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A Sourcebook for the Worldwide Discovery of a Creative Organic Universe
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VI. Earth Life Emergence: Development of Body, Brain, Selves and Societies

6. Cooperative Societies

Gavrilets, Sergey. On the Evolutionary Origins of the Egalitarian Syndrome. Proceedings of the National Academy of Sciences. 109/14069, 2012. In a widely reported paper, a University of Tennessee mathematical biologist quantifies that viable human and animal social assemblies are distinguished by a mutual, palliative reciprocity of individual and group. Most importantly this is achieved by an ability to constrain self-serving, destructive bully behavior by way of cooperative coalitions. Once again, these archetypal, “creative union” complements achieve a social viability, which are so aberrantly out of balance and kilter in our violent, male-dominated civilization, or lack thereof.

The evolutionary emergence of the egalitarian syndrome is one of the most intriguing unsolved puzzles related to the origins of modern humans. Standard explanations and models for cooperation and altruism—reciprocity, kin and group selection, and punishment — are not directly applicable to the emergence of egalitarian behavior in hierarchically organized groups that characterized the social life of our ancestors. Here I study an evolutionary model of group living individuals competing for resources and reproductive success. In the model, the differences in fighting abilities lead to the emergence of hierarchies where stronger individuals take away resources from weaker individuals and, as a result, have higher reproductive success.

First, I show that the logic of within-group competition implies under rather general conditions that each individual benefits if the transfer of the resource from a weaker group member to a stronger one is prevented. This effect is especially strong in small groups. Then I demonstrate that this effect can result in the evolution of a particular, genetically controlled psychology causing individuals to interfere in a bully–victim conflict on the side of the victim. A necessary condition is a high efficiency of coalitions in conflicts against the bullies. The egalitarian drive leads to a dramatic reduction in within-group inequality. Simultaneously it creates the conditions for the emergence of inequity aversion, empathy, compassion, and egalitarian moral values via the internalization of behavioral rules imposed by natural selection. It also promotes widespread cooperation via coalition formation. (Abstract)

Humans exhibit a strong egalitarian syndrome, i.e., the complex of cognitive perspectives, ethical principles, social norms, and individual and collective attitudes promoting equality (1–9). The universality of egalitarianism in mobile hunter-gatherers suggests that it is an ancient, evolved human pattern (2, 5, 6). Political egalitarianism of contemporary foragers is accomplished by a variety of cultural practices (leveling mechanisms) aiming at controlling overassertive, dominant, or very successful individuals who might wish to monopolize resources. (14069)

The origins of moral values have intrigued scholars for millennia. Darwin saw human morality as derived from animal “social instincts” that transform to a “moral sense or conscience as soon as . . . intellectual powers become . . . well developed.” In a modern perspective, viewing human conscience as a mere by-product of intelligence is an oversimplification. Boehm convincingly argues that additional processes and factors such as moralistic punishment, internalization of culturally enforced norms, symbolic language and gossiping, and social selection for altruism and self-restraint applied by groups to its members need to be considered. That notwithstanding, identifying evolutionary roots for and the dynamics of genetically controlled egalitarian social instincts is a necessary step in getting a better understanding of the origins of a uniquely human sense of right and wrong. (14072)

Gfrerer, Nastassja and Michael Taborsky. Working Dogs Cooperate Among One Another by Generalised Reciprocity. Nature Scientific Reports. 7/43867, 2017. University of Bern behavioral ecologists quantify and aver this altruistic, do unto others, propensity as the naturally preference of social interactivity. We would do well to heed in our human, supposedly religious, societies which are actually rift with the opposite, competitive, me vs. We, behaviors.

