Cargando…
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...
Autores principales: | , , , |
---|---|
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 |
_version_ | 1782304259360948224 |
---|---|
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. |
format | Online Article Text |
id | pubmed-3928434 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT wanggangsheng representationofdormantandactivemicrobialdynamicsforecosystemmodeling AT mayesmelaniea representationofdormantandactivemicrobialdynamicsforecosystemmodeling AT gulianhong representationofdormantandactivemicrobialdynamicsforecosystemmodeling AT schadtchristopherw representationofdormantandactivemicrobialdynamicsforecosystemmodeling |