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.

Keywords

Null modelEcologyEcological successionCommunityCompetition (biology)Similarity (geometry)Noise (video)EconometricsEnvironmental scienceMathematicsStatisticsComputer scienceBiologyEcosystemArtificial intelligence

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Publication Info

Year
2019
Type
article
Volume
116
Issue
34
Pages
16892-16898
Citations
1003
Access
Closed

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Daliang Ning, Ye Deng, James M. Tiedje et al. (2019). A general framework for quantitatively assessing ecological stochasticity. Proceedings of the National Academy of Sciences , 116 (34) , 16892-16898. https://doi.org/10.1073/pnas.1904623116

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DOI
10.1073/pnas.1904623116