title: Effect of variable surrounding on species creation.
abstract: We constructed a model of speciation from evolution in an ecosystem consisting of a limited amount of energy recources. The species possesses genetic information, which is inherited according to the rules of the Penna model of genetic evolution. The increase in the number of the individuals of each species depends on the quality of their genotypes and the available energy resources. The decrease in number of the individuals results from genetic death or maximum-age reaching by the individual. The amount of energy resources is represented by a solution of the differential logistic equation, where the growth rate of the amount of the energy resources has been modified to include the number of individuals from all species in the ecosystem under consideration. The fluctuating surrounding is modelled with the help of the function V(x, t) = 1/4 x4 + 1/2 b(t)x2, where x represents phenotype and the coefficient b(t) shows the cos(omega t) time dependence. The closer the value x of an individual to the minimum of V(x, t), the better adapted its genotype to the surrounding. We observed that the life span of the organisms strongly depends on the value of the frequency omega. It becomes shorter the more frequent the changes of the surrounding. However, there is a tendency for the species that have a higher value of the reproduction age aR to win the competition with the other species. Another observation is that small evolutionary changes of the inherited genetic information lead to spontaneous bursts of the evolutionary activity when many new species may appear in a short period.
authors.affiliation: Institute of Microbiology, University of Wrocław ul. Przybyszewskiego 63/77, 54-148 Wrocław, Poland.
authors.forename: Aleksandra
authors.initials: A
authors.lastname: Nowicka
authors.forename: Artur
authors.initials: A
authors.lastname: Duda
authors.forename: Mirosław R
authors.initials: MR
authors.lastname: Dudek
mesh_terms: D000465:Algorithms; D005075:Biological Evolution; D003198:Computer Simulation; D017753:Ecosystem; D019143:Evolution, Molecular; D008433:Mathematics; D008954:Models, Biological