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Representation of Dormant and Active Microbial Dynamics for Ecosystem Modeling

Dormancy is an essential strategy for microorganisms to cope with environmental stress. However, global ecosystem models typically ignore microbial dormancy, resulting in notable model uncertainties. To facilitate the consideration of dormancy in these large-scale models, we propose a new microbial...

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Autores principales: Wang, Gangsheng, Mayes, Melanie A., Gu, Lianhong, Schadt, Christopher W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3928434/
https://www.ncbi.nlm.nih.gov/pubmed/24558490
http://dx.doi.org/10.1371/journal.pone.0089252
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author Wang, Gangsheng
Mayes, Melanie A.
Gu, Lianhong
Schadt, Christopher W.
author_facet Wang, Gangsheng
Mayes, Melanie A.
Gu, Lianhong
Schadt, Christopher W.
author_sort Wang, Gangsheng
collection PubMed
description Dormancy is an essential strategy for microorganisms to cope with environmental stress. However, global ecosystem models typically ignore microbial dormancy, resulting in notable model uncertainties. To facilitate the consideration of dormancy in these large-scale models, we propose a new microbial physiology component that works for a wide range of substrate availabilities. This new model is based on microbial physiological states and the major parameters are the maximum specific growth and maintenance rates of active microbes and the ratio of dormant to active maintenance rates. A major improvement of our model over extant models is that it can explain the low active microbial fractions commonly observed in undisturbed soils. Our new model shows that the exponentially-increasing respiration from substrate-induced respiration experiments can only be used to determine the maximum specific growth rate and initial active microbial biomass, while the respiration data representing both exponentially-increasing and non-exponentially-increasing phases can robustly determine a range of key parameters including the initial total live biomass, initial active fraction, the maximum specific growth and maintenance rates, and the half-saturation constant. Our new model can be incorporated into existing ecosystem models to account for dormancy in microbially-driven processes and to provide improved estimates of microbial activities.
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spelling pubmed-39284342014-02-20 Representation of Dormant and Active Microbial Dynamics for Ecosystem Modeling Wang, Gangsheng Mayes, Melanie A. Gu, Lianhong Schadt, Christopher W. PLoS One Review Dormancy is an essential strategy for microorganisms to cope with environmental stress. However, global ecosystem models typically ignore microbial dormancy, resulting in notable model uncertainties. To facilitate the consideration of dormancy in these large-scale models, we propose a new microbial physiology component that works for a wide range of substrate availabilities. This new model is based on microbial physiological states and the major parameters are the maximum specific growth and maintenance rates of active microbes and the ratio of dormant to active maintenance rates. A major improvement of our model over extant models is that it can explain the low active microbial fractions commonly observed in undisturbed soils. Our new model shows that the exponentially-increasing respiration from substrate-induced respiration experiments can only be used to determine the maximum specific growth rate and initial active microbial biomass, while the respiration data representing both exponentially-increasing and non-exponentially-increasing phases can robustly determine a range of key parameters including the initial total live biomass, initial active fraction, the maximum specific growth and maintenance rates, and the half-saturation constant. Our new model can be incorporated into existing ecosystem models to account for dormancy in microbially-driven processes and to provide improved estimates of microbial activities. Public Library of Science 2014-02-18 /pmc/articles/PMC3928434/ /pubmed/24558490 http://dx.doi.org/10.1371/journal.pone.0089252 Text en https://creativecommons.org/publicdomain/zero/1.0/ This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration, which stipulates that, once placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose.
spellingShingle Review
Wang, Gangsheng
Mayes, Melanie A.
Gu, Lianhong
Schadt, Christopher W.
Representation of Dormant and Active Microbial Dynamics for Ecosystem Modeling
title Representation of Dormant and Active Microbial Dynamics for Ecosystem Modeling
title_full Representation of Dormant and Active Microbial Dynamics for Ecosystem Modeling
title_fullStr Representation of Dormant and Active Microbial Dynamics for Ecosystem Modeling
title_full_unstemmed Representation of Dormant and Active Microbial Dynamics for Ecosystem Modeling
title_short Representation of Dormant and Active Microbial Dynamics for Ecosystem Modeling
title_sort representation of dormant and active microbial dynamics for ecosystem modeling
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3928434/
https://www.ncbi.nlm.nih.gov/pubmed/24558490
http://dx.doi.org/10.1371/journal.pone.0089252
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