Extending eco-evolutionary theory with oligomorphic dynamics

Understanding the interplay between ecological processes and the evolutionary dynamics of quantitative traits in natural systems remains a major challenge. Two main theoretical frameworks are used to address this question, adaptive dynamics and quantitative genetics, both of which have strengths and limitations and are often used by distinct research communities to address different questions. In order to make progress, new theoretical developments are needed that integrate these approaches and strengthen the link to empirical data. Here, we discuss a novel theoretical framework that bridges the gap between quantitative genetics and adaptive dynamics approaches. ‘Oligomorphic dynamics’ can be used to analyse eco-evolutionary dynamics across different time scales and extends quantitative genetics theory to account for multimodal trait distributions, the dynamical nature of genetic variance, the potential for disruptive selection due to ecological feedbacks, and the non-normal or skewed trait distributions encountered in nature. Oligomorphic dynamics explicitly takes into account the effect of environmental feedback, such as frequency- and density-dependent selection, on the dynamics of multi-modal trait distributions and we argue it has the potential to facilitate a much tighter integration between eco-evolutionary theory and empirical data.     

The Effects of Predator Evolution and Genetic Variation on Predator–Prey Population-Level Dynamics

This paper explores how predator evolution and the magnitude of predator genetic variation alter the population-level dynamics of predator–prey systems. We do this by analyzing a general eco-evolutionary predator–prey model using four methods: Method 1 identifies how eco-evolutionary feedbacks alter system stability in the fast and slow evolution limits; Method 2 identifies how the amount of standing predator genetic variation alters system stability; Method 3 identifies how the phase lags in predator–prey cycles depend on the amount of genetic variation; and Method 4 determines conditions for different cycle shapes in the fast and slow evolution limits using geometric singular perturbation theory. With these four methods, we identify the conditions under which predator evolution alters system stability and shapes of predator–prey cycles, and how those effect depend on the amount of genetic variation in the predator population. We discuss the advantages and disadvantages of each method and the relations between the four methods. This work shows how the four methods can be used in tandem to make general predictions about eco-evolutionary dynamics and feedbacks.     

Eco-evolutionary dynamics in herbivorous insect communities mediated by induced plant responses

It is increasingly recognized that the ecology of communities and evolution of species within communities are interdependent, and researchers have been paying attention to this rapidly emerging field of research, i.e., through studies on eco-evolutionary dynamics. Most of the studies on eco-evolutionary dynamics have been concerned with direct trophic interactions. However, community ecologists have shown that trait-mediated indirect effects play an important role in shaping the structure of natural communities. In particular, in terrestrial plant–insect systems, indirect effects mediated through herbivore-induced plant responses are common and have a great impact on the structure of herbivore communities. This review describes eco-evolutionary dynamics in herbivorous insect communities, and specifically focuses on the key role of herbivore-induced plant responses in eco-evolutionary dynamics. First, I review studies on the evolution of herbivore traits relevant to plant induction and discuss evolution in a community context mediated by induced plant responses. Second, I highlight how intraspecific genetic variation or evolution in herbivore traits can influence herbivore community structure. Finally, I propose the hypothetical model that induced plant responses supports eco-evolutionary feedback in herbivore communities. In this review, I argue that the application of the indirect interaction web approaches into studies on eco-evolutionary will provide profound insights into understanding of mechanisms of the generation and maintenance of biodiversity.     

极小种群野生植物生存力分析: 方法、问题与展望

日益加剧的环境变化与人类活动严重威胁种群的生存, 因此预测多种胁迫下种群的命运至关重要。种群生存力分析(population viability analysis, PVA)是评估种群所受威胁、灭绝或衰退风险以及恢复可能性的有效方法。基于物种及环境数据和建模, 种群生存力分析能够整合不同类型变量, 为目标物种的保护提供建议。然而, 极小种群野生植物的个体数据难以获取, 种群参数估计困难, 这导致传统种群生存力分析方法在此类种群中的应用存在局限性。在此, 本文提出了极小种群野生植物生存力分析的潜在方法: 小样本非统计分析法及环境变化下的种群适应力分析。小样本非统计分析法有益于提高种群统计学参数的估计精度, 而立足于生态进化生物学的种群生存力研究有助于从生物学机理方面了解和预测种群动态, 为极小种群野生植物的保护提供更适宜的理论指导。     

