Observing dynamics of species-rich systems is challenging. In microbiology, studies on generation-time dependent dynamic community assembly are still rather unique (Shen et al., 2018). The up-to-date technology to resolve community assembly is next generation sequencing with Illumina, PacBio, and Nanopore (Goodwin, McPherson, and McCombie, 2016) as the currently most used ones. However, sequencing data are most often only snapshots and by no means in a state to provide results on-site and within performance corridors. We developed microbial flow cytometry to rapidly generate community data and bioinformatics evaluation tools for fast and automated computation. Recently an on-line tool to determine community stability properties, i.e. resilience and resistance, was developed (Liu et al., 2018).</p><p>We designed an experiment where we wanted to study in detail the succession of a microbial community in parallel bioreactors, which were initiated with an identical natural, species-rich inoculum. We wanted to test if steady state conditions, as typical for mono-dominant pure cultures, can lead to synchronized community states. To this end, we implemented bioreactor experiments in parallel, using the identical inoculum for two reactors used as control, and for three which were exposed to changing temperature profiles, switching between 30 and 40 °C forth and back. We ran those experiments for about 100 generations. The replica continuous reactors were designed to not allow immigration (mass-transfer) which is a standard situation for many biotechnological processes (Abubackar et al., 2018 Xie et al., 2017 Liu et al., 2014).</p><p>If only neutral mechanism would dominate community assembly with no restrains from niche differentiation forces, inherent stochastic processes can be expected to prevent synchrony and make prediction of community assembly difficult. But the principal aim of process control is to operate niche-differentiating boundarie s to strengthen and sustain an initially manufactured community. But there are also many indications that this aim might hardly be achieved (Evans et al., 2017 Du et al., 2017 Zhou et al., 2013). We expect stochastic community assembly to occur frequently in such reactor set ups and cause unexpected and varying community structure deviations. Disturbances may either add to this confusion due to their stochastic nature or shape community structures or even synchronize them if they are of niche differentiating power. We wanted to know how seemingly contrarily acting paradigms balance in closed environments to irrevocably open ways of their control .