DOI: 10.26650/ase.2025.1921540 ISSN: 2602-473X

Spatial and Temporal Variation of Marine algae along the Southern Coasts of the Caspian Sea (Azerbaijan, Neftchala)

Aytaj Muradova Sayadli, Shakar Mukhtarova, Muzhgan Masimli, Umudova Shafiqa, Yaqut Malikli
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From January to October 2025, the coastal waters of the Neftchala district (Azerbaijan, Caspian Sea) were investigated for the first taxonomic and ecological assessment of marine algae communities. Seasonal sampling was conducted at four coastal stations, and algal diversity, abundance, and community structure were evaluated using the Shannon–Wiener diversity index, Pielou’s evenness index, ANOSIM, PERMANOVA, SIMPER, UPGMA cluster analysis, and Spearman correlation analysis. A total of 35 taxa representing 16 families and 19 genera were identified, grouped into five phyla: Charophyta (1), Ochrophyta (2), Rhodophyta (6), Bacillariophyta (7), Cyanobacteria (8), and Chlorophyta (11 taxa). The predominant group consisted of green algae (31.4%), followed by blue-green (22.9%), diatoms (20%), red algae (17.1%), brown algae (5.7%), and chara algae (2.9%). Algal abundance peaked in summer (30.4% of total individuals), followed by spring (29.9%), whereas winter assemblages showed the lowest abundance. Cyanobacteria and Chlorophyta dominated during the warm seasons, while red algae became relatively more prominent in autumn and winter. Spatial analysis indicated pronounced differences among stations, with the highest abundance recorded at Station 3, contributing 25.93% of the total number of individuals. Species of the genus Lyngbya and Ulva were the most abundant taxa across all stations and seasons.The saprobic index (2.59–2.62) revealed β–α-mesosaprobic conditions, indicating weak hydrodynamic circulation and moderate organic pollution brought on by human inputs. The results demonstrate that seasonal environmental variability plays a dominant role in shaping algal communities along the southern Caspian Sea coast. The observed variation in algal species composition may be associated with seasonal variability and local environmental heterogeneity, with anthropogenic inputs potentially contributing to the observed ecological patterns. The acquired data offer a useful point of reference for upcoming coastal monitoring and bioindication research in the area.

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