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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

A. A Survey of Common Principles

Herrada, E. Alejandro, et al. Universal Scaling in the Branching of the Tree of Life. PLoS ONE. 3/7, 2008. Novel applications of scale-free network theory are utilized to reveal consistent, non-random patterns across life’s evolutionary florescence. Google this Public Library of Science online journal along with the author’s name to access the article.

The finding of non-random universal patterns of phylogenetic differentiation suggests that similar evolutionary forces drive diversification across the broad range of scales, from macro-evolutionary to micro-evolutionary processes, shaping the diversity of life on the planet. (1) In summary, the remarkably similar allometric exponents reported here to characterize universally the scaling properties of intra- and inter-specific phylogenies across kingdoms, reproductive systems and environments, strongly suggests the conservation of branching rules, and hence of the evolutionary processes that drive biological diversification, across the entire history of life. (3-4)

Jagers op Akkerhuis, Gerard. Analysing Hierarchy in the Organization of Biological and Physical Systems. Biological Reviews. 83/1, 2008. A Wageningen University research ecologist proposes, after several earlier versions and much literature review, a formal scheme by which to rank nature’s successive spatial emergence of ‘developmental stages’ from superstrings to encephalized organisms. This is accomplished by two attributes or groupings – operators and interactions, or elemental organization and relational dynamics. Along with William Lidicker’s paper (Dynamic Ecosystems) in the same issue, what is noteworthy is that after some 50 years of study, and centuries of intimation, a confirmation is dawning that cosmic and earthly creation is indeed stratified in kind, and distinguished by a repetitive scale of being and becoming.

Jiang, Luo-luo and Matjaz Perc. Spreading of Cooperative Behavior Across Interdependent Groups. Nature Scientific Reports. 3/2483, 2013. Indicative of the present 21st century global reach of an electronic noosphere, Wenzhou University, China, and University of Maribor, Slovenia theorists apply network mathematics to anthropological studies of hunter-gather groups, such as the Hadza of Tanzania, to identify their success as due to an “intermediate interdependence” via a reciprocity of member and troop. Thus one more such phrase occurs to identify this universal natural principle from microbes to civilizations.

Recent empirical research has shown that links between groups reinforce individuals within groups to adopt cooperative behaviour. Moreover, links between networks may induce cascading failures, competitive percolation, or contribute to efficient transportation. Here we show that there in fact exists an intermediate fraction of links between groups that is optimal for the evolution of cooperation in the prisoner's dilemma game. We consider individual groups with regular, random, and scale-free topology, and study their different combinations to reveal that an intermediate interdependence optimally facilitates the spreading of cooperative behaviour between groups. Excessive between-group links simply unify the two groups and make them act as one, while too rare between-group links preclude a useful information flow between the two groups. Interestingly, we find that between-group links are more likely to connect two cooperators than in-group links, thus supporting the conclusion that they are of paramount importance. (Abstract)

Jordan, Ferenc, et al. A Hierarchy of Networks Spanning from Individual Organisms to Ecological Landscapes. Estrada, Ernesto, et al, eds. Network Science: Complexity in Nature and Technology. London, Springer, 2010. Jordan, with Federica Ciocchetta, Centre for Computational and Systems Biology, University of Trento, and Gabriella Baranyi, Institute of Environmental Studies, Eotvos University, in this volume about this natural phenomena from common principles, and instantiation from protein to financial webs, provide a cogent paper over this ubiquity. As the quotes convey, a nested net repetition or iteration is the evident case, as informed by convergent statistical physics and systems ecology approaches.

