Speciation by Self-Organizing Barriers to Gene Flow in Simulated Populations with Localized Mating
Workshop Proceedings for the Genetic and Evolutionary Computation Conference (GECCO) 2006, , , 2006
Abstract: Speciation caused by intrinsically forming barriers to gene flow is demonstrated using simulated populations. Although theory predicts that underdominance would be quickly eliminated from randomly mating populations, herein it is shown that when mating interactions are localized, mild underdominance can persist for long periods, as interbreeding populations self-organize into patches of compatible types separated by viable hybrid zones. Under certain types of even mild epistasis, hybrid zones will coalesce to create intrinsic barriers to gene flow between subgroups, resulting in speciation. Since underdominance, epistasis, and spatially localized mating/dispersal have all been observed in natural populations, the proposed mechanism is feasible and parsimonious. This model of speciation does not require any pre-mating isolation mechanisms, such as geographic isolation or assortative mating interactions due to niche differentiation or sexual selection. However, the presence of these would enhance the effects and reduce the time to speciation. It is probable that in natural systems, many mechanisms are operating simultaneously to cause speciation.
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Bongard's work focuses on understanding the general nature of cognition, regardless of whether it is found in humans, animals or robots. This unique approach focuses on the role that morphology and evolution plays in cognition. Addressing these questions has taken him into the fields of biology, psychology, engineering and computer science.
Danforth is an applied mathematician interested in modeling a variety of physical, biological, and social phenomenon. He has applied principles of chaos theory to improve weather forecasts as a member of the Mathematics and Climate Research Network, and developed a real-time remote sensor of global happiness using messages from Twitter: the Hedonometer. Danforth co-runs the Computational Story Lab with Peter Dodds, and helps run UVM's reading group on complexity.
Laurent studies the interaction of structure and dynamics. His research involves network theory, statistical physics and nonlinear dynamics along with their applications in epidemiology, ecology, biology, and sociology. Recent projects include comparing complex networks of different nature, the coevolution of human behavior and infectious diseases, understanding the role of forest shape in determining stability of tropical forests, as well as the impact of echo chambers in political discussions.
Hines' work broadly focuses on finding ways to make electric energy more reliable, more affordable, with less environmental impact. Particular topics of interest include understanding the mechanisms by which small problems in the power grid become large blackouts, identifying and mitigating the stresses caused by large amounts of electric vehicle charging, and quantifying the impact of high penetrations of wind/solar on electricity systems.
Bagrow's interests include: Complex Networks (community detection, social modeling and human dynamics, statistical phenomena, graph similarity and isomorphism), Statistical Physics (non-equilibrium methods, phase transitions, percolation, interacting particle systems, spin glasses), and Optimization(glassy techniques such as simulated/quantum annealing, (non-gradient) minimization of noisy objective functions).