[SS08] Emerging Mathematical and Modeling Approaches in Community and Ecosystem Ecology

[SS08-04] The evaluation of microbial dynamics from two mathematical approaches.

*Hiroaki Fujita¹ (1. CeLiSIS, Kyoto University (Japan))

Keywords:

Community dynamics,Stability,Microbiome

It is well known that community dynamics can undergo drastic changed. This phenomenon can be explained from two aspects, that is shifting among stable states or moving within the same attractor state. Conventionally, a mathematical model was required to distinguish between these mechanisms based on observed dynamics. Quantifying species interactions and their strength is necessary to reconstruct community dynamics. It is very difficult, however, to observe and estimate these interactions in natural systems. In the past decade, some approaches to evaluating community dynamics without mathematical models have been proposed. One is the empirical dynamic modeling (EDM), which reconstructs state space without any specific model. The other is energy landscape analysis, estimating the potential of each community state based on maximum pairwise entropy model. Applying these approaches to ecological communities help us understand the mechanisms behind dynamical systems, and, furthermore, evaluate the stability of communities.In this presentation, I will introduce the predictability of microbiome dynamics with stability indices through understanding dynamical systems. Using these two approaches, I evaluated the stability of 48 microbial communities in six different systems. Those communities were cultured for 110 days and monitored every 24 hours by quantifying 16S rRNA amplicon sequences. Microbial communities showed nonlinear dynamics; however, I was able to predict community dynamics using EDM. Furthermore, stability indices explained abrupt changes in community dynamics and helped us to predict the events.