Three perspectives on the prediction of chemical effects in ecosystems

The increasing production, use and emission of synthetic chemicals into the environment represents a major driver of global change. The large number of synthetic chemicals, limited knowledge on exposure patterns and effects in organisms and their interaction with other global change drivers hamper the prediction of effects in ecosystems. However, recent advances in biomolecular and computational methods are promising to improve our capacity for prediction. We delineate three idealised perspectives for the prediction of chemical effects: the suborganismal, organismal and ecological perspective, which are currently largely separated. Each of the outlined perspectives includes essential and complementary theories and tools for prediction but captures only part of the phenomenon of chemical effects. Links between the perspectives may foster predictive modelling of chemical effects in ecosystems and extrapolation between species. A major challenge for the linkage is the lack of data sets simultaneously covering different levels of biological organisation (here referred to as biological levels) as well as varying temporal and spatial scales. Synthesising the three perspectives, some central aspects and associated types of data seem particularly necessary to improve prediction. First, suborganism- and organism-level responses to chemicals need to be recorded and tested for relationships with chemical groups and organism traits. Second, metrics that are measurable at many biological levels, such as energy, need to be scrutinised for their potential to integrate across levels. Third, experimental data on the simultaneous response over multiple biological levels and spatiotemporal scales are required. These could be collected in nested and interconnected micro- and mesocosm experiments. Lastly, prioritisation of processes involved in the prediction framework needs to find a balance between simplification and capturing the essential complexity of a system. For example, in some cases, eco-evolutionary dynamics and interactions may need stronger consideration. Prediction needs to move from a static to a real-world eco-evolutionary view.     

Eco-evolutionary consequences of habitat warming and fragmentation in communities

Eco-evolutionary dynamics can mediate species and community responses to habitat warming and fragmentation, two of the largest threats to biodiversity and ecosystems. The eco-evolutionary consequences of warming and fragmentation are typically studied independently, hindering our understanding of their simultaneous impacts. Here, we provide a new perspective rooted in trade-offs among traits for understanding their eco-evolutionary consequences. On the one hand, temperature influences traits related to metabolism, such as resource acquisition and activity levels. Such traits are also likely to have trade-offs with other energetically costly traits, like antipredator defences or dispersal. On the other hand, fragmentation can influence a variety of traits (e.g. dispersal) through its effects on the spatial environment experienced by individuals, as well as properties of populations, such as genetic structure. The combined effects of warming and fragmentation on communities should thus reflect their collective impact on traits of individuals and populations, as well as trade-offs at multiple trophic levels, leading to unexpected dynamics when effects are not additive and when evolutionary responses modulate them. Here, we provide a road map to navigate this complexity. First, we review single-species responses to warming and fragmentation. Second, we focus on consumer–resource interactions, considering how eco-evolutionary dynamics can arise in response to warming, fragmentation, and their interaction. Third, we illustrate our perspective with several example scenarios in which trait trade-offs could result in significant eco-evolutionary dynamics. Specifically, we consider the possible eco-evolutionary consequences of (i) evolution in thermal performance of a species involved in a consumer–resource interaction, (ii) ecological or evolutionary changes to encounter and attack rates of consumers, and (iii) changes to top consumer body size in tri-trophic food chains. In these scenarios, we present a number of novel, sometimes counter-intuitive, potential outcomes. Some of these expectations contrast with those solely based on ecological dynamics, for example, evolutionary responses in unexpected directions for resource species or unanticipated population declines in top consumers. Finally, we identify several unanswered questions about the conditions most likely to yield strong eco-evolutionary dynamics, how better to incorporate the role of trade-offs among traits, and the role of eco-evolutionary dynamics in governing responses to warming in fragmented communities.     

Tackling the population genetics of clonal and partially clonal organisms

Many clonal organisms experience occasional events of sexual recombination, with profound consequences for their population dynamics and evolutionary trajectories. With the recent development of polymorphic genetic markers and new statistical methods, we now have an unprecedented ability to detect recombination in organisms that are thought to reproduce strictly, or essentially asexually. However, it is not always obvious which methodology to apply. Consequently, biologists might decide how to analyse their data without clear guidelines. Here, we discuss the available methods, focusing on those best suited when working with limited genetic information, such as a few genetic markers or DNA sequences. We conclude by commenting on the prospects offered by some recent conceptual advances and the access to high throughput technologies in an increasing number of model organisms.     

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.     

