Limitations of inclusive fitness

Nonlinear social evolution and the emergence of collective action

Organisms from microbes to humans engage in a variety of social behaviors, which affect fitness in complex, often nonlinear ways. The question of how these behaviors evolve has consequences ranging from antibiotic resistance to human origins. However, evolution with nonlinear social interactions is challenging to model mathematically, especially in combination with spatial, group, and/or kin assortment. We derive a mathematical condition for natural selection with synergistic interactions among any number of individuals. This result applies to populations with arbitrary (but fixed) spatial or network structure, group subdivision, and/or mating patterns. In this condition, nonlinear fitness effects are ascribed to collectives, and weighted by a new measure of collective relatedness. For weak selection, this condition can be systematically evaluated by computing branch lengths of ancestral trees. We apply this condition to pairwise games between diploid relatives, and to dilemmas of collective help or harm among siblings and on spatial networks. Our work provides a rigorous basis for extending the notion of "actor", in the study of social evolution, from individuals to collectives.

Aging and group selection: New arguments in favor of partially directed evolution

In this study, theories of aging and its mechanisms under various environmental conditions were analyzed. The analysis of published data suggested that aging is a controlled process. It is known that many mathematical algorithms utilize an analogy of aging. However, this is possible only when a "target set" is known in advance. Various forms of selection in relation to aging were analyzed both collectively and separately. The general conclusion is that aging is one of the mechanisms of directed evolution. A model was constructed, which shows how aging is integrated into partially directed evolution.

Evolutionarily stable strategy analysis and its links to demography and genetics through invasion fitness

Evolutionarily stable strategy (ESS) analysis pioneered by Maynard Smith and Price took off in part because it often does not require explicit assumptions about the genetics and demography of a population in contrast to population genetic models. Though this simplicity is useful, it obscures the degree to which ESS analysis applies to populations with more realistic genetics and demography: for example, how does ESS analysis handle complexities such as kin selection, group selection and variable environments when phenotypes are affected by multiple genes? In this paper, I review the history of the ESS concept and show how early uncertainty about the method lead to important mathematical theory linking ESS analysis to general population genetic models. I use this theory to emphasize the link between ESS analysis and the concept of invasion fitness. I give examples of how invasion fitness can measure kin selection, group selection and the evolution of linked modifier genes in response to variable environments. The ESSs in these examples depend crucially on demographic and genetic parameters, which highlights how ESS analysis will continue to be an important tool in understanding evolutionary patterns as new models address the increasing abundance of genetic and long-term demographic data in natural populations. This article is part of the theme issue 'Half a century of evolutionary games: a synthesis of theory, application and future directions'.

Explaining workers' inactivity in social colonies from first principles

Social insects are among the ecologically most successful collectively living organisms, with efficient division of labour a key feature of this success. Surprisingly, these efficient colonies often have a large proportion of inactive workers in their workforce, sometimes referred to as lazy workers. The dominant hypotheses explaining this are based on specific life-history traits, specific behavioural features or uncertain environments where inactive workers can provide a 'reserve' workforce that can spring into action quickly. While there is a number of experimental studies that show and investigate the presence of inactive workers, mathematical and computational models exploring specific hypotheses are not common. Here, using a simple mathematical model, we show that a parsimonious hypothesis can explain this puzzling social phenomenon. Our model incorporates social interactions and environmental influences into a game-theoretical framework and captures how individuals react to environment by allocating their activity according to environmental conditions. This model shows that inactivity can emerge under specific environmental conditions as a by-product of the task allocation process. Our model confirms the empirical observation that in the case of worker loss, prior homeostatic balance is re-established by replacing some of the lost force with previously inactive workers. Most importantly, our model shows that inactivity in social colonies can be explained without the need to assume an adaptive function for this phenomenon.

Hamilton's rule: A non-causal explanation?

The explanatory power of Hamilton's rule, the main explanatory principle of social evolution theory, is an ongoing subject of controversy. In this paper, we reinforce the case for the considerable value of the regression-based version of the rule in explaining the evolution of social traits. Although we agree that the rule can have an organizing role in social evolution research, we maintain that it does not explain in virtue of citing causes or providing an organizing framework. Instead, we argue it either provides an explanation by constraint or a non-causal counterfactual explanation.

