Abstract
The human gut microbiome is a dynamic ecosystem. Host behaviors (e.g., diet) provide a regular source of environmental variation that induces fluctuations in the abundances of resident microbiota. Despite these displacements, microbial community members remain highly resilient. Population abundances tend to fluctuate around a characteristic steady-state over long timescales in healthy human hosts. These temporary excursions from steady-state abundances, known as sojourn trajectories, have the potential to inform our understanding of the fundamental dynamics of the microbiome. However, to our knowledge, the macroecology of sojourn trajectories has yet to be systematically characterized. In this study, we leverage theoretical tools from the study of random walks to characterize the duration of sojourn trajectories, their shape, and the degree that diverse community members exhibit similar qualitative and quantitative dynamics. We apply the stochastic logistic model as a theoretical lens for interpreting our empirical observations. We find that the typical timescale of a sojourn trajectory does not depend on the mean abundance of a community member (i.e., carrying capacity), although it is strongly related to its coefficient of variation (i.e., environmental noise). This work provides fundamental insight into the dynamics, timescales, and fluctuations exhibited by diverse microbial communities.IMPORTANCEMicroorganisms in the human gut often fluctuate around a characteristic abundance in healthy hosts over extended periods of time. These typical abundances can be viewed as steady states, meaning that fluctuating abundances do not continue towards extinction or dominance but rather return to a specific value over a typical timescale. Here, we empirically characterize the (i) length (i.e., number of days), (ii) relationship between length and height, and (iii) typical deviation of a sojourn trajectory. These three patterns can be explained and unified through an established minimal model of ecological dynamics, the stochastic logistic model of growth.