Digging through model complexity: using hierarchical models to uncover evolutionary processes in the wild

The growing interest for studying questions in the wild requires acknowledging that eco-evolutionary processes are complex, hierarchically structured and often partially observed or with measurement error. These issues have long been ignored in evolutionary biology, which might have led to flawed inference when addressing evolutionary questions. Hierarchical modelling (HM) has been proposed as a generic statistical framework to deal with complexity in ecological data and account for uncertainty. However, to date, HM has seldom been used to investigate evolutionary mechanisms possibly underlying observed patterns. Here, we contend the HM approach offers a relevant approach for the study of eco-evolutionary processes in the wild by confronting formal theories to empirical data through proper statistical inference. Studying eco-evolutionary processes requires considering the complete and often complex life histories of organisms. We show how this can be achieved by combining sequentially all life-history components and all available sources of information through HM. We demonstrate how eco-evolutionary processes may be poorly inferred or even missed without using the full potential of HM. As a case study, we use the Atlantic salmon and data on wild marked juveniles. We assess a reaction norm for migration and two potential trade-offs for survival. Overall, HM has a great potential to address evolutionary questions and investigate important processes that could not previously be assessed in laboratory or short time-scale studies.     

Trophic cascades alter eco-evolutionary dynamics and body size evolution

Trait evolution in predator–prey systems can feed back to the dynamics of interacting species as well as cascade to impact the dynamics of indirectly linked species (eco-evolutionary trophic cascades; EETCs). A key mediator of trophic cascades is body mass, as it both strongly influences and evolves in response to predator–prey interactions. Here, we use Gillespie eco-evolutionary models to explore EETCs resulting from top predator loss and mediated by body mass evolution. Our four-trophic-level food chain model uses allometric scaling to link body mass to different functions (ecological pleiotropy) and is realistically parameterized from the FORAGE database to mimic the parameter space of a typical freshwater system. To track real-time changes in selective pressures, we also calculated fitness gradients for each trophic level. As predicted, top predator loss generated alternating shifts in abundance across trophic levels, and, depending on the nature and strength in changes to fitness gradients, also altered trajectories of body mass evolution. Although more distantly linked, changes in the abundance of top predators still affected the eco-evolutionary dynamics of the basal producers, in part because of their relatively short generation times. Overall, our results suggest that impacts on top predators can set off transient EETCs with the potential for widespread indirect impacts on food webs.     

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.     

Integrative structural modeling with small angle X-ray scattering profiles

Recent technological advances enabled high-throughput collection of Small Angle X-ray Scattering (SAXS) profiles of biological macromolecules. Thus, computational methods for integrating SAXS profiles into structural modeling are needed more than ever. Here, we review specifically the use of SAXS profiles for the structural modeling of proteins, nucleic acids, and their complexes. First, the approaches for computing theoretical SAXS profiles from structures are presented. Second, computational methods for predicting protein structures, dynamics of proteins in solution, and assembly structures are covered. Third, we discuss the use of SAXS profiles in integrative structure modeling approaches that depend simultaneously on several data types.     

Environmental fluctuations restrict eco-evolutionary dynamics in predator–prey system

Environmental fluctuations, species interactions and rapid evolution are all predicted to affect community structure and their temporal dynamics. Although the effects of the abiotic environment and prey evolution on ecological community dynamics have been studied separately, these factors can also have interactive effects. Here we used bacteria–ciliate microcosm experiments to test for eco-evolutionary dynamics in fluctuating environments. Specifically, we followed population dynamics and a prey defence trait over time when populations were exposed to regular changes of bottom-up or top-down stressors, or combinations of these. We found that the rate of evolution of a defence trait was significantly lower in fluctuating compared with stable environments, and that the defence trait evolved to lower levels when two environmental stressors changed recurrently. The latter suggests that top-down and bottom-up changes can have additive effects constraining evolutionary response within populations. The differences in evolutionary trajectories are explained by fluctuations in population sizes of the prey and the predator, which continuously alter the supply of mutations in the prey and strength of selection through predation. Thus, it may be necessary to adopt an eco-evolutionary perspective on studies concerning the evolution of traits mediating species interactions.     

Eco-evolutionary dynamics

Evolutionary ecologists and population biologists have recently considered that ecological and evolutionary changes are intimately linked and can occur on the same time-scale. Recent theoretical developments have shown how the feedback between ecological and evolutionary dynamics can be linked, and there are now empirical demonstrations showing that ecological change can lead to rapid evolutionary change. We also have evidence that microevolutionary change can leave an ecological signature. We are at a stage where the integration of ecology and evolution is a necessary step towards major advances in our understanding of the processes that shape and maintain biodiversity. This special feature about ‘eco-evolutionary dynamics’ brings together biologists from empirical and theoretical backgrounds to bridge the gap between ecology and evolution and provide a series of contributions aimed at quantifying the interactions between these fundamental processes.     

