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Joshua B. Plotkin

Publications and source records attributed to Joshua B. Plotkin.

At least 37 records · Page 2Linked to original sources

Evolution of social norms for moral judgment

Reputations provide a powerful mechanism to sustain cooperation, as individuals cooperate with those of good social standing. But how should moral reputations be updated as we observe social behavior, and when will a population converge on a common norm of moral assessment? Here we develop a mathematical model of cooperation conditioned on reputations, for a population that is stratified into groups. Each group may subscribe to a different social norm for assessing reputations, and so norms compete as individuals choose to move from one group to another. We show that a group initially comprising a minority of the population may nonetheless overtake the entire population--especially if it adopts the Stern Judging norm, which assigns a bad reputation to individuals who cooperate with those of bad standing. When individuals do not change group membership, stratifying reputation information into groups tends to destabilize cooperation, unless individuals are strongly insular and favor in-group social interactions. We discuss the implications of our results for the structure of information flow in a population and the evolution of social norms of moral judgment.

q-bio.PE↗

Optimality of intercellular signaling: direct transport versus diffusion

Intercellular signaling has an important role in organism development, but not all communication occurs using the same mechanism. Here, we analyze the energy efficiency of intercellular signaling by two canonical mechanisms: diffusion of signaling molecules and direct transport mediated by signaling cellular protrusions. We show that efficient contact formation for direct transport can be established by an optimal rate of projecting protrusions, which depends on the availability of information about the location of the target cell. The optimal projection rate also depends on how signaling molecules are transported along the protrusion, in particular the ratio of the energy cost for contact formation and molecule synthesis. Also, we compare the efficiency of the two signaling mechanisms, under various model parameters. We find that the direct transport is favored over the diffusion when transporting a large amount of signaling molecules. There is a critical number of signaling molecules at which the efficiency of the two mechanisms are the same. The critical number is small when the distance between cells is far, which helps explain why protrusion-based mechanisms are observed in long-range cellular communications.

q-bio.QM↗

The arrow of evolution when the offspring variance is large

The concept of fitness is central to evolution, but it quantifies only the expected number of offspring an individual will produce. The actual number of offspring is also subject to noise, arising from environmental or demographic stochasticity. In nature, individuals who are more fecund tend to have greater variance in their offspring number -- sometimes far greater than the Poisson variance assumed in classical models of population genetics. Here, we develop a model for the evolution of two types reproducing in a population of non-constant size. The frequency-dependent fitness of each type is determined by pairwise interactions in a prisoner's dilemma game, but the offspring number is subject to an exogenously controlled variance that may depend upon the mean. Whereas defectors are preferred by natural selection in classical well-mixed populations, since they always have greater fitness than cooperators, we show that large offspring variance can reverse the direction of evolution and favor cooperation. Reproductive over-dispersion produces qualitatively new dynamics for other types of social interactions, as well, which cannot arise in populations with a fixed size or Poisson offspring variance.

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Evolutionary Dynamics Within and Among Competing Groups

Biological and social systems are structured at multiple scales, and the incentives of individuals who interact in a group may diverge from the collective incentive of the group as a whole. Mechanisms to resolve this tension are responsible for profound transitions in evolutionary history, including the origin of cellular life, multi-cellular life, and even societies. Here we synthesize a growing literature that extends evolutionary game theory to describe multilevel evolutionary dynamics, using nested birth-death processes and partial differential equations to model natural selection acting on competition within and among groups of individuals. We apply this theory to analyze how mechanisms known to promote cooperation within a single group -- including assortment, reciprocity, and population structure -- alter evolutionary outcomes in the presence of competition among groups. We find that population structures most conducive to cooperation in multi-scale systems may differ from those most conducive within a single group. Likewise, for competitive interactions with a continuous range of strategies we find that among-group selection may fail to produce socially optimal outcomes, but it can nonetheless produce second-best solutions that balance individual incentives to defect with the collective incentives for cooperation. We conclude by describing the broad applicability of multi-scale evolutionary models to problems ranging from the production of diffusible metabolites in microbes to the management of common-pool resources in human societies.