Living systems are hierarchically organised. A number of components are linked by the multiplicity of interactions at each level (from organisms to species to ecosystems). This kind of compositional and hierarchical complexity is a computational and conceptual challenge. We need new approaches to determine the key components of large interaction networks and we need to better understand how they influence the system dynamics horizontally (at the same level) and vertically (between organisational levels). We provide examples for various interaction networks (animal social group, food web, landscape) and discuss how to dynamically link them. (Abstract, 165)

Biological systems are composed of a large number of various components, like millions of molecules in a cell, thousands of cells in an organism, hundreds of individuals in a population and dozens of species in an ecological system. Yet, biosystems are complex not primarily because of the number of components but rather because of composition: the multiplicity of interactions among similar components and the hierarchical, nested nature of different kinds of components at several organizational levels. These components are composed of subsystems as well as compose larger systems, and all layers have been coevolved in evolution. (165)

Kaschube, Matthias, et al. Universality in the Evolution of Orientation Columns in the Visual Cortex. Science. 330/1113, 2010. German and American neurogeneticists first report a specific instance of how dynamic nonlinearites are found to guide the formation and acuity of optical shapes, and go on, re the second quote, to advise that their common prevalence across living systems would attest to a generative spontaneity on a par with genetic and behavioral influences. For our nascent 2010 revolution, here is tangible evidence of an innately creative complexity that is manifest in a similar fashion everywhere. This implicate independence can then be realized to take on a genomic identity, so as to grace, propel, and ascend through, a natural genesis.

The brain’s visual cortex processes information concerning form, pattern, and motion within functional maps that reflect the layout of neuronal circuits. We analyzed functional maps of orientation preference in the ferret, tree shrew, and galago—three species separated since the basal radiation of placental mammals more than 65 million years ago—and found a common organizing principle. A symmetry-based class of models for the self-organization of cortical networks predicts all essential features of the layout of these neuronal circuits, but only if suppressive long-range interactions dominate development. We show mathematically that orientation-selective long-range connectivity can mediate the required interactions. Our results suggest that self-organization has canalized the evolution of the neuronal circuitry underlying orientation preference maps into a single common design. (Abstract, 1113)

We conclude that wherever such complex biological systems unfold, especially in the mammalian brain where they are likely to abound, the principles of dynamical network self-organization may design and constrain system behavior as powerfully as an organisms genetic endowment or early life experiences. (1116)

Kashtan, Padav and Uri Alon. Spontaneous Evolution of Modularity and Network Motifs. Proceedings of the National Academy of Sciences. 102/13773, 2005. Another example of how new understandings of evolution by way of complexity theory can identify a universally emergent structure and dynamics.

Biological networks have an inherent simplicity: they are modular with a design that can be separated into units that perform almost independently. Furthermore, they show reuse of recurring patterns termed network motifs. (13773)

Keil, Petr, et al. Macroecological and Macroevolutionary Patterns Emerge in the Universe of GNU/Linux Operating Systems. Ecography. 41/11, 2018. When we first posted this section in the early 2000s, any notice of environmental regularities was sparsely evident. In these later 2010s, eight European theoretical ecologists based at the German Centre for Intergrative Biodiversity Research, Leipzig not only aver their wide, constant presence, indeed an untangled bank, but go on to find a cross-affinity with computer software. A true universality across nature’s diversities is becoming patently apparent. See also Evolution in the Debian GNU/Linux Software Network: Analogies and Differences with Gene Regulatory Networks by Pablo Villegas, et al in the Journal of the Royal Society Interface (February 2020) which cites this paper.

What leads to classically recognized patterns of biodiversity remains an open question. Here, we employ analogies between GNU/Linux operating systems, and biodiversity. We demonstrate that patterns of the Linux universe generally match macroecological patterns. Moreover, the composition of functional traits (software packages) exhibits significant phylogenetic signal. The emergence of macroecological patterns across Linux suggests that the patterns are produced independently of the system identity, which points to the possibility of non‐biological drivers of fundamental biodiversity patterns. (Abstract excerpt)

