation in many taxa. Yet understanding the adaptive process that drives such patterns is challenging; it requires disentangling the ecological agents of selection, determining the relevant timescales over which evolution occurs, and elucidating the genetic architecture of adaptation. Doing so for the adaptation of hosts to their microbiome is of particular interest with growing recognition of the importance and complexity of host-microbe interactions. Here, we track the pace and genomic architecture of adaptation to an experimental microbiome manipulation in replicate populations of Drosophila melanogaster in field mesocosms. Shifts in microbiome composition altered population dynamics and led to divergence between treatments in allele frequencies, with regions showing strong divergence found on all chromosomes. Moreover, at divergent loci previously associated with adaptation across natural populations, we found that the more common allele in fly populations experimentally enriched for a certain microbial group was also more common in natural populations with high relative abundance of that microbial group. These results suggest that microbiomes may be an agent of selection that shapes the pattern and process of adaptation and, more broadly, that variation in a single ecological factor within a complex environment can drive rapid, polygenic adaptation over short timescales.

A way forward with eco evo devo: an extended theory of resource polymorphism with postglacial fishes as model systems

A major goal of evolutionary science is to understand how biological diversity is generated and altered. Despite considerable advances, we still have limited insight into how phenotypic variation arises and is sorted by natural selection. Here we argue that an integrated view, which merges ecology, evolution and developmental biology (eco evo devo) on an equal footing, is needed to understand the multifaceted role of the environment in simultaneously determining the development of the phenotype and the nature of the selective environment, and how organisms in turn affect the environment through eco evo and eco devo feedbacks. To illustrate the usefulness of an integrated eco evo devo perspective, we connect it with the theory of resource polymorphism (i.e. the phenotypic and genetic diversification that occurs in response to variation in available resources). In so doing, we highlight fishes from recently glaciated freshwater systems as exceptionally well-suited model systems for testing predictions of an eco evo devo framework in studies of diversification. Studies on these fishes show that intraspecific diversity can evolve rapidly, and that this process is jointly facilitated by (i) the availability of diverse environments promoting divergent natural selection; (ii) dynamic developmental processes sensitive to environmental and genetic signals; and (iii) eco evo and eco devo feedbacks influencing the selective and developmental environments of the phenotype. We highlight empirical examples and present a conceptual model for the generation of resource polymorphism - emphasizing eco evo devo, and identify current gaps in knowledge.

Evolutionary and demographic consequences of phenological mismatches

Climate change has often led to unequal shifts in the seasonal timing (phenology) of interacting species, such as consumers and their resource, leading to phenological 'mismatches'. Mismatches occur when the time at which a consumer species's demands for a resource are high does not match with the period when this resource is abundant. Here, we review the evolutionary and population-level consequences of such mismatches and how these depend on other ecological factors, such as additional drivers of selection and density-dependent recruitment. This review puts the research on phenological mismatches into a conceptual framework, applies this framework beyond consumer-resource interactions and illustrates this framework using examples drawn from the vast body of literature on mismatches. Finally, we point out priority questions for research on this key impact of climate change.

Random PCR-based genotyping by sequencing technology GRAS-Di (genotyping by random amplicon sequencing, direct) reveals genetic structure of mangrove fishes

While various technologies for high-throughput genotyping have been developed for ecological studies, simple methods tolerant to low-quality DNA samples are still limited. In this study, we tested the availability of a random PCR-based genotyping-by-sequencing technology, genotyping by random amplicon sequencing, direct (GRAS-Di). We focused on population genetic analysis of estuarine mangrove fishes, including two resident species, the Amboina cardinalfish (Fibramia amboinensis, Bleeker, 1853) and the Duncker's river garfish (Zenarchopterus dunckeri, Mohr, 1926), and a marine migrant, the blacktail snapper (Lutjanus fulvus, Forster, 1801). Collections were from the Ryukyu Islands, southern Japan. PCR amplicons derived from ~130 individuals were pooled and sequenced in a single lane on a HiSeq2500 platform, and an average of three million reads was obtained per individual. Consensus contigs were assembled for each species and used for genotyping of single nucleotide polymorphisms by mapping trimmed reads onto the contigs. After quality filtering steps, 4,000-9,000 putative single nucleotide polymorphisms were detected for each species. Although DNA fragmentation can diminish genotyping performance when analysed on next-generation sequencing technology, the effect was small. Genetic differentiation and a clear pattern of isolation-by-distance was observed in F. amboinensis and Z. dunckeri by means of principal component analysis, F_ST and the admixture analysis. By contrast, L. fulvus comprised a genetically homogeneous population with directional recent gene flow. These genetic differentiation patterns reflect patterns of estuary use through life history. These results showed the power of GRAS-Di for fine-grained genetic analysis using field samples, including mangrove fishes.

Demographic responses underlying eco-evolutionary dynamics as revealed with inverse modelling

Changes in population dynamics due to interacting evolutionary and ecological processes are the direct result of responses in vital rates, that is stage‐specific growth, survival and fecundity. Quantifying through which vital rates population fitness is affected, instead of focusing on population trends only, can give a more mechanistic understanding of eco‐evolutionary dynamics.

