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Eusocial insects-ants, bees, wasps, and termites-are being recognized as model organisms to unravel the evolutionary paradox of aging for two reasons: (1) queens (and kings, in termites) of social insects outlive similarly sized solitary insects by up to several orders of magnitude and (2) all eusocial taxa show a divergence of long queen and shorter worker life spans, despite their shared genomes and even under risk-free laboratory environments. Traditionally, these observations have been explained by invoking the classical evolutionary aging theory: well-protected inside their nests, queens are much less exposed to external hazards than foraging workers, and this provides natural selection the opportunity to favor queens that perform well at advanced ages. Although quite plausible, these verbal arguments have not been backed up by mathematical analysis. Here, for the first time, we provide quantitative models for the evolution of caste-specific aging patterns. We show that caste-specific mortality risks are in general neither sufficient nor necessary to explain the evolutionary divergence in life span between queens and workers and the extraordinary queen life spans. Reproductive monopolization and the delayed production of sexual offspring in highly social colonies lead natural selection to inherently favor queens that live much longer than workers, even when exposed to the same external hazards. Factors that reduce a colony's reproductive skew, such as polygyny and worker reproduction, tend to reduce the evolutionary divergence in life span between queens and workers. Caste-specific extrinsic hazards also affect life span divergence, but to a much smaller extent than reproductive monopolization.

'Evolvability' - the ability to undergo adaptive evolution - is a key concept for understanding and predicting the response of biological systems to environmental change. Evolvability has various facets and is applied in many ways, easily leading to misunderstandings among researchers. To clarify matters, we first categorize the mechanisms and organismal features underlying evolvability into determinants providing variation, determinants shaping the effect of variation on fitness, and determinants shaping the selection process. Second, we stress the importance of timescale when studying evolvability. Third, we distinguish between evolvability determinants with a broad and a narrow scope. Finally, we highlight two contrasting perspectives on evolvability: general evolvability and specific evolvability. We hope that this framework facilitates communication and guides future research.

The coevolution of predators and prey has been the subject of much empirical and theoretical research that produced intriguing insights into the interplay of ecology and evolution. To allow for mathematical analysis, models of predator–prey coevolution are often coarse-grained, focussing on population-level processes and largely neglecting individual-level behaviour. As selection is acting on individual-level properties, we here present a more mechanistic approach: an individual-based simulation model for the coevolution of predators and prey on a fine-grained resource landscape, where features relevant for ecology (like changes in local densities) and evolution (like differences in survival and reproduction) emerge naturally from interactions between individuals. Our focus is on predator–prey movement behaviour, and we present a new method for implementing evolving movement strategies in an efficient and intuitively appealing manner. Throughout their lifetime, predators and prey make repeated movement decisions on the basis of their movement strategies. Over the generations, the movement strategies evolve, as individuals that successfully survive and reproduce leave their strategy to more descendants. We show that the movement strategies in our model evolve rapidly, thereby inducing characteristic spatial patterns like spiral waves and static spots. Transitions between these patterns occur frequently, induced by antagonistic coevolution rather than by external events. Regularly, evolution leads to the emergence and stable coexistence of qualitatively different movement strategies within the same population. Although the strategy space of our model is continuous, we often observe the evolution of discrete movement types. We argue that rapid evolution, coexistent movement types, and phase shifts between different ecological regimes are not a peculiarity of our model but a result of more realistic assumptions on eco-evolutionary feedbacks and the number of evolutionary degrees of freedom.

BackgroundIn a diverse microbial world immune function of animals is essential. Diverse microbial environments may contribute to extensive variation in immunological phenotypes of vertebrates, among and within species and individuals. As maternal effects benefit offspring development and survival, whether females use cues about their microbial environment to prime offspring immune function is unclear. To provide microbial environmental context to maternal effects, we asked if the bacterial diversity of the living environment of female zebra finchesTaeniopygia guttatashapes maternal effects on egg immune function. We manipulated environmental bacterial diversity of birds and tested if females increased immunological investment in eggs in an environment with high bacterial diversity (untreated soil) versus low (gamma-sterilized soil). We quantified lysozyme and ovotransferrin in egg albumen and IgY in egg yolk and in female blood, and we used 16S rRNA gene sequencing to profile maternal cloacal and eggshell microbiotas.ResultsWe found a maternal effect on egg IgY concentration that reflected environmental microbial diversity: females who experienced high diversity deposited more IgY in their eggs, but only if maternal plasma IgY levels were relatively high. We found no effects on lysozyme and ovotransferrin concentrations in albumen. Moreover, we uncovered that variation in egg immune traits could be significantly attributed to differences among females: for IgY concentration in yolk repeatabilityR = 0.80; for lysozyme concentration in albumenR = 0.27. Furthermore, a partial least squares path model (PLS-PM) linking immune parameters of females and eggs, which included maternal and eggshell microbiota structures and female body condition, recapitulated the treatment-dependent yolk IgY response. The PLS-PM additionally suggested that the microbiota and physical condition of females contributed to shaping maternal effects on egg immune function, and that (non-specific) innate egg immunity was prioritized in the environment with low bacterial diversity.ConclusionsThe microbial environment of birds can shape maternal effects on egg immune function. Since immunological priming of eggs benefits offspring, we highlight that non-genetic maternal effects on yolk IgY levels based on cues from the parental microbial environment may prove important for offspring to thrive in the microbial environment that they are expected to face.

The invasion of a novel host species can create a mismatch in host choice and offspring survival (performance) when native parasitoids attempt to exploit the invasive host without being able to circumvent its resistance mechanisms. Invasive hosts can therefore act as evolutionary trap reducing parasitoids' fitness and this may eventually lead to their extinction. Yet, escape from the trap can occur when parasitoids evolve behavioral avoidance or a physiological strategy compatible with the trap host, resulting in either host-range expansion or a complete host-shift. We developed an individual based model to investigate which conditions promote parasitoids to evolve behavioral preference that matches their performance, including host-trap avoidance, and which conditions lead to adaptations to the unsuitable hosts. The model was inspired by solitary endo-parasitoids attacking larval host stages. One important aspect of these conditions was reduced host survival during incompatible interaction, where a failed parasitization attempt by a parasitoid resulted not only in death of her offspring but also in host killing. This non-reproductive host mortality had a strong influence on the likelihood of establishment of novel host-parasitoid relationship, in some cases constraining adaptation to the trap host species. Moreover, our model revealed that host-search efficiency and genetic variation in host-preference play a key role in the likelihood that parasitoids will include the suboptimal host in their host range, or will evolve behavioral avoidance resulting in specialization and host-range conservation, respectively. Hence, invasive species might change the evolutionary trajectory of native parasitoid species, which is important for predicting biocontrol ability of native parasitoids towards novel hosts.