To explain these patterns, we can invoke uniquely ecological and evolutionary processes: the patterns could be an outcome of assembly rules, natural selection, behavior, species interactions, or interplay between specific functional traits and environments. However, it has been demonstrated that some of the patterns are not unique to ecological and evolutionary systems, and often emerge in other complex systems. Examples are: species‐abundance distributions of music festival setlists, frequency distributions of components of software, latitudinal gradients of language diversity, species–area relationships in corporations, industrial codes, and minerals. However, structural constraints are not the only way that biological and non‐biological systems can resemble one another – similarity may also arise from analogous underlying processes. (2)

Kelso, Scott and David Engstrom. The Complementary Nature. Cambridge: MIT Press, 2006. This unique work is mainly noted in Current Vistas and by an extensive review in Recent Writings. An important, overdue statement of this obvious universal quality which is a main theme of this website.

Khaluf, Yara, et al. Scale Invariance in Natural and Artificial Collective Systems. Journal of the Royal Society Interface. Online November, 2017. From General systems theory in the 1960s and before, the Santa Fe Institute in the 1980s, unto this site going online in 2004, the hope and goal has been a common, code-like, form and flow that recurs in kind everywhere. Here complex bioinformatics theorists Khaluf and Pieter Simoens, Ghent University, Eliseo Ferrante, KU Leuven Belgium and Cristian Huepe, Northwestern University provide a deep and wide affirmation. From physical nature to human cultures and in between, an iconic fractal-like, self-organizing, network dynamics is recurrent effect as an exemplary presence. An aspect is its tendency to reach a critical state between discrete individuals and a communal whole, e.g. biofilms, brains and flocks. The authors then begin to consider ways to apply these findings for a better, viable society and technology. And if to reflect at this late day, here is an epochal, salutary discovery coming together in our midst due to worldwise humankinder. In the long arc of uniVerse to humanVerse evolution, nature’s procreative code may pass to our sentient, palliative and creative, intention.

Self-organized collective coordinated behaviour is an impressive phenomenon, observed in a variety of natural and artificial systems, in which coherent global structures or dynamics emerge from local interactions between individual parts. If the degree of collective integration of a system does not depend on size, its level of robustness and adaptivity is typically increased and we refer to it as scale-invariant. In this review, we first identify three main types of self-organized scale-invariant systems: scale-invariant spatial structures, scale-invariant topologies and scale-invariant dynamics. We then provide examples of scale invariance from different domains in science, describe their origins and main features and discuss potential challenges and approaches for designing and engineering artificial systems with scale-invariant properties. (Abstract)

Khovanov, Igor, et al. Editorial. European Physical Journal Special Topics. 222/10, 2013. An introduction to an issue on Nonlinear Dynamics of Deterministic and Stochastic Systems: Unraveling Complexity. And again a standard format for articles of this kind is held to by first citing how every realm from stellar to snail are now known to exemplify this emergent phenomena. With this place, a revitalized systems physics can be sighted as quite morphing into a true cosmic biology.

From the dynamics of the solar system to the functioning of the nerve cell of a snail, nonlinear phenomena are related to some of the most intriguing features of the world around us. In the form of self-sustained oscillations, synchronization, bifurcations, pattern formation, and chaos, nonlinear dynamic phenomena are manifest in physical, chemical, ecological and biological systems. Life itself is characterized by the large number of mutually interacting rhythmic processes it sustains. Nonlinear dynamic phenomena are also important for many types of engineering systems, and the same type of phenomena may be involved in the generation of complex forms of economic and managerial dynamics. (1)

Investigation of the complex dynamic phenomena that can arise in all of these different circumstances help us to get a deeper understanding of the mechanisms underlying a broad range of important problems that, for lack of a proper theoretical framework, were inaccessible for many years and, hence, considered as irrelevant or poorly posed. At the same time the study of nonlinear dynamic phenomena has proved to challenge several classical concepts in physics and mathematics. (1)

Koonin, Eugene. Are There Laws of Genome Evolution? PLoS Computational Biology. 7/8, 2011. As now broadly evident, as documented herein, life from cosmos to cities seems to be graced by repetitive, similar nonlinear patterns and processes in manifest effect everywhere. A NIH bioinformatician, geneticist, and author, ponders whether this ubiquitous presence, as apparent in cellular protoplasm, would in fact imply and arise from a realm of independent natural principles. In lieu of more review, the gist of these insights is well conveyed by extended excerpts. See also Koonin’s new book The Logic of Chance: The Nature and Origin of Biological Evolution (Financial Times Press, 2011).

