metatron

The reason I used the mineral kingdom as a comparison is because we are aware of the varying conditions and elements that occur within the lithosphere that cause the formation of these mineral assemblages. We also understand that within a simple cell are certain metabolic process occurring as a dynamic interaction that also reflects the earthly environment at large, so life reflects not an unknowable but a known. Quote; This is also the axiom of the "bootstrap" physicists, according to whom a particle is completely defined by the set of interactions in which it participates.” In other words when you look deeply inside a particle, mineral, cell, animal, rock, or person you can see back to the environment in which it emerged.

I believe it occurred during the implosion of certain massive stars that reach a mass that causes a fusion of lighter atoms into heaver elements. This star creates a rich and diverse disc of elements that form second generation stars and planets. The differing elements form as the first generation stars form shells or layers inside the star just before it super novas, these layers form the periodic table of elements. Heaver elements forming the deeper the layers. It has been theorized that gold may have formed by the collision of two neutron stars.

The big deal is that this vesica attractor shows that biological systems arose in the same fundamental way as the elemental and cosmological phases prior to the emergence of life. This has been theorized in attractor models, and is currently being applied to the interacting genetic components in biological systems, reflecting changes in morphology over time, and has been theorized that these components could have been originally unified in a self-organizing process, but………. this is the first time an actual physical artifact represents how these process originated. In other words, this could represent a rosetta stone of life. quote: -------------------------------------------------------------------------------- SYSTEMS THEORY: Systems theory or systems science argues that however complex or diverse the world that we experience, we will always find different types of organization in it, and such organization can be described by principles which are independent from the specific domain at which we are looking. Hence, if we would uncover those general laws, we would be able to analyze and solve problems in any domain, pertaining to any type of system. (Principia Cybernetica) --------------------------------------------------------------------------------

