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A Sourcebook for the Worldwide Discovery of a Creative Organic Universe
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VI. Earth Life Emergence: Development of Body, Brain, Selves and Societies

7. Dynamic Ecosystems

Stochastic Models in Ecology and Evolutionary Biology. www.pd.infn.it/~maritan/veniceworkshop/veniceworkshop. An April 5-7, 2018 conference at the Istituto Veneto di Scienze, Venice organized by the physics, mathematics and astronomy departments of the University of Padova, namely Samir Suweis, Marco Formentin, Amos Martial, and Paolo Dai Pra (search each). Our interest is the content, venue, sponsors, but also its summary next, which is a strong, clear statement to date of the global complexity revolution as it fills in and affirms an independent, generative source as it repeats in an exemplary way at each and every scale and instance. A constant self-organized criticality ithen springs from a duality of discrete component, and dynamic interactions as they evolve and emerge from universe to human.

Living systems are characterized by the emergence of recurrent dynamical patterns at all scales of magnitude. Self-organized behaviors are observed both in large communities of microscopic components - like neural oscillations and gene network activity - as well as on larger levels - as predator-prey equilibria to name a few. Such regularities are deemed to be universal in the sense they are due to common mechanisms, independent of the details of the system. This belief justifies investigation through quantitative models able to grasp key features while disregarding inessential complications. The attempt of modeling such complex systems leads naturally to consider large families of microscopic identical units. Complexity and self-organization then arise on a macroscopic scale from the dynamics of these minimal components that evolve coupled by interaction terms. (Summary)

Aerts, Diederik, et al. Quantum Structure in Competing Lizard Communities. Ecological Modelling. 281/38, 2014. As the extended quotes allude, Vrije Universiteit Brussel, Polytechnika Gdanska, and University of Leicester theorists broach a number of ways that quantum phenomena, as it now becomes reinterpreted and understood in macro classical terms, are in fact evidently, at work, as they must be, in all aspects of living systems such as animal behaviors.

Almost two decades of research on applications of the mathematical formalism of quantum theory as a modeling tool in domains different from the micro-world has given rise to many successful applications in situations related to human behavior and thought, more specifically in cognitive processes of decision-making and the ways concepts are combined into sentences. In this article, we extend this approach to animal behavior, showing that an analysis of an interactive situation involving a mating competition between certain lizard morphs allows one to identify a quantum theoretic structure. We work out an explicit quantum-mechanical representation in Hilbert space for the lizard situation and show that it faithfully models a set of experimental data collected on three throat-colored morphs of a specific lizard species. Furthermore, we investigate the Hilbert space modeling, and show that the states describing the lizard competitions contain entanglement for each one of the considered confrontations of lizards with different competing strategies, which renders it no longer possible to interpret these states of the competing lizards as compositions of states of the individual lizards. (Abstract)

Identification of quantum structure in the lizard dynamics can be seen as an example of the use of the mathematical formalism of quantum theory as a modeling instrument in domains different from the micro-world. This approach has led to interesting results in recent years and is now an active and emergent research field in itself. In cognitive science (concept theory and decision theory), in economics (finance and behavioral economics), and in computer science (semantic theories, information retrieval, and artificial intelligence), several situations have been identified where application of classical structures is problematic, whereas modeling based on quantum structures is successful. (39)

Our investigation links up with the new developments of ‘identification of quantum structure in domains different from the micro-world’, and extends to animal behavior the results obtained in the context of human cognition. Furthermore, it suggests that ecological systems are intrinsically contextual, and constitutes a powerful support for systematic applications of quantum-structural modeling in biology. (50)

Agrawal, Anurag. Community Genetics: New Insights into Community Ecology by Integrating Population Genetics. Ecology. 84/3, 2004. From a special issue on how a synthesis of these disparate approaches is bringing theoretical and practical advances. By this view, e.g., extended phenotypes and a community level heritability and selection become evident.

Community genetics is the study of the interaction between genes within a species and populations of other species in a community. (543)

Alados, C., et al. Self-organized Spatial Patterns of Vegetation in Alpine Grasslands. Ecological Modelling. 201/2, 2007. In the Central Pyrenees mountains , a case study example of and portal to universal nonlinear dynamics.

