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

5. Cooperative Member/Group Societies

Sosna, Matthew, et al. Individual and Collective Encoding of Risk in Animal Groups. Proceedings of the National Academy of Sciences. 116/20556, 2019. A seven person group from Princeton, University of Pennsylvania, Arizona State (Bryan Daniels), Humboldt University and MPI Animal Behavior (Iain Couzin) well quantify that a dynamic mutual interactivity of member creatures within their overall flock, troop, clan,, pod or herd and serves an optimum survival. Each entity is seen to possess a vital degree of autonomy and liberty rather than subservience to a communal totality. Once again, a complementary, ubuntu-like reciprocity seems to prevail across Metazoan species.

Many biological systems exhibit an emergent ability to process information about their environment. This collective cognition occurs due to the behavior of components and of their interactions, yet the relative importance of the two is often hard to disentangle. Here, we combined experiments and modeling to study how fish schools encode information about the external environment. We find that risk is mainly encoded in the physical structure of groups, which individuals modulate to augment or dampen behavioral cascades. We show that this modulation causes overall reactions to spread and allows collective systems to be responsive to their environments. (Abstract)

Sridhar, Vivek, et al. The Geometry of Decision-Making in Individuals and Collectives. PNAS. 118/50, 2021. This December entry by eight systems scientists at MPI Animal Behavior (Iain Couzin), University of Konstanz, Eotvos Lorand University, Budapest, University of Waterloo, Canada and Weizmann Institute of Science, Israel is a good example of the present degree to which creaturely behaviors and movements can be seen to rise from and express a common independent, mathematical source. When we first set up this section circa 2002 any dimension like this was hardly considered. Two decades of collaborative worldwise science studies like this have by now proven such a pervasive, genomic-like occasion.

Almost all animals must make decisions on the move. Here we cite an approach that integrates theory and high-throughput experiments (using state-of-the-art virtual reality), which reveals that there exist fundamental geometrical principles that result from the inherent interplay between movement and organisms’ internal representation of space. We find that animals spontaneously reduce the world into a series of sequential binary decisions, a response that facilitates effective decision-making and is robust both to the number of options available and to context, such as whether options are static or mobile (e.g., other animals). We present evidence that these same principles apply across scales of biological organization, from individual to collective decision-making. (Significance)

We demonstrate that, across taxa and contexts, a consideration of the time-varying geometry during spatial decision-making provides key insights that help understand how and why animals move the way they do. The features revealed here are highly robust, and occur in decision-making processes across various scales of biological organization from individuals to animal collectives suggesting they are fundamental features of spatiotemporal computation. (Conclusion)

Steen, David, et al. Conceptualizing Communities as Natural Entities. Biology & Philosophy. Online September, 2017. Steen, Auburn University, Kyle Barrett, Clemson University, Ellen Clarke, Oxford University and Craig Guyer, University of Leeds, propose that the pervasive presence of creaturely group assemblies merit more recognition and attention than they have received with regard to effective ecosystem remedial sustainability.

Recent work has suggested that conservation efforts such as restoration ecology and invasive species eradication are largely value-driven pursuits. Concurrently, changes to global climate are forcing ecologists to consider if and how collections of species will migrate, and whether or not we should be assisting such movements. Herein, we propose a philosophical framework which addresses these issues by utilizing ecological and evolutionary interrelationships to delineate individual ecological communities. Specifically, our Evolutionary Community Concept (ECC) recognizes unique collections of species that interact and have co-evolved in a given geographic area. Specifically, our framework allows us to establish a biological and science-driven context for making decisions regarding the restoration of systems and the removal of exotic species. The ECC also has implications for how we view shifts in species assemblages due to climate change and it advances our understanding of various ecological concepts, such as resilience. (Abstract)

Sterelny, Kim, et al, eds. Cooperation and Its Evolution. Cambridge: MIT Press, 2013. Akin to the 2013 MIT volume From Groups to Individuals (search Bouchard), the theoretic turn to admit persistent, mutually shared, support between animal members as a survival factor has now gained wide agreement. The Introduction by editors KS, Richard Joyce, Brett Calcott, and Ben Fraser is The Ubiquity, Complexity, and Diversity of Cooperation, see the second quote. A notable aspect of the book is to situate animal propensities to form viable assemblies within the major transition scale, whence a reciprocity of competition and cooperation fosters emergent levels of individuality. Typical chapters are “Culture-Gene Coevolution, Large-Scale Cooperation, and Human Social Psychology” by Maciek Chudek, Wanying Zhao, and Joseph Henrich, “What can Imitation do for Cooperation?” Cecilia Heyes, and “Timescales, Symmetry, and Uncertainty Reduction in the Origins of Hierarchy in Biological Systems” by Jessica Flack, Doug Erwin, Tanya Elliot, and David Krakauer.