I just found this very abreviated but really well written intro to chaos theory, this should help anyone that is having trouble understanding this post. Quote Chaos and Complexity One of the themes straddling both biological and physical sciences is the quest for a mathematical model of phenomena of emergence (spontaneous creation of order), and in particular adaptation, and a physical justification of their dynamics (which seems to violate physical laws). The physicist Sadi Carnot, one of the founding fathers of Thermodynamics, realized that the statistical behavior of a complex system can be predicted if its parts were all identical and their interactions weak. At the beginning of the century, another French physicist, Henri Poincare`, realizing that the behavior of a complex system can become unpredictable if it consists of few parts that interact strongly, invented "chaos" theory. A system is said to exhibit the property of chaos if a slight change in the initial conditions results in large-scale differences in the result. Later, Bernard Derrida will show that a system goes through a transition from order to chaos if the strength of the interactions among its parts is gradually increased. But then very "disordered" systems spontaneously "crystallize" into a higher degree of order. First of all, the subject is "complexity", because a system must be complex enough for any property to "emerge" out of it. Complexity can be formally defined as nonlinearity. The world is mostly nonlinear. The science of nonlinear dynamics was originally christened "chaos theory" because from nonlinear equations unpredictable solutions emerge. A very useful abstraction to describe the evolution of a system in time is that of a "phase space". Our ordinary space has only three dimensions (width, height, depth) but in theory we can think of spaces with any number of dimensions. A useful abstraction is that of a space with six dimensions, three of which are the usual spatial dimentions. The other three are the components of velocity along those spatial dimensions. In ordinary 3-dimensional space, a "point" can only represent the position of a system. In 6-dimensional phase space, a point represents both the position and the motion of the system. The evolution of a system is represented by some sort of shape in phase space. The shapes that chaotic systems produce in phase space are called "strange attractors" because the system will tend towards the kinds of state described by the points in the phase space that lie within them. The program then becomes that of applying the theory of nonlinear dynamic systems to Biology. Inevitably, this implies that the processes that govern human development are the same that act on the simplest organisms (and even some nonliving systems). They are processes of emergent order and complexity, of how structure arises from the interaction of many independent units. The same processes recurr at every level, from morphology to behavior. Darwin's vision of natural selection as a creator of order is probably not sufficient to explain all the spontaneous order exhibited by both living and dead matter. At every level of science (including the brain and life) the spontaneous emergence of order, or self-organization of complex systems, is a common theme. Koestler and Salthe have shown how complexity entails hierarchical organization. Von Bertalanffi's general systems theory, Haken's synergetics, and Prigogine's non-equilibrium Thermodynamics belong to the class of mathematical disciplines that are trying to extend Physics to dynamic systems. These theories have in common the fact that they deal with self-organization (how collections of parts can produce structures) and attempt at providing a unifying view of the universe at different levels of organization (from living organisms to physical systems to societies). Holarchies The Hungarian writer and philosopher Arthur Koestler first brought together a wealth of biological, physical, anthropological and philosophical notions to construct a unified theory of open hierarchical systems. Language has to do with a hierarchical process of spelling out implicit ideas in explicit terms by means of rules and feedbacks. Organisms and societies also exhibit the same hierarchical structure. In these hierarchies, each intermediary entity ("holon") functions as a self-contained whole relative to its subordinates and as one of the dependent parts of its superordinates. Each holon tends to persist and assert its pattern of activity. Wherever there is life, it must be hierarchically organized. Life exhibits an integrative property (that manifests itself as symbiosis) that enables the gradual construction of complex hierarchies out of simple holons. In nature there are no separated, indivisible, self-contained units. An "individual" is an oxymoron. An organism is a hierarchy of self-regulating holons (a "holarchy") that work in coordination with their environment. Holons at the higher levels of the hierarchy enjoy progressively more degrees of freedom and holons at the lower levels of the hierarchy have progressively less degrees of freedom. Moving up the hierarchy, we encounter more and more complex, flexible and creative patterns of activity. Moving down the hierarchy behavior becomes more and more mechanized. A hierarchical process is also involved in perception and memorization: it gradually reduces the percept to its fundamental elements. A dual hierarchical processis involved in recalling: it gradually reconstructs the percept. Hierarchical processes of the same nature can be found in the development of the embryo, in the evolution of species and in consciousness itself (which should be analyzed not in the context of the mind/body dichotomy but in the context of a multi-levelled hierarchy and of degrees of consciousness). They all share common themes: a tendency towards integration (a force that is inherent in the concept of hierarchic order, even if it seems to challenge the second law of Thermodynamics as it increases order), an openess at the top of the hierarchy (towards higher and higher levels of complexity) and the possibility of infinite regression. Hierarchies from Complexity Stanley Salthe, by combining the metaphysics of Justus Buchler and Michael Conrad's "statistical state model" of the evolutionary process, has developed what amounts to a theory of everything: an ontology of the world, a formal theory of hierarchies and a model of the evolution of the world. The world is viewed as a determinate machine of unlimited complexity. Within complexity, discontinuities arise. The basic structure of this world must allow for complexity that is spontaneously stable and that can be broken down in things divided by boundaries. The most natural way for the world to satisfy this requirement is to employ a hierarchical structure, which is also implied by Buchler's principle of ordinality: Nature (i.e., our representation of the world) is a hierarchy of entities existing at different levels of organization. Hierarchical structure turns out to be a consequence of complexity. Entities are defined by four criteria: boundaries, scale, integration, continuity. An entity has size, is limited by boundaries, and consists of an integrated system which varies continuously in time. Entities at different levels interact through mutual constraints, each constraint carrying information for the level it operates upon. A process can be described by a triad of contiguous levels: the one it occurs at, its context (what the philosopher Mario Bunge calls "environment") and its causes (Bunge's "structure"). In general, a lower level provides initiating conditions for a process and an upper level provides boundary conditions. Representing a dynamic system hierarchically requires a triadic structure. Aggregation occurs upon differentiation. Differentiation interpolates levels between the original two and the new entities aggregate in such a way that affects the structure of the upper levels: every time a new level emerges, the entire hierarchy must reorganize itself. Salthe also recalls a view of complexity due to the physicist Howard Hunt Pattee: complexity as the result of interactions between physical and symbolic systems. A physical system is dependent on the rates at which processes occur, whereas a symbolic system is not. Symbolic systems frequently serve as constraints applied to the operation of physical systems, and frequently appear as products of the activity of physical systems (e.g., the genome in a cell). A physical system can be said to be "complex" when a part of it functions as a symbolic system (as a representation, and therefore as an observer) for another part of it. These abstract principles can then be applied to organic evolution. Over time, Nature generates entities of gradually more limited scope and more precise form and behavior. This process populates the hierarchy of intermediate levels of organization as the hierarchy spontaneously reorganizes itself. The same model applies to all open systems, whether organisms or ecosystems or planets. By applying principles of complex systems to biological and social phenomena, Salthe attempts to reformulate Biology on development rather than on evolution. His approach is non-Darwinian to the extent that development, and not evolution, is the fundamental process in self-organization. Evolution is merely the result of a margin of error. His theory rests on a bold fusion of hierarchy theory, Information Theory and Semiotics. Salthe is looking for a grand theory of nature, which turns out to be essentially a theory of change, which turns out to be essentially a theory of emergence. General Systems Theory "General Systems Theory" was born before Cybernetics, and cybernetic systems are merely a special case of self-organizing systems; but General System Theory took longer to establish itself. It was conceived in the 1930s by the Austrian biologist Ludwig Von Bertalanffy. His ambition was to create a "universal science of organization". His legacy is to have started "system thinking", thinking about systems as systems and not as mere aggregates of parts. The classical approach to the scientific description of a system's behavior (whether in Physics or in Economics) can be summarized as the search for "isolable causal trains" and the reduction to atomic units. This approach is feasible under two conditions: 1. that the interaction among the parts of the system be negligible and 2. that the behavior of the parts be linear. Von Bertalanffy's "systems", on the other hand, are those entities (oe "organized complexities") that consist of interacting parts, usually described by a set of nonlinear differential equations. Systems Theory studies principles which apply to all systems, properties that apply to any entity qua system. Basic concepts of Systems Theory are, for example, the following: every whole is based upon the competition among its parts; individuality is the result of a never-ending process of progressive centralization whereby certain parts gain a dominant role over the others. General Systems Theory looks for laws that can be applied to a variety of fields (i.e., for an isomorphism of law in different fields), particularly in the biological, social and economic sciences (but even in history and politics). General Systems Theory mainly studies "wholes", which are characterized by such holistic properties as hierarchy, stability, teleology. "Open Systems Theory" is a subset of General Systems Theory. Because of the second law of Thermodynamics, a change in entropy in closed systems is always positive: order is continually destroyed. In open systems, on the other hand, entropy production due to irreversible processes is balanced by import of negative entropy (as in all living organisms). If an organism is viewed as an open system in a steady state, a theory of organismic processes can be worked out. Furthermore, a living organism can be viewed as a hierarchical order of open systems, where each level maintains its structure thanks to continuous change of components at the next lower level. Living organisms maintain themselves in spite of continuous irreversible processes and even proceed towards higher and higher degrees of order. Ervin Laszlo's take at a "theory of natural systems" (i.e., a theory of the invariants of organized complexity) is centered around the concept of "ordered whole", whose structure is defined by a set of constraints. Laszlo adopts a variant of Ashby's principle of self-organization, according to which any isolated natural system subject to constant forces is inevitably inhabited by "organisms" that tend towards stationary or quasi-stationary non-equilibrium states. In Laszlo's view, the combination of internal constraints and external forces yields adaptive self-organization. Natural systems evolve towards increasingly adapted states, corresponding to increasing complexity (or negative entropy). Natural systems sharing an environment tend to organize in hierarchies. The set of such systems tends to become itself a system, its subsystems providing the constraints for the new system. Laszlo offered rigorous foundations to deal with the emergence of order at the atomic ("micro-cybernetics"), organismic ("bio-cybernetics") and social levels ("socio-cybernetics"). A systemic view also permits a formal analysis of a particular class of natural systems: cognitive systems. The mind, just like any other natural system, exhibits an holistic character, adaptive self-organization, and hierarchies, and can be studied with the same tools ("psycho-cybernetics"). Synergetics "Synergetics", as developed in Germany by the physicist Hermann Haken, is a theory of pattern formation in complex systems. It tries to explain structures that develop spontaneously in nature. Synergetics studies cooperative processes of the parts of a system far from equilibrium that lead to an ordered structure and behavior for the system. Haken's favorite example was the laser: how do the atoms of the laser agree to produce a single coherent wave flow? The answer is that the laser is a self-organizing system far from the equilibrium (what Prigogine would call a dissipative structure). A "synergetic" process in a physical system is one in which, when energy is pumped into the system, some macroscopic structure emerges from the disorderly behavior of the large number of microscopic particles that make up the physical system. As energy is pumped into the system, initially nothing seems to happen, other than additional excitation of the particles, but then the system reaches a threshold beyond which structure suddenly emerges. The laser is such a synergetic process: a beam of coherent light is created out of the chaotic movement of particles. What happens is that energy pushes the system of particles beyond a threshold, and suddenly the particles start behaving harmoniously.. Since order emerges out of chaos, and chaos is not well defined, synergetics employs probabilities (to describe uncertainty) and information (to describe approximation). Entropy becomes a central concept, relating Physics to Information Theory. Synergetics revolves around a number of technical concepts: compression of the degrees of freedom of a complex system into dynamic patterns that can be expressed as a collective variable; behavioral attractors of changing stabilities; and the appearance of new forms as non-equilibrium phase transitions. Synergetics applies to systems driven far from equilibrium, where the classic concepts of Thermodynamics are no longer adequate. It expresses the fact that order can arise from chaos and can be maintained by flows of energy/matter. Systems at instability points (at the "threshold") are driven by a "slaving principle": long-lasting quantities (the macroscopic pattern) can enslave short-lasting quantities (the chaotic particles), and they can force order on them (thereby becoming "order parameters"). The system exhibits a stable "mode", which is the chaotic motion of its particles, and an unstable "mode", which is its macroscopic structure and behavior of the whole system. Close to instability, stable modes are "enslaved" by unstable modes and can be ignored. Instead of having to deal with millions of chaotic particles, one can focus on the macroscopic quantities. De facto, the degrees of freedom of the system are reduced. Haken shows how one can write the dynamic equations for the system, and how such mathematical equations reflect the interplay between stochastic forces ("chance") and deterministic forces ("necessity"). Hypercycles The German chemist Manfred Eigen was awarded the Nobel Prize in 1967 for discovering that very short pulses of energy could trigger extremely fast chemical reactions. In the following years, he started looking for how very fast reactions could be used to create and sustain life. Indirectly, he ended up studying the behavior of biochemical systems far from equilibrium. Eventually, Eigen came up with the concept of an "hypercycle". A hypercycle is a cyclic reaction network, i.e. a cycle of cycles of cycles (of chemical reactions). Then he proved that life can be viewed as the product of a hierarchy of such hypercycles. A catalist is a substance that favors a chemical reaction. When enough energy is provided, some catalytic reactions tend to combine to form networks, and such networks may contain closed loops, called catalytic cycles. If even more energy is pumped in, the system moves even farther from equilibrium, and then catalytic cycles tend ot combine to form closed loops of a higher level, or hypercycles, in which the enzymes produced by a cycle act as catalysts for the next cycle in the loop. Each link of the loop is now a catalytic cycle itself. Eigen showed that hypercycles are capable of self-replication, which may therefore have been a property of nature even before the invention of living organisms. Hypercycles are capable of evolution through more and more complex stages. Hypercycles compete for natural resources and are therefore subject to natural selection. The hypercycle falls short of being a living system because it defines no "boundary": the boundary is the container where the chemical reaction is occurring. A living system, on the other hand, has a boundary that is part of the living system (eg, the skin). Catalysis is the phenomenon by which a chemical reaction is sped up: without catalysis, all processes that give rise to life would take a lot longer, and probably would not be fast enough for life to happen. Then Eigen shows that they can be organized into an autocatalytic cycle, i.e. a cycle that is capable of self-reproducing: this is the fundamental requirement of life. A set of autocatalytic cycles gets, in turn, organized into a catalytic hypercycle. This catalytic hypercycle represents the basic form of life. Formally: "hypercycles" are a class of nonlinear reaction networks. They can originate spontaneously within the population of a species through natural selection and then evolve to higher complexity by allowing for the coherent evolution of a set of functionally coupled self-replicating entities. A hypercycle is based on nonlinear autocatalysis, which is a chain of reproduction cycles which are linked by cyclic catalysis, i.e. by another autocatalysis. A hypercycle is a cycle of cycles of cycles. A hypercycle can be viewed as the next higher level in the hierarchy of autocatalytic systems. Systems can be classified in four groups according to their stability with respect