scholarly journals Cluster size distributions: signatures of self–organization in spatial ecologies

2002 ◽  
Vol 357 (1421) ◽  
pp. 657-666 ◽  
Author(s):  
Mercedes Pascual ◽  
Manojit Roy ◽  
Frédéric Guichard ◽  
Glenn Flierl
Keyword(s):  
Power Law ◽  
Cluster Size ◽  
Environmental Variability ◽  
Size Distributions ◽  
Ecological Interactions ◽  
Positive Slope ◽  
Predator Prey ◽  
Self Organized ◽  
Self Organized Criticality ◽  
Recovery Dynamics

Three different lattice–based models for antagonistic ecological interactions, both nonlinear and stochastic, exhibit similar power–law scalings in the geometry of clusters. Specifically, cluster size distributions and perimeter–area curves follow power–law scalings. In the coexistence regime, these patterns are robust: their exponents, and therefore the associated Korcak exponent characterizing patchiness, depend only weakly on the parameters of the systems. These distributions, in particular the values of their exponents, are close to those reported in the literature for systems associated with self–organized criticality (SOC) such as forest–fire models; however, the typical assumptions of SOC need not apply. Our results demonstrate that power–law scalings in cluster size distributions are not restricted to systems for antagonistic interactions in which a clear separation of time–scales holds. The patterns are characteristic of processes of growth and inhibition in space, such as those in predator–prey and disturbance–recovery dynamics. Inversions of these patterns, that is, scalings with a positive slope as described for plankton distributions, would therefore require spatial forcing by environmental variability.

Self-Similar Criticality

Fractals ◽  
2003 ◽  
Vol 11 (03) ◽  
pp. 221-231 ◽  
Author(s):  
Sarah F. Tebbens ◽  
Stephen M. Burroughs
Keyword(s):  
Power Law ◽  
Similar Distribution ◽  
Scaling Exponent ◽  
Cumulative Frequency ◽  
Size Distributions ◽  
Scaling Exponents ◽  
Natural Systems ◽  
Self Organized ◽  
Self Organized Criticality ◽  
Self Similar

Cumulative frequency-size distributions associated with many natural phenomena follow a power law. Self-organized criticality (SOC) models have been used to model characteristics associated with these natural systems. As originally proposed, SOC models generate event frequency-size distributions that follow a power law with a single scaling exponent. Natural systems often exhibit power law frequency-size distributions with a range of scaling exponents. We modify the forest fire SOC model to produce a range of scaling exponents. In our model, uniform energy (material) input produces events initiated on a self-similar distribution of critical grid cells. An event occurs when material is added to a critical cell, causing that material and all material in occupied non-diagonal adjacent cells to leave the grid. The scaling exponent of the resulting cumulative frequency-size distribution depends on the fractal dimension of the critical cells. Since events occur on a self-similar distribution of critical cells, we call this model Self-Similar Criticality (SSC). The SSC model may provide a link between fractal geometry in nature and observed power law frequency-size distributions for many natural systems.

scholarly journals Observational evidence in favor of scale-free evolution of sunspot groups

2018 ◽  
Vol 618 ◽  
pp. A183
Author(s):  
A. Shapoval ◽  
J.-L. Le Mouël ◽  
M. Shnirman ◽  
V. Courtillot
Keyword(s):  
Weibull Distribution ◽  
Power Law ◽  
Large Range ◽  
Scale Free ◽  
Self Organized ◽  
Self Organized Criticality ◽  
Spatio Temporal ◽  
Computational Procedures ◽  
Definition Of ◽  
Sunspot Groups

Context. The hypothesis stating that the distribution of sunspot groups versus their size (φ) follows a power law in the domain of small groups was recently highlighted but rejected in favor of a Weibull distribution. Aims. In this paper we reconsider this question, and are led to the opposite conclusion. Methods. We have suggested a new definition of group size, namely the spatio-temporal “volume” (V) obtained as the sum of the observed daily areas instead of a single area associated with each group. Results. With this new definition of “size”, the width of the power-law part of the distribution φ ∼ 1/Vβ increases from 1.5 to 2.5 orders of magnitude. The exponent β is close to 1. The width of the power-law part and its exponent are stable with respect to the different catalogs and computational procedures used to reduce errors in the data. The observed distribution is not fit adequately by a Weibull distribution. Conclusions. The existence of a wide 1/V part of the distribution φ suggests that self-organized criticality underlies the generation and evolution of sunspot groups and that the mechanism responsible for it is scale-free over a large range of sizes.

