VI. Earth Life Emergence: Development of Body, Brain, Selves and Societies
1. Geosphere, Hydrosphere, Atmosphere
Klinger, Lee. Gaia and Complexity. Schneider, Stephen, et al, eds. Scientists Debate Gaia. Cambridge: MIT Press, 2004. Noted more in A Living Planet, the paper also discusses self-organizing, fractal landscapes.
L’Heureux, Ivan. Self-Organized Rhythmic Patterns in Geochemical Systems. Philosophical Transactions of the Royal Society A. 371/20120356, 2013. In this issue on Pattern Formation in the Geosciences (Goehring above), a University of Ottawa “condensed matter physicist” details how rock formations, such as “periodic precipitation of pyrite bands,” express the same dynamical topologies and behaviors as everywhere else in nature. In regard, as an increasing number of similar reports confirm, as strongly implied, it can be realized that these recurrent phenomena spring from universal, “intrinsic” material spontaneities.
Chemical oscillating patterns are ubiquitous in geochemical systems. Although many such patterns result from systematic variations in the external environmental conditions, it is recognized that some patterns are due to intrinsic self-organized processes in a non-equilibrium nonlinear system with positive feedback. In rocks and minerals, periodic precipitation (Liesegang bands) and oscillatory zoning constitute good examples of patterns that can be explained using concepts from nonlinear dynamics. (Abstract)
Lofta, Nastaran, et al. Centrality in Earthquake Multiplex Networks. Chaos. 28/063113, 2018. University of Zanjan, Iran and University of Sao Paulo physicists achieve a detailed global complex systems analysis of these spurious geological calamities. To reflect, out of this arduous planetary evolution and human history a collective, cumulative knowledge at last arises which then might be fed back to give better warnings, and maybe mitigate. What could its cosmic identity and purpose be?
Seismic time series has been mapped as a complex network, where a geographical region is divided into square cells that represent the nodes and connections are defined according to the sequence of earthquakes. In this paper, we map a seismic time series to a multiplex network, and characterize the evolution of the network structure in terms of the eigenvector centrality measure. We generalize previous works that considered the single layer representation of earthquake networks. Our results suggest that the multiplex representation captures better earthquake activity than methods based on single layer networks. We also verify that the regions with highest seismological activities in Iran and California can be identified from the network centrality analysis. The temporal modeling of seismic data provided here may open new possibilities for a better comprehension of the physics of earthquakes. (Abstract)
Ma, Hongbo, et al. Universal Relation with Regime Transition for Sediment Transport in Fine-Grained Rivers. Proceedings of the National Academy of Sciences. 117/171, 2020. A thirteen member team of geoscientists from across China and the USA, with a global cast of names, uncover and quantify a common mathematical basis which underlie and guide such sediment flows and depositions across the world’s waterways. We also cite as more current proof that a natural genesis is graced by an independent generative source code across land, sea, air and space.
Fine-grained sediment transport systems (grain size under 2,000 μm) are ubiquitous over time and space on Earth and extraplanetary surfaces, and include rivers, deltaic coastal settings, and submarine, subglacial systems. Forecasting the evolution of Earth’s surface requires a predictive algorithm for sediment transport. Herein we provide a universal relation for sediment transport in fine-grained rivers. Surprisingly, it is shown that sediment flux differs by up to 2 orders of magnitude as grain size changes only slightly near the boundary between very fine sand and fine sand. The universal applicability of the sediment transport formulation enables quantitative understanding of the sedimentology and morphology of fine-grained rivers. (Significance)
Mann, Daniel. On Patterned Ground. Science. 299/354, 2003. A report on how intricate, ever changing landscape patterns are being understood through complex systems theory.
The (geomorphology) field is experiencing a paradigm shift from a reductionist approach towards concepts such as universality and self-organization. (355)
Martin, Miguel Angel, et al. Fractal Modeling and Scaling in Natural Systems. Ecological Complexity. 6/3, 2009. An introduction to a special section as an update to the wealth of findings across nature, noted herein, from snowy surfaces and rainfall amounts to Amazonian meteorology and fishery biomass, that evidence the same scale invariant geometries and dynamics. A number of these papers about soil complexities are drawn from a series of PEDOFRACT international seminars, see, e.g., J. Ibanez, et al.
