Ocean acidification impacts bacteria–phytoplankton coupling at low-nutrient conditions

• Published in: Biogeosciences
• Main Authors: T. Hornick, L. T. Bach, K. J. Crawfurd, K. Spilling, E. P. Achterberg, J. N. Woodhouse, K. G. Schulz, C. P. D. Brussaard, U. Riebesell, H.-P. Grossart
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2017
• Subjects: Ecology; QH540-549.5; Life; QH501-531; Geology; QE1-996.5; Ocean acidification
• Online Access: https://doi.org/10.5194/bg-14-1-2017; https://doaj.org/article/6914e8aca9b54711be90b2a09a689b86

The oceans absorb about a quarter of the annually produced anthropogenic atmospheric carbon dioxide (CO 2 ), resulting in a decrease in surface water pH, a process termed ocean acidification (OA). Surprisingly little is known about how OA affects the physiology of heterotrophic bacteria or the coupling of heterotrophic bacteria to phytoplankton when nutrients are limited. Previous experiments were, for the most part, undertaken during productive phases or following nutrient additions designed to stimulate algal blooms. Therefore, we performed an in situ large-volume mesocosm ( ∼ 55 m 3 ) experiment in the Baltic Sea by simulating different fugacities of CO 2 ( f CO 2 ) extending from present to future conditions. The study was conducted in July–August after the nominal spring bloom, in order to maintain low-nutrient conditions throughout the experiment. This resulted in phytoplankton communities dominated by small-sized functional groups (picophytoplankton). There was no consistent f CO 2 -induced effect on bacterial protein production (BPP), cell-specific BPP (csBPP) or biovolumes (BVs) of either free-living (FL) or particle-associated (PA) heterotrophic bacteria, when considered as individual components (univariate analyses). Permutational Multivariate Analysis of Variance (PERMANOVA) revealed a significant effect of the f CO 2 treatment on entire assemblages of dissolved and particulate nutrients, metabolic parameters and the bacteria–phytoplankton community. However, distance-based linear modelling only identified f CO 2 as a factor explaining the variability observed amongst the microbial community composition, but not for explaining variability within the metabolic parameters. This suggests that f CO 2 impacts on microbial metabolic parameters occurred indirectly through varying physicochemical parameters and microbial species composition. Cluster analyses examining the co-occurrence of different functional groups of bacteria and phytoplankton further revealed a separation of the four f CO 2 -treated ...