Taming fitness: Organism‐environment interdependencies preclude long‐term fitness forecasting

Fitness is a central but notoriously vexing concept in evolutionary biology. The propensity interpretation of fitness is often regarded as the least problematic account for fitness. It ties an individual's fitness to a probabilistic capacity to produce offspring. Fitness has a clear causal role in evolutionary dynamics under this account. Nevertheless, the propensity interpretation faces its share of problems. We discuss three of these. We first show that a single scalar value is an incomplete summary of a propensity. Second, we argue that the widespread method of “abstracting away” environmental idiosyncrasies by averaging over reproductive output in different environments is not a valid approach when environmental changes are irreversible. Third, we point out that expanding the range of applicability for fitness measures by averaging over more environments or longer time scales (so as to ensure environmental reversibility) reduces one's ability to distinguish selectively relevant differences among individuals because of mutation and eco‐evolutionary feedbacks. This series of problems leads us to conclude that a general value of fitness that is both explanatory and predictive cannot be attained. We advocate for the use of propensity‐compatible methods, such as adaptive dynamics, which can accommodate these difficulties.     

Evolution of Dispersal in a Structured Metapopulation Model in Discrete Time

In this article, a structured metapopulation model in discrete time with catastrophes and density-dependent local growth is introduced. The fitness of a rare mutant in an environment set by the resident is defined, and an efficient method to calculate fitness is presented. With this fitness measure evolutionary analysis of this model becomes feasible. This article concentrates on the evolution of dispersal. The effect of catastrophes, dispersal cost, and local dynamics on the evolution of dispersal is investigated. It is proved that without catastrophes, if all population–dynamical attractors are fixed points, there will be selection for no dispersal. A new mechanism for evolutionary branching is also found: Even though local population sizes approach fixed points, catastrophes can cause enough temporal variability, so that evolutionary branching becomes possible.     

Interpretations arising from Wrightian and Malthusian fitness under strong frequency dependent selection

Fitness is the central concept in evolutionary theory. It measures a phenotype's ability to survive and reproduce. There are different ways to represent this measure: Malthusian fitness and Wrightian fitness. One can go back and forth between the two, but when we characterize model properties or interpret data, it can be important to distinguish between them. Here, we discuss a recent experiment to show how the interpretation changes if an alternative definition is used.     

Rapid climate change and the rate of adaptation: insight from experimental quantitative genetics

CONTENTS: Summary 752 I. Introduction 752 II. Will migration be enough? 753 III. Can adaptation proceed fast enough? 754 IV. Fitness links demographic and evolutionary processes 755 V. Experimental studies: what do they tell us and how can we improve them? 756 VI. Predicting evolutionary change based on genetic variation and natural selection 757 VII. The chronosequence approach 758 VIII. Resurrection of ancestral propagules 759 IX. The mean and variance in fitness, a link between genetics and demography 760 X. Conclusions 762 Acknowledgements 762 References 762 SUMMARY: Evolution proceeds unceasingly in all biological populations. It is clear that climate-driven evolution has molded plants in deep time and within extant populations. However, it is less certain whether adaptive evolution can proceed sufficiently rapidly to maintain the fitness and demographic stability of populations subjected to exceptionally rapid contemporary climate change. Here, we consider this question, drawing on current evidence on the rate of plant range shifts and the potential for an adaptive evolutionary response. We emphasize advances in understanding based on theoretical studies that model interacting evolutionary processes, and we provide an overview of quantitative genetic approaches that can parameterize these models to provide more meaningful predictions of the dynamic interplay between genetics, demography and evolution. We outline further research that can clarify both the adaptive potential of plant populations as climate continues to change and the role played by ongoing adaptation in their persistence.     

