Quantification of the effects of ocean acidification on sediment microbial communities in the environment: the importance of ecosystem approaches

• Published in: FEMS Microbiology Ecology
• Main Authors: Hassenrück, Christiane, Fink, Artur, Lichtschlag, Anna, Tegetmeyer, Halina, de Beer, Dirk, Ramette, Alban
• Format: Article in Journal/Newspaper
• Language: English
• Published: Oxford University Press (OUP) 2016
• Subjects: Ocean acidification
• Online Access: https://pub.uni-bielefeld.de/record/2902052

Hassenrück C, Fink A, Lichtschlag A, Tegetmeyer H, de Beer D, Ramette A. Quantification of the effects of ocean acidification on sediment microbial communities in the environment: the importance of ecosystem approaches. FEMS Microbiology Ecology . 2016;92(5): fiw027. To understand how ocean acidification (OA) influences sediment microbial communities, naturally CO2-rich sites are increasingly being used as OA analogues. However, the characterization of these naturally CO2-rich sites is often limited to OA-related variables, neglecting additional environmental variables that may confound OA effects. Here, we used an extensive array of sediment and bottom water parameters to evaluate pH effects on sediment microbial communities at hydrothermal CO2 seeps in Papua New Guinea. The geochemical composition of the sediment pore water showed variations in the hydrothermal signature at seep sites with comparable pH, allowing the identification of sites that may better represent future OA scenarios. At these sites, we detected a 60% shift in the microbial community composition compared with reference sites, mostly related to increases in Chloroflexi sequences. pH was among the factors significantly, yet not mainly, explaining changes in microbial community composition. pH variation may therefore often not be the primary cause of microbial changes when sampling is done along complex environmental gradients. Thus, we recommend an ecosystem approach when assessing OA effects on sediment microbial communities under natural conditions. This will enable a more reliable quantification of OA effects via a reduction of potential confounding effects.