ena-STUDY-H4B 1R6-20-10-2014-22:14:47:719-534
Seasonal assemblages and short-lived blooms in coastal northwest Atlantic Ocean bacterioplankton
Temperate oceans are inhabited by diverse and temporally dynamic bacterioplankton communities. However, the role of the environment, resources and phytoplankton dynamics in shaping marine bacterioplankton communities at different time scales remains poorly constrained. Here, we combined time-series observations (time scales of weeks to years) with molecular analysis of formalin-fixed samples from a coastal inlet of the northwest Atlantic Ocean to show that a combination of temperature, nitrate, small phytoplankton and Synechococcus abundances are best predictors for annual bacterioplankton community variability, explaining 38% of the variation. Using Bayesian mixed modeling we identified assemblages of co-occurring bacteria associated with different seasonal periods, including the spring bloom (e.g. Polaribacter, Ulvibacter, Alteromonadales, and ARCTIC96B-16) and the autumn bloom (e.g. OM42, OM25, OM38 and Arctic96A-1 clades of Alpha-proteobacteria and SAR86, OM60, and SAR92 clades of Gamma-proteobacteria). Community variability over spring bloom development was best explained by silicate (32%) – an indication of rapid succession of bacterial taxa in response to diatom biomass– while nanophytoplankton as well as picophytoplankton abundance explained community variability (16-27%) over the transition into and out of the autumn bloom. Moreover, the seasonal structure was punctuated with short-lived blooms of rare bacteria including the KSA-1 clade of Sphingobacteria related to aromatic hydrocarbon-degrading bacteria.
Temperate oceans are inhabited by diverse and temporally dynamic bacterioplankton communities. However, the role of the environment, resources and phytoplankton dynamics in shaping marine bacterioplankton communities at different time scales remains poorly constrained. Here, we combined time-series observations (time scales of weeks to years) with molecular analysis of formalin-fixed samples from a coastal inlet of the northwest Atlantic Ocean to show that a combination of temperature, nitrate, small phytoplankton and Synechococcus abundances are best predictors for annual bacterioplankton community variability, explaining 38% of the variation. Using Bayesian mixed modeling we identified assemblages of co-occurring bacteria associated with different seasonal periods, including the spring bloom (e.g. Polaribacter, Ulvibacter, Alteromonadales, and ARCTIC96B-16) and the autumn bloom (e.g. OM42, OM25, OM38 and Arctic96A-1 clades of Alpha-proteobacteria and SAR86, OM60, and SAR92 clades of Gamma-proteobacteria). Community variability over spring bloom development was best explained by silicate (32%) – an indication of rapid succession of bacterial taxa in response to diatom biomass– while nanophytoplankton as well as picophytoplankton abundance explained community variability (16-27%) over the transition into and out of the autumn bloom. Moreover, the seasonal structure was punctuated with short-lived blooms of rare bacteria including the KSA-1 clade of Sphingobacteria related to aromatic hydrocarbon-degrading bacteria.