Environment-dependent inbreeding depression: its ecological and evolutionary significance

Inbreeding depression is a major evolutionary and ecological force that influences population dynamics and the evolution of inbreeding-avoidance traits such as mating systems and dispersal. There is now compelling evidence that inbreeding depression is environment-dependent. Here, we discuss ecological and evolutionary consequences of environment-dependent inbreeding depression. The environmental dependence of inbreeding depression may be caused by environment-dependent phenotypic expression, environment-dependent dominance, and environment-dependent natural selection. The existence of environment-dependent inbreeding depression challenges classical models of inbreeding as caused by unconditionally deleterious alleles, and suggests that balancing selection may shape inbreeding depression in natural populations; loci associated with inbreeding depression in some environments may even contribute to adaptation to others. Environment-dependent inbreeding depression also has important, often neglected, ecological and evolutionary consequences: it can influence the demography of marginal or colonizing populations and alter adaptive optima of mating systems, dispersal, and their associated traits. Incorporating the environmental dependence of inbreeding depression into theoretical models and empirical studies is necessary for understanding the genetic and ecological basis of inbreeding depression and its consequences in natural populations.     

EVOLUTION OF DISPERSAL RATES IN METAPOPULATION MODELS: BRANCHING AND CYCLIC DYNAMICS IN PHENOTYPE SPACE

We study the evolution of dispersal rates in a two patch metapopulation model. The local dynamics in each patch are given by difference equations, which, together with the rate of dispersal between the patches, determine the ecological dynamics of the metapopulation. We assume that phenotypes are given by their dispersal rate. The evolutionary dynamics in phenotype space are determined by invasion exponents, which describe whether a mutant can invade a given resident population. If the resident metapopulation is at a stable equilibrium, then selection on dispersal rates is neutral if the population sizes in the two patches are the same, while selection drives dispersal rates to zero if the local abundances are different. With non-equilibrium metapopulation dynamics, non-zero dispersal rates can be maintained by selection. In this case, and if the patches are ecologically identical, dispersal rates always evolve to values which induce synchronized metapopulation dynamics. If the patches are ecologically different, evolutionary branching into two coexisting dispersal phenotypes can be observed. Such branching can happen repeatedly, leading to polymorphisms with more than two phenotypes. If there is a cost to dispersal, evolutionary cycling in phenotype space can occur due to the dependence of selection pressures on the ecological attractor of the resident population, or because phenotypic branching alternates with the extinction of one of the branches. Our results extend those of Holt and McPeek (1996), and suggest that phenotypic branching is an important evolutionary process. This process may be relevant for sympatric speciation.     

How is dispersal integrated in life histories: a quantitative analysis using butterflies

As dispersal plays a key role in gene flow among populations, its evolutionary dynamics under environmental changes is particularly important. The inter-dependency of dispersal with other life history traits may constrain dispersal evolution, and lead to the indirect selection of other traits as a by-product of this inter-dependency. Identifying the dispersal's relationships to other life-history traits will help to better understand the evolutionary dynamics of dispersal, and the consequences for species persistence and ecosystem functioning under global changes. Dispersal may be linked to other life-history traits as their respective evolutionary dynamics may be inter-dependent, or, because they are mechanistically related to each other. We identify traits that are predicted to co-vary with dispersal, and investigated the correlations that may constrain dispersal using published information on butterflies. Our quantitative analysis revealed that (1) dispersal directly correlated with demographic traits, mostly fecundity, whereas phylogenetic relationships among species had a negligible influence on this pattern, (2) gene flow and individual movements are correlated with ecological specialisation and body size, respectively and (3) routine movements only affected short-distance dispersal. Together, these results provide important insights into evolutionary dynamics under global environmental changes, and are directly applicable to biodiversity conservation.     

CHAOS AND UNPREDICTABILITY IN EVOLUTION

The possibility of complicated dynamic behavior driven by nonlinear feedbacks in dynamical systems has revolutionized science in the latter part of the last century. Yet despite examples of complicated frequency dynamics, the possibility of long‐term evolutionary chaos is rarely considered. The concept of “survival of the fittest” is central to much evolutionary thinking and embodies a perspective of evolution as a directional optimization process exhibiting simple, predictable dynamics. This perspective is adequate for simple scenarios, when frequency‐independent selection acts on scalar phenotypes. However, in most organisms many phenotypic properties combine in complicated ways to determine ecological interactions, and hence frequency‐dependent selection. Therefore, it is natural to consider models for evolutionary dynamics generated by frequency‐dependent selection acting simultaneously on many different phenotypes. Here we show that complicated, chaotic dynamics of long‐term evolutionary trajectories in phenotype space is very common in a large class of such models when the dimension of phenotype space is large, and when there are selective interactions between the phenotypic components. Our results suggest that the perspective of evolution as a process with simple, predictable dynamics covers only a small fragment of long‐term evolution.     