Self-Organized Criticality and Dynamic Instability of Microtubule Growth

1995 ◽  
Vol 50 (9-10) ◽  
pp. 739-740 ◽  
Author(s):  
Peter Babinec ◽  
Melánia Babincová
Keyword(s):  
Power Law ◽  
Dynamic Instability ◽  
Relative Number ◽  
Self Organized ◽  
Self Organized Criticality ◽  
Microtubule Growth

Abstract We have shown that the distribution of lengths of site nucleated microtubules obey an algebraic power law relationship D(s) = As-τ, where D(s) is relative number of microtubules with length 5, A and τ are constants. This relationship indicates the possibility of a self-organized criticality in the dynamic instability of microtubule growth

Power-Law Phenomena in Adhesive De-Bonding

1996 ◽  
Vol 458 ◽  
Author(s):  
G. Kendall ◽  
P. J. Cote ◽  
D. Crayon ◽  
F. J. Bonetto
Keyword(s):  
Power Law ◽  
Characteristic Length ◽  
Power Laws ◽  
Structural Features ◽  
Fractal Nature ◽  
Pressure Sensitive Adhesive ◽  
Self Organized ◽  
Pressure Sensitive ◽  
Self Organized Criticality ◽  
Glass Interface

ABSTRACTAcoustic emission (AE) events were recorded during the peeling of pressure-sensitive adhesive (PSA) tape from a silicate glass surface. The distributions of AE event durations and energies are found to have the form of power laws. Power-law dependencies (hyperbolic distributions) are recognized as a consequence of self-organized criticality (SOC), resulting from the absence of any characteristic length or time scales. In these studies, standard optical microscopy was used to characterize the fractal nature of the PSA-glass interface. The present results suggest that it is the inherent static structural features found at the fractal PSA-glass interface which produce the observed hyperbolic distributions in AE events, rather than a true SOC process.

SELF-ORGANIZED CRITICALITY AND THE BARKHAUSEN EFFECT IN AMORPHOUS AND POLYCRYSTALLINE METALS

1993 ◽  
Vol 07 (01n03) ◽  
pp. 934-937 ◽  
Author(s):  
PAUL J. COTE ◽  
LAWRENCE V. MEISEL
Keyword(s):  
Power Law ◽  
Barkhausen Effect ◽  
Self Organized ◽  
Polycrystalline Metals ◽  
Power Spectral ◽  
Power Spectral Densities ◽  
Spatially Extended ◽  
Self Organized Criticality ◽  
Dissipative Dynamical Systems ◽  
Pulse Energies

An investigation of the possibility that the Barkhausen effect in amorphous and polycrystalline ferromagnets is an example of self-organized criticality is described. Since the theory of self-organized criticality was introduced by Bak, Tang, and Weisenfeld to explain the behavior of spatially extended, dissipative, dynamical systems the Barkhausen effect is a natural candidate for such a description. The data are consistent with self-organized critical behavior: the power spectral densities depend on frequency f as 1/fa and the distribution of pulse energies are well described by a power law analogous to the Gutenberg-Richter law for earthquakes. Alternative explanations for power law dependences are also presented.

SELF-ORGANIZED CRITICALITY MODEL FOR EARTHQUAKES: QUIESCENCE, FORESHOCKS AND AFTERSHOCKS

1999 ◽  
Vol 09 (12) ◽  
pp. 2249-2255 ◽  
Author(s):  
S. HAINZL ◽  
G. ZÖLLER ◽  
J. KURTHS
Keyword(s):  
Power Law ◽  
B Value ◽  
Power Law Distribution ◽  
Aftershock Activity ◽  
Omori Law ◽  
Self Organized ◽  
Spatiotemporal Clustering ◽  
Self Organized Criticality ◽  
Clustering Of Events ◽  
Foreshock Activity