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The evolution of forecasting for decision making in dynamic environments

Global change is reshaping ecosystems and societies. Strategic choices that were best yesterday may be sub-optimal tomorrow; and environmental conditions that were once taken for granted may soon cease to exist. In this setting, how people choose behavioral strategies has important consequences for environmental dynamics. Economic and evolutionary theories make similar predictions for strategic behavior in a static environment, even though one approach assumes perfect rationality and the other assumes no cognition whatsoever; but predictions differ in a dynamic environment. Here we explore a middle ground between economic rationality and evolutionary myopia. Starting from a population of myopic agents, we study the emergence of a new type that forms environmental forecasts when making strategic decisions. We show that forecasting types can have an advantage in changing environments, even when the act of forecasting is costly. Forecasting types can invade but not overtake the population, producing a stable coexistence with myopic types. Moreover, forecasters provide a public good by reducing the amplitude of environmental oscillations and increasing mean payoff to forecasting and myopic types alike. We interpret our results for understanding the evolution of different modes of decision-making. And we discuss implications for the management of environmental systems of great societal importance.

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Selfish optimization and collective learning in populations

A selfish learner seeks to maximize their own success, disregarding others. When success is measured as payoff in a game played against another learner, mutual selfishness typically fails to produce the optimal outcome for a pair of individuals. However, learners often operate in populations, and each learner may have a limited duration of interaction with any other individual. Here, we compare selfish learning in stable pairs to selfish learning with stochastic encounters in a population. We study gradient-based optimization in repeated games like the prisoner's dilemma, which feature multiple Nash equilibria, many of which are suboptimal. We find that myopic, selfish learning, when distributed in a population via ephemeral encounters, can reverse the dynamics that occur in stable pairs. In particular, when there is flexibility in partner choice, selfish learning in large populations can produce optimal payoffs in repeated social dilemmas. This result holds for the entire population, not just for a small subset of individuals. Furthermore, as the population size grows, the timescale to reach the optimal population payoff remains finite in the number of learning steps per individual. While it is not universally true that interacting with many partners in a population improves outcomes, this form of collective learning achieves optimality for several important classes of social dilemmas. We conclude that naïve learning can be surprisingly effective in populations of individuals navigating conflicts of interest.

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Mito-nuclear selection induces a trade-off between species ecological dominance and evolutionary lifespan

Mitochondrial and nuclear genomes must be co-adapted to ensure proper cellular respiration and energy production. Mito-nuclear incompatibility reduces individual fitness and induces hybrid infertility, suggesting a possible role in reproductive barriers and speciation. Here we develop a birth-death model for evolution in spatially extended populations under selection for mito-nuclear co-adaptation. Mating is constrained by physical and genetic proximity, and offspring inherit nuclear genomes from both parents, with recombination. The model predicts macroscopic patterns including a community's long-term species diversity, its species abundance distribution, speciation and extinction rates, as well as intra- and inter-specific genetic variation. We explore how these long-term outcomes depend upon the microscopic parameters of reproduction: individual fitness governed by mito-nuclear compatibility, constraints on mating compatibility, and ecological carrying capacity. We find that strong selection for mito-nuclear compatibility reduces the equilibrium number of species after a radiation, increases the species' abundances, while simultaneously increasing both speciation and extinction rates. The negative correlation between species diversity and diversification rates in our model agrees with the broad empirical pattern of lower species diversity and higher speciation/extinction rates in temperate regions, compared to the tropics. We therefore suggest that these empirical patterns may be caused in part by latitudinal variation in metabolic demands, and corresponding variation in selection on mito-nuclear function.

