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

5. Cooperative Member/Group Societies

Gomez-Nava, Luis, et al. Fish Shoals Resemble a Stochastic Excitable system Driven by Environmental Perturbations. Nature Physics. May, 2023. Humboldt University of Berlin, Berlin Institute of Technology, Leibniz-Institute of Freshwater Ecology and Inland Fisheries, Berlin, and Universidad Juárez Autónoma de Tabasco, Mexico including Pawel Romanczuk (search) and Jens Krause continue their collegial project by to further quantify nature’s persistent self-organization such that any member/group in motion tends toward an optimum criticality. Whether flock, herd, pod or swarm, the Metazoan lineages from invertebrate slime molds and insects to primates and ourselves are being found to exemplify this universal viability. At the same while, we log Universality of Critical Dynamics with Finite Entanglement in (arXiv:2301.09681, Sherman) about quantum occasions.

Groups of animals can perform coordinated collective behaviours that confer benefits for members by information exchanges and protection from predators. Our interest is that these feature could arise at critical points in structural and functional states which respond best to external stimuli. We cite prior work that these conditions exemplify self-organized systems at criticality, but evidence in the wild is sparse. Here we show repetitive and rhythmic dive cascades under high risk exhibit a stochastic phase driven by environmental perturbations. Together with an agent-based model, such dense schools locate at a critical point between high and low diving activities which allows information to efficiently propagate. (Abstract excerpt)

Gorbonos, Dan, et al. Geometrical Structure of Bifurcations during Spatial Decision-Making. PRX Life. 2/1, 2024. In this new Physical Review journal, DG and Iain Cousin, MPI Animal Behavior, and Nir Gur, Weizmann Institute of Science add a further technical finesse about how creaturely movements keep their assemblage and perform so well. Rapid internal responses are seen to imply a statistical physics spin model along with an active particle coherence.

Animals must constantly make decisions on the move among multiple options. Here we model this process to explore how its dynamics accounts for branching trajectories exhibited by animals during spatial decision-making, and to provide new insights into spatiotemporal computation. Our analysis reveals the nature of the spontaneous symmetry breaking bifurcations in trajectory space and new geometric principles for spatiotemporal decision-making. This suggests that a non-Euclidean neural representation of space may be expected to have evolved across species in order to facilitate spatial decision-making. (Excerpt)

These results highlight the richness of this spin model, where movement through space is determined by spin-spin interactions, which are in turn dependent on the position of the animal or group with respect to the targets. The model has a broader theoretical physics perspective due to its coupling of equilibrium spin dynamics and propulsion of active-matter particles, as well as its connection to general research on decision-making in moving agents. (10)

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)

Gosztolai, Adam and Pavan Ramdya. Connecting the Dots in Ethology: Apply Network Theory to Understand Neural and Animal Collectives. arXiv:2112.02361. Brain Mind Institute & Interfaculty Institute of Bioengineering, EPFL, Lausanne researchers show how the latest perceptions of nature’s dynamic connectivity can well inform studies from cellular to social groupings. A graphic notes Migration in a Patchy Landscape, Body Kinematics, Population Velocity and so on. Another Figure displays integral interactions from Connectomes to Animal Ensembles. In regard, a major appreciation is established of how vital these real relationships are which then serve to join all the entities into an evolutionary procession.

A major goal shared by neuroscience and collective behavior is to understand how dynamic interactions between individual elements give rise to behaviors in populations of neurons and animals, respectively. This goal has become within reach thanks to techniques providing access to the connectivity and action of neuronal ensembles as well as to group behaviors. The work ahead is to use these datasets to unravel network mechanisms generating population behaviors. Here we avail network theory, a field that studies structure-function relationships in interconnected systems such as individual and collective animal behaviors. (Abstract excerpt)

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.

Guo, H., et al. Evolutionary Games on Simplical Complexes. arXiv:2103.03498. Eleven system theorists based in China, Spain, Chile, Russia, and Italy including Stefano Boccaletti consider a novel explanation of life’s cooperative propensities by way of complex network principles. It is concluded that this mathematical structuration is realistically present and an appropriate method to study.

Elucidating the mechanisms that lead to cooperation is still one of the main scientific challenges of current times, as many common cooperative scenarios remain at odds with Darwin's natural selection theory. Here, we study evolutionary games beyond pairwise interactions by way of situations in which indirect interactions via a neighbor or a group of neighbors. We report a number of results that: (i) support that higher-order games allow for non-dominant strategists to emerge and coexist with dominant ones; (ii) characterize a novel transition from defection to cooperation as a function of the simplicial structure of the population; and (iii) demonstrate that 2-simplex interactions are a source of strategy diversity. Our study constitutes a step toward understanding the roots of cooperation and the mechanisms that sustain it. (Abstract excerpt)

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.”

Hammerstein, Peter, ed. Genetic and Cultural Evolution of Cooperation. Cambridge: MIT Press, 2003. The report of a Dahlem workshop which explored a constant tendency from genes to cells and societies to form cooperative modules, divisions of labor and whole individuals. In contrast to a Darwinian emphasis on competition and conflict, these assemblies take place not only due to kin selection but for survival and “market economy” advantages. Notable conferees such as Eors Szathmary, Richard Michod, Samuel Bowles, Lewis Wolpert and others provide a representative survey.

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