to fluctuations: stable systems (the fluctuations are self-regulating), indifferent systems (the fluctuations have no effect), unstable systems (self-amplification of the fluctuations) and variable systems (which can be in any of the previous states). Only the last type is suitable for generation of biological information because it can play all best tactics: indifference towards a broad mutant spectrum, stability towards selective advantages and instability towards unfavorable configurations. In other words, it can take the most efficient stance in the face of both favorable and adverse situations. Eigen’s model explains the simultaneous unity (due to the use of a universal genetic code) and diversity (due to the "trial and error" approach of natural selection) in evolution. This dual process started even before life was created. Evolution of species was preceded by an analogous stepwise process of molecular evolution. Whatever the mathematics, the bottom line is that natural selection itself turns out to be inevitable: given a set of self-reproducing entities that feed on a common and limited source of energetic/material supply, natural selection will spontaneously appear. Natural selection is a mathematical consequence of the dynamics of self-reproducing systems of this kind. Dissipative Systems By far, though, the most influential school of thought has been the one related to Ilya Prigogine's non-equilibrium Thermodynamics, which redefined the way scientists approach natural phenomena and brought self-organizing processes to the forefront of the study of complex systems. His theory found a stunning number and variety of fields of application, from Chemistry to Sociology. In his framework, the most difficult problems of Biology, from morphogenesis to evolution, found a natural model. Classical Physics describes the world as a static and reversible system that undergoes no evolution, whose information is constant in time. Classical Physics is the science of being. Thermodynamics, instead, describes an evolving world in which irreversible processes occurs. Thermodynamics is the science of becoming. The second law of Thermodynamics, in particular, describes the world as evolving from order to disorder, while biological evolution is about the complex emerging from the simple (i.e. order arising from disorder). While apparently contradictory, these two views show that irreversible processes are an essential part of the universe. Furthermore, conditions far from equilibrium foster phenomena such as life that classical Physics does not cover at all. Irreversible processes and non-equilibrium states turn out to be fundamental features of the real world. Prigogine distinguishes between "conservative" systems (which are governed by the three conservation laws for energy, translational momentum and angular momentum, and which give rise to reversible processes) and "dissipative" systems (subject to fluxes of energy and/or matter). The latter give rise to irreversible processes. The theme of science is order. Order can come either from equilibrium systems or from non-equilibrium systems that are sustained by a constant source (or, dually, by a persistent dissipation) of matter/energy. In the latter systems, order is generated by the flux of matter/energy. All living organisms (as well as systems such as the biosphere) are non-equilibrium systems. Prigogine proved that, under special circumstances, the distance from equilibrium and the nonlinearity of a system drive the system to ordered configurations, i.e. create order. The science of being and the science of becoming describe dual aspects of Nature. What is needed is a combination of factors that are exactly the ones found in living matter: a system made of a large collection of independent units which are interacting with each other, a flow of energy through the system that drives the system away from equilibrium, and nonlinearity. Nonlinearity expresses the fact that a perturbation of the system may reverberate and have disproportionate effects. Non-equilibrium and nonlinearity favor the spontaneous development of self-organizing systems, which maintain their internal organization, regardless of the general increase in entropy, by expelling matter and energy in the environment. When such a system is driven away from equilibrium, local fluctuations appear. This means that in places the system gets very unstable. Localized tendencies to deviate from equilibrium are amplified. When a threshold of instability is reached, one of these runaway fluctuations is so amplified that it takes over as a macroscopic pattern. Order appears from disorder through what are initially small fluctuations within the system. Most fluctuations die along the way, but some survive the instability and carry the system beyond the threshold: those fluctuations "create" new form for the system. Fluctuations become sources of innovation and diversification. The potentialities of nonlinearity are dormant at equilibrium but are revelead by non-equilibrium: multiple solutions appear and therefore diversification of behavior becomes possible. Technically speaking, nonlinear systems driven away from equilibrium can generate instabilities that lead to bifurcations (and symmetry breaking beyond bifurcation). When the system reaches the bifurcation point, it is impossible to determine which path it will take next. Chance rules. Once the path is chosen, determinism resumes. The multiplicity of solutions in nonlinear systems can even be interpreted as a process of gradual "emancipation" from the environment. Most of Nature is made of such "dissipative" systems, of systems subject to fluxes of energy and/or matter. Dissipative systems conserve their identity thanks to the interaction with the external world. In dissipative structures, non-equilibrium becomes a source of order. These considerations apply very much to living organisms, which are prime examples of dissipative structures in non-equilibrium. Prigogine's theory explains how life can exist and evolution work towards higher and higher forms of life. A "minimum entropy principle" characterizes living organisms: stable near-equilibrium dissipative systems minimize their rate of entropy production. From non-equilibrium Thermodynamics a wealth of concepts has originated: invariant manifolds, attractors, fractals, stability, bifurcation analysis, normal forms, chaos, Lyapunov exponents, entropies. Catastrophe and chaos theories turn out to be merely special cases of nonlinear non-equilibrium systems. In concluding, self-organization is the spontaneous emergence of ordered structure and behavior in open systems that are in a state far from equilibrium described mathematically by nonlinear equations. Catastrophe Theory Rene' Thom's catastrophe theory, originally formulated in 1967 and popularized ten years later by the work of the British mathematician Erich Zeeman, became a widely used tool for classifying the solutions of nonlinear systems in the neighborhood of stability breakdown. In the beginning, Thom, a French mathematician, was interested in structural stability in topology (stability of topological form) and was convinced of the possibility of finding general laws of form evolution regardless of the underlying substance of form, as already stated at the beginning of the century by D'Arcy Thompson. Thom's goal was to explain the "succession of form". Our universe presents us with forms (that we can perceive and name). A form is defined, first and foremost, by its stability: a form lasts in space and time. Forms change. The history of the universe, insofar as we are concerned, is a ceaseless creation, destruction and transformation of form. Life itself is, ultimately, creation, growth and decaying of form. Every physical form is represented by a mathematical quantity called "attractor" in a space of internal variables. If the attractor satisfies the mathematical property of being "structurally stable", then the physical form is the stable form of an object. Changes in form, or morphogenesis, are due to the capture of the attractors of the old form by the attractors of the new form. All morphogenesis is due to the conflict between attractors. What catastrophe theory does is to "geometrize" the concept of "conflict". The universe of objects can be divided into domains of different attractors. Such domains are separated by shock waves. Shock wave surfaces are singularities called "catastrophes". A catastrophe is a state beyond which the system is detroyed in an irreversible manner. Technically speaking, the "ensembles de catastrophes" are hypersurfaces that divide the parameter space in regions of completely different dynamics. The bottom line is that dynamics and form become dual properties of nonlinear systems. This is a purely geometric theory of morphogenesis, His laws are independent of the substance, structure and internal forces of the system. Thom proves that in a 4-dimensional space there exist only 7 types of elementary catastrophes. Elementary catastrophes include: "fold", destruction of an attractor which is captured by a lesser potential; "cusp", bufurcation of an attractor into two attractors; etc. From these singularities, more and more complex catastrophes unfold, until the final catastrophe. Elementary catastrophes are "local accidents". The form of an object is due to the accumulation of many of these "accidents". The Origin of Regularity Prigogine's "bifurcation theory" is a descendent of the theory of stability initiated by the Russian mathematician Aleksander Lyapounov. Rene' Thom's catastrophe theory is particular case of bifurcation theory, so they all belong to the same family. They all elaborate on the same theorem, Lyapounov's theorem: for isolated systems, thermodynamic equilibrium is an attractor of nonequilibrium states. Then the story unfolds, leading to dissipative systems and eventually to the reversing of Thermodynamics' fundamental assumption, the destruction of structure. Order emerges from the very premises that seem to deny it. Jack Cohen and Ian Steward are among those who study how the regularities of nature (from Cosmology to Quantum Theory, from Biology to Cognitive Psychology) emerge from the underlying chaos and complexity of nature: "emergent simplicities collapse chaos". They proved that external constraints are fundamental in shaping biological systems (DNA does not uniquely determine an organism) and defined new concepts: "simplexity" (the tendency of simple rules to emerge from underlying disorder and complexity) and "complicity" (the tendency of interacting systems to coevolve leading to a growth of complexity). Simplexity is a "weak" form of emergence, and is ubiquitous. Complicity is a stronger form of emergence, and is responsible for consciousness and evolution. Emergence is the rule, not the exception, and it is shaped by simplexity and complicity. Emergent Computation Emergent computation is to standard computation what nonlinear systems are to linear systems: it deals with systems whose parts interact in a nontrivial way. Both Turing and Von Neumann, the two mathematicians who inspired the creation of the computer, were precursors in emergent computation: Turing formulated a theory of self-catalytic systems and Von Neumann studied self-replicating automata. Alan Turing (in the 1950's) advanced the reaction-diffusion theory of pattern formation, based on the bifurcation properties of the solutions of differential equations. Turing devised a model to generate stable patterns: X catalyzes itself: X diffuses slowly X catalyzes Y: Y diffuses quickly Y inhibits X Y may or may not catalyze or inhibit itself Some reactions might be able to create ordered spatial schemes from disordered schemes. The function of genes is purely catalytic: they catalyze the production of new morphogenes, which will catalyze more morphogenes until eventually form emerges. Von Neumann saw life as a particular class of automata (of programmable machines). Life's main property is the ability to reproduce. Von Neumann proved that a machine can be programmed to make a copy of itself. Von Neumann's automaton was conceived to absorb matter from the environment and process it to build another automaton, including a description of itself. Von Neumann realized (years before the genetic code was discovered) that the machine needed a description of itself in order to reproduce. The description itself would be copied to make a new machine, so that the new machine too could copy itself. In Von Neumann's simulated world, a large checkerboard was a simplified version of the world, in which both space and time were discrete. Time, in particular, was made to advance in discrete steps, which meant that change could occur only at each step, and simultaneously for everything that had to change. Von Neumann's studies of the 1940s led to an entire new field of Mathematics, called "cellular automata". Technically speaking, cellular automata are discrete dynamical systems whose behavior is completely specified in terms of a local relation. In practice, cellular automata are the computer scientist's equivalent of the physicist's concept of field. Space is represented by a uniform grid and time advances in discrete steps. Each cell of space contains bits of information. Laws of nature express what operation must be performed on each cell's bits of information, based on its neighbor's bits of information. Laws of nature are local and uniform. The amazing thing is that such simple "organisms" can give rise to very complex structures, and those structures recur periodically, which means that they achieve some kind of stability. Von Neumann's idea of the dual genetics of self-reproducing automata (that the genetic code must act as instructions on how to build and organism and as data to be passed on to the offspring) was basically the idea behind what will be called DNA: DNA encodes the instructions for making all the enzymes and the protein that a cell needs to function and DNA makes a copy of itself every time the cell divides in two. Von Neumann indirectly understood other properties of life: the ability to increase its complexity (an organism can generate organisms that are more complex than itself) and the ability to self-organize. When a machine (e.g., an assembly line) builds another machine (e.g., an appliance), there occurs a degradation of complexity, whereas the offsprings of living organisms are at least as complex as their parents and their complexity increases in evolutionary times. A self-reproducing machine would be a machine that produces another machine of equal of higher complexity. By representing an organism as a group of contigous multi-state cells (either empty or containing a component) in a 2-dimensional matrix, Von Neumann proved that a Turing-type machine that can reproduce itself could be simulated by using a 29-state cell component. John Conway is the inventor of a game "Life", that is staged in Von Neumann’s checkerboard world (in which the state of a square changes depending on the adjacent squares). Conway proved that, given enough resources and time, self-reproducing patterns will occur. Turing proved that there exists a universal computing machine. Von Neumann proved that there exists a universal computing machine which, given a description of an automaton, will construct a copy of it, and, by extension, that there exists a universal computing machine which, given a description of a universal computing machine, will construct a copy of it, and, by extension, that there exists a universal computing machine which, given a description of itself, will construct a copy of itself. The two most futuristic topics addressed by Cybernetics were self-reproducing machines and self-organizing systems. They are pervasive in nature, and modern technologies make it possible to dream of building them artificially as well. Still, they remained merely speculative. The step that made emergent computation matter to the real world came from the computational application of the two pillars of the synthetic theory of evolution, namely the genetic code and adaptation. Genetic Algorithms The momentum for the computational study of genetic algorithms and adaptive systems was created in large part by John Holland's work. In the 1970s, the American computer scientist John Holland had the intuition that the best way to solve a problem is to mimick what biological organisms do to solve their problem of survival: to evolve (through natural selection) and to reproduce (through genetic recombination). Genetic algorithms apply recursively a series of biologically-inspired operators to a population of potential solutions of a given problem. Each application of operators generates new populations of solutions which should better and better approximate the best solution. What evolves is not the single individual but the population as a whole. Genetic algorithms are actually a further refinement of search methods within problem spaces. Genetic algorithms improve the search by incorporating the criterion of "competition". Recalling Newell and Simon's definition of problem solving as "searching in a problem space", David Goldberg defines genetic algorithms as "search algorithms based on the mechanics of natural selection and natural genetics". Unlike most optimization methods, that work from a single point in the decision space and employ a transition method to determine the next point, genetic algorithms work from an entire "population" of points simultaneously, trying many directions in parallel and employing a combination of several genetically-inspired methods to determine the next population of points. One can employ simple algorithms such as "reproduction" (that copies chromosomes according to a fitness function), "crossover" (that switches segments of two chromosomes) and "mutation", as well as more complex algorithms such as "dominance" (a genotype-to-phenotype mapping), "diploidy" (pairs of chromosomes), "abeyance" (shielded against overselection), "inversion" (the primary natural mechanism for recoding a problem, by switching two points of a chromosome); and so forth. Holland's classifier (which learns new rules to optimize its performance) was the first practical application of genetic algorithms. A classifier system is a machine learning system that learns syntactically rules (or "classifiers") to guide its performance in the environment. A classifier system consists of three main components: a production system, a credit system (such as the "bucket brigade") and a genetic algorithm to generate new rules. Its emphasis on competition and coopertation, on feedback and reinforcement, rather than on pre-programmed rules, set it apart from knowledge-based models of Artificial Intelligence. A measure function computes how "fit" an individual is. The selection process starts from a random population of individual. For each individual of the population the fitness function provides a numeric value for how much the solution is far from the ideal solution. The probability of selection for that individual is made proportional to its "fitness". On the basis of such fitness values a subset of the population is selected. This subset is allowed to reproduce itself through biologically-inspired operators of crossover, mutation and inversion. Each individual (each point in the space of solutions) is represented as a string of symbols. Each genetic operators perform an operation on the sequence or content of the symbols. When a message from the