Abstract.

The article is devoted to the problem of species life span, as well as relatedthe problem of aging. The basis of the presented work is the concept of evolutionary optimality. As an optimized adaptive trait the species life span is considered, which, along with other adaptive traits, is a product of evolution. The author presents aging as an increase in energy consumption for self-preservation (metabolism, active metabolism, thermoregulation) with age. According to the proposed mathematical model, an age comes, the excess of which leads to a shortage of energy received by organisms with food. As a result, the body is forced to compensate the deficit of energy by the tissue of vital organs, which leads to death of the body. To determine the value of species life span, the author introduces the concept of aging coefficient, which establishes a relationship between energy expenses on self-preservation and age. Based on the evolutionary optimality of life expectancy, the magnitude of the aging coefficient is determined, which, as a result, makes it possible to express the species life expectancy as a function of other parameters organism and environmental factors. The author not only expounds the theory of the question, but also illustrates its validity with concrete calculate

Keywords:

ecosystem, evolutionary optimality, adaptive traits, coefficient of aging, life expectancy.

PP. 78-90.

DOI: 10.14357/20790279190209

References

1. Volosova N.V. 2016. Evolucia I optimalnost biologicheskih sistem.\\ Matematicheskie strukturi I modelirovanie. [Evolution and optimality of biological systems. \\ Mathematical Structures and Modeling], Vol. 2 (38), pp. 27-42.
2. Gavrilov LA, Gavrilova N.S. 1991. Biology of life expectancy.M. The science. 280 s.
3. Dorfman N.L., Ovsyannikov L.L., Khanin M.A. 1978. Determination of optimal biological parameters using a simulation mathematical model of the population. // Abstracts of the 3rd All-Union Conference on Biological and Medical Physics. Moscow – Sukhumi .; V.3. P. 263-267.
4. Novoseltsev V.N., Novoseltseva Z.A., Yashin A.I. 2003. Mathematical modeling in gerontology-STRATEGIC PROSPECTS. / / Successes of gerontology.. vyp. 12.- pp. 149- 165.
5. Obraztsov I.A., Khanin M.A. 1989., Optimalnie biomehanicheskie sistemi. [Optimal biomechanical systems]. M. “Medicine”., 271 p.
6. Ovsyannikov L.L., Svirezhev Yu.M. 1983. [The evolution of fecundity and the Fisher criterion] // Zhurn. biol. V. 44, No. 5, p. 621-626.
7. Ovsyannikov L.L., Pasekov V.P. Energetika i evolyutsionnaya optimal’nost’ priznakov organizma.[Energy and evolutionary optimality traits of an organism]. Zhurnal obshchej biologii. 51, No. 5, P. 709-716.
8. Rashevski N. Modeli i matematicheskie printsypy v biologii. [Models and mathematical principles in biology]. In the book Theoretical and mathematical biology. Moscow. The world, 1968, p.48-68.
9. Rosen R. 1969. Principi optimalnocti v biologii. [The principle of optimality in biology] .- Trans. from English.World. M. 214 s.
10. Semevsky F.N., Semenov S.M. 1982. Matematicheskoe modelirovanie ekologicheskih procesov. [Mathematical modeling of ecological processes]. Hydrometeoizdat. 280c.
11. Terekhin A.T., Budilova E.V. 2012. Evoluciya ziznenogo cikla. Modely osnovannie na optimalnm raspredelenii energii. [The Evolution of the Life Cycle: Models Based on Optimization of the Energy Distribution]. In the book Mathematics and Reality: Confrontation of Austerity and Complexity., Moscow. Soliton. С. 70-85.
12. Fursova P.V., Levich L.P., Alekseev I.L. 2003, Ekstremalnie prinsipi v matematicheskoi biologii//. Uspehi sovremennoi biologii. [Extreme principles in mathematical biology. / / Successes of modern biology]. Vol 123, No. 2, P.115-137.
13. Khanin M.A., Dorfman N.L., Bukharov I.B., Levadnii V.G. 1978. Ekstremalnie principi v biologii b phiziologii. [Extreme principles in biology and physiology]. – M .: Nauka, 256 p.
14. Kozlovski J., Weiner J. 1997. Intrcpecific allometriies are byproducts of body size optimization // Amer. Nat. V.149. P. 423-441.
15. Charnov E.L. 1993. Lafe history invariants. Some exploration of sinnetryin evolutionary ecology. Oxford: Univ. Press. P. 125-136.