Mutation provides novelty, and thus the raw material for selection to act on. Previous evidence has shown that increased mutation rates can indeed lead to higher evolutionary rates and faster adaptation. However, when organisms are well adapted, most mutations are likely to be maladaptive – depending on the current degree of adaptation, increased mutation rates may thus be either beneficial or harmful. Particularly interesting in this context is stress-induced mutagenesis: a condition-dependent upregulation of mutation rates under stress. As stress may be a signal for maladaptation, stress-induced mutagenesis may allow mutations to occur predominantly in times of maladaptation, i.e. when they are more likely to be adaptive. Whilst this has received much attention in empirical work, comparatively few theoretical models have explored this topic. Here, we use individual-based simulations to investigate the evolution of condition-dependent mutation rates in fluctuating environments, where environmental change repeatedly leads to maladaptation and thus to stress. We show that condition-dependent mutation rates are indeed adaptive in this scenario – however, they only evolve under specific circumstances. We explore how this relates to initial conditions, selection strength, genome structure and patterns of environmental change. Overall, we discuss the relevance of condition-dependent mutation rates for evolvability, i.e. for the capacity for adaptive evolution.

As pathogens and other microbes become progressively resistant to antibiotics, there is a growing world-wide concern that their use for treating and preventing diseases is rapidly becoming less effective and unsustainable. An important mechanism in the evolution of antibiotic resistance is horizontal gene transfer (HGT), as it is one of the most effective ways of transferring information between bacteria. Until now, HGT has experimentally mainly been studied in single bacterial populations. Yet, bacterial pathogens often do not live in isolation. It is therefore important to understand the role of HGT in the spread of antimicrobial resistance in a community context. This will be crucial for elucidating the nature of polymicrobial infections, given that ecological interactions and the microbial context can greatly impact bacterial growth and antibiotic efficacy. In this project, we investigate the community conjugation rates of pathogens isolated from polymicrobial urinary tract infections (UTIs). My research will provide fundamental knowledge on HGT in infectious communities by identifying eco-evolutionary principles that govern the rate of HGT and the spread of antimicrobial resistance in polymicrobial communities.

Mitigating trade-offs between different resource-utilization functions is key to an organism’s ecological and evolutionary success. These trade-offs often reflect metabolic constraints with a complex molecular underpinning; therefore, their consequences for evolutionary processes have remained elusive. Here, we investigate how metabolic architecture induces resource-utilization constraints and how these constraints, in turn, elicit evolutionary specialization and diversification. Guided by the metabolic network structure of the bacterium Lactococcus cremoris, we selected two carbon sources (fructose and galactose) with predicted coutilization constraints. By evolving L. cremoris on either fructose, galactose, or a mix of both sugars, we imposed selection favoring divergent metabolic specializations or coutilization of both resources, respectively. Phenotypic characterization revealed the evolution of either fructose or galactose specialists in the single-sugar treatments. In the mixed-sugar regime, we observed adaptive diversification: both specialists coexisted, and no generalist evolved. Divergence from the ancestral phenotype occurred at key pathway junctions in the central carbon metabolism. Fructose specialists evolved mutations in the fbp and pfk genes that appear to balance anabolic and catabolic carbon fluxes. Galactose specialists evolved increased expression of pgmA (the primary metabolic bottleneck of galactose metabolism) and silencing of ptnABCD (the main glucose transporter) and ldh (regulator/enzyme of downstream carbon metabolism). Overall, our study shows how metabolic network architecture and historical contingency serve to predict targets of selection and inform the functional interpretation of evolved mutations. The elucidation of the relationship between molecular constraints and phenotypic trade-offs contributes to an integrative understanding of evolutionary specialization and diversification.

By means of a simulation study, DiNuzzo & Griffen [1] investigate whether individual variation in a personality trait can explain ‘undermatching’, an often-observed deviation from the ideal free distribution (IFD). Here, we raise five points of concern about this study, regarding (i) the interpretation of the results in terms of personality variation; (ii) deficiencies in the technical implementation of the model, leading to wrong conclusions; (iii) the effects of population size on deviations from the IFD; (iv) the measure used for quantifying deviations from the IFD and (v) the analysis of the mud crab data. Finally, we provide an overview of the evolutionary ramifications of the relation between animal personality and the IFD.

Horseshoe crabs (Xiphosura) have a long evolutionary history starting in the Ordovician, but they have rarely been reported from the Netherlands. We report on the first Triassic horseshoe crab from the Netherlands identifiable to the species level, a specimen of the limulid Limulitella bronnii. We provide the first diagnosis for this species and refigure the holotype. The new specimen was found in the Middle Triassic (Anisian) Muschelkalk sediments of the Vossenveld Formation, in the Illyrian part of the stratigraphic profile of the Winterswijk quarry complex. The Winterswijk specimen represents the youngest occurrence of L. bronnii. The inferred non-marine habitat of this horseshoe crab species elsewhere in conjunction with occurrences of plant and insect remains within the same layer at Winterswijk suggest the specimen herein most probably did not live in marine conditions either. This species has previously been found in non-marine sediments in France and Germany, expanding its geographic range northward. Several faunal elements from Winterswijk including L. bronnii show resemblance to the roughly co-eval non-marine components of the Anisian Grès à Voltzia Formation in NE France, suggesting a paleobiogeographic connection between these regions in Western Europe.

Numerous cases of evolutionary trait loss and regain have been reported over the years. Here, we argue that such reverse evolution can also become apparent when trait expression is plastic in response to the environment. We tested this idea for the loss and regain of fat synthesis in parasitic wasps. We first show experimentally that the wasp Leptopilina heterotoma switches lipogenesis on in a fat-poor environment, and completely off in a fat-rich environment. Plasticity suggests that this species did not regain fat synthesis, but that it can be switched off in some environmental settings. We then compared DNA sequence variation and protein domains of several more distantly related parasitoid species thought to have lost lipogenesis, and found no evidence for non-functionality of key lipogenesis genes. This suggests that other parasitoids may also show plasticity of fat synthesis. Last, we used individual-based simulations to show that a switch for plastic expression can remain functional in the genome for thousands of generations, even if it is only used sporadically. The evolution of plasticity could thus also explain other examples of apparent reverse evolution.