environment matches the antecedent of a rule, the message specified in the consequent of the rule is produced. Some messages produced by the rules cycle back into the classifier system, some generate action on the environment. A message is a string of characters from a specified alphabet. The rules are not written in the first-order predicate logic of expert systems, but in a language that lacks descriptive power and is limited to simple conjunctive expressions. Credit assignment is the process whereby the system evaluates the effectiveness of its rules. The "bucket brigade" algorithm assigns a strength (a maesure of its past usefulness) to each rule. Each rule then makes a bid (proportional to its strength and to its relevance to the current situation) and only the highest bidding rules are allowed to pass their messages on. The strengths of the rules are modified according to an economic analogy: every time a rule bids, its strength is reduced of the value of the bid while the strength of its "suppliers" (the rules that sent the messages matched by this bidder) are increased. The bidder strength will in turn increase if its consumers (the rules that receive its message) will become bidders. This leads to a chain of suppliers/consumers whose success ultimately depends on the success of the rules that act directly on the environment. Then the system replaces the least useful (weak) rules with newly generated rules that are based on the system's accumulated experience, i.e. by combining selected "building blocks" ("strong" rules) according to some genetic algorithms. Holland then went on to focus on "complex adaptive systems". Such systems are governed by principles of anticipation and feedback. Based on a model of the world, an adaptive system anticipates what is going to happen. Models are improved based on feedback from the environment. Complex adaptive system are ubiquitous in nature. They include brains, ecosystems and even economies. They share a number of features: each of these systems is a network of agents acting in parallel and interacting; behavior of the system arises from cooperation and competitiong among its agents; each of these systems has many levels of organization, with agents at each level serving as building blocks for agents at a higher level; such systems are capable of rearranging their structure based on their experience; they are capable of anticipating the future by means of innate models of the world; new opportunities for new types of agents are continously beeing created within the system. All complex adaptive systems share four properties (aggregation, nonlinearity, flowing, diversity) and three mechanisms (categorization by tagging, anticipation through internal models, decomposition in building blocks). Each adaptive agent can be represented by a framework consisting of a performance system (to describe the system's skills), a credit-assignment algorithm (to reward the fittest rules) and a rule-discovery algorithm (to generate plausible hypotheses). The Edge of Chaos A new theoretical breakthrough occurred when Chris Langton demonstrated that physical systems achieve the prerequisites for the emergence of computation (i.e., transmission, storage, modification) in the vicinity of a phase transition ("at the edge of chaos"). Specifically, information becomes an important factor in the dynamics of cellular automata in the vicinity of the phase transition between periodic and chaotic behavior, i.e. between order and chaos. The idea is that systems undergo transformations, and while they transform they constantly move from order to chaos and back. This transition is similar to the "phase transitions" undergone by a substance when it turns liquid or solid or fluid. When ice turns into water, the atoms have not changed, but the system as a whole has undergone a phase transition. Microscopically, this means that atoms are behaving in a different way. The transition of a system from chaos to order and back is similar in that the system is still made of the same parts, but they behave in a different way. The state between order and chaos (the "edge of chaos") is sometimes a very "informative" state, because the parts are not as rigidly assembled as in the case of order and, at the same time, they are not as loose as in the case of chaos. The system is stable enough to keep information and unstable enough to dissipate it. The system at the edge of chaos is both a storage and a broadcaster of information. At the edge of chaos, information can propagate over long distances without decaying appreciably, thereby allowing for long-range correlation in behavior: ordered configurations do not allow for information to propagate at all, and disordered configurations cause information to quickly decay into random noise. This conclusion is consistent with Von Neumann's findings. A fundamental connection therefore exists between computation and phase transition. The edge of chaos is where the system can perform computation, can metabolize, can adapt, can evolve. In a word: these systems can be alive. Basically, Langton proved that Physics can support life only in a very narrow boundary between chaos and order. In that locus it is possible to build artificial organisms that will settle into recurring patterns conductive to an orderly transmission of information. Langton also related phase transitions, computation and life, which means that he built a bridge between Thermodynamics, Information Theory and Biology. The edge of chaos is also the locus of Murray Gell-Man's speculations. Gell-Man, a physicist who was awarded the Nobel prize for theorizing about the quarks, thinks that biological evolution is a complex adaptive system that complies with the second law of Thermodynamics once the entire environment, and not only the single organism, is taken into account. Living organisms dwell "on the edge of chaos", as they exhibit order and chaos at the same time, and they must exhibit both in order to survive. Living organisms are complex adaptive systems that retrieve information from the world, find regularities, compress them into a schema to represent the world, predict the evolution of the world and prescribe behavior for themselves. The schema may undergo variants that compete with one another. Their competition is regulated by feedback from the real world under the form of selection pressure. Disorder is useful for the development of new behavior patterns that enable the organism to cope with a changing environment. Technically speaking, once complex adaptive systems establish themselves, they operate through a cycle that involves variable schemata, randomness, phenotypic consequences and feedback of selection pressures to the competition among schemata. Complex Systems The American biologist Stuart Kauffman is the prophet of "complex" systems. Kauffman's quest is for the fundamental force that counteracts the universal drift towards disorder required by the second law of Thermodynamics. His idea is that Darwin was only half right: systems do evolve under the pressure of natural selection, but their quest for order is helped by a property of our universe, the property that "complex" systems just tend to organize themselves. Darwin's story is about the power of chance: by chance life developed and then evolved. Kauffman's story is about destiny: life is the almost inevitable result of a process inherent in nature. Kauffman's first discovery was that cells behave like mathematical networks. In the early 1960s, Monod and others discovered that genes are assembled not in a long string of instructions but in "genetic circuits". Within the cell, there are regulatory genes whose job is to turn on or off other genes. Therefore genes are not simply instructions to be carried out one after the other, they realize a complex network of messages. A regulatory gene may trigger another regulatory gene that may trigger another gene… etc. Each gene is typically controlled by two to ten other genes. Turning on just one gene may trigger an avalanche of effects. The genetic program is not a sequence of instructions but rather a regulatory network that behaves like a self-organizing system. By using a computer simulation of a cell-like network, Kauffman proved that, in any organism, the number of cell types must be approximately the square root of the number of genes. He starts where Langton ended. His "candidate principle" states that organisms change their interactions in such a way to reach the boundary between order and chaos. For example, the Danish physicist Per Bak studied the pile of sand, whose collapse under the weight of a new grain is unpredictable: the pile self-organizes. No external force is shaping the pile of sand, it is the pile of sand that organizes itself. Further examples include any ecosystem (in which organisms live at the border between extinction and overpopulation), the price of a product (which is defined by supply and demand at the border of where nobody wants to buy it and where everybody wants to buy it). Evolution proceeds towards the edge of chaos. Systems on the boundary between order and chaos have the flexibility to adapt rapidly and successfully. Living organisms are a particular type of complex adaptive systems. Natural selection and self-organization complement each other: they create complex systems poised at the edge between order and chaos, which are fit to evolve in a complex environment. At all levels of organization, whether of living organisms or ecosystems, the target of selection is a type of adaptive system at the edge between chaos and order. Kauffman's mathematical model is based on the concept of "fitness landscapes" (originally introduced by Sewall Wright). A fitness landscape is a distribution of fitness values over the space of genotypes. Evolution is the traversing of a fitness landscape. Peaks represent optimal fitness. Populations wander driven by mutation, selection and drift across the landscape in their search for peaks. It turns out that the best strategy for reaching the peaks occurs at the phase transition between order and disorder, or, again, at the edge of chaos. The same model applies to other biological phenomena and even nonbiological phenomena, and may therefore represent a universal law of nature. Adaptive evolution can be represented as a local hill climbing search converging via fitter mutants toward some local or global optimum. Adaptive evolution occurs on rugged (multipeaked) fitness landscapes. The very structure of these landscapes implies that radiation and stasis are inherent features of adaptation. The Cambrian explosion and the Permian extinction (famous paradoxes of the fossil record) may be the natural consequences of inherent properties of rugged landscapes. Kauffman also noted how complex (nonlinear dynamic) systems which interact with the external world classify and know their world through their attractors. Kauffman's view of life can be summarized as follows: autocatalytic networks (networks that feed themselves) arise spontaneously; natural selection brings them to the edge of chaos; a genetic regulatory mechanism accounts for metabolism and growth; attractors lay the foundations for cognition. The requirements for order to emerge are far easier than traditionally assumed. The main theme of Kauffman's research is the ubiquitous trend towards self-organization. This trend causes the appearance of "emergent properties" in complex systems. One such property is life. There is order for free. Far from equilibrium, systems organize themselves. The way they organize themselves is such that it creates systems at higher levels, which in turn tend to organize themselves. Atoms organize in molecules that organize in autocatalytic sets that organize in living organisms that organize in ecosystems. The whole universe may be driven by a principle similar to autocatalysis. The universe may be nothing but a hierarchy of autocatalytic sets. Autonomous Systems The Chilean neurologist Francisco Varela has adapted Maturana's thought to the theory of autonomous systems, by merging the themes of autonomy of natural systems (i.e. internal regulation, as opposed to control) and their informational abilities (i.e., cognition) into the theme of a system possessing an identity and interacting with the rest of the world. The organization of a system is the set of relations that define it as a unity. The structure of a system is the set of relations among its components. The organization of a system is independent of the properties of its components. A machine can be realized by many sets of components and relations among them. Homeostatic systems are systems that keep the values of their variables within a small range of values, i.e. whose organization makes all feedback internal to them. An autopoietic system is a homeostatic system that continously generates its own organization (by continously producing components that are capable of reproducing the organization that created them). Autopoietic systems turn out to be autonomous, to have an identity, to be unities, and to compensate external perturbations with internal structural changes. Living systems are autopoietic systems in the physical space. The two main features of living systems follow from this: self-reproduction can only occur in autopoietic systems, and evolution is a direct consequence of self-reproduction. Every autonomous system is organizationally closed (they are defined as a unity by their organization). The structure constitutes the system and determines its behavior in the environment; therefore, information is a structural aspect, not a semantic one. There is no need for a representation of information. Information is "codependent". Mechanisms of information and mechanisms of identity are dual. The cognitive domain of an autonomous system is the domain of interaction that it can enter without loss of closure. An autonomous unit always exhibits two aspects: it specifies the distinction between self and notself, and deals with its environment in a cognitive fashion. The momentous conclusion that Varela reaches is that every autonomous system (ecosystems, societies, brains, conversations) is a "mind" (in the sense of cognitive processes). A Science of Prisms Alternatives to traditional science now abound. One is interesting because it starts with a completely different approach towards reality and it encompasses more than just matter. In the 1970's the American physicist Buckminster Fuller developed a visionary theory, also called "synergetics", that attacked traditional science at its very roots. "Synergy" is the behavior of a whole that cannot be explained by the parts taken separately. Synergetics, therefore, studies system in a holistic (rather than reductionistic) way. The way it does this, is by focusing on form rather than internal structure. Because of its emphasis on shape, Synergetics becomes a branch of Geometrics, the discipline of configurations (or patterns). Synergetics employs 60-degree coordination instead of the usual 90-degree coordination. The triangle (and tetrahedron) instead of the square (and the cube) is the fundamental geometric unit. Fuller's thought is inspired by one of his own inventions, the "geodesic" dome (1954), a structure that exploits a very efficient way of enclosing space and that gets stronger as it gets larger. The bottom line is that reality is not made of "things", but of angle and frequency events. All experience can be reduced to only angles and frequencies. Fuller finds "prisms" to be ubiquitous in nature and in culture. All systems contained in the universe are polyhedra, "universe" being the collection of all experiences of all individuals. Synergetics rediscovers, in an almost mystical way, most of traditional science, but mainly through topological considerations (with traditional topology extended to "omnitopology"). For example, Synergetics proves that the universe is finite and expanding, and that Planck's constant is a "cosmic relationship". The Emergence of a Science of Emergence Prigogine's non-equilibrium Thermodynamics, Haken's synergetics, Von Bertalanffi's general systems theory and Kauffman's complex adaptive systems all point to the same scenario: the origin of life from inorganic matter is due to emergent processes of self-organization. The same processes account for phenomena at different levels in the organization of the universe, and, in particular, for cognition. Cognition appears to be a general property of systems, not an exclusive of the human mind. A science of emergence, as an alternative to traditional, reductionist, science, could possibly explain all systems (living and not). Further Reading Buchler Justus: METAPHYSICS OF NATURAL COMPLEXES (Columbia University Press, 1966) Bunge Mario: TREATISE ON BASIC PHILOSOPHY (Reidel, 1974-83) Cohen Jack & Steward Ian: THE COLLAPSE OF CHAOS (Viking, 1994) Coveney Peter: FRONTIERS OF COMPLEXITY (Fawcett, 1995) Dalenoort G.J.: THE PARADIGM OF SELF-ORGANIZATION (Gordon & Breach, 1989) Dalenoort G.J.: THE PARADIGM OF SELF-ORGANIZATION II (Gordon & Breach, 1994) Davies Paul: GOD AND THE NEW PHYSICS (Penguin, 1982) Eigen Manfred & Schuster Peter: THE HYPERCYCLE (Springer Verlag, 1979) Forrest Stephanie: EMERGENT COMPUTATION (MIT Press, 1991) Fuller Richard Buckminster: SYNERGETICS: EXPLORATIONS IN THE GEOMETRY OF THINKING (Macmillan, 1975) Fuller Buckminster: COSMOGRAPHY ( Macmillan, 1992) Gell-Mann Murray: THE QUARK AND THE JAGUAR (W.H.Freeman, 1994) Gleick James: CHAOS (Viking, 1987) Goldberg David: GENETIC ALGORITHMS (Addison Wesley, 1989) Haken Hermann: SYNERGETICS (Springer-Verlag, 1977) Holland John: ADAPTATION IN NATURAL AND ARTIFICIAL SYSTEMS (Univ of Michigan Press, 1975) Holland John: HIDDEN ORDER (Addison Wesley, 1995) Kauffman Stuart: THE ORIGINS OF ORDER (Oxford University Press, 1993) Kauffman Stuart: AT HOME IN THE UNIVERSE (Oxford Univ Press, 1995) Koestler Arthur: THE GHOST IN THE MACHINE (Henry Regnery, 1967) Langton Christopher: ARTIFICIAL LIFE (Addison-Wesley, 1989) Laszlo Ervin: INTRODUCTION TO SYSTEMS PHILOSOPHY (Gordon & Breach, 1972) Lewin Roger: COMPLEXITY (Macmillan, 1992) Mandelbrot Benoit: THE FRACTAL GEOMETRY OF NATURE (W.H.Freeman, 1982) Nicolis Gregoire & Prigogine Ilya: SELF-ORGANIZATION IN NON-EQUILIBRIUM SYSTEMS (Wiley, 1977) Nicolis Gregoire & Prigogine Ilya: EXPLORING COMPLEXITY (W.H.Freeman, 1989) Nicolis Gregoire: INTRODUCTION TO NONLINEAR SCIENCE (Cambridge University Press, 1995) Pattee Howard Hunt: HIERARCHY THEORY (Braziller, 1973) Prigogine Ilya: INTRODUCTION TO THERMODYNAMICS OF IRREVERSIBLE PROCESSES (Interscience Publishers, 1961) Prigogine Ilya: NON-EQUILIBRIUM STATISTICAL MECHANICS (Interscience Publishers, 1962) Prigogine Ilya & Stengers Isabelle: ORDER OUT OF CHAOS (Bantham, 1984) Salthe Stanley: EVOLVING HIERARCHICAL SYSTEMS (Columbia University Press, 1985) Salthe Stanley: DEVELOPMENT AND EVOLUTION (MIT Press, 1993) Thom Rene': MATHEMATICAL MODELS OF MORPHOGENESIS (Horwood, 1983) Thom Rene': STRUCTURAL STABILITY AND MORPHOGENESIS (Benjamin, 1975) Toffoli Tommaso & Margolus Norman: CELLULAR AUTOMATA MACHINES (MIT Press, 1987) Turing Alan Mathison: MORPHOGENESIS (North-Holland, 1992) Varela Francisco: PRINCIPLES OF BIOLOGICAL AUTONOMY (North Holland, 1979) Von Bertalanffy Ludwig: GENERAL SYSTEMS THEORY (Braziller, 1968) Von Neumann John: THEORY OF SELF-REPRODUCING AUTOMATA (Princeton Univ Press, 1947) Waldrop Mitchell: COMPLEXITY (Simon & Schuster, 1992) Zeeman Erich Christian: CATASTROPHE THEORY (Addison-Wesley, 1977)