On indirect genetic effects in structured populations

Indirect genetic effects (IGEs) occur when the phenotype of an individual, and possibly its fitness, depends, at least in part, on the genes of its social partners. The effective result is that environmental sources of phenotypic variance can themselves evolve. Simple models have shown that IGEs can alter the rate and direction of evolution for traits involved in interactions. Here we expand the applicability of the theory of IGEs to evolution in metapopulations by including nonlinear interactions between individuals and population genetic structure. Although population subdivision alone generates some dramatic and nonintuitive evolutionary dynamics for interacting phenotypes, the combination of nonlinear interactions with subdivision reveals an even greater importance of IGEs. The presence of genetic structure links the evolution of interacting phenotypes and the traits that influence their expression ("effector traits") even in the absence of genetic correlations. When nonlinear social effects occur in subdivided populations, evolutionary response is altered and can even oppose the direction expected due to direct selection. Because population genetic structure allows for multilevel selection, we also investigate the role of IGEs in determining the response to individual and group selection. We find that nonlinear social effects can cause interference between levels of selection even when they act in the same direction. In some cases, interference can be so extreme that the actual evolutionary response to multilevel selection is opposite in direction to that predicted by summing selection at each level. This theoretical result confirms empirical data that show higher levels of selection cannot be ignored even when selection acts in the same direction at all levels.     

Behavioral and neural Darwinism: Selectionist function and mechanism in adaptive behavior dynamics

An evolutionary theory of behavior dynamics and a theory of neuronal group selection share a common selectionist framework. The theory of behavior dynamics instantiates abstractly the idea that behavior is selected by its consequences. It implements Darwinian principles of selection, reproduction, and mutation to generate adaptive behavior in virtual organisms. The behavior generated by the theory has been shown to be quantitatively indistinguishable from that of live organisms. The theory of neuronal group selection suggests a mechanism whereby the abstract principles of the evolutionary theory may be implemented in the nervous systems of biological organisms. According to this theory, groups of neurons subserving behavior may be selected by synaptic modifications that occur when the consequences of behavior activate value systems in the brain. Together, these theories constitute a framework for a comprehensive account of adaptive behavior that extends from brain function to the behavior of whole organisms in quantitative detail.     

Invasive plant rhizome production and competitiveness vary based on neighbor identity

入侵植物根茎的生长和竞争力因相邻植物的不同而不同 物种内的遗传和表型变异对进化过程的影响已众所周知，但人们对种内变异如何影响群落水平过程还知之甚少。在人类对自然系统造成影响的大背景下，由于人类活动可能会产生巨大的选择压力，因此具有生态意义的种内变异可能会特别重要。在一项温室实验中，我们研究了一种分布广泛的入侵物种和农业杂草石茅(Sorghum halepense)在受到种间竞争、种内竞争和土壤肥力的影响时，其在生物量和根茎方面发生的种内变异和生态型变异。与我们的预期和此前的研究结果不同的是，我们并没有在这一早期生命阶段中发现石茅各生态型生物量的改变。然而，我们确实发现石茅的生物量会随着竞争植株种类和土壤施肥方式的不同而发生很显著的变化，同时不同株之间也存在很大差异。农业生态型的根茎较其它生态型大了11%，经施肥处理后的增大幅度更高至3倍；虽然施肥后的根茎生物量增加了~50%，但生态型之间却并无差异。有趣的是，当受到种内竞争时，与玉米(Zea mays)发生种间竞争时的情况相比，石茅的生物量和根茎生物量产出分别减少了32%和20%。我们的研究结果表明，针对相邻植株的种类而发生的物种特异性竞争响应以及根茎分配的改变，石茅在受竞争时可能会产生适应性响应，从而使分配情况发生改变。     

