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Title: Long-Term Stochasticity Combines With Short-Term Variability in Assembly Processes to Underlie Rice Paddy Sustainability

Abstract

Revealing temporal patterns of community assembly processes is important for understanding how microorganisms underlie the sustainability of agroecosystem. The ancient terraced rice paddies at Longji provide an ideal platform to study temporal dynamics of agroecosystem sustainability due to their chronosequential records of soil physicochemistry and well-archived microbial information along 630-year rice cultivation. We used statistical null models to evaluate microbial assembly processes along the soil chronosequences of Longji rice paddies through time. Stochastic and deterministic assembly processes jointly governed microbial community composition within successional eras (less than 250 years), and within-era determinism was mainly driven by soil fertility and redox conditions alone or in combination. Conversely, across successional eras (i.e., over 300 years), stochasticity linearly increased with increasing duration between eras and was eventually predominant for the whole 630 years. We suggest that the impact of stochasticity vs. determinism on assembly is timescale-dependent, and we propose that the importance of stochastic assembly of microbial community at longer timescales is due to the gradual changes in soil properties under long-term rice cultivation, which in turn contribute to the sustainability of paddy ecosystem by maintaining a diverse community of microorganisms with multi-functional traits. In total, our results indicate that knowledge on themore » timescales at which assembly processes govern microbial community composition is key to understanding the ecological mechanisms generating agroecosystem sustainability.« less

Authors:
 [1]; ORCiD logo [2];  [3];  [4];  [5];  [4];  [4]
  1. Chinese Academy of Sciences (CAS), Nanjing (China); Univ. of Chinese Academy of Sciences, Beijing (China)
  2. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  3. Pennsylvania State Univ., Mont Alto, PA (United States)
  4. Chinese Academy of Sciences (CAS), Nanjing (China)
  5. Chinese Academy of Sciences (CAS), Guiyang (China); Chinese Academy of Sciences (CAS), Nanjing (China)
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
National Natural Science Foundation of China (NNSFC); National Key R&D Program; Chinese Academy of Sciences (CAS); USDOE Office of Science (SC), Biological and Environmental Research (BER)
OSTI Identifier:
1639168
Report Number(s):
PNNL-SA-140335
Journal ID: ISSN 1664-302X
Grant/Contract Number:  
AC05-76RL01830; ISSASIP 1639
Resource Type:
Accepted Manuscript
Journal Name:
Frontiers in Microbiology
Additional Journal Information:
Journal Volume: 11; Journal ID: ISSN 1664-302X
Publisher:
Frontiers Research Foundation
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; paddy soil; neutral theory; niche theory; microbial ecology; community ecology; null model

Citation Formats

Liu, Wenjing, Graham, Emily B., Zhong, Linghao, Zhang, Jianwei, Li, Shijie, Lin, Xiangui, and Feng, Youzhi. Long-Term Stochasticity Combines With Short-Term Variability in Assembly Processes to Underlie Rice Paddy Sustainability. United States: N. p., 2020. Web. https://doi.org/10.3389/fmicb.2020.00873.
Liu, Wenjing, Graham, Emily B., Zhong, Linghao, Zhang, Jianwei, Li, Shijie, Lin, Xiangui, & Feng, Youzhi. Long-Term Stochasticity Combines With Short-Term Variability in Assembly Processes to Underlie Rice Paddy Sustainability. United States. https://doi.org/10.3389/fmicb.2020.00873
Liu, Wenjing, Graham, Emily B., Zhong, Linghao, Zhang, Jianwei, Li, Shijie, Lin, Xiangui, and Feng, Youzhi. Fri . "Long-Term Stochasticity Combines With Short-Term Variability in Assembly Processes to Underlie Rice Paddy Sustainability". United States. https://doi.org/10.3389/fmicb.2020.00873. https://www.osti.gov/servlets/purl/1639168.
@article{osti_1639168,
title = {Long-Term Stochasticity Combines With Short-Term Variability in Assembly Processes to Underlie Rice Paddy Sustainability},
author = {Liu, Wenjing and Graham, Emily B. and Zhong, Linghao and Zhang, Jianwei and Li, Shijie and Lin, Xiangui and Feng, Youzhi},
abstractNote = {Revealing temporal patterns of community assembly processes is important for understanding how microorganisms underlie the sustainability of agroecosystem. The ancient terraced rice paddies at Longji provide an ideal platform to study temporal dynamics of agroecosystem sustainability due to their chronosequential records of soil physicochemistry and well-archived microbial information along 630-year rice cultivation. We used statistical null models to evaluate microbial assembly processes along the soil chronosequences of Longji rice paddies through time. Stochastic and deterministic assembly processes jointly governed microbial community composition within successional eras (less than 250 years), and within-era determinism was mainly driven by soil fertility and redox conditions alone or in combination. Conversely, across successional eras (i.e., over 300 years), stochasticity linearly increased with increasing duration between eras and was eventually predominant for the whole 630 years. We suggest that the impact of stochasticity vs. determinism on assembly is timescale-dependent, and we propose that the importance of stochastic assembly of microbial community at longer timescales is due to the gradual changes in soil properties under long-term rice cultivation, which in turn contribute to the sustainability of paddy ecosystem by maintaining a diverse community of microorganisms with multi-functional traits. In total, our results indicate that knowledge on the timescales at which assembly processes govern microbial community composition is key to understanding the ecological mechanisms generating agroecosystem sustainability.},
doi = {10.3389/fmicb.2020.00873},
journal = {Frontiers in Microbiology},
number = ,
volume = 11,
place = {United States},
year = {2020},
month = {5}
}

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