Nutrient limitation is one of the most common triggers of antibiotic tolerance and persistence. Here, we present two microfluidic setups to study how spatial and temporal variation in nutrient availability lead to increased survival of bacteria to antibiotics. The first setup is designed to mimic the growth dynamics of bacteria in spatially structured populations (e.g., biofilms) and can be used to study how spatial gradients in nutrient availability, created by the collective metabolic activity of a population, increase antibiotic tolerance. The second setup captures the dynamics of feast-and-famine cycles that bacteria recurrently encounter in nature, and can be used to study how phenotypic heterogeneity in growth resumption after starvation increases survival of clonal bacterial populations. In both setups, the growth rates and metabolic activity of bacteria can be measured at the single-cell level. This is useful to build a mechanistic understanding of how spatiotemporal variation in nutrient availability triggers bacteria to enter phenotypic states that increase their tolerance to antibiotics. ISSN:1064-3745 ISSN:1940-6029

Many microorganisms face a fundamental trade-off between reproduction and survival: Rapid growth boosts population size but makes microorganisms sensitive to external stressors. Here, we show that starved bacteria encountering new resources can break this trade-off by evolving phenotypic heterogeneity in lag time. We quantify the distribution of single-cell lag times of populations of starved Escherichia coli and show that population growth after starvation is primarily determined by the cells with shortest lag due to the exponential nature of bacterial population dynamics. As a consequence, cells with long lag times have no substantial effect on population growth resumption. However, we observe that these cells provide tolerance to stressors such as antibiotics. This allows an isogenic population to break the trade-off between reproduction and survival. We support this argument with an evolutionary model which shows that bacteria evolve wide lag time distributions when both rapid growth resumption and survival under stressful conditions are under selection. Our results can explain the prevalence of antibiotic tolerance by lag and demonstrate that the benefits of phenotypic heterogeneity in fluctuating environments are particularly high when minorities with extreme phenotypes dominate population dynamics. ISSN:0027-8424 ISSN:1091-6490

Central to the origin of life is the question how a chemical system transitioned from interacting molecules to an entity with the capacity for self-replication, diversification and adaptive evolution. Here, we study a chemical system that is comprised of macrocycles that have been shown to spontaneously give rise to self-replicating entities. By combining experimental and theoretical approaches, we strive to understand the evolutionary potential of this system. In particular, we apply eco-evolutionary reasoning to investigate whether and when this system of chemical replicators can diversify. Here, we report first results of a simplified stochastic chemical reaction model that is parameterized on the basis of experimental data. The model considers the competition of two replicators that do not interact directly but need similar building blocks for their growth and reproduction. Interestingly, the replicator that emerges first is being overtaken by the later one. By means of stochastic simulations, we will explore how the competitive ability of a replicator is determined by its chemical characteristics, and under which conditions replicators can coexist. The results will subsequently inform the design of future experiments.

Models of trait evolution form an important part of macroevolutionary biology. The Brownian motion model and Ornstein–Uhlenbeck models have become classic (null) models of character evolution, in which species evolve independently. Recently, models incorporating species interactions have been developed, particularly involving competition where abiotic factors pull species toward an optimal trait value and competitive interactions drive the trait values apart. However, these models assume a fitness function rather than derive it from population dynamics and they do not consider dynamics of the trait variance. Here, we develop a general coherent trait evolution framework where the fitness function is based on a model of population dynamics, and therefore it can, in principle, accommodate any type of species interaction. We illustrate our framework with a model of abundance-dependent competitive interactions against a macroevolutionary background encoded in a phylogenetic tree. We develop an inference tool based on Approximate Bayesian Computation and test it on simulated data (of traits at the tips). We find that inference performs well when the diversity predicted by the parameters equals the number of species in the phylogeny. We then fit the model to empirical data of baleen whale body lengths, using three different summary statistics, and compare it to a model without population dynamics and a model where competition depends on the total metabolic rate of the competitors. We show that the unweighted model performs best for the least informative summary statistic, while the model with competition weighted by the total metabolic rate fits the data slightly better than the other two models for the two more informative summary statistics. Regardless of the summary statistic used, the three models substantially differ in their predictions of the abundance distribution. Therefore, data on abundance distributions will allow us to better distinguish the models from one another, and infer the nature of species interactions. Thus, our framework provides a conceptual approach to reveal species interactions underlying trait evolution and identifies the data needed to do so in practice. [Approximate Bayesian computation; competition; phylogeny; population dynamics; simulations; species interaction; trait evolution.]

The protracted speciation model presents a realistic and parsimonious explanation for the observed slowdown in lineage accumulation through time, by accounting for the fact that speciation takes time. A method to compute the likelihood for this model given a phylogeny is available and allows estimation of its parameters (rate of initiation of speciation, rate of completion of speciation and extinction rate) and statistical comparison of this model to other proposed models of diversification. However, this likelihood computation method makes an approximation of the protracted speciation model to be mathematically tractable: it sometimes counts fewer species than one would do from a biological perspective. This approximation may have large consequences for likelihood-based inferences: it may render any conclusions based on this method completely irrelevant. Here, we study to what extent this approximation affects parameter estimations. We simulated phylogenies from which we reconstructed the tree of extant species according to the original, biologically meaningful protracted speciation model and according to the approximation. We then compared the resulting parameter estimates. We found that the differences were larger for high values of extinction rates and small values of speciation-completion rates. Indeed, a long speciation-completion time and a high extinction rate promote the appearance of cases to which the approximation applies. However, surprisingly, the deviation introduced is largely negligible over the parameter space explored, suggesting that this approximate likelihood can be applied reliably in practice to estimate biologically relevant parameters under the original protracted speciation model.

International audience; Although many environments like soils are constantly subjected to invasion by alien microbes, invaders usually fail to succeed, succumbing to the robust diversity often found in nature. So far, only successful invasions have been explored, and it remains unknown to what extent an unsuccessful invasion can impact resident communities. Here we hypothesized that unsuccessful invasions can cause impacts to soil functioning by decreasing the diversity and niche breadth of resident bacterial communities, which could cause shifts to community composition and niche structure\textemdashan effect that is likely exacerbated when diversity is compromised. To examine this question, diversity gradients of soil microbial communities were subjected to invasion by the frequent, yet oft-unsuccessful soil invader, Escherichia coli, and evaluated for changes to diversity, bacterial community composition, niche breadth, and niche structure. Contrary to expectations, diversity and niche breadth increased across treatments upon invasion. Community composition and niche structure were also altered, with shifts of niche structure revealing an escape by the resident community away from the invader's resources. Importantly, the extent of the escape varied in response to the community's diversity, where less diverse communities experienced larger shifts. Thus, although transient and unsuccessful, the invader competed for resources with resident species and caused tangible impacts that modified both the diversity and functioning of resident communities, which can likely generate a legacy effect that influences future invasion attempts.

Despite its vernacular names (e.g. ‘woodlice’) Isopoda is a group with mostly aquatic species, with most species living in marine environments. The fossil record for isopods compared to other groups of Eucrustacea is relatively sparse. This applies even more for the Triassic. While in the Jurassic Isopoda is relatively well represented by fossils, only eight species have previously been described from the Triassic. In this study three new species of Isopoda are described from two field sites in Europe: Obtusotelson summesbergeri sp. nov. and Discosalaputium aschauerorum sp. nov. from Polzberg (Gaming, Lower Austria, Austria) and Gelrincola winterswijkensis sp. nov. from Winterswijk (Gelderland, Netherlands). All three new species are interpreted as representatives of Scutocoxifera (ingroup of Isopoda). The species Gelrincola winterswijkensis sp. nov. is further interpreted to be a representative of Cymothoida (ingroup of Scutocoxifera). Most of the oldest fossils of Isopoda belong to Phreatoicidea, which is supposed to be the sistergroup to all remaining Isopoda. Nowadays, Phreatoicidea is a small relic group, its representatives living in freshwater environments. The new species herein presented contribute to our understanding of the diversity of Isopoda in the Triassic and support the assumption that the transition from a dominance of Phreatoicidea towards the dominance of the remaining lineages of Isopoda happened quite early (likely prior to the Triassic).

