Assessing mechanisms for microbial taxa and community dynamics using process models

Author:

Wu Linwei123ORCID,Yang Yunfeng4ORCID,Ning Daliang23,Gao Qun4,Yin Huaqun5,Xiao Naija23,Zhou Benjamin Y.6,Chen Si78,He Qiang78,Zhou Jizhong2391011

Affiliation:

1. Institute of Ecology, Key Laboratory for Earth Surface Processes of the Ministry of Education, College of Urban and Environmental Sciences Peking University Beijing China

2. Institute for Environmental Genomics University of Oklahoma Norman OK USA

3. Department of Microbiology and Plant Biology University of Oklahoma Norman OK USA

4. State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment Tsinghua University Beijing China

5. School of Minerals Processing and Bioengineering Central South University Changsha China

6. Department of Mathematics, Lunt Hall Northwestern University Evanston Illinois USA

7. Department of Civil and Environmental Engineering The University of Tennessee Knoxville Tennessee USA

8. Institute for a Secure and Sustainable Environment The University of Tennessee Knoxville Tennessee USA

9. School of Civil Engineering and Environmental Sciences University of Oklahoma Norman Oklahoma USA

10. Earth and Environmental Sciences, Lawrence Berkeley National Laboratory Berkeley California USA

11. School of Computer Science University of Oklahoma Norman OK USA

Abstract

AbstractDisentangling the assembly mechanisms controlling community composition, structure, distribution, functions, and dynamics is a central issue in ecology. Although various approaches have been proposed to examine community assembly mechanisms, quantitative characterization is challenging, particularly in microbial ecology. Here, we present a novel approach for quantitatively delineating community assembly mechanisms by combining the consumer–resource model with a neutral model in stochastic differential equations. Using time‐series data from anaerobic bioreactors that target microbial 16S rRNA genes, we tested the applicability of three ecological models: the consumer–resource model, the neutral model, and the combined model. Our results revealed that model performances varied substantially as a function of population abundance and/or process conditions. The combined model performed best for abundant taxa in the treatment bioreactors where process conditions were manipulated. In contrast, the neutral model showed the best performance for rare taxa. Our analysis further indicated that immigration rates decreased with taxa abundance and competitions between taxa were strongly correlated with phylogeny, but within a certain phylogenetic distance only. The determinism underlying taxa and community dynamics were quantitatively assessed, showing greater determinism in the treatment bioreactors that aligned with the subsequent abnormal system functioning. Given its mechanistic basis, the framework developed here is expected to be potentially applicable beyond microbial ecology.

Funder

National Natural Science Foundation of China

National Science Foundation

U.S. Environmental Protection Agency

Publisher

Wiley

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