16S and 18S rRNA Gene Metabarcoding Provide Congruent Information on the Responses of Sediment Communities to Eutrophication

Metabarcoding analyses of bacterial and eukaryotic communities have been proposed as efficient tools for environmental impact assessment. It has been unclear, however, to which extent these analyses can provide similar or differing information on the ecological status of the environment. Here, we used 16S and 18S rRNA gene metabarcoding to compare eutrophication-induced shifts in sediment bacterial and eukaryotic community structure in relation to a range of porewater, sediment and bottom-water geochemical variables, using data obtained from six stations near a former rainbow trout farm in the Archipelago Sea (Baltic Sea). Shifts in the structure of both community types were correlated with a shared set of variables, including porewater ammonium concentrations and the sediment depth-integrated oxygen consumption rate. Distance-based redundancy analyses showed that variables typically employed in impact assessments, such as bottom water nutrient concentrations, explained less of the variance in community structure than alternative variables (e.g., porewater NH4+ inventories and sediment depth-integrated O2 consumption rates) selected due to their low collinearity (up to 40 vs. 58% of the variance explained, respectively). In monitoring surveys where analyses of both bacterial and eukaryotic communities may be impossible, either 16S or 18S rRNA gene metabarcoding can serve as reliable indicators of wider ecological impacts of eutrophication.

Automated summary

Metabarcoding analyses of 16S and 18S rRNA genes showed that shifts in bacterial and eukaryotic community structures were correlated with common variables, such as porewater ammonium concentrations and sediment depth-integrated oxygen consumption rates. These analyses suggested that traditional impact assessment variables explained less variance in community structure compared to alternative variables selected for low collinearity.