One of the most amazing phenomena in the world is the coexistence of an incredible diversity of species. How and why species have evolved so distinct morphological traits from a common ancestor constantly puzzles biologists. Although substantial details in underlying mechanisms of ecology and evolution remain to be revealed, biotic and abiotic interactions are widely accepted as key drivers. I investigate the influence of species interactions on macroecological and macroevolutionary patterns. I confirmed that species interactions can slow down diversity accumulation if the environment has a limited capacity to host species of the same trophic level. However, spatial geographic structure may reduce the power of current methods to detect local limits to diversification. This result indicates that biologists need to be cautious when using diversity-dependent diversification to explain species assembly. Besides species diversity, species interactions can also influence trait diversity. I use a novel model to explain how trait evolution unfolds under environmental stabilizing selection and species interactions together with population dynamics. This model can potentially lead to novel approaches in phylogenetic comparative methods. Furthermore, I use a simulation model to explore how an ecological hypothesis of species interactions - the phylogenetic Janzen-Connell effect - results in a wide range of realistic macroecological and macroevolutionary community patterns. To summarize, species interactions are the fundamental elements beneath any biological mechanism and require further research to better understand the world we are living in.

International audience

1. Microbial evolution experiments provide a powerful tool to unravel the molecular basis of adaptive evolution but their outcomes can be difficult to interpret, unless the selective forces that are applied during the experiment are carefully controlled. In this respect, experimental evolution in continuous cultures provides advantages over commonly used sequential batch-culture protocols because continuous cultures allow for more accurate control over the induced selective environment. However, commercial continuous-culture systems are large and expensive, while available DIY continuous-culture systems are not versatile enough to allow for multiple sensors and rigorous stirring.2. We present a modular continuous-culture system that adopts the commonly used GL45 glass laboratory bottle as a bioreactor vessel. Our design offers three advantages: first, it is equipped with a large head plate, fitting two sensors and seven input/output ports, enabling the customization of the system for many running modes (chemostat, auxostat, etc.). Second, the bioreactor is small (25-250 ml), which makes it feasible to run many replicates in parallel. Third, bioreactor modules can be coupled by uni- or bi-directional flows to induce spatiotemporal variation in selection. These features result in a particularly flexible culturing platform that facilitates the investigation of a broad range of evolutionary and ecological questions.3. To illustrate the versatility of our culturing system, we outline two evolution experiments that impose a temporally or spatially variable regime of selection. The first experiment illustrates how controlled temporal variation in resource availability can be utilized to select for anticipatory switching. The second experiment illustrates a spatially structured morbidostat setup that is designed to probe epistatic interactions between adaptive mutations. Furthermore, we demonstrate how sensor data can be used to stabilize selection pressures or track evolutionary adaptation.4. Evolution experiments in which populations are exposed to controlled spatiotemporal variation, are essential to gain insight into the process of adaptation and the mechanisms that constrain evolution. Continuous-culture systems, like the one presented here, offer control over key environmental parameters and establish a well-defined regime of selection. As such, they create the opportunity to expose evolutionary constraints in the form of phenotypic trade-offs, contributing to a mechanistic understanding of adaptive evolution.

The interplay between environmental selection and available variation within a population are central in the adaptation of populations to changing environments, for seemingly all levels of complexity in life. In order to investigate properties and mode of actions of the two counterplayers, more and more studies have started to conduct experiments, that expose populations to different, non-optimal conditions and describe changes in phenotypic traits and genotypes observed. Whereas the extrinsic selection regimes surrounding the populations can easily be changed at will by the investigators and hereby serves the elucidation of the properties of selection, modifying the intrinsic genetic variation of the individuals remains challenging and less of an experimental subject so far. In order to investigate mechanisms that cause genetic mutations, we constructed bacterial strains, that harbour mutator genes on plasmids with an inducible expression system. We present results of the characterization of the mutator strains, as a first step towards understanding mutation mechanisms and their influence on standing genetic variation and subsequent adaptation, in order to complement the investigations on selection for a full picture of the driving forces in evolution.

When a population faces a novel (stressful) environment this may cause the population to decline. In such situations evolutionary rescue theoryaims to predict the probability that a population adapts to the new environment (rescue), instead of facing the otherwise inevitable extinction. Thus, evolutionary rescue theory has the potential to help us understand when to expect the evolution of antibiotic resistance in bacterial populations. Yet, current models of evolutionary rescue fail to account for the mechanisms deployed by bacteria to cope with stressful conditions (like the presence of antibiotics). Here we examine two such mechanisms using stochastic modelling. First we examine the effect of biofilm formation, which occurs in the majority of bacterial infections. Biofilms have an explicit spatial structure, whilst standard evolutionary rescue theory assumes well-mixed populations. Secondly we examine the influence of persistercells, these are dormant cells that tolerate antibiotics exposure, which are also not modeled in standard evolutionary rescue theory.

Glycolysis is a conserved central pathway in energy metabolism that converts glucose to pyruvate with net production of two ATP molecules. Because ATP is produced only in the lower part of glycolysis (LG), preceded by an initial investment of ATP in the upper glycolysis (UG), achieving robust start-up of the pathway upon activation presents a challenge: a sudden increase in glucose concentration can throw a cell into a self-sustaining imbalanced state in which UG outpaces LG, glycolytic intermediates accumulate and the cell is unable to maintain high ATP concentration needed to support cellular functions. Such metabolic imbalance can result in “substrate-accelerated death”, a phenomenon observed in prokaryotes and eukaryotes when cells are exposed to an excess of substrate that previously limited growth. Here, we address why evolution has apparently not eliminated such a costly vulnerability and propose that it is a manifestation of an evolutionary trade-off, whereby the glycolysis pathway is adapted to quickly secure scarce or fluctuating resource at the expense of vulnerability in an environment with ample resource. To corroborate this idea, we perform individual-based eco-evolutionary simulations of a simplified yeast glycolysis pathway consisting of UG, LG, phosphate transport between a vacuole and a cytosol, and a general ATP demand reaction. The pathway is evolved in constant or fluctuating resource environments by allowing mutations that affect the (maximum) reaction rate constants, reflecting changing expression levels of different glycolytic enzymes. We demonstrate that under limited constant resource, populations evolve to a genotype that exhibits balanced dynamics in the environment it evolved in, but strongly imbalanced dynamics under ample resource conditions. Furthermore, when resource availability is fluctuating, imbalanced dynamics confers a fitness advantage over balanced dynamics: when glucose is abundant, imbalanced pathways can quickly accumulate the glycolytic intermediate FBP as intracellular storage that is used during periods of starvation to maintain high ATP concentration needed for growth. Our model further predicts that in fluctuating environments, competition for glucose can result in stable coexistence of balanced and imbalanced cells, as well as repeated cycles of population crashes and recoveries that depend on such polymorphism. Overall, we demonstrate the importance of ecological and evolutionary arguments for understanding seemingly maladaptive aspects of cellular metabolism., Author summary Glycolysis is a central pathway in cellular energy metabolism that breaks down glucose to produce ATP, yet it can sometimes fail to start up properly after cells have experienced a period of starvation. This puzzling failure occurs when a sudden increase in glucose concentration throws a cell into a self-sustaining imbalanced state in which upper and lower glycolysis work at different rates. As a result, glycolytic intermediates accumulate in the cell, and it is unable to maintain high ATP concentration needed to support cellular functions. Here, we perform individual-based eco-evolutionary simulations of a simplified yeast glycolysis pathway and show that this apparently costly vulnerability allows for faster growth in environments with scarce or fluctuating resource availability. Accordingly, we propose that vulnerability to metabolic imbalance can be interpreted as a manifestation of an evolutionary trade-off between performance in rich, stable environments and poor, fluctuating ones. Furthermore, we show that when resource availability fluctuates, imbalanced dynamics itself can be advantageous: when glucose is abundant, imbalanced pathways can quickly accumulate glycolytic intermediates as intracellular storage that is used to sustain growth during periods of starvation. Finally, we find that in variable environments, competition for glucose can support stable coexistence of balanced and imbalanced cells in the population, as well as repeated cycles of population crashes and recoveries. Overall, our results show that ecological and evolutionary mechanisms provide a fruitful context for interpreting seemingly flawed aspects of cellular metabolism.