Identifying Causes of Social Evolution: Contextual Analysis, the Price Approach, and Multilevel Selection

Kin selection theory and multilevel selection theory are distinct approaches to explaining the evolution of social traits. The latter claims that it is useful to regard selection as a process that can occur on multiple levels of organisation such as the level of individuals and the level of groups. This is reflected in a decomposition of fitness into an individual component and a group component. This multilevel view is central to understanding and characterising evolutionary transitions in individuality, e.g., from unicellular life to multicellular organisms, but currently suffers from the lack of a consistent, quantifiable measure. Specifically, the two major statistical tools to determine the coefficients of such a decomposition, the multilevel Price equation and contextual analysis, are inconsistent and may disagree on whether group selection is present. Here we show that the reason for the discrepancies is that underlying the multilevel Price equation and contextual analysis are two non-equivalent causal models for the generation of individual fitness effects (thus leaving different “remainders” explained by group effects). While the multilevel Price equation assumes that the individual effect of a trait determines an individual's relative success within a group, contextual analysis posits that the individual effect is context-independent. Since these different assumptions reflect claims about the causal structure of the system, the correct approach cannot be determined on general theoretical or statistical grounds but must be identified by experimental intervention. We outline interventions that reveal the underlying causal structure and thus facilitate choosing the appropriate approach. We note that kin selection theory with its focus on the individual is immune to such inconsistency because it does not address causal structure with respect to levels of organisation. In contrast, our analysis of the two approaches to measuring group selection demonstrates that multilevel selection theory adds meaningful (falsifiable) causal structure to explain the sources of individual fitness and thereby constitutes a proper refinement of kin selection theory. Taking such refined causal structure into account seems indispensable for studying evolutionary transitions in individuality because these transitions are characterised by changes in the selection pressures that act on the respective levels.

Inclusive fitness and Hamilton's rule in a stochastic environment

The evolution of cooperation in Prisoner's Dilemmas with additive random cost and benefit for cooperation cannot be accounted for by Hamilton's rule based on mean effects transferred from recipients to donors weighted by coefficients of relatedness, which defines inclusive fitness in a constant environment. Extensions that involve higher moments of stochastic effects are possible, however, and these are connected to a concept of random inclusive fitness that is frequency-dependent. This is shown in the setting of pairwise interactions in a haploid population with the same coefficient of relatedness between interacting players. In an infinite population, fixation of cooperation is stochastically stable if a mean geometric inclusive fitness of defection when rare is negative, while fixation of defection is stochastically unstable if a mean geometric inclusive fitness of cooperation when rare is positive, and these conditions are generally not equivalent. In a finite population, the probability for cooperation to ultimately fix when represented once exceeds the probability under neutrality or the corresponding probability for defection if the mean inclusive fitness of cooperation when its frequency is 1/3 or 1/2, respectively, exceeds 1. All these results rely on the simplifying assumption of a linear fitness function. It is argued that meaningful applications of random inclusive fitness in complex settings (multi-player game, diploidy, population structure) would generally require conditions of weak selection and additive gene action.

Hamilton's rule and kin competition in a finite kin population

Kin selection means that individuals can increase their own inclusive fitness through displaying more altruistically toward their relatives. So, Hamilton's rule says kin selection will work if the coefficient of relatedness exceeds the cost-to-benefit ratio of the altruistic act. However, some studies have shown that the kin competition due to the altruism among relatives can reduce, and even totally negate, the kin-selected benefits of altruism toward relatives. In order to understand how the evolution of cooperation is influenced by both kin selection and kin competition under a general theoretical framework, we here consider the evolutionary dynamics of cooperation in a finite kin population, where kin competition is incorporated into a simple Prisoner's Dilemma game between relatives. Differently from the previous studies, we emphasize that the difference between the effects of mutually and unilaterally altruistic acts on kin competition may play an important role for the evolution of cooperation. The main results not only show the conditions that Hamilton's rule still works under the kin competition but also reveal the evolutionary biological mechanism driving the evolution of cooperation in a finite kin population.

Question framing and sensitivity to consequences in sacrificial moral dilemmas

In sacrificial dilemmas, participants judge the morality of killing one person to save several others. For five sacrificial dilemmas, participants rated on separate unidimensional scales how "morally right" and how "morally wrong" they felt such actions would be under six combinations of beneficiaries (strangers, cousins, one's children) and targets (firefighter, bank robber). Framing a survey question in terms of "morally right" potentially primes prescriptive moral norms, directing attention to the beneficiaries; framing it in terms of "morally wrong" potentially primes proscriptive moral norms, directing attention to the targets. Selective attention induced by a question should heighten sensitivity to changes in levels of the corresponding independent variable. Accordingly, ratings of right changed more than ratings of wrong across beneficiaries; ratings of wrong changed more than ratings of right across targets. Question framing can bias moral appraisal by heightening or attenuating attentiveness to individuals who would benefit or suffer from sacrificial action.

