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A Sourcebook for the Worldwide Discovery of a Creative Organic Universe
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Genesis Vision
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V. Life's Corporeal Evolution Develops, Encodes and Organizes Itself: An EarthWinian Genesis Synthesis

5. Cooperative Member/Group Societies

Ioannou, Christos and Kate Laskowski. A Multi-scale Review of the Dynamics of Collective Behavior: From Rapid Responses to Ontogeny to Evolution. Philosophical Transactions of the Royal Society B. February, 2023. University of Bristol and UC, Davis bioecologists introduce and survey a special collection from a 2022 Royal Society topical meeting. An overall view then describes a recurrent self-organization process in unifying effect. As the select papers below note, once more into these 2020s another take on a steady evolutionary propensity to move toward, gain and avail a group-wide, beneficial social intelligence is persistently evident.

See for example Ontogeny of Collective Behavior by Isabella Muratore and Simon Garnier; A Study of Transfer of Information in Animal Collectives using Deep Learning Tools by Francisco Romero-Ferrero, et al.; Molecular Patterns and Processes in Evolving Sociality: Lessons from Insects by Seirian Sumner, et al.; The Evolution of Intergroup Cooperation by Antonio Rodigues; and Inferring Social Influence in Animal Groups across Multiple Timescales by Vivek Sridhar, et al.

Collective behaviours, such as flocking in birds or decision making by bee colonies, exhibit intriguing behavioural phenomena in the animal kingdom. Their study often focuses on interactions between individuals within groups which occur over close ranges and short timescales. A further aspect is how they drive larger scale properties such as group size, information transfer and group-level decision making. Here, we view collective behaviour from short to longer frames so to gain better understandings all the way to developmental and evolutionary biology. (Ioannou Excerpt)

Jayles, Bertrand, et al. Collective Information Processing in Human Phase Separation. Philosophical Transactions of the Royal Society B. July, 2020. In this same Collective Migration in Biological Systems issue, nine University of Toulouse researchers proceed to trace commonly recurrent people behavioral patterns all the way to deep physical phenomena. Our review issue introduction review (A. Deutsch herein) thus makes a proposal that in mid 2020, if of a mind to view and allow, a revolutionary genesis universe with its own genetic-like source code program has been well documented and explained.

In our digital societies, individuals interact through interfaces whose impact on collective dynamics can be important. In some contexts, segregation processes of human groups have been shown to share similarities with phase separation phenomena in physics. Here, we study the effect of information filtering on collective segregation behaviour of human groups. We introduce a model that describes the random motion of a group of pedestrians in a confined space, and which faithfully reproduces and allows interpretation of the results. (Abstract)

Johnson, Craig and Maarten Boerlijst. Selection at the Level of the Community. Trends in Ecology & Evolution. 17/2, 2002. The increased recognition of a sequential evolutionary scale is helped by how the same nonlinear spiral pattern recurs at each stage. As evident in bacteria and symbiotic cells, aggregate groups or societies employ an interplay of semi-autonomous individuals and modular “subcommunities” which locally interact to create and maintain a coherent, emergent organization.

Recently developed models show that spatial self-structuring in multispecies systems can…provide a rich substrate for community-level selection and a major transition in evolution. (83)

Jolles, Jolle, et al. Consistent Individual Differences Drive Collective Behavior and Group Functioning of Schooling Fish. Current Biology. Online September, 2017. As such studies of ubiquitous self-organized animal groupings become ever more sophisticated, Cambridge University and MPI Ornithology behavioral zoologists including Iain Couzin can move from overall dynamic formations to the complementary, interactive influences of semi-autonomous individual members.

The ubiquity of consistent inter-individual differences in behavior (“animal personalities”) suggests that they might play a fundamental role in driving the movements and functioning of animal groups, including their collective decision-making, foraging performance, and predator avoidance. Despite increasing evidence that highlights their importance, we still lack a unified mechanistic framework to explain and to predict how consistent inter-individual differences may drive collective behavior. These effects of consistent individual differences on group-level states emerged naturally from a generic model of self-organizing groups composed of individuals differing in speed and goal-orientedness. Our study provides experimental and theoretical evidence for a simple mechanism to explain the emergence of collective behavior from consistent individual differences, including variation in the structure, leadership, movement dynamics, and functional capabilities of groups, across social and ecological scales. In addition, we demonstrate individual performance is conditional on group composition, indicating how social selection may drive behavioral differentiation between individuals. (Abstract excerpts)

Jolles, Jolle, et al. The Role of Individual Heterogeneity in Collective Animal Behavior. Trends in Ecology and Evolution. Online December, 2019. Jolle J, MPI Animal Behavior, Andrew King, Swansea University, UK, and Shuan Killen, University of Glasgow scope out ways that an array of diverse member behaviors can actually foster their overall group cohesion and viability.