Advances in biomolecular technology allow us to sequence entire genomes, but how genes and molecular networks influence the emergence and evolution of phenotypic traits is still unclear. Different fields in biology and medicine are working hard to unravel the relationship between the genome and phenotypes. In this thesis, a new (mechanistic) approach combining systems biology and evolutionary biology is explored to tackle the genotype-phenotype problem. The chemotaxis network of Escherichia coli is used as a model system for its relatively simple network configuration associated with a complex trait such as chemotactic performance. A mathematical model was developed and in silico evolutionary experiments were performed with different environmental conditions. The results show that due to the complexity of the genomic architecture, most individual gene loci have an inconsistent relationship with fitness. In other words, direct relationships between genes and phenotypes are far more complex than just a linear correlation. The reconstruction of the fitness landscape shows that its structure is highly heterogeneous and there are cases in which mutations have unpredictable and inconsistent effects. Another result shows that contrary to static environments, fluctuating environments facilitate the exploration of the fitness landscape. The results in this thesis show the potential of the evolutionary-systems-biology approach, which could help to understand how complex diseases (e.g. cancer or diabetes) develop or how bacteria evolve to become drug resistant.

This article covers all macroinvertebrates not ascribed to the Arthropoda found in the Muschelkalk (Middle Triassic, Anisian) of Winterswijk. The Muschelkalk contains 18 bivalve species, two gastropod species, two brachiopod species, one ammonite species, and a putative jellyfi sh taxon. Five bivalve species not previously photographed from Winterswijk are fi gured herein. Briefl y, we present the invertebrates known from the Upper Triassic shales and Lower Jurassic clays of Winterswijk. The invertebrates from the Muschelkalk suggest deposition in a hypersaline and stressed environment

Whether there are ecological limits to species diversification is a hotly debated topic. Molecular phylogenies show slowdowns in lineage accumulation, suggesting that speciation rates decline with increasing diversity. A maximum-likelihood (ML) method to detect diversity-dependent (DD) diversification from phylogenetic branching times exists, but it assumes that diversity-dependence is a global phenomenon and therefore ignores that the underlying species interactions are mostly local, and not all species in the phylogeny co-occur locally. Here, we explore whether this ML method based on the nonspatial diversity-dependence model can detect local diversity-dependence, by applying it to phylogenies, simulated with a spatial stochastic model of local DD speciation, extinction, and dispersal between two local communities. We find that type I errors (falsely detecting diversity-dependence) are low, and the power to detect diversity-dependence is high when dispersal rates are not too low. Interestingly, when dispersal is high the power to detect diversity-dependence is even higher than in the nonspatial model. Moreover, estimates of intrinsic speciation rate, extinction rate, and ecological limit strongly depend on dispersal rate. We conclude that the nonspatial DD approach can be used to detect diversity-dependence in clades of species that live in not too disconnected areas, but parameter estimates must be interpreted cautiously.

Bourgeois and parasitic males produce sperm maximizing either performance or endurance, according to divergent spawning roles., Males pursuing alternative reproductive tactics have been predicted to face a trade-off between maximizing either swimming performance or endurance of their sperm. However, empirical evidence for this trade-off is equivocal, which may be due to simplistic assumptions. In the shell-brooding cichlid fish Lamprologus callipterus, two Mendelian male morphs compete for fertilization by divergent means: Bourgeois nest males ejaculate sperm, on average, about six times farther from the unfertilized ova than do parasitic dwarf males. This asymmetry is opposite to the usual situation, in which bourgeois males typically benefit from superior fertilization opportunities, suggesting that nest males’ sperm should persist longer than dwarf male sperm. The assumed trade-off between sperm swimming performance and longevity predicts that, in turn, sperm of dwarf males should outperform that of nest males in swimming efficiency. Measurement of sperm performance and endurance reveals that dwarf male spermatozoa swim straighter initially than those of nest males, but their motility declines earlier and their velocity slows down more abruptly. Nest male sperm survives longer, which relates to a larger sperm head plus midpiece, implying more mitochondria. Thus, the trade-off between sperm performance and endurance is optimized in opposite directions by alternative male morphs. We argue that the relative success of alternative sperm performance strategies can be influenced strongly by environmental factors such as the time window between gamete release and fertilization, and the position of gamete release. This is an important yet little understood aspect of gametic adaptations to sperm competition.

International audience; The large body of theory on speciation with gene flow has brought to light fundamental differences in the effects of two types of mating rules on speciation: preference/trait rules, in which divergence in both (female) preferences and (male) mating traits is necessary for assortment, and matching rules, in which individuals mate with like individuals on the basis of the presence of traits or alleles that they have in common. These rules can emerge from a variety of behavioral or other mechanisms in ways that are not always obvious. We discuss the theoretical properties of both types of rules and explain why speciation is generally thought to be more likely under matching rather than preference/trait rules. We furthermore discuss whether specific assortative mating mechanisms fall under a preference/trait or matching rule, present empirical evidence for these mechanisms, and propose empirical tests that could distinguish between them. The synthesis of the theoretical literature on these assortative mating rules with empirical studies of the mechanisms by which they act can provide important insights into the occurrence of speciation with gene flow. Finally, by providing a clear framework we hope to inspire greater alignment in the ways that both theoreticians and empiricists study mating rules and how these rules affect speciation through maintaining or eroding barriers to gene flow among closely related species or populations.