The problem with the Price equation

In this paper, I will argue that the generality of the Price equation comes at a cost, and that is that the terms in it become meaningless. There are simple linear models that can be written in a Price equation-like form, and for those the terms in them have a meaningful interpretation. There are also models for which that is not the case, and in general, when no assumptions on the shape of the fitness function are made, and all possible models are allowed for, the regression coefficients in the Price equation do not allow for a meaningful interpretation. The failure to recognize that the Price equation, although general, only has a meaningful interpretation under restrictive assumptions, has done real damage to the field of social evolution, as will be illustrated by looking at an application of the Price equation to group selection. This article is part of the theme issue 'Fifty years of the Price equation'.

Cultural group selection and human cooperation: a conceptual and empirical review

Cultural group selection has been proposed as an explanation for humans' highly cooperative nature. This theory argues that social learning mechanisms, combined with rewards and punishment, can stabilise any group behaviour, cooperative or not. Equilibrium selection can then operate, resulting in cooperative groups outcompeting less-cooperative groups. This process may explain the widespread cooperation between non-kin observed in humans, which is sometimes claimed to be altruistic. This review explores the assumptions of cultural group selection to assess whether it provides a convincing explanation for human cooperation. Although competition between cultural groups certainly occurs, it is unclear whether this process depends on specific social learning mechanisms (e.g. conformism) or a norm psychology (to indiscriminately punish norm-violators) to stabilise groups at different equilibria as proposed by existing cultural group selection models. Rather than unquestioningly adopt group norms and institutions, individuals and groups appear to evaluate, design and shape them for self-interested reasons (where possible). As individual fitness is frequently tied to group fitness, this often coincides with constructing group-beneficial norms and institutions, especially when groups are in conflict. While culture is a vital component underlying our species' success, the extent to which current conceptions of cultural group selection reflect human cooperative evolution remains unclear.

Genetic relatedness and its causal role in the evolution of insect societies

The role of genetic relatedness in social evolution has recently come under critical attention. These arguments are here critically analyzed, both theoretically and empirically. It is argued that when the conceptual structure of the theory of natural selection is carefully taken into account, genetic relatedness can be seen to play an indispensable role in the evolution of both facultative and advanced eusociality. Although reviewing the empirical evidence concerning the evolution of eusociality reveals that relatedness does not play a role in the initial appearance of helper phenotypes, this follows simply from the fact that natural selection - of which relatedness is a necessary component - does not play a causal role in the origin of any traits. Further, separating two logically distinct elements of causal explanation - necessity and sufficiency - explains why the debate lingers on: although relatedness plays a necessary role in the evolution of helping and advanced eusociality, relatedness alone is not sufficient for their appearance. Therefore, if the relatedness variable in a given data set is held at a uniformly high value, then it indeed may turn out that other factors occupy a more prominent role. However, this does not change the fact that high relatedness functions as a necessary background condition for the evolution of advanced eusociality.

Neo-Paleyan biology

There is a 'Neo-Paleyan' tradition in British evolutionary theorising, which began with Darwin and continues to the present day. This tradition conceives of adaptation in terms of design, and it often puts natural selection in the role of an ersatz designer. There are significant disanalogies between Paleyan conceptions of design and modern conceptions of adaptation and selection, which help to explain why the neo-Paleyan programme is sometimes treated with hostility. These general disanalogies do not suffice to dismiss the most interesting forms of recent neo-Paleyanism, which draw on theoretical principles such as Fisher's Fundamental Theorem to ground a general approach to what we can call (following Grafen) the 'criterion' of evolutionary design. It is important to distinguish between justifications of this 'criterion' and justifications of approaches to nature which presuppose that natural selection produces good designs.

Inclusive fitness and the major transitions in evolution

Inclusive fitness theory is the leading framework for explaining the major transitions in evolution, whereby free-living subunits (e.g. cells, organisms) have cooperated to form new, higher-level units (e.g. organisms, eusocial societies). The theory has attracted considerable controversy. From a brief survey of the controversy's present status, I conclude that inclusive fitness theory continues to provide both a concept and a principled modelling tool of value for understanding social evolution, including major transitions. Turning to new developments in the study of major transitions, I describe work defining the point of occurrence of major transitions and, from inclusive fitness theory, the required conditions. I also suggest that it remains important to understand the evolution of individuality that occurs beyond such thresholds.