Research in quantitative evolutionary genomics and systems biology led to the discovery of several universal regularities connecting genomic and molecular phenomic variables. These universals include the log-normal distribution of the evolutionary rates of orthologous genes; the power law–like distributions of paralogous family size and node degree in various biological networks; the negative correlation between a gene's sequence evolution rate and expression level; and differential scaling of functional classes of genes with genome size. The universals of genome evolution can be accounted for by simple mathematical models similar to those used in statistical physics…. These models do not explicitly incorporate selection; therefore, the observed universal regularities do not appear to be shaped by selection but rather are emergent properties of gene ensembles. (Abstract, 1)

The most conspicuous universals include: log-normal distribution of the evolutionary rates between orthologous genes; power law–like distributions of membership in paralogous gene families and node degree in biological ‘‘scale-free’’ networks; negative correlation between a gene’s sequence evolution rate and expression level (or protein abundance); distinct scaling of functional classes of genes with genome size. (1)

The universality of these dependencies appears genuinely surprising. For example, the distributions of sequence evolution rate of orthologous genes are virtually indistinguishable in all evolutionary lineages for which genomic data are available, including diverse groups of bacteria, archaea, and eukaryotes. The shape of the distribution did not perceptibly change through about 3.5 billion years of the evolution of life even though the number of genes in the compared organisms differs by more than an order of magnitude, and the repertoires of gene functions are dramatically different as well. The same conundrum pertains to the other universals: despite major biological differences between organisms, these quantitative regularities hold, often to a high precision. What is the nature of the genomic universals? Do they reflect fundamental ‘‘laws’’ of genome evolution or are they ‘‘just’’ pervasive statistical patterns that do not really help us understand biology? (1)

Networks have become ubiquitous images and tools of systems biology. Indeed, any class of interacting objects can be naturally represented by nodes, and the interactions between these objects, regardless of their specific nature, can be represented by edges. (3) These networks are said to be scale-free because the shape of their node degree distribution remains the same regardless of the chosen scale, that is, any subnetwork is topologically similar to the complete network (in other words, scale-free networks display fractal properties). (3) Collectively, the ability of simple models to generate the universals of genome evolution and additional results indicating that the global architecture of biological networks is not a selected feature suggest that all evolutionary universals are not results of adaptive evolution. (3)

Kovacs, Istvan, et al. Community Landscapes: An Integrative Approach to Determine Overlapping Network Module Hierarchy, Identify Key Nodes and Predict Network Dynamics. PLoS One. 5/9, 2010. In this 100 page entry with bioinformatic programs and references, Semmelweis University, Budapest, living system scientists, including Peter Csermely, parse modular networks to uncover a ubiquitous topological feature. Indeed, nature seems intent on forming communal groupings of an appropriate size and populace at each and every strata and instance. Might one even broach an “ubuntu Universe.”

Background: Network communities help the functional organization and evolution of complex networks. However, the development of a method, which is both fast and accurate, provides modular overlaps and partitions of a heterogeneous network, has proven to be rather difficult. Methodology/Principal Findings: Here we introduce the novel concept of ModuLand, an integrative method family determining overlapping network modules as hills of an influence function-based, centrality-type community landscape, and including several widely used modularization methods as special cases. As various adaptations of the method family, we developed several algorithms, which provide an efficient analysis of weighted and directed networks, and (1) determine pervasively overlapping modules with high resolution; (2) uncover a detailed hierarchical network structure allowing an efficient, zoom-in analysis of large networks; (3) allow the determination of key network nodes and (4) help to predict network dynamics.

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