Streptococcus pneumoniae becomes competent for genetic transformation when exposed to an autoinducer peptide known as competence-stimulating peptide (CSP). This peptide was originally described as a quorum-sensing signal, enabling individual cells to regulate competence in response to population density. However, recent studies suggest that CSP may instead serve as a probe for sensing environmental cues, such as antibiotic stress or environmental diffusion. Here, we show that competence induction can be simultaneously influenced by cell density, external pH, antibiotic-induced stress, and cell history. Our experimental data is explained by a mathematical model where the environment and cell history modify the rate at which cells produce or sense CSP. Taken together, model and experiments indicate that autoinducer concentration can function as an indicator of cell density across environmental conditions, while also incorporating information on environmental factors or cell history, allowing cells to integrate cues such as antibiotic stress into their quorum-sensing response. This unifying perspective may apply to other debated quorum-sensing systems., Peptide CSP regulates natural competence in pneumococci and has been proposed as a quorum-sensing signal or a probe for sensing environmental cues. Here, the authors show that CSP levels can indeed act as an indicator of cell density and also incorporate information on environmental factors or cell history.

The signal-transduction network responsible for chemotaxis in Escherichia coli has been characterised in extraordinary detail. Yet, relatively little is known about eco-evolutionary aspects of chemotaxis, such as how the network has been shaped by selection and to what extent natural populations may fine-tune their chemotactic behaviour to the ecological conditions. To address these questions, we here develop an evolutionary-systems biology model of the chemotaxis network of E. coli, which we apply to estimate the resource accumulation rate (here used as a proxy for fitness) of wildtype and a large number of potential mutant genotypes. Mutant genotypes differ from the wildtype in the concentrations of one or more constituent proteins of the chemotaxis signalling network or in one or more of its kinetic parameters. To guarantee model consistency across the genotype space, we explicitly incorporated biochemical constraints that underly observed phenotypic trade-offs. The model was validated by reconstructing the phenotypic properties of several known mutant genotypes. We also characterised differences in the fitness distribution between genotypes, and reconstructed adaptive walks in genotype space for populations exposed to different environmental conditions. We found that the local fitness landscape is rugged, due to non-additive interactions between mutations. When selection has a consistent direction, just a few adaptive mutations are required to reach a local peak, and different local peaks can be reached by adaptive walks starting from the same initial genotype. However, when the direction of selection is fluctuating, evolutionary paths are much longer and genotype space is explored further. Longer adaptive walks were also observed when evolution was started from a low-fitness genotype such as a CheZ knockout mutant. In line with empirical observations, the initial Delta cheZ mutant did not respond to a step-down stimulus, but a dynamic response similar to the wildtype was recovered following the fixation of compensatory mutations.

Cooperating animals frequently show closely coordinated behaviours organized by a continuous flow of information between interacting partners. Such real-time coaction is not captured by the iterated prisoner's dilemma and other discrete-time reciprocal cooperation games, which inherently feature a delay in information exchange. Here, we study the evolution of cooperation when individuals can dynamically respond to each other's actions. We develop continuous-time analogues of iterated-game models and describe their dynamics in terms of two variables, the propensity of individuals to initiate cooperation (altruism) and their tendency to mirror their partner's actions (coordination). These components of cooperation stabilize at an evolutionary equilibrium or show oscillations, depending on the chosen payoff parameters. Unlike reciprocal altruism, cooperation by coaction does not require that those willing to initiate cooperation pay in advance for uncertain future benefits. Correspondingly, we show that introducing a delay to information transfer between players is equivalent to increasing the cost of cooperation. Cooperative coaction can therefore evolve much more easily than reciprocal cooperation. When delays entirely prevent coordination, we recover results from the discrete-time alternating prisoner's dilemma, indicating that coaction and reciprocity are connected by a continuum of opportunities for real-time information exchange. (C) 2014 Elsevier Ltd. All rights reserved.

The chaplin proteins are instrumental in the formation of reproductive aerial structures by the filamentous bacterium Streptomyces coelicolor. They lower the water surface tension thereby enabling aerial growth. In addition, chaplins provide surface hydrophobicity to the aerial hyphae by assembling on the cell surface into an amphipathic layer of amyloid fibrils. We here show that mixtures of cell wall-extracted chaplins can be used to modify a variety of hydrophilic and hydrophobic surfaces in vitro thereby changing their nature. Assembly on glass leads to a protein coating that makes the surface hydrophobic. Conversely, the assembly of chaplins on hydrophobic surfaces renders them hydrophilic. Furthermore, we show that chaplins can stabilize emulsions of oil into water and have an unprecedented surface activity at high pH. Interestingly, this high surface activity coincides with the interfacial assembly of chaplins into a semi-liquid membrane, as opposed to the rigid membrane formed at neutral pH. This semi-liquid membrane possibly represents a trapped intermediate in the assembly process towards the more rigid amyloidal conformation. Taken together, our data shows that chaplins are suitable candidate proteins for a wide range of biotechnological applications.

When organisms encounter environments that are heterogeneous in time, phenotypic plasticity is often favored by selection. The degree of such plasticity can vary during an organism’s lifetime, but the factors promoting differential plastic responses at different ages or life stages remain poorly understood. Here we develop and analyze an evolutionary model to investigate how environmental information is optimally collected and translated into phenotypic adjustments at different ages. We demonstrate that plasticity must often be expected to vary with age in a nonmonotonic fashion. Early in life, it is generally optimal to delay phenotypic adjustments until sufficient information has been collected about the state of the environment to warrant a costly phenotypic adjustment. Toward the end of life, phenotypic adjustments are disfavored as well because their beneficial effects can no longer be fully reaped before death. Our analysis clarifies how patterns of age-dependent plasticity are shaped by the interplay of environmental uncertainty, the accuracy of perceived information, and the costs of phenotypic adjustments with life-history determinants such as the relative strengths of fecundity and viability selection experienced by the organism over its lifetime. We conclude by comparing our results with expectations for alternative mechanisms, including developmental constraints, that promote age-dependent plasticity. © 2014 University of Chicago Press