The universe designs networks of finer and finer connections. Intelligent systems are the finest of these networks, embedded inside a whole hierarchy, like layers of an onion. The First layer we theorize was the big bang. This initial pulses of energy sends out waves of energy and atoms that curl into points of swirling matter. At the center of this points vortices form. From these black holes implode sending out a second pulse a gravity waves. These waves curl into points forming stars bound into the matrix of the galaxy. This structure contains a balance of forces enabling all points to interact though gravity. Some stars explode then create complex elements in a third pulse of energy. This assemblage of elements curl into a yet more complex internal matrix of solar systems. Now the stage is set for pre-existing possibilities to form networks of life. Life and Intelligents will manifest though the natural flow patterns inherent between waves and elements. The elements will firstly juxtapose themselves one to another forming simple chemical matrixes, organic molecules. Just as the central black hole has formed into a catch basin for light waves, there lies an inherent pattern in these molecules to direct waves of light energy . The first cells form around the energy of light waves. This is the secret to build any self-sustaining, self-evolving system. The components form around the energy that sustains it ! The vesica attractor; The blueprint for biologic systems resulted from a compression of information from its surrounding matrices. quote: “The shapes that chaotic systems produce in phase space are called "strange attractors" because the system will tend towards the kinds of state described by the points in the phase space that lie within them.” Once the adjacent matrix, in this case the Cambrian sea had reached a critical threshold of complexity. This threshold being one of fractal self-similarity, these representative components spiral together and bond in a self-similar fashion as the surrounding matrix. { see vesica attractor}. Information at large is then transferred though this dissipative torus structure. quote: “as system goes through a transition from order to chaos if the strength of the interactions among its parts is gradually increased. But then very "disordered" systems spontaneously "crystallize" into a higher degree of order” This spontaneous ordering occurs as the oolitic matrix dissipates among the microbial substrate, leaving in its place a connected cellular matrix. The first animal life. Now this system can further compress its own hierarchal matrix [body plan] into a signal cell and self-replicate. So what is this showing us about complexity and spontaneous self-ordering. Complex systems manifest by compressing surrounding complexity though simple coded channels.