Inclusive fitness as a criterion for improvement

I distinguish two roles for a fitness concept in the context of explaining cumulative adaptive evolution: fitness as a predictor of gene frequency change, and fitness as a criterion for phenotypic improvement. Critics of inclusive fitness argue, correctly, that it is not an ideal fitness concept for the purpose of predicting gene-frequency change, since it relies on assumptions about the causal structure of social interaction that are unlikely to be exactly true in real populations, and that hold as approximations only given a specific type of weak selection. However, Hamilton took this type of weak selection, on independent grounds, to be responsible for cumulative assembly of complex adaptations. In this special context, I argue that inclusive fitness is distinctively valuable as a criterion for improvement and a standard for optimality. Yet to call inclusive fitness a criterion for improvement and a standard for optimality is not to make any claim about the frequency with which inclusive fitness optimization actually occurs in nature. This is an empirical question that cannot be settled by theory alone. I close with some reflections on the place of inclusive fitness in the long running clash between 'causalist' and 'statisticalist' conceptions of fitness.

Inclusive fitness is an indispensable approximation for understanding organismal design

For some decades most biologists interested in design have agreed that natural selection leads to organisms acting as if they are maximizing a quantity known as "inclusive fitness." This maximization principle has been criticized on the (uncontested) grounds that other quantities, such as offspring number, predict gene frequency changes accurately in a wider range of mathematical models. Here, we adopt a resolution offered by Birch, who accepts the technical difficulties of establishing inclusive fitness maximization in a fully general model, while concluding that inclusive fitness is still useful as an organizing framework. We set out in more detail why inclusive fitness is such a practical and powerful framework, and provide verbal and conceptual arguments for why social biology would be more or less impossible without it. We aim to help mathematicians understand why social biologists are content to use inclusive fitness despite its theoretical weaknesses. Here, we also offer biologists practical advice for avoiding potential pitfalls.

Mutual altruism and long-term optimization of the inclusive fitness in multilocus genetic systems

The dynamics of long-term evolution in a complex genetically-structured population with a flux of random mutations is employed here to study the evolution of mutual altruism between relatives that are encountered repeatedly, where the level of altruism is measured by the risk one is willing to accept in order to save the life of one's relative. It is shown that regardless of the number of loci involved, of the rates of recombination among them, and of the intensity of the selection forces, the long-term dynamics can phenotypically converge only to a level of altruism that maximizes the individual inclusive fitness as it has previously defined by students of the individual approach to evolution. Except for the widely studied case of weak selection, however, the convergence to such a level of altruism is not necessarily generation-to-next monotone. It is further shown that, unlike the case of the one-shot encounter, repeated encounters between relatives allow for more than one level of altruism which may maximize the inclusive fitness, in which case not all such levels of altruism are evolutionarily accessible.

Evolution of Groupwise Cooperation: Generosity, Paradoxical Behavior, and Non-Linear Payoff Functions

Evolution of cooperation by reciprocity has been studied using two-player and n-player repeated prisoner’s dilemma games. An interesting feature specific to the n-player case is that players can vary in generosity, or how many defections they tolerate in a given round of a repeated game. Reciprocators are quicker to detect defectors to withdraw further cooperation when less generous, and better at maintaining a long-term cooperation in the presence of rare defectors when more generous. A previous analysis on a stochastic evolutionary model of the n-player repeated prisoner’s dilemma has shown that the fixation probability of a single reciprocator in a population of defectors can be maximized for a moderate level of generosity. However, the analysis is limited in that it considers only tit-for-tat-type reciprocators within the conventional linear payoff assumption. Here we extend the previous study by removing these limitations and show that, if the games are repeated sufficiently many times, considering non-tit-for-tat type strategies does not alter the previous results, while the introduction of non-linear payoffs sometimes does. In particular, under certain conditions, the fixation probability is maximized for a “paradoxical” strategy, which cooperates in the presence of fewer cooperating opponents than in other situations in which it defects.

The benefits of grouping as a main driver of social evolution in a halictine bee

Over the past decade, the cause of sociality has been much debated. Inclusive fitness [br in Hamilton's rule (br - c > 0)] has been criticized but is still useful in the organization of a framework by elucidating mechanisms through which br (benefit × relatedness) becomes larger than c (cost). The bee Lasioglossum baleicum is suitable for investigation of this issue because of the sympatric occurrence of both social and solitary nesting in its populations. We show that a large part (approximately 92%) of the inclusive fitness of a eusocial worker can be attributed to the benefits of grouping. A 1.5-fold relatedness asymmetry benefit in singly mated haplo-diploids explains a small part (approximately 8.5%) of the observed inclusive fitness. Sociality enables this species to conduct foraging and nest defense simultaneously, which is not the case in solitary nests. Our results indicate that this benefit of grouping is the main source of the increased inclusive fitness of eusocial workers.