Cooperation by generalised reciprocity implies that individuals apply the decision rule “help anyone if helped by someone”. This mechanism has been shown to generate evolutionarily stable levels of cooperation, but as yet it is unclear how widely this cooperation mechanism is applied among animals. Dogs (Canis familiaris) are highly social animals with considerable cognitive potential and the ability to differentiate between individual social partners. Here we show that dogs trained in an instrumental cooperative task to provide food to a social partner help conspecifics more often after receiving help from a dog before. Apparently, dogs use the simple decision rule characterizing generalised reciprocity, although they are probably capable of using the more complex decision rule of direct reciprocity: “help someone who has helped you”. However, generalized reciprocity involves lower information processing costs and is therefore a cheaper cooperation strategy. Our results imply that generalised reciprocity might be applied more commonly than direct reciprocity also in other mutually cooperating animals. (Abstract)

Ghoul, Melanie, et al. Sociomics: Using Omic Approaches to Understand Social Evolution. Trends in Genetics. 33/6, 2017. To advance these studies, since genetic techniques have gained a robust maturity, Oxford University and New York University zoologists including Stuart West propose a novel application of methylation, transcriptome, metabolome, and proteome methods. By their lights, the presence of symbiosis, labor division, cooperators or cheators, and more can be illumed in animal groupings. A starter level would be microbial and insect colonies where whole-genome sequencing is related to social dynamics. See also Division of Labor in Microorganisms: An Evolutionary Perspective by West and Guy Cooper in Nature Microbiology (14/11, 2016).

All of life is social, from genes cooperating to form organisms, to animals cooperating to form societies. Omic approaches offer exceptional opportunities to solve major outstanding problems in the study of how sociality evolves. First, omics can be used to clarify the extent and form of sociality in natural populations. This is especially useful in species where it is difficult to study social traits in natural populations, such as bacteria and other microbes. Second, omics can be used to examine the consequences of sociality for genome evolution and gene expression. This is especially useful in cases where there is clear variation in the level of sociality, such as the social insects. Major tasks for the future are to apply these approaches to a wider range of non-model organisms, and to move from exploratory analyses to the testing of evolutionary theory. (Abstract)

Giardina, Irene. Collective Behavior in Animal Groups: Theoretical Models and Empirical Studies. HFSP Journal. 2/4, 2008. This free online and paper journal stands for Human Frontier Science Program: Frontiers of Interdisciplinary Research in the Life Sciences, and is supported by a research consortium from Tokyo to Strasbourg. Living up to its mission, this report by a Centre for Statistical Mechanics and Complexity, University of Rome, (Google for info) physicist achieves a novel advance for nonlinear science. As not possible earlier, not only is an exemplary complex, agent-based self-organization described for avian bird flocks, specifically starlings, but this activity, widespread across animal communities from microbes and insects to primates and economies, is seen to imply and spring from a general, independent, informative source. A vital discernment is thus achieved of such a dual, dimension which has been heretofore missed or rejected so that only relative chaotic complexity is apparent, sans an endemic, natural direction or drive.

Collective phenomena in animal groups have attracted much attention in the last years, becoming one of the hottest topics in ethology. There are various reasons for this. On the one hand, animal grouping provides a paradigmatic example of self-organization, where collective behavior emerges in absence of centralized control. The mechanism of group formation, where local rules for the individuals lead to a coherent global state, is very general and transcends the detailed nature of its components. (Abstract, 205)

In this context, the origin and emergence of collective behavior have been understood in great detail, and this is why physics is often regarded as an inspiration source for interpreting and modeling collective phenomena in other fields. There are at least two main facts…. (i) A system of individual units that interact locally in space can generate, under appropriate conditions, an ordered state with collective global properties. (ii) The mechanisms leading to collective behavior are very general; for example, the large scale features of many order-disorder transitions do not depend on the details of the local interaction….what is known as universality. These two properties, locality of the interactions and universality, have been thoroughly proven in physics. (206)

Goldstone, Robert and Todd Gureckis. Collective Behavior. Topics in Cognitive Science. 1/3, 2009. A survey article for an issue about how novel insights via nonlinear dynamics and other methods now quantify that creaturely groups, especially human communities, can achieve and possess “an integrity of their own” which, as information processing systems, gains a modicum of cognitive acuity. See also Moussaid, et al, below from the same issue. The upshot, which guides this website, as the authors do allude, is that worldwide humankind ought to be seen, in our internetworked century, as coming to its own palliative knowledge.

