Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

A quantitative framework reveals the ecological drivers of grassland soil microbial community assembly in response to warming

Daliang Ning, Mengting Yuan, Linwei Wu, Ya Zhang, Xue Guo, Xishu Zhou, Yunfeng Yang, Adam P. Arkin, Mary K. Firestone, Jizhong Zhou
doi: https://doi.org/10.1101/2020.02.22.960872
Daliang Ning
1Institute for Environmental Genomics, Department of Microbiology and Plant Biology, and School of Civil Engineering and Environmental Sciences, University of Oklahoma, Norman, OK, USA
2State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Mengting Yuan
1Institute for Environmental Genomics, Department of Microbiology and Plant Biology, and School of Civil Engineering and Environmental Sciences, University of Oklahoma, Norman, OK, USA
3Department of Environmental Science, Policy and Management, University of California, Berkeley, CA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Linwei Wu
1Institute for Environmental Genomics, Department of Microbiology and Plant Biology, and School of Civil Engineering and Environmental Sciences, University of Oklahoma, Norman, OK, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Ya Zhang
1Institute for Environmental Genomics, Department of Microbiology and Plant Biology, and School of Civil Engineering and Environmental Sciences, University of Oklahoma, Norman, OK, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Xue Guo
1Institute for Environmental Genomics, Department of Microbiology and Plant Biology, and School of Civil Engineering and Environmental Sciences, University of Oklahoma, Norman, OK, USA
2State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Xishu Zhou
1Institute for Environmental Genomics, Department of Microbiology and Plant Biology, and School of Civil Engineering and Environmental Sciences, University of Oklahoma, Norman, OK, USA
4School of Minerals Processing and Bioengineering, Central South University, Changsha, Hunan, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Yunfeng Yang
2State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Adam P. Arkin
5Earth and Environmental Sciences, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
6Department of Bioengineering, University of California, Berkeley, CA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Mary K. Firestone
3Department of Environmental Science, Policy and Management, University of California, Berkeley, CA, USA
5Earth and Environmental Sciences, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jizhong Zhou
1Institute for Environmental Genomics, Department of Microbiology and Plant Biology, and School of Civil Engineering and Environmental Sciences, University of Oklahoma, Norman, OK, USA
2State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China
5Earth and Environmental Sciences, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: jzhou@ou.edu
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Preview PDF
Loading

Abstract

Unraveling the drivers controlling community assembly is a central issue in ecology. Selection, dispersal, diversification and drift are conceptually accepted as major community assembly processes. Defining their relative importance in governing biodiversity is compellingly needed, but very challenging. Here, we present a novel framework to quantitatively infer community assembly mechanisms by phylogenetic bin-based null model analysis (iCAMP). Our results with simulated microbial communities showed that iCAMP had high accuracy (0.93 - 0.99), precision (0.80 - 0.94), sensitivity (0.82 - 0.94), and specificity (0.95 - 0.98), which were 10-160% higher than those from the entire community-based approach. Applying it to grassland microbial communities in response to experimental warming, our analysis showed that homogeneous selection (38%) and “drift” (59%) played dominant roles in controlling grassland soil microbial community assembly. Interestingly, warming enhanced homogeneous selection, but decreased “drift” over time. Warming-enhanced selection was primarily imposed on Bacillales in Firmicutes, which were strengthened by increased drought and reduced plant productivity. This general framework should also be useful for plant and animal ecology.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
Back to top
PreviousNext
Posted February 25, 2020.
Download PDF

Supplementary Material

Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
A quantitative framework reveals the ecological drivers of grassland soil microbial community assembly in response to warming
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
A quantitative framework reveals the ecological drivers of grassland soil microbial community assembly in response to warming
Daliang Ning, Mengting Yuan, Linwei Wu, Ya Zhang, Xue Guo, Xishu Zhou, Yunfeng Yang, Adam P. Arkin, Mary K. Firestone, Jizhong Zhou
bioRxiv 2020.02.22.960872; doi: https://doi.org/10.1101/2020.02.22.960872
Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
Citation Tools
A quantitative framework reveals the ecological drivers of grassland soil microbial community assembly in response to warming
Daliang Ning, Mengting Yuan, Linwei Wu, Ya Zhang, Xue Guo, Xishu Zhou, Yunfeng Yang, Adam P. Arkin, Mary K. Firestone, Jizhong Zhou
bioRxiv 2020.02.22.960872; doi: https://doi.org/10.1101/2020.02.22.960872

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Ecology
Subject Areas
All Articles
  • Animal Behavior and Cognition (2235)
  • Biochemistry (4302)
  • Bioengineering (2958)
  • Bioinformatics (13483)
  • Biophysics (5959)
  • Cancer Biology (4633)
  • Cell Biology (6641)
  • Clinical Trials (138)
  • Developmental Biology (3939)
  • Ecology (6240)
  • Epidemiology (2053)
  • Evolutionary Biology (9181)
  • Genetics (6883)
  • Genomics (8803)
  • Immunology (3918)
  • Microbiology (11286)
  • Molecular Biology (4458)
  • Neuroscience (25625)
  • Paleontology (183)
  • Pathology (722)
  • Pharmacology and Toxicology (1209)
  • Physiology (1776)
  • Plant Biology (3999)
  • Scientific Communication and Education (892)
  • Synthetic Biology (1194)
  • Systems Biology (3627)
  • Zoology (654)