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Sketching the Human Microbiome Biogeography with DAR (Diversity-Area Relationship) Profiles

  • Zhanshan (Sam) Ma
Human Microbiome

Abstract

SAR (species area relationship) is a classic ecological theory that has been extensively investigated and applied in the studies of global biogeography and biodiversity conservation in macro-ecology. It has also found important applications in microbial ecology in recent years thanks to the breakthroughs in metagenomic sequencing technology. Nevertheless, SAR has a serious limitation for practical applications—ignoring the species abundance and treating all species as equally abundant. This study aims to explore the biogeography discoveries of human microbiome over 18 sites of 5 major microbiome habitats, establish the baseline DAR (diversity-area scaling relationship) parameters, and perform comparisons with the classic SAR. The extension from SAR to DAR by adopting the Hill numbers as diversity measures not only overcomes the previously mentioned flaw of SAR but also allows for obtaining a series of important findings on the human microbiome biodiversity and biogeography. Specifically, two types of DAR models were built, the traditional power law (PL) and power law with exponential cutoff (PLEC), using comprehensive datasets from the HMP (human microbiome project). Furthermore, the biogeography “maps” for 18 human microbiome sites using their DAR profiles for assessing and predicting the diversity scaling across individuals, PDO profiles (pair-wise diversity overlap) for measuring diversity overlap (similarity), and MAD profile (for predicting the maximal accrual diversity in a population) were sketched out. The baseline biogeography maps for the healthy human microbiome diversity can offer guidelines for conserving human microbiome diversity and investigating the health implications of the human microbiome diversity and heterogeneity.

Keywords

Species area relationship (SAR) Diversity-area relationship (DAR) profile Maximal accrual diversity (MAD) profile Pair-wise diversity overlap (PDO) profile Biogeography of human microbiome Power law Self similarity Scale invariance 

Notes

Acknowledgements

I am indebted to DD Ye, LW Li, and J. Li, from the Chinese Academy of Sciences, for their computational help.

Author Contributions

ZS Ma designed and conducted the study and wrote the paper. The author read and approved the final manuscript for submission.

Funding Information

This study received funding from the following sources: National Science Foundation of China (Grant No. 71473243) and Yun-Ridge Industry Technology Leader Grant, a China-US International Cooperation Project on Genomics/Metagenomics Big Data.

Compliance with Ethical Standards

Conflict of Interest

The author declares that he has no conflict of interest.

Permit

No permission is needed since the datasets involved in this study were already published and publically available at http://hmpdacc.org.

Supplementary material

248_2018_1245_MOESM1_ESM.pdf (832 kb)
ESM 1 (PDF 832 kb)

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Computational Biology and Medical Ecology Laboratory, State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of ZoologyChinese Academy of SciencesKunmingChina
  2. 2.Center for Excellence in Animal Evolution and GeneticsChinese Academy of SciencesKunmingChina

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