Parameter δ 18 O in the Marine Environment Ecosystem Studies on the Example of the Barents Sea

• Published in: Water
• Main Authors: A. A. Namyatov, P. R. Makarevich, E. I. Druzhkova, I. A. Pastukhov
• Format: Article in Journal/Newspaper
• Language: English
• Published: MDPI AG 2023
• Subjects: Barents Sea; Svalbard archipelago; nutrients; phytoplankton; primary production; net primary production; Hydraulic engineering; TC1-978; Water supply for domestic and industrial purposes; TD201-500; Svalbard; Svalbard Archipelago
• Online Access: https://doi.org/10.3390/w15020328; https://doaj.org/article/8163acaec37a47dbb7ea0d4b3358d767

The isotopic parameter δ 18 O in oceanography is used for the calculation of mixing proportions of the Atlantic, rivers, and melted waters as well as the relative content of ice-forming waters. Using these values, as well as nutrient concentrations in the nuclei of these waters, it is possible to calculate a conservative concentration, which is determined only by the water’s mixing. These values are the points of reference for water nutrients reserve changes at the expense of the «nonconservative» factors (photosynthesize and geochemical sedimentation). This approach in the calculation of primary production allows moving from the use of the constant stoichiometric ratios to the floating ones, which is observed in the actual ecosystem. Based on the proposed method, the nutrient consumption features and production changes in the Barents Sea were studied. According to the maximum value of production in the summer, the following areas were identified—an early autumn period in the Barents Sea, an area with the maximum values of gross primary production (GPP > 150 g C m −2 ), three regions with increased values (GPP > 100 g C m −2 ), and two regions with relatively low values (GPP < 100 g C m −2 ). The use of this technique with a long-term data series available on salinity and the content of nutrients will allow the future to proceed to the study of the climatic variability of these parameters, ranging from the nutrient consumption variability to the productivity variability of the study area.