SEXUAL SELECTION BY THE HANDICAP MECHANISM

The handicap mechanism of sexual selection by female choice has been strongly criticized because it does not cause sexual selection to reinforce viability selection and it cannot account for the origin of mating preferences. However, several models indicate that the handicap mechanism can have important effects when operating in conjunction with Fisher's mechanism in polygynous populations. These models have been criticized because they require that fitness remains heritable indefinitely. I develop a simple haploid model of the handicap mechanism based on nonheritable variation in paternal investment, thus eliminating the problem of heritable fitness. This model produces the same evolutonary dynamics as both simple and quantitative genetic models of the handicap mechanism based on heritable fitness. If the parameters are such that Fisherian runaway selection does not occur in the null model (i.e., the polymorphic equilibria, which lie along the “Fisher line,” are stable), then the handicap mechanism turns the Fisher line into an evolutionary trajectory upon which all other trajectories converge. This occurs because Fisher's mechanism generates no net selection on female preference when the population is on the Fisher line, so that any additional source of selection (direct or indirect) on female choice causes the population to evolve deterministically along the Fisher line. This change in the evolutionary dynamics has the important consequence of eliminating the potential for rapid population divergence for mating systems via genetic drift along the Fisher line.     

Evolutionary dynamics of predator-prey systems: an ecological perspective

 Evolution takes place in an ecological setting that typically involves interactions with other organisms. To describe such evolution, a structure is needed which incorporates the simultaneous evolution of interacting species. Here a formal framework for this purpose is suggested, extending from the microscopic interactions between individuals – the immediate cause of natural selection, through the mesoscopic population dynamics responsible for driving the replacement of one mutant phenotype by another, to the macroscopic process of phenotypic evolution arising from many such substitutions. The process of coevolution that results from this is illustrated in the context of predator–prey systems. With no more than qualitative information about the evolutionary dynamics, some basic properties of predator–prey coevolution become evident. More detailed understanding requires specification of an evolutionary dynamic; two models for this purpose are outlined, one from our own research on a stochastic process of mutation and selection and the other from quantitative genetics. Much of the interest in coevolution has been to characterize the properties of fixed points at which there is no further phenotypic evolution. Stability analysis of the fixed points of evolutionary dynamical systems is reviewed and leads to conclusions about the asymptotic states of evolution rather different from those of game-theoretic methods. These differences become especially important when evolution involves more than one species. Received 10 November 1993; received in revised form 25 July 1994     

Genetic versus phenotypic models of selection: can genetics be neglected in a long-term perspective?

Game theoretical concepts in evolutionary biology have been criticized by populations geneticists, because they neglect such crucial aspects as the mating system or the mode of inheritance. In fact, the dynamics of natural selection does not necessarily lead to a fitness maximum or an ESS if genetic constraints are taken into account. Yet, it may be premature to conclude that game theoretical concepts do not have a dynamical justification. The new paradigm of long-term evolution postulates that genetic constraints, which may be dominant in a short-term perspective, will in the long run disappera in the face of the ongoing influx of mutations. Two basic results (see Hammerstein; this issue) seem to reconcile the dynamical approach of long-term population genetics with the static approach of evolutionary game theory: (1) only populations at local fitness optima (Nash strategies) can be long-term stable; and (2) in monomorphic populations, evolutionary stability is necessary and sufficient to ensure long-term dynamic stability. The present paper has a double purpose. On the one hand, it is demonstrated by fairly general arguments that the scope of the results mentioned above extends to non-linear frequency dependent selection, to multiple loci, and to quite general mating systems. On the other hand, some limitations of the theory of long-term evolution will also be stressed: (1) there is little hope for a game theoretical characterization of stability in polymorphic populations; (2) many interesting systems do not admit long-term stable equilibria; and (3) even if a long-term stable equilibrium exists, it is not at all clear whether and how it is attainable by a series of gene substition events.     

Eco-evolutionary dynamics in Pacific salmon

Increasing acceptance of the idea that evolution can proceed rapidly has generated considerable interest in understanding the consequences of ongoing evolutionary change for populations, communities and ecosystems. The nascent field of 'eco-evolutionary dynamics' considers these interactions, including reciprocal feedbacks between evolution and ecology. Empirical support for eco-evolutionary dynamics has emerged from several model systems, and we here present some possibilities for diverse and strong effects in Pacific salmon (Oncorhynchus spp.). We specifically focus on the consequences that natural selection on body size can have for salmon population dynamics, community (bear-salmon) interactions and ecosystem process (fluxes of salmon biomass between habitats). For example, we find that shifts in body size because of selection can alter fluxes across habitats by up to 11% compared with ecological (that is, numerical) effects. More generally, we show that selection within a generation can have large effects on ecological dynamics and so should be included within a complete eco-evolutionary framework.     

