How to Measure Group Selection in Real-world Populations

Multilevel selection and the evolution of cooperation are fundamental to the formation of higher-level organisation and the evolution of biocomplexity, but such notions are controversial and poorly understood in natural populations. The theoretic principles of group selection are well developed in idealised models where a population is neatly divided into multiple semi-isolated sub-populations. But since such models can be explained by individual selection given the localised frequency-dependent effects involved, some argue that the group selection concepts offered are, even in the idealised case, redundant and that in natural conditions where groups are not well-defined that a group selection framework is entirely inapplicable. This does not necessarily mean, however, that a natural population is not subject to some interesting localised frequency-dependent effects – but how could we formally quantify this under realistic conditions? Here we focus on the presence of a Simpson’s Paradox where, although the local proportion of cooperators decreases at all locations, the global proportion of cooperators increases. We illustrate this principle in a simple individual-based model of bacterial biofilm growth and discuss various complicating factors in moving from theory to practice of measuring group selection

Social niche construction: evolutionary explanations for cooperative group formation

Cooperative behaviours can be defined as those that benefit others at an apparent cost to self. How these kinds of behaviours can evolve has been a topic of great interest in evolutionary biology, for at first sight we would not expect one organism to evolve to help another. Explanations for cooperation rely on the presence of a population structure that clusters cooperators together, such that they enjoy the benefits of each others' actions. But, the question that has been left largely unaddressed is, how does this structure itself evolve? If we want to really explain why organisms cooperate, then we need to explain not just their adaptation to their social environment, but why they live in that environment.It is well-known that individual genetic traits can affect population structure; an example is extracellular matrix production by bacteria in a biofilm. Yet, the concurrent evolution of such traits with social behaviour is very rarely considered. We show here that social behaviour can exert indirect selection pressure on population structure-modifying traits, causing individuals to adaptively modify their population structure to support greater cooperation. Moreover, we argue that any component of selection on structure modifying traits that is due to social behaviour must be in the direction of increased cooperation; that component of selection cannot be in favour of the conditions for greater selfishness. We then examine the conditions under which this component of selection on population structure exists. Thus, we argue that not only can population structure drive the evolution of cooperation, as in classical models, but that the benefits of greater cooperation can in turn drive the evolution of population structure - a positive feedback process that we call social niche construction.We argue that this process is necessary in providing an adaptive explanation for some of the major transitions in evolution (such as from single- to multi- celled organisms, and from solitary insects to eusocial colonies). Any satisfactory account of these transitions must explain how the individuals came to live in a population structure that supported high degrees of cooperation, as well as showing that cooperation is individually advantageous given that structure

The Efficacy of Group Selection is Increased by Coexistence Dynamics within Groups

Selection on the level of loosely associated groups has been suggested as a route towards the evolution of cooperation between individuals and the subsequent formation of higher-level biological entities. Such group selection explanations remain problematic, however, due to the narrow range of parameters under which they can overturn within-group selection that favours selfish behaviour. In principle, individual selection could act on such parameters so as to strengthen the force of between-group selection and hence increase cooperation and individual fitness, as illustrated in our previous work. However, such a process cannot operate in parameter regions where group selection effects are totally absent, since there would be no selective gradient to follow. One key parameter, which when increased often rapidly causes group selection effects to tend to zero, is initial group size, for when groups are formed randomly then even moderately sized groups lack significant variance in their composition. However, the consequent restriction of any group selection effect to small sized groups is derived from models that assume selfish types will competitively exclude their more cooperative counterparts at within-group equilibrium. In such cases, diversity in the migrant pool can tend to zero and accordingly variance in group composition cannot be generated. In contrast, we show that if within-group dynamics lead to a stable coexistence of selfish and cooperative types, then the range of group sizes showing some effect of group selection is much larger