The structure and composition of bacterial communities can compromise antibiotic efficacy. For example, the secretion of β-lactamase by individual bacteria provides passive resistance for all residents within a polymicrobial environment. Here, we uncover that collective resistance can also develop via intracellular antibiotic deactivation. Real-time luminescence measurements and single-cell analysis demonstrate that the opportunistic human pathogen Streptococcus pneumoniae grows in medium supplemented with chloramphenicol (Cm) when resistant bacteria expressing Cm acetyltransferase (CAT) are present. We show that CAT processes Cm intracellularly but not extracellularly. In a mouse pneumonia model, more susceptible pneumococci survive Cm treatment when coinfected with a CAT-expressing strain. Mathematical modeling predicts that stable coexistence is only possible when antibiotic resistance comes at a fitness cost. Strikingly, CAT-expressing pneumococci in mouse lungs were outcompeted by susceptible cells even during Cm treatment. Our results highlight the importance of the microbial context during infectious disease as a potential complicating factor to antibiotic therapy., Author Summary Antibiotic-resistant bacterial infections are on the rise and pose a serious threat to society. The influence of genetic resistance mechanisms on antibiotic therapy is well described. However, other factors, such as epigenetic resistance or the impact of the environment on antibiotic therapy, are less well understood. Here, we describe and characterize a mechanism of noninherited antibiotic resistance that enables the survival and outgrowth of genetically susceptible bacteria during antibiotic therapy. We show that bacteria expressing the resistance factor chloramphenicol (Cm) acetyltransferase (CAT) can potently deactivate Cm in their immediate environment. The reduced Cm concentration then allows for the outgrowth of genetically susceptible bacteria in the same environment. Mathematical modeling demonstrates the presence of a parameter space in which stable coexistence between Cm-susceptible and -resistant bacteria is possible during antibiotic therapy, which we validated using single-cell analyses. Strikingly, mixed culture experiments in which mice were infected with both Cm-susceptible and -resistant pneumococci revealed that Cm-sensitive “freeloader” bacteria even outcompeted resistant bacteria during antibiotic therapy. Together, we show that the microbial context during infection is a potential complicating factor to antibiotic treatment outcomes.

The extraordinarily long lifespans of queens (and kings) in eusocial insects and the strikingly large differences in life expectancy between workers and queens challenge our understanding of the evolution of aging and provide unique opportunities for studying the causes underlying adaptive variation in lifespan within species. Here we review the major evolutionary theories of aging, focusing on their scope and limitations when applied to social insects. We show that reproductive division of labor, interactions between kin, caste specific gene regulation networks, and the integration of colony-level trade-offs with individual-level trade-offs provide challenges to the classical theories We briefly indicate how these challenges could be met in future models of adaptive phenotypic plasticity in lifespan between and within different castes.

Non-human primates use various communicative means in interactions with others. While primate gestures are commonly considered to be intentionally and flexibly used signals, facial expressions are often referred to as inflexible, automatic expressions of affective internal states. To explore whether and how non-human primates use facial expressions in specific communicative interactions, we studied five species of small apes (gibbons) by employing a newly established Facial Action Coding System for hylobatid species (Gibbon- FACS). We found that, despite individuals often being in close proximity to each other, in social (as opposed to non-social contexts) the duration of facial expressions was significantly longer when gibbons were facing another individual compared to non-facing situations. Social contexts included grooming, agonistic interactions and play, whereas nonsocial contexts included resting and self-grooming. Additionally, gibbons used facial expressions while facing another individual more often in social contexts than non-social contexts where facial expressions were produced regardless of the attentional state of the partner. Also, facial expressions were more likely ‘responded to’ by the partner’s facial expressions when facing another individual than non- facing. Taken together, our results indicate that gibbons use their facial expressions differentially depending on the social context and are able to use them in a directed way in communicative interactions with other conspecifics.

Two alternative frameworks explain the evolution of cooperation in the face of conflicting interests. Conflicts can be alleviated by kinship, the alignment of interests by virtue of shared genes, or by negotiation strategies, allowing mutually beneficial trading of services or commodities. Although negotiation often occurs in kin-structured populations, the interplay of kin- and negotiation-based mechanisms in the evolution of cooperation remains an unresolved issue. Inspired by the biology of a cooperatively breeding fish, we developed an individual-based simulation model to study the evolution of negotiation-based cooperation in relation to different levels of genetic relatedness. We show that the evolution of negotiation strategies leads to an equilibrium where subordinates appease dominants by conditional cooperation, resulting in high levels of help and low levels of aggression. This negotiation-based equilibrium can be reached both in the absence of relatedness and in a kin-structured population. However, when relatedness is high, evolution often ends up in an alternative equilibrium where subordinates help their kin unconditionally. The level of help at this kin-selected equilibrium is considerably lower than at the negotiation-based equilibrium, and it corresponds to a level reached when responsiveness is prevented from evolving in the simulations. A mathematical invasion analysis reveals that, quite generally, the alignment of payoffs due to the relatedness of interaction partners tends to impede selection for harsh but effective punishment of defectors. Hence kin structure will often hamper rather than facilitate the evolution of productive cooperation.

Evolutionary conflict between the sexes can induce arms races in which males evolve traits that are detrimental to the fitness of their female partners, and vice versa. This interlocus sexual conflict (IRSC) has been proposed as a cause of perpetual intersexual antagonistic coevolution with wide-ranging evolutionary consequences. However, theory suggests that the scope for perpetual coevolution is limited, if traits involved in IRSC are subject to pleiotropic constraints. Here, we consider a biologically plausible form of pleiotropy that has hitherto been ignored in treatments of IRSC and arrive at drastically different conclusions. Our analysis is based on a quantitative genetic model of sexual conflict, in which genes controlling IRSC traits have side effects in the other sex, due to incompletely sex-limited gene expression. As a result, the genes are exposed to intralocus sexual conflict (IASC), a tug-of-war between opposing male- and female-specific selection pressures. We find that the interaction between the two forms of sexual conflict has contrasting effects on antagonistic coevolution: Pleiotropic constraints stabilize the dynamics of arms races if the mating traits are close to evolutionary equilibrium but can prevent populations from ever reaching such a state. Instead, the sexes are drawn into a continuous cycle of arms races, causing the buildup of IASC, alternated by phases of IASC resolution that trigger the next arms race. These results encourage an integrative perspective on the biology of sexual conflict and generally caution against relying exclusively on equilibrium stability analysis.

Infections with rapidly evolving pathogens are often treated using combinations of drugs with different mechanisms of action. One of the major goal of combination therapy is to reduce the risk of drug resistance emerging during a patient's treatment. Although this strategy generally has significant benefits over monotherapy, it may also select for multidrug-resistant strains, particularly during long-term treatment for chronic infections. Infections with these strains present an important clinical and public health problem. Complicating this issue, for many antimicrobial treatment regimes, individual drugs have imperfect penetration throughout the body, so there may be regions where only one drug reaches an effective concentration. Here we propose that mismatched drug coverage can greatly speed up the evolution of multidrug resistance by allowing mutations to accumulate in a stepwise fashion. We develop a mathematical model of within-host pathogen evolution under spatially heterogeneous drug coverage and demonstrate that even very small single-drug compartments lead to dramatically higher resistance risk. We find that it is often better to use drug combinations with matched penetration profiles, although there may be a trade-off between preventing eventual treatment failure due to resistance in this way and temporarily reducing pathogen levels systemically. Our results show that drugs with the most extensive distribution are likely to be the most vulnerable to resistance. We conclude that optimal combination treatments should be designed to prevent this spatial effective monotherapy. These results are widely applicable to diverse microbial infections including viruses, bacteria, and parasites.