Allen, T. P. H. and Thomas Hoekstra. Toward a Unified Ecology. New York: Columbia University Press, 1992. If ecology is to become a theoretical science, it should be based on the pervasive fractal, stratified anatomy and physiology of diverse, complex ecosystems.

Allen, Timothy and Thomas Hoekstra. Toward a Unified Ecology. New York: Columbia University Press, 2015. This second edition of their 1993 classic by the University of Wisconsin botanist and a U. S. Forest Service environmentalist draws on 21st century advances to achieve a comprehensive theoretical and practical treatise. The chapters begin with Principles of Ecological Integration and proceed to Landscape, Ecosystem, Community, Organism, Population, Biome, Biosphere, Complexity narratives. The salient unifying theme and natural quality is still a fractal self-similarity from the smallest microbial to the largest biota scale.

The first edition of Toward a Unified Ecology was ahead of its time. For the second edition, the authors present a new synthesis of their core ideas on evaluating communities, organisms, populations, biomes, models, and management. The book now places greater emphasis on post-normal critiques, cognizant of ever-present observer values in the system. The problem it addresses is how to work holistically on complex things that cannot be defined, and this book continues to build an approach to the problem of scaling in ecosystems. Provoked by complexity theory, the authors add a whole new chapter on the central role of narrative in science and how models improve them. The book takes data and modeling seriously, with a sophisticated philosophy of science.

Anand, Madhur. Quantification of Biocomplexity. International Conference on Complex Systems. May 16-21, 2004. A systems biologist from Laurentian University makes the notable observation that healthy ecosystems are characterized by self-organizing processes which generate a power-law, fractal-like scaling. Disturbances can be measured by deviations from this state. The return to a viable ecosystem then requires a restoration of this dynamical, non-equilibrium condition. The abstract is available at www.necsi.org, ICCS 2004. Also check Professor Anand’s website at www.laurentian.ca/biology/MANAND/anandlab/main.html for more info and papers.

Atkinson, R., et al. Scale-Free Dynamics in the Movement Patterns of Jackals. OIKOS. 98/1, 2002. A typical contribution that finds invariant mathematical processes throughout a newly knowable natural realm.

Using conventional radio-tracking techniques employed by field ecologists, evidence for scale-free (fractal) behavior in the foraging trajectories of a species of African jackal is presented….The methods used in this study are completely general and can be applied to other radio-tracked species, thus beginning a systematic investigation of foraging strategies in mammals. (134)

Azovsky, A. I., et al. Fractal Properties of Spatial Distribution of Intertidal Benthic Communities. Marine Biology. 136/3, 2006. Diatom algae inherently take on the form of a nested, self-similar, hierarchical community.

In accordance with another hypothesis, a fractal spatial pattern is the result of community self-organization, which is then transformed into other structures (fixed patches or gradients) under the evident external (environmental) influences. If so, fractals may be a universal way of a biota’s self-organization and filling up the space. (589)

Ba, Rui, et al. Analysis of Multifractal and Organization/Order Structure in Suomi-NPP VIIRS Normalized Difference Vegetation Index Series of Wildfire Sites. Entropy. 22/4, 2020. Circa 2004, any perception, let alone proof, of endemic patterns by which to untangle nature were sparse at best. A worldwide decade and half later systems ecologists from China and Italy can describe, along with similar works, the actual presence of mathematic patternings in self-similar scalar array everywhere. One might ask and wonder again how does this deep animate order come to be, whatever agency put it there in the first place?

Bailey, Joseph, et al. Fractal Geometry is Heritable in Trees. Evolution. 58/9, 2004. More quantitative insights into a universally self-similar nature.

Here for the first time we show that the fractal architecture of a dominant plant on the landscape exhibits high broad-sense heritability and thus has a genetic basis. This result provides a crucial link between genes and fractal scaling theory, and places the study of landscape ecology with an evolutionary framework. (2100)

Bascompte, Jordi and Pedro Jordano. Mutualistic Networks. Princeton: Princeton University Press, 2014. Spanish Research Council theoretical ecologists provide the first book-length treatment for evolving nature’s cooperative propensity that graces all manner of flora and fauna from whelks to whales.

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