Evolution of balanced genetic polymorphism

Extreme genetic polymorphism maintained by balancing selection (so called because many alleles are maintained in a balance by a mechanism of rare allele advantage) is intimately associated with the important task of self/non-self-discrimination. Widely disparate self-recognition systems of plants, animals and fungi share several general features, including the maintenance of large numbers of alleles at relatively even frequency, and persistence of this variation over very long time periods. Because the evolutionary dynamics of balanced polymorphism are very different from those of neutral genetic variation, data on balanced polymorphism have been used as a novel source for inference of the history of populations. This review highlights the unique evolutionary properties of balanced genetic polymorphism, and the use of theoretical understanding in analysis and application of empirical data for inference of population history. However, a second goal of this review is to point out where current theory is incomplete. Recent observations suggest that entirely novel selective forces may act in concert with balancing selection, and these novel forces may be extremely potent in shaping genetic variation at self-recognition loci.     

Cancer in light of experimental evolution

Cancer initiation, progression, and the emergence of therapeutic resistance are evolutionary phenomena of clonal somatic cell populations. Studies in microbial experimental evolution and the theoretical work inspired by such studies are yielding deep insights into the evolutionary dynamics of clonal populations, yet there has been little explicit consideration of the relevance of this rapidly growing field to cancer biology. Here, we examine how the understanding of mutation, selection, and spatial structure in clonal populations that is emerging from experimental evolution may be applicable to cancer. Along the way, we discuss some significant ways in which cancer differs from the model systems used in experimental evolution. Despite these differences, we argue that enhanced prediction and control of cancer may be possible using ideas developed in the context of experimental evolution, and we point out some prospects for future research at the interface between these traditionally separate areas.     

Natural Selection and Material Culture

Natural selection is the basis of all evolutionary applications in biology as well as studies of cultural process in archaeology. Natural selection is important because it allows us the tools to talk not only about variation in biological systems but also material culture that are the by-products of the human decision-making processes. In this paper, we provide a baseline of the concept of natural selection and explanatory application in evolutionary archaeology.     

The long-term evolution of multilocus traits under frequency-dependent disruptive selection

Frequency-dependent disruptive selection is widely recognized as an important source of genetic variation. Its evolutionary consequences have been extensively studied using phenotypic evolutionary models, based on quantitative genetics, game theory, or adaptive dynamics. However, the genetic assumptions underlying these approaches are highly idealized and, even worse, predict different consequences of frequency-dependent disruptive selection. Population genetic models, by contrast, enable genotypic evolutionary models, but traditionally assume constant fitness values. Only a minority of these models thus addresses frequency-dependent selection, and only a few of these do so in a multilocus context. An inherent limitation of these remaining studies is that they only investigate the short-term maintenance of genetic variation. Consequently, the long-term evolution of multilocus characters under frequency-dependent disruptive selection remains poorly understood. We aim to bridge this gap between phenotypic and genotypic models by studying a multilocus version of Levene's soft-selection model. Individual-based simulations and deterministic approximations based on adaptive dynamics theory provide insights into the underlying evolutionary dynamics. Our analysis uncovers a general pattern of polymorphism formation and collapse, likely to apply to a wide variety of genetic systems: after convergence to a fitness minimum and the subsequent establishment of genetic polymorphism at multiple loci, genetic variation becomes increasingly concentrated on a few loci, until eventually only a single polymorphic locus remains. This evolutionary process combines features observed in quantitative genetics and adaptive dynamics models, and it can be explained as a consequence of changes in the selection regime that are inherent to frequency-dependent disruptive selection. Our findings demonstrate that the potential of frequency-dependent disruptive selection to maintain polygenic variation is considerably smaller than previously expected.     

Self-structuring in spatial evolutionary ecology

Spatial self-structuring has been a focus of recent interest among evolutionary ecologists. We review recent developments in the study of the interplay between spatial self-structuring and evolution. We first discuss the relative merits of the various theoretical approaches to spatial modelling in ecology. Second, we synthesize the main theoretical studies of the evolution of cooperation in spatially structured populations. We show that population viscosity is generally beneficial to cooperation, because cooperators can reap additional benefits from being clustered. A similar mechanism can explain the evolution of honest communication and of reduced virulence in host–parasite interactions. We also discuss some recent innovative empirical results that test these theories. Third, we show the relevance of these results to the general field of evolutionary ecology. An important conclusion is that kin selection is the main process that drives evolution of cooperation in viscous populations. Many results of kin selection theory can be recovered as emergent properties of spatial ecological dynamics. We discuss the implications of these results for the study of multilevel selection and evolutionary transitions. We conclude by sketching some perspectives for future research, with a particular emphasis on the topics of evolutionary branching, criticality, spatial fluctuations and experimental tests of theoretical predictions.     