This collection reports on the latest research on an increasingly pivotal issue for evolutionary biology: cooperation. The chapters explore a wide taxonomic range, concentrating on bacteria, social insects, and, especially, humans. Part I ("Agents and Environments") investigates the connections of social cooperation in social organizations to the conditions that make cooperation profitable and stable, focusing on the interactions of agent, population, and environment. Part II ("Agents and Mechanisms") focuses on how proximate mechanisms emerge and operate in the evolutionary process and how they shape evolutionary trajectories. Throughout the book, certain themes emerge that demonstrate the ubiquity of questions regarding cooperation in evolutionary biology: the generation and division of the profits of cooperation; transitions in individuality; levels of selection, from gene to organism; and the "human cooperation explosion" that makes our own social behavior particularly puzzling from an evolutionary perspective. (Publisher)

One overarching trend in the history of life has been an increase in complexity: from prebiotic and marginally biotic systems of various kinds, to prokaryotes, eukaryotes, multicellular organisms, and social collectives. Buss, Maynard Smith, and Szathmary all pointed out that this macroevolutionary pattern of increasing maximal complexity depended on a series of revolutions in cooperation, as more complex evolutionary agents (metazoans, eusocial insects colonies) emerged out of cooperatively interacting simpler ones. Groups become new evolutionary individuals as the members of those groups go through an evolutionary transition from independence through contingent cooperation to mandatory cooperation. Transitions in individuality, then, seem to imply a shift in the unit of selection: Composite agents evolve from collectives, but composites themselves are differentially fit, mot merely groups of individuals with competing fitness interests. (5)

Strassmann, Joan and David Queller. The Social Organism. Evolution. 64/3, 2010. Rice University evolutionary ecologists contribute to the shifting paradigm from only competition rules to new appreciations by way of scientific theories and philosophic musings of how actually pervasive and palliative across nested cellular and creaturely kingdoms is cooperative behavior.

We propose that what makes an organism is nearly complete cooperation, with strong control of intraorganism conflicts, and no affiliations above the level of the organism as unified as those at the organism level. Organisms can be made up of like units, which we call fraternal organisms, or different units, making them egalitarian organisms. Previous definitions have concentrated on the factors that favor high cooperation and low conflict, or on the adapted outcomes of organismality. Our approach brings these definitions together, conceptually unifying our understanding of organismality. Although the organism is a concerted cluster of adaptations, nearly all directed toward the same end, some conflict may remain. To understand such conflict, we extend Leigh's metaphor of the parliament of genes to include parties with different interests and committees that work on particular tasks. (605)

Su, Qi, et al. Evolutionary Dynamics with Stochastic Game Transitions. arXiv:1905.10269. Harvard University mathematicians including Martin Nowak explain why creaturely groupings seem to have an inherent drive and incentive toward beneficial cooperative behaviors versus negative selfishness. See also Su, Qi, et al Spatial Reciprocity in the Evolution of Cooperation by Qi Su, et al in the Proceedings of the Royal Society B. (Vol.286/Iss.1900, 2019) for another analysis that reaches a similar conclusion.

The environment has a strong influence on a population's evolutionary dynamics. Driven by both intrinsic and external factors, the environment is subject to continuous change in nature. To model an ever-changing environment, we develop a framework of evolutionary dynamics with stochastic game transitions, where individuals' behaviors together with the games they play in one time step decide the games to be played next time step. We then study the evolution of cooperation in structured populations and find a simple rule: natural selection can favor cooperation over defection. We show that even if each individual game opposes cooperation, allowing for a transition between them can result in a favorable outcome for cooperation. Our work suggests that interdependence between the environment and the individuals' behaviors may explain the large-scale cooperation in realistic systems even when it is expensive relative to its benefit. (Abstract excerpt)

Sueur, Cedric, et al. Mechanisms of Network Evolution: A Focus on Socioecological Factors. Primates. 60/3, 2019. This is a lead article in an issue on Social Networks Analyses in Primates: A Multilevel Perspective by University of Strasbourg, Kyoto University, Sun Yat-sen University and University of Agder, Norway system primatologists. They report that simian groupings, as they formed viable niches, can be found to spontaneously exhibit similar interconnective linkages as most everywhere else. See also in this issue Social Style and Resilience of Macaques Networks by Ivan Puga-Gonzalez, et al and Using Multiplex Networks to Capture the Multidimensional nature of Social Structure by Sandra Smith-Aguilar.