Field studies reveal functions of chemical mediators in plant interactions

Plants are at the trophic base of most ecosystems, embedded in a rich network of ecological interactions in which they evolved. While their limited range and speed of motion precludes animal-typical behavior, plants are accomplished chemists, producing thousands of specialized metabolites which may function to convey information, or even to manipulate the physiology of other organisms. Plants' complex interactions and their underlying mechanisms are typically dissected within the controlled environments of growth chambers and glasshouses, but doing so introduces conditions alien to plants evolved in natural environments, such as being pot-bound, and receiving artificial light with a spectrum very different from sunlight. The mechanistic understanding gained from a reductionist approach provides the tools required to query and manipulate plant interactions in real-world settings. The few tests conducted in natural ecosystems and agricultural fields have highlighted the limitations of studying plant interactions only in artificial environments. Here, we focus on three examples of known or hypothesized chemical mediators of plants' interactions: the volatile phytohormone ethylene (ET), more complex plant volatile blends, and as-yet-unknown mediators transferred by common mycorrhizal networks (CMNs). We highlight how mechanistic knowledge has advanced research in all three areas, and the critical importance of field work if we are to put our understanding of chemical ecology on rigorous experimental and theoretical footing, and demonstrate function.

A Metabolic Trade-Off Modulates Policing of Social Cheaters in Populations of Pseudomonas aeruginosa

Pseudomonas aeruginosa uses quorum sensing (QS) to regulate the production of public goods such as the secreted protease elastase. P. aeruginosa requires the LasI-LasR QS circuit to induce elastase and enable growth on casein as the sole carbon and energy source. The LasI-LasR system also induces a second QS circuit, the RhlI-RhlR system. During growth on casein, LasR-mutant social cheaters emerge, and this can lead to a population collapse. In a minimal medium containing ammonium sulfate as a nitrogen source, populations do not collapse, and cheaters and cooperators reach a stable equilibrium; however, without ammonium sulfate, cheaters overtake the cooperators and populations collapse. We show that ammonium sulfate enhances the activity of the RhlI-RhlR system in casein medium and this leads to increased production of cyanide, which serves to control levels of cheaters. This enhancement of cyanide production occurs because of a trade-off in the metabolism of glycine: exogenous ammonium ion inhibits the transformation of glycine to 5,10-methylenetetrahydrofolate through a reduction in the expression of the glycine cleavage genes gcvP1 and gcvP2, thereby increasing the availability of glycine as a substrate for RhlR-regulated hydrogen cyanide synthesis. Thus, environmental ammonia enhances cyanide production and stabilizes QS in populations of P. aeruginosa.

The genetics underlying natural variation of plant-plant interactions, a beloved but forgotten member of the family of biotic interactions

Despite the importance of plant-plant interactions on crop yield and plant community dynamics, our understanding of the genetic and molecular bases underlying natural variation of plant-plant interactions is largely limited in comparison with other types of biotic interactions. By listing 63 quantitative trait loci (QTL) mapping and global gene expression studies based on plants directly challenged by other plants, we explored whether the genetic architecture and the function of the candidate genes underlying natural plant-plant interactions depend on the type of interactions between two plants (competition versus commensalism versus reciprocal helping versus asymmetry). The 16 transcriptomic studies are unevenly distributed between competitive interactions (n = 12) and asymmetric interactions (n = 4, all focusing on response to parasitic plants). By contrast, 17 and 30 QTL studies were identified for competitive interactions and asymmetric interactions (either weed suppressive ability or response to parasitic plants), respectively. Surprisingly, no studies have been carried out on the identification of genetic and molecular bases underlying natural variation in positive interactions. The candidate genes underlying natural plant-plant interactions can be classified into seven categories of plant function that have been identified in artificial environments simulating plant-plant interactions either frequently (photosynthesis, hormones), only recently (cell wall modification and degradation, defense pathways against pathogens) or rarely (ABC transporters, histone modification and meristem identity/life history traits). Finally, we introduce several avenues that need to be explored in the future to obtain a thorough understanding of the genetic and molecular bases underlying plant-plant interactions within the context of realistic community complexity.

