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Many theoretical models have been formulated to better understand the coevolutionary patterns that emerge from antagonistic interactions. These models usually assume that the attacks by the exploiters are random, so the effect of victim selection by exploiters on coevolutionary patterns remains unexplored. Here we analytically studied the payoff for predators and prey under coevolution assuming that every individual predator can attack only a small number of prey any given time, considering two scenarios: (i) predation occurs at random; (ii) predators select prey according to phenotype matching. We also develop an individual based model to verify the robustness of our analytical prediction. We show that both scenarios result in well known similar coevolutionary patterns if population sizes are sufficiently high: symmetrical coevolutionary branching and symmetrical coevolutionary cycling (Red Queen dynamics). However, for small population sizes, prey selection can cause unexpected coevolutionary patterns. One is the breaking of symmetry of the coevolutionary pattern, where the phenotypes evolve towards one of two evolutionarily stable patterns. As population size increases, the phenotypes oscillate between these two values in a novel form of Red Queen dynamics, the episodic reversal between the two stable patterns. Thus, prey selection causes prey phenotypes to evolve towards more extreme values, which reduces the fitness of both predators and prey, increasing the likelihood of extinction., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

In kin selection theory in the evolution of social behaviours, the relatedness between interacting individuals is influenced by the spatial structure of the population. It is generally considered that in the 'viscous' population competition among individuals tends to suppress the evolution of altruism. We consider that more complex interactions produce specific spatial patterns in the presence of competitive interaction, which could alter the process of kin selection in a given space. Here, we theoretically studied the joint evolution of altruism and resource exploitation in a spatially structured population. The simulations indicated that joint evolution can result in self-organisation of regularly arranged cluster structures, which creates a new 'level of selection', and significantly promotes the evolution of altruism through a promotion of kin selection. The analysis also suggested synergetic effects of the joint evolution of two traits, including an evolutionary suicide of the population., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Like many other bacteria, Pseudomonas aeruginosa sequesters iron from the environment through the secretion, and subsequent uptake, of iron-binding molecules. As these molecules can be taken up by other bacteria in the population than those who secreted them, this is a form of cooperation through a public good. Traditionally, this problem has been studied by comparing the relative fitnesses of siderophore-producing and non-producing strains, but this gives no information about the fate of strains that do produce intermediate amounts of siderophores. Here, we investigate theoretically how the amount invested in this form of cooperation evolves. We use a mechanistic description of the laboratory protocols used in experimental evolution studies to describe the competition and cooperation of the bacteria. From this dynamical model we derive the fitness following the adaptive dynamics method. The results show how selection is driven by local siderophore production and local competition. Because siderophore production reduces the growth rate, local competition decreases with the degree of relatedness (which is a dynamical variable in our model). Our model is not restricted to the analysis of small phenotypic differences and allows for theoretical exploration of the effects of large phenotypic differences between cooperators and cheats. We predict that an intermediate ESS level of cooperation (molecule production) should exist. The adaptive dynamics approach allows us to assess evolutionary stability, which is often not possible in other kin-selection models. We found that selection can lead to an intermediate strategy which in our model is always evolutionarily stable, yet can allow invasion of strategies that are much more cooperative. Our model describes the evolution of a public good in the context of the ecology of the microorganism, which allows us to relate the extent of production of the public good to the details of the interactions., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

Group selection can overcome individual selection for selfishness and favour altruism if there is variation among the founders of the spatially distinct groups, and groups with many altruists become substantially larger (or exist longer) than groups with few. Whether altruism can evolve in populations that do not have an alternation of local population growth and global dispersal ("viscous populations") has been disputed for some time. Limited dispersal protects the altruists from the non-altruists, but also hinders the export of altruism. In this article, we used the Pair Approximation technique (tracking the dynamics of pairs of neighbours instead of single individuals) to derive explicit invasion conditions for rare mutants in populations with limited dispersal. In such viscous populations, invading mutants form clusters, and ultimately, invasion conditions depend on the properties of such clusters. Thus there is selection on a higher level than that of the individual; in fact, invasion conditions define the unit of selection in viscous populations. We treat the evolution of altruism as a specific example, but the method is of more general interest. In particular, an important advantage is that the spatial aspects can be incorporated into game theory in a straightforward fashion; we will specify the ESS for a more general model. The invasion condition can be interpreted in terms of inclusive fitness. In contrast with Hamilton's model, the coefficient of relatedness is not merely a given genetical constant but depends on local population dynamical processes (birth, dispersal and death of individuals). With a simple birth rate function, Hamilton's rule is recovered: the cost to the donor should be less than the benefit to the recipient weighted with the coefficient of relatedness. As the coefficient of relatedness is roughly proportional to an individual's number of neighbours, benefits to the recipient must be substantial to outweigh the costs, confirming earlier studies. We discuss the consequences for the evolution of dispersal and outline how the method may be extended to study evolution in interacting populations.Copyright 1998 Academic Press