Social grouping is omnipresent in the animal kingdom. Considerable research has focused on understanding how animal groups form and function, including how collective behaviour emerges via self-organising mechanisms and how phenotypic variation drives the behaviour and functioning of animal groups. Here we present a common framework to quantify heterogeneity in the literature so as to explain and predict its role in collective behaviour across species, contexts, and traits. We show that member diversity provides a key intermediary factor with regard to group structure, functioning, response to environmental change, and evolution. (Abstract)

Joshi, Jaideep, et al. Mobility can Promote the Evolution of Cooperation via Emergent Self-Assortment Dynamics. PLoS Computational Biology. September 2017, 2017. Jaideep and Vishwesh Guttal, Indian Institute of Science with Iain Couzin, MPI Ornithology, and Simon Levin, Princeton University, achieve further insights into how animal groupings seem to behave in such a way as to improve their composite advantage.

The evolution of costly cooperation, where cooperators pay a personal cost to benefit others, requires that cooperators interact more frequently with other cooperators. This condition, called positive assortment, is known to occur in spatially-structured viscous populations, where individuals typically have low mobility and limited dispersal. However many social organisms across taxa, from cells and bacteria, to birds, fish and ungulates, are mobile, and live in populations with considerable inter-group mixing. Our results offer insights into differential adhesion based mechanisms for positive assortment and reveal the possibility of cooperative aggregations in dynamic fission-fusion populations. (Abstract excerpt)

Kao, Albert, et al. Collective Learning and Optimal Consensus Decisions in Social Animal Groups. PLoS Computational Biology. Online August, 2014. As the Abstract explains, a Princeton University team including Iain Couzin quantifies the presence among fluid creaturely communities of an overall intelligent, cognitive capacity to think and act on their own. By extension could we imagine that composite, collaborative humankind, reflected in this article, and millions more in cyberspace, is similarly coming to her/his own knowledge. By a ready, obvious shift, the premise of our website, a grand new domain of natural wisdom and guidance we so desperately need could be in our midst for the asking.

Learning has been studied extensively in the context of isolated individuals. However, many organisms are social and consequently make decisions both individually and as part of a collective. Reaching consensus necessarily means that a single option is chosen by the group, even when there are dissenting opinions. This decision-making process decouples the otherwise direct relationship between animals' preferences and their experiences (the outcomes of decisions). Instead, because an individual's learned preferences influence what others experience, and therefore learn about, collective decisions couple the learning processes between social organisms. This introduces a new, and previously unexplored, dynamical relationship between preference, action, experience and learning.

Here we model collective learning within animal groups that make consensus decisions. We reveal how learning as part of a collective results in behavior that is fundamentally different from that learned in isolation, allowing grouping organisms to spontaneously (and indirectly) detect correlations between group members' observations of environmental cues, adjust strategy as a function of changing group size (even if that group size is not known to the individual), and achieve a decision accuracy that is very close to that which is provably optimal, regardless of environmental contingencies. Because these properties make minimal cognitive demands on individuals, collective learning, and the capabilities it affords, may be widespread among group-living organisms. (Abstract)

Kappeler, Peter and Carel van Schaik, eds. Cooperation in Primates and Humans. Berlin: Springer, 2006. Reports from interdisciplinary theory and field studies by evolutionary biologists, primatologists, and anthropologists who discuss new admissions and understandings of pervasive cooperative behavior, long at odds with strict Darwinism.

Kappeler, Peter, et al. Social Complexity: Patterns, Processes, and Evolution. Behavioral Ecology and Sociobiology. 73/1, 2019. PK, Leibniz Institute for Primatology, Gottingen, Tim Clutton-Brock, Cambridge University, Susanne Shultz, University of Manchester, and Dieter Lukas, MPI Evolutionary Anthropology introduce a Topical Collection with this title so to review and advance the field. See, e.g., A Framework of Studying social Complexity, Teaching and Curiosity as Drivers of Cumulative Cultural Evolution in the Hominin Lineage, and Kinship, Association and Social Complexity in Bats.