Progress in and promise of bacterial quorum sensing research

This Review highlights how we can build upon the relatively new and rapidly developing field of research into bacterial quorum sensing (QS). We now have a depth of knowledge about how bacteria use QS signals to communicate with each other and to coordinate their activities. In recent years there have been extraordinary advances in our understanding of the genetics, genomics, biochemistry, and signal diversity of QS. We are beginning to understand the connections between QS and bacterial sociality. This foundation places us at the beginning of a new era in which researchers will be able to work towards new medicines to treat devastating infectious diseases, and use bacteria to understand the biology of sociality.

The inclusive fitness controversy: finding a way forward

This paper attempts to reconcile critics and defenders of inclusive fitness by constructing a synthesis that does justice to the insights of both. I argue that criticisms of the regression-based version of Hamilton's rule, although they undermine its use for predictive purposes, do not undermine its use as an organizing framework for social evolution research. I argue that the assumptions underlying the concept of inclusive fitness, conceived as a causal property of an individual organism, are unlikely to be exactly true in real populations, but they are approximately true given a specific type of weak selection that Hamilton took, on independent grounds, to be responsible for the cumulative assembly of complex adaptation. Finally, I reflect on the uses and limitations of 'design thinking' in social evolution research.

The general form of Hamilton's rule makes no predictions and cannot be tested empirically

Hamilton's rule asserts that a trait is favored by natural selection if the benefit to others, [Formula: see text], multiplied by relatedness, [Formula: see text], exceeds the cost to self, [Formula: see text] Specifically, Hamilton's rule states that the change in average trait value in a population is proportional to [Formula: see text] This rule is commonly believed to be a natural law making important predictions in biology, and its influence has spread from evolutionary biology to other fields including the social sciences. Whereas many feel that Hamilton's rule provides valuable intuition, there is disagreement even among experts as to how the quantities [Formula: see text], [Formula: see text], and [Formula: see text] should be defined for a given system. Here, we investigate a widely endorsed formulation of Hamilton's rule, which is said to be as general as natural selection itself. We show that, in this formulation, Hamilton's rule does not make predictions and cannot be tested empirically. It turns out that the parameters [Formula: see text] and [Formula: see text] depend on the change in average trait value and therefore cannot predict that change. In this formulation, which has been called "exact and general" by its proponents, Hamilton's rule can "predict" only the data that have already been given.

Kin selection promotes female productivity and cooperation between the sexes

Hamilton's theory of kin selection explains the evolution of costly traits that benefit other individuals by highlighting the fact that passing genes to offspring is not the only way of increasing the representation of those genes in subsequent generations: Genes are also shared with other classes of relatives. Consequently, any heritable trait that affects fitness of relatives should respond to kin selection. We tested this core prediction of kin selection theory by letting bulb mites (Rhizoglyphus robini) evolve in populations structured into groups of relatives or nonrelatives during the reproductive phase of the life cycle. In accordance with predictions derived from kin selection theory, we found that evolution in groups of relatives resulted in increased female reproductive output. This increase at least partly results from the evolution of male traits that elevate their partners' fecundity. Our results highlight the power and universality of kin selection.

What's wrong with evolutionary biology?

There have been periodic claims that evolutionary biology needs urgent reform, and this article tries to account for the volume and persistence of this discontent. It is argued that a few inescapable properties of the field make it prone to criticisms of predictable kinds, whether or not the criticisms have any merit. For example, the variety of living things and the complexity of evolution make it easy to generate data that seem revolutionary (e.g. exceptions to well-established generalizations, or neglected factors in evolution), and lead to disappointment with existing explanatory frameworks (with their high levels of abstraction, and limited predictive power). It is then argued that special discontent stems from misunderstandings and dislike of one well-known but atypical research programme: the study of adaptive function, in the tradition of behavioural ecology. To achieve its goals, this research needs distinct tools, often including imaginary agency, and a partial description of the evolutionary process. This invites mistaken charges of narrowness and oversimplification (which come, not least, from researchers in other subfields), and these chime with anxieties about human agency and overall purpose. The article ends by discussing several ways in which calls to reform evolutionary biology actively hinder progress in the field.

