V. Life's Corporeal Evolution Develops, Encodes and Organizes Itself: An Earthtwinian Genesis Synthesis

5. Cooperative Member/Group Societies

Dukas, Reuven. Effects of Learning on Evolution: Robustness, Innovation and Speciation. Animal Behavior. Online March, 2013. The McMaster University neuropsychologist identifies the value of a good environmental education for all creaturly domains for their survival and posterity. It is very vital to be able to record and accumulate experiences, which can foster novel, creative responses. Speciation follows in turn by a more assortative mating which leads to population divergence. See also Dukas’ chapter, with Thomas Hills, “The Evolution of Cognitive Search” in Cognitive Search: Evolution, Algorithms, and the Brain (MIT Press 2012, search Todd).

All animals are highly plastic and rely on the modulation of gene action, physiology and behaviour to continuously modify their phenotypes. Compared to other types of plasticity, learning, defined as the internal representation of novel information, allows animals to better exploit environmental features unique to certain times and places. This distinctive property of learning gives it an enormous potential to promote evolution through increased robustness, innovation and speciation rate. First, learning can enhance robustness because it allows individuals to adopt new resources and avoid novel threats. The best examples are cases of social learning that lead to the exploitation of novel food sources followed by genetic changes that optimize use of the new diet. Finally, learning can increase the levels of assortative mating that lead to population divergence either when young imprint on their parents or when individuals restrict their mate choice criteria based on interactions with prospective mates. (Abstract)

Dunbar, Robin. Evolution of the Social Brain. Science. 302/1160, 2003. A review of two articles in this issue that find sociality in baboons aided by relationships between primate females and an associated communicative component. Anthropologist Dunbar’s own important work is noted is several places.

Dunbar, Robin. Structural and Cognitive Mechanisms of Group Cohesion in Primates. Behavioral and Brain Sciences. Online April 30, 2024. The senior Oxford University evolutionary psychologist is well known for his primate to human social studies and Dunbar number scale. (search). This entry provides is his latest thorough explanations for their beneficial veracity

Group-living creates stresses that often lead to fragmentation and conflict. Here I refer to grooming networks and cognitive abilities in primates to show that living in large, stable assemblies involved structural solutions which led to ‘friendship’ linkages, bonding behaviours so that coalitions work effectively, and cognitive skills similar to social relationships in humans. The first ensures that individuals synchronise their activity cycles; the second allows issues to be defused; and the third can manage difficulties. In primates, these strategies appear at specific group sizes, suggesting that they break through ‘glass ceilings.’ This sequence maps onto the grades that underpin the fractal-like Social Brain Hypothesis known to optimize information conversant flow.

Dunbar, Robin, et al. Primate Social Group Sizes Exhibit a Regular Scaling Pattern with Natural Attractors. Biology Letters. 14/1, 2018. Psychologists Dunbar and Padraig Mac Carron, Oxford University, and biologist Susanne Shultz, University of Manchester offer further extensive evidence that simian groupings across many species tend to common, default sizes within a general nested sequence. See also Optimizing Human Community Sizes by Dunbar and Richard Sosis in Evolution and Human Behavior (39/1, 2018), and Sizes of Permanent Campsite Communities Reflect Constraints on Natural Human Communities by Tobias Kordsmeyer, et al in Current Anthropology (58/2, 2017), second Abstract.

Primate groups vary considerably in size across species. Nonetheless, the distribution of mean species group size has a regular scaling pattern with preferred sizes approximating 2.5, 5, 15, 30 and 50 individuals (although strepsirrhines lack the latter two), with a scaling ratio of approximately 2.5 similar to that observed in human social networks. These clusters appear to form distinct social grades that are associated with rapid evolutionary change, presumably in response to intense environmental selection pressures. These findings may have wider implications for other highly social mammal taxa. (Dunbar Abstract)

Both small-scale human societies and personal social networks have a characteristic hierarchical structure with successively inclusive layers of 15, 50, 150, 500, and 1,500 individuals. It has been suggested that these values represent a set of natural social attractors, or “sweet spots,” in organizational terms. We exploited the new phenomenon of permanent (i.e., residential) campsites to ask whether these values are present in the size distribution of the numbers of residents in these naturally small-scale communities. In two separate data sets of different grain, we find consistent evidence for sites with 50, 150, 500, and maybe 1,500 residents. (Kordsmeyer Abstract)

Emery, Nathan, et al, eds. Social Intelligence: From Brain to Culture. Oxford: Oxford University Press, 2007. Not yet seen, we quote from the OUP website. Eighteen papers cover in breadth and depth the persistent formation across the animal kingdoms of a ramifying collective cognition. See also the 2007 Philosophical Transactions of the Royal Society B issue edited by Emery and posted in The Appearance of Homo Sapiens section.