The diversity and patchy phylogenetic distribution of genetic sex-determining mechanisms observed in some taxa is thought to have arisen by the addition, modification, or replacement of regulators at the upstream end of the sex-determining pathway. Here, I review the various evolutionary forces acting on upstream regulators of sexual development that can cause transitions between sex-determining systems. These include sex-ratio selection and pleiotropic benefits, as well as indirect selection mechanisms involving sex-linked sexually antagonistic loci or recessive deleterious mutations. Most of the current theory concentrates on the population-genetic aspects of sex-determination transitions, using models that do not reflect the developmental mechanisms involved in sex determination. However, the increasing availability of molecular data creates opportunities for the development of mechanistic models that can clarify how selection and developmental architecture interact to direct the evolution of sex-determination genes.

Little is known about facial communication of lesser apes (family Hylobatidae) and how their facial expressions (and use of) relate to social organization. We investigated facial expressions (defined as combinations of facial movements) in social interactions of mated pairs in five different hylobatid species belonging to three different genera using a recently developed objective coding system, the Facial Action Coding System for hylobatid species (GibbonFACS). We described three important properties of their facial expressions and compared them between genera. First, we compared the rate of facial expressions, which was defined as the number of facial expressions per units of time. Second, we compared their repertoire size, defined as the number of different types of facial expressions used, independent of their frequency. Third, we compared the diversity of expression, defined as the repertoire weighted by the rate of use for each type of facial expression. We observed a higher rate and diversity of facial expression, but no larger repertoire, in Symphalangus (siamangs) compared to Hylobates and Nomascus species. In line with previous research, these results suggest siamangs differ from other hylobatids in certain aspects of their social behavior. To investigate whether differences in facial expressions are linked to hylobatid socio-ecology, we used a Phylogenetic General Least Square (PGLS) regression analysis to correlate those properties with two social factors: group-size and level of monogamy. No relationship between the properties of facial expressions and these socio-ecological factors was found. One explanation could be that facial expressions in hylobatid species are subject to phylogenetic inertia and do not differ sufficiently between species to reveal correlations with factors such as group size and monogamy level. Am. J. Primatol. 76:618-628, 2014.

Recent research focuses on animal personalities, that is individual differences in behaviour that are consistent across contexts and over time. From an adaptive perspective, such limited behavioural plasticity is surprising, since a more flexible structure of behaviour should provide a selective advantage. Here, we argue that consistency can be advantageous because it makes individuals predictable. Predictability, however, can only be advantageous if at least some individuals in the population respond to individual differences. Consequently, the evolution of consistency and responsiveness are mutually dependent. We present a general analysis of this coevolutionary feedback for scenarios that can be represented as matrix games with two pure strategies (e.g. hawk-dove game, snowdrift game). We first show that responsive strategies are favoured whenever some individual differences are present in the population (e.g. due to mutation and drift). We then show that the presence of responsive individuals can trigger a coevolutionary process between responsiveness and consistency that gives rise to populations in which responsive individuals coexist with unresponsive individuals who show high levels of adaptive consistency in their behaviour. Next to providing an adaptive explanation for consistency, our results also link two key features associated with personalities, individual differences in responsiveness and behavioural consistency.

Intralocus sexual conflict arises when there are sex-specific optima for a trait that is expressed in both sexes and when the constraint of a shared gene pool prevents males and females from reaching their optima independently. This situation may result in a negative intersexual correlation for fitness. Here I first discuss key differences between intra- and interlocus conflict, the type of sexual conflict that arises in mating interactions between males and females. I then review the experimental evidence for the existence of genomewide sexually antagonistic variation and discuss how intralocus conflict can be resolved. Substantial genomewide sexually antagonistic variation exists in Drosophila melanogaster lab populations. Yet, in the same species, sex-specific gene regulation appears to evolve rapidly, suggesting that the obstacles to the resolution of intralocus conflict are minor. The fact that negative intersexual correlations for fitness are observed even if sexual dimorphism can evolve rapidly suggests that intralocus conflict is highly dynamic. The final part of this review examines the evolutionary consequences of intralocus sexual conflict for the evolution of the sex chromosomes, sexual selection, and sex determination. Intralocus conflict helps to explain many of the peculiar features of the sex chromosomes and has shaped the functional bias and expression biases of sex-linked genes. The genomic distribution of sexually selected genes, in particular, affects sexual selection in various ways. The presence of sexually antagonistic variation can strongly interfere with the good genes' process of sexual selection and erode the genetic benefits of mate choice. Regarding sex determination, this review concentrates on evolutionary transitions between different sex determination mechanisms. Such transitions have occurred frequently in several taxa. Theory and empirical data suggest an important role for intralocus conflict in triggering switches between sex determination systems.

In many animal species, individuals differ consistently in suites of correlated behaviors, comparable with human personalities. Increasing evidence suggests that one of the fundamental factors structuring personality differences is the responsiveness of individuals to environmental stimuli. Whereas some individuals tend to be highly responsive to such stimuli, others are unresponsive and show routine-like behaviors. Much research has focused on the proximate causes of these differences but little is known about their evolutionary origin. Here, we provide an evolutionary explanation. We develop a simple but general evolutionary model that is based on two key ingredients. First, the benefits of responsiveness are frequency-dependent; that is, being responsive is advantageous when rare but disadvantageous when common. This explains why responsive and unresponsive individuals can coexist within a population. Second, positive-feedback mechanisms reduce the costs of responsiveness; that is, responsiveness is less costly for individuals that have been responsive before. This explains why individuals differ consistently in their responsiveness, across contexts and over time. As a result, natural selection gives rise to stable individual differences in responsiveness. Whereas some individuals respond to environmental stimuli in all kinds of contexts, others consistently neglect such stimuli. Interestingly, such differences induce correlations among all kinds of other traits (e.g., boldness and aggressiveness), thus providing an explanation for environment-specific behavioral syndromes.

In recent years evidence has been accumulating that personalities are not only found in humans(1) but also in a wide range of other animal species(2-8). Individuals differ consistently in their behavioural tendencies and the behaviour in one context is correlated with the behaviour in multiple other contexts. From an adaptive perspective, the evolution of animal personalities is still a mystery, because a more flexible structure of behaviour should provide a selective advantage(9-11). Accordingly, many researchers view personalities as resulting from constraints imposed by the architecture of behaviour(7) (but see ref. 12). In contrast, we show here that animal personalities can be given an adaptive explanation. Our argument is based on the insight that the trade-off between current and future reproduction(13) often results in polymorphic populations(14) in which some individuals put more emphasis on future fitness returns than others. Life-history theory predicts that such differences in fitness expectations should result in systematic differences in risk-taking behaviour(15). Individuals with high future expectations (who have much to lose) should be more risk-averse than individuals with low expectations. This applies to all kinds of risky situations, so individuals should consistently differ in their behaviour. By means of an evolutionary model we demonstrate that this basic principle results in the evolution of animal personalities. It simultaneously explains the coexistence of behavioural types, the consistency of behaviour through time and the structure of behavioural correlations across contexts. Moreover, it explains the common finding that explorative behaviour and risk-related traits like boldness and aggressiveness are common characteristics of animal personalities(2-8).