Supercomputer simulation of hydrobiological processes of coastal systems
Matematičeskoe modelirovanie, Tome 34 (2022) no. 1, pp. 81-103.

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The paper discusses supercomputer modeling of the dynamics of plankton populations, including phyto- and zooplankton, in coastal systems. The mathematical model of the dynamics of planktonic populations includes a system of convection-diffusion-reaction equations with nonlinear members, allows to study the mechanism of external hormonal regulation based on the scenario approach. The proposed mathematical 3D model is linearized, its discretization is carried out, and on the basis of splitting by coordinates, a chain is obtained, consisting of two-dimensional and one-dimensional problems. For the numerical implementation of the proposed mathematical model of the hydrobiology of the coastal system in the form of a software module (SM), a multiprocessor computing system (MCS) was used, designed for massively parallel computations, its use made it possible to significantly reduce the operating time of the SM. To improve the accuracy of the calculations, a procedure was used to refine the solution on a sequence of thickening uniform rectangular grids. The influence of the mechanism of ectocrine regulation and the regime of nutrient intake on the production and destruction processes of plankton has been studied. The mathematical model includes a nonlinear dependence used to describe the growth rate of algal cells on the concentration of the metabolite, which made it possible to describe the ability of algal excretion products to control their growth even under conditions of massive influx of pollutants. The approach used meets modern concepts of the functioning of hydrobiocenosis. On the basis of the developed supercomputer-oriented software toolkit, not only direct trophic interactions, but also the actions of the waste products of individuals, which are mediated — chemical interactions, have been studied.
Keywords: mathematical model of hydrobiology, mechanism of external hormonal regulation, chemical interactions of plankton, splitting, algorithm, super-computer.
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A. I. Sukhinov; A. V. Nikitina; A. M. Atayan; V. N. Litvinov; Yu. V. Belova; A. E. Chistyakov. Supercomputer simulation of hydrobiological processes of coastal systems. Matematičeskoe modelirovanie, Tome 34 (2022) no. 1, pp. 81-103. http://geodesic.mathdoc.fr/item/MM_2022_34_1_a5/

[1] M. A. Novikov, M. N. Harlamova, “Transabioticheskie faktory v vodnoi srede (obzor)”, Zhurn. obshchei biologii, 61:1 (2000), 22–46

[2] W. R. DeMott, F. Moxter, “Foraging on cyanobacteria by copepods: responses to chemical defenses and resources abundance”, Ecology, 72 (1991), 1820–1834 | DOI

[3] G. Iörgensen, “Growth-inhibing substances formed by algae”, Physiol. Plant., 9 (1956), 712–717 | DOI

[4] W. Wang, “Chromate ion as a referense toxicant for aquatic phytotoxicity tests”, Environ. Toxicol. and Chem., 6:12 (1987), 953–960 | DOI

[5] J. Findeneg, “Factors controlling primary prodyctivity, especially with regard to water replenishment, stratification and mixing”, Proc. of 1 B.P. Symp. on Prymary Productivity in Aquatic Enviroments (Pallanza, 1965), v. 18, 1965, 105–119

[6] L. M. Zimina, T. G. Sazykina, “Vydelenie ekzometabolitov mikrovodorosliami kak mekhanizm regulirovaniia plotnosti populiatsii”, Gidrobiol. zhurn., 23:4 (1987), 50–55

[7] Iu. A. Dombrovskij, G. S. Markman, Prostranstvennaia i vremennaia uporiadochennost v ekologicheskikh i biokhimicheskikh sistemakh, Izd-vo Rostovskogo universiteta, Rostov-na-Donu, 1983, 120 pp.

[8] A. A. Samarskii, P. N. Vabishchevich, “Finite-difference approximations to the transport equation. II”, Differ. Eq., 36:7 (2000), 1069–1077 | DOI | MR | Zbl

[9] A. A. Sukhinov, A. E. Chistyakov, E. V. Alekseenko, “Numerical realization of the three-dimensional model of hydrodynamics for shallow water basins on a high-performance system”, Mathematical Models and Computer Simulations, 3:5 (2011), 562–574 | DOI | MR | Zbl

[10] G. G. Matishov, V. G. Il'ichev, V. L. Semin, V. V. Kulygin, “Adaptation of populations to temperature conditions: results of computer simulation”, Doklady Biological Sciences, 420:1 (2008), 183–186 | DOI | Zbl

[11] Yu. V. Tyutyunov, A. D. Zagrebneva, A. I. Azovsky, “Spatiotemporal pattern formation in a prey-predator system: The case study of short-term interactions between diatom microalgae and microcrustaceans”, Mathematics, 8:7 (2020), 1065–1080 | DOI

[12] A. Ju. Perevariukha, “Neinterpretiruemoe povedenie modelei dinamiki populiatsii i granitsy parametricheskikh intervalov”, Ekologicheskie sistemy i pribory, 2021, no. 6, 15–23

[13] O. L. Zhdanova, A. I. Abakumov, “Modeling of the phytoplankton dynamics considering the mechanisms of ectocrine regulation”, Mat. Biolog. Bioinform., 10:1 (2015), 178–192

[14] K. Fennel, “The generation of phytoplankton patchiness by mesoscale current patterns”, Ocean Dynamics, 52 (2001), 58–70 | DOI

[15] E. Alekseenko, B. Roux, D. Fougere, P. G. Chen, “The effect of wind induced bottom shear stress and salinity on Zostera noltii replanting in a Mediterranean coastal lagoon”, Estuarine, Coastal and Shelf Science, 187 (2017), 293–305 | DOI

[16] A. I. Sukhinov, A. E. Chistiakov, V. V. Sidoriakina, E. A. Protsenko, “Economic explicit-implicit schemes for solving multidimensional diffusion-convection problems”, Computational Continuum Mechanics, 12:4 (2019), 435–445

[17] A. I. Sukhinov, A. E. Chistyakov, E. A. Protsenko, “Difference scheme for solving problems of hydrodynamics for large grid Peclet numbers”, Computer Research and Modeling, 11:5 (2019), 833–848 | DOI | MR

[18] A. A. Samarskij, P. N. Vabishhevich, Chislennye metody resheniia zadach konvektsii-diffuzii, URSS, M., 2009, 248 pp.

[19] A. I. Sukhinov, A. E. Chistyakov, Y. V. Belova, “The difference scheme for the two-dimensional convection-diffusion problem for large Peclet numbers”, MATEC Web of Conf., 226 (2019), 04030 | DOI

[20] A. I. Sukhinov, A. E. Chistyakov, G. A. Ugolnitskii, A. B. Usov, A. V. Nikitina, M. V. Puchkin, I. S. Semenov, “Game-theoretic regulations for control mechanisms of sustainable develop-ment for shallow water ecosystems”, Automation and Remote Control, 78:6 (2017), 1059–1071 | DOI | MR | Zbl

[21] A. Nikitina, Y. Belova, A. Atayan, “Mathematical modeling of the distribution of nutrients and the dynamics of phytoplankton populations in the Azov Sea, taking into account the influence of salinity and temperature”, AIP Conference Proc., 2188 (2019), 050027 | DOI

[22] Elektronnyj atlas, podgotovlen IUNTS RAN, , 2018 http://atlas.iaz.ssc-ras.ru/sitemap-ecoatlas.html

[23] Ekologicheskij Atlas. Chernoe i Azovskoe moria, PAO NK «Rosneft», OOO «Arkticheskij Nauchnyj tsentr», Fond «NIR», Fond «NIR», M., 2019, 464 pp.