Bioindication of the water salinity dynamics by the microalgae communities in the Lena River Delta, Laptev Sea, Russian Arctic

The Lena River in the Laptev Sea forms a vast delta, one of the largest in the world. The Ust-Lensky State Nature Reserve saves biodiversity on the Lena Delta territory beyond the Arctic Circle, in the zone of continuous permafrost. In recent years, large-scale plans for the development of extractive industries are implemented in this Russian Arctic sector. In this regard, the study of biodiversity and bioindication properties of aquatic organisms in the Lena River estuary area is becoming more and more relevant. This study aims to identify the species composition of microalgae in lotic and lentic water bodies of the Lena River Delta and use their indicator property for water salinity. It was a trace indicator of species distribution over the delta and their dynamics along the delta main watercourses to assess the impact of river waters on the Laptev Sea coastal areas. For this, all previously published materials on algae and chemical composition of the region waters as well as data obtained in recent years for the waters of the lower Lena reach were involved. In total, 700 species considered to 10 phyla were analyzed: Cyanobacteria (83), Euglenozoa (13), Ochrophyta (Chrysophyta, Xanthophyta) (41), Eustigmatophyta (4), Bacillariophyta (297), Miozoa (20), Cryptophyta (3), Rhodophyta (1), Chlorophyta (125), and Charophyta (111). The available materials of the field and reference observations were analyzed using several statistical methods. The study results indicate that hydrological conditions are the main factor regulating the spatial structure of the species composition of the microalgae communities in the Lena River Delta. The distribution of groups of salinity indicators across flowing water bodies reflects the effect of water salinity, and this allows suggesting possible sources of this effect. The mechanism of tracking the distribution of environmental indicators itself is a sensitive method, that reveals even their subtle changes in them; therefore, as an integral method, it can be helpful for further monitoring.