Neo-Darwinists and Neo-Aristotelians: how to talk about natural purpose

This paper examines the points of disagreement between Neo-Darwinian and recent Neo-Aristotelian discussions of the status of purposive language in biology. I discuss recent Neo-Darwinian "evolutionary" treatments and distinguish three ways to deal with the philosophical status of teleological language of purpose: teleological error theory, methodological teleology, and Darwinian teleological realism. I then show how "non-evolutionary" Neo-Aristotelian approaches in the work of Michael Thompson and Philippa Foot differ from these by offering a view of purposiveness grounded in life-cycle patterns, rather than in long-term evolutionary processes or natural selection. Finally, I argue that the crucial difference between Neo-Darwinian and Neo-Aristotelian approaches regards the question of whether or not reproduction deserves the status of an "ultimate" aim of organisms. I offer reasons to reject the concept of an "ultimate" aim in evolutionary biology and to reject the notion that reproduction serves a purpose. I argue that evolutionary biology is not in the position to determine what the "ultimate" explanation of natural purpose is.

Unified and simple understanding for the evolution of conditional cooperators

Cooperation is a mysterious phenomenon which is observed in this world. The potential explanation is a repeated interaction. Cooperation is established if individuals meet the same opponent repeatedly and cooperate conditionally. Previous studies have analyzed the following four as characters of conditional cooperators mainly. (i) niceness (i.e., when a conditional cooperator meets an opponent in the first place, he (she) cooperates or defects), (ii) optimism (when a conditional cooperator meets an opponent in the past, but he (she) did not get access to information about the opponent's behavior in the previous round, he (she) cooperates or defects), (iii) generosity (even when a conditional cooperator knows that an opponent defected in the previous round, he (she) cooperates or defects) and (iv) retaliation (a conditional cooperator cooperates with a cooperator with a higher probability than with a defector). Previous works deal with these four characters mainly. However, these four characters basically have been regarded as distinct topics and unified understanding has not been done fully. Here we, by studying the iterated prisoner's dilemma game (in particular, additive games) and using evolutionarily stable strategy (ESS) analysis, find that when retaliation is large, the condition under which conditional cooperators are stable against the invasion by an unconditional defector is loose, while none of "niceness", "optimism", and "generosity" makes impact on the condition under which conditional cooperators are stable against an invasion by an unconditional defector. Furthermore, we show that we can understand "niceness", "optimism", and "generosity" uniformly by using one parameter indicating "cooperative", and when the conditional cooperators have large "retaliation" enough to resist an invasion by an unconditional defector, natural selection favors more "cooperative" conditional cooperators to invade the resident conditional cooperative strategy. Moreover, we show that these results are robust even when taking the existence of mistakes in behavior into consideration.

Multilevel Selection in Kin Selection Language

Few issues have raised more debate among evolutionary biologists than kin selection (KS) versus multilevel selection (MLS). They are formally equivalent, but use different-looking mathematical approaches, and are not causally equivalent: for a given problem KS can be a more suitable causal explanation than MLS, and vice versa. Methods for analyzing a given model from both viewpoints would therefore be valuable. I argue that there is often an easy way to achieve this: MLS can be written using the components of KS. This applies to the very general regression approach as well as to the practical evolutionarily stable strategy (ESS) maximization approach, and can hence be used to analyze many common ESS models from a multilevel perspective. I demonstrate this with example models of gamete competition and limitation.

Hamilton's rule

This paper reviews and addresses a variety of issues relating to inclusive fitness. The main question is: are there limits to the generality of inclusive fitness, and if so, what are the perimeters of the domain within which inclusive fitness works? This question is addressed using two well-known tools from evolutionary theory: the replicator dynamics, and adaptive dynamics. Both are combined with population structure. How generally Hamilton's rule applies depends on how costs and benefits are defined. We therefore consider costs and benefits following from Karlin and Matessi's (1983) "counterfactual method", and costs and benefits as defined by the "regression method" (Gardner et al., 2011). With the latter definition of costs and benefits, Hamilton's rule always indicates the direction of selection correctly, and with the former it does not. How these two definitions can meaningfully be interpreted is also discussed. We also consider cases where the qualitative claim that relatedness fosters cooperation holds, even if Hamilton's rule as a quantitative prediction does not. We furthermore find out what the relation is between Hamilton's rule and Fisher's Fundamental Theorem of Natural Selection. We also consider cancellation effects - which is the most important deepening of our understanding of when altruism is selected for. Finally we also explore the remarkable (im)possibilities for empirical testing with either definition of costs and benefits in Hamilton's rule.

