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Article

A general framework for quantitatively assessing ecological stochasticity

Daliang NingInstitute for Environmental Genomics, Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK 73019;Ye DengInstitute for Environmental Genomics, Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK 73019;James M. TiedjeCenter for Microbial Ecology, Michigan State University, East Lansing, MI 48824;Jizhong ZhouSchool of Civil Engineering and Environmental Sciences, University of Oklahoma, Norman, OK 73019;
2019en
ABI

Abstract

Significance An ecological community is a dynamic complex system with a myriad of interacting species, which are controlled by various scale-dependent deterministic and stochastic forces. With rapid advances in genomics technologies, categorizing biological diversity, particularly microbial diversity, becomes relatively easy, but the great challenge is to disentangle the mechanisms controlling biological diversity. The general null model-based framework developed in this study provides an effective and robust tool to ecologists for quantitatively assessing ecological stochasticity. By highlighting the caveats such as model selection, similarity metrics, and spatial scales, this study provides guidance for appropriate use of null model-based approaches for examining community assembly processes. Although this framework was tested with microbial data, it should also be applicable to plant and animal ecology.

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