The genetical evolution of social behaviour. I
Abstract
A genetical mathematical model is described which allows for interactions between relatives on one another's fitness. Making use of Wright's Coefficient of Relationship as the measure of the proportion of replica genes in a relative, a quantity is found which incorporates the maximizing property of Darwinian fitness. This quantity is named “inclusive fitness”. Species following the model should tend to evolve behaviour such that each organism appears to be attempting to maximize its inclusive fitness. This implies a limited restraint on selfish competitive behaviour and possibility of limited self-sacrifices.
Special cases of the model are used to show (a) that selection in the social situations newly covered tends to be slower than classical selection, (b) how in populations of rather non-dispersive organisms the model may apply to genes affecting dispersion, and (c) how it may apply approximately to competition between relatives, for example, within sibships. Some artificialities of the model are discussed.
References (9)
- J.B.S. Haldane
Trans. Camb. phil. Soc
(1923) - J.B.S. Haldane et al.
J. Genet
(1962) - O. Kempthorne
An Introduction to Genetical Statistics
(1957) - J.F.C. Kingman
Quart. J. Math
(1961)
Cited by (10124)
Homophily and the evolution of cooperation in the Volunteer's Dilemma: A computational study on dynamic graphs
2024, Social NetworksWe study the evolution of cooperation in the Volunteer’s Dilemma using the stochastic Moran process on dynamic graphs, which models a birth–death dynamic on structured finite populations. According to the Moran process, in each period one player is selected to reproduce, where the probability of being selected is proportional to payoff-related fitness levels, and a copy of this player is substituted for a player who is randomly selected to die. The interaction of the players is embedded in a network structure which determines the overlapping groups within which the Volunteer’s Dilemma is played. Networks vary to the extent they exhibit homophily, i.e., they vary in the extent to which the interacting groups primarily encompass either cooperators or defectors instead of a mix of both types of players. By varying the degree of homophily in the network, we thus can study the question if and to what extent assortment of strategies favors the evolution of cooperation in the Volunteer’s Dilemma. Our results show that a surprisingly high extent of homophily is required to ensure the evolution of cooperation in the Volunteer’s Dilemma when modeled as a stochastic process in pure strategies. Other parameters, such as selection pressure or the number of initial cooperators, have a comparatively small effect on the fixation of cooperation in the population.
Depression and fitness: the Portuguese-Brazilian version of the evolutionary fitness scale
2024, Personality and Individual DifferencesThe concept of fitness is crucial to the study of human behavior from an evolutionary perspective. A proposed causal link between fitness-related problems and depression has been suggested. Measuring fitness in humans requires exploring behavioral components, such as mating, parental investment, social capital, and health-oriented actions. This study navigates the relationship between depression and fitness, exploring the validity of the Evolutionary Fitness Scale in the Brazilian context. A sample of 804 Brazilian participants completed the EFS online. Exploratory Factor Analysis suggested a 4-factor model. Internal consistency was good (partner α = 0.87; health α = 0.80; social capital α = 0.85; offspring α = 0.74). The EFS differentiated between nondepressed and depressed individuals based on PHQ-9 scores, with a large effect size for health (d = 0.93) and social capital (d = 0.89) dimensions, and a medium effect for partner (d = 0.40). However, the offspring subscale did not discriminate between depressed and nondepressed. In summary, we demonstrated that the EFS represents an efficient, reliable, and valid measure for assessing self-reported data on human fitness.
Evolution of delayed dispersal with group size effect and population dynamics
2024, Theoretical Population BiologyIndividuals delay natal dispersal for many reasons. There may be no place to disperse to; immediate dispersal or reproduction may be too costly; immediate dispersal may mean that the individual and their relatives miss the benefits of group living. Understanding the factors that lead to the evolution of delayed dispersal is important because delayed dispersal sets the stage for complex social groups and social behavior. Here, we study the evolution of delayed dispersal when the quality of the local environment is improved by greater numbers of individuals (, safety in numbers). We assume that individuals who delay natal dispersal also expect to delay personal reproduction. In addition, we assume that improved environmental quality benefits manifest as changes to fecundity and survival. We are interested in how do the changes in these life-history features affect delayed dispersal. We use a model that ties evolution to population dynamics. We also aim to understand the relationship between levels of delayed dispersal and the probability of establishing as an independent breeder (a population-level feature) in response to changes in life-history details. Our model emphasizes kin selection and considers a sexual organism, which allows us to study parent–offspring conflict over delayed dispersal. At evolutionary equilibrium, fecundity and survival benefits of group size or quality promote higher levels of delayed dispersal over a larger set of life histories with one exception. The exception is for benefits of increased group size or quality reaped by the individuals who delay dispersal. There, the increased benefit does not change the life histories supporting delay dispersal. Next, in contrast to previous predictions, we find that a low probability of establishing in a new location is not always associated with a higher incidence of delayed dispersal. Finally, we find that increased personal benefits of delayed dispersal exacerbate the conflict between parents and their offspring. We discuss our findings in relation to previous theoretical and empirical work, especially work related to cooperative breeding.