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Evolution of prosocial behavior in multilayer populations

Human societies include diverse social relationships. Friends, family, business colleagues, and online contacts can all contribute to one's social life. Individuals may behave differently in different domains, but success in one domain may engender success in another. Here, we study this problem using multilayer networks to model multiple domains of social interactions, in which individuals experience different environments and may express different behaviors. We provide a mathematical analysis and find that coupling between layers tends to promote prosocial behavior. Even if prosociality is disfavored in each layer alone, multilayer coupling can promote its proliferation in all layers simultaneously. We apply this analysis to six real-world multilayer networks, ranging from the socio-emotional and professional relationships in a Zambian community, to the online and offline relationships within an academic University. We discuss the implications of our results, which suggest that small modifications to interactions in one domain may catalyze prosociality in a different domain.

physics.soc-ph↗

Measuring frequency-dependent selection in culture

Cultural traits such as words, names, decorative styles, and technical standards often assume arbitrary values and are thought to evolve neutrally. But neutral evolution cannot explain why some traits come and go in cycles of popularity while others become entrenched. Here we study frequency-dependent selection (FDS)--where a trait's tendency to be copied depends on its current frequency regardless of the trait value itself. We develop a maximum-likelihood method to infer the precise form of FDS from time series of trait abundance, and we apply the method to data on baby names and pet dog breeds over the last century. We find that the most common names tend to decline by 2%-6% per yr on average; whereas rare names--1 in 10,000 births--tend to increase by 1%-3% per yr. This specific form of negative FDS explains patterns of diversity and replicates across the United States, France, Norway and the Netherlands, despite cultural, linguistic and demographic variation. We infer a fixed fitness offset between male and female names that implies different rates of innovation. We also find a strong selective advantage for biblical names in every frequency class, which explains their predominance among the most common names. In purebred dog registrations we infer a form of negative FDS that is consistent with a preference for novelty, in which each year's newest breeds outgrow the previous by about 1%/yr, which also recapitulates boom-bust cycles in dog fanciers. Finally, we define the concept of effective frequency-dependent selection, which enables a meaningful interpretation of inferred FDS even for complex mechanisms of evolution. Our analysis generalizes neutral evolution to incorporate pressures of conformity and anti-conformity as fundamental forces in social evolution, and our inference procedure provides a quantitative account of how these forces operate within and across cultures.

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Inequality, Identity, and Partisanship: How redistribution can stem the tide of mass polarization

The form of political polarization where citizens develop strongly negative attitudes towards out-party policies and members has become increasingly prominent across many democracies. Economic hardship and social inequality, as well as inter-group and racial conflict, have been identified as important contributing factors to this phenomenon known as "affective polarization." Such partisan animosities are exacerbated when these interests and identities become aligned with existing party cleavages. In this paper we use a model of cultural evolution to study how these forces combine to generate and maintain affective political polarization. We show that economic events can drive both affective polarization and sorting of group identities along party lines, which in turn can magnify the effects of underlying inequality between those groups. But on a more optimistic note, we show that sufficiently high levels of wealth redistribution through the provision of public goods can counteract this feedback and limit the rise of polarization. We test some of our key theoretical predictions using survey data on inter-group polarization, sorting of racial groups and affective polarization in the United States over the past 50 years.

econ.GN↗

Optimal, near-optimal, and robust epidemic control

In the absence of drugs and vaccines, policymakers use non-pharmaceutical interventions such as social distancing to decrease rates of disease-causing contact, with the aim of reducing or delaying the epidemic peak. These measures carry social and economic costs, so societies may be unable to maintain them for more than a short period of time. Intervention policy design often relies on numerical simulations of epidemic models, but comparing policies and assessing their robustness demands clear principles that apply across strategies. Here we derive the theoretically optimal strategy for using a time-limited intervention to reduce the peak prevalence of a novel disease in the classic Susceptible-Infectious-Recovered epidemic model. We show that broad classes of easier-to-implement strategies can perform nearly as well as the theoretically optimal strategy. But neither the optimal strategy nor any of these near-optimal strategies is robust to implementation error: small errors in timing the intervention produce large increases in peak prevalence. Our results reveal fundamental principles of non-pharmaceutical disease control and expose their potential fragility. For robust control, an intervention must be strong, early, and ideally sustained.

