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

6. Dynamic Fractal Network Ecosystems

Gautestad, Arlid and Ivar Mysterud. Intrinsic Scaling Complexity in Animal Dispersion and Abundance. American Naturalist. 165/1, 2005. Progress toward a generalized theoretical framework for populations kinetics and spatial dynamics based on statistical mechanics and complex systems.

We describe, simulate, and discuss three testable aspects of a model for multiscaled habitat use at the individual level: (1) scale-free distribution of movement steps under influence of self-reinforcing site fidelity, (2) fractal spatial dispersion of intra-home range relocations, and (3) nonasymptotic expansion of observed intra-home range patch use with increasing set of relocations. (44)

Getzin, Stephan, et al. Discovery of Fairy Circles in Australia Supports Self-Organization Theory. Proceedings of the National Academy of Sciences. Early Edition, March, 2016. An eleven person team from Germany, Israel, and Australia including Ehud Meron quantify how these curious flora patterns are an exemplary manifestation of innate physical topologies and dynamics.

Pattern-formation theory predicts that vegetation gap patterns, such as the fairy circles of Namibia, emerge through the action of pattern-forming biomass–water feedbacks and that such patterns should be found elsewhere in water-limited systems around the world. We report here the exciting discovery of fairy-circle patterns in the remote outback of Australia. Using fieldwork, remote sensing, spatial pattern analysis, mathematical modeling, and pattern-formation theory we show that the Australian gap patterns share with their Namibian counterparts the same characteristics but are driven by a different biomass–water feedback. These observations are in line with a central universality principle of pattern-formation theory and support the applicability of this theory to wider contexts of spatial self-organization in ecology. (Significance)

Gilarranz, Luis, et al. Effects of Network Modularity on the Spread of Perturbation Impact in Experimental Metapopulations. Science. 357/199, 2017. Spanish National Research Group CSIC, McGill University, and University of Seville integrative ecologists including Jordi Bascompte argue for a common propensity for creatures to form distinctly viable community subassemblies in an environment. See also The Importance of Being Modular by Marta Sales-Pardo in the same issue.

Networks with a modular structure are expected to have a lower risk of global failure. However, this theoretical result has remained untested until now. We used an experimental microarthropod metapopulation to test the effect of modularity on the response to perturbation. We perturbed one local population and measured the spread of the impact of this perturbation, both within and between modules. Our results show the buffering capacity of modular networks. To assess the generality of our findings, we then analyzed a dynamical model of our system. We show that in the absence of perturbations, modularity is negatively correlated with metapopulation size. However, even when a small local perturbation occurs, this negative effect is offset by a buffering effect that protects the majority of the nodes from the perturbation. (Abstract)

In the 1970s, ecologists began to speculate that modular systems—which are organized into blocks or modules—can better contain perturbations and are therefore more resilient against external damage. This simple concept can be applied to any networked system, be it an ecosystem, cellular metabolism, traffic flows, human disease contagion, a power grid, or an economy. However, experimental evidence has been lacking. On page 199 of this issue, Gilarranz et al. provide empirical evidence showing that modular networked systems do indeed have an advantage over nonmodular systems when faced with external perturbations. (Sales-Pardo)

Goyal, Akshit, et al.. Closed Ecosystems Extract Energy through Self-Organized Nutrient Cycles. PNAS. 120/52, 2023.. 120/52, 2023. Into 2023, MIT, CalTech, Clark University and University of Chicago ecotheorists find still more way that nature’s intricate flora and fauna are formed and sustained as universal dynamic complex environs.

Our planet is a self-sustaining ecosystem powered by solar energy, but roughly closed to matter. Many ecosystems on Earth recycle nutrients by self-organizing stable cycles. However, existing ecological models do not express these features as observed in such global and biotic regimes. Here, we advance a hypothesis that explains their presence by a thermodynamic feedback loop that enables diverse metabolic communities to stabilize nutrient cycles. Our results highlight that self-organization promotes the efficiency and stability of complex ecosystems at extracting energy from the environment. (Abstract)

Green, David and Suzanne Sadedin. Interactions Matter – Complexity in Landscapes and Ecosystems. Ecological Complexity. 2/2, 2005. From a new journal, a survey of this “new paradigm for ecology” which finds ecosystems to exemplify nonlinear, self-organizing, critically poised, nested networks.

Green, David, et al. Complexity in Landscape Ecology. Berlin: Springer, 2006. Research ecologists provide a good primer on how natural environments are graced by and thoroughly express the principles of dynamical systems of self-organization, fractal scale-invariance, modularity, and cellular automata. A proper grasp of this endemic viability will then contribute to a global biosphere sustainability.

Greenbaum, Gili and Nina Fefferman. Application of Networks Methods for Understanding Evolutionary dynamics in Discrete Habitats. Molecular Ecology. 26/11, 2017. Ben-Gurion University of the Negev and University of Tennessee bioecologists provide another tutorial entry to an effective application of interactive network phenomena to ecosystem populations. Once again, the invitation is that these common connective aspects, although invisible, are in fact a major formative property. See also The Multilayer Nature of Ecological Networks by Shai Pilosof, et al in Nature Ecology & Evolution (1/0101, 2017), along with Complex Networks in Ecology by Gili Greenbaum, et al in Israel Journal of Ecology & Evolution (61/2, 2015).