Extended inclusive fitness theory: synergy and assortment drives the evolutionary dynamics in biology and economics

W.D. Hamilton's Inclusive Fitness Theory explains the conditions that favor the emergence and maintenance of social cooperation. Today we know that these include direct and indirect benefits an agent obtains by its actions, and through interactions with kin and with genetically unrelated individuals. That is, in addition to kin-selection, assortation or homophily, and social synergies drive the evolution of cooperation. An Extended Inclusive Fitness Theory (EIFT) synthesizes the natural selection forces acting on biological evolution and on human economic interactions by assuming that natural selection driven by inclusive fitness produces agents with utility functions that exploit assortation and synergistic opportunities. This formulation allows to estimate sustainable cost/benefit threshold ratios of cooperation among organisms and/or economic agents, using existent analytical tools, illuminating our understanding of the dynamic nature of society, the evolution of cooperation among kin and non-kin, inter-specific cooperation, co-evolution, symbioses, division of labor and social synergies. EIFT helps to promote an interdisciplinary cross fertilization of the understanding of synergy by, for example, allowing to describe the role for division of labor in the emergence of social synergies, providing an integrated framework for the study of both, biological evolution of social behavior and economic market dynamics. Another example is a bio-economic understanding of the motivations of terrorists, which identifies different forms of terrorism.

Kin and multilevel selection in social evolution: a never-ending controversy?

Kin selection and multilevel selection are two major frameworks in evolutionary biology that aim at explaining the evolution of social behaviors. However, the relationship between these two theories has been plagued by controversy for almost half a century and debates about their relevance and usefulness in explaining social evolution seem to rekindle at regular intervals. Here, we first provide a concise introduction into the kin selection and multilevel selection theories and shed light onto the roots of the controversy surrounding them. We then review two major aspects of the current debate: the presumed formal equivalency of the two theories and the question whether group selection can lead to group adaptation. We conclude by arguing that the two theories can offer complementary approaches to the study of social evolution: kin selection approaches usually focus on the identification of optimal phenotypes and thus on the endresult of a selection process, whereas multilevel selection approaches focus on the ongoing selection process itself. The two theories thus provide different perspectives that might be fruitfully combined to promote our understanding of the evolution in group-structured populations.

Evolution of worker policing

Workers in insect societies are sometimes observed to kill male eggs of other workers, a phenomenon known as worker policing. We perform a mathematical analysis of the evolutionary dynamics of policing. We investigate the selective forces behind policing for both dominant and recessive mutations for different numbers of matings of the queen. The traditional, relatedness-based argument suggests that policing evolves if the queen mates with more than two males, but does not evolve if the queen mates with a single male. We derive precise conditions for the invasion and stability of policing alleles. We find that the relatedness-based argument is not robust with respect to small changes in colony efficiency caused by policing. We also calculate evolutionarily singular strategies and determine when they are evolutionarily stable. We use a population genetics approach that applies to dominant or recessive mutations of any effect size.

Hamilton׳s Rule in finite populations with synergistic interactions

Much debate has appeared in the literature over the generality of the inclusive fitness approach in the modeling of evolutionary behavior. Here I focus on the capacity of the inclusive fitness approach to effectively handle non-additive or synergistic interactions. I work with a binary interaction with the matrix game [abcd] and I restrict attention to transitive (homogeneous) populations with weak selective effects. First of all I observe that the construction of "higher-order" relatedness coefficients permits these synergistic interactions to be analyzed with an inclusive fitness analysis. These coefficients are an immediate generalization of Hamilton׳s original coefficient and can be calculated with exactly the same type of recursive equations. Secondly I observe that for models in which the population is not too large and local genetic renewal is rare (e,g, rare mutation), these higher order coefficients are not needed even with non-additive interactions; in fact the synergistic interaction is entirely equivalent to a closely-related additive one. The overall conclusion is that in the study of synergistic binary social interactions (2-player games) in a finite homogeneous population with weak selection and rare genetic renewal, a standard inclusive-fitness analysis is able to predict the direction of allele-frequency change. I apply this result to analyze a recent model of Allen and Nowak (2015).

The causal meaning of Hamilton's rule

Hamilton's original derivation of his rule for the spread of an altruistic gene (rb>c) assumed additivity of costs and benefits. Recently, it has been argued that an exact version of the rule holds under non-additive pay-offs, so long as the cost and benefit terms are suitably defined, as partial regression coefficients. However, critics have questioned both the biological significance and the causal meaning of the resulting rule. This paper examines the causal meaning of the generalized Hamilton's rule in a simple model, by computing the effect of a hypothetical experiment to assess the cost of a social action and comparing it to the partial regression definition. The two do not agree. A possible way of salvaging the causal meaning of Hamilton's rule is explored, by appeal to R. A. Fisher's 'average effect of a gene substitution'.