Explaining cooperative groups via social niche construction

Cooperative behaviours can be defined as those that benefit others at an apparent cost to self. How these kinds of behaviours evolve has been a topic of great interest in evolutionary biology, as the Darwinian paradigm seems to suggest that nature will be “red in tooth and claw” and that we would not expect one organism to evolve to help another. The evolution-of-cooperation literature has therefore generally been about showing how the altruism involved in these cases is only apparent (see Bergstrom 2002 for an excellent review). Consider kin selection, in which interactions are more likely to occur between related individuals. The cost of altruism to the individual is real but, having identified the correct score-keeping level as the genetic one, it turns out that the cooperative act is not costly but profitable. More generally, successful explanations for cooperation rely on the presence of a population structure that clusters cooperators together, such that they enjoy the benefits of each others' actions. However, the question that has been left largely unaddressed is how does this structure itself evolve? If we want to really explain why organisms cooperate, then we need to explain not just their adaptation to their social environment, but how they came to live in that environment. Recent work by Powers (2010) and Powers et al. (in press) has addressed this question. They show that social behaviour can exert indirect selection pressure on population structure-modifying traits, causing individuals to adaptively modify their population structure to support greater cooperation. Moreover, they argue that any component of selection on structure-modifying traits that is due to social behaviour must be in the direction of increased cooperation; that component of selection cannot be in favour of the conditions for greater selfishness. Powers et al. then examine the conditions under which this component of selection on population structure exists. They argue that not only can population structure drive the evolution of cooperation, as in classical models, but that the benefits of greater cooperation can in turn drive the evolution of population structure: a positive feedback process that they refer to as social niche construction (after Odling-Smee et al. 2003). Maynard Smith and Szathmary (1995) note that most of the big unanswered questions in biology are not about how a particular behaviour is selected for at one level of organization but about the emergence of whole new levels of organization, e.g., the transition from single- to multi-celled organisms, or from solitary insects to eusocial colonies. Any satisfactory account of these transitions must explain how the individuals came to live in a population structure that supported high degrees of cooperation, as well as showing that cooperation is individually advantageous given that structure. The social niche construction process identified by Powers et al. can explain some of the major transitions, by showing how a new selective level can begin through evolution of individual characters, such as group size preference or dispersal tendency. The potential emergence of reliable cooperation via the co-evolution of individual cooperative and population-structuring behaviours demonstrates that groups of cooperating agents can create an environment in which they become so “locked in” to their group identity that the group warrants redescription as an individual in its own right. Consider the move from independent protozoans, to an intermediate cooperative stage as in slime moulds, to fully multi-cellular animals. Such creation of population structures that support cooperation parallels negotiation of a social contract. What are the philosophical implications of this perspective for understanding and explaining human social behaviour? On the one hand, it gives respectability and unique explanatory value to group-selectionist accounts. Explaining the origin of within-group cooperation and the origin of the groups themselves become part of the same project, which in turn means that we cannot understand social and cooperative behaviour in humans without understanding human population-structuring traits, e.g., living in family groups, group fission-fusion behaviours, migratory behaviours, etc. What will the explanations we seek look like? de Pinedo and Noble (2008) have argued that the description of evolved behaviour cannot be exclusively in mechanistic terms: we need both explanations that focus on an agent’s interaction with its environment, and explanations that focus on the physical or computational enabling conditions of such an interaction. In a context in which what counts as an agent is taken for granted, de Pinedo and Noble argue that both agent and sub-agent level explanations will be required. The perspective being outlined here forces an expansion of that position and reminds us that agency is not to be taken for granted; that it emerges from a lower level of organization after a history of selection brings simpler entities together in a coherent cooperative whole. The implication is that truly multi-level explanations will be necessary in the area of social behaviour. We explain the origin of the multi-cellular organism as the result of a cooperative merger of single-celled organisms, and we explain the origin of a super-organism such as an ant colony in a similar way. At each transition, the autonomous agents of the previous level become component mechanisms in the next, but no explanatory level can be entirely done away with. A human being is an example of a multi-cellular organism with a highly developed social aspect, occupying an intermediate point between radical individual independence and total group cohesion. To fully explain human behaviour, we need to know about the cellular machinery that enables personal-level agency. But we also need to know how human machinery fits together into families, communities and nations that will, at least partially, have their own emergent goals and purposes: “partially” because we are not yet a super-organism, of course. In conclusion, the perspective we outline suggests a view of the social contract as not at all unique to Hobbesian rational agents who have become tired of an insecure and violent lifestyle. Instead the ongoing negotiation of the social contract amongst ourselves can be seen as echoing earlier, now-successfully-concluded negotiations between the entities that became our genes and then our cells

The institutional approach for modeling the evolution of human societies

Artificial Life is concerned with understanding the dynamics of human societies. A defining feature of any society is its institutions. However, defining exactly what an institution is has proven difficult, with authors often talking past each other. This paper presents a dynamic model of institutions, which views institutions as political game forms that generate the rules of a group's economic interactions. Unlike most prior work, the framework presented here allows for the construction of explicit models of the evolution of institutional rules. It takes account of the fact that group members are likely to try to create rules that benefit themselves. Following from this, it allows us to determine the conditions under which self-interested individuals will create institutional rules that support cooperation, e.g. that prevent a Tragedy of the Commons. The paper finishes with an example of how a model of the evolution of institutional rewards and punishments for promoting cooperation can be created. It is intended that this framework will allow Artificial Life researchers to examine how human groups can themselves create conditions for cooperation. This will help provide a better understanding of historical human social evolution, and facilitate the resolution of pressing societal social dilemmas

How to measure group selection in real-world populations

Multilevel selection and the evolution of cooperation are fundamental to the formation of higher-level organisation and the evolution of biocomplexity, but such notions are controversial and poorly understood in natural populations. The theoretic principles of group selection are well developed in idealised models where a population is neatly divided into multiple semi-isolated sub-populations. But since such models can be explained by individual selection given the localised frequency-dependent effects involved, some argue that the group selection concepts offered are, even in the idealised case, redundant and that in natural conditions where groups are not well-defined that a group selection framework is entirely inapplicable. This does not necessarily mean, however, that a natural population is not subject to some interesting localised frequency-dependent effects -- but how could we formally quantify this under realistic conditions? Here we focus on the presence of a Simpson's Paradox where, although the local proportion of cooperators decreases at all locations, the global proportion of cooperators increases. We illustrate this principle in a simple individual-based model of bacterial biofilm growth and discuss various complicating factors in moving from theory to practice of measuring group selection.Comment: pp. 672-679 in Proceedings of the Eleventh European Conference on the Synthesis and Simulation of Living Systems (Advances in Artificial Life, ECAL 2011). Edited by Tom Lenaerts, Mario Giacobini, Hugues Bersini, Paul Bourgine, Marco Dorigo and Ren\'e Doursat. MIT Press (2011). http://mitpress.mit.edu/catalog/item/default.asp?ttype=2&tid=12760. 8 pages, 5 figure