V. Life's Corporeal Evolution Encodes and Organizes Itself: An EarthWinian Genesis Synthesis
5. Cooperative Societies
Krause, Jens and Graeme Ruxton. Living in Groups. Oxford: Oxford University Press, 2002. A study of how social animals self-organize collective behavior such as bird migration, which is based on “multiple often simultaneous interactions between individual group members.” (5)
Krause, Jens, et al. Swarm Intelligence in Animals and Humans. Trends in Ecology and Evolution. 25/12, 2009. From quorum-sensing in microbes and social insects to social networks on the worldwide web, a common, constant propensity to form groups which can acquire a modicum of their own cerebral capacity is found to grace and span the natural hierarchies.
Krause, Jens, et al, eds. Animal Social Networks. Oxford: Oxford University Press, 2015. Jens Krause, Humboldt University, Richard James, University of Bath, UK, Dan Franks, University of York, and Darren Croft, University of Exeter update and expand earlier works on this pervasive communal propensity by further applications of widely used network theories. In chapters, leading authorities consider Metazoan classes from insects and fish to primates and aspects such as mating, personalities, and disease transmission.
The scientific study of networks - computer, social, and biological - has received an enormous amount of interest in recent years. However, the network approach has been applied to the field of animal behaviour relatively late compared to many other biological disciplines. Understanding social network structure is of great importance for biologists since the structural characteristics of any network will affect its constituent members and influence a range of diverse behaviours. These include finding and choosing a sexual partner, developing and maintaining cooperative relationships, and engaging in foraging and anti-predator behavior. This novel text provides an overview of the insights that network analysis has provided into major biological processes, and how it has enhanced our understanding of the social organisation of several important taxonomic groups. It brings together researchers from a wide range of disciplines with the aim of providing both an overview of the power of the network approach for understanding patterns and process in animal populations, as well as outlining how current methodological constraints and challenges can be overcome.
Kronauer, Daniel and Joel Levine.
The Ultimate and Proximate Underpinnings of Social Behavior.
Journal of Experimental Biology.
An introduction by the Rockefeller University and University of Toronto scientists for a special Evolution of Social Behavior issue. Articles include The Ecology and Evolution of Social in Microbes by Corina Tarnita, Cognitive Skills and the Evolution of Social Systems by Russell Fernald, and Individual versus Collective Cognition in Social Insects by Ofer Feinerman and Amos Korman. Kornauer’s own paper with Waring Trible is Caste Development and Evolution in Ants, which was noted in the New York Times on January 24, 2017 by Natalie Angier as Gene-Modified Ants Shed Light on How Societies are Organized.
In particular, social evolutionary theory provides a unifying framework in which social behavior and the evolutionary dynamics between interacting components can be understood at a variety of organizational levels, ranging from genes in a genome, to cells in multicellular organisms, individuals in a social group, and between-species interactions. This Special Issue of the Journal of Experimental Biology highlights how the same evolutionary concepts apply to different levels of biological organization and across the tree of life. While the altruistic behavior of worker ants that defend their colony while foregoing reproduction, or the mutualistic interaction between ants that milk and defend aphids is immediately apparent, other social evolutionary interactions are less obvious, yet governed by the same principles. (4)
Kurvers, Ralf, et al. The Evolutionary and Ecological Consequences of Animal Social Networks. Trends in Ecology and Evolution. Online April, 2014. Leibniz Institute of Freshwater Ecology and Inland Fisheries, Berlin, and University of Exeter, behavioral ecologists, including Jens Krause, laud how much the application of network analysis to animal groupings has paid off because it is universally and beneficially in effect. After some 15 years, both generic network topologies and dynamics, and their exemplary presence everywhere is well studied and proven. Along with an array of self-organizing propensities, an inherent spontaneity is verified that precedes vicarious selection. Cooperation, Symbiosis, and Social Network Structures would seem to be aspects of a singular incentive to reciprocate, survive, prosper, evolve, and emerge.
The first generation of research on animal social networks was primarily aimed at introducing the concept of social networks to the fields of animal behaviour and behavioural ecology. More recently, a diverse body of evidence has shown that social fine structure matters on a broader scale than initially expected, affecting many key ecological and evolutionary processes. Here, we review this development. We discuss the effects of social network structure on evolutionary dynamics (genetic drift, fixation probabilities, and frequency-dependent selection) and social evolution (cooperation and between-individual behavioural differences). We discuss how social network structure can affect important coevolutionary processes (host–pathogen interactions and mutualisms) and population stability. We also discuss the potentially important, but poorly studied, role of social network structure on dispersal and invasion. (Abstract)
Lehmann, L. and L. Keller. The Evolution of Cooperation and Altruism – a General Framework and a Classification of Models. Journal of Evolutionary Biology. 19/5, 2007. An introduction to a dedicated issue on this occurrence, which seems to be at odds with selfish selection, but is widespread amongst organisms. However the many efforts to do this, from genetic, behavioral, or other means, remain in need of a common terminology and synthesis. Some 16 comments follow from leading researchers. Of typical note might be Cooperation and Conflict during Evolutionary Transitions in Individuality by Richard Michod and Matthew Herron. And see also in this regard Social Semantics: Altruism, Cooperation, Mutualism, Strong Reciprocity and Group Selection by S. A. West, et al, in the same journal (20/2, 2007).
