title: Stochasticity, succession, and environmental perturbations in a fluidic ecosystem.
abstract: Unraveling the drivers of community structure and succession in response to environmental change is a central goal in ecology. Although the mechanisms shaping community structure have been intensively examined, those controlling ecological succession remain elusive. To understand the relative importance of stochastic and deterministic processes in mediating microbial community succession, a unique framework composed of four different cases was developed for fluidic and nonfluidic ecosystems. The framework was then tested for one fluidic ecosystem: a groundwater system perturbed by adding emulsified vegetable oil (EVO) for uranium immobilization. Our results revealed that groundwater microbial community diverged substantially away from the initial community after EVO amendment and eventually converged to a new community state, which was closely clustered with its initial state. However, their composition and structure were significantly different from each other. Null model analysis indicated that both deterministic and stochastic processes played important roles in controlling the assembly and succession of the groundwater microbial community, but their relative importance was time dependent. Additionally, consistent with the proposed conceptual framework but contradictory to conventional wisdom, the community succession responding to EVO amendment was primarily controlled by stochastic rather than deterministic processes. During the middle phase of the succession, the roles of stochastic processes in controlling community composition increased substantially, ranging from 81.3% to 92.0%. Finally, there are limited successional studies available to support different cases in the conceptual framework, but further well-replicated explicit time-series experiments are needed to understand the relative importance of deterministic and stochastic processes in controlling community succession.
authors.affiliation: State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China.
authors.forename: Jizhong
authors.initials: J
authors.lastname: Zhou
authors.forename: Ye
authors.initials: Y
authors.lastname: Deng
authors.forename: Ping
authors.initials: P
authors.lastname: Zhang
authors.forename: Kai
authors.initials: K
authors.lastname: Xue
authors.forename: Yuting
authors.initials: Y
authors.lastname: Liang
authors.forename: Joy D
authors.initials: JD
authors.lastname: Van Nostrand
authors.forename: Yunfeng
authors.initials: Y
authors.lastname: Yang
authors.forename: Zhili
authors.initials: Z
authors.lastname: He
authors.forename: Liyou
authors.initials: L
authors.lastname: Wu
authors.forename: David A
authors.initials: DA
authors.lastname: Stahl
authors.forename: Terry C
authors.initials: TC
authors.lastname: Hazen
authors.forename: James M
authors.initials: JM
authors.lastname: Tiedje
authors.forename: Adam P
authors.initials: AP
authors.lastname: Arkin
mesh_terms: D017753:Ecosystem; D060587:Groundwater / Q000382:microbiology*; D064307:Microbiota / Q000187:drug effects / Q000235:genetics*; D008954:Models, Biological; D010938:Plant Oils / Q000494:pharmacology*; D011157:Population Dynamics; D013045:Species Specificity; D013269:Stochastic Processes; D013997:Time Factors; D014871:Water Microbiology
chemical_list: D010938:Plant Oils
keywords: GeoChip; community assembly; disturbances; metagenomics; remediation