RUSSIAN JOURNAL OF EARTH SCIENCES, VOL. 21, ES6001, doi:10.2205/2021ES000782, 2021

New Approach for Analyzing Marine Ecosystem Structure Using Bayesian Networks

Denis Krivoguz, Sergey Chernyi, and Artur Manukov

Abstract

Aquatic ecosystems of the Black Sea are complex multiparametric systems with a hierarchical structure. Thus, the main goal of our research was to investigate possibilities of using Bayesian networks to study the structure fo the natural systems in the Black Sea. We used CMEMS Black Sea environmental dataset, which consists of 7 different variables, that, in our opinion, can describe structural relations in the Black Sea ecosystem – sea surface temperature and salinity, concentrations of nitrates and phosphates, amount of chlorophyll-a and net primary production and also dissolved oxygen concentration. We think, that these variables can generally define interactions in water environment of the Black Sea, organisms, that live there and human activity. As a modeling result, we receive a structure of environmental variables interactions. At the top of this structure is a dissolved oxygen, as a final result of the ecosystem functioning. Further, we think it’s more appropriate to use Dynamic Bayesian networks for investigation of spatio-temporal changes to distinguish main drivers of changes and provide more balanced management of natural territories.

Received 8 June 2021; accepted 27 October 2021; published 20 November 2021.

Citation: Denis Krivoguz, Sergey Chernyi, and Artur Manukov (2021), New Approach for Analyzing Marine Ecosystem Structure Using Bayesian Networks, Russ. J. Earth Sci., 21, ES6001, doi:10.2205/2021ES000782.