The resurgence of interest in collective behavior is in large part due to tools recently made available for conducting laboratory experiments on groups, statistical methods for analyzing large data sets reflecting social interactions, the rapid growth of a diverse variety of online self-organized collectives, and computational modeling methods for understanding both universal and scenario-specific social patterns. We consider case studies of collective behavior along four attributes: the primary motivation of individuals within the group, kinds of interactions among individuals, typical dynamics that result from these interactions, and characteristic outcomes at the group level. With this framework, we compare the collective patterns of noninteracting decision makers, bee swarms, groups forming paths in physical and abstract spaces, sports teams, cooperation and competition for resource usage, and the spread and extension of innovations in an online community. (Abstract, 412)

Gordon, Deborah. Measuring Collective Behavior: An Ecological Approach. Theory in Biosciences. Online September, 2019. For a special Quantifying Collectivity issue, the Stanford University bioecologist and expert ant colony student in the Arizona desert adds one more affirmation of life’s organic persistence to join into social groupings for their many benefits.

Collective behavior is ubiquitous throughout nature. Many systems from brains to ant colonies are regulated by interactions among the individual participants without central control. Interactions create feedback that produce the outcome, the behavior that we observe: Brains via neurons think and remember, ant colonies collect food or move nests, flocks of birds turn, human societies develop new forms of social organization. But the processes by which interactions produce outcomes are as diverse as the behavior itself. Just as convergent evolution has led to organs, such as the eye, that are similar in function but based on different physiological processes, so it has led to forms of collective behavior that appear similar but arise from different social processes. (Abstract)

Gordon, Deborah. The Evolution of the Algorithms for Collective Behavior. Cell Systems. 3/December, 2016. After years of studying insect colonies in the Arizona desert, the Stanford University behavioral zoologist theorizes a mathematical basis for their beneficial self-organizing, complex adaptive systems behavior.

Collective behavior is the outcome of a network of local interactions. Here, I consider collective behavior as the result of algorithms that have evolved to operate in response to a particular environment and physiological context. I discuss how algorithms are shaped by the costs of operating under the constraints that the environment imposes, the extent to which the environment is stable, and the distribution, in space and time, of resources. I suggest that a focus on the dynamics of the environment may provide new hypotheses for elucidating the algorithms that produce the collective behavior of cellular systems. (Abstract)

Grueter, Cyril, et al. Multilevel Organization of Animal Society. Trends in Ecology and Evolution. May, 2020. Sixteen researchers posted in Australia, China, Germany, the USA, Switzerland, and India including Larissa Swedell describe how animal groupings typically array into multiple nested networked units. And we note that a diagram display of this threading out appears as another epitome of life’s iterative evolutionary emergence whether bodies, brains or organisms.

Multilevel societies (MLSs), stable nuclear social units within a larger collective with multiple nested social levels, occur in several mammalian lineages. Their architectural complexity and size impose require their members to find adaptive solutions in disparate domains. Here, we propose a unifying terminology and operational definition of MLS. To identify new avenues for integrative research, we synthesise current literature on the selective pressures underlying the evolution of MLSs and their implications for cognition, intersexual conflict, and sexual selection. Mapping the drivers and consequences of MLS provides a reference point for the social evolution of many taxa, including our own species. (Abstract)

Grund, Thomas, et al. How Natural Selection Can Create Both Self- and Other-Regarding Preferences, and Networked Minds. Nature Scientific Reports. 3/1480, 2013. It is well to note that concurrent papers across scalar realms from immune systems (Bransburg-Zabary), microbes (Jaeger), insects, birds, people (Yong, Couzin), animal groups (Noam Miller) to digital ecosystems (Fortuna), each report a viable systemic reciprocity of an entity mode (bacteria, starlings) and communal unity (colony, flock). By our global witness, the presence of such an independent, salutary principle of individual-group complementarity is most evident. With Christian Waloszek and Dirk Helbing, ETH Zurich social physicists here describe a mutual interaction between a person’s commercial interests and a cooperative societal consideration. But while this node/network balance is extolled, which would altogether imply an independent program or source at work, it is remains attributed to selective forces alone.