In populations occupying discrete habitat patches, gene flow between habitat patches may form an intricate population structure. In such structures, the evolutionary dynamics resulting from interaction of gene-flow patterns with other evolutionary forces may be exceedingly complex. In the last decades, network theory – a branch of discrete mathematics concerned with complex interactions between discrete elements – has been applied to address several problems in population genetics by modelling gene flow between habitat patches using networks. Here, we present the idea and concepts of modelling complex gene flows in discrete habitats using networks. Our goal is to raise awareness to existing network theory applications in molecular ecology studies, as well as to outline the current and potential contribution of network methods to the understanding of evolutionary dynamics in discrete habitats. (Abstract)

Griffen, Blaine and John Drake. Scaling Rules for the Final Decline to Extinction. Proceedings of the Royal Society B. 276/1361, 2009. From the University of Georgia Odum School of Ecology, a report that the same geometries, as if due to an original, complementary genetic code, seem to occur at each and every phase of life and death.

The consistency of certain spatial and temporal dynamics among highly different nonlinear ecological systems is astounding. Such scaling rules have been found to characterize individual behaviour; the use of space by organisms; life-history patterns of individuals; population growth, regulation and abundance; community stability; and, by integrating across species ensembles, even patterns of biodiversity across regional landscapes. (1361)

Guimaraes, Paulo. The Structure of Ecological Networks across Levels of Organization. Annual Review of Ecology, Evolution and Systematics. 51/433, 2020. As a Universidade de São Paulo researcher provides a latest exposition of how nature’s interactive networks, as a heretofore overlooked feature, suffuse and serve to join, connect, inform and sustain living systems. As we have noted, here is another way that Darwin’s famous tangled bank can yet gain a consistent comprehension.

Interactions connect the units of ecological systems, by which to form networks. Individual-based networks characterize variation in niches within populations as they merge with each other to compose species-based networks and food webs in ecological communities. At spatiotemporal scales, networks portray the structure of ecological interactions across landscapes and over macroevolutionary time, which I review across multiple levels. By such studies, regularities in network structure are seen to emerge due to the fundamental architectural patterns shared by complex networks. (Abstract excerpt)

Hagstrom, George and Simon Levin. Marine Ecosystems as Complex Adaptive Systems: Emergent Patterns, Critical Transitions, and Public Goods. Ecosystems. Online February, 2017. Princeton University, Ecology and Evolutionary Biology professors write a 20th Anniversary Paper for this journal which attests to how much these nonlinear dynamics act to organize the breadth and depth of environments and their creaturely inhabitants. We cite its Abstract and the Ecosystems vision.

Complex adaptive systems provide a unified framework for explaining ecosystem phenomena. In the past 20 years, complex adaptive systems have been sharpened from an abstract concept into a series of tools that can be used to solve concrete problems. These advances have been led by the development of new techniques for coupling ecological and evolutionary dynamics, for integrating dynamics across multiple scales of organization, and for using data to infer the complex interactions among different components of ecological systems. Focusing on the development and usage of these new methods, we discuss how they have led to an improved understanding of three universal features of complex adaptive systems, emergent patterns; tipping points and critical phenomena; and cooperative behavior. Many of these are currently undergoing dramatic changes due to anthropogenic perturbations, and we take the opportunity to discuss how complex adaptive systems can be used to improve the management of public goods and to better preserve critical ecosystem services. (Abstract)

The study and management of ecosystems represents the most dynamic field of contemporary ecology. Ecosystem research bridges fundamental ecology, environmental ecology and environmental problem-solving. The scope of ecosystem science extends from bounded systems such as watersheds to spatially complex landscapes, to the Earth itself, and crosses temporal scales from seconds to millennia. Ecosystem science has strong links to other disciplines including landscape ecology, global ecology, biogeochemistry, aquatic ecology, soil science, hydrology, ecological economics and conservation biology. Studies of ecosystems employ diverse approaches, including theory and modeling, long-term investigations, comparative research and large experiments. (Ecosystems journal)

Hammond, Sean and Karl Niklas. Modeling Forest Self-assembly Dynamics Using Allometric and Physical First Principles. Science. 61/663, 2011. Charles Darwin’s apt phrase “tangled bank” is often used to convey nature’s seemingly chaotic flora. Some century and a half later, Cornell University botanists now describe a computational method that reveals a heretofore elusive, endemic regularity springing from an implicate mathematical source. Galileo Galilei would say tell me about it, for we seem at the cusp of realizing a profoundly new nature with such an algorithmic, read genetic, testament. The cover image for the issue depicts a forest as if rising from an instructive program.

Computer models are used by ecologists for studying a broad range of research questions, from long-term forest dynamics to the functional traits that theoretically give one species an advantage over others. Despite their increasing popularity, these models have been criticized for simulating complex biological phenomena, involving numerous biotic and abiotic variables, using seeming overly simplistic computational approaches. In this article, we review the usefulness and limitations of spatially explicit individual-based models for forested ecosystems by focusing on the attributes of a recent model, called SERA (spatially explicit reiterative algorithm), that employs seven allometric formulas and a few physical principles. Despite its simplicity, SERA successfully predicts forest self-assembly and dynamics. (Abstract, 663)

Harte, John and Erica Newman. Maximum Information Entropy: A Foundation for Ecological Theory. Trends in Ecology and Evolution. 29/7, 2014. UC Berkeley environmentalists finesse thermodynamic effects by way of probability distributions so as to achieve a better, more optimum, analysis of dynamic ecosystems. A later paper with Andrew Rominger is Metabolic Partitioning Across Individuals in Ecological Communities in Global Ecology and Biogeography (Online July 2017).

The maximum information entropy (MaxEnt) principle is a successful method of statistical inference that has recently been applied to ecology. Here, we show how MaxEnt can accurately predict patterns such as species–area relationships (SARs) and abundance distributions in macroecology and be a foundation for ecological theory. We discuss the conceptual foundation of the principle, why it often produces accurate predictions of probability distributions in science despite not incorporating explicit mechanisms, and how mismatches between predictions and data can shed light on driving mechanisms in ecology. We also review possible future extensions of the maximum entropy theory of ecology (METE), a potentially important foundation for future developments in ecological theory. (Abstract)

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