Abstract

The coastal zone and shelf of the north-western of the Sea of Japan have high biological productivity. The vegetation of microalgae is realized due to insolation, nutrient input with river runoff and as a result of seasonal vertical mixing of water masses. Also, the productivity activity relates to the type of marine landscape. Phytoplankton assemblages are first-order food resources for zooplankton and the second for nekton (fish, mammals), and they also serve as a source of biological minerals from the decayed of their dead cell products, which as suspended particles (detritus) provide food for pelagic bacteria and bottom biocenoses. The vertical subdivision of the landscape - neritho-pelagial (coastal zone) of the studied part of the sea reflects a wide biological diversity represented by bottom communities of living organisms. The research objective of this article studied to analyze the spatial and temporal dynamics of chlorophyll-a concentration in phytoplankton in different landscape-bionomic areas in the north- western of the Sea of Japan for each season from 2003 to 2022’s. The article is used the landscape-bionomic and space monitoring data approaches. The known system of units of global zoning of ecoregions (sea basins) describes the natural features of the sea. The fundamental unit of regional zoning is coastal morphostructures or marine landscape which builds ecological conditions for hydrobionts. Space monitoring from the Aqua satellite, NASA, covers the upper layers of water at a wide resolution. Water surface temperature and chlorophyll-a concentration for 20 years (2003-2022's) are compared on the basis of satellite data. Practical significance: the paper discloses the links between landscape-bionomic areas and seasonal multiyear dynamics of temperature and phytoplankton productivity in the north- western of the Sea of Japan. The comprehensive approach will serve as a necessity for the rational use of aquatic biological resources. Moreover, satellite data can be applied to the construction of long-term forecasts of climate variability in the region.

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