This is a clarification on my first post, quote;There is a definitive difference between the "IDism Movement" (IDism) and "Design Science": Namely, that the ID movement is purposefully designed to further the special interest agenda of a group of religiously biased theologians known as the "wedge strategists" at the Discovery Institute. Whereas "Design Science" is a rigorous, systematic study of the ordering of components in our Universe. True "science" in this regard neither imparts or encourages theologically based philosophical biases.;quote

I first started reading on system science in the late seventies with the Tao of Physics by, FRITJOF CAPRA The real pioneers of system science, Mantarana; Varela, Prigogine just to name a few. Yes you are correct, it was been around a long time but…… universities take time to catch up to the theorist. There can be a gap of decades between what is known to a few, and what is than accepted enough to be taught in the universities. This type of science is a way of thinking, it is not a structure of information, and is just emerging in the mainstream academics in the last twenty years or so, which makes it new.

no, good point! quote: -------------------------------------------------------------------------------- SYSTEMS THEORY: Systems theory or systems science argues that however complex or diverse the world that we experience, we will always find different types of organization in it, and such organization can be described by principles which are independent from the specific domain at which we are looking. Hence, if we would uncover those general laws, we would be able to analyze and solve problems in any domain, pertaining to any type of system. (Principia Cybernetica) --------------------------------------------------------------------------------

There is a new science emerging, one of chaos! Its a new way to see the natural phenomenon of evolution. Opening vast areas of study, and has brought with it, its own vocabulary of —"fractals," "bifurcations," "strange attractors," and "dissipative structures.” These new models go well beyond the traditional views of reductionism. I have come to realizes, there is an ever increasing gap in science today. One that will leave the two opposing views of "IDism Movement" and Darwinism out of mainstream. The real divergence lies not in Idst and Darwinist, but rather between the view points of systems thinking, that deals in the dynamical relationships of causality in cooperative networks. As opposed to the traditional reductionist approach, applied to Darwinistic view points. While the Idst, and reductionist Darwinist, stand upon the dock arguing over how best to classify and contain nature into manageable parts and slogans. The systems theorist are sailing away into the future…. http://www.fractalwisdom.com/FractalWisdom/fourattr.html

This is a powerful concept, that a mere thought can produce its own organizational power in a landscape of shared thought. This is a natural evolutionary step when beings emerge from the evolutionary constraints of the genome, into the realm of the primarily cognitive. This is why communication technology has become such a powerful tool. It has “flattened the world” as Thomas Freidman put it. Now the most powerful force has become the idea. Evolution was passed into a new landscape, I believe by studying certain evolutionary patterns inherent in life as a whole. We can begin to see patterns that can be applied to memes. These governing dynamics of physics, biology, and genetics also apply to the meme-space.