The development and application of fractal models has become an important part of the ongoing quest to quantify, analyze, and manage the complexity of natural systems. Such models can help to reveal underlying relationships between structure and function, provide a succinct representation of scaling properties, and improve parameterization of natural variability and heterogeneity. (219)
Martin, Miguel Angel, et al, eds. Scaling, Fractals and Diversity in Soils and Ecohydrology. Ecological Modelling. 182/3-4, 2005. An introduction to a dedicated issue on self-similar, invariant spatial and temporal geometries that characterize hydrated earth. An example studied is the Aegean islands.
Scaling relations in ecosystems can be interpreted as the result of self-organization. (220)
Matthews, Robert. And Now the Forecast: Cloudy with a Chance of Fractals. New Scientist. November 7, 2009. Whereby the 1920s climate models of British mathematician Lewis Fry Richardson that were graced by cascades of similar weather patterns are being rediscovered and confirmed by the latest satellite data. Indeed, multifractal power laws abound in repetitive scales from local rainfalls to planetwide currents. A prime technical reference cited in this regard is Shaun Lovejoy, et al. Atmospheric Complexity or Scale by Scale Simplicity? in Geophysical Research Letters (36/L36801, 2009), see also Lovejoy above.
Meng, Fanzhen, et al. Power Law Relations in Earthquakes from Microscopic to Macroscopic Scales. Nature Scientific Reports. 9/10705, 2019. University of Hong Kong, and Chinese Academy of Sciences, Wuhan systems geologists provide a latest technical analysis of Earth shaking catastrophic events by way of self-similar complexity theories. As they become more common in China, Iran and the USA, these insights can aid better warning systems.
Understanding the physics of earthquakes is a crucial step towards improving their prediction accuracy. Scale invariance or fractal features are often reported in earthquakes, such as the size distribution, the spatial distribution of hypocenters, and the frequency of aftershocks. Here we assess whether other key parameters and quantities involved in earthquakes also conform to the power law. By analyzing a large amount of data collected from the laboratory experiments and field monitoring of earthquakes, we find that the crack density on the two sides of small scale fracture or large scale fault decreases with increasing distance following the power law, and the crack number-crack length distribution is also scale invariant like natural faults. (Abstract excerpt)
Murray, Brad and Mark Fonstad. Preface: Complexity (and Simplicity) in Landscapes. Geomorphology. 91/3-4, 2007. A topical issue which covers in part Power-Law Scaling, Emergent and Self Organized Behavior, and Catastrophes, Biology and Intentionality. How might it then collectively dawn upon us that a grand new nonlinear genesis universe is being revealed by the very soil of the earth?
The self-similarity or self-affinity of a landscape (including the extension of multifractality), detected and quantified by power-law scalings, suggest that the same dynamics – the same cause in this sense – produce similar effects across a wide range of scales. (174)
Neugebauer, Horst and Clemens Simmer, ed. Dynamics of Multiscale Earth Systems. Berlin: Springer, 2003. On the hierarchical repetition of geological forms and processes.
Nkono, Collin, et al. Fractal Analysis of Lineaments in Equatorial Africa: Insights on Lithospheric Structure. Open Journal of Geology. 3/157, 2013. A team of French and Belgian geoscientists, including Annick Lesne, describe an aerial photography technique as a novel perspective for studying geological strata in remote, ravaged regions such as Cameroon and the Central African Republic. By virtue of aviation and satellite imaging, along with computer analysis, spatial desert and plateau landscapes, and temporal histories to the Paleozoic, can be constructed that are not possible otherwise. And one cannot help but perceive a collaborative humanity who returns to study the fraught regions from whence homo sapiens came. Might such a worldwise progeny also be able to attain a palliative knowledge, akin to African organic wisdom, that could save and heal these war-torn lands. Indeed, as I write in April 2014, Nigeria has just sent a plea to the whole world to help find a way to release their peoples from its consuming ignorance and violence. Indeed, the same abilities can now be applied to study extraterrestrial planets.
In this paper, the complexity in the spatial distribution of the lineaments was investigated from on remote sensing topographic (SRTM DEM) and multispectral (Landsat) data. Lineaments in equatorial Africa were chosen to apply the fractal analysis methodology. The good correlations of the obtained data with some geophysical data from the same area allow that the complexity in the spatial distribution of the lineaments can give qualitative information on the interior of the earth (or on other planets). This method can provide a bridge between classical geology and geophysics, and particularly powerful for studying large and inaccessible regions. (Abstract)