We introduce a crust relaxation process in a continuous cellular automaton version of the Burridge–Knopoff model. Analogously to the original model, our model displays a robust power law distribution of event sizes (Gutenberg–Richter law). The principal new result obtained with our model is the spatiotemporal clustering of events exhibiting several characteristics of earthquakes in nature. Large events are accompanied by a precursory quiescence and by localized fore- and aftershocks. The increase of foreshock activity as well as the decrease of aftershock activity follows a power law (Omori law) with similar exponents p and q. All empirically observed power law exponents, the Richter B-value, p and q and their variability can be reproduced simultaneously by our model, which depends mainly on the level of conservation and the relaxation time.

scholarly journals Entropy production and self-organized (sub)criticality in earthquake dynamics

2010 ◽  
Vol 368 (1910) ◽  
pp. 131-144 ◽  
Author(s):  
Ian G. Main ◽  
Mark Naylor
Keyword(s):  
Numerical Model ◽  
Entropy Production ◽  
Power Law ◽  
Subcritical State ◽  
Earthquake Dynamics ◽  
Broad Bandwidth ◽  
Rupture Area ◽  
Self Organized ◽  
Self Organized Criticality ◽  
Definition Of

We derive an analytical expression for entropy production in earthquake populations based on Dewar’s formulation, including flux (tectonic forcing) and source (earthquake population) terms, and apply it to the Olami–Feder–Christensen numerical model for earthquake dynamics. Assuming the commonly observed power-law rheology between driving stress and remote strain rate, we test the hypothesis that maximum entropy production (MEP) is a thermodynamic driver for self-organized ‘criticality’ (SOC) in the model. MEP occurs when the global elastic strain is near-critical, with small relative fluctuations in macroscopic strain energy expressed by a low seismic efficiency, and broad-bandwidth power-law scaling of frequency and rupture area. These phenomena, all as observed in natural earthquake populations, are hallmarks of the broad conceptual definition of SOC (which has, to date, often included self-organizing systems in a near but strictly subcritical state). In the MEP state, the strain field retains some memory of past events, expressed as coherent ‘domains’, implying a degree of predictability, albeit strongly limited in practice by the proximity to criticality and our inability to map the natural stress field at an equivalent resolution to the numerical model.

scholarly journals SIMULATION OF MAJORITY RULE DISTURBED BY POWER-LAW NOISE ON DIRECTED AND UNDIRECTED BARABÁSI–ALBERT NETWORKS

2008 ◽  
Vol 19 (07) ◽  
pp. 1063-1067 ◽  
Author(s):  
F. W. S. LIMA
Keyword(s):  
Power Law ◽  
Majority Rule ◽  
Noise Spectrum ◽  
Square Lattice ◽  
Complex Environment ◽  
Time Step ◽  
Disorder Phase Transition ◽  
Self Organized ◽  
Self Organized Criticality ◽  
Power Law Noise

On directed and undirected Barabási–Albert networks the Ising model with spin S = 1/2 in the presence of a kind of noise is now studied through Monte Carlo simulations. The noise spectrum P(n) follows a power law, where P(n) is the probability of flipping randomly select n spins at each time step. The noise spectrum P(n) is introduced to mimic the self-organized criticality as a model influence of a complex environment. In this model, different from the square lattice, the order-disorder phase transition of the order parameter is not observed. For directed Barabási–Albert networks the magnetisation tends to zero exponentially and undirected Barabási–Albert networks remain constant.

Fractality and Self-Organized Criticality of Wars

Fractals ◽  
1998 ◽  
Vol 06 (04) ◽  
pp. 351-357 ◽  
Author(s):  
D. C. Roberts ◽  
D. L. Turcotte
Keyword(s):  
Forest Fire ◽  
Power Law ◽  
Forest Fires ◽  
Size Dependence ◽  
Fire Model ◽  
Self Organized ◽  
Battle Deaths ◽  
Forest Fire Model ◽  
Alternative Measures ◽  
Self Organized Criticality

This paper considers the frequency-size statistics of wars. Using several alternative measures of the intensity of a war in terms of battle deaths, we find a fractal (power-law) dependence of number on intensity. We show that the frequency-size dependence of forest fires is essentially identical to that of wars. The forest-fire model provides a basis for understanding the distribution of forest firest in terms of self-organized criticality. We extend the analogy to wars in terms of the initial ignition (outbreak of war) and its spread to a group of metastable countries.

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