路径依赖下的物种形成机制

生物科学几乎所有研究都需要物种概念作为基础, 生物多样性研究亦需要可操作的物种概念, 但现有物种概念存在不同程度的人为因素或难操作性, 对物种划分造成不利影响。本文引入“进化路径”这一概念, 说明适合度景观时刻变化着, 物种在每个进化时间点上依据瞬时适合度选择下一时刻的进化状态, 且总是沿着动态适合度景观中适合度增加的方向进化。基于演化博弈的方法, 以随机过程为例模拟物种的进化过程。进而提出路径依赖下的物种形成机制, 并在此基础上给出可操作的物种定义, 即: 针对基因、性状、生态过程等任一状态下两个群体内个体的多个变量做统计分析, 若群体之间同时在两个或多个维度状态下呈现出的不连续性d大于群体内变量呈现出的差异性σ_k, 则拥有相应变量的个体属于不同物种。     

动物生活史进化理论研究进展

综述了生活史性状、生活史对策、权衡、适合度及进化种群统计学等动物生活史进化领域的进展。权衡是生活史性状之间相互联系的纽带,分为生理权衡与进化权衡。适合度是相对的,与个体所处的特定环境条件有关,性状进化与适合度之间关系紧密。适合度是生活史进化理论研究的焦点。探讨动物生活史对策的理论很多,影响最大的是MacArthur和Wilson提出的r对策及K对策理论。随年龄的增长,动物存活率及繁殖率逐步下降的过程,称为衰老;解释衰老的进化理论主要有突变-选择平衡假设和多效对抗假设。进化种群统计学将种群统计学应用于生活史进化研究,为探讨表型适合度的进化提供了有效的手段。将进化种群统计学、数量遗传学及特定种系效应理论进行整合,建立完整的动物生活史进化综合理论体系,是当代此领域的最大挑战。     

FOUNDER EFFECTS AND PEAK SHIFTS WITHOUT GENETIC DRIFT: ADAPTIVE PEAK SHIFTS OCCUR EASILY WHEN ENVIRONMENTS FLUCTUATE SLIGHTLY

Two similar evolutionary theories, the shifting balance theory and founder-flush models, invoke random genetic drift to allow evolution on complex adaptive landscapes. These models, in their usual incarnations, deal with fitness as a static entity, and the probability of transition from one form to another is predicted to be quite small by analysis of these models. Fitness itself can change, however, and the amount of change in the parameters of the fitness functions required to allow deterministic evolution to new adaptive peaks is very small. The probability of environmental changes sufficient to allow substantial morphological evolution or reproductive isolation is large relative to the probability that similar changes could occur by processes requiring genetic drift, even with very small population sizes. The rapid evolution or speciation following a population founding event is more closely linked with environmental changes than genetic drift.     

Reverse evolution of fitness in Drosophila melanogaster

Abstract The evolution of fitness is central to evolutionary theory, yet few experimental systems allow us to track its evolution in genetically and environmentally relevant contexts. Reverse evolution experiments allow the study of the evolutionary return to ancestral phenotypic states, including fitness. This in turn permits well‐defined tests for the dependence of adaptation on evolutionary history and environmental conditions. In the experiments described here, 20 populations of heterogeneous evolutionary histories were returned to their common ancestral environment for 50 generations, and were then compared with both their immediate differentiated ancestors and populations which had remained in the ancestral environment. One measure of fitness returned to ancestral levels to a greater extent than other characters did. The phenotypic effects of reverse evolution were also contingent on previous selective history. Moreover, convergence to the ancestral state was highly sensitive to environmental conditions. The phenotypic plasticity of fecundity, a character directly selected for, evolved during the experimental time frame. Reverse evolution appears to force multiple, diverged populations to converge on a common fitness state through different life‐history and genetic changes.     

The fitness of filamentous fungi

Fitness is a common currency in comparative biology. Without data on fitness, hypotheses about the adaptive significance of phenotypes or basic mechanisms of evolution, for example natural selection, remain speculative. Experiments with fungi can address questions specific to fungi or questions with a broader significance. Fungi can challenge the generality of fundamental evolutionary principles, yet there are no standard measures of fungal fitness. We argue that focusing on a single aspect of a complex life cycle, or a single measure of fitness (e.g. the number of asexual spores) is appropriate. Choosing which aspect of fitness to measure can be facilitated by an understanding of how fitness measures are correlated. Choices can also be based on the ecology of a species, for example whether a fungus is semelparous and reproduces once, or iteroparous and reproduces multiple times.     