Computational Biology Methods and Their Application to the Comparative Genomics of Endocellular Symbiotic Bacteria of Insects

Comparative genomics has become a real tantalizing challenge in the postgenomic era. This fact has been mostly magnified by the plethora of new genomes becoming available in a daily bases. The overwhelming list of new genomes to compare has pushed the field of bioinformatics and computational biology forward toward the design and development of methods capable of identifying patterns in a sea of swamping data noise. Despite many advances made in such endeavor, the ever-lasting annoying exceptions to the general patterns remain to pose difficulties in generalizing methods for comparative genomics. In this review, we discuss the different tools devised to undertake the challenge of comparative genomics and some of the exceptions that compromise the generality of such methods. We focus on endosymbiotic bacteria of insects because of their genomic dynamics peculiarities when compared to free-living organisms.     

Size-dependent predation and correlated life history traits alter eco-evolutionary dynamics and selection for faster individual growth

Age at maturation is a key life history trait influencing individual fitness, population age structure, and ecological interactions. We investigated the evolution of age at maturity through changes in the von Bertalanffy growth constant for organisms with a simple juvenile-adult life history. We used Gillespie eco-evolutionary models to uncover the role of predation in driving the evolution of the growth constant when eco-evolutionary dynamics are present. We incorporated both size-independent and size-dependent predation into our models to generate differences in selection and dynamics in the system. Our results generally support the idea that faster ontogenetic growth is beneficial when populations are growing but that predation tends to have little effect on age at maturity unless there are trade-offs with other life history traits. In particular, if faster ontogenetic growth comes at the cost of fecundity, our results suggest that predation selects for intermediate levels of growth and fecundity. Eco-evolutionary dynamics influenced the nature of selection only when growth was linked to fecundity. We also found that predators that increasingly consume larger prey tend to have higher population sizes due to the greater energy intake from larger prey, but the growth rate-fecundity trade-off reversed this pattern. Overall, our results suggest an important role for interactions between size-dependent foraging and life-history trade-offs in generating varying selection on age at maturity through underlying growth traits.     

pedagog: software for simulating eco-evolutionary population dynamics

pedagog is a Windows program that can be used to determine power for, and validate inferences drawn from, eco-evolutionary studies. It models dynamics of multiple populations and their interactions through individual-based simulations while simultaneously recording genotype, pedigree and trait information at the individual level. pedagog also allows for specification of heritable traits, natural and sexual selection acting upon those traits, population sampling schemes and incorporation of genetic and demographic errors into the output. Overall, parameters can be specified for genetic diversity, demographics, mating design, genetic and demographic errors, individual growth models, trait heritability and selection, and output formatting. Demographic parameters can be either age or function based, and all parameters can be drawn from 12 statistical distributions where appropriate. Simulation results can be automatically formatted for 57 existing software programs to facilitate postsimulation analyses. pedagog is freely available for download at https://bcrc.bio.umass.edu/pedigreesoftware/.     

Game theory sheds new light on ecological responses to current climate change when phenology is historically mismatched

Phenological changes are well documented biological effects of current climate change but their adaptive value and demographic consequences are poorly known. Game theoretical models have shown that deviating from the fitness-maximising phenology can be evolutionary stable under frequency-dependent selection. We study eco-evolutionary responses to climate change when the historical phenology is mismatched in this way. For illustration we model adaptation of arrival dates in migratory birds that compete for territories at their breeding grounds. We simulate climate change by shifting the timing and the length of the favourable season for breeding. We show that initial trends in changes of population densities can be either reinforced or counteracted during the ensuing evolutionary adaptation. We find in total seven qualitatively different population trajectories during the transition to a new evolutionary equilibrium. This surprising diversity of eco-evolutionary responses provides adaptive explanations to the observed variation in phenological responses to recent climate change.     

Molecular phylogenetics: state-of-the-art methods for looking into the past

As the amount of molecular sequence data in the public domain grows, so does the range of biological topics that it influences through evolutionary considerations. In recent years, a number of developments have enabled molecular phylogenetic methodology to keep pace. Likelihood-based inferential techniques, although controversial in the past, lie at the heart of these new methods and are producing the promised advances in the understanding of sequence evolution. They allow both a wide variety of phylogenetic inferences from sequence data and robust statistical assessment of all results. It cannot remain acceptable to use outdated data analysis techniques when superior alternatives exist. Here, we discuss the most important and exciting methods currently available to the molecular phylogeneticist.