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Mathematical Modeling Techniques for Studying the Growth of the Arctic Flounder (Liopsetta glacialis) in the White Sea. P. 123–132

Версия для печати

Section: Biology

UDC

597.587.9(268.46):52-17

Authors

Gennadiy V. Fuks*, Natal’ya A. Shilova**
*Northern Branch of the Polar Research Institute of Marine Fisheries and Oceanography named after N.M. Knipovich (Arkhangelsk, Russian Federation)
**Northern (Arctic) Federal University (Arkhangelsk, Russian Federation)
Corresponding author: Gennadiy Fuks, address: ul. Uritskogo, 17, Arkhangelsk, 163002, Russian Federation;
e-mail: fuks@pinro.ru

Abstract

An actual issue of studying the dynamics of fish growth in populations is the analysis of linear and weight characteristics of individuals; and the choice of the method is important. Mathematical methods of analysis serve as a tool for solving a wide range of problems, but each of them requires an individual method, which allows obtaining reliable results. The paper analyzes the empirical data using mathematical modeling techniques to determine the patterns of body mass changes of the Arctic flounder, depending on its length in various areas of the Dvina and Onega Bays of the White Sea. The proposed methodology elicits the fact that the growth rate of males and females differs largely in all studied areas. The body mass dynamics of the Arctic flounder, depending on the body length variation, is described by a power function for both Onega and Dvina Bays of the White Sea. The regression analysis lead to the conclusion that two separate zones can be distinguished in the Onega Bay, characterized by different growth rates of linear and weight characteristics for both males and females living in the apex and sea part of the bay. Such isolated zones are not identified in the Dvina Bay. The universal equations can be used to study the dependence of body mass on the length of the Arctic flounder species living in different parts of the Onega and Dvina Bays.

Keywords

Arctic flounder of the White Sea, linear growth of the Arctic flounder, weight growth of the Arctic flounder, correlation analysis, regression analysis, parametric test
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