Ergodicity in natural earthquake fault networks.

Numerical simulations have shown that certain driven nonlinear systems can be characterized by mean-field statistical properties often associated with ergodic dynamics [C. D. Ferguson, W. Klein, and J. B. Rundle, Phys. Rev. E 60, 1359 (1999); D. Egolf, Science 287, 101 (2000)]. These driven mean-field threshold systems feature long-range interactions and can be treated as equilibriumlike systems with statistically stationary dynamics over long time intervals. Recently the equilibrium property of ergodicity was identified in an earthquake fault system, a natural driven threshold system, by means of the Thirumalai-Mountain (TM) fluctuation metric developed in the study of diffusive systems [K. F. Tiampo, J. B. Rundle, W. Klein, J. S. Sá Martins, and C. D. Ferguson, Phys. Rev. Lett. 91, 238501 (2003)]. We analyze the seismicity of three naturally occurring earthquake fault networks from a variety of tectonic settings in an attempt to investigate the range of applicability of effective ergodicity, using the TM metric and other related statistics. Results suggest that, once variations in the catalog data resulting from technical and network issues are accounted for, all of these natural earthquake systems display stationary periods of metastable equilibrium and effective ergodicity that are disrupted by large events. We conclude that a constant rate of events is an important prerequisite for these periods of punctuated ergodicity and that, while the level of temporal variability in the spatial statistics is the controlling factor in the ergodic behavior of seismic networks, no single statistic is sufficient to ensure quantification of ergodicity. Ergodicity in this application not only requires that the system be stationary for these networks at the applicable spatial and temporal scales, but also implies that they are in a state of metastable equilibrium, one in which the ensemble averages can be substituted for temporal averages in studying their spatiotemporal evolution.

Thermodynamic behavior of a phase transition in a model for sympatric speciation.

We investigate the macroscopic effects of the ingredients that drive the origin of species through sympatric speciation. In our model, sympatric speciation is obtained as we tune up the strength of competition between individuals with different phenotypes. As a function of this control parameter, we can characterize, through the behavior of a macroscopic order parameter, a phase transition from a nonspeciation to a speciation state of the system. The behavior of the first derivative of the order parameter with respect to the control parameter is consistent with a phase transition and exhibits a sharp peak at the transition point. For different resources distribution, the transition point is shifted, an effect similar to pressure in a PVT system. The inverse of the parameter related to a sexual selection strength behaves like an external field in the system and, as thus, is also a control parameter. The macroscopic effects of the biological parameters used in our model are a reminiscent of the behavior of thermodynamic quantities in a phase transition of an equilibrium physical system.

Simple bit-string model for lineage branching.

We introduce a population dynamics model, where individual genomes are represented by bit strings. Selection is described by death probabilities which depend on these genomes, and new individuals continuously replace the ones that die, keeping the population constant. An offspring has the same genome as its (randomly chosen) parent, except for a small amount of (also random) mutations. Chance may thus generate a newborn with a genome that is better than that of its parent, and the newborn will have a smaller death probability. When this happens, this individual is a would-be founder of a new lineage. A new lineage is considered created if the number of its live descendants grows above a certain previously defined threshold. The time evolution of populations evolving under these rules is followed by computer simulations and the probability densities of lineage duration and size, among others, are computed. These densities show a scale-free behavior, in accordance with some conjectures in paleoevolution, and suggesting a simple mechanism as explanation for the ubiquity of these power laws.

Evolutionary advantage of diploidal over polyploidal sexual reproduction.

We modify the Penna model for biological aging, which is based on the mutation-accumulation theory, in order to verify if there would be any evolutionary advantage of triploid over diploid organisms. We show that this is not the case, and that diploidal sex is always better than that involving three individuals.

Precursory dynamics in threshold systems.

A precursory dynamics, motivated by the analysis of recent experiments on solid-on-solid friction, is introduced in a continuous cellular automaton that mimics the physics of earthquake source processes. The resulting system of equations for the interevent cycle can be decoupled and yields an analytical solution in the mean-field limit, exhibiting a smoothing effect of the dynamics on the stress field. Simulation results show the resulting departure from scaling at the large-event end of the frequency distribution, and support claims that the field leakage may parametrize the superposition of scaling and characteristic regimes observed in real earthquake faults.

Self-organization in leaky threshold systems: the influence of near-mean field dynamics and its implications for earthquakes, neurobiology, and forecasting.

Threshold systems are known to be some of the most important nonlinear self-organizing systems in nature, including networks of earthquake faults, neural networks, superconductors and semiconductors, and the World Wide Web, as well as political, social, and ecological systems. All of these systems have dynamics that are strongly correlated in space and time, and all typically display a multiplicity of spatial and temporal scales. Here we discuss the physics of self-organization in earthquake threshold systems at two distinct scales: (i) The "microscopic" laboratory scale, in which consideration of results from simulations leads to dynamical equations that can be used to derive the results obtained from sliding friction experiments, and (ii) the "macroscopic" earthquake fault-system scale, in which the physics of strongly correlated earthquake fault systems can be understood by using time-dependent state vectors defined in a Hilbert space of eigenstates, similar in many respects to the mathematics of quantum mechanics. In all of these systems, long-range interactions induce the existence of locally ergodic dynamics. The existence of dissipative effects leads to the appearance of a "leaky threshold" dynamics, equivalent to a new scaling field that controls the size of nucleation events relative to the size of background fluctuations. At the macroscopic earthquake fault-system scale, these ideas show considerable promise as a means of forecasting future earthquake activity.

Simulated ecology-driven sympatric speciation.

We introduce a multilocus genetically acquired phenotype, submitted to mutations and with selective value, in an age-structured model for biological aging. This phenotype describes a single-trait effect of the environment on an individual, and we study the resulting distribution of this trait among the population. In particular, our simulations show that the appearance of a double phenotypic attractor in the ecology induces the emergence of a stable polymorphism, as observed in the Galapagos finches. In the presence of this polymorphism, the simulations generate short-term speciation, when mating preferences are also allowed to suffer mutations and acquire selective value.

Simulated coevolution in a mutating ecology.

The bit-string Penna model is used to simulate the competition between an asexual parthenogenetic and a sexual population sharing the same environment. A newborn of either population can mutate and become a part of the other with some probability. In a stable environment the sexual population soon dies out. When an infestation by rapidly mutation genetically coupled parasites is introduced, however, sexual reproduction prevails, as predicted by the so-called Red Queen hypothesis for the evolution of sex.