The fitness value of information

Communication and information are central concepts in evolutionary biology. In fact, it is hard to find an area of biology where these concepts are not used. However, quantifying the information transferred in biological interactions has been difficult. How much information is transferred when the first spring rainfall hits a dormant seed, or when a chick begs for food from its parent? One measure that is commonly used in such cases is fitness value: by how much, on average, an individual's fitness would increase if it behaved optimally with the new information, compared to its average fitness without the information. Another measure, often used to describe neural responses to sensory stimuli, is the mutual information – a measure of reduction in uncertainty, as introduced by Shannon in communication theory. However, mutual information has generally not been considered to be an appropriate measure for describing developmental or behavioral responses at the organismal level, because it is blind to function; it does not distinguish between relevant and irrelevant information. In this paper we show that there is in fact a surprisingly tight connection between these two measures in the important context of evolution in an uncertain environment. In this case, a useful measure of fitness benefit is the increase in the long‐term growth rate, or the fold increase in number of surviving lineages. We show that in many cases the fitness value of a developmental cue, when measured this way, is exactly equal to the reduction in uncertainty about the environment, as described by the mutual information.     

Environmental uncertainty, autocorrelation and the evolution of survival

Survival is a key fitness component and the evolution of age- and stage-specific patterns in survival is a central question in evolutionary biology. In variable environments, favouring chances of survival at the expense of other fitness components could increase fitness by spreading risk across uncertain conditions, especially if environmental conditions improve in the future. Both the magnitude of environmental variation and temporal autocorrelation in the environment might therefore affect the evolution of survival patterns. Despite this, the influence of temporal autocorrelation on the evolution of survival patterns has not been addressed. Here, we use a trade-off structure which reflects the empirically inspired paradigm of acquisition and allocation of resources to investigate how the evolutionarily stable survival probability is shaped in variable, density-dependent environments. We show that temporal autocorrelation is likely to be an important aspect of environmental variability that contributes to shaping age- and stage-specific patterns of survival probabilities in nature.     

Evolutionarily stable strategies in food selection models with fitness sets

Most current models for optimal food selection apply to ecological and behavioural optimization. In this paper optimal food selection theory is extended to apply to evolutionary optimization. A general evolutionary model for optimal food selection must incorporate the concept of fitness sets--or that variables, changing as a result of natural selection in evolutionary time, cannot, in general, vary independently of each other. A "Charnov type" optimal food selection model with a fitness set is investigated, and evolutionarily stable strategy (ESS) solutions of the evolutionary variables (i.e., the efficiencies of using available food types) are found. From this analysis it follows that the relative frequency of various food types in the environment may, under specified conditions, influence the evolutionarily optimal diet. Secondly, the analysis demonstrates that a food type not in the optimal diet may, in evolutionary time, be added to this by becoming more abundant. Thirdly, it follows from the analysis that the ecological result of MacArthur and Pianka, that food types are worth eating even if there is competition for them, is not generally applicable when referring to an evolutionary time scale. Finally, it is pointed out that for the diet to be an ESS, it is necessary that the consumer's density is stable and that the consumer's population dynamics are subjected to some density-dependent factor.     

Should ecological factors affect the evolution of age at maturity in freshwater clams?

We studied the evolution of age at maturity in freshwater clams of the genus Anodonta in relation to their ecology. We analysed an age-structured density-dependent population dynamics model, which we developed for freshwater clams, using several different options for density dependence. As evolutionary optimality criteria we applied both the maximization of a fitness measure (either intrinsic rate of increase or expected lifetime fecundity) and the concept of evolutionarily stable strategies (ESSs). All three evolutionary criteria yielded estimates which were too high for the optimal age at maturity in a deterministic model with a constant survival rate. The predictions are improved when size-selective predation is included in the model. Mature clams also face a risk of infection by castrating parasites, which would select for delayed maturity. Variable newborn survival selects for earlier reproduction, though the observed levels of stochasticity probably have a negligible effect.     