Levin, Samuel and Stuart West. Kin Selection in the RNA World. Life. Online December 5, 2017. We cite this paper about this primordial stage of rudimentary organisms because senior Oxford University zoologists find cooperative social tendencies in effect back then so as to mitigate competition even among these early nucleotide phases.
Various steps in the RNA world required cooperation. Why did life’s first inhabitants, from polymerases to synthetases, cooperate? We develop kin selection models of the RNA world to answer these questions. We develop a very simple model of RNA cooperation and then elaborate it to model three relevant issues in RNA biology: (1) whether cooperative RNAs receive the benefits of cooperation; (2) the scale of competition in RNA populations; and (3) explicit replicator diffusion and survival. We show: (1) that RNAs are likely to express partial cooperation; (2) that RNAs will need mechanisms for overcoming local competition; and (3) in a specific example of RNA cooperation, persistence after replication and offspring diffusion allow for cooperation to overcome competition. More generally, we show how kin selection can unify previously disparate answers to the question of RNA world cooperation. (Abstract)
Levin, Simon, ed. Games, Groups, and the Global Good. Berlin: Springer, 2009. The proceedings of a Templeton Foundation conference to report, contrary to a misunderstood Darwinism, that cooperative behavior is as prevalent across an actual nested, integrative evolution than brutal competition. Authorities such as Franz de Waal, Martin Nowak, David Sloan Wilson, Rebecca Flack, and others, provide robust reasons from genomes to social networks, across three inclusive sections: The Evolution of Cooperation at the Level of Individuals, Cooperation and Group Formation, and Cooperation and Problems of the Commons.
In biology, the evolution of increasingly cooperative groups has shaped the history of life. Genes collaborate in the control cells; cells efficiently divide tasks to produce cohesive multicellular individuals; individuals members of insect colonies cooperate in integrated societies. Biological cooperation provides a foundation on which to understand human behavior. (Steven Frank “Evolutionary Foundations of Cooperation and Group Cohesion” (3)
Li, Wei, et al. How Scale-free Networks and Large-scale Collective Cooperation Emerge in Complex Homogeneous Social Systems. Physical Review E. 76/045102, 2007. Physicists at Beijing Normal University and Shenzhen University propose theoretical reasons for this persistent tendency across emergent nature to develop into cognitively active societies.
In particular, our simple model suggests that the SF (scale-free) feature, which has been shown to be so pervasive in complex systems, can arise from dynamic evolution via a self-organizing mechanism through individual learning ability. These results shed light on understanding how complex networks with global collective cooperation can emerge from social individuals with local and primary abilities and instincts. (045102-4)
Lindenfors, Patrik. Neocortex Evolution in Primates: The ‘Social Brain’ is for Females. Biology Letters. 1/4, 2005. In this new journal from the Royal Society, a note about the importance of gender differences when studying how primate societies evolved and grew complex. In an extension of Robin Dunbar’s theory that increased sociality drove brain development, this process is seen to take place mostly amongst female members who took care of food resources and group survival.
Ling, Hangjian, et al. Costs and Benefits of Social Relationships in the Collective Motion of Bird Flocks. Nature Ecology & Evolution. 3/948, 2019. A six person team from Stanford University, University of Exeter and Simon Fraser University including Nicholas Ouellette contend that prior models underplay local, individual interactions between semi-autonomous group members, which in reality can be a major component of successful swarm patterns. See also Environmental Perturbations Induce Correlations in Midge Swarms in the Journal of the Royal Society Interface (March 2020) for an update and finesse.
Lord, Warren, et al. Inference of Causal Information Flow in Collective Animal Behavior. arXiv:1606.01932. By mid 2016, systems mathematicians Lord, Jie Sun, and Erik Bollt, Clarkson University, and Nicholas Ouellette, Stanford University, can achieve a sophisticated analysis of creaturely group activities in terms of basic physical principles. Since the same phenomena applies to any species from invertebrate insects to mammals and humans, a deep rooted connection is achieved with a lively, iterative cosmic genesis. See also Empirical Questions for Collective-Behavior Modelling by N. Ouellette in Pramana – Journal of Physics (84/3, 2015).
Collectively interacting groups of social animals such as herds, schools, flocks, or crowds go by many names depending on the specific animal species. But in all cases, they tend to display seemingly purposeful, coordinated group-level dynamics despite the apparent absence of leaders or directors. These coordinated group behaviors appear to emerge only from interactions between individuals, analogous to the manner in which macroscopic observables are determined by microscopic interactions in statistical physics. Thus, collective behavior has captivated a broad spectrum of researchers from many different disciplines –. Making the analogy to statistical physics more concrete, it is reasonable to suggest that a deep understanding of collective group motion may arise from three parallel pursuits. We can perform a macroscopic analysis, focusing on the observed group-level behavior such as the group morphology or the material-like properties; we can perform a microscopic analysis, determining the nature of the interactions between individuals; and we can study how the microscopic interactions scale up to give rise to the macroscopic properties. (1)
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