Phycosphere microbial succession patterns and assembly mechanisms in a marine dinoflagellate bloom

Abstract

Given the ecological significance of microorganisms in algal blooming events, it is critical to understand the mechanisms regarding their distribution under different conditions. We tested the hypothesis that microbial community succession is strongly associated with algal bloom stages, and that the assembly mechanisms are cocontrolled by deterministic and stochastic processes. Community structures and underlying ecological processes of microbial populations (attached and freeliving bacteria) at three algal bloom stages (pre-, during, and postbloom) over a complete dinoflagellate Scrippsiella trochoidea bloom were investigated. Both attached and free-living taxa had a strong response to the bloom event, and the latter was more sensitive than the former. The contribution of environmental parameters to microbial variability was 40.2%. Interaction analysis showed that complex positive or negative correlation networks exist in phycosphere microbes. These relationships were the potential drivers of mutualist and competitive interactions that impacted bacterial succession. Null model analysis showed that the attached bacterial community primarily exhibited deterministic processes at pre- and during-bloom stages, while dispersal-related processes contributed to a greater extent at the postbloom stage. In the free-living bacterial community, homogeneous selection and dispersal limitation dominated in the initial phase, which gave way to more deterministic processes at the two later stages. Relative contribution analyses further demonstrated that the community turnover of attached bacteria was mainly driven by environmental selection, while stochastic factors had partial effects on the assembly of free-living bacteria. Taken together, these data demonstrated that a robust link exists between bacterioplankton community structure and bloom progression, and phycosphere microbial succession trajectories are cogoverned by both deterministic and random processes.