Accurate Alternative Measurements for Female Lifetime Reproductive Success in Drosophila melanogaster

Fitness is an individual’s ability to survive and reproduce, and is an important concept in evolutionary biology. However, accurately measuring fitness is often difficult, and appropriate fitness surrogates need to be identified. Lifetime reproductive success, the total progeny an organism can produce in their lifetime, is thought to be a suitable proxy for fitness, but the measure of an organism’s reproductive output across a lifetime can be difficult or impossible to obtain. Here we demonstrate that the short-term measure of reproductive success across five days provides a reasonable prediction of an individual''s total lifetime reproductive success in Drosophila melanogaster. However, the lifetime reproductive success of a female that has only mated once is not correlated to the lifetime reproductive success of a female that is allowed to mate multiple times, demonstrating that these measures should not serve as surrogates nor be used to make inferences about one another.     

Quantitative genetic versions of Hamilton's rule with empirical applications

Hamilton''s theory of inclusive fitness revolutionized our understanding of the evolution of social interactions. Surprisingly, an incorporation of Hamilton''s perspective into the quantitative genetic theory of phenotypic evolution has been slow, despite the popularity of quantitative genetics in evolutionary studies. Here, we discuss several versions of Hamilton''s rule for social evolution from a quantitative genetic perspective, emphasizing its utility in empirical applications. Although evolutionary quantitative genetics offers methods to measure each of the critical parameters of Hamilton''s rule, empirical work has lagged behind theory. In particular, we lack studies of selection on altruistic traits in the wild. Fitness costs and benefits of altruism can be estimated using a simple extension of phenotypic selection analysis that incorporates the traits of social interactants. We also discuss the importance of considering the genetic influence of the social environment, or indirect genetic effects (IGEs), in the context of Hamilton''s rule. Research in social evolution has generated an extensive body of empirical work focusing—with good reason—almost solely on relatedness. We argue that quantifying the roles of social and non-social components of selection and IGEs, in addition to relatedness, is now timely and should provide unique additional insights into social evolution.     

How should we define 'fitness' for general ecological scenarios?

Beginners in life history theory or evolutionary ecology seemingly face a variety of almost unrelated approaches. Yet the biomathematical literature of the last 10-20 years reflects the implicit acceptance of a common evolutionary framework, the core idea being that there exists a unique general fitness measure that concisely summarizes the overall time course of potential invasions by initially rare mutant phenotypes. Using such an invasion criterion to characterize fitness implicitly presupposes a scenario in which, during periods o f clear evolutionary change, the rate of evolution is set primarily by the random occurrence (and initial establishment) of favourable mutations. Evolutionarily stable life history strategies (ESSs) may then be regarded as traps for the evolutionary random walk.     

The long and winding road of evolutionary demography: preface

Fitness can be calculated using demographic parameters such as survival and fecundity, which are normally used to examine population dynamics in ecology. This concept is at the heart of Darwin's thinking on natural selection. Natural selection optimizes survival and fertility schedules through differential fitness, and these optimal schedules drive changes in population dynamics. Therefore, there must exist an interaction between ecology and evolution. One of the disciplines that focus on the interaction is "Evolutionary demography". It uses age- or stage-specific demographic parameters throughout the whole life history to explore the evolution of life histories. Data throughout the life history of a species is indispensable to study evolutionary demography. To this end, two large-scale databases of plant and animal life history are now available online, the COMPADRE Plant Matrix Database and the COMADRE Animal Matrix Database. We are now in a revolutionary era in the demographic research of plant and animal populations (including human populations). Many skills and approaches are needed to answer questions on evolutionary demography including bodies of theory and analytical toolkits. This special issue covers a wide array of subjects: (1) Demographic analysis of populations (including human populations) from the point of view of evolutionary ecology, (2) Meta-analysis using big databases of populations, (3) Eco-evolutionary studies at the population and/or community level and (4) Theoretical studies and the development of mathematical models of life history evolution. 14 collected papers are published to answer a variety of questions using original ideas, new tools, and big data.     