This photo and photo-shop rendering is all I can find at the moment. What I really need is a photo shop animation of the dynamic. It is beautiful system but at the moment I am the only one that can imagine it. I find this frustrating. This is going to be a long step by step process, I am still trying to locate the other photos. I do not have the software and time that I used to have, so be patient with more photos. The fossil has a opening all the way though the center just as the photo-shop rendering. This representation is what I think this fossil would have looked like when it was alive. The right intake aperture became dominant over the left, resulting in an asymmetrical growth of extruding mineralization around the left aperture. This particular vesica attractor would have resulted in a conch, or gastropod design. The dominant right intake would develop a gill while the left developed a spiraling shell and central axis of the [columella.] This would keep spiraling until the shell enclosed the left aperture complexly. This left spiraling point then became what most would assume as the front. Myself included. If both chambers keep a symmetrical flow, which would have been very rare, the result would be a symmetrical body plan and two gills. If the attractor retained the shell and a symmetrical flow though the apertures, the result would be a cephalopod. This shell is not a genetic adaptation but more precisely the receipt from paying {Schrödinger entropy debt} http://64.233.167.104/search?q=cache:FKs97eM3WIoJ:www.entropylaw.com/thermoevolution7.html+Schr%C3%B6dinger+entropy+debt%7D&hl=en {The oolitic mass would shrink[dissipate] during this pulse into a higher ordered state.} A fish’s body plan is the most perfect of all the possible out comes, and looks as though it only occurred once. All the myriad shell designs now appear to me as beautiful attempts at a fish’s body plan. Even natures screw up’s are geometrical marvels. The fossil came from a creek bed cutting down though early Cambrian strata This strata is made up of dolomite limestone. The strata this originated from developed layers of a microbial mats in fine silty mud, that is devoid of any particles that would induce the growth of stromatalites, so instead you just find layers of cyanobacteia. When fine quartz particles our introduced, oolites are formed.

I believe you are being honest, and I apologize if I am not reading you correctly. I may be reacting to others that are not as sincere as yourself. I will try to clarify and condense my view. The fossil record show a disparity in the formation of complex body plans. The individual eukaryote cannot build these structures, they do not carry within themselves a blue print for an overall structure. science today is attempting to answer these questions [ via, systems science] though genomic constraints. My discovery shows the missing information in the original body design, was provided by a wave function, acting on a mass of oolitic spheres bound by a microbial substrate. This substrate crystallized into an archetypal pattern, the first complex animal life. [source of a body plan pattern] that then spawned an entire phyla. This central archetype then becomes a sustained, central information bank for the phyla. Releasing new genetic information in pulses when they have been accumulated over time. This model not only accounts for the original forms but also genetic control patterns of punctuated equilibrium. …… This is what the fossil is saying to me in the context of the fossil record . I hope this has clarified my point.

Context, only can be achieved when one refers to the information on a whole. let me be clear as possible The fossil record does not reflect Darwinian evolutionary models. The reason I am becoming redundant is because I have been accused of having only one out of context post to back this up. There are many very good questions to be ask why do you keep asking the same questions over and over, challenge me ! I have actually made some very controversial claims with this model but no one seems to catch them. The gaps in our understanding of the basic fossil record are very well known, and are not even ones that need defending. What is worth discussing is possible solutions to these gaps not if there are gaps. It appears you are defending rather than inquiring. What I know about scientific approach is that you ask many question on many levels in order to achieve perspective. What is your function here?

Read my post it is about (Punctuated Equilibrium) Punctuated Equilibrium; archetypal life forms were born on the cusp of two worlds. I believe the purpose of this is to establish an informational feed back loop anchored at a central Source. From this evolutionary still point genetic novelty could be collected and recombined so new species can be created.

Hey now that hurt, I hate Tom Delay!!

Vesica attractor; Gastrapoda Images of the artifact can now be veiwed at; http://www.imagestation.com/album/?id=2128032952

Chapter13 A Blindfolded Watchmaker: The Arrival of the Fittest David L. Wilcox http://www.leaderu.com/orgs/fte/darwinism/chapter13.html quote: 1. Life's origin. The origin of life requires the initial encoding of specified blueprints, a non-Darwinian process. Specification involves arbitrary definitions for the "letters" used to write the "messages." How then did specified complexity (blueprints and their described products/"machines") arise from any amount of nonspecified complexity (complex machines, but no blueprints)? Are we really making progress in explaining the source of the genetic code? "The holy grail is to combine information content with replication" (Orgel in Amato, 1992). That is, we need a machine that can write down its own specifications (Thaxton, 1984). 2. Origin of the first animals (Cambrian era). The Cambrian explosion illustrates the abrupt formulation of body-plan constraints (Erwin, et al. 1987). But how within 25 million years (impalas have remained unchanged longer than that) could the full complexity of 70plus metazoan phylum level body-plans arise, and be individuated with error-checking developmental cybernetic controls from protozoans? Remember that protozoans do not have encoded genetic information for morphology due to cellular interaction. How can code that does not yet exist be mutated? Further, given the appearance of new code, how are phylum level morphological "norms" generated, capable of holding for the remainder of the Phanerozoic? As David Jablonski put it, "The most dramatic kinds of evolutionary novelty, major innovations, are among the least understood components of the evolutionary process" (Lewin, 1988). 3. Species stasis. Species show morphological stasis in the face of high levels of selectable diversity (Stanley, 1979 & 1985). But what sort of genetic anchor can hold constant a species' morphological mean and variance for several million years (Michaux, 1989), when enough genetic diversity exists in such species to allow laboratory selection to cause a ten-fold movement of that morphological mean? Are current models of the informational organization of the genome adequate to explain this? This difficulty is reinforced by the still greater morphological stasis shown by the body-plans of the higher levels of the taxonomic system, a stasis that seems to shape, direct, and constrain lower level change in an almost " archetypic " manner. This is hardly the neo-Darwinian prediction....quote Archetypal life forms Curiously the fossil record shows a top down hierarchical pattern of appearance in which major structural themes of body plans or [bauplans] emerge before minor variations on those themes. The vesica attractor enables an archetype to form around a preexisting possibility for order. Form will follow both Internal structures and environmental dynamics. These two basins of order represent the factors involved in determining the bauplan that emerges from the vesica attractor [ Example] archetypal forms developing in the high energy tidal zone will manifest mobile, dynamic, heart based bauplans. Whereas an archetype forming in the stable depths will manifest a static configuration around a basin of internal structure. The original archetypes would not have had time to be based on genetic adaptation but rather on geometrical patterns inherent in preexisting possibilities. From these basic configurations, genetics could then use time to develop variations on these “Eternal true forms” That emerged quickly and directly from the vesica attractor. This scenario fits the fossil record, as well as current genome research that suggests the phyla arose separately, simultaneously and abruptly from a ''common primordial pond" of genetics and this artifact shows clearly and precisely how. The embryonic structure appears to have ruptured a developing chamber. This chamber could no longer contain pressure so the system collapsed. Fortunately for science this was well timed to preserve a window into a miracle of transformation, any further along the oolites would have completed the transformation into shell, any sooner the structure would not have developed into the complex geometrical form. This form contains an extraordinary set of patterns when interpreted exposes a link between two worlds. Allowing a special insight into both. Punctuated Equilibrium Archetypal life forms were born on the cusp of two worlds. I believe the purpose of this is to establish an informational feed back loop anchored at a central Source. From this evolutionary still point genetic novelty could be collected and recombined so new species can be created. This renewing cycle of information from a separate bank of selective genetics could also keep the system far from equilibrium. This feedback loop cycles between two states, one of stability, and one of renewal. The Archetypal life forms would inherit an carbon\silicon based information gathering and storage system, {oolitic core} thus acting as the central, sustainable, creative, pool for the phyla. This is the best of both worlds... Unlimited life span in their own self-replicating systems, and access to creative adaptive change from its progeny. If this model proves to be correct, it begs an obvious and fascinating question..... Where are these original archetypes now?

Images of the artifact can now be veiwed at http://www.imagestation.com/album/?id=2128032952

This is one of the stepping stones emerging from systems science that connects to my new model. That is based on a fossil -------------------------------------------------------------------------------- The Landscape of Possibility: A Dynamic Systems Perspective on Archetype and Change http://cogprints.org/1084/00/Jap_9.html Maxson J. McDowell Imagine a sand-dune rippled by the wind. The dune is an emergent, self-organized structure. Its surface organizes itself according to information contained within the wind, its velocity, for instance, and its direction. That information is translated into a particular set of ripples by the constraints of the dune's height and shape (equivalent to the gross anatomy of the brain) and by the constraints of an individual grain of sand (equivalent to the anatomy and physiology of a neuron). Once the ripples have been established they influence the subsequent movement of air over the surface of the dune. In the same way, once the fine structure of the brain has been established it controls the subsequent flow of sensory information. Genes and Self-Organization A more general argument concerns the machinery of inheritance. I have only about 100,000 different genes while a bacterium has 3 to 5,000 genes (Alberts et. al., 1994, pp. 339-340). But my anatomy is astronomically more complex than that of a bacterium. It has been estimated that the human body contains about 5x1025 bits of information in the arrangement of its molecules while the human genome contains less than 109 bits of information. Again the disparity is of astronomical proportions. These numbers prove that my genes must be used economically. They must code for processes which enable my structure to evolve, but they are too few to form a "blueprint", or image, of my final structure (Calow 1976, pp. 101-103; Elman et. al., 1998, p. 319). My body's structure, therefore, must be emergent. An emergent structure is layered in distinct, successive levels of complexity; each level self-organizes with minimal guidance from the genes. Self-organization is directed by the inherent properties of the component parts (what fits with what). It is also directed by the inherent tendency of a dynamic system to assume an ordered form. I will say more about this later. Finally self-organization is directed by information from the environment (Elman et. al., 1998, pp. 319-323). Dynamic Systems A triangle is static, but a dynamic system also has such pre-existing possibilities. Think of a mountain stream. It is a dynamic system because it only exists while energy flows through it, in this case the water's kinetic energy. Sometimes the stream forms a whirlpool. Sometimes it assumes the serpentine form. The latter is seen most clearly in an aerial photograph of a river delta. Both forms are pre-existing possibilities, characteristic of rivers and streams everywhere. Even the stream of stars in a galaxy sometimes forms a whirlpool (Hildebrandt and Tromba 1996, pp. 12-13). A stream organizes itself, but the ways it can do so are constrained: only certain pre-determined forms are possible. Like a mountain stream, a living creature is also a dynamic system. It too exists only while energy flows through it, either from food if it is an animal, or from the sun if it is a plant. Like the evolution of a mountain stream, evolution in biology is self-organized: it is directed by no outside agent and it leads to emergent levels of order (Holland 1998, pp 225-231). Like a mountain stream, a living creature evolves forms which are pre-existing possibilities.The snake is an example. Not all snakes are related: at different times, several different groups of reptiles evolved the snake body-form (Zug 1993, p. 119) as an adaptation for moving through narrow spaces. A snake-like body-form also occurs in fish (the eel) and in mammals (the ferret). Amongst invertebrates roundworms, earthworms, and centipedes have a similar body-form. The first worm-like fossils, of animals about a meter long, appear in the Precambrian era, about 700 million years ago (Kauffman 1995, pp. 158-161). Thus the body-form of the snake is a pre-existing possibility which waits to be discovered by evolution. "I said earlier that my body's structure is layered in a hierarchy of successive levels of complexity. Within each layer, complex order self-organizes from simpler components. In a rigorous analysis Holland (1998, pp. 225-231) has shown that each layer is itself a higher-order dynamic system. Thus molecules form a cell and cells form an organ. Immune cells, for example, form a functioning immune system and nerve cells form a functioning brain. Organs, in turn, form an organism. We have already seen that organisms, in their turn, form an ecosystem. These layered higher-order dynamic systems are the basis for emergence in life. Because the personality is an emergent living structure, it is very likely that it too represents a layer within this hierarchy, that is, it too belongs to a higher-order dynamic system."|Quote My model follows these systems just described, and can be observed though the lens of the The vesica attractor .....and not only followed this self-organizing system but also filled these gaps in Morphology. Infact, As I have stated before.... when viewed objectively, Morphology itself, can be seen as an artifact of this developmental process, Anatomically, as well as viewed from the record of metazoan paleontology. An analogy of the Genetic controls in the formation of the original body plans might be compared to how snow fakes crystallize from the underlying order of the water molecule. As the oolitic mass shrinks....A crystallization of genetic probabilities emerge from a medium of cohesive networks, forming self reflexive circuits of tension.{ see tensegrity } This is what I am referring to as a {descending order of iteration matrices that self organize the cellular structure}Tensigrity combined with fluid dynamics, builds the architectural framework first. This wave of tension descends to the cellular level. The extracellular matrix will begin to form bonds with the intracellular matrix inside the individual cell. [This intracellular matrix controls gene switching] This resonance results in a synchronization and amplification of genetic responses resulting in network of connections in the architecture of the emerging organism, enabling the individual cell though it's own intracellular matrix to respond to this outer matrix. This crystallization of the recursive dynamic structure might well result in an "algorithmic self-assembly" of genetic probabilities. This may be a solution to some lose ends in our present understanding the development of complex morphology. The answer it appears is the architectural framework formed first, from wave dynamics working from the outside inward, while the interior design of genetics, worked from the inside out. Presently most research is focused solely on genomic controls in the formation of complex morphology. The answer it appears is that nature hired its architect first {wave dynamics} its interior designer second, {genetic probabilities} Just as we would in building a structure. You may be interested to know that the heart is an artifact of this process. The heart as you probably know is an attractor. Coincidentally this fact my be perfect for proving this theory.

