250 Chemical composition and growth responses of brown, green, and red macroalgae to pollution in the Russian black sea

Zakharikhina L.V., Gorbunova T.L., Ryndin A.V., Lesnikova P.S., Rogozhina E.V. (2024) Marine Pollution Bulletin, 207, art. no. 116831,  DOI: 10.1016/j.marpolbul.2024.116831

ABSTRACT: Macroalgae have long served as bioindicators of pollution in coastal marine environments. However, conventional pollution assessment methods often take a compartmentalized approach, either focusing on macrophyte biological parameters or independently analyzing heavy metal and oil product bioaccumulation within them. This study establishes connections between: (1) the characteristics of chemical pollution in brown, green, and red macroalgae, (2) organic pollution in the nutrient medium, and (3) the resulting changes in phytocenosis composition and macrophyte morphological characteristics. The research was conducted in the coastal zone near the Sochi River mouth on the Black Sea coast of Russia, encompassing the urban center of the Sochi metropolitan area. Inductively Coupled Plasma (ICP) analysis quantified the accumulation levels of 60 chemical elements within macrophyte algae. The novel aspect of this study is the development of a quantitative metric for assessing the overall chemical pollution impacting the ecologically crucial macroalgae Cystoseira. This systematic approach represents a significant advancement in the comprehensive evaluation and management of coastal water quality. The study identified two contrasting accumulation patterns: (1) pollution-tolerant annual algae exhibited an exclusion mechanism for chemical elements, while (2) Cystoseira displayed a non-exclusion accumulation pattern, potentially explaining its absence in the most heavily polluted zone. This approach paves the way for establishing a standardized scale for algal chemical pollution, reflecting a range from permissible to highly hazardous levels in seawater. This will enable rapid acquisition of both qualitative and quantitative pollution data, streamline monitoring efforts, and expedite the implementation of control measures.

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