Biological competition is widely believed to result in the evolution of selfish preferences. The related concept of the ‘homo economicus’ is at the core of mainstream economics. However, there is also experimental and empirical evidence for other-regarding preferences. Here we present a theory that explains both, self-regarding and other-regarding preferences. Assuming conditions promoting non-cooperative behaviour, we demonstrate that intergenerational migration determines whether evolutionary competition results in a ‘homo economicus’ (showing self-regarding preferences) or a ‘homo socialis’ (having other-regarding preferences). Our model assumes spatially interacting agents playing prisoner’s dilemmas, who inherit a trait determining ‘friendliness’, but mutations tend to undermine it. Reproduction is ruled by fitness-based selection without a cultural modification of reproduction rates. Our model calls for a complementary economic theory for ‘networked minds’ (the ‘homo socialis’) and lays the foundations for an evolutionarily grounded theory of other-regarding agents, explaining individually different utility functions as well as conditional cooperation. (Abstract)

In conclusion, we offer an over-arching theoretical perspective that could help to overcome the historical controversy in the behavioural sciences between largely incompatible views about human nature. Both, self-regarding and other-regarding types of humans may result from the same evolutionary process. Whereas high levels of intergenerational migration promote the evolution of a ‘homo economicus’, low levels of intergenerational migration promote a ‘homo socialis’, even under ‘Darwinian’ conditions of a survival of the fittest and random mutations. The significance of local reproduction for the evolution of other-regarding preferences is striking and may explain why such preferences are more common in some parts of the world than in others. (4)

A great share of economic literature is based on the assumption of the ‘homo economicus’, who takes decisions without considering the payoff or utility of others. In contrast to this traditional view, the ‘homo socialis’ never takes independent decisions, if the behaviour has external effects. We might characterise this as a situation of ‘networked minds’, where everybody is trying to put himself or herself into other people’s shoes, to take into account their utilities in the decision-making process. (4) A theory of networked minds could make a significant contribution to the convergence of the behavioural sciences, and it might also shed new light on social capital, power, reputation and value, and create a fundamentally new understanding of these. We believe that this view can stimulate a huge and exciting field of research, and lead to a complementary theory to the one based on the ‘homo economicus.’ (4)

Guimaraes, Paulo, et al. Vulnerability of a Killer Whale Social Network to Disease Outbreaks. Physical Review E. 76/042901, 2007. Even small pods of 50 or so orcas can exhibit a small world, non-random scale-free network. Our novel human ability to discover such common system complexities can then inform activities to detect and contain disease vectors in animal populations.

Guzman, Diego, et al. The Fractal Organization of Ultradian Rhythms in Avian Behavior. Nature Scientific Reports. 7/684, 2017. University of Cordova and Johns Hopkins University researchers contribute to our total quantification of every phase of natural and social activity by way of a common mathematical dynamics, which is then being found in this example to reliably repeat in kind at each and every phase and instance.

Living systems exhibit non-randomly organized biochemical, physiological, and behavioral processes that follow distinctive patterns. In particular, animal behavior displays both fractal dynamics and periodic rhythms yet the relationship between these two dynamic regimens remain unexplored. Herein we studied locomotor time series of visually isolated Japanese quails sampled every 0.5 s during 6.5 days (>106 data points). These high-resolution, week-long, time series enabled simultaneous evaluation of ultradian rhythms as well as fractal organization according to six different analytical methods that included Power Spectrum, Enright, Empirical Mode Decomposition, Wavelet, and Detrended Fluctuation analyses. This is the first demonstration that avian behavior presents fractal organization that predominates at shorter time scales and coexists with synchronized ultradian rhythms. This chronobiological pattern is advantageous for keeping the organism’s endogenous rhythms in phase with internal and environmental periodicities, notably the feeding, light-dark and sleep-wake cycles. (Abstract)

Hammerstein, Peter and Edward Hagen. The Second Wave of Evolutionary Economics in Biology. Trends in Ecology and Evolution. 20/11, 2005. In the 1970’s and 1980’s, biologists and economists borrowed concepts from each other such as optimal foraging theory, game theory, and analogies between adaptation by natural selection and rational decision making. But the two disciplines had little interaction. Recently a new phase of joint exploration has commenced which this article documents. One result is an appreciation of “a desire for prosocial outcomes that value the welfare of others.”

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