title: Simple bit-string model for lineage branching.
abstract: 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.
authors.affiliation: Laboratoire de Physique et Mécanique des Milieux Hétérogènes, Ecole Supérieure de Physique et de Chimie Industrielles, 10 rue Vauquelin, 75231 Paris Cedex 05, France.
authors.forename: P M C
authors.initials: PM
authors.lastname: de Oliveira
authors.forename: J S
authors.initials: JS
authors.lastname: Sá Martins
authors.forename: D
authors.initials: D
authors.lastname: Stauffer
authors.forename: S
authors.initials: S
authors.lastname: Moss de Oliveira
mesh_terms: D000818:Animals; D005075:Biological Evolution; D002874:Chromosome Mapping / Q000379:methods*; D003198:Computer Simulation; D014644:Genetic Variation; D005828:Genetics, Population; D006801:Humans; D015810:Linkage Disequilibrium / Q000235:genetics; D008957:Models, Genetic; D009154:Mutation; D010802:Phylogeny; D011157:Population Dynamics; D017422:Sequence Analysis, DNA / Q000379:methods*; D016019:Survival Analysis