title: [On the problems of the evolutionary optimization of life history. II. To justification of optimization criterion for nonlinear Leslie model].
abstract: The paper considers the problems in the adaptive evolution of life-history traits for individuals in the nonlinear Leslie model of age-structured population. The possibility to predict adaptation results as the values of organism's traits (properties) that provide for the maximum of a certain function of traits (optimization criterion) is studied. An ideal criterion of this type is Darwinian fitness as a characteristic of success of an individual's life history. Criticism of the optimization approach is associated with the fact that it does not take into account the changes in the environmental conditions (in a broad sense) caused by evolution, thereby leading to losses in the adequacy of the criterion. In addition, the justification for this criterion under stationary conditions is not usually rigorous. It has been suggested to overcome these objections in terms of the adaptive dynamics theory using the concept of invasive fitness. The reasons are given that favor the application of the average number of offspring for an individual, R(L), as an optimization criterion in the nonlinear Leslie model. According to the theory of quantitative genetics, the selection for fertility (that is, for a set of correlated quantitative traits determined by both multiple loci and the environment) leads to an increase in R(L). In terms of adaptive dynamics, the maximum R(L) corresponds to the evolutionary stability and, in certain cases, convergent stability of the values for traits. The search for evolutionarily stable values on the background of limited resources for reproduction is a problem of linear programming.
authors.forename: V P
authors.initials: VP
authors.lastname: Pasekov
mesh_terms: D000222:Adaptation, Physiological / Q000235:genetics*; D000818:Animals; D005075:Biological Evolution; D056084:Genetic Fitness / Q000235:genetics; D006801:Humans; D008018:Life Cycle Stages / Q000235:genetics*; D008962:Models, Theoretical; D017711:Nonlinear Dynamics; D012098:Reproduction