The evolution of fitness in life-history theory

Theory concerning the evolution of life history (the schedule of reproduction and survival) focuses on describing the life history which maximises fitness. Although there is an intuitive link between life history and fitness, there are in fact several measures of the 'black box' concept of fitness. There has been a debate in the bio-mathematical literature on the predictive difference between the two most commonly used measures; intrinsic rate of increase r and net reproductive ratio R0. Although both measures aim to describe fitness, models using one of the measures may predict the opposite of similar models using the other measure, which is clearly undesirable. Here, I review the evolution of these fitness measures over the last four decades, the predictive differences between these measures and the resulting shift of the fitness concept. I focus in particular on some recent developments, which have solved the dilemma of predictive differences between these fitness measures by explicitly acknowledging the game-theoretical nature of life-history evolution.     

Escaping an evolutionary lobster trap: drug resistance and compensatory mutation in a fluctuating environment

The fitness landscape concept aids intuition on adaptive evolution through low fitness genotypes. Evolutionary processes become complex when environments and therefore fitnesses fluctuate. Antibiotic resistance evolution in bacteria is an important example of such dynamics. Resistance bears a cost in the drug-free environment, but compensatory mutation can lower this cost, creating a fitness valley. With the drug present, the valley becomes a hill that is easily climbed. Once a population is dominated by resistant-compensated genotypes, reversion to sensitivity is difficult: this phenomenon has been described as an evolutionary lobster trap. With increasing frequencies of drug resistance among pathogenic bacteria, it is critical to understand how this trap can be escaped. Here, we develop stochastic models to investigate these dynamics. The residual fitness cost (the cost remaining after compensatory mutation has occurred) is a key parameter. Reversion to sensitivity is favored when the time spent in the absence of the drug relative to its presence is high compared to the residual fitness cost. Population sizes are also important: in large populations, resistant-compensated mutants appear in resistant-uncompensated or sensitive-compensated genotypes without fixation of these intermediates. This stochastic tunneling effect occurs when sufficient time is allowed by the rates of environmental fluctuation.     

Role of Utility and Inference in the Evolution of Functional Information

Functional information means an encoded network of functions in living organisms from molecular signaling pathways to an organism’s behavior. It is represented by two components: code and an interpretation system, which together form a self-sustaining semantic closure. Semantic closure allows some freedom between components because small variations of the code are still interpretable. The interpretation system consists of inference rules that control the correspondence between the code and the function (phenotype) and determines the shape of the fitness landscape. The utility factor operates at multiple time scales: short-term selection drives evolution towards higher survival and reproduction rate within a given fitness landscape, and long-term selection favors those fitness landscapes that support adaptability and lead to evolutionary expansion of certain lineages. Inference rules make short-term selection possible by shaping the fitness landscape and defining possible directions of evolution, but they are under control of the long-term selection of lineages. Communication normally occurs within a set of agents with compatible interpretation systems, which I call communication system. Functional information cannot be directly transferred between communication systems with incompatible inference rules. Each biological species is a genetic communication system that carries unique functional information together with inference rules that determine evolutionary directions and constraints. This view of the relation between utility and inference can resolve the conflict between realism/positivism and pragmatism. Realism overemphasizes the role of inference in evolution of human knowledge because it assumes that logic is embedded in reality. Pragmatism substitutes usefulness for truth and therefore ignores the advantage of inference. The proposed concept of evolutionary pragmatism rejects the idea that logic is embedded in reality; instead, inference rules are constructed within each communication system to represent reality, and they evolve towards higher adaptability on a long time scale.