The aim of this study was to estimate the underlying demographic rates of aphid (Myzus persicae) populations. We analysed unpublished stage‐structure population dynamics data of a field experiment with caged and uncaged populations in which rapid evolutionary dynamics were observed, as well as unpublished results from an individual life table experiment performed in a glasshouse.

Using data on changes in population abundance and stage distributions over time, we estimated transition matrices with inverse modelling techniques, in a Bayesian framework. The model used to fit across all experimental treatments included density as well as clone‐specific caging effects. We additionally used individual life table data to inform the model on survival, growth and reproduction.

Results suggest that clones varied considerably in vital rates, and imply trade‐offs between reproduction and survival. Responses to densities also varied between clones. Negative density dependence was found in growth and reproduction, and the presence of predators and competitors further decreased these two vital rates, while survival estimates increased. Under uncaged conditions, population growth rates of the evolving populations were increased compared to the expectation based on the pure clones.

Our inverse modelling approach revealed how much vital rates contributed to the eco‐evolutionary dynamics. The decomposition analysis showed that variation in population growth rates in the evolving populations was to a large extent shaped by plant size. Yet, it also revealed an impact of evolutionary changes in clonal composition. Finally, we discuss that inverse modelling is a complex problem, as multiple combinations of individual rates can result in the same dynamics. We discuss assumptions and limitations, as well as opportunities, of this approach.

On the deformability of an empirical fitness landscape by microbial evolution

A fitness landscape is a map between the genotype and its reproductive success in a given environment. The topography of fitness landscapes largely governs adaptive dynamics, constraining evolutionary trajectories and the predictability of evolution. Theory suggests that this topography can be deformed by mutations that produce substantial changes to the environment. Despite its importance, the deformability of fitness landscapes has not been systematically studied beyond abstract models, and little is known about its reach and consequences in empirical systems. Here we have systematically characterized the deformability of the genome-wide metabolic fitness landscape of the bacterium Escherichia coli Deformability is quantified by the noncommutativity of epistatic interactions, which we experimentally demonstrate in mutant strains on the path to an evolutionary innovation. Our analysis shows that the deformation of fitness landscapes by metabolic mutations rarely affects evolutionary trajectories in the short range. However, mutations with large environmental effects produce long-range landscape deformations in distant regions of the genotype space that affect the fitness of later descendants. Our results therefore suggest that, even in situations in which mutations have strong environmental effects, fitness landscapes may retain their power to forecast evolution over small mutational distances despite the potential attenuation of that power over longer evolutionary trajectories. Our methods and results provide an avenue for integrating adaptive and eco-evolutionary dynamics with complex genetics and genomics.

Taxonomy in the Kunming Institute of Botany (KIB): Progress during the past decade (2008-2018) and perspectives on future development

The development of new taxonomical theories and approaches, particularly molecular phylogenetics, has led to the expansion of traditional morphology-based taxonomy into the concept of "integrative taxonomy." Taxonomic knowledge has assumed greater significance in recent years, particularly because of growing concerns over the looming biodiversity crisis. Since its establishment in 1938, the Kunming Institute of Botany (KIB), which is located in Yunnan province in Southwest China, has focused attention on the taxonomy and conservation of the flora of China. For the forthcoming 80th anniversary of KIB, we review the achievements of researchers at KIB and their associates with respect to the taxonomy of land plants, fungi, and lichen. Major taxonomic advances are summarized for families of Calymperaceae, Cryphaeaceae, Lembophyllaceae, Neckeraceae, Polytrichaceae and Pottiaceae of mosses, Pteridaceae and Polypodiaceae of ferns, Taxaceae and Cycadaceae of gymnosperms, Asteraceae, Begoniaceae, Ericaceae, Euphorbiaceae, Gesneriaceae, Lamiaceae, Orchidaceae, Orobanchaceae, Poaceae, Theaceae and Urticaceae of angiosperms, Agaricaceae, Amanitaceae, Boletaceae, Cantharellaceae, Physalacriaceae Russulaceae, Suillaceae and Tuberaceae of fungi, and Ophioparmaceae and Parmeliaceae of lichens. Regarding the future development of taxonomy at KIB, we recommend that taxonomists continue to explore the biodiversity of China, integrate new theories and technologies with traditional taxonomic approaches, and engage in creative monographic work, with support from institutions, funding agencies, and the public.

Evolution as an ecosystem process: insights from genomics

Evolution is a fundamental ecosystem process. The study of genomic variation of organisms can not only improve our understanding of evolutionary processes, but also of contemporary and future ecosystem dynamics. We argue that integrative research between the fields of genomics and ecosystem ecology could generate new insights. Specifically, studies of biodiversity and ecosystem functioning, evolutionary rescue, and eco-evolutionary dynamics could all benefit from information about variation in genome structure and the genetic architecture of traits, whereas genomic studies could benefit from information about the ecological context of evolutionary dynamics. We propose new ways to help link research on functional genomic diversity with (reciprocal) interactions between phenotypic evolution and ecosystem change. Despite numerous challenges, we anticipate that the wealth of genomic data being collected on natural populations will improve our understanding of ecosystems.