Diversity of Cyanobacteria and Algae in Biological Soil Crusts of the Northern Ural Mountain Region Assessed through Morphological and Metabarcoding Approaches

• Published in: Diversity
• Main Authors: Elena Patova, Irina Novakovskaya, Evgeniy Gusev, Nikita Martynenko
• Format: Article in Journal/Newspaper
• Language: English
• Published: MDPI AG 2023
• Subjects: biological soil crusts; terrestrial cyanobacteria and eukaryotic algae; mountain tundra; Polar; Subpolar and Northern Urals; Biology (General); QH301-705.5; Tundra; ural mountains
• Online Access: https://doi.org/10.3390/d15101080; https://doaj.org/article/48d3de7d5a394e63a09ad88c01b5a260

In mountain regions, biological soil crusts (BSCs) provide essential ecological services by being involved in primary production and nitrogen fixation. Eukaryotic algae and cyanobacteria are important photosynthetic components of these unique cryptogamic communities. Here, we present an overview of the eukaryotic and prokaryotic diversity of such phototrophs in BSCs in the mountain tundra of the northern Ural Mountains. Such assessment is based on morphological surveys and the first metabarcoding analysis in the region. In total, 166 taxa of Cyanobacteria and 256 eukaryotic algae (including Euglenophyta, Ochrophyta, Dinophyta, Bacillariophyta, Chlorophyta, and Charophyta) were identified. For the first time, 86 taxa new to the BSCs of the high-mountain belt of the region were discovered. Considering species composition, Cyanobacteria and Chlorophyta are the most abundant taxa in all the analyzed BSCs. The genera Nostoc, Coccomyxa, Chlamydomonas, Leptolyngbya, Stenomitos, Pycnacronema, Stigonema , and Eunotia had the highest number of taxonomic units. These groups shape the structure, function, and ecology of the BSC communities in the studied region. Our results show that BSCs in the tundras of the Ural Mountains have a high active and passive biodiversity of terrestrial cyanobacteria and algae. Both implemented methods resulted in similar results with a comparable number of algae and cyanobacteria species per sample. Metabarcoding could be implemented in future in the region to accurately screen photosynthetic organisms in BSCs.