A system identification analysis of neural adaptation dynamics and nonlinear responses in the local reflex control of locust hind limbs

Nonlinear type system identification models coupled with white noise stimulation provide an experimentally convenient and quick way to investigate the often complex and nonlinear interactions between the mechanical and neural elements of reflex limb control systems. Previous steady state analysis has allowed the neurons in such systems to be categorised by their sensitivity to position, velocity or acceleration (dynamics) and has improved our understanding of network function. These neurons, however, are known to adapt their output amplitude or spike firing rate during repetitive stimulation and this transient response may be more important than the steady state response for reflex control. In the current study previously used system identification methods are developed and applied to investigate both steady state and transient dynamic and nonlinear changes in the neural circuit responsible for controlling reflex movements of the locust hind limbs. Through the use of a parsimonious model structure and Monte Carlo simulations we conclude that key system dynamics remain relatively unchanged during repetitive stimulation while output amplitude adaptation is occurring. Whilst some evidence of a significant change was found in parts of the systems nonlinear response, the effect was small and probably of little physiological relevance. Analysis using biologically more realistic stimulation reinforces this conclusion.     

Multilevel Selection in Models of Prebiotic Evolution II: A Direct Comparison of Compartmentalization and Spatial Self-Organization

Multilevel selection has been indicated as an essential factor for the evolution of complexity in interacting RNA-like replicator systems. There are two types of multilevel selection mechanisms: implicit and explicit. For implicit multilevel selection, spatial self-organization of replicator populations has been suggested, which leads to higher level selection among emergent mesoscopic spatial patterns (traveling waves). For explicit multilevel selection, compartmentalization of replicators by vesicles has been suggested, which leads to higher level evolutionary dynamics among explicitly imposed mesoscopic entities (protocells). Historically, these mechanisms have been given separate consideration for the interests on its own. Here, we make a direct comparison between spatial self-organization and compartmentalization in simulated RNA-like replicator systems. Firstly, we show that both mechanisms achieve the macroscopic stability of a replicator system through the evolutionary dynamics on mesoscopic entities that counteract that of microscopic entities. Secondly, we show that a striking difference exists between the two mechanisms regarding their possible influence on the long-term evolutionary dynamics, which happens under an emergent trade-off situation arising from the multilevel selection. The difference is explained in terms of the difference in the stability between self-organized mesoscopic entities and externally imposed mesoscopic entities. Thirdly, we show that a sharp transition happens in the long-term evolutionary dynamics of the compartmentalized system as a function of replicator mutation rate. Fourthly, the results imply that spatial self-organization can allow the evolution of stable folding in parasitic replicators without any specific functionality in the folding itself. Finally, the results are discussed in relation to the experimental synthesis of chemical Darwinian systems and to the multilevel selection theory of evolutionary biology in general. To conclude, novel evolutionary directions can emerge through interactions between the evolutionary dynamics on multiple levels of organization. Different multilevel selection mechanisms can produce a difference in the long-term evolutionary trend of identical microscopic entities.     

Natural selection and self-organization

The Darwinian concept of natural selection was conceived within a set of Newtonian background assumptions about systems dynamics. Mendelian genetics at first did not sit well with the gradualist assumptions of the Darwinian theory. Eventually, however, Mendelism and Darwinism were fused by reformulating natural selection in statistical terms. This reflected a shift to a more probabilistic set of background assumptions based upon Boltzmannian systems dynamics. Recent developments in molecular genetics and paleontology have put pressure on Darwinism once again. Current work on self-organizing systems may provide a stimulus not only for increased problem solving within the Darwinian tradition, especially with respect to origins of life, developmental genetics, phylogenetic pattern, and energy-flow ecology, but for deeper understanding of the very phenomenon of natural selection itself. Since self-organizational phenomena depend deeply on stochastic processes, self-organizational systems dynamics advance the probability revolution. In our view, natural selection is an emergent phenomenon of physical and chemical selection. These developments suggest that natural selection may be grounded in physical law more deeply than is allowed by advocates of the autonomy of biology, while still making it possible to deny, with autonomists, that evolutionary explanations can be modeled in terms of a deductive relationship between laws and cases. We explore the relationship between, chance, self-organization, and selection as sources of order in biological systems in order to make these points.