title: Evolutionary dynamics and highly optimized tolerance.
abstract: We develop a numerical model of a lattice community based on Highly Optimized Tolerance (HOT), which relates the evolution of complexity to robustness tradeoffs in an uncertain environment. With the model, we explore scenarios for evolution and extinction which are abstractions of processes which are commonly discussed in biological and ecological case studies. These include the effects of different habitats on the phenotypic traits of the organisms, the effects of different mutation rates on adaptation, fitness, and diversity, and competition between generalists and specialists. The model exhibits a wide variety of microevolutionary and macroevolutionary phenomena which can arise in organisms which are subject to random mutation, and selection based on fitness evaluated in a specific environment. Generalists arise in uniform habitats, where different disturbances occur with equal frequency, while specialists arise when the relative frequency of different disturbances is skewed. Fast mutators are seen to play a primary role in adaptation, while slow mutators preserve well-adapted configurations. When uniform and skewed habitats are coupled through migration of the organisms, we observe a primitive form of punctuated equilibrium. Rare events in the skewed habitat lead to extinction of the specialists, whereupon generalists invade from the uniform habitat, adapt to their new surroundings, ultimately leading their progeny to become vulnerable to extinction in a subsequent rare disturbance.
authors.affiliation: Department of Physics, University of California, Santa Barbara, CA 93106, USA.
authors.forename: Tong
authors.initials: T
authors.lastname: Zhou
authors.forename: J M
authors.initials: JM
authors.lastname: Carlson
authors.forename: John
authors.initials: J
authors.lastname: Doyle
mesh_terms: D000222:Adaptation, Physiological; D000818:Animals; D005075:Biological Evolution; D004777:Environment; D014644:Genetic Variation; D008954:Models, Biological; D009154:Mutation; D010641:Phenotype; D011157:Population Dynamics; D013534:Survival