Animal and human societies exhibit extreme diversity in the size, composition and cohesion of their social units with regard to sex-specific reproductive skew, parental care, form and frequency of cooperation, and their competitive regime creating a wide array of complex societies. However, there is an ongoing debate about whether these are real, emergent properties of a society or only a framework for studying the diversity and evolution of societies. In this introduction, we identify three areas of current research that address the study of social complexity. First, previous studies have suffered from a lack of common concepts and shared definitions. Second, features such as intraspecific variation and interactions in social complexity have been overlooked. Third, comparative studies offer can explore biological causes and correlates but the identify the causal relationships are elusive. (Abstract edits)

Kattas, Graciano, et al. Generating Self-Organizing Collective Behavior Using Separation Dynamics from Experimental Data. Chaos. Online July, 2012. In a paper that could be seen, in a way, to summarize a decade of proving how such universal nonlinear dynamics in fact distinguish and drive animal assemblies of every stripe, feather, and domain, Hong Kong Polytechnic University, Qingdao Technological University, and University of Western Australia researchers go on to articulate both their experimental and theoretical essences.

Mathematical models for systems of interacting agents using simple local rules have been proposed and shown to exhibit emergent swarming behavior. Most of these models are constructed by intuition or manual observations of real phenomena, and later tuned or verified to simulate desired dynamics. In contrast to this approach, we propose using a model that attempts to follow an averaged rule of the essential distance-dependent collective behavior of real pigeon flocks, which was abstracted from experimental data. By using a simple model to follow the behavioral tendencies of real data, we show that our model can exhibit a wide range of emergent self-organizing dynamics such as flocking, pattern formation, and counter-rotating vortices. (Abstract)

Kelley, Douglas and Nicholas Ouellette. Emergent Dynamics of Laboratory Insect Swarms. Nature Scientific Reports. 3/1073, 2013. The journal Subject Areas for this paper are cited as Biological Physics, Statistical Physics, Nonlinear Dynamics, Behavioral Ecology, Emergence. MIT and Yale researchers find the same complex, self-organizing system behaviors that infuse every animal kingdom to similarly guide the movements of small, two-winged midge flies. Again a reciprocity of discrete entities and constant fluid interrelations are found to produce the characteristic swarm geometries. One may witness their cloud as if a 3-dimensional graph of the implicate mathematics that spawn them. Irene Giardina (search) and her group find starling flocks to visually behave the same way. By way of a natural philosophy reflection, this ubiquitous phenomena begs to be seen in its dual phases of universal manifestation, and independent, mathematical, indeed genetic-like source.

Collective animal behaviour occurs at nearly every biological size scale, from single-celled organisms to the largest animals on earth. It has long been known that models with simple interaction rules can reproduce qualitative features of this complex behaviour. But determining whether these models accurately capture the biology requires data from real animals, which has historically been difficult to obtain. Here, we report three-dimensional, time-resolved measurements of the positions, velocities, and accelerations of individual insects in laboratory swarms of the midge Chironomus riparius. Even though the swarms do not show an overall polarisation, we find statistical evidence for local clusters of correlated motion. We also show that the swarms display an effective large-scale potential that keeps individuals bound together, and we characterize the shape of this potential. Our results provide quantitative data against which the emergent characteristics of animal aggregation models can be benchmarked. (Abstract)

Spontaneous, collective biological activity—in swarms, flocks, schools, herds, or crowds—has evolved independently across the entire biological size spectrum, from single cells to insects, birds or fish. Nature has found such self-organized behaviour to be a robust, simple solution to a broad range of biological problems. The ubiquity of emergent collective behaviour suggests that it may arise from relatively simple interactions between individuals—and indeed, a vast literature on modelling animal aggregations has developed over the past few decades. Models with simple rules have been shown to reproduce, at least qualitatively, patterns and behaviours observed in the wild, including bulk alignment or polarisation, milling, swarming, aggregation, and predator avoidance. (1)

Kennedy, Patrick, et al. Deconstructing Superorganisms and Societies to Address Big Questions in Biology. Trends in Ecology & Evolution. Online September, 2017. A fourteen person group from the Universities of Bristol, London, Copenhagen, Helsinki, and Oxford once more consider how to express a persistent tendency of organisms to merge together for survival benefits. If these assemblies gain a sufficient integrity such a colonial groupings can be seen as a relative individual in its own right. Circa 2017 this old issue can now be informed by advances in major evolutionary transitions theory, eusociality, reproductive divisions of labor, biological heterogeneity, epigenetics, social immunity, transcriptomics and so on. A significant contribution.

Social insect societies are long-standing models for understanding social behaviour and evolution. Unlike other advanced biological societies (such as the multicellular body), the component parts of social insect societies can be easily deconstructed and manipulated. Recent methodological and theoretical innovations have exploited this trait to address an expanded range of biological questions. We illustrate the broadening range of biological insight coming from social insect biology with four examples. These new frontiers promote open-minded, interdisciplinary exploration of one of the richest and most complex of biological phenomena: sociality. (Abstract)

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