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The natural selection of good science

Scientists in some fields are concerned that many, or even most, published results are false. A high rate of false positives might arise accidentally, from shoddy research practices. Or it might be the inevitable result of institutional incentives that reward publication irrespective of veracity. Recent models and discussion of scientific culture predict selection for false-positive publications, as research labs that publish more positive findings out-compete more diligent labs. There is widespread debate about how scientific practices should be modified to avoid this degeneration. Some analyses suggest that "bad science" will persist even when labs are incentivized to undertake replication studies, and penalized for publications that later fail to replicate. Here we develop a framework for modelling the cultural evolution of research practices that allows labs to expend effort on theory - enabling them, at a cost, to focus on hypotheses that are more likely to be true on theoretical grounds. Theory restores the evolution of high effort in laboratory practice, and it suppresses false-positive publications to a technical minimum, even in the absence of replication. In fact, the mere ability choose between two sets of hypotheses - one with greater chance of being correct than the other - promotes better science than can be achieved by having effortless access to the better set of hypotheses. Combining theory and replication can have a synergistic effect in promoting good scientific methodology and reducing the rate of false-positive publications. Based on our analysis we propose four simple rules to promote good science in the face of pressure to publish.

physics.soc-ph↗

Evolutionary forces in language change

Languages and genes are both transmitted from generation to generation, with opportunity for differential reproduction and survivorship of forms. Here we apply a rigorous inference framework, drawn from population genetics, to distinguish between two broad mechanisms of language change: drift and selection. Drift is change that results from stochasticity in transmission and it may occur in the absence of any intrinsic difference between linguistic forms; whereas selection is truly an evolutionary force arising from intrinsic differences -- for example, when one form is preferred by members of the population. Using large corpora of parsed texts spanning the 12th century to the 21st century, we analyze three examples of grammatical changes in English: the regularization of past-tense verbs, the rise of the periphrastic `do', and syntactic variation in verbal negation. We show that we can reject stochastic drift in favor of a selective force driving some of these language changes, but not others. The strength of drift depends on a word's frequency, and so drift provides an alternative explanation for why some words are more prone to change than others. Our results suggest an important role for stochasticity in language change, and they provide a null model against which selective theories of language evolution must be compared.

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Host-pathogen coevolution and the emergence of broadly neutralizing antibodies in chronic infections

The vertebrate adaptive immune system provides a flexible and diverse set of molecules to neutralize pathogens. Yet, viruses such as HIV can cause chronic infections by evolving as quickly as the adaptive immune system, forming an evolutionary arms race. Here we introduce a mathematical framework to study the coevolutionary dynamics of antibodies with antigens within a host. We focus on changes in the binding interactions between the antibody and antigen populations, which result from the underlying stochastic evolution of genotype frequencies driven by mutation, selection, and drift. We identify the critical viral and immune parameters that determine the distribution of antibody-antigen binding affinities. We also identify definitive signatures of coevolution that measure the reciprocal response between antibodies and viruses, and we introduce experimentally measurable quantities that quantify the extent of adaptation during continual coevolution of the two opposing populations. Using this analytical framework, we infer rates of viral and immune adaptation based on time-shifted neutralization assays in two HIV-infected patients. Finally, we analyze competition between clonal lineages of antibodies and characterize the fate of a given lineage in terms of the state of the antibody and viral populations. In particular, we derive the conditions that favor the emergence of broadly neutralizing antibodies, which may be useful in designing a vaccine against HIV.

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Evolutionary consequences of behavioral diversity

Iterated games provide a framework to describe social interactions among groups of individuals. Recent work stimulated by the discovery of "zero-determinant" strategies has rapidly expanded our ability to analyze such interactions. This body of work has primarily focused on games in which players face a simple binary choice, to "cooperate" or "defect". Real individuals, however, often exhibit behavioral diversity, varying their input to a social interaction both qualitatively and quantitatively. Here we explore how access to a greater diversity of behavioral choices impacts the evolution of social dynamics in finite populations. We show that, in public goods games, some two-choice strategies can nonetheless resist invasion by all possible multi-choice invaders, even while engaging in relatively little punishment. We also show that access to greater behavioral choice results in more "rugged " fitness landscapes, with populations able to stabilize cooperation at multiple levels of investment, such that choice facilitates cooperation when returns on investments are low, but hinders cooperation when returns on investments are high. Finally, we analyze iterated rock-paper-scissors games, whose non-transitive payoff structure means unilateral control is difficult and zero-determinant strategies do not exist in general. Despite this, we find that a large portion of multi-choice strategies can invade and resist invasion by strategies that lack behavioral diversity -- so that even well-mixed populations will tend to evolve behavioral diversity.