sorry double post

Dishonesty is misrepresenting my post by suggesting they were out of context. Darwin assumed transitional fossils would be rare and postulated that these gaps would be filled in with new fossil discoveries, yet after 150 years these gaps have not been filled. He also postulated; "The number of intermediate varieties, which have formerly existed on the earth, (must) be truly enormous. Why then is not every geological formation and every stratum full of such intermediate links? Geology assuredly does not reveal any such finely graduated organic chain; and this, perhaps, is the most obvious and gravest objection which can be urged against my theory". The two views are not contradictory , he was just stating that his model was subject to new evidence. He was making sure that people understood that fact, because he was a great scientist, and understood that all scientific models are only stepping stones to understanding, not dogma to be defended by well….you’ve defined yourself fairly well. Here are a few other quotes that can be checked for contextual meaning I suggest you start work early they are all saying the same thing Darwin said and they have been saying it for a very long time. "It is still, as it was in Darwin's day, overwhelmingly true that the first representatives of all the major classes of organisms known to biology are already highly characteristic of their class when they make their initial appearance in the fossil record. This phenomenon is particularly obvious in the case of the invertebrate fossil record. At its first appearance in the ancient paleozoic seas, invertebrate life was already divided into practically all the major groups with which we are familiar today. Denton, Michael (1986) Evolution: A Theory in Crisis Bethesda, Maryland, Adler & Adler, Pub., p.162 As the years passed after the Darwinian revolution, and as evolution became more and more consolidated into dogma, the gestalt of continuity imposed itself on every facet of biology. The discontinuities of nature could no longer be perceived. (p. 74) Denton, Michael (1986) Evolution: A Theory in Crisis Bethesda, Maryland, Adler & Adler, Pub. -------------------------------------------------------------------------------- No wonder paleontologists shied away from evolution for so long. It never seemed to happen. Assiduous collecting up cliff faces yields zigzags, minor oscillations, and the very occasional slight accumulation of change--over millions of years, at a rate too slow to account for all the prodigious change that has occurred in evolutionary history. When we do see the introduction of evolutionary novelty, it usually shows up with a bang, and often with no firm evidence that the fossils did not evolve elsewhere! Evolution cannot forever be going on somewhere else. Yet that's how the fossil record has struck many a forlorn paleontologist looking to learn something about evolution. Eldredge, N., 1995 Reinventing Darwin Wiley, New York, p. 95 -------------------------------------------------------------------------------- Most families, orders, classes, and phyla appear rather suddenly in the fossil record, often without anatomically intermediate forms smoothly interlinking evolutionarily derived descendant taxa with their presumed ancestors. Eldredge, N., 1989 Macro-Evolutionary Dynamics: Species, Niches, and Adaptive Peaks McGraw-Hill Publishing Company, New York, p. 22 -------------------------------------------------------------------------------- We are faced more with a great leap of faith -- that gradual, progressive adaptive change underlies the general pattern of evolutionary change we see in the rocks -- than any hard evidence. Eldredge, N. and Tattersall, I. (1982) The Myths of Human Evolution Columbia University Press, p. 57 -------------------------------------------------------------------------------- The record jumps, and all the evidence shows that the record is real: the gaps we see reflect real events in life's history -- not the artifact of a poor fossil record. Eldredge, N. and Tattersall, I. (1982) The Myths of Human Evolution Columbia University Press, p. 59 -------------------------------------------------------------------------------- The fossil record flatly fails to substantiate this expectation of finely graded change. Eldredge, N. and Tattersall, I. (1982) The Myths of Human Evolution Columbia University Press, p. 163 -------------------------------------------------------------------------------- The fossil record suggests that the major pulse of diversification of phyla occurs before that of classes, classes before that of orders, and orders before families. This is not to say that each higher taxon originated before species (each phylum, class, or order contained at least one species, genus, family, etc. upon appearance), but the higher taxa do not seem to have diverged through an accumulation of lower taxa. Erwin, D., Valentine, J., and Sepkoski, J. (1988) "A Comparative Study of Diversification Events" Evolution, vol. 41, p. 1183 ------ "Moreover, within the slowly evolving series, like the famous horse series, the decisive steps are abrupt and without transition." Goldschmidt, Richard B. (1952) "Evolution, As Viewed By One Geneticist" American Scientist, Vol. 40, No. 1, pp. 84-94 -------------------------------------------------------------------------------- The history of most fossil species include two features particularly inconsistent with gradualism: 1) Stasis - most species exhibit no directional change during their tenure on earth. They appear in the fossil record looking much the same as when they disappear; morphological change is usually limited and directionless; 2) Sudden appearance - in any local area, a species does not arise gradually by the steady transformation of its ancestors; it appears all at once and 'fully formed'. Gould, S.J. (1977) "Evolution's Erratic Pace" Natural History, vol. 86, May -------------------------------------------------------------------------------- Writing on Darwin's decision to portray evolution as a gradual and stately process, Gould states, "I do not know why Darwin chose to follow Lyell and the gradualists so strictly, but I am certain of one thing: preference for one view or the other had nothing to do with superior perception of empirical information. On this question, nature spoke (and continues to speak) ambiguously and multifariously. Cultural and methodological preferences had as much influence upon any decision as the actual data." ... "... in defending gradualism as a nearly universal tempo, Darwin had to use Lyell's most characteristic method of argument -- he had to reject literal appearance and common sense for an underlying "reality." (Contrary to popular myths, Darwin and Lyell were not the heroes of true science, defending objectivity against the the theological fantasies of such "catastrophists" as Cuvier and Buckland. Catastrophists were as committed to science as any gradualist; in fact, they adopted the more "objective" view that one should believe what one sees and not interpolate missing bits of a gradual record into a literal tale of rapid change." ... "The extreme rarity of transitional forms in the fossil record persists as the trade secret of paleontology. The evolutionary trees that adorn our textbooks have data only at the tips and nodes of their branches; the rest is inference, however reasonable, not the evidence of fossils. Yet Darwin was so wedded to gradualism that he wagered his entire theory on a denial of this literal record: The geological record is extremely imperfect and this fact will to a large extent explain why we do not find interminable varieties, connecting together all the extinct and existing forms of life by the finest graduated steps. He who rejects these views on the nature of the geological record, will rightly reject my whole theory. Darwin's argument still persists as the favored escape of most paleontologists from the embarrassment of a record that seems to show so little of evolution. In exposing the its cultural and methodological roots, I wish in no way to impugn the potential validity of gradualism (for all general views have similar roots). I wish only to point out that it was never "seen" in the rocks. Paleontologists have paid an exorbitant price for Darwin's argument. We fancy ourselves as the only true students of life's history, yet to preserve our favored account of evolution by natural selection we view our data as so bad that we never see the very process we profess to study." ... Comment: Gould goes on to explain that Darwinian process do not require slow gradual change and that a model of punctuated equilibrium can explain the pattern of sudden appearance and stasis in the fossil record. "Eldredge and I believe that speciation is responsible for almost all evolutionary change." The problem is complicated, however, by the fact that species diversity is the one feature conspiculously absent upon the appearance of most phyla. See Valentine, J., and Erwin, D. (1985) "Interpreting Great Developmental Experiments: The Fossil Record", Development as an Evolutionary Process. ... "The history of most fossil species include two features particularly inconsistent with gradualism: 1) Stasis - most species exhibit no directional change during their tenure on earth. They appear in the fossil record looking much the same as when they disappear; morphological change is usually limited and directionless; 2) Sudden appearance - in any local area, a species does not arise gradually by the steady transformation of its ancestors; it appears all at once and 'fully formed'." Gould, S.J. (1977) "Evolution's Erratic Pace" Natural History, vol. 86, May -------------------------------------------------------------------------------- Gould honestly admits that the neo-Darwinian synthesis is not supported by the fossil evidence and "is effectively dead, despite its persistence as textbook orthodoxy." Gould, S. J. (1980) "Is a new and general theory of evolution emerging?" Paleobiology, 6(1), p. 120 -------------------------------------------------------------------------------- [T]he absence of fossil evidence for intermediate stages between major transitions in organic design, indeed our inability, even in our imagination, to construct functional intermediates in many cases, has been a persistent and nagging problem for gradualistic accounts of evolution. Gould, S.J., 1982 "Is a new and general theory of evolution emerging?" Evolution Now: A Century After Darwin Maynard Smith, J. (editor) W. H. Freeman and Co. in association with Nature, p. 140 -------------------------------------------------------------------------------- Indeed, it is the chief frustration of the fossil record that we do not have empirical evidence for sustained trends in the evolution of most complex morphological adaptations. Gould, S. J. and Eldredge, N., 1988 "Species selection: its range and power" Scientific correspondence in Nature, Vol. 334, p. 19 -------------------------------------------------------------------------------- "As is now well known, most fossil species appear instantaneously in the fossil record." Kemp, Tom (1985) "A Fresh Look at the Fossil Record" New Scientist, Vol. 108, No. 1485, December 5, 1985), p. 66 (Dr. Tom Kemp is Curator of Zoological Collections at the Oxford University Museum.) -------------------------------------------------------------------------------- Described recently as "the most important evolutionary event during the entire history of the Metazoa," the Cambrian explosion established virtually all the major animal body forms -- Bauplane or phyla -- that would exist thereafter, including many that were 'weeded out' and became extinct. Compared with the 30 or so extant phyla, some people estimate that the Cambrian explosion may have generated as many as 100. The evolutionary innovation of the Precambrian/Cambrian boundary had clearly been extremely broad: "unprecedented and unsurpassed," as James Valentine of the University of California, Santa Barbara, recently put it (Lewin, 1988). Lewin then asked the all important question: "Why, in subsequent periods of great evolutionary activity when countless species, genera, and families arose, have there been no new animal body plans produced, no new phyla?" Lewin, R. (1988) Science, vol. 241, 15 July, p. 291 -------------------------------------------------------------------------------- Paleontologists had long been aware of a seeming contradiction between Darwin's postulate of gradualism ... and the actual findings of paleontology. Following phyletic lines through time seemed to reveal only minimal gradual changes but no clear evidence for any change of a species into a different genus or for the gradual origin of an evolutionary novelty. Anything truly novel always seemed to appear quite abruptly in the fossil record. Mayr, E., 1991 One Long Argument: Charles Darwin and the Genesis of Modern Evolutionary Thought Harvard University Press, Cambridge, p. 138 -------------------------------------------------------------------------------- What one actually found was nothing but discontinuities. All species are separated from each other by bridgeless gaps; intermediates between species are not observed. ... The problem was even more serious at the level of the higher categories. Mayr, E., 1982 The Growth of Biological Thought: Diversity, Evolution, and Inheritance The Belknap Press of Harvard University Press, p. 524 -------------------------------------------------------------------------------- [W]e have so many gaps in the evolutionary history of life, gaps in such key areas as the origin of the multicellular organisms, the origin of the vertebrates, not to mention the origins of most invertebrate groups. McGowan, C., 1984 In the Beginning... A Scientist Shows Why the Creationists are Wrong Prometheus Books, p. 95 -------------------------------------------------------------------------------- With the benefit of hindsight, it is amazing that palaeontologists could have accepted gradual evolution as a universal pattern on the basis of a handful of supposedly well-documented lineages (e.g. Gryphaea, Micraster, Zaphrentis) none of which actually withstands close scrutiny. Paul, C. R. C., 1989 "Patterns of Evolution and Extinction in Invertebrates" Allen, K. C. and Briggs, D. E. G. (editors), Evolution and the Fossil Record Smithsonian Institution Press, Washington, D. C., 1989, p. 105 -------------------------------------------------------------------------------- [G]aps between higher taxonomic levels are general and large. Raff, R. A. and Kaufman, T. C., 1991 Embryos, Genes, and Evolution: The Developmental-Genetic Basis of Evolutionary Change Indiana University Press, p. 35 -------------------------------------------------------------------------------- -------------------------------------------------------------------------------- "A large number of well-trained scientists outside of evolutionary biology and paleontology have unfortunately gotten the idea that the fossil record is far more Darwinian than it is. This probably comes from the oversimplification inevitable in secondary sources: low-level textbooks, semipopular articles, and so on. Also, there is probably some wishful thinking involved. In the years after Darwin, his advocates hoped to find predictable progressions. In general these have not been found yet the optimism has died hard, and some pure fantasy has crept into textbooks." Science July 17, 1981, p. 289 -------------------------------------------------------------------------------- The known fossil record is not, and has never has been, in accord with gradualism. What is remarkable is that, through a variety of historical circumstances, even the history of opposition has been obscured. ... 'The majority of paleontologists felt their evidence simply contradicted Darwin's stress on minute, slow, and cumulative changes leading to species transformation.' ... their story has been suppressed. Stanley, S. M., 1981 The New Evolutionary Timetable: Fossils, Genes, and the Origin of Species Basic Books, Inc., Publishers, N.Y., p. 71 If any event in life's history resembles man's creation myths, it is this sudden diversification of marine life when multicellular organisms took over as the dominant actors in ecology and evolution. Baffling (and embarrassing) to Darwin, this event still dazzles us and stands as a major biological revolution on a par with the invention of self-replication and the origin of the eukariotic cell. The animal phyla emerged out of the Precambrian mists with most of the attributes of their modern descendants." Bengston, Stefan (1990) Nature 345:765 Simpson, G. G. (1944) Tempo and Mode in Evolution Columbia University Press, New York, p. 105, 107 -------------------------------------------------------------------------------- "It remains true, as every paleontologist knows, that most new species, genera, and families, and that nearly all categories above the level of families, appear in the [fossil] record suddenly, and are not led up to by gradual, completely continuous transitional sequences" Simpson, George Gaylord (1953) The Major Features of Evolution New York: Columbia University Press, p. 360 -------------------------------------------------------------------------------- [F]or more than a century biologists have portrayed the evolution of life as a gradual unfolding ... Today the fossil record ... is forcing us to revise this conventional view. Stanley, S. M., 1981 The New Evolutionary Timetable: Fossils, Genes, and the Origin of Species Basic Books, Inc., Publishers, N.Y., p.3 -------------------------------------------------------------------------------- [T]he fossil record itself provided no documentation of continuity -- of gradual transitions from one kind of animal or plant to another of quite different form. Stanley, S. M., 1981 The New Evolutionary Timetable: Fossils, Genes, and the Origin of Species Basic Books, Inc., Publishers, N.Y., p. 40 -------------------------------------------------------------------------------- Since the time of Darwin, paleontologists have found themselves confronted with evidence that conflicts with gradualism, yet the message of the fossil record has been ignored. This strange circumstance constitutes a remarkable chapter in the history of science, and one that gives students of the fossil record cause for concern. Stanley, S. M., 1981 The New Evolutionary Timetable: Fossils, Genes, and the Origin of Species Basic Books, Inc., Publishers, N.Y., p. 101 -------------------------------------------------------------------------------- The gaps in the fossil record are real, however. The absence of a record of any important branching is quite phenomenal. Species are usually static, or nearly so, for long periods, species seldom and genera never show evolution into new species or genera but replacement of one by another, and change is more or less abrupt. Wesson, R., 1991 Beyond Natural Selection MIT Press, Cambridge, MA, p. 45 -------------------------------------------------------------------------------- [T]he origin of no innovation of large evolutionary significance is known. Wesson, R., 1991 Beyond Natural Selection MIT Press, Cambridge, MA, p. 45 -------------------------------------------------------------------------------- [L]arge evolutionary innovations are not well understood. None has ever been observed, and we have no idea whether any may be in progress. There is no good fossil record of any. Wesson, R., 1991 Beyond Natural Selection MIT Press, Cambridge, MA, p. 206 -------------------------------------------------------------------------------- Taxa recognized as orders during the (Precambrian-Cambrian) transition chiefly appear without connection to an ancestral clade via a fossil intermediate. This situation is in fact true of most invertebrate orders during the remaining Phanerozoic as well. There are no chains of taxa leading gradually from an ancestral condition to the new ordinal body type. Orders thus appear as rather distinctive subdivisions of classes rather than as being segments in some sort of morphological continuum. Valentine, J.W., Awramik, S.M., Signor, P.W., and Sadler, P.M. (1991) "The Biological Explosion at the Precambrian-Cambrian Boundary" Evolutionary Biology, Vol. 25, Max K. Hecht, editor, Plenum Press, New York and London, p.284 -------------------------------------------------------------------------------- Valentine and Erwin review hypotheses as to the mode of origin of animal body plans for consistency with the fossil evidence. They conclude that both Darwinian gradualism and punctuated equilibrium are inadequate to account for the appearance of invertebrate body plans and their major modifications: "The models we consider are of three sorts: those that extrapolate processes of speciation to account for higher taxa via divergence, those that invoke selection among species, and those that emphasize that many higher taxa originated as novel lineages in their own right, not only as a consequence of species-level processes. It is in this latter class of model that we believe the record favors." (Valentine and Erwin, 1985, p. 71) If large populations have gradually evolved there should be unmistakable evidence in the fossil record, yet it is simply not found. "... many of the large populations should have been preserved, yet we simply do not find them. Small populations are called for, then, but there are difficulties here also. The populations must remain small (and undetected) and evolve steadily and consistently toward the body plan that comprises the basis of a new phylum (or class). This is asking a lot. Deleterious mutations would tend to accumulate in small populations to form genetic loads that selection might not be able to handle. Stable intermediate adaptive modes cannot be invoked as a regular feature, since we are then again faced with the problem of just where their remains are. We might imagine vast arrays of such small populations fanning continually and incessantly into adaptive space. Vast arrays should have produced at least some fossil remains also. Perhaps an even greater difficulty is the requirement that these arrays of lineages change along a rather straight and true course --- morphological side trips or detours of any frequency should lengthen the time of origin of higher taxa beyond what appears to be available. Why should an opportunistic, tinkering process set on such a course and hold it for so long successfully among so many lineages? We conclude that the extrapolation of microevolutionary rates to explain the origin of new body plans is possible, but does not accord with the primary evidence." (Valentine and Erwin, 1985, pp. 95, 96) The model of punctuated equilibrium or species selection attempts to account for the lack of evidence by relying primarily on the evolution of small isolated populations which would have a diminished chance of leaving a fossil record. This scenario has its difficulties, however, as Valentine and Erwin point out: "The required rapidity of the change implies either a few large steps or many and exceedingly rapid smaller ones. Large steps are tantamount to saltations and raise the problems of fitness barriers; small steps must be numerous and entail the problems discussed under microevolution. The periods of stasis raise the possibility that the lineage would enter the fossil record, and we reiterate that we can identify none of the postulated intermediate forms. Finally, the large numbers of species that must be generated so as to form a pool from which the successful lineage is selected are nowhere to be found. We conclude that the probability that species selection is a general solution to the origin of higher taxa is not great, and that neither of the contending theories of evolutionary change at the species level, phyletic gradualism or punctuated equilibrium, seem applicable to the origin of new body plans." (p. 96) Valentine, J., and Erwin, D. (1985) "Interpreting Great Developmental Experiments: The Fossil Record" Development as an Evolutionary Process Rudolf A. Raff and Elizabeth C. Raff, Editors Alan R. Liss, Inc., New York, pp. 71, 95, 96