title: Testing the Neutral Theory of Biodiversity with Human Microbiome Datasets.
abstract: The human microbiome project (HMP) has made it possible to test important ecological theories for arguably the most important ecosystem to human health-the human microbiome. Existing limited number of studies have reported conflicting evidence in the case of the neutral theory; the present study aims to comprehensively test the neutral theory with extensive HMP datasets covering all five major body sites inhabited by the human microbiome. Utilizing 7437 datasets of bacterial community samples, we discovered that only 49 communities (less than 1%) satisfied the neutral theory, and concluded that human microbial communities are not neutral in general. The 49 positive cases, although only a tiny minority, do demonstrate the existence of neutral processes. We realize that the traditional doctrine of microbial biogeography "Everything is everywhere, but the environment selects" first proposed by Baas-Becking resolves the apparent contradiction. The first part of Baas-Becking doctrine states that microbes are not dispersal-limited and therefore are neutral prone, and the second part reiterates that the freely dispersed microbes must endure selection by the environment. Therefore, in most cases, it is the host environment that ultimately shapes the community assembly and tip the human microbiome to niche regime.
authors.affiliation: Computational Biology and Medical Ecology Lab, State Key Lab of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China.
authors.forename: Lianwei
authors.initials: L
authors.lastname: Li
authors.affiliation: Computational Biology and Medical Ecology Lab, State Key Lab of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China.
authors.forename: Zhanshan Sam
authors.initials: ZS
authors.lastname: Ma
mesh_terms: D001419:Bacteria / Q000145:classification*; D058448:Biota; D006801:Humans; D064307:Microbiota; D008954:Models, Biological