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Integrating Theory and Experiment to Explain the Breakdown of Population Synchrony in a Complex Microbial Community

We consider the extension of the `Moran effect', where correlated noise generates synchrony between isolated single species populations, to the study of synchrony between populations embedded in multi-species communities. In laboratory experiments on complex microbial communities, comprising both predators (protozoa) and prey (bacteria), we observe synchrony in abundances between isolated replicates. A breakdown in synchrony occurs for both predator and prey as the reactor dilution rate increases, which corresponds to both an increased rate of input of external resources and an increased effective mortality though washout. The breakdown is more rapid, however, for the lower trophic level. We can explain this phenomenon using a mathematical framework for determining synchrony between populations in multi-species communities at equilibrium. We assume that there are multiple sources of environmental noise with different degrees of correlation that affect the individual species population dynamics differently. The deterministic dynamics can then influence the degree of synchrony between species in different communities. In the case of a stable equilibrium community synchrony is controlled by the eigenvalue with smallest negative real part. Intuitively fluctuations are minimally damped in this direction. We show that the experimental observations are consistent with this framework but only for multiplicative noise.

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Small games and long memories promote cooperation

Complex social behaviors lie at the heart of many of the challenges facing evolutionary biology, sociology, economics, and beyond. For evolutionary biologists in particular the question is often how such behaviors can arise \textit{de novo} in a simple evolving system. How can group behaviors such as collective action, or decision making that accounts for memories of past experience, emerge and persist? Evolutionary game theory provides a framework for formalizing these questions and admitting them to rigorous study. Here we develop such a framework to study the evolution of sustained collective action in multi-player public-goods games, in which players have arbitrarily long memories of prior rounds of play and can react to their experience in an arbitrary way. To study this problem we construct a coordinate system for memory-$m$ strategies in iterated $n$-player games that permits us to characterize all the cooperative strategies that resist invasion by any mutant strategy, and thus stabilize cooperative behavior. We show that while larger games inevitably make cooperation harder to evolve, there nevertheless always exists a positive volume of strategies that stabilize cooperation provided the population size is large enough. We also show that, when games are small, longer-memory strategies make cooperation easier to evolve, by increasing the number of ways to stabilize cooperation. Finally we explore the co-evolution of behavior and memory capacity, and we find that longer-memory strategies tend to evolve in small games, which in turn drives the evolution of cooperation even when the benefits for cooperation are low.

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The diversity of evolutionary dynamics on epistatic versus non-epistatic fitness landscapes

The class of epistatic fitness landscapes is much more diverse than the class of non-epistatic landscapes, and so it stands to reason that there exist dynamical phenomena that can only be realized in the presence of epistasis. Here, we compare evolutionary dynamics on all finite epistatic landscapes versus all finite non-epistatic landscapes, under weak mutation. We first analyze the mean fitness trajectory - that is, the time course of the expected fitness of a population. We show that for any epistatic fitness landscape and starting genotype, there always exists a non-epistatic fitness landscape and starting genotype that produces the exact same mean fitness trajectory. Thus, surprisingly, the space of mean fitness trajectories that can be realized by epistatic landscapes is no more diverse than the space of mean fitness trajectories that can be realized by non-epistatic landscapes. On the other hand, we show that epistatic fitness landscapes can produce dynamics in the time-evolution of the variance in fitness across replicate populations and in the time-evolution of the expected number of substitutions that cannot be produced by any non-epistatic landscape. These results on identifiability have implications for efforts to infer epistasis from the types of data often measured in experimental populations.

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