Why are humans so clever? The 'Social intelligence' hypothesis explores the idea that this cleverness has evolved through the increasing complexity of social groups. Our ability to understand and control nature is a by-product of our ability to understand the mental states of others and to use this knowledge to co-operate or deceive. These abilities have not emerged out of the blue. They can be found in many social animals that co-operate and compete with one another, birds as well as mammals.

This book brings together contributions from an impressive list of authorities in the field, appropriately concluding with a chapter by Nick Humphrey (one of the pioneers in this field). This volume examines social intelligence in many different animal species and explores its development, evolution and the brain systems upon which it depends. Better understanding and further development of social intelligence is critical for the future of the human race and the world that we inhabit. Our problems will not be solved by mere cleverness, but by increased social co-operation.

Fehr, Ernst, et al. Strong Reciprocity, Human Cooperation, and the Enforcement of Social Norms. Human Nature. 13/1, 2002. The lead article in a special issue that seeks to quantify an innate tendency for cooperation.

This paper provides strong evidence challenging the self-interest assumption that dominates the behavioral sciences and much evolutionary thinking. The evidence indicates that many people have a tendency to voluntarily cooperate, if treated fairly, and to punish noncooperators.

Fewell, Jennifer. Social Insect Networks. Science. 1867/301, 2003. Universal principles of self-organizing complex systems are found to characterize colonoial insects such as ants and bees. Their superorganism-like communities have become a useful candidate to exhibit and model these common properties such as network dynamics.

Social insect colonies (and social groups generally) have key network attributes that appear consistently in complex biological systems, from molecules to ecosystems; these include nonrandom systems of connectivity and the self-organization of group-level phenotypes. (1867)

Fewell, Jennifer, et al. Division of Labor in the Context of Complexity. Gadau, Jurgen and Jennifer Fewell, eds. Organization of Insect Societies: From Genome to Sociocomplexity. Cambridge: Harvard University Press, 2009. A good example of how nonlinear mathematical dynamics as a genetic-like source will produce similar yet diverse, symbiotic modules which then form and serve the rise and viability of higher-order, bounded phases. We offer extended quotes which illustrate their pervasive presence throughout natural kingdoms.

Sociobiology is undergoing a shift in its theoretical framework toward the paradigm that societies are complex and dynamical systems rather than amalgamated groups of individuals. (483) Over the past few decades, there has been a large increase in the pervasiveness of complexity theory across disciplines, allowing us to tap into a growing theoretical framework. (483-484)

If a social system has multiple clusters of individuals with localized interactions, and if they are each connected somehow to the group as a whole (and thus contribute to the behavior of the whole group), the social group becomes a complex system. Thus, complex systems are by definition distributed, because the behavior of the collective whole results from multiple local interactions rather than being directed externally or form a central source. These local interactions collectively produce group-level phenotypes, or emergent properties, at the larger scale that cannot be described or explained simply by measuring the behaviors of the individual group members alone. The process of local dynamics generating emergent effects is called self-organization, and the ubiquity of this effect has let to the suggestion that the presence of self-organization could be considered the defining characteristic of complex systems. (486-487)

The properties of emergence and resiliency outlines above lead to the consideration of social insects as complex adaptive systems (CAS). The concept of CAS was developed primarily to understand how some systems of interacting agents can develop amd maintain a group-level structure in the absence of a central organizing source. It originated in the observation that groups of interacting units, from economies to ecosystems, seen to share certain properties in common. (496)

Finn, Kelly, et al. Novel Insights into Animal Sociality from Multilayer Networks. arXiv:1712.01790. Finn, UC Davis animal behavior, Matthew Silk, University of Exeter environmental sustainability, along with Mason Porter, mathematics and Noa Pinter-Wollman, evolutionary biology UCLA apply these latest appreciations of dynamic network structures (search Porter) to creaturely groupings across their many instances and scales.