Adaptive rock-paper-scissors game enhances eco-evolutionary performance at cost of dynamic stability
2024, Applied Mathematics and ComputationThe rock-paper-scissors (RPS) game is a classic model for exploring the performance of how multiple strategies interact and evolve over time. The classic RPS game assumes a fixed benefit and cost for each strategy against another one when two players meet, while its evolutionary game considers the frequency dynamics of the three strategies with each's fitness influenced by its net payoff. This may not reflect the complexity of real-world scenarios as strategies can co-adapt with each other. We introduce an adaptive RPS game that captures the dynamics of strategy densities with trait-mediated payoffs, and the adaptive dynamics of coevolving traits via incremental mutations leading to adaptively evolving payoffs. Results show that the adaptive RPS game approaches a steady state of strategy density, if any, faster than the evolutionary RPS game. The stable coexistence of all strategies in the evolutionary game can be easily destabilized in the adaptive game. Strategies that are allowed to adaptively change their traits also performed better and achieved greater strategy densities than those fixed strategies in the adaptive game. The coevolving strategies in the adaptive RPS game exhibit complex and diverse attractors in the trait space, sensitive to both initial conditions and model parameters, but exhibiting positive payoffs with greater benefits than costs. These findings highlight how adaptive games enhance strategy performance by sacrificing eco-evolutionary dynamic stability.
Evolution of spite versus evolution of altruism through a disbandment mechanism
2024, Theoretical Population BiologyAltruism and spite are costly to the actor, making their evolution unlikely without specific mechanisms. Nonetheless, both altruistic and spiteful behaviors are present in individuals, which suggests the existence of an underlying mechanism that drives their evolution. If altruistic individuals are more likely to be recipients of altruism than non-altruistic individuals, then altruism can be favored by natural selection. Similarly, if spiteful individuals are less likely to be recipients of spite than non-spiteful individuals, then spite can be favored by natural selection. Spite is altruism's evil twin, ugly sister of altruism, or a shady relative of altruism. In some mechanisms, such as repeated interactions, if altruism is favored by natural selection, then spite is also favored by natural selection. However, there has been limited investigation into whether both behaviors evolve to the same extent. In this study, we focus on the mechanism by which individuals choose to keep or stop the interaction according to the opponent's behavior. Using the evolutionary game theory, we investigate the evolution of altruism and spite under this mechanism. Our model revealed that the evolution of spite is less likely than the evolution of altruism.
On aims and methods of collective animal behaviour
2024, Animal BehaviourCollective animal behaviour is a subfield of behavioural ecology, making extensive use of its tools of observation, experimental manipulation and model building. However, a fundamental behavioural ecology approach, the application of optimality theory, has been comparatively neglected in collective animal behaviour. This article seeks to address this imbalance, by outlining an evolutionary theory framework for the discipline. The application of optimality theory to collective animal behaviour requires a number of questions to be addressed. First, what is the correct quantity to optimize? This can be achieved via a combination of considering the organisms' life history, alongside tools such as statistical decision theory and stochastic dynamic programming. Second, what mechanism is appropriate for optimal behaviour? This involves ensuring that models are self-consistent rather than assuming parameter values. Third, at what level of selection does optimization act? Selection acts on the individual except in very particular circumstances, yet collective animal behaviour phenomena are group level, thus introducing a risk of confusing at what level adaptive properties emerge. This article presents examples under each of the three questions, as well as discussing mismatches between theory and observation. In doing so, it is hoped that collective animal behaviour fully inherits the tools and philosophy of its parent discipline of behavioural ecology.