Since group-living animals are embedded in a network of social interactions, socioecological factors may not only affect individual behaviors but also group-level social interactions, i.e., the network structure. These co-variations between socioecological factors, individual behavior, and group-level structure are important to study since they may strongly influence animal health outcomes and reproductive success. This paper reviews how causal factors (food distribution, predation, and infectious agent risk), via intermediary mechanisms (stress, information sharing, and mating system), may affect individual behavior and social network topology. We conclude that studies focusing on how well networks resist changing conditions might provide a better understanding of underlying individual behavior, a process we have called network evolution. Evolutionary processes may favor a group phenotypic composition, thus a network topology, aka “collective social niche construction”. (Abstract excerpts)

Sumpter, D. J. T.. The Principles of Collective Animal Behavior. Philosophical Transactions of the Royal Society B. 361/5, 2006. A post-doctoral zoologist at Oxford University provides an exemplary, well-written paper on how the new sciences of complex dynamic systems are revealing pervasive tendencies for animal groupings to take on cooperative, salutary structures. From ant trails to flocks, schools, and human crowds, the same principles and processes which marry individual and society can now be quantified and understood.

The central tenet of self-organization is that simple repeated interactions between individuals can produce complex adaptive patterns as the level of the group. (5) I argue that the key to understanding collective behavior lies in identifying the principles of the behavioural algorithms followed by individual animals and of how information flows between the animals. These principles, such as positive feedback, response thresholds and individual integrity, are repeatedly observed in very different animal societies. (5) Ultimately, this research could inform not only our understanding of animal societies, but also the principles by which we organize our own society. (5)

Sumpter, David. Collective Animal Behavior. Princeton: Princeton University Press, 2010. Over the past years, the realization that social creatures prevail by way of common modes of group reciprocities has reached the point that an Uppsala University mathematician can provide a cogent theoretical review. Researchers in this field are seen to engage two aspects – detailed quantifications of bird flock or fish pod dynamics, for example, or since in every case the same topologies recur, to discern general, phenomenal patterns and laws. I n line with biological norms, two approaches are thus followed – a “mechanistic” view of just “how” animals interact, or a “functional” approach as to “why” they do so.

Throughout this book, I emphasize how the same mechanisms arise again and again in many different systems. Mathematical models formalize these logical connections between systems. For some scientists this gives these models and the principles that underlie them an equal, if not greater, importance than natural selection. (11)

Sumpter, David, et al. Using Activity and Sociability to Characterize Collective Motion. Philosophical Transactions of the Royal Society B. Vol.373/Iss.1746, 2018. Uppsala University and Stockholm University systems zoologists including James Herbert-Read describe the latest methods for better quantifications of life’s universal propensity to form viable member/commune groupings from amoebas and prokaryotes to our ecovillages. In this Collective Movement in Ecology issue, such integral assemblies are seen to attain a relative personality, emergent sensitivity, collective intelligence, and social learning as they survive and evolve.

A wide range of measurements can be made on the collective motion of groups, and the movement of individuals within them. These include group size, polarization, speed, turning speed, speed or directional correlations, and distances to near neighbours, which help capture biologically meaningful aspects of an animal's behaviour and contribute to its survival chances. Here, we use a factor analysis to identify two main axes of collective motion in guppies: (i) sociability, which corresponds to attraction (and to a lesser degree alignment) to neighbours, and (ii) activity, which combines alignment with directed movement. We suggest that the activity and sociability axes provide a useful framework for measuring the behaviour of animals in groups, allowing the comparison of individual and collective behaviours within and between species. (Abstract excerpt)

Tokita, Christopher and Corina Tarnita. Social Influence and Interaction Bias can Drive Emergent Behavioural Specialization and Modular Social Networks Across Systems. Journal of the Royal Society Interface. January, 2020. Princeton University evolutionary ecologists identify how complex adaptive system features such as diverse group modules, and appropriation of tasks are present and evident for many animal species. See also Fitness Benefits and Emergent Division of Labour at the Onset of Group Living by Y. Ulrich, et al (C. Tarnita) in Nature (560/635, 2018).

In social systems ranging from ant colonies to human society, consistent differences in behavior are common. Individuals can specialize in tasks they perform (division of labour DOL), their political poles, or various personalities they exhibit. Behavioural specialization often co-occurs with modular and assortative social networks as entities tend to associate with similar others. We then wonder whether the same mechanism could drive co-emergent social network structures. Here we extend a model of self-organized DOL to account for influence and interaction bias among various social dynamics. Our findings suggest that DOL and political polarization—two social phenomena not typically considered together—may actually share a common core. (Abstract excerpt)

Torney, Colin, et al. Context-dependent Interaction Leads to Emergent Search Behavior in Social Aggregates. Proceedings of the National Academy of Sciences. 106/22055, 2009. A contribution to the growing appreciation that animal societies from microbes to a metropolis can be in fact modeled as self-organizing complex adaptive systems.

Instead, our method is based on the collective behavior of autonomous individuals following simple social interaction rules which are modified according to the local conditions they are experiencing. Through these context-dependent interactions, the group is able to locate the source of a chemical signal and in doing so displays an awareness of the environment not present at the individual level. This behavior illustrates an alternative pathway to the evolution of higher cognitive capacity via the emergent, group-level intelligence that can result from local interactions. (22055)

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