Network analysis has driven key developments in animal behavior research by providing quantitative methods to study the social structure of animal groups and populations. A recent advancement in network science, multilayer network analysis, the study of network structures of multiple interconnected `layers', offers a novel way to represent and analyze the structure of animal behavior, and help strengthen links to broader ecological and evolutionary contexts. We outline the potential uses of these new methods at individual-, group-, population-, and evolutionary-levels, and we highlight their potential to advance behavioral ecology research. This novel quantitative approach makes it possible to address classic research questions from a new perspective and opens a diversity of new questions that previously have been out of reach. (Abstract)

Flack, Jessica. Multiple Time-Scales and the Developmental Dynamics of Social Systems. Philosophical Transactions of the Royal Society. 367/1802, 2012. A Wisconsin Institute for Discovery, Center for Complexity and Collective Computation (C4), and Santa Fe Institute systems behaviorist contributes to a special issue on The Social Network and Communicative Complexity, with Robin Dunbar as a main organizer. We note three quotes in regard – the article Abstract, another from the issue Introduction, and a statement for the C4 Center.

To build a theory of social complexity, we need to understand how aggregate social properties arise from individual interaction rules. Here, I review a body of work on the developmental dynamics of pigtailed macaque social organization and conflict management that provides insight into the mechanistic causes of multi-scale social systems. In this model system coarse-grained, statistical representations of collective dynamics are more predictive of the future state of the system than the constantly in-flux behavioural patterns at the individual level. (Abstract, 1802)

The complex social worlds of many animal species may be linked to complex communicative systems in those species. We now have evidence in diverse taxa and in different communicative modalities suggesting that complexity in social groups can drive complexity in signalling systems. The aim of this theme issue is to develop the theory behind this link between social complexity and communicative complexity, and to provide an overview of the lines of research testing this link. (Introduction, 1782)

The mission of C4 is to discover the information processing, regulatory, and computational principles underlying the emergence of societies of cells and organisms in the history of life on earth. Research in C4 sits at the interface of collective behavior and evolution, statistical mechanics, information theory, and model selection. Research projects include the origins of biological and social complexity, the roles of inference, uncertainty reduction and robustness in evolutionary processes, complexity measures for biological systems, the role of collective social computation in the developmental dynamics of social systems, the causes of multi scale structure in brains and societies, inductive game theory and conflict dynamics and control, and the cultural evolution of artifacts, including novels and constitutions. (C4 website, David Krakauer director)

Fletcher, Jeffery and Martin Zwick. Strong Altruism can Evolve in Randomly Formed Groups. Journal of Theoretical Biology. 228/3, 2004. A liability to helping and sharing behaviors was thought to be a high cost to the altruistic organism. This simulation and analysis finds a positive bias for these cooperative traits, not requiring special conditions, if such groups persist for more than one generation.

The fact that strong altruism can increase when groups are periodically and randomly formed suggests that altruism may evolve more readily and in simpler organisms than is generally appreciated. (303)

Foster, Kevin. The Sociobiology of Molecular Systems. Nature Reviews Genetics. Online, March, 2011. The Oxford University zoologist seeks to advance insights into human social behavior as set within their certain evolutionary ground, long a contentious subject. Although the 1970s “sociobiology” remains a loaded term, we ought not ignore that biological and communal life phases are deeply rooted and related. An appropriate synthesis might be lately gained through the fluid network topologies being found at every organic scale. Four aspects are enlisted: multiple nested levels of spatial life and temporal evolution, kinds and density of nodes and connections, system diversities, and how networks change. By the 2010s, a complementary balance of entity and empathy from protein webs and cell symbiosis to primate troops and country towns can be observed and documented.

It is often assumed that molecular systems are designed to maximize the competitive ability of the organism that carries them. In reality, natural selection acts on both cooperative and competitive phenotypes, across multiple scales of biological organization. Here I ask how the potential for social effects in evolution has influenced molecular systems. I discuss a range of phenotypes, from the selfish genetic elements that disrupt genomes, through metabolism, multicellularity and cancer, to behaviour and the organization of animal societies. I argue that the balance between cooperative